INSPIRE Track 1: Nanotechnology for Adaptive Optics

INSPIRE 轨道 1：自适应光学纳米技术

• 批准号: 1344219
• 负责人: Edward Boyden
• 金额: $ 100万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-10-01 至 2016-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1344219&HistoricalAwards=false
• 关键词: INSPIRE; Track; Nanotechnology; Adaptive; Optics

ABSTRACTThis INSPIRE award is partially funded by the Biophotonics (7236)and Biomedical Engineering (5345) programs in the CBET Division in the Directorate for Engineering; the Robust Intelligence (7495) program in the Division of Information and Intelligent Systems in the Directorate for Computer and Information Science and Engineering; and the the Organization (7712) program in the Division of Integrative Organismal Systems in the Directorate for Biology and the Instrumentation and Instrument Development (1108) program in the Division of Biological Infrastructure, also in the Directorate for Biology. Emerging Frontiers (7275) money was provided for the Organization and Instrumentation and Instrument Development programs by the Directorate for Biology.The ability to optically image real-time physiological processes in living systems is of central importance for understanding how biological systems compute and function. In order to enable the imaging of deep, arbitrary-scale tissues, the PI proposes to address one of the fundamental limitations in live tissue imaging: the scattering of light by live tissues. Much work has been devoted to adaptive optics using conventional off-the-shelf spatial light modulators, interferometers, cameras, and other hardware. Here the PI proposes to create new technologies for adaptive optics based instead upon nanotechnology, which can help correct optical imaging for the scattering properties of living tissues. The project goal is nothing less than that of making real-time physiological processes visible throughout live tissues and organs, important for understanding how biological computations occur. The impact will be large for any field where understanding complex 3-D systems is key - for the study of live organs such as heart and brain, for the immune system, for the study of metabolism, for the study of development and aging, and for cancer biology. They will distribute all tools as freely as possible, and pursue distribution mechanisms to maximize the availability of tools, at cost whenever possible. The proposed innovations will also benefit the field of optogenetic control of complex systems. These innovations will also greatly help with teaching of biology and medicine at all levels of education, since the ability to visualize things is powerful in education; we will incorporate these tools into teaching both at MIT and elsewhere, engaging scientists-in-training, as well as the public. Through both direct impact of tool usage, as well as via teaching, they anticipate that these proposed technologies will result in a more scientifically literate workforce. they also anticipate commercial impact, in the creation of new methods of diagnostics and medicine. The ability to hunt down better disease mechanisms, or mechanisms of disease treatment, may accelerate the development of new drugs and therapies. Some of the technologies here proposed could also lead to new companies, or new products, thus contributing to economic development, as well as helping with dissemination of the tools.

摘要该INSPIRE奖项的部分资金来自工程理事会CBET部门的生物光子学（7236）和生物医学工程（5345）项目;计算机和信息科学与工程理事会信息与智能系统部门的鲁棒智能（7495）项目;以及生物学理事会综合有机系统司的组织（7712）计划和生物基础设施司的仪器和仪器开发（1108）计划，也在生物学理事会。 新兴前沿（7275）资金由生物学理事会提供给组织和仪器与仪器开发计划。在生命系统中光学成像实时生理过程的能力对于理解生物系统如何计算和运作至关重要。 为了实现对深度、任意尺度组织的成像，PI提出解决活组织成像的基本限制之一：活组织对光的散射。 许多工作已经致力于使用传统的现成的空间光调制器，干涉仪，相机和其他硬件的自适应光学。在这里，PI建议创建基于纳米技术的自适应光学新技术，这可以帮助校正活组织散射特性的光学成像。该项目的目标不亚于使实时生理过程在整个活组织和器官中可见，这对于理解生物计算是如何发生的很重要。 对于理解复杂的3D系统是关键的任何领域，其影响都将是巨大的-对于心脏和大脑等活体器官的研究，对于免疫系统，对于新陈代谢的研究，对于发育和衰老的研究，以及对于癌症生物学。 他们将尽可能免费分发所有工具，并尽可能以成本价推行分发机制，以最大限度地提供工具。 所提出的创新也将有利于复杂系统的光遗传学控制领域。 这些创新也将极大地帮助各级教育的生物学和医学教学，因为可视化事物的能力在教育中是强大的;我们将把这些工具纳入麻省理工学院和其他地方的教学中，吸引科学家和公众。 通过工具使用的直接影响，以及通过教学，他们预计这些拟议的技术将导致更科学的劳动力。 他们还预计在创造新的诊断和医学方法方面会产生商业影响。 寻找更好的疾病机制或疾病治疗机制的能力可能会加速新药和疗法的开发。 这里提出的一些技术也可能导致新的公司或新产品，从而促进经济发展，并有助于传播这些工具。