Evidence map›Paper›PMID 42029690›Full record

ArticleAnalytical and bioanalytical chemistry2026

Highly sensitive detection of ochratoxin A by fluorescence polarization assay based on rolling circle amplification.

Ailing Yao, Xin Liu, Yiwen Zhang, Ruijie Xue, Jingjin Zhao

Abstract readEvaluation Study
PubMed Publisher
In one paragraph

Article in Analytical and bioanalytical chemistry, 2026. 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
–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

0 citing papers in PubMed.

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

5 authors.

Ailing YaoGuangxi Key Laboratory of Environmental Processes and Remediation in Ecologically Fragile Regions, Guangxi Normal University, Guilin, 541004, PR China.
Xin LiuGuangxi Key Laboratory of Environmental Processes and Remediation in Ecologically Fragile Regions, Guangxi Normal University, Guilin, 541004, PR China.
Yiwen ZhangGuangxi Key Laboratory of Environmental Processes and Remediation in Ecologically Fragile Regions, Guangxi Normal University, Guilin, 541004, PR China.
Ruijie XueGuangxi Key Laboratory of Environmental Processes and Remediation in Ecologically Fragile Regions, Guangxi Normal University, Guilin, 541004, PR China.
Jingjin ZhaoGuangxi Key Laboratory of Environmental Processes and Remediation in Ecologically Fragile Regions, Guangxi Normal University, Guilin, 541004, PR China. jzhao12@163.com.

Funding

National Natural Science Foundation of China 22376040
6 · The paper itself

Abstract

Sensitive and highly selective analysis of ochratoxin A (OTA) plays an important role in food safety. In this paper, an aptamer sensing system based on rolling circle amplification (RCA) technology is proposed for the ultrasensitive fluorescence polarization detection of OTA. The binding of OTA to its aptamer releases the primer S, which rapidly hybridizes with the dumbbell-shaped ring template (HH) to initiate RCA. The effects of the complementary strand length, the hybridization ratio of aptamer (AP) to primer S, the target recognition time, and the reaction temperature on the sensing performance were systematically investigated. Under the optimal experimental conditions, this sensing method demonstrated a well-defined linear relationship with OTA concentrations ranging from 1 × 10

Indexed as

Fluorescence PolarizationFood ContaminationNucleic Acid Amplification TechniquesOchratoxinsAptamers, NucleotideBiosensing TechniquesFood AnalysisLimit of DetectionAptamers, Nucleotideochratoxin AOchratoxinsAptamerFluorescence polarizationFood detectionOchratoxin A (OTA)Rolling circle amplification

Identifiers

PMID42029690

What OpenQuestion holds

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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.