Evidence map›Paper›PMID 34206715›Full record

ArticleBiomolecules2021

A Multi-Chamber Paper-Based Platform for the Detection of Amyloid β Oligomers 42 via Copper-Enhanced Gold Immunoblotting.

Le-Minh-Tu Phan, Sungbo Cho

Abstract read
In one paragraph

Article in Biomolecules, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
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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.

Le-Minh-Tu PhanSchool of Medicine and Pharmacy, The University of Danang, Danang 550000, Vietnam.ORCID 0000-0002-6590-046X
Sungbo ChoDepartment of Electronic Engineering, Gachon University, Seongnam 13120, Gyeonggi-do, Korea.ORCID 0000-0003-3839-6410

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The early diagnosis of Alzheimer's disease (AD) remains a challenge for medical scientists worldwide, leading to a number of research efforts that focus on biosensor development for AD biomarkers. However, the application of these complicated biosensors is limited in medical diagnosis, due to the difficulties in robust sensing platform development, high costs, and the necessity for technical professionals. We successfully developed a robust straightforward manufacturing process for the fabrication of multi-chamber paper devices using the wax printing method and exploited it to detect amyloid beta 42 oligomers (AβO42, a significant biomarker of AD) using copper-enhanced gold nanoprobe colorimetric immunoblotting. Small hydrophilic reaction chambers could concentrate the target sample to the desired size to improve the sensing performance. The copper-enhanced gold nanoprobe immunoblot using the designed multi-chamber platform exhibited a highly sensitive performance with a limit of detection of 320 pg/mL by the naked eye and 23.7 pg/mL by a smartphone camera. This process from sensing manufacture to sensing conduction is simple to perform whenever medical technicians require time- and cost-savings, without complicated instruments or the need for technical professionals, making it feasible to serve as a diagnostic tool worldwide for the early monitoring of AD and scalable devices for the sensing application of various biomarkers in clinical settings.

Indexed as

Alzheimer DiseaseAmyloid beta-PeptidesBiomarkersBiosensing TechniquesCopperGoldHumansImmunoblottingLimit of DetectionMetal NanoparticlesPeptide FragmentsAmyloid beta-PeptidesBiomarkersCopperGoldPeptide FragmentsAlzheimer’s diseaseamyloid beta 42 oligomerscolorimetric immunoblotcopper-enhanced gold nanoprobemulti-chamberwax printing

Identifiers

PMID34206715
PMCPMC8301831

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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.