NIH Director's Pioneer Award

一个科学领域的发展往往被一段时期的不同观察所打断 按照一套统一的原则来理解。这一重要的时间时刻发生在一个临界值 (和类型)的观察变得可用，机械原理通常是由合并而来的 来自不同智力学科的思想。这一时期也标志着预测性模型的出现。 T淋巴细胞(T细胞)协调(也可以错误地调节)适应性免疫反应。我相信T 细胞生物学，特别是T细胞介导的自身免疫，正处于一个关键时刻，多样化的数据很快就会出现 在总体原则方面进行了整合。现代实验正在以前所未有的细节揭示， T细胞介导的自身免疫产生的重要因素，而不是对自身的耐受。 然而，预测模型所需的一般机械原理已被证明难以捉摸。这是因为T 细胞介导的自身免疫的特征是发生在一系列 长度和时间刻度。大尺度(组织)上发生的现象影响合作的分子事件 单个T细胞，进而影响组织环境。这种复杂的等级协作性使它 仅从实验观察中很难直观地了解潜在的机制。我建议发展 通过分析发生在T细胞介导的自身免疫中的相关合作动态来管理原理 通过整合二十世纪的三大进步，构建一个分子和细胞变量的复杂空间： 统计力学、计算技术、遗传学、生物化学和成像实验。一把钥匙 成功将是与实验免疫学家的合作，我最近展示了如何做到这一点 协同效应可能是卓有成效的。如果成功，我设想的工作将提供指导 开发多发性硬化症和糖尿病等疾病的治疗方法，这些疾病困扰着数百万人。

The development of a scientific field is often punctuated by a period when diverse observations can be understood in terms of a set of unifying principles. This important moment in time occurs when a critical number (and type) of observations becomes available, and the mechanistic principles often result from an amalgamation of ideas drawn from different intellectual disciplines. This period also marks the emergence of predictive models. T lymphocytes (T cells) orchestrate (and can also misregulate) the adaptive immune response. I believe that T cell biology, especially T cell-mediated autoimmunity, is at a critical juncture where diverse data will soon be integrated in terms of overarching principles. Modern experiments are revealing, in unprecedented detail, the factors that are important in the emergence of T cell-mediated autoimmunity rather than tolerance to ?self?. However, general mechanistic principles necessary for predictive models have proven elusive. This is because T cell-mediated autoimmunity is characterized by cooperative dynamic processes that occur over a spectrum of length and time scales. Phenomena occurring on large scales (tissues) influence cooperative molecular events in a single T cell which, in turn, influences the tissue environment. This complex hierarchical cooperativity makes it difficult to intuit underlying mechanisms from experimental observations alone. I propose to develop the principles governing T cell-mediated autoimmunity by parsing the pertinent cooperative dynamics which occur in a complex space of molecular and cellular variables by integrating three great advances of the twentieth century: statistical mechanics, computational technology, and genetic, biochemical, and imaging experiments. A key to success will be collaborations with experimental immunologists, and I have recently demonstrated how such synergies can be fruitful. If successful, the work that I envisage will provide the principles that could guide the development of therapies for diseases such as multiple sclerosis and diabetes which afflict millions of people.