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International audience; The study describes a method to set up disease specific deep brain stimulation (DBS) atlases based on intra-operative stimulation test data exemplified with data from 6 essential tremor (ET) patients implanted in the ventrointermediate nucleus of the thalamus (Vim).I. INTRODUCTION DBS consists in delivering electric stimulation to the brain structures responsible for movement regulation using multi-contact electrodes in order to control symptoms of movement disorders. To ensure proper placement of the electrode during surgery, awake intra-operative testing of symptoms is common. Normative analysis methods have been applied by other groups [1] to study the mechanisms of action of DBS, but focus on stimulation settings and longterm symptoms and rarely study ET. In comparison, intra-operative tests during awake surgery produce a large amount of exploration data. We present in this paper the group analysis of intra-operative stimulation test data in patients who received DBS for ET.II. METHOD A group specific anatomical template was created based on WAIR (white matter attenuated inversion recovery) and T1 MR (magnetic resonance) images from 19 bilaterally implanted DBS patients (PD:13, ET:6). Deep brain structures manually delineated by the neurosurgeon were projected to and summarized in the template. The distribution of the electric field (EF) was resolved for the ET patients for each position and amplitude evaluated during surgery. In each voxel, tremor improvement and EF norm were used to discriminate voxels with scores significantly above or below average using one-sampled two-sided t-test.III. RESULTS The stimulation atlas describes the efficacy of DBS by combining the probabilistic anatomical template, outlines of deep brain structures and improvement scores. IVoxels associated for improvement above average concentrate in the Posterior subthalamic area (infero-posterior to Vim) extending in the direction of Zi and along the posterior limit of Vim. Voxels significant for improvement below average concentrate in the anterior and posterior limits of the region of interest.IV. DISCUSSION This study underlines the potential of the high quality data collected during surgery for the analysis of the mechanisms of action of DBS in tremor using state-of-the art group-analysis approaches. The low number of patients is compensated by the high number of tests in each patient, allowing to identify significant improvement regions. The next steps are the integration of more patients and investigation in different statistics approaches to capture and quantify reliability of the results.

Quantitative MRI provides biophysical measures of the microstructural integrity of the CNS, which can be compared across CNS regions, patients, and centres. In patients with multiple sclerosis, quantitative MRI techniques such as relaxometry, myelin imaging, magnetization transfer, diffusion MRI, quantitative susceptibility mapping, and perfusion MRI, complement conventional MRI techniques by providing insight into disease mechanisms. These include: (i) presence and extent of diffuse damage in CNS tissue outside lesions (normal-appearing tissue); (ii) heterogeneity of damage and repair in focal lesions; and (iii) specific damage to CNS tissue components. This review summarizes recent technical advances in quantitative MRI, existing pathological validation of quantitative MRI techniques, and emerging applications of quantitative MRI to patients with multiple sclerosis in both research and clinical settings. The current level of clinical maturity of each quantitative MRI technique, especially regarding its integration into clinical routine, is discussed. We aim to provide a better understanding of how quantitative MRI may help clinical practice by improving stratification of patients with multiple sclerosis, and assessment of disease progression, and evaluation of treatment response., Quantitative MRI techniques provide biophysical measures of the microstructural integrity of the CNS. Granziera et al. review the information provided by qMRI in the field of multiple sclerosis research and the potential for translation of qMRI techniques into clinical practice.

A major impediment preventing normal wound healing is insufficient vascularization, which causes hypoxia, poor metabolic support, and dysregulated physiological responses to injury. To combat this, the delivery of angiogenic factors, such as vascular endothelial growth factor (VEGF), has been shown to provide modest improvement in wound healing. Here, the importance of specialty delivery systems is explored in controlling wound bed drug distribution and consequently improving healing rate and quality. Two intradermal drug delivery systems, miniaturized needle arrays (MNAs) and liquid jet injectors (LJIs), are evaluated to compare effective VEGF delivery into the wound bed. The administered drug's penetration depth and distribution in tissue are significantly different between the two technologies. These systems' capability for efficient drug delivery is first confirmed in vitro and then assessed in vivo. While topical administration of VEGF shows limited effectiveness, intradermal delivery of VEGF in a diabetic murine model accelerates wound healing. To evaluate the translational feasibility of the strategy, the benefits of VEGF delivery using MNAs are assessed in a porcine model. The results demonstrate enhanced angiogenesis, reduced wound contraction, and increased regeneration. These findings show the importance of both therapeutics and delivery strategy in wound healing.

Aging; Arteriosclerosis; Hemodynamics Envelliment; Arteriosclerosi; Hemodinàmica Envejecimiento; Arteriosclerosis; Hemodinámica Arterial pulse waves (PWs) such as blood pressure and photoplethysmogram (PPG) signals contain a wealth of information on the cardiovascular (CV) system that can be exploited to assess vascular age and identify individuals at elevated CV risk. We review the possibilities, limitations, complementarity, and differences of reduced-order, biophysical models of arterial PW propagation, as well as theoretical and empirical methods for analyzing PW signals and extracting clinically relevant information for vascular age assessment. We provide detailed mathematical derivations of these models and theoretical methods, showing how they are related to each other. Finally, we outline directions for future research to realize the potential of modeling and analysis of PW signals for accurate assessment of vascular age in both the clinic and in daily life. This article is based upon work from COST Action “Network for Research in Vascular Ageing” (VascAgeNet, CA18216), supported by COST (European Cooperation in Science and Technology, www.cost.eu). This work was supported by British Heart Foundation Grants PG/15/104/31913 (to J.A. and P.H.C.), FS/20/20/34626 (to P.H.C.), and AA/18/6/34223, PG/17/90/33415, SPG 2822621, and SP/F/21/150020 (to A.D.H.); Kaunas University of Technology Grant INP2022/16 (to B.P.); European Research Executive Agency, Marie-Sklodowska Curie Actions Individual Fellowship Grant 101038096 (to S.P.); Istinye University, BAP Project Grant 2019B1 (to S.P.); “la Caixa” Foundation Grant LCF/BQ/PR22/11920008 (to A.G.); and National Institute for Health and Care Research Grant AI AWARD02499 and EU Horizon 2020 Grant H2020 848109 (to A.D.H.).

International audience; Group analysis consists of using an anatomical space as reference, transferring data such as contact location and extend of stimulation from each patient and relating them to the symptomatic effect. Analyzing past implantations should support understanding the mechanisms of action of DBS and predicting outcome in new patients. Most studies place their focus on the chronic stimulation situation, with the lead at a fixed position in the brain. This results in few data samples per patient, requiring large cohorts. On the other hand, intra-operative tests are an attractive source of data. The aim of this study was to develop a fully automated pipeline for analyzing the results of intra-operative stimulation tests of ventro-intermediate nucleus of the thalamus (Vim) for ET using high-fidelity data and exemplify the pipeline on a group of patients. Data from 19 DBS patients (6 ET, 16 PD) from the University Hospital Clermont-Ferrand (France) was used to create an MR template including patient-specific labels, resulting in a probabilistic definition of 57 deep brain structures. Data from the 6 ET patients in the group was used to create a probabilistic stimulation map (PSM). Tremor reduction was assessed during intra-operative stimulation tests using a wrist-worn acceleration sensor. These scores were combined with patient-specific electric field (EF) simulations into a 4D volume. The latter was first summarized into a weighted mean map (average of the improvement weighted by the EF norm). Voxels with low occurrence of fields (10% of max) and number of patients (2 of 6) were excluded. Secondly, the significance of the relationship between tremor reduction and electric field was estimated with Linear mixed models using patient as a random effect. Voxels in the weighted mean map with |p|>0.05 were excluded. A fully automated, reproducible workflow was established to normalize and analyze intra-operative data and allowed to identify regions with significant relationship between electric field and tremor suppression. In the future more patients will be integrated to conduct statistical verification of the identified regions.

Tendon injuries are prevalent, debilitating and difficult to treat. Common interventions such as anti-inflammatory medication, growth factor injections and surgery are associated with short-term efficacy and long rehabilitation periods. Tendons possess an incomplete healing response which is reparative (scar-mediated) rather than regenerative, resulting in a 'healed' tissue that is mechanically inferior to the native tendon. While it is widely accepted that mechanical-loading based treatments offer long-term symptomatic resolution and improved functionality, the exact mechanisms of action of such mechanotransduction-based healing cascades remain unclear. Nevertheless, there is significant motivation for the development of non-invasive and efficient rehabilitative treatments that mechanically stimulate the injured tendons to achieve functional healing responses. Focused Ultrasound (FUS) methods are an attractive treatment option as they are non-invasive, utilize higher intensities for shorter durations and are targeted to a very specific treatment volume, hence inducing significant bio-effects in the tissue without affecting surrounding structures. Herein, we present a body of work that includes the development of FUS pulsing to precisely target murine Achilles tendons and emphasize distinct bioeffects (thermal-dominant and mechanical-dominant). We investigated the feasibility of applying FUS pulsing to murine Achilles tendons ex vivo and in vivo and demonstrated that FUS can be safely applied without any deleterious effects in the tendons and surrounding tissues. The animals showed no symptoms of distress after multi-session treatments. Overall, results suggest that tendon material properties are not adversely altered by FUS pulsing. Histological analyses showed mild matrix disorganization, suggesting the need for slight modifications in the ultrasound pulsing parameters and treatment durations. When applied to injured tendons, mechanical dominant schemes seemed to drive larger improvements in material properties compared to thermal-dominant pulsing, confirming our original hypothesis that mechanical stimulation may play a bigger role in tendon healing compared to purely thermal-dominant stimulation. Additionally, feasibility of histotripsy ablation in murine Achilles tendons was successfully investigated ex vivo and in vivo and experimentation to further optimize these methods are ongoing. Such (non-thermal) ablative paradigms will be extremely useful when conservative treatment options are unavailable and debridement of scar tissue is warranted to interrupt the degenerative process and stimulate healing. Finally, a pilot investigation into FUS-induced strains was performed to guide our parameter selection process and deliver controlled strains to achieve healing responses (similar to current clinical rehabilitation protocols). We were able confirm that strains between 1% and 6% (or higher) can be induced by manipulating ultrasound treatment parameters. Overall, or results reiterate the potential of FUS in eliciting the desired bioeffects and thus achieve healing in tendons and provide a snapshot of the expected effects of using such pulsing methods to treat tendon injuries. Doctor of Philosophy Tendons are tissues that connect muscles to bones, and are unfortunately prone to injuries. Such injuries are prevalent and difficult to treat. Effective treatment options remain limited, as common methods such as surgery, anti-inflammatory medications and corticosteroid injections do not provide long-term relief. One of the few treatments that has been proven to provide symptomatic relief and improved the functionality of chronically (over a long period of time) injured tendons is physical therapy. However, researchers are still investigating the reasons for this successful healing response. Some limitations of physical therapy are long rehabilitation and recovery periods, and the need for patient compliance (i.e., performing painful exercises while already being under significant pain). In this research, we explore the use of a non-invasive modality known as ultrasound to treat tendon injuries. Ultrasound is commonly thought of as a diagnostic tool, i.e., to detect injuries in musculoskeletal medicine. It, however, is also an attractive therapeutic (treatment) modality, as sound waves can be concentrated in the required area of interest which results in different types of effects in the chosen tissue, such as heating. A huge advantage is that ultrasound is non-invasive, painless, and safe, as the energy is only applied to the chosen volume of interest and surrounding structures are unaffected. To examine the utility of therapeutic ultrasound in treating tendon injuries, we used a mouse model that has been previously used in our lab, and designed different types of ultrasound treatments that elicit two main types of effects in the tissue, namely, thermal, or heating effects and mechanical, or physical therapy-like effects. Prior to applying these treatments, we measured how much heating is produced in mouse Achilles tendons via these treatments, to establish safety. Once we identified safe thermal and mechanical treatment sets, we treated mouse Achilles tendons ex vivo, i.e., after euthanasia. We tested the mechanical properties of the treated tendons and determined that treatments do not alter the mechanical properties of tendons, which is encouraging, given that we do not want treatments to interfere with the properties of native tendons. We also examined the influence of treatments on structure of Achilles tendons after treatments and deducted that the structure was not damaged due to treatments. We followed up these studies with treatments conducted in live mice, which received four treatment sessions in one week. These studies were conducted to further determine the safety and tolerance to these procedures and also examine the healing effects of treatments in injured Achilles tendons. Results suggest that focused ultrasound treatments are safe and tolerable to mice and seem to elicit improvements in tendon properties. In other studies, we also examined a different ultrasound method named histotripsy, as a non-invasive alternative to dry needling (which is another methodology used to treat tendon injuries) and scar debridement (removal of scar tissue to stimulate a new healing response). This research establishes that therapeutic ultrasound is a novel, non-invasive alternative with good potential to treat tendon injuries. Future studies will investigate the effects of ultrasound treatments over longer durations and also aim to clarify the exact type and magnitude of physical therapy-like forces that are produced by ultrasound treatments. This understanding will enhance our treatment design process to be able to mimic clinical treatments that are known to be effective.

Every year millions of individuals suffer from traumatic brain injury (TBI) leading to permanent disabilities and even death. Mild TBI (mTBI) is the most common form of TBI comprising about 80-90% of all occurrences. Following a CNS insult like an mTBI, astrocytes can undergo activation resulting in the transformation into reactive astrocytes (RAs). RAs also play an important role in brain remodeling following an mTBI. Research on the mechanical complexity of the brain has important implications for understanding brain function and dysfunction, as well as for the development of new diagnostic and therapeutic tools for neurological disorders. This study aimed to develop and utilize an emph{in vitro} mTBI platform to investigate the intricate mechanical interplay between the extracellular matrix (ECM) and astrocytes following a simulated mTBI. Cellular mechanisms underlying mTBI and the contribution of mechanical forces that result in prolonged brain damage are yet to be comprehensively understood. Successfully devised mechanical characterization techniques for tissue-engineered models were developed utilizing atomic force microscopy and rheology. Astrocyte exposure to high-rate overpressure revealed altered mechanical properties of the surrounding matrix and decreased expression of laminin and collagen IV, which are critical for brain function and may contribute to pathologies associated with mTBI. The developed platform and methods provide new insights into the mechanistic complexity underlying ECM-astrocyte interactions following an mTBI. Master of Science Every year, millions of people suffer from traumatic brain injury (TBI), which can lead to permanent disabilities or even death. The most common form of TBI is mild TBI (mTBI), which accounts for 80-90% of all cases. After a mTBI, astrocytes, the most common cell type in the brain, can become activated and turn into reactive astrocytes (RAs). RAs play an important role in the brain's recovery following a mTBI. Understanding the mechanical complexity of the brain is crucial for developing new diagnostic and therapeutic tools for neurological disorders. This study aimed to investigate the mechanical interplay between the modeled tissue and astrocytes following a simulated mTBI using an emph{in vitro} platform. Development of mechanical characterization techniques allowed for any alterations caused by the astrocytes to their environment to be detectable. The astrocyte exposure to the simulated mTBI revealed altered mechanical properties of the surrounding environment and decreased expression of proteins laminin and collagen IV, which are critical to brain function and may contribute to pathologies associated with mTBI. This study provides new insights into the mechanistic complexity underlying the interaction between astrocytes and their environment, which could lead to the development of new treatments.

