Disparities in disaster healthcare: A review through a pandemic lens.

Objective: To provide an overview of the literature on the impact of the coronavirus disease 2019 (COVID-19) pandemic on healthcare disparities in various groups, in relation to social determinants of health (SDOH) and longstanding social disparities.

Design: The Disaster Preparedness and Response Committee of the American College of Emergency Physicians (ACEP) addressed the impact of health disparities in disaster planning and response. A workgroup composed of seven physicians with academic and deployment disaster medicine experience was formed.

Suppression of Huntington's Disease Somatic Instability by Transcriptional Repression and Direct CAG Repeat Binding.

Huntington's disease (HD) arises from a CAG expansion in the () gene beyond a critical threshold. A major thrust of current HD therapeutic development is lowering levels of mutant mRNA (m) and protein (mHTT) with the aim of reducing the toxicity of these product(s). Human genetic data also support a key role for somatic instability (SI) in 's CAG repeat - whereby it lengthens with age in specific somatic cell types - as a key driver of age of motor dysfunction onset.

Effects of High Amylose-Resistant Starch on Gut Microbiota and Uremic Toxin Levels in Patients With Stage-G3a-G4 Chronic Kidney Disease: A Randomized Trial.

Objective: This study was designed to determine the effect of 16 weeks of supplementation with Hi-maize 260 resistant starch (RS) on the gut microbiota, uremic toxins (indoxyl sulfate and p-cresyl sulfate [PCS]), markers of inflammation, and oxidative stress along with vascular function in patients with stage G3a-G4 chronic kidney disease (CKD).

Design And Methods: This was a double-blind, placebo-controlled, parallel-arm, randomized controlled trial. Sixty-eight patients with stage-G3a-G4 CKD were randomized to either RS with usual care or placebo and usual care.

Evaluation of Machine Learning Classification Models for False-Positive Reduction in Prostate Cancer Detection Using MRI Data.

In this work, several machine learning (ML) algorithms, both classical ML and modern deep learning, were investigated for their ability to improve the performance of a pipeline for the segmentation and classification of prostate lesions using MRI data. The algorithms were used to perform a binary classification of benign and malignant tissue visible in MRI sequences. The model choices include support vector machines (SVMs), random decision forests (RDFs), and multi-layer perceptrons (MLPs), along with radiomic features that are reduced by applying PCA or mRMR feature selection.

Population structure and pathogen interaction of Escherichia coli in freshwater: Implications of land-use for water quality and public health in Aotearoa New Zealand.

Freshwater samples (n = 199) were obtained from 41 sites with contrasting land-uses (avian, low impact, dairy, urban, sheep and beef, and mixed sheep, beef and dairy) and the E. coli phylotype of 3980 isolates (20 per water sample enrichment) was determined. Eight phylotypes were identified with B1 (48.