Evidence map›Paper›PMID 41366288›Full record

ArticleBMC microbiology2025

Integrative computational modeling framework linking mycotoxin contamination, microbial hazards, and antimicrobial resistance risk in dairy systems.

Ruby Khan, Sumbal Khan, Bakht Pari

Abstract read
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Article in BMC microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Ruby KhanDepartment of System Biology and Engineering, Silesian University of Technology, Gliwice, Poland. ruby.khan@polsl.pl.ORCID 0000-0002-5419-1944
Sumbal KhanLady Reading Hospital, Peshawar, Pakistan.ORCID 0009-0006-8703-7907
Bakht PariSarhad University of Science and Information Technology, Peshawar, KP, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMilk can sometimes carry harmful mycotoxins, which pose health risks, especially in hot and humid areas. We collected samples from both farms and households in Khyber Pakhtunkhwa (KP), Pakistan, to see how common these toxins are, whether the genes that make them are present, and which environmental factors might make contamination worse.

methodsWe tested raw milk for aflatoxins (AFM1, AFM2), ochratoxin A (OTA), and zearalenone (ZEN) using TLC, HPLC, and UHPLC-MS/MS. All testing procedures were validated following ICH Q2(R2), ISO 17025, and FDA guidance. PCR was applied to check for the genes aflC, otaA, and zen1. We then combined chemical, molecular, microbial, and environmental data and used multivariate statistics and PLS-DA modeling to find the main factors driving contamination.

resultsMilk from farms had higher mycotoxin levels than household milk. Average AFM1 concentrations were [Formula: see text]g/kg in farm milk and [Formula: see text]g/kg in domestic milk (p < 0.001). AFM2 and OTA showed similar patterns, while ZEN was below detection in all samples. UHPLC-MS/MS confirmed the HPLC findings and offered greater sensitivity. The genes aflC and otaA were found in 68% of farm samples and were strongly linked to AFM1 and OTA levels, while zen1 was absent. High temperature (over 28°C) and humidity (over 75%) were associated with increased contamination. PLS-DA modeling effectively distinguished high- and low-risk samples (AUC = 0.92), highlighting AFM1 concentration, aflC presence, and humidity as key predictors.

conclusionsCombining chemical testing, gene screening, and environmental monitoring provides a practical way to detect and evaluate mycotoxin risk in milk. Farm milk showed higher contamination than household milk, emphasizing the need for targeted monitoring and preventive measures. Identifying environmental thresholds and risk factors can support early interventions to improve food safety and protect public health.

Indexed as

Food ContaminationMilkMycotoxinsAflatoxinsAnimalsCattleChromatography, High Pressure LiquidComputer SimulationDairyingOchratoxinsPakistanTandem Mass SpectrometryAflatoxinsMycotoxinsochratoxin AOchratoxinsAFM1Biosynthetic genesMilk contaminationMycotoxinsOTAPLS-DAPredictive modelingUHPLC-MS/MS

Identifiers

PMID41366288
PMCPMC12817779

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.