Evidence map›Paper›PMID 33312326›Full record

ReviewBiomicrofluidics2020

Microfluidic compartmentalization to identify gene biomarkers of infection.

Ahmad Ismat Kathrada, Shih-Chung Wei, Ying Xu, Lih Feng Cheow, Chia-Hung Chen

Open access · bronzeAbstract readReview
In one paragraph

Review in Biomicrofluidics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 33% 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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. 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

5 authors at 2 institutions in 2 countries.

Ahmad Ismat KathradaDepartment of Biomedical Engineering, National University of Singapore, 4 Engineering Drive 3, Block 4, #04-08, Singapore 117583.
Shih-Chung Wei
Ying XuDepartment of Biomedical Engineering, City University of Hong Kong, Room Y6700, 6/F, Yeung Kin Man Academic Building, 83 Tat Chee Avenue, Hong Kong, China.
Lih Feng Cheow
Chia-Hung ChenDepartment of Biomedical Engineering, City University of Hong Kong, Room Y6700, 6/F, Yeung Kin Man Academic Building, 83 Tat Chee Avenue, Hong Kong, China.ORCID 0000-0001-5097-3968
National University of Singapore · SGCity University of Hong Kong · HK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Infectious diseases caused by pathogens, such as SARS-COV, H7N9, severe fever with thrombocytopenia syndrome virus, and human immunodeficiency virus, have fatal outcomes with common features of severe fever and subsequent bacterial invasion progressing to multiorgan failure. Gene biomarkers are promising to distinguish specific infections from others with similar presenting symptoms for the prescription of correct therapeutics, preventing pandemics. While routine laboratory methods based on polymerase chain reaction (PCR) to measure gene biomarkers have provided highly sensitive and specific viral detection techniques over the years, they are still hampered by their precision and resource intensity precluding their point-of-care use. Recently, there has been growing interest in employing microfluidic technologies to advance current methods for infectious disease determination via gene biomarker measurements. Here, based on the requirement of infection detection, we will review three microfluidic approaches to compartmentalize gene biomarkers: (1) microwell-based PCR platforms; (2) droplet-based PCR; and (3) point-of-care devices including centrifugal chip, SlipChip, and self-powered integrated microfluidic point-of-care low-cost enabling chip. By capturing target genes in microwells with a small sample volume (∼

Identifiers

PMID33312326
PMCPMC7717927
OpenAlexW3106939830

What OpenQuestion holds

Textmetadata
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.