Evidence map›Paper›PMID 20140968›Full record

ArticleCytometry. Part A : the journal of the International Society for Analytical Cytology2010

Low-cost, high-throughput, automated counting of bacterial colonies.

Matthew L Clarke, Robert L Burton, A Nayo Hill, Maritoni Litorja, Moon H Nahm, Jeeseong Hwang

Abstract read
In one paragraph

Article in Cytometry. Part A : the journal of the International Society for Analytical Cytology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.

0numbers the graph read from it
0cells of the map it votes in
52citing 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

52 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. UMicroorganisms · 2024
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Machine learning for enumeration of cell colony forming units.Visual computing for industry, biomedicine, and art · 2022
    Article
  14. Review
  15. Article
  16. Article
  17. Dihydroconiferyl Ferulate Isolated fromPharmaceuticals (Basel, Switzerland) · 2022
    Article
  18. Article
  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

6 authors.

Matthew L ClarkeOptical Technology Division, Physics Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland 20899, USA.
Robert L Burton
A Nayo Hill
Maritoni Litorja
Moon H Nahm
Jeeseong Hwang

Funding

NIAID NIH HHS N01 AI030021
6 · The paper itself

Abstract

Research involving bacterial pathogens often requires enumeration of bacteria colonies. Here, we present a low-cost, high-throughput colony counting system consisting of colony counting software and a consumer-grade digital camera or document scanner. We demonstrate that this software, called "NICE" (NIST's Integrated Colony Enumerator), can count bacterial colonies as part of a high-throughput multiplexed opsonophagocytic killing assay used to characterize pneumococcal vaccine efficacy. The results obtained with NICE correlate well with the results obtained from manual counting, with a mean difference of less than 3%. NICE is also rapid; it can count colonies from multiple reaction wells within minutes and export the results to a spreadsheet for data processing. As this program is freely available from NIST, NICE should be helpful in bacteria colony enumeration required in many microbiological studies, and in standardizing colony counting methods.

Indexed as

AutomationColony Count, MicrobialEscherichia coliHigh-Throughput Screening AssaysReproducibility of ResultsTetrazolium SaltsTetrazolium Saltstriphenyltetrazolium

Identifiers

PMID20140968
PMCPMC2909336

What OpenQuestion holds

Textmetadata
LicenceTDM
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.