Evidence map›Paper›PMID 40092372›Full record

ArticleFrontiers in bioengineering and biotechnology2025

Mathematical modeling of a MoSe₂-based SPR biosensor for detecting SARS-CoV-2 at nM concentrations.

Talia Tene, Nataly Bonilla García, Jessica Alexandra Marcatoma Tixi, Martha Ximena Dávalos Villegas, Cristian Vacacela Gomez, Stefano Bellucci

Abstract read
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Article in Frontiers in bioengineering and biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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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

6 authors.

Talia TeneDepartment of Chemistry, Universidad Técnica Particular de Loja, Loja, Ecuador.
Nataly Bonilla GarcíaFacultad de Ciencias, Escuela Superior Politécnica de Chimborazo (ESPOCH), Riobamba, Ecuador.
Jessica Alexandra Marcatoma TixiCarrera de Estadística, Escuela Superior Politécnica de Chimborazo (ESPOCH), Riobamba, Ecuador.
Martha Ximena Dávalos VillegasCarrera de Matemática, Escuela Superior Politécnica de Chimborazo (ESPOCH), Riobamba, Ecuador.
Cristian Vacacela GomezINFN-Laboratori Nazionali di Frascati, Frascati, Italy.
Stefano BellucciINFN-Laboratori Nazionali di Frascati, Frascati, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rapid and accurate detection of SARS-CoV-2 remains a critical challenge in biosensing technology, necessitating the development of highly sensitive and selective platforms. In this study, we present a mathematical modeling approach to optimize a MoSe₂-based Surface Plasmon Resonance (SPR) biosensor for detecting the novel coronavirus at nM scale. Using the Transfer Matrix Method (TMM), we systematically optimize the biosensor's structural parameters, including silver (Ag), silicon nitride (Si₃N₄), molybdenum diselenide (MoSe₂), and thiol-tethered single-stranded DNA (ssDNA) layers, to enhance sensitivity, detection accuracy, and optical performance. The results indicate that an optimized 45 nm Ag layer, 10 nm Si₃N₄ layer, and monolayer MoSe₂ configuration achieves a resonance shift (Δθ) of 0.3° at 100 nM, with a sensitivity of 197.70°/RIU and a detection accuracy of 5.24 × 10⁻

Indexed as

biosensorMoSe2SARS-CoV-2silicon nitridesurface plasmon resonanceTMM approach

Identifiers

PMID40092372
PMCPMC11907102

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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.