Review and meta-analysis of gene expression biomarkers predictive of chemical-induced genotoxicity in vivo.

There is growing recognition across broad sectors of the toxicology community that gene expression biomarkers have the potential to identify genotoxic and nongenotoxic carcinogens through a weight-of-evidence approach, providing opportunities to reduce reliance on the 2-year bioassay to identify carcinogens. In August 2022, a workshop within the International Workshops on Genotoxicity Testing (IWGT) was held to critically review current methods to identify genotoxicants using various 'omics profiling methods. Here, we describe the findings of a workshop subgroup focused on the state of the science regarding the use of biomarkers to identify chemicals that act as genotoxicants in vivo.

The ACTION VAD registry: A collective five-year experience.

Background: The Advanced Cardiac Therapies Improving Outcomes Network (ACTION) began in 2018 as a collaborative learning health system committed to improving outcomes in pediatric heart failure, including children and adults with congenital heart disease, supported with ventricular assist devices (VADs). This report describes patient and device characteristics, and outcomes through 1-year post-implant.

Methods: The ACTION VAD registry report was created from data submitted to the ACTION learning network from April 2018 to June 2023.

Quantifying liver-toxic responses from dose-dependent chemical exposures using a rat genome-scale metabolic model.

Because the liver plays a vital role in the clearance of exogenous chemical compounds, it is susceptible to chemical-induced toxicity. Animal-based testing is routinely used to assess the hepatotoxic potential of chemicals. While large-scale high-throughput sequencing data can indicate the genes affected by chemical exposures, we need system-level approaches to interpret these changes.

Bayesian Gene Set Benchmark Dose Estimation for "omic" responses.

Motivation: Estimating a toxic reference point using tools like the benchmark dose (BMD) is a critical step in setting policy to regulate pollution and ensure safe environments. Toxicity can be measured for different endpoints, including changes in gene expression and histopathology for various tissues, and is typically explored one gene or tissue at a time in a univariate setting that ignores correlation. In this work, we develop a multivariate estimation procedure to estimate the BMD for specified gene sets.