Evidence map›Paper›PMID 32433644›Full record

ArticlePLoS computational biology2020

Modelling the dynamics of tuberculosis lesions in a virtual lung: Role of the bronchial tree in endogenous reinfection.

Martí Català, Jordi Bechini, Montserrat Tenesa, Ricardo Pérez, Mariano Moya, Cristina Vilaplana, Joaquim Valls, Sergio Alonso, Daniel López, Pere-Joan Cardona and 1 more

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2020. 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
0.2field-weighted citation impact, top 35% 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

6 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
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  5. SARS-CoV-2 andJournal of clinical tuberculosis and other mycobacterial diseases · 2021
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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

11 authors at 4 institutions in 1 country.

Martí CatalàComparative Medicine and Bioimage Centre of Catalonia (CMCiB), Fundació Institut d'Investigació en Ciències de la Salut Germans Trias i Pujol, Badalona, Catalonia, Spain.
Jordi BechiniServei de Radiodiagnòstic, Hospital Universitari Germans Trias i Pujol, Badalona, Catalonia, Spain.
Montserrat TenesaServei de Radiodiagnòstic, Hospital Universitari Germans Trias i Pujol, Badalona, Catalonia, Spain.
Ricardo PérezServei de Radiodiagnòstic, Hospital Universitari Germans Trias i Pujol, Badalona, Catalonia, Spain.
Mariano MoyaServei de Radiodiagnòstic, Hospital Universitari Germans Trias i Pujol, Badalona, Catalonia, Spain.
Cristina VilaplanaExperimental Tuberculosis Unit, Fundació Institut d'Investigació en Ciències de la Salut Germans Trias i Pujol, Universitat Autònoma de Barcelona, Can Ruti Campus, Edifici Mar, Badalona, Catalonia, Spain.ORCID 0000-0002-2808-7270
Joaquim VallsDepartament de Física, Universitat Politècnica de Catalunya, Castelldefels, Barcelona, Catalonia, Spain.ORCID 0000-0002-2346-5041
Sergio AlonsoDepartament de Física, Universitat Politècnica de Catalunya, Castelldefels, Barcelona, Catalonia, Spain.ORCID 0000-0002-3989-8757
Daniel LópezDepartament de Física, Universitat Politècnica de Catalunya, Castelldefels, Barcelona, Catalonia, Spain.
Pere-Joan CardonaComparative Medicine and Bioimage Centre of Catalonia (CMCiB), Fundació Institut d'Investigació en Ciències de la Salut Germans Trias i Pujol, Badalona, Catalonia, Spain.ORCID 0000-0001-5623-7873
Clara PratsDepartament de Física, Universitat Politècnica de Catalunya, Castelldefels, Barcelona, Catalonia, Spain.ORCID 0000-0002-1398-7559
Hospital Universitari Germans Trias i Pujol · ESUniversitat Politècnica de Catalunya · ESUniversitat Autònoma de Barcelona · ESInstitut d'Investigació en Ciències de la Salut Germans Trias i Pujol · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tuberculosis (TB) is an infectious disease that still causes more than 1.5 million deaths annually. The World Health Organization estimates that around 30% of the world's population is latently infected. However, the mechanisms responsible for 10% of this reserve (i.e., of the latently infected population) developing an active disease are not fully understood, yet. The dynamic hypothesis suggests that endogenous reinfection has an important role in maintaining latent infection. In order to examine this hypothesis for falsifiability, an agent-based model of growth, merging, and proliferation of TB lesions was implemented in a computational bronchial tree, built with an iterative algorithm for the generation of bronchial bifurcations and tubes applied inside a virtual 3D pulmonary surface. The computational model was fed and parameterized with computed tomography (CT) experimental data from 5 latently infected minipigs. First, we used CT images to reconstruct the virtual pulmonary surfaces where bronchial trees are built. Then, CT data about TB lesion' size and location to each minipig were used in the parameterization process. The model's outcome provides spatial and size distributions of TB lesions that successfully reproduced experimental data, thus reinforcing the role of the bronchial tree as the spatial structure triggering endogenous reinfection. A sensitivity analysis of the model shows that the final number of lesions is strongly related with the endogenous reinfection frequency and maximum growth rate of the lesions, while their mean diameter mainly depends on the spatial spreading of new lesions and the maximum radius. Finally, the model was used as an in silico experimental platform to explore the transition from latent infection to active disease, identifying two main triggering factors: a high inflammatory response and the combination of a moderate inflammatory response with a small breathing amplitude.

Indexed as

AlgorithmsAnimalsAntitubercular AgentsBronchiCommunicable DiseasesComputer SimulationFemaleHumansLungModels, TheoreticalMycobacterium tuberculosisSwineTomography, X-Ray ComputedTuberculosisTuberculosis, PulmonaryAntitubercular Agents

Identifiers

PMID32433644
PMCPMC7239440
OpenAlexW3027956949

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.