Machine learning prioritization of antibiotic residues in aquatic foods reveals exposure-driven genotoxic risk mediated by BCL2

Antibiotic residues in aquatic foods pose genotoxic risks. Traditional monitoring focuses on individual Maximum Residue Limit (MRL) compliance, often overlooking cumulative multi-residue risks. We developed an interpretable machine learning (ML) framework integrating surveillance data (3719 samples,...

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Bibliografische Detailangaben

Hauptverfasser:	Huangqu Zhu, Kaili Zhou, Yuanzhi Li, Qingqiong Zhou, Mingjun Peng, Xinlan Wu, Xinwu Mao, Qiaoyuan Yang
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	Elsevier 2026-02-01
Schriftenreihe:	Food Chemistry: X
Schlagworte:	Antibiotic residues Machine learning Risk prioritization Regulatory decision-making Food safety Genotoxicity
Online-Zugang:	http://www.sciencedirect.com/science/article/pii/S2590157526001677
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