Extracorporeal Membrane Oxygenation in Children with Pulmonary Atresia and Intact Ventricular Septum: Mortality and Associated Outcomes.

Data on outcomes of extracorporeal membrane oxygenation (ECMO) are limited in patients with pulmonary atresia intact ventricular septum (PAIVS). The objective of this study was to describe the use of ECMO and the associated outcomes in patients with PAIVS. We retrospectively reviewed neonates with PAIVS who received ECMO between 2009 and 2019 in 19 US hospitals affiliated with the Collaborative Research for the Pediatric Cardiac Intensive Care Society (CoRe-PCICS).

The mediating role of processing speed on the relationship between executive functions and social cognition in relapsing-remitting multiple sclerosis patients.

This study examined the mediating role of processing speed between executive functions and social cognition in 67 relapsing-remitting multiple sclerosis (RRMS) patients. Executive functions were assessed using the Trail Making Test-Part B (TMT-B) and the Stroop Neuropsychological Screening Test (SNST); social cognition with the Reading the Mind in the Eyes Test (RMET); and processing speed with the Symbol Digit Modalities Test (SDMT). Mediated effects were explored using a series of regression analyses and were further confirmed through bootstrapping procedures.

BioTextQuest v2.0: An evolved tool for biomedical literature mining and concept discovery.

The process of navigating through the landscape of biomedical literature and performing searches or combining them with bioinformatics analyses can be daunting, considering the exponential growth of scientific corpora and the plethora of tools designed to mine PubMed(®) and related repositories. Herein, we present BioTextQuest v2.0, a tool for biomedical literature mining.

scRNA-Explorer: An End-user Online Tool for Single Cell RNA-seq Data Analysis Featuring Gene Correlation and Data Filtering.

In the majority of downstream analysis pipelines for single-cell RNA sequencing (scRNA-seq), techniques like dimensionality reduction and feature selection are employed to address the problem of high-dimensional nature of the data. These approaches involve mapping the data onto a lower-dimensional space, eliminating less informative genes, and pinpointing the most pertinent features. This process ultimately leads to a reduction in the number of dimensions used for downstream analysis, which in turn speeds up the computation of large-scale scRNA-seq data.