Evidence map›Paper›PMID 41149318›Full record

ArticleBiosensors2025

Harnessing in Silico Design for Electrochemical Aptasensor Optimization: Detection of Okadaic Acid (OA).

Margherita Vit, Sondes Ben-Aissa, Alfredo Rondinella, Lorenzo Fedrizzi, Sabina Susmel

Abstract read
In one paragraph

Article in Biosensors, 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

5 authors.

Margherita VitBioanalytical Chemistry and Biosensors Lab, Department of Agri-Food, Environment and Animal Sciences (Di4A), University of Udine, Via Sondrio 2/A, 33100 Udine, Italy.
Sondes Ben-AissaMolecular Sciences Research Hub, Department of Chemistry, Imperial College London, London W12 0BZ, UK.
Alfredo RondinellaPolytechnic Department of Engineering and Architecture, University of Udine, Via del Cotonifico 108, 33100 Udine, Italy.
Lorenzo FedrizziPolytechnic Department of Engineering and Architecture, University of Udine, Via del Cotonifico 108, 33100 Udine, Italy.
Sabina SusmelBioanalytical Chemistry and Biosensors Lab, Department of Agri-Food, Environment and Animal Sciences (Di4A), University of Udine, Via Sondrio 2/A, 33100 Udine, Italy.ORCID 0000-0002-6916-7373

Funding

NRRP - funded by the European Union - NextGenerationEU Grant PhD39-411-34-DOT13QKUB3-6680
6 · The paper itself

Abstract

The urgent need for advanced analytical tools for environmental monitoring and food safety drives the development of novel biosensing approaches and solutions. A computationally driven workflow for the development of a rapid electrochemical aptasensor for okadaic acid (OA), a critical marine biotoxin, is reported. The core of this strategy is a rational design process, where in silico modeling was employed to optimize the biological recognition element. A 63-nucleotide aptamer was successfully truncated to a highly efficient 31-nucleotide variant. Molecular docking simulations confirmed the high binding affinity of the minimized aptamer and guided the design of the surface immobilization chemistry to ensure robust performance. The fabricated sensor, which utilizes a ferrocene-labeled aptamer, delivered a sensitive response with a detection limit of 2.5 nM (

Indexed as

Aptamers, NucleotideBiosensing TechniquesElectrochemical TechniquesOkadaic AcidAnimalsComputer SimulationLimit of DetectionMolecular Docking SimulationAptamers, NucleotideOkadaic Acidaptamer truncationelectrochemical aptasensorferrocene labelin silico modelingokadaic acidprobe design

Identifiers

PMID41149318
PMCPMC12562321

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.