Evidence map›Paper›PMID 17402841›Full record

ReviewExpert review of anti-infective therapy2007

Novel approaches to bacterial infection therapy by interfering with bacteria-to-bacteria signaling.

Vanessa Sperandio

Abstract readReview
In one paragraph

Review in Expert review of anti-infective therapy, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Article
  6. Anti-biofilm and Anti-Virulence Efficacy of Celastrol AgainstInternational journal of medical sciences · 2018
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Review
  13. Article
  14. Review
  15. 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

1 author.

Vanessa SperandioUniversity of Texas Southwestern Medical Center, Dept of Microbiology, 5325 Harry Hines Blvd, Dallas, TX 75390-9048, USA. vanessa.sperandio@utsouthwestern.edu

Funding

Quorum sensing regulation of EHEC virulence genesR01AI053067 · NIAID · UT SOUTHWESTERN MEDICAL CENTER · PI SPERANDIO, VANESSA · 2003 to 2017
$6.3M
EHEC interactions with the normal intestinal floraR21AI054468 · NIAID · UNIVERSITY OF TEXAS SW MED CTR/DALLAS · PI SPERANDIO, VANESSA · 2003 to 2004
$468k
Screen for Quorum Sensing Molecular Inhibitors (RMI)R03NS053582 · NINDS · UNIVERSITY OF TEXAS SW MED CTR/DALLAS · PI SPERANDIO, VANESSA · 2005 to 2005
$78k
NIAID NIH HHS R01 AI053067NIAID NIH HHS R21 AI054468NINDS NIH HHS R03 NS053582
6 · The paper itself

Abstract

The growing challenge of antimicrobial resistance and the paucity of novel antibiotics underscore the importance of developing novel therapeutics. Bacterial cell-to-cell signaling constitutes a novel drug target. Quorum sensing (QS) is a cell-to-cell signaling mechanism that refers to the ability of bacteria to respond to chemical hormone-like molecules called autoinducers. QS is responsible for controlling a plethora of virulence genes in several bacterial pathogens. Antagonists to autoinducers will intercept bacterial intercellular communication, hindering their ability to act in a coordinated manner to express virulence traits. Moreover, since QS is not involved directly in essential processes, such as bacterial growth, one can reason that inhibition of QS will not yield a selective pressure for the development of resistance.

Indexed as

AnimalsAnti-Bacterial AgentsBacterial InfectionsGene Expression Regulation, BacterialHumansQuorum SensingSignal TransductionTechnology, PharmaceuticalAnti-Bacterial Agents

Identifiers

PMID17402841
PMCPMC2613682

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.