Evidence map›Paper›PMID 33233440›Full record

ArticleBiosensors2020

Three-Dimensional Paper-Based Microfluidic Analysis Device for Simultaneous Detection of Multiple Biomarkers with a Smartphone.

Seung Ho Baek, Chanyong Park, Jaehyung Jeon, Sungsu Park

Abstract read
In one paragraph

Article in Biosensors, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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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.

Seung Ho BaekSchool of Mechanical Engineering, Sungkyunkwan University, Suwon 16419, Korea.
Chanyong ParkDepartment of Biomedical Engineering, Sungkyunkwan University, Suwon 16419, Korea.
Jaehyung JeonSchool of Mechanical Engineering, Sungkyunkwan University, Suwon 16419, Korea.
Sungsu ParkSchool of Mechanical Engineering, Sungkyunkwan University, Suwon 16419, Korea.ORCID 0000-0003-3062-1302

Funding

National Research Foundation (NRF) in Korea 2018R1A2B2002066the Ministry of Science and ICT (MSIT) BioNano Health-Guard Research Center as Global Frontier Project (H-GUARD-2018M3A6B2057299
6 · The paper itself

Abstract

Paper-based microfluidic analysis devices (μPADs) have attracted attention as a cost-effective platform for point-of-care testing (POCT), food safety, and environmental monitoring. Recently, three-dimensional (3D)-μPADs have been developed to improve the performance of μPADs. For accurate diagnosis of diseases, however, 3D-μPADs need to be developed to simultaneously detect multiple biomarkers. Here, we report a 3D-μPADs platform for the detection of multiple biomarkers that can be analyzed and diagnosed with a smartphone. The 3D-μPADs were fabricated using a 3D digital light processing printer and consisted of a sample reservoir (300 µL) connected to 24 detection zones (of 4 mm in diameter) through eight microchannels (of 2 mm in width). With the smartphone application, eight different biomarkers related to various diseases were detectable in concentrations ranging from normal to abnormal conditions: glucose (0-20 mmol/L), cholesterol (0-10 mmol/L), albumin (0-7 g/dL), alkaline phosphatase (0-800 U/L), creatinine (0-500 µmol/L), aspartate aminotransferase (0-800 U/L), alanine aminotransferase (0-1000 U/L), and urea nitrogen (0-7.2 mmol/L). These results suggest that 3D-µPADs can be used as a POCT platform for simultaneous detection of multiple biomarkers.

Indexed as

Microfluidic Analytical TechniquesSmartphoneBiomarkersBiosensing TechniquesColorimetryGlucoseHumansLab-On-A-Chip DevicesPaperBiomarkersGlucosecolorimetricmultiple detectionpaper-based microfluidic devicesmartphone application

Identifiers

PMID33233440
PMCPMC7700338

What OpenQuestion holds

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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.