Evidence map›Paper›PMID 24843148›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2014

Exploring the collaboration between antibiotics and the immune response in the treatment of acute, self-limiting infections.

Peter Ankomah, Bruce R Levin

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 83 papers.

0numbers the graph read from it
0cells of the map it votes in
83citing 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

83 citing papers in PubMed.

  1. Two-dayTherapeutic advances in respiratory disease
    Trial
  2. Article
  3. Article
  4. Article
  5. Climate change and antimicrobial resistance.Nature reviews. Microbiology · 2026
    Review
  6. Review
  7. Review
  8. Review
  9. Antibiotic killing of drug-induced bacteriostatic cells.Antimicrobial agents and chemotherapy · 2025
    Article
  10. Article
  11. Article
  12. Review
  13. Toward better cures forClinical microbiology reviews · 2024
    Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Antibiotic killing of drug-induced bacteriostatic cells.bioRxiv : the preprint server for biology · 2024
    Article
  19. Article
  20. Review

23 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.

Peter AnkomahDepartment of Biology, Emory University, Atlanta, GA 30322.
Bruce R LevinDepartment of Biology, Emory University, Atlanta, GA 30322 blevin@emory.edu.

Funding

NIGMS NIH HHS GM098175
6 · The paper itself

Abstract

The successful treatment of bacterial infections is the product of a collaboration between antibiotics and the host's immune defenses. Nevertheless, in the design of antibiotic treatment regimens, few studies have explored the combined action of antibiotics and the immune response to clearing infections. Here, we use mathematical models to examine the collective contribution of antibiotics and the immune response to the treatment of acute, self-limiting bacterial infections. Our models incorporate the pharmacokinetics and pharmacodynamics of the antibiotics, the innate and adaptive immune responses, and the population and evolutionary dynamics of the target bacteria. We consider two extremes for the antibiotic-immune relationship: one in which the efficacy of the immune response in clearing infections is directly proportional to the density of the pathogen; the other in which its action is largely independent of this density. We explore the effect of antibiotic dose, dosing frequency, and term of treatment on the time before clearance of the infection and the likelihood of antibiotic-resistant bacteria emerging and ascending. Our results suggest that, under most conditions, high dose, full-term therapy is more effective than more moderate dosing in promoting the clearance of the infection and decreasing the likelihood of emergence of antibiotic resistance. Our results also indicate that the clinical and evolutionary benefits of increasing antibiotic dose are not indefinite. We discuss the current status of data in support of and in opposition to the predictions of this study, consider those elements that require additional testing, and suggest how they can be tested.

Indexed as

Adaptive ImmunityAnti-Bacterial AgentsBacteriaBacterial InfectionsComputer SimulationDose-Response Relationship, DrugDrug Resistance, MicrobialHumansModels, TheoreticalTreatment OutcomeAnti-Bacterial Agentsimmunologypopulation dynamics

Identifiers

PMID24843148
PMCPMC4060691

What OpenQuestion holds

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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.