Evidence map›Paper›PMID 33274447›Full record

ReviewAnnals of the New York Academy of Sciences2021

Understanding tolerance to cell wall-active antibiotics.

Tobias Dörr

Open access · hybridAbstract readReview
In one paragraph

Review in Annals of the New York Academy of Sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

28 citing papers in PubMed, 47 citations in OpenAlex.

  1. Review
  2. The Metabolic State ofACS infectious diseases · 2026
    Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. The innate immune protein calprotectin ablates the bactericidal activity of β-lactam antibiotics.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  8. Article
  9. Article
  10. Review
  11. Article
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  13. Article
  14. Lion's Mane Mushroom (Nutrients · 2025
    Review
  15. Review
  16. Article
  17. Review
  18. Article
  19. Article
  20. 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 at 1 institution in 1 country.

Tobias DörrWeill Institute for Cell and Molecular Biology, Department of Microbiology, and Cornell Institute of Host-Pathogen Interactions and Disease, Cornell University, Ithaca, New York.ORCID 0000-0003-3283-9161
Cornell University · US

Funding

Cell envelope stress responses and the mechanism of antibiotic tolerance in Gram-negative pathogensR01AI143704 · NIAID · CORNELL UNIVERSITY · PI DOERR, TOBIAS · 2019 to 2023
$2.0M
NIAID NIH HHS R01 AI143704
6 · The paper itself

Abstract

Antibiotic tolerance-the ability of bacteria to survive for an extended time in the presence of bactericidal antibiotics-is an understudied contributor to antibiotic treatment failure. Herein, I review the manifestations, mechanisms, and clinical relevance of tolerance to cell wall-active (CWA) antibiotics, one of the most important groups of antibiotics at the forefront of clinical use. I discuss definitions of tolerance and assays for tolerance detection, comprehensively discuss the mechanism of action of β-lactams and other CWA antibiotics, and then provide an overview of how cells mitigate the potentially lethal effects of CWA antibiotic-induced cell damage to become tolerant. Lastly, I discuss evidence for a role of CWA antibiotic tolerance in clinical antibiotic treatment failure.

Indexed as

Anti-Bacterial AgentsBacteriaCell WallMicrobial Sensitivity TestsAnti-Bacterial Agentsantibiotic toleranceautolysinsbeta lactamspeptidoglycanphenotypic tolerance

Identifiers

PMID33274447
PMCPMC8359209
OpenAlexW3109489801

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.