Evidence map›Paper›PMID 35425533›Full record

ArticleRSC advances2022

A gold nanoparticle-based visual aptasensor for rapid detection of acetamiprid residues in agricultural products using a smartphone.

Chengnan Xu, Mei Lin, Chaonan Song, Danli Chen, Caimiao Bian

Abstract read
In one paragraph

Article in RSC advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
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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.

Chengnan XuZhejiang Citrus Research Institute Taizhou 318026 China xcnpub@163.com.ORCID https://orcid.org/0000-0001-7968-4633
Mei LinZhejiang Citrus Research Institute Taizhou 318026 China xcnpub@163.com.
Chaonan SongSchool of Life Science, Taizhou University Taizhou 318001 China blancaimiao@tzc.edu.cn.
Danli ChenSchool of Life Science, Taizhou University Taizhou 318001 China blancaimiao@tzc.edu.cn.
Caimiao BianSchool of Life Science, Taizhou University Taizhou 318001 China blancaimiao@tzc.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Based on the colorimetric analysis of gold nanoparticles and a smartphone readable strategy, a stable, sensitive, and visual method was established for rapid detection of acetamiprid residues in agricultural products. By optimizing the key parameters, the detection process only took 40 minutes with good specificity. The acetamiprid aptamer can help AuNPs to resist salt-induced aggregation. Conversely, in the presence of acetamiprid, the anti-protection is weakened and the AuNPs aggregated with the color change of the solution. The photographs of the solution are recorded by the smartphone and analyzed through image processing. In the range from 25 to 300 μM the method can realize a quantitative analysis of acetamiprid, and the detection limit is about 3.81 μM. Excellent recoveries are taken in samples of cucumber, cabbage, and river water, ranging from 96.78% to 129.95%. These results show no significant difference from the results obtained by the microplate reader. What's more, the method employs a smartphone to read without the assistance of professional equipment, which greatly reduces the cost of detection, and shows a promising application prospect for on-site rapid detection of acetamiprid.

Identifiers

PMID35425533
PMCPMC8981225

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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.