Alzheimer's disease (AD) is a neurodegenerative disorder characterized by cognitive decline and progressive neuronal damage. Recent research has highlighted the significant roles of the gut microbiota and microRNAs (miRNAs) in the pathogenesis of AD. This review explores the intricate interaction between gut microbiota and miRNAs, emphasizing their combined impact on Alzheimer's progression.
View Article and Find Full Text PDFHigher prevalence of inappropriate medication use among cancer patients increases risk of drug-related problems(DRP) like drug-drug interactions, ADR, and non-adherence. Potentially inappropriate medication (PIM) and Potential Prescription Omission (PPO) were identified using Screening Tool of Older Person's Prescriptions (STOPP) and Screening Tool to Alert Doctors to the Right Treatment (START) criteria. The study objective was to optimize prescriptions for the elderly by analyzing the impact of medication review.
View Article and Find Full Text PDFObjectives: Vasopressin is used for shock and acute pulmonary hypertension in the neonatal intensive care unit (NICU) and is associated with hyponatremia. The purpose of this study was to determine the incidence, severity, contributing risk factors associated with vasopressin-induced hyponatremia in neonates and infants <3 months of age in the NICU. The primary objective was to determine the incidence of hyponatremia (<130 mEq/L) and severe hyponatremia (<125 mEq/L).
View Article and Find Full Text PDFMitochondria, essential organelles responsible for cellular energy production, emerge as a key factor in the pathogenesis of neurodegenerative disorders. This review explores advancements in mitochondrial biology studies that highlight the pivotal connection between mitochondrial dysfunctions and neurological conditions such as Alzheimer's, Parkinson's, Huntington's, ischemic stroke, and vascular dementia. Mitochondrial DNA mutations, impaired dynamics, and disruptions in the ETC contribute to compromised energy production and heightened oxidative stress.
View Article and Find Full Text PDFObjective: The aim of our research is to enhance the calibration of machine learning models for glaucoma classification through a specialized loss function named Confidence-Calibrated Label Smoothing (CC-LS) loss. This approach is specifically designed to refine model calibration without compromising accuracy by integrating label smoothing and confidence penalty techniques, tailored to the specifics of glaucoma detection.
Design: This study focuses on the development and evaluation of a calibrated deep learning model.