Evidence map›Paper›PMID 32634369›Full record

ArticleJournal of the Royal Society, Interface2020

A data-based mathematical modelling study to quantify the effects of ciprofloxacin and ampicillin on the within-host dynamics of

Myrto Vlazaki, Omar Rossi, David J Price, Callum McLean, Andrew J Grant, Pietro Mastroeni, Olivier Restif

Open access · bronzeAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of the Royal Society, Interface, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.9field-weighted citation impact, top 24% 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

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Antibiotic-recalcitrant Salmonella during infection.Nature reviews. Microbiology · 2025
    Review
  2. Article
  3. Tissue compartmentalization enablesProceedings of the National Academy of Sciences of the United States of America · 2021
    Article
  4. 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

7 authors at 3 institutions in 3 countries.

Myrto VlazakiDepartment of Veterinary Medicine, University of Cambridge, Madingley Road, Cambridge CB3 0ES, UK.
Omar RossiGSK Vaccines Institute for Global Health, Via Fiorentina 1, 53100 Siena, Italy.
David J PriceCentre of Epidemiology and Biostatistics, University of Melbourne, Grattan Street, Parkville, Victoria 3010, Australia.
Callum McLeanDepartment of Veterinary Medicine, University of Cambridge, Madingley Road, Cambridge CB3 0ES, UK.
Andrew J GrantDepartment of Veterinary Medicine, University of Cambridge, Madingley Road, Cambridge CB3 0ES, UK.
Pietro MastroeniDepartment of Veterinary Medicine, University of Cambridge, Madingley Road, Cambridge CB3 0ES, UK.
Olivier RestifDepartment of Veterinary Medicine, University of Cambridge, Madingley Road, Cambridge CB3 0ES, UK.
University of Cambridge · GBThe University of Melbourne · AUToscana Life Sciences · IT

Funding

Biotechnology and Biological Sciences Research Council BB/M020193
6 · The paper itself

Abstract

Antibiotic therapy has drastically reduced the mortality and sequelae of bacterial infections. From naturally occurring to chemically synthesized, different classes of antibiotics have been successfully used without detailed knowledge of how they affect bacterial dynamics

Indexed as

CiprofloxacinSalmonella entericaAmpicillinAnimalsAnti-Bacterial AgentsHumansMiceMicrobial Sensitivity TestsModels, TheoreticalRecurrenceAmpicillinAnti-Bacterial AgentsCiprofloxacinbacterial persistencedata-based modelheterogeneityisogenic tagged strainsmechanistic modelmodel selection

Identifiers

PMID32634369
PMCPMC7423434
OpenAlexW3038895504

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.