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M Luisetto, Yesvi Ar, Edbey Khaled, N Almukthar, L Cabianca, Gr Mashori, Ilman Ahnaf, Ar Yesvi, Oy Latyschev
Annals of Proteomics and Bioinformatics, Volume 5, pp 027-041; https://doi.org/10.29328/journal.apb.1001014

Abstract:
Related the need to search new strategy in vaccine design in order to reduce also some rare effect like trombosys for some registered products it is interesting the role played by the SPIKE RGD domain. The binding with molecules like Fibronectin is a process that must to be deeply investigated. A better understanding in this process can be used to improve safety of the new generation of COVID vaccine. The rare effect like thrombosis recognized by regulatory agency produced a modification of technical data sheet of some vaccine so the phenomena Is interesting to be more investigated. Spike protein and its domains are involved in producing pathological effect of the COVID-19 disease. What it is interesting is that some pathological effect of this pathology are similar to some rare side effect produced by some COVID-19 vaccine classes. After a review of interesting literature related this topics is submitted an experimental projects able to verify in vitro the spike procoaugulant property.
Dang Thi Ngan, Bui Mai Ngoc, Ha Thi Thanh Huong, Nguyen Thi Hai Yen
VNU Journal of Science: Medical and Pharmaceutical Sciences, Volume 36; https://doi.org/10.25073/2588-1132/vnumps.4258

Abstract:
This study aims to prepare green tea effervescent tablets with high EGCG content to retain the antioxidant and antibacterial effects of green tea as well as to diversify green tea product lines. The green tea effervescent tablets, prepared in the study by the method of wet granulation and stamping, met the general quality standards for effervescent tablets according to Vietnam Pharmacopeia V with the content of EGCG, quantified by HPLC, reaching 8.423 ± 0.023%. Keywords Green tea, effervescent tablets, epigallocatechin gallate, HPLC. References [1] Do Tat Loi, Vietnamese medicinal plants andherbs, Thoi Dai Publishing House, Vietnam, 2013, pp. 187-188.[2] Shutsung Liao, Yung-hsi Kao, Richard A.Hiipakka, Green Tea: Biochemical and Biological Basis for Health benefits, Vitamins and Hormones. 62 (2001) 09-61. https://doi.org/10.1016/s0083-6729(01)62001-6.[3] Shuichi Masuda, Yuko Shimamura, Colin R. Martin, Effect of Green Tea on Nitrosamines: Implications for Cancer, Tea in health and disease prevention. 68 (2013) 813-820. https://doi.org/10.1016/C2010-0-64948-0[4] Richard S. Bruno, Joshua A. Bomser, Mario G. Ferruzzi, Antioxidant capacity of Green tea (Camellia sinensis). 4 (2014) 33-39. https://doi.org/10.1016/B978-0-12-404738-9.00004-0. [5] C.J. Chang et al, Separation of catechins from green tea using carbon dioxide extraction, Food chemistry. 68 (1) (2000) 109-113. https://doi.org/10.1016/S0308-8146(99)00176-4[6] M.E. Harbowy et al, Tea chemistry, Critical reviews in plant sciences. 16 (5) (1997) 415-480. https://doi.org/10.1080/07352689709701956[7] Le Quan Nghiem, Huynh Van Hoa, Preparation and biopharmaceutical, Hanoi Education Publishing House, Vietnam, 2007, pp. 194-200.[8] S. Taymouri et al, Formulation and optimization of effervescent tablet containing bismuth sub-citrate, Journal of Reports in Pharmaceutical Sciences. 8 (2) (2019) 236. https://doi.org/10.4103/jrptps.JRPTPS_11_19[9] A. Aslani et al, Formulation, characterization and physicochemical evaluation of potassium citrate effervescent tablets, Advanced pharmaceutical bulletin. 3 (1) (2013) 217. https://doi.org/10.5681/apb.2013.036[10] Herbert A Liberman, Leon Lachman, Joseph B. Schwartz, Effervescent tablets, Pharmaceutical dosage form: Tablets. 1 (2005) 285-302. https://doi.org/10.1002/jps.2600790225[11] Ministry of Health Portal, Vietnam pharmacopeia V, Medical Publishing House, Vietnam, 2018.[12] I.H.T. Guideline, Validation of analytical procedures: text and methodology Q2 (R1), International conference on harmonization, Geneva, Switzerland, 2005.[13] A. Bradfleld et al,The catechins of green tea. Part I, Journal of the Chemical Society (Resumed). (1947) 32-36.[14] M.J. Lee. et al, Pharmacokinetics of tea catechins after ingestion of green tea and (−)-epigallocatechin-3-gallate by humans: formation of different metabolites and individual variability, Cancer Epidemiology and Prevention Biomarkers. 11 (10) (2002) 1025-1032.
Paola C. L. Leocádio, Reinaldo B. Oriá, ,
Published: 14 January 2020
Frontiers in Immunology, Volume 10; https://doi.org/10.3389/fimmu.2019.03092

Abstract:
Much is discussed if obesity or diet components modify the “healthy” microbiota or if microbiota modifications trigger events that culminate in obesity. This association is probably reciprocal, and inflammation has crucial participation on it. We will discuss recent studies showing gut microbiome as an obesogenic factor and the mechanisms linked to the associated of diet, microbiota, and low-grade inflammation. Obesity is a growing epidemy, despite the efforts to contain it. The inflammation generated by the adipocyte hypertrophy and hyperplasia initiates crosstalk between adipocyte and resident macrophage (M2) in white adipose tissue (WAT). Once activated, both adipocyte and activated macrophage (M1) release several adipokines that trigger the infiltration of other immune cells such as neutrophils, CD8+ and CD4+ T cells (1). Tissue-resident innate lymphocytes also play an important role in the homeostasis of WAT and, consequently, in obesity. Although this resident lymphocyte plays regulatory and anti-inflammatory properties in non-obese individuals, obesity promotes changes in the profile of these cells (2). Invariant Natural Killer cells (iNKT) and mucosal-associated invariant T cells (MAIT) are important examples. The frequency of iNKT is reduced in WAT in obesity and is inversely related to the degree of obesity, insulin resistance and fasting blood glucose, suggesting that these cells play a role against metabolic disorders associated with obesity (1, 2). MAIT cells also present reduced frequency and change of phenotype in WAT in obesity, reducing IL-10 synthesis and gamma interferon (IFNγ) and increasing IL-17 production (1, 2) and can play an important role in the progression of inflammation (3). Adipocytes also produce macrophage colony-stimulating factor (M-CSF-1), causing an increased influx of monocytes from bone marrow-derived precursors and regulating macrophage differentiation and survival (4, 5). The expanded WAT also secrets pro-inflammatory and prothrombotic factors such as interleukin (IL)-1β, IL-6, tumoral necrosis factor (TNF), monocytes and macrophages chemoattractant protein (MCP-1/CCL2), C-reactive protein (CRP), tissue factor and factor VII, plasminogen activator inhibitor type-1 (PAI-1) (6). This pro-inflammatory, prothrombotic environment contributes to the onset of obesity-related complications such as metabolic syndrome, insulin resistance, hypertension, and systemic sterile inflammation. One of the first studies linking obesity and microbiota was conducted by Ley et al. (7), showing that obesity is associated with a specific microbiota profile. The gut microbiota of healthy individuals is mostly composed of Firmicutes (70%) and the Bacteroidetes (30%). Other minor phyla are Actinobacteria, Proteobacteria, Fusobacteria, and Verrucomicrobia (8). The genetically obese ob/ob mice have in their microbiota 50% fewer Bacterioidetes and a higher proportion of Firmicutes when compared to lean mice. This altered ratio between Firmicutes and Bacteroidetes (F/B ratio) has also been described in obese individuals (9). Nonetheless, obesity in adulthood is influenced by several factors besides the different profiles of gut microbiota and, until now, studies have not found enough consistency to point out specific obesogenic bacteria (10). However, preclinical studies revealed that the obesogenic microbiota profile could be transmitted from twins discordant for obesity to germ-free (GF) mice. When the fecal microbiota of the obese twin is transplanted to GF mice, the mice eventually become obese, the same occurring with the transplantation of microbiota from the lean twin to GF mice. Moreover, obesity was prevented when mice carrying the obese twin's microbiota were kept in the same cage with mice carrying the lean twin's microbiota (11). The influence of microbiota on obesity development and low-grade inflammation seems to occur even before or immediately after birth. The gut-associated lymphoid tissues (GALT) are formed during embryogenesis and become mature during the microbial colonization, after birth. Bacterial antigens were recognized by the intestinal epithelium via pattern recognition receptors (PRR), such as Toll-like receptors (TLRs) and nucleotide-binding oligomerization domain 1 (NOD-1) (12, 13). Changes in the microbial composition, which occur in the presence of obesity, disrupt the barrier integrity promoted by GALT, increase the intestinal permeability, favor bacterial translocation that triggers the inflammatory process (14). Maternal obesity, caesarian section (CS), infections, and antibiotic utilization were described as factors influencing obesity (15) (Figure 1). Antibiotic therapy in the perinatal period is associated with intestinal microbiota disruption and metabolic changes sufficiently strong to affect body composition in late childhood (16, 17). Indeed, babies from mothers receiving antibiotics during the last gestational trimester presented an 84% higher risk of obesity (16). Moreover, CS is associated with the reduction in Bacteroidetes abundance and microbiota diversity in the first 2 years of life. Systemic levels of CXCL10 and CXCL11 chemokines were also reduced in children born by CS (17). Young adults born by CS have a higher risk for increased central and peripheral adiposity than those born by vaginal delivery (18). These associations are stronger in children whose mothers were obese compared to children of non-obese mothers (19). Figure 1. An overview of the relationships described in this opinion paper. An obesogenic profile (characterized by a very high Firmicutes/Bacteroidetes ratio, F/B) can be caused in the fetus by conditions such as maternal obesity, caesarian section, infections, or antibiotics treatments during pregnancy. The immune and pro-inflammatory response caused by intestinal dysbiosis over life can eventually lead the individual to obesity in adulthood. This scenario can be worsened by the chronic intake of a high-fat diet, responsible for the increase of bacteria producing hydrogen disulfide (H2S-bacteria) and pathogenic bacterial lipopolysaccharide (LPS) translocation. A healthy dietary pattern and physical activity may contribute to revert dysbiosis. Although probiotics and fecal microbiota transplantation could eventually improve this condition, presently, there is not enough clinical evidence supporting the adoption of such intervention. Previous studies clarified the crosstalk between the immune system and microbiota in obesity (20). The IgA is produced by intestinal B cells after interaction with T follicular helper cells (TFH) and secreted into the gut lumen covering bacteria membrane and reducing gut colonization (20, 21). Although bacteria-IgA binding participates in hosting defense against pathogens, IgA can also regulate the gene expression of some gut bacteria population and intestinal cells. It has been proposed that IgA promotes colonization of a healthy microbiota reducing dysbiosis (22). It was tested in MyD88−/− mice that develop obesity faster than controls and are defective in TFH and IgA (23). The expansion of WAT in MyD88−/− is associated with the increase of Desulfovibrio and the loss of Clostridia populations. When mice were treated with antibiotics or replacement of Clostridia, the weight gain was reduced, confirming a cause-effect interaction (20). It suggests that by regulating IgA production, TFH cells maintain the intestinal Clostridia population, reducing fatty acids (FA) absorption and protecting the host against obesity. Previous studies addressed the interaction of microbiota, and pro-inflammatory markers (24) showed that Bifidobacterium, Faecalibacterium, Ruminococcus, and Prevotella genus abundances were inversely associated with blood levels of CRP or pro-inflammatory cytokines (14, 25–29). Besides the abundance of a specific genus, gut microbial diversity has also been related to obesity. Individuals with low microbial diversity presented higher blood leukocyte count and CRP level that is related to higher triglyceridemia and lower high-density lipoprotein (HDL) levels, insulin resistance and increased risk of atherosclerosis-associated disorders (30). The decrease in commensal bacteria levels and diversity (dysbiosis) permit the establishment of foreign bacteria, increasing the lipopolysaccharide (LPS) concentration in the gut lumen (Figure 1). LPS can reach systemic circulation by crossing the intestinal mucosa through altered tight junctional complex or linked to dietary fat incorporated into chylomicrons. In the plasma, LPS is transported bound to lipoproteins. Initially, LPS is transported in chylomicrons and then distributed to the other lipoproteins, mainly HDL (31). LPS increases the scavenger receptor binding to lipoproteins, as well as the endocytoses in endothelium and adipocytes. The expanded adipocytes and activated macrophages internalize LPS-rich lipoproteins (32), perpetuating the expansion and inflammation of the WAT. Indeed, LPS triggers the innate immune response on macrophages and adipocytes via TLR4 signaling, resulting in nuclear factor-kappa B (NF-κB) release and pro-inflammatory cytokine production (14, 33). Previous studies have demonstrated the effect of high-fat diets (HFD) in increasing Firmicutes/Bacteroidetes ratio and in inducing dysbiosis (34–40) (Figure 1). Not only the amount of fat but also the type of FA may influence microbiota. Saturated FA (SFA) promotes dysbiosis by increasing H2S-bacteria, which results in the disruption of epithelial integrity by suppression of the tight junction proteins (41). Comparing the effects of HFD with different FAs, SFA quickly and persistently increased the proportion of H2S-bacteria over time. When SFA was replaced by ω6-polyunsaturated FAs (ω6-PUFA), the proportion of H2S-bacteria remained stable, while replacing SFA for ω3-PUFA, the proportion of H2S-bacteria was reduced. This result aggregates beneficial effects to ω3-PUFA, a well-known systemic anti-inflammatory agent. HFD may also favor obesity not only by promoting dysbiosis but directly by favoring the entry of bacterial components such as LPS (42) (Figure 1). As mentioned before, the absorption of dietary fat facilitates the absorption of LPS since both are transported by chylomicron (43). In the WAT, LPS and palmitic acid increase expression of chemokines and cytokines such as MCP-1 and IL-1β, and inflammation-related enzymes such cyclooxygenase-2, inducing macrophages infiltration and adipocyte expansion. In the liver, palmitic acid also increases the ceramide synthesis of CD36 and free-fatty-acid receptor-1 (FFA1/Gpr40) (41). Protein-rich/carbohydrate-poor diet may also lead to dysbiosis, changes in barrier integrity and inflammatory activity. Unabsorbed proteins reach the colon, where microbiota exchanges fermentation substrate from carbohydrates to proteins, increasing colonic transit time and pH (41, 44). Protein fermentation increases H2S, reactive oxygen species and ammonia production and reduces butyrate and Roseburia/Eubacterium abundance, suggesting a worse microbiota profile (45–47). Nonetheless, microbial metabolites from the proteolysis of the essential amino acid tryptophan also influence and modulate host microbiota. Indole groups bind aryl hydrocarbon receptor (AHR) that interfere with several metabolic steps, activate the immune system and reduce intestinal permeability (48). The presence of non-digested carbohydrates in the colon increases the short-chain FAs produced by microbiota fermentation. These FAs can be absorbed and contribute to the host energy input. In addition to the additional energy absorption caused by short-chain FAs absorption, dysbiosis decreases the expression of FIAF (a lipase lipoprotein inhibitor), stimulating fat deposition in the WAT (33). Changing in diet and physical activity are crucial points in the treatment of obesity. Some studies suggest that such changes can alter not only bodyweight but also the microbiota in those individuals. The effects of physical activity modifying microbiota composition and metabolism have been studied, but the results are still controversial (49). Previous studies (50, 51) observed in HFD-fed animals that moderate and high-intensity exercise induced an abundance of Bacteroidetes in the colon. Nonetheless, an abundance of Firmicutes after physical exercise was also observed in animals with and without diabetes compared to sedentary ones (52). Thus, the influence of exercise on microbiota needs to be carefully evaluated. Some of the well-established approaches, such as adopting a healthy dietary pattern (53–55), by reducing saturated fat and increasing fiber and antioxidant compounds intake (56, 57) have partially reverse dysbiosis and obesity in experimental studies. Nonetheless, it seems not to be enough to control obesity epidemy. Furthermore, new insights using pre and probiotics and fecal microbiota transplantation (FMT) have now been tested in humans (Figure 1). Akkermansia muciniphila, which is a mucin-degrading bacterium that resides in the mucus layer, has been the most studied, mainly in animal models (58, 59). Clinical studies (60, 61) showed that, in overweight/obese individuals, the oral supplementation of A. muciniphila reduced insulin resistance and plasma total cholesterol and levels of blood markers for liver dysfunction and inflammation. However, there was only a modest effect on body weight and composition with A. muciniphila supplementation. Although FMT could be a rational strategy to treat obesity-linked dysbiosis (62), few clinical studies have assessed FMT in individuals with metabolic syndrome or obesity (63–67). Results are until now disappointing, despite the improvement in insulin sensitivity seen in two studies (66, 67), none of them presented promising results in terms of weight loss or reduction in the inflammatory profile. It is confirmed by recent reviews (68, 69) reinforcing the need for studies evaluating the mechanisms by which FMT affect host metabolism and its long-term effects. Moreover, the best preparation, concentration and form of administration of FMT should be defined. In summary, the study of the complex network formed by gut microbiota, obesity, and inflammation are only in its first steps. The role of the dysbiosis in the genesis of obesity has been progressively uncovered, and the infectious component of this disease has gained more interest. However, up to date, no intervention based on microbes was able to reduce body weight effectively and persistently. Considering the relatively well-established relationship between microbiota and obesity in preclinical studies, additional efforts are necessary for the development of clinical interventions that support the microbiota manipulation as a realistic alternative to combat obesity. PL and JA-L wrote the paper. MC-L and RO revised the paper. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The authors thank the Fundação Cearense de Apoio ao Desenvolvimento Científico e Tecnológico (FUNCAP), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) PROCAD 88881.068408/2014-01 for their support. 1. Kane H, Lynch L. Innate immune control of adipose tissue homeostasis. Trends Immunol. (2019) 40:857–72. doi: 10.1016/j.it.2019.07.006 PubMed Abstract | CrossRef Full Text | Google Scholar 2. Del Cornò M, Conti L, Gessani S. Innate lymphocytes in adipose tissue homeostasis and their alterations in obesity and colorectal cancer. Front Immunol. (2018) 9:2556. doi: 10.3389/fimmu.2018.02556 CrossRef Full Text | Google Scholar 3. Chehimi M, Vidal H, Eljaafari A. Pathogenic role of IL-17-producing immune cells in obesity, and related inflammatory diseases. J Clin Med. (2017) 6:68. doi: 10.3390/jcm6070068 PubMed Abstract | CrossRef Full Text | Google Scholar 4. Weisberg SP, McCann D, Desai M, Rosenbaum M, Leibel RL, Ferrante AW. Obesity is associated with macrophage accumulation in adipose tissue. J Clin Invest. (2003) 112:1796–808. doi: 10.1172/JCI200319246 PubMed Abstract | CrossRef Full Text | Google Scholar 5. Engin AB. Adipocyte-macrophage cross-talk in obesity. Adv Exp Med Biol. 960:327–43. doi: 10.1007/978-3-319-48382-5_14 PubMed Abstract | CrossRef Full Text | Google Scholar 6. Liu R, Nikolajczyk BS. Tissue immune cells fuel obesity-associated inflammation in adipose tissue and beyond. Front Immunol. (2019) 10:1587. doi: 10.3389/fimmu.2019.01587 PubMed Abstract | CrossRef Full Text | Google Scholar 7. Ley RE, Backhed F, Turnbaugh P, Lozupone CA, Knight RD, Gordon JI. Obesity alters gut microbial ecology. Proc Natl Acad Sci USA. (2005) 102:11070–5. doi: 10.1073/pnas.0504978102 PubMed Abstract | CrossRef Full Text | Google Scholar 8. Belizário JE, Faintuch J, Garay-Malpartida M. Gut microbiome dysbiosis and immunometabolism: new frontiers for treatment of metabolic diseases. Mediat Inflamm. (2018) 2018:1–12. doi: 10.1155/2018/2037838 PubMed Abstract | CrossRef Full Text | Google Scholar 9. Ley RE, Turnbaugh PJ, Klein S, Gordon JI. Human gut microbes associated with obesity Two. Nature. (2006) 444:1022–3. doi: 10.1038/4441022a CrossRef Full Text | Google Scholar 10. Castaner O, Goday A, Park YM, Lee SH, Magkos F, Shiow SATE, et al. The gut microbiome profile in obesity: a systematic review. Int J Endocrinol. (2018) 2018:1–9. doi: 10.1155/2018/4095789 CrossRef Full Text | Google Scholar 11. Ridaura VK, Faith JJ, Rey FE, Cheng J, Duncan AE, Kau AL, et al. Gut microbiota from twins discordant for obesity modulate metabolism in mice. Science. (2013) 341:1241214. doi: 10.1126/science.1241214 PubMed Abstract | CrossRef Full Text | Google Scholar 12. Renz H, Brandtzaeg P, Hornef M. The impact of perinatal immune development on mucosal homeostasis and chronic inflammation. Nat Rev Immunol. (2012) 12:9–23. doi: 10.1038/nri3112 PubMed Abstract | CrossRef Full Text | Google Scholar 13. Bouskra D, Brézillon C, Bérard M, Werts C, Varona R, Boneca IG, et al. Lymphoid tissue genesis induced by commensals through NOD1 regulates intestinal homeostasis. Nature. (2008) 456:507–10. doi: 10.1038/nature07450 PubMed Abstract | CrossRef Full Text | Google Scholar 14. Gomes JMG, Costa J de A, Alfenas R de CG. Metabolic endotoxemia and diabetes mellitus: a systematic review. Metabolism. (2017) 68:133–44. doi: 10.1016/j.metabol.2016.12.009 PubMed Abstract | CrossRef Full Text | Google Scholar 15. Milani C, Duranti S, Bottacini F, Casey E, Turroni F, Mahony J, et al. The first microbial colonizers of the human gut: composition, activities, and health implications of the infant gut microbiota. Microbiol Mol Biol Rev. (2017) 81:e00036–17. doi: 10.1128/MMBR.00036-17 PubMed Abstract | CrossRef Full Text | Google Scholar 16. Mueller NT, Whyatt R, Hoepner L, Oberfield S, Dominguez-Bello MG, Widen EM, et al. Prenatal exposure to antibiotics, cesarean section and risk of childhood obesity. Int J Obes. (2015) 39:665–70. doi: 10.1038/ijo.2014.180 PubMed Abstract | CrossRef Full Text | Google Scholar 17. Jakobsson HE, Abrahamsson TR, Jenmalm MC, Harris K, Quince C, Jernberg C, et al. Decreased gut microbiota diversity, delayed Bacteroidetes colonisation and reduced Th1 responses in infants delivered by Caesarean section. Gut. (2014) 63:559–66. doi: 10.1136/gutjnl-2012-303249 PubMed Abstract | CrossRef Full Text | Google Scholar 18. Mesquita DN, Barbieri MA, Goldani HAS, Cardoso VC, Goldani MZ, Kac G, et al. Cesarean section is associated with increased peripheral and central adiposity in young adulthood: cohort study. PLoS ONE. (2013) 8:e66827. doi: 10.1371/journal.pone.0066827 PubMed Abstract | CrossRef Full Text | Google Scholar 19. Blustein J, Attina T, Liu M, Ryan AM, Cox LM, Blaser MJ, et al. Association of caesarean delivery with child adiposity from age 6 weeks to 15 years. Int J Obes. (2013) 37:900–6. doi: 10.1038/ijo.2013.49 PubMed Abstract | CrossRef Full Text | Google Scholar 20. Petersen C, Bell R, Klag KA, Lee S-H, Soto R, Ghazaryan A, et al. T cell–mediated regulation of the microbiota protects against obesity. Science. (2019) 365:eaat9351. doi: 10.1126/science.aat9351 PubMed Abstract | CrossRef Full Text | Google Scholar 21. Wang Y, Hooper L V. Immune control of the microbiota prevents obesity. Science. (2019) 365:316–17. doi: 10.1126/science.aay2057 PubMed Abstract | CrossRef Full Text | Google Scholar 22. Donaldson GP, Ladinsky MS, Yu KB, Sanders JG, Yoo BB, Chou WC, et al. Gut microbiota utilize immunoglobulin a for mucosal colonization. Science. (2018) 360:795–800. doi: 10.1126/science.aaq0926 PubMed Abstract | CrossRef Full Text | Google Scholar 23. Kubinak JL, Petersen C, Stephens WZ, Soto R, Bake E, O'Connell RM, et al. MyD88 signaling in T cells directs IgA-mediated control of the microbiota to promote health. Cell Host Microbe. (2015) 17:153–63. doi: 10.1016/j.chom.2014.12.009 PubMed Abstract | CrossRef Full Text | Google Scholar 24. van den Munckhof ICL, Kurilshikov A, ter Horst R, Riksen NP, Joosten LAB, Zhernakova A, et al. Role of gut microbiota in chronic low-grade inflammation as potential driver for atherosclerotic cardiovascular disease: a systematic review of human studies. Obes Rev. (2018) 19:1719–34. doi: 10.1111/obr.12750 PubMed Abstract | CrossRef Full Text | Google Scholar 25. Le Chatelier E, Nielsen T, Qin J, Prifti E, Hildebrand F, Falony G, et al. Richness of human gut microbiome correlates with metabolic markers. Nature. (2013) 500:541–6. doi: 10.1038/nature12506 PubMed Abstract | CrossRef Full Text | Google Scholar 26. Cândido FG, Valente FXFX, Grześkowiak ŁM, Moreira APB, Rocha DMUP, Alfenas RCG, et al. Impact of dietary fat on gut microbiota and low-grade systemic inflammation: mechanisms and clinical implications on obesity. Int J Food Sci Nutr. (2018) 69:125–43. doi: 10.1080/09637486.2017.1343286 PubMed Abstract | CrossRef Full Text | Google Scholar 27. Furet J-P, Kong L-C, Tap J, Poitou C, Basdevant A, Bouillot J-L, et al. Differential adaptation of human gut microbiota to bariatric surgery–induced weight loss. Diabetes. (2010) 59:3049–57. doi: 10.2337/db10-0253 PubMed Abstract | CrossRef Full Text | Google Scholar 28. Rajkumar H, Mahmood N, Kumar M, Varikuti SR, Challa HR, Myakala SP. Effect of probiotic (VSL#3) and omega-3 on lipid profile, insulin sensitivity, inflammatory markers, and gut colonization in overweight adults: a randomized, controlled trial. Mediat Inflamm. (2014) 2014:348959. doi: 10.1155/2014/348959 CrossRef Full Text | Google Scholar 29. Martínez I, Lattimer JM, Hubach KL, Case JA, Yang J, Weber CG, et al. Gut microbiome composition is linked to whole grain-induced immunological improvements. ISME J. (2013) 7:269–80. doi: 10.1038/ismej.2012.104 PubMed Abstract | CrossRef Full Text | Google Scholar 30. Manco M, Putignani L, Bottazzo GF. Gut microbiota, lipopolysaccharides, and innate immunity in the pathogenesis of obesity and cardiovascular risk. Endocr Rev. (2010) 31:817–44. doi: 10.1210/er.2009-0030 PubMed Abstract | CrossRef Full Text | Google Scholar 31. Hersoug LG, Møller P, Loft S. Role of microbiota-derived lipopolysaccharide in adipose tissue inflammation, adipocyte size and pyroptosis during obesity. Nutr Res Rev. (2018) 31:153–63. doi: 10.1017/S0954422417000269 PubMed Abstract | CrossRef Full Text | Google Scholar 32. Hersoug L-G, Møller P, Loft S. Gut microbiota-derived lipopolysaccharide uptake and trafficking to adipose tissue: implications for inflammation and obesity. Obes Rev. (2016) 17:297–312. doi: 10.1111/obr.12370 PubMed Abstract | CrossRef Full Text | Google Scholar 33. Muscogiuri G, Cantone E, Cassarano S, Tuccinardi D, Barrea L, Savastano S, et al. Gut microbiota: a new path to treat obesity. Int J Obes Suppl. (2019) 9:10–19. doi: 10.1038/s41367-019-0011-7 PubMed Abstract | CrossRef Full Text | Google Scholar 34. Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, Gordon JI. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature. (2006) 444:1027–31. doi: 10.1038/nature05414 PubMed Abstract | CrossRef Full Text | Google Scholar 35. Cani PD, Bibiloni R, Knauf C, Waget A, Neyrinck AM, Delzenne NM, et al. Changes in gut microbiota control metabolic endotoxemia-induced inflammation in high-fat diet-induced obesity and diabetes in mice. Diabetes. (2008) 57:1470–81. doi: 10.2337/db07-1403 PubMed Abstract | CrossRef Full Text | Google Scholar 36. Ding S, Chi MM, Scull BP, Rigby R, Schwerbrock NMJ, Magness S, et al. High-fat diet: bacteria interactions promote intestinal inflammation which precedes and correlates with obesity and insulin resistance in mouse. PLoS ONE. (2010) 5:e12191. doi: 10.1371/journal.pone.0012191 PubMed Abstract | CrossRef Full Text | Google Scholar 37. Nguyen SG, Kim J, Guevarra RB, Lee JH, Kim E, Kim SI, et al. Laminarin favorably modulates gut microbiota in mice fed a high-fat diet. Food Funct. (2016) 7:4193–201. doi: 10.1039/C6FO00929H PubMed Abstract | CrossRef Full Text | Google Scholar 38. Turnbaugh PJ, Hamady M, Yatsunenko T, Cantarel BL, Duncan A, Ley RE, et al. A core gut microbiome in obese and lean twins. Nature. (2009) 457:480–4. doi: 10.1038/nature07540 PubMed Abstract | CrossRef Full Text | Google Scholar 39. Araujo JR, Tomas J, Brenner C, Sansonetti PJ, Araújo JR, Tomas J, et al. Impact of high-fat diet on the intestinal microbiota and small intestinal physiology before and after the onset of obesity. Biochimie. (2017) 141:97–106. doi: 10.1016/j.biochi.2017.05.019 PubMed Abstract | CrossRef Full Text | Google Scholar 40. Ussar S, Griffin NW, Bezy O, Fujisaka S, Vienberg S, Softic S, et al. Interactions between gut microbiota, host genetics and diet modulate the predisposition to obesity and metabolic syndrome. Cell Metab. (2015) 22:516–30. doi: 10.1016/j.cmet.2015.07.007 PubMed Abstract | CrossRef Full Text | Google Scholar 41. Wisniewski PJ, Dowden RA, Campbell SC. Role of dietary lipids in modulating inflammation through the gut microbiota. Nutrients. (2019) 11:E117. doi: 10.3390/nu11010117 PubMed Abstract | CrossRef Full Text | Google Scholar 42. Burcelin R, Garidou L, Pomié C. Immuno-microbiota cross and talk: the new paradigm of metabolic diseases. Semin Immunol. (2012) 24:67–74. doi: 10.1016/j.smim.2011.11.011 PubMed Abstract | CrossRef Full Text | Google Scholar 43. Erridge C, Attina T, Spickett CM, Webb DJ. A high-fat meal induces low-grade endotoxemia: evidence of a novel mechanism of postprandial inflammation. Am J Clin Nutr. (2007) 86:1286–92. doi: 10.1093/ajcn/86.5.1286 PubMed Abstract | CrossRef Full Text | Google Scholar 44. Roager HM, Hansen LBS, Bahl MI, Frandsen HL, Carvalho V, Gøbel RJ, et al. Colonic transit time is related to bacterial metabolism and mucosal turnover in the gut. Nat Microbiol. (2016) 1:16093. doi: 10.1038/nmicrobiol.2016.93 PubMed Abstract | CrossRef Full Text | Google Scholar 45. Geypens B, Claus D, Evenepoel P, Hiele M, Maes B, Peeters M, et al. Influence of dietary protein supplements on the formation of bacterial metabolites in the colon. Gut. (1997) 41:70–6. doi: 10.1136/gut.41.1.70 PubMed Abstract | CrossRef Full Text | Google Scholar 46. Nyangale EP, Mottram DS, Gibson GR. Gut microbial activity, implications for health and disease: the potential role of metabolite analysis. J Proteome Res. (2012) 11:5573–85. doi: 10.1021/pr300637d PubMed Abstract | CrossRef Full Text | Google Scholar 47. Russell WR, Gratz SW, Duncan SH, Holtrop G, Ince J, Scobbie L, et al. High-protein, reduced-carbohydrate weight-loss diets promote metabolite profiles likely to be detrimental to colonic health. Am J Clin Nutr. (2011) 93:1062–72. doi: 10.3945/ajcn.110.002188 PubMed Abstract | CrossRef Full Text | Google Scholar 48. Roager HM, Licht TR. Microbial tryptophan catabolites in health and disease. Nat Commun. (2018) 9:3294. doi: 10.1038/s41467-018-05470-4 PubMed Abstract | CrossRef Full Text | Google Scholar 49. Bianchi F, Duque ALRF, Saad SMI, Sivieri K. Gut microbiome approaches to treat obesity in humans. Appl Microbiol Biotechnol. (2019) 103:1081–94. doi: 10.1007/s00253-018-9570-8 PubMed Abstract | CrossRef Full Text | Google Scholar 50. Evans CC, LePard KJ, Kwak JW, Stancukas MC, Laskowski S, Dougherty J, et al. Exercise prevents weight gain and alters the gut microbiota in a mouse model of high fat diet-induced obesity. PLoS ONE. (2014) 9:e92193. doi: 10.1371/journal.pone.0092193 PubMed Abstract | CrossRef Full Text | Google Scholar 51. Denou E, Marcinko K, Surette MG, Steinberg GR, Schertzer JD. High-intensity exercise training increases the diversity and metabolic capacity of the mouse distal gut microbiota during diet-induced obesity. Am J Physiol Endocrinol Metab. (2016) 310:E982–93. doi: 10.1152/ajpendo.00537.2015 PubMed Abstract | CrossRef Full Text | Google Scholar 52. Lambert JE, Myslicki JP, Bomhof MR, Belke DD, Shearer J, Reimer RA. Exercise training modifies gut microbiota in normal and diabetic mice. Appl Physiol Nutr Metab. (2015) 40:749–52. doi: 10.1139/apnm-2014-0452 PubMed Abstract | CrossRef Full Text | Google Scholar 53. Haro C, Garcia-Carpintero S, Alcala-Diaz JF, Gomez-Delgado F, Delgado-Lista J, Perez-Martinez P, et al. The gut microbial community in metabolic syndrome patients is modified by diet. J Nutr Biochem. (2016) 27:27–31. doi: 10.1016/j.jnutbio.2015.08.011 PubMed Abstract | CrossRef Full Text | Google Scholar 54. Lopez-Legarrea P, Fuller NR, Zulet MA, Martinez JA, Caterson ID. The influence of Mediterranean, carbohydrate and high protein diets on gut microbiota composition in the treatment of obesity and associated inflammatory state. Asia Pac J Clin Nutr. (2014) 23:360–8. doi: 10.6133/apjcn.2014.23.3.16 PubMed Abstract | CrossRef Full Text | Google Scholar 55. Del Chierico F, Vernocchi P, Dallapiccola B, Putignani L. Mediterranean diet and health: food effects on gut microbiota and disease control. Int J Mol Sci. (2014) 15:11678. doi: 10.3390/ijms150711678 PubMed Abstract | CrossRef Full Text | Google Scholar 56. Pandey KB, Rizvi SI. Plant polyphenols as dietary antioxidants in human health and disease. Oxid Med Cell Longev. (2009) 2:270–8. doi: 10.4161/oxim.2.5.9498 PubMed Abstract | CrossRef Full Text | Google Scholar 57. Roopchand DE, Carmody RN, Kuhn P, Moskal K, Rojas-Silva P, Turnbaugh PJ, et al. Dietary polyphenols promote growth of the gut bacterium Akkermansia muciniphila and attenuate high-fat diet–induced metabolic syndrome. Diabetes. (2015) 64:2847–58. doi: 10.2337/db14-1916 PubMed Abstract | CrossRef Full Text | Google Scholar 58. Chelakkot C, Choi Y, Kim DK, Park HT, Ghim J, Kwon Y, et al. Akkermansia muciniphila-derived extracellular vesicles influence gut permeability through the regulation of tight junctions. Exp Mol Med. (2018) 50:e450–11. doi: 10.1038/emm.2017.282 PubMed Abstract | CrossRef Full Text | Google Scholar 59. Li J, Lin S, Vanhoutte PM, Woo CW, Xu A. Akkermansia muciniphila protects against atherosclerosis by preventing metabolic endotoxemia-induced inflammation in apoe−/− mice. Circulation. (2016) 133:2434–46. doi: 10.1161/CIRCULATIONAHA.115.019645 CrossRef Full Text | Google Scholar 60. Depommier C, Everard A, Druart C, Plovier H, Van Hul M, Vieira-Silva S, et al. Supplementation with Akkermansia muciniphila in overweight and obese human volunteers: a proof-of-concept exploratory study. (2019). 25:1. doi: 10.1038/s41591-019-0495-2 PubMed Abstract | CrossRef Full Text | Google Scholar 61. Dao MC, Everard A, Aron-Wisnewsky J, Sokolovska N, Prifti E, Verger EO, et al. Akkermansia muciniphila and improved metabolic health during a dietary intervention in obesity: relationship with gut microbiome richness and ecology. Gut. (2016) 65:426–36. doi: 10.1136/gutjnl-2014-308778 PubMed Abstract | CrossRef Full Text | Google Scholar 62. Lee P, Yacyshyn BR, Yacyshyn MB. Gut microbiota and obesity: an opportunity to alter obesity through faecal microbiota transplant (FMT). Diabetes, Obes Metab. (2019) 21:479–90. doi: 10.1111/dom.13561 PubMed Abstract | CrossRef Full Text | Google Scholar 63. Allegretti JR, Kassam Z, Mullish BH, Chiang A, Carrellas M, Hurtado J, et al. Effects of fecal microbiota transplantation with oral capsules in obese patients. Clin Gastroenterol Hepatol. (2019) doi: 10.1016/j.cgh.2019.07.006. [Epub ahead of print]. PubMed Abstract | CrossRef Full Text | Google Scholar 64. Allegretti JR, Mullish BH, Kelly C, Fischer M. The evolution of the use of faecal microbiota transplantation and emerging therapeutic indications. Lancet. (2019) 394:420–31. doi: 10.1016/S0140-6736(19)31266-8 PubMed Abstract | CrossRef Full Text | Google Scholar 65. Smits LP, Kootte RS, Levin E, Prodan A, Fuentes S, Zoetendal EG, et al. Effect of vegan fecal microbiota transplantation on carnitine- and choline-derived trimethylamine-N-oxide production and vascular inflammation in patients with metabolic syndrome. J Am Heart Assoc. (2018) 7:e008342. doi: 10.1161/JAHA.117.008342 PubMed Abstract | CrossRef Full Text | Google Scholar 66. Vrieze A, Van Nood E, Holleman F, Salojärvi J, Kootte RS, Bartelsman JFWM, et al. Transfer of intestinal microbiota from lean donors increases insulin sensitivity in individuals with metabolic syndrome. Gastroenterology. (2012) 143:913–16.e7. doi: 10.1053/j.gastro.2012.06.031 PubMed Abstract | CrossRef Full Text | Google Scholar 67. Kootte RS, Levin E, Salojärvi J, Smits LP, Hartstra AV, Udayappan SD, et al. Improvement of insulin sensitivity after lean donor feces in metabolic syndrome is driven by baseline intestinal microbiota composition. Cell Metab. (2017) 26:611–19.e6. doi: 10.1016/j.cmet.2017.09.008 PubMed Abstract | CrossRef Full Text | Google Scholar 68. Aron-Wisnewsky J, Prifti E, Belda E, Ichou F, Kayser BD, Dao MC, et al. Major microbiota dysbiosis in severe obesity: fate after bariatric surgery. Gut. (2019) 68:70–82. doi: 10.1136/gutjnl-2018-316103 PubMed Abstract | CrossRef Full Text | Google Scholar 69. Zhang Z, Mocanu V, Cai C, Dang J, Slater L, Deehan EC. Impact of fecal microbiota transplantation on obesity and metabolic syndrome—a systematic review. Nutrients. (2019) 11:2291. doi: 10.3390/nu11102291 PubMed Abstract | CrossRef Full Text | Google Scholar Keywords: obesity, microbiota, diet, dysbiosis, inflammation Citation: Leocádio PCL, Oriá RB, Crespo-Lopez ME and Alvarez-Leite JI (2020) Obesity: More Than an Inflammatory, an Infectious Disease? Front. Immunol. 10:3092. doi: 10.3389/fimmu.2019.03092 Received: 10 September 2019; Accepted: 17 December 2019; Published: 14 January 2020. Edited by: Reviewed by: Copyright © 2020 Leocádio, Oriá, Crespo-Lopez and Alvarez-Leite. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. *Correspondence: Jacqueline I. Alvarez-Leite, [email protected]
Published: 11 December 2019
Frontiers in Genetics, Volume 10; https://doi.org/10.3389/fgene.2019.01210

