Journal of Biomechanical Engineering

Intervertebral disc degeneration (IVDD) compromises disc structures and mechanics, yet systematic evaluations of the mechanical responses and their relationship to morphological changes in preclinical models remain limited. This systematic review and meta-analysis synthesized mechanical and morphological alterations following experimental disc injury in in vivo animal models. Searches of MEDLINE, EMBASE and Web of Science databases were conducted in accordance with PRISMA guidelines. Study quality and risk of bias were assessed using modified CAMARADES and SYRCLE tools. Twenty-eight studies were included. Pooled analyses showed significant reductions in stiffness, Youngs modulus, and disc height, and significant increases in range of motion and degeneration grade, indicating both mechanical and structural deterioration. Youngs modulus appeared to be the most sensitive marker of functional degeneration. By contrast, creep and other viscoelastic responses showed non-significant changes. High heterogeneity was evident across studies, reflecting variability in injury models, species, timepoints, and testing methods. Evidence of publication bias was detected in several domains, and moderate methodological quality was noted with overall insufficient blinding and lack of sample size calculations. In vivo animal models of IVDD demonstrate robust and consistent mechanical and morphological degeneration after injury. Youngs modulus is a sensitive mechanical indicator, supporting its use in future preclinical research. Standardization of outcome definitions, methodology, and reporting is essential to improve comparability and enhance translation of preclinical findings to clinical research.

ObjectiveTo investigate the effects of different gait patterns on knee joint biomechanics and dynamic stability during stair ascent. MethodsFourteen healthy males were recruited to ascend stairs using two distinct gait patterns: the "single-step" (leading with the same leg) and "cross-step" (alternating legs) strategies. Kinematic and kinetic data were collected synchronously using a Qualisys infrared motion capture system and a Kistler 3D force plate. Dynamic stability was quantified using the Margin of Stability (MOS), and knee joint biomechanics were evaluated using Patellofemoral Joint Stress (PFJS) and other relevant metrics. ResultsThroughout the gait cycle, there was no significant difference in the Medio-Lateral (ML) MOS between the single-step and cross-step patterns (P=0.318). However, in the Anterior-Posterior (AP) direction, the MOS for both patterns remained negative and decreased over time, with the cross-step pattern exhibiting significantly lower AP MOS values than the single-step pattern (P=0.002). At the moment of left foot-off, significant differences were observed in the right knee joint angle, right knee joint moment, net joint moment, effective quadriceps muscle lever arm, Quadriceps Force (QF), the angle between the quadriceps tendon and patellar ligament, Patellofemoral Joint Force (PFJF), patellofemoral joint stress, and patellofemoral contact area (all P<0.001). ConclusionsDuring stair ascent, the cross-step pattern reduces body stability, thereby increasing the risk of backward falls. Furthermore, this pattern increases patellofemoral joint stress, subjecting the knee to greater loading. Therefore, it is recommended to enhance lower limb muscle strength through targeted training to reduce fall risk. Additionally, adopting a more cautious gait strategy (such as the single-step pattern) can help minimize patellofemoral joint loading and mitigate the risk of patellofemoral pain.

Alzheimers disease (AD) is characterized by the accumulation of amyloid-{beta} (A{beta}), yet the specific link between plaque burden and cognitive decline remains a subject of intense investigation. This paper presents a mathematical model that simulates the coupled dynamics of A{beta} monomers, soluble oligomers, and fibrillar species in the brain tissue. By modifying existing moment equations to include a dedicated conservation equation for A{beta} monomers, the model explores how various microscopic processes, such as primary nucleation, surface-catalyzed secondary nucleation, fibril elongation, and fragmentation, contribute to macroscopic disease progression. Central to this study is the concept of "accumulated neurotoxicity" as a surrogate marker of biological age, defined as the time-integrated concentration of soluble A{beta} oligomers. Unlike plaque burden, accumulated neurotoxicity cannot be reversed, and the harm it causes depends critically on the sequence of events that produced it. Numerical results demonstrate that while plaque burden and neurotoxicity both increase over time, their relationship is non-linear and highly sensitive to the efficiency of protein degradation machinery. Specifically, impaired degradation leads to a rapid advancement of biological age relative to calendar age. The model further identifies oligomer dissociation and fibril fragmentation as potential protective mechanisms that can counterintuitively reduce neurotoxic burden by diverting monomers away from the soluble oligomer pool. These findings provide a quantitative framework for understanding why individuals with similar plaque burdens may experience vastly different cognitive outcomes, underscoring the importance of targeting soluble oligomers early in therapeutic interventions.

