Evidence map›Paper›PMID 28726727›Full record

ArticleBiosensors2017

In Vitro Quantified Determination of β-Amyloid 42 Peptides, a Biomarker of Neuro-Degenerative Disorders, in PBS and Human Serum Using a Simple, Cost-Effective Thin Gold Film Biosensor.

Yifan Dai, Alireza Molazemhosseini, Chung Chiun Liu

Abstract read
In one paragraph

Article in Biosensors, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Review
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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

3 authors.

Yifan DaiDepartment of Chemical & Biomolecular Engineering and Electronics Design Center, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA. yxd176@case.edu.
Alireza MolazemhosseiniDip. Chimica Materiali e Ing. Chimica "Giulio Natta", Politecnico di Milano, Via Mancinelli 7, 20131 MIlan, Italy. axm1058@case.edu.
Chung Chiun LiuDepartment of Chemical & Biomolecular Engineering and Electronics Design Center, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA. cxl9@case.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A simple in vitro biosensor for the detection of β-amyloid 42 in phosphate-buffered saline (PBS) and undiluted human serum was fabricated and tested based on our platform sensor technology. The bio-recognition mechanism of this biosensor was based on the effect of the interaction between antibody and antigen of β-amyloid 42 to the redox couple probe of K₄Fe(CN)₆ and K₃Fe(CN)₆. Differential pulse voltammetry (DPV) served as the transduction mechanism measuring the current output derived from the redox coupling reaction. The biosensor was a three-electrode electrochemical system, and the working and counter electrodes were 50 nm thin gold film deposited by a sputtering technique. The reference electrode was a thick-film printed Ag/AgCl electrode. Laser ablation technique was used to define the size and structure of the biosensor. Cost-effective roll-to-roll manufacturing process was employed in the fabrication of the biosensor, making it simple and relatively inexpensive. Self-assembled monolayers (SAM) of 3-Mercaptopropionic acid (MPA) was employed to covalently immobilize the thiol group on the gold working electrode. A carbodiimide conjugation approach using

Indexed as

Biosensing TechniquesAmyloid beta-PeptidesBiomarkersElectrochemical TechniquesGoldHumansPeptide Fragmentstau ProteinsAmyloid beta-Peptidesamyloid beta-protein (1-42)BiomarkersGoldPeptide Fragmentstau Proteinsdifferential pulse voltammetryferrocyanide/ferricyanide redox coupleneuro-degenerative disordersβ-amyloid 42

Identifiers

PMID28726727
PMCPMC5618035

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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.