Highly Automated Vehicles (AVs) have the capability to revolutionize the transportation system. These systems have the possibility to make roads safer as AVs do not have limitations that human drivers do, many of which are common causes of vehicle crashes (e.g., distraction or fatigue) often defined generically as human error. The deployment of AVs is likely to be very gradual however, and there will exist situations in which the AV will be driving in close proximity with human drivers across the foreseeable future. Given the persistent crash problem in which the makority of crashes are attributed to driver error, humans will continue to create potential collision scenarios that an AV will be expected to try and avoid or mitigate if developed appropriately. The absence of unreasonable risk in an AVs ability to comprehend and react in these situations is referred to as operational safety. Unlike advanced driver assistance systems (ADAS), highly automated vehicles are required to perform the entirety of the dynamic driving task (DDT) and have a greater responsibility to achieve a high level of operational safety. To address this concern, scenario-based testing has increasingly become a popular option for evaluating AV performance. On a functional level, an AV typically consists of three basic systems: the perception system, the decision and path planning system, and vehicle motion control system. A minimum level of performance is needed in each of these functional blocks to achieve an adequate level of operational safety. The goal of this study was to investigate the effects that perception system performance (i.e., target object state errors) has on vehicle operational safety in collision scenarios similar to that created by human drivers. In the first part of this study, recent annual crash data was used to define a relevant crash population of possible scenarios involving intersections that an AV operating as an urban taxi may encounter. Common crash maneuvers and characteristics were combined to create a set of testing scenarios that represent a high iii percentage of the overall crash population. In the second part of this study, each test scenario was executed using an AV test platform during closed road testing to determine possible real-world perception system performance. This provided a measure of the error in object detection measurements compared to the ideal (i.e., where a vehicle was detected to be compared to where it actually was). In the third part of this study, a set of vehicle simulations were performed to assess the effect of perception system performance on crash outcomes. This analysis simulated hypothetical crashes between an AV and one other collision partner. First an initial worst-case impact configuration was defined and was based on injury outcomes seen in crash data. The AV was then simulated to perform a variety of evasive maneuvers based on an adaptation of a non-impaired driver model. The impact location and orientation of the collision partner was simulated as two states: one based on the object detection of an ideal perception system and the other based on the object detection of the perception system from the AV platform used during the road testing. For simulations in which the two vehicles contacted each other, a planar momentum-impulse model was used for impact modeling and injury outcomes were predicted using an omni-directional injury model taken from recent literature. Results from this study indicate that errors in perception system measurements can change the perceived occupant injury risk within a crash. Sensitivity was found to be dependent on the specific crash type as well as what evasive maneuver is taken. Sensitivities occurred mainly due to changes in the principal direction of force for the crash and the interaction within the injury risk prediction curves. In order to achieve full operational safety, it will likely be important to understand the influence that each functional system (perception, decision, and control) may have on AV performance in these crash scenarios. Master of Science Highly Automated Vehicles (AVs) have the capability to revolutionize the transportation system. These systems have the possibility to make roads safer as AVs do not have many of the limitations that human drivers do, many of which are common causes of vehicle crashes (e.g., distraction or fatigue). AVs will be expected to drive alongside human drivers, and so these drivers are likely to continue to be at fault in causing crashes. As part of ensuring safety, AVs will reasonably be expected to try and avoid or help reduce the severity of these crashes. AVs operate using three main systems: the perception system which consists of sensors that see the objects around the AV, the decision and path planning system, which makes decision on what the AV will do, and the vehicle motion control system. Due to the nature of the real-world, these systems may not work exactly as intended which may affect the ability of the AV to react to possible crash scenarios. Because of this, the goal of this study was to investigate the effects that perception system performance (i.e., target object state errors) has on the ability of an AV to react to crash scenarios similar to those created by human drivers. This study first defined crash scenarios using real-world crash data. A real-world perception system was then tested in these scenarios to determine object detection performance. Based on this performance, effects on safety were assessed through vehicle crash simulations. Results from this analysis showed that safety can vary based on both perception system performance and crash scenario. This highlights that it will be important to address system performance in order to achieve high levels of driving safety.

Current return-to-drive recommendations for patients following rotator cuff repair (RCR) surgery are not uniform due to a lack of empirical evidence relating driving safety and time-after-surgery. To address the limitations of previous work, Badger et al. (2022) evaluated, on public roads, the driving fitness of patients prior to RCR and at multiple post-operative timepoints. The goal of the Badger, et al. study was to make evidence-based return-to-drive recommendations in an environment with higher fidelity than that of a simulator and not subject to biases inherent to surveys. Badger et al., however, do not fully investigate the driving practices exhibited by subjects, overlooking the potential presence of compensatory driver behaviors. Further investigation of these behaviors through observation of direct driving techniques and practices over time can specifically answer how drivers may modify their behaviors to address a perceived state of impairment. Additionally, the degree of success in vehicle operation by comparing an ideal turn to the path taken by the driver allows for a level of quantification of the effectiveness of the compensatory techniques. Moreover, driver trajectories inferred from the vehicle Controller Area Network (CAN) metrics and from global positioning system (GPS) coordinates are contrasted with the ideal turn to assess minimum requirements for future sensors that are used to make these trajectory comparisons. This investigation leverages pre-existing data collected by the Virginia Tech Transportation Institute (VTTI) and Carilion Clinic as used in the analysis performed by Badger et al. (2022). RCR patients (n=27) executed the same prescribed driving maneuvers and drove the same route in a preoperative state and at 2-, 4-, 6-, and 12-weeks post operation. Behavioral data were annotated to extract key characteristics of interest and related them to relevant vehicle sensor readings. To construct vehicle paths, data was obtained from the on-board data acquisition system (DAS). Behavioral metrics considered the use of ipsilateral vehicle controls, performance of non-primary vehicle tasks, and steering techniques utilized to assess the impact of mobility restrictions due to sling use. Sling use was found to be a significant factor in use of the non-ipsilateral hand associated with the operative extremity (i.e., operative hand) on vehicle functions and, in particular, difficulty with the gear shifting control. Additionally, when considering the performance of non-primary vehicle tasks as assessed through a prescribed visor manipulation, sling use was not a significant factor for the task duration or completion of the task in a fluid motion. Sling use was, however, significant with respect to operative hand position prior to the completion of the visor manipulation: the operative hand was often not on the steering wheel prior to the visor maneuver. In addition, the operative hand was never used to manipulate the visor when the sling was worn. One-handed steering was also more frequent with the presence of the sling. Further behavioral analysis assessed the presence of compensatory behavior exhibited by subjects during periods in which impairment was perceived. Perceived impairment was observed as a function of the different experimental timepoints. Findings indicated a significant decrease in the lateral vehicle jerk during post-operative weeks 6 and 12. Significant differences, however, were not observed in body position alteration to avoid contact with the interior vehicle cabin, in over-the-shoulder checks, and in forward leans during yield and merge maneuvers. Regarding trajectory analysis, sling use did not produce a significant difference in the error metrics between the actual and ideal paths. In completion of turning maneuvers, however, operative extremity was significant for left turns, with greater error against the ideal path observed from those in the left operative cohort compared to those in the right operative cohort. For the right turn, however, operative extremity was not found to be a significant factor. In addition, the GPS data accuracy proved insufficient to support comparison against the ideal path. Overall, findings from this study provide metrics beyond those used in Badger, et al. that can be used in answering when it is safe for rotator cuff repair patients to return-to-drive. With the limited differences observed as a function of study timepoint and sling use, it is recommended that patients are able to safely return-to-drive at two weeks post-operation. If anything, results suggest that overcompensation, as inferred from observation of safer driving behaviors than normal, is present during some experimental timepoints, particularly post-operative week 2. Master of Science Current recommendations based on when it is safe for rotator cuff repair patients to return-to-drive are not standard because of a lack of suitable evidence. Previous work and recommendations rely on surveys and simulators which do not create fully realistic conditions and are subject to biases. To address the limitations of previous work, Badger et. al (2022) studied actual rotator cuff repair patients on public roads prior and following operation at multiple timepoints. Badger et al., however, did not consider the potential adaptations in driver behavior due to mobility restrictions and the perception of inferiority due to injury. Additionally, the degree of success of the adaptive driving behaviors based on the error between the actual vehicle path taken and a defined ideal path have not been explored in conjunction with the injury. This investigation is based on the pre-existing data collected by the Virginia Tech Transportation Institute (VTTI) and Carilion Clinic as used in the analysis performed by Badger et al. (2022). RCR patients (n=27) executed identical driving maneuvers and drove the same route before operation and at 2-, 4-, 6-, and 12-weeks post operation. Behavioral observations were recorded and related to relevant vehicle sensor readings. To construct vehicle paths, data was taken from the on-board data acquisition system (DAS). Participants adopted different behaviors, such as using the right hand to use the turn signal when the left arm was in a sling and the left hand to operate the gear shifter when the right arm was on a sling, to assist in combating mobility restrictions. One-handed steering was also more prominent during periods of sling-use. Sling-use, however, did not produce a significant difference in error between the actual vehicle path taken and the ideal path available to the driver. For left-operated participants completing left turns, there was also greater error in comparison to the ideal path than for the group of right-operated patients. However, there was not a difference between left- and right-operated arm participant error in completion of a right turn. The GPS data did not provide a suitable approximation of vehicle trajectory. Overall, findings from this study help to answer when it is safe for rotator cuff repair patients to return-to-drive through evaluation of the effectiveness of compensatory behaviors adopted by participants. With no significant difference in turn execution based on sling use, results suggest that patients can safely return-to-drive at two weeks post-operation. In fact, results suggest that overcompensation towards safer behaviors is present during some experimental timepoints, particularly post-operative week 2.

Formalin-fixed, paraffin embedded (FFPE) tissue is the most abundant, accessible, and versatile tissue sample type available for genetic research and clinical applications. However, FFPE DNA extraction presents unique challenges and requires lengthy incubation periods, which can be impractical for certain applications. Here, we propose the use of focused ultrasound extraction (FUSE) technology for improved DNA extraction from FFPE tissue. FUSE generates a dense bubble cloud of acoustic cavitation capable of ablating tissue into an acellular lysate. FUSE treatment was applied to de-paraffinized porcine pancreas FFPE scrolls, followed by heated incubation for formaldehyde-induced DNA-protein crosslink reversal. When applied for 30 minutes, FUSE was found to successfully extract DNA from FFPE tissue as defined by increased DNA yield and improved purity ratios compared to conventional methods. DNA extracted via FUSE showed comparable fragmentation to conventional methods, and three out of four samples successfully amplified via PCR, indicating suitability for downstream analysis. These findings suggest that FUSE has the potential to increase the efficiency and effectiveness of DNA extraction from FFPE tissue. Further development and optimization of this protocol could develop a streamlined, easy to use extraction method that would simplify FFPE DNA extraction methods and address the primary time constraints which currently make FFPE DNA extraction time-consuming and impracticable for high-throughput applications. Master of Science Formalin-fixed, paraffin embedding (FFPE) has historically been the most popular method of biological tissue preservation, as it allows tissue to remain shelf stable for decades. As such, FFPE tissue is the most abundant, accessible, and versatile tissue sample type available for genetic research applications. Here, we propose the use of focused ultrasound extraction (FUSE) technology for improved DNA extraction from FFPE tissue. FUSE treatment applies rapid, focused ultrasound waves to tissue, resulting in the mechanical breakdown of cells and subsequent release of DNA. FUSE treatment was applied to pig pancreatic FFPE samples. When applied for 30 minutes, FUSE was found to successfully extract DNA from FFPE tissue as defined by increased DNA yield and improved purity compared to conventional methods. Three out of four DNA samples extracted via FUSE were successfully amplified, and DNA fragment lengths were comparable between FUSE and conventional methods, showing that FUSE did not fragment DNA beyond useful fragment lengths. These findings suggest that FUSE has the potential to increase the efficiency and effectiveness of DNA extraction from FFPE tissue. Further development and optimization of this protocol could develop a streamlined, easy to use extraction method that would simplify FFPE DNA extraction methods and address the primary time constraints which currently make FFPE DNA extraction time-consuming and impracticable for high-throughput applications.

One of the principal challenges of primary blast injury research is imitation of shock waves accurately and consistently in a safe and tunable platform. Existing simulators have been effective in these goals but have not been conducive for in vitro models due to their large size and air-mediated wave propagation. In this thesis, a redesigned benchtop shock wave generator (SWG) has provided a platform for in vitro models. A pulsed power generator charges a capacitor and discharges the capacitor through a bridge wire. The discharge causes the bridge wire to experience phase changes, momentarily becoming a gas or plasma. In this moment, the bridge wire expands radially and creates a pressure wave in the surrounding water. As the wave propagates, it forms a shock wave and strikes the cell platform at the far end of the conical tank. Current design efforts are focused on the tunability of the SWG, by varying the bridge wire material and diameter. Five materials at three bridge wire diameters have been tested. Each bridge wire was inserted into the SWG via a pinching mechanism. Either side of the pinching mechanism was connected to either terminal of the capacitor. When the pulsed power generator was cycled, the bridge wire was vaporized and generated a shock wave. A piezoelectric sensor near the wide end of the tank recorded the passing of the shock wave, which was used to derive various pressure metrics that correlate to injury. The sample size for each combination of diameter and material was five, with a grand total of seventy-five samples run. Two-way ANOVAs measuring the impacts of bridge wire material and diameter on a variety of shock wave metrics found that the diameter played a significant role in determining the peak overpressure and positive impulse generated while the main effect of material played a much smaller role. The interaction between material and diameter was also found to be significant. The tunable benchtop SWG provides a platform for exploration of primary blast injury using in vitro models. By adjusting the bridge wire diameter, the SWG can generate waves with a variety of shock wave metrics, providing an opportunity for researchers to address various degrees of injury. With the addition of this technology to the efforts to understand primary blast injury, development of treatments and protective equipment can be expedited. Master of Science Primary blast injury, the injury caused by the blast wave moving through the body, has been affecting those exposed to blast for nearly a century, since the regular use of conventional explosives in World War I. As equipment and war has changed in the past two decades, there has been heightened interest in understanding the effects of blast waves on the body. To assist in this research, blast wave simulators have been developed to recreate the blast wave in a controlled environment. However, current designs are not conducive to experiments on cultured cells. A new blast wave simulator, called the shock wave generator (SWG), has been designed as a platform for cultured cell-based experiments. The simulator generates a shock wave by exploding a thin bridge wire using high electrical current. The explosion occurs underwater, generating a shock wave capable of injuring cells at the opposite end of the tank. A platform such as this provides multiple opportunities to tune the pressure metrics related to the shock waves. Bridge wire material and volume play critical roles in the resulting shock wave, working together to define the amount of energy required to vaporize the bridge wire. Five materials and three diameters, a derivative of the wire volume, were investigated to determine their impacts on the resulting peak pressure, positive duration, and positive impulse. While wire material was not found to have a significant impact on peak pressure, wire diameter had a significant effect on the resulting overpressures. The thickest wire generated the lowest peak pressure while the thinner wires generated higher peak pressures. The thinner wires were not significantly different from one another. A similar result was found for positive duration and impulse. Overall, the use of an exploding wire to generate shock waves is applicable as an injury mechanism for cell cultures in primary blast injury research. This work along with future work will provide a tunable and controlled platform that has opened a new frontier for investigating the primary blast injury.

Low back pain is one of the most common and disabling musculoskeletal disorders worldwide and the third most common reason for surgery in the United States. The lower back, or lumbar region, supports most of the body's weight; it controls spinal movement and stability through the interaction between bones, nerves, muscles, ligaments, and fascia within the lumbar region. Any disorder of those tissues could cause low back pain (LBP); emerging evidence indicates that the thoracolumbar fascia (TLF) is the lower back's most pain-sensitive soft tissue structure. TLF consists of dense connective tissue separated by loose connective tissue, allowing TLF layers to pass easily during torso movement. A series of foundational studies found that patients enduring long-term low back pain have different TLF structures than those without LBP. Injuries may result in adhesions and fibrosis, which may cause adjacent dense connective tissue layers to lose independent motion, limiting movement and causing pain. LBP is diagnosed by investigating the patient's medical history to identify symptoms and then examining the patient to determine the cause of the pain. If the pain persists after diagnosis and treatment, further investigation is required; an ultrasound scan is used as the next step. Ultrasound (US) imaging is a non-invasive and instantaneous method to evaluate soft, connective tissue structures such as muscles, tendons, ligaments, and fascia. Even though measuring echo intensity helps evaluate the soft tissues, this method still has limitations in diagnosing LBP; 90 % of all LBP patients are diagnosed with non-specific LBP, referred to as pain with no definitive cause . An in-depth investigation of US images could potentially provide more specificity in identifying sources of LBP. By providing information about soft tissue structure, texture analysis could increase US images' diagnostic power. The texture of an ultrasound image is the variation of pixel intensities throughout the region of interest (ROI) that produces different patterns; texture analysis is an approach that quantifies the characteristic variation of pixel intensities within ROI to describe tissue morphological characteristics. First-order texture analysis, second-order texture analysis, and grey-level run length texture analysis are types of analysis that could be applied to quantify parameters that describe the features of the texture; the grey-level analysis is usually conducted in four directions of the texture. This study has four objectives; the first objective is to use first-order and second-order analysis to determine texture parameters and determine whether those parameters can differentiate between individuals with and without LBP. The second objective is to use grey level run length analysis to quantify texture parameters in four directions (0^°,45^°,90^°,135^°) and examine whether those parameters can differentiate between individuals with and without LBP. The third objective is to determine the correlation between the first, second, and run length parameters. The fourth objective is to explore how first-order, second order and grey level run length parameters are affected by US machine settings. A custom-written MATLAB program was developed to quantify first and second-order texture parameters and grey-level run length parameters. Using JMP software, each parameter was statistically compared between individuals with and without LBP. Among nine first- and second-order texture parameters, four showed statistically significant differences between individuals with and without LBP. Among 44 run-length parameters, 9 showed statistically significant differences between individuals with and without LBP. The current study also revealed some strong correlations between first, second, and run length parameters; it also shows that the US machine setting has minor effects on the three types of parameters. Although the present study was conducted on a relatively small sample size, the results indicate that one direction of grey level run length analysis and first and second-order texture analysis can differentiate between people with and without LBP. Master of Science Low back pain (LBP) is one of the most common and disabling musculoskeletal disorders worldwide and the third most common reason for surgery in the United States. Due to LBP's effect on mobility, it is one of the leading causes of absence from work, early retirement, and long-term disability payments. The thoracolumbar fascia (TLF), a connective tissue that stabilizes the trunk, pelvis, and spine, is considered the most sensitive tissue to LBP. LBP diagnosis is based on the patient's medical history to identify symptoms and then on an examination to determine the cause. If the pain persists after diagnosis and treatment, imaging is recommended as the next step. Ultrasound (US) imaging produces a cross-sectional image of the structure and has been used to compare TLF structure in people with and without LBP. Additional analyses must be done to increase US images' ability to diagnose LBP. In the current project, three types of analysis of US images were performed; first-order, second-order, and grey level run length analyses were performed to determine parameters for the images of the two groups of people; selected parameters were noted to distinguish between people with and without LBP.

