Evidence map›Paper›PMID 31248141›Full record

ReviewMicromachines2019

Microfluidic-Based Nucleic Acid Amplification Systems in Microbiology.

Lena Gorgannezhad, Helen Stratton, Nam-Trung Nguyen

Abstract readReview
In one paragraph

Review in Micromachines, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Application of Microfluidics for Bacterial Identification.Pharmaceuticals (Basel, Switzerland) · 2022
    Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. Micro and Nanoscale Technologies for Diagnosis of Viral Infections.Small (Weinheim an der Bergstrasse, Germany) · 2021
    Review
  10. Article
  11. Review
  12. Review
  13. Article
  14. Article
  15. Review
  16. Article
  17. Review
  18. Advances in automated techniques to identifyAsian biomedicine : research, reviews and news · 2020
    Review
  19. Article
  20. 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

3 authors.

Lena GorgannezhadQueensland Micro- and Nanotechnology Centre, Nathan Campus, Griffith University, 170 Kessels Road, Brisbane QLD 4111, Australia. lena.gorgannezhad@griffithuni.edu.au.
Helen StrattonSchool of Environment and Science, Nathan Campus, Griffith University, 170 Kessels Road, Brisbane QLD 4111, Australia. h.stratton@griffith.edu.au.
Nam-Trung NguyenQueensland Micro- and Nanotechnology Centre, Nathan Campus, Griffith University, 170 Kessels Road, Brisbane QLD 4111, Australia. nam-trung.nguyen@griffith.edu.au.ORCID 0000-0003-3626-5361

Funding

Australian Research Council DP180100055
6 · The paper itself

Abstract

Rapid, sensitive, and selective bacterial detection is a hot topic, because the progress in this research area has had a broad range of applications. Novel and innovative strategies for detection and identification of bacterial nucleic acids are important for practical applications. Microfluidics is an emerging technology that only requires small amounts of liquid samples. Microfluidic devices allow for rapid advances in microbiology, enabling access to methods of amplifying nucleic acid molecules and overcoming difficulties faced by conventional. In this review, we summarize the recent progress in microfluidics-based polymerase chain reaction devices for the detection of nucleic acid biomarkers. The paper also discusses the recent development of isothermal nucleic acid amplification and droplet-based microfluidics devices. We discuss recent microfluidic techniques for sample preparation prior to the amplification process.

Indexed as

bacterial nucleic aciddropletLAMPmicrofluidicPCR

Identifiers

PMID31248141
PMCPMC6630468

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.