Evidence map›Paper›PMID 28588268›Full record

ArticleScientific reports2017

Optimisation of a murine splenocyte mycobacterial growth inhibition assay using virulent Mycobacterium tuberculosis.

Christina Jensen, Line Lindebo Holm, Erik Svensson, Claus Aagaard, Morten Ruhwald

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
1.6field-weighted citation impact, top 18% 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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. TheF1000Research · 2021
    Article
  7. Article
  8. Article
  9. Observational
  10. Article
  11. Frontiers in immunology · 2019
    Article
  12. Article
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  14. Frontiers in immunology · 2018
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Christina JensenDepartment of Infectious Disease Immunology, Statens Serum Institut, Copenhagen, Denmark.
Line Lindebo HolmDepartment of Infectious Disease Immunology, Statens Serum Institut, Copenhagen, Denmark.
Erik SvenssonInternational Reference Laboratory of Mycobacteriology, Statens Serum Institut, Copenhagen, Denmark.ORCID 0000-0003-0797-1080
Claus AagaardDepartment of Infectious Disease Immunology, Statens Serum Institut, Copenhagen, Denmark.ORCID 0000-0001-6433-3056
Morten RuhwaldDepartment of Infectious Disease Immunology, Statens Serum Institut, Copenhagen, Denmark. moru@ssi.dk.ORCID 0000-0002-1597-441X
Statens Serum Institut · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the absence of a validated correlate of protection or robust animal models for human tuberculosis, Mycobacterial growth inhibition assays (MGIAs) aim to assess vaccines ability to inhibit mycobacterial growth in-vitro. We optimised a reproducible murine splenocyte MGIA based on in-vitro infection with virulent Mycobacterium tuberculosis (M.tb) Erdman. We identified splenocyte viability as a problem in state-of-art MGIA protocols, which can be improved by simple changes in culture conditions (viability increase from 21% to 46% at last day of culture). The growth inhibitory potential in mice immunised with either BCG, H56:CAF01 or H56:CAF01 administered side-by-side with BCG was significantly better compared to placebo in all groups (0.3 log

Indexed as

AnimalsCytokinesFemaleMiceMycobacterium bovisMycobacterium tuberculosisSpleenT-LymphocytesTuberculosisVaccinationVirulenceCytokines

Identifiers

PMID28588268
PMCPMC5460210
OpenAlexW2619585973

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.