Evidence map›Paper›PMID 39056623›Full record

ArticleBiosensors2024

Development of a "Signal-On" Fluorescent Aptasensor for Highly Selective and Sensitive Detection of ZEN in Cereal Products Using Nitrogen-Doped Carbon Dots Based on the Inner Filter Effect.

Qi Sun, Yuting Zhou, Miaomiao Ma, Fuyan Zhang, Shuang Li, Zhuoer Chen, Yu Fang, Tao Le, Fuguo Xing

Abstract read
In one paragraph

Article in Biosensors, 2024. 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. Review
  2. 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

9 authors.

Qi SunChongqing Key Laboratory of Conservation and Utilization of Freshwater Fishes, College of Life Sciences, Chongqing Normal University, No. 37 Chengzhong Road, Shapingba District, Chongqing 401331, China.
Yuting ZhouChongqing Key Laboratory of Conservation and Utilization of Freshwater Fishes, College of Life Sciences, Chongqing Normal University, No. 37 Chengzhong Road, Shapingba District, Chongqing 401331, China.
Miaomiao MaChongqing Key Laboratory of Conservation and Utilization of Freshwater Fishes, College of Life Sciences, Chongqing Normal University, No. 37 Chengzhong Road, Shapingba District, Chongqing 401331, China.
Fuyan ZhangChongqing Key Laboratory of Conservation and Utilization of Freshwater Fishes, College of Life Sciences, Chongqing Normal University, No. 37 Chengzhong Road, Shapingba District, Chongqing 401331, China.
Shuang LiChongqing Key Laboratory of Conservation and Utilization of Freshwater Fishes, College of Life Sciences, Chongqing Normal University, No. 37 Chengzhong Road, Shapingba District, Chongqing 401331, China.
Zhuoer ChenChongqing Key Laboratory of Conservation and Utilization of Freshwater Fishes, College of Life Sciences, Chongqing Normal University, No. 37 Chengzhong Road, Shapingba District, Chongqing 401331, China.
Yu FangChongqing Key Laboratory of Conservation and Utilization of Freshwater Fishes, College of Life Sciences, Chongqing Normal University, No. 37 Chengzhong Road, Shapingba District, Chongqing 401331, China.
Tao LeChongqing Key Laboratory of Conservation and Utilization of Freshwater Fishes, College of Life Sciences, Chongqing Normal University, No. 37 Chengzhong Road, Shapingba District, Chongqing 401331, China.ORCID 0000-0002-2771-7744
Fuguo XingKey Laboratory of Agro-Products Quality and Safety Control in Storage and Transport Process, Ministry of Agriculture and Rural Affairs, Beijing 100193, China.ORCID 0000-0002-9078-6523

Funding

This research was financially supported by Opening Foundation of Key Laboratory of Agro-Products Processing, Key Laboratory of Agro-products Quality and Safety Control in Storage and Transport Process, Ministry of Agriculture and Rural Affairs, P. R. Chin No. S2022KFKT-12
6 · The paper itself

Abstract

This study aimed to develop a novel fluorescent aptasensor for the quantitative detection of zearalenone (ZEN), addressing the limitations of conventional detection techniques in terms of speed, sensitivity, and ease of use. Nitrogen-doped carbon dots (N-CDs) were synthesized via the hydrothermal method, resulting in spherical particles with a diameter of 3.25 nm. These N-CDs demonstrated high water solubility and emitted a bright blue light at 440 nm when excited at 355 nm. The fluorescence of N-CDs was quenched by dispersed gold nanoparticles (AuNPs) through the inner filter effect, while aggregated AuNPs induced by NaCl did not affect the fluorescence of N-CDs. The aptamer could protect AuNPs from NaCl-induced aggregation, but the presence of ZEN weakened this protective effect. Based on this principle, optimal conditions for ZEN detection included 57 mM NaCl, 12.5 nM aptamer concentration, incubation of AuNPs with NaCl for 15 min in Tris-EDTA(TE) buffer, and incubation of aptamer with ZEN and NaCl for 30 min. Under these optimized conditions, the "signal-on" fluorescent aptasensor for ZEN detection showed a linear range of 0.25 to 200 ng/mL with a low detection limit of 0.0875 ng/mL. Furthermore, the developed aptasensor exhibited excellent specificity and could rapidly detect ZEN in corn flour samples or corn oil, achieving satisfactory recovery rates ranging from 84.7% to 108.6%. Therefore, this study presents an economical, convenient, sensitive, and rapid method for accurately quantifying ZEN in cereal products.

Indexed as

Biosensing TechniquesCarbonEdible GrainGoldMetal NanoparticlesNitrogenZearalenoneAptamers, NucleotideFluorescenceLimit of DetectionQuantum DotsAptamers, NucleotideCarbonGoldNitrogenZearalenonecereal productsdetection mechanismfluorescent aptasensornitrogen-doped carbon dotszearalenone

Identifiers

PMID39056623
PMCPMC11274622

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LicenceCC BY
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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.