This study investigates closed kinematic chain biomechanics in cycling with a focus on knee joint loading. Data from 16 cyclists collected on a standardized ergometer were analyzed in OpenSim using inverse dynamics, static optimization, and joint reaction analysis. To keep the pipeline consistent across all subjects, the report summarizes right-knee outputs over a steady-state interval between 120 and 124 s. Peak knee joint moments ranged from 15.79 to 44.85 Nm (mean 30.49 {+/-} 7.66 Nm), while peak resultant knee reaction forces ranged from 1187.61 to 3309.04 N (mean 2317.19 {+/-} 728.19 N). Static optimization showed strong contributions from the rectus femoris and vastus lateralis during power production, with additional stabilization from the biceps femoris long head and gastrocnemius medialis. Mean peak muscle activation was highest for the rectus femoris (0.72 {+/-} 0.19), followed by the biceps femoris long head (0.66 {+/-} 0.20). Mean peak muscle force was highest for the vastus lateralis (1078.1 {+/-} 305.8 N) and rectus femoris (994.1 {+/-} 379.2 N). The results confirm substantial inter-subject variability in knee loading and support the use of personalized training or rehabilitation strategies when cycling is used for performance development or joint recovery.

Clavicle fractures often exhibit markedly different clinical outcomes: some patients recover acceptable function despite shortening or displacement, whereas others with apparently similar deformity develop persistent pain, functional loss, or poor healing. To explain this distinction, we propose a minimal nonlinear mechanical model for prognostic analysis of clavicle fractures. The model describes the interaction between fracture-related shortening and compensatory shoulder-girdle posture through a reduced equilibrium equation incorporating stiffness, geometric nonlinearity, and shortening-posture coupling. Within this framework, we analyze equilibrium branches, local stability, and the emergence of critical thresholds. We show that post-fracture destabilization can be interpreted as a fold bifurcation, while more complex parameter dependence gives rise to cusp-type structures and multistability. These bifurcation mechanisms provide a mathematical explanation for sudden deterioration after injury or treatment, as well as for strong inter-individual variability. We further introduce an optimization principle based on a utility functional to guide treatment planning. The analysis predicts that the optimal safe correction should lie strictly below the bifurcation threshold, thereby generating a natural safety margin. Although the model is simplified and has not yet been calibrated against patient data, it nevertheless provides a theoretical framework for understanding why fracture prognosis may deteriorate abruptly near critical mechanical conditions and offers a dynamical-systems interpretation of empirical treatment thresholds used in clinical practice.

IntroductionTrabecular bone exhibits brittle behaviour governed by microscale deformation and damage processes, yet quantitative characterisation of crack progression remains challenging because classical fracture mechanics approaches do not apply to architecturally discontinuous porous tissues. This study evaluates whether synchrotron X-ray computed tomography (XCT) combined with digital volume correlation (DVC) can provide a practical experimental approach for quantifying crack opening behaviour in human trabecular bone. MethodSemicylindrical specimens harvested from femoral heads of hip-fracture donors (n = 5) and non-fracture controls (n = 5) underwent stepwise three-point-bending during XCT imaging. Full-field displacement maps enabled direct measurement of crack mouth opening displacement (CMOD), crack length (a), and their ratio, CMOD/a, used here as a geometry-normalised comparative descriptor of brittle response. Automated crack segmentation using phase-congruency crack detection (PCCD) was compared against manual measurements. ResultsXCT-DVC successfully resolved three-dimensional displacement discontinuities during crack initiation and propagation in all specimens. Hip-fracture donors exhibited significantly lower critical crack-opening ratios (CMOD/a)* than Controls (0.31 vs 0.47; p = 0.008) and reached mechanical instability at lower applied loads, consistent with a more brittle structural response under this test configuration. Despite these differences, total crack extension ({Delta}a*) was similar between groups. Automated crack tracking using phase-congruency-based segmentation showed excellent agreement with manual measurements (r{superscript 2} = 0.98), confirming reliable extraction of crack geometry from DVC displacement fields. DiscussionThese results indicate that XCT-DVC can provide a practical approach for quantifying crack-opening behaviour in trabecular bone when classical fracture-mechanics parameters are not applicable in anatomically constrained specimens. The reduced critical crack-opening ratios and earlier instability observed in Hip-fracture donors are consistent with a more brittle comparative mechanical response that is not captured by crack extension alone. The strong agreement between automated and manual crack measurements further supports displacement-based descriptors as reliable comparative indicators of brittle behaviour in porous, architecturally discontinuous tissues. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=76 SRC="FIGDIR/small/714043v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@31c5d7org.highwire.dtl.DTLVardef@1b3d9a4org.highwire.dtl.DTLVardef@95df7borg.highwire.dtl.DTLVardef@1834216_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstractC_FLOATNO C_FIG

