Evidence map›Paper›PMID 33712945›Full record

ArticleJournal of mathematical biology2021

A novel mathematical model of heterogeneous cell proliferation.

Sean T Vittadello, Scott W McCue, Gency Gunasingh, Nikolas K Haass, Matthew J Simpson

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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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

5 authors.

Sean T VittadelloSchool of Mathematical Sciences, Queensland University of Technology, Brisbane, QLD, Australia. sean.vittadello@unimelb.edu.au.ORCID 0000-0002-4476-6732
Scott W McCueSchool of Mathematical Sciences, Queensland University of Technology, Brisbane, QLD, Australia.ORCID 0000-0001-5304-2384
Gency GunasinghThe University of Queensland Diamantina Institute, The University of Queensland, Brisbane, QLD, Australia.
Nikolas K HaassThe University of Queensland Diamantina Institute, The University of Queensland, Brisbane, QLD, Australia.ORCID 0000-0002-3928-5360
Matthew J SimpsonSchool of Mathematical Sciences, Queensland University of Technology, Brisbane, QLD, Australia.ORCID 0000-0001-6254-313X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present a novel mathematical model of heterogeneous cell proliferation where the total population consists of a subpopulation of slow-proliferating cells and a subpopulation of fast-proliferating cells. The model incorporates two cellular processes, asymmetric cell division and induced switching between proliferative states, which are important determinants for the heterogeneity of a cell population. As motivation for our model we provide experimental data that illustrate the induced-switching process. Our model consists of a system of two coupled delay differential equations with distributed time delays and the cell densities as functions of time. The distributed delays are bounded and allow for the choice of delay kernel. We analyse the model and prove the nonnegativity and boundedness of solutions, the existence and uniqueness of solutions, and the local stability characteristics of the equilibrium points. We find that the parameters for induced switching are bifurcation parameters and therefore determine the long-term behaviour of the model. Numerical simulations illustrate and support the theoretical findings, and demonstrate the primary importance of transient dynamics for understanding the evolution of many experimental cell populations.

Indexed as

Cell ProliferationModels, BiologicalCell CountCell DivisionComputer SimulationEukaryotic CellsNeoplasmsAsymmetric cell divisionDelay differential equationDistributed time delayInduced switchingIntegrodifferential equationTransient dynamics

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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.