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Cancer is a complex disease and thus is complicated to model. However, simple models that describe the main processes involved in tumoral dynamics, e.g., competition and mutation, can give us clues about cancer behaviour, at least…

动力系统 · 数学 2014-11-25 V. Castillo , J. Tomas Lazaro , J. Sardanyes

This paper explores fluctuations and noise in various facets of cancer development. The three areas of particular focus are the stochastic progression of cells to cancer, fluctuations of the tumor size during treatment, and noise in cancer…

细胞行为 · 定量生物学 2009-11-10 Matthew J. Berryman , Sabrina L. Spencer , Andrew Allison , Derek Abbott

We consider a phase-field model of prostate cancer growth with chemotherapy and antiangiogenic therapy effects which is introduced in [2]. It is comprised of phase-field equation to describe tumor growth, which is coupled to a…

偏微分方程分析 · 数学 2020-10-22 Tania Biswas , Elisabetta Rocca

Major efforts to sequence cancer genomes are now occurring throughout the world. Though the emerging data from these studies are illuminating, their reconciliation with epidemiologic and clinical observations poses a major challenge. In the…

We argue that volumetric growth dynamics of a solid cancer depend on the tumor system's overall surface extension. While this at first may seem evident, to our knowledge, so far no theoretical argument has been presented explaining this…

组织与器官 · 定量生物学 2007-05-23 Thomas S. Deisboeck , Caterina Guiot , Pier Paolo Delsanto , Nicola Pugno

Autopsy studies of adults dying of non-cancer causes have shown that virtually all of us possess occult, cancerous lesions. This suggests that, for most individuals, cancer will become dormant and not progress, while only in some will it…

定量方法 · 定量生物学 2014-06-06 Sébastien Benzekry , Alberto Gandolfi , Philip Hahnfeldt

Cancer cells co-cultured in vitro reveal unexpected differential growth rates that classical exponential growth models cannot account for. Two non-interacting cell lines were grown in the same culture, and counts of each species were…

定量方法 · 定量生物学 2014-12-04 Agnès Hamon , Marie Tosolini , Bernard Ycart , Pont Frédéric , Jean-Jacques Fournié

In this study, the analytic expressions of the steady probability distribution of tumor cells were established based on the steady state solution to the corresponding Fokker-Planck equation. Then, the effects of two uncorrelated white…

数据分析、统计与概率 · 物理学 2015-06-05 Ning Xing Wang , Xiao Miao Zhang , Xiao Bing Han

We present a mathematical model that describes how tumour heterogeneity evolves in a tissue slice that is oxygenated by a single blood vessel. Phenotype is identified with the stemness level of a cell, $s$, that determines its proliferative…

细胞行为 · 定量生物学 2023-11-14 Giulia L. Celora , Helen M. Byrne , P. G. Kevrekidis

We consider a macroscopic model for the growth of living tissues incorporating pressure-driven dispersal and pressure-modulated proliferation. Assuming a power-law relation between the mechanical pressure and the cell density, the model can…

偏微分方程分析 · 数学 2024-03-29 Tomasz Dębiec , Piotr Gwiazda , Błażej Miasojedow , Zuzanna Szymańska

The aim of this paper is to discuss the role of robustness and diversity in population dynamics in particular to some properties of the multi-step from healthy tissue to fully malignant tumours. Recent evidence shows that diversity within…

种群与进化 · 定量生物学 2010-03-12 Tomas Alarcon , Henrik Jeldtoft Jensen

Both compressible and incompressible porous medium models are used in the literature to describe the mechanical properties of living tissues. These two classes of models can be related using a stiff pressure law. In the incompressible…

偏微分方程分析 · 数学 2020-06-25 Noemi David , Benoît Perthame

We analyze a phase field model for tumor growth consisting of a Cahn-Hilliard-Brinkman system, ruling the evolution of the tumor mass, coupled with an advection-reaction-diffusion equation for a chemical species acting as a nutrient. The…

偏微分方程分析 · 数学 2023-07-26 Pierluigi Colli , Gianni Gilardi , Andrea Signori , Jürgen Sprekels

In this work, we present and analyze a system of PDEs, which models tumor growth by considering chemotaxis, active transport, and random effects. The stochasticity of the system is modelled by random initial data and Wiener noises that…

偏微分方程分析 · 数学 2023-12-12 Marvin Fritz , Luca Scarpa

We have previously reported that a universal growth law, as proposed by West and collaborators for all living organisms, appears to be able to describe also the growth of tumors in vivo. In contrast to the assumption of a fixed power…

The nervous system is today recognized to play an important role in the development of cancer. Indeed, neurons extend long processes (axons) that grow and infiltrate tumors in order to regulate the progression of the disease in a positive…

动力系统 · 数学 2022-05-25 Sophie Chauvet , Florence Hubert , Fanny Mann , Mathieu Mezache

Tumor development is an evolutionary process in which a heterogeneous population of cells with differential growth capabilities compete for resources in order to gain a proliferative advantage. What are the minimal ingredients needed to…

种群与进化 · 定量生物学 2016-01-19 Jeffrey West , Zaki Hasnain , Jeremy Mason , Paul K. Newton

This paper deals with a general system of equations and conditions arising from a mathematical model of prostate cancer growth with chemotherapy and antiangiogenic therapy that has been recently introduced and analyzed (see [P. Colli et…

偏微分方程分析 · 数学 2021-04-02 Pierluigi Colli , Gianni Gilardi , Jürgen Sprekels

Tumor growth from a single transformed cancer cell up to a clinically apparent mass spans many spatial and temporal orders of magnitude. Implementation of cellular automata simulations of such tumor growth can be straightforward but…

定量方法 · 定量生物学 2013-09-25 Jan Poleszczuk , Heiko Enderling

The availability of cancer measurements over time enables the personalised assessment of tumour growth and therapeutic response dynamics. However, many tumours are treated after diagnosis without collecting longitudinal data, and cancer…

偏微分方程分析 · 数学 2024-04-19 Elena Beretta , Cecilia Cavaterra , Matteo Fornoni , Guillermo Lorenzo , Elisabetta Rocca
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