Quantitative analysis of estrogen and sleep deprivation-induced blood and lymphatic vascular remodeling in the brain system

雌激素和睡眠剥夺引起的大脑系统血液和淋巴血管重塑的定量分析

• 批准号: 10404487
• 负责人: Olga V Glinskii
• 金额: $ 53.13万
• 依托单位: UNIVERSITY OF MISSOURI-COLUMBIA
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-04-15 至 2024-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10404487
• 关键词: Acute; Algorithmic Analysis; Algorithms; Alzheimer' s Disease; Anatomy; Aneurysm; Animals; Arteriovenous fistula; Blood; Blood Circulation; Blood Vessels; Blood capillaries; Brain; Brain Mapping; Cardiovascular system; Cephalic; Cerebrospinal Fluid; Cerebrovascular Disorders; Chronic; Chronic Insomnia; Communication; Complex; Computer software; Cystic Lymphangioma; Development; Disease; Dura Mater; Dural Arteriovenous Fistulas; Effectiveness; Elements; Estrogens; Evaluation; Female; Functional disorder; Geometry; Gonadal Steroid Hormones; Health; Hematoma; Heterogeneity; Hybrids; Image; Image Analysis; Imaging Techniques; Impaired cognition; Impairment; Individual; Knowledge; Lead; Life; Link; Lymphatic; Lymphatic System; Machine Learning; Magnetic Resonance Imaging; Maps; Measurement; Meningeal; Metabolism; Methods; Microscopy; Migraine; Modeling; Molecular; Morphology; Mosaicism; Multiple Sclerosis; Mus; Nerve; Neuraxis; Neuroglia; Neurologic; Neurons; Optical Coherence Tomography; Parietal; Pathogenesis; Pathologic; Pathway interactions; Physiological; Positioning Attribute; Resolution; Route; Sex Differences; Shapes; Site; Sleep; Sleep Deprivation; Sleep Disorders; Sleep disturbances; Software Tools; Stroke; Structure; Subdural Hematoma; Subdural Hygroma; System; Techniques; Testing; Therapeutic; Therapeutic Intervention; Thinness; Tissues; Translations; Treatment Effectiveness; Vascular Diseases; Vascular remodeling; Vascular resistance; Venous; associated symptom; base; body system; cerebral microvasculature; cerebrovascular; clinically relevant; confocal imaging; deep learning; deprivation; detection limit; diagnostic tool; disability; effectiveness evaluation; geometric structure; in vivo; lymphatic circulation; lymphatic vasculature; lymphatic vessel; machine learning algorithm; male; microleakage; nervous system disorder; neuronal circuitry; noninvasive diagnosis; novel; response; sex; sleep pattern; solute; stem; submicron; translational progress; wasting

Abstract Numerous small vessels making up the central nervous system blood and lymphatic vascular networks are heterogeneous and region-specific dynamic structures, whose segments, position, shape and function can change in response to physiological and pathophysiological conditions. To date it has not been possible to integrate blood and lymphatic vascular elements and their microenvironment to achieve a holistic quantitative characterization of the combined brain and meningeal tissue-scale vascular networks, its structure and function in normal and disease states. This application proposes to develop microscopy- based high-throughput image analysis techniques for automated extraction of blood and lymphatic vascular networks enabling quantitative morphodynamic characterization of cerebrovascular microenvironment changes in two intracranial compartments – the brain and dura mater. The study will focus on new algorithms for precise region-specific microvessel registration, mosaicing, segmentation, fusion and colocalization for constructing large tissue scale spatially aligned dual blood/lymphatic vascular network structural maps in the animals of both sexes, as well as characterization of heterogeneities of microvascular networks, including blood and lymphatic vasculature, under estrogen and sleep deprivation (the conditions relevant to multiple cerebrovascular disorders) compared to physiological settings. In other words, advanced microscopy-based techniques will be used to image blood and lymphatic vessels at sub-micron resolution in dura mater and the brain, and then cutting-edge deep machine learning imaging analysis methods will be employed to segment and quantify these vessels, their geometry, vessel wall structure, functionality, and interrelationship. Detailed structural analysis of microvascular networks is essential for accurate evaluation of the distribution of physical forces, substrate delivery and tissue clearance of waste, as well as sex differences and consequences of intracranial networks remodeling under physiological and pathological conditions. This will create knowledge enabling a better understanding of the pathogenesis of vascular impairments under estrogen and sleep deprivation, identify common molecular mechanisms and the efficacy and effectiveness of different therapeutic treatments. Without the ability to construct total structural and functional blood/lymphatic vascular network maps from studies limited to individual tissue component parts, it is little wonder that translation from the molecular and cellular levels to the whole organ and system levels is deficient and hinders translational progress towards a comprehensive understanding of the pathophysiology associated with a range of neurological disorders.

抽象的 构成中枢神经系统血液和淋巴血管网络的许多小血管是 异质和特定区域的动态结构，其段，位置，形状和功能可以 对物理和病理生理状况的响应变化。迄今为止，不可能 综合血液和淋巴血管元素及其微环境以实现整体 大脑和脑膜组织规模的血管网络的定量表征，其 正常和疾病状态的结构和功能。此应用提案要发展显微镜 - 基于基于血液和淋巴管自动提取的高通量图像分析技术 网络实现脑血管微环境的定量形态动力学表征 两个颅内室的变化 - 大脑和硬脑膜母乳。该研究将重点放在新的 精确区域特异性微血管注册，镶嵌，分割，融合和算法 用于构建大型组织量表的共定位，空间对齐的双血/淋巴血管网络 两性动物的结构图，以及微血管异质性的表征 雌激素和睡眠剥夺（条件 与物理环境相比，与多种脑血管疾病有关）。换句话说， 高级基于显微镜的技术将用于在亚微米处成像血液和淋巴管 在硬脑膜和大脑中的分辨率，然后是尖端的深度机器学习成像分析 将执行方法以分割和量化这些容器，它们的几何形状，容器壁结构， 功能和相互关系。微血管网络的详细结构分析对于 准确评估物理力的分布，底物递送和废物的组织清除， 以及在生理和 病理状况。这将创造知识，以更好地理解 雌激素和睡眠剥夺下的血管障碍，确定常见的分子机制和 不同治疗治疗的有效性和有效性。没有能力构造总数 从研究限制到单个组织的结构和功能性血/淋巴血管网络图 组成部分，毫无疑问，从分子和细胞水平转换为整个器官 系统水平不足，阻碍将进步转化为对对的全面理解 与一系列神经系统疾病相关的病理生理学。