Subconcussions in sport is a growing field of interest and concern as deteriorative effects of these impacts have been shown in athletes without a diagnosed concussion. Detecting subconcussions is extremely difficult and there is no standardized method to recognize these injuries. A first step in identifying subconcussion is taking a closer look at concussions. The vestibular system has been shown to be negatively affected after concussive injuries which can be quantified via oculomotor function and pupillometry. Currently, King Devick (KD) style tests and Pupillary Light Reflex (PLR) are two popular tests that can be administered to athletes to gather clinical eye measures relating to oculomotor function and pupillometry. This study aimed to investigate how clinical eye measures change through serial in-season testing of Division 1 (D1) soccer athletes. Head impacts throughout a soccer season were recorded and we hypothesized that a greater number of head impacts would result in negative clinical changes even in the absence of a diagnosed concussion. No major trends were observed in soccer athletes that can be associated with trends seen in concussed populations. Soccer athletes were found to be slightly more likely to test abnormally than non-contact controls and soccer athletes with a greater number of head impacts were found to have slightly more abnormal tests than athletes with fewer head impacts. Overall, this study provides a dataset of pre and post-season measurements and uniquely includes multiple in-season measurements to provide a new perspective on oculomotor function and pupillary light reflex over the course of a sports season. Master of Science Subconcussions in sport is a growing field of interest and concern as deteriorative effects of these impacts have been shown in athletes without a diagnosed concussion. Detecting subconcussions is extremely difficult and there is no standardized method to recognize these injuries. The first step at identifying subconcussions is to more closely look at concussions. Eye movements and pupil response to stimuli can be affected after a concussive injury. Currently, King Devick (KD) style tests and Pupillary Light Reflex (PLR) are two popular tests that can be administered to athletes to gather clinical eye measures relating to eye motion and pupil response to stimuli. This study aimed to investigate how clinical eye measures change through repeated in-season testing of Division 1 (D1) soccer athletes. Head impacts throughout a soccer season were recorded and we hypothesized that a greater number of head impacts would result in negative clinical changes even in the absence of a diagnosed concussion. No major trends were observed in soccer athletes that can be associated with trends seen in concussed populations. Soccer athletes were found to be slightly more likely to test abnormally than non-contact controls and soccer athletes with a greater number of head impacts were found to have slightly more abnormal tests than athletes with fewer head impacts. Overall, this study provides a dataset of pre and post-season measurements and uniquely includes multiple in-season measurements to provide a new perspective on clinical eye measures over the course of a sports season.

Historically, the rear seat has been considered safer compared to the front seat for all restrained occupants; however, studies have found that the front seat in newer vehicles might be safer for older adults than the rear seat. While adults make up only 19% of rear seat occupants in frontal crashes, they make up 48% of fatalities (Tatem and Gabler, 2019). The rate of rear-seat occupancy by adults is expected to increase due to the use of ride share services and the potential of autonomous vehicles. Minimal research has been done to assess rear-seat occupant protection for a mid-sized adult male. Submarining, in which the lap belt slips off of the pelvis and directly loads the abdomen, is of particular concern as a restraint-based injury mechanism of the abdomen. The objective of this study is to investigate submarining protection and abdominal injury risk for rear-seated mid-sized male occupants in frontal crashes and to assess the biofidelity of two anthropomorphic test devices (ATDs) with respect to submarining response when compared to post-mortem human surrogates (PMHS). Twenty-four frontal crash sled tests were conducted with the THOR-50M and Hybrid III 50th-percentile male ATDs in three crash conditions and seven modern vehicles. The vehicles included a minivan, an SUV, 3 compact SUVs, and 2 sedans from the US vehicle fleet (model years 2017-2018). Four vehicles had conventional restraints (ie. 3-point belt with retractor at the shoulder) in the rear seat and three vehicles had advanced restraints (ie. 3-point belts with a pretensioner and load limiter at the retractor). Two of the crash conditions were vehicle-specific pulses: NCAP85 (ΔV = 56 kph) and Scaled (ΔV = 32 kph). The final pulse was a Generic (ΔV = 32 kph) pulse, created by averaging all seven Scaled pulses. Matched PMHS tests were conducted on four of the vehicles in the NCAP85 condition. Two tests were conducted for each vehicle with 8 PMHS for a total of 8 sled tests. The occurrence of submarining was identified and assessed for severity by: symmetry of lap belt slip, degree of abdominal loading, and forward excursion of the pelvis. Pelvis and lap-belt kinematics were assessed for the matched NCAP85 tests to identify trends with respect to submarining. Damage to the abdomen, pelvis, and lumbar spine of the PMHS was identified during post-test autopsy. The Hybrid III did not submarine in any test, but the THOR submarined in 16/24 tests. Three PMHS underwent submarining in 2/4 vehicles, and the THOR submarined in 3/4 vehicles in the matched NCAP85 tests. Three PMHS did not undergo submarining but sustained pelvis fractures at lap belt loads of 7.4 kN and higher, and damage to the abdominal viscera occurred regardless of submarining occurrence. Pelvis and lap-belt kinematics revealed the complex nature of the interactions of the occupant and the restraints within each vehicle environment, but did not clearly differentiate between submarining and non-submarining tests. The Hybrid III was not able to predict submarining risk for the PMHS in the rear seat environment. While the THOR underwent submarining, it was not perfect in predicting submarining risk. Pelvis geometry, lap belt engagement, and other factors contributed to the differences in submarining between the two ATDs and the PMHS. Restraint type was not indicative of whether or not the THOR or PMHS would submarine. Many other factors in the rear seat environments of these vehicles likely contribute in combination to the effectiveness of submarining prevention and occupant protection in the rear seat. This study provides information regarding submarining and abdominal injury for three surrogate types, two crash severities, and seven modern, real-world vehicle environments. Ultimately, this study found substantive gaps in occupant protection in the rear seats of modern vehicles for mid-sized adult male occupants. Tatem, W. M., and Gabler, H. C. (2019). Differential fatality risk between rear and front seat passenger vehicle occupants in frontal crashes. In Proceedings of the 2019 International IRCOBI Conference on the Biomechanics of Injury (pp. 554–560). Doctor of Philosophy Historically, the rear seat has been considered safer than the front seat for restrained occupants in frontal crashes. However, with advances in safety systems for the front seat, studies have found that the front seat might be safer for older adult occupants. The objective of this study is to investigate submarining protection and abdominal injury risk for rear-seated mid-sized male occupants in frontal crashes. Submarining occurs when the lap belt slips off of the pelvis and directly loads the abdomen, potentially producing severe abdominal injuries. Twenty-four sled tests were conducted with the THOR-50M and Hybrid III 50th-percentile male anthropomorphic test devices (ATDs) in three crash conditions and seven modern vehicles. The vehicles selected included a minivan, SUVs, compact SUVs, and sedans from the US vehicle fleet. Three of the vehicles had advanced restraints in the rear seat and four had conventional restraints. The three crash conditions were a generic low speed test and a low and high-speed vehicle-specific crash pulse. Eight tests were conducted with eight different post-mortem human surrogates on a subset of four vehicles (2 with advanced restraints, 2 with conventional restraints) using the high-speed crash condition. The Hybrid III never submarined, but the THOR submarined in 16 out of 24 tests (5 out of 7 vehicles). Three out of eight PMHS submarined, in two of the four vehicles. Three heavier PMHS sustained pelvis fractures, and all but one PMHS had sustained damage to the abdominal viscera. Restraint type was not an indicator of submarining risk in the rear seat, suggesting that other seat and vehicle design variables contribute to submarining risk. Comparison of the responses of the ATDs with the PMHS suggests that the THOR is a more reasonable surrogate than the Hybrid III for submarining assessment in the rear seat. Inclusion of data from other body regions is necessary to make a definitive determination of the appropriate ATD for the assessment of occupant protection for a mid-sized male in the rear seat during frontal crashes. Overall, this study suggests that protection against submarining and injury to the pelvis and abdomen for mid-sized male passengers in the rear seat of modern vehicles in the US fleet could be improved.

The increased prevalence of crash avoidance technologies like autonomous emergency braking necessitates understanding of occupant responses during low-speed frontal pre-crash braking and low-severity crash events. Active human body models (HBMs) have emerged as valuable tools to evaluate occupant safety during these events, but must be validated with relevant volunteer data to accurately represent the responses of live occupants. The objective of this dissertation was to quantify the occupant responses of relaxed and braced 5th percentile female and 50th percentile male volunteers during low-speed frontal and frontal-oblique sled tests designed to simulate pre-crash braking and low-severity crash events. A study comprised of 160 low-speed sled tests was performed with 20 volunteers. The volunteers' kinematics, kinetics, and muscle responses were compared to determine how altering impact direction (frontal and frontal-oblique), impact severity (1 g and 2.5 g), demographic group (mid-size male and small female), and muscle state (relaxed and braced) affected occupant responses. The volunteers' occupant responses were significantly affected by impact direction, impact severity, demographic group, and muscle state. The frontal-oblique tests resulted in greater leftward excursions compared to the frontal tests. Increasing the pulse severity resulted in greater forward excursions, reaction forces, and muscle activation. The male volunteers exhibited greater forward excursions and reaction forces compared to the female volunteers. However, the two demographic groups exhibited similar muscle activation during the sled tests. Bracing increased the volunteers' initial joint angles, muscle activation, and reaction forces prior to the sled tests. Bracing decreased forward excursions and increased reaction forces during the sled tests. The relaxed volunteers exhibited greater relative changes in occupant responses compared to the braced volunteers. Overall, this study demonstrated that muscle activation significantly affected the volunteers' kinematics, kinetics, and muscle responses for both mid-size males and small females during low-speed events. Observed differences between demographic groups were more prominent when relaxed and more diminished when braced. These results underscore the importance of validating active HBMs with relevant volunteer data in order to be more representative of live occupants for a wider range of demographic groups in varying muscle states. Finally, this dissertation provides a large, comprehensive, and novel biomechanical dataset that can be used to develop and validate active HBMs for use in assessing occupant response during frontal pre-crash braking and low-severity crash events. These models will help improve the understanding of potential injury risk and development of effective vehicle safety systems for use during low-speed events. Doctor of Philosophy Computer models, known as active human body models (HBMs), have emerged as tools that can be used to assess occupant safety during low-speed vehicle crashes. In these types of events, occupants have enough time to react and potentially brace before the crash, which could in turn affect their responses during the crash. It is important to understand how occupants respond during crashes so that effective vehicle safety systems can be developed. Active HBMs are particularly valuable because they can simulate muscle activation to reflect the response of live occupants. However, data are needed from live occupants to ensure that these models are accurate. To gather this data, a study was performed where volunteers experienced low-speed frontal sled tests when they were relaxed and braced. The sled tests were designed to simulate pre-crash braking and low-severity vehicle crashes. Mid-size male and small female volunteers were recruited to participate to represent the standard adult occupant populations used in current frontal impact vehicle safety standards. A motion capture system was used to measure the volunteers' forward motion, load cells were used to measure the volunteers' exerted reaction forces on the test buck, and electrodes were used to measure the volunteers' muscle activity. The volunteers' responses were significantly different between the relaxed and braced muscle states, and between the males and females. Comparing between males and females, the males moved farther forward and exerted larger reaction forces, but both demographic groups exhibited similar muscle responses. Comparing between muscle states, bracing increased the volunteers' muscle activation and reaction forces before the sled tests. Bracing also increased the volunteers' reaction forces during the sled tests, but decreased forward movement. Overall, the volunteers exhibited greater relative changes in response when they were relaxed compared to when they were braced. Overall, this study demonstrated that muscle activation significantly affected the volunteers' responses for both mid-size males and small females during low-speed events. These results highlight the importance of developing active HBMs with relevant volunteer data in order to be more representative of live occupants. Finally, the data from this study can be used to develop active HBMs to improve their accuracy, so that the models can be used to assess occupant safety during low-speed frontal vehicle crashes. This will help improve the understanding of potential injury risk and development of effective vehicle safety systems, to reduce the number of injuries caused by vehicle crashes.

Histotripsy is a non-invasive and non-thermal focused ultrasound therapy that can be used to ablate tissue within the body while overcoming many of the limitations of thermal ablation. Histotripsy utilizes short-duration, high pressure ultrasound pulses to create a cavitation bubble cloud of numerous rapidly expanding and collapsing bubbles, which cause mechanical stress on the targeted region. Histotripsy contains multiple subtypes including intrinsic threshold, shock scattering, and boiling histotripsy, where intrinsic threshold histotripsy utilizes single cycle pulses focused to a single point to create a bubble cloud from the peak negative pressure (p- ≥ 25 MPa for water-based tissues). Nanoparticle-mediated histotripsy (NMH) uses perfluorocarbon-filled nanoparticles to create bubble clouds at lower pressures than that of the intrinsic threshold of histotripsy. Prior studies have shown that nanodroplets (NDs) and nanocone clusters (NCCs) both reduce the cavitation threshold, but further investigation on different parameters to optimize treatments have not fully been studied. Additional research is needed for the characterization of these nanoparticles with different pulsing parameters such as cycle number and frequency in order to better predict and understand the mechanisms underlying NMH. In this thesis, I investigate the ability of new nanodroplets and nanocone clusters to reduce histotripsy cavitation threshold with NMH. I also investigate the effect that multi-cycle pulsing parameters have on NMH and stable bubble formation from acoustic droplet vaporization (ADV) for nancone clusters. The culmination of this thesis will advance our understanding of the behavior of acoustically-active nanoparticles when exposed to varied pulsing schemes and frequencies. This knowledge will allow for the further investigation of more efficient, effective, and safe methods for clinical focused ultrasound therapies. Master of Science Histotripsy is a non-invasive and non-thermal focused ultrasound therapy that can be used to destroy targeted tissue within the body. Histotripsy is currently being developed for non-invasive and non-thermal cancerous tissue destruction with the first-in-man trial having been conducted within the last year for the treatment of liver tumors. Histotripsy utilizes high-pressure, short-duration pulses focused to a single region to create a cloud of bubbles that are rapidly expanding and collapsing which causes mechanical damage to the targeted cells. Nanoparticle-mediated histotripsy (NMH) has been developed to utilize nanoparticles to reduce the pressure needed to induce cavitation. Despite many studies and advances in histotripsy, there are many areas within the topic that need additional research to better understand the capabilities of the treatment method. This additional research is crucial in allowing for the development of new nanoparticles, faster treatment times, and new parameters that could allow for more precision near critical structures. In this thesis, I investigate the ability of new nanoparticles to reduce histotripsy cavitation threshold with NMH. I also investigate the effect that multi-cycle pulsing parameters have on NMH and stable bubble formation for nanoparticles. The culmination of this thesis will advance our understanding of the behavior of acoustically-active nanoparticles when exposed to varied pulsing schemes and frequencies. This knowledge will allow for the further investigation of more efficient, effective, and safe methods for clinical focused ultrasound therapies.

