Evidence map›Paper›PMID 37593680›Full record

ReviewFrontiers in nutrition2023

A review on recent advances in mass spectrometry analysis of harmful contaminants in food.

Qiannan Sun, Yide Dong, Xin Wen, Xu Zhang, Shijiao Hou, Wuduo Zhao, Dan Yin

Abstract readReview
In one paragraph

Review in Frontiers in nutrition, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Article
  6. Review
  7. Review
  8. Review
  9. Article
  10. Article
  11. Review
  12. Review
  13. 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.

Qiannan SunCollege of Chemistry, Zhengzhou University, Zhengzhou, Henan, China.
Yide DongCollege of Chemistry, Zhengzhou University, Zhengzhou, Henan, China.
Xin WenCollege of Chemistry, Zhengzhou University, Zhengzhou, Henan, China.
Xu ZhangSchool of Ecology and Environment, Zhengzhou University, Zhengzhou, Henan, China.
Shijiao HouCollege of Chemistry, Zhengzhou University, Zhengzhou, Henan, China.
Wuduo ZhaoCollege of Chemistry, Zhengzhou University, Zhengzhou, Henan, China.
Dan YinSchool of Ecology and Environment, Zhengzhou University, Zhengzhou, Henan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Food safety is a widespread global concern with the emergence of foodborne diseases. Thus, establishing accurate and sensitive detection methods of harmful contaminants in different food matrices is essential to address and prevent the associated health risks. Among various analytical tools, mass spectrometry (MS) can quantify multiple impurities simultaneously due to high resolution and accuracy and can achieve non-target profiling of unknown pollutants in food. Therefore, MS has been widely used for determination of hazardous contaminants [e.g., mycotoxin, pesticide and veterinary drug residues, polychlorinated biphenyls (PCBs), dioxins, acrylamide, perfluorinated compounds (PFCs) and p-Phenylenediamine compounds (PPDs) in food samples]. This work summarizes MS applications in detecting harmful contaminants in food matrices, discusses advantages of MS for food safety study, and provides a perspective on future directions of MS development in food research. With the persistent occurrence of novel contaminants, MS will play a more and more critical role in food analysis.

Indexed as

acrylamidefood additivesfood analysismass spectrometrymycotoxinpesticide and veterinary drug residuespolychlorinated biphenyls and dioxins

Identifiers

PMID37593680
PMCPMC10428016

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.