Cerebrospinal fluid (CSF) is a Newtonian fluid that bathes the brain and spinal cord and oscillates in response to the physiological periodic changes in brain volume, of which the cardiac cycle is a major driver. Understanding this motion is essential for clarifying its contribution to solute transport, waste clearance, and drug delivery. In this work, we study oscillatory and steady streaming flow in the cranial subarachnoid space using a lubrication-based theoretical framework. The model represents the cranial CSF compartment as a thin fluid layer bounded internally by the brain surface and externally by the dura, driven by time-dependent brain surface displacements. We first derive simplified governing equations for flow over an arbitrary smooth sphere-like brain surface and obtain analytical solutions for an idealised spherical geometry with uniform displacements. We then incorporate realistic displacement fields reconstructed from MRI measurements in healthy subjects and solve the reduced equations numerically. The results show that oscillatory forcing produces a steady streaming component that may enhance solute transport compared with diffusion alone. This work provides a mechanistic description of the flow generated by physiological brain motion and highlights the potential presence of steady streaming in cranial subarachnoid fluid dynamics.

Modelling of hemodynamics in the circle of Willis (CoW) depends on vascular segmentation, which may vary based on imaging modality. Computed tomography angiography (CTA) is commonly used in clinic but involves radiation and injection of contrast agents, whereas magnetic resonance angiography (MRA) offers a non-invasive alternative. This study aims to compare CoW morphology and modelled cerebral perfusion pressure of CTA and MRA segmentations, validating if MRA can replace CTA in modelling workflows. CTA and time-of-flight MRA (TOF-MRA) of the CoW was performed in 19 patients undergoing elective aortic arch surgery (67{+/-}7 years, 8 women). The CoW was semi-automatically segmented based on signal intensity thresholding. A TOF-MRA threshold was optimized against the CTA segmentation, using the CTA as reference standard. Computational fluid dynamics (CFD) modelling with boundary conditions based on subject-specific flow rates from 4D flow MRI simulated cerebral perfusion pressure in the segmented geometries. A baseline simulation and a unilateral brain inflow simulation, i.e., occlusion of a carotid, were carried out. Linear mixed models indicated there was no effect of choice of modality on either average arterial lumen area (CTA - TOF-MRA: -0.2{+/-}1.3 mm2; p=0.762) or baseline pressure drops (0.2{+/-}1.9 mmHg; p=0.257). In the unilateral inflow simulation, we found no difference in pressure laterality (-6.6{+/-}18.4 mmHg; p=0.185) or collateral flow rate (10{+/-}46 ml/min; p=0.421). TOF-MRA geometries can with signal intensity thresholding be matched to produce similar morphology and modelled cerebral perfusion pressure to CTA geometries. The modelled pressure drops over the collateral arteries were sensitive to the segmentation regardless of modality.

