Evidence map›Paper›PMID 29723210›Full record

ArticlePLoS computational biology2018

Predictive modelling of a novel anti-adhesion therapy to combat bacterial colonisation of burn wounds.

Paul A Roberts, Ryan M Huebinger, Emma Keen, Anne-Marie Krachler, Sara Jabbari

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.5field-weighted citation impact, top 17% 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

3 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Article
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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

5 authors at 2 institutions in 2 countries.

Paul A RobertsSchool of Mathematics, University of Birmingham, Edgbaston, Birmingham, United Kingdom.ORCID 0000-0001-5293-6431
Ryan M HuebingerDepartment of Surgery, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America.
Emma KeenInstitute of Microbiology and Infection, School of Biosciences, University of Birmingham, Edgbaston, Birmingham, United Kingdom.
Anne-Marie KrachlerDepartment of Microbiology and Molecular Genetics, University of Texas McGovern Medical School at Houston, Houston, Texas, United States of America.ORCID 0000-0002-0936-0016
Sara JabbariSchool of Mathematics, University of Birmingham, Edgbaston, Birmingham, United Kingdom.ORCID 0000-0001-5235-0406
University of Birmingham · GBThe University of Texas Southwestern Medical Center · US

Funding

Mechanoregulation of EHEC virulenceR01AI132354 · NIAID · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI Anne-Marie Krachler · 2018 to 2026
$3.5M
Medical Research Council MC_PC_16066NIAID NIH HHS R01 AI132354Wellcome Trust
6 · The paper itself

Abstract

As the development of new classes of antibiotics slows, bacterial resistance to existing antibiotics is becoming an increasing problem. A potential solution is to develop treatment strategies with an alternative mode of action. We consider one such strategy: anti-adhesion therapy. Whereas antibiotics act directly upon bacteria, either killing them or inhibiting their growth, anti-adhesion therapy impedes the binding of bacteria to host cells. This prevents bacteria from deploying their arsenal of virulence mechanisms, while simultaneously rendering them more susceptible to natural and artificial clearance. In this paper, we consider a particular form of anti-adhesion therapy, involving biomimetic multivalent adhesion molecule 7 coupled polystyrene microbeads, which competitively inhibit the binding of bacteria to host cells. We develop a mathematical model, formulated as a system of ordinary differential equations, to describe inhibitor treatment of a Pseudomonas aeruginosa burn wound infection in the rat. Benchmarking our model against in vivo data from an ongoing experimental programme, we use the model to explain bacteria population dynamics and to predict the efficacy of a range of treatment strategies, with the aim of improving treatment outcome. The model consists of two physical compartments: the host cells and the exudate. It is found that, when effective in reducing the bacterial burden, inhibitor treatment operates both by preventing bacteria from binding to the host cells and by reducing the flux of daughter cells from the host cells into the exudate. Our model predicts that inhibitor treatment cannot eliminate the bacterial burden when used in isolation; however, when combined with regular or continuous debridement of the exudate, elimination is theoretically possible. Lastly, we present ways to improve therapeutic efficacy, as predicted by our mathematical model.

Indexed as

AnimalsAnti-Bacterial AgentsBacterial AdhesionBacterial InfectionsBurnsComputational BiologyDisease Models, AnimalModels, StatisticalRatsRats, Sprague-DawleyWound InfectionAnti-Bacterial Agents

Identifiers

PMID29723210
PMCPMC5933687
OpenAlexW2963042980

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.