Abstract:
Since the discovery of the biological clock, the concept of treating cancer according to biological rhythms, here termed cancer chronotherapy, has rapidly evolved. Its fundamental aim is to improve the efficacy of drugs and to minimize adverse effects by administering chemotherapeutic drugs at the appropriate time-of-day. In the last two decades, several experimental and clinical studies have reported positive associations between the circadian clock and drug response in cancer patients. However, the lack of mechanistic insights into critical, deterministic clock-controlled genetic, and metabolic variations between and within individual cancer patients continue to cast a shadow on the potential benefits cancer chronotherapy may provide. Here, we provide first a simplified overview on our biological clocks and how our life-style induces complex biochemical reactions and genetic interactions. Next, we summarize how these reactions directly and indirectly modulate the effectiveness and toxicity of oncological drug treatments. Since cytotoxic chemotherapy represents the most common and affordable of cancer treatments, a case should be made that we need to ensure these treatments are used in the best possible manner. Thus, we list current challenges and future directions toward that goal. Professor Francis Albert Lévi is Clinical Professor of Biomedicine – Medical Oncology at the University of Warwick Medical School and Honorary Consultant at the Cancer Center, University Hospital Birmingham Queen Elisabeth. His team aims to streamline basic and clinical research on biological clocks, drugs, and diseases to promote the integration of chronotherapy into drug development and daily medical practice. The ultimate goal of Prof. Francis Lévi and his team is to predict and prevent diseases through the fine-tuning of our biological rhythms. “The scientific and technological challenges are to adjust chronotherapy to the circadian clock in both healthy and tumor tissues of cancer patients. To do this, we need to stratify cancer patients according to how their circadian clocks are working, and to identify the optimal timing for the delivery of chronotherapy accordingly. This means that we would need to develop five to ten Phase I-II and III clinical trials with strong translational components and have them funded through long-term investment strategies. In parallel, we need Regulatory Agencies to make the recording of time, day, and month of treatments and sample collections a mandatory information during drug trials, and convince pharmaceutical companies that drug development could greatly benefit from considering timing issues during preclinical and early clinical testing. This could help us obtain the clinical data that we need in order to evaluate the potential benefit of therapeutic strategies.” “Generally, basic chronopharmacology research involves a standardized, systematic approach when studying physiology and pharmacology in animals or cultured cells. This allows us to generate a substantial amount of quantitative information on time-dependent drug pharmacology, efficacy, and toxicity. We need mathematical approaches to systematically map cancer chronopharmacology mechanisms in cellular models with synchronized clocks. Next, we need the ability to adjust these models established in rodent models in healthy volunteers and in cancer patients. Thus, a systems chronopharmacology approach going from cells to whole organisms would appear to be the currently best available option for modern cancer chronotherapeutics. In addition, novel approaches aiming to enhance the robustness of the circadian clocks in the host or in the cancer also represent a way forward, as illustrated by the recent findings of Dr. Panda and his team (Mure et al., 2018). However, as suggested in their studies, primates and mice share very few common genes of which display rhythmical expression. This finding highlights the diversity of the molecular clock across species. Thus, the design and evaluation of chrono-modulatory treatments in animal models calls for additional attention.” “With our constantly expanding mechanistic understanding of the molecular clock and its dynamic interaction with many metabolites, with the cell cycle and with cell survival pathways, as well as the refinement of mathematical models applied to systems-level data, I believe we will soon be able to change the landscape of chronotherapy. I look forward to seeing you, along with all other young scientists, working further and deeper on the biological clock in order to achieve this goal.” Despite immense advances in cancer research and the development of novel therapies in oncology over the past decades, cancer remains one of the leading causes of death worldwide. According to the World Health Organization’s (WHO) estimates of cancer incidence and mortality of all ages and both sexes presented for 2012, there were c.a. 1.8 million new cases and 1.6 million deaths of lung cancer alone. Therapeutic treatment options for many of these cancers are limiting, despite of intense research activities and many technological and biological innovations. Indeed, from a standpoint of pharmaceutical development, recent analysis on the development of novel oncologic drugs for breast, colorectal, and nonsmall cell lung cancer show very high attrition rates. Between 1979 and 2014 (Nixon et al., 2017), attrition rate for new cancer therapies has been significantly high. Over 80% for drug classes including cytotoxic chemotherapeutic reagents and cancer immunomodulators failed to advance to later stages in clinical trial. According to this analysis, oncological drugs are more likely to fail in late stage clinical trials (transition from Phase II to III) compared to other drugs. The authors concluded that adjusting and refining the design of early stage clinical trials may aid in the successful selection of drugs in later and more expensive stages of drug development (Nixon et al., 2017). An additional, important aspect – and possibly the real, “biological” crux of the matter at hand – is the distinct variation in drug responses between individual patients. This highlights the urgency and a need to understand the variables that exist between individuals in order to improve the current status of cancer treatment. Such knowledge could clearly benefit the testing and selection of potential drugs for further development and clinical testing. From this standpoint, the distinct genetic and epigenetic make-up of individuals contributes greatly to individual variation. Increasingly, we will therefore likely see basket trials in oncology, for example, where patients are stratified based on genetic/genomic markers, such as the absence of a particular tumor suppressor gene, for example, rather than the etiology of the tumor itself. Moreover, emerging evidence in chronobiology strongly supports the intertwining relationship between our cyclic environment, behavior, and physiology, as well as the influence on the biochemical and genetic activity of our tissues and organs. The question then is how we can exploit our fundamental knowledge of environmental and metabolic cycles to improve cancer treatment? While many factors come into play, this brief perspective focuses on how an appreciation for circadian biology might improve on the clinical use of global care standards in cancer chemotherapy. Over half a century ago, Dr. Mauricio Garcia-Sainz and Dr. Franz Halberg identified, through computational analyses, a 24-h mitotic rhythmicity in human mammary but not squamous and basal cell cancer biopsy samples obtained before or after radiotherapy (Garcia-Sainz and Halberg, 1966). They were able to distinguish the variance as rhythmicity <20 h and observed a population reduction of such ultradian rhythmicity in samples obtained after radiotherapy. This discovery established chronopathology and opened up the conceptual possibility for the development of chrono-modulated therapies. However, the potential of this information did not fully blossom until the identification of the first clock gene by Michael W. Young, Michael Rosbash, and Jeffrey C. Hall in the 1990’s. Since then, Prof. Francis Albert Lévi, a clinician and scientist, his team, as well as others in the field have been actively researching and promoting the concept of targeting the circadian clock to improve current cancer treatments* (see a short interview with Prof. Lévi on page XX of this perspective). However, to date, cancer chronotherapy faces numerous challenges, some of which we will discuss in this article. In the following sections, we will provide a simplified summary of the circadian clock, how circadian regulatory network extends into chemotherapeutics, and summarize up-to-date implications of chronobiology in cancer therapy *https://warwick.ac.uk/fac/sci/med/research/biomedical/labs/chronotherapy/about/. Due to the Earth’s rotation, virtually all life has adapted and evolved an approximately 24-h biological rhythmicity in order to anticipate periodic changes in our environment, such as light, temperature, and food availability. This behavioral and physiological rhythmicity driven by natural sunlight is termed the circadian clock (circa diem). One tenable theory is that organisms evolved to store and utilize energy in synchrony with its environments. Thus, most fundamental biological processes such as cell metabolism and growth are thought to follow a daily circa 24-h oscillation [for a review, see (Takahashi, 2016)]. However, a recent metabolomic analysis has elegantly demonstrated the existence of other (non-24-h) rhythmicity and periodicity as well (Krishnaiah et al., 2017). Overall, cellular processes are thus greatly subjected to cyclic environmental cues, responses, and behaviors. In animals, the eye possesses the ability to sense light. Upon exposure to light, complex signals are sent through the retinohypothalamic tract and subsequently processed in the suprachiasmatic nucleus (SCN). In the SCN, a relatively small population of specialized cells regulates the synthesis of the hormone melatonin by the pineal gland. The result of fluctuating melatonin levels, in turn, triggers the “resetting” of peripheral clocks, such as the liver and kidneys. These seemingly simple neurochemical and hormonal processes drive the most overt biological rhythmicity, the sleep-wake cycle, and is regarded as the central clock [for a review, see (Korf and von Gall, 2013)]. However, the molecular mechanism of how melatonin and likely other hormones synchronize peripheral tissues remains unclear. While natural cyclic exposure to light remains the key driver of our biological clocks, nutrients have emerged as another key factor in the synchrony of peripheral clocks. Liver, regarded as the metabolic hub, has been extensively characterized as a circadian organ (Koike et al., 2012). Transcriptomic and proteomic analyses on mice liver demonstrate the diurnal transcriptional and post-translational regulation of discrete cellular processes, which range from glucose and fatty acid metabolism to the cell cycle and autophagy (Robles et al., 2016; Wang et al., 2018). In agreement, several clinical studies have reported circadian rhythmicity in glucose, lipid and energy metabolism, such as insulin sensitivity and secretion, cholesterol synthesis, and fat oxidation (Poggiogalle et al., 2018). These findings further strengthen the concept of multiple cellular processes being under the direct and indirect influence of our environment, nutrition, behavior, and metabolism. At the cellular level, neurochemical and hormonal cues induced by light and nutrients prompt the resetting of the molecular clock. However, the molecular clock is governed by several interlocking transcription and translation feedback loops (TTFLs), which proceeds for a long time even in the absence of external cues. A recent, groundbreaking circadian transcriptomics study in the olive baboon (Papio anubis) revealed over 80% of protein-coding genes displayed a daily oscillation pattern in more than 60 examined tissues (Mure et al., 2018). The majority of cycling genes were mainly ubiquitously expressed genes, which are often involved in fundamental cellular processes, such as circadian rhythmicity, DNA replication, DNA repair, amino-sugar metabolism, and oxidative phosphorylation (Mure et al., 2018). To conclude, the biochemical and genetic response of a metazoan organism is influenced not only by our predetermined genetic and epigenetic make-up; but also by a plethora of ever-changing external stimuli, including light and nutrients. Thus, in addition to well-studied genetic (Kandoth et al., 2013) and metabolic alterations (DeNicola and Cantley, 2015) in cancer, we must now take into account both “clock alterations” and clock regulatory genetic and metabolic networks. Only in combination, will we potentially succeed in profiling cancer subtypes and strategizing treatments. In the following section, we will present our case on cancer chronotherapy and up-to-date findings on the relationship between the clock, cancer, and chemotherapeutics. Several recent findings indicate that there is a correlation between the circadian clock and the etiology of cancer. One bioinformatic study reported that clock genes in human tumor samples have altered gene expression profiles in comparison to normal, adjacent tissues (Ye et al., 2018). To no surprise, they also found a correlation between clock gene expression and anticancer drug sensitivity in cancer cell lines (Ye et al., 2018). To support this, a number of experimental and clinical studies have reported a negative correlation between clock disruption during and/or after treatment with survival rate in cancer animal models and patients (Sephton et al., 2013; Lévi et al., 2014; Papagiannakopoulos et al., 2016). These findings indicate a dysfunctional or functional clock may serve as an indicator for the outcome of cancer progression and treatment response. However, circadian modulated anticancer drug response and the potential effect of our environment and behavior on cancer development lack well-defined molecular insights necessary to comprehend and exploit the clock for common cancer treatments. In the following paragraphs, we summarize state-of-the-art findings in explaining how the circadian clock may improve the current status of cancer chemotherapy. There are various approaches targeted at treating cancer. Notably, in recent years, immunotherapeutic approaches have shown great promise and interest in the research and clinical community. Nevertheless, conventional chemotherapy, regardless whether administered as induction, combined, consolidation, or through other therapeutic strategies, remains one of the most broadly used and affordable treatments following surgical resection of tumor tissue. Despite current knowledge on how, for example, platinum-based and similar chemotherapeutic drugs function, debilitating adverse effects resulting from severe damage to normal and healthy tissues limits the dosing of drugs and treatment duration (Tacar et al., 2012; Dasari and Bernard Tchounwou, 2014). Using chemotherapeutic drugs at suboptimal doses and treatment duration, in turn, provides space for the cancer to develop drug resistance. Cancer therapy using chemotherapeutic agents thus persistently faces the major challenge of relapse. In the following, we summarize how the clock regulates the DNA damage repair machinery targeted by cytotoxic chemotherapeutical drugs, drug metabolism, and potentially drug resistance in cancer. Conventional chemotherapy targets cells with enhanced proliferation rates and/or an impaired DNA repair machinery to achieve elimination of cancerous cells (Corrie, 2008). The circadian clock regulates these key hallmarks of cancer of which includes cell proliferation, metabolism, and genome stability [for extensive reviews, see (Sancar et al., 2010; Masri et al., 2013; Panda, 2016)]. For example, cisplatin, a widely used and well-established chemotherapeutic drug in the treatment of numerous human cancers, exerts its function by crosslinking purine bases on DNA, causing bulky lesions. These bulky lesions interfere with DNA replication and overwhelm the DNA repair machinery, which generally results in cell death (for a review, see (Dasari & Bernard Tchounwou, 2014)). These bulky DNA adducts are typically sensed and resolved by the nucleotide excision repair (NER) pathway. The activity of one particular key DNA repair protein, xeroderma pigmentosum A (XPA), was shown to be under direct circadian control in vivo (Kang et al., 2009; Kang et al., 2010). This knowledge strengthens the notion of timed drug (such as cisplatin) administration in accordance to the circadian “trough” of the targeted cell process (in this case, NER repair machinery) to increase drug efficacy. Cancer is a highly heterogeneous disease, rendering it a challenge to target and treat, as the genome rapidly evolves and resistance mechanisms arise albeit the simplicity of “timely” targeting. There are several proposed mechanisms of resistance to chemotherapy. Beside suboptimal drug dosage and treatment duration, this includes changes in the cellular uptake and efflux of the chemotherapeutic agent, increased drug metabolism and elimination, as well as enhanced DNA repair machineries, mechanisms, which suppress tumor cell death (Mansoori et al., 2017). These resistance mechanisms emerge from processes that are controlled by the circadian clock (Sancar et al., 2010; Dallmann et al., 2014; Dallmann et al., 2016). Thus far, clinical studies have shown that several adverse effects experienced by cancer patients taking cisplatin-based chemotherapy decreases when cisplatin is applied in a chrono-modulated context (Li et al., 2015; Zhang et al., 2017). The results and outcomes of these studies indicate that the proper timing of drug administration reduces cisplatin-induced adverse effects in patients. Chronotherapy may thus potentially enable substantial increases in the maximally tolerated dose. This raises the possibility that more effective toxicity to the tumor cells could be achieved, providing potentially a higher selectivity relative to the toxic effect of chemotherapy on normal cells. In sum, the clock regulates the fundamental cell processes, which are often the targeted machinery of cytotoxic anticancer drugs. The clock also modulates the absorption, metabolism, and elimination of these drugs. In combination, chrono-modulated drug administration provides the potential to optimize the dosage of drugs and duration of treatments to efficiently eliminate highly proliferative cancerous cells while reducing limiting adverse effects to circumvent drug resistance. The potential for chronotherapy thus arises out of the physiological link between the cytotoxic cancer agents and molecular processes that respond to these agents on an organismic and cellular level. Several studies report clear changes in the effectiveness of cancer chronotherapy. However, significant interpatient variability persistently poses a major challenge for cancer chronotherapy to gain statistical power (Ballesta et al., 2017). Giacchetti and colleagues conducted a comparative meta-analysis on conventional and chrono-modulated chemotherapeutic treatments in 842 patients with metastatic colorectal cancer from three international randomized trials (Giacchetti et al., 2012). They found improved tumor response rate and overall survival, as compared to conventional chemotherapy in male patients by +3.3 months. Unexpectedly, the overall survival of female patients decreased by 1.8 months (Giacchetti et al., 2012). One pilot study involving 55 healthy people and 12 cancer patients found significant sex- and age-related variations in the coordination of individual circadian clocks as well (Komarzynski et al., 2018). These critical findings underscore the relevance of sex and age for cancer chronotherapy and require further investigations on their respective impacts for the scheduling of chronotherapy. Such variations likely stem from and result in the challenges listed below. There are at least three challenges faced by cancer chronotherapy. These include: 1. There is insufficient mechanistic insight at the level of basic research of how cancer and chemotherapeutic drugs affect the molecular clock and vice versa. This hampers the design of appropriate chrono-modulated clinical trials. In the last decade, tremendous effort has been put into deciphering the structure, function, and regulatory network of the molecular clock and its core components. While the field is rapidly gaining new insights on these fundamental biological questions, we have yet directly addressed the impact of the clock and metabolic environment on cytotoxic drug sensitivity in a systematic manner. Thus, in our opinion, the field requires a systematic high-throughput cell (organelle)-based screening capability on the circadian-dependent effects of chemotherapeutic cytotoxicity in both model cancer and primary cell lines. This would help confer novel mechanistic information. Ultimately, such information could provide valuable data to generate unique combinatorial (cancer, drug, and clock) profiles which may serve as guidelines clinical trial designs. 2. In clinical research, large variations among patients’ clocks can alter the statistical power of trials comparing chronotherapy to conventional treatment in patients with varying chronotypes (circadian clock). Cancer profiling is under constant refinement from tumor localization, cell morphology, and cell surface biomarkers to genetic and epigenetic aberrations. We now must also acknowledge that the variation extends to our biological clocks. The design of chrono-modulated chemotherapy may benefit immensely from compulsory documentation of patient routines including sleep/wake cycles, activity, metabolic profile, and drug administration in all related drug trials. While this is of course a great challenge in terms of data gathering and analysis, the European Medicines Agency (EMA) and its nearing release of the EMA Clinical Trial Information System (CTIS) with uniformed regulations and absolute transparency will aid us in moving towards an improved era of personalized and precise medicine tailored to individual chronotypes. Making chronotyping simple and easy. Some wear it for fashion; some wear it for health. Regardless, smart watches, apps (Gill and Panda, 2015, https://mycircadianclock.org/) or other digital devices have the ability of recording valuable information of our cyclic behavior, such as when we sleep, how we sleep, and when and how we eat and exercise. By combining a given patient’s “digital” chrono-data with “biological” chrono-data, such as biopsies and/or blood samples, clinicians could then start to successfully chronotype individual patients and strategize cancer treatments accordingly. Applying such routines to clinical trials could help stratify patients and the results of the effectiveness of particular pharmacological therapies. 3. Pharmaceutical companies should be incentivized to invest in (re-)examining the time-dependent efficacy and toxicity of chemotherapeutic drugs, or to design clock-based drugs. As suggested earlier (Nixon et al., 2017), the adjustment and refinement of early stage clinical trial design could permit a higher success rate in anticancer drug development. To put this into perspective, it costs on average a striking $2.6 billion USD to develop a drug (DiMasi et al., 2016). Considering the attrition rate of 80%, chronotherapeutic approaches could lead to the development of effective new anti-cancer drugs or improved dosing regimens. Pharmaceutical companies should take into account the effect of the clock and recognize the potential in re-examining drugs to increase not only the therapeutic value of approved drugs, but also re-evaluate new chemical entities. In conclusion, these interlinking challenges require collaborative efforts between basic science and medicine, clinicians, regulatory authorities, and pharmaceutical companies in order to obtain mechanistic insights and clinical statistics that would help shed light on how a given cancer affects the clock and vice versa, how a given oncotherapy affects the clock, and what other factors, such as our lifestyle and environment (personal chronotypes), can affect the clock and treatment responses. The landscape of chronotherapy is gradually maturing with the application of in silico pharmacology (Ekins et al., 2007), clinical big data (Mayo et al., 2017; Singh et al., 2018), in vitro pharmacology, and mathematical modeling (Dulong et al., 2015) to help expand our knowledge of the molecular clock and its relevance to human disease, consistent with the important trend toward personalized medicine. Here, we have analyzed and explored the case for chronotherapy as an option to improve the effectiveness of existing and future cytotoxic cancer therapies. A better appreciation for this underlying fundamental biological phenomenon and its potential for chronotherapy could benefit many cancer patients worldwide (Figure 1). Figure 1 Exploiting the circadian clock for improved cancer therapy. We are exposed to ever-changing light, temperatures, and nutrients on a daily basis. In response to these Cyclic Stimuli, our bodies modulate a wide range of physiological and cellular processes in an oscillatory manner (Chronobiology). Since chronobiology is a complex physiological phenomenon, it is currently not greatly considered as a factor in the research and development of novel anticancer drugs, nor in clinical trials. Nonetheless, recent studies have reported correlations between the circadian clock, cancer and therapy response. Giacchetti et al., 2012; Sephton et al., 2013; Lévi et al., 2014; Papagiannakopoulos et al., 2016; Ye et al., 2018. We suggest that an in-depth understanding of circadian mechanisms from single tissue types to entire systems, could potentially allow us to stratify individual patients not only by genomic and genetic aberrations in their tumors, but also by clock functions (Chronotype). this could be of great benefit and improve cancer therapies. TK contributed the idea, the draft and conducted the interview with Professor Francis Lévi. AL contributed the overall structure and corrected the text. AL is Co-Founder and CSO of Eisbach Bio GmbH. TK declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Ballesta, A., Innominato, P. F., Dallmann, R., Rand, D. A., Lévi, F. A. (2017). “Systems Chronotherapeutics,” in Ed. Watts, S. W.Pharmacological Review 69 (2), 161–199. doi: 10.1124/pr.116.013441 CrossRef Full Text | Google Scholar Corrie, P. G. (2008). Cytotoxic chemotherapy: clinical aspects. Medicine 36 (1), 24–28. doi: 10.1016/j.mpmed.2007.10.012 CrossRef Full Text | Google Scholar Dallmann, R., Brown, S. A., Gachon, F. (2014). Chronopharmacology: new insights and therapeutic implications. Annu. Rev. Pharmacol. Toxicol. 54 (1), 339–361. doi: 10.1146/annurev-pharmtox-011613-135923 PubMed Abstract | CrossRef Full Text | Google Scholar Dallmann, R., Okyar, A., Lévi, F. (2016). Dosing-time makes the poison: circadian regulation and pharmacotherapy. Trends Mol. Med. 22 (5), 430–445. doi: 10.1016/j.molmed.2016.03.004 PubMed Abstract | CrossRef Full Text | Google Scholar Dasari, S., Bernard Tchounwou, P. (2014). Cisplatin in cancer therapy: molecular mechanisms of action. Eur. J. Pharmacol. 740, 364–378. doi: 10.1016/j.ejphar.2014.07.025 PubMed Abstract | CrossRef Full Text | Google Scholar DeNicola, G. M., Cantley, L. C. (2015). Cancer’s fuel choice: new flavors for a picky eater. Mol. Cell 60 (4), 514–523. doi: 10.1016/j.molcel.2015.10.018 PubMed Abstract | CrossRef Full Text | Google Scholar DiMasi, J. A., Grabowski, H. G., Hansen, R. W. (2016). Innovation in the pharmaceutical industry: new estimates of R######D costs. J. Health Economics 47, 20–33. doi: 10.1016/j.jhealeco.2016.01.012 CrossRef Full Text | Google Scholar Dulong, S., Ballesta, A., Okyar, A., Lévi, F. (2015). Identification of circadian determinants of cancer chronotherapy through in vitro chronopharmacology and mathematical modeling. Mol. Cancer Ther. 14 (9), 2154–2164. doi: 10.1158/1535-7163.MCT-15-0129 PubMed Abstract | CrossRef Full Text | Google Scholar Ekins, S., Mestres, J., Testa, B. (2007). In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling. Br. J. Pharmacol. 152 (1), 9–20. doi: 10.1038/sj.bjp.0707305 PubMed Abstract | CrossRef Full Text | Google Scholar Garcia-Sainz, M., Halberg, F. (1966). Mitotic rhythms in human cancer, reevaluated by electronic computer programs-evidence for chronopathology2 . JNCI J. Natl. Cancer Institute 37 (3), 279–292. doi: 10.1093/jnci/37.3.279 CrossRef Full Text | Google Scholar Giacchetti, S., Dugué, P. A., Innominato, P. F., Bjarnason, G. A., Focan, C., Garufi, C. (2012). Sex moderates circadian chemotherapy effects on survival of patients with metastatic colorectal cancer: a meta-analysis. Ann. Oncol. 23 (12), 3110–3116. doi: 10.1093/annonc/mds148 PubMed Abstract | CrossRef Full Text | Google Scholar Gill, S., Panda, S. (2015). A smartphone app reveals erratic diurnal eating patterns in humans that can be modulated for health benefits. Cell Metab. 22 (5), 789–798. doi: 10.1016/j.cmet.2015.09.005 PubMed Abstract | CrossRef Full Text | Google Scholar Kandoth, C., McLellan, M. D., Vandin, F., Ye, K., Niu, B., Lu, C. (2013). Mutational landscape and significance across 12 major cancer types. Nat. Publishing Group 502 (7471), 333–339. doi: 10.1038/nature12634 CrossRef Full Text | Google Scholar Kang, T. H., Reardon, J. T., Kemp, M., Sancar, A. (2009). Proceedings of the National Academy of Sciences Feb 2009. 106 (8), 2864–2867. doi: 10.1073/pnas.0812638106 CrossRef Full Text | Google Scholar Kang, T. H., Lindsey-Boltz, L. A., Reardon, J. T., Sancar, A. (2010). Circadian control of XPA and excision repair of cisplatin-DNA damage by cryptochrome and HERC2 ubiquitin ligase. Proc. Natl. Acad. Sci. 107 (11), 4890–4895. doi: 10.1073/pnas.0915085107 CrossRef Full Text | Google Scholar Koike, N., Yoo, S. H., Huang, H. C., Kumar, V., Lee, C., Kim, T. K., et al. (2012). Transcriptional architecture and chromatin landscape of the core circadian clock in mammals. Science 1–7. Google Scholar Komarzynski, S., Huang, Q., Innominato, P. F., Maurice, M., Arbaud, A., Beau, J. (2018). Relevance of a mobile internet platform for capturing inter- and intrasubject variabilities in circadian coordination during daily routine: pilot study. J. Med. Internet Res. 20 (6), e204–e218. doi: 10.2196/jmir.9779 PubMed Abstract | CrossRef Full Text | Google Scholar Korf, H.-W., von Gall, C. (2013). “Circadian Physiology,” in Neuroscience in the 21st Century: From Basic to Clinical. Neuroscience in the 21st Century: From Basic to Clinical. Ed. Pfaff, D. W. (New York, NY: Springer New York), 1813–1845. doi: 10.1007/978-1-4614-1997-6_65 CrossRef Full Text | Google Scholar Krishnaiah, S. Y., Wu, G., Altman, B. J., Growe, J., Rhoades, S. D., Coldren, F. (2017). Clock regulation of metabolites reveals coupling between transcription and metabolism. Cell Metab. 25 (4), 961–974.e4. doi: 10.1016/j.cmet.2017.03.019 CrossRef Full Text | Google Scholar Lévi, F., Dugué, P. A., Innominato, P., Karaboué, A., Dispersyn, G., Parganiha, A. (2014). Wrist actimetry circadian rhythm as a robust predictor of colorectal cancer patients survival. Chronobiol. Int. 31 (8), 891–900. doi: 10.3109/07420528.2014.924523 PubMed Abstract | CrossRef Full Text | Google Scholar Li, J., Chen, R., Ji, M., Zou, S. L., Zhu, L. N. (2015). Cisplatin-based chronotherapy for advanced non-small cell lung cancer patients: a randomized controlled study and its pharmacokinetics analysis. Cancer Chemother. Pharmacol. 76 (3), 651–655. doi: 10.1007/s00280-015-2804-x PubMed Abstract | CrossRef Full Text | Google Scholar Mansoori, B., Mohammadi, A., Davudian, S., Shirjang, S., Baradaran, B. (2017). The different mechanisms of cancer drug resistance: a brief review. Tabriz Univ. Med. Sci. 7 (3), 339–348. doi: 10.15171/apb.2017.041 CrossRef Full Text | Google Scholar Masri, S., Cervantes, M., Sassone-Corsi, P. (2013). The circadian clock and cell cycle: interconnected biological circuits. Curr. Opin. Cell Biol. 25 (6), 730–734. doi: 10.1016/j.ceb.2013.07.013 PubMed Abstract | CrossRef Full Text | Google Scholar Mayo, C. S., Matuszak, M. M., Schipper, M. J., Jolly, S., Hayman, J. A., Ten Haken, R. K. (2017). Big data in designing clinical trials: opportunities and challenges. Front. Oncol. 7, 187–187. doi: 10.3389/fonc.2017.00187 PubMed Abstract | CrossRef Full Text | Google Scholar Mure, L.S., Le, H.D., Benegiamo, G., Chang, M.W., Rios, L., Jillani, N. (2018). Diurnal transcriptome atlas of a primate across major neural and peripheral tissues. Science 359 (6381), eaao0318–20. doi: 10.1126/science.aao0318 PubMed Abstract | CrossRef Full Text | Google Scholar Nixon, N. A., Khan, O. F., Imam, H., Tang, P. A., Monzon, J., Li, H. (2017). Drug development for breast, colorectal, and non-small cell lung cancers from 1979 to 2014 . Cancer 123 (23), 4672–4679. doi: 10.1002/cncr.30919 PubMed Abstract | CrossRef Full Text | Google Scholar Panda, S. (2016). Circadian physiology of metabolism. Science 354 (6315), 1008–1015. doi: 10.1126/science.aah4967 PubMed Abstract | CrossRef Full Text | Google Scholar Papagiannakopoulos, T., Bauer, M. R., Davidson, S. M., Heimann, M., Subbaraj, L., Bhutkar, A. (2016). Circadian rhythm disruption promotes lung tumorigenesis. Cell Metab. 24 (2), 324–331. doi: 10.1016/j.cmet.2016.07.001 PubMed Abstract | CrossRef Full Text | Google Scholar Poggiogalle, E., Jamshed, H., Peterson, C. M. (2018). Circadian regulation of glucose, lipid, and energy metabolism in humans. Metabolism 84 (C), 11–27. doi: 10.1016/j.metabol.2017.11.017 PubMed Abstract | CrossRef Full Text | Google Scholar Robles, M. S., Humphrey, S. J., Mann, M. (2016). Phosphorylation is a central mechanism for circadian control of metabolism and physiology. Cell Metab. 25 (1), 118–127 . doi: 10.1016/j.cmet.2016.10.004 PubMed Abstract | CrossRef Full Text | Google Scholar Sancar, A., Lindsey-Boltz, L. A., Kang, T. H., Reardon, J. T., Lee, J. H., Ozturk, N. (2010). Circadian clock control of the cellular response to DNA damage. FEBS Lett. 584 (12), 2618–2625. doi: 10.1016/j.febslet.2010.03.017 PubMed Abstract | CrossRef Full Text | Google Scholar Sephton, S. E., Lush, E., Dedert, E. A., Floyd, A. R., Rebholz, W. N., Dhabhar, F. S. (2013). Diurnal cortisol rhythm as a predictor of lung cancer survival. Advances in cancer and brain, behavior, and immunity. A Decade Prog. 30, S163–S170. doi: 10.1016/j.bbi.2012.07.019 CrossRef Full Text | Google Scholar Singh, G., Schulthess, D., Hughes, N., Vannieuwenhuyse, B., Kalra, D. (2018). Real world big data for clinical research and drug development. Drug Discovery Today 23 (3), 652–660. doi: 10.1016/j.drudis.2017.12.002 PubMed Abstract | CrossRef Full Text | Google Scholar Tacar, O., Sriamornsak, P., Dass, C. R. (2012). Doxorubicin: an update on anticancer molecular action, toxicity and novel drug delivery systems. J. Pharm. Pharmacol. 65 (2), 157–170. doi: 10.1111/j.2042-7158.2012.01567.x PubMed Abstract | CrossRef Full Text | Google Scholar Takahashi, J. S. (2016). Transcriptional architecture of the mammalian circadian clock. Nat. Rev. Genet. 18, 3, 164–179. doi: 10.1038/nrg.2016.150 PubMed Abstract | CrossRef Full Text | Google Scholar Wang, Y., Song, L., Liu, M., Ge, R., Zhou, Q., Liu, W. (2018). A proteomics landscape of circadian clock in mouse liver. Nat. Commun. 1–16. doi: 10.1038/s41467-018-03898-2 PubMed Abstract | CrossRef Full Text | Google Scholar Ye, Y., Xiang, Y., Ozguc, F. M., Kim, Y., Liu, C. J., Park, P. K. (2018). The genomic landscape and pharmacogenomic interactions of clock genes in cancer chronotherapy. Cell Syst. 6 (13), 1–19. PubMed Abstract | Google Scholar Zhang, P. X., Jin, F., Li, Z. L., Wu, W. L., Li, Y. Y., Long, J. H. (2017). A randomized phase II trial of induction chemotherapy followed by cisplatin chronotherapy versus constant rate delivery combined with radiotherapy. Chronobiol. Int. 35 (2), 240–248. doi: 10.1080/07420528.2017.1397684 PubMed Abstract | CrossRef Full Text | Google Scholar Keywords: chronotherapeutic, circadian rhythm, chemotherapy, cancer, precision (stratified) medicine Citation: Kuo TT and Ladurner AG (2019) Exploiting the Circadian Clock for Improved Cancer Therapy: Perspective From a Cell Biologist. Front. Genet. 10:1210. doi: 10.3389/fgene.2019.01210 Received: 18 March 2019; Accepted: 04 November 2019; Published: 11 December 2019. Edited by: Reviewed by: Copyright © 2019 Kuo and Ladurner. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. *Correspondence: Tia Tyrsett Kuo, [email protected]
Ramesh C Mishra, Darrell Belke, Cini Mathew John, Heike Wulff, Andrew P Braun
Published: 1 April 2019
The FASEB Journal, Volume 33, pp 683.3-683.3; https://doi.org/10.1096/fasebj.2019.33.1_supplement.683.3

