Evidence map›Paper›PMID 35072353›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2022

Deep-dLAMP: Deep Learning-Enabled Polydisperse Emulsion-Based Digital Loop-Mediated Isothermal Amplification.

Linzhe Chen, Jingyi Ding, Hao Yuan, Chi Chen, Zida Li

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Review
  2. Review
  3. Droplet Digital CRISPR for Nucleic Acid Detection.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  4. Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. A Guide to Biodetection in Droplets.Analytical chemistry · 2024
    Review
  10. StratoLAMP: Label-free, multiplex digital loop-mediated isothermal amplification based on visual stratification of precipitate.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  11. Article
  12. 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

5 authors.

Linzhe ChenDepartment of Biomedical Engineering, School of Medicine, Shenzhen University, Shenzhen, 518060, China.
Jingyi DingDepartment of Biomedical Engineering, School of Medicine, Shenzhen University, Shenzhen, 518060, China.
Hao YuanSchool of Life Sciences and Engineering, Southwest Jiaotong University, Chengdu, Sichuan, 610031, China.
Chi ChenDepartment of Nanoengineering, University of California San Diego, La Jolla, CA, 92093, USA.
Zida LiDepartment of Biomedical Engineering, School of Medicine, Shenzhen University, Shenzhen, 518060, China.ORCID 0000-0002-1353-9414

Funding

Natural Science Foundation of Guangdong Province 2019A1515012010Shenzhen Overseas Talent ProgramShenzhen Science and Technology Innovation Commission JCYJ20180507182025817Shenzhen University Student Research Grants 315-470833Shenzhen University Student Research Grants 860-1021991
6 · The paper itself

Abstract

Digital nucleic acid amplification tests enable absolute quantification of nucleic acids, but the generation of uniform compartments and reading of the fluorescence requires specialized instruments that are costly, limiting their widespread applications. Here, the authors report deep learning-enabled polydisperse emulsion-based digital loop-mediated isothermal amplification (deep-dLAMP) for label-free, low-cost nucleic acid quantification. deep-dLAMP performs LAMP reaction in polydisperse emulsions and uses a deep learning algorithm to segment and determine the occupancy status of each emulsion in images based on precipitated byproducts. The volume and occupancy data of the emulsions are then used to infer the nucleic acid concentration based on the Poisson distribution. deep-dLAMP can accurately predict the sizes and occupancy status of each emulsion and provide accurate measurements of nucleic acid concentrations with a limit of detection of 5.6 copies µl

Indexed as

deep learningdigital LAMPdigital PCRnucleic acid test

Identifiers

PMID35072353
PMCPMC8948574

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.