Evidence map›Paper›PMID 36615388›Full record

ArticleMolecules (Basel, Switzerland)2022

A Novel Aptamer-Imprinted Polymer-Based Electrochemical Biosensor for the Detection of Lead in Aquatic Products.

Nianxin Zhu, Xinna Liu, Kaimin Peng, Hui Cao, Min Yuan, Tai Ye, Xiuxiu Wu, Fengqin Yin, Jinsong Yu, Liling Hao and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Molecules (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
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  5. 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

11 authors.

Nianxin ZhuShanghai Engineering Research Center of Food Rapid Detection, School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Xinna LiuShanghai Engineering Research Center of Food Rapid Detection, School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Kaimin PengShanghai Engineering Research Center of Food Rapid Detection, School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Hui CaoShanghai Engineering Research Center of Food Rapid Detection, School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Min YuanShanghai Engineering Research Center of Food Rapid Detection, School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Tai YeShanghai Engineering Research Center of Food Rapid Detection, School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Xiuxiu WuShanghai Engineering Research Center of Food Rapid Detection, School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Fengqin YinShanghai Engineering Research Center of Food Rapid Detection, School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Jinsong YuShanghai Engineering Research Center of Food Rapid Detection, School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Liling HaoShanghai Engineering Research Center of Food Rapid Detection, School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Fei XuShanghai Engineering Research Center of Food Rapid Detection, School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.

Funding

National Natural Science Foundation of China 32072312Science and Technology Innovation Action Plan of Shanghai 20392001600
6 · The paper itself

Abstract

Lead contamination in aquatic products is one of the main hazard factors. The aptasensor is a promising detection method for lead ion (Pb(II)) because of its selectivity, but it is easily affected by pH. The combination of ion-imprinted polymers(IIP) with aptamers may improve their stability in different pH conditions. This paper developed a novel electrochemical biosensor for Pb(II) detection by using aptamer-imprinted polymer as a recognition element. The glassy carbon electrode was modified with gold nanoparticles and aptamers. After the aptamer was induced by Pb(II) to form a G-quadruplex conformation, a chitosan-graphene oxide was electrodeposited and cross-linked with glutaraldehyde to form an imprint layer, improving the stability of the biosensor. Under the optimal experimental conditions, the current signal change (∆I) showed a linear correlation of the content of Pb(II) in the range of 0.1-2.0 μg/mL with a detection limit of 0.0796 μg/mL (S/N = 3). The biosensor also exhibited high selectivity for the determination of Pb(II) in the presence of other interfering metal ion. At the same time, the stability of the imprinted layer made the sensor applicable to the detection environment with a pH of 6.4-8.0. Moreover, the sensor was successfully applied to the detection of Pb(II) in mantis shrimp.

Indexed as

Aptamers, NucleotideBiosensing TechniquesGraphiteMetal NanoparticlesElectrochemical TechniquesElectrodesGoldLeadLimit of DetectionPolymersAptamers, NucleotideGoldGraphiteLeadPolymersaptamer-imprinted polymerchitosan–graphene oxide compositelead detection

Identifiers

PMID36615388
PMCPMC9822230

What OpenQuestion holds

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LicenceCC BY
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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.