Evidence map›Paper›PMID 39188696›Full record

ArticleSmart medicine2024

Digital droplet RT-LAMP increases speed of SARS-CoV-2 viral RNA detection.

Yuan Yuan, Perry Ellis, Ye Tao, Dimitri A Bikos, Emma K Loveday, Mallory M Thomas, James N Wilking, Connie B Chang, Fangfu Ye, David A Weitz

Abstract read
In one paragraph

Article in Smart medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
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

10 authors.

Yuan YuanOujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health) Wenzhou Institute University of Chinese Academy of Sciences Wenzhou Zhejiang China.ORCID https://orcid.org/0000-0002-1198-6392
Perry EllisJohn A. Paulson School of Engineering and Applied Sciences Harvard University Cambridge Massachusetts USA.
Ye TaoJohn A. Paulson School of Engineering and Applied Sciences Harvard University Cambridge Massachusetts USA.
Dimitri A BikosDepartment of Chemical and Biological Engineering Montana State University Bozeman Montana USA.
Emma K LovedayDepartment of Chemical and Biological Engineering Montana State University Bozeman Montana USA.
Mallory M ThomasDepartment of Chemical and Biological Engineering Montana State University Bozeman Montana USA.
James N WilkingDepartment of Chemical and Biological Engineering Montana State University Bozeman Montana USA.
Connie B ChangDepartment of Chemical and Biological Engineering Montana State University Bozeman Montana USA.
Fangfu YeOujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health) Wenzhou Institute University of Chinese Academy of Sciences Wenzhou Zhejiang China.
David A WeitzJohn A. Paulson School of Engineering and Applied Sciences Harvard University Cambridge Massachusetts USA.

Funding

High-throughput droplet qRT-PCR microfluidic platform for quantification of virus from single cellsR56AI156137 · NIAID · MONTANA STATE UNIVERSITY - BOZEMAN · PI CHANG, CONNIE B · 2021 to 2021
$360k
NIAID NIH HHS R56 AI156137
6 · The paper itself

Abstract

Nucleic acid amplification testing (NAAT) remains one of the most reliable methods for pathogen identification. However, conventional bulk NAATs may not be sufficiently fast or sensitive enough for the detection of clinically-relevant pathogens in point-of-care testing. Here, we have developed a digital droplet RT-LAMP (ddRT-LAMP) assay that rapidly and quantitatively detects the SARS-CoV-2 viral E gene in microfluidic drops. Droplet partitioning using ddRT-LAMP significantly accelerates detection times across a wide range of template concentrations compared to bulk RT-LAMP assays. We discover that a reduction in droplet diameter decreases assay times up to a certain size, upon which surface adsorption of the RT-LAMP polymerase reduces reaction efficiency. Optimization of drop size and polymerase concentration enables rapid, sensitive, and quantitative detection of the SARS-CoV-2 E gene in only 8 min. These results highlight the potential of ddRT-LAMP assays as an excellent platform for quantitative point-of-care testing.

Indexed as

ddRT‐LAMPdroplet microfluidicsdroplet sizeRNA rapid detectionSARS‐CoV‐2 virus

Identifiers

PMID39188696
PMCPMC11235653

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.