Introduction:
Radical cystectomy plays the main role in the treatment of muscle-invasive and high-grade bladder cancers; however, it still has significant rates of perioperative complications and mortality. The risk of complications is higher in elderly patients with multiple comorbidities. In certain patients, due to simultaneous comorbidities, it becomes challenging to perform long-term orthotopic radical cystectomy surgery.Keywords: Urinary diversion, Hematuria, Bladder Cancer, Cystectomy
Link: https://brieflands.com/articles/ijcm-146426
Identification of miRNA-Target Gene-Transcription Factor Regulatory Network as Functional Motifs Involved in Glomerular Diabetic Nephropathy
Abstract
The gene regulatory approach based on retrieving information from the database provides a detailed characterization of the molecular mechanisms of disease progression at the level of miRNAs, Transcription Factors (TFs), and genes. Moreover, gene regulatory networks can find an interaction between the miRNAs, TFs, and genes involved in diabetic nephropathy (DN), but the underlying mechanisms of motif remain unclear. We first gathered genes related to glomeruli diabetic nephropathy from GEO and CTD database. Besides, miRNAs targeting genes were collected from the public databases and GEO. Furthermore, regulator TFs were accumulated from related public databases. After that, we explored the regulatory relationships between TF-miRNA, miRNA-Gene, TF-Gene, and miRNA–TF using FANMOD software. Finally, a gene regulatory network consisting of miRNAs, genes, and TFs was constructed, helping the Cytoscape. The global const parameter in FANMOD software used to discover the interaction between miRNAs, genes, TFs, and 3-node regulatory motif types were detected in the resulting network. Among them, it led to the discovery of the two-node feedback motif (2FB) in charge of the up-regulation of miRNA-target gene-TF and TF-mediated cascade motif and co-pointing motif (COP) responsible for the down-regulation of miRNA-target gene–TF. In this study, we found a correlation between miRNAs, TFs, and target genes using a gene regulatory network. We revealed the candidate 3-node motifs associated with the progression of DN. Therefore, detected molecular mechanisms, as well as the relationship between previous studies, demonstrated targets that can help in the discovery of a novel treatment for DN.
Keywords: diabetic nephropathy ,transcription factor , miRNA, motif ,gene regulatory network
Link: https://link.springer.com/
TNF-α, and TNFRs in gastrointestinal cancers
Abstract
Unmet Needs, Pain, Shame, Regret, and Loss of Identity among Men with Urethral Injuries Resulting from Traffic Accidents; A Qualitative Study
Introduction
Urethral injuries are the most severe injuries caused by high-energy mechanisms such as traffic accidents, which have significant long-term serious consequences on the quality of life of the injured.
Objectives
Exploration of lived experiences of urethral injury in traffic accident victims is the main goal of this study.
Keywords: Injury, Qualitative study, Traffic accident, Trauma
Link: https://link.springer.com/article/10.1007/s11136-024-03862-2
Unraveling Cancer Progression in Oral Squamous Cell Carcinoma through Regulatory Network Analysis; miRNA-Target Gene Interaction
Abstract
Dysregulation of microRNAs (miRs) plays an essential role in tumor progression of oral squamous cell carcinoma (OSCC) through altering target genes’ function and expression. This study aims to investigate the regulatory network of the miR-target gene involved in cancer progression to find key miRs and target genes. We used OSCC transcriptomic data obtained from GSE28100. To find the critical target genes shared between the miRs, we used miRecord and mirTarBase databases and analyzed the regulatory of miR-target genes using network analysis by Cytoscape. We selected 11 miRs and assessed their expression with qRT-PCR in 10 OSCC tissue samples compared to normal oral tissues. UACLAN database was applied to find the expression of these 11 miRs and their overall survival in OSCC. We found that eight miRNAs were upregulated, and three of them were down-regulated. The highest expression level belonged to miR-10b. The other up-regulated microRNAs were miR-196a, miR-103, miR-21, miR-31, miR-494, miR-9 and miR-200c. Three miRs that were downregulated are miR-195, miR-133a, and miR-221. Expression data of the UACLAN database confirmed the transcriptomic data. The miR-target gene network of 11 miRs released some crucial molecules, including miR-21, miR-9, miR-196a, miR-221, miR-133a, CDK6, ZEB1, MYC, E2F3, RHOA, SP1, and CCND1. Our analysis showed that miRNAs can be suggested as potential biomarkers for prognosis and predicting the OSCC progression.
Link: https://link.springer.com/article/10.1134/S0026893324060025