Predicting disease progression: new models in mathematical immunology

预测疾病进展：数学免疫学的新模型

• 批准号: 342116-2007
• 负责人: Heffernan, Jane
• 金额: $ 1.09万
• 依托单位: York University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2011
• 资助国家: 加拿大
• 起止时间: 2011-01-01 至 2012-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=482432
• 关键词: Predicting; disease; progression; new; models

When a foreign substance - a virus or bacterium - invades the tissues of a higher vertebrate, the organism defends itself through the immune response. The immune system is highly adaptive - it is able to "learn" to respond to an enormous variety of pathogens. In order for a disease to infect a host, it must circumvent the immune system (i.e. mutation), grow at a faster rate than it is killed by the immune system or, as in the case of HIV, infect the immune system itself.

当外来物质-病毒或细菌-侵入高等脊椎动物的组织时，生物体通过免疫反应进行自卫。 免疫系统是高度适应性的-它能够“学习”对各种各样的病原体做出反应。 为了使疾病感染宿主，它必须绕过免疫系统（即突变），以比被免疫系统杀死的速度更快的速度生长，或者像艾滋病毒一样，感染免疫系统本身。