Abstract:
Endothelial dysfunction represents an independent risk factor contributing to the onset and progression of cardiovascular complications (e.g. hypertension, cardiomyopathy, stroke) in patients with Type 2 Diabetes (T2D). It is further predicted that reduction/reversal of endothelial dysfunction will mitigate T2D-associated cardiovascular deficits. Small- and intermediate-conductance, Ca2+-activated K+ channels (KCa2.3 and KCa3.1, respectively) are prominently expressed in the vascular endothelium, and pharmacologic activators of these channels (e.g. SKA-31) induce robust vasodilation upon acute application to isolated resistance arteries and intact animals. However, the effects of prolonged, in vivo administration of a KCa activator on the cardiovascular system have not been examined to date. In our current study, we have hypothesized that daily administration of SKA-31 (10 and 30 mg/kg, I.P. injection) to male, non-obese Type 2 Diabetic Goto-Kakizaki rats (T2D GK, 14 weeks of age) for 12 weeks would oppose the development of diabetes-related cardiac dysfunction. Echocardiographic analyses revealed that left ventricular (LV) ejection fraction, stroke volume and fractional shortening all significantly declined over time in vehicle-treated rats, but remained at pre-trial levels in animals administered either 10 or 30 mg/kg SKA-31 for 12 weeks (n = 5–6/group). Chronic blood pressure measurements over the same period via radiotelemetry further revealed that SKA-31 treatment lowered mean arterial pressure, compared with vehicle treated animals, with effects observed on both systolic and diastolic pressures (n = 5–6/group). To determine if the observed improvements in cardiac performance may be due to direct changes in the responsiveness of the coronary vasculature, isolated hearts from vehicle and SKA-31 treated T2D GK rats were mounted in a Langendorff perfusion system under constant pressure (n ≥ 3/group). We observed that endothelium-dependent, agonist-evoked increases in coronary flow were similar in hearts from vehicle and SKA-31 treated animals, as was baseline LV developed pressure. Histological staining of isolated hearts revealed differing levels of LV collagen content in the 3 treatment groups. In summary, these results indicate that prolonged SKA-31 administration in T2D GK rats can improve cardiac function, which likely occur via both direct and indirect effects. Support or Funding Information This study was supported by research funding to APB from the Canadian Institutes of Health Research (MOP-142467) and the Natural Sciences and Engineering Research Council of Canada (RGPIN-2017-04116), and to HW from the National Institutes of Health (R21 NS101876). This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.
Kole J Hermanson, Atrayee Bhattacharya, Archana J Dhasarathy
Published: 1 April 2019
The FASEB Journal, Volume 33, pp 647.11-647.11; https://doi.org/10.1096/fasebj.2019.33.1_supplement.647.11

Abstract:
Breast cancer is the most common cancer among women worldwide, with many breast cancer-associated deaths being attributed to metastasis of the primary tumor. In a process known as Epithelial to Mesenchymal transition (EMT), normal epithelial cells lose their cell-to-cell adhesions, become elongated and migratory, resulting in the mesenchymal phenotype. The SNAIL protein is known to be a master regulator of EMT, serving to repress expression of genes associated with cellular adhesion and activate genes involved in chemoresistance. In vivo and in vitro studies have both indicated that high levels of SNAIL correlate with poor prognosis, increased chemoresistance, and greater probability of recurrence of the tumor. Calcium signaling in the cell is important for several biological functions, and was implicated in EMT and breast cancer. To determine which calcium channels were involved in SNAIL upregulation during TGF-β induced EMT, we blocked store-operated calcium entry (SOCE) with 2-aminoethoxydiphenylborane (2APB). This reduced cell migration but, paradoxically, increased the level of TGF-β dependent SNAIL gene activation. We determined that this increased SNAIL transcription involved signaling through the AKT pathway and subsequent binding of NF-κB (p65) at the SNAIL promoter in response to TGF-β. We also demonstrated that the calcium channel protein ORAI3 and the stromal interaction molecule 1 (STIM1) are required for TGF-β dependent SNAIL transcription. These results suggest that calcium channels differentially regulate cell migration and SNAIL transcription, indicating that each of these steps could be targeted to ensure complete blockade of cancer progression. We are currently testing whether this increase in SNAIL contributes to chemoresistance, and if blockade of ORAI3 can inhibit chemoresistance. Support or Funding Information This work was funded by grant support from the National Institutes of Health grants P20-GM104360 to Archana Dhasarathy and UND School of Medicine and Health Sciences. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.
Kristen A Engevik, Hikaru Hanyu, Andrea L Matthis, Eitaro Aihara, Marshall H Montrose
Published: 1 April 2019
The FASEB Journal, Volume 33, pp 869.18-869.18; https://doi.org/10.1096/fasebj.2019.33.1_supplement.869.18

Abstract:
Background Calcium (Ca2+) is a known accelerator for gastric repair. However the mechanism by which Ca2+ mobilizes to promote repair remains unclear, and cannot be readily evaluated in vivo. Using gastric organoids derived from transgenic mice expressing a fluorescent Ca2+ reporter (yellow cameleon-nano15; YC-Nano), we previously observed intracellular Ca2+ increases in cells directly adjacent to a damaged cell. Using this Ca2+ sensor, we investigate the potential sources of intracellular Ca2+ essential for repair. Methods Gastroids generated from YC-Nano mouse stomach corpus were cultured 4–5 days prior to experiments. Photodamage and resultant cell death was induced to 1–2 gastroid epithelial cells by ~3 sec high intensity 840 nm light. YC-Nano reports Förster resonance energy transfer (FRET) from CFP to YFP in response to increased intracellular Ca2+. Change in intracellular Ca2+ was measured as FRET/CFP ratio, in cells adjacent to damaged cells. Inhibitors were used to test roles of Ca2+ channels (10 μM verapamil, 20 μM YM58483), intracellular Ca2+ (50 μM BAPTA/AM), Phospholipase C (10 μM U73122), and IP3R (50 μM 2-APB). Results Unperturbed gastroid cells maintain a constant FRET ratio, indicating stable Ca2+ levels. In response to photodamage of the gastroid epithelium, increased levels of Ca2+ were observed specifically within the lateral membranes of cells neighboring the damaged cell. Chelation of intracellular Ca2+ by BAPTA/AM resulted in significant dampening of Ca2+ response, as well as blocking prompt repair. Inhibition of L-type channels (verapamil) or store operated Ca2+ entry (YM58483) resulted in delaying repair and dampening intracellular Ca2+ response. Furthermore, inhibition of PLC (U73122) or IP3R (2-APB) resulted in delayed repair and dampened Ca2+ response. Conclusion These results suggest both extracellular and intracellular Ca2+ sources are essential for supplying the Ca2+ that stimulates repair. The findings implicate an intracellular Ca2+ raise mediated via Ca2+ uptake via plasma membrane Ca2+ channels and intracellular Ca2+ release from the ER. Collectively this work indicates the usefulness of YC-Nano to further assess intracellular Ca2+ dynamics and further investigate the signaling cascade behind Ca2+-mediated repair. Support or Funding Information This work was supported by the National Institutes of Health (NIH) R01DK102551 (Montrose; Aihara) and F31DK115126 (Engevik). This project was also supported in part by the NIH P30 DK078392; Live Microscopy Core and DNA Sequencing and Genotyping Core of the Digestive Disease Research Core Center in Cincinnati. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.
Helen Rachel Heathcote, Matthew David Lee, Calum Wilson, John G McCarron
Published: 1 April 2019
The FASEB Journal, Volume 33, pp 827.7-827.7; https://doi.org/10.1096/fasebj.2019.33.1_supplement.827.7

Abstract:
The vascular endothelium lines the the entire vascular network and is a critical regulator of vascular tone given its ability to sense the complex composition of vasoactive substances in the circulating blood, as well as hemodynamic stresses and mechanical forces acting on the blood vessel wall. TRPV4 is a Ca2+ permeable cation channel which is expressed in the membrane of the endothelium and is activated by osmotic, mechanical and chemical stimuli, including the pharmacological agent GSK1016790A (GSK101). TRPV4 is an important contributor to endothelial regulation of vascular tone. Ca2+ influx from outside cells is a key messenger in the signalling cascades which transduce activating stimuli sensed by the endothelium into a functional output in the underlying smooth muscle. Previous studies suggested that the TRPV4 activation evoked endothelium-dependent relaxation solely as a result of Ca2+ influx via TRPV4. However, recently, we found the endothelium-dependent vasorelaxation evoked by TRPV4 activation was attenuated when Ca2+ release from the internal store was prevented. Here, we investigated the link between TRPV4 activation and Ca2+ release from the internal store. In mesenteric arteries from 8–12 week old Sprague Dawley rats, we visualised Ca2+ signalling (Cal-520/AM) in response to GSK101(20 nM) and used pharmacological agents to characterise the signalling pathway leading to vasorelaxation. In conjunction, we also measured the contractile response of the arteries in response to the vasoconstrictor phenylephrine (PE), in the absence and presence of GSK101, the endothelium and after Ca2+ store depletion. All vessels were perfused with MOPS buffer in which all drugs were diluted. Images were captured using a high-sensitivity CCD camera and analysed using custom analysis packages written in Python. The TRPV4 activator GSK101 (20 nM) stimulated a ‘slow’ continuous global rise in intracellular Ca2+ on which ‘fast’ sporadic intracellular waves which propagated both within and between cells occurred. All Ca2+ signals (slow and fast) were inhibited by the removal of extracellular Ca2+ or by prior treatment with the TRPV inhibitors, Ruthenium Red and HC067047. On the other hand, prior depletion of the intracellular store with cyclopiazonic acid (CPA) or inhibition of phospholipase C (PLC) using U73122, or block of the IP3-receptor with 2-APB inhibited only the widespread propagating waves. These data suggest that TRPV4 activation caused Ca2+ influx that induced IP3-evoked Ca2+ release and propagating Ca2+ waves. In PE pre-constricted vessels, GSK101 (20 nM) induced a dilation that was entirely dependent upon an intact endothelium. Prior depletion of the intracellular store using CPA prevented the inhibitory effect of GSK on PE-induced contractions indicating that vasodilation induced by the TRPV4 activator GSK101 is dependent upon IP3-stimulated Ca2+ release from the endothelium's internal Ca2+ store. These results suggest that Ca2+ influx via the plasma membrane channel TPRV4, evokes a novel Ca2+-induced Ca2+ release like mechanism acting at the IP3 receptor in the intact endothelium to evoke vasodilation. Support or Funding Information BHF This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.
Guylain Boulay, Julien Malette, Jade Degrandmaison, Hugo Giguère, Jonathan Berthiaume, Maude Frappier, Jean‐Luc Parent, Mannix Auger‐Messier
Published: 1 April 2019
Abstract:
STIM1 is a regulatory protein of store-operated calcium entry (SOCE) and its expressions of in the cardiomyocytes suggests that it may play a role in cardiomyocytes function. To better understand this role, we sought to identify unknown protein partners of STIM1. We fused the ERM domain of STIM1 (amino acids 219–548) to GST and used it for a GST-pulldown assay combined with analytical liquid chromatography-mass spectrometry. From the lysate of RIPA-solubilized proteins from adult rat hearts, we identified the muscle-related coiled-coil protein (MURC), also known as Cavin-4, as a potential candidate. Also, we show that is the HR1 domain of MURC interacts with the ERM domains of STIM1. To understand the role of this interaction, we overexpressed MURC in neonatal rat ventricular myocytes (NRVM) and determined is impact on SOCE. NRVM were loaded with the Ca2+ probe, FURA-2AM, and incubated with nifedipine to prevent Ca2+ entry at the plasma membrane via L-type calcium channels. To induce intracellular store depletion and SOCE activation, 10mM caffeine and 2μM thapsigargin were added to the perfusion buffer in the absence of extracellular Ca2+ and Ca2+ entry was determined when Ca2+ was re-introduced in the extracellular medium. Using this protocol, we demonstrated that the Ca2+ entry in NRVM overexpressing MURC is 1.8-fold higher that control bGal condition. This effect is reduced by SOCE inhibitors (SKF-96365, 2-APB, and YM-58483). The Ca2+ entry measured in NRVM overexpressing ΔHR1-MURC was similar to the Ca2+ entry in the bGal control. These results indicate that MURC overexpression relies on its HR1 domain to potentiate SOCE in these cells. The increase in SOCE in MURC overexpressing NRVM may be the result from an enhanced interaction between Orai1 and STIM1. To test this possibility, we assessed the extent of STIM1-Orai1 complex formation with a co-immunoprecipitation assay using HA-Orai1 as the target protein. The STIM1-Orai1 interaction was evaluated in resting conditions or upon SOCE activation. As expected, SOCE activation enhanced the interaction between STIM1 and Orai1 by 2.80-fold compared to the control condition. MURC overexpression was also sufficient to increase the STIM1-Orai1 complex formation in resting (1.78-fold) and Ca2+ store-depleted (2.44-fold) conditions. These results show that MURC overexpression in NRVM favors the interaction of STIM1 with Orai1. Also, we show that R140W-MURC mutant, a missense variant of the HR1 domain associated with human dilated cardiomyopathy, exacerbates the SOCE increase in NRVM. Our study provides novel evidence that MURC regulates SOCE by interacting with STIM1 in cardiomyocytes. In addition, we identified a first potential mechanism by which the R140W mutation may contribute to Ca2+ mishandling and the development of cardiomyopathies. Support or Funding Information Supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) [M.A.M, and G.B.], CRMUS graduate student research award [J.M.], FRQS doctoral training award [J.D.], CIHR graduate scholarship [H.G.], André-Lussier Research Chair [J.-L.P.], and FRQS and Heart and Stroke Foundation of Canada Investigator awards [M.A-M.]. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.
Michael William Country, Michael Jonz
Published: 1 April 2019
The FASEB Journal, Volume 33, pp 727.1-727.1; https://doi.org/10.1096/fasebj.2019.33.1_supplement.727.1

Abstract:
About 65 years ago, the first intracellular recordings ever to be made in the retina were made in horizontal cells (HCs) of goldfish (Carassius auratus). These recordings were some of the first examples of graded potentials (where membrane potential changes in proportion with a stimulus), and it was assumed that outer retinal neurons did not present action potentials (APs). HCs are interneurons which provide inhibitory feedback to photoreceptors, and in vision they are responsible for improving contrast, edge detection, and color opponency. Since these first recordings, Ca2+-based APs and spontaneous increases in intracellular Ca2+ concentration ([Ca2+]i) have been found in fish HCs, although they are poorly understood and their role in vision (if any) is unknown. We characterized spontaneous, Ca2+-based APs in isolated goldfish HCs by measuring changes in [Ca2+]i and membrane potential (Vm). Using Fura-2 Ca2+ imaging, we found spontaneous Ca2+ activity characterized by transient elevation in [Ca2+]i of short (seconds) and long (minutes) duration, in 157/177 cells (89%). These APs were similar in amplitude to Ca2+ responses evoked by glutamate. APs were reversibly eliminated in Ca2+-free solutions (n=18), and were abolished by the L-type Ca2+ channel blocker, nifedipine (100 μM; n=5). APs were also dependent on intracellular Ca2+ stores: they were abolished by the ryanodine receptor antagonists, ryanodine (20 μM; in 7/8 cells) and dantrolene (50 μM; n=7). The ryanodine receptor agonist, caffeine (n=10), increased AP frequency 2.8-fold (p<0.0002) and reduced median duration (29.3 s to 18.7 s), time to peak (12.3 s to 7.8 s), and area under the curve (by 59.6%). When caffeine was co-applied with the store-operated channel antagonist, 2-aminoethyldiphenyl borate (2-APB), frequency was unaffected, further confirming a role for stores. We tracked changes in Vm with whole-cell current-clamp recording, and with the voltage-sensitive dye, FluoVolt. Phenotypes of APs in FluoVolt (n=6) and current-clamp (48/57 cells; 84%) experiments displayed a sharp rise to peak, followed by a slow decline for the duration of the transient, and a steep return to baseline. In current-clamp experiments, APs were dependent on L-type Ca2+ channel activity. APs were blocked by Co2+ (5 mM; n=5) and nifedipine (100 μM; n=5), and were amplified and prolonged by the L-type channel-permeant ion, Ba2+ (15 mM; n=6). In addition, APs were abolished in 6/9 cells in Ca2+-free solution. Collectively, our data suggest that activation of voltage-dependent L-type Ca2+ channels leads to Ca2+ influx, depolarization of Vm, and additional Ca2+ release from stores via ryanodine receptors. Understanding this phenomenon is a first step to elucidating a possible role for APs in vision or retinal physiology. This work also challenges the long-held belief that outer retinal neurons do not present APs, and may lead to new paradigms about how visual information is encoded in the vertebrate retina. Support or Funding Information We acknowledge the support of the Natural Sciences and Engineering Research Council of Canada (NSERC), grant 342303. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.
Rayan Khaddaj Mallat, Cini Mathew John, Ramesh C Mishra, Dylan J Kendrick, Heike Wulff, Andrew P Braun
Published: 1 April 2019
The FASEB Journal, Volume 33, pp 685.2-685.2; https://doi.org/10.1096/fasebj.2019.33.1_supplement.685.2

Abstract:
Endothelial dysfunction has been identified as an early event in the progression of cardiovascular complications (e.g. hypertension, cardiomyopathy, stroke) commonly observed in patients with Type 2 Diabetes (T2D). Importantly, reduction/reversal of endothelial dysfunction is expected to mitigate the cardiovascular deficits associated with T2D. Small- and intermediate-conductance, Ca2+-activated K+ channels (KCa2.3 and KCa3.1, respectively) are prominently expressed in the vascular endothelium, and pharmacologic activators of these channels (e.g. SKA-31) induce robust vasodilation upon acute exposure in isolated arteries and intact animals. However, the effects of prolonged in vivo administration of KCa activators such as SKA-31 have not been examined to date. In our current study, we have hypothesized that daily administration of SKA-31 (10 and 30 mg/kg, I.P. injection) to male, Type 2 Diabetic Goto-Kakizaki rats (T2D GK, 14 weeks of age) for 12 weeks would ameliorate diabetes-related cardiovascular deficits. In isolated mesenteric resistance arteries examined by pressure myography, we observed that SKA-31 treatment significantly improved endothelium-dependent vasodilation in response to 0.3 μM acetylcholine (ACh) (percent of maximal dilation = 37.7 ± 7.3% and 33.6 ± 6.2% for 10 and 30 mg/kg treatments) compared with vehicle-treated animals (20.7 ± 3.1%) (means ± S.D., n = 6 animals/group). Similar effects were observed for 0.3 μM bradykinin (BK) (evoked vasodilation = 54.1 ±7.8% and 47.9 ± 6.6% for 10 and 30 mg/kg SKA-31, respectively) compared with vehicle (33.6 ±6.1%). SKA-31 administration also reduced alpha1-adrenergic (phenylephrine, 1 μM) stimulated constriction in 10 and 30 mg/kg treated T2D GK rats (percent of maximal contraction = 37.1 ± 5.0% and 36.1 ± 3.7%, respectively) compared with vehicle treated animals (46.6 ± 4.5%, n = 6 per group). Western blot analyses further revealed that SKA-31 administration increased the expression of mesenteric KCa2.3 and KCa3.1 channels and associated cell-signaling components (i.e. type 1 IP3 receptor and the SERCA2 Ca2+-ATPase) that contribute to endothelium-dependent, agonist-evoked vasodilation. In contrast, SKA-31 treatment did not augment ACh and BK evoked vasodilation in myogenically active, cremaster skeletal muscle resistance arteries from the same animals, compared with the vehicle treated group. Collectively, these data demonstrate that in vivo administration of an endothelial KCa channel activator can selectively improve vascular function in the setting of T2D. Support or Funding Information This study was supported by research funding to APB from the Canadian Institutes of Health Research (MOP-142467) and the Natural Sciences and Engineering Research Council of Canada (RGPIN-2017-04116), and to HW from the National Institutes of Health (R21 NS101876). This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.
, Martial Saugy, Louis Passfield, James Hopker
Published: 1 March 2019
Frontiers in Physiology, Volume 10; https://doi.org/10.3389/fphys.2019.00169

Abstract:
Editorial on the Research TopicPerformance Modeling and Anti-doping Medals shine under the spotlight for the winning athletes. In the context of global sport, athletic performance is scrutinized more than ever and the fight against doping is often considered as the shady side of the medal. The Athlete's Biological Passport (ABP) was developed in an attempt to impede athletes' use of substances identical to those naturally produced by the human body (Sottas et al., 2011). Since its progressive implementation, the APB has become a strong tool for the indirect detection of doping (in blood) (Saugy et al., 2014; Zorzoli et al., 2014). Athletes aim to improve athletic performance via doping, but these practices may also influence biomarkers measured longitudinally as part of the ABP. However, numerous confounding factors (e.g., exercise training, hypoxic exposure, heat stress) are also known to alter these ABP parameters (Bouchard, 2015). There is therefore a need to gather additional information on athletes to strengthen the ABP, and provide a more forensic style intelligence led approach to anti-doping. One such approach is afford by the recent growth of technology in sports affording the ability to analyse and large volumes of data from both training and performance. Indeed, experts and scientists have gathered rudimentary performance data for decades to better understand the mechanisms underlying performance production (Faria et al., 2005; Borresen and Lambert, 2009; Sweeting et al., 2017), and with the aim of objectifying successes and failures of training strategies (Jobson et al., 2009; Passfield et al., 2017). The potential use of performance data for anti-doping purposes has only relatively recently been proposed (Schumacher and Pottgiesser, 2009), but has led to heightened interest in the area. The objective of this Research Topic is to discuss the potential for scientific evidence-based models of athletic performance to provide a cost effective tool that can be used by anti-doping organizations in the fight against doping in sports. This research topic initially considers the outlook for athlete performance monitoring within an anti-doping context (and beyond!) from scientific experts of the anti-doping community (Iljukov and Schumacher; Hopker et al.). Next, it is interesting to consider how data can be utilized in the field to track changes in performance and adjust training strategies. In cycling for instance, power output is recorded extensively by nearly all professional teams and athletes both during training and races. This allows, for example, the use of peak power profiles to monitor training load and to adjust training programs to reach peak fitness at certain moments of the season (Pinot and Grappe, 2011, 2015). Since the ABP was first adopted in cycling by the Union Cycliste Internationale (UCI) in 2009 (by tracking hematological changes in professional cyclists), there has been a desire to better exploit this data by incorporating changes in performance in order to improve targeting. The development and selection of an adequate model is the first step that needs to be addressed, with some propositions in this research topic (Menaspà and Abbiss; Montagna and Hopker; Puchowicz et al.). Concretely, Montagna and Hopker address the use of athlete performance data with a Bayesian approach much similar to the monitoring of hematological parameters in the ABP. Puchowicz et al. then propose a model specific to cycling using calculation of critical power (i.e., modelof the power-duration curve) to interpret performance variations. Such pragmatic approaches for cycling are put in perspective by Menaspà and Abbiss for the operational application in the ABP. Iljukov et al. additionally illustrate in practical ways how “unusual performances by an athlete would trigger a more thorough testing program” with a case report in middle- and long-distance runners. Moreover, Iljukov and Schumacher bring practical examples in 800 m runners, discus and hammer throwers with respective performance analyses. The latter shows the way to increase the efficiency of anti-doping measures by adjusting targeted testing using performance data. There is also novel data on how cobalt may alter both hemoglobin mass and aerobic performance (Hoffmeister et al. ), and an innovative statistical code tool allowing the calculation of the Abnormal Blood Profile Score marker as used in the ABP (Schütz and Zollinger). Finally, one should consider the opinion brought by a group of experts underlining the need for robust performance data before considering performance modeling (e.g., with the use of micro-technology monitoring activity and training) but also the potential of performance models in terms of risk prediction to identify athletes who are more likely to be involved in doping (Hopker et al.). The body of evidence provided in this Research Topic supports the direction proposed in the ABP guidelines (Menaspà and Abbiss). This direction is that the term passport shall “include all other relevant information also comprising training and competition results” (Vernec, 2014). Thus the ABP could consist not only of a longitudinal profile of the athlete's hematological markers, but also considers performance models (including competition results and training contents) to formally support the ABP too. To date, more conclusive evidence highlighting associations between variations in the ABP and performance changes in competitive athletes is required. Defining links between existing or new biomarkers and performance would consequently represent an attractive strategy for indirect detection of the use of doping substances or methods. Moreover, the longitudinal monitoring of additional performance variables in different sports could be used to identify athletes “at risk” of doping worthy of closer scrutiny by anti-doping authorities. The aim of this Research Topic is ultimately to collect and discuss new evidence defining associations between performance models from various sports and existing or novel performance models to strengthen the fight against doping. Addressing this topic may help support anti-doping agencies seeking to remove the shady side of the medal when under the spotlight. All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. We acknowledge the contributors to this research topic and all scientists committed to improve the fight against doping and support athletes of integrity. Borresen, J., and Lambert, M. I. (2009). The quantification of training load, the training response and the effect on performance. Sports Med. 39, 779–795. doi: 10.2165/11317780-000000000-00000 PubMed Abstract | CrossRef Full Text | Google Scholar Bouchard, C. (2015). Adaptation to acute and regular exercise: from reductionist approaches to integrative biology. Prog. Mol. Biol. Transl. Sci. 135, 1–15. doi: 10.1016/bs.pmbts.2015.07.009 PubMed Abstract | CrossRef Full Text | Google Scholar Faria, E. W., Parker, D. L., and Faria, I. E. (2005). The science of cycling: factors affecting performance - part 2. Sports Med. 35, 313–337. doi: 10.2165/00007256-200535040-00003 PubMed Abstract | CrossRef Full Text Jobson, S. A., Passfield, L., Atkinson, G., Barton, G., and Scarf, P. (2009). The analysis and utilization of cycling training data. Sports Med. 39, 833–844. doi: 10.2165/11317840-000000000-00000 PubMed Abstract | CrossRef Full Text | Google Scholar Passfield, L., Hopker, J.G., Jobson, S., Friel, D., and Zabala, M. (2017). Knowledge is power: issues of measuring training and performance in cycling. J. Sports Sci. 35, 1426–1434. doi: 10.1080/02640414.2016.1215504 PubMed Abstract | CrossRef Full Text | Google Scholar Pinot, J., and Grappe, F. (2011). The record power profile to assess performance in elite cyclists. Int. J. Sports Med. 32, 839–844. doi: 10.1055/s-0031-1279773 PubMed Abstract | CrossRef Full Text | Google Scholar Pinot, J., and Grappe, F. (2015). A six-year monitoring case study of a top-10 cycling Grand Tour finisher. J. Sports Sci. 33, 907–914. doi: 10.1080/02640414.2014.969296 PubMed Abstract | CrossRef Full Text | Google Scholar Saugy, M., Lundby, C., and Robinson, N. (2014). Monitoring of biological markers indicative of doping: the athlete biological passport. Br. J. Sports Med. 48, 827–832. doi: 10.1136/bjsports-2014-093512 PubMed Abstract | CrossRef Full Text | Google Scholar Schumacher, Y. O., and Pottgiesser, T. (2009). Performance profiling: a role for sport science in the fight against doping? Int. J. Sports Physiol. Perform. 4, 129–133. doi: 10.1123/ijspp.4.1.129 PubMed Abstract | CrossRef Full Text | Google Scholar Sottas, P. E., Robinson, N., Rabin, O., and Saugy, M. (2011). The athlete biological passport. Clin. Chem. 57, 969–976. doi: 10.1373/clinchem.2011.162271 PubMed Abstract | CrossRef Full Text | Google Scholar Sweeting, A. J., Cormack, S. J., Morgan, S., and Aughey, R. J. (2017). When is a sprint a sprint? A review of the analysis of team-sport athlete activity profile. Front. Physiol. 8:432. doi: 10.3389/fphys.2017.00432 PubMed Abstract | CrossRef Full Text | Google Scholar Vernec, A. R. (2014). The Athlete Biological Passport: an integral element of innovative strategies in antidoping. Br. J. Sports Med. 48, 817–819. doi: 10.1136/bjsports-2014-093560 PubMed Abstract | CrossRef Full Text | Google Scholar Zorzoli, M., Pipe, A., Garnier, P. Y., Vouillamoz, M., and Dvorak, J. (2014). Practical experience with the implementation of an athlete's biological profile in athletics, cycling, football and swimming. Br. J. Sports Med. 48, 862–866. doi: 10.1136/bjsports-2014-093567 PubMed Abstract | CrossRef Full Text | Google Scholar Keywords: doping, sports, performance, modeling, biological passport Citation: Faiss R, Saugy M, Passfield L and Hopker J (2019) Editorial: Performance Modeling and Anti-doping. Front. Physiol. 10:169. doi: 10.3389/fphys.2019.00169 Received: 04 December 2018; Accepted: 12 February 2019; Published: 01 March 2019. Edited and reviewed by: Geoffrey A. Head, Baker Heart and Diabetes Institute, Australia Copyright © 2019 Faiss, Saugy, Passfield and Hopker. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. *Correspondence: Raphael Faiss, [email protected]
Published: 1 January 2019
BIO-PROTOCOL, Volume 9; https://doi.org/10.21769/bioprotoc.3191

Abstract:
Queuosine (Q) is a hypermodified base in the wobble anticodon position of tRNAs coding for the amino acids Tyr, His, Asn, and Asp. tRNA Q-modification is introduced by a queuine tRNA-ribosyltransferase (TGT) that replaces the guanine base at G34 at these tRNAs with the modified base. tRNA Q-modification is widely distributed among prokaryotic and eukaryotic organisms, but only bacteria synthesize Q-modified tRNA de novo. In mammals, tRNA Q-modifications strictly rely on the presence of gut microbiomes or diets to produce the queuine base. Despite decades of study, cellular roles of tRNA Q-modification are still not fully understood. Here we describe a method to quantify tRNA Q-modification levels in individual tRNAs from human cells based on the presence of a cis-diol in the Q modification. This cis-diol moiety slows modified tRNA migration through polyacrylamide gels supplemented with N-acryloyl-3-aminophenylboronic acid (APB) compared to the unmodified tRNA. This difference can be visualized by Northern blots using probes for specific tRNA. Bio-protocol is an online peer-reviewed protocol journal. Its mission is to make life science research more efficient and reproducible by curating and hosting high quality, free access protocols.
Retraction
Advanced Pharmaceutical Bulletin, Volume 8, pp 727-727; https://doi.org/10.15171/apb.2018.082

Abstract:
The main and corresponding author, "Mohammad Tasyriq Che Omar" submitted this article to the "Advanced Pharmaceutical Bulletin" Journal on 20 of April 2017 and it was published after positive reviews in: Adv Pharm Bull, 2017, 7(2), 299-312, doi: 10.15171/apb.2017.036. Recently we were informed by an email that this work was carried out under direct supervision of a researcher in the "Advanced Medical and Dental Institute, Universiti Sains Malaysia" between 2013-2016. On the submitted and published manuscript "Mohammad Tasyriq Che Omar" did not include the name of his supervisor as an author, who substantially contributed to conception and design of the work. No permission was obtained from the supervisor for submission of this work. We contacted "Mohammad Tasyriq Che Omar" regarding this issue and he admitted this mistake. He requested to add his supervisor’s name on the published paper. This could not be happened as it is against the current regulations and professional ethics. Publication of this work without the knowledge, consent, and permission of the PhD supervisor and without his name is unacceptable and reflective of extremely poor professional ethics. The editors of the "Advanced Pharmaceutical Bulletin" Journal who act according to the COPE Code of Conduct, consider this an infringement of professional ethics and the decision has been made to retract the article published in the Journal. The editors of "Advanced Pharmaceutical Bulletin" Journal are sorry for any inconveniences caused to the reviewers, editorial staff and to the readers. Prof Hadi Valizadeh "Advanced Pharmaceutical Bulletin" Editor-in-Chief
Published: 4 September 2018
Frontiers in Oncology, Volume 8; https://doi.org/10.3389/fonc.2018.00334

Abstract:
Nitric oxide (NO) is a free radical that can target cellular biomolecules directly, or by means of the activity of its metabolites (RNS) generated upon reaction with transition metals (e.g., NO+), oxygen (e.g., N2O3), or superoxide (ONOO). For instance, it is well-documented that NO and RNS affect DNA integrity and mitochondrial physiology, this leading to genetic mutations (1) and damage to the mitochondrial respiratory chain (2, 3), respectively. Processes ranging from apoptosis, angiogenesis, immunity, and neuronal physiology, all show seemingly contradictory behavior in response to NO. Indeed, the relevance of the steady-state NO concentrations represents a key determinant of its biological function. In support to this assumption, it has been demonstrated that cGMP-mediated processes occur at the low nM range, whereas higher NO concentrations cause protein kinase B (PKB)/Akt phosphorylation; stabilization of hypoxia inducible factor (HIF)-1α; phosphorylation of p53 and, at the μM range, they can generate detrimental conditions usually referred as to nitrosative stress (Figure 1). Likewise, in tumor biology, it is now commonly accepted that high NO concentrations mediate apoptosis and cancer growth inhibition, whereas (relatively) low concentrations usually promote tumor growth and proliferation, this supporting the nature of “doubled-edged sword” molecule for NO (4, 5). This dichotomy originates from the observations that the inducible form of NO synthase (iNOS or NOS2) was implicated in the macrophage-mediated tumor killing process (6, 7) (Figure 1). NOS2−/− mice develop intestinal tumors (8), thereby substantiating the protective role of NOS2 within host defense mechanisms (9, 10). In accordance, a growing body of evidence pointed out that NO-releasing drugs can be toxic for cancer cells. Figure 1. Roles of NO signaling and protein denitrosylation in cancer. Nitric oxide plays different roles in cancer biology depending on its concentration. GSNOR is the main cellular denitrosylase. Counteracting the effects induced by NOS, GSNOR finely modulates protein S-nitrosylation (second panel from the top), which is establishing as the main posttranslational modification underlying NO bioactivity. A disbalance in NO signaling can promote tumor induction, survival and progression. NOS2 deficiency impairs the capability of macrophages to kill cancer cells (Top). Conversely, in conditions of normal (or induced) NOS activity, GSNOR decrease has been linked to many cancer hallmarks, such as: (i) apoptosis and anoikis resistance (due to caspases and, reasonably, FAK-1 S-nitrosylation); (ii) genomic instability (DNA repair impairment, due to AGT S-nitrosylation and degradation); (iii) cells hyperproliferation (via the NO-mediated activation of oncoproteins, such as AKT, RAS, and Src); (iv) angiogenesis (putatively regulated by HIF-1α and TRPs S-nitrosylation). Extreme nitrosative stress conditions—induced, for instance, by NOS overexpression or by the use of NO-donors—activate cell death and are implemented (or physiologically activated in macrophages) to destroy cancer cells (Bottom). NO, nitric oxide; GSNOR, S-nitrosoglutathione reductase; NOS, nitric oxide synthase; FAK1, focal adhesion kinase 1; AGT, O6-methylguanine-DNA methyltransferase; HIF-1α, hypoxia-inducible factor-1α; TRP, Transient receptor potential channel. On the other hand, low rate of NO production can promote tumor growth rather than killing. In line with this assumption, the overexpression of NOS isoforms has been detected in a wide range of human tumors. In particular, NOS2 has been found to be upregulated in melanoma, estrogen receptor-negative (ER)-breast cancer, as well as in pancreatic, cervical liver and ovarian cancers (10). Moreover, NOS2 seems to be involved in maintaining physiologically relevant levels of NO to sustain the progression phase of carcinogenesis; mainly it is required to promote angiogenesis and to enhance the ability of cancer cells to counteract nutrient paucity in solid tumors and to metastasize (11, 10). NOS2 is also overexpressed in glioma stem cells, and its activity is required for the expression of the cell cycle inhibitor cell division autoantigen-1 (CDA1), which sustains growth and tumorigenicity (12). NOS2 has been also found to be upregulated in hepatocellular carcinoma (HCC), and is often increased in the hepatocytes of patients with chronic hepatitis and alcoholic cirrhosis, conditions that predispose to HCC (13–15). Notwithstanding all these lines of evidence, investigations on NOS2−/− mice, in spontaneous and fibrosis-associated models of HCC, reveal little effect of NOS2-derived NO on hepatocarcinogenesis (16), meaning that other players are also involved. Redox signal underlying both pro-survival and death pathways, is a molecular information transduced by means of reactive cysteine residues that can undergo S-hydroxylation (SOH), upon reaction with ROS (i.e., H2O2) or S-nitrosylation (SNO), the posttranslational modification induced by NO, which is now emerging to underlie NO bioactivity (17). In the presence of a sulfhydryl group in their close proximity, both these modifications can resolve in a more stable disulfide bridge (S-thiolation, SS) (18–20). Actually, it has been recently questioned whether S-nitrosylation—given its nature of instable posttranslational modification—is able to convey the NO-mediated signal, or just acts as mere intermediate for disulfide bridge formation (21). Whatever is the end effector (if directly the SNO group or, indirectly, the SS adduct), the extent of S-nitrosylation is determined by a delicate balance between: (i) the rate of NO production, which is catalyzed by NOSs (22, 23), (ii) the activity of a recently discovered class of enzymes termed nitrosylases (24, 25), and (iii) the efficiency of SNO removal, that is mediated by denitrosylases. S-nitrosoglutathione reductase (GSNOR) represents the prototype of this class of oxidoreductases and, so far, the only denitrosylase able to completely reduce NO moiety, reason why it has been also termed GSNO terminase (26–28). Notwithstanding current literature offers still conflicting lines of evidence about the role of NOS/NO system in cancer biology, even less is known on the role played by GSNOR and denitrosylation. In this scenario, it has been reported that GSNOR-ablated (GSNOR-KO) mice show predilection to hepatocellular carcinoma (HCC) in association with S-nitrosylation and proteasomal degradation of the DNA damage repair enzyme O6-alkylguanine-DNA alkyltransferase (AGT) (29). As a result, the repair of carcinogenic O6-alkylguanines is significantly impaired with a consequence increase in tumorigenesis (29, 30). Analyses performed on human HCC patients showed a significant decrease of GSNOR protein levels and activity in the 50% of cases (30), arguing for a functional link between GSNOR-dependent S-nitrosylation and HCC. Although this evidence supports a driving role for GSNOR and excessive S-nitrosylation in HCC ontogenesis, it is still unknown whether they are also implicated in the other phases of carcinogenesis, e.g., tumor promotion and progression (31). In this regard, it has been published that GSNOR deficient HCC cells have a compromised mitochondrial electron transport chain characterized by the upregulation of succinate dehydrogenase (SDH), likely as an adapting response to the general impairment of the mitochondrial respiratory machinery (32) derived from excessive nitrosative stress. The hyper-nitrosylation of the mitochondrial chaperone TNF receptor–associated protein 1 (Trap1) has been identified as the molecular event responsible for such a rearrangement and, in turn, for the enhanced sensitivity of GSNOR-downregulating HCC to SDH-targeting mitochondrial drugs (32). Nevertheless, it is worth to note that the mean size of GSNOR-deficient tumor xenografts is larger (approximately the double) than parental (GSNOR-proficient) HCC (32), suggesting that excessive S-nitrosylation arising from GSNOR loss, might promote tumor progression and growth in vivo. This hypothesis finds support in a recent study correlating GSNOR downregulation with HER2+ breast cancer resistance to trastuzumab and poor patient prognosis (33). Altogether, these pieces of evidence argue for a new role of GSNOR in malignancy and resistant phenotypes of breast cancer. However, no evidence about the molecular mechanisms underneath has been provided so far. Based on what above reported, it is plausible that impairments of denitrosylation capacity (e.g., upon GSNOR deficiency) modulates the function/activity of oncoproteins susceptible to S-nitrosylation. These defects, more specifically than a general increase of NO production (that could impact on a plethora of different targets and to a different extent) might account for a deregulated NO-signaling in carcinogenesis. This hypothesis is further sustained by a very recent study indicating that GSNOR-deficiency (and excessive S-nitrosylation deriving from it), is a condition associated with aging (34, 35), which represents a major risk factor for cancer development. Actually, cancer might count as an aging disease, and shares with aging some common features (e.g., genomic instability, telomere shortening, oxidative stress, deregulation of nutrient sensing) that, indeed, characterize both disorders (36). Besides those previously mentioned, and others well documented to play a role in apoptosis (e.g., p53, Bcl2, and Fas), many oncoproteins have been discovered in the last decades to undergo S-nitrosylation. The modification of oncoproteins and tumor suppressors by NO—independently on the effects induced, whether gain- or loss-of-function (23, 37)—is emerging as a critical phenomenon associated with neoplastic transformation. Some of these NO-modified oncoproteins participate to signal transduction and are found mutated or modulated in cancer. Within this class of proteins in which S-nitrosylation has been identified as pro-oncogenic modification, we can list: (i) the GTPase Ras (nitrosylated at Cys118) (23, 38), which underlies cancer cell growth downstream of receptor-associated tyrosine kinases; (ii) the phosphatase and tensin homolog PTEN (nitrosylated at Cys83) (39), which regulates the levels of phosphatidyl inositole-3-phosphate/Akt-dependent pathway; (iii) the protein kinase c-Src, which represents one of the master regulators of tumor proliferation, invasion and metastatic phenotype, and has been found to be nitrosylated at Cys498 (40) (Figure 1). Interestingly, this residue is conserved throughout the Src family of protein tyrosine kinases (SFKs) and, at least for other two members, i.e., Yes and Fyn, has been also reported to stimulate their activation (40). Focal adhesion kinase 1 (FAK1) is also comprised in the SFKs family. It is phosphorylated upon integrin engagement in a Src-dependent or independent (auto-phosphorylation) fashion, thus initiating multiple downstream signaling pathways responsible for aggressive and metastatic phenotype (e.g., resistance to anoikis and cell migration) (41). Similarly to Src, Yes and Fyn have been reported to act as FAK1-interacting kinases and to be involved in FAK1 activation as well (42, 43). Notwithstanding this tight relationship, triple-KO cells in which Src, Yes, and Fyn expression is suppressed (SYF cells), still show phospho-active levels of FAK1 upon treatment with NO donors (40). This unexpected evidence clearly indicates that S-nitrosylation of Src, Yes, and Fyn is dispensable for NO-driven phosphorylation of FAK1 and, interestingly, suggests that FAK1 might represent a direct target of S-nitrosylation (Figure 1), with this modification driving its oncogenic function. Another oncoprotein, which has been identified to be crucial in cancer cell survival and growth, especially under low-oxygen tension (hypoxia), is HIF-1α. HIF-1α deregulation has been deeply implicated in different aspects of cancer biology, such as angiogenesis, cell resistance, and tumor invasion (44–47). From a metabolic point of view, HIF-1α aberrant activation underpins the so-called “Warburg effect”: the preferential glycolytic consumption of glucose in cancer cells, which takes place also under normal oxygen tension. HIF1α has been found nitrosylated at Cys533 (48), with this being relevant in stroke and cardiovascular disease. However, if S-nitrosylation might somehow induce HIF1α oncogenic activity still remains neglected (Figure 1) and would deserve to be investigated in the future. Among the various classes of proteins that have been identified in the last decades as being activated by S-nitrosylation, the transient receptor potential (TRP) ion channels (49), which represent a huge family of proteins underpinning, among others, warm, taste, and pain sensory transduction, are worth to be mentioned. Besides their well-documented role in the nervous system as mediators of sensations, in the last years it is emerging that many TRPs, such as those belonging to the “melastatin” (TRPM), “vanilloid” (TRPV), and “ankyrin” (TRPA) subfamilies, are overexpressed in many cancer types, this being pivotal for calcium signaling-dependent control of tumor-promoting processes, e.g., vascularization and metastasis (50, 51). In particular, it has been proposed that, by modulating intracellular Ca2+ concentrations, TRPs are deeply involved in tumor initiation, progression and resistance (52). In this context, it has been very recently found out that TRPA1 is upregulated in breast and lung cancer downstream of the activation of Nrf2, the master regulator of antioxidant response, this conferring non-canonical resistance to tumor cells against oxidative stress and ROS-producing chemotherapeutics (53). Many other observations argue for TRPs inhibition being a promising tool to eradicate cancer (54–56). However, notwithstanding the evidence that S-nitrosylation interferes with TRPs activity and calcium signaling, to date there's still no indication supporting a direct involvement of TRPs S-nitrosylation in carcinogenesis (Figure 1). Mostly, there's still no study aimed at understanding whether TRPs targeting on nitrosylable cysteines might represent a novel line of intervention in cancer treatment. The above reported evidence points out that defects in GSNOR expression and denitrosylation are pivotal for sustaining the tumorigenic effects of NO, namely, its role in the progression phase of cancer (31). A recent report on the epigenetic regulation of GSNOR might be of help to understand how this condition can be established in cancer. In particular, it has been demonstrated that GSNOR expression is controlled by the activity of the demethylase Ten-eleven translocation protein 1 (Tet1), a member of the 2-oxoglutarate–dependent dioxygenases that regulates transcription by removing methyl groups from CpG islands located in the promoter regions of genes (34). Remarkably, Tet1 expression has been found to be reduced in a wide range of solid cancers, such as melanoma, prostate, lung, and liver tumors (57, 58)—where also GSNOR mRNA seems to be downregulated—and to correlate with advanced cancer stage, nodal metastases, and poor survival rate in breast cancer patients (59). These lines of evidence suggest that GSNOR might be epigenetically downregulated in aggressive cancer as a consequence of Tet1 reduction, thus providing a new link between epigenetics and redox signaling. This hypothesis can be even extended to further mechanisms of epigenetic regulation. Indeed, given the complex structure of GSNOR mRNA, it has been proposed that GSNOR expression might be also regulated via microRNAs (miRs) (27). However, no putative miRs, able to target GSNOR transcript, has been so far identified to be upregulated in cancer, or hypothesized acting as additional modulators of S-nitrosylation. The role of GSNOR-mediated denitrosylation in carcinogenesis has been capturing the interest of many researchers working on cancer biology, as many lines of evidence indicate that this process is frequently deregulated in cancer cells. In this article, we have tried to summarize what has been discovered in the last years and provide some hints on possible aspects that are still overlooked. Understanding how GSNOR expression is deregulated in may cancer histotypes, as well as the mechanisms underlying the modification of new protein targets involved in cancer resistance and aggressiveness, are, indeed, issues that deserve to be investigated in the future, since they could set the stage for new anticancer approaches interfering with the redox adaptation distinctive of many cancer cells. GF conceived the paper. GF and SR wrote the paper. SR drew the figure. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. This work has been supported by Danish Cancer Society Grant KBVU R146-A9414, and Associazione Italiana per la Ricerca sul Cancro (AIRC) Grant IG20719. 1. Dizdaroglu M, Jaruga P. Mechanisms of free radical-induced damage to DNA. Free Radic Res. (2012) 46:382–419. doi: 10.3109/10715762.2011.653969 PubMed Abstract | CrossRef Full Text | Google Scholar 2. Boveris A, Costa LE, Poderoso JJ, Carreras MC, Cadenas E. Regulation of mitochondrial respiration by oxygen and nitric oxide. Ann NY Acad Sci. (2006) 899:121–35. doi: 10.1111/j.1749-6632.2000.tb06181.x PubMed Abstract | CrossRef Full Text | Google Scholar 3. Brown GC, Borutaite V. Nitric oxide inhibition of mitochondrial respiration and its role in cell death. Free Radic Biol Med. (2002) 33:1440–50. doi: 10.1016/S0891-5849(02)01112-7 PubMed Abstract | CrossRef Full Text | Google Scholar 4. Burke AJ, Sullivan FJ, Giles FJ, Glynn SA. The yin and yang of nitric oxide in cancer progression. Carcinogenesis (2013) 34:503–12. doi: 10.1093/carcin/bgt034 PubMed Abstract | CrossRef Full Text | Google Scholar 5. Vanini F, Kashfi K, Nath N. The dual role of iNOS in cancer. Redox Biol. (2015) 6:334–43. doi: 10.1016/j.redox.2015.08.009 CrossRef Full Text | Google Scholar 6. Marletta MA. Nitric oxide synthase: aspects concerning structure and catalysis. Cell (1994) 78:927–30. doi: 10.1016/0092-8674(94)90268-2 PubMed Abstract | CrossRef Full Text | Google Scholar 7. Bogdan C. Nitric oxide and the immune response. Nat Immunol. (2001) 2:907–16. doi: 10.1038/ni1001-907 PubMed Abstract | CrossRef Full Text | Google Scholar 8. Yerushalmi HF, Besselsen DG, Ignatenko NA, Blohm-Mangone KA, Padilla-Torres JL, Stringer DE, et al. The role of NO synthases in arginine-dependent small intestinal and colonic carcinogenesis. Mol Carcinog. (2006) 45:93–105. doi: 10.1002/mc.20168 PubMed Abstract | CrossRef Full Text | Google Scholar 9. Xu W, Liu LZ, Loizidou M, Ahmed M, Charles IG. The role of nitric oxide in cancer. Cell Res. (2002) 12:311–20. doi: 10.1038/sj.cr.7290133 PubMed Abstract | CrossRef Full Text | Google Scholar 10. Thomas DD, Wink DA. NOS2 as an emergent player in progression of cancer. Antioxid Redox Signal (2017) 26:963–5. doi: 10.1089/ars.2016.6835 PubMed Abstract | CrossRef Full Text | Google Scholar 11. Jadeski LC, Hum KO, Chakraborty C, Lala PK. Nitric oxide promotes murine mammary tumour growth and metastasis by stimulating tumour cell migration, invasiveness and angiogenesis. Int J Cancer (2000) 86:30–9. doi: 10.1002/(SICI)1097-0215(20000401)86:13.0.CO;2-I PubMed Abstract | CrossRef Full Text | Google Scholar 12. Eyler CE, Wu Q, Yan K, MacSwords JM, Chandler-Militello D, Misuraca KL, et al. Glioma stem cell proliferation and tumor growth are promoted by nitric oxide synthase-2. Cell (2011) 146:53–66. doi: 10.1016/j.cell.2011.06.006 PubMed Abstract | CrossRef Full Text | Google Scholar 13. Majano PL, García-monzón C, López-cabrera M, Lara-pezzi E, Fernández-ruiz E, García-iglesias C, et al. Inducible Nitric oxide synthase expression in chronic viral Hepatitis. evidence for a virus-induced gene upregulation. J Clin Invest. (1998) 101:1343-52. PubMed Abstract | Google Scholar 14. Kane JM, Shears LL, Hierholzer C, Ambs S, Billiar TR, Posner MC. Chronic hepatitis C virus infection in humans: induction of hepatic nitric oxide synthase and proposed mechanisms for carcinogenesis. J Surg Res. (1997) 69:321–4. doi: 10.1006/jsre.1997.5057 PubMed Abstract | CrossRef Full Text | Google Scholar 15. McNaughton L, Puttagunta L, Martinez-Cuesta MA, Kneteman N, Mayers I, Moqbel R, et al. Distribution of nitric oxide synthase in normal and cirrhotic human liver. Proc Natl Acad Sci USA. (2002) 99:17161–6. doi: 10.1073/pnas.0134112100 PubMed Abstract | CrossRef Full Text 16. Tang CH, Wei W, Hanes MA, Liu L. Hepatocarcinogenesis driven by GSNOR deficiency is prevented by iNOS inhibition. Cancer Res. (2013) 73:2897–904. doi: 10.1158/0008-5472.CAN-12-3980 CrossRef Full Text | Google Scholar 17. Stamler JS, Lamas S, Fang FC. Nitrosylation: the prototypic redox-based signaling mechanism. Cell (2001) 106:675–83. doi: 10.1016/S0092-8674(01)00495-0 PubMed Abstract | CrossRef Full Text | Google Scholar 18. Sengupta R, Holmgren A. Thioredoxin and thioredoxin reductase in relation to reversible S -Nitrosylation. Antioxid Redox Signal (2013) 18:259–69. doi: 10.1089/ars.2012.4716 PubMed Abstract | CrossRef Full Text | Google Scholar 19. Martínez-Ruiz A, Araújo IM, Izquierdo-Álvarez A, Hernansanz-Agustín P, Lamas S, Serrador JM. Specificity in S-Nitrosylation: a short-range mechanism for NO signaling? Antioxid Redox Signal (2013) 19:1220–35. doi: 10.1089/ars.2012.5066 PubMed Abstract | CrossRef Full Text | Google Scholar 20. Jones DP, Sies H. The Redox Code. Antioxid Redox Signal (2015) 23: 734–46. doi: 10.1089/ars.2015.6247 PubMed Abstract | CrossRef Full Text | Google Scholar 21. Wolhuter K, Whitwell HJ, Switzer CH, Burgoyne JR, Timms JF, Eaton P. Evidence against stable protein S-Nitrosylation as a Widespread mechanism of post-translational regulation. Mol Cell (2018) 69:438–50.e5. doi: 10.1016/j.molcel.2017.12.019 PubMed Abstract | CrossRef Full Text | Google Scholar 22. Hess DT, Stamler JS. Regulation by S-Nitrosylation of protein post-translational modification. J Biol Chem. (2012) 287:4411–8. doi: 10.1074/jbc.R111.285742 PubMed Abstract | CrossRef Full Text | Google Scholar 23. Hess DT, Matsumoto A, Kim S-OO, Marshall HE, Stamler JS. Protein S-Nitrosylation: purview and parameters. Nat Rev Mol Cell Biol. (2005) 6:150–66. doi: 10.1038/nrm1569 PubMed Abstract | CrossRef Full Text | Google Scholar 24. Seth D, Hess DT, Hausladen A, Wang L, Wang Y, Stamler JS. A multiplex enzymatic machinery for cellular protein S-Nitrosylation. Mol Cell (2018) 69:451–64.e6. doi: 10.1016/j.molcel.2017.12.025 PubMed Abstract | CrossRef Full Text | Google Scholar 25. Jia J, Arif A, Terenzi F, Willard B, Plow EF, Hazen SL, et al. Target-selective protein S-Nitrosylation by sequence motif recognition. Cell (2014) 159:623–34. doi: 10.1016/j.cell.2014.09.032 PubMed Abstract | CrossRef Full Text | Google Scholar 26. Liu L, Hausladen A, Zeng M, Que L, Heitman J, Stamler JS. A metabolic enzyme for S-nitrosothiol conserved from bacteria to humans. Nature (2001) 410:490–4. doi: 10.1038/35068596 PubMed Abstract | CrossRef Full Text | Google Scholar 27. Rizza S, Filomeni G. Chronicles of a reductase: biochemistry, genetics and physio-pathological role of GSNOR. Free Radic Biol Med. (2017) 110:19–30. doi: 10.1016/j.freeradbiomed.2017.05.014 PubMed Abstract | CrossRef Full Text | Google Scholar 28. Jensen DE, Belka GK, Du Bois GC. S-Nitrosoglutathione is a substrate for rat alcohol dehydrogenase class III isoenzyme. Biochem J. (1998) 331(Pt. 2):659–68. PubMed Abstract | Google Scholar 29. Wei W, Yang Z, Tang CH, Liu L. Targeted deletion of GSNOR in hepatocytes of mice causes nitrosative inactivation of O6-alkylguanine-dna alkyltransferase and increased sensitivity to genotoxic diethylnitrosamine. Carcinogenesis (2011) 32:973–7. doi: 10.1093/carcin/bgr041 PubMed Abstract | CrossRef Full Text | Google Scholar 30. Wei W, Li B, Hanes MA, Kakar S, Chen X, Liu L, et al. S-Nitrosylation from GSNOR deficiency impairs DNA repair and promotes hepatocarcinogenesis. Sci Transl Med. (2010) 2:19ra13. doi: 10.1126/scitranslmed.3000328 PubMed Abstract | CrossRef Full Text | Google Scholar 31. Rizza S, Filomeni G. Tumor suppressor roles of the denitrosylase GSNOR. Crit Rev Oncog. (2016) 21:433–45. doi: 10.1615/CritRevOncog.2017021074 PubMed Abstract | CrossRef Full Text | Google Scholar 32. Rizza S, Montagna C, Cardaci S, Maiani E, Di Giacomo G, Sanchez-Quiles V, et al. S-Nitrosylation of the mitochondrial chaperone TRAP1 sensitizes hepatocellular carcinoma cells to inhibitors of succinate dehydrogenase. Cancer Res. (2016) 76:4170–82. doi: 10.1158/0008-5472.CAN-15-2637 PubMed Abstract | CrossRef Full Text | Google Scholar 33. Cañas A, López-Sánchez LM, Peñarando J, Valverde A, Conde F, Hernández V, et al. Altered S-nitrosothiol homeostasis provides a survival advantage to breast cancer cells in HER2 tumors and reduces their sensitivity to trastuzumab. Biochim Biophys Acta (2016) 1862:601–10. doi: 10.1016/j.bbadis.2016.02.005 PubMed Abstract | CrossRef Full Text | Google Scholar 34. Rizza S, Cardaci S, Montagna C, Di Giacomo G, De Zio D, Bordi M, et al. S -Nitrosylation drives cell senescence and aging in mammals by controlling mitochondrial dynamics and mitophagy. Proc Natl Acad Sci USA. (2018) 21:7–13. doi: 10.1073/pnas.1722452115 CrossRef Full Text | Google Scholar 35. Rizza S, Filomeni G. Denitrosylate and live longer: how GSNOR links mitophagy to aging. Autophagy (2018) 20:1–3. doi: 10.1080/15548627.2018.1475818 CrossRef Full Text | Google Scholar 36. Aunan JR, Cho WC, Søreide K. The biology of aging and cancer: a brief overview of shared and divergent molecular hallmarks. Aging Dis. (2017) 8:628–42. doi: 10.14336/AD.2017.0103 PubMed Abstract | CrossRef Full Text | Google Scholar 37. Wang Z. Protein S-Nitrosylation and cancer. Cancer Lett. (2012) 320:123–9. doi: 10.1016/j.canlet.2012.03.009 PubMed Abstract | CrossRef Full Text | Google Scholar 38. Heo J, Campbell SL. Mechanism of p21Ras S-NITROSYLATION and kinetics of nitric oxide-mediated guanine nucleotide exchange. Biochemistry (2004) 43:2314–22. doi: 10.1021/bi035275g PubMed Abstract | CrossRef Full Text | Google Scholar 39. Numajiri N, Takasawa K, Nishiya T, Tanaka H, Ohno K, Hayakawa W, et al. On-off system for PI3-kinase-Akt signaling through S-Nitrosylation of phosphatase with sequence homology to tensin (PTEN). Proc Natl Acad Sci USA. (2011) 108:10349–54. doi: 10.1073/pnas.1103503108 PubMed Abstract | CrossRef Full Text | Google Scholar 40. Rahman MA, Senga T, Ito S, Hyodo T, Hasegawa H, Hamaguchi M. S-Nitrosylation at cysteine 498 of c-Src tyrosine kinase regulates nitric oxide-mediated cell invasion. J Biol Chem. (2010) 285:3806–14. doi: 10.1074/jbc.M109.059782 PubMed Abstract | CrossRef Full Text | Google Scholar 41. Sulzmaier FJ, Jean C, Schlaepfer DD. FAK in cancer: mechanistic findings and clinical applications. Nat Rev Cancer (2014) 14:598–610. doi: 10.1038/nrc3792 PubMed Abstract | CrossRef Full Text | Google Scholar 42. Hamamura K, Tsuji M, Hotta H, Ohkawa Y, Takahashi M, Shibuya H, et al. Functional activation of Src family kinase yes protein is essential for the enhanced malignant properties of human melanoma cells expressing ganglioside GD3. J Biol Chem. (2011) 286:18526–37. doi: 10.1074/jbc.M110.164798 PubMed Abstract | CrossRef Full Text | Google Scholar 43. Sen B, Johnson FM. Regulation of Src family kinases in human cancers. J Signal Transduct. (2011) 2011:1–14. doi: 10.1155/2011/865819 PubMed Abstract | CrossRef Full Text | Google Scholar 44. Unwith S, Zhao H, Hennah L, Ma D. The potential role of HIF on tumour progression and dissemination. Int J Cancer (2015) 136:2491–503. doi: 10.1002/ijc.28889 PubMed Abstract | CrossRef Full Text | Google Scholar 45. Semenza GL. HIF-1 mediates metabolic responses to intratumoral hypoxia and oncogenic mutations. J Clin Invest. (2013) 123:3664–71. doi: 10.1172/JCI67230 PubMed Abstract | CrossRef Full Text | Google Scholar 46. Rankin EB, Giaccia A J. The role of hypoxia-inducible factors in tumorigenesis. Cell Death Differ. (2008) 15:678–85. doi: 10.1038/cdd.2008.21 PubMed Abstract | CrossRef Full Text | Google Scholar 47. Wu L, Fu Z, Zhou S, Gong J, Liu CA, Qiao Z, et al. HIF-1α and HIF-2α: Siblings in promoting angiogenesis of residual hepatocellular carcinoma after high-intensity focused ultrasound ablation. PLoS ONE (2014) 9:1–10. doi: 10.1371/journal.pone.0088913 PubMed Abstract | CrossRef Full Text | Google Scholar 48. Li F, Sonveaux P, Rabbani ZN, Liu S, Yan B, Huang Q, et al. Regulation of HIF-1α Stability through S-Nitrosylation. Mol Cell (2007) 26:63–74. doi: 10.1016/j.molcel.2007.02.024 PubMed Abstract | CrossRef Full Text | Google Scholar 49. Yoshida T, Inoue R, Morii T, Takahashi N, Yamamoto S, Hara Y, et al. Nitric oxide activates TRP channels by cysteine S-Nitrosylation. Nat Chem Biol. (2006) 2:596–607. doi: 10.1038/nchembio821 PubMed Abstract | CrossRef Full Text | Google Scholar 50. Fels B, Bulk E, Petho Z, Schwab A. The role of TRP channels in the metastatic cascade. Pharmaceuticals (2018) 11:E48. doi: 10.3390/ph11020048 PubMed Abstract | CrossRef Full Text | Google Scholar 51. Pla AF, Gkika D. Emerging role of TRP channels in cell migration: from tumor vascularization to metastasis. Front Physiol. (2013) 4:311. doi: 10.3389/fphys.2013.00311 CrossRef Full Text | Google Scholar 52. Fliniaux I, Germain E, Farfariello V, Prevarskaya N. TRPs and Ca2+ in cell death and survival. Cell Calcium (2018) 69:4–18. doi: 10.1016/j.ceca.2017.07.002 PubMed Abstract | CrossRef Full Text | Google Scholar 53. Reczek CR, Chandel NS. ROS promotes cancer cell survival through calcium signaling. Cancer Cell (2018) 33:949–51. doi: 10.1016/j.ccell.2018.05.010 PubMed Abstract | CrossRef Full Text | Google Scholar 54. Almasi S, Kennedy BE, El-Aghil M, Sterea AM, Gujar S, Partida-Sánchez S, et al. TRPM2 channel–mediated regulation of autophagy maintains mitochondrial function and promotes gastric cancer cell survival via the JNK-signaling pathway. J Biol Chem. (2018) 293:3637–50. doi: 10.1074/jbc.M117.817635 PubMed Abstract | CrossRef Full Text | Google Scholar 55. Bao L, Chen S, Conrad K, Keefer K, Abraham T, Lee JP, et al. Depletion of the human ion channel TRPM2 in neuroblastoma demonstrates its key role in cell survival through modulation of mitochondrial reactive oxygen species and bioenergetics. J Biol Chem. (2016) 291:24449–64. doi: 10.1074/jbc.M116.747147 PubMed Abstract | CrossRef Full Text | Google Scholar 56. Singh AK, Saotome K, McGoldrick LL, Sobolevsky AI. Structural bases of TRP channel TRPV6 allosteric modulation by 2-APB. Nat Commun. (2018) 9:2465. doi: 10.1038/s41467-018-04828-y PubMed Abstract | CrossRef Full Text | Google Scholar 57. Liu C, Liu L, Chen X, Shen J, Shan J, Xu Y, et al. Decrease of 5-hydroxymethylcytosine is associated with progression of hepatocellular carcinoma through downregulation of TET1. PLoS ONE (2013) 8:e62828. doi: 10.1371/journal.pone.0062828 PubMed Abstract | CrossRef Full Text | Google Scholar 58. Yang H, Liu Y, Bai F, Zhang JY, Ma SH, Liu J, et al. Tumor development is associated with decrease of TET gene expression and 5-methylcytosine hydroxylation. Oncogene (2013) 32:663–9. doi: 10.1038/onc.2012.67 PubMed Abstract | CrossRef Full Text | Google Scholar 59. Hsu CH, Peng KL, Kang ML, Chen YR, Yang YC, Tsai CH, et al. TET1 suppresses cancer invasion by activating the tissue inhibitors of metalloproteinases. Cell Rep. (2012) 2:568–79. doi: 10.1016/j.celrep.2012.08.030 PubMed Abstract | CrossRef Full Text | Google Scholar Keywords: ADH5, GSNOR, nitric oxide, NOS, nitrosylation, cancer, FAK1, HIF-1α Citation: Rizza S and Filomeni G (2018) Role, Targets and Regulation of (de)nitrosylation in Malignancy. Front. Oncol. 8:334. doi: 10.3389/fonc.2018.00334 Received: 13 June 2018; Accepted: 02 August 2018; Published: 04 September 2018. Edited by: Reviewed by: Copyright © 2018 Rizza and Filomeni. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. *Correspondence: Giuseppe Filomeni, [email protected] Salvatore Rizza, [email protected]
F Karademir, Ç. Ayhan, G. Arın, Osman Dag, R. Soylu
Published: 12 June 2018
by BMJ
Saturday, 16 JUNE 2018, Volume 77, pp 1837-1837; https://doi.org/10.1136/annrheumdis-2018-eular.6645

Abstract:
Background Muscle thickness and cross-sectional area (CSA) of the thenar muscles can vary depending on different pathologies (such as neuropathies, arthritis etc.). It is important to evaluate these muscles throughout the diagnosis and treatment processes to understand the pathophysiology of diseases and to identify new treatment strategies. Ultrasonographic imaging has been shown to be valid and reliable tool for the measurement of the muscle thickness and CSA of the particular thenar muscles,1–2 however there are no studies demonstrating normative values of all thenar muscles. Objectives The purpose of this study is to obtain normative thickness and CSA values for the thenar muscles in healthy individuals by ultrasound and to assess the inter-rater reliability of sonographic muscle assessments. Methods The thenar muscles was examined ultrasonographically in eleven healthy volunteers. The assessment was carried out using Shimadzu SDU 1200-Pro US system working with 8–10 MHz linear probe. A custom-made foam cast was used for standardised positioning of the probe. The thickness and CSA parameters of FDI, OP, APB, flexor pollicis brevis (FPB), adductor pollicis (AdP) muscles were examined by two different investigators on the same image. Measurements were made from the palm side of the hand for APB, FPB, OP muscles and from the dorsal side of the hand for AdP and FDI muscles, using five different positions.3 To analyse inter-rater reliability, the examinations of both raters were compared. Results Eleven healthy female subjects (mean age: 24.45±2.77 years; BMI: 21.43±2.48 kg/m2) were included in this study. Nine subjects had right hand dominancy and 2 had left hand dominancy. The reliability between two assessors, expressed as an interclass correlation coefficient (ICC), was excellent for all muscles (ICC range min:0.759, max:0.993 p<0.05). The mean thickness values of muscles were ordered from thick to thin in longitudinal assessment as AP, FDI, FPB, OP, APB. The mean thickness values of muscles were ordered from thick to thin in transverse assessment as AP, FDI, FPB, OP, APB. The mean CSA values of muscles were ordered from thick to thin as AP, FPB, FDI, APB, OP. Conclusions Ultrasonography can be used to reliably assess the thenar muscle architecture. This study is important to reveal the normative thickness and CSA values of the thenar muscles in healthy subjects. This data may provide a more comprehensive understanding of musculoskeletal problems and underlying pathophysiological mechanisms which consequently may have an impact on clinical decision making. References [1] Mohseny, B., Nijhuis, T. H., Hundepool, C. A., Janssen, W. G., Selles, R. W., &Coert, J. H. (2015). Ultrasonographic quantification of intrinsic hand muscle cross-sectional area; reliability and validity for predicting muscle strength. Archives of physical medicine and rehabilitation, 96(5),845–853. [2] Simon, N. G., Ralph, J. W., Lomen-Hoerth, C., Poncelet, A. N., Vucic, S., Kiernan, M. C., & Kliot, M. (2015). Quantitative ultrasound of denervated hand muscles. Muscle & nerve, 52(2),221–230. [3] Grechenig, W., Peicha, G., Weiglein, A., Tesch, P., Lawrence, K., Mayr, J., & Preidler, K. W. (2000). Sonographic evaluation of the thenar compartment musculature. Journal of ultrasound in medicine, 19(11),733–741. Disclosure of Interest None declared
Loren Kline
Published: 1 April 2018
The FASEB Journal, Volume 32, pp 764.1-764.1; https://doi.org/10.1096/fasebj.2018.32.1_supplement.764.1

Abstract:
Luteolin, a flavone, is found in celery, broccoli, green pepper, parsley, carrots, and olive oil. Luteolin was shown to relax rat aortic rings by stimulating the release of nitric oxide (NO) and rat thoracic aortic strips by blocking intracellular Ca2+ release and activating K+ channels. The purpose of this study was to determine if luteolin had an effect on gallbladder motility. An in vitro technique was used to determine which system(s) mediated the relaxation. Both paired t-tests and analysis of variance were used for statistical analysis; differences between mean values of p<0.05 were considered significant. Luteolin relaxed cholecystokinin octapeptide (CCK)-induced tension in male guinea pig gallbladder strips in a concentration-dependent manner. Adding luteolin prior to either CCK or KCl produced a significant decrease in the amount of tension (0.99±0.07 g vs. 0.82+0.09 g CCK [p<0.02]; 1.1±0.09 g vs. 0.97±0.08 g KCl [p<0.001]. The protein kinase A blocker, PKA inhibitor 14–22 amide myristolated, significantly (p<0.01) reduced the amount of luteolin-induced relaxation (53.9±3.9% vs. 46.5±4.3%). The blocker of intracellular Ca2+ release, 2-APB, significantly (p<0.001) decreased the amount of luteolin-induced relaxation (55.9±5.3% vs. 28.9±4.6%). Neither tetraethylammonium (TEA), a non-selective K+ channel blocker; NO synthase blocker, L-NAME; KT5823, blocker of protein kinase G; bisindolymaleimide IV and chelerythrine Cl− were used together and are blockers of PKC; fulvestrant, an estrogen receptor blocker; nor genistein, a protein tyrosine kinase blocker had a significant effect on the luteolininduced relaxation. The luteolin-induced relaxation of CCK- or KCl-induced tension was mediated by blocking extracellular Ca2+ entry which affected downstream events such as intracellular Ca2+ release, and the activation of protein kinase A. Th. Support or Funding Information This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.
Rayan Khaddaj‐Mallat, Cini John, Heike Wulff, Andrew P. Braun
Published: 1 April 2018
The FASEB Journal, Volume 32, pp 710.1-710.1; https://doi.org/10.1096/fasebj.2018.32.1_supplement.710.1

Abstract:
Endothelial dysfunction occurs in healthy ageing, and may contribute to the development of cardiovascular complications (e.g. hypertension, atherosclerosis) that are more prevalent in aged individuals. One cause of age-related endothelial dysfunction is an imbalance in the generation and/or release of vasodilatory and constrictor agents by the vascular endothelium (e.g. reduced NO bioavailability). Ageing may also impact the expression of endothelial proteins involved with vasoactive signaling to the surrounding smooth muscle. The goal of our study was to assess the effects of long term, in vivo administration of SKA-31, a small molecule activator of KCa 2.x and KCa 3.1 channels, on the functional reactivity of mesenteric arteries in healthy aged rats. Young (225–250 g, 12 weeks of age) and aged (600–700 g, 18 months of age) male Sprague Dawley (SD) rats were treated daily with either vehicle or 10 mg/kg SKA-31 for 8 weeks, after which mesenteric arteries (i.e. 200–400 μm internal diameter) were isolated and cannulated in an arterial pressure myography chamber. Experimentally, arteries were pressurized to 70 mmHg, preconstricted with 1 μM phenylephrine (PE) and superfused at 6–7 ml/min with Krebs' solution at ~36°C using a peristaltic pump. Vasoactive agents were added directly to the superfusate. The PE-induced decrease in the intraluminal diameter of pressurized mesenteric arteries (i.e. % change of maximal passive diameter) was significantly greater in aged (44.3 ± 2.7%, n=8) vs. young animals (38.1 ± 3.6%, n=12), whereas chronic SKA-31 treatment of aged rats reduced the level of vasoconstriction to 36.5 ± 4.0% (n=8). Aged mesenteric arteries dilated less in response to 0.3 μM acetylcholine (ACh), 0.3 μM bradykinin (BK) and 10 μM sodium nitroprusside (SNP) (i.e. inhibition of active tone = 37.0 ± 1.9%, 44.6 ± 4.5%, 55.5 ± 4.8%, respectively; n=4) compared with young arteries (48.3 ± 6.8%, 62.0 ± 7.1%, 68.0 ± 7.9%, respectively, n=4). Chronic treatment of aged SD rats with SKA-31 improved vasodilation evoked by ACh, BK and SNP (58.5 ± 5.5%, 64.3 ± 5.5%, 76.7 ± 4.4%, respectively; n=4), however, SKA-31 treatment had no effect on the dilations evoked by either 10 μM adenosine or 5 μM pinacidil. Molecular analysis confirmed that expression of KCa 2.3 and KCa 3.1 channels was significantly decreased in aged mesenteric arteries compared with young vessels. Chronic SKA-31 administration significantly increased the expression of these channels relative to vehicle-treated animals (n=3). Collectively, these data demonstrate that chronic SKA-31 treatment can improve evoked vasodilation in the aged mesenteric microcirculation, in part by enhancing the expression of endothelial KCa 2.3 and KCa 3.1 channels. Support or Funding Information Supported by research funding to APB from the Canadian Institutes of Health Research. RKM is a recipient of a postdoctoral scholarship from the Libin Cardiovascular Institute and Cumming School of Medicine, Univ. of Calgary. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.
Xun Zhang, Calum Wilson, Matthew Lee, John Girkin, Chris Saunter, John G. McCarron
Published: 1 April 2018
The FASEB Journal, Volume 32, pp 843.1-843.1; https://doi.org/10.1096/fasebj.2018.32.1_supplement.843.1

