Evidence map›Paper›PMID 37700165›Full record

ReviewMikrochimica acta2023

Research advances of SERS analysis method based on silent region molecules for food safety detection.

Yuhang Sun, Xinxin Zheng, Hao Wang, Mengmeng Yan, Zilei Chen, Qinzheng Yang, Yong Shao

Abstract readReview
PubMed Publisher
In one paragraph

Review in Mikrochimica acta, 2023. 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. Review
  2. 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

7 authors.

Yuhang SunSchool of Bioengineering, State Key Laboratory of Biobased Material and Green Papermaking, Qilu University of Technology, Shandong Academy of Sciences, Jinan, 250353, Shandong, People's Republic of China.
Xinxin ZhengSchool of Bioengineering, State Key Laboratory of Biobased Material and Green Papermaking, Qilu University of Technology, Shandong Academy of Sciences, Jinan, 250353, Shandong, People's Republic of China.
Hao WangSchool of Bioengineering, State Key Laboratory of Biobased Material and Green Papermaking, Qilu University of Technology, Shandong Academy of Sciences, Jinan, 250353, Shandong, People's Republic of China.
Mengmeng YanInstitution of Quality Standard and Testing Technology for Agro-Products, Shandong Academy of Agricultural Sciences, Jinan, 250100, China.
Zilei ChenInstitution of Quality Standard and Testing Technology for Agro-Products, Shandong Academy of Agricultural Sciences, Jinan, 250100, China.
Qinzheng YangSchool of Bioengineering, State Key Laboratory of Biobased Material and Green Papermaking, Qilu University of Technology, Shandong Academy of Sciences, Jinan, 250353, Shandong, People's Republic of China. yqz@qlu.edu.cn.
Yong ShaoInstitute of Quality Standard and Testing Technology for Agro-Products, Chinese Academy of Agricultural Science, Beijing, 100081, China. luckystarsy@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Food safety is a critical issue that is closely related to people's health and safety. As a simple, rapid, and sensitive detection technique, surface-enhanced Raman scattering (SERS) technology has significant potential for food safety detection. Recently, researchers have shown a growing interest in utilizing silent region molecules for SERS analysis. These molecules exhibit significant Raman scattering peaks in the cellular Raman silent region between 1800 and 2800 cm

Indexed as

MycotoxinsPesticidesAlkynesFood SafetyHumansNitrilesAlkynesMycotoxinsNitrilesPesticidesFood safetyMatrix effectsSERSSilent region molecules

Identifiers

PMID37700165

What OpenQuestion holds

Textmetadata
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.