Integrating Environmental Exposure Profiles with Temporal Transcriptomics: An Explainable Machine Learning Model for Cardiovascular Disease Risk Prediction and Biological Validation.
BACKGROUND
Air pollution is an established modifiable risk factor for cardiac arrhythmia, yet the metabolic mechanisms underlying this association remain poorly understood. This study aimed to elucidate how air pollutants promote arrhythmias through metabolic pathway perturbations.
METHODS
We conducted a prospective...
Hong-Guang Wu, Nan He, Pei-Yao Li et al.· Ecotoxicology and Environmen...· 0 citations
Childhood exposure to environmental antibiotics, particularly those related to veterinary use, may contribute to health risks, but evidence on the association between mixture patterns and childhood cardiovascular risk and underlying pathways remains limited. We aimed to identify reproducible urinary antibiotic exposure...
Yi Zhang, Xin-Li Song, Zhi-Ying Song et al.· Environment International· 0 citations
Childhood obesity (CO) is a complex chronic disease driven by environmental, behavioral, and genetic factors. Dysregulation of branched-chain amino acid metabolism (BCAAM) contributes to CO development, highlighting the need to identify reliable biomarkers for diagnosis and treatment. Biomarkers associated with BCAAM...
Hui-Jie Zhang, Yi Lei, Li-Mei Guan et al.· Scientific Reports· 0 citations
Ambient air pollutants have been associated with increased risks of mortality and chronic diseases; however, population-based evidence on their shared versus pollutant- and outcome-specific molecular mechanisms remains unclear. Leveraging proteomics data from 48,645 participants in the UK Biobank, we characterized prot...
Currently, there remains a lack of effective prognostic biomarkers specifically for ARDS patients.
We conducted a retrospective study profiling plasma metabolomics (ARDS = 55, non-ARDS = 37) via high-throughput NPELDI-MS. Machine learning (LR, SVM, NN) developed age-stratified prognostic models (< 65 vs. ≥...
These findings highlight the advantage of a unified, supervised tree-based strategy capable of delivering stable classification and interpretable dimensionality reduction across independent untargeted metabolomics platforms, providing a structured and transferable framework for metabolomics-driven biomarker discovery a...
Markus Zetes, Vlad Moisoiu, Carmen Socaciu et al.· Analytical and Bioanalytical...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.