Evidence map›Paper›PMID 32993106›Full record

ArticleSensors (Basel, Switzerland)2020

New Uses for the Personal Glucose Meter: Detection of Nucleic Acid Biomarkers for Prostate Cancer Screening.

Clara Abardía-Serrano, Rebeca Miranda-Castro, Noemí de-Los-Santos-Álvarez, María Jesús Lobo-Castañón

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.9field-weighted citation impact, top 29% 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

6 citing papers in PubMed, 16 citations in OpenAlex.

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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

4 authors at 1 institution in 1 country.

Clara Abardía-SerranoDepartamento de Química Física y Analítica, Universidad de Oviedo, Av. Julián Clavería 8, 33006 Oviedo, Spain.ORCID 0000-0001-7017-5816
Rebeca Miranda-CastroDepartamento de Química Física y Analítica, Universidad de Oviedo, Av. Julián Clavería 8, 33006 Oviedo, Spain.ORCID 0000-0001-7586-2009
Noemí de-Los-Santos-ÁlvarezDepartamento de Química Física y Analítica, Universidad de Oviedo, Av. Julián Clavería 8, 33006 Oviedo, Spain.ORCID 0000-0002-5216-6825
María Jesús Lobo-CastañónDepartamento de Química Física y Analítica, Universidad de Oviedo, Av. Julián Clavería 8, 33006 Oviedo, Spain.ORCID 0000-0002-2964-9490
Universidad de Oviedo · ES

Funding

Gobierno del Principado de Asturias IDI/2018/000217Ministerio de Ciencia, Innovación y Universidades RTI-2018-095756-B-I00
6 · The paper itself

Abstract

A personal glucose meter (PGM)-based method for quantitative detection of a urinary nucleic acid biomarker in prostate cancer screening, the so-called PCA3, is reported herein. A sandwich-type genoassay is conducted on magnetic beads to collect the target from the sample by specific hybridization, making the assay appropriate for PCA3 detection in biological fluids. The success of the method hinges on the use of alkaline phosphatase (ALP) to link the amount of nucleic acid biomarker to the generation of glucose. In particular, specifically attached ALP molecules hydrolyze D-glucose-1-phosphate into D-glucose, thus enabling the amplification of the recorded signal on the personal glucose meter. The developed genoassay exhibits good sensitivity (3.3 ± 0.2 mg glucose dL

Indexed as

Biosensing TechniquesProstatic NeoplasmsBiomarkersEarly Detection of CancerHumansMaleNucleic AcidsProstate-Specific AntigenBiomarkersNucleic AcidsProstate-Specific Antigenalkaline phosphatasegenoassayhandheld instrumentnucleic acid detectionpersonal glucose meterpoint-of-care testingprostate cancer

Identifiers

PMID32993106
PMCPMC7583019
OpenAlexW3088320900

What OpenQuestion 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 OpenQuestion graph.