Objective: Although various studies have linked environmental toxins, mumps infections, alcohol consumption, and abnormal body mass index (BMI) to impaired semen quality, the precise causes of infertility remain unclear. This study investigates the impact of BMI on oxidative stress markers in semen analysis among infertile men, illuminating the role of oxidative stress in cases of unexplained infertility. Methods: In this cross-sectional study, 280 patients exhibiting infertility symptoms were recruited. Comprehensive semen analysis was conducted, evaluating reactive oxygen species (ROS) levels, sperm plasma membrane lipid peroxidation via flow cytometry, total antioxidant capacity (TAC), and results from the sperm chromatin structure assay. Participants were categorized based on their BMI, facilitating comparisons between obese and non-obese individuals. Results: Both BMI and age significantly influenced male fertility, particularly in obese individuals. Strong correlations were identified between elevated BMI, increased ROS levels, and decreased TAC. The obese infertile group exhibited substantially lower TAC compared to controls, highlighting obesity's detrimental effect on antioxidant defenses. Furthermore, significant reductions in sperm count, motility, and normal morphology were observed, alongside an increase in non-motile sperm. These outcomes demonstrate the complex relationship among oxidative stress, BMI, and fertility, emphasizing the necessity for targeted interventions addressing obesity's effects on reproductive health. Conclusion This study underscores the importance of managing obesity and understanding its impact on oxidative stress as essential components in improving reproductive outcomes among affected men.

Objectives: Heart failure (HF) is a common disease with a high hospital readmission rate. This study considered class imbalance and missing data, which are two common issues in medical data. The current study’s main goal was to compare the performance of six machine learning (ML) methods for predicting hospital readmission in HF patients. Methods: In this retrospective cohort study, information of 1,856 HF patients was analyzed. These patients were hospitalized in Farshchian Heart Center in Hamadan Province in Western Iran, from October 2015 to July 2019. The support vector machine (SVM), least-square SVM (LS-SVM), bagging, random forest (RF), AdaBoost, and naïve Bayes (NB) methods were used to predict hospital readmission. These methods’ performance was evaluated using sensitivity, specificity, positive predictive value, negative predictive value, and accuracy. Two imputation methods were also used to deal with missing data. Results: Of the 1,856 HF patients, 29.9% had at least one hospital readmission. Among the ML methods, LS-SVM performed the worst, with accuracy in the range of 0.57–0.60, while RF performed the best, with the highest accuracy (range, 0.90–0.91). Other ML methods showed relatively good performance, with accuracy exceeding 0.84 in the test datasets. Furthermore, the performance of the SVM and LS-SVM methods in terms of accuracy was higher with the multiple imputation method than with the median imputation method. Conclusions This study showed that RF performed better, in terms of accuracy, than other methods for predicting hospital readmission in HF patients.

Background: Wide use of biocidal agents such as benzalkonium chloride (BCC) and chlorhexidine digluconate (CHX) in hospitals and non-hospital environments, has raised concerns over the emergence of non-susceptible strains. Efflux pumps are of known main mechanisms in biocide tolerance which have been rarely addressed in enterococci - members of gut microbiota which can cause serious problems particularly in hospitalized patients. The purpose of this study was to investigate the susceptibility of enterococci from different sources (clinical and fecal isolates) toward BCC and CHX, and its correlation with efflux associated genes. Also, possible link between biocide tolerance and antibiotic resistance was examined. Materials and Methods: One hundred and four enterococcus isolates including clinical (n = 54) and fecal isolates (n = 50) were studied for susceptibility toward BCC, CHX, ciprofloxacin, gentamicin and vancomycin. Twelve efflux associated genes were investigated by polymerase chain reaction assay. Results: In clinical isolates, reduced susceptibility to CHX and resistance to gentamicin and ciprofloxacin were significantly higher than fecal isolates. Vancomycin resistance was associated with increasing minimum inhibitory concentration of CHX. Among all investigated genes, only three ones, efrA, efrB and emeA were detected which were significantly associated with reduced susceptibility to CHX and were more frequent among clinical isolates. Also, high level resistance to gentamicin was significantly associated with the presence of efrA/B as well as with reduced susceptibility to CHX. Conclusion As expected, reduced susceptibility to CHX, was significantly higher in clinical isolates. However, the presence of a vancomycin-resistant enterococci among fecal isolates of healthy people which showed resistance/tolerance to studied antimicrobial agents, was unexpected and highlights the need to investigate other non-hospital environments to avoid dissemination of antimicrobial resistance. Correlation between reduced susceptibility to CHX and high level resistance to gentamicin, substantiates monitoring of biocide tolerance particularly in the healthcare settings to control the establishment of antimicrobial resistant strains.

BACKGROUND: In this study, the expression of interleukin-9 (IL-9), IL-17, IL-22, and IL-25 genes that might be the potential predisposing factors for asthma as well as count of innate lymphoid cells (ILCs) as another source of inflammatory cytokines have been evaluated. OBJECTIVE: The aim of this study was to evaluate the expression of newly identified helper T cells signature cytokines and amount of ILCs. METHODS: Blood and sputum samples from 23 patients with moderate to severe asthma and 23 healthy volunteers were collected. The types of allergens to which our patients were sensitive were defined using immunoblotting method. Gene expression of studied cytokines was evaluated using quantitative transcription-polymerase chain reaction and ILCs were counted by the flow cytometry method. RESULTS: In this research, the gene expressions of IL-9, IL-17, IL-22, and IL-25 were significantly higher in asthmatics, especially in the severe form of the disease. This increase was even higher in serum samples compared with sputum samples. Counting ILCs revealed their increase in comparison with normal people. CONCLUSION: We showed the importance of IL-25, IL-22, IL-17, and IL-9 cytokines in patients with asthma as their expression levels are increased and these increase are correlated with the severity of the disease. We also showed that the increased amount of ILCs in asthmatics could confirm their potential role in the immunopathogenesis of asthma as another source of inflammatory cytokines.
Allergens ; Asthma ; Causality ; Cytokines ; Flow Cytometry ; Gene Expression ; Healthy Volunteers ; Humans ; Immunoblotting ; Interleukin-17 ; Interleukin-9 ; Lymphocytes ; Methods ; Sputum ; T-Lymphocytes, Helper-Inducer