CRCNS:Comput./Exp.Study:Hypothal.-Pituitary Interaction

CRCNS：计算机/实验研究：下丘脑-垂体相互作用

• 批准号: 6935401
• 负责人: Richard Bertram
• 金额: $ 33.9万
• 依托单位: FLORIDA STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-07-01 至 2009-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6935401
• 关键词: calcium ion; circadian rhythms; computational neuroscience; confocal scanning microscopy; dopamine; fluorescent dye /probe; gene expression; hormone regulation /control mechanism; hypothalamus; immunocytochemistry; interdisciplinary collaboration; laboratory rat; model design /development; neuroendocrine system; neurogenetics; neurons; neuroregulation; oxytocin; pituitary gland; prolactin; radioimmunoassay; secretion; serotonin; suprachiasmatic nucleus; tissue /cell culture; voltage /patch clamp

DESCRIPTION (provided by applicant): The overall aim of this project is to combine experimental studies with mathematical modeling to understand the interactions between the hypothalamus and the pituitary gland that lead to rhythmic secretion of the hormone prolactin. This work will be done in close collaboration between an experimental lab and a mathematical modeling lab; both labs reside at the same university, facilitating daily interactions. The primary goal of this research is to understand how neurosecretory cells within the hypothalamus interact with the pituitary gland to produce daily rhythms of prolactin secretion in the rat during pregnancy. Prolactin is one of the most versatile hormones of mammalian organisms, with over 300 separate biological activities. The prolactin secreted following the mating stimulus has many targets, including other endocrine glands, and is important for maintaining a normal pregnancy in the rat. Prolactin is secreted by pituitary lactotrophs. Secretion from these cells is tightly regulated by the hypothalamus, a region of the brain that transmits time-of-day information to the rest of the body. The interaction between hypothalamic neurons and lactotrophs is complex; the neurons influence each other as well as the lactotrophs, and prolactin from lactotrophs feeds back onto and influences the hypothalamic neurons. Such a complex system is ideal for mathematical modeling, which can provide insight into the influence of the various network interactions, and can be used as a tool for integrating information. In this project, mathematical modeling is combined with experimental studies. The model will be calibrated by experimental data, and will make predictions that will be tested in the laboratory. This joint experimental-computational approach is well suited for understanding the complex hypothalamus-pituitary network. Student training is an important element of this project. It is anticipated that graduate students and postdoctoral fellows will play very active roles in the research described herein. This participation will provide multi-disciplinary training that will be invaluable for an increasingly multi-disciplinary workplace. There are four specific aims in this proposal. First, a mathematical model will be developed for pituitary lactotrophs. This model, based largely on experimental data on cultured lactotrophs from our lab, will provide a mechanistic understanding of the activity patterns of these cells. It will also be used to understand how the activity is modified by hormones such as dopamine and oxytocin. Second, mathematical models will be developed of hypothalamic dopamine- and oxytocin-secreting neurons, using hypothalamus slice data from our lab. These neurosecretory cells regulate prolactin secretion from lactotrophs, and are themselves under the influence of neurons within the suprachiasmatic nucleus (SCN). The third specific aim is to develop a mathematical model of the network interactions among the various hypothalamic neurons and pituitary lactotrophs. This model will be minimal, focusing on the network interactions between cells rather than the detailed biophysical processes that take place within cells (the goal of the first two aims). Fourth, the role of rhythmic clock gene expression in dopamine- and oxytocin-secreting neurons will be investigated. If the expression patterns are shown to be rhythmic, then this suggests that these cells provide circadian input to the pituitary that is separate from, but may be entrained by, neurons within the SCN. These studies will support the mission of NIDA by establishing the way the normal brain functions in the absence of drugs of abuse to support the pituitary gland. It will then lead to studies of effects of drugs of abuse on brain-pituitary function.

描述（由申请人提供）：该项目的总体目标是将实验研究与数学模型相结合，以了解下丘脑和垂体之间的相互作用，从而导致催乳素激素的节律性分泌。这项工作将由实验实验室和数学建模实验室密切合作完成；两个实验室都位于同一所大学，促进日常互动。这项研究的主要目标是了解下丘脑内的神经分泌细胞如何与垂体相互作用，以产生怀孕期间大鼠催乳素分泌的每日节律。催乳素是哺乳动物生物体中最通用的激素之一，具有 300 多种不同的生物活性。交配刺激后分泌的催乳素有许多靶标，包括其他内分泌腺，对于维持大鼠的正常妊娠很重要。催乳素由垂体泌乳素分泌。这些细胞的分泌受到下丘脑的严格调节，下丘脑是大脑中负责将时间信息传输到身体其他部位的区域。下丘脑神经元和泌乳素细胞之间的相互作用是复杂的。神经元相互影响，也影响泌乳素，而来自泌乳素的催乳素反馈并影响下丘脑神经元。这样的复杂系统非常适合数学建模，可以深入了解各种网络交互的影响，并可以用作集成信息的工具。在这个项目中，数学建模与实验研究相结合。该模型将通过实验数据进行校准，并做出将在实验室进行测试的预测。这种联合实验-计算方法非常适合理解复杂的下丘脑-垂体网络。学生培训是该项目的一个重要组成部分。预计研究生和博士后将在本文所述的研究中发挥非常积极的作用。这种参与将提供多学科培训，这对于日益多学科的工作场所来说非常宝贵。该提案有四个具体目标。首先，将为垂体泌乳素细胞开发一个数学模型。该模型主要基于我们实验室培养的泌乳素细胞的实验数据，将提供对这些细胞活动模式的机械理解。它还将用于了解多巴胺和催产素等激素如何改变活性。其次，将使用我们实验室的下丘脑切片数据开发下丘脑多巴胺和催产素分泌神经元的数学模型。这些神经分泌细胞调节催乳素的催乳素分泌，并且它们本身受到视交叉上核（SCN）内神经元的影响。第三个具体目标是开发各种下丘脑神经元和垂体催乳素之间网络相互作用的数学模型。该模型将是最小的，重点关注细胞之间的网络相互作用，而不是细胞内发生的详细生物物理过程（前两个目标的目标）。第四，将研究节律时钟基因表达在多巴胺和催产素分泌神经元中的作用。如果表达模式显示出有节律性，则表明这些细胞向垂体提供昼夜节律输入，该输入与 SCN 内的神经元分开，但可能被其夹带。这些研究将通过建立在不滥用药物支持垂体的情况下正常大脑的运作方式来支持 NIDA 的使命。然后它将导致滥用药物对脑垂体功能影响的研究。