CAREER: Multiplex microfluidic and automation tools for neurogenetics and live imaging

职业：用于神经遗传学和实时成像的多重微流体和自动化工具

• 批准号: 0954578
• 负责人: Hang Lu
• 金额: $ 40.05万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-01-01 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0954578&HistoricalAwards=false
• 关键词: CAREER; Multiplex; microfluidic; automation; tools

0954578LuThe long-term objective is to develop and use powerful microfluidic and automation tools to understand genetic pathways that regulate the biochemical communications between neurons and other tissues in C. elegans. Microfluidics is ideal for studies of small organisms such as C. elegans because of the relevant length scales and the possibility of integration and automation. The research objective of the CAREER project is to engineer a microfluidic system for live imaging of dynamic processes in vivo, to accomplish automated image processing, and to identify roles of genes in neuronal biochemical communications.This system will significantly increase the throughput and accuracy of in vivo live imaging experiments in model organisms. It streamlines and automates the painstakingly manual procedure of microscopy, in some cases enables some experiments that are otherwise impossible to do, and reduces the noise and artifacts in these experiments. The image analysis algorithms will provide quantitative data with large throughput to allow good statistics. The approach is innovative because the technologies developed here dramatically increase the capabilities and throughput of current assay tools, enabling key biological experiments that are not currently performed. Furthermore, the technology is broadly applicable to other biological systems and could potentially lead to new therapeutics for related diseases.

长期目标是开发和使用强大的微流体和自动化工具，以了解调节C.优雅的微流控技术是研究小生物如C。因为相关的长度尺度和集成和自动化的可能性。CAREER项目的研究目标是设计一种微流控系统，用于活体动态过程的实时成像，实现自动化图像处理，并识别神经元生化通讯中的基因角色，该系统将显著提高模型生物活体成像实验的通量和准确性。它简化和自动化了显微镜的手工操作，在某些情况下，使一些实验，否则不可能做，并减少这些实验中的噪音和文物。图像分析算法将提供具有大吞吐量的定量数据，以允许良好的统计。该方法是创新的，因为这里开发的技术大大提高了当前分析工具的能力和吞吐量，使目前尚未进行的关键生物实验成为可能。此外，该技术广泛适用于其他生物系统，并可能导致相关疾病的新疗法。