Non–small cell lung cancer (NSCLC) is an important cause of cancer-associated deaths worldwide. Therefore, the exact molecular mechanisms of NSCLC are unidentified. The present investigation aims to identify the miRNAs with predictive value in NSCLC. The two datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed miRNAs (DEmiRNA) and mRNAs (DEmRNA) were selected from the normalized data. Next, miRNA-mRNA interactions were determined. Then, co-expression network analysis was completed using the WGCNA package in R software. The co-expression network between DEmiRNAs and DEmRNAs was calculated to prioritize the miRNAs. Next, the enrichment analysis was performed for DEmiRNA and DEmRNA. Finally, the drug-gene interaction network was constructed by importing the gene list to dgidb database. A total of 3,033 differentially expressed genes and 58 DE miRNA were recognized from two datasets. The co-expression network analysis was utilized to build a gene co-expression network. Next, four modules were selected based on the Zsummary score. In the next step, a bipartite miRNA-gene network was constructed and hub miRNAs (let-7a-2-3p, let-7d-5p, let-7b-5p, let-7a-5p, and let-7b-3p) were selected. Finally, a drug-gene network was constructed while SUNITINIB, MEDROXYPROGESTERONE ACETATE, DOFETILIDE, HALOPERIDOL, and CALCITRIOL drugs were recognized as a beneficial drug in NSCLC. The hub miRNAs and repurposed drugs may act a vital role in NSCLC progression and treatment, respectively; however, these results must validate in further clinical and experimental assessments.

BACKGROUND: In peritoneal dialysis, technique failure is an important metric to be considered. This study was performed in order to identify the relationship between trajectories of serum albumin levels and peritoneal dialysis technique failure on end-stage renal disease patients according to diabetic status. Furthermore, this study was performed to reveal predictors of serum albumin and technique failure simultaneously. METHODS: This retrospective cohort study included 300 (189 non-diabetic and 111 diabetic) end-stage renal disease patients on continuous ambulatory peritoneal dialysis treated in Al-Zahra Hospital, Isfahan, Iran, from May 2005 to March 2015. Bayesian joint modeling was carried out in order to determine the relationship between trajectories of serum albumin levels and peritoneal dialysis technique failure in the patients according to diabetic status. Death from all causes was considered as a competing risk. RESULTS: Using joint modeling approach, a relationship between trajectories of serum albumin with hazard of transfer to hemodialysis was estimated as −0.720 (95% confidence interval [CI], −0.971 to −0.472) for diabetic and −0.784 (95% CI, −0.963 to −0.587) for non-diabetic patients. From our findings it was showed that predictors of low serum albumin over time were time on peritoneal dialysis for diabetic patients and increase in age and time on peritoneal dialysis, history of previous hemodialysis, and lower body mass index in non-diabetic patients. CONCLUSION: The results of current study showed that controlling serum albumin over time in non-diabetic and diabetic patients undergoing continuous ambulatory peritoneal dialysis treatment can decrease risk of adverse outcomes during the peritoneal dialysis period.
Body Mass Index ; Cohort Studies ; Humans ; Iran ; Joints* ; Kidney Failure, Chronic ; Peritoneal Dialysis* ; Peritoneal Dialysis, Continuous Ambulatory ; Renal Dialysis ; Retrospective Studies ; Serum Albumin*

Objectives: Widespread use of β-lactam antibiotics could cause resistance to this group of antibiotics in pathogenic bacteria through the production of the enzyme β-lactamases. The aim of this study is to determine the molecular detection of AmpC β-lactamases among clinical Escherichia coli isolated from Ilam hospitals in Ilam, Iran. Methods: One hundred and twelve clinical isolates of E. coli were collected from hospitalized patients and were identified by biochemical tests. They were evaluated for extended spectrum beta-lactamases (ESBLs) production, and the positive strains were subjected to AmpC enzymes; for detection of AmpC cluster genes, multiplex polymerase chain reaction was applied. Results: The analysis showed 62.5% of isolates were ESBLs positive and that five strains revealed the AmpC cluster genes. This is the first report of FOXM cluster genes in E. coli in Iran. Conclusion Based on our results, the prevalence of AmpC β-lactamases is increasing in Iran, which caused failure in antibiotic therapy. So, the current study recommended the revision of antibiotic policy in Iranian hospitals.