Evidence map›Paper›PMID 40823025›Full record

ReviewFrontiers in nutrition2025

A comprehensive review on optical and electrochemical aptasensor for detection of fumonisin B1.

Jiayu Ma, Xiaodong Guo

Abstract readReview
In one paragraph

Review in Frontiers in nutrition, 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. 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

2 authors.

Jiayu MaCollege of Animal Science and Technology, Yangzhou University, Yangzhou, China.
Xiaodong GuoCollege of Animal Science and Technology, Yangzhou University, Yangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fumonisin B1 (FB1) contamination has emerged as a global concern due to its high incidence, severe toxicity, and profound implications for food safety and human health. Consequently, there is an urgent demand for the development of novel analytical techniques that enable simple, rapid, and accurate detection of FB1. Conventional methods for mycotoxin analysis, such as high-performance liquid chromatography (HPLC), liquid chromatography-mass spectrometry (LC-MS), thin-layer chromatography (TLC), gas chromatography-mass spectrometry (GC-MS), and enzyme-linked immunosorbent assay (ELISA), often suffer from limitations including high cost, time-consuming procedures, environmental sensitivity, and reliance on specialized expertise. Nucleic acid aptamers, generated via Systematic Evolution of Ligands by Exponential Enrichment (SELEX), have garnered significant attention as next-generation bioreceptors, demonstrating remarkable progress in food safety applications. Leveraging their high specificity and strong affinity for target molecules, aptamers have been successfully employed as alternatives to conventional methods for FB1 detection, leading to the development of diverse aptasensor platforms. This review systematically summarizes recent advancements (2013-2025) in optical and electrochemical aptasensors for FB1 detection, elucidating their working principles, merits, and limitations. It further evaluates the impact of material integration on sensor performance, identifies existing limitations in selected aptasensor configurations, and proposes corresponding optimization strategies. Finally, the current challenges hindering the practical implementation of aptasensors are critically analyzed, and future research directions are outlined to advance this promising field.

Indexed as

aptasensorselectrochemical signalfood safetyfumonisin B1optical signal

Identifiers

PMID40823025
PMCPMC12351934

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.