Exploring the constituent mechanisms of hepatitis: a dynamical systems approach.

IF 0.8 4区 数学 Q4 BIOLOGY
Joanne L Dunster, Jonathan M Gibbins, Martin R Nelson
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引用次数: 1

Abstract

Hepatitis is the term used to describe inflammation in the liver. It is associated with a high rate of mortality, but the underlying disease mechanisms are not completely understood and treatment options are limited. We present a mathematical model of hepatitis that captures the complex interactions between hepatocytes (liver cells), hepatic stellate cells (cells in the liver that produce hepatitis-associated fibrosis) and the immune components that mediate inflammation. The model is in the form of a system of ordinary differential equations. We use numerical techniques and bifurcation analysis to characterize and elucidate the physiological mechanisms that dominate liver injury and its outcome to a healthy or unhealthy, chronic state. This study reveals the complex interactions between the multiple cell types and mediators involved in this complex disease and highlights potential problems in targeting inflammation in the liver therapeutically.

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探索肝炎的组成机制:动力系统方法。
肝炎是用来描述肝脏炎症的术语。它与高死亡率有关,但潜在的疾病机制尚不完全清楚,治疗方案有限。我们提出了一个肝炎的数学模型,该模型捕获了肝细胞(肝细胞)、肝星状细胞(肝脏中产生肝炎相关纤维化的细胞)和介导炎症的免疫成分之间复杂的相互作用。该模型是常微分方程组的形式。我们使用数值技术和分岔分析来表征和阐明主导肝损伤及其健康或不健康慢性状态的生理机制。这项研究揭示了参与这种复杂疾病的多种细胞类型和介质之间的复杂相互作用,并强调了靶向肝脏炎症治疗的潜在问题。
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来源期刊
CiteScore
2.20
自引率
0.00%
发文量
15
审稿时长
>12 weeks
期刊介绍: Formerly the IMA Journal of Mathematics Applied in Medicine and Biology. Mathematical Medicine and Biology publishes original articles with a significant mathematical content addressing topics in medicine and biology. Papers exploiting modern developments in applied mathematics are particularly welcome. The biomedical relevance of mathematical models should be demonstrated clearly and validation by comparison against experiment is strongly encouraged. The journal welcomes contributions relevant to any area of the life sciences including: -biomechanics- biophysics- cell biology- developmental biology- ecology and the environment- epidemiology- immunology- infectious diseases- neuroscience- pharmacology- physiology- population biology
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