Evidence map›Paper›PMID 40124325›Full record

ArticleMethodsX2025

A novel method for the determination of organophosphorus pesticides in urine samples using a combined gas diffusion microextraction (GDME) and gas chromatography-mass spectrometry (GC-MS) technique.

Mohammadreza Jafari, Ali Gholami, Maryam Akhgari

Abstract read
In one paragraph

Article in MethodsX, 2025. 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. Review
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.

Mohammadreza JafariDepartment of Analytical Chemistry, Faculty of Chemistry, University of Kashan, Kashan, Iran.
Ali GholamiDepartment of Analytical Chemistry, Faculty of Chemistry, University of Kashan, Kashan, Iran.
Maryam AkhgariLegal Medicine Research Center, Legal Medicine Organization, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study introduces a novel and sensitive method for determining organophosphorus pesticides in urine using Gas Diffusion Microextraction (GDME) combined with Gas Chromatography-Mass Spectrometry (GC-MS). The goal is to offer an efficient, cost-effective method for extracting and analyzing these toxic compounds, which are widely used and harmful to human health and the environment. Organophosphorus pesticides, such as diazinon and chlorpyrifos, are among the most toxic and prevalent. The study aims to validate a specific, sensitive sample preparation and detection method for diazinon in urine. Urine samples from individuals not exposed to these pesticides were extracted with GDME, under optimal conditions of 60°C, 34 minutes, and 300 µL of receptor phase. Samples were analyzed using GC-MS. The method showed good linearity (0.01 to 100 µg/L) and excellent sensitivity with detection limits of 0.0058 µg/L for diazinon and 0.016 µg/L for chlorpyrifos.•Results indicate the higher sensitivity and selectivity of GDME compared to traditional methods like solid-phase microextraction.•GDME method for pesticide extraction demonstrated superior performance, with a much lower limit of detection for diazinon (0.0058 µg/L) than conventional methods (0.02 µg/L).•This study highlights GDME's potential for accurate and reliable pesticide detection.

Indexed as

ChlorpyrifosDiazinonForensic toxicologyGas Chromatography-Mass Spectrometry (GC–MS)Gas Diffusion Microextraction (GDME)Gas Diffusion Microextraction (GDME) combined with Gas Chromatography-Mass Spectrometry (GC–MS)Organophosphorus pesticides

Identifiers

PMID40124325
PMCPMC11927743

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.