Integrated hepatic transcriptomics and metabolomics identify Pck1 as a key factor in the broad dysregulation induced by vehicle pollutants.

Background: Exposure to air pollution is associated with worldwide morbidity and mortality. Diesel exhaust (DE) emissions are important contributors which induce vascular inflammation and metabolic disturbances by unknown mechanisms. We aimed to determine molecular pathways activated by DE in the liver that could be responsible for its cardiometabolic toxicity.

Utilization of an Off-Site Patient Navigator to Facilitate HIV Pre-Exposure Prophylaxis Referrals in Patients with Sexually Transmitted Infections in the Emergency Department.

The emergency department (ED) is an important setting to identify people at increased risk of HIV infection who may benefit from HIV pre-exposure prophylaxis (PrEP). However, prescribing or referral for PrEP in the ED is not widespread. The purpose of this study is to evaluate the use of an off-site HIV PrEP patient navigator to facilitate PrEP access for patients who seek care for sexually transmitted infections (STIs) in the ED.

ChatGPT-4 Omni Performance in USMLE Disciplines and Clinical Skills: Comparative Analysis.

Background: Recent studies, including those by the National Board of Medical Examiners, have highlighted the remarkable capabilities of recent large language models (LLMs) such as ChatGPT in passing the United States Medical Licensing Examination (USMLE). However, there is a gap in detailed analysis of LLM performance in specific medical content areas, thus limiting an assessment of their potential utility in medical education.

Objective: This study aimed to assess and compare the accuracy of successive ChatGPT versions (GPT-3.

Critical Analysis of ChatGPT 4 Omni in USMLE Disciplines, Clinical Clerkships, and Clinical Skills.

Background: Recent studies, including those by the National Board of Medical Examiners (NBME), have highlighted the remarkable capabilities of recent large language models (LLMs) such as ChatGPT in passing the United States Medical Licensing Examination (USMLE). However, there is a gap in detailed analysis of these models' performance in specific medical content areas, thus limiting an assessment of their potential utility for medical education.

Objective: To assess and compare the accuracy of successive ChatGPT versions (GPT-3.