Identification of patient demographic, clinical, and SARS-CoV-2 genomic factors associated with severe COVID-19 using supervised machine learning: a retrospective multicenter study.

Background: Drivers of COVID-19 severity are multifactorial and include multidimensional and potentially interacting factors encompassing viral determinants and host-related factors (i.e., demographics, pre-existing conditions and/or genetics), thus complicating the prediction of clinical outcomes for different severe acute respiratory syndrome coronavirus (SARS-CoV-2) variants.

Chemical Redox Agent-Driven Noncorrosive Formation of Nanoporous Mg Structures for Advanced Hydrogen Storage.

Light metal-based nanomaterials are widely used for energy storage due to their high energy density and surface-to-volume ratio. However, their high reactivity is paradoxically both the source of advantageous properties and a hurdle to the fabrication of stable nanostructures. Here, we demonstrate the formation of nanoporous Mg via chemical redox agent-driven dealloying, which ensures minimized surface passivation and results in fine nanostructures with <50 nm of interconnected metallic ligament despite the labile chemical properties of Mg.

Post-SARS-CoV-2 Onset Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Symptoms in Two Cohort Studies of COVID-19 Recovery.

Objective: To determine how many people with long COVID also meet diagnostic criteria for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS).

Methods: We identified which participants with long COVID also met the Institute of Medicine (IOM) or the 2003 Canadian Consensus Criteria (CCC) for ME/CFS at approximately 6-8 months post-SARS-CoV-2 infection in two cohorts: (1) the JHU COVID Recovery cohort, which enrolled participants within 4 weeks of infection and (2) the Long-term Impact of Infection with Novel Coronavirus (LIINC) cohort, which enriched for participants with long COVID. Neither study administered ME/CFS-specific surveys, so available data elements were mapped onto each ME/CFS diagnostic criteria.

OpenAI's Sora and Google's Veo 2 in Action: A Narrative Review of Artificial Intelligence-driven Video Generation Models Transforming Healthcare.

The rapid evolution of generative artificial intelligence (AI) has introduced transformative technologies across various domains, with text-to-video (T2V) generation models emerging as transformative innovations in the field. This narrative review explores the potential of T2V AI generation models used in healthcare, focusing on their applications, challenges, and future directions. Advanced T2V platforms, such as Sora Turbo (OpenAI, Inc.