Evidence map›Paper›PMID 35386844›Full record

ReviewFrontiers in chemistry2022

Multiple Recognition-Based Sensor for Pesticide Residues.

Jie Li, Keren Chen, Longjiao Zhu, Xiangyang Li, Changmo Li, Qiaoying Chang, Wentao Xu

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Frontiers in chemistry, 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
0.6field-weighted citation impact, top 36% of its field
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, 7 citations in OpenAlex.

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

7 authors at 3 institutions in 1 country.

Jie LiState Key Laboratory of Food Nutrition and Safety, Tianjin University of Science & Technology, Tianjin, China.
Keren ChenKey Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University, Beijing, China.
Longjiao ZhuKey Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University, Beijing, China.
Xiangyang LiBeijing Laboratory for Food Quality and Safety, Food Science and Engineering College, Beijing University of Agriculture, Beijing, China.
Changmo LiState Key Laboratory of Food Nutrition and Safety, Tianjin University of Science & Technology, Tianjin, China.
Qiaoying ChangKey Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University, Beijing, China.
Wentao XuKey Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University, Beijing, China.
China Agricultural University · CNTianjin University of Science and Technology · CNBeijing University of Agriculture · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The use of pesticides is gradually increasing to improve the yield and quality of crops. However, excessive pesticide use has led to a dramatic pollution increase in the environment and agricultural products, posing severe human health risks. Therefore, rapid, sensitive pesticide detection is essential. Various pesticides detection methods and products have been developed in recent years. This brief review summarized the point-of-care testing (POCT) detection of pesticides based on multiple recognition, including protein-, aptamer-, nanomaterial-, and macrocycle-based recognition. The review aimed to address the growing demands for regulating and destroying pesticides or other adverse agriculture-related applications in the real world.

Indexed as

aptamermacrocyclenanomaterialpesticide detectionprotein

Identifiers

PMID35386844
PMCPMC8979164
OpenAlexW4226090700

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.