Real-time computer vision tracking of stemness

实时计算机视觉跟踪干性

基本信息

批准号：
7248933
负责人：
PHIL GORDON CAMPBELL
金额：
$ 32.93万
依托单位：
CARNEGIE-MELLON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2007
资助国家：
美国
起止时间：
2007-05-01 至 2011-02-28
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7248933
关键词：
Address Adult Alkaline Phosphatase Apoptosis Apoptotic Behavior Behavioral Blinded Cell Count Cell Differentiation process Cell Line Cell Proliferation Cell Separation Cell division Cell model Cell physiology Cells Cellular biology Computer Vision Systems Condition Cultured Cells Dactinomycin Data Data Set Daughter Development Drops Elements Engineering Epidermal Growth Factor Excision Exhibits Extracellular Matrix Feedback Fibroblast Growth Factor 2 Future Generic Drugs Goals Growth Growth Factor Heterogeneity Human Image Imagery In Situ In Vitro Indium Individual Kinetics Life Maintenance Measurement Measures Mediating Medicine Mesenchymal Stem Cells Metric Mitotic Modeling Monitor Motion Mus Muscle Muscle Cells Muscle Fibers Muscle satellite cell Osteoblasts Osteogenesis Output Parents Pattern Phase Population Population Growth Principal Investigator Printing Process Production Proliferating Protocols documentation Quality Control Range Rate Recording of previous events Regenerative Medicine Relative (related person)Research Research Personnel Robotics Sampling Serum Signal Transduction Software Tools Sorting - Cell Movement Specific qualifier value Staining method Stains Standards of Weights and Measures Stem cells System Technology Testing Time Translations Update Validation Video Microscopy adult stem cell base bone bone morphogenetic protein 2 cell behavior cell type cellular engineering clinical application combinatorial cytochemistry desire detector experience human stem cells imaging Segmentation immortalized cell immunocytochemistry in vivo in vivo regeneration indexing member myogenesis novel novel strategies platelet-derived growth factor BB programs research study response self-renewal spatiotemporal stemness tool vector

项目摘要

DESCRIPTION (provided by applicant): This proposal addresses the need for new stem cell engineering toolsets that can regulate adult stem cell expansion (self-renewal, without differentiation) ex vivo in order to create sufficient numbers of cells for clinical applications. The goals of this proposal are to: 1) develop a computer vision system that tracks in real-time the spatiotemporal histories of cell divisions in vitro in phase-contrast imagery; 2) use this data to automatically derive real-time metrics of symmetry, division times, confluence, and predictive population growth models; and, 3) apply this system to develop novel strategies that maximize the yield of adult stem cell expansion in growth factor-mediated conditions. 'Real-time' means that processing is completed 'on-line' in the 15 minute intervals between image acquisitions, and this information is available during cell culture as feedback for process monitoring and control. In Aim 1, robust image segmentation and tracking of dense cell populations will be achieved using multi-modal cell tracking modules that represent and reason about cell states and motion from different perspectives, and then fuse and coordinate their respective outputs to make collaborative decisions. The multi-modal modules will be formulated for fast implementation on vector-based graphics processing hardware. The system will measure: proliferation, lineage (i.e., parent-daughter relationship), quiescence, and apoptotic states of each cell in culture within developing confluent populations of muscle-derived stem cells (MDSCs), including immortalized pluripotent C2C12, primary mouse MDSCs, and primary human MDSCs. In Aim 2, the system will be applied to efficient discovery and characterization of cell expansion behaviors and determination of nominal culture conditions to maximize symmetry using bio-printed combinatorial arrays of immobilized growth factors on extracellular matrix substrates. In Aim 3, real-time monitoring and control of cell expansion will be demonstrated using an adaptive subculturing strategy; the predictive growth model will signal when to suspend cell culture, followed by fluorescent-activated cell sorting to exclude apoptotic or differentiating cells, thus selectively enriching subcultures for cells exhibiting the highest proliferation rates. Maintenance of differentiative potential will be monitored between subcultures using in vitro osteogenesis and myogenesis as paradigm differentiation indices.

描述（由申请人提供）：该提案解决了对新的干细胞工程工具集的需求，该工具集可以调节成体干细胞离体扩增（自我更新，无分化），以便为临床应用产生足够数量的细胞。该提案的目标是：1）开发一种计算机视觉系统，以相差图像实时跟踪体外细胞分裂的时空历史； 2) 使用这些数据自动导出对称性、分裂时间、汇合度和预测种群增长模型的实时指标； 3) 应用该系统开发新策略，在生长因子介导的条件下最大限度地提高成体干细胞扩增的产量。 “实时”意味着处理在图像采集之间的 15 分钟间隔内“在线”完成，并且该信息在细胞培养期间可作为过程监测和控制的反馈。在目标 1 中，将使用多模式细胞跟踪模块来实现对密集细胞群的鲁棒图像分割和跟踪，这些模块从不同角度表示和推理细胞状态和运动，然后融合和协调各自的输出以做出协作决策。多模式模块将被制定为在基于矢量的图形处理硬件上快速实现。该系统将测量：在发育汇合的肌肉源性干细胞 (MDSC) 群体中培养的每个细胞的增殖、谱系（即亲子关系）、静止和凋亡状态，包括永生化多能 C2C12、原代小鼠 MDSC、和原代人类 MDSC。在目标 2 中，该系统将用于有效发现和表征细胞扩增行为，并确定标称培养条件，以使用细胞外基质基质上固定生长因子的生物打印组合阵列最大化对称性。在目标 3 中，将使用自适应传代培养策略来演示对细胞扩增的实时监测和控制；预测生长模型将发出何时暂停细胞培养的信号，然后进行荧光激活细胞分选以排除凋亡或分化细胞，从而选择性地富集表现出最高增殖率的细胞的传代培养物。将使用体外成骨和肌生成作为范式分化指标来监测亚培养物之间分化潜力的维持。