Evidence map›Paper›PMID 41096726›Full record

ArticleInternational journal of molecular sciences2025

Utilizing Network Toxicology and Molecular Dynamics Simulations to Efficiently Evaluate the Neurotoxicity and Underlying Mechanisms of the Endocrine-Disrupting Chemical Triclosan.

Hao Wang, Yunyun Du, Jin Ji, Chunyan Wang, Zexin Yu, Xianjia Li, Yueyi Lv, Suzhen Guan

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

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

8 authors.

Hao WangNingxia Key Laboratory of Environmental Factors and Chronic Disease Control, School of Public Health, Ningxia Medical University, Yinchuan 750004, China.
Yunyun DuNingxia Key Laboratory of Environmental Factors and Chronic Disease Control, School of Public Health, Ningxia Medical University, Yinchuan 750004, China.
Jin JiNingxia Key Laboratory of Environmental Factors and Chronic Disease Control, School of Public Health, Ningxia Medical University, Yinchuan 750004, China.
Chunyan WangNingxia Key Laboratory of Environmental Factors and Chronic Disease Control, School of Public Health, Ningxia Medical University, Yinchuan 750004, China.
Zexin YuNingxia Key Laboratory of Environmental Factors and Chronic Disease Control, School of Public Health, Ningxia Medical University, Yinchuan 750004, China.
Xianjia LiNingxia Key Laboratory of Environmental Factors and Chronic Disease Control, School of Public Health, Ningxia Medical University, Yinchuan 750004, China.
Yueyi LvNingxia Key Laboratory of Environmental Factors and Chronic Disease Control, School of Public Health, Ningxia Medical University, Yinchuan 750004, China.
Suzhen GuanNingxia Key Laboratory of Environmental Factors and Chronic Disease Control, School of Public Health, Ningxia Medical University, Yinchuan 750004, China.

Funding

National Natural Science Foundation of China 82260647Ningxia Key Research and Development Program 2023BEG02005Ningxia Medical University 2023 University-level Scientific Research Project XZ2023001Open competition mechanism to select the best candidates for key research projects of Ningxia Medical University XJKF240317
6 · The paper itself

Abstract

This study aims to elucidate the neurodevelopmental toxicity and molecular mechanisms of endocrine-disrupting chemicals (EDCs) in neurodevelopmental disorders (NDDs) through a network toxicology approach, using triclosan exposure as a case example. Potential targets of triclosan were identified via comparative analysis of toxicogenomics databases such as the Comparative Toxicogenomics Database (CTD), Similarity Ensemble Approach (SEA), SwissTargetPrediction, and TargetNet. NDD-related targets were retrieved from GeneCards, Disease Gene Network (DisGeNET), and Online Mendelian Inheritance in Man (OMIM), resulting in 633 overlapping genes associated with disease pathology and triclosan effectors. Protein-protein interaction networks were constructed using STRING and Cytoscape, applying median-based algorithms to identify six core genes:

Indexed as

Endocrine DisruptorsMolecular Dynamics SimulationNeurodevelopmental DisordersTriclosanGene OntologyGene Regulatory NetworksHumansMolecular Docking SimulationProtein Interaction MapsProto-Oncogene Proteins c-aktSignal TransductionToxicogeneticsEndocrine DisruptorsProto-Oncogene Proteins c-aktTriclosanmolecular dockingmolecular dynamics simulationnetwork toxicologyneurodevelopmental disorderstriclosan

Identifiers

PMID41096726
PMCPMC12525291

What OpenQuestion holds

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Registered trials

None linked

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.