Evidence map›Paper›PMID 41644987›Full record

ArticleScientific reports2026

Ultrasensitive on-site detection of aflatoxin M

Romina Vahab Zadeh, Ali Mohamadi Sani, Vahid Hakimzadeh, Afshin Farahbakhsh

Abstract read
In one paragraph

Article in Scientific reports, 2026. 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. Article
  2. Article
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

4 authors.

Romina Vahab ZadehDepartment of Food Science and Technology, Qu.C., Islamic Azad University, Quchan, Iran.
Ali Mohamadi SaniDepartment of Food Science and Technology, Qu.C., Islamic Azad University, Quchan, Iran. mohamadisani@yahoo.com.
Vahid HakimzadehDepartment of Food Science and Technology, Qu.C., Islamic Azad University, Quchan, Iran.
Afshin FarahbakhshDepartment of chemical engineering, Qu.C., Islamic Azad University, Quchan, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study presents a novel electrochemical aptasensor for ultrasensitive detection of aflatoxin M1 (AFM1) in milk samples, utilizing a gold electrode modified with chitosan-functionalized multiwalled carbon nanotube/graphene nanocomposite (CS/f-MWCNTs-Gr). The platform was fabricated through covalent immobilization of an amino-modified aptamer onto the nanocomposite surface, enhancing electronic transmission and biorecognition efficiency. Cyclic voltammetry (CV) confirmed stepwise electrode modification, while square wave voltammetry (SWV) quantified AFM1 via suppression of the [Fe(CN)6]3−/4− redox signal upon target binding. Under optimized conditions, the sensor demonstrated a wide linear range (1–1000 nM) covering EU/US regulatory limits, an ultra-low detection limit (0.03 nM, 9.8 ng/L, below EU regulatory limit of 25 ng/kg), and exceptional specificity (> 90% signal suppression against interferents at 10-fold higher concentrations). The aptasensor exhibited high reproducibility (RSD = 5.4%, n = 5) and retained 92% signal after 14-day storage. Validated in commercial milk, it achieved 96–106% recoveries with RSD < 4.9% (n = 5), outperforming reference methods in precision and practicality. This cost-effective platform shows significant potential for on-site monitoring of mycotoxins in dairy products.

Indexed as

Aflatoxin M1Aptamers, NucleotideBiosensing TechniquesChitosanGraphiteMilkNanocompositesNanotubes, CarbonAnimalsElectrochemical TechniquesElectrodesFood ContaminationGoldLimit of DetectionReproducibility of ResultsAflatoxin M1Aptamers, NucleotideChitosanGoldGraphiteNanotubes, CarbonAFM1Chitosan filmDairy safety monitoringElectrochemical aptasensorMWCNT/graphene

Identifiers

PMID41644987
PMCPMC12923857

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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.