This study aimed to assess the levels of contamination by pesticide residues in several types of vegetables collected from different regions in Egypt. A total of 100 samples of vegetables (pepper, tomato, cucumber, and strawberry) were collected from markets in five cities (Al-Obour, Al-Salheia El-Gadida, Giza, Zagazig, and Fayed) and analyzed for the presence of 42 different pesticide residues. The Quick, Easy, Cheap, Effective, Rugged, and Safe (QuEChERS) method was used to extract the target pesticides, which were then quantified using Gas Chromatography-Mass Spectrometry (GC-MS/MS) and Liquid Chromatography-Mass Spectrometry (LC-MS/MS) techniques. The results showed that 72% of the vegetable samples contained detectable levels of pesticide residues, with 21% exceeding the European Union Maximum Residue Levels (EU-MRLs) and 51% containing residues below the MRLs. The detected residues were primarily insecticides (56.4%) and fungicides (43.6%), with tomato and strawberry samples showing the highest frequency of both types of pesticides. Tomato also had the highest absolute intake from consumption (2.89 g/kg BW/day), followed by strawberries, peppers, and cucumbers (0.47, 0.159, and 0.096 g/kg BW/day, respectively). A hazard index (HI) was used to assess the dietary risk posed by the pesticide residues, with tomato having the highest contribution value. These findings highlight the need for Integrated Pest Management (IPM) programs to reduce the excessive use of pesticides, particularly in relation to raw food commodities. Action is required to minimize the unacceptable risks identified in this study.

Xenotransplantation, in its broadest sense, is the transplantation, implantation, or infusion of cells, tissues, or organs from one species to another. While there is a high demand for human tissues, cells, and organs for use in clinical transplantation, they are often in short supply. Recent scientific and biotechnological advancements, coupled with the scarcity of human allografts, have led to renewed interest in developing exploratory treatment strategies that use xenotransplantation products in human recipients. However, despite its potential benefits, the use of xenotransplantation is still limited due to various considerations, as discussed in this review of the past, present, and future directions of xenotransplantation. One of the key ethical concerns surrounding xenotransplantation is the potential impact on the animals from which the cells, tissues, or organs are obtained. As with genetic modification to fix genetic defects or prevent disease, the ideal outcome for these animals is that they will be better off as a result of the change. However, unless there are major changes in the way science is taught to incorporate ethics into recognized scientific theory and practice, these concerns will not be adequately addressed

Wheat is an important crop for global food security and a key crop for many developing countries. Thanks to next-generation sequencing (NGS) technologies, researchers can analyze the transcriptome of wheat and reveal differentially expressed genes (DEGs) responsible for essential agronomic traits and biotic stress tolerance. In addition, machine learning (ML) methods have opened new avenues to detect patterns in expression data and make predictions or decisions based on these patterns. We used both techniques to identify potential molecular markers in wheat associated with biotic stress in six gene expression studies conducted to investigate powdery mildew, blast fungus, rust, fly larval infection, greenbug aphid, and Stagonospora nodorum infections. A total of 24,152 threshold genes were collected from different studies, with the highest threshold being 7580 genes and the lowest being 1073 genes. The study identified several genes that were differentially expressed in all comparisons and genes that were present in only one data set. The study also discussed the possible role of certain genes in plant resistance. The Ta-TLP, HBP-1, WRKY, PPO, and glucan endo-1,3-beta-glucosidase genes were selected by the interpretable model-agnostic explanation algorithm as the most important genes known to play a significant role in resistance to biotic stress. Our results support the application of ML analysis in plant genomics and can help increase agricultural efficiency and production, leading to higher yields and more sustainable farming practices.

