{"doi":"10.3390/ijms27010295","title":"Biologically Informed Machine Learning Prioritizes Dietary Supplements That Protect Neural Crest Cells from Ethanol-Induced Epigenetic Dysregulation and Developmental Impairment","abstract":"The impairment of neural crest cells (NCCs) plays a pivotal role in the pathogenesis of fetal alcohol spectrum disorders (FASD). Epigenetic regulators mediate ethanol-induced disruptions in NCC development and represent promising targets for nutritional interventions. Here, we developed a biologically informed machine learning framework to predict nutritional supplements that modulate five key epigenetic regulators (miR-34a, DNMT3a, HDAC, miR-125b, and miR-135a) and mitigate ethanol’s adverse effects on NCCs. The optimized models demonstrated robust predictive performance and identified a number of nutritional supplements that could attenuate ethanol-induced NCC impairment, including resveratrol, vitamin B12, emodin, quercetin, and broccoli sprout-derived compounds. Our optimized models also revealed structural features that are critical for mitigating ethanol-induced NCC impairment through specific epigenetic mechanisms. These findings support predictive modeling as a tool to prioritize nutritional supplements for further investigation and the development of dietary strategies to prevent or reduce the risk of FASD.","journal":"International Journal of Molecular Sciences","year":2025,"id":549784,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9608,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1436952,"name":"Miao Bai","orcid":"0000-0003-3786-5326","position":1,"is_corresponding":false},{"id":1444519,"name":"Shuoyang Wang","orcid":"0000-0001-6963-6267","position":2,"is_corresponding":false},{"id":1414950,"name":"Hongjia Qian","orcid":null,"position":3,"is_corresponding":false},{"id":121247,"name":"J. Liu","orcid":null,"position":4,"is_corresponding":false},{"id":295154,"name":"Wenke Feng","orcid":"0000-0001-5456-5347","position":5,"is_corresponding":false},{"id":10782,"name":"H. Zhang","orcid":null,"position":6,"is_corresponding":false},{"id":505165,"name":"Xiaoyang Wu","orcid":"0000-0001-6378-3207","position":7,"is_corresponding":false},{"id":620411,"name":"Shao-yu Chen","orcid":"0000-0003-4086-1721","position":8,"is_corresponding":false},{"id":1436953,"name":"Xiaoqing Wang","orcid":"0000-0003-0055-0224","position":0,"is_corresponding":true}],"reference_count":91,"raw_metadata":null,"created_at":"2026-07-19T02:54:12.321988Z","pmid":"41516175","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}