Abstract:
The endothelium is the innermost lining of blood vessels and plays a significant role in controlling virtually every cardiovascular function. Constant signalling among endothelial cells and between endothelial cells and blood cells and smooth muscle cells is critical for the control of blood fluidity, vascular tone and angiogenesis. Intracellular Ca2+ signals act as a messenger system that decodes extracellular signals arriving at the endothelium and encodes intracellular signals to determine cardiovascular activity. Hydrogen peroxide (H2O2), a key reactive oxygen species (ROS) generated by the respiratory chain in mitochondria, is also an important regulator of endothelial function. In endothelial cells, H2O2 may also be produced by NADPH oxidase, xanthine oxidase and nitric oxide synthases. Although mitochondria-derived ROS are usually considered to induce oxidative stress and damage cells, the physiological roles of ROS in mechano-stress signal transduction, vascular relaxation, permeability of endothelial cells is now acknowledged. In this study, the interactions of low, physiological, concentrations (1 μM) H2O2 and Ca2+ signals were examined in the endothelium of intact rat mesenteric arteries. The intracellular Ca2+ was visualized and measured in ~200 endothelial cells using the Ca2+ indicator Cal-520 through high-resolution, high-speed imaging. Endothelial cells responded to ACh (100 nM) with Ca2+ signals that initiated in clusters of endothelial cells and propagated within and between cells. ACh-evoked Ca2+ signals were largely IP3-evoked signalling events since the signals persisted after removal of external Ca2+ and were blocked by the SERCA inhibitor cyclopiazonic acid (10 μM) and channel blocker 2-APB (100 μM). H2O2 (100 nM – 1 mM) inhibited ACh-evoked Ca2+ signals in a concentration-dependent manner. Low concentrations (e.g. 1 μM) of H2O2 are likely to be most physiologically relevant in signalling and were investigated further. H2O2 suppression of ACh-evoked Ca2+ signals appeared as a decrease in the amplitude of the Ca2+ signal in each activated cell and a reduced number of cells activated. H2O2 inhibition of Ca2+ signals were reversed by catalase (1000 U/ml). H2O2 may decrease ACh-evoked Ca2+ signals by reducing the affinity of the ACh receptor, decreasing the production of IP3 or limiting the activity of the IP3 receptor. To distinguish between these possibilities, the effects of H2O2 on direct activation of the IP3 receptor was examined using photoactivatable caged-inositol 1,4,5-trisphosphate (cIP3). Ca2+ release from IP3 receptor, by photolysis of cIP3, was inhibited by H2O2, an effect reversed by catalyse (1000 U/ml). Together, these results suggest low concentrations of H2O2 inhibit intracellular Ca2+ signalling by desensitizing IP3 receptors. These findings point an important interaction in low concentrations of ROS in the control of physiological Ca2+ signalling. Support or Funding Information Supported by the Wellcome Trust and British Heart Foundation This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.
Helen Rachel Heathcote, Matthew David Lee, Calum Wilson, Chris D. Saunter, John M. Girkin, John G. McCarron
Published: 1 April 2018
The FASEB Journal, Volume 32, pp 843.3-843.3; https://doi.org/10.1096/fasebj.2018.32.1_supplement.843.3

Abstract:
The vascular endothelium is the innermost layer of cells lining blood vessels and is the key regulator of vascular tone. A critical feature of endothelial signalling, in the control of vascular function, is the endothelium's ability to coordinate function by communicating information between cells. Changes in the intracellular Ca2+ concentration is a major regulator of endothelial function. Central to an understanding of the control and coordination of endothelial function is an appreciation of the control of Ca2+ signalling across cells. While Ca2+ release from the internal store is of acknowledged significance in the control of endothelial function, the mechanism(s) permitting Ca2+ influx to coordinate activity across cells are less well understood. Ca2+ influx via the transient receptor potential vanilloid channel 4 (TRPV4), a non-selective Ca2+ permeant cation channel, is reported to be an important contributor of endothelial signalling and vascular tone. TRPV4 is activated by thermal and mechanical stimuli, endogenous signalling molecules such as phorbol esters and the downstream metabolites of arachidonic acid, as well as pharmacological compounds including GSK1016790A (GSK101) and 4alphaPDD. However, how Ca2+ influx via one or few channels on the outside membrane of endothelial cells is communicated across multiple cells is not understood. Here in the endothelium of isolated mesenteric arteries (8–12 week old Sprague Dawley rats) intracellular Ca2+ signalling in response to TRPV4 activation was visualised using the Ca2+ indicator Cal 520/AM (80–100 cells per field of view). En face artery preparations were perfused with TRPV4 activators diluted in MOPS buffer, at a rate of 1.5 ml/min. Ca2+ images were captured using a high-sensitivity CCD camera and analysed using a custom analysis package written in Python. The TRPV4 activators GSK101 (20 nM) and 4alphaPDD (5 μM) initially evoked sporadic, localized rises in Ca2+. The Ca2+ rises increased in frequency and amplitude and endothelial cells eventually exhibited a global increase in intracellular Ca2+ that propagated as widespread waves within and between cells. Both Ca2+ influx and widespread propagated waves were prevented by the removal of extracellular Ca2+ or pre-incubation with the TRPV4 antagonists HC067047 or ruthenium red. On the other hand, prior depletion of the intracellular store with cyclopiazonic acid (CPA) or inhibition of phospholipase C (PLC) using U73122, or block of the IP3-receptor with 2-APB inhibited the widespread propagating waves. However, neither U73122 nor 2-APB prevented the global rise in Ca2+ evoked by GSK101. These data suggest that TRPV4 activation causes Ca2+ influx that induces IP3 and store dependent propagating waves. Ca2+ influx and propagating waves may be an important contributor for vasorelaxation mediated by TRPV4. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.
Xin-Yu Bao, Zhiyuan Ye, David Carlson, Errol Sanchez
Abstract:
III-V semiconductor materials have been drawing extensive interests in the past decades due to their superior electronic and optical properties with great potential to improve the device performance. Compared to Si, III-V materials have mobility about 10 times higher and injection speed 2~3 times faster. CMOS devices can benefit from higher mobility and injection speed to improve operation frequency, current, power consumption, and reduce short channel effect, etc. With direct bandgap and sophisticated bandgap engineering, III-V materials also provide board range of optical applications such as optical transceivers, infrared and visible LEDs/photo detectors, photovoltaics, and lasers. It's ideal and cost effective to integrate III-V with large Si substrate (e.g. 300mm) to take advantage of the main stream Si process flow in the semiconductor industry. The biggest challenges are lattice mismatch and anti-phase boundary (APB) caused by polar/nonpolar planes. In this paper, we reviewed the issues for growth on blanket wafers and selective growth on patterned wafers using the Applied Materials' 300mm III-V metal-organic chemical vapor deposition tool (MOCVD). On nominal non-offcut Si (100) blanket wafers prevalently used in industry, multiple layers are typically used as buffer stack to bridge the lattice mismatch between the Si substrate and final device layer. Ge buffer layer was first tested to achieve high quality GaAs film with APB free top surface on Si substrates with very small off-cut angles (≤0.5º) [1]. For growth directly on Si, it is critical to form proper double-step Si layers prior to the III-V layer deposition to reduce APB density. We found the oxygen and carbon residual contamination is directly correlated to the APB density for GaAs growth on Si (100). The APB density at the GaAs top surface increased significantly from 0.14 to 3.2μm-1 while the O and C dose at Si/GaAs interface increased from 7.3x1011 to 4.0x1012 atoms/cm2 and from 1.9x1014 to 1.7x1015 atoms/cm2, respectively. [2] By optimizing the process, the GaAs top surface can be virtually APB free with total thickness as thin as 150nm. The electrical and optical properties of GaAs film can be greatly improved when APB is eliminated. Hall Effect measurements revealed a mobility enhancement from 200 to 2000 cm2/V.s. The room temperature photoluminescence (PL) intensity increased almost 10 times. [3] Planar ultrathin InAs-channel MOSFETs were demonstrated on Si substrates with gate lengths (Lg) as small as 20 nm which showed high transconductance about 2000 μS/μm at VDS=0.5V and 142 mV/dec subthreshold swing (SS). The III-V buffer layers were grown on 300 mm Si substrates by MOCVD and the subsequent InAlAs bottom barriers and InAs channel were grown by MBE. [4] Selective growth on patterned wafers can benefit from defect trapping in high aspect ratio structures. We successfully grew high quality GaAs, InGaAs and InAlAs layers in both narrow and wide trenches ranging from tens of nanometers to hundreds of nanometers. [5-7] It's shown that the APB density is lower in higher aspect ratio trenches. InxGa1-xAs (x=0.1-0.4) quantum wells with stack GaAs/AlAs/InGaAs/AlAs/GaAs in 100nm wide trenches were demonstrated and room temperature μPL spectra were observed. We also explored the concept of III-V FinFET devices which uses InGaAs as channel layer. Reference [1] Y. Bogumilowicz, et al., Applied Physics Letters 107, 212105 (2015). [2] C. Barrett, et al., Journal of Materials Science 51, 449-456 (2016). [3] R. Alcotte, et al., APL Materials 4, 046101 (2016). [4] C. Y. Huang, et. al., International Symposium VLSI Technology, Systems and Application (2015). [5] W. Guo, et al., Applied Physics Letters 105, 062101 (2014). [6] R. Cipro, et al., Applied Physics Letters 104, 262103 (2014). [7] B. Wood, et al., International Symposium VLSI Technology, Systems and Application (2015).
David B. Allison, Josep Bassaganya-Riera, , , , , Willem Van Eden, Johan Garssen, Raquel Hontecillas, Chor San H. Khoo, et al.
Published: 8 September 2015
Frontiers in Nutrition, Volume 2; https://doi.org/10.3389/fnut.2015.00026

