Evidence map›Paper›PMID 39795500›Full record

ArticlePolymers2025

A Molecularly Imprinted Electrochemical Sensor for Carbendazim Detection Based on Synergy Amplified Effect of Bioelectrocatalysis and Nanocomposites.

Wenjing Lian, Xinyu Zhang, Yongbin Han, Xintong Li, Hongyun Liu

Abstract read
In one paragraph

Article in Polymers, 2025. 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. Article
  2. 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

5 authors.

Wenjing LianDepartment of Applied Chemistry, College of Basic Science, Tianjin Agricultural University, Tianjin 300392, China.
Xinyu ZhangDepartment of Applied Chemistry, College of Basic Science, Tianjin Agricultural University, Tianjin 300392, China.
Yongbin HanDepartment of Applied Chemistry, College of Basic Science, Tianjin Agricultural University, Tianjin 300392, China.
Xintong LiDepartment of Applied Chemistry, College of Basic Science, Tianjin Agricultural University, Tianjin 300392, China.
Hongyun LiuKey Laboratory of Radiopharmaceuticals, Ministry of Education, College of Chemistry, Beijing Normal University, Beijing 100875, China.

Funding

Key Research and Development Program of Ningxia Province of China 2023BEG03020National Natural Science Foundation of China 22102115Research Project of Tianjin Municipal Education Commission 2020KJ099
6 · The paper itself

Abstract

The highly selective and sensitive determination of pesticide residues in food is critical for human health protection. Herein, the specific selectivity of molecularly imprinted polymers (MIPs) was proposed to construct an electrochemical sensor for the detection of carbendazim (CBD), one of the famous broad-spectrum fungicides, by combining with the synergistic effect of bioelectrocatalysis and nanocomposites. Gold nanoparticle-reduced graphene oxide (AuNP-rGO) composites were electrodeposited on a polished glassy carbon electrode (GCE). Then the MIP films were electropolymerized on the surface of the nanolayer using CBD as the template molecule and o-phenylenediamine (OPD) as the monomer. The detection sensitivity of CBD on the heterogeneous structure films was greatly amplified by AuNP-rGO composites and the bioelectrochemical oxidation of glucose, which was catalyzed by glucose oxidase (GOD) with the help of mediator in the underlying solution. The developed sensor showed high selectivity, good reproducibility, and excellent stability towards CBD with the linear range from 2.0 × 10

Indexed as

bioelectrocatalysiscarbendazimelectrochemical sensorgold nanoparticlesgraphene oxidemolecularly imprinted polymer

Identifiers

PMID39795500
PMCPMC11722815

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Registered trials

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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.