Evidence map›Paper›PMID 41590264›Full record

ArticleBiosensors2025

Highly Sensitive Biosensor for the Detection of Cardiac Troponin I in Serum via Surface Plasmon Resonance on Polymeric Optical Fiber Functionalized with Castor Oil-Derived Molecularly Imprinted Nanoparticles.

Alice Marinangeli, Pinar Cakir Hatir, Mustafa Baris Yagci, Alessandra Maria Bossi

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. 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

4 authors.

Alice MarinangeliDepartment of Biotechnology, University of Verona, Strada Le Grazie 15, 37134 Verona, Italy.ORCID 0009-0003-5605-4980
Pinar Cakir HatirDepartment of Biomedical Engineering, Faculty of Engineering and Natural Sciences, İstinye University, Ayazağa Mah. Azerbaycan Cad. (Vadistanbul 4A Blok) Sariyer, İstanbul 34396, Türkiye.ORCID 0000-0002-3806-7118
Mustafa Baris YagciKoç University Surface Science and Technology Center (KUYTAM), Koç University, Istanbul 34450, Türkiye.
Alessandra Maria BossiDepartment of Biotechnology, University of Verona, Strada Le Grazie 15, 37134 Verona, Italy.ORCID 0000-0002-2542-8412

Funding

Ministry of University and Research (MUR) D.M. 351 PON PNRR D.M. 351 PON PNRR
6 · The paper itself

Abstract

In this work, we report the development of a highly sensitive optical sensor for the detection of cardiac troponin I (cTnI), a key biomarker for early-stage myocardial infarction diagnosis. The sensor combines castor oil-derived biomimetic receptors, called GreenNanoMIPs and prepared via the molecular imprinting technology using as a template an epitope of cTnI (i.e., the NR10 peptide), with a portable multimode plastic optical fiber surface plasmon resonance (POF-SPR) transducer. For sensing, gold SPR chips were functionalized with GreenNanoMIPs as proven by refractive index changes and confirmed by means of XPS. Binding experiments demonstrated the cTnI_nanoMIP-SPR sensor's ability to detect both the NR10 peptide epitope and the full-length cTnI protein within minutes (t = 10 min), with high sensitivity and selectivity in buffer and serum matrices. The cTnI_nanoMIP-SPR showed an LOD of 3.53 × 10

Indexed as

Biosensing TechniquesCastor OilNanoparticlesSurface Plasmon ResonanceTroponin IHumansMolecular ImprintingOptical FibersPolymersCastor OilPolymersTroponin Ibiosensorscardiac troponin Icastor oil monomermolecularly imprinted polymersmyocardial infarctionplant oil based functional monomer

Identifiers

PMID41590264
PMCPMC12839181

What Socratic 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 Socratic graph.