Evidence map›Paper›PMID 41171383›Full record

ReviewMycotoxin research2025

Immunosensors for mycotoxin detection: techniques, applications and future directions.

Harshvadan Patel

Abstract readReview
PubMed Publisher
In one paragraph

Review in Mycotoxin research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

1 author.

Harshvadan PatelDepartment of Microbiology, Vanita Vishram Women's University, Surat, 395001, Gujarat, India. Harsh7708@yahoo.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fungal contamination in food matrices poses significant health and economic challenges worldwide. Mycotoxins, toxic secondary metabolites produced by fungi like Aspergillus, Penicillium, and Fusarium, are primary contributors to food safety concerns. These toxins contaminate various food products, including grains, nuts, and dairy, leading to severe health risks such as immune suppression, liver cancer, and kidney damage. Traditional detection methods like chromatography and mass spectrometry are precise but limited by their high costs and operational complexity. Immunosensors offer a promising alternative, providing rapid, sensitive, and cost-effective detection of mycotoxins in diverse food matrices. These biosensors leverage antigen-antibody interactions and employ advanced signal transduction mechanisms, such as electrochemical, optical, and piezoelectric systems, to ensure specificity and accuracy. Recent advancements, including the integration of nanotechnology, machine learning and Internet of Things (IoT), have enhanced the sensitivity, portability, and real-time monitoring capabilities of immunosensors. Furthermore, the development of multiplexed sensors facilitates the simultaneous detection of multiple toxins, ensuring comprehensive food safety monitoring. Despite their potential, challenges remain in addressing regulatory standards, sensor stability, and matrix interference. Continued innovation in immunosensor technology, coupled with global standardization efforts, is vital for effective mycotoxin detection and food safety assurance, especially in resource-limited settings.

Indexed as

Biosensing TechniquesFood ContaminationMycotoxinsFood MicrobiologyFood SafetyHumansImmunoassayMycotoxinsBiosensor sensitivityFood safetyImmunosensorsMycotoxin detectionMycotoxins

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.