Abstract:
With the definition of goals in Nutrition Science, we are taking a brave step and a leap of faith with regard to predicting the scope and direction of nutrition science over the next 5 years. The content of this editorial has been discussed, refined, and evaluated with great care by the Frontiers in Nutrition editorial board. We feel the topics described represent the key opportunities, but also the biggest challenges in our field. We took a clean-slate, bottom-up approach to identify and address these topics and present them in eight categories. For each category, the authors listed take responsibility, and deliberately therefore this document is a collection of thoughts from active minds, rather than a complete integration or consensus. At Frontiers in Nutrition, we are excited to develop and share a platform for this discussion. Healthy Nutrition for all – an ambition too important to be handled by detached interest groups. Johannes le Coutre, Field Chief Editor, Frontiers in Nutrition (Barbara Burlingame, Chor San H. Khoo, and Dietrich Knorr) To deliver successfully, nutrition research needs a bold dose of innovation. Moving forward from the Millennium Development Goals to the post-2015 sustainable development goals (SDG), global nutrition appears to require an improved model. Under current practices, feeding the exploding world population necessitates to close a gap of nearly 70% between the amount of food available today and the projected availability by 2050 (1). Today, globally, an estimated 805 million people are undernourished or food insecure (2), yet one out of four calories from food goes uneaten. Meanwhile, overweight and obesity affect approximately two billion people, including 42 million children under the age of 5. Human health notwithstanding environmental health is also at stake. Agriculture alone accounts for about 70% of our global water usage and 24% of our greenhouse gas emissions. As a result, our strategies to overcome issues of food sustainability, food waste, and food loss must be multifarious and include, at the very least: (i) Improving the global consumption of food. (ii) Increasing production efficiencies on existing agricultural land. (iii) Developing sustainable approaches that reduce the environmental impact of food production, and in particular greenhouse gas emissions. Certainly, the impact of agriculture on climate, ecosystems, and water will have to be reduced, while at the same time, we will need to ensure that it supports inclusive economic and social development (1). Systems science, the interdisciplinary field that explores the nature of complex systems, is perhaps the best research model we have for addressing the urgent needs of a precariously unhealthy planet. For better or for worse, nutrition imparts a quintessential challenge, straddling many sectors and disciplines. In the past, at times, the agenda for mainstream nutrition has been pushing sectoral lines of reasoning by implementing policies that leave long-standing problems unresolved, while disrupting other sectors in the process. Of course, nutrition is not alone in this, but the history of unintended consequence is long and discouraging (3, 4). Agriculture and health have been the mainstay sectors at the United Nations level, in government ministries, and in academic departments. Increasingly, nutrition is being recognized as an important pillar for the environmental sector, with biodiversity for food and nutrition acknowledged by the Convention on Biological Diversity (5), and the Commission on Genetic Resources for Food and Agriculture accepting whole diets, food, and nutrients for human nutrition as ecosystem services (6). For all their embracing of nutrition, these sectors often work at cross-purposes, providing many useful illustrations of policies and programs that undermine each other’s development efforts. We have policies and interventions in agriculture that contribute to diet-related chronic disease, environmental degradation, and food insecurity (4, 7); conversely, in the health sector we have policies and interventions that compromise agricultural development (8); and in the environmental sector that lead to micronutrient malnutrition (9). Agriculture in particular, while solving some of its own sector problems, has been associated with many of the environmental and human health crises we now face, which directly impact upon nutrition, including chemical contamination of food supplies, loss of agrobiodiversity, and severe environmental degradation (10). In spite of the clear need to develop innovation for the future, “systematic attempts to explore existing methods and to develop new technologies of more sustainable food production systems have so far been scarce” (11). Although this quote is from over 30 years ago, it still quite accurately describes the current situation regarding activities related to sustainable diets and sustainable food systems. A sustainable development lens with a systems science approach offers not only a new analytical model for nutrition, but also an ethical and inclusive framework. Within this framework, nutrition encompasses more than its traditional domains and takes on issues of climate change (12), biodiversity and ecosystems (13), water use/waste (14), food losses and waste (15, 16), sustainable forests and seas (17), chemical contamination of food and water supplies (18), environmental regulatory issues and food law, risk and risk/benefit assessments (19), and monitoring adherence to and compliance with a range of relevant treaties and signed declarations/commitments (13). With this mindset of sensitive, cross-sectoral resolve, tangible and specific solutions will envisage a holistic food chain integration taking into account a total life cycle assessment. Food and nutrition security must be an intrinsic component of any solution for food sustainability. Forthcoming strategies will also have to explore the potential and utilization of new raw materials. Improvements of food safety, storage, packaging, and transportation – including the use of sensor technologies – can reduce food losses and waste. Innovation will have to equally encompass the re-evaluation of existing food processing, storage, and home preparation operations employing existing modern toolboxes. Moreover, low energy, waste-free or waste-reduced processing, and preparation operations need to be implemented to a larger extent, including alternative energy sources. In the same context, water decontamination, recycling, and preservation tools need to be applied. Unintended consequences must be considered with any sustainability program and global solutions are not necessarily applicable in local contexts. For example, reducing livestock production and consumption in one setting may benefit both human and environmental health, while in another setting it may reduce further already marginal intakes of high-quality protein and micronutrients and marginalize grazing lands that are self-renewing, sustainable repositories of biodiversity. Finally, young engineers and scientists need to be encouraged, trained, and involved to tackle the challenges of the future. We have a planet in crisis on so many fronts. Regardless of how the SDGs evolve, this multi-sectoral vision of nutrition research and action has the potential to make meaningful, and sustainable, contributions. (David B. Allison, Andrew W. Brown, and Tapan Mehta) “Science,” as Adam Smith famously said, “is the great antidote to the poison of enthusiasm and superstition” (20). Complementarily, Stephen Hawking has called scientists, “the bearers of the torch of discovery in our quest for knowledge” (21). Thus, science can be seen as having two key complementary roles – dispelling false beliefs, and creating new knowledge. For science to fulfill this joint mission, its practice must be true to its principles and precepts, including objectivity, methodological rigor, transparency, and reproducibility. Yet, there are concerns that departures from these precepts are too common (22–28). Some have speculated that deviations from good scientific practices have increased in recent years due to a number of social, institutional, and economic factors in science (25, 29). Others have speculated that the problem may be especially severe in the related domains of nutrition research and obesity research, perhaps because of emotional, economic, and other factors involved in those topics or because the everyday familiarity with aspects of those topics is mistaken for expertise (23, 26–28). It is difficult to quantify whether the situation is better or worse today than in the past, or whether this is especially true in nutrition and obesity research compared to other fields. Nevertheless, it is clear that the problem exists. Several initiatives are going to be important in the coming years to improve nutrition as a science. First is classifying errors that exist in the nutrition literature. Just as Mendeleev’s Periodic Table of the Elements led to increased understanding of chemistry and Linnaeus’ taxonomy of life led to a framework for the study of biology, if we can develop a “pathology” or classification of these errors, we may be better able to quantify the situation, identify patterns, develop an understanding of origins, and ultimately reduce the occurrence and severity of these errors. In our non-systematic study of these issues, we see a number of categories of common errors (Table 1). We refer to them as errors without making any inference that they are intentional or unintentional errors. Table 1. Common errors noted in the published literaturea. Second, there is a general movement in science for “Transparency and Openness Promotion,” formalized in “The TOP Guidelines” (30). The guidelines recognize eight standards: citation, data transparency, analytic methods (code) transparency, research materials transparency, design and analysis transparency, preregistration of studies, preregistration of analysis plans, and replication. These standards aim to improve the communication of science, allowing improved understanding and replicability of results. Because the TOP Guidelines are being adopted across fields of science, the field of nutrition will not have to act in isolation to improve its scientific practices. Instead, we can build on and work with the minds and resources coming from a spectrum of scientific inquiry. Indeed, Frontiers in Nutrition was one of the initial signatories. Third, there is a need to develop sound methodology for evaluating nutrition and diet in free-living research participants. Issues are continually documented with self-report diet methodology (31–33), and yet dietary recommendations depend heavily on dietary recall data (34). Similarly, although existing nutrition-related health hypotheses can be investigated using randomized controlled trials (pragmatic or explanatory), the field often relies on ordinary association tests using observational data to quantify evidence (35, 36) that policy-makers may then use to create policies or guidelines. The needs here are twofold: to develop and implement study designs that lie in the causality spectrum between ordinary association tests and randomized controlled trials (37, 38) and to develop objective, reliable data on dietary patterns and nutrient status (31–33). We believe that by recognizing and acknowledging these problems, we also recognize and acknowledge that our field can do better. This will pave the way toward constructive efforts to reduce such problems and to ultimately improve the scientific foundations of nutrition science. (Martin Kussmann, Josep Bassaganya-Riera, Raquel Hontecillas, Tapan Mehta, and Chor San H. Khoo) Diet is considered a key environmental factor for maintaining health and preventing disease. As such, we need to better understand the interactions of nutrition and lifestyle with an individual’s genetic makeup in order to delay or prevent metabolic and cognitive decline. Nutrition science is therefore undergoing a paradigm shift to better leverage the potential of nutrigenomics, a discipline that is already transforming the field (39). To achieve this, the field will need to transform its current approach to research and implementation actions, and to take advantage of emerging advances in other disciplines – research designs, methods, new technologies, big data analysis, and bioinformation sharing. The conceptual basis of gene – environmental interactions require not only research and technology, but also the cross-fertilization of disciplines: genomics will encompass other-omics, and nutrition research will need to take on a holistic or system biology approach rather than just nutrients, ingredients, or genes. Nutrition science now encompasses more than the classic reductionist and descriptive approaches to more quantitative and systems-level approaches (40). Translational research to maintain health and prevent or delay disease onset requires a transdisciplinary approach that embraces the complexity of human individuality in a rapidly changing environment. Nutrigenomics fuels this research by investigating how genomic and epigenomic individuality predisposes dietary, health, and disease responses. It also influences how an individual’s genome expresses itself at different omic levels (proteomics, metabolomics, lipidomics) in response to environmental factors, including nutrition. Molecular phenotyping of humans over time and across healthy and safe exposures and challenges have thus been proposed (41). Both the ongoing prevalence of malnutrition and the increasing incidence of nutrition- and lifestyle-related chronic diseases require comprehensive characterization of the complex interactions between environment and genetic makeup. Systems thinking in human nutrition, environment, and health requires improvement and translational thinking in three areas: (a) In vitro and in vivomodels: a systems approach to human health implies rethinking of in vitro and in vivo models with regard to their translatability into human phenotypes: natural human cell models and panels of rodent strains should complement cancer cell lines and single rodent strains. (b) Human intervention study designs: classical case/control designs of human clinical/nutritional intervention studies should be complemented by longitudinal crossover studies, in which every subject is one’s own case and control. Human clinical study subjects should not only be assessed at homeostasis, but also during a challenge to, and restoration of, homeostasis. (c) Tools for molecular phenotyping and capturing of human diet and lifestyle: nutrigenomic studies have typically been technology-driven rather than technology-rooted. Normative science methods and approaches need to be complemented by more comprehensive systems biology-based investigations deploying a multitude of omic platforms in an integrated fashion (41). While comprehensive and quantitative omics are rapidly progressing in terms of data generation, quantitative capture and monitoring of diet and lifestyle have lagged behind. Non-invasive technologies are now providing more attractive and precise image- and web-based or body-wearable consumer/research interfaces (42). The bottleneck in knowledge generation has moved from (omics and clinical) data acquisition to processing, visualization, and interpretation. Innovative tools and methods for statistical treatment and biological network analysis are now at the forefront of nutritional and biomedical sciences (43). To achieve this transformation and advancement of nutritional science, it is critical to connect researchers from all disciplines conducting direct or indirect research in the areas, e.g., (gen)omics, clinicals, dietetics, food science and technology, physiology, epidemiology, bioengineering, analytics, biomathematics. A transdisciplinary approach needs to be considered – enabling a spectrum of communicating and sharing from fundamental laboratory research, patient- and consumer-relevant outputs from personalized dietary/nutritional counseling to monitoring/diagnostics. Progress in advancing nutrigenomic interventions for consumers and patients can only be accelerated if nutrition research is broadened to include quantitative, holistic, and molecular sciences (44). “Let the food be your medicine, and medicine be your food,” a statement attributed to Hippocrates, the father of Western Medicine, delineates the impact of nutrition in human health and disease. Indeed, several decades of research at the interface of nutrition and immunology demonstrate that infectious, immune-mediated and metabolic diseases are safely and effectively preventable through dietary interventions. Nonetheless, there is a major disconnect between the description of nutrition-based protection from disease and an insufficient mechanistic understanding at the systems-level of the complex network interactions by which nutrition mediates clinical protection. As a result, a comprehensive understanding of the mechanisms of action underlying the actions of nutritional interventions and the combinatorial effects of nutrients (i.e., synergistic, antagonistic, or additive) at the systems-level remains largely unknown. As about 70% of the immune system is located in the gastrointestinal tract since the gut mucosa houses the largest repertoire of immune cells and commensal microbiota that symbiotically coexist to elicit protective immunity, studying nutritional immunology of the gut mucosa is incredibly important (45). Coupling host-nutrient-microbiota actions, enabled through computational modeling of the gastrointestinal tract (46–50) with systems immunology frameworks has the potential to predict combinatorial outcomes of nutrient-microbiota–immune system interactions and advance toward a comprehensive systems-level mechanistic understanding of how nutrition and foods prevent disease. Computational models of nutritional immunology that funnel omics and cellular data judiciously, coupled with systems biology models of the underlying disease/organ, will bridge the connection between traditional methods of nutritional immunology research and their effect on the whole organism, which will enhance mechanistic insights and translational value. Over 163 nutrition themed systems biology markup language models (SBML) are already available in the Biomodels database (51). In summary, applying the iterative systems biology cycle of model building, calibration, refinement, and validation in nutritional immunology research has the potential to accelerate the discovery of novel network biomarkers and systems-level mechanistic understanding of the action of dietary components on immune responses. There has been an explosion in data collection and aggregation, some of which can be used for public health purposes, including obesity and nutrition-related research. Consequently, ample opportunities emerge to utilize “big data” in the pursuit of interesting outcomes and effectiveness studies related to nutrition and obesity using techniques such as quasi-experimental approaches. These approaches, when assumptions are satisfied, are intermediate between ordinary association tests and randomized controlled trials (37) in terms of presenting evidence for causality. In this article, the term “big data,” which is often used subjectively, refers to very large amounts of data: structured and unstructured that may also increase over time rapidly (52). These types of data are collected by both the public and private sectors and increasingly require a distributed architecture to manage them efficiently. Big data analysis has generally referred to the confluence of statistical, machine learning and computational approaches to synthesize and analyze these large amounts of data. Administrative data, such as micro-level data aggregated by governments as well as private companies, can be used to evaluate the effectiveness of pharmacological and surgical interventions. In fact, private companies have started collecting unprecedented amounts of data with some companies specializing in data linkages. For example, companies such as Optum not only aggregate claims data from private insurance companies but are able to provide linked clinical data from the corresponding electronic health records (EHR). Data linkages are an extremely powerful tool since they allow researchers to answer questions that are otherwise not accessible using a single data source. For example, claims data do not provide information about the height and weight of an individual, but the linked clinical data do. Similarly, the increasing availability of EHR data and the initiatives to link these EHR data with genomic data can enable us to pursue a variety of studies, including pharmacogenetic and precision medicine studies. One of the challenges in accessing and leveraging “big data” is the resources, including the associated cost of purchasing the data, especially from private companies. Collaborations between industry and academic researchers are essential to fully exploit the data and to overcome logistical challenges (53, 54). So far, big data analysis has primarily focused on high-dimensional prediction models. The data mining and statistical toolkit for such approaches includes, but is not limited to, techniques such as boosting, random forests, classification and regression trees, and lasso-like penalized regression models (53). While randomized control trials are considered gold standards, there are a variety of methods and designs that may allow us to generate evidence that may lie in the spectrum between purely association and definitively causal. Coupled with “big data” is an opportunity to estimate a degree of causality using techniques such as high-dimensional propensity score and differential comparison approaches to provide evidence that is indicative of causality (55, 56). There is also a potential to use instrument variable approaches, used commonly in health policy studies, by identifying appropriate instruments from “big data.” Recent attempts to develop methods that enable to provide a degree of causal evidence are very encouraging and can allow us to maximize the potential of “big data” (57, 58). (Michael Rychlik) The authenticity of food is generally related to one or more of the following attributes: geographic origin, type of agricultural production, species and kind of raw materials, or certain process qualities such as sustainability or ecological foot print. Regularly uncovered crises of food adulteration underline the sensitivity of consumers to this issue. Apart from meat, foods that are often adulterated are olive oil, fish, organic foods, spices, tea, cocoa, coffee, and nuts. In recent years, there has been tremendous progress in high-resolution methods to elucidate the molecular fingerprint of food. On the genetic scale, apart from classical polymerase chain reaction, new developments of isothermal amplifications or next generation sequencing will enable more accurate identification of species. On the protein level, specific biomarker peptides can be used. For a fingerprint of metabolites, the new methods of non-targeted and targeted metabolomics already allow a specific authentication. In this field, the methods currently showing the best resolution are Fourier transform ion cyclotron mass spectrometry (FT/ICR-MS) or nuclear magnetic resonance (NMR) spectroscopy (59). These new methodologies generate “big data,” from which the relevant information is only accessible when applying novel bioinformatics approaches. Regarding food safety, microbiological decay and foodborne infections still play an important role. However, contaminants also endanger the safety of all links in the whole food chain. The recent discoveries of process contaminants encompass simple molecules, such as acrylamide, furan, benzene, styrene, as well as more complex compounds such as 3-monochloropropane-1,2-diol (MCPD) esters. An end of new discoveries cannot be foreseen yet and we may assume that the sum of all these contaminants has a significant impact on life-style diseases such as cancer. Further new contaminants arise from packaging materials such as mineral oil saturated hydrocarbons (MOSH) or mineral oil aromatic hydrocarbons (MOAH), and pollutants from the environment such as the polyfluorinated alkyl substances (PFAS). Moreover, the historic toxin arsenic is more relevant than ever as rice and rice products are often contaminated and the mechanisms of arsenic carcinogenicity are still under controversial discussion. Generally, risk assessment of food contaminants or residues is predominantly performed on single compounds. However, almost completely missing is an assessment of the combined effects of toxins, be it within one group of compounds or spanning various structural groups. The current concept for assessing combinatorial effects is that of cumulative assessment groups (CAGs), which, e.g., assess the cumulative potency corrected dose of acute reference doses (ARfD) for pesticides showing the same mode of toxic action (60). However, this approach is still preliminary and lacks comprehensive confirmation. (Adrian Meule, Chor San H. Khoo, and Claus Vögele) Numerous environmental, social, and individual factors influence human food choice and intake (61). In Western and Westernized societies, household expenditures and dietary energy availability decreased for unprocessed or minimally processed foods in the last decades while they increased for convenience foods and processed products (62, 63). An environment where there is easy and frequent accessibility to food, and where cues signaling food are ubiquitous, requires constant self-monitoring and -regulation in order to prevent or manage weight gain (61). This, however, can be a highly effortful endeavor, leading many people to struggle with long-term weight maintenance. As evident from data from the last century, these self-regulatory efforts are made more difficult by increased consumption of energy-dense palatable foods and ingredients (e.g., sugar, fat, and salt) (64). As a result, some have argued that these foods might have an addictive potential and that a subset of individuals who have difficulties in controlling consumption of these foods may be addicted to them (65–68). In the scientific literature, the association between food and addiction and the actual use of the term food addiction has a long history, dating back to the 1950s and even earlier times (69, 70). Not until recently, however, have researchers tried to more precisely define what is meant by food addiction and to systematically investigate its validity, as a consequence of which the number of publications, including the term food addiction, increased substantially over the past 5–6 years (65, 71). In humans, research on food addiction has been promoted by the Yale Food Addiction Scale (YFAS), a self-report questionnaire developed in 2009, which measures symptoms of addiction-like eating based on the diagnostic criteria for substance dependence as outlined in the fourth version of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV)(72). Since 2013, these diagnostic criteria have been revised in the fifth version of the DSM and a new version of the YFAS, which has been adapted accordingly, is currently under way (73). Although research on food addiction is growing, it remains a controversial and debated topic with many researchers questioning the validity of the food addiction concept based on conceptual considerations or physiological mechanisms (74–78). To address these issues, more and better human studies are needed to resolve questions related to, for example, whether animal models of food addiction are transferable to human eating behavior (79, 80). These controversies, in particular, lead us to argue that food addiction research in humans is still in its infancy, that it would be premature to conclude that some foods are addictive, and that research efforts to clarify this will further increase in the years to come. There are numerous avenues for future directions, which may include, but are not limited to: how do we define and harmonize definitions of food addiction? What are the implications of changes in the diagnostic criteria for substance dependence in the DSM-5 for food addiction (73)? Are all addiction criteria (as described in the DSM-5) equally applicable to human eating behavior? If not, does this obliterate the concept of food addiction (81)? How can food addiction be measured in humans other than using the YFAS and which methodological improvements need to be made to better design human behavior studies, including randomized controlled trials (72)? How relevant is the concept of food addiction for the treatment of obesity or binge eating and in public policy making? If it is relevant, how can it best be implemented (70, 82)? What are the disadvantages (if any) of the concept of food addiction (83–85)? How can animal models of addiction-like eating be improved to more specifically reflect relevant processes in humans (86)? Which foods are possibly addictive (87)? Can addiction-like eating actually be reduced to the addictive effects of substances or should the discussion about “food addiction” rather be replaced by a discussion on “eating addiction” (88)? (Pierre Magistretti, Johannes le Coutre, and Suzanne L. Dickson) Cognitive decline, dementia, Alzheimer’s disease, and other age-related neurological diseases are on a rise in high income countries as well as in low and middle income countries (89). Achieving and maintaining brain health is a lifelong endeavor with identifiable targets that are specific for each period in a lifetime. Thus, targeting cognitive development in the early phases of life and preventing cognitive decline during aging are priorities for any preventive or interventional approach. While pharmacological approaches can only be envisioned for brief periods of time and, for the most part, have been unsuccessful, nutritional approaches are implementable for extended periods of time. Initiatives on brain health should incorporate a nutrition-based approach that can be implemented throughout the different phases of life. In order to identify valid nutritional approaches for brain health, it is important to better understand the mechanisms that are at the basis of brain energy metabolism regulation. Key advances have been made in recent years in the identification of the molecular and cellular mechanisms that regulate the delivery of energy to active neurons. In particular, an active metabolic exchange has been characterized between neurons and astrocytes with specific molecular steps that can become targets for nutritional interventions. For the identification of the efficacy of such nutritional interventions, means for appropriate monitoring of markers need to be defined. This can be achieved by monitoring with brain imaging techniques, structural markers with morphometric approaches and myelination with MR as well as functional activation with fMRI, PET, EEG, and MRS, coupled with neuropsychological tests monitoring cognitive performance, motivation, and attention. The utility of these technologies goes beyond brain health and many of these approaches are being used to validate, in humans, the neuroscience of nutrition that, so far, has only been conducted in rodent models (90, 91). There is no doubt that targeting the molecular steps of brain metabolism with nutritional interventions and monitoring their structural and functional outcomes in vivo in humans, in particular regarding cognitive performance, represents a promising approach for developing nutritional interventions for achieving brain health that can be maintained on the long term. Meaningful nutrient intake and nutritional intervention likely has an impact on the development of cognitive and behavioral performance measures, thereby determining our health span throughout life. Brain imaging studies on infants demonstrate how breast milk promotes healthy neural growth and early white matter ­development (92). Nutrients also engage brain pathways linked to metabolic control, appetite, and food-linked behaviors. There has been a general expectation that it must be possible to use food formulation/composition to control how much and what we eat by altering the satiating and/or reward value of food combinations (93, 94). Currently, we lack a sufficient scientific evidence base that certain “unhealthy” foods fall short of “healthy” foods in their ability to induce satiation, limit hunger, or reduce hedonic over-eating. Moreover, it has not yet been demonstrated that any food or combination of foods has beneficial effects on appetite and energy intake of sufficient duration or magnitude to impact on body weight or metabolic health (95). This is a new and emerging field for which major advances are likely to progress through a better understanding of how nutrients communicate with the appetite-regulatory brain networks. Nutrient-brain communication could be direct but likely engages intrinsic physiological control systems. For example, when we eat, sensing mechanisms in the gut signal information about the amount and content of the food to the brain by nervous and endocrine afferent signals. Indeed, gut-derived hormones such as ghrelin and glucagon-like peptide 1 communicate with hypothalamic and brainstem areas linked to energy balance but also to brain areas processing the reward value of food and even brain areas linked to emotion and cognition (96, 97). Thus, while it seems clear that appetite-regulating hormones have a capacity to redirect behaviors important for governing how much and what we eat, the extent to which nutrients can control these behaviors through engaging intrinsic endocrine signals remains to be elucidated. A related question is whether specific nutrients or food combinations can act on the brain to reinforce their own intake, leading to addictive-like over-consumption. As reviewed recently (88) and as mentioned already in the previous section, it is very difficult to demonstrate in humans or rodents that foods act on the brain in a manner similar to addictive drugs, causing individuals to become addicted to them. It was suggested therefore that the term “eating addiction” rather than “food addiction” should be used to better describe addiction-like behavioral over-eating disorders. If it becomes possible to diagnose this patient group, e.g., through combining questionnaires about addictive-like behavior for food with brain imaging (98, 99), there will be a large public health impact on treatment and prevention strategies. Additionally, industrial stakeholders and politicians will need to find solutions to circumvent or treat eating addiction (88). (Dietrich Knorr and Chor San H. Khoo) The human body harbors over 8 million microbial genes, over 10,000 species, and plays host to over a trillion microbes. Microbial cells outnumber human cells by a factor of 10 (100). As a result, there is considerable interest to better define and understand the microbial role in host physiology, health, and disease etiology. In the last decade, there has been a tremendous surge in microbiome research funded by programs such as the Human Microbiome Project (HMP) and the MetHIT Program. Advancing new and multiple technological approaches – whole genome sequencing, metagenomics, high-throughput-analysis, proteomics, transcriptomics, cultivation, metabolomics, and bioinformatics – has led to new insights into microbial variety and abundance in 15–18 body sites, including the oral cavity, skin, airway, gut, and vagina, from 242 healthy participants in the largest cohort study to date. Findings from this research were published in two seminal papers in 2012 by the Human Microbiome Consortium (100, 101). The HMP study has the largest collection of data on abundance and variety of the human microbiome, with 5,177 unique microbial taxonomic profiles from 16S ribosomal RNA genes, more than 3.5 terabases of metagenomic sequence, and 800 reference strains isolated and sequenced (100). Noteworthy observations from the HMP study are outlined in Table 2 (102). Table 2. Variation in microbial ecology among individuals (102). Translating learnings from emerging microbiome and health research presents exciting opportunities for future food and nutrition development. The use of microbes in food product development is not new. Fermented products are widespread and common in the market place. Food biotechnology has been in existence for more than 8,000 years (103). The potential health impact of gut microbiota has been postulated by Metchnikoff (104) and since then, numerous related research results have been provided (105–107). Probiotics are supplied in starter cultures and thus need to be preserved for transportation and use. As the highest possible cell density is required, losses that occur during processing, transportation, and storage, including in products, are detrimental. Consequently, approaches to increase and retain physiological fitness have been explored (108, 109). Emerging capabilities to characterize microbial communities and their functions in the oral cavity present insights into the role microbes may play in taste and olfaction, and present new opportunities to further personalize and refine food products to better suit individual taste and palatability preferences. Oral pre- and probiotics may be an opportunity for innovation. These emerging advances in human microbiome structure, diversity, and function present exciting new opportunities for new food products, ingredients, or dietary approaches that can be used for supporting daily health, direct or adjunct intervention for risk reduction, or for new therapeutics for symptom reliefs (IBS). However, to advance these undertakings, several key questions need to be addressed. How easy is it to translate microbiome research to food and dietary applications? Limited well-designed studies have been performed that explore the impact of food and diet on microbial ecology and function. What biomarkers are available or need to be developed to understand how food and diet impact on the microbiome (gut, gut-brain, gut-kidney, etc.)? What microbial combination will be best suited for achieving specific outcomes? Of challenge is the ability to identify and separate the “good” from the “bad” microbes that can present food borne illness or exacerbate disease risks. Gene sequencing and whole genome sequencing technologies have been used to diagnose and trace food contamination, and are now also applied in medicine. How can current microbiome research be easily translated for food and product applications? How easy is it to transfer available technologies and tools already developed for use in food and nutrition applications? In addition, there remains room for improvement when translating to innovative or tailor-made products. Needs and opportunities include process generated structures, which impact on food properties (process–structure–function relationship) as outlined in the European Technology Platform Strategic Research Agenda (ETP SRA) (2007; 2012; 2014) for designing tailor-made foods for the targeted release of essential food constituents at points of need to support human microbiota growth and metabolic fitness. This needs to include the entire human digestion system encompassing the chewing apparatus, mouth microbiota, and enzymes. Moreover, food can contain viable microbial cultures as well as active enzymes. Understanding their role in and during digestion as well as their impact on gut, mouth, and skin microbiota may lead to the development of new food design concepts with targeted nutritional benefits. Finally, emerging technologies are being introduced to the food processing area, including high hydrostatic pressure, pulsed electric fields, and atmospheric plasma. Little is known about their impact and function with regard to the human microbiota. These technologies could open new avenues for process–­function–structure relationships as well as provide foods with metabolic properties not achieved via traditional processing (36). (Johan Garssen, Willem van Eden, and Josep Bassaganya-Riera) Whereas the disciplines of pharmaceutical and nutritional sciences have evolved separately in the Western world, for Asia these two research areas have been connected for centuries. However, today, with the ever-growing burden of chronic diseases in modern societies, the high relevance of specialized nutrition in both prevention and therapeutic approaches receives increased attention and recognition. The gap between food and pharma is narrowing (110). One reason might be that, scientifically, the evidence for the so-called multi-target or polypharmacology approaches aimed at disease management is growing. Medical nutrition is beginning to be recognized as a unique and potentially powerful area in Western societies at the interface between food and pharma. Medical nutrition targets innovative nutritional therapies, offering healthcare professionals solutions to effectively manage disease-related malnutrition and specific disease states. Medical nutrition is and will be increasingly understood as a useful and sometimes even essential component in the management of patient health. Many medical conditions can be managed better when patients are receiving a specialized diet adapted to their unique circumstances. Sometimes, the constraints to appetite may be physical, as in the case of stroke patients who may find it difficult or impossible to swallow, or of young children with neurological disabilities. Sometimes, the problem may simply be insufficient intake, caused by the loss of appetite. It is well known that many chronic diseases are associated with malnutrition, a phenomenon that is not solely based on body mass index or body weight. Many obese patients suffer from specific malnutrition. Examples of disease areas that might be associated with specific malnutrition are cancer, stroke, and COPD. However, frail or elderly people are treated and fed with this type of medical nutrition as well. Medical nutrition might bring solutions and support to these cases across a broad range of care settings – in the hospital, in the care home, or in the community. It contains unique compositions of specific nutrients that would be impossible or impractical to achieve through normal food intake alone. In most cases, it is administered via the gastrointestinal tract orally or with a feeding tube, utilizing the natural route for nutrient digestion and absorption. These cases are underpinned by a unique scientific rationale, preclinical and clinical research, and health economic evaluation making it very similar to the traditional pharma approach. By making medical nutrition an integral part of care, patient outcomes are significantly improved. Lower healthcare costs by shortening hospital stays and keeping patients independent for longer are key outcomes for medical nutrition intervention. The food for special medical purposes (FSMP) is the regulatory directive involved with the quality/safety and efficacy of medical foods. Another and unique medical area for which medical nutrition is aimed is disease-specific (the so-called disease targeted) medical nutrition. This type of medical nutrition is a unique, effective, therapeutic nutritional intervention for patients with, e.g., a clinical need to avoid certain nutrients due to specific diseases or conditions where normal food intake is harmful. Examples are inborn errors of metabolism such as phenylketonuria (PKU) or severe cow’s milk allergy and childhood epilepsy. Ketogenic therapy during refractory epilepsy can reduce seizures significantly. Other examples for disease-specific medical nutrition are science-driven concepts containing different and uniquely selected nutrients that can act in an orchestra leading to a delay in disease progression. Validated examples have been described for Alzheimer’s, HIV, diabetes, and cancer (111–114). Disease-targeted medical nutrition can be aimed at conditions such as chronic inflammation. These inflammatory conditions are on the rise. This is caused by changes in life-style, food consumption patterns, and aging. Inflammation-associated conditions, such as atherosclerosis, type 1 and type 2 diabetes, obesity, Alzheimer’s disease, and many others, are a growing burden to health budgets. Inflammatory conditions are thought to result from failing mechanisms of immunological tolerance. Of these mechanisms, deficient suppressive activities of a specialized subset of T cells, called regulatory T cells (Tregs), are being recognized as a major factor in the failure of immunological tolerance. A start has been made with the definition of antigen-specific Tregs with a broad anti-inflammatory effect, such as, for example, those that recognize inflammation-associated stress-proteins (115). Herewith, the restoration of this regulation will be a widely sought goal, also for the field of nutrition. A telling example of what may be possible is the following. Wieten et al. have shown that the up-regulation of stress-proteins, such as heat shock protein 70 (HSP70), in the cells lining the gut, leads to the local induction of Tregs (116). Working with a model of chronic and relapsing arthritis, it was found that HSP70 was also induced in Peyer’s patches and the induced HSP70-specific Tregs were having a systemic effect seen to fully control arthritis. This up-regulation was achieved by the oral administration in mice of carvacrol, an essential oil of Oregano species. It showed that our diet may contain effective co-inducers of stress-proteins and that these co-induced proteins can elicit anti-inflammatory activity in the immune system. Similar activities have now been described for other food components (117). Therefore, especially for the diets of the aging individual, substances with anti-inflammatory activities will be an attractive component. In the field of veterinary medicine and food animal production, restrictions are now being imposed on the use of antibiotics, certainly on the use of antibiotics as growth-enhancers. Also here, feed additives are searched with the purpose of controlling inflammation and thereby enhancing weight gain. In combination with drugs, medical devices and lifestyle modification, medical nutrition, and immune system targeted nutraceuticals can play an essential role in health care and precision medicine. Expectedly, it will lead to lower costs of care: fewer complications, shorter hospital stays and reduced mortality, and the reduction of disease manifestations. Over the coming years, Medical Nutrition and Nutraceuticals have the opportunity to be accepted as a bridge between food and traditional pharma approaches – not as isolated therapy but as part of integrated systems-wide health care. Additionally, pharma often is focusing on a monotherapeutic approach (one molecule one target) and medical nutrition will be recognized as the multi-target approach for disease management. Regulation and acceptance depends on national and international guidelines. Changes in regulation for medical nutrition are to be expected since medical nutrition is a relatively new therapeutic area that falls between different regulations and guidelines. For instance, in the USA, under section 5(b) of the Orphan Drug Act [21 U. S. C. 360ee (b)(3)], a medical food is formulated to be consumed or administered enterally under the supervision of a physician and which is intended for the specific dietary management of a disease or condition for which distinctive nutritional requirements, based on recognized scientific principles, are established by medical evaluation. Thus, from a regulatory perspective, medical foods are different than dietary supplements in that claims for medical foods can allude to disease management whereas dietary supplement claims cannot. Medical foods are exempted from the labeling requirements for health claims and nutrient content claims under the Nutrition Labeling and Education Act of 1990. In order to be a medical food, a product must meet the following criteria: to be a food for oral or tube feeding, the product must be labeled for the dietary management of a specific medical disorder, disease, or condition for which there are distinctive nutritional requirements, and the product must be intended to be used under medical supervision. Essentially, medical food comes into play when dietary management cannot be achieved by the modification of the normal diet alone. For instance, medical foods could be used to replete key metabolic components that might be depleted in diabetes or inflammation. Only translational research and randomized, placebo controlled double-blind clinical trials can validate these new concepts. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. 1. Creating a Sustainable Food Future. Available from: http://www.wri.org/sites/default/files/wri13_report_4c_wrr_online.pdf Google Scholar 2. FAO, IFAD, and WFP. The State of Food Insecurity in the World 2014. Strengthening the Enabling Environment for Food Security and Nutrition. Rome (2014). Available from: http://www.fao.org/3/a-i4030e.pdf Google Scholar 3. Garnett T, Appleby MC, Balmford A, Bateman IJ, Benton TG, Bloomer P, et al. Agriculture. Sustainable intensification in agriculture: premises and policies. Science (2013) 341:33–4. doi: 10.1126/science.1234485 CrossRef Full Text | Google Scholar 4. Tillotson JE. America’s obesity: conflicting public policies, industrial economic development, and unintended human consequences. Annu Rev Nutr (2004) 24:617–43. doi:10.1146/annurev.nutr.24.012003.132434 PubMed Abstract | CrossRef Full Text | Google Scholar 5. Agricultural Biodiversity A. Cross-Cutting Initiative on Biodiversity for Food and Nutrition (2006). Available from: https://www.cbd.int/decision/cop/?id=11037 Google Scholar 6. Fourteenth Regular Session of the Commission on Genetic Resources for Food and Agriculture. Rome (2013). Available from: http://www.fao.org/docrep/meeting/028/mg538e.pdf Google Scholar 7. Zhang R. Food security: food trade regime and food aid regime. J Int Econ Law (2004) 7:565–84. doi:10.1093/jiel/7.3.565 CrossRef Full Text | Google Scholar 8. Latham M. The great vitamin A fiasco. World Nutr (2010) 1:12–45. Google Scholar 9. Golden CD, Fernald LCH, Brashares JS, Rasolofoniaina BJR, Kremen C. Benefits of wildlife consumption to child nutrition in a biodiversity hotspot. Proc Natl Acad Sci U S A (2011) 108:19653–6. doi:10.1073/pnas.1112586108 PubMed Abstract | CrossRef Full Text | Google Scholar 10. Foley JA, Defries R, Asner GP, Barford C, Bonan G, Carpenter SR, et al. Global consequences of land use. Science (2005) 309:570–4. doi:10.1126/science.1111772 PubMed Abstract | CrossRef Full Text | Google Scholar 11. Knorr D, editor. Sustainable Food Systems. Westport, CT: AVI Publishing (1983). Google Scholar 12. Wheeler T, von Braun J. Climate change impacts on global food security. Science (2013) 341:508–13. doi:10.1126/science.1239402 PubMed Abstract | CrossRef Full Text | Google Scholar 13. Toledo Á, Burlingame B. Biodiversity and nutrition: a common path toward global food security and sustainable development. J Food Compost Anal (2006) 19:477–83. doi:10.1016/j.jfca.2006.05.001 CrossRef Full Text | Google Scholar 14. Waldron S, Flowers H, Arlaud C, Bryant C, McFarlane S. The significance of organic carbon and nutrient export from peatland-dominated landscapes subject to disturbance, a stoichiometric perspective. Biogeosciences (2009) 6:363–74. doi:10.5194/bg-6-363-2009 CrossRef Full Text | Google Scholar 15. Gustavsson J, Cederberg C, Sonesson U, Meybeck A, van Otterdijk R. Global food losses and food waste. In: Interpack 2011 (Düsseldorf) (2011). Available from: http://www.fao.org/docrep/014/mb060e/mb060e.pdf Google Scholar 16. Godfray HCJ, Beddington JR, Crute IR, Haddad L, Lawrence D, Muir JF, et al. Food security: the challenge of feeding 9 billion people. Science (2010) 327:812–8. doi:10.1126/science.1185383 PubMed Abstract | CrossRef Full Text | Google Scholar 17. Vinceti B, Termote C, Ickowitz A, Powell B, Kehlenbeck K, Hunter D. The contribution of forests and trees to sustainable diets. Sustainability (2013) 5:4797–824. doi:10.3390/su5114797 CrossRef Full Text | Google Scholar 18. Meffe R, de Bustamante I. Emerging organic contaminants in surface water and groundwater: a first overview of the situation in Italy. Sci Total Environ (2014) 481:280–95. doi:10.1016/j.scitotenv.2014.02.053 PubMed Abstract | CrossRef Full Text | Google Scholar 19. Myers GJ, Davidson PW, Strain JJ. Nutrient and methyl mercury exposure from consuming fish. J Nutr (2007) 137:2805–8. PubMed Abstract | Google Scholar 20. Smith A. An Inquiry into the Nature and Causes of the Wealth of Nations. Vol 3, 4th ed. London: W. Strahan and T. Cadell (1786). 206 p. Google Scholar 21. Hawking S, Mlodinow L. The Grand Design. New York: Random House Publishing Group (2010) p. 5. Google Scholar 22. Collins FS, Tabak LA. Policy: NIH plans to enhance reproducibility. Nature (2014) 505:612–3. doi:10.1038/505612a CrossRef Full Text | Google Scholar 23. Schoenfeld JD, Ioannidis JPA. Is everything we eat associated with cancer? A systematic cookbook review. Am J Clin Nutr (2013) 97:127–34. doi:10.3945/ajcn.112.047142 PubMed Abstract | CrossRef Full Text | Google Scholar 24. Cofield SS, Corona RV, Allison DB. Use of causal language in observational studies of obesity and nutrition. Obes Facts (2010) 3:353–6. doi:10.1159/000322940 PubMed Abstract | CrossRef Full Text | Google Scholar 25. Kaiser KA, Cofield SS, Fontaine KR, Glasser SP, Thabane L, Chu R, et al. Is funding source related to study reporting quality in obesity or nutrition randomized control trials in top-tier medical journals? Int J Obes (Lond) (2012) 36:977–81. doi:10.1038/ijo.2011.207 PubMed Abstract | CrossRef Full Text | Google Scholar 26. Casazza K, Allison DB. Stagnation in the clinical, community and public health domain of obesity: the need for probative research. Clin Obes (2012) 2:83–5. doi:10.1111/j.1758-8111.2012.00052.x CrossRef Full Text | Google Scholar 27. Casazza K, Fontaine KR, Astrup A, Birch LL, Brown AW, Bohan Brown MM, et al. Myths, presumptions, and facts about obesity. N Engl J Med (2013) 368:446–54. doi:10.1056/NEJMsa1208051 PubMed Abstract | CrossRef Full Text | Google Scholar 28. Bohan Brown MM, Brown AW, Allison DB. Nutritional epidemiology in practice: learning from data or promulgating beliefs? Am J Clin Nutr (2013) 97:5–6. doi:10.3945/ajcn.112.052472 CrossRef Full Text | Google Scholar 29. PLoS Medicine Editors. Making sense of non-financial competing interests. PLoS Med (2008) 5:e199. doi:10.1371/journal.pmed.0050199 PubMed Abstract | CrossRef Full Text | Google Scholar 30. Nosek BA, Alter G, Banks GC, Borsboom D, Bowman SD, Breckler SJ, et al. Promoting an open research culture. Science (2015) 348:1422–5. doi:10.1126/science.aab2374 CrossRef Full Text | Google Scholar 31. Archer E, Pavela G, Lavie CJ. The inadmissibility of what we eat in America and NHANES dietary data in nutrition and obesity research and the scientific formulation of national dietary guidelines. Mayo Clinic Proceedings (2015) 90(7):911–26. doi:10.1016/j.mayocp.2015.04.009 CrossRef Full Text | Google Scholar 32. Dhurandhar NV, Schoeller D, Brown AW, Heymsfield SB, Thomas D, Sørensen TIA, et al. Energy balance measurement: when something is not better than nothing. Int J Obes (Lond) (2014) 39(7):1109–13. doi:10.1038/ijo.2014.199 PubMed Abstract | CrossRef Full Text | Google Scholar 33. Schoeller DA, Thomas D, Archer E, Heymsfield SB, Blair SN, Goran MI, et al. Self-report-based estimates of energy intake offer an inadequate basis for scientific conclusions. Am J Clin Nutr (2013) 97:1413–5. doi:10.3945/ajcn.113.062125 CrossRef Full Text | Google Scholar 34. Dietary Guidelines Advisory Committee. Scientific Report of the 2015 Dietary Guidelines Advisory Committee (2015). Available from: http://www.health.gov/dietaryguidelines/2015-scientific-report/PDFs/Scientific-Report-of-the-2015-Dietary-Guidelines-Advisory-Committee.pdf Google Scholar 35. Brown AW, Bohan Brown MM, Allison DB. Belief beyond the evidence: using the proposed effect of breakfast on obesity to show 2 practices that distort scientific evidence. Am J Clin Nutr (2013) 98:1298–308. doi:10.3945/ajcn.113.064410 CrossRef Full Text | Google Scholar 36. Brown J, de Vos WM, DiStefano PS, Doré J, Huttenhower C, Knight R, et al. Translating the human microbiome. Nat Biotechnol (2013) 31:304–8. doi:10.1038/nbt.2543 CrossRef Full Text | Google Scholar 37. Mehta T, Allison DB. From measurement to analysis reporting: grand challenges in nutritional methodology. Front Nutr (2014) 1. doi:10.3389/fnut.2014.00006 CrossRef Full Text | Google Scholar 38. Pavela G, Wiener H, Fontaine KR, Fields DA, Voss JD, Allison DB. Packet randomized experiments for eliminating classes of confounders. Eur J Clin Invest (2015) 45(1):45–55. doi:10.1111/eci.12378 PubMed Abstract | CrossRef Full Text | Google Scholar 39. Kussmann M, Van Bladeren PJ. The extended nutrigenomics – understanding the interplay between the genomes of food, gut microbes, and human host. Front Genet (2011) 2:21. doi:10.3389/fgene.2011.00021 PubMed Abstract | CrossRef Full Text | Google Scholar 40. van Ommen B, El-Sohemy A, Hesketh J, Kaput J, Fenech M, Evelo CT, et al. The Micronutrient Genomics Project: a community-driven knowledge base for micronutrient research. Genes Nutr (2010) 5:285–96. doi:10.1007/s12263-010-0192-8 PubMed Abstract | CrossRef Full Text | Google Scholar 41. Kussmann M, Morine MJ, Hager J, Sonderegger B, Kaput J. Perspective: a systems approach to diabetes research. Front Genet (2013) 4:205. doi:10.3389/fgene.2013.00205 PubMed Abstract | CrossRef Full Text | Google Scholar 42. Stumbo PJ, Weiss R, Newman JW, Pennington JA, Tucker KL, Wiesenfeld PL, et al. Web-enabled and improved software tools and data are needed to measure nutrient intakes and physical activity for personalized health research. J Nutr (2010) 140:2104–15. doi:10.3945/jn.110.128371 PubMed Abstract | CrossRef Full Text | Google Scholar 43. Nguyen T-P, Scotti M, Morine MJ, Priami C. Model-based clustering reveals vitamin D dependent multi-centrality hubs in a network of vitamin-related proteins. BMC Syst Biol (2011) 5:195. doi:10.1186/1752-0509-5-195 PubMed Abstract | CrossRef Full Text | Google Scholar 44. Kussmann M, Fay LB. Nutrigenomics and personalized nutrition: science and concept. Per Med (2008) 5:447–55. doi:10.2217/17410541.5.5.447 CrossRef Full Text | Google Scholar 45. Viladomiu M, Hontecillas R, Yuan L, Lu P, Bassaganya-Riera J. Nutritional protective mechanisms against gut inflammation. J Nutr Biochem (2013) 24:929–39. doi:10.1016/j.jnutbio.2013.01.006 PubMed Abstract | CrossRef Full Text | Google Scholar 46. Carbo A, Bassaganya-Riera J, Pedragosa M, Viladomiu M, Marathe M, Eubank S, et al. Predictive computational modeling of the mucosal immune responses during Helicobacter pylori infection. PLoS One (2013) 8:e73365. doi:10.1371/journal.pone.0073365 PubMed Abstract | CrossRef Full Text | Google Scholar 47. Carbo A, Hontecillas R, Kronsteiner B, Viladomiu M, Pedragosa M, Lu P, et al. Systems modeling of molecular mechanisms controlling cytokine-driven CD4+ T cell differentiation and phenotype plasticity. PLoS Comput Biol (2013) 9:e1003027. doi:10.1371/journal.pcbi.1003027 PubMed Abstract | CrossRef Full Text | Google Scholar 48. Carbo A, Olivares-Villagómez D, Hontecillas R, Bassaganya-Riera J, Chaturvedi R, Piazuelo MB, et al. Systems modeling of the role of interleukin-21 in the maintenance of effector CD4+ T cell responses during chronic Helicobacter pylori infection. MBio (2014) 5:e1243–1214. doi:10.1128/mBio.01243-14 PubMed Abstract | CrossRef Full Text | Google Scholar 49. Mei Y, Abedi V, Carbo A, Zhang X, Lu P, Philipson C, et al. Multiscale modeling of mucosal immune responses. BMC Bioinformatics (2015) 16(Suppl 12). Google Scholar 50. Leber A, Viladomiu M, Hontecillas R, Abedi V, Philipson C, Hoops S, et al. Systems modeling of interactions between mucosal immunity and the gut microbiome during clostridium difficile infection. PLoS One (2015) 10:e0134849. doi:10.1371/journal.pone.0134849 PubMed Abstract | CrossRef Full Text | Google Scholar 51. Mc Auley MT, Proctor CJ, Corfe BM, Cuskelly GC, Mooney KM. Nutrition research and the impact of computational systems biology. J Comput Sci Syst Biol (2013) 6:271–85. doi:10.4172/jcsb.1000122 CrossRef Full Text | Google Scholar 52. Laney D. 3D Data Management: Controlling Data Volume, Velocity, and Variety. Application Delivery Strategies. Stamford, CT: META Group Inc. (2001). Google Scholar 53. Einav L, Levin J. Economics in the age of big data. Science (2014) 346:1243089. doi:10.1126/science.1243089 PubMed Abstract | CrossRef Full Text | Google Scholar 54. Wallace PJ, Shah ND, Dennen T, Bleicher PA, Bleicher PD, Crown WH. Optum labs: building a novel node in the learning health care system. Health Aff (Millwood) (2014) 33:1187–94. doi:10.1377/hlthaff.2014.0038 PubMed Abstract | CrossRef Full Text | Google Scholar 55. Schneeweiss S, Rassen JA, Glynn RJ, Avorn J, Mogun H, Brookhart MA. High-dimensional propensity score adjustment in studies of treatment effects using health care claims data. Epidemiology (2009) 20:512–22. doi:10.1097/EDE.0b013e3181a663cc PubMed Abstract | CrossRef Full Text | Google Scholar 56. Rosenbaum PR. Using Differential Comparisons in Observational Studies (2013). Available from: http://amstat.tandfonline.com/doi/abs/10.1080/09332480.2013.845002 (accessed May 23, 2015). Google Scholar 57. Peters J, Bühlmann P, Meinshausen N. Causal Inference Using Invariant Prediction: Identification and Confidence Intervals (2015). Available from: http://arxiv.org/abs/1501.01332 (accessed May 23, 2015). Google Scholar 58. Bühlmann P, Peters J, Ernest J. CAM: causal additive models, high-dimensional order search and penalized regression. Ann Stat (2014) 42:2526–56. doi:10.1214/14-AOS1260 CrossRef Full Text | Google Scholar 59. Roullier-Gall C, Witting M, Gougeon RD, Schmitt-Kopplin P. High precision mass measurements for wine metabolomics. Front Chem (2014) 2:102. doi:10.3389/fchem.2014.00102 PubMed Abstract | CrossRef Full Text | Google Scholar 60. Leeman WR, Krul L, Houben GF. Complex mixtures: relevance of combined exposure to substances at low dose levels. Food Chem Toxicol (2013) 58:141–8. doi:10.1016/j.fct.2013.03.050 PubMed Abstract | CrossRef Full Text | Google Scholar 61. Meule A, Vögele C. The psychology of eating. Front Psychol (2013) 4:215. doi:10.3389/fpsyg.2013.00215 CrossRef Full Text | Google Scholar 62. Moubarac J-C, Batal M, Martins APB, Claro R, Levy RB, Cannon G, et al. Processed and ultra-processed food products: consumption trends in Canada from 1938 to 2011. Can J Diet Pract Res (2014) 75:15–21. doi:10.3148/75.1.2014.15 PubMed Abstract | CrossRef Full Text | Google Scholar 63. Poti JM, Mendez MA, Ng SW, Popkin BM. Is the degree of food processing and convenience linked with the nutritional quality of foods purchased by US households? Am J Clin Nutr (2015) 101:1251–62. doi:10.3945/ajcn.114.100925 PubMed Abstract | CrossRef Full Text | Google Scholar 64. Davis C. Evolutionary and neuropsychological perspectives on addictive behaviors and addictive substances: relevance to the “food addiction” construct. Subst Abuse Rehabil (2014) 5:129–37. doi:10.2147/SAR.S56835 PubMed Abstract | CrossRef Full Text | Google Scholar 65. Gearhardt AN, Davis C, Kuschner R, Brownell KD. The addiction potential of hyperpalatable foods. Curr Drug Abuse Rev (2011) 4:140–5. doi:10.2174/1874473711104030140 PubMed Abstract | CrossRef Full Text | Google Scholar 66. Davis C. From passive overeating to “food addiction”: a spectrum of compulsion and severity. ISRN Obes (2013) 2013:435027. doi:10.1155/2013/435027 PubMed Abstract | CrossRef Full Text | Google Scholar 67. Avena NM, Gold MS. Food and addiction – sugars, fats and hedonic overeating. Addiction (2011) 106:1214–5. doi:10.1111/j.1360-0443.2011.03373.x CrossRef Full Text | Google Scholar 68. Ahmed SH, Guillem K, Vandaele Y. Sugar addiction: pushing the drug-sugar analogy to the limit. Curr Opin Clin Nutr Metab Care (2013) 16:434–9. doi:10.1097/MCO.0b013e328361c8b8 PubMed Abstract | CrossRef Full Text | Google Scholar 69. Davis C, Carter JC. Compulsive overeating as an addiction disorder. A review of theory and evidence. Appetite (2009) 53:1–8. doi:10.1016/j.appet.2009.05.018 PubMed Abstract | CrossRef Full Text | Google Scholar 70. Davis C, Carter JC. If certain foods are addictive, how might this change the treatment of compulsive overeating and obesity? Curr Addict Rep (2014) 1:89–95. doi:10.1007/s40429-014-0013-z CrossRef Full Text | Google Scholar 71. Krashes MJ, Kravitz AV. Optogenetic and chemogenetic insights into the food addiction hypothesis. Front Behav Neurosci (2014) 8:57. doi:10.3389/fnbeh.2014.00057 PubMed Abstract | CrossRef Full Text | Google Scholar 72. Meule A, Gearhardt AN. Five years of the Yale Food Addiction Scale: taking stock and moving forward. Curr Addict Rep (2014) 1:193–205. doi:10.1007/s40429-014-0021-z CrossRef Full Text | Google Scholar 73. Meule A, Gearhardt AN. Food addiction in the light of DSM-5. Nutrients (2014) 6:3653–71. doi:10.3390/nu6093653 PubMed Abstract | CrossRef Full Text | Google Scholar 74. Rogers PJ. Obesity – is food addiction to blame? Addiction (2011) 106:1213–4. doi:10.1111/j.1360-0443.2011.03371.x CrossRef Full Text | Google Scholar 75. Benton D. The plausibility of sugar addiction and its role in obesity and eating disorders. Clin Nutr (2010) 29:288–303. doi:10.1016/j.clnu.2009.12.001 PubMed Abstract | CrossRef Full Text | Google Scholar 76. Wilson GT. Eating disorders, obesity and addiction. Eur Eat Disord Rev (2010) 18:341–51. doi:10.1002/erv.1048 PubMed Abstract | CrossRef Full Text | Google Scholar 77. Ziauddeen H, Farooqi IS, Fletcher PC. Obesity and the brain: how convincing is the addiction model? Nat Rev Neurosci (2012) 13:279–86. doi:10.1038/nrn3212 PubMed Abstract | CrossRef Full Text | Google Scholar 78. Ziauddeen H, Fletcher PC. Is food addiction a valid and useful concept? Obes Rev (2013) 14:19–28. doi:10.1111/j.1467-789X.2012.01046.x PubMed Abstract | CrossRef Full Text | Google Scholar 79. Hill JO, Berridge K, Avena NM, Ziauddeen H, Alonso-Alonso M, Allison DB, et al. Neurocognition: the food-brain connection. Adv Nutr (2014) 5:544–6. doi:10.3945/an.114.006437 PubMed Abstract | CrossRef Full Text | Google Scholar 80. Salamone JD, Correa M. Dopamine and food addiction: lexicon badly needed. Biol Psychiatry (2013) 73:e15–24. doi:10.1016/j.biopsych.2012.09.027 PubMed Abstract | CrossRef Full Text | Google Scholar 81. Gearhardt AN, Corbin WR, Brownell KD. Food addiction: an examination of the diagnostic criteria for dependence. J Addict Med (2009) 3:1–7. doi:10.1097/ADM.0b013e318193c993 PubMed Abstract | CrossRef Full Text | Google Scholar 82. Gearhardt AN, Brownell KD. Can food and addiction change the game? Biol Psychiatry (2013) 73:802–3. doi:10.1016/j.biopsych.2012.07.024 CrossRef Full Text | Google Scholar 83. DePierre JA, Puhl RM, Luedicke J. A new stigmatized identity? Comparisons of a “food addict” label with other stigmatized health conditions. Basic Appl Soc Psych (2013) 35:10–21. doi:10.1080/01973533.2012.746148 CrossRef Full Text | Google Scholar 84. Latner JD, Puhl RM, Murakami JM, O’Brien KS. Food addiction as a causal model of obesity. Effects on stigma, blame, and perceived psychopathology. Appetite (2014) 77:77–82. doi:10.1016/j.appet.2014.03.004 PubMed Abstract | CrossRef Full Text | Google Scholar 85. Lee NM, Hall WD, Lucke J, Forlini C, Carter A. Food addiction and its impact on weight-based stigma and the treatment of obese individuals in the U.S. and Australia. Nutrients (2014) 6:5312–26. doi:10.3390/nu6115312 PubMed Abstract | CrossRef Full Text | Google Scholar 86. Avena NM. The study of food addiction using animal models of binge eating. Appetite (2010) 55:734–7. doi:10.1016/j.appet.2010.09.010 PubMed Abstract | CrossRef Full Text | Google Scholar 87. Schulte EM, Avena NM, Gearhardt AN. Which foods may be addictive? The roles of processing, fat content, and glycemic load. PLoS One (2015) 10:e0117959. doi:10.1371/journal.pone.0117959 PubMed Abstract | CrossRef Full Text | Google Scholar 88. Hebebrand J, Albayrak Ö, Adan R, Antel J, Dieguez C, de Jong J, et al. “Eating addiction”, rather than “food addiction”, better captures addictive-like eating behavior. Neurosci Biobehav Rev (2014) 47:295–306. doi:10.1016/j.neubiorev.2014.08.016 PubMed Abstract | CrossRef Full Text | Google Scholar 89. Wimo A, Prince, M. World Alzheimer Report 2010 (2010). Available from: http://www.alz.co.uk/research/files/WorldAlzheimerReport.pdf Google Scholar 90. Ohla K, Toepel U, le Coutre J, Hudry J. Visual-gustatory interaction: orbitofrontal and insular cortices mediate the effect of high-calorie visual food cues on taste pleasantness. PLoS One (2012) 7:e32434. doi:10.1371/journal.pone.0032434 PubMed Abstract | CrossRef Full Text | Google Scholar 91. Crouzet SM, Busch NA, Ohla K. Taste quality decoding parallels taste sensations. Curr Biol (2015) 25:890–6. doi:10.1016/j.cub.2015.01.057 PubMed Abstract | CrossRef Full Text | Google Scholar 92. Deoni SCL, Dean DC, Piryatinsky I, O’Muircheartaigh J, Waskiewicz N, Lehman K, et al. Breastfeeding and early white matter development: a cross-sectional study. Neuroimage (2013) 82:77–86. doi:10.1016/j.neuroimage.2013.05.090 PubMed Abstract | CrossRef Full Text | Google Scholar 93. Blundell J. Making claims: functional foods for managing appetite and weight. Nat Rev Endocrinol (2010) 6:53–6. doi:10.1038/nrendo.2009.224 PubMed Abstract | CrossRef Full Text | Google Scholar 94. Mercer JG, Johnstone AM, Halford JCG. Approaches to influencing food choice across the age groups: from children to the elderly. Proc Nutr Soc (2015) 74(2):1–9. doi:10.1017/S0029665114001712 PubMed Abstract | CrossRef Full Text | Google Scholar 95. Halford JCG, Harrold JA. Satiety-enhancing products for appetite control: science and regulation of functional foods for weight management. Proc Nutr Soc (2012) 71:350–62. doi:10.1017/S0029665112000134 PubMed Abstract | CrossRef Full Text | Google Scholar 96. Skibicka KP, Dickson SL. Enteroendocrine hormones – central effects on behavior. Curr Opin Pharmacol (2013) 13:977–82. doi:10.1016/j.coph.2013.09.004 PubMed Abstract | CrossRef Full Text | Google Scholar 97. Egecioglu E, Skibicka KP, Hansson C, Alvarez-Crespo M, Friberg PA, Jerlhag E, et al. Hedonic and incentive signals for body weight control. Rev Endocr Metab Disord (2011) 12:141–51. doi:10.1007/s11154-011-9166-4 PubMed Abstract | CrossRef Full Text | Google Scholar 98. Gearhardt AN, Corbin WR, Brownell KD. Preliminary validation of the Yale Food Addiction Scale. Appetite (2009) 52:430–6. doi:10.1016/j.appet.2008.12.003 CrossRef Full Text | Google Scholar 99. Iozzo P, Guiducci L, Guzzardi MA, Pagotto U. Brain PET imaging in obesity and food addiction: current evidence and hypothesis. Obes Facts (2012) 5:155–64. doi:10.1159/000338328 PubMed Abstract | CrossRef Full Text | Google Scholar 100. Human Microbiome Project Consortium. A framework for human microbiome research. Nature (2012) 486:215–21. doi:10.1038/nature11209 PubMed Abstract | CrossRef Full Text | Google Scholar 101. Human Microbiome Project Consortium. Structure, function and diversity of the healthy human microbiome. Nature (2012) 486:207–14. doi:10.1038/nature11234 PubMed Abstract | CrossRef Full Text | Google Scholar 102. Ding T, Schloss PD. Dynamics and associations of microbial community types across the human body. Nature (2014) 509:357–60. doi:10.1038/nature13178 PubMed Abstract | CrossRef Full Text | Google Scholar 103. Knorr D, Sinskey AJ. Biotechnology in food production and processing. Science (1985) 229:1224–9. doi:10.1126/science.229.4719.1224 CrossRef Full Text | Google Scholar 104. Metchnikoff E. The Prolongation of Life: Optimistic Studies. New York, London: G.P. Putnam’s Sons (1908). Google Scholar 105. Chung D. It’s a jungle in there. New Sci (2004) 182:42–5. Google Scholar 106. Claesson MJ, Jeffery IB, Conde S, Power SE, O’Connor EM, Cusack S, et al. Gut microbiota composition correlates with diet and health in the elderly. Nature (2012) 488:178–84. doi:10.1038/nature11319 PubMed Abstract | CrossRef Full Text | Google Scholar 107. Salonen A, Lahti L, Salojärvi J, Holtrop G, Korpela K, Duncan SH, et al. Impact of diet and individual variation on intestinal microbiota composition and fermentation products in obese men. ISME J (2014) 8:2218–30. doi:10.1038/ismej.2014.63 PubMed Abstract | CrossRef Full Text | Google Scholar 108. Ananta E, Birkeland S-E, Corcoran B, Fitzgerald G, Hinz S, Klijn A, et al. Processing effects on the nutritional advancement of probiotics and prebiotics. Microb Ecol Health Dis (2004) 16:114–24. doi:10.3402/mehd.v16i2-3.7933 CrossRef Full Text | Google Scholar 109. Volkert M, Ananta E, Luscher C, Knorr D. Effect of air freezing, spray freezing, and pressure shift freezing on membrane integrity and viability of Lactobacillus rhamnosus GG. J Food Eng (2008) 87:532–40. doi:10.1016/j.jfoodeng.2008.01.008 CrossRef Full Text | Google Scholar 110. Georgiou NA, Garssen J, Witkamp RF. Pharma-nutrition interface: the gap is narrowing. Eur J Pharmacol (2011) 651:1–8. doi:10.1016/j.ejphar.2010.11.007 PubMed Abstract | CrossRef Full Text | Google Scholar 111. Gori A, Rizzardini G, Van’t Land B, Amor KB, van Schaik J, Torti C, et al. Specific prebiotics modulate gut microbiota and immune activation in HAART-naive HIV-infected adults: results of the “COPA” pilot randomized trial. Mucosal Immunol (2011) 4:554–63. doi:10.1038/mi.2011.15 PubMed Abstract | CrossRef Full Text | Google Scholar 112. Cahn P, Ruxrungtham K, Gazzard B, Diaz RS, Gori A, Kotler DP, et al. The immunomodulatory nutritional intervention NR100157 reduced CD4+ T-cell decline and immune activation: a 1-year multicenter randomized controlled double-blind trial in HIV-infected persons not receiving antiretroviral therapy (The BITE Study). Clin Infect Dis (2013) 57:139–46. doi:10.1093/cid/cit171 PubMed Abstract | CrossRef Full Text | Google Scholar 113. Scheltens P, Twisk JWR, Blesa R, Scarpini E, von Arnim CAF, Bongers A, et al. Efficacy of Souvenaid in mild Alzheimer’s disease: results from a randomized, controlled trial. J Alzheimers Dis (2012) 31:225–36. doi:10.3233/JAD-2012-121189 PubMed Abstract | CrossRef Full Text | Google Scholar 114. Faber J, Berkhout M, Fiedler U, Avlar M, Witteman BJ, Vos AP, et al. Rapid EPA and DHA incorporation and reduced PGE2 levels after one week intervention with a medical food in cancer patients receiving radiotherapy, a randomized trial. Clin Nutr (2013) 32:338–45. doi:10.1016/j.clnu.2012.09.009 PubMed Abstract | CrossRef Full Text | Google Scholar 115. van Herwijnen MJC, Wieten L, van der Zee R, van Kooten PJ, Wagenaar-Hilbers JP, Hoek A, et al. Regulatory T cells that recognize a ubiquitous stress-inducible self-antigen are long-lived suppressors of autoimmune arthritis. Proc Natl Acad Sci U S A (2012) 109:14134–9. doi:10.1073/pnas.1206803109 PubMed Abstract | CrossRef Full Text | Google Scholar 116. Wieten L, van der Zee R, Spiering R, Wagenaar-Hilbers J, van Kooten P, Broere F, et al. A novel heat-shock protein coinducer boosts stress protein Hsp70 to activate T cell regulation of inflammation in autoimmune arthritis. Arthritis Rheum (2010) 62:1026–35. doi:10.1002/art.27344 PubMed Abstract | CrossRef Full Text | Google Scholar 117. Wieten L, van der Zee R, Goedemans R, Sijtsma J, Serafini M, Lubsen NH, et al. Hsp70 expression and induction as a readout for detection of immune modulatory components in food. Cell Stress Chaperones (2010) 15:25–37. doi:10.1007/s12192-009-0119-8 PubMed Abstract | CrossRef Full Text | Google Scholar 118. Levitsky DA, Brown AW, Hansen BC, Atkinson RL, Byrne N, Cheskin LJ, et al. An unjustified conclusion from self-report-based estimates of energy intake. Am J Med (2014) 127:e33. doi:10.1016/j.amjmed.2014.08.029 CrossRef Full Text | Google Scholar 119. Schoeller D, Archer E, Dawson JA, Heymsfield S. Implausible results from the use of invalid methods. J Nutr (2015) 145:150. doi:10.3945/jn.114.199521 CrossRef Full Text | Google Scholar 120. Keith SW, Stommel M, Allison DB, Schoenborn CA. Self-report corrections for BMI: comment on Keith et al. Int J Obes (Lond) (2012) 36:1591. doi:10.1038/ijo.2011.277 CrossRef Full Text | Google Scholar 121. Le A, Judd SE, Allison DB, Oza-Frank R, Affuso O, Safford MM, et al. The geographic distribution of obesity in the US and the potential regional differences in misreporting of obesity. Obesity (Silver Spring) (2014) 22:300–6. doi:10.1002/oby.20451 PubMed Abstract | CrossRef Full Text | Google Scholar 122. Keith SW, Fontaine KR, Pajewski NM, Mehta T, Allison DB. Use of self-reported height and weight biases the body mass index-mortality association. Int J Obes (Lond) (2011) 35:401–8. doi:10.1038/ijo.2010.148 PubMed Abstract | CrossRef Full Text | Google Scholar 123. Tarro L, Llauradó E, Albaladejo R, Moriña D, Arija V, Solà R, et al. A primary-school-based study to reduce the prevalence of childhood obesity – the EdAl (Educació en Alimentació) study: a randomized controlled trial. Trials (2014) 15:58. doi:10.1186/1745-6215-15-58 PubMed Abstract | CrossRef Full Text | Google Scholar 124. Barr SB, Wright JC. Postprandial energy expenditure in whole-food and processed-food meals: implications for daily energy expenditure. Food Nutr Res (2010) 54:5144. doi:10.3402/fnr.v54i0.5144 PubMed Abstract | CrossRef Full Text | Google Scholar 125. Williams LK, Abbott G, Thornton LE, Worsley A, Ball K, Crawford D. Improving perceptions of healthy food affordability: results from a pilot intervention. Int J Behav Nutr Phys Act (2014) 11:33. doi:10.1186/1479-5868-11-33 PubMed Abstract | CrossRef Full Text | Google Scholar 126. Siontis GCM, Tzoulaki I, Castaldi PJ, Ioannidis JPA. External validation of new risk prediction models is infrequent and reveals worse prognostic discrimination. J Clin Epidemiol (2015) 68:25–34. doi:10.1016/j.jclinepi.2014.09.007 PubMed Abstract | CrossRef Full Text | Google Scholar 127. Cassani RSL, Fassini PG, Silvah JH, Lima CM, Marchini JS. Impact of weight loss diet associated with flaxseed on inflammatory markers in men with cardiovascular risk factors: a clinical study. Nutr J (2015) 14:5. doi:10.1186/1475-2891-14-5 PubMed Abstract | CrossRef Full Text | Google Scholar 128. Bland JM, Altman DG. Comparisons against baseline within randomised groups are often used and can be highly misleading. Trials (2011) 12:264. doi:10.1186/1745-6215-12-264 PubMed Abstract | CrossRef Full Text | Google Scholar 129. Weerts SE, Amoran A. Pass the fruits and vegetables! A community – university – industry partnership promotes weight loss in African American women. Health Promot Pract (2009) 12:252–60. doi:10.1177/1524839908330810 PubMed Abstract | CrossRef Full Text | Google Scholar 130. Kaiser KA, Affuso O, Beasley TM, Allison DB. Getting carried away: a note showing baseline observation carried forward (BOCF) results can be calculated from published complete-cases results. Int J Obes (2011) 36:886–9. doi:10.1038/ijo.2011.25 PubMed Abstract | CrossRef Full Text | Google Scholar 131. Elobeid MA, Padilla MA, McVie T, Thomas O, Brock DW, Musser B, et al. Missing data in randomized clinical trials for weight loss: scope of the problem, state of the field, and performance of statistical methods. PLoS One (2009) 4:e6624. doi:10.1371/journal.pone.0006624 PubMed Abstract | CrossRef Full Text | Google Scholar 132. Li P, Brown A, Oakes JM, Allison D. Comment on “Intervention effects of a school-based health promotion programme on obesity related behavioural outcomes”. J Obes (2015). doi:10.1155/2015/708181 CrossRef Full Text | Google Scholar 133. Li P, Brown A, Oakes JM, Allison D. School-based obesity prevention Intervention in Chilean children: effective in controlling, but not reducing obesity. J Obes (2015). doi:10.1155/2015/183528 CrossRef Full Text | Google Scholar 134. Grydeland M, Bjelland M, Anderssen SA, Klepp K-I, Bergh IH, Andersen LF, et al. Effects of a 20-month cluster randomised controlled school-based intervention trial on BMI of school-aged boys and girls: the HEIA study. Br J Sports Med (2014) 48:768–73. doi:10.1136/bjsports-2013-092284 PubMed Abstract | CrossRef Full Text | Google Scholar 135. Bere E, Klepp K-I, Øverby N. Free school fruit: can an extra piece of fruit every school day contribute to the prevention of future weight gain? A cluster randomized trial. Food Nutr Res (2014) 58:23194. doi:10.3402/fnr.v58.23194 PubMed Abstract | CrossRef Full Text | Google Scholar 136. Brown AW, Li PB, Bohan Brown MM, Kaiser KA, Keith SW, Oakes JM, et al. Best (but oft forgotten) practices: designing, analyzing, and reporting cluster randomized controlled trials. Am J Clin Nutr (2015) 102:1–8. doi:10.3945/ajcn.114.105072 PubMed Abstract | CrossRef Full Text | Google Scholar 137. Lewis DW, Fields DA, Allison DB. Inconsistencies and inaccuracies in reporting on choice of endpoints and of statistical results in RCT of maternal diet. Pediatr Obes (2015). doi:10.1111/ijpo.12030 CrossRef Full Text | Google Scholar 138. Su C-X, Han M, Ren J, Li W-Y, Yue S-J, Hao Y-F, et al. Empirical evidence for outcome reporting bias in randomized clinical trials of acupuncture: comparison of registered records and subsequent publications. Trials (2015) 16:28. doi:10.1186/s13063-014-0545-5 PubMed Abstract | CrossRef Full Text | Google Scholar 139. Simonsohn U, Nelson LD, Simmons JP. P-curve: a key to the file-drawer. J Exp Psychol Gen (2014) 143:534–47. doi:10.1037/a0033242 PubMed Abstract | CrossRef Full Text | Google Scholar 140. Simmons JP, Nelson LD, Simonsohn U. False-positive psychology: undisclosed flexibility in data collection and analysis allows presenting anything as significant. Psychol Sci (2011) 22:1359–66. doi:10.1177/0956797611417632 PubMed Abstract | CrossRef Full Text | Google Scholar 141. Gadbury GL, Allison DB. Inappropriate fiddling with statistical analyses to obtain a desirable p-value: tests to detect its presence in published literature. PLoS One (2012) 7:e46363. doi:10.1371/journal.pone.0046363 PubMed Abstract | CrossRef Full Text | Google Scholar 142. Hernández-Cordero S, Barquera S, Rodríguez-Ramírez S, Villanueva-Borbolla MA, González de Cossio T, Dommarco JR, et al. Substituting water for sugar-sweetened beverages reduces circulating triglycerides and the prevalence of metabolic syndrome in obese but not in overweight Mexican women in a randomized controlled trial. J Nutr (2014) 144:1742–52. doi:10.3945/jn.114.193490 PubMed Abstract | CrossRef Full Text | Google Scholar 143. Brown AW, Sievenpiper JL, Kyle TA, Kaiser KA. Communication of randomized controlled trial results must match the study focus. J Nutr (2015) 145:1027–9. doi:10.3945/jn.114.207282 CrossRef Full Text | Google Scholar 144. Katz TJ. Propagation of errors in review articles. Science (2006) 313:1236. doi:10.1126/science.313.5791.1236a CrossRef Full Text | Google Scholar 145. Cope MB, Allison DB. Critical review of the World Health Organization’s (WHO) 2007 report on “evidence of the long-term effects of breastfeeding: systematic reviews and meta-analysis” with respect to obesity. Obes Rev (2008) 9:594–605. doi:10.1111/j.1467-789X.2008.00504.x PubMed Abstract | CrossRef Full Text | Google Scholar 146. Allison DB, Faith MS, Gorman BS. Publication bias in obesity treatment trials? Int J Obes Relat Metab Disord (1996) 20:931–7. PubMed Abstract | Google Scholar 147. Boutron I, Dutton S, Ravaud P, Altman DG. Reporting and interpretation of randomized controlled trials with statistically nonsignificant results for primary outcomes. JAMA (2010) 303:2058–64. doi:10.1001/jama.2010.651 PubMed Abstract | CrossRef Full Text | Google Scholar 148. Yavchitz A, Boutron I, Bafeta A, Marroun I, Charles P, Mantz J, et al. Misrepresentation of randomized controlled trials in press releases and news coverage: a cohort study. PLoS Med (2012) 9:e1001308. doi:10.1371/journal.pmed.1001308 PubMed Abstract | CrossRef Full Text | Google Scholar 149. Brown AW, Hall KD, Thomas D, Dhurandhar NV, Heymsfield SB, Allison DB. Order of magnitude misestimation of weight effects of children’s meal policy proposals. Child Obes (2014) 10:542–4. doi:10.1089/chi.2014.0081 CrossRef Full Text | Google Scholar 150. Bohan Brown MM, Brown AW, Allison DB. Linear extrapolation results in erroneous overestimation of plausible stressor-related yearly weight changes. Biol Psychiatry (2014) 78(4):e10–1. doi:10.1016/j.biopsych.2014.10.028 CrossRef Full Text | Google Scholar Keywords: nutrition, food, sustainable development, big data analysis, food safety, behavior, brain health, human microbiome Citation: Allison DB, Bassaganya-Riera J, Burlingame B, Brown AW, le Coutre J, Dickson SL, van Eden W, Garssen J, Hontecillas R, Khoo CSH, Knorr D, Kussmann M, Magistretti PJ, Mehta T, Meule A, Rychlik M and Vögele C (2015) Goals in nutrition science 2015–2020. Front. Nutr. 2:26. doi: 10.3389/fnut.2015.00026 Received: 26 May 2015; Accepted: 14 August 2015; Published: 08 September 2015 Edited by: Reviewed by: Copyright: © 2015 Allison, Bassaganya-Riera, Burlingame, Brown, le Coutre, Dickson, van Eden, Garssen, Hontecillas, Khoo, Knorr, Kussmann, Magistretti, Mehta, Meule, Rychlik and Vögele. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. *Correspondence: Johannes le Coutre, [email protected], [email protected]
Corrigendum
, Daniel Francis, Rômulo S. Dezonne, Ana P. B. De Araújo, Lays Souza, Carolina A. Moraes,
Frontiers in Cellular Neuroscience, Volume 9; https://doi.org/10.3389/fncel.2015.00232

