Evidence map›Paper›PMID 28002883›Full record

ReviewBritish journal of pharmacology2017

Cholesterol metabolism: a potential therapeutic target in Mycobacteria.

Areej Abuhammad

Open access · bronzeAbstract readReview
In one paragraph

Review in British journal of pharmacology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
2.9field-weighted citation impact, top 9% 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

25 citing papers in PubMed, 45 citations in OpenAlex.

  1. Safety and Effects ofNutrients · 2023
    Trial
  2. Review
  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. TargetingRSC medicinal chemistry · 2023
    Review
  9. Review
  10. Article
  11. Pathogens (Basel, Switzerland) · 2023
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Nicotinamide and Demographic and Disease transitions: Moderation is Best.International journal of tryptophan research : IJTR · 2019
    Review
  18. Review
  19. Article
  20. 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

1 author at 1 institution in 1 country.

Areej AbuhammadSchool of Pharmacy, The University of Jordan, Amman, Jordan.
University of Jordan · JO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tuberculosis (TB), although a curable disease, is still one of the most difficult infections to treat. Mycobacterium tuberculosis infects 10 million people worldwide and kills 1.5 million people each year. Reactivation of a latent infection is the major cause of TB. Cholesterol is a critical carbon source during latent infection. Catabolism of cholesterol contributes to the pool of propionyl-CoA, a precursor that is incorporated into lipid virulence factors. The M. tuberculosis genome contains a large regulon of cholesterol catabolic genes suggesting that the microorganism can utilize host sterol for infection and persistence. The protein products of these genes present ideal targets for rational drug discovery programmes. This review summarizes the development of enzyme inhibitors targeting the cholesterol pathway in M. tuberculosis. This knowledge is essential for the discovery of novel agents to treat M. tuberculosis infection. LINKED ARTICLES: This article is part of a themed section on Drug Metabolism and Antibiotic Resistance in Micro-organisms. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v174.14/issuetoc.

Indexed as

Anti-Bacterial AgentsCholesterolDrug DiscoveryHumansMycobacterium tuberculosisTuberculosisAnti-Bacterial AgentsCholesterol

Identifiers

PMID28002883
PMCPMC5481656
OpenAlexW2564932068

What OpenQuestion holds

Textmetadata
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.