Evidence map›Paper›PMID 29902223›Full record

ArticlePloS one2018

Modelling of ciprofloxacin killing enhanced by hyperbaric oxygen treatment in Pseudomonas aeruginosa PAO1 biofilms.

Peter Alexander Vistar Gade, Terkel Bo Olsen, Peter Østrup Jensen, Mette Kolpen, Niels Høiby, Kaj-Åge Henneberg, Thomas Sams

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.4field-weighted citation impact, top 12% 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

13 citing papers in PubMed, 23 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Biofilm and wound healing: from bench to bedside.European journal of medical research · 2023
    Review
  6. Review
  7. Hyperbaric Oxygen Therapy and A-PRF Pre-Treated Implants in Severe Periodontitis: A Case Report.International journal of environmental research and public health · 2021
    Article
  8. Review
  9. Improved FRAP Measurements on Biofilms.Biophysical journal · 2020
    Article
  10. Review
  11. Review
  12. Article
  13. Tolerance and Resistance ofFrontiers in microbiology · 2019
    Review
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 2 institutions in 1 country.

Peter Alexander Vistar GadeBiomedical Engineering, Dept. of Electrical Engineering, Technical University of Denmark, DK-2800 Lyngby, Denmark.
Terkel Bo OlsenBiomedical Engineering, Dept. of Electrical Engineering, Technical University of Denmark, DK-2800 Lyngby, Denmark.
Peter Østrup JensenDepartment of Clinical Microbiology, Rigshospitalet, DK-2100 Copenhagen, Denmark.
Mette KolpenDepartment of Clinical Microbiology, Rigshospitalet, DK-2100 Copenhagen, Denmark.ORCID 0000-0001-5575-0384
Niels HøibyDepartment of Clinical Microbiology, Rigshospitalet, DK-2100 Copenhagen, Denmark.
Kaj-Åge HennebergBiomedical Engineering, Dept. of Electrical Engineering, Technical University of Denmark, DK-2800 Lyngby, Denmark.ORCID 0000-0001-9418-6587
Thomas SamsBiomedical Engineering, Dept. of Electrical Engineering, Technical University of Denmark, DK-2800 Lyngby, Denmark.ORCID 0000-0002-6316-2539
Technical University of Denmark · DKUniversity of Copenhagen · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

outlineIn chronic lung infections by Pseudomonas aeruginosa (PA) the bacteria thrive in biofilm structures protected from the immune system of the host and from antibiotic treatment. Increasing evidence suggests that the susceptibility of the bacteria to antibiotic treatment can be significantly enhanced by hyperbaric oxygen treatment. The aim of this study is to simulate the effect of ciprofloxacin treatment in a PAO1 biofilm model with aggregates in agarose when combined with hyperbaric oxygen treatment. This is achieved in a reaction-diffusion model that describes the combined effect of ciprofloxacin diffusion, oxygen diffusion and depletion, bacterial growth and killing, and adaptation of the bacteria to ciprofloxacin. In the model, the oxygen diffusion and depletion use a set of parameters derived from experimental results presented in this work. The part of the model describing ciprofloxacin killing uses parameter values from the literature in combination with our estimates (Jacobs, et al., 2016; Grillon, et al., 2016). Micro-respirometry experiments were conducted to determine the oxygen consumption in the P. aeruginosa strain PAO1. The parameters were validated against existing data from an HBOT experiment by Kolpen et al. (2017). The complete oxygen model comprises a reaction-diffusion equation describing the oxygen consumption by using a Michaelis-Menten reaction term. The oxygen model performed well in predicting oxygen concentrations in both time and depth into the biofilm. At 2.8 bar pure oxygen pressure, HBOT increases the penetration depth of oxygen into the biofilm almost by a of factor 4 in agreement with the scaling that follows from the stationary balance between the consumption term and diffusion term.

conclusionIn the full reaction-diffusion model we see that hyperbaric oxygen treatment significantly increases the killing by ciprofloxacin in a PAO1 biofilm in alignment with the experimental results from Kolpen et al. (Kolpen, et al., 2017; Kolpen, et al. 2016). The enhanced killing, in turn, lowers the oxygen consumption in the outer layers of the biofilm, and leads to even deeper penetration of oxygen into the biofilm.

Indexed as

Models, BiologicalAnti-Bacterial AgentsBiofilmsCiprofloxacinDrug SynergismMicrobial ViabilityOxygenOxygen ConsumptionPseudomonas aeruginosaAnti-Bacterial AgentsCiprofloxacinOxygen

Identifiers

PMID29902223
PMCPMC6002088
OpenAlexW2808130519

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.