Evidence map›Paper›PMID 39853016›Full record

ArticleToxics2024

Organophosphorus Pesticides Management Strategies: Prohibition and Restriction Multi-Category Multi-Class Models, Environmental Transformation Risks, and Special Attention List.

Yingwei Wang, Lu Wang, Yufei Li

Abstract read
In one paragraph

Article in Toxics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Yingwei WangColleges of Forestry, Northeast Forestry University, 26 Hexing Road, Harbin 150040, China.
Lu WangJilin Province Ecological Environmental Monitoring Centre, 813 Pudong Road, Changchun 130011, China.
Yufei LiColleges of Forestry, Northeast Forestry University, 26 Hexing Road, Harbin 150040, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Organophosphorus pesticides (OPs) have become one of the most widely used pesticides in Chinese agriculture; however, methods to identify potential restrictions on OPs molecules are lacking. Therefore, this study retrieved the OPs restriction list and constructed eight multi-class, multi-category machine learning models for OPs restrictions. Among these, the random forest (RF) model demonstrated excellent predictive performance, as it was successfully validated and applied. Potential environmental transformation products of OPs were obtained using EAWAG-BBD software, while toxicity indicators for the parent OPs and their transformation products were predicted with ADMETlab 3.0 software. This study found that unrestricted OPs, such as phorate, parathion, and chlorpyrifos, exhibited a high probability of toxicity. Additionally, the environmental transformation products of OPs posed similar comprehensive toxicity risks as the parent compounds. A special attention list for OPs was created based on the toxicity risks of unrestricted parent OPs and their transformation products, using standard deviation classification. Phorate and parathion were identified as OPs requiring special attention. This paper aims to provide an effective method for identifying the potential restriction levels of OPs and to propose an evaluation system that comprehensively considers the health risk, thereby supporting the improvement and optimization of management and usage strategies for OPs.

Indexed as

environmental transformation productsmachine learningorganophosphate pesticidesspecial attention listtoxicity characteristics

Identifiers

PMID39853016
PMCPMC11768814

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.