Mood and anxiety disorders, including major depressive disorder (MDD), bipolar disorder (BD), and anxiety disorders, affect millions worldwide and pose sig

The low survival rate of Kidney renal clear cell carcinoma (KIRC) patients is largely attributed to cisplatin resistance. Rather than focusing solely on individual proteins, exploring protein-protein interactions could offer greater insight into drug resistance. To this end, a series of in silico and in vitro experiments were conducted to identify hub genes in the intricate network of cisplatin resistance-related genes in KIRC chemotherapy. The genes involved in cisplatin resistance across KIRC were retrieved from the National Center for Biotechnology Information (NCBI) database using search terms as “Kidney renal clear cell carcinoma” and “Cisplatin resistance”. The genes retrieved were analyzed for hub gene identification using the STRING database and Cytoscape tool. Expression and promoter methylation profiling of the hub genes was done using UALCAN, GEPIA, OncoDB, and HPA databases. Mutational, survival, functional enrichment, immune cell infiltration, and drug prediction analyses of the hub genes were performed using the cBioPortal, GEPIA, GSEA, TIMER, and DrugBank databases. Lastly, expression and methylation levels of the hub genes were validated on two cisplatin-resistant RCC cell lines (786-O and A-498) and a normal renal tubular epithelial cell line (HK-2) using two high throughput techniques, including targeted bisulfite sequencing (bisulfite-seq) and RT-qPCR. A total of 124 genes were identified as being associated with cisplatin resistance in KIRC. Out of these genes, MCL1, IGF1R, CCND1, and PTEN were identified as hub genes and were found to have significant (p < 0.05) variations in their mRNA and protein expressions and effects on the overall survival (OS) of the KIRC patients. Moreover, an aberrant promoter methylation pattern was found to be associated with the dysregulation of the hub genes. In addition to this, hub genes were also linked with different cisplatin resistance-causing pathways. Thus, hub genes can be targeted with Alvocidib, Estradiol, Tretinoin, Capsaicin, Dronabinol, Metribolone, Calcitriol, Acetaminophen, Acitretin, Cyclosporine, Azacitidine, Genistein, and Resveratrol drugs. As the pathogenesis of KIRC is complex, targeting hub genes and associated pathways involved in cisplatin resistance could bring a milestone change in the drug discovery and management of drug resistance, which might uplift overall survival among KIRC patients.

Dera Ismail Khan, Khyber Pakhtunkhwa province was deeply affected by the massive floods of July and August 2022. These unprecedented floods not only threatened human lives at national scale but also caused unprecedented damage to livestock, agriculture, forests, and wildlife, while the destruction of infrastructure is incalculable. These floods resulted in total crop loss in most the cases and death of animal herds. The fluctuations in monsoon patterns due to erratic climate changes additionally alarm the future scenarios of peak pest infestations and heat stress. Some crops i.e., cotton (quantity and quality) were partially affected, and sugar cane, rice, and other types of seeds were most used as adaptation options. Inaccessibility, lack of awareness, expertise and baseline information of the natural resources-livelihood nexus, no organization has considered the damage caused to natural forests, wildlife, rangelands, and aquatic flora and fauna. The floods have directly devastated natural resources and the environment in several ways i.e., flushing out of forests, the carnage of wildlife and the destruction of native aquatic fauna. The post-flood scenarios are the spread of exotic flora and fauna, the spreading of epidemic diseases, and the destruction of habitats. Eventually, natural resources must bear the brunt of the damage caused by the flood in one form or another which ranges from extracting timber, firewood, and fodder to earning a livelihood from forest sales. The farming community of D.I. Khan have been gravely affected by the flood, altering cropping patterns, and ultimately impacting the market economy of agricultural-based economies shortly.

Introduction: The underlying mechanisms of gastric cancer (GC) remain unknown. Therefore, in this study, we employed a comprehensive approach, combining computational and experimental methods, to identify potential key genes and unveil the underlying pathogenesis and prognosis of GC. Methods: Gene expression profiles from GEO databases (GSE118916, GSE79973, and GSE29272) were analyzed to identify DEGs between GC and normal tissues. A PPI network was constructed using STRING and Cytoscape, followed by hub gene identification with CytoHubba. Investigations included expression and promoter methylation analysis, survival modeling, mutational and miRNA analysis, gene enrichment, drug prediction, and in vitro assays for cellular behaviors. Results: A total of 83 DEGs were identified in the three datasets, comprising 41 up-regulated genes and 42 down-regulated genes. Utilizing the degree and MCC methods, we identified four hub genes that were hypomethylated and up-regulated: COL1A1, COL1A2, COL3A1, and FN1. Subsequent validation of their expression and promoter methylation on clinical GC samples through targeted bisulfite sequencing and RT-qPCR analysis further confirmed the hypomethylation and overexpression of these genes in local GC patients. Furthermore, it was observed that these hub genes regulate tumor proliferation and metastasis in in vivo and exhibited mutations in GC patients. Conclusion: We found four potential diagnostic and prognostic biomarkers, including COL1A1, COL1A2, COL3A1, and FN1 that may be involved in the occurrence and progression of GC.