The osteochondral junction is a specialized region ensuring the biomechanical and biological integration of the unmineralized articular cartilage with the subchondral bone through an intermediate layer of mineralized cartilage. This location is of clinical relevance, being the target of osteoarthritis. While aging is considered a risk factor for osteoarthritis, the interplay between microstructural and material changes during aging and predisposing to joint degeneration is not fully clear. This is especially true for mineralized cartilage, which remains understudied despite its critical role in load transfer from unmineralized articular cartilage to bone. We investigate age-related alterations of mineralized cartilage and subchondral bone in rat tibiae of adult and aged animals using a multimodal, high-resolution, correlative analysis. Our approach includes micro-computed tomography to measure microstructural features, second harmonic generation imaging to visualize collagen organization, quantitative backscattered electron imaging to map local mineral content, and nanoindentation to obtain mechanical properties. Mineralized cartilage and subchondral bone exhibited distinct age-related modifications. At the architectural level, the subchondral plate thickened and the trabecular network became coarser, those changes being different from those observed in the metaphysis. At the tissue level, mineralized cartilage was less mineralized than bone but exhibits a greater relative increase of mineral content with age, underlying differences in mineralization. A central observation is that aging led to an abrupt transition in mineral content and mechanical properties across the interface between unmineralized and mineralized cartilage, with a conceivable impact on stress localization. Overall, these changes may alter load transfer and contribute to age-related joint degeneration.

Objective: Abdominal aortic aneurysms (AAA) affect more than 1% of adults over 50 and carry significant mortality risk. Current surveillance relies on intermittent imaging (ultrasound or MRI) at 6--24 month intervals, which may miss rapid growth acceleration between visits. We investigate the feasibility of continuous aneurysm diameter tracking using peripheral pulse waves, like those detected by photoplethysmography (PPG) devices. Approach: We use a simplified one-dimensional hemodynamic model that simulates pulse wave propagation from the heart to the pedal digital artery. We first demonstrate diameter estimation when the hemodynamic model parameters defining systemic circulation are known within bounds for an individual, aggregating thousands of observations over hours or days. We then address the more challenging scenario where systemic circulation parameters are only known to be within wider population-level physiological bounds, using a sequential Monte Carlo approach that combines ensemble MCMC with Kalman filtering to marginalise over unknown parameters while tracking the aneurysm diameter. Both approaches are validated through 12-month tracking simulations with constant and accelerating aneurysm growth rates. Main results: While single-observation diameter estimation is fundamentally limited by noise and confounding variables, aggregating 1,600 measurements under baseline noise conditions reduces diameter uncertainty to 0.8~mm when patient-specific hemodynamic parameters are known within bounds. In this setting, tracking simulations across eight virtual patients achieve average root-mean-square error (RMSE) of $\sim$0.3~mm. When systemic parameters are known only within population-level bounds, joint Bayesian estimation over the full parameter space achieves a median RMSE of 0.65~mm (1.4$\pm$0.3~mm, mean$\pm$standard error) across 50 virtual patients, remaining within clinically relevant ranges despite the underlying parameters being only partially identifiable. Significance: These physically-grounded, computational results suggest that peripheral pulse wave monitoring through wearable PPG sensors could complement traditional imaging for aneurysm surveillance, potentially enabling earlier detection of growth acceleration and more timely clinical intervention.

A passive device that attaches to the feet, called an exotendon, can reduce the energetic cost of running at moderate speeds, but its efficacy and optimal design parameters at higher speeds are unknown. Identifying optimal parameters at new speeds experimentally would require many experimental trials with different exotendon designs, which is challenging for participants at higher running speeds. We developed a muscle-driven simulation framework to predict the effect of various exotendon designs on the energetic cost of running at an experimentally untested speed (4 m/s). We used these predictions to select four designs, which we evaluated experimentally as users ran at this speed. The framework correctly predicted that an exotendon that reduced energetic cost at 2.7 m/s would also reduce energetic cost at 4 m/s (10% predicted vs. 5.7% measured) and that a short, stiff exotendon and a long, compliant exotendon would not significantly reduce energetic cost. However, exotendon parameters predicted by the simulation to maximize energetic savings did not significantly reduce energetic cost when evaluated experimentally. There was variability between participants in both the magnitude of maximum energy savings and the exotendon condition associated with those savings. In a 5-km time trial performed with and without the exotendon condition that elicited the largest energy savings for each participant during the experiment, we observed a lower average heart rate (-3.9 {+/-} 3.8 beats/min; P=0.03; mean {+/-} standard deviation) and increased cadence (15.9 {+/-} 9.6 steps/min; P=0.002) when participants ran with the exotendon but did not observe a statistically significant difference in finishing time (-13.5 {+/-} 24.6 sec; P=0.3). These results demonstrate exotendons can reduce energetic cost across multiple running speeds and that predictive simulations provide a framework for guiding experiments to evaluate assistive device designs. Author summaryDesigning assistive devices that help people move more efficiently usually requires many experimental trials. These studies can be time-consuming and physically demanding, especially when testing multiple device designs. In this study, we explored whether computer simulations could help guide the design of an assistive device for running called an exotendon. The exotendon is a simple elastic band that connects the feet and can help runners use less energy. Previous experiments showed that the device reduces the energy needed to run at moderate speeds, but it was unclear whether it would also work at faster speeds or which design would lead to energetic savings. We first used simulations of human running to test many possible exotendon designs at a faster speed. These simulations allowed us to identify promising designs before conducting experiments. We then tested a small number of these designs with runners. The experiments confirmed that the exotendon can reduce the energy required to run at faster speeds, although the efficacy of different designs varied between individuals. Our results show that computer simulations can help researchers rapidly evaluate a variety of assistive device ideas and focus experimental testing on the most promising designs.

