# Collaborative Research: A Predictive Theory of Muscle Energy Consumption

> **NIH NIH R01** · WORCESTER POLYTECHNIC INSTITUTE · 2020 · $398,198

## Abstract

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, re...

## Key facts

- **NIH application ID:** 10378797
- **Project number:** 7R01GM135923-03
- **Recipient organization:** WORCESTER POLYTECHNIC INSTITUTE
- **Principal Investigator:** samuel walcott
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $398,198
- **Award type:** 7
- **Project period:** 2019-09-23 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10378797

## Citation

> US National Institutes of Health, RePORTER application 10378797, Collaborative Research: A Predictive Theory of Muscle Energy Consumption (7R01GM135923-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10378797. Licensed CC0.

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