Evidence map›Paper›PMID 34436682›Full record

ArticleJournal of mathematical biology2021

An investigation of tuberculosis progression revealing the role of macrophages apoptosis via sensitivity and bifurcation analysis.

Wenjing Zhang, Leif Ellingson, Federico Frascoli, Jane Heffernan

Open access · bronzeAbstract read
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Article in Journal of mathematical biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 42% 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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. Article
4 · The record

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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

4 authors at 3 institutions in 3 countries.

Wenjing ZhangDepartment of Mathematics and Statistics, Texas Tech University, Broadway and Boston, Lubbock, 79409-1042, TX, USA. wenjing.zhang@ttu.edu.ORCID 0000-0001-8779-5106
Leif EllingsonDepartment of Mathematics and Statistics, Texas Tech University, Broadway and Boston, Lubbock, 79409-1042, TX, USA.
Federico FrascoliDepartment of Mathematics, Faculty of Science, Engineering and Technology, Swinburne University of Technology, John St, 3122, Hawthorne, VIC, Australia.
Jane HeffernanDepartment of Mathematics and Statistics, Centre for Disease Modelling, York University, 4700 Keele St, Toronto, ON, M3J 1P3, Canada.
Texas Tech University · USSwinburne University of Technology · AUYork University · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mycobacterium tuberculosis infection features various disease outcomes: clearance, latency, active disease, and latent tuberculosis infection (LTBI) reactivation. Identifying the decisive factors for disease outcomes and progression is crucial to elucidate the macrophages-tuberculosis interaction and provide insights into therapeutic strategies. To achieve this goal, we first model the disease progression as a dynamical shift among different disease outcomes, which are characterized by various steady states of bacterial concentration. The causal mechanisms of steady-state transitions can be the occurrence of transcritical and saddle-node bifurcations, which are induced by slowly changing parameters. Transcritical bifurcation, occurring when the basic reproduction number equals to one, determines whether the infection clears or spreads. Saddle-node bifurcation is the key mechanism to create and destroy steady states. Based on these two steady-state transition mechanisms, we carry out two sample-based sensitivity analyses on transcritical bifurcation conditions and saddle-node bifurcation conditions. The sensitivity analysis results suggest that the macrophage apoptosis rate is the most significant factor affecting the transition in disease outcomes. This result agrees with the discovery that the programmed cell death (apoptosis) plays a unique role in the complex microorganism-host interplay. Sensitivity analysis narrows down the parameters of interest, but cannot answer how these parameters influence the model outcomes. To do this, we employ bifurcation analysis and numerical simulation to unfold various disease outcomes induced by the variation of macrophage apoptosis rate. Our findings support the hypothesis that the regulation mechanism of macrophage apoptosis affects the host immunity against tuberculosis infection and tuberculosis virulence. Moreover, our mathematical results suggest that new treatments and/or vaccines that regulate macrophage apoptosis in combination with weakening bacillary viability and/or promoting adaptive immunity could have therapeutic value.

Indexed as

Mycobacterium tuberculosisTuberculosisApoptosisBasic Reproduction NumberComputer SimulationHumansMacrophagesDisease progressionIn-host tuberculosis infection modelSensitivity analysis and bifurcation analysisTuberculosis treatments.

Identifiers

PMID34436682
PMCPMC8387667
OpenAlexW3193620403

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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.