Silvia S. Blemker, Ph.D. - US grants

[unreadable] DESCRIPTION (provided by applicant): Muscle strain injuries are one of the most common conditions seen in sports medicine clinics. However, methods of treatment are variable and re-injury rates tend to be high which, in part, reflects a lack of fundamental understanding of the factors that influence injury risk. The prevailing theory is that injury occurs as a result of excessive strain of active muscle fibers. The goal of this study is to develop novel biocomputational tools to predict and analyze the strain distributions within skeletal muscles during movements associated with injury. Model predictions will be compared with strain measures obtained using state-of-the-art dynamic magnetic resonance imaging experiments. Once validated, we will use the biocomputational tools to investigate how morphology and coordination influence hamstring injury risk during running. Following are the specific aims. Aim 1 will use a dynamic magnetic resonance imaging technique to measure the strain distributions within the individual hamstring muscles during lengthening contractions, a loading condition commonly associated with injury. Comparisons between muscles will provide new insights into the propensity for hamstring injury to occur in the biceps femoris long head. Aim 2 will build a biocomputational framework to predict muscle strain distributions during movement. The framework will couple finite-element simulations of muscle tissue behavior with dynamic simulations of whole body movement. The methods will be validated by comparing strain predictions with those determined from the dynamic images in Aim 1. We will then use the framework to investigate the relationship between muscle excitations, hamstring tissue strains and skeletal movement during running. Aim 3 will evaluate whether computational models predict re-injury prevention strategies. We will build and validate models of subjects who exhibit residual changes in tissue structures as a result of a previous hamstring injury. We will then use the software framework to identify how movement coordination can be adapted to accommodate injury-induced changes in morphology. This research will establish a biocomputational framework that reveals the complex relationship between muscle morphology, coordination and injury risk, thus providing a new paradigm for identifying rehabilitation and injury prevention strategies. Muscle strain injuries are one of the most common conditions seen in sports medicine clinics. However, methods of treating muscle injuries are variable and re-injury rates tend to be high. This proposal couples novel biocomputational tools and imaging techniques to establish a scientific basis for preventing and rehabilitating hamstring muscle injuries. [unreadable] [unreadable] [unreadable]

? DESCRIPTION (provided by applicant): It is expected that 25-35% of children with repaired cleft palate will have VPD as evidenced by hypernasal speech. If a child has a primary repair of the levator veli palatini (levator) muscle (i.e., primary muscle for velar elevation during speech) that does not conform to that of normal anatomy, it is likely that the child will develop hypernasa speech and will require secondary palate surgery. The primary cause of VPD is due to what we term disadvantageous biomechanics. Specifically, the anatomy and mechanics of the velopharyngeal (VP) mechanism post-surgically are not adequate for proper VP function. Our research team has demonstrated that surgical planning in which pre-surgical muscle arrangement and function are used to determine post-surgical structure is critical to a successful speech outcome. The goal of this proposal will be to develop subject-specific models based on magnetic resonance imaging data to determine how and why certain children have VPD following surgery. Our vision is to ultimately improve outcomes of cleft palate repair by providing a framework in which pre-surgical muscle arrangement and function are used to inform surgical plans to optimize post-surgical structure. Our goals are in this project are to: (i) determine whic anatomical features lead to disadvantageous biomechanics in children who have VPD, and (ii) reveal the ways in which the anatomy could be changed to restore normal VP function. We intend to achieve these goals through the following specific aims: (Aim 1) Create computational models of children with and without VPD who have had cleft palate repair; and (Aim 2) Use the subject-specific models to determine the cause of VPD in each child. After successful completion of this R21 project, we will have demonstrated that the subject-specific models are predictive of function in children post-cleft palate repair. These results will empower us to move towards modeling patients pre-repair and determining if patient-specific models can be used as a guide for making patient-specific surgical decisions. This and follow-on studies will address long-standing questions of speech outcomes following surgery and the effect of growth and maturation of the VP structures on VP function.

