High H Solubility of Perfluorocarbon Solvents and Their Use in Reversible Polarization Transfer from -Hydrogen.

This research uses perfluorocarbons (PFCs) as effective alternatives to traditional toxic solvents in reversible -hydrogen-induced polarization (PHIP) for NMR signal enhancement. Hydrogen solubility in PFCs is shown here to be an order of magnitude higher than in typical organic solvents by determination of Henry's constants. We demonstrate how this high H solubility enables the PFCs to deliver substantial polarization transfer from -hydrogen, achieving up to 2400-fold signal gains for H NMR detection and 67,000-fold (22% polarization) for N NMR detection at 9.

Transforming the logistics of liver transplantation with normothermic machine perfusion: Clinical impact versus cost.

Normothermic machine perfusion (NMP) facilitates utilization of marginal liver allografts. It remains unknown whether clinical benefits offset additional costs in the real-world setting. We performed a comparison of outcomes and hospitalization costs for donor livers preserved by NMP versus static cold storage (SCS) at a high-volume center.

Obesity modulates NK-cell activity via LDL & DUSP1 signaling for Populations with Adverse Social Determinants.

African American (AA) women are disproportionally affected by obesity and hyperlipidemia, particularly in the setting of adverse social determinants of health (aSDoH) contributing to health disparities. Obesity, hyperlipidemia, and aSDoH appear to impair Natural Killer cells (NKs). As potential common underlying mechanisms are largely unknown, we sought to investigate common signaling pathways involved in NK dysfunction related to obesity and hyperlipidemia in AA women from under-resourced neighborhoods.

Not the Models You Are Looking For: Traditional ML Outperforms LLMs in Clinical Prediction Tasks.

Objectives: To determine the extent to which current Large Language Models (LLMs) can serve as substitutes for traditional machine learning (ML) as clinical predictors using data from electronic health records (EHRs), we investigated various factors that can impact their adoption, including overall performance, calibration, fairness, and resilience to privacy protections that reduce data fidelity.

Materials And Methods: We evaluated GPT-3.5, GPT-4, and ML (as gradient-boosting trees) on clinical prediction tasks in EHR data from Vanderbilt University Medical Center and MIMIC IV.