Human locomotion is a topic that has been studied for many years in biomechanics. To perform athletic tasks or everyday tasks, balance and symmetry is needed. Symmetry is the perfect balance and correspondence of the body or parts of the body. This concept has often been used to evaluate the normality of movements. Limb symmetry, specifically, is the equal actions of the lower limbs during movement. This is needed to perform tasks safely and efficiently without injury. Gait and movement symmetry has been used to predict lower limb injury risk for many populations and improve performance for athletes. It has also been used in assessment for rehabilitation processes and return to sport processes following injury or surgery. For many years, healthy gait was considered to be symmetrical for simplification purposes. However, many studies have contradicted that conclusion showing that even for has asymmetrical patterns. Deficits in symmetry can reduce quality of life for some individuals and can have detrimental health effects. Many measures have been used to assess symmetry in various tasks that have important implications on gait patterns. Another component of gait and movement that affects performance and injury risk is limb stiffness. Limb stiffness is the body's resistance to deformation when moments and forces are applied to it. The body has been shown to be modeled as a spring mass system that can restore and reuse energy. This is associated with the stretch shortening cycle during cyclic movements, such as running and walking. Limb stiffness is also associated with musculoskeletal loading that impacts performance and injury. Therefore, optimizing limb stiffness is important to improve utilization of elastic energy for athletic performance and reduce injuries associated with high and low limb stiffness values. Imbalances in limb stiffness have been shown to increase injury risk during walking and other tasks. Studying these imbalances using symmetry indices could give insight into the injury risk associated with this metric. In addition, limb stiffness in humans has been shown to change with the type of contact surface. This is associated with compensation methods used by humans when contacting different surfaces. Studying the relationship between limb stiffness symmetry and different surfaces during walking is important to observe how humans adjust and how it impacts injury risk. The purpose of this research was to assess the impact that surface stiffness has on limb stiffness symmetry during walking in healthy adults. To assess limb stiffness differences when transitioning to different surface stiffnesses anteriorly and posteriorly, the Normalized Symmetry Index (NSI) was determined for the two transition conditions and the control. The results showed that limb stiffness NSI was significant between the conditions (p=0.012). More specifically, a difference was seen between the stiff to compliant transition and the control (p=0.020) and the compliant to stiff transition and the control (p=0.032). These results show that humans do compensate when transitioning onto different surfaces. This is essential for understanding how humans adjust during real world walking and what patterns are used to maintain stability. To assess limb stiffness symmetry, when surface stiffness is different between limbs, the limb stiffness NSI was compared between two conditions. This included the side-to-side stiffness difference condition and the control condition. The results revealed that surface stiffness was not significant between conditions (p=0.244). Based on these results, limb stiffness symmetry is not significantly impacted when the surface stiffness is different between limbs. This contradicts prior studies that observed changes limb stiffness and symmetry depending on the surface stiffness. This may be due to overcompensation or the ability of the healthy adult population to quickly adjust to the surface stiffness changes before the measurements were taken. Simulating uneven surfaces is important to understand how humans compensate to maintain stability on surfaces in real world walking and for imbalances due to disorders. Further research is needed to study the changes in limb stiffness symmetry on different surfaces during walking to improve injury prevention methods. Master of Science Humans perform many daily tasks and athletic tasks that have been observed in human movement analysis. To perform these tasks safely and efficiently, many factors must be considered. One of the important factors in performing tasks is symmetry. Symmetry is the perfect balance between parts of the body, such as the lower limbs during walking or gait. Gait in healthy adults was considered to be symmetrical for simplification purposes. However, studies have revealed that gait asymmetry is present in the healthy adult population during walking and other movements. Gait symmetry has been used to assess normality of gait patterns in healthy individuals and in clinical populations. Asymmetrical gait patterns can lead to injury and have detrimental effects on health. Therefore, limb symmetry has been an important metric to assess lower limb injury risk and improving injury prevention methods to correct asymmetrical patterns in healthy adults and other populations. Another aspect of human movement that impacts injury is limb stiffness. Limb stiffness is the body's resistance to deformation under applied forces. High limb stiffness values have been associated with bony injuries due to increased loading. However, low stiffness values have been associated with soft tissue injuries. Therefore, regulating limb stiffness is important to reduce injuries in the long term. The type of contact surface during walking and other tasks has been shown to change limb stiffness values. Humans often encounter changes to surfaces when walking. For example, hikers who encounter uneven terrain or everyday walking on uneven pavement. Uneven surfaces have been shown to require more energy and work to move forwards during walking. Therefore, simulating uneven surfaces in the real world is important to understand how humans compensate on different surfaces. This could be important for understanding how limb stiffness imbalances on different surfaces affect injury. To quantify these imbalances, the metric of limb stiffness symmetry will be used. Limb stiffness imbalances due to surface stiffness are essential to assess how humans adapt to instability during real world walking. Therefore, this study aims to determine how humans adjust when transitioning to different surface stiffnesses and when surface stiffness is different between limbs. To determine how humans adjust when transitioning to different surfaces of different stiffnesses, the limb stiffness symmetry was calculated using the Normalized Symmetry Index (NSI). This was calculated for three different surface stiffness conditions, consisting of a stiff to compliant transition, a compliant to stiff transition, and the control condition. The results showed that there was a significant difference between the NSI values of the three conditions. However, there was no difference between the two transition conditions. This indicated that there was no difference between the transition order. Based on the results, limb stiffness symmetry does change when transitioning to different surface stiffness conditions. This agrees with previous literature that suggests that surface stiffness has an impact on limb stiffness. This information is beneficial to understand the patterns humans use to compensate to maintain stability. To determine how limb stiffness symmetry is impacted when surface stiffness is different between limbs, the limb stiffness NSI was calculated for two surface conditions. This included the side-to-side condition and the control condition. The results showed that there was no statistical difference between the limb stiffness NSI values of the two conditions. This shows that limb stiffness symmetry doesn't change when the surface stiffness is different between limbs, which disagrees with previous literature. Overall, this information is important to understand how humans compensate when transitioning on different surfaces or walking on uneven surfaces. This is important to understand how stability is maintained despite imbalances for improvement of injury prevention methods.

Non-contact injuries can occur when athletes use poor or inconsistent mechanics during typical sport-related movements like landing from a jump. Anterior cruciate ligament (ACL) injuries are especially devastating, and certain populations like female athletes and athletes with a previous ACL reconstruction (ACLR) are at greater risk of suffering an ACL injury, with altered biomechanical strategies being one proposed reason. Asymmetric landings where one limb experiences greater landing force can decrease joint stability and place the overloaded limb at greater risk for ACL injury. Additionally, a stiff landing, characterized by increased ground reaction force (GRF), extended joints at initial ground contact, and decreased joint flexion throughout the landing, has been proposed to increase ACL injury risk. While load distribution between limbs is a common landing assessment to determine injury risk, it is unclear what role limb stiffness plays in the likelihood of experiencing an ACL injury. Limb stiffness is simply the deformation of the limb in response to the downward force applied to the lower limb during ground contact, which can be approximated using GRF. Limb stiffness has been commonly used to assess performance in running, hopping, and jumping, however, its relationship with injury risk during landings is relatively unexplored. Past research has revealed that the ACL experiences peak strain prior to initial ground contact when the knee is at or near full extension. Additionally, expert video analyses have determined that ACL injuries most likely occur within 50 milliseconds of ground contact. It is possible that limb stiffness and limb stiffness asymmetry can be used during the early impact phase of landings to reveal ACLR- and sex-specific landing mechanics differences when the ACL appears to be most vulnerable. Moreover, game-like, sport-specific landing tasks with a greater horizontal component that load the ACL and those that divert attention away from landing strategies may uncover differences that do not appear in standard, controlled laboratory tasks. The overall goal of this project was to use limb stiffness, limb stiffness asymmetry, and related measures to analyze the early landing phase mechanics of groups at greater risk for ACL injury during game-like, sport-specific landings. First, in an ACLR cohort, greater knee power and knee work asymmetries were found when compared to healthy recreational athletes, supporting previous literature that found that athletes with an ACLR land unevenly by offloading their surgical limb. However, limb stiffness asymmetry was not different between groups, implying that the groups may have modulated limb stiffness differently between limbs. Second, minimal sex-by-task interactions were determined for landings that varied by horizontal approach prior to initial ground contact. Significant differences were found for most measures across tasks overall, however, male and female athletes displayed similar landing mechanics, indicating that expected sex-specific differences may not exist during the immediate landing phase when ACL injuries are thought to occur. Last a landing task that mimicked a ball in mid-air and diverted attention away from landing mechanics produced a sex-by-task interaction for peak impact force but no other measure. When comparing each sex-task pairing, a trend for greater peak impact force by female athletes during the distracted landing (p=0.098) was found which may indicate that future tasks with additional external focuses or another game-like component will reveal anticipated sex-specific differences. Increased time between limbs for initial ground contact for female athletes also revealed that a time-synchronized assessment of between-limb coordination may be beneficial for future research. Doctor of Philosophy Non-contact injuries can occur when athletes use poor or inconsistent mechanics during typical sport-related movements like landing from a jump. Anterior cruciate ligament (ACL) injuries are especially tough, and certain populations like female athletes and athletes with a previous ACL reconstruction surgery (ACLR) are at greater risk of suffering an ACL injury, with different movement techniques being one proposed reason. Uneven landings where one limb has greater landing forces can decrease joint posture and place the overloaded limb at greater risk for ACL injury. Additionally, a stiff landing, defined by larger ground reaction force (GRF), extended joints at initial ground contact, and decreased joint flexion throughout the landing, is thought to increase ACL injury risk. While landing force distribution between limbs is a common way of evaluating landings to determine injury risk, it is unclear what role limb stiffness plays in the likelihood of experiencing an ACL injury. Limb stiffness is simply the deformation of the limb in response to the downward force applied on the lower limb during ground contact, which can be estimated using GRF. Limb stiffness has been commonly used to assess performance in running, hopping, and jumping, however, its relationship with injury risk during landings is pretty limited. Past research has revealed that the ACL experiences maximum stretch prior to initial ground contact when the knee is or is almost completely straight. Additionally, expert video investigations have determined that ACL injuries most likely occur within 50 milliseconds of ground contact. It is possible that limb stiffness and limb stiffness asymmetry can be used during the early impact phase of landings to reveal sex- and ACLR-specific landing mechanics differences when the ACL appears to be most in danger. Additionally, game-like, sport-specific landing tasks with a greater horizontal element that load the ACL and those that redirect attention away from landing strategies may show differences that do not appear in basic laboratory tasks. The overall goal of this project was to use limb stiffness, limb stiffness asymmetry, and related measures to examine the early landing phase techniques of groups at greater risk for ACL injury during game-like, sport-specific landings. First, in a group of athletes with a previous ACLR, greater knee storage differences between limbs were found when compared to healthy recreational athletes, supporting previous research studies that found that athletes with an ACLR land unevenly by offloading their surgical limb. However, limb stiffness asymmetry was not different between groups, implying that the groups may have regulated limb stiffness differently between limbs. Second, only a couple measures were significantly affected by the combined effect of sex and task during landings that were different due to their horizontal element. Significant differences were found for most measures across tasks overall, however, male and female athletes had similar landing techniques, showing that the expected differences between sexes may not happen very early in the landing phase when ACL injuries are thought to happen. Last, a landing task that imitated a ball in mid-air and redirected attention away from landing mechanics produced a larger sex-specific difference for peak impact force compared to a basic landing task. When comparing each sex-task pairing, a trend for greater peak impact force by female athletes during the distracted landing (p=0.098) was found which may show that future tasks with additional distractions or another game-like element will reveal expected differences between sexes. Increased time between limbs for initial ground contact for female athletes also revealed that looking at the coordination of both limbs on the same timescale may be useful for future research.

Evaluating side-to-side symmetry in the lower extremity has been significant in assessing injury risk and the success of rehabilitation programs. Considering limb dominance in the lower limbs is also important as limb dominance could influence symmetry measures. There is a need to assess symmetry, particularly in healthy populations, in tasks other than walking and running and establish how the dominant limb can impact symmetry. By evaluating symmetry in healthy adults, how the limbs function with respect to one another can be determined. Therefore, the first purpose of this study was to investigate the impact of lower limb dominance on walking and sitting-to-standing. Data was collected from 49 healthy older adults, aged 50-89 years old. Using loadsol® sensors (Novel, St. Paul, MN, USA), plantar loading data such as peak impact force and loading rate was calculated. Participants completed one sit-to-stand trial and three 10-meter walking trials, as these serve as prime examples of daily activities. The secondary purpose of this study was to assess the impact of lower limb dominance on athletic tasks like running and agility. The pedar-X® pressure insoles (Novel, St. Paul, MN, USA) were used to collect plantar loading data such as peak force, contact area, and contact time, from 10 athletes. Participants completed five t-drill trials and five agility ladder drill trials. The acceleration phase of the t-drill served as standard running. A mixed effects model was used to test if differences existed in various plantar loading outcome measures based on limb dominance. Non-parametric tests were used for non-normally distributed data. The statistical analysis determined that no significant differences existed between the dominant limb and non-dominant limb for the 10-meter walking trials peak impact force (p=0.245) or average loading rate (p=0.943). During the sit-to-stand trial, no significant differences existed in peak impact force (p=0.317) or average loading rate (p=0.943). For the agility ladder drill, the maximum force (p=0.427), contact area (p=0.517), or contact time (p=0.734) showed no significant differences. In the T-drill, the maximum force (p=0.385), contact area (p=0.571), or contact time (p=0.571) had no significant differences. These drive the conclusion that limb dominance does not need to be considered when assessing side-to-side symmetry. Master of Science Understanding how the left and right lower limbs of the body compare is important to preventing injuries and measuring if rehabilitation interventions are beneficial. A factor in that is knowing how the dominant limb can affect how the lower limbs compare to one another. Through symmetry, especially in healthy adults, a greater comprehension for over limb functionality can be better understood. There is need to assess the lower limb symmetry in healthy populations in tasks aside from walking and running as well as establish how the dominant limb is impacting that symmetry. The first purpose of this study was to observe how lower limb dominance affects walking and standing from a seated position. Data was collected from 49 healthy older adults, aged 50-89 years old. Insoles were placed in participants' shoes to collect plantar loading data. Each participant did two tasks: one trial of the sit-to-stand and three trials of 10-meter walking. The second purpose of this study was to observe how lower limb dominance affects athletic tasks such as running and agility. Loading insoles were used to collect data from 10 current or previous athletes. Each participant did five t-drill trials and five agility ladder trials. Statistical analyses established no significant differences were shown between the dominant and non-dominant limbs peak impact force for the 10-meter walking trials (p=0.245) nor for the average loading rate (p=0.943). For the sit-to-stand trial, no significant differences were seen in peak impact force (p=0.317) or average loading rate (p=0.943). In the agility ladder drill, no significant differences were shown for the maximum force (p=0.427), contact area (p=0.517), or contact time (p=0.734). In the agility ladder drill, no significant differences existed for the maximum force (p=0.385), contact area (p=0.571), or contact time (p=0.571). These findings suggested that the dominant limb does not impact lower limb comparisons.

Joint kinematics of upper extremity (UE) impairments in a pediatric population are often difficult to examine using marker-based motion capture. As a result of the cost and availability of tools such as marker-based motion capture in clinical settings, clinicians use functional tasks to examine improvement in movement quality. However, some of these tasks, such as the Box and Block test (BBT), which is examined in this study, rely on scoring to assess motor improvement. This scoring method can be misleading due to the possibility of movement compensation to improve scores. Therefore, finding kinematic correlations that can lead to improved BBT scores could improve the quality of functional assessments by providing discrete measures for clinicians. Understanding human motion using marker-based motion capture has been the accepted standard in biomechanics. However, it is not without its drawbacks, especially in upper extremity examination due to complex anatomical positioning. The introduction of markerless motion capture software could drastically alter how human biomechanics is analyzed in various settings. Additionally, avoiding possible errors due to clothing and skin movement could greatly improve reported results. Therefore, examining similarities in UE joint kinematics between accepted marker-based and markerless software could introduce markerless motion capture as a method for examining complex kinematics. This study aims to examine UE joint kinematics in a typically developing pediatric population while they complete the BBT, as well as validate Theia3D (Theia Markerless Inc., Kingston, ON, Canada). Marker-based motion capture was used to capture UE kinematics during the BBT. This study was performed on typically developing children aged 7, 9, and 11. Average and peak joint angles were determined, as well as hand segment velocity and path length. Significant correlations to BBT scores were found in peak shoulder flexion (FLEX) angle (r = -0.556, p-value = 0.009), peak (r = -0.479, p-value = 0.028), and average (ρ = -0.535, p-value = 0.012) wrist extension (EXT) angle, average mediolateral (ML) hand segment velocity (r = 0.494, p-value = 0.023), and path length (r = -0.522, p-value = 0.015). Additionally, significant differences between BBT scores (p-value = 0.005), peak shoulder FLEX (p-value = 0.024), and peak shoulder abduction (ABD) angle (p-value = 0.022) were found between the 7- and 11-year-old age groups. Peak elbow FLEX angle was significantly different (p-value = 0.049) between 9- and 11-year-old age groups. These results show that the BBT score could be related to the shoulder and wrist angle, as well as hand segment velocity and path length for typically developing children. Furthermore, root mean square deviation (RMSD) values less than 6° existed in all joint angles. Intraclass correlation coefficients (ICCs) greater than 0.75 were found in shoulder ABD (ICC = 0.79), forearm pronation (ICC = 0.81), wrist EXT (ICC = 0.75), and radial deviation (ICC = 0.87). Additionally, validation results between the marker-based and markerless systems show that there are differences in pose estimations and joint calculations based on rotation sequences. Overall, UE joint kinematics are shown to have correlations to BBT scores, so scores alone may not be indicative of movement quality in other patient populations. Markerless motion capture shows many benefits, however, it should be noted that, due to the complexity of upper extremity motion analysis, understanding what joint rotation sequences align the best with task-specific motions is important. Master of Science Human motion is commonly analyzed using marker-based motion capture, which consists of fitting participants with retroreflective markers that can be seen by specialized cameras. However, due to equipment costs, difficult implementation, and the occurrence of markers shifting on skin or being concealed by clothing, markerless motion capture is beginning to be introduced into biomechanics research and could be used in hospitals, clinical settings, and for outdoor examination due to its versatility. The software uses machine learning software that can determine skin landmarks in videos from several cameras to develop a 3D skeleton. Markerless motion capture could be beneficial in examining patients with neuromotor disorders or injuries due to being able to capture abnormal or quick movement which often accompanies many neurological disorders that affect motor function. Additionally, observing movement in children is a challenge due to markers being too close together on smaller limbs. Due to cost and obtainability, clinicians tend to use functional tests to examine improvements in motor function by a scoring system relevant to the specific test, such as the Box and Block test (BBT) which will be used in this study. However, there is the possibility of the patient's ability to adapt to the test to improve their score without improving general motor function. Therefore, it is important to find a relationship between upper limb movement and BBT scores. This study aims to find correlations between upper limb movement and Box and Block test scores as well as differences between 7-, 9-, and 11-year-old age groups and compare marker-based motion capture and the Theia3D (Theia Markerless Inc., Kingston, ON, Canada) markerless motion capture software. Joint assessment is completed with motion capture, which uses reflective markers on specific landmarks on the skin surface. Markerless motion capture is collected simultaneously with marker-based motion capture to assess similarities. The entire procedure was also completed 2 times within 1 visit. The results showed meaningful comparisons between the BBT scores and shoulder and wrist angle, and hand velocity. BBT scores and shoulder angles were shown to be different between the 7- and 11-year-old age groups. Elbow angles were shown to be different between the 9- and 11-year-old age groups. Additionally, comparisons between the marker-based and markerless results showed that all resulting joint angle data captured by each system were similar. Markerless measurement comparisons showed similarities between both sessions as well. These results show that there are ways to provide discrete measurements in clinical settings to examine movement quality. Comparisons between both motion analysis systems show the need to determine task-specific analyses to obtain meaningful results concerning the upper limbs, due to the inherent joint complexity and differing methods of completing the same task.

