Evidence map›Paper›PMID 38066021›Full record

ArticleScientific reports2023

Ag nanorod@PEI-Ag nanohybrid as an excellent signal label for sensitive and rapid detection of serum HER2.

Fatemeh Hakimian, Mohammad Mazloum-Ardakani

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.9field-weighted citation impact, top 24% 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

7 citing papers in PubMed, 6 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

2 authors at 1 institution in 1 country.

Fatemeh HakimianDepartment of Chemistry, Faculty of Science, Yazd University, Yazd, 89195-741, Iran.
Mohammad Mazloum-ArdakaniDepartment of Chemistry, Faculty of Science, Yazd University, Yazd, 89195-741, Iran. mazloum@yazd.ac.ir.
Yazd University · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The accurate detection of Human epidermal growth factor receptor-2 (HER2) as a critical breast cancer biomarker can be essential for the early selection of therapeutic approaches. HER2 is a prominent component of a signaling network. Overexpression of the HER2 protein due to amplification of its gene leads to the development of an aggressive subtype of breast cancer. Patients with tumors that overexpress HER2 are eligible for treatment that significantly reduces mortality rates. Herein, we present a fast and simple method for detecting serum HER2. A new electrochemical label has been developed using charged Ag nanorod@ polyethylenimine-Ag (Ag NR@ PEI-Ag) nanohybrid. The synthesized Ag NR@PEI-Ag nanohybrid simultaneously has the electroactive property of silver and the large surface area of the PEI, which results in the enhancement of the detection signal. So, using Ag NR@PEI-Ag nanohybrid as the electrochemical label, a simple, fast, and sensitive electrochemical biosensor was designed to detect HER2. This way, after immobilizing HER2 aptamer on the Au electrode surface, HER2 or human serum was exposed to the aptamer. Then, the positively charged Ag NR@PEI-Ag nanohybrid was adsorbed onto the negatively charged aptamer-HER2 complex, and the current that was produced due to the Ag/AgCl reaction was measured as the electrochemical signal. The aptasensor shows a broad linear response from 10

Indexed as

Aptamers, NucleotideBiomarkers, TumorBiosensing TechniquesBreast NeoplasmsErb-b2 Receptor Tyrosine KinasesMetal NanoparticlesNanotubesElectrochemical TechniquesFemaleGoldHumansLimit of DetectionAptamers, NucleotideBiomarkers, TumorERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesGold

Identifiers

PMID38066021
PMCPMC10709618
OpenAlexW4389473651

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Registered trials

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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.