? DESCRIPTION (provided by applicant): A reduction in plantarflexor power during the push-off phase of walking leads to the slowing of preferred walking speed with age, which in turn negatively affects old adults' health and independence. Although commonly implicated, sarcopenia and muscle weakness alone cannot fully explain the reduction in plantarflexor power or accompanying changes in coordination. We postulate that this disconnect arises from age-related changes in Achilles tendon behavior that alter muscle-tendon dynamics during movement. This study tightly integrates novel in vivo imaging, computational modeling, and motion analysis to investigate tendon deformations associated with physiological loading and movement to an unprecedented level of detail. Our overarching hypothesis is that age-related changes in tendon elasticity and inter-fascicle adhesions have a substantial effect on the ability for muscles to generate sufficient plantarflexor power during movement. This study has three aims. The first aim is to determine how advancing age affects the in vivo behavior of the plantarflexor muscles and Achilles tendon during prescribed ankle flexion movements under physiological loading. We will combine high-resolution static MRI, dynamic MRI, and shear wave elastography to test the hypothesis that advancing age brings altered spatial patterns of Achilles tendon tissue elasticity that predict measured muscle tissue deformation patterns. The second aim is to predict the functional implications of age- related changes in Achilles tendon tissue mechanics on plantarflexor performance during movement. We will link measurements of human movement with a unique computational framework that includes detailed structural representations of the 3D morphology of the plantarflexor muscle-tendons and their dynamic interactions. We will test the primary hypothesis that simulating age-related changes in Achilles tendon elasticity and inter-fascicle adhesions will diminish power production and increase localized tissue strains. The third aim is to investigate age-related changes in Achilles tendon behavior during walking and its relevance to functional motor performance and response to gait interventions. We will measure in vivo Achilles tendon deformations, plantarflexor fascicle behavior, and plantarflexor power during walking. We will couple these measurements with biofeedback designed to elicit prescribed increases in plantarflexor power output. We will use these data to test the hypotheses that: 1) more uniform tendon deformations during walking with aging, which would reflect a reduction in sliding between tendon fascicles, will predict reduced ankle joint kinetics and altered plantarflexor muscle fascicle kinematics, and 2) with aging, different coordination strategies will be used to increase plantarflexor power, adaptations that will be consistent with Aim 2 model predictions. Combined, these aims will reveal the influence of age-related changes in Achilles tendon mechanics on plantarflexor muscle behavior during movement, insights critical for developing informed interventions to maintain or restore mobility while mitigating risk for muscle-tendon tissue damage.

? DESCRIPTION (provided by applicant): Duchenne muscular dystrophy (DMD), a genetic mutation in the dystrophin gene that affects 1 in 3500 male births, causes rapid progressive muscle degeneration. Boys with DMD gradually lose ambulation, often in their teens, and die of respiratory and cardiac complications by their twenties or thirties. Currently, there are no definitive effective cures for DMD. While potential treatments are in trial phases, priorities of care and exercise management for patients with DMD are to prolong ambulation, maintain quality of life and improve longevity. However, there is currently a paucity of scientifically base guidelines for prescribing safe exercise management for boys with DMD. A better understanding of how physical activity leads to muscle degeneration in DMD is critical for establishing evidence-based practices for maintaining ambulation as long as possible. It remains unclear why some lower limb muscles degenerate more quickly than others in DMD (selective degeneration), despite the fact that dystrophin is deficient in all lower limb muscles. Although multiple factors could affect the pace of degeneration, our central hypothesis is that specifically for lower limb muscles in DMD, differing degree of eccentric contraction during walking across muscles significantly contributes to the selective degeneration. The goal of our work is to develop computer models to predict the impact of various activities on the progression of muscle degeneration in DMD, thereby providing scientific guidelines for DMD care and exercise management. Since walking is the most frequent and essential activity for lower limb muscles, this exploratory project will test the hypothesis that eccentric contractions estimated from musculoskeletal simulations of walking predict the patterns of muscle degeneration in the lower limb of children with DMD. This work will lead to a more scientific basis for determining exercise and designing assistive devices that promote muscle health and mobility while minimizing damage in children with DMD. We propose to integrate computer simulations, gait experiments and magnetic resonance imaging (MRI) to achieve this goal with two specific aims. In aim 1, we will determine if muscle loads during gait - determined from computer simulations - predict selective degeneration of lower limb muscles in DMD. In aim 2, we will determine if impaired DMD gait leads to increased muscle loads during gait. This project will provide a new innovative framework for developing rehabilitation regimens that optimize gait and prolong ambulation. The experiment-simulation framework developed in this project can be further applied to understand the influences of various other activities on the progression of DMD, and potentially on the progression of other types of muscular dystrophy, such as Becker or Limb-Girdle. The research proposed here will be crucial to develop quantitative guidelines for care and exercise management as well as in designing assistive devices that would alleviate muscle degeneration, prolonging ambulation, maintaining quality of life and improving longevity.

? DESCRIPTION (provided by applicant): Duchenne muscular dystrophy (DMD) is an inherited, severe muscle degenerative disease that affects one in every 3,500 boys. Pervasive and progressive skeletal muscle atrophy and weakness is generally first observed in patients at 3-5 years of age, leaves patients wheelchair bound by age 12 years, and ultimately leads to death due to respiratory or cardiac failure by the mid-20s. There is no cure for DMD, and currently, the only treatment is corticosteroids, which targets inflammation in muscle degeneration. However, corticosteroids are merely palliative: they extend the time of mobility and life by only a few years. Furthermore, corticosteroids have major troublesome side effects, causing boys to gain weight, become highly prone to fractures due to brittle bones, and potentially develop significant behavioral issues, all of which make lives of boys and families extremely difficult. The initiating cause of DMD is due to a mutation in the dystrophin gene, which renders muscle fibers prone to membrane tearing during everyday movements and initiates a cascade of muscle fiber necrosis, chronic inflammation, and ultimately muscle degeneration. This cascade of pathological remodeling events involves multiple different mechanisms that span spatial and temporal scales and pertain to biomechanical signals and inflammation in the muscle tissue. We hypothesize that it is the feedback between biomechanical signals and inflammatory signals that ultimately leads to muscle degeneration. We posit that testing this hypothesis requires a multiscale computational model. We propose to couple biomechanical modeling with agent-based modeling to develop and then experimentally validate a unified multiscale computational model (Aim 1). We then propose to use our multiscale model of muscle remodeling to test our hypothesis by challenging the model to predict the response to different treatment interventions and to explore why the most widely used murine model of DMD, the mdx mouse, poorly recapitulates human disease (Aim 2). Finally, we propose to make a human version of the multiscale model, based on novel data collected in boys with DMD, and use it to test different front-running treatments that have had variable degrees of efficacy and to identify new treatments that are informed by understanding how biomechanics and inflammation feedback on one another to cause this terrible disease (Aim 3).