The default mode network (DMN) is a highly cited neural network whose functional roles are not well understood. Until recently, event related fMRI experiments used to study the DMN could only be conducted in an open-loop format. The purpose of this study was to demonstrate the potential statistical advantages of real-time fMRI studies to conduct closed-loop experiments to directly test putative DMN functions. Using both fMRI simulations and large archival datasets, we demonstrate that open-loop designs are less statistically powerful than closed-loop experiments that can trigger stimuli at controlled levels of brain activity. When simulating event scheduling on resting state data, DMN levels were normally distributed, but the event timing proved to be ineffective in capturing the highest and lowest DMN values on average across subjects. Statistical differences in DMN levels collected by the Human Connectome Project-Aging (HCP-A) during a Go/NoGo task were also reported, along with the network's distributional effects across subjects. When examining DMN levels in 136 subjects more prone to commission errors the mean DMN levels were reported to be higher during and prior to incorrect NoGo responses. Exploring DMN levels in these same individuals reacting to a Go task also revealed differing measurement patterns when compared to all 711 subjects in the study. Additionally, the distribution of total DMN levels across all participants, as well as during a Go or NoGo trial, showed a shift in the mean towards deactivation. Furthermore, the peak at this location was greater and revealed that increased sampling occurred at the mean and under sampling at the tails. Overall, the cumulative findings in this study were successful in providing statistical arguments to support propositions for more powerful closed-loop experimentation in fMRI. Master of Science Activity in a neural network is observed through the use of functional MRI (fMRI) by tracking higher levels of oxygenated blood to that region when active and lower quantities when inactive. Neural networks vary in their responsibilities, thus fMRI tasks are designed to trigger a response based on the functional role of the network. This can be exemplified by studying the blood flow to default mode network (DMN), a network responsible for mind wandering, during a task that requires focus. Researchers can then correlate moments of high activity, which indicates a greater degree of mind wandering, or low activity to a correct or incorrect response to the task. Unfortunately, the timing in which a task is presented to the participant is predetermined prior to the subject entering the MRI making it difficult to capture a correct or incorrect response at the precise moment of activation or deactivation. This concept is known as open-loop and often collects data at moments of neutral activity, neither high nor low. In contrast, a closed-loop design allows a researcher to monitor the DMN's activation levels in real time and present the task at a desired time. This provides more useful data to the experimenter as all recorded responses to the task correlate with exact moments of high and low activation. This makes claims about the neural network's role statistically more powerful as there is a greater quantity of data at these moments rather than during a neutral activation state. The purpose of this thesis is to provide statistical arguments that support propositions for more powerful closed-loop experimentation in fMRI.

Anterior cruciate ligament (ACL) injuries are common orthopaedic injuries among athletes who participate in sports that involve cutting and changing directions. Many of these adolescent athletes intend to return to sports (RTS), and therefore undergo ACL reconstruction (ACLR). These athletes exhibit unfavorable landing biomechanics from muscle atrophy and asymmetrical neuromuscular control post-ACLR, putting them at a higher risk of re-injury. Thus, rehabilitation following ACLR is important to improve kinetic and kinematic outcomes and reduce re-injury risk. Biofeedback during rehabilitation is thought to be one way to potentially restore neuromuscular control deficits of athletes recovering from ACLR. Therefore, understanding the effectiveness of a biofeedback intervention on factors associated with re-injury among post-ACLR patients is essential in successful RTS. The purpose of this study is to analyze the effect of a 6-week biofeedback intervention on eccentric knee joint power (ECCKP), limb stiffness, and limb stiffness symmetry (using normalized symmetry index, NSI), in addition to secondary lower extremity outcomes that are associated with these metrics, during landing among patients following ACLR. This study used data collected from an ACL-Biofeedback Trial (ClinicalTrials.gov: AR069865) where participants were randomized into a biofeedback (BF) or control group (C). The BF group received visual and tactile feedback during a series of controlled squats while the C group participated in several online and in-person educational sessions. Participants completed 10 stop-jump tasks before (pre), after (post), and 6 weeks after (ret) the intervention. Kinetic, kinematic, and ground reaction forces (GRF) were collected from embedded force plates and 3D motion capture. Partaking in a biofeedback intervention did not improve ECCKP, limb stiffness, or limb stiffness NSI compared to controls. A group-by-time interaction was found for hip excursion (p=0.035), and a main effect of time was found for ECCKP, with this variable increasing by 18.5% from pre to ret (p=0.001). In addition, when considering surgical versus non-surgical limbs, this cohort exhibited interlimb asymmetries in stiffness, peak resultant GRF (rGRF), and time to reach peak rGRF (p

Breast cancer (BC) is the second most common cause of cancer-related deaths for women in the United States, estimated to affect 1 in 8 women. Difficulties arise in BC treatment due to the hormone sensitivity and heterogeneity of the malignancies, and the poor prognosis after metastases. Due to the immense physical and psychological effects of conventional surgical methods, minimally invasive, non-thermal, focal electroporation-based ablation therapies are being investigated for the treatment of BC. Irreversible Electroporation (IRE) delivers a series of long, monopolar electrical pulses via electrodes inserted directly into the targeted tissue which disrupt cellular membranes by creating nano-scale pores, killing the cells via loss of homeostasis while promoting an immune response. However, IRE requires cardiac synchronization and a full-body paralytic to mitigate unwanted muscle contractions, which motivated the creation of second generation High-Frequency IRE or H-FIRE. H-FIRE delivers short, bipolar pulses to destroy cancer cells without muscle contractions and nerve excitation, and allows for more tunable treatment parameters. Throughout my thesis, I discuss investigations of H-FIRE for the treatment of triple-negative and hormone-sensitive BC cell lines and compare efficacy to IRE outcomes. To further establish the translation and understanding of H-FIRE for BC applications, my master's thesis focuses on: (1) determining the lethal electric field threshold of both cell lines in a 3D hydrogel matrix after H-FIRE and IRE; and (2) employ those values in a single bipolar probe numerical model to simulate in vivo treatments. The culmination of this thesis advances the use of H-FIRE in breast tissues, as well as demonstrates how in vitro data can be used to develop clinically relevant numerical models to better predict in vivo treatment outcome. Master of Science Breast cancer (BC) is one of the most deadly forms of cancer for women in the United States, affecting every 1 in 8 women. Difficulties arising in the treatment of BC include the hormone sensitivity of malignancies, metastatic tendencies, and the diversity of the tissue that characterizes the breast. Surgical options like mastectomy or lumpectomy are most often used when treating BC; however, these are incredibly taxing on the patient. This reason has sparked investigations of focused ablation modalities for the treatment of BC, specifically non-thermal mechanisms like electroporation-based therapies. Electroporation explains the phenomenon that cells subjected to a high enough electric field will result in increased membrane permeability, allowing for the entrance of therapeutic agents in reversible mechanisms, or cell death beyond an irreversible point. Irreversible Electroporation (IRE) has shown success for the treatment of prostate, liver, kidney, and pancreas. However, due to some drawbacks, second generation High-Frequency IRE (H-FIRE) is increasingly being investigated for certain cancer types and is the main focus of this thesis project. Within this thesis, I discuss investigations of H-FIRE with applications to treat malignant breast cell lines. Specifically, my thesis focuses on: (1) determining the point at which cancer cells damage is irreversible; and (2) incorporate those values into a numerical model used to simulate electroporation treatment if a tumor were embedded in a layer of fatty connective breast tissue. The culmination of this thesis enhances our understanding of H-FIRE in the breast, with the hopes of future transition of application into animal studies and ultimately the clinic.

Blast-induced traumatic brain injury (bTBI) remains a significant problem among military populations. When an explosion occurs, a high magnitude positive pressure rapidly propagates away from the detonation source. Upon contact, biological tissues throughout the body undergo deformation at high strain rates and then return to equilibrium following a brief negative pressure phase. This mechanical disruption of the tissue is known to cause oxidative stress and neuroinflammation in the brain, which can lead to neurodegeneration and consequently poor cognitive and behavioral outcomes. Further, these clinical outcomes, which can include chronic headaches, problems with balance, light and noise sensitivity, anxiety, and depression, may be sustained years following blast exposure and there are currently no effective treatments. Thus, there is a need to investigate the acute molecular responses following bTBI in order to motivate the development of effective therapeutic strategies and ultimately improve or prevent long-term patient outcomes. It is important to not only understand the acute molecular response, but how the brain tissue mechanics drive these metabolic changes. The objective of this work was to identify the interplay between the tissue-level biomechanics and the acute bTBI pathophysiology. In a rodent bTBI model, using adult rats, intracranial pressure was mapped throughout the brain during blast exposure where frequency contributions from skull flexure and wave dynamics were significantly altered between brain regions and were largely dependent on blast magnitude. These findings informed the subsequent spatial and temporal changes in neurometabolism. Amino acid molecular precursor concentrations decreased at four hours post-blast in the cortex and hippocampus regions. This motivates further investigation of amino acids as therapeutic targets aimed to reduce oxidative stress and prevent prolonged injury cascades. However, neurochemical changes were not consistent across blast magnitudes, which may be explained by the disparities in biomechanics at lower blast pressures. Lastly, we investigated the acute changes in metabolic regulators influencing excitotoxicity where it was found that astrocytes maintained normal clearance of excitatory and inhibitory neurotransmitters prior to astrocyte reactivity. Outcomes of this work provide improved understanding of blast mechanics and associated acute pathophysiology and inform future therapeutic and diagnostic approaches following bTBI. Doctor of Philosophy Blast-induced traumatic brain injury (bTBI) remains a significant problem among military populations. When an explosion occurs, a high magnitude positive pressure wave rapidly propagates away from the detonation source. Upon contact, biological tissues throughout the body undergo deformation that can cause injury. This mechanical disruption of the tissue is known to trigger negative biological processes that lead to persistent cognitive and behavioral deficits. Further, these clinical outcomes, which can include chronic headaches, problems with balance, light and noise sensitivity, anxiety, and depression, may be sustained years following blast exposure. There are currently no effective treatments that can help those afflicted, and biomarkers for injury diagnostics are limited. Thus, there is a great need to investigate the early biological responses following bTBI in order to motivate the development of effective therapeutic strategies and ultimately improve or prevent long-term patient outcomes. It is important to not only understand the immediate responses, but also how the brain tissue mechanics drive these metabolic changes. The objective of this work was to identify the interplay between the brain biomechanics and the acute bTBI pathophysiology. Using a translational animal model, pressure inside the brain was measured with pressure sensors during blast exposure. Subsequent spatial and temporal changes in neurochemical concentrations were quantified. The results showed (1) significant disparities in the pressure dynamics inside the brain and it varied across brain regions, (2) neurochemical precursors may have therapeutic potential post-injury, and (3) biomechanical and neurochemical responses were dependent on blast severity. Outcomes of this work provide improved understanding of blast mechanics and associated pathophysiology and inform future therapeutic and diagnostic approaches to prevent prolonged injury cascades.

Pain is a complex neuro-psychosocial experience that is internal and private making it difficult to assess in both humans and animals. In research approximately 95% of animal models use rodents, with rats being among the most common for pain studies [3]. However, traditional assessments of the pain response struggle to demonstrate that the behaviors are a direct measurement of pain. The rat grimace scale (RGS) was developed based on facial action coding systems (FACS) which have known utility in non-verbal humans [6, 9]. The RGS measures facial action units of orbital tightening, ear changes, nose flattening, and whisker changes in an attempt to quantify the pain behaviors of the rat. These action units are measured on frontal images of rats with their face in clear view on a scale of 0-2, then summed together. The total score is then averaged to find a final value for RGS between 0-2. Currently, the software program Rodent Face Finder® can extract frontal face images. However, the RGS scores are still manually recorded which is a labor-intensive process, requiring hours of training. Furthermore, the scoring can be subjective, with differences existing between researchers and lab groups. The primary aim of this study is to develop an automated system that can detect action unit regions and generate a RGS score for each image. To accomplish this objective, a YOLOv5 object detector and Vision Transformers (ViT) for classification were trained on a dataset of frontal-facing images extracted using Rodent Face Finder®. Subsequently, the model was then validated using a RGS test for blast traumatic brain injury (bTBI). The validation dataset consisted of 40 control images of uninjured rats, 40 images from the bTBI study on the day of injury, and 40 images 1-month post-injury. All 120 images in the validation set were then manually graded for RGS and tested using the automated RGS system. The results indicated that the automated RGS system accurately and efficiently graded the images with minimal variation in results compared to human graders in just 1/14th of the time. This system provides a fast and reliable method to extract meaningful information of rats' internal pain state. Furthermore, the study presents an avenue for future research into real-time pain monitoring. Master of Science Pain is a difficult experience to measure, both in humans and animals. It can be a subjective experience that is largely based on individual perception and interpretation. Furthermore, in animals, pain is even more challenging to assess because they cannot communicate their experience through language. Nonetheless, animal research plays an important role in understanding and treating the underlying mechanisms of pain. In animal research, rats are commonly used to study pain. However, traditional methods of assessing pain behaviors are not meant to observe the pain experience, but instead analyze a response to an external stimulus. The rat grimace scale (RGS) was developed as a direct measurement of the pain experience by analyzing the facial features. Currently, RGS scores are manually recorded by trained researchers which is time-consuming and can be subjective. This study aimed to develop an automated system to identify pain related facial expressions and generate a RGS score for frontal-images of rats. The system was trained using a dataset of frontal-facing rat images with varying levels of RGS scores and validated using images of rats from a traumatic brain injury study. The results showed that the automated RGS system accurately identified RGS pain level differences between recently injured rats, uninjured rats, and rats which were allowed to recover for 1-month. Furthermore, the system provided a fast and reliable method for measuring rat pain behavior when compared to manual grading. With this system, researchers will be able to efficiently perform RGS test. Additionally, this study presents an opportunity for future automation of other grimace scales as well as research into real-time pain monitoring.

