Evidence map›Paper›PMID 38664343›Full record

ArticleBulletin of mathematical biology2024

A Genuinely Hybrid, Multiscale 3D Cancer Invasion and Metastasis Modelling Framework.

Dimitrios Katsaounis, Nicholas Harbour, Thomas Williams, Mark Aj Chaplain, Nikolaos Sfakianakis

Open access · hybridAbstract read
In one paragraph

Article in Bulletin of mathematical biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.2field-weighted citation impact, top 26% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  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 at 3 institutions in 2 countries.

Dimitrios KatsaounisSchool of Mathematics and Statistics, University St Andrews, North Haugh, St Andrews, UK. dk204@st-andrews.ac.uk.ORCID http://orcid.org/0009-0002-7918-9805
Nicholas HarbourSchool of Mathematical Sciences, University Nottingham, Nottingham, UK.
Thomas WilliamsSchool of Mathematics and Statistics, The University of Melbourne, Melbourne, Australia.
Mark Aj ChaplainSchool of Mathematics and Statistics, University St Andrews, North Haugh, St Andrews, UK.
Nikolaos SfakianakisSchool of Mathematics and Statistics, University St Andrews, North Haugh, St Andrews, UK.
University of St Andrews · GBThe University of Melbourne · AUUniversity of Nottingham · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We introduce in this paper substantial enhancements to a previously proposed hybrid multiscale cancer invasion modelling framework to better reflect the biological reality and dynamics of cancer. These model updates contribute to a more accurate representation of cancer dynamics, they provide deeper insights and enhance our predictive capabilities. Key updates include the integration of porous medium-like diffusion for the evolution of Epithelial-like Cancer Cells and other essential cellular constituents of the system, more realistic modelling of Epithelial-Mesenchymal Transition and Mesenchymal-Epithelial Transition models with the inclusion of Transforming Growth Factor beta within the tumour microenvironment, and the introduction of Compound Poisson Process in the Stochastic Differential Equations that describe the migration behaviour of the Mesenchymal-like Cancer Cells. Another innovative feature of the model is its extension into a multi-organ metastatic framework. This framework connects various organs through a circulatory network, enabling the study of how cancer cells spread to secondary sites.

Indexed as

Epithelial-Mesenchymal TransitionMathematical ConceptsModels, BiologicalNeoplasm InvasivenessNeoplasm MetastasisNeoplasmsTumor MicroenvironmentCell MovementComputer SimulationHumansPoisson DistributionStochastic ProcessesTransforming Growth Factor betaTransforming Growth Factor betaCancer invasionCoupled partial and stochastic partial differential equationsHybrid continuum-discreteMultiscale modelling

Identifiers

PMID38664343
PMCPMC11045634
OpenAlexW4395448351

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.