Nephroblastoma is one of the most frequent solid tumors in childhood. It is also a classical example of success in oncology achieved by consequent and randomized studies run since mid-XX until now. As systemic treatment is constantly very effective and has not changed markedly since the last 30 years, the development of precise imaging and surgical technique allowed for the introduction of several new operative methods offering intriguing advantages. This paper is based on the literature review limited to the state-of-the-art or corner-stone positions and over 30 years of personal experience of the author. It does not pretend to be a form of a systematic meta-analysis.

Objectives: To investigate the efficiency of the ECOLAB “Drape ArmourTM” device in limiting the eye-lens doses absorbed by healthcare personnel exposed to ionizing radiation, in a four-month trial during gastroenterology interventional radiology procedures. Methods: Eyelens doses measured with eye-lens dosimeters calibrated in terms of equivalent dose at 3 mm depth ( Hp(3) ) were collected and analyzed since 2016 along with the irradiation parameters (Dose Area Product - DAP). The eye-lens doses received during the four-month trial, have been compared with doses normally received, in the same conditions of irradiation, in the absence of the protection drape. Results: During the period of use of Drape ArmourTM, the average dose to the eye lens was estimated to be 0.73 mSv (St.dev = 0.40 mSv). The average dose to the eye lens, measured in the same four-month period, across different years from 2017 to 2021, was equal to 1.30 mSv (st. dev = 0.35 mSv). Conclusions: Results suggest the effectiveness of Drape ArmourTM in containing the doses to the eye lens. Keypoint: Limiting eye-lens doses to a maximum value of 20 mSv/year is a real challenge, especially in interventional radiologic facilities. The use of suitable radio-opaque drapes may help healthcare workers involved in such facilities. The aim of the work is to evaluate the efficiency of the ECOLAB “Drape ArmourTM” sterile mono-use drape.

Purpose: The aim of this study was to investigate the effects of a chemotherapeutic agent Cytosine Arabinoside (Ara-C) and a natural anticancer agent of Thymoquinone (TQ) on apoptosis and cell proliferation of AML cell lines (Kasumi-6) both alone and in combined form. Material and method: Kasumi-6 AML cells were treated with three different doses of Ara-C (0.1, 0.5 and 1 µmol) and TQ (25, 50 and 100 µM) for 48 and 72 hours incubations. After Annexin V and Propidium Iodide (PI) staining, apoptosis, viability, and cell proliferation were evaluated for each group in flow cytometry. Results: As a result, AML cell lines showed a statistically significant difference in a single treatment of the active substances. Their combined treatment showed an increase in apoptosis and a decrease in viability in both groups at 48 and 72 hours incubation times (p < 0.001). In each group, it was observed that apoptosis was increased and viability was decreased and consequently cell proliferation was suppressed. Conclusion: Ara-C was used for the first time in this study with TQ in AML. It was determined that the combined use of TQ and Ara-C did not have a synergistic effect on apoptosis.

Receptors Tyrosine Kinases (RTKs) act as sensors for extracellular ligands, the binding of which triggers dimerization, activation, and autophosphorylation of specific tyrosine (Y) residues in the Cytoplasmic Domain (CD). This leads to the recruitment and activation of multiple downstream signaling proteins, which regulate various aspects of cellular physiology.

Cancer therapy using Photodynamic Therapy (PDT) has been investigated for some time [1,2] and now it is a growing area of interest in clinical trials [3]. Monte Carlo (MC) simulations were used for early laboratory studies [4,5] for analysis in PDT. Various improvements in the MC method have advanced the field in recent years.

Chronic diseases are still known as incurable diseases, and we suspect that the medical research model is unfit for characterizing chronic diseases. In this study, we examined accuracy and reliability required for characterizing chronic diseases, reviewed implied presumptions in clinical trials and assumptions used in statistical analysis, examined sources of variances normally encountered in clinical trials, and conducted numeric simulations by using hypothetical data for several theoretical and hypothetical models. We found that the sources of variances attributable to personal differences in clinical trials can distort hypothesis test outcomes, that clinical trials introduce too many errors and too many inaccuracies that tend to hide weak and slow-delivering effects of treatments, and that the means of treatments used in statistical analysis have little or no relevance to specific patients. We further found that a large number of uncontrolled co-causal or interfering factors normally seen in human beings can greatly enlarge the means and the variances or experimental errors, and the use of high rejection criteria (e.g., small p values) further raises the chances of failing to find treatment effects. As a whole, we concluded that the research model using clinical trials is wrong on multiple grounds under any of our realistic theoretical and hypothetical models, and that misuse of statistical analysis is most probably responsible for failure to identify treatment effects for chronic diseases and failure to detect harmful effects of toxic substances in the environment. We proposed alternative experimental models involving the use of single-person or mini optimization trials for studying low-risk weak treatments.

Medicine fails to find predictable cures for cancer in more than a century, and we explored the feasibility of controlling cancer growth speed by using lifestyle factors. After conducting an extensive literature review, we conducted simulations for cancer growth courses to see the feasibility of controlling cancer growth speeds. We found that (1) medical treatments are often accompanied by three to four lethal factors: treatment side-effects, emotional distress, and chronic stress, reduced exercises and physical inactivity, and excessive nutrition in some cases; (2) clinical trial exaggerates treatments short-term benefits and underestimates the slow-delivering adverse side effects as a result of statistical averaging, interfering effects of personal lifestyle factors and insufficient follow-up times; (3) the benefits of medical treatments are limited by chain comparisons, where surgery may work as a negative standard relative to the best alternatives for resolving cancer; (4) the strategy of destroying the tumor or killing all cancer cells is unworkable; (5) medical treatments can turn natural cancer growth curve into approximately doubly exponential curve; (6) multiple-factor non-medical measures are potentially much more powerful than medical treatments in controlling cancer growth and metastasis speeds; and (7) cancer early diagnosis and over treatments are unwise strategies in light of discoveries. Based on huge increases in cancer growth rate constants, substantial loss of vital organ functional capacity, and severe systemic aging-like cellular damages, we concluded that medical treatments may promote cancer growth and metastasis speeds and shorten patient lives in most situations, and the claimed benefits are caused by triple biases of clinical trials. By using the same method to explore how several lifestyle factors affect cancer growth rates, we concluded that the better strategy for ending the global cancer epidemic in the future is changing caner treatment strategy from killing cancer cells to slowing down cancer growth rates by using various lifestyle factors in combination. This study in part explains why cancer can self-resolve.

In the setting of upfront chemotherapy, some degree of reduction in primary tumor volume may occur.