Traffic cameras are those cameras operated with the purpose of observing traffic, often streaming video in real-time to traffic management centers. These camera video streams allow transportation authorities to respond to traffic events and maintain situational awareness. However, traffic cameras also have the potential to directly capture crashes and conflicts, providing enough information to perform reconstruction and gain insights regarding causation and remediation. Beyond crash events, traffic camera video also offers an opportunity to study normal driving. Normal driver behavior is important for traffic planners, vehicle designers, and in the form of numerical driver models is vital information for the development of automated vehicles. Traffic cameras installed by state departments of transportation have already been placed in locations relevant to their interests. A wide range of driver behavior can be studied from these locations by observing vehicles at all times and under all weather conditions. Current systems to analyze traffic camera video focus on detecting when traffic events occur, with very little information about the specifics of those events. Prior studies into traffic event detection or reconstruction used 1-7 cameras placed by the researchers and collected dozens of hours of video. Crashes and other interesting events are rare and cannot be sufficiently characterized by camera installations of that size. The objective of this dissertation was to explore the utility of traffic camera data for transportation research by modeling and characterizing crash and non-crash behavior in pedestrians and drivers using a captured dataset of traffic camera video from the Commonwealth of Virginia, named the VT-CAST (Virginia Traffic Cameras for Advanced Safety Technologies) 2020 dataset. A total of 6,779,726 hours of traffic camera video was captured from live internet streams from December 17, 2019 at 4:00PM to 11:59PM on December 31, 2020. Video was analyzed by a custom R-CNN convolutional neural network keypoint detector to identify the locations of vehicles on the ground. The OpenPifPaf model was used to identify the locations of pedestrians on the ground. The location, pan, tilt, zoom, and altitude of each traffic camera was reconstructed to develop a mapping between the locations of vehicles and pedestrians on-screen and their physical location on the surface of the Earth. These physical detections were tracked across time to determine the trajectories on the surface of the Earth for each visible vehicle and pedestrian in a random sample of the captured video. Traffic camera video offers a unique opportunity to study crashes in-depth which are not police reported. Crashes in the traffic camera video were identified, analyzed, and compared to nationally representative datasets. Potential crashes were identified during the study interval by inspecting Virginia 511 traffic alerts for events which occurred near traffic cameras and impacted the flow of traffic. The video from these cameras was manually reviewed to determine whether a crash was visible. Pedestrian crashes, which did not significantly impact traffic, were identified from police accident reports (PARs) as a separate analysis. A total of 292 crashes were identified from traffic alerts, and six pedestrian crashes were identified from PARs. Road departure and rear-end crashes occurred in similar proportions to national databases, but intersection crashes were underrepresented and severe and rollover cases were overrepresented. Among these crashes, 32% of single-vehicle crashes and 50% of multi-vehicle crashes did not appear in the Virginia crash database. This finding shows promise for traffic cameras as a future data source for crash reconstruction, indicating traffic cameras are a capable tool to study unreported crashes. The safe operation of autonomous vehicles requires perception systems which make accurate short-term predictions of driver and pedestrian behavior. While road user behavior can be observed by the autonomous vehicles themselves, traffic camera video offers another potential information source for algorithm development. As a fixed roadside data source, these cameras capture a very large number of traffic interactions at a single location. This allows for detailed analyses of important roadway configurations across a wide range of drivers. To evaluate the efficacy of this approach, a total of 58 intersections in the VT-CAST 2020 dataset were sampled for driver trajectories at intersection entry, yielding 58,180 intersection entry trajectories. K-means clustering was used to group these trajectories into a family of 45 trajectory clusters. Likely as a function of signal phase, distinct groups of accelerating, constant speed, and decelerating trajectories were present. Accelerating and decelerating trajectories each occurred more frequently than constant speed trajectories. The results indicate that roadside data may be useful for understanding broad trends in typical intersection approaches for application to automated vehicle systems or other investigations; however, data utility would be enhanced with detailed signal phase information. A similar analysis was conducted of the interactions between drivers and pedestrians. A total of 35 crosswalks were identified in the VT-CAST 2020 dataset with sufficient trajectory information, yielding 1,488 trajectories of drivers interacting with pedestrians. K-means clustering was used to group these trajectories into a family of 16 trajectory clusters. Distinct groups of accelerating, constant speed, and decelerating trajectories were present, including trajectory clusters which described vehicles slowing down around pedestrians. Constant speed trajectories occurred the most often, followed by accelerating trajectories and decelerating trajectories. As with the prior investigation, this finding suggests that roadside data may be used in the development of driver-pedestrian interaction models for automated vehicles and other use cases involving a combination of pedestrians and vehicles. Overall, this dissertation demonstrates the utility of standard traffic camera data for use in traffic safety research. As evidence, there are already three current studies (beyond this dissertation) using the video data and trajectories from the VT-CAST 2020 dataset. Potential future studies include analyzing the mobile phone use of pedestrians, analyzing mid-block pedestrian crossings, automatically performing roadway safety assessments, considering the behavior of drivers following congested driving, evaluating the effectiveness of work zone hazard countermeasures, and understanding roadway encroachments. Doctor of Philosophy Traffic cameras are those cameras operated with the purpose of observing traffic, often streaming video in real-time to traffic management centers. These video streams allow transportation authorities to maintain situational awareness and respond to traffic events. However, traffic cameras also have the potential to directly capture crashes, providing enough information to perform reconstruction and gain insights regarding causation and remediation. Beyond crash events, traffic camera video also offers an opportunity to study normal driving, which is vital information for the operation of automated vehicles. Traffic cameras installed by state departments of transportation have already been placed in thousands of locations around the country capturing traffic scenes relevant to their interests. A wide range of driver and pedestrian behavior can be studied from these locations by observing vehicles at all times and under all weather conditions. Current systems to analyze traffic camera video focus on detecting when traffic events occur, with very little information about the specifics of those events. Previous studies into traffic event detection or reconstruction used 1-7 cameras placed by the researchers and collected dozens of hours of video. Crashes and other interesting events are rare and cannot be sufficiently characterized by camera installations of that size. The objective of this dissertation was to explore the utility of traffic camera data for transportation research by modeling and characterizing crash and non-crash behavior in pedestrians and drivers using a dataset of statewide traffic camera video captured from the Commonwealth of Virginia. A total of 6,779,726 hours of traffic camera video from live internet streams was captured from December 17, 2019 at 4:00PM to 11:59PM on December 31, 2020. This captured video was processed by a trajectory analysis system which determined the path on the ground for each visible vehicle and pedestrian in a random sample of the captured video. Additionally, 298 crashes visible in the traffic camera video were analyzed, comparing them to nationally representative crash datasets. With anticipated uses in traffic modeling and automated vehicle development, two additional potential use cases of the dataset were explored: cases where a driver enters an intersection, and cases where a driver interacts with a pedestrian.

Mild traumatic brain injury (mTBI) accounts for approximately 73-83% of all traumatic brain injuries (TBI) and continues to be a serious clinical challenge [1]. The role of injury mechanism in TBI has been widely debated, and it is believed that although there are differences between diffuse and focal TBI, the resulting injury is not influenced by the way in which it was acquired [1], [2]. It is known that TBIs can cause cognitive impairments that are often due to injury experienced in the hippocampus [2]. In response to insult, quiescent neural stem cell (NSC) populations within the dentate gyrus region of the hippocampus become activated. Stem cell differentiation following injury is hypothesized to be unique for diffuse and impact TBIs, primarily due to the differences in mechanotransduction pathways triggered by each respective injury. By quantifying the lineage of stem cells through immunohistochemistry, this study examined the dentate gyrus following mTBI in a rodent model, and the contribution that injury mechanism plays in mTBI outcomes. Additionally, the behavioral effects of mTBI were assessed through open field testing at 72 hours and four weeks following injury. Overall, these findings indicated that after four weeks following mTBI, there are not significant differences between impact and blast both from an immunohistochemical and behavioral standpoint. Despite there being few differences between injury groups, these findings help clarify the role of injury mechanism not only in the context of neurogenesis, but they also inform future studies addressing preventative and treatment strategies for mTBI. Master of Science Mild traumatic brain injury (mTBI) accounts for approximately 73-83% of all traumatic brain injuries (TBI) [1]. There are two main ways in which a mTBI can occur: through diffuse or focal injury. A diffuse injury is due to the brain experiencing a force that does not physically come into contact with the head, such as a shockwave from an explosion. These types of injuries typically affect the entire head. Impact injuries on the other hand, are caused by the head encountering an object at a force that causes injury to the brain. These injuries tend to be focal, as the entire head rarely comes into contact with an object. Both diffuse and focal injuries can cause mTBI, and there is a current debate questioning if the mode of injury has an impact on the damage experienced by the brain [1], [2]. However, it is also known that mTBI can cause cognitive impairments such as changes in behavior, memory, and even mental health, which can occur in the hippocampus of the brain [2]. Within the hippocampus, there is a small subset of cells referred to as neural stem cells (NSC) that become active following injury. The activation of these cells is believed to be in response to injury in the brain. Furthermore, NSCs have the ability to differentiate into various cell types within the brain, including astrocytes, oligodendrocytes, and neurons. Each of these cell types perform an integral role in the function of the brain. It is hypothesized that the response of NSCs in the hippocampus is unique depending on if an injury was acquired through diffuse or impact mechanisms. To investigate this, the lineage of NSCs was quantified within the hippocampus following blast and impact mTBI in a rodent model. Additionally, the behavioral effects of diffuse and impact injury were investigated at 72 hours and four weeks following injury. Despite there being no significant differences in outcomes between injury groups, these findings help clarify the role of injury mechanism not only in the context of NSC response, but they also inform future studies addressing preventative and treatment strategies for mTBI.

Since 2015, there have been more than 35,000 fatalities annually due to crashes on United States roads [1], [2]. Typically, road departure crashes account for less than 10% of all annual crash occupants yet comprise nearly one third of all crash fatalities in the US [3]. In the year 2020, road departure crashes accounted for 50% of crash fatalities [2]. Road departure crashes are characterized by a vehicle leaving the intended lane of travel, departing the roadway, and striking a roadside object, such as a tree or pole, or roadside condition, such as a slope or body of water. One strategy currently implemented to mitigate these types of crashes is the use of roadside barriers. Roadside barriers, such as metal guardrails, concrete barriers, and cable barriers, are designed to reduce the severity of road departure crashes by acting as a shield between the departed vehicle and more hazardous roadside obstacles. Much like new vehicles undergo regulatory crash tests, barriers must adhere to a set of crash test procedures to ensure the barriers perform as intended. Currently, the procedures for full-scale roadside barrier crash tests used to evaluate the crash performance of roadside safety hardware are outlined in The Manual for Assessing Safety Hardware (MASH) [4]. During roadside barrier tests, the assessment of occupant injury risk is crucial, as the purpose of the hardware is to prevent the vehicle from colliding with a more detrimental roadside object, all the while minimizing, and not posing additional, risk to the occupants. Unlike the new vehicle regulatory crash tests conducted by the National Highway Traffic Safety Administration (NHTSA), MASH does not require the use of instrumented anthropomorphic test devices (ATD). Instead, one of the prescribed occupant risk assessment methods in MASH is the flail space model (FSM), which was introduced in 1981 and models an occupant as an unrestrained point mass. The FSM is comprised of two crash severity metrics that can be calculated using acceleration data from the test vehicle. Each metric is prescribed a maximum threshold in MASH and if either threshold is exceeded during a crash test the test fails due to high occupant injury risk. Since the inception of the FSM metrics and their thresholds, the injury prediction capabilities of these metrics have only been re-investigated in the frontal crash mode, despite MASH prescribing an oblique 25-degree impact angle for passenger vehicle barrier tests. The focus of this dissertation was to use EDR data from real-world crashes to assess the current relevance of roadside barrier crash test occupant risk assessment methods to the modern vehicle fleet and occupant population. Injury risk prediction models were constructed for the two FSM-based metrics and five additional crash severity metrics for three crash modes: frontal, side, and oblique. For each crash mode and metric combination, four injury prediction models were constructed: one to predict probability of injury to any region of the body and three to predict probability of injury to the head/face, neck, and thorax regions. While the direct application of these models is to inform future revisions of MASH crash test procedures, the developed models have valuable applications for other areas of transportation safety besides just roadside safety. The final two chapters of this dissertation explore these additional applications: 1) assessing the injury mitigation effectiveness of an advanced automatic emergency braking system, and 2) informing speed limit selection that supports the safe system approach. The findings in this dissertation indicate that both the FSM and additional crash severity metrics do a reasonable job predicting occupant injury risk in oblique crashes. One of the additional metrics performs better than the two FSM metrics. Additionally, several occupant factors, such as belt status and age, play significant roles in occupant risk prediction. These findings have important implications for future revisions of MASH, which could benefit from considering additional metrics and occupant factors in the occupant risk assessment procedures. Doctor of Philosophy Every year, there are more than 35,000 fatalities due to crashes on United States roads. While there are many different types of crashes, there is a small collection of crash types that are responsible for the majority of these fatalities. One of the worst crash types is a road departure crash. Road departure crashes describe when a vehicle leaves the roadway and collides with an object off the roadway (such as a tree, pole, or ditch). Road departure crashes typically comprise 10% of crashes but are responsible for more than 30% of the annual crash fatalities. In 2020, road departure crashes were responsible for 50% of the 39,000 fatalities. One strategy that is currently used to reduce road departure fatalities is the use of roadside barriers. Common roadside barrier types include metal guardrails, concrete barriers, and cable guardrails, and are used to prevent vehicles that are departing the roadway from hitting an object that would be more dangerous than the barrier. To ensure barriers successfully protect the vehicle and vehicle occupants from heightened danger, they are crash tested in scenarios that are designed to mimic real-world crashes. The Manual for Assessing Safety Hardware (MASH) is the document that currently outlines the details necessary to conduct one of these crash tests. During roadside barrier tests, it is crucial to determine whether occupants are at risk of injury or fatality. For a variety of reasons, barrier tests do not use the traditional crash test dummies, which are designed to replicate human presence in a crash vehicle. Instead, MASH recommends using vehicle velocity data to assess how much risk is posed to an occupant. Using this velocity data, two values can be computed and if either value exceeds the maximum values provided in MASH, the crash test fails due to high occupant risk. The suggestion to use velocity data to assess occupant risk was first introduced in 1981. Since then, there have been significant advances in vehicle design, barrier design, and occupants' willingness to partake in safe habits, such as wearing seatbelts. Therefore, it is necessary to determine if the occupant risk values used in MASH are still applicable today. The focus of this dissertation was to use real-world crash data to assess the current relevance of roadside barrier crash test occupant risk values. The results presented in this dissertation can be used to select new occupant risk values in future versions of MASH. The findings within this dissertation show that the current methods in MASH do a good job estimating an occupant's risk of injury. Additionally, the findings show that certain occupant factors, such as the age of an occupant and whether the occupant is belted, help to more accurately estimate occupant injury risk. This finding has important implications for MASH, which does not currently consider different occupant conditions.

Histotripsy is a non-thermal, non-invasive focused ultrasound therapy using controlled acoustic cavitation to mechanically disintegrate tissue into an acellular homogenate. Histotripsy applies microsecond-length, high pressure (> 10 MPa) pulses to initiate the rapid expansion and collapse of nuclei in a millimeter-scale focal region, applying large stresses and strains to targeted tissues. The cavitation "bubble cloud" generated during histotripsy treatment can be visualized in real time on ultrasound imaging, assisting with treatment guidance and monitoring. Past studies have demonstrated histotripsy's potential for a variety of applications, but histotripsy has not yet been investigated for superficial musculoskeletal tumor ablation. Additionally, preliminary investigations using histotripsy to ablate brain tumors are underway, but require advanced histotripsy devices capable of overcoming attenuation of the therapeutic ultrasound signal by the skull and rely on MRI for real-time guidance. As a result, open questions remain regarding ultrasound-guided histotripsy for brain tumors. Early evidence also suggests that histotripsy ablation may induce immunogenic changes in the tumor microenvironment. Continued research is needed to explain and corroborate these findings under conditions more immunologically representative of human cancers, such as in large animal models with spontaneous tumors. This dissertation investigates the safety and feasibility of using ultrasound-guided histotripsy to ablate superficial soft tissue sarcomas (STS), osteosarcomas (OS), and brain tumors and considers the immunological impacts of histotripsy treatment for STS and OS. The research described herein (1) investigates the ability of histotripsy to treat superficial STS tumors in companion animals with spontaneous tumors, (2) investigates the feasibility of treating bone tumors with histotripsy through a series of ex vivo and in vivo studies, and (3) applies histotripsy for the minimally invasive treatment of superficial brain tumors. The completion of this dissertation will provide significant insight into the ability of ultrasound-guided histotripsy to treat novel tumor types (i.e., STS, OS, and brain tumors) and the potential role of histotripsy in veterinary medicine. Future work will build upon the studies detailed in this dissertation to optimize ultrasound-guided histotripsy for the treatment of complete STS, OS, and brain tumors in veterinary and human patients. Doctor of Philosophy Histotripsy is a non-invasive focused ultrasound therapy that mechanically breaks down targeted tissues through acoustic cavitation. Histotripsy is currently being developed for a number of clinical applications, including tumor ablation, but its potential for treating many cancer types remains unknown. Histotripsy uses very short, high pressure ultrasound pulses to initiate the nucleation of bubbles in the target region. These bubbles then expand and rapidly collapse to impart large stresses and strains on surrounding tissues, leaving behind only acellular debris. The cavitation "bubble cloud" generated during histotripsy treatment can be visualized on ultrasound imaging, offering real-time treatment guidance and monitoring. Histotripsy has not yet been investigated for superficial musculoskeletal tumor ablation, and preliminary studies using histotripsy to ablate brain tumors are underway, but require advanced histotripsy devices still under development. As a result, open questions remain regarding histotripsy ablation as a treatment for musculoskeletal and brain tumors. Additionally, early evidence suggests that histotripsy ablation may be able to stimulate an immune response, treating not only the targeted tumor but also multifocal or metastatic disease. Continued research is needed to explain and corroborate these findings under conditions more similar to human cancers, such as in large animal models with naturally-occurring tumors. This dissertation investigates the safety and feasibility of using ultrasound-guided histotripsy to ablate superficial soft tissue sarcomas (STS), osteosarcomas (OS), and brain tumors and considers the immunological impacts of histotripsy treatment for STS and OS. This research (1) investigates the ability of histotripsy to treat superficial STS tumors in companion animals with spontaneous tumors, (2) investigates the feasibility of treating bone tumors with histotripsy through a series of ex vivo and in vivo studies, and (3) applies histotripsy for the minimally invasive treatment of superficial brain tumors. The completion of this dissertation will provide significant insight into the ability of ultrasound-guided histotripsy to treat novel tumor types (i.e., STS, OS, and brain tumors) and the potential role of histotripsy in veterinary medicine. Future work will build upon the studies detailed in this dissertation to optimize ultrasound-guided histotripsy for the treatment of complete STS, OS, and brain tumors in veterinary and human patients.

