Evidence map›Paper›PMID 30906555›Full record

ReviewEvolution, medicine, and public health2019

Evolutionary ecology meets the antibiotic crisis: Can we control pathogen adaptation through sequential therapy?

Roderich Roemhild, Hinrich Schulenburg

Abstract readReview
In one paragraph

Review in Evolution, medicine, and public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

  1. Review
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  3. Review
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  9. One Health in Medical Education: A Proposed Framework.Hawai'i journal of health & social welfare · 2024
    Article
  10. Article
  11. Article
  12. Evolution ofGut microbes · 2023
    Article
  13. Article
  14. Article
  15. Sequential antibiotic therapy in the laboratory and in the patient.Journal of the Royal Society, Interface · 2023
    Article
  16. Article
  17. Article
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  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

2 authors.

Roderich RoemhildDepartment of Evolutionary Ecology and Genetics, Zoological Institute, Christian-Albrechts-Universität zu Kiel, Am Botanischen Garten 1-9, Kiel, Germany.ORCID 0000-0001-9480-5261
Hinrich SchulenburgDepartment of Evolutionary Ecology and Genetics, Zoological Institute, Christian-Albrechts-Universität zu Kiel, Am Botanischen Garten 1-9, Kiel, Germany.ORCID 0000-0002-1413-913X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The spread of antibiotic resistance is a global challenge that is fueled by evolution and ecological processes. Therefore, the design of new sustainable therapy should take account of these underlying processes-as proposed within the field of evolutionary medicine, yet usually not receiving the necessary attention from national and international health agencies. We here put the spotlight on a currently neglected treatment strategy: sequential therapy. Changes among antibiotics generate fluctuating selection conditions that are in general difficult to counter by any organism. We argue that sequential treatment designs can be specifically optimized by exploiting evolutionary trade-offs, for example collateral sensitivity and/or inducible physiological constraints, such as negative hysteresis, where pre-exposure to one antibiotic induces temporary hyper-sensitivity to another antibiotic. Our commentary provides an overview of sequential treatment strategies and outlines steps towards their further optimization.

Indexed as

antagonistic pleiotropycollateral sensitivityfluctuating selectionnegative hysteresissequential therapy

Identifiers

PMID30906555
PMCPMC6423369

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.