Evidence map›Paper›PMID 36636312›Full record

ArticleRoyal Society open science2023

Homogenization modelling of antibiotic diffusion and adsorption in viral liquid crystals.

M T van Rossem, S Wilks, P R Secor, M Kaczmarek, G D'Alessandro

Abstract read
In one paragraph

Article in Royal Society open science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Heterogenous biofilm mass-transport model replicates periphery sequestration of antibiotics inProceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  5. Article
  6. 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

5 authors.

M T van RossemPhysics and Astronomy, University of Southampton, Southampton SO17 1BJ, UK.ORCID 0000-0002-7232-0789
S WilksHealth Sciences, University of Southampton, Southampton SO17 1BJ, UK.
P R SecorDivision of Biological Sciences, University of Montana, Missoula, MT 59812, USA.
M KaczmarekPhysics and Astronomy, University of Southampton, Southampton SO17 1BJ, UK.
G D'AlessandroMathematical Sciences, University of Southampton, Southampton SO17 1BJ, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Systems of rod-shaped viruses have long been important to the science of living liquid crystals, as their monodispersity and uniform charge make them convenient model systems. Recently, it was shown that, upon the addition of polymers, suspensions of rod-shaped viruses form liquid crystals that are linked with increased tolerance of bacteria against antibiotics. We use homogenization to obtain effective equations describing antibiotic diffusion through these liquid crystals. The analytical results of homogenization are compared with numerical results from an exact microscopic model, showing good agreement and thus allowing us to identify the key parameters behind the process. Our modelling shows that the adsorption plays a key role in increasing antibiotic diffusion time and therefore the presence of nematic rod-shaped viruses may increase antibiotic tolerance through physical mechanisms alone. These results demonstrate the applicability of homogenization as an analytical tool to systems of liquid crystalline viruses, with relatively straightforward extension to more complex problems such as liquid crystalline biofilms, other biological liquid crystals and biological systems with different types of local structural order.

Indexed as

biofilmsdiffusionhomogenizationliquid crystalsmodellingP. aeruginosa

Identifiers

PMID36636312
PMCPMC9810422

What OpenQuestion holds

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Registered trials

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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.