Collaborative Research: The Dynamics of the Innate Immune Systems: A Study of the Toll-like Receptors (TLR) Network

合作研究:先天免疫系统的动力学:Toll 样受体 (TLR) 网络的研究

基本信息

  • 批准号:
    1137906
  • 负责人:
  • 金额:
    $ 14.32万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2011
  • 资助国家:
    美国
  • 起止时间:
    2011-12-01 至 2014-12-31
  • 项目状态:
    已结题

项目摘要

Intellectual Merit:The first line of defense to microbial infections or tissue damage is the innate immune system, which responds to harmful stimuli by triggering inflammation, a defensive response that is essential for tissue repair and pathogen removal. However, excessive inflammation is harmful because it can produce further tissue damage; inflammation must therefore be countered by anti-inflammatory responses. Hence, it is crucial to understand how the dynamics of the pro- and anti-inflammatory responses of the immune system are regulated. The overarching aim of this project is to elucidate the regulation dynamics of the Toll-like family of receptors (TLR), which are components of the innate immune system that recognize microbial pathogens. The project constitutes a pilot study exploring the use of systems and control theory and formal methods to study the dynamics of the innate immune system. Formal methods is a branch of mathematics and theoretical computer science that has been developed to verify the execution of complex engineering systems. The investigators will use existing published experimental data from TLR excitation experiments, to develop an integrated mathematical model combining the dynamics of signaling and transcription networks. Further, they will develop novel formal methods to analyze this model. Because of the anticipated complexity of the TLR network, the investigators will initially test their framework using data generated in silico, as well as existing, smaller data sets from other signaling networks, such as the NF-kB network. It is anticipated that successful completion of this project will create a framework capable of producing testable predictions that can be used in subsequent studies of the TLR.Broader Impacts: While the project focuses on quantitative study of the dynamical properties of the TLR network, the theory that will be developed is expected to be broadly applicable to other phenomena related to the innate immunity, including, autoimmunity, chronic inflammation, and obesity. Furthermore, because of its generality, the framework developed in this project should lend itself to the study of other cellular signaling mechanisms and the related transcriptional regulation systems, for example, the growth-factor signaling system and the cell-cycle regulatory system. As part of this project, graduate and undergraduate students will be trained and prepared for academic and industrial careers at the leading edge of the interface between biology and engineering. The investigators will integrate the research activity into graduate and undergraduate curriculum. Outreach activities to K-12 students and teachers, particularly targeting students from underrepresented minorities, will be carried out under the auspices of BU Academy at Boston University and the Center for Initiatives in Pre-College Education (CIPCE) at Rensselaer.
智力优势:抵抗微生物感染或组织损伤的第一道防线是先天免疫系统,它通过引发炎症来对有害刺激做出反应,这是一种对于组织修复和病原体清除至关重要的防御反应。然而,过度的炎症是有害的,因为它会造成进一步的组织损伤。因此,必须通过抗炎反应来对抗炎症。因此,了解免疫系统促炎和抗炎反应的动态如何调节至关重要。该项目的首要目标是阐明 Toll 样受体家族 (TLR) 的调节动态,TLR 是识别微生物病原体的先天免疫系统的组成部分。该项目构成了一项试点研究,探索使用系统和控制理论以及形式方法来研究先天免疫系统的动态。形式方法是数学和理论计算机科学的一个分支,旨在验证复杂工程系统的执行情况。研究人员将利用现有已发表的 TLR 激发实验数据,开发一个结合信号传导和转录网络动力学的综合数学模型。 此外,他们将开发新颖的形式方法来分析该模型。由于预期 TLR 网络的复杂性,研究人员将首先使用计算机生成的数据以及来自其他信号网络(例如 NF-kB 网络)的现有较小数据集来测试他们的框架。预计该项目的成功完成将创建一个能够产生可测试预测的框架,可用于 TLR 的后续研究。 更广泛的影响:虽然该项目侧重于 TLR 网络动态特性的定量研究,但该理论将开发的技术预计将广泛适用于与先天免疫相关的其他现象,包括自身免疫、慢性炎症和肥胖。此外,由于其通用性,该项目开发的框架应适用于其他细胞信号传导机制和相关转录调控系统的研究,例如生长因子信号传导系统和细胞周期调控系统。作为该项目的一部分,研究生和本科生将接受培训,并为在生物学和工程学之间的前沿领域的学术和工业职业生涯做好准备。研究人员将把研究活动整合到研究生和本科生课程中。针对 K-12 学生和教师的外展活动,特别是针对代表性不足的少数族裔的学生,将在波士顿大学 BU 学院和伦斯勒大学预科教育倡议中心 (CIPCE) 的赞助下开展。

项目成果

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Anak Agung Julius其他文献

Anak Agung Julius的其他文献

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{{ truncateString('Anak Agung Julius', 18)}}的其他基金

Collaborative Research: Spatiotemporal Fractional Modeling of Blood-Oxygen-Level Dependent Signals
合作研究:血氧水平相关信号的时空分数建模
  • 批准号:
    1936578
  • 财政年份:
    2020
  • 资助金额:
    $ 14.32万
  • 项目类别:
    Standard Grant
SenSE: Multimodal Biometric Sensor for Optimal Regulation of Circadian Rhythm and Neurocognitive Performance
SenSE:用于最佳调节昼夜节律和神经认知性能的多模态生物识别传感器
  • 批准号:
    2037357
  • 财政年份:
    2020
  • 资助金额:
    $ 14.32万
  • 项目类别:
    Standard Grant
CSR: Small: Provably Correct Design of Observation for Fault Diagnosis and State Estimation under Privacy and Network Constraints
CSR:小:隐私和网络约束下可证明正确的故障诊断和状态估计观测设计
  • 批准号:
    1618369
  • 财政年份:
    2016
  • 资助金额:
    $ 14.32万
  • 项目类别:
    Standard Grant
CSR: Small: Human-Centered Synthesis of Provably Correct Controllers for Hybrid Systems
CSR:小:以人为中心综合可证明正确的混合系统控制器
  • 批准号:
    1218109
  • 财政年份:
    2012
  • 资助金额:
    $ 14.32万
  • 项目类别:
    Standard Grant
CAREER: Robust Trajectory Based Analysis for Stochastic Hybrid Systems Abstraction and Verification
职业:基于稳健轨迹的随机混合系统抽象和验证分析
  • 批准号:
    0953976
  • 财政年份:
    2010
  • 资助金额:
    $ 14.32万
  • 项目类别:
    Continuing Grant
Collaborative Research: Motion Control of Bacteria-Powered Microrobots
合作研究:细菌动力微型机器人的运动控制
  • 批准号:
    1000284
  • 财政年份:
    2010
  • 资助金额:
    $ 14.32万
  • 项目类别:
    Standard Grant

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