Integrating network analysis and machine learning to elucidate chemical-induced pancreatic toxicity in zebrafish embryos.

ABSTRACT: Zebrafish (Danio rerio) are a popular vertebrate model for high-throughput toxicity testing, serving as a model for embryonic development and disease etiology. However, standardized protocols using zebrafish tend to explore pathologies and behaviors at the organism level rather than at the organ-specific level. This study investigates the effects of chemical exposures on pancreatic function in whole-embryo zebrafish by integrating network analysis and machine learning, leveraging widely available datasets to probe an organ-specific effect. We compiled transcriptomics data for zebrafish exposed to 53 exposures from 25 unique chemicals, including halogenated organic compounds, pesticides/herbicides, endocrine-disrupting chemicals, pharmaceuticals, parabens, and solvents. All raw sequencing d

SUBMITTER: Schwartz AV 

PROVIDER: S-EPMC12342976 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature