Evidence map›Paper›PMID 38178999›Full record

ArticleToxicology research2024

Developmental neurotoxicity (DNT) QSAR combination prediction model establishment and structural characteristics interpretation.

Lu Zhang, Min Li, Dalong Zhang, Shujing Zhang, Li Zhang, Xiaojun Wang, Zhiyong Qian

Open access · greenAbstract read
In one paragraph

Article in Toxicology research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 41% of its field
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

2 citing papers in PubMed, 1 citations in OpenAlex.

  1. Article
  2. 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

7 authors at 1 institution in 1 country.

Lu ZhangDepartment of Toxicology, Tianjin Centers for Disease Control and Prevention, Tianjin 300011, China.
Min LiDepartment of Toxicology, Tianjin Centers for Disease Control and Prevention, Tianjin 300011, China.
Dalong ZhangDepartment of Toxicology, Tianjin Centers for Disease Control and Prevention, Tianjin 300011, China.
Shujing ZhangDepartment of Toxicology, Tianjin Centers for Disease Control and Prevention, Tianjin 300011, China.
Li ZhangDepartment of Toxicology, Tianjin Centers for Disease Control and Prevention, Tianjin 300011, China.
Xiaojun WangDepartment of Toxicology, Tianjin Centers for Disease Control and Prevention, Tianjin 300011, China.
Zhiyong QianDepartment of Toxicology, Tianjin Centers for Disease Control and Prevention, Tianjin 300011, China.
Tianjin Centers for Disease Control and Prevention · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the incidence of neurodevelopmental disorders on the rise, it is imperative to screen and evaluate developmental neurotoxicity (DNT) compounds from a large number of environmental chemicals and understand their mechanisms. In this study, DNT qualitative structure-activity relationship (QSAR) study was carried out for the first time based on DNT data of mammals and structural characterization of DNT compounds was preliminarily illustrated. Five different classification algorithms and two feature selection methods were used to construct prediction models. The best model had good predictive ability on the external test set, but a small application domain (AD). Through combining of three different models, both MCC and AD values were improved. Furthermore, electronical properties, van der Waals volume-related properties and S, Cl or P containing substructure were found to be associated with DNT through modeling descriptors analysis and structure alerts (SAs) identification. This study lays a foundation for further DNT prediction of environmental exposures in human and contributes to the understanding of DNT mechanism.

Indexed as

developmental neurotoxicityqualitative structure-activity relationship classification algorithmsstructural alertsstructural characterizationvoting rules

Identifiers

PMID38178999
PMCPMC10762666
OpenAlexW4389775948

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.