Evidence map›Paper›PMID 35647718›Full record

ArticleJournal of food and drug analysis2022

Direct immersion solid-phase microextraction combined with ambient ionization tandem mass spectrometry to rapidly distinguish pesticides in serum for emergency diagnostics.

Hung Su, Hsin-Hua Lin, Lin-Jhen Su, Chia-Chen Lin, Zong-Han Jiang, Shiang-Jin Chen, Jentaie Shiea, Chi-Wei Lee

Open access · hybridAbstract read
In one paragraph

Article in Journal of food and drug analysis, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.2field-weighted citation impact, top 25% 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

3 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
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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

8 authors at 1 institution in 1 country.

Hung SuDepartment of Chemistry, National Sun Yat-Sen University, Kaohsiung, Taiwan.
Hsin-Hua LinInstitute of Medical Science and Technology, National Sun Yat-Sen University, Kaohsiung, Taiwan.
Lin-Jhen SuInstitute of Medical Science and Technology, National Sun Yat-Sen University, Kaohsiung, Taiwan.
Chia-Chen LinInstitute of Medical Science and Technology, National Sun Yat-Sen University, Kaohsiung, Taiwan.
Zong-Han JiangInstitute of Medical Science and Technology, National Sun Yat-Sen University, Kaohsiung, Taiwan.
Shiang-Jin ChenDepartment of Emergency Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan.
Jentaie ShieaDepartment of Chemistry, National Sun Yat-Sen University, Kaohsiung, Taiwan.
Chi-Wei LeeInstitute of Medical Science and Technology, National Sun Yat-Sen University, Kaohsiung, Taiwan.
National Sun Yat-sen University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite the fact that carbamates and organophosphates cause acute poisoning via different mechanisms and require disparate management, they are indistinguishable by current clinical assays. Herein, direct immersion solid-phase microextraction (DI-SPME) plus thermal desorption-electrospray ionization tandem mass spectrometry (TD-ESI/MS/MS) was developed to discern them. Both pesticides spiked in human serum were extracted by SPME and analyzed by TD-ESI/MS/MS. This is a promising emergency care platform as rapid analyses could be done in tiny sample volumes with satisfactory recovery (89.46%-116.32%), precision (covariance <20%), sensitivity (LOD <0.1 μg/mL), turnaround time (<5 minutes), and linearity (R

Indexed as

PesticidesSolid Phase MicroextractionHumansImmersionTandem Mass SpectrometryPesticides

Identifiers

PMID35647718
PMCPMC9930999
OpenAlexW4220942850

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.