Evidence map›Paper›PMID 24564297›Full record

ReviewBMC infectious diseases2014

Reflections on the immunology of tuberculosis: will we ever unravel the skein?

Maurizio de Martino, Luisa Galli, Elena Chiappini

Abstract readReview
In one paragraph

Review in BMC infectious diseases, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Immune Response toFrontiers in pediatrics · 2019
    Review
  5. Article
  6. Frontiers in immunology · 2017
    Article
  7. Article
  8. Article
  9. Article
  10. 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.

Maurizio de Martino
Luisa Galli
Elena Chiappini

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many and large dumps exist in our knowledge about Mycobacterium tuberculosis infection and disease in infants and children. We still do not understand why some individuals do acquire and others do not acquire the infection in the presence of the same risk factors. We do not understand why some individuals convert from latent to active tuberculosis and why other individuals convert from active to inactive tuberculosis even without treatment. As a matter of fact the immune system mounts a bouncing, robust and polyedral defence against Mycobacterium tuberculosis, but the bacillus is so much artful and dextrous that it has ahead from this immunological fierce accoutrements. Mycobacterium tuberculosis survival, multiplication, and transmission are largely favoured by the immune mechanisms. The granuloma itself is more bacillus- than host-protective. These abilities make Mycobacterium tuberculosis one of more successful human pathogens, but dumps in our knowledge and the counterproductive immunity hinder development of new diagnostics, therapies and vaccines. This occurs in front of an infection which engages one third of the world population and a disease which kills in a year about 1.5 million individuals worldwide. Understanding mechanisms and meaning of immune response in tuberculosis marks out the foundations of strategies with a view to prepare effective vaccines and reliable diagnostic tools as well as to build up therapeutic weapons. To gain these objectives is vital and urgent considering that tuberculosis is a common cause of morbidity and is a leading cause of death.

Indexed as

Adaptive ImmunityAntibodiesB-LymphocytesGranulomaHumansImmunity, InnateLatent TuberculosisMycobacterium tuberculosisTuberculosisTuberculosis VaccinesAntibodiesTuberculosis Vaccines

Identifiers

PMID24564297
PMCPMC4015689

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.