Evidence map›Paper›PMID 41590315›Full record

ArticleBiosensors2026

Long-Term Stable Biosensing Using Multiscale Biostructure-Preserving Metal Thin Films.

Kenshin Takemura, Taisei Motomura, Yuko Takagi

Abstract read
In one paragraph

Article in Biosensors, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Kenshin TakemuraIntegrated Research Center for Wellbeing, National Institute of Advanced Industrial Science and Technology (AIST), Tosu 841-0052, Saga, Japan.ORCID 0000-0002-7892-8488
Taisei MotomuraSensing Technology Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tosu 841-0052, Saga, Japan.ORCID 0000-0002-1791-9190
Yuko TakagiMolecular Biosystems Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba 305-8566, Ibaraki, Japan.ORCID 0000-0002-4567-0986

Funding

Japan Society for the Promotion of Science JP23K13566
6 · The paper itself

Abstract

Microparticle detection technology uses materials that can specifically recognize complex biostructures, such as antibodies and aptamers, as trapping agents. The development of antibody production technology and simplification of sensing signal output methods have facilitated commercialization of disposable biosensors, making rapid diagnosis possible. Although this contributed to the early resolution of pandemics, traditional biosensors face issues with sensitivity, durability, and rapid response times. We aimed to fabricate microspaces using metallic materials to further enhance durability of mold fabrication technologies, such as molecular imprinting. Low-damage metal deposition was performed on target protozoa and Norovirus-like particles (NoV-LPs) to produce thin metallic films that adhere to the material. The procedure for fitting the object into the bio structured space formed on the thin metal film took less than a minute, and sensitivity was 10 fg/mL for NoV-LPs. Furthermore, because it was a metal film, no decrease in reactivity was observed even when the same substrate was stored at room temperature and reused repeatedly after fabrication. These findings underscore the potential of integrating stable metallic structures with bio-recognition elements to significantly enhance robustness and reliability of environmental monitoring. This contributes to public health strategies aimed at early detection and containment of infectious diseases.

Indexed as

Biosensing TechniquesMetalsMolecular ImprintingNorovirusMetalsbiosensorbiostructureinfectious diseasemicroparticle

Identifiers

PMID41590315
PMCPMC12838530

What OpenQuestion holds

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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.