Evidence map›Paper›PMID 37504134›Full record

ArticleBiosensors2023

LSPR-Based Aptasensor for Rapid Urinary Detection of NT-proBNP.

Maria António, Rui Vitorino, Ana L Daniel-da-Silva

Open access · goldAbstract read
In one paragraph

Article in Biosensors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.5field-weighted citation impact, top 17% of its field
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

3 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

3 authors at 2 institutions in 1 country.

Maria AntónioCICECO-Aveiro Institute of Materials, Department of Chemistry, University of Aveiro, 3810-193 Aveiro, Portugal.
Rui VitorinoLAQV-REQUIMTE, Chemistry Department, University of Aveiro, 3810-193 Aveiro, Portugal.ORCID 0000-0003-3636-5805
Ana L Daniel-da-SilvaCICECO-Aveiro Institute of Materials, Department of Chemistry, University of Aveiro, 3810-193 Aveiro, Portugal.ORCID 0000-0001-6581-8880
University of Aveiro · PTUniversidade do Porto · PT

Funding

Fundação para a Ciência e Tecnologia COVID/BD/152911/2023Fundação para a Ciência e Tecnologia LA/P/0006/2020Fundação para a Ciência e Tecnologia POCI-01-0145-FEDER-007628Fundação para a Ciência e Tecnologia SFRH/BD/136881/2018Fundação para a Ciência e Tecnologia UIDB/04501/2020Fundação para a Ciência e Tecnologia UIDB/50006/2020Fundação para a Ciência e Tecnologia UIDB/50011/2020Fundação para a Ciência e Tecnologia UID/IC/00051/2019Fundação para a Ciência e Tecnologia UIDP/50011/2020
6 · The paper itself

Abstract

N-terminal pro-brain natriuretic peptide (NT-proBNP) is a myocardial stress biomarker that can be found in serum or plasma, saliva, and urine in the context of cardiovascular disease. In this study, we developed a rapid (~25 min) and straightforward localized surface plasmon resonance (LSPR)-based assay for detecting NT-proBNP in urine. The assay employs citrate-capped gold nanoparticles (AuNPs) and an aptamer specific for NT-proBNP, which initially interacts with NT-proBNP. The remaining unbound aptamer then interacts with the AuNPs, and the addition of NaCl induces the aggregation of the unprotected AuNPs, resulting in a decrease in absorbance at the LSPR band (A

Indexed as

Cardiovascular DiseasesMetal NanoparticlesBiomarkersGoldHumansInfant, NewbornInfant, PrematureNatriuretic Peptide, BrainPeptide FragmentsSurface Plasmon ResonanceUrinalysisBiomarkersGoldNatriuretic Peptide, BrainPeptide Fragmentspro-brain natriuretic peptide (1-76)aptamergold nanoparticlesLSPR-based assayNT-proBNPurine

Identifiers

PMID37504134
PMCPMC10377000
OpenAlexW4384558063

What OpenQuestion holds

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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.