The recent pandemic that has hit the world has affected humanity in all aspects of life. Since the outbreak of this worldwide epidemic, a huge amount of data has been generated. In this article, we have provided a new simplified insight into the 2019 coronavirus disease (COVID-19) using the Pareto principle to highlight the main contributors to morbidity and mortality. A time series database of confirmed cumulative cases and deaths for all countries was processed from the Humanitarian Data Exchange website provided by the United Nations Office for the Coordination of Humanitarian Affairs. More than 85% of the incidents recorded worldwide were from the AMRO, EURO, and SEARO WHO regions, and the United States, Russia, and India were found to account for the largest proportion of cases and deaths in these affected areas. The application of Pareto analysis is useful in finding focus groups for further study and modeling

Inflammatory bowel diseases (IBDs), which primarily include Crohn's disease (CD) and ulcerative colitis (UC), are chronic recurrent diseases of the gastrointestinal tract with increasing prevalence and incidence worldwide. In this study, we aimed to identify key factor genes that control the progression of inflammatory bowel disease, identify common and unique nodal genes, examine gene-protein interactions, assess current advances in the published literature on inflammatory bowel disease, and examine the impact of various biological pathways. Gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database. We performed gene expression analysis to identify deferentially expressed genes. Subsequently, GO and KEGG pathway enrichment analyzes and protein-protein interaction network analyzes (PPI) of DEGs were performed. Text mining was used to examine the frequency of genes in the published IBD literature. Four GEO databases (GSE156044, GSE159751, GSE159008, and GSE102746) were downloaded from GEO databases. A total of 368 DEGs were identified. The results of GO term analysis showed that DEGs were mainly involved in the activity of cytokine receptors, integral components of the plasma membrane, and cytokine-mediated signaling. KEGG pathway analysis showed that DEGs were mainly enriched in bile secretion, mineral absorption, and cytokine-cytokine receptor interaction. The results of PPI analysis showed that about 10 genes were the key genes for the occurrence of CED. Text mining revealed the existence of 399 genes associated with CED. Our results suggest a possible link between CED and other diseases such as triple negative breast cancer (TNBC) and lung adenocarcinoma (LUAD), and provide new insights into the mechanisms of inflammatory bowel disease and new treatment targets.

In this review, it is discussed the prominent effect generated from aquaculture wastewater considered as the major water polluting crisis in the entire world. The cause rose due to intense development and improvement in aquaculture by the aquatic habitat species triggering quite a challenge in the environment. Scrutinizing this problem, researchers have found a way to tackle it by cultivating algal species in aquaculture wastewater in order to remove its high content of organic and inorganic pollutants. The theory proves wastewater serves as a nutrient source for algal growth and development such as phosphorous, nitrogen, and other trace elements. Besides harvesting the algal biomass from aquaculture wastewater, the extraction of lipid is also processed for biofuel production. Hence, the discussion includes conversion of wastewater into organic and inorganic pollutant-free water with low cost-effective method via algal cultivation in wastewater and high lipid yield for biofuel with a carbon-free and sustainable environment.

Chronic hepatitis C virus (HCV) and hepatocellular carcinoma (HCC) are common liver diseases that lead to death in Egypt, especially in men. The current study aimed to evaluate the diagnostic sensitivity of arginase (ARG) activity, alpha-1 antitrypsin (AAT), and alpha-fetoprotein (AFP) in the sera of patients with HCV (with & without viremia) and HCC. A total of 190 men classified as 40 healthy used as control (G1), 100 infected with HCV (subdivided into 50 with viremia (G2) and 50 without viremia (G3), and 50 with HCC (G4). The activity of ARG significantly decreased in HCV and HCC groups along with significant elevation in the level of AAT and AFP as compared with the control. Although a non-significant variation was scored in AST/ALT, significant differences were observed among AST/ARG and ARG/ALT in the pathogenic groups as compared with the healthy group. Moreover, significant variations in ARG, AAT, AFP, AST/ARG, and ARG/ALT were observed between viremia and non-viremia. Although AFP scored significant change among the viremia and HCC, the rest parameters scored non-significant changes between both groups. Furthermore, a receiver operating characteristic curve (ROC) showed the diagnostic ability for the selected parameters with high sensitivity and multiple linear regressions exhibited good associations between those parameters. These findings suggest the using possibility of ARG, AAT, and AFP in the diagnosis and/or follow-up of patients with HCV or HCC.

