Neck and back pain have a tremendous annual incidence and associated cost. The facet capsular ligament (FCL), which encloses the bilateral articulating joints of the spinal vertebrae, is richly innervated to provide proprioception during normal motions. The FCL also has nociceptive innervation and may act as a pain sensor during abnormal conditions. Although aberrant spinal motions and pathologic conditions have long been associated with pain, the relationship between tissue loading and nociceptor activation is unclear because FCL function involves mechanics and physiology across length scales. Relating spinal motions to neuronal function within the FCL requires multi-scale modeling and experiments to identify mechanisms by which tissue loading may mediate neuronal function. Under this U01, we will test the hypothesis that the neuronal response is governed by local forces on the neurons, which are determined by the complex interaction of the macroscopic load and the microscopic structure of the tissue in which it resides. To do so, we will create new, multiscale models of FCL mechanics at the tissue and collagen fiber network scales. We will use those models to study the mechanical environment of neuronal cells in the tissue and to predict the forces transmitted from the collagen fibers to the neurons. Complementary experiments at the tissue and cell scales will define mechanical interactions between the FCL, collagen fibers, and neurons while also describing the relationship between local strain and the neuronal response. We will integrate modeling and experimental work under coordinated specific aims to understand how the organization of fibrillar and non-fibrillar material in the FCL govern its mechanical response, how the micro-scale fiber motion translates into forces on neurons, and how those forces affect neuronal signaling and function.
In Aim 1, we will extend our existing multiscale model of bioengineered tissues to the complex geometry and architecture of the FCL;
in Aim 2, we will study a cell- populated collagen gel model to predict and assess how a neuron is affected when the matrix in which it resides is deformed. Finally, in Aim 3, we will use the mechanical function model (mm-to-um scale) of Aim 1 and the cellular response model (um-to-nm scale) of Aim 2 to create a realistic model of the neuronal mechanical environment and response during tissue loading. This model, bridging length scales in a clinically significant tissue, will serve a twofold purpose. First, we will test the central hypothesis above. Second, by connecting the tissue and cellular scales, the project will facilitate efforts to include relevant physiological data on joint mechanics and afferent neuronal function, which will promote understanding of the in vivo responses of the facet capsule during pathologic spinal motions. The multiscale predictive models being developed not only will enhance our understanding of degeneration, arthritis, and injury in the facet capsule but also will provide insight into other innervated soft tissues with complex structure and geometry and speculative pain etiology.

Public Health Relevance

Although joint loading can produce pain under certain loading conditions and clinical pathologies, the mechanisms of pain receptor activation are poorly understood. Realistic multiscale models that incorporate mechanics at the tissue and cellular scales are requisite to define the relationship between tissue loading and the mechano-transduction responses of the neurons that innervate such tissues. The proposed multiscale predictive models will not only define such mechanisms, but also generate new hypotheses enhancing our understanding of degeneration, arthritis, and injury in the spine and other innervated soft tissues with complex structure and geometry and speculative pain etiology.

National Institute of Health (NIH)
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Research Project--Cooperative Agreements (U01)
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Special Emphasis Panel (ZEB1-OSR-C (J2))
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Peng, Grace
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University of Minnesota Twin Cities
Biomedical Engineering
Schools of Engineering
United States
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