Evidence map›Paper›PMID 20081869›Full record

ReviewNature reviews. Drug discovery2010

Anti-virulence strategies to combat bacteria-mediated disease.

David A Rasko, Vanessa Sperandio

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Drug discovery, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 677 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
677citing papers in PubMed, 1 pooled it
–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

677 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Indole decreases the virulence of enterotoxigenic Escherichia coli.World journal of microbiology & biotechnology · 2026
    Article
  4. Anthranilate ReducesAntibiotics (Basel, Switzerland) · 2026
    Article
  5. Beyond the gut microbe: Rethinking infection, microbiome harmony, and the one-health continuum.World journal of gastrointestinal pharmacology and therapeutics · 2026
    Review
  6. Article
  7. Article
  8. mLife · 2026
    Article
  9. Review
  10. Review
  11. Article
  12. Collective fluctuations underlying nanobody inhibitory activity targetingbioRxiv : the preprint server for biology · 2026
    Article
  13. Article
  14. AnResearch square · 2026
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Article

617 more citing papers are in PubMed but not listed here.

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

2 authors.

David A RaskoDepartment of Microbiology and Immunology, Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland 21201, USA.
Vanessa Sperandio

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antibiotic resistance is one of the greatest challenges of the twenty-first century. However, the increasing understanding of bacterial pathogenesis and intercellular communication has revealed many potential strategies to develop novel drugs to treat bacteria-mediated disease. Interference with bacterial virulence and/or cell-to-cell signalling pathways is an especially compelling approach, as it is thought to apply less selective pressure for the development of bacterial resistance than traditional strategies, which are aimed at killing bacteria or preventing their growth. Here, we discuss the mechanisms of bacterial virulence and present promising anti-virulence strategies and compounds for the future treatment of bacterial infections.

Indexed as

Drug Resistance, BacterialAnimalsAnti-Bacterial AgentsBacteriaBacterial InfectionsDrug DesignHumansSignal TransductionVirulenceAnti-Bacterial Agents

Identifiers

PMID20081869

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.