Evidence map›Paper›PMID 39380087›Full record

ReviewChinese medicine2024

Applications of nanomaterials with enzyme-like activity for the detection of phytochemicals and hazardous substances in plant samples.

Lei Xu, Mao-Ling Luo, Jing-Jing Dai, Huan Zhu, Peng Li, Dan Wang, Feng-Qing Yang

Abstract readReview
In one paragraph

Review in Chinese medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Lei XuSchool of Chemistry and Chemical Engineering, Chongqing University, Chongqing, 401331, People's Republic of China.
Mao-Ling LuoSchool of Chemistry and Chemical Engineering, Chongqing University, Chongqing, 401331, People's Republic of China.
Jing-Jing DaiSchool of Chemistry and Chemical Engineering, Chongqing University, Chongqing, 401331, People's Republic of China.
Huan ZhuSchool of Chemistry and Chemical Engineering, Chongqing University, Chongqing, 401331, People's Republic of China.
Peng LiState Key Laboratory of Quality Research in Chinese Medicine, Macau Centre for Research and Development in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau, China. PengLi@umac.mo.
Dan WangSchool of Chemistry and Chemical Engineering, Chongqing University, Chongqing, 401331, People's Republic of China.
Feng-Qing YangSchool of Chemistry and Chemical Engineering, Chongqing University, Chongqing, 401331, People's Republic of China. fengqingyang@cqu.edu.cn.ORCID http://orcid.org/0000-0002-9300-5710

Funding

Fundo para o Desenvolvimento das Ciências e da Tecnologia 0024/2021/A1National Key Research and Development Program of China 2022YFC2105700
6 · The paper itself

Abstract

Plants such as herbs, vegetables, fruits, and cereals are closely related to human life. Developing effective testing methods to ensure their safety and quantify their active components are of significant importance. Recently, nanomaterials with enzyme-like activity (known as nanozymes) have been widely developed in various assays, including colorimetric, fluorescence, chemiluminescence, and electrochemical analysis. This review presents the latest advances in analyzing phytochemicals and hazardous substances in plant samples based on nanozymes, including some active ingredients, organophosphorus pesticides, heavy metal ions, and mycotoxins. Additionally, the current shortcomings and challenges of the actual sample analysis were discussed.

Indexed as

Hazardous substancesNanozymesPhytochemicalsPlant samples

Identifiers

PMID39380087
PMCPMC11462967

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.