Abstract:
A Corrigendum on TGF-β1 promotes cerebral cortex radial glia-astrocyte differentiation in vivoby Stipursky, J., Francis, D., Dezonne, R. S., Bérgamo de Araújo, A. P., Souza, L., Moraes, C. A., et al. (2014). Front Cell Neurosci. 8:393. doi: 10.3389/fncel.2014.00393 The last author Flavia Carvalho Alcantara Gomes appears with the incorrect citation name in this article (Stipursky et al., 2014). The correct citation name for this author is Gomes FC. Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ), Conselho Nacional para o Desenvolvimento Científico e Tecnológico (CNPq), and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES). The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Stipursky, J., Francis, D., Dezonne, R. S., Bérgamo de Araújo, A. P., Souza, L., Moraes, C. A., et al. (2014). TGF-β1 promotes cerebral cortex radial glia-astrocyte differentiation in vivo. Front Cell Neurosci. 8:393. doi: 10.3389/fncel.2014.00393 PubMed Abstract | CrossRef Full Text | Google Scholar Keywords: radial glia, TGF-β, gliogenesis, neurogenesis, cerebral cortex Citation: Stipursky J, Francis D, Dezonne RS, de Araújo APB, Souza L, Moraes CA and Gomes FCA (2015) Corrigendum: TGF-β1 promotes cerebral cortex radial glia-astrocyte differentiation in vivo. Front. Cell. Neurosci. 9:232. doi: 10.3389/fncel.2015.00232 Received: 22 April 2015; Accepted: 26 May 2015; Published: 18 June 2015. Edited by: Copyright © 2015 Stipursky, Francis, Dezonne, de Araújo, Souza, Moraes and Gomes. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. *Correspondence: Joice Stipursky, [email protected]; Flávia C. A. Gomes, [email protected]
Frontiers in Cellular Neuroscience, Volume 8; https://doi.org/10.3389/fncel.2014.00085

Abstract:
Under natural motor control, repetitive firing of motoneurons is transmitted by their motor axons to muscle fibers in the “one to one” fashion that allows the analysis of human motoneuron firing via recordings of motor unit (MU) action potentials (see Kernell, 2006; Heckman and Enoka, 2012). However, when axons are diseased or damaged, local increasing axonal excitability may result in disturbing this basic principle and creating an additional focus of excitation in an axon itself, leading to different symptoms, including MU spontaneous discharges. In order to gain an insight into possible pathophysiological mechanisms underlying changes in axonal excitability, many studies were addressed exploring axonal excitability properties in healthy humans and their fundamental characteristics have been obtained (reviewed by Bostock et al., 1998; Burke et al., 2001; Nodera and Kaji, 2006). In particular, axonal activation has been found to be followed by certain excitability recovery cycle as tested commonly after a supramaximal conditioning stimulus (e.g., Kiernan et al., 1996; Bostock et al., 1998; Murray and Jankelowitz, 2011) or after the cessation of maximal voluntary muscle contractions (Vagg et al., 1998; Kuwabara et al., 2001; Rossi et al., 2012). Traditionally, axon excitability properties were explored for whole motoneuronal pool, using a compound muscle action potential (CMAP), without analysing the behavior of single MUs. However, such approach gives no information on the excitability properties of motor axons belonging to different types of MUs. A few reports, beginning with the seminal studies of Bergmans (1970, 1973), addressed the excitability properties of single motor axons, as a rule, low-threshold to electrical stimulation and thus belonging to large MUs, high-threshold to voluntary muscle contraction (Borg, 1980; Bostock and Baker, 1988; Shefner et al., 1996; Hales et al., 2004; Bostock et al., 2005). At the same time there are no data on the excitability properties of axons belonging to small, slow MUs during their natural activation, while these MUs are essential part of motoneuronal pools as they are primarily activated during both voluntary movements and the maintenance of posture, as well as at reflex activation. The question arises of whether or not the excitability properties of these axons are similar to that of MUs with high-threshold to voluntary muscle contraction. Our findings reported below give some possibility to start the discussion of this question. Experiments were carried out on four healthy human volunteers, aged 46–62 years. The tibialis anterior (TA), flexor carpi ulnaris (FCU), and abductor pollicis brevis (APB) were investigated. The subject recruited a few MUs of a muscle under study by weak voluntary contraction and kept steady MU firing. It is commonly accepted that in normal motor behavior, MUs are typically used such that the most easily recruited, small MUs are the slowest ones (“size principle” of Henneman; for review see Henneman and Mendell, 1981; Kernell et al., 1999; Kernell, 2006). In our experiments, during gentle voluntary contraction the slowest MUs tend to be recruited. The potentials of single MUs were recorded using a bipolar needle electrode and stored on the magnetic tape for off-line analysis. Action potentials of each MU were identified on the basis of their amplitude and waveform shape. The results of the computer identification were verified by an experienced operator. Only the recordings of steady firing MUs with 100% proper identification were accepted for further analysis. While the subject maintained muscle contraction, single (random in relation to MU background firing), low-intensity stimuli of 0.5–1.0 ms duration, at interstimulus interval of 1–5 s were applied through bipolar surface electrode to the following mixed nerves: common peroneal, ulnaris, or median nerve during TA, FCU, or APB studies, respectively. In response to weak stimulation of mixed nerve, low-threshold to voluntary contraction MUs commonly fire at the H-reflex latency. Their thin motor axons are normally high-threshold to electric stimulation and their selective activation is rather a challenge. However, in the majority of our experiments, we were successful in evoking M-response in some of the slow MUs, under conditions of a thorough manual adjustment of the stimulating electrode position. For significant evaluation of MU responses to a test volley and their latencies, peri-stimulus time histograms (PSTHs) of single MUs were plotted. In order to estimate stimulation effect on regular motoneuron firing, for each MU, in each trial, a target interspike interval (ISI), in which the motor volley arrived, and a corresponding background ISI (just preceding an each stimulus) were calculated and their distributions for all trials were plotted. Exploring excitability changes in an axon after propagation of a regular motoneuron discharge, we based on assuming that the most functionally significant measure of axon excitability recovery is axonal spike occurrence itself. Therefore, in each trial, the presence or absence of the M-response of an MU tested provided unequivocal evidence of whether or not axonal excitability was recovered. At multiple testing, changes in axonal excitability throughout the target ISI were estimated by the firing index (FI), showing the percentage of MU responses at the M-response latency to the total number of test volleys arriving in this step of a target ISI. Thus, the FI gave a quantitative measure of axonal excitability recovery after transmitting a regular voluntary discharge. A total of 96 MUs were recorded (36 MUs of TA, 24 MUs of FCU, and 36 MUs of APB); 39 MUs (40.6%) exhibited M-responses and could be divided into two groups: MUs showing both M-responses and H-reflex (group 1) and those displaying M-responses only (group 2). Examples of MU recordings are presented in Figure 1A. Mean background firing rates of MUs in the muscles investigated ranged between 5 and 14 imp/s. The group 1 included 34 MUs that fired 430 responses to motor volleys. Some of these MUs exhibited very few M-responses; the others demonstrated the M-responses more frequently (25–154, mean 54.2 responses per an MU). For these MUs, PSTHs revealed a significant increase in MU discharge probability at both the M-response and H-reflex latencies (Figure 1B, top). The MUs from group 2 displayed a significant increase in MU firing probability at the M-response latency alone (Figure 1B, bottom). This type of behavior was encountered only in 5 MUs (4 MUs in FCU and 1 MU in APB) from 3 experiments in two out of four subjects. However, in each of the MUs of group 2, the motor axon stimulation elicited M-responses in the most trials, in contrast to the MUs of group 1. The target ISIs for MUs of both groups were significantly shortened as compared with background ones (see Figure 1C). Figure 1. Single motor axon excitability testing by mixed nerve stimulations during voluntary muscle contractions. (A) Examples of MU recordings. Two top records, an MU of group 1 displaying both the H-reflex and M-response; two bottom records, an MU of group 2 displaying M-response only. Asterisks, stimulation time. (B) Peri-stimulus time histograms (PSTHs) of single MUs. Top, an MU of group 1 showing a significant increase in firing probability at the M-response and H-reflex latencies (the tibialis anterior, 2462 trials). Bottom, an MU of group 2 displaying a significant increase in firing probability at the M-response latency only (the flexor carpi ulnaris, 379 trials). M-response was observed in 6.9% trials in top PSTH and in 90.1% trials in bottom PSTH. Zero, stimulation time. The bin width, 2 ms. (C) Distributions of target and background ISIs of single MUs. Top, three MUs of group 1 from one experiment (the tibialis anterior); bottom, an MU of group 2 (the flexor carpi ulnaris). Target ISIs (open bars), n = 257 in top and n = 421 in bottom; background ISIs (filled bars) from the same trials. Bin width, 5 ms. (D) Testing of changes in axonal excitability throughout a target ISI of single MUs. Top, an MU of group 1 (the tibialis anterior, 897 trials); bottom, an MU of group 2 (the flexor carpi ulnaris, 294 trials). Changes in the firing index (FI) after a regular voluntary discharge (taken as 0 ms) are shown within the first 50 ms of the target ISI. The remaining part of the ISI, in which the FI continued to be equal to 0% (in top) and to 100% (in bottom), is not shown. Note bin width of 2 ms within 0–20 and 5 ms within 20–50 ms of the target ISI. To understand the mechanisms underlying different character of MU responses to motor volley, we explored the axonal excitability recovery after a regular discharge for MUs of group 1 and group 2 (Figure 1D, top and bottom, respectively). When the motor volley arrived just in the beginning of the target ISI, it did not evoke an M-response in the both MU groups, and FI was equal to 0% (the refractory period). About 3–5 ms after a regular discharge, as refractoriness subsided, the MUs began to respond to a motor volley and FI sharply rose. At 5–8 ms of target ISI, FI reached to 90–100%. Further, for MUs of group 1, FI fell to zero at 12–19 ms; thereafter, the motor volley appeared ineffective again up to the end of an ISI (FI = 0%). In contrast, MUs of group 2, responded to a motor volley at any moment of the target ISI, with FI up to 100%. Thus, axons belonging to MUs of group 1, after transmitting a regular discharge, displayed early and late irresponsive periods and a short-lasting period of high responsiveness to the motor volley. MUs of group 2 were characterized by a long-lasting period of axonal responsiveness with no late irresponsiveness. The present study provides data on excitability changes in single slow motor axons (belonging to small MUs) transmitting natural motoneuron firing during gentle voluntary muscle contractions. To our knowledge, the question has not been studied before. The axonal excitability recovery of the majority of small MUs was found to be qualitatively similar to that reported previously for both CMAP and single large MUs with a high threshold for voluntary muscle contractions. However, apart from MUs with usual axonal excitability recovery, in two out of four healthy subjects, we had the opportunity to record some MUs displaying the especial excitability properties in axons of the ulnaris and median nerves. It has been revealed that after the short irresponsive period, these MUs were able to respond to motor volley within an ISI throughout. The long duration of the responsibility could be surprising, but it is consistent with data by Bergmans (1970), who pioneered the study of single human motor axons by surface stimulation. He has reported that two axons of the median nerve were found to have the unusual excitability recovery cycle: a long duration supernormal period with no late subnormality. In our experiments, four out of five MUs with especial axonal excitability properties were recorded in FCU supplied by the ulnaris nerve. However, at present, there are no sufficient data to discuss, in total, the possible differences in axonal excitability properties among the muscles investigated. Hence, the population of small MUs was found not to be homogenous as their motor axons were not identical and displayed different excitability properties after the transmission of a regular motoneuron discharge. Previously, Kiernan et al. (1996), analysing the axonal recovery cycle after a supra-maximal conditioning stimulus with using test stimulus evoking CMAP of 30, 50, and 70% max, have concluded that there is no difference in excitability recovery of axons with different thresholds. Obviously, MUs with thin axons (like those from the present experiments) did not contribute to the CMAPs above. It is important to note that using CMAP can hardly give any possibility to analyse excitability recovery in small, slow MUs because they are commonly “dissembled” in the CMAP, whose the main characteristics, such as the latency and amplitude, are generally controlled by large MUs with fast axons. Therefore, we are of opinion that it is necessary further investigations of excitability properties of slow motor axons using single MU recordings but not only CMAP. The next question that arises is: what is mechanism underlying this unusual excitability property revealed in some motor axons? It is widely accepted that the depolarizing after-potential underlies the super-excitability phase lasting up to some 20 ms in the recovery cycle of large axons (see Burke et al., 2001). The same mechanism obviously underlies the short responsive phase in the axonal recovery cycle of small MUs of group 1 from our experiments. At the same time, our findings on a prolonged, broad responsible period in axonal excitability recovery with no irresponsiveness throughout the whole ISI revealed in the MUs of group 2 are not readily explained based on this mechanism alone. What are additional mechanisms that could conceivably contribute to the phenomenon? Bostock et al. (1991) have provided evidence that fast motor axons can display two stable states (high- and low-threshold) following ischemia. In the study of Bostock and Bergmans (1994), it has been suggested that post-tetanic ectopic discharges in motor axons depended on the bistability of the axonal membrane potential and “occur on transitions from a hyperpolarized to a depolarized state. The transitions may occur spontaneously, but are readily triggered by an action potential, giving rise to a prolonged supernormal period.” Following these suggestions, it might be proposed that MUs with slow axons could presumably possess the similar ability for two threshold states and that transition to a low-threshold state resulted in a prolonged responsive phase in the excitability recovery cycle (distinctive axonal plateau potential?). The further exploration is required to clarify the underlying mechanisms. In normal motor behavior, an axon is only a transmitter of motoneuron firing without any discharge distortion. If so, within a given MU, the excitability recovery cycle in the axon has to be some counterpart of that in the motoneuron, certainly including late irresponsive period (equivalent of the after-hyperpolarization which inevitably follows each spike of each motoneuron). However, axons of low-threshold MUs were found not to be identical as some of them, after refractoriness, displayed prolonged responsiveness with no late irresponsible period. In this case, the axonal capacity for transmitting spikes without late irresponsiveness must be unclaimed. An important question is obviously: what are the benefits of such axonal property in normal motor control? This is presently no answer to this question. On the other hand, in neuromuscular diseases, it may be assumed that axons with a long-lasting responsive period can be predisposed to dysfunction to a greater extent than others, in particular, to creating an additional focus of excitation in an axon itself, leading to MU spontaneous firing that emphasizes the importance of further analysis of the excitability properties of similar axons in healthy subjects. Bergmans, J. (1970). The Physiology of Single Human Nerve Fibres. Louvain: Vander. Bergmans, J. (1973). “Physiological observations on single human nerve fibers,” in New Developments in Electromyography and Clinical Neurophysiology, Vol. 2, ed J. E. Desmedt (Basel: Karger), 89–127. Borg, J. (1980). Axonal refractory period of single short toe extensor motor units in man. J. Neurol. Neurosurg. Psychiatry 43, 917–924. doi: 10.1136/jnnp.43.10.917 Pubmed Abstract | Pubmed Full Text | CrossRef Full Text Bostock, H., and Baker, M. (1988). Evidence for two types of potassium channel in human motor nerves in vivo. Brain Res. 462, 354–358. doi: 10.1016/0006-8993(88)90564-1 Pubmed Abstract | Pubmed Full Text | CrossRef Full Text Bostock, H., Baker, M., and Reid, G. (1991). Changes in excitability of human motor axons underlying post-ischaemic fasciculations: evidence for two stable states. J. Physiol. 441, 537–557. Pubmed Abstract | Pubmed Full Text Bostock, H., and Bergmans, J. (1994). Post-tetanic excitability changes and ectopic discharges in a human motor axon. Brain 117, 913–928. doi: 10.1093/brain/117.5.913 Pubmed Abstract | Pubmed Full Text | CrossRef Full Text Bostock, H., Cikurel, K., and Burke, D. (1998). Threshold tracking techniques in the study of human peripheral nerve. Muscle Nerve 21, 137–158. Pubmed Abstract | Pubmed Full Text Bostock, H., Lin, C. S.-Y., Howells, J., Trevillion, L., Jankelowitz, S., and Burke, D. (2005). After-effects of near-threshold stimulation in single human motor axons. J. Physiol. 564, 931–940. doi: 10.1113/jphysiol.2005.083394 Pubmed Abstract | Pubmed Full Text | CrossRef Full Text Burke, D., Kiernan, M. C., and Bostock, H. (2001). Excitability of human axons. Clin. Neurophysiol. 112, 1575–1585. doi: 10.1016/S1388-2457(01)00595-8 Pubmed Abstract | Pubmed Full Text | CrossRef Full Text Hales, J. P., Lin, C. S.-Y., and Bostock, H. (2004). Variations in excitability of single human motor axons, related to stochastic properties of nodal sodium channels. J. Physiol. 559, 953–964. doi: 10.1113/jphysiol.2004.068726 Pubmed Abstract | Pubmed Full Text | CrossRef Full Text Heckman, C. J., and Enoka, R. M. (2012). Motor unit. Compr. Physiol. 2, 2629–2681. doi: 10.1002/cphy.c100087 Pubmed Abstract | Pubmed Full Text | CrossRef Full Text Henneman, E., and Mendell, L. M. (1981). “Functional organization of motoneuron pool and its inputs,” in Handbook of Physiology, The Nervous System, Motor Control, ed V. B. Brooks (Bethesda, MD: American Physiological Society), 423–507. Kernell, D. (2006). The Motoneurone and its Muscle Fibres. New York, NY: Oxford University Press. doi: 10.1093/acprof:oso/9780198526551.001.0001 CrossRef Full Text Kernell, D., Bakels, R., and Copray J.C. V. M. (1999). Discharge properties of motoneurones: how are they matched to the properties and use of their muscle units? J. Physiol. (Paris) 93, 87–96. doi: 10.1016/S0928-4257(99)80139-9 Pubmed Abstract | Pubmed Full Text | CrossRef Full Text Kiernan, M. C., Mogyoros, I., and Burke, D. (1996). Differences in the recovery of excitability in sensory and motor axons of human median nerve. Brain 119, 1099–1105. doi: 10.1093/brain/119.4.1099 Pubmed Abstract | Pubmed Full Text | CrossRef Full Text Kuwabara, S., Lin, C. S.-Y., Mogyoros, I., Cappelen-Smith, C., and Burke, D. (2001). Voluntary contraction impairs the refractory period of transmission in healthy human axons. J. Physiol. 531, 265–275. doi: 10.1111/j.1469-7793.2001.0265j.x Pubmed Abstract | Pubmed Full Text | CrossRef Full Text Murray, J. M., and Jankelowitz, S. K. (2011). A comparison of the excitability of motor axons innervating the APB and ADM muscles. Clin. Neurophysiol. 122, 2290–2293. doi: 10.1016/j.clinph.2011.04.007 Pubmed Abstract | Pubmed Full Text | CrossRef Full Text Nodera, H., and Kaji, R. (2006). Nerve excitability testing and its clinical application to neuromuscular diseases. Clin. Neurophysiol. 117, 1902–1916. doi: 10.1016/j.clinph.2006.01.018 Pubmed Abstract | Pubmed Full Text | CrossRef Full Text Rossi, A., Rossi, S., and Ginanneschi, F. (2012). Activity-dependent changes in intrinsic excitability of human spinal motoneurones produced by natural activity. J. Neurophysiol. 108, 2473–2480. doi: 10.1152/jn.00477.2012 Pubmed Abstract | Pubmed Full Text | CrossRef Full Text Shefner, J. M., Preston, D. C., and Logigian, E. L. (1996). Activity-dependent conduction in single motor units. Neurology 46, 1387–1390. doi: 10.1212/WNL.46.5.1387 Pubmed Abstract | Pubmed Full Text | CrossRef Full Text Vagg, R., Mogyoros, I., Kiernan, M. C., and Burke, D. (1998). Activity-dependent hyperpolarization of human motor axons produced by natural activity. J. Physiol. 507, 919–925. doi: 10.1111/j.1469-7793.1998.919bs.x Pubmed Abstract | Pubmed Full Text | CrossRef Full Text Keywords: motor control, voluntary muscle contraction, single firing motor units, axonal excitability recovery, superexcitability Citation: Kudina LP and Andreeva RE (2014) Excitability properties of single human motor axons: are all axons identical? Front. Cell. Neurosci. 8:85. doi: 10.3389/fncel.2014.00085 Received: 17 January 2014; Accepted: 06 March 2014; Published online: 19 March 2014. Edited by: Reviewed by: Copyright © 2014 Kudina and Andreeva. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. *Correspondence: [email protected]
Fs Gravina, Hc Parkington, Kp Kerr, Rb De Oliveira, P Jobling, Ha Coleman, , Mm Davies, Ms Imtiaz,
Journal of Cerebral Blood Flow & Metabolism, Volume 161, pp 1375-1390; https://doi.org/10.1111/j.1476-5381.2010.00949.x

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C McKenzie, A MacDonald, Am Shaw
Journal of Cerebral Blood Flow & Metabolism, Volume 157, pp 581-596; https://doi.org/10.1111/j.1476-5381.2008.00084.x

Abstract:
Background and purpose: Thromboxane A2 and endothelial dysfunction are implicated in the development of pulmonary hypertension. The receptor-transduction pathway for U46619 (9,11-dideoxy-9α, 11α-methanoepoxy prostaglandin F2α)-induced contraction was examined in endothelium-intact (E+) and denuded (E−) rat pulmonary artery rings. Experimental approach: Artery rings were mounted on a wire myograph under a tension of 7–7.5 mN at 37°C and gassed with 95% O2/5% CO2. Isometric recording was made by using Powerlab data collection and Chart 5 software. Key results: Both E+ and E− contractile responses were sensitive to Rho-kinase inhibition and the chloride channel blocker NPPB [5-nitro-2-(3-phenylpropylamino)benzoic acid]. The E+ response was sensitive to the store-operated calcium channel blockers SKF-96365 {1-[B-[3-(4-methoxyphenyl)propoxy]-4-methoxy-phenethyl]-1H-imidazole hydrochloride} and 2-APB (2-amino ethoxy diphenylborate) (75–100 µmol·L−1). The E− response was sensitive to 2-APB (10–30 µmol·L−1), a putative IP3 receptor antagonist, and the calcium and chloride channel blockers nifedipine, DIDS (4,4′-diisothiocyanostilbene-2,2′-disulphonic acid) and niflumic acid but was insensitive to SKF-96365. Inhibiting KV with 4-AP in E+ rings exposed a contraction sensitive to nifedipine, DIDS and niflumic acid, whereas inhibiting BKCa exposed a contraction sensitive to mibefradil, DIDS and niflumic acid. This indicates that removal of the endothelium allows the TP receptor to inhibit KV, which may involve coupling to phospholipase C, because inhibition of phospholipase C with U73122 (1-[6-[[(17β)-3-methoxyestra-1,3,5(10)-trien-17-y]amino]hexyl]– 1H-pyrrole-2,5-dione) switched the E− pathway to the E+ pathway. Conclusions and implications: The results from this study indicate that distinct transduction pathways can be employed by the TP receptor to produce contraction and that the endothelium is able to influence the coupling of the TP receptor. British Journal of Pharmacology (2009) 157, 581–596; doi:10.1111/j.1476-5381.2008.00084.x; published online 22 April 2009 This article is part of a themed section on Endothelium in Pharmacology. For a list of all articles in this section see the end of this paper, or visit: http://www3.interscience.wiley.com/journal/121548564/issueyear?year=2009
S. Scheerer
Published: 29 December 2008
Balint Journal, Volume 9, pp 114-115; https://doi.org/10.1055/s-0028-1098748