Glioblastoma multiforme (GBM) is the most aggressive type of primary brain tumor. Even after patients undergo maximum and safe surgical resection followed by adjuvant chemotherapy and radiation therapy, residual GBM cells form secondary tumors which lead to poor survival times and prognoses for patients. This tumor recurrence can be attributed to the inherent GBM heterogeneity that makes it difficult to eradicate the therapy-resistant and tumorigenic subpopulation of GBM cells with stem cell-like properties, referred to as glioma stem cells (GSCs). Additionally, the migratory nature of GBM/GSCs enable them to invade into the healthy brain parenchyma beyond the resection cavity to generate new tumors. In an effort to address these challenges of GBM recurrence, this research aimed to develop a biomaterials-based approach to attract, capture, and eradicate GBM cells and GSCs with chemical and physical stimuli. Specifically, it is proposed that after surgical removal of the primary GBM tumor mass, an injectable hydrogel can be dispensed into the resection cavity for crosslinking in situ. A combination of chemical and physical cues can then induce the migration of the residual GBM/GSCs into the injectable hydrogel to localize and concentrate the malignant cells prior to non-invasively abating them. In order to develop this proposed treatment, this dissertation focused on 1) characterizing and optimizing the thiol-Michael addition injectable hydrogel, 2) attracting and entrapping GBM/GSCs into the hydrogel with CXCL12-mediated chemotaxis, and 3) assessing the feasibility of utilizing histotripsy to mechanically and non-invasively ablate cells entrapped in the hydrogel. The results revealed that hydrogel formulations comprising 0.175 M NaHCO3(aq) and 50 wt% water content were the most optimal for physical, chemical, and biological compatibility with the GBM microenvironment on the basis of their swelling characteristics, sufficiently crosslinked polymer networks, degradation rates, viscoelastic properties, and interactions with normal human astrocytes. Loading the hydrogel with 5 µg/mL of CXCL12 was optimal for the slow, sustained release of the chemokine payload. A dual layer hydrogel platform demonstrated in vitro that the resulting chemotactic gradient induced the invasion of GBM cells and GSCs from the extracellular matrix and into the synthetic hydrogel with ameboid migration and myosin IIA activation. This injectable hydrogel also demonstrated direct therapeutic benefits by passively eradicating entrapped GBM cells through matrix diffusion limitations as well as decreasing the GBM malignancy and GSC stemness upon cancer cell-hydrogel interactions. Research findings revealed the hydrogels can be synthesized under clinically relevant conditions mimicking GBM resection in vitro, and hydrogels were distinguishable with ultrasound imaging. Furthermore, the synthetic hydrogel was acoustically active to generate a stable cavitation bubble cloud with histotripsy treatment for ablation of entrapped red blood cells with well-defined, uniform lesion areas. Overall, the results from this research demonstrate this injectable hydrogel is a promising platform to attract and entrap malignant GBM/GSCs for subsequent eradication with chemical and physical stimuli. Further development of this platform, such as by integrating electric cues for electrotaxis-directed cell migration, may help to improve the cancer cell trapping capabilities and thereby mitigate GBM tumor recurrences in patients. Doctor of Philosophy Glioblastoma multiforme (GBM) is the deadliest type of primary brain cancer. Upon GBM diagnosis, patients first undergo surgery to remove the tumor from the brain. After waiting several weeks for the wound healing process due to surgery, patients are administered chemotherapy with drugs and radiation therapy to eradicate any remaining GBM cells. Even after undergoing these combinatorial treatments, the cancer returns and leads to median survival times of only 15 months in 90% of patients. Complete GBM eradication is difficult, since the cancer cells can migrate into healthy brain tissue beyond the original tumor site. Additionally, GBM is highly heterogenous and composed of different cell types that can resist chemotherapy and radiation therapy, which lead to secondary tumors and cancer relapse. To address these challenges, this dissertation aimed to develop a polymer-based material (specifically a hydrogel) that can attract, entrap, and localize the GBM cells into the material to subsequently eradicate them with chemical and physical signals. This hydrogel platform would have important clinical implications, as it can potentially be dispensed into the empty cavity after surgical removal of the tumor in the brain. The hydrogel can then be harnessed to attract residual GBM cells for directed migration into the hydrogel to concentrate and localize the cancer cells for their subsequent destruction with a non-invasive technology. In order to develop this proposed treatment, this dissertation investigated the following three aims: 1) to study and optimize the injectable hydrogel for chemical, physical, and biological compatibility with the GBM therapy; 2) to utilize chemical signals to attract and entrap the GBM cells into the hydrogel; and 3) to apply focused ultrasound with high amplitude, short duration negative pressure pulses to mechanically fractionate and destroy the cells entrapped in the hydrogel. The results revealed that the hydrogel comprising 0.175 M NaHCO3(aq) and 50 wt% water content was the most optimal formulation. CXCL12 chemokine proteins loaded into the hydrogel at 5 µg/mL released slowly from the hydrogel to generate a chemical gradient and thereby attract GBM cells to promote their invasion into the hydrogel matrix. The hydrogel was demonstrated to respond well to focused ultrasound treatment, which was capable of mechanically fractionating and destroying red blood cells in the hydrogel uniformly. Overall, the results from this research provide support that this hydrogel platform can attract, entrap, and eradicate GBM cells with chemical and physical stimuli. Hence, further improvement of this platform and implementation of this novel GBM treatment may in the future help minimize GBM cancer relapse in patients who undergo conventional therapies, thereby extending their survival times.

Irreversible electroporation (IRE) is a non-thermal tissue ablation modality in which electrical pulses are used to generate targeted disruption of cellular membranes. Clinically, IRE is administered by inserting one or more needles within or around a region of interest, then applying a series of short, high amplitude pulsed electric fields (PEFs). The treatment effect is dictated by the local field magnitude, which is quite high near the electrodes but dissipates exponentially. When cells are exposed to fields of sufficient strength, nanoscale "pores" form in the membrane, allowing ions and macromolecules to rapidly travel into and out of the cell. If enough pores are generated for a substantial amount of time, cell homeostasis is disrupted beyond recovery and cells eventually die. Due to this unique non-thermal mechanism, IRE generates targeted cell death without injury to extracellular proteins, preserving tissue integrity. Thus, IRE can be used to treat tumors precariously positioned near major vessels, ducts, and nerves. Since its introduction in the late 2000s, IRE has been used successfully to treat thousands of patients with focal, unresectable malignancies of the pancreas, prostate, liver, and kidney. It has also been used to decellularize tissue and is gaining attention as a cardiac ablation technique. Though IRE opened the door to treating previously inoperable tumors, it is not without limitation. One drawback of IRE is that pulse delivery results in intense muscle contractions, which can be painful for patients and causes electrodes to move during treatment. To prevent contractions in the clinic, patients must undergo general anesthesia and temporary pharmacological paralysis. To alleviate these concerns, high-frequency irreversible electroporation (H-FIRE) was introduced. H-FIRE improves upon IRE by substituting the long (~100 µs) monopolar pulses with bursts of short (~1 µs) bipolar pulses. These pulse waveforms substantially reduce the extent of muscle excitation and electrochemical effects. Within a burst, each pulse is separated from its neighboring pulses by a short delay, generally between 1 and 5 µs. Since its introduction, H-FIRE burst waveforms have generally been constructed simply by choosing the duration of constitutive pulses within the burst, with little attention given to this delay. This is quite reasonable, as it has been well documented that pulse duration plays a critical role in determining ablation size. In this dissertation, we explore the role of these latent periods within burst waveforms as well as their interaction with other pulse parameters. Our central hypothesis is that tuning the latent periods will allow for improved ablation size with reduced muscle contractions over traditional waveforms. After gaining a simple understanding of how pulse width and delay interact in vitro, we demonstrate theoretically that careful tuning of the delay within (interphase) and between (interpulse) bipolar pulses in a burst can substantially reduce nerve excitation. We then analyze how pulse duration, polarity, and delays affect the lethality of burst waveforms toward determining the most optimal parameters from a clinical perspective. Knowing that even the most ideal waveform will require slightly increased voltages over what is currently used clinically, we compare the clinical efficacy of two engineered thermal mitigation strategies to determine what probe design modifications will be needed to successfully translate H-FIRE to the clinic while maintaining large, non-thermal ablation volumes. Finally, we translate these findings in two studies. First, we demonstrate that burst waveforms with an improved delay structure allow for enhanced safety and larger ablation volumes in vivo. And finally, we examine the efficacy of H-FIRE in spontaneous canine liver tumors while also comparing the ablative effect of H-FIRE in tumor and non-neoplastic tissue in a veterinary clinical setting. Doctor of Philosophy Cancer is soon to become the most common cause of death in the United States. In 2023, approximately 2 million new cases of cancer will be diagnosed, leading to roughly 650 thousand lost lives. Interestingly, about half of newly diagnosed cancers are caught in the early stages before the disease has spread throughout the body. With effective local intervention, these patients could potentially be cured of their malignancy. Surgical removal of the tumor is the gold standard, but it is often not possible due to tumor location, patient comorbidities, or organ health status. In some instances, focal thermal ablation with radiofrequency or microwave energy can be performed when resection is not possible. These treatments entail the delivery of thermal energy through a needle electrode, which causes local tissue damage through coagulation (cooking) of the tissue. However, thermal ablation destroys tissue indiscriminately, meaning that any nearby blood vessels or neural components will also be damaged, which precludes thousands of patients from treatment each year. Irreversible electroporation (IRE) was introduced to overcome these challenges and provide a treatment option for patients diagnosed with otherwise untreatable tumors. IRE uses pulsed electric fields to generate nanoscale pores in cell membranes, which lead to a homeostatic imbalance and cell death. Because IRE is a membrane-based effect, it does not rely on thermal effects to generate cellular injury, which allows it to be administered to tumors that are adjacent to critical tissue structures such as major nerves and vasculature. Though IRE opened the door to treating otherwise inoperable tumors, procedures are technically challenging and require specialized anesthesia protocols. High-frequency irreversible electroporation (H-FIRE) was introduced by our group roughly a decade ago to simplify the procedure through the use of an alternate pulsing strategy. These higher frequency pulses offer several advantages such as limiting muscle contractions and reducing the risk of cardiac interference, both of which were concerns with IRE. However, H-FIRE ablations have been limited in size, and there is limited knowledge regarding the optimal pulsing strategy needed in order to maximize the ratio of therapeutic benefits to undesirable side effects like muscle stimulation and Joule heating. In this dissertation, we sought to understand how different pulse parameters affect these outcomes. Using a combination of computational, benchtop, and in vivo experiments, we comprehensively characterized the behavior of user-tunable pulse parameters and identified optimal methods for constructing H-FIRE protocols. We then translated our findings in a proof-of-principle study to demonstrate the ability of newly introduced waveform designs to increase ablation size with H-FIRE. Overall, this dissertation improves our understanding of how H-FIRE waveform selection affects clinical outcomes, introduces a new strategy for maximizing therapeutic outcomes with minimal side effects, and provides a framework for selecting parameters for specific applications.

International audience; Single-molecule localization microscopy (SMLM) has matured into one of the most widely used super-resolution imaging methods and has been used to address a broad spectrum of biological research questions1. This success has inspired the community to develop numerous computational techniques to extract localizations from raw images or turn them into biologically meaningful quantities [...]

Contains fulltext : 173122.pdf (Publisher’s version ) (Closed access) In conjunction with the ISBI 2015 conference, we organized a longitudinal lesion segmentation challenge providing training and test data to registered participants. The training data consisted of five subjects with a mean of 4.4 time-points, and test data of fourteen subjects with a mean of 4.4 time-points. All 82 data sets had the white matter lesions associated with multiple sclerosis delineated by two human expert raters. Eleven teams submitted results using state-of-the-art lesion segmentation algorithms to the challenge, with ten teams presenting their results at the conference. We present a quantitative evaluation comparing the consistency of the two raters as well as exploring the performance of the eleven submitted results in addition to three other lesion segmentation algorithms. The challenge presented three unique opportunities: (1) the sharing of a rich data set; (2) collaboration and comparison of the various avenues of research being pursued in the community; and (3) a review and refinement of the evaluation metrics currently in use. We report on the performance of the challenge participants, as well as the construction and evaluation of a consensus delineation. The image data and manual delineations will continue to be available for download, through an evaluation website2 as a resource for future researchers in the area. This data resource provides a platform to compare existing methods in a fair and consistent manner to each other and multiple manual raters.

Örgüt kültürü ve ilgili araştırmalar, 21. Yüzyıl’da tüm dünyada neo-klasik yaklaşımların etkisinde çağdaş yönetim teorileri ile birlikte oldukça büyük bir ilgi görmüş ve birçok işletme bu anlamda kurum etkinliğinin zarar görmemesini hedeflemiştir. Özellikle hastanelerde, sağlık çalışanlarının kurum tarafından benimsenmiş normlara uyumu ve bu doğrultuda performanslarının hangi yönde etkileneceği hem kurumsal hem de bireysel başarı için son derece önemlidir. Bu amaçla hastane çalışanlarının performanslarına örgüt kültürünün bir etkisinin olup olmadığı incelenmiştir. Bu çalışma, hastanelerde örgüt kültürünün çalışanların performansları üzerine etkilerini ortaya koymayı amaçlayan tanımlayıcı türde bir literatür taramasıdır ve bu çalışmada ulusal ve uluslararası çalışmalardan faydalanılmıştır. Çalışmanın sonucunda sağlık çalışanları mesleklerinin gerekleri ile ilgili unsurlardan performans anlamında etkilenirken çalışanların örgüt kültüründen de ulusal ve uluslararası boyutta negatif ve pozitif yönde etkilendikleri kanısına varılmaktadır. Organizational culture and related reseraches have attracted considerable interest in the 21st century with contemporary management theories under the influence of neo-classical approaches all over the World, and many enterprises habe aimed not to harm the institutional effect in this sense .Especially in hospitals, compliance of healhcare professionals with the norms adopted by the institution and how their performance will be affected accordingly are extremely important for both institutional and individual success. Fort his purpose, it has been examined whether organizational culture and stress has an effect on the performance of hospital employees. This study has a descriptive literatüre review with nitaonal and international studies aiming to reveal the effects of organizational culture and stress on the performance of employees in hospitals. As a result of the study, it is cocluded that while health workers are affected by the elements related to the requirements of their profession in terms of performance, they are also negatively and positively affected by the organizational culture at the national and international level. Publisher's Version

The uterosacral ligaments (USLs) are important anatomical structures that support the uterus and apical vagina within the pelvis. As these structures are over-stretched, become weak, and exhibit laxity, pelvic floor disorders such as pelvic organ prolapse occur. Although several surgical procedures to treat pelvic floor disorders are directed toward the USLs, there is still a lot that is unknown about their function. These surgeries often result in poor outcomes, demonstrating the need for new surgical approaches and biomaterials. The first chapter of this dissertation presents a review of the current knowledge on the mechanical properties of the USLs. The anatomy, microstructure, and clinical significance of the USLs are first reviewed. Then, the results of published experimental studies on the {emph{in vivo}} and {emph{ex vivo}}, uniaxial and biaxial tensile tests are compiled. Based on the existing findings, research gaps are identified and future research directions are discussed. The second chapter proposes the use of planar biaxial testing, digital image correlation (DIC), and optical coherence tomography (OCT) to quantify the deformations of the USLs, both in-plane and out-of-plane. Using virgin swine as an animal model, the USLs were found to deform significantly less in their main direction (MD) of {emph{in vivo}} loading than in the direction perpendicular to it (PD) at increasing equibiaxial stresses. Under constant equibiaxial loading, the USLs deformed over time equally, at comparable rates in both the MD and PD. The thickness of the USLs decreased as the equibiaxial loading increased but, under constant equibiaxial loading, the thickness increased in some specimens and decreased in others. The third chapter presents new experimental methods for testing the {emph{ex vivo}} tensile properties of the uterosacral ligaments (USLs) in rats. USL specimens were carefully dissected to preserve their anatomical attachments, and they were loaded along their main {emph{in vivo}} loading direction (MD) using a custom-built uniaxial tensile testing device. This chapter reports the first mechanical data on the rat USLs in isolation from surrounding organs. It is also the first experimental study to provide measurements of the inhomogeneous deformations of the USLs during loading along their main textit{in vivo} loading direction, revealing that the USLs may behave as auxetic structures. The fourth and final chapter presents preliminary findings on novel imaging applications to characterize the evolving structure of the USLs before, during, and after tensile pulling along the ligaments' main textit{in vivo} axis of loading. Rat USLs were excised using the proposed novel dissection method and pulled uniaxially as was performed in the previous chapter. Before and after mechanical testing, second harmonic generation (SHG) was used to image collagen and muscle within the three anatomical regions of the USLs. During mechanical testing, OCT was used to collect out-of-plane images of the cervical/intermediate regions of the USL specimens, resulting in 3D volume scans of the regions. SHG images showed the USLs to have complex microstructures with significant wavy collagen bundles interwoven with muscle bundles. Preliminary observation of the microstructure during testing revealed interwoven sections of tissue with collagenous fibers that reoriented in all directions illustrating how the USLs may expand laterally during uniaxial loading, causing the auxetic properties documented in the previous chapter. Though more quantitative work remains to be done, the findings presented in this dissertation improve our understanding of how the USLs deform with increasing load, such as what occurs during pregnancy. Together, these studies serve as a springboard for future investigations on the supportive function of the USLs in animal models by offering guidelines on testing methods that capture their complex mechanical behavior. Doctor of Philosophy The uterosacral ligaments (USLs) are important anatomical structures that support the uterus and vagina and are often used to restore the support of pelvic organs during surgeries for pelvic organ prolapse. These surgeries often result in poor outcomes, demonstrating the need for new surgical approaches and graft materials. Due to their supportive role, the mechanical properties of the USLs are important for their physiological function, and they must be investigated to improve current treatment strategies for pelvic organ prolapse. To this end, we designed new equipment, dissection, and testing methods to characterize the mechanical behavior of the USLs using swine and rats as animal models. We provided the first three-dimensional characterization of time-dependent deformations of swine USLs as they were pulled along their two physiological loading directions using advanced imaging methods, including digital image correlation and optical coherence tomography. We isolated the USLs from rats with their anatomical attachments and mechanically tested them along their main physiological loading direction, reporting the first mechanical data on the rat USLs in isolation from surrounding organs. Finally, we used the advanced imaging techniques optical second harmonic generation microscopy and optical coherence tomography to determine how the microstructure (e.g., collagen and muscle) of the rat USLs evolves before, during, and after mechanical testing. These findings advance our understanding of the three-dimensional, nonlinear, heterogeneous, elastic, and viscoelastic deformations of the USLs. Our work may serve as a springboard for future investigations on the supportive function of the USLs by offering guidelines on testing methods that capture their complex mechanical behavior.

