Evidence map›Paper›PMID 32771534›Full record

ArticleJournal of theoretical biology2020

Modelling the effects of environmental heterogeneity within the lung on the tuberculosis life-cycle.

Michael J Pitcher, Ruth Bowness, Simon Dobson, Raluca Eftimie, Stephen H Gillespie

Open access · hybridAbstract read
In one paragraph

Article in Journal of theoretical biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.2field-weighted citation impact, top 39% 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

7 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Review
  3. Within-Host Mathematical Models of Antibiotic Resistance.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  4. Article
  5. Article
  6. Article
  7. Field Grand Challenge Frontiers in Antibiotics.Frontiers in antibiotics · 2022
    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 at 2 institutions in 1 country.

Michael J PitcherSchool of Immunology and Microbial Sciences, King's College London, United Kingdom; School of Computer Science, University of St Andrews, United Kingdom. Electronic address: michael.pitcher@kcl.ac.uk.
Ruth BownessSchool of Medicine, University of St Andrews, United Kingdom.
Simon DobsonSchool of Computer Science, University of St Andrews, United Kingdom.
Raluca EftimieSchool of Science and Engineering, University of Dundee, United Kingdom.
Stephen H GillespieSchool of Medicine, University of St Andrews, United Kingdom.
University of St Andrews · GBUniversity of Dundee · GB

Funding

Medical Research Council MR/P014704/1Medical Research Council MR/P014704/2
6 · The paper itself

Abstract

Progress in shortening the duration of tuberculosis (TB) treatment is hampered by the lack of a predictive model that accurately reflects the diverse environment within the lung. This is important as TB has been shown to produce distinct localisations to different areas of the lung during different disease stages, with the environmental heterogeneity within the lung of factors such as air ventilation, blood perfusion and oxygen tension believed to contribute to the apical localisation witnessed during the post-primary form of the disease. Building upon our previous model of environmental lung heterogeneity, we present a networked metapopulation model that simulates TB across the whole lung, incorporating these notions of environmental heterogeneity across the whole TB life-cycle to show how different stages of the disease are influenced by different environmental and immunological factors. The alveolar tissue in the lung is divided into distinct patches, with each patch representing a portion of the total tissue and containing environmental attributes that reflect the internal conditions at that location. We include populations of bacteria and immune cells in various states, and events are included which determine how the members of the model interact with each other and the environment. By allowing some of these events to be dependent on environmental attributes, we create a set of heterogeneous dynamics, whereby the location of the tissue within the lung determines the disease pathological events that occur there. Our results show that the environmental heterogeneity within the lung is a plausible driving force behind the apical localisation during post-primary disease. After initial infection, bacterial levels will grow in the initial infection location at the base of the lung until an adaptive immune response is initiated. During this period, bacteria are able to disseminate and create new lesions throughout the lung. During the latent stage, the lesions that are situated towards the apex are the largest in size, and once a post-primary immune-suppressing event occurs, it is the uppermost lesions that reach the highest levels of bacterial proliferation. Our sensitivity analysis also shows that it is the differential in blood perfusion, causing reduced immune activity towards the apex, which has the biggest influence of disease outputs.

Indexed as

Mycobacterium tuberculosisTuberculosisHumansLungBacteriaComputational biologyLocalisationLungMetapopulationTuberculosisWithin–host model

Identifiers

PMID32771534
PMCPMC7511696
OpenAlexW3048311904

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.