Abstract:
Der Ulmer Deutsche Ärztetag (DÄT) hatte das Generalthema explizit und implizit: Die Gestaltung und Rolle der Arzt-Patient-Beziehung (APB) unter den Bedingungen des rasanten gesellschaftlich-sozialen-ökonomischen Strukturwandels mit dem verstärkten Anpassungsdruck und dem Phänomen der „Gegenwartsschrumpfung“ des „digitalen Kapitalismus“ (E. R. Petzold, A. Doering-Manteuffel 2008). So dezidiert wurde die Programmgestaltung des DÄT nicht angekündigt, ist aber aus der Tagesordnung ableitbar: Ulmer Papier Arztbild der Zukunft und Zusammenarbeit mit anderen Gesundheitsberufen Situation pflegebedürftiger Menschen in Deutschland am Beispiel Demenz Lebensqualität dementer Menschen Auswirkungen der Telematik und Kommunikation auf das Arzt-Patient-Verhältnis Die Balintgesellschaft (DBG) hatte bereits 2006 besorgt auf die „Industrialisierung der Medizin“ (heftig formuliert) hingewiesen und davor gewarnt, das die Gesetze des Marktes die „Inseln des Vertrauens“ durchdrungen haben, wenn Evaluation der Veräußerlichung die inneren Dynamiken zum Erliegen bringen (Editorial Balint-Journal 2006). Aktuelle Entwicklungen der globalen Wirtschafts- und Finanzstrukturen bestätigen die Sorge, dass der APB immer stärker droht, in einer Geschäftsbeziehung zu verkommen mit dem Verlust der Beziehungs- und Bindungsqualität. Im Gegensatz dazu ist ständig aus offiziellem Munde zu hören, es müsse sich die Qualität im Medizinalltag verbessern, eine begrüßenswerte Vorstellung, doch sind die Bedingungen dazu geschaffen (auch vom Gesetzgeber!)?
Rikke L. Schrøder, Søren Friis, Morten Sunesen, Chris Mathes, Niels J. Willumsen
Journal of Biomolecular Screening, Volume 13, pp 638-647; https://doi.org/10.1177/1087057108320274

Abstract:
The suitability of an automated patch clamp for the characterization and pharmacological screening of calcium release—activated calcium (CRAC) channels endogenously expressed in RBL-2H3 cells was explored with the QPatch system. CRAC currents (I CRAC) are small, and thus precise recordings require high signal-to-noise ratios obtained by high seal resistances. Automated whole-cell establishment resulted in membrane resistances of 1728 ± 226 MΩ ( n = 44). CRAC channels were activated by a number of methods that raise intracellular calcium concentration, including EGTA, ionomycin, Ins(1,4,5)P3, and thapsigargin. ICRAC whole-cell currents ranged from 30 to 120 pA with rise times of 40 to 150 s. An initial delay in current activation was observed in particular when ICRAC was activated by passive store depletion using EGTA. Apparent rundown of ICRAC was commonly observed, and the current could be reactivated by subsequent addition of thapsigargin. ICRAC was blocked by SKF-96365 and 2-APB with IC50 values of 4.7 ± 1.1 µM ( n = 9) and 7.5 ± 0.7 ( n = 9) µM, respectively. The potencies of these blockers were similar to values reported for ICRAC in similar conventional patch-clamp experiments. The study demonstrates that CRAC channels can be rapidly and efficiently targeted with automated patch-clamp techniques for characterization of physiological and pharmacological properties. ( Journal of Biomolecular Screening 2008:638-647)
K Togashi, ,
British Journal of Pharmacology, Volume 153, pp 1324-1330; https://doi.org/10.1038/sj.bjp.0707675

Abstract:
Background and purpose: Transient receptor potential melastatin 2 (TRPM2) is a non‐selective Ca2+‐permeable cation channel and is known to be activated by adenosine 5′‐diphosphoribose (ADP‐ribose) and hydrogen peroxide. TRPM2 current responses are reported to be drastically potentiated by the combination of each of these ligands with heat. Furthermore, the combination of cyclic ADP‐ribose with heat also activates TRPM2. Although flufenamic acid, antifungal agents (miconazole and clotrimazole), and a phospholipase A2 inhibitor (N‐(p‐amylcinnamoyl)anthranilic acid) inhibit TRPM2, their inhibition was either gradual or irreversible. Experimental approach: To facilitate future research on TRPM2, we screened several compounds to investigate their potential to activate or inhibit the TRPM2 channels using the patch‐clamp technique in HEK293 cells, transfected with human TRPM2. Key results: 2‐aminoethoxydiphenyl borate (2‐APB) exhibited a rapid and reversible inhibition of TRPM2 channels that had been activated by its ADP‐ribose or cADP‐ribose and heat in a dose‐dependent manner (IC50 about 1 μM). 2‐APB also inhibited heat‐evoked insulin release from pancreatic islets, isolated from rats. Conclusions and implications: 2‐APB proved to be a powerful and effective tool for studying the function of TRPM2. British Journal of Pharmacology (2008) 153, 1324–1330; doi:10.1038/sj.bjp.0707675; published online 21 January 2008
, H Hashitani, M A Tonta, H Suzuki, H C Parkington
Journal of Cerebral Blood Flow & Metabolism, Volume 152, pp 1248-1259; https://doi.org/10.1038/sj.bjp.0707535

Abstract:
Electrically active atypical smooth muscle cells (ASMCs) within the renal pelvis have long been considered to act as pacemaker cells driving pelviureteric peristalsis. We have investigated the role of Ca2+ entry and uptake into and release from internal stores in the generation of Ca2+ transients and spontaneous transient depolarizations (STDs) in ASMCs. The electrical activity and separately visualized changes in intracellular Ca2+ concentration in typical smooth muscle cells (TSMCs), ASMCs and interstitial cells of Cajal‐like cells (ICC‐LCs) were recorded using intracellular microelectrodes and a fluorescent Ca2+ indicator, fluo‐4. In 1 μM nifedipine, high frequency (10–30 min−1) Ca2+ transients and STDs were recorded in ASMCs, while ICC‐LCs displayed low frequency (1–3 min−1) Ca2+ transients. All spontaneous electrical activity and Ca2+ transients were blocked upon removal of Ca2+ from the bathing solution, blockade of Ca2+ store uptake with cyclopiazonic acid (CPA) and with 2‐aminoethoxy‐diphenylborate (2‐APB). STD amplitudes were reduced upon removal of the extracellular Na+ or blockade of IP3 dependent Ca2+ store release with neomycin or U73122. Blockade of ryanodine‐sensitive Ca2+ release blocked ICC‐LC Ca2+ transients but only reduced Ca2+ transient discharge in ASMCs. STDs in ASMCS were also little affected by DIDS, La3+, Gd3+ or by the replacement of extracellular Cl‐ with isethionate. ASMCs generated Ca2+ transients and cation‐selective STDs via mechanisms involving Ca2+ release from IP3‐dependent Ca2+ stores, STD stimulation of TSMCs was supported by Ca2+ entry through L type Ca2+ channels and Ca2+ release from ryanodine‐sensitive stores. British Journal of Pharmacology (2007) 152, 1248–1259; doi:10.1038/sj.bjp.0707535; published online 29 October 2007
L Johansson, M E Ekholm,
Journal of Cerebral Blood Flow & Metabolism, Volume 150, pp 97-104; https://doi.org/10.1038/sj.bjp.0706959

Abstract:
Background and purpose: Orexin (OX) receptors induce Ca2+ elevations via both receptor‐operated Ca2+ channels (ROCs) and the “conventional” phospholipase C (PLC)–Ca2+ release–store‐operated Ca2+ channel (SOC) pathways. In this study we assessed the ability of these different Ca2+ influx pathways to amplify OX1 receptor signalling to PLC in response to stimulation with the physiological ligand orexin‐A. Experimental approach: PLC activity was assessed in CHO cells stably expressing human OX1 receptors. Key results: Inhibition of total Ca2+ influx by reduction of the extracellular [Ca2+] to 1 μM effectively inhibited the receptor‐stimulated PLC activity at low orexin‐A concentrations (by 93% at 1 nM), and this effect was gradually reduced by higher orexin‐A concentrations. A similar but weaker inhibitory effect (84% at 1 nM) was obtained on depolarization to ∼0 mV, which disrupts most of the driving force for Ca2+ entry. The inhibitor of the OX1 receptor‐activated ROCs, tetraethylammonium chloride (TEA), was somewhat less effective than the reduction in extracellular [Ca2+] at inhibiting PLC activation, probably because it only partially blocks ROCs. The partial inhibitor of both ROCs and SOCs, Mg2+, and the SOC inhibitors, dextromethorphan, SKF‐96365 (1‐[β‐(3‐(4‐methoxyphenyl)propoxy)‐4‐methoxyphenethyl]‐1H‐imidazole HCl) and 2‐APB (2‐aminoethoxydiphenyl borate), inhibited PLC activity at low concentrations of orexin‐A, but were not as effective as TEA. Conclusions and implications: Both ROCs and SOCs markedly amplify the OX1 receptor‐induced PLC response, but ROCs are more central for this response. These data indicate the crucial role of ROCs in orexin receptor signalling. British Journal of Pharmacology (2007) 150, 97–104. doi:10.1038/sj.bjp.0706959
Michael Grimm, Nina Mahnecke, Friederike Soja, Ali El-Armouche, Pascal Haas, Hendrik Treede, Hermann Reichenspurner,
Journal of Cerebral Blood Flow & Metabolism, Volume 148, pp 991-1000; https://doi.org/10.1038/sj.bjp.0706803

Abstract:
1 The present study examined the role of myosin light chain kinase (MLCK), PKC isozymes, and inositol 1,4,5-trisphosphate (IP3) receptor in the positive inotropic effect of α1-adrenergic stimulation in atrial myocardium. 2 We measured inotropic effects of phenylephrine (0.3–300 μM) in isolated left atrial preparations (1 Hz, 37°C, 1.8 mM Ca2+, 0.3 μM nadolol) from male 8-week FVB mice (n=200). Phenylephrine concentration-dependently increased force of contraction from 1.5±0.1 to 2.8±0.1 mN (mean±s.e.m., n=42), which was associated with increased MLC-2a phosphorylation at serine 21 and 22 by 67% and translocation of PKCɛ but not PKCα to membrane (+30%) and myofilament (+50%) fractions. 3 MLCK inhibition using ML-7 or wortmannin right-shifted the concentration–response curve of phenylephrine, reducing its inotropic effect at 10 μM by 73% and 81%, respectively. 4 The compound KIE1-1 (500 nM), an intracellularly acting PKCɛ translocation inhibitor peptide, prevented PKCɛ translocation and augmented the maximal inotropic effect of phenylephrine by 40%. In contrast, inhibition of Ca2+-dependent PKC translocation (KIC1-1, 500 nM) had no effect. Chelerythrine, a PKC inhibitor, decreased basal force without changing the inotropic effect of phenylephrine. 5 The IP3 receptor blocker 2-APB (2 and 20 μM) concentration-dependently decreased basal force, but did not affect the concentration–response curve of phenylephrine. 6 These results indicate that activation of MLCK is required for the positive inotropic effect of α1-adrenergic stimulation, that the Ca2+-independent PKCɛ negatively modulates this effect, and that PKCα and IP3 receptor activation is not involved. British Journal of Pharmacology (2006) 148, 991–1000. doi:10.1038/sj.bjp.0706803
N Tugba Durlu-Kandilci,
Journal of Cerebral Blood Flow & Metabolism, Volume 148, pp 376-384; https://doi.org/10.1038/sj.bjp.0706723

Abstract:
1 The signal transduction pathways involved in carbachol (CCh)-induced calcium sensitization in β-escin permeabilized rat and guinea-pig bladder smooth muscles were investigated and the results were compared with guinea-pig taenia caecum. 2 Calcium contractions elicited cumulatively (pCa 7.5–5) in the presence of calmodulin were significantly increased in all three tissues when CCh (50 μM) was added to the medium. 3 Under constant [Ca2+]i conditions (pCa 6), calmodulin (1 μM) and then GTP (100 μM) initiated significant contractions. CCh (50 μM) added to the bath caused a further contraction in all three tissues – calcium sensitization. This sensitization was significantly inhibited by atropine (50 μM). 4 The incubation of the tissues with the IP3-receptor blocker 2-APB (30 μM) reduced the subsequent development of calcium sensitization by CCh in rat bladder but did not affect it in guinea-pig bladder and taenia ceacum. 5 The Rho kinase (ROK) inhibitor Y-27632 (5 μM) added in the presence of CCh reversed the calcium sensitization in rat bladder, whereas a transient contraction followed by a relaxation to a level not significantly different from the CCh contraction was seen in both guinea-pig bladder and taenia caecum. Y-27632 (1 μM) continuously present significantly inhibited the CCh-induced Ca2+ sensitization in rat bladder but not in guinea-pig bladder or taenia caecum. 6 In the presence of cyclopiazonic acid (CPA) (1 μM) and calmodulin (1 μM), Y-27632 (5 μM) did not change the calcium response curve (3 × 10−7–10−5 M) in rat bladder but increased the contractile responses significantly in both guinea-pig bladder and taenia caecum. 7 The protein kinase C (PKC) inhibitor GF 109203X (5 μM) added in the presence of CCh inhibited the calcium sensitization induced by this muscarinic agonist in all three tissues in different ratios. 8 In conclusion, muscarinic receptor activation induces calcium sensitization in rat and guinea-pig detrusor smooth muscles but there are differences in their pathways. British Journal of Pharmacology (2006) 148, 376–384. doi:10.1038/sj.bjp.0706723
, Fanning Zeng, Guylain Boulay, , Christian Harteneck,
British Journal of Pharmacology, Volume 145, pp 405-414; https://doi.org/10.1038/sj.bjp.0706197

Abstract:
1 2‐Aminoethoxydiphenyl borate (2‐APB) has been widely used to examine the roles of inositol 1,4,5‐trisphosphate receptors (IP3Rs) and store‐operated Ca2+ entry and is an emerging modulator of cationic channels encoded by transient receptor potential (TRP) genes. 2 Using Ca2+‐indicator dye and patch‐clamp recording we first examined the blocking effect of 2‐APB on human TRPC5 channels expressed in HEK‐293 cells. 3 The concentration–response curve has an IC50 of 20 μM and slope close to 1.0, suggesting one 2‐APB molecule binds per channel. The blocking effect is not shared by other Ca2+ channel blockers including methoxyverapamil, nifedipine, N‐propargylnitrendipine, or berberine. 4 In whole‐cell and excised membrane patch recordings, 2‐APB acts from the extracellular but not intracellular face of the membrane. 5 Block of TRPC5 by 2‐APB is less at positive voltages, suggesting that it enters the electric field or acts by modulating channel gating. 6 2‐APB also blocks TRPC6 and TRPM3 expressed in HEK‐293 cells, but not TRPM2. 7 Block of TRP channels by 2‐APB may be relevant to cell proliferation because 2‐APB has a greater inhibitory effect on proliferation in cells overexpressing TRPC5. 8 Our data indicate a specific and functionally important binding site on TRPC5 that enables block by 2‐APB. The site is only available via an extracellular route and the block shows mild voltage‐dependence. British Journal of Pharmacology (2005) 145, 405–414. doi:10.1038/sj.bjp.0706197
, Hikaru Suzuki
Journal of Cerebral Blood Flow & Metabolism, Volume 141, pp 199-204; https://doi.org/10.1038/sj.bjp.0705622

Abstract:
This study shows for the first time the presence of interstitial cells of Cajal (ICC) and their possible role in the initiation of spontaneous excitation in the corporal tissue of the guinea‐pig penis. ICC, which were identified by their c‐kit immunoreactivity, were abundantly distributed in the corporal smooth muscle meshwork. Spontaneous increases in the intracellular calcium concentration ([Ca2+]i; calcium transients) were visualized in preparations loaded with the fluorescent dye fura‐2. Ca transients originated from the boundary of muscle bundles and then spread throughout the meshwork (Ca waves). Ca waves were strongly suppressed by either CPA (10 μM), ryanodine (50 μM) or 2‐APB (10 μM), and their synchronicity was disrupted by 18β‐GA (30 μM). These results suggest that ICC in the corporal tissue may have a role as pacemakers to drive the bulk of smooth muscles, and that intracellular Ca2+ stores and gap junctions are critical for the generation of spontaneous excitation. British Journal of Pharmacology (2004) 141, 199–204. doi:10.1038/sj.bjp.0705622
Jun Zhao,
Journal of Cerebral Blood Flow & Metabolism, Volume 140, pp 1399-1413; https://doi.org/10.1038/sj.bjp.0705573

Abstract:
In vitro experiments were performed to investigate the actions of endothelin‐1 (ET‐1) on vasomotion and vasospasm in guinea‐pig mesenteric lymphatics. ET‐1 modulated lymphatic vasomotion independent of the endothelium, with lower concentrations (10 nM) increasing lymphatic vasomotion and higher concentrations (100 nM) causing vasospasm. ET‐1‐induced increases in vasomotion were accompanied by an increase in tonic [Ca2+]i. These actions were inhibited by the ETA receptor antagonist BQ‐123 (1 μM), the phospholipase C (PLC) inhibitor U73122 (5 μM), removal of extracellular Ca2+, chelation of intracellular Ca2+ with BAPTA/AM (10 μM), the store Ca2+‐ATPase inhibitor thapsigargin (1 μM), caffeine (10 mM) and the inositol 1,4,5‐trisphosphate (IP3) receptor blocker heparin and 2‐APB (30 μM). In contrast, the ETB receptor antagonist BQ‐788 (1 μM), ryanodine (1 & 20 μM), pertussis toxin (PTx) or Cs+ had no significant actions on vasomotion or the magnitude of increase in tonic [Ca2+]i. ET‐1‐induced vasospasm was accompanied by a transient increase in smooth muscle [Ca2+]i followed by a sustained plateau, an action that was abolished by removal of extracellular Ca2+, but only marginally inhibited by nifedipine (1 μM). Caffeine (10 mM), SKF 96165 (30 μM) or U73122 (5 μM) together with nifedipine (1 μM) abolished ET‐1‐induced vasospasm and increase in [Ca2+]i. These results indicate that ET‐1 increases lymphatic vasomotion by acting on smooth muscle ETA receptors and activation of G‐protein‐PLC‐IP3 cascade, which is known to cause pacemaker Ca2+ release and resultant pacemaker potentials. High concentrations of ET‐1 cause a failure in Ca2+ homeostasis causing vasospasm, triggered by excessive Ca2+ influx primarily through store‐operated channels (SOCs) with L‐Ca2+ voltage‐operated channels (VOCs) also contributing, but to a much lesser extent. British Journal of Pharmacology (2003) 140, 1399–1413. doi:10.1038/sj.bjp.0705573
Vladimir A Snetkov, , Jeremy P T Ward, , Tom P Robertson
Journal of Cerebral Blood Flow & Metabolism, Volume 140, pp 97-106; https://doi.org/10.1038/sj.bjp.0705408

Abstract:
The effect of induction of capacitative Ca2+ entry (CCE) upon tone in small (i.d. 200–500 μm) intrapulmonary (IPA), mesenteric (MA), renal (RA), femoral (FA), and coronary arteries (CA) of the rat was examined. Following incubation of IPA with 100 nM thapsigargin (Thg) in Ca2+‐free physiological salt solution (PSS), a sustained contraction was observed upon reintroduction of 1.8 mM Ca2+, which was unaffected by either diltiazem (10 μM) or the reverse mode Na+/Ca2+ antiport inhibitor KB‐R7943 (10 μM). An identical protocol failed to elicit contraction in MA, RA, or CA, while a small transient contraction was sometimes observed in FA. The effect of this protocol on the intracellular Ca2+ concentration ([Ca2+]i) was assessed using Fura PE3‐loaded IPA, MA, and FA. Reintroduction of Ca2+ into the bath solution following Thg treatment in Ca2+‐free PSS caused a large, rapid, and sustained increase in [Ca2+]i in all the three types of artery. 100 nM Thg induced a slowly developing noisy inward current in smooth muscle cells (SMC) isolated from IPA, which was due to an increase in the activity of single channels with a conductance of ∼30 pS. The current had a reversal potential near 0 mV in normal PSS, and persisted when Ca2+‐dependent K+ and Cl− currents were blocked; it was greatly inhibited by 1 μM La3+, 1 μM Gd3+, and the IP3 receptor antagonist 2‐APB (75 μM), and by replacement of extracellular cations by NMDG+. In conclusion, depletion of intracellular Ca2+ stores with Thg caused capacitative Ca2+ entry in rat small muscular IPA, MA, and FA. However, a corresponding contraction was observed only in IPA. CCE in IPA was associated with the development of a small La3+‐ and Gd3+‐sensitive current, and an increased Mn2+ quench of Fura PE‐3 fluorescence. These results suggest that although CCE occurs in a number of types of small arteries, its coupling to contraction appears to be of particular importance in pulmonary arteries. British Journal of Pharmacology (2003) 140, 97–106. doi:10.1038/sj.bjp.0705408
Sergey I Zakharov, Tarik Smani, Endri Leno, Regina Macianskiene, Kanigula Mubagwa,
Journal of Cerebral Blood Flow & Metabolism, Volume 138, pp 234-244; https://doi.org/10.1038/sj.bjp.0705074

Abstract:
Previously we have described a monovalent cation (MC) current that could be unmasked by the removal of extracellular divalent cations in vascular smooth muscle cells (SMC) and cardiac myocytes, but specific and potent inhibitors of MC current have not been found, and the mechanism of its intracellular regulation remains obscure. Here we show that small MC current is present in intact cells and could be dramatically up‐regulated during cell dialysis. MC current in dialyzed cells strongly resembled monovalent cation current attributed to Ca2+ release‐activated Ca2+‐selective (CRAC) channels, but its activation did not require depletion of Ca2+ stores, and was observed when the cells were dialyzed with, or without BAPTA. Intracellular free Mg2+ inhibits MC current with Kd=250 μM. Extracellular (but not intracellular) spermine effectively blocked MC current with Kd =3–10 μM, while store‐operated cations (SOC) channels and capacitative Ca2+ influx were not affected. Spermine effectively inhibited MC current‐induced SMC depolarization, and prevented Ca2+ paradox‐induced vascular contracture. Both, MC and SOC currents were inhibited by 2‐aminoethoxydiphenyl borate (2‐APB). It is concluded that MC current could be regulated by intracellular Mg2+, and low concentrations of extracellular spermine could be used to discriminate it from SOC current, and to assess its role in cellular function. British Journal of Pharmacology (2003) 138, 234–244. doi:10.1038/sj.bjp.0705074
A. Thomasson, S. Geffroy, E. Frejafon, D. Weidauer, R. Fabian, Y. Godet, M. Nominé, T. Ménard, P. Rairoux, D. Moeller, et al.
Published: 1 April 2002
Applied Physics B, Volume 74, pp 453-459; https://doi.org/10.1007/s003400200826

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, H Hashitani, S Keller, H Takano, E L Mulholland, H Fukuta, H Suzuki
Journal of Cerebral Blood Flow & Metabolism, Volume 135, pp 1363-1374; https://doi.org/10.1038/sj.bjp.0704609

Abstract:
The role of internal Ca2+ stores in the generation of the rhythmic electrical and contractile activity in the guinea‐pig proximal renal pelvis was examined using intracellular microelectrode and muscle tension recording techniques. Ryanodine (30 μM) transiently increased contraction amplitude, while caffeine (0.5 – 3 mM) reduced contraction amplitude and frequency. Contractility was also reduced by 2‐aminoethoxy‐diphenylborate (2‐APB 60 μM), xestospongin C (1 μM), U73122 (5 μM) and neomycin (4 mM), blockers of IP3‐dependent release from Ca2+ stores. 60 mM K+ saline‐evoked contractions were reduced by caffeine (1 mM), U73122 (5 μM) and neomycin (4 mM), but little affected by ryanodine or 2‐APB (60 μM). Spontaneous action potentials consisting of an initial spike followed by a long plateau were recorded (frequency 8.6±1.0 min−1) in small urothelium‐denuded strips of proximal renal pelvis. Action potential discharge was blocked in 75 and 35% of cells by 2‐APB (60 μM) and caffeine (1 mM), respectively. In the remaining cells, only a truncation of the plateau phase was observed. Cyclopiazonic acid (CPA 10 μM for 10 – 180 min), blocker of CaATPase, transiently increased contraction frequency and amplitude. Action potential durations were increased 3.6 fold. Contraction amplitude and frequency slowly declined during a prolonged (>60 min) CPA exposure. We conclude that the action potential in caffeine‐sensitive cells and the shoulder component of caffeine‐insensitive action potential arise from the entry of Ca2+ through Ca2+ channels. The inhibitory actions of modulators of internal Ca2+ release were partially explained by a blockade of Ca2+ entry. British Journal of Pharmacology (2002) 135, 1363–1374; doi:10.1038/sj.bjp.0704609
Nour B Bishara, Timothy V Murphy,
Journal of Cerebral Blood Flow & Metabolism, Volume 135, pp 119-128; https://doi.org/10.1038/sj.bjp.0704465

Abstract:
Agonists increase endothelial cell intracellular Ca2+, in part, by capacitative entry, which is triggered by the filling state of intracellular Ca2+ stores. It has been suggested that depletion of endoplasmic reticulum (ER) Ca2+ stores either leads to a physical coupling between the ER and a plasma membrane channel, or results in production of an intracellular messenger which affects the gating of membrane channels. As an axis involving the IP3 receptor has been implicated in a physical coupling mechanism the aim of this study was to examine the effects of the putative IP3 receptor antagonists/modulators, 2 aminoethoxydiphenyl borate (2APB) and xestospongin C, on endothelial cell Ca2+ entry. Studies were conducted in fura 2 loaded cultured bovine aortic endothelial cells and endothelial cells isolated from rat heart. 2APB (30 – 300 μM) inhibited Ca2+ entry induced by both agonists (ATP 1 μM, bradykinin 0.1 μM) and receptor‐independent mechanisms (thapsigargin 1 μM, ionomycin 0.5 and 5 μM). 2APB did not diminish endothelial cell ATP‐induced production of IP3 nor effect in vitro binding of [3H]‐IP3 to an adrenal cortex binding protein. Capacitative Ca2+ entry was also blocked by disruption of the actin cytoskeleton with cytochalasin (100 nM) while the initial Ca2+ release phase was unaffected. Similarly to 2APB, xestospongin C (3 – 10 μM) inhibited ATP‐induced Ca2+ release and capacitative Ca2+ entry. Further, xestospongin C inhibited capacitative Ca2+ entry induced by thapsigargin (1 μM) and ionomycin (0.5 μM). The data are consistent with a mechanism of capacitative Ca2+ entry in vascular endothelial cells which requires (a) IP3 receptor binding and/or an event distal to the activation of the ER receptor and (b) a spatial relationship, dictated by the cytoskeleton, between Ca2+ release and entry pathways. British Journal of Pharmacology (2002) 135, 119–128; doi:10.1038/sj.bjp.0704465
Simon J Potocnik,
Journal of Cerebral Blood Flow & Metabolism, Volume 134, pp 247-256; https://doi.org/10.1038/sj.bjp.0704270

Abstract:
Arteriolar myogenic tone shows a marked dependency on extracellular Ca2+. The contribution played by mechanisms such as intracellular Ca2+ release and capacitative entry, however, are less certain. The present studies aimed to demonstrate functional evidence for involvement of such mechanisms in myogenic tone and reactivity. Single cremaster arterioles were denuded of endothelium, pressurized under no‐flow conditions and loaded with fura 2‐AM for measurement of changes in intracellular Ca2+ [Ca2+]i. The cell permeable, putative, IP3 receptor antagonist 2APB (2 aminoethoxydiphenyl borate) was used to determine the possible role of IP3 receptor‐mediated mechanisms in arteriolar myogenic tone and reactivity. Arterioles dilated in response to increasing concentrations of 2APB (1 – 300 μM) without a concomitant change in global [Ca2+]i. Also 2APB (50 μM) completely inhibited the myogenic constriction in response to a step change in luminal pressure (50 – 120 mmHg) with no apparent effect on pressure‐mediated increases in [Ca2+]i. 2APB markedly attenuated the constrictor response and [Ca2+]i increase stimulated by phenylephrine but not KCl. Capacitative Ca2+ influx in arterioles was demonstrated either by re‐addition of extracellular [Ca2+] following pre‐treatment with 1 or 10 μM nifedipine in Ca2+ free buffer or exposure of vessels to thapsigargin (1 μM) to induce store depletion. In both cases 2APB inhibited the increase in [Ca2+]i. Capacitative Ca2+ entry showed an inverse relationship with intraluminal pressure over the range 10 – 120 mmHg. Consistent with an effect on a Ca2+ entry pathway, 2APB had no effect on intracellular (caffeine releasable) Ca2+ stores while decreasing the rate of Mn2+ quench of fura 2 fluorescence. The results provide functional evidence for capacitative Ca2+ entry in intact arteriolar smooth muscle. The effectiveness of 2APB in inhibiting both non‐voltage gated Ca2+ entry and responsiveness to an acute pressure step is consistent with the involvement of an axis involving IP3‐mediated and or capacitative Ca2+ entry mechanisms in myogenic reactivity. Given the lack of effect of 2APB on pressure‐induced changes in global [Ca2+]i it is suggested that such mechanisms participate on a localized level to couple the myogenic stimulus to contraction. British Journal of Pharmacology (2001) 134, 247–256; doi:10.1038/sj.bjp.0704270
James R Jezior, Jeffrey D Brady, Daniel I Rosenstein, Kurt A McCammon, Amy S Miner, Paul H Ratz
Journal of Cerebral Blood Flow & Metabolism, Volume 134, pp 78-87; https://doi.org/10.1038/sj.bjp.0704241

Abstract:
The subcellular mechanisms regulating stimulus‐contraction coupling in detrusor remain to be determined. We used Ca2+‐free solutions, Ca2+ channel blockers, cyclopiazonic acid (CPA), and RhoA kinase (ROK) inhibitors to test the hypothesis that Ca2+ influx and Ca2+ sensitization play primary roles. In rabbit detrusor, peak bethanechol (BE)‐induced force was inhibited 90% by incubation for 3 min in a Ca2+‐free solution. By comparison, a 20 min incubation of rabbit femoral artery in a Ca2+‐free solution reduced receptor‐induced force by only 5%. In detrusor, inhibition of sarcoplasmic reticular (SR) Ca2+ release by 2APB, or depletion of SR Ca2+ by CPA, inhibited BE‐induced force by only 27%. The CPA‐insensitive force was abolished by LaCl3. By comparison, 2APB inhibited receptor‐induced force in rabbit femoral artery by 71%. In the presence of the non‐selective cation channel (NSCC) inhibitor, LOE‐908, BE did not produce an increase in [Ca2+]i but did produce weak increases in myosin phosphorylation and force. Inhibitors of ROK‐induced Ca2+ sensitization, HA‐1077 and Y‐27632, inhibited BE‐induced force by ∼50%, and in combination with LOE‐908, nearly abolished force. These data suggest that two principal muscarinic receptor‐stimulated detrusor contractile mechanisms include NSCC activation, that elevates [Ca2+]i and ROK activation, that sensitizes cross bridges to Ca2+. British Journal of Pharmacology (2001) 134, 78–87; doi:10.1038/sj.bjp.0704241
Sally M. Schultz, Roxanne T. Johnson
Accounting Historians Journal, Volume 25, pp 81-111; https://doi.org/10.2308/0148-4184.25.2.81

Abstract:
The appropriate means of accounting for income taxes on financial statements has been among the most hotly debated and frequently recycled issues of the past 50 years. This retrospective account begins with the issuance of the first professional standards during the 1930s and 1940s, and illustrates how theoretical arguments, developed in professional and academic journals during the 1950s, were subsequently recycled and revised during later decades. The problems that led to reconsideration of the deferred tax issue by both the APB during the 1960s and the FASB during the 1980s and 1990s are discussed, as are the solutions offered by these standard setters.
Kenneth Harwood
Published: 1 December 1969
Journal of Broadcasting, Volume 14, pp 5-12; https://doi.org/10.1080/08838156909363571

Abstract:
This is the fifth in a series on the economics of broadcasting written by Kenneth Harwood. Articles on the “ecology” of broadcasters (Vol. 6, No. 3), distribution of payrolls (7:4), “On Earning a Non‐Profit” (11:1), and “On Public Broadcasting for Private Profit” (11:3) already have appeared in the Journal. Dr. Harwood is professor and dean in the School of Communications and Theater of Temple University, chairman of the board of Broadcast Foundation of California, and an active member of numerous professional associations. For a dozen years he served as an officer or director of the APBE.
Kenneth Harwood
Published: 1 June 1967
Journal of Broadcasting, Volume 11, pp 191-198; https://doi.org/10.1080/08838156709363546

Abstract:
The following paper is intended to “give good cheer to those who suppose that broadcasting for profit is not proper, as well as to those who suppose that broadcasting for profit is quite proper.” It is a companion piece to the author's “On Earning a Non‐Profit,” which was published in the Winter, 1966–67, issue of the Journal of Broadcasting. This article is copyright (1967) by Dr. Harwood, who currently is professor and chairman in the Department of Telecommunications at the University of Southern California, but will take up duties as Dean of the School of Communications and Theater at Temple University in January, 1968. He is also president of the Oak Knoll Broadcasting Company (KRLA, Los Angeles), chairman of the board of the Broadcast Foundation of California, and a member of the Radio Board of Directors of the NAB. For a dozen years he served as an officer or director of the APBE, and often has contributed to the Journal in the past.
Kenneth Harwood
Published: 1 December 1966
Journal of Broadcasting, Volume 11, pp 17-26; https://doi.org/10.1080/08838156609363525

Abstract:
Kenneth Harwood is professor and chairman in the Department of Telecommunications at the University of Southern California. He is currently president of the Oak Knoll Broadcasting Company (KRLA, Los Angeles), chairman of the board of the Broadcast Foundation of California, Inc., and a member of the Radio Board of Directors of the National Association of Broadcasters. For a dozen years he served as an officer or director of the APBE, and often has contributed to the Journal. The following article is copyright (1966) by Dr. Harwood, and was prepared as a chapter in a forthcoming book, tentatively titled The Farther Vision: Educational Television Today, edited by Allen E. Koenig and Ruane B. Hill, to be published next fall by the University of Wisconsin Press.
Paul H. Wagner
Published: 1 September 1966
Journal of Broadcasting, Volume 10, pp 327-338; https://doi.org/10.1080/08838156609386212

Abstract:
The increasing availability of statistical information on the characteristics and growth of the broadcasting industry have led to a surprisingly small number of studies that attempt to find relationships between the various factors that contribute to an understanding of the economics of broadcasting. The following study is an attempt to use these data to provide indices of broadcasting's growth over the past 30 years. Paul H. Wagner is Associate Professor in the School of Journalism at Ohio University, and has served as a member of the research committees of both the RTNDA and the APBE.
Don C. Smith, Kenneth Harwood
Published: 1 September 1966
Journal of Broadcasting, Volume 10, pp 339-355; https://doi.org/10.1080/08838156609386213

Abstract:
The following article is based on hitherto unprocessed data drawn from the 1960 APBE‐NAB study of People in Broadcasting. The Journal has, in the past, published articles from this major research on the topics of broadcasting management, problems in finding qualified employees, the broadcasting employee, employee attitudes toward the broadcasting industry, and the former broadcast employee. Reprints are still available from the Journal, office.
Leonard H. Marks
Published: 1 March 1965
Journal of Broadcasting, Volume 9, pp 97-101; https://doi.org/10.1080/08838156509386137

Abstract:
During the past five years, the Journal has published a half‐dozen articles on some aspect of space satellite communication. The following is a revised and edited version of the featured address at the Annual APBE Luncheon during its convention in Washington this spring. Mr. Marks is well known to many broadcasters as a partner in the Washington communications law firm of Cohn and Marks. He also serves as a member of the Board of Directors of the Communication Satellite Corporation.
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