Evidence map›Paper›PMID 37087604›Full record

ArticleSe pu = Chinese journal of chromatography2023

[Development of a multi-residue detection method for 27 typical pharmaceuticals and personal-care products in plants and analysis of their migration patterns in sprouts].

Yong-Fu Zeng, Mei-Fang Chen, Yu Shao, Yong-Huan Yan, Hai-Chao Zhang, Jing Wang, Lian-Feng Ai, Wei-Jun Kang

Abstract readEnglish Abstract
In one paragraph

Article in Se pu = Chinese journal of chromatography, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Yong-Fu ZengSchool of Public Health, Hebei Medical University, Shijiazhuang 050017, China.
Mei-Fang ChenSchool of Public Health, Hebei Medical University, Shijiazhuang 050017, China.
Yu ShaoChina National Accreditation Service for Conformity Assessment, Beijing 100062, China.
Yong-Huan YanSchool of Forensic Medicine, Hebei Medical University, Shijiazhuang 050017, China.
Hai-Chao ZhangShijiazhuang Customs Technology Center, Shijiazhuang 050051, China.
Jing WangShijiazhuang Customs Technology Center, Shijiazhuang 050051, China.
Lian-Feng AiSchool of Public Health, Hebei Medical University, Shijiazhuang 050017, China.
Wei-Jun KangSchool of Public Health, Hebei Medical University, Shijiazhuang 050017, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An analytical method based on ultra-performance liquid chromatography-tandem mass spectrometry was developed for the simultaneous determination of 27 pharmaceutical and personal-care product (PPCP) residues in plants. The enrichment and cleanup of PPCPs in plants were achieved using an HLB extraction column, and the separation was performed on a BEH C18 column (100 mm×2.1 mm, 1.7 μm) with 0.1% formic acid water-acetonitrile as the mobile phase via gradient elution. PPCPs were detected with electrospray ionization mass spectrometry in positive-ion multiple-reaction monitoring (MRM) mode. The limits of detection and quantification of the 27 PPCPs in plants were 0.01-0.30 μg/kg and 0.03-0.98 μg/kg, respectively. Good linearities were observed with coefficients of determination (

Indexed as

CosmeticsTandem Mass SpectrometryChromatography, High Pressure LiquidChromatography, LiquidDrug ResiduesPharmaceutical PreparationsSeedlingsSolid Phase ExtractionWaterCosmeticsPharmaceutical PreparationsWaterpharmaceuticals and personal care products (PPCPs)sproutstransfer factorsultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS)

Identifiers

PMID37087604
PMCPMC10122767

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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.