Evidence map›Paper›PMID 36644334›Full record

ArticleMicrosystems & nanoengineering2023

DropLab: an automated magnetic digital microfluidic platform for sample-to-answer point-of-care testing-development and application to quantitative immunodiagnostics.

Xuyang Hu, Xiangyu Gao, Songlin Chen, Jinhong Guo, Yi Zhang

Open access · goldAbstract read
In one paragraph

Article in Microsystems & nanoengineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
4.7field-weighted citation impact, top 4% 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

9 citing papers in PubMed, 36 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

5 authors at 3 institutions in 2 countries.

Xuyang HuChina-Singapore International Joint Research Institute, Guangzhou, China.
Xiangyu GaoChina-Singapore International Joint Research Institute, Guangzhou, China.
Songlin ChenSchool of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, Singapore.
Jinhong GuoSchool of Sensing Science and Engineering, Shanghai Jiao Tong University, Shanghai, China.
Yi ZhangSchool of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China.ORCID 0000-0002-1239-3441
Nanyang Technological University · SGShanghai Jiao Tong University · CNUniversity of Electronic Science and Technology of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In point-of-care testing (POCT), tests are performed near patients and results are given rapidly for timely clinical decisions. Immunodiagnostic assays are one of the most important analyses for detecting and quantifying protein-based biomarkers. However, existing POCT immunodiagnostics mainly rely on the lateral flow assay (LFA), which has limited sensitivity or quantification capability. Although other immunodiagnostic assays, such as enzyme-linked immunosorbent assays (ELISAs), offer more sensitive and quantitative results, they require complex liquid manipulations that are difficult to implement in POCT settings by conventional means. Here, we show the development of DropLab, an automated sample-in-answer-out POCT immunodiagnostic platform based on magnetic digital microfluidic (MDM) technology. DropLab performs microbead-based ELISA in droplets to offer more sensitive and quantitative testing results. The intricate liquid manipulations required for ELISA are accomplished by controlling droplets with magnetic microbeads using MDM technology, which enables us to achieve full automation and easy operations with DropLab. Four ELISAs (the sample in triplicates and a negative control) can be run in parallel on the thermoformed disposable chip, which greatly improves the throughput and accuracy compared to those of other POCT immunodiagnostic devices. DropLab was validated by measuring two protein targets and one antibody target. The testing results showed that the limit of detection (LOD) of DropLab matched that of the conventional ELISA in a microwell plate. DropLab brings MDM one step closer to being a viable medical technology that is ready for real-world POCT applications.

Indexed as

BiosensorsElectrical and electronic engineeringMicrofluidics

Identifiers

PMID36644334
PMCPMC9833028
OpenAlexW4315574471

What OpenQuestion 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 OpenQuestion graph.