AI based system for longitudinal, repeated measure analyses of freely moving C. elegans worms

基于人工智能的系统，用于对自由移动的秀丽隐杆线虫进行纵向、重复测量分析

• 批准号: 10258638
• 负责人: JACOB R GLASER
• 金额: $ 45万
• 依托单位: MICROBRIGHTFIELD, LLC
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-09 至 2022-07-08
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10258638
• 关键词: Acetylcholine; Address; Agar; Aging; Alzheimer' s Disease; Animal Behavior; Animal Model; Appearance; Artificial Intelligence; Behavior; Behavioral; Behavioral Research; Biological Assay; Biotechnology; Brain; Brain Diseases; Caenorhabditis elegans; Classification; Collaborations; Complex; Computer software; Data; Development; Disease; Dopamine; Eukaryota; Feasibility Studies; Glutamates; Goals; Human; Image; Individual; Laboratories; Legal patent; Lighting; Locomotion; Longevity; Longitudinal Studies; Market Research; Massachusetts; Measures; Microscope; Molecular; Motion; Mus; Names; National Institute of Mental Health; Nematoda; Neurodegenerative Disorders; Neurodevelopmental Disorder; Neurosciences; Neurotransmitters; Pathologic; Pharmacologic Substance; Phase; Population Analysis; Preparation; Psyche structure; Rattus; Research; Research Design; Research Personnel; Rodent; Schizophrenia; Schools; Serotonin; Speed; Strategic Planning; System; Technology; Testing; Time; Toxicology; Traumatic Brain Injury; Validation; Visual Fields; Work; analytical method; autism spectrum disorder; base; behavioral study; convolutional neural network; design; digital; drug discovery; fighting; free behavior; gamma-Aminobutyric Acid; high throughput screening; innovation; intelligent algorithm; longitudinal analysis; neural network architecture; neurodevelopment; neuropsychiatric disorder; neurotransmitter release; next generation; novel; novel therapeutics; prevent; prototype; receptor; social; usability

Abstract This project aims to develop WormInvestigator™, a novel, highly innovative system for performing automated, high-throughput and longitudinal studies of the behavior of C. elegans worms freely moving and socially interacting on agar plates (hereafter: "freely moving worms") across multiple time points over extended times (e.g., multiple days) with repeated measures designs. Work in Phase I will focus on demonstrating feasibility of our novel, patent pending, WormRecognizer™ technology – the ability to perform automatic, image-based identification of individual C. elegans worms within a group of freely moving worms ("digital tagging of freely moving worms"). Work in Phase II will focus on creating the full functionality of WormInvestigator for the commercial release. The innovation inherent in WormRecognizer will serve as the basis for enabling a game- changing innovation in the field – the ability to perform high throughput longitudinal, repeated measures design analyses of locomotion and other behavior of freely moving C. elegans worms from discrete, non-continuous video sequences. Compared to study designs that have independent groups repeated measures designs offer more statistical power and the possibility to track an effect over time. Specifically, repeated measures designs for analyzing locomotion and other behavior of freely moving worms will allow researchers to definitively assess the likelihood that a particular behavior is associated with a prior behavior, which is impossible without repeated measures designs or impractical continuous imaging and tracking under constant illumination. WormRecognizer will leverage the Deep Convolutional Neural Network (CNN) architecture to perform automatic identification of the tracks of the same worm in videos of groups of freely moving worms recorded at different time points; encouraging pilot data were generated during preparation of this application. C. elegans is increasingly used as a model organism in research focusing on brain mechanisms underlying complex behaviors and pathological alterations thereof, including research into neurodevelopment, Alzheimer's disease, autism, schizophrenia and traumatic brain injury. Thus, WormInvestigator will enable significant advancements in various mental neuroscience applications that use C. elegans as a model organism. Specifically, the fact that C. elegans express many of the neurotransmitters and associated receptors that are found in higher eukaryotes, including humans, makes C. elegans highly attractive for the (high throughput) screening of next generation therapeutics for mental diseases such as Alzheimer's disease, as well as for disorders that rely on neurotransmitter release modulation such as next generation treatments for schizophrenia. We will perform extensive feasibility studies, product validation and usability studies of WormInvestigator in close collaboration with expert neuroscientists. Market research performed during preparation of this application indicated that WormInvestigator will expand the use of C. elegans as a model organism to many laboratories that do not currently use them. A competing technology is not available. We anticipate the global market size for WormInvestigator to be more than 300 systems.

抽象的 该项目旨在开发worminvestigator™，这是一种用于执行自动化的新颖，高度创新的系统， 对秀丽隐杆线虫蠕虫的行为的高通量和纵向研究 在琼脂板上（以下：“自由移动蠕虫”）在长时间的多个时间点上进行互动 （例如，多天）具有重复测量设计。第一阶段的工作将专注于证明的可行性 我们的小说，申请申请的，蠕虫™技术 - 执行自动，基于图像的能力 在一组自由移动蠕虫中识别单个秀丽隐杆线虫蠕虫（“自由数字标签 移动蠕虫”。第二阶段的工作将集中于创建蠕虫的全部功能 商业发行。蠕虫的创新继承将成为实现游戏的基础 - 改变现场的创新 - 执行高通量纵向，重复措施设计的能力 从离散的，非连续的移动秀丽隐杆线虫蠕虫的运动和其他行为的分析 视频序列。与具有独立组重复措施设计的研究设计相比 随着时间的流逝，更具统计能力和跟踪效果的可能性。具体而言，重复的措施设计 为了分析运动和自由移动蠕虫的其他行为，将使研究人员能够明确评估 特定行为与先前行为相关联的可能性，如果没有重复，这是不可能的 在恒定照明下进行衡量设计或不切实际的连续成像和跟踪。蠕虫 将利用深层卷积神经网络（CNN）体系结构进行自动识别 在不同时间点记录的一组免费移动蠕虫的视频中，同一蠕虫的轨道； 在准备此应用程序期间生成了鼓励的试点数据。秀丽隐杆线虫越来越被用作 在研究重点是复杂行为和病理学基础的大脑机制的研究中的模型生物 其改变，包括研究神经发育，阿尔茨海默氏病，自闭症，精神分裂症和 创伤性脑损伤。这是蠕虫分门者将在各种心理方面取得重大进步 使用秀丽隐杆线虫作为模型生物的神经科学应用。具体而言，秀丽隐杆线虫表达的事实 在包括人类在内的较高真核生物中发现的许多神经递质和相关接收器， 使秀丽隐杆线虫对（高通量）筛查的下一代疗法具有很高的吸引力 阿尔茨海默氏病等疾病以及依赖神经递质释放调节的疾病 例如针对精神分裂症的下一代治疗方法。我们将进行广泛的可行性研究，产品 与专家神经科学家密切合作的蠕虫评估者的验证和可用性研究。市场 在此应用程序准备期间进行的研究表明，蠕虫申请者将扩大使用 秀丽隐杆线虫是当前不使用它们的许多实验室的模型生物。竞争技术是 无法使用。我们预计，蠕虫申请器的全球市场规模将超过300个系统。