Evidence map›Paper›PMID 37112468›Full record

ReviewSensors (Basel, Switzerland)2023

Advances in Electrochemical Biosensor Technologies for the Detection of Nucleic Acid Breast Cancer Biomarkers.

Ana-Maria Chiorcea-Paquim

Open access · goldAbstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
6.3field-weighted citation impact, top 3% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 41 citations in OpenAlex.

  1. Pooled it
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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

1 author at 1 institution in 1 country.

Ana-Maria Chiorcea-PaquimUniversity of Coimbra, CEMMPRE, ARISE, Department of Chemistry, 3004-535 Coimbra, Portugal.ORCID 0000-0002-0605-5147
Instituto Pedro Nunes · PT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer is the second leading cause of cancer deaths in women worldwide; therefore, there is an increased need for the discovery, development, optimization, and quantification of diagnostic biomarkers that can improve the disease diagnosis, prognosis, and therapeutic outcome. Circulating cell-free nucleic acids biomarkers such as microRNAs (miRNAs) and breast cancer susceptibility gene 1 (BRCA1) allow the characterization of the genetic features and screening breast cancer patients. Electrochemical biosensors offer excellent platforms for the detection of breast cancer biomarkers due to their high sensitivity and selectivity, low cost, use of small analyte volumes, and easy miniaturization. In this context, this article provides an exhaustive review concerning the electrochemical methods of characterization and quantification of different miRNAs and BRCA1 breast cancer biomarkers using electrochemical DNA biosensors based on the detection of hybridization events between a DNA or peptide nucleic acid probe and the target nucleic acid sequence. The fabrication approaches, the biosensors architectures, the signal amplification strategies, the detection techniques, and the key performance parameters, such as the linearity range and the limit of detection, were discussed.

Indexed as

Biosensing TechniquesBreast NeoplasmsMicroRNAsNucleic AcidsBiomarkers, TumorDNAElectrochemical TechniquesFemaleHumansNucleic Acid HybridizationBiomarkers, TumorDNAMicroRNAsNucleic AcidsBRCA1breast cancercancer biomarkerelectrochemical biosensorelectrochemistrymicroRNAmiR-155miR-21mi-RNA

Identifiers

PMID37112468
PMCPMC10145521
OpenAlexW4366598851

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.