Novel Assignment of Gene Markers to Hematological and Immune Cells Based on Single-Cell Transcriptomics.

There are many different cells that perform highly specialized functions in the human hematological and immune systems. Due to the relevance of their activity, in this work we investigated the cell types and subtypes that form this complex system, using single-cell RNA sequencing (scRNA-seq) to dissect and assess the markers that best define each cell population. We first developed an optimized computational workflow for analyzing large scRNA-seq datasets.

Assessment of Humoral Response at SARS-CoV-2 Infection by Multipronged Functional Proteomics Approaches.

In the past decade, a major goal in biomedical research has been to understand why individuals differ in disease susceptibility, disease dynamics, and progression. In many pathologies, this variability stems from evolved immune mechanisms that resist inflammatory stress from various diseases that have been encountered throughout life. These may provide advantages against other diseases, reduce comorbidities, and enhance longevity.

Chronic Use of Benzodiazepine in Older Adults and Its Relationship with Dementia: A Systematic Review and Meta-Analysis.

Learning Objective: After participating in this CME activity, the psychiatrist should be better able to:• Explain current understanding of the relationship between chronic benzodiazepine use and dementia.

Background: Chronic use of benzodiazepines (BZ) for managing conditions such as anxiety disorders, depression, sleep disorders, and other chronic diseases is widespread; yet, there is considerable controversy regarding its potential links to dementia risk. This systematic review and meta-analysis aims to clarify this relationship by synthesizing and analyzing the available evidence to provide a clearer understanding of whether prolonged BZ use contributes to developing dementia.

Cross-species regulatory network analysis identifies FOXO1 as a driver of ovarian follicular recruitment.

The transcriptional regulation of gene expression in the latter stages of follicular development in laying hen ovarian follicles is not well understood. Although differentially expressed genes (DEGs) have been identified in pre-recruitment and pre-ovulatory stages, the master regulators driving these DEGs remain unknown. This study addresses this knowledge gap by utilizing Master Regulator Analysis (MRA) combined with the Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNe) for the first time in laying hen research to identify master regulators that are controlling DEGs in pre-recruitment and pre-ovulatory phases.