ReviewToxins2017
Nano-Aptasensing in Mycotoxin Analysis: Recent Updates and Progress.
Review in Toxins, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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.
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.
Who cites it
15 citing papers in PubMed.
- Aflatoxin exposure and health impacts: global burden and advances in detection technologies.Genes and environment : the official journal of the Japanese Environmental Mutagen Society · 2026Review
- Recent Advances in Recognition Receptors for Electrochemical Biosensing of Mycotoxins-A Review.Biosensors · 2023Review
- Recent Progress in Electrochemical Nano-Biosensors for Detection of Pesticides and Mycotoxins in Foods.Biosensors · 2023Review
- The efficacy of metal nanocomposite (FeBMC veterinary research · 2022Article
- Nano optical and electrochemical sensors and biosensors for detection of narrow therapeutic index drugs.Mikrochimica acta · 2021Review
- Review
- Review
- Nanohybrid Antifungals for Control of Plant Diseases: Current Status and Future Perspectives.Journal of fungi (Basel, Switzerland) · 2021Review
- Advances in Colorimetric Strategies for Mycotoxins Detection: Toward Rapid Industrial Monitoring.Toxins · 2020Review
- Noble metal nanomaterial-based aptasensors for microbial toxin detection.Journal of food and drug analysis · 2020Review
- Advances in Analysis and Detection of Major Mycotoxins in Foods.Foods (Basel, Switzerland) · 2020Review
- Assessment of Ochratoxin A Exposure in Ornamental and Self-Consumption Backyard Chickens.Veterinary sciences · 2020Article
- A review on recent developments in optical and electrochemical aptamer-based assays for mycotoxins using advanced nanomaterials.Mikrochimica acta · 2019Review
- Nanoparticles as a Solution for Eliminating the Risk of Mycotoxins.Nanomaterials (Basel, Switzerland) · 2018Review
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent years have witnessed an overwhelming integration of nanomaterials in the fabrication of biosensors. Nanomaterials have been incorporated with the objective to achieve better analytical figures of merit in terms of limit of detection, linear range, assays stability, low production cost, etc. Nanomaterials can act as immobilization support, signal amplifier, mediator and artificial enzyme label in the construction of aptasensors. We aim in this work to review the recent progress in mycotoxin analysis. This review emphasizes on the function of the different nanomaterials in aptasensors architecture. We subsequently relate their features to the analytical performance of the given aptasensor towards mycotoxins monitoring. In the same context, a critically analysis and level of success for each nano-aptasensing design will be discussed. Finally, current challenges in nano-aptasensing design for mycotoxin analysis will be highlighted.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.