Risk and Prognosis of Hepatocellular Carcinoma in Mexican Americans with Type 2 Diabetes Mellitus.

Introduction: Hepatocellular carcinoma (HCC) disproportionately affects Hispanic persons with higher age-specific incidence and increased mortality rates compared to non-Hispanic Whites. These high rates of incidence and mortality may be explained by the variation in risk factors. Given the high prevalence of type 2 diabetes mellitus (DM) among the Hispanic population, we aimed to assess the risk and prognosis of HCC in Mexican Americans with type 2 DM with consideration of treatment for DM.

Plasma brain-related biomarkers and potential therapeutic targets in pediatric ECMO.

Extracorporeal membrane oxygenation (ECMO) is a technique used to support severe cardiopulmonary failure. Its potential life-saving benefits are tempered by the significant risk for acute brain injury (ABI), from both primary pathophysiologic factors and ECMO-related complications through central nervous system cellular injury, blood-brain barrier dysfunction (BBB), systemic inflammation and neuroinflammation, and coagulopathy. Plasma biomarkers are an emerging tool used to stratify risk for and diagnose ABI, and prognosticate neurofunctional outcomes.

Targeting mutant p53: Evaluation of novel anti-p53 monoclonal antibodies as diagnostic tools.

About 50% of all cancers carry a mutation in p53 that impairs its tumor suppressor function. The p53 missense mutation p53 (p53 in mice) is a hotspot mutation in various cancer types. Therefore, monoclonal antibodies selectively targeting clinically relevant mutations like p53 could prove immensely value.

SCC-NET: segmentation of clinical cancer image for head and neck squamous cell carcinoma.

Purpose: Squamous cell carcinoma (SCC) accounts for 90% of head and neck cancer. The majority of cases can be diagnosed and even treated with endoscopic examination and surgery. Deep learning models have been adopted for various medical endoscopy exams.

BindingDB in 2024: a FAIR knowledgebase of protein-small molecule binding data.

BindingDB (bindingdb.org) is a public, web-accessible database of experimentally measured binding affinities between small molecules and proteins, which supports diverse applications including medicinal chemistry, biochemical pathway annotation, training of artificial intelligence models and computational chemistry methods development. This update reports significant growth and enhancements since our last review in 2016.