Evidence map›Paper›PMID 40388053›Full record

ArticleBulletin of mathematical biology2025

Spatial Segregation Across Travelling Fronts in Individual-Based and Continuum Models for the Growth of Heterogeneous Cell Populations.

José A Carrillo, Tommaso Lorenzi, Fiona R Macfarlane

Abstract read
In one paragraph

Article in Bulletin of mathematical biology, 2025. 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
–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

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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

1 citing paper in PubMed.

  1. Review
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

3 authors.

José A CarrilloMathematical Institute, University of Oxford, Oxford, UK. carrillo@maths.ox.ac.uk.ORCID http://orcid.org/0000-0001-8819-4660
Tommaso LorenziDepartment of Mathematical Sciences "G. L. Lagrange", Politecnico di Torino, Turin, Italy.ORCID https://orcid.org/0000-0001-9165-1666
Fiona R MacfarlaneSchool of Mathematics and Statistics, University of St Andrews, St Andrews, UK.

Funding

Engineering and Physical Sciences Research Council EP/V051121/1European Research Council Executive Agency 883363European Union - Next Generation EU P2022Z7ZAJItalian Ministry of University and Research (MUR) 2020JLWP23"Maria de Maeztu" Excellence Unit CEX2020-001105-M
6 · The paper itself

Abstract

We consider a partial differential equation model for the growth of heterogeneous cell populations subdivided into multiple distinct discrete phenotypes. In this model, cells preferentially move towards regions where they are less compressed, and thus their movement occurs down the gradient of the cellular pressure. The cellular pressure is defined as a weighted sum of the densities (i.e. the volume fractions) of cells with different phenotypes. To translate into mathematical terms the idea that cells with distinct phenotypes have different morphological and mechanical properties, both the cell mobility and the weighted amount the cells contribute to the cellular pressure vary with their phenotype. We formally derive this model as the continuum limit of an on-lattice individual-based model, where cells are represented as single agents undergoing a branching biased random walk corresponding to phenotype-dependent and pressure-regulated cell division, death, and movement. Then, we study travelling wave solutions whereby cells with different phenotypes are spatially segregated across the invading front. Finally, we report on numerical simulations of the two models, demonstrating excellent agreement between them and the travelling wave analysis. The results presented here indicate that inter-cellular variability in mobility can support the maintenance of spatial segregation across invading fronts, whereby cells with a higher mobility drive invasion by occupying regions closer to the front edge.

Indexed as

Models, BiologicalCell DivisionCell MovementCell ProliferationComputer SimulationHumansMathematical ConceptsPhenotypeContinuum modelsIndividual-based modelsPhenotypic heterogeneitySpatial segregationTravelling waves

Identifiers

PMID40388053
PMCPMC12089248

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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.