SUMMARY The goal of this proposal is to develop a quantitative framework to address sex as a biological variable in musculoskeletal modeling and simulation research. This new framework will allow the field to understand how sex differences in musculoskeletal structure influence movement biomechanics, musculoskeletal injury, and neuromuscular disease. There are many known differences in bone anatomy, joint mechanics, muscle architecture, and movement function between males and females. Likewise, it is well documented that there are significant sex differences in susceptibility to musculoskeletal injury and neuromuscular disease. However, while the use of computer simulations of movement to study how musculoskeletal structure influences neuromuscular injury and disease has increased dramatically due to advances in numerical algorithms and computational power, the models that are used are based on musculoskeletal data that (1) are derived from a male-only population, and/or (2) combine measures from males and females in a way that averages out any potential sex differences. These profound limitations leave the field without any tools to examine how the known sex differences in musculoskeletal structures may influence biomechanics, injury, and disease. This project has three key aims that will resolve these profound limitations. The first aim will develop a comprehensive digital database of lower limb muscles, joints, and bones across female and male populations of varying body sizes. This aim will be achieved through using high throughput image segmentation analysis of magnetic resonance images collected of 50 male and 50 female subjects. The second aim will incorporate the measurements from the first aim into a computational framework that enables for accurate sex-specific scaling of lower limb models, including the ability to capture the measured variability in the form of uncertainty analysis. The third aim will use the models in the second aim to develop a model-based analysis method to generate novel insights into sex differences in lower limb biomechanics. The analysis method will be applied to examine sex differences in muscle forces during walking and landing. Taken together, these aims will not only address critical questions related to differences in musculoskeletal structure and function between males and females, but also provide a rigorous, detailed, sex-specific digital database of data and models that will be provided open-access for the entire scientific community to use. This posted resource will empower the field with a set of tools to rigorously examine sex as a biological variable in musculoskeletal modeling research.

PROJECT SUMMARY This application seeks support for UVA's Biotechnology Training Program (BTP). The BTP is a highly interactive, multidisciplinary and >50% diverse community of PhD trainees drawn selectively from an annual May competition open to PhD students from all science and engineering departments university-wide for which we request 10 predoctoral slots. Trainee funding is for 2 years. Our emphasis is on scientific rigor and communication using the latest tools available with award winning and collaborative dual mentoring giving rise to a breadth of multidisciplinary and academic/industrial training unmatched at UVA. Our advocacy for trainee exposure to a wide variety of careers has been transformational - most importantly for trainees but also for the university with which we share many of our offerings. We believe in trainee career preparedness that is personalized, evolving and built on trust, and that relationships do not necessarily end at graduation. Indeed, our graduates welcome the opportunity to return as BTP seminar or industrial panel speakers with talks focused on, or interlaced with, career reflections; or to help in a trainee advisory/advocate role as members of the BTP Board of Corporate Advisors. They are the ultimate measure of our success. Their outcomes are updated at least quarterly on our grads web page with information drawn from LinkedIn. BTP students in training (21, including 11 minorities) or graduated (65) entered with an average undergraduate GPA of 3.7, are currently hosted by 8 different departments. BTP trainees and graduates have received multiple awards, experienced 73 different externships from 51 different companies, and after graduation are now employed in industry (37), academia (15; including an HBCU Dean), government (3), medicine (3), or foundation (2). Since '05, 164 first author articles have been published in journals with impact factors as high as 24. Trainees develop leadership and teamwork skills by taking direct responsibility for programmatic features of the BTP including: BTP Symposia and Seminars, BTP Day of Caring, BTP Industrial Q&A Panels and BTP company tours. Mentoring our trainees is a highly engaged, collaborative and well-funded faculty of 55 individuals from 14 departments. Institutional support has been essential for our success, including Vice President for Research help with externship and Symposia funding, and an additional training slot funded by the School of Engineering. Our overall goal is to develop the next generation of exceptionally rigorous, creative, talented and diverse scientists who are socialized in biotechnology themes and practiced in teamwork. Our aims are to: (1) cement a foundation of rigor in experimental planning, data organization and transparency built on the Nature and eLife recognized 'Open Science Framework' in a collaboration with Charlottesville's 'Center for Open Science', (2) to energetically nurture our trainees love and inquisitiveness for science as they acquire new skills to solve important scientific problems, and (3) to overlay this training with various forms of biotechnology exposure, including required externships ? all coupled with a strong and constant commitment to trainee diversity.