Evidence map›Paper›PMID 33779022›Full record

ArticleJournal of occupational health2021

Development of a strategic approach for comprehensive detection of organophosphate pesticide metabolites in urine: Extrapolation of cadusafos and prothiofos metabolomics data of mice to humans.

Karin Nomasa, Naoko Oya, Yuki Ito, Takehito Terajima, Takahiro Nishino, Nayan Chandra Mohanto, Hirotaka Sato, Motohiro Tomizawa, Michihiro Kamijima

Open access · goldAbstract read
In one paragraph

Article in Journal of occupational health, 2021. 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
0.1field-weighted citation impact, top 55% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  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

9 authors at 3 institutions in 1 country.

Karin NomasaDepartment of Occupational and Environmental Health, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan.
Naoko OyaDepartment of Occupational and Environmental Health, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan.ORCID https://orcid.org/0000-0001-5546-6084
Yuki ItoDepartment of Occupational and Environmental Health, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan.ORCID https://orcid.org/0000-0003-1617-1595
Takehito TerajimaDepartment of Chemistry, Faculty of Life Sciences, Tokyo University of Agriculture, Tokyo, Japan.ORCID https://orcid.org/0000-0002-3503-090X
Takahiro NishinoDepartment of Occupational and Environmental Health, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan.
Nayan Chandra MohantoDepartment of Occupational and Environmental Health, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan.ORCID https://orcid.org/0000-0002-5803-1534
Hirotaka SatoDepartment of Occupational and Environmental Health, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan.ORCID https://orcid.org/0000-0001-8377-8464
Motohiro TomizawaDepartment of Chemistry, Faculty of Life Sciences, Tokyo University of Agriculture, Tokyo, Japan.ORCID https://orcid.org/0000-0002-5579-4114
Michihiro KamijimaDepartment of Occupational and Environmental Health, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan.ORCID https://orcid.org/0000-0003-0670-8790
Nagoya City University · JPTokyo University of Agriculture · JPJapan Society for the Promotion of Science · JP

Funding

Japan Society for the Promotion of Science JP19H01078the Ministry of the Environment, Japan JPMEERF20185051
6 · The paper itself

Abstract

objectivesThe comprehensive detection of environmental chemicals in biospecimens, an indispensable task in exposome research, is advancing. This study aimed to develop an exposomic approach to identify urinary metabolites of organophosphate (OP) pesticides, specifically cadusafos and prothiofos metabolites, as an example chemical group, using an original metabolome dataset generated from animal experiments.

methodsUrine samples from 73 university students were analyzed using liquid chromatography-high-resolution mass spectrometry. The metabolome data, including the exact masses, retention time (t

resultsUsing the existing databases, one chromatographic peak was annotated as 2,4-dichlorophenol, which could be a prothiofos metabolite. Using our original dataset, one peak was annotated as a putative cadusafos metabolite and three peaks as putative prothiofos metabolites. Of these, all three peaks suggestive of prothiofos metabolites, 2,4-dichlorophenol, 3,4,5-trihydroxy-6-(2,4-dichlorophenoxy) oxane-2-carboxylic acid, and (2,4-dichlorophenyl) hydrogen sulfate were confirmed as authentic compounds by comparing their peak data with both the original dataset and peak data of the standard reagents. The putative cadusafos metabolite was identified as a level C compound (metabolite candidate with limited plausibility).

conclusionsOur developed method successfully identified prothiofos metabolites that are usually not a target of biomonitoring studies. Our approach is extensively applicable to various environmental contaminants beyond OP pesticides.

Indexed as

AnimalsChromatography, LiquidDatabases, FactualEnvironmental MonitoringHumansMetabolomeMetabolomicsMiceOccupational ExposureOrganothiophosphatesOrganothiophosphorus CompoundsPesticidesReference ValuesTandem Mass SpectrometrycadusafosOrganothiophosphatesOrganothiophosphorus CompoundsPesticidesprothiophoscomprehensive analysishigh-resolution mass spectrometrymetaboliteorganophosphate pesticideurine

Identifiers

PMID33779022
PMCPMC8005856
OpenAlexW3145940571

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.