The purpose of this study was to provide more light on the effect of Qatada (Acacia hamulosa) honey from Saudi Arabia as a dressing on pilonidal sinus wound healing, antibacterial activity, and cytokine levels. The results revealed that the pH of 3.56 of tested honey, where glucose was 378 mmol/l also the specific gravity was 1.435, while contents of total phenolic and flavonoid and DPPH activity (32.15 mg GAE/100 g honey), (54.27 mg RE/100 g honey) and (127.83 mg/ml) respectively. The mean duration of pilonidal sinus wounds to be ready for surgical closure was 43.5 days in the control (standard dressing) group where the honey dressing group was 28.5 days. Less pain, edema, and foul-smelling discharge were expressed in the honey group if compared with the standard dressing group. The total bacterial count was 9 × 109 at the begging of the experiment then it reduced after the application of standard dressing traditional therapy to (9 ×105) and honey treatment group (9 ×102) after 21 days post-treatment. Significant reduction (p<0.05) was observed in serum TNFα(-52), IL6 - 46), and IL-17 (-60) relatively to pre-treatment values. Based on our findings, we may conclude that Qatada honey bioactivities aided wound healing by increasing tissue growth while decreasing overall bacterial count and inflammation.

The scope of this study was to investigate the presence of pathogenic bacteria in milk from female camels with mastitis and to select antibiotics for treatment with antibiotic susceptibility testing. A total of 40 milk samples taken from 20 dromedarian females, after application of CMT test and determination of SCC values, the camels were diagnosed with subclinical mastitis. Milk samples were inoculated into blood agar for identification of bacterial agents leading to mastitis. A total of 4 (12.5%) Staphylococcus aureus, 4 (12.5%) S. auricularis, 2 (6.25%) S. pettenkoperi, 2 (6.25%) S. cohnii spp. cohnii, 2 (6.25%) S. equorum, 2 (6.25%) S. capitis, 2 (6.25%) Streptococcus agalactiae, 2 (6.25%) S. dysgalactiae, 4 (12.5%) Escherichia coli, 2 (%) 6.25) Pseudomonas pseudalcaligenes, 2 (6.25%) Corynebacterium pseudotuberculosis, 2 (6.25%) Aerococcus viridans and 2 (6.25%) Gemella morbillorum were identified. Gram-positive bacteria were sensitive to Levofloxacin, Linezolid and Tetracycline and Daptomycin, resistant to Beta lactam-group antibiotics and macrolides. Vancomycin resistance was determined in S. aureus and S. cohnii spp. cohnii strains. Gram-negative strains are found generally susceptible to Cefepime and Pipersilin; resistant to Trimethoprim-sulfomethoxazole and Amoxicillin-Clavulanic acid. As a result, it is recommended to use antibiotic use to prevent the development of antimicrobial resistance as well as mastitis control methods such as the prevention of infection and monitoring the health status of the mammary of camels.

Melanoma is one of the most dangerous skin cancers in the world. It accounts for 55% of all deaths associated with skin cancer. Researchers believe that skin cancer increases the risk of other cancers if not diagnosed early. Therefore, prompt and timely diagnosis of this disease is very important for the successful treatment of the patient. This system can detect melanoma lethal carcinoma from other skin lesions without the need for surgery, with a low cost, accuracy of about 98.88% and specificity 99%. In this article, a new, intelligent and accurate software (Delphi) system has been used to diagnose melanoma skin cancer. To detect malignant melanoma, the ABCDT rule, asymmetry (A), boundary (B), color (C), diameter (D) and textural variation (T) of the lesion are calculated and finally, an artificial neural network (ANN) is used to obtain an accurate result. The ANN with Multi-Layer Perceptron (MLP) contains the five extraction Characteristics (ABCDT) of lesions is used as inputs, two hidden layers, and two outputs. Very good results were obtained using this method. It was observed that for a dataset of 180 dermoscopic lesion images including 80 malignant melanomas, 20 benign melanomas and 80 nevus lesions. Due to its automatic recognition and ability to be installed on a computer, this system can be very useful for dermatologists as well as the general public.