Evidence map›Paper›PMID 28559484›Full record

ArticlemBio2017

Finding the Needle in the Haystack-the Use of Microfluidic Droplet Technology to Identify Vitamin-Secreting Lactic Acid Bacteria.

Jun Chen, Mike Vestergaard, Thomas Glasdam Jensen, Jing Shen, Martin Dufva, Christian Solem, Peter Ruhdal Jensen

Open access · goldAbstract read
In one paragraph

Article in mBio, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

19 citing papers in PubMed, 64 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Droplet-Based Microfluidic High Throughput Screening ofFrontiers in bioengineering and biotechnology · 2021
    Article
  11. Enhancement of amino acid production and secretion byMetabolic engineering communications · 2020
    Article
  12. Review
  13. EngineeringFrontiers in bioengineering and biotechnology · 2020
    Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Review
  19. Review
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

7 authors at 1 institution in 1 country.

Jun ChenNational Food Institute, Technical University of Denmark, Lyngby, Denmark junch@food.dtu.dk chso@food.dtu.dk.ORCID 0000-0002-4751-9315
Mike VestergaardNational Food Institute, Technical University of Denmark, Lyngby, Denmark.
Thomas Glasdam JensenDepartment of Micro- and Nanotechnology, Technical University of Denmark, Lyngby, Denmark.
Jing ShenNational Food Institute, Technical University of Denmark, Lyngby, Denmark.
Martin DufvaDepartment of Micro- and Nanotechnology, Technical University of Denmark, Lyngby, Denmark.
Christian SolemNational Food Institute, Technical University of Denmark, Lyngby, Denmark junch@food.dtu.dk chso@food.dtu.dk.
Peter Ruhdal JensenNational Food Institute, Technical University of Denmark, Lyngby, Denmark.
Technical University of Denmark · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Efficient screening technologies aim to reduce both the time and the cost required for identifying rare mutants possessing a phenotype of interest in a mutagenized population. In this study, we combined a mild mutagenesis strategy with high-throughput screening based on microfluidic droplet technology to identify

Indexed as

AnimalsFermentationGenetic EngineeringHigh-Throughput Screening AssaysLactococcus lactisMicrofluidicsMilkMutagenesisMutationPhenotypePurinesRiboflavinPurinesRiboflavinroseoflavinclassical mutagenesisdroplet microfluidicshigh-throughput screeninglactic acid bacteriavitamin B2

Identifiers

PMID28559484
PMCPMC5449655
OpenAlexW2618262793

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.