ArticleScientific reports2025
Integrative human intervention study for mycotoxin biomarker discovery and toxicokinetic characterization.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Aflatoxins and Fumonisins: Assessment Methods, Biomarkers of Exposure, Modified Forms, Co-Exposure, and Impact on Human Health.Molecules (Basel, Switzerland) · 2026Review
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Authors and funding
8 authors.
Funding
Abstract
Mycotoxin exposure contributes to adverse human health outcomes, however, data regarding validated human biomarkers of exposure are lacking. This study presents an integrated framework for the biomarker discovery and toxicokinetic characterization of mycotoxin in humans. The aim of the study is to identify new biomarkers, determine their toxicokinetic (TK) properties, and build an integrated data analysis workflow using machine learning (ML), whilst focusing on non- and minimally-invasive sampling strategies. Following sample collection and chemical analysis, obtained datasets are used for the computation of ML models. Probability-based techniques are employed to calculate specific boundaries in the multidimensional space and, in parallel, ML classification methodologies are evaluated to scrutinize controls from intervened volunteers. Furthermore, multivariate regression models are computed to study the correlation of potential biomarkers with mycotoxin dosages. Once biomarkers have been identified, data are fit using Bayesian methods to a population-TK model to estimate key parameters related to absorption, distribution, metabolism, and excretion. This standardized framework allows the scientific community to identify and validate new mycotoxin biomarkers and related ADME-properties in both a precise and accurate manner. Although we developed the proposed trial for various different mycotoxins, due to ethical considerations, focus was set towards IARC group III-classified mycotoxins.
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Registered trials
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.