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相关论文: Strange Attractor in Immunology of Tumor Growth

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We propose a strange-attractor model of tumor growth and metastasis. It is a 4-dimensional spatio-temporal cancer model with strong nonlinear couplings. Even the same type of tumor is different in every patient both in size and appearance,…

细胞行为 · 定量生物学 2008-10-28 Tijana T. Ivancevic , Murk J. Bottema , Lakhmi C. Jain

Although the immune response is often regarded as acting to suppress tumor growth, it is now clear that it can be both stimulatory and inhibitory. The interplay between these competing influences has complex implications for tumor…

细胞行为 · 定量生物学 2013-05-17 Kathleen P. Wilkie , Philip Hahnfeldt

We model the interaction between the immune system and tumor cells including a time delay to simulate the time needed by the latter to develop a chemical and cell mediated response to the presence of the tumor. The results are compared with…

Cancer is a disease that takes millions of lives every year. Then, to propose treatments, avoid recurrence, and improve the patient's life quality, we need to analyze this disease from a biophysical perspective with a solid mathematical…

定量方法 · 定量生物学 2024-07-09 Carlos M. Nieto , Oscar M. Pimentel , Fabio D. Lora-Clavijo

Tumors constitute a wide family of diseases kinetically characterized by the co-presence of multiple spatio-temporal scales. So, tumor cells ecologically interplay with other kind of cells, e.g. endothelial cells or immune system effectors,…

计算工程、金融与科学 · 计算机科学 2012-08-21 Giulio Caravagna , Alex Graudenzi , Marco Antoniotti , Giancarlo Mauri , Alberto d'Onofrio

This paper proposes a novel chaotic reaction-diffusion model of cellular tumor growth and metastasis. The model is based on the multiscale diffusion cancer-invasion model (MDCM) and formulated by introducing strong nonlinear coupling into…

细胞行为 · 定量生物学 2008-07-29 Tijana T. Ivancevic , Murk J. Bottema , Lakhmi C. Jain

Initiation and development of a malignant tumor is a complex phenomenon that has critical stages determining its long time behavior. This phenomenon is mathematically described by means of various models: from simple heuristic models to…

种群与进化 · 定量生物学 2020-03-23 Yuri Kozitsky , Krzysztof Pilorz

In this article a generalized mathematical model describing the interactions between malignant tumour and immune system with discrete time delay incorporated into the system is considered. Time delay represents the time required to generate…

组织与器官 · 定量生物学 2015-11-05 Monika Joanna Piotrowska

We propose an extension of a standard stochastic individual-based model in population dynamics which broadens the range of biological applications. Our primary motivation is modelling of immunotherapy of malignant tumours. In this context…

种群与进化 · 定量生物学 2016-04-18 Martina Baar , Loren Coquille , Hannah Mayer , Michael Hölzel , Meri Rogava , Thomas Tüting , Anton Bovier

Tumor cells develop different features to adapt to environmental conditions. A prominent example is the ability of tumor cells to switch between migratory and proliferative phenotypes, a phenomenon known as go-or-grow mechanism. It is…

组织与器官 · 定量生物学 2014-07-14 Katrin Böttger , Haralambos Hatzikirou , Anja Voss-Boehme , Miguel A. Herrero , Andreas Deutsch

This paper investigates dynamic behaviors of the tumor-immune system perturbed by environmental noise. The model describes the response of the cytotoxic T lymphocyte (CTL) to the growth of an immunogenic tumour. The main methods are…

概率论 · 数学 2019-02-06 Xiaoyue Li , Guoting Song , Yang Xia , Chenggui Yuan

The stochastic discrete space-time model of an immune response on tumor spreading in a two-dimensional square lattice has been developed. The immunity-tumor interactions are described at the cellular level and then transferred into the…

comp-gas · 物理学 2007-05-23 Margarita Voitikova

Cancer is a term used to refer to a large set of diseases. The cancerous cells grow and divide and, as a result, they form tumours that grow in size. The immune system recognise the cancerous cells and attack them, though, it can be…

The influence of random fluctuations on the recruitment of effector cells towards a tumor is studied by means of a stochastic mathematical model. Aggressively growing tumors are confronted against varying intensities of the cell-mediated…

其他定量生物学 · 定量生物学 2020-10-28 Irina Bashkirtseva , Lev Ryashko , Álvaro G. López , Jesus M. Seoane , Miguel A. F. Sanjuán

In this paper, we studied phase-space analysis of a certain mathematical model of tumor growth with an immune responses and chemotherapy therapy. Mathematical modelling of this process is viewed as a potentially powerful tool in the…

动力系统 · 数学 2018-03-15 Veli Shakhmurov , Akif Maharramov , Bunyad Shahmurzada

Tumor growth, which plays a central role in cancer evolution, depends on both the internal features of the cells, such as their ability for unlimited duplication, and the external conditions, e.g., supply of nutrients, as well as the…

生物物理 · 物理学 2018-06-19 Youness Azimzade , Abbas Ali Saberi , Muhammad Sahimi

Tumor-immune interactions are shaped by both antigenic heterogeneity and stochastic perturbations in the tumor microenvironment, yet the mathematical mechanisms underlying immune phase transitions remain poorly understood. We propose a…

种群与进化 · 定量生物学 2025-09-16 Mengfan Tan , Shaoqing Chen , Chunjin Wei , Da Zhou

Cancer stem cells have been shown to be critical to the development of a variety of solid cancers. The precise interplay mechanisms between cancer stem cells and the rest of a tissue are still not elucidated. To shed light on the…

细胞行为 · 定量生物学 2019-09-04 L. Benítez , L. Barberis , C. A. Condat

Tumor growth has a number of features in common with a physical process known as molecular beam epitaxy. Both growth processes are characterized by the constraint of growth development to the body border, and surface diffusion of…

定量方法 · 定量生物学 2009-11-13 Carlos Escudero

The US and Hungarian statistical records of the years 1900 and 1896, respectively, before the dramatic medical advances, show 32% and 27% deaths attributable to infections, whereas only 5% and 2% due to cancer. These data can be interpreted…

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