Evidence map›Paper›PMID 36753364›Full record

ArticleJournal of food and drug analysis2022

Optimum synthesis of Au@Ag nanoparticle as plasma amplifier to detect trace concentration of AFB1 via object-binder-metal SERS method.

Wenwen Chen, Qiang Chen, Wei Zhang, De Zhang, Zhi Yu, Ying Song, Xiubing Zhang, Dejiang Ni, Pei Liang

Abstract 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. 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

9 authors.

Wenwen ChenCollege of Optical and Electronic Technology, China Jiliang University, 310018, Hangzhou, China.
Qiang ChenCollege of Metrology and Measurement Engineering, China Jiliang University, 310018, Hangzhou, China.
Wei ZhangCollege of Optical and Electronic Technology, China Jiliang University, 310018, Hangzhou, China.
De ZhangCollege of Optical and Electronic Technology, China Jiliang University, 310018, Hangzhou, China.
Zhi YuCollege of Horticulture & Forestry Sciences, Huazhong Agricultural University, Key Laboratory of Horticultural Plant Biology, Ministry of Education, 430070, Wuhan, China.
Ying SongCollege of Horticulture & Forestry Sciences, Huazhong Agricultural University, Key Laboratory of Horticultural Plant Biology, Ministry of Education, 430070, Wuhan, China.
Xiubing ZhangCollege of Optical and Electronic Technology, China Jiliang University, 310018, Hangzhou, China.
Dejiang NiCollege of Horticulture & Forestry Sciences, Huazhong Agricultural University, Key Laboratory of Horticultural Plant Biology, Ministry of Education, 430070, Wuhan, China.
Pei LiangCollege of Optical and Electronic Technology, China Jiliang University, 310018, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The problem of aflatoxin contamination emerged gradually in the field of food safety. Surface-enhanced Raman spectroscopy (SERS) is an ultra-sensitive and non-destructive spectroscopy technology with extensive application prospects in the detection field. In this paper, with the detection of AFB1 as the target, Au@Ag NPs substrate with uniform morphology and strong SERS effect was prepared. Furthermore, the intermediates formed by hydrogen bonding between AFB1 and melamine facilitate the binding of toxin molecules to the substrate. Moreover, the AFB1-melamine-Au@Ag NPs detection system was established by optimizing the melamine dosage, and the limit of detection can reach 10

Indexed as

AflatoxinsMetal NanoparticlesGoldSilverSpectrum Analysis, RamanAflatoxinsGoldSilver

Identifiers

PMID36753364
PMCPMC9910294

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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.