Multilayer Analysis of RNA Sequencing Data in Alzheimer's Disease to Unravel Molecular Mysteries.

Alzheimer's disease (AD) is a complex disease, and numerous cellular events may be involved in etiology. RNAseq-based transcriptome data hold multilayer information content, which could be crucial in unraveling molecular mysteries of AD. It enables quantification of gene expression levels, identification of genomic variants, and elucidation of splicing anomalies such as exon skipping and intron retention.

Integration of genomic and transcriptomic layers in RNA-Seq data leads to protein interaction modules with improved Alzheimer's disease associations.

Alzheimer's disease (AD) is the most common neurodegenerative disease, and it is currently untreatable. RNA sequencing (RNA-Seq) is commonly used in the literature to identify AD-associated molecular mechanisms by analysing changes in gene expression. RNA-Seq data can also be used to detect genomic variants, enabling the identification of the genes with a higher load of deleterious variants in patients compared with controls.

Is It Necessary to Endoscopically Evaluate the Anastomosis in Robotic or Laparoscopic Surgical Procedures for Colorectal Cancer?

In the surgical treatment of colorectal cancers, disease-free survival and life expectancy are inversely proportional to the increase in complications. We evaluated the superiority of colonoscopy and air and water tests in detecting anastomotic leaks in sigmoid and rectosigmoid junction colon cancers. Data of patients who underwent robotic/laparoscopic surgical procedures for sigmoid and rectosigmoid junctional colon cancers at a single center between January 2018 and February 24 were retrospectively evaluated.

Comparative Proteomics Highlights that GenX Exposure Leads to Metabolic Defects and Inflammation in Astrocytes.

Exposure to PFAS such as GenX (HFPO dimer acid) has become increasingly common due to the replacement of older generation PFAS in manufacturing processes. While neurodegenerative and developmental effects of legacy PFAS exposure have been studied in depth, there is a limited understanding specific to the effects of GenX exposure. To investigate the effects of GenX exposure, we exposed to GenX and assessed the motor behavior and performed quantitative proteomics of fly brains to identify molecular changes in the brain.

A benchmark of RNA-seq data normalization methods for transcriptome mapping on human genome-scale metabolic networks.

Genome-scale metabolic models (GEMs) cover the entire list of metabolic genes in an organism and associated reactions, in a tissue/condition non-specific manner. RNA-seq provides crucial information to make the GEMs condition-specific. Integrative Metabolic Analysis Tool (iMAT) and Integrative Network Inference for Tissues (INIT) are the two most popular algorithms to create condition-specific GEMs from human transcriptome data.