Evidence map›Paper›PMID 39716390›Full record

ArticleJournal of biophotonics2025

Tailored Functionalization of Plasmonic AgNPs/C:H:N:O Nanocomposite for Sensitive and Selective Detection.

Sanjay Kumar, Hana Maskova, Anna Kuzminova, Paval Curda, Lenka Doudova, Jan Sterba, Ondřej Kylián, Ryan O M Rego, Vítězslav Straňák

Abstract read
In one paragraph

Article in Journal of biophotonics, 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

9 authors.

Sanjay KumarFaculty of Science, University of South Bohemia, Ceske Budejovice, Czech Republic.ORCID 0000-0003-1042-4491
Hana MaskovaFaculty of Science, University of South Bohemia, Ceske Budejovice, Czech Republic.
Anna KuzminovaFaculty of Mathematics and Physics, Charles University, Prague, Czech Republic.
Paval CurdaFaculty of Science, University of South Bohemia, Ceske Budejovice, Czech Republic.
Lenka DoudovaFaculty of Science, University of South Bohemia, Ceske Budejovice, Czech Republic.
Jan SterbaFaculty of Science, University of South Bohemia, Ceske Budejovice, Czech Republic.
Ondřej KyliánFaculty of Mathematics and Physics, Charles University, Prague, Czech Republic.
Ryan O M RegoFaculty of Science, University of South Bohemia, Ceske Budejovice, Czech Republic.
Vítězslav StraňákFaculty of Science, University of South Bohemia, Ceske Budejovice, Czech Republic.

Funding

Czech Science Foundation (Grant Number GACR 21-0503K)
6 · The paper itself

Abstract

We report here on the development of tailored plasmonic AgNPs/C:H:N:O plasma polymer nanocomposites for the detection of the pathogenic bacterium Borrelia afzelii , with high selectivity and sensitivity. Silver (Ag) nanoparticles, generated by a gas aggregation source, are incorporated onto a C:H:N:O plasma polymer matrix, which is deposited by magnetron sputtering of a nylon 6.6. These anchored Ag nanoparticles propagate localized surface plasmon resonance (LSPR), optically responding to changes caused by immobilized pathogens near the nanoparticles. The tailored functionalization of AgNPs/C:H:N:O nanocomposite surface allows both high selectivity for the pathogen and high sensitivity with an LSPR red-shift Δλ > (4.20 ± 0.71) nm for 50 Borrelia per area 0.785 cm

Indexed as

Limit of DetectionMetal NanoparticlesNanocompositesSilverSurface Plasmon ResonanceSilverag nanoparticlesborreliaC:H:N:O thin filmlocalized surface plasmon resonanceLyme diseasemagnetron sputteringnanocompositenylonplasma polymersurface functionalization

Identifiers

PMID39716390
PMCPMC11793947

What OpenQuestion holds

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LicenceCC BY
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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.