Evidence map›Paper›PMID 41865346›Full record

ArticleMolecular diversity2026

Effect of PET-MPs exposure on the toxicology of PCOS: a multi-platform computational toxicology investigation.

Hai Bai, Yuxiao Jiang, Bozhi Zhu, Jing Huang, Yu Zhang, Xunrui Liu, Liying Ge, Shanshan Zhang, Yue Shi, Mingming Wang

Abstract read
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In one paragraph

Article in Molecular diversity, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Hai Bai *Institute of Applied Biotechnology, College of Agronomy and Life Science, Shanxi Datong University, Datong, 037009, Shanxi Province, People's Republic of China.
Yuxiao Jiang *Department of Physiology, School of Basic Medical Sciences, Xuzhou Medical University, Xuzhou, 221009, Jiangsu Province, People's Republic of China.
Bozhi Zhu *The Second Clinical Medical School, Xuzhou Medical University, Xuzhou, 221009, Jiangsu Province, People's Republic of China.
Jing Huang *Department of Physiology, School of Basic Medical Sciences, Xuzhou Medical University, Xuzhou, 221009, Jiangsu Province, People's Republic of China.
Yu ZhangThe Second Clinical Medical School, Xuzhou Medical University, Xuzhou, 221009, Jiangsu Province, People's Republic of China.
Xunrui LiuThe First Clinical Medical School, Xuzhou Medical University, Xuzhou, 221009, Jiangsu Province, People's Republic of China.
Liying GeThe First Clinical Medical School, Xuzhou Medical University, Xuzhou, 221009, Jiangsu Province, People's Republic of China.
Shanshan ZhangSchool of Life Sciences, Jining Medical University, Rizhao, 276826, Shandong Province, People's Republic of China. Zss982454453@126.com.
Yue ShiDepartment of Physiology, School of Basic Medical Sciences, Xuzhou Medical University, Xuzhou, 221009, Jiangsu Province, People's Republic of China. 183418903@qq.com.
Mingming WangDepartment of Physiology, School of Basic Medical Sciences, Xuzhou Medical University, Xuzhou, 221009, Jiangsu Province, People's Republic of China. wmm@xzhmu.edu.cn.

Funding

National Demonstration Center for Experimental Basic Medical Science Education (Xuzhou Medical University) Student Science and Technology Innovation Project 2024BMS08National Natural Science Foundation of China 82401923
6 · The paper itself

Abstract

Polyethylene terephthalate microplastics (PET-MPs) function as endocrine-disrupting agents that interfere with steroidogenesis and folliculogenesis, potentially contributing to polycystic ovary syndrome (PCOS). This study integrates computational toxicology and machine learning to delineate the mechanisms linking PET-MP exposure to PCOS pathogenesis. We conducted systematic multi-omics analysis by merging PET-MP-associated targets from ChemBL, PubChem, SwissTargetPrediction, SuperPred, and GeneCards with PCOS-related genes from GeneCards and the Comparative Toxicogenomics Database. Differential expression and weighted gene co-expression network analysis (WGCNA) were then applied to ovarian transcriptome datasets (GSE106724 and GSE137684). LASSO regression was used to prioritize hub genes, which underwent validation via diagnostic nomograms, molecular docking, molecular dynamics simulations, single-cell expression analysis, immune microenvironment profiling, and pathway enrichment. The results identified 22 overlapping genes connecting PET-MP exposure to PCOS, with RAB9A and MAOB highlighted as potential diagnostic biomarkers that appear to influence inflammatory responses, disrupt steroid hormone homeostasis, and induce mitochondrial dysfunction. Single-cell analysis revealed hub gene enrichment in ovarian granulosa cells (GCs), indicating targeted impacts on the follicular microenvironment, while immune profiling showed macrophage and γδ T cells as possible mediators of PET-MP-induced PCOS. Molecular docking and dynamics simulations demonstrated stable binding affinities of PET-MPs to RAB9A and MAOB. Overall, these findings position RAB9A and MAOB as environmental susceptibility biomarkers associating PET-MP exposure with PCOS development, providing molecular insights for targeted interventions.

Indexed as

Computational toxicologyMachine learningMolecular dynamics simulationsPolycystic ovary syndromePolyethylene terephthalate microplastics

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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.