Estimating the contribution of early and late noise in vision from psychophysical data.

Human performance in psychophysical detection and discrimination tasks is limited by inner noise. It is unclear to what extent this inner noise arises from early noise (e.g.

Contribution of Video Directly Observed Therapy (VDOT) to Tuberculosis Treatment in Brazil.

Directly Observed Treatment (DOT) involves the administration of medication and in-person monitoring by a healthcare team alongside the patient to improve adherence to tuberculosis (TB) treatment. Implementing DOT requires healthcare professionals, transportation, time dedication, and presence at the patient's residence. Meeting all these conditions is not always possible to address the high demand of TB patients who would benefit from this supervision.

Functional analysis of conserved C. elegans bHLH family members uncovers lifespan control by a peptidergic hub neuron.

Throughout the animal kingdom, several members of the basic helix-loop-helix (bHLH) family act as proneural genes during early steps of nervous system development. Roles of bHLH genes in specifying terminal differentiation of postmitotic neurons have been less extensively studied. We analyze here the function of 5 Caenorhabditis elegans bHLH genes, falling into 3 phylogenetically conserved subfamilies, which are continuously expressed in a very small number of postmitotic neurons in the central nervous system.

Exploring social determinants and hepatocellular carcinoma: a scoping review of evidence and implications.

Background: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths worldwide. Social determinants of health (SDH) significantly impact HCC outcomes, yet comprehensive insights into these effects are lacking. This scoping review aimed to examine the influence of SDH on HCC outcomes.

Development and Content Analysis Protocol for Evaluating Artificial Intelligence in Drug-Related Information.

Introduction: Artificial intelligence (AI) has significant transformative potential across various sectors, particularly in health care. This study aims to develop a protocol for the content analysis of a method designed to assess AI applications in drug-related information, specifically focusing on contraindications, adverse reactions, and drug interactions. By addressing existing challenges, this preliminary research seeks to enhance the safe and reliable integration of AI into healthcare practices.