Evidence map›Paper›PMID 40428440›Full record

ArticleFoods (Basel, Switzerland)2025

High-Throughput Determination of Multiclass Chemical Hazards in Poultry Muscles and Eggs Using UPLC-MS/MS.

Rong Chen, Lan Chen, Mingyue Du, Qiaozhen Guo, Ciping Zhong, Jing Zhang, Xiaoqin Yu

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

7 authors.

Rong ChenKey Laboratory of Liquor Regulation Technology, State Administration for Market Regulation, Sichuan Institute of Food Inspection, No. 8 Xinwen Road, West Hi-Tech Zone, Chengdu 611731, China.ORCID 0009-0009-3097-7430
Lan ChenBeijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning, Beijing Center for Disease Control and Prevention, Beijing 100013, China.
Mingyue DuBeijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning, Beijing Center for Disease Control and Prevention, Beijing 100013, China.
Qiaozhen GuoBeijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning, Beijing Center for Disease Control and Prevention, Beijing 100013, China.
Ciping ZhongKey Laboratory of Liquor Regulation Technology, State Administration for Market Regulation, Sichuan Institute of Food Inspection, No. 8 Xinwen Road, West Hi-Tech Zone, Chengdu 611731, China.
Jing ZhangBeijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning, Beijing Center for Disease Control and Prevention, Beijing 100013, China.ORCID 0000-0001-6285-9425
Xiaoqin YuKey Laboratory of Liquor Regulation Technology, State Administration for Market Regulation, Sichuan Institute of Food Inspection, No. 8 Xinwen Road, West Hi-Tech Zone, Chengdu 611731, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A high-throughput method for the determination of a variety of chemical hazards in poultry muscle and egg samples was established via ultra-performance liquid chromatography-tandem triple quadrupole mass spectrometry (UPLC-QqQ-MS). The sample preparation procedure was developed based on this quick, easy, cheap, effective, rugged, and safe (QuEChERS) method and validated for 280 chemical hazards potentially present in poultry products. The target compounds in poultry samples were extracted with a 1% formic acid-acetonitrile solution (15:85,

Indexed as

chemical hazardshigh-throughput detectionpoultry productsUPLC–MS/MS

Identifiers

PMID40428440
PMCPMC12111322

What OpenQuestion holds

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LicenceCC BY
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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.