Evidence map›Paper›PMID 40863947›Full record

ArticleToxics2025

Coupled In Silico Toxicology Models Reveal Equivalent Ecological Risks from BPA and Its Alternatives in Chinese Surface Waters.

Jiawei Zhang, Jingzi Xiao, Huanyu Tao, Mengtao Zhang, Lu Lu, Changbo Qin

Abstract read
In one paragraph

Article in Toxics, 2025. 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
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Jiawei ZhangInstitute of Strategic Planning, Chinese Academy of Environmental Planning, Ministry of Ecology and Environment, Beijing 100041, China.
Jingzi XiaoInstitute of Strategic Planning, Chinese Academy of Environmental Planning, Ministry of Ecology and Environment, Beijing 100041, China.
Huanyu TaoDepartment of Chemistry, University of California, Riverside, CA 92521, USA.ORCID 0009-0001-6212-539X
Mengtao ZhangState Key Laboratory of Soil Pollution Control and Safety, Southern University of Science and Technology, Shenzhen 518055, China.
Lu LuInstitute of Strategic Planning, Chinese Academy of Environmental Planning, Ministry of Ecology and Environment, Beijing 100041, China.
Changbo QinInstitute of Strategic Planning, Chinese Academy of Environmental Planning, Ministry of Ecology and Environment, Beijing 100041, China.

Funding

China Postdoctoral Science Foundation 2024M752165National Key R&D Program of China 2022YFF1301205
6 · The paper itself

Abstract

As bisphenol A (BPA) has gradually become restricted in production scenarios, the ecological risk level of its main replacement chemicals, i.e., bisphenol S (BPS) and bisphenol F (BPF), should be noted. To overcome the limitations of toxicity data, two kinds of in silico toxicology models (quantitative structure-activity relationship (QSAR) and interspecies correlation estimation (ICE) models) were used to predict enough toxicity data for multiple species. The accuracy of the coupled in silico toxicology models was verified by comparing experimental and predicted data results. Reliable predicted no-effect concentrations (PNECs) of 8.04, 35.2, and 34.2 μg/L were derived for BPA, BPS, and BPF, respectively, using species sensitivity distribution (SSD). Accordingly, the ecological risk quotient (RQ) values of BPA, BPS, and BPF for aquatic organisms were assessed in 32 major Chinese surface waters; they ranged from nearly 0 to 1.86, but were <0.1 in most cases, which indicated that the overall ecological risk level of BPA and its alternatives was low. However, in some cases, the ecological risks posed by BPA alternatives have reached equivalent levels to those posed by BPA (e.g., Liuxi River, Taihu Lake, and Pearl River), which requires further attention. This study provides evidence that the application of coupled in silico toxicology models can effectively predict toxicity data for new chemicals, avoiding time-consuming and laborious animal experiments. The main findings of this study can support environmental risk assessment and management for new chemicals that lack toxicity data.

Indexed as

bisphenolsChinese surface watersecotoxicityin silico modelsrisk quotients

Identifiers

PMID40863947
PMCPMC12390238

What OpenQuestion holds

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Registered trials

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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.