Collaborative Research: A Predictive Theory of Muscle Energy Consumption

合作研究:肌肉能量消耗的预测理论

基本信息

  • 批准号:
    10378797
  • 负责人:
  • 金额:
    $ 39.82万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2019
  • 资助国家:
    美国
  • 起止时间:
    2019-09-23 至 2023-08-31
  • 项目状态:
    已结题

项目摘要

A predictive theory of muscle contraction and chemical energy consumption can transform human movement science, e.g., helping us better understand movements such as walking and running and informing the design of effort-reducing assistive and prosthetic devices. Such a theory can also inform a quantitative understanding of the genetic basis of heart disease and other muscular dysfunction. An accurate theory of muscle contraction and energy consumption does not exist. While a clear picture of muscle contraction, including energy consumption, has emerged at the single molecule scale, the simplified conditions of these experiments limit their application to larger scales. We propose to produce a multi- scale mathematical theory of muscle contraction, based on molecular and cellular measurements, to understand muscle function in vivo and test such a bottom-up theory's accuracy at the whole muscle or whole body level, as will be relevant in applications. The proposed research builds on previous work, where we developed a theory, described by linear ordinary differential equations, coupled to integro-partial differential equations, that quantitatively describes experiments from single molecules to large ensembles. Because our theory is described by differential equations, unlike other models, it can be inverted to predict muscle energy consumption from muscle force. Such simulations predict a cost for the rate of muscle force production, which is thought to be critical to understanding the energetics of human walking. Despite this promising result, the theory lacks components necessary to quantitatively describe muscle at larger (i.e. cellular, organ, etc.) scales. We will therefore perform experiments, motivated by the theory, to identify and quantify the missing components. In Aim 1 we will extend the theory to the cellular scale by generating a self-consistent data set from the single molecule to cellular (muscle fiber) scale. These experiments will characterize the transient interactions (weak binding) between molecules involved in muscle contraction that are too rapid to measure at the molecular scale, and so must be characterized via multi-scale measurements interpreted with the theory. In Aim 2 we will extend the theory to conditions relevant to locomotion by performing novel experiments on muscle molecules and cells under conditions that replicate forcibly lengthened muscle (eccentric contraction), a situation that frequently occurs during locomotion. We will test hypotheses, motivated by the model, that 1) molecular bonds are forcibly broken when muscle is lengthened, and 2) this bond breaking leads to transient instabilities that cause catastrophic loss of muscle force. In Aim 3, we will collect data for muscle energy consumption from human subjects. These experiments will allow us to test and refine candidate muscle energy cost models. The theory already makes testable predictions; our measurements will allow us to test these predictions, refine the model, and improve on current muscle energy cost models.
肌肉收缩和化学能量消耗的预测理论可以改变人类 运动科学,例如,帮助我们更好地理解运动,如行走和跑步, 为设计省力的辅助和假肢装置提供信息。这样的理论也可以告诉一个 定量了解心脏病和其他肌肉功能障碍的遗传基础。一个 不存在肌肉收缩和能量消耗的精确理论。虽然一个清晰的画面, 肌肉收缩,包括能量消耗,已经出现在单分子尺度上,简化的 这些实验的条件限制了它们在更大规模上的应用。我们建议建立一个多- 基于分子和细胞测量的肌肉收缩的比例数学理论, 了解体内肌肉功能,并在整个肌肉上测试这种自下而上理论的准确性, 整个身体水平,如在应用中相关的。拟议的研究建立在以前的工作, 在那里,我们开发了一个理论,由线性常微分方程描述,耦合到积分-偏微分方程, 微分方程,定量描述从单分子到大集合的实验。 因为我们的理论是由微分方程描述的,不像其他模型,它可以被反演来预测 肌肉能量消耗来自肌肉力量。这样的模拟预测了肌肉力量的速度的成本 这被认为是理解人类行走的能量学的关键。尽管如此 有希望的结果,该理论缺乏必要的组件来定量描述肌肉在更大的(即, 细胞、器官等)鳞片因此,我们将进行实验,由理论的动机,以确定和 量化缺失的成分。在目标1中,我们将通过生成一个 从单分子到细胞(肌肉纤维)规模的自洽数据集。这些实验将 表征参与肌肉收缩的分子之间的瞬时相互作用(弱结合) 这些变化太快,无法在分子尺度上测量,因此必须通过多尺度来表征。 用理论解释的测量。在目标2中,我们将把理论扩展到与以下相关的条件: 通过对肌肉分子和细胞进行新的实验, 强迫拉长肌肉(离心收缩),这种情况经常发生在运动过程中。我们 将测试由该模型激发的假设:1)当肌肉断裂时,分子键被强制断裂 延长,2)这种键断裂导致短暂的不稳定性,导致肌肉的灾难性损失 力在目标3中,我们将收集人类受试者的肌肉能量消耗数据。这些 实验将使我们能够测试和完善候选肌肉能量成本模型。这个理论已经 做出可测试的预测;我们的测量将使我们能够测试这些预测,完善模型, 改进当前肌肉能量消耗模型。

项目成果

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samuel walcott其他文献

samuel walcott的其他文献

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{{ truncateString('samuel walcott', 18)}}的其他基金

Collaborative Research: A Predictive Theory of Muscle Energy Consumption
合作研究:肌肉能量消耗的预测理论
  • 批准号:
    10493166
  • 财政年份:
    2019
  • 资助金额:
    $ 39.82万
  • 项目类别:
Collaborative Research: A Predictive Theory of Muscle Energy Consumption
合作研究:肌肉能量消耗的预测理论
  • 批准号:
    9902713
  • 财政年份:
    2019
  • 资助金额:
    $ 39.82万
  • 项目类别:
Collaborative Research: A Predictive Theory of Muscle Energy Consumption
合作研究:肌肉能量消耗的预测理论
  • 批准号:
    10267169
  • 财政年份:
    2019
  • 资助金额:
    $ 39.82万
  • 项目类别:

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