ReviewFood science and biotechnology2025
Computational approaches to predict the toxicity of bioactive natural products: a mini review of methodologies.
Review in Food science and biotechnology, 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.
- Novel C3/C28-bis-1,2,4-Triazolyl-sulfanylacetate-betulin Derivatives: Synthesis and Evaluation of Anticancer Potential.International journal of molecular sciences · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite the increasing global demand for functional foods, the challenges associated with bioactive natural food products due to their complex composition remain. Bioactive natural products can potentially interfere with physiological activity regulation and lead to undesired side effects. This finding emphasizes the need for machine learning (ML)-based food safety predictions focused on intrinsic toxicity. This review explores various strategies involved in current methods of model selection and validation techniques used in predictive analysis, highlighting their strengths, limitations, and progress. Future studies should focus on testing compound combinations using top-down or bottom-up approaches with appropriate models to advance in silico toxicity modeling of bioactive natural products.
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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.