Purpose Polycystic ovary syndrome (PCOS) has a series of reproductive and metabolic consequences. Although the link between PCOS, IR, and obesity, their impact on the pathogenesis of PCOS has yet to be determined. Dysfunction of PI3K/AKT pathway has been reported as the main cause of IR in PCOS. This study purposed to explore the effects of selenium nanoparticles (SeNPs) alone and combined with metformin (MET) in a PCOS-IR rat model. Methods After 3 weeks of treatment with SeNPs and/or MET, biochemical analysis of glycemic & lipid profiles, and serum reproductive hormones was performed. Inflammatory, oxidative stress, and mitochondrial dysfunction markers were determined colormetrically. The expression of PI3K and Akt genes were evaluated by Real-time PCR. Histopathological examination and Immunohistochemical analysis of Ki-67 expression were performed. Results The results showed that treatment with SeNPs and/or MET significantly attenuated insulin sensitivity, lipid profile, sex hormones levels, inflammatory, oxidative stress and mitochondrial functions markers. Additionally, PI3K and Akt genes expression were significantly upregulated with improved ovarian histopathological changes. Conclusion Combined SeNPs and MET therapy could be potential therapeutic agent for PCOS-IR model via modulation of the PI3K/Akt pathway, enhancing anti-inflammatory and anti-oxidant properties and altered mitochondrial functions. Highlights The strong relationship between obesity, insulin resistance, and polycystic ovarian syndrome. Disturbance of the PI3K/Akt signaling pathway is involved in the progression of polycystic ovary syndrome-insulin resistance (PCOS-IR). In PCOS-IR rats, combined SeNPs and metformin therapy considerably alleviated IR by acting on the PI3K/Akt signaling pathway. The combination of SeNPs and metformin clearly repaired ovarian polycystic pathogenesis and improved hormonal imbalance in PCOS-IR rats.
Chemoinformatics involves integrating the principles of physical chemistry with computer-based and information science methodologies, commonly referred to as “in silico techniques”, in order to address a wide range of descriptive and prescriptive chemistry issues, including applications to biology, drug discovery, and related molecular areas. On the other hand, the incorporation of machine learning has been considered of high importance in the field of drug design, enabling the extraction of chemical data from enormous compound databases to develop drugs endowed with significant biological features. The present review discusses the field of cheminformatics and proposes the use of virtual chemical libraries in virtual screening methods to increase the probability of discovering novel hit chemicals. The virtual libraries address the need to increase the quality of the compounds as well as discover promising ones. On the other hand, various applications of bioinformatics in disease classification, diagnosis, and identification of multidrug-resistant organisms were discussed. The use of ensemble models and brute-force feature selection methodology has resulted in high accuracy rates for heart disease and COVID-19 diagnosis, along with the role of special formulations for targeting meningitis and Alzheimer’s disease. Additionally, the correlation between genomic variations and disease states such as obesity and chronic progressive external ophthalmoplegia, the investigation of the antibacterial activity of pyrazole and benzimidazole-based compounds against resistant microorganisms, and its applications in chemoinformatics for the prediction of drug properties and toxicity—all the previously mentioned—were presented in the current review.
Chemoinformatics is the combination of physical chemistry theory with computer and information science techniques "in silico techniques" to a variety of descriptive and prescriptive chemistry issues, including applications to biology, drug discovery, and related molecular areas. On the other hand, machine learning has become a vital tool for drug designers to mine chemical information from enormous compound databases in order to build medications with important biological features. In Egypt, chemoinformatics were used recently in different applications. For example; the development of new antimicrobial agents like tetracycline analog B (Iodocycline). Another area of application in bioinformatics included heart disease classification based on hybrid ensemble stacking technique. In the era of COVID-19, hybrid approach for COVID-19 detection from chest radiography was applied. Furthermore, bio/chemoinformatics methods were used to compare antimicrobial medications in order to choose an effective nose-to-brain formulation targeting meningitis infection by using differences in the drugs' primary structural, topological, and electronic characteristics. An example for this included cefotaxime and ceftriaxone that were examined at three levels: at formulation level, by comparing the loading in gelatin and tripalmitin matrices as basis for the production of nanoparticulate systems, at biopharmaceutical level, through interaction with mucin and the P-gp efflux pumps, and at therapeutic level, through studying the interaction with S. pneumoniae bacterial receptors.
Nutrigenomics is the study of the interaction of nutrition and genes, focusing on the influence of nutrients on the genome, proteome, and metabolome, and how nutrition affects human health. In the context of nutrigenomics, bioactive components are dietary ingredients that may transmit information from the external environment and alter gene expression in the cell, and hence the overall function of the organism. It is critical to consider food not only as a source of energy and essential nutrients necessary for life and growth, but also as a factor impacting health/disease, biochemical processes, biochemical pathway activation and affecting the diversity of the gut microbiome. Antimicrobial resistance in pathogenic and commensal microorganisms has emerged as a major public health concern due to emerging antimicrobial resistance genes in E. coli isolates from pig, cattle, chicken, and turkey meat, against tetracycline, streptomycin, and sulfonamides. Also, Salmonella spp. and Campylobacter spp. have shown antibiotic resistance at farms and slaughterhouses, and in animal-based food products. A correlation has been proven between a critical nutrient-responsive signaling system and catabolite control of gene expression, and a two-component signaling system that drives antibiotic resistance in E. faecalis, revealing a previously unknown integration between the nutritional status of the cell and intrinsic antibiotic resistance. Moreover, different nutrigenomic approaches can be applied to mitigate possible emergence of antimicrobial resistance against novel antibiotics. However, little progress has been achieved in converting nutrigenomics information into clinical advice, so far.
Background: Total laparoscopic hysterectomy (TLH) is a feasible, efficient way to manage benign uterine pathology, and is better than standard abdominal hysterectomy as it offers less postoperative discomfort, shorter hospitalization, rapid recovery, and early return to daily living activities.Methods: A retrospective comparative cohort study was done on patients with abnormal uterine bleeding due to large myomas in the Department of Obstetrics and Gynecology, Tanta University Hospital, Tanta, Egypt, and Institute of Obstetrics and Gynecology, Cagliari University, Cagliari, Italy. Participants were classified into two groups. Group I (Laparoscopy group) included 20 patients for whom TLH was done. Group II (Laparotomy group) included 20 patients for whom open hysterectomy (OH) was done.Results: Our result revealed that statistically significant differences were observed between the studied groups in post-operative Hb value, postoperative return of bowel sounds, and amount of blood loss however, prolonged duration of surgery was noticed in laparoscopic group than laparotomy group.Conclusions: TLH is an accessible technique and an alternative to laparotomy when it was done by experienced surgeons for large uteri regardless of the site, size.
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