Mass-conserved reaction-diffusion systems are used as mathematical models for various phenomena such as cell polarity. Numerical simulations of this system present transient dynamics in which multiple stripe patterns converge to spatially monotonic patterns. Previous studies indicated that the transient dynamics are driven by a mass conservation law and by variations in the amount of substance contained in each pattern, which we refer to as "pattern flux". However, it is challenging to mathematically investigate these pattern dynamics. In this study, we introduce a reaction-diffusion compartment model to investigate the pattern dynamics in view of the conservation law and the pattern flux. This model is defined on multiple intervals (compartments), and diffusive couplings are imposed on each boundary of the compartments. Corresponding to the transient dynamics in the original system, we consider the dynamics around stripe patterns in the compartment model. We derive ordinary differential equations describing the pattern dynamics of the compartment model and analyze the existence and stability of equilibria for the reduced ODE with respect to the boundary parameters. For a specific parameter setting, we obtained results consistent with previous studies. Moreover, we present that the stripe patterns in the compartment model are potentially stabilized by changing the parameter, which is not observed in the original system. We expect that the methodology developed in this paper is extendable to various directions, such as membrane-induced pattern control.

Despite the increased water content in fibrotic livers, numerous studies reported a decrease in ADC (apparent diffusion coefficient) in liver fibrosis. We argue that the ADC decrease in fibrotic livers is due to the T2 shine-through of ADC, as the longer T2 in liver fibrosis leads to less signal decay between the low and high b-value images. The metric slow diffusion coefficient (SDC) was proposed to mitigate the difficulties associated with this T2 shine-through of ADC. This study calculated ADC and SDC of one rat study with liver fibrosis induced by biliary duct ligation (BDL), and three sets of human liver fibrosis data. To tease out the menopausal effect on SDC, only the results of mens livers were analysed for the human datasets. The rat study showed, liver ADC decreased stepwise (in weeks after BDL procedure) following fibrosis induction, SDC increased stepwise. In human studies, all three datasets consistently showed advanced fibrosis had an ADC lower than that of earlier stage fibrosis; advanced fibrosis had a SDC higher than that of earlier stage fibrosis. When each liver SDC datum was normalized by the mean value of the controls without fibrosis, and the three human datasets were summed together, stage-1 liver fibrosis had a normalized SDC value lower than that of the controls, and there was a stepwise increase of SDC value from stage-1 liver fibrosis to stage-4 liver fibrosis. It is known that liver fibrosis is associated with lower perfusion, higher iron/susceptibility, and higher water content, and these three factors all contribute to the lower ADC measure. Higher iron/susceptibility lowers SDC measure, whereas higher water content elevates SDC measure. It is likely that for early-stage fibrosis, the net effect of susceptibility and water leads to a lower SDC, while for advanced fibrosis, the net effect leads to a higher SDC.

Digital volume correlation (DVC) has become the benchmark experimental technique for full-field strain measurement in bone mechanics. In our previous work we developed a novel data-driven image mechanics (D2IM) approach that learns from DVC data and predicts displacement fields directly from undeformed X-ray computed tomography (XCT) images, deriving strain fields from such predictions. However, strain fields derived through numerical differentiation of displacement fields amplify high-frequency noise, and regularization techniques compromise spatial resolution while incurring substantial computational costs. Here we propose the upgrade D2IM-Strain to predict strain fields directly from XCT images of bone. Two prediction strategies were compared: displacement-derived strain and direct strain prediction. The direct strain prediction model significantly improved accuracy particularly for strain magnitudes below 10000{micro}{varepsilon}, taken as a representative threshold value for bone tissue yielding in compression. In addition, the direct approach reduced false-positive high-strain classifications by 75%. By eliminating numerical differentiation, the approach reduces noise amplification while maintaining computational efficiency. These findings represent a critical step toward developing robust data-driven volume correlation methods for hierarchical materials.

Intervertebral disc (IVD) injury is a major cause of low-back pain and can lead to structural deficits and mechanical instability. When the IVD is compromised, neuromuscular compensation by paraspinal muscles, such as the multifidus (MF) and longissimus (ML), is critical for maintaining spine stability. However, it is unknown how IVD injury and its interaction with nociception affect neuromuscular control. This study assessed the effects of IVD injury and additional muscle-derived nociception on trunk motor control during locomotion in a rat model. IVD injury was induced via needle puncture at L4/L5. One week later, hypertonic saline was injected into the lumbar MF to induce nociception. Trunk and pelvic kinematics, bilateral EMG activity of MF and ML were recorded during treadmill locomotion at baseline, one week after IVD injury, and immediately following hypertonic saline injection. Trunk and pelvic kinematics and bilateral muscle activation patterns remained largely consistent across conditions. No significant changes were found in stride duration, pelvic, lumbar and spine angle changes, variability, or movement asymmetry. MF activation was bilaterally synchronized, whereas ML showed left-right alternating activation patterns. Following IVD injury, right MF mean activation and EMG variability increased significantly compared to baseline. When muscle-derived nociception was added in the unstable spine (IVD injury) condition, left MF minimum amplitude was significantly reduced, and instability-related increases in right MF mean activation and variability were attenuated, but not fully reversed. These findings suggest that IVD injury, alone or in combination with muscle-derived nociception, elicits localized neuromuscular adaptations without disrupting the global locomotor patterns.

BackgroundConventional left ventricular assist device ramp metrics are load dependent, obscuring intrinsic myocardial recovery. A mechanistic, patient-specific representation of ventricular mechanics, identifiable from routine clinical data, could provide quantitative indices of intrinsic left ventricular (LV) function for longitudinal recovery surveillance. ObjectiveTo develop and verify a ramp-integrated, patient-specific model of HeartMate 3-assisted LV function that can yield indices of intrinsic myocardial contractility and remodeling. MethodsWe represented LV pressure-volume (PV) behavior with a PV envelope composed of a monotonic passive PV relation (pPVR) and a unimodal active PV relation (aPVR). We developed a parameterization procedure to infer the patient-specific shape of this envelope directly from routine ramp-test data. We then embedded the parameterized envelope within the PSCOPE framework, a hybrid platform that couples a lumped-parameter network to a physical HeartMate 3 flow loop, to reproduce clinical ramp hemodynamics. Percent residuals between simulated outputs and the corresponding clinical measurements verified the implementation of the PV envelope within PSCOPE. ResultsIn three HeartMate 3 recipients, the PSCOPE models reproduced ramp hemodynamics with residuals generally [&le;] 20% across pump speeds and measured variables. Cardiac index residuals ranged from 0-18.5%, systemic and pulmonary arterial pressure residuals remained [&le;] 18.4%, and pulmonary arterial wedge pressure residuals remained [&le;] 20%. The PSCOPE models matched central venous pressure within [&le;] 3 mmHg in all cases, although one setting yielded a 33.3% residual due to a low reference pressure. For one patient, the model reproduced ramp hemodynamics at a speed deliberately withheld from PV-envelope parameterization with residuals [&le;] 10%, supporting cross-speed generalizability. Patient-specific PV envelopes also revealed clinically meaningful heterogeneity in LV diastolic stiffness, volume threshold for declining systolic function, operating PV points for peak systolic function, and contractile reserve. ConclusionsRamp-integrated parameterization of the monotonic pPVR and unimodal aPVR yields a compact, mechanistic PV envelope that is identifiable from routine clinical data and verifiable within PSCOPE. The resulting indices characterize intrinsic LV function and may enhance longitudinal recovery surveillance and inform LVAD