Objective. Numerical modeling of electric fields induced by transcranial alternating current stimulation (tACS) is currently a part of the standard procedure to predict and understand neural response. Quasi-static approximation (QSA) for electric field calculations is generally applied to reduce the computational cost. Here, we aimed to analyze and quantify the validity of the approximation over a broad frequency range. Approach. We performed electromagnetic modeling studies using an anatomical head model and considered approximations assuming either a purely ohmic medium (i.e. static formulation) or a lossy dielectric medium (QS formulation). The results were compared with the solution of Maxwell’s equations in the cases of harmonic and pulsed signals. Finally, we analyzed the effect of electrode positioning on these errors. Main results. Our findings demonstrate that the QSA is valid and produces a relative error below 1% up to 1.43 MHz. The largest error is introduced in the static case, where the error is over 1% across the entire considered spectrum and as high as 20% in the brain at 10 Hz. We also highlight the special importance of considering the capacitive effect of tissues for pulsed waveforms, which prevents signal distortion induced by the purely ohmic approximation. At the neuron level, the results point a difference of sense electric field as high as 22% at focusing point, impacting pyramidal cells firing times. Significance. QSA remains valid in the frequency range currently used for tACS. However, neglecting permittivity (static formulation) introduces significant error for both harmonic and non-harmonic signals. It points out that reliable low frequency dielectric data are needed for accurate transcranial current stimulation numerical modeling.

The post-prognosis lifespan for those suffering with Glioblastoma (GBM) is approximately 13 months with current standard of care. Intratumoral heterogeneity is a common characteristic that hinders GBM treatment in the form of therapy resistant cell subsets and influence on cellular phenotypes. One cell subset in particular, glioma stem cells (GSCs), is frequently left behind in the brain parenchyma once the bulk of the tumor has been resected. Previous research has found that patient-derived GSCs displayed varying invasion responses with and without the presence of interstitial flow. Interestingly, GSCs from a single patient are heterogeneous, displaying differences among sub-colonies derived from the same parental line. To study the motility of cells under flow, PDMS microfluidics are commonly used. Unfortunately, this setup often involves active flow generation using pumps, limiting the number of cell lines that can be imaged at a time. To increase the throughput of GSC sub-colonies imaged simultaneously, we developed a bio-compatible, printable device fabricated to allow for passive, gravity-driven flow through a hydrogel that recapitulates the brain microenvironment, eliminating the need for pumps. Stereo lithography 3D printing was chosen as the manufacturing method for the device, and this facilitated design feature modification when prototyping, increased the potential complexity of future iterations, and avoided some of the hurdles associated with fabricating PDMS microfluidics. This printable imaging device allows for higher throughput live-imaging of cell lines to aid in the understanding of the relationships between intratumoral heterogeneity, invasion dynamics, and interstitial flow. Master of Science For those suffering with Glioblastoma, a high-grade brain cancer, the life span post treatment is approximately 13 months. The cells in this and many forms of cancer have physical and biological differences that make successfully eliminating the disease difficult. One of the cell types contributing to this are Glioma Stem Cells (GSCs) that are often left in brain tissue once most of the tumor has been surgically removed. Previous research has found that GSCs from different sources had different responses with and without the simulated or actual presence of flow in brain tissue. This was further complicated when different responses were observed in cells obtained when breaking apart one of the cell lines and propagating these into their own sub-colonies. The current standard for studying the movement of cells under flow is by using compact chips made of a clear silicone rubber. The setup with microfluidics typically requires connection to external tubing and pumps to create flow and this limits the amount of cell types that can be imaged at a time. In order to monitor more cells at a time we created a 3D printable device that uses gravity for flow to go through a gel that mimics brain tissue and these cells of interest. Resin 3D printing was used to make these small devices so that they could be easily re-designed for other experimental purposes in the future. Hopefully this device could be used to more rapidly gain an understanding of cell movement in GBM and other disease models.

Histotripsy is a noninvasive mechanical ablation method that uses focused ultrasound to disintegrate target tissues into acellular homogenate through the generation of acoustic cavitation and is currently being developed for numerous clinical applications. Histotripsy uses high-pressure (>10 MPa), short-duration (

Doctor of Philosophy Electric scooters, or e-scooters, have become an increasingly popular form of transportation over the recent years. However, there have been numerous reports of safety concerns, crashes, and injuries for e-scooter riders and other road users as a result of e-scooter misuse. Until recently, very little formal research has been conducted on the safety of this micromobility solution. This dissertation describes a series of studies that have investigated the contributing factors to safety concerns and identified countermeasures, such as policy recommendations, design optimization, and training, that can be implemented with an end goal of improving e-scooter safety.

The human brain is a complex organ that is responsible for regulating all the physiological processes in the body, ranging from memory to movement. As humans age, the brain goes through a variety of changes including a reduction in glymphatic waste clearance and increase in glial reactivity. Two neurological conditions that affect individuals over the age of 65 include glioblastoma (GBM) and Alzheimer's disease (AD). Interestingly, patients with GBM do not present with AD and vice versa. Both conditions are characterized by a disruption in interstitial fluid flow (IFF) and an increase in neuroinflammation. Throughout the following dissertation, we examined the role of IFF in AD and GBM progression using a three-sided approach (in vivo, in vitro, and in silico). Increased IFF underlies glioma invasion into the surrounding tumor microenvironment (TME) in GBM. We used a 3D hydrogel model of the GBM TME to examine potential pathways by which astrocytes and microglia contribute to glioma invasion. A reduction in IFF contributes to accumulation of the toxic protein amyloid beta (Aβ) in AD. We sought to create a novel, patient-inspired model of the AD hippocampus for examination of the relationship between IFF and Aβ clearance. Human AD and unaffected control hippocampal brain samples were stained for markers of neurons, astrocytes, microglia and Aβ. The percentage of each cell population in the CA1 region of the hippocampus was calculated. We also analyzed the amount and characteristics of the Aβ aggregates present in this hippocampal region. Pearson correlation analysis was completed to assess the relationships between the various cell populations, Aβ load, and patient descriptors. The cell ratios gleaned from the patient samples were incorporated into a novel, 3D hydrogel model of the AD hippocampus. This model features a hydrogel mixture like the native brain extracellular matrix (ECM) and allows for the application of IFF and Aβ. To our knowledge, we are the first group to create a patient-specific triculture model of the AD hippocampus, which is the main site of Aβ aggregation in the AD brain. We used this model to examine the relationship between IFF-mediated Aβ clearance and glial reactivity. The last aim of this dissertation was to create a computational model for examining Aβ binding within the ECM and the effects of IFF on Aβ clearance. In vitro experiments were conducted to generate 3D renderings of glial cells and to determine relevant parameters for our model. Throughout this work, we discuss the relationship between disruption in IFF and glial reactivity in the context of GBM and AD. Doctor of Philosophy The human brain is a complex organ that is responsible for regulating all the physiological processes in the body, ranging from memory to movement. As humans age, the brain goes through a variety of changes including a reduction in brain waste removal and an increase in inflammation. Two neurological conditions that affect individuals over the age of 65 include glioblastoma (GBM) and Alzheimer's disease (AD). Interestingly, patients with GBM do not present with AD and vice versa. Both conditions are characterized by a disruption in brain interstitial fluid flow (IFF) and an increase in neuroinflammation. Throughout the following dissertation, we examined the role of IFF in AD and GBM progression using a three-sided approach including analysis of mouse and human tissues, engineered cell models, and computational methods. Specific interactions between brain cell types and their relationships with glioma invasion were examined using a 3D cell model that mimics the brain. Through the work presented here, we also sought to create a novel cell model of the hippocampus region located in the AD brain. We quantified the various cell types in the hippocampus of AD patient samples and incorporated this information into our hydrogel model. The resulting model features three brain cell types (astrocytes, microglia, and neurons) that are added at patient relevant ratios, a matrix that mimics the native brain scaffold, and allows for the application of IFF. In the AD brain there is a reduction in brain waste removal that leads to accumulation of the toxic protein amyloid beta (Aβ). We were successfully able to incorporate this protein within our model so we could assess the relationship between IFF and Aβ removal from the brain. We further studied this relationship using a new computational model of Aβ accumulation in the brain. Throughout this work, we discuss the connection between disrupted IFF and neuroinflammation in the context of GBM and AD.

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Linear models are the dominant means of extracting summaries of events in fMRI for feature vector based machine learning. While they are both useful and robust, they are limited by the assumptions made in modeling. In this work, we examine a number of feature extraction techniques adjacent to linear models that account for or allow wider variation. Primarily, we construct mixed effects models able to account for variation between stimuli of the same class and perform empirical tests on the resulting feature extraction – classifier system. We extend this analysis to spatial temporal models as well as summary models. We find that mixed effects models increase classifier performance at the cost of increased uncertainty in prediction estimates. In addition, these models identify similar regions of interest in separating classes. While they currently require knowledge hidden during testing, we present these results as an optimum to be reached in additional works. Doctor of Philosophy Machine learning is a popular tool for extracting useful information from functional MR images. One approach is classification using feature vectors derived from observations. In this work, we examine new strategies for extracting feature vectors time varying data and explore the effect these feature vectors have on the results of machine learning analysis. In a set of simulations and real data, we compare a range of standard methods for feature extraction to new methods developed for this work. We find the most effective approach for successful classification is feature extraction through the use of mixed effects models. We also find that these models preserve the selection of feature sets that are maximally important to classification. We then explore the range of considerations required to use any of the methods examined in this work for a range of cases. We hope this provides solid ground for both future expansion of feature extraction methods and helpful advice for future users of these methods.

Traumatic brain injury (TBI) is a major medical concern that has demonstrated to be particularly challenging to treat because of the disparity amongst injury modes and severities. Increased use of explosive devices during combat has caused blast TBI (bTBI) to become a widespread consequence in military and Veteran populations, and impact-related trauma from contact-related sports or motor vehicle accidents has made mild impact-induced TBIs (concussion) a major health problem. There is a high risk for those who have sustained a TBI to develop behavioral and cognitive disorders following injury, and these symptoms can present as delayed onset, causing diagnosis to be a major feat when planning for treatment and long-term healthcare. Both preclinical and clinical studies report the neuropathological changes following TBI, yet investigating the distinct mechanistic changes in blast and impact trauma that contribute to pathological disparities has yet to be elucidated. Microglia dynamics play a key role in initiating the inflammatory response after injury, as microglia become activated by undergoing morphological changes that influence their function in the injured brain, and unique signaling pathways influence their functional inflammatory states. While previous literature report on the unique responses of microglia, their mediated-inflammatory responses are still not well defined. This work aimed to investigate the acute and subacute responses of microglia to injury through their diverse activation states following blast and impact trauma. The work herein employed rodent models to investigate these changes, finding that microglia activation was spatially and temporally heterogeneous within and across injury paradigms. Three days following bTBI, activated microglia in the cortex displayed morphologies similar to microglia that are known to increase their interactions with dysfunctional synapses, while dystrophic microglia were prevalent in the hippocampus seven days following injury. Moreover, transhemispheric changes in microglia activation were noted following impact TBI, with stressed/primed microglia responding to immune challenges of the cortex at three days, whereas a unique morphological state that was markedly different from those traditionally reported in CNS injury and disease was present within the hippocampus three- and seven-days following injury. State-of-the-art cell sorting techniques were used for in vivo analysis of microglia, which also exhibited that functional changes of microglia vary between injury paradigms, providing insight into how differences in primary insult may elicit distinct signaling pathways involved in microglia-mediated inflammatory responses. These in vivo studies were then crucial in understanding the malleable responses of microglia to complex injuries such as "blast plus impact" TBI, indicating that phenotypic changes in microglia following this injury are also unique and spatially heterogeneous. To date, therapeutic efforts for TBI are limited due to the lack of understanding the underlying mechanisms that influence TBI pathology. This work also investigated novel therapeutic targets, noting that administration of polyester nanoparticles restored microglia to baseline levels following impact. The fundamental research presented in this study is innovative and advantageous as it can provide essential data into targeted and personalized treatments that can improve long-term healthcare and ultimately, the quality of life for those suffering from a TBI. Doctor of Philosophy Traumatic brain injury (TBI) is a major medical concern that has demonstrated to be particularly challenging to treat because of the differences in injury modes and severities. Increased use of explosive devices during combat has caused blast TBI (bTBI) to become a widespread result in military and Veteran populations, and impact-related trauma from contact sports or motor vehicle accidents has made mild impact-induced TBIs (concussion) a major health problem. There is a high risk for those who have sustained a TBI to develop behavioral and cognitive disorders following injury, and these symptoms can present later on, causing diagnosis to be a major feat when planning for treatment and long-term healthcare. Microglia play a key role in inducing the inflammatory response after injury, as they change shape and size, which then influences their function in the injured brain. Although prior research reports on the unique responses of microglia, their effects on inflammation following TBI are still not well defined. This work aimed to investigate the early responses of microglia to injury through their diverse activation states following blast and impact trauma. The experiments in this study used animal models, finding that microglia activation can be distinct across time and brain regions, which may be injury-type-specific. To date, therapeutic efforts of TBI are limited due to the lack of understanding the underlying mechanisms that influence TBI pathology. This work also investigated beneficial treatments for TBI, noting that administration of nanoparticles helped restore microglia to levels similar to the control group. The fundamental research presented in this study is innovative and important as it can provide essential data into targeted and personalized treatments that can improve long-term healthcare and ultimately the quality of life for those suffering from a TBI.

The last decade has seen the development of a wide set of tools, such as wavefront shaping, computational or fundamental methods, that allow to understand and control light propagation in a complex medium, such as biological tissues or multimode fibers. A vibrant and diverse community is now working on this field, that has revolutionized the prospect of diffraction-limited imaging at depth in tissues. This roadmap highlights several key aspects of this fast developing field, and some of the challenges and opportunities ahead., submitted to J.Phys Photonics (IOP), 116 pages, 23 sections

The novel coronavirus (COVID-19) could be described as the greatest human challenge of the 21st century. The development and transmission of the disease have increased mortality in all countries. Therefore, a rapid diagnosis of COVID-19 is necessary to treat and control the disease. In this paper, a new method for the automatic identification of pneumonia (including COVID-19) is presented using a proposed deep neural network. In the proposed method, the chest X-ray images are used to separate 2–4 classes in 7 different and functional scenarios according to healthy, viral, bacterial, and COVID-19 classes. In the proposed architecture, Generative Adversarial Networks (GANs) are used together with a fusion of the deep transfer learning and LSTM networks, without involving feature extraction/selection for classification of pneumonia. We have achieved more than 90% accuracy for all scenarios except one and also achieved 99% accuracy for separating COVID-19 from healthy group. We also compared our deep proposed network with other deep transfer learning networks (including Inception-ResNet V2, Inception V4, VGG16 and MobileNet) that have been recently widely used in pneumonia detection studies. The results based on the proposed network were very promising in terms of accuracy, precision, sensitivity, and specificity compared to the other deep transfer learning approaches. Depending on the high performance of the proposed method, it can be used during the treatment of patients. This work was supported by Research and Innovation Management Center (PPPI) and Faculty of Engineering, Universiti Malaysia Sabah (UMS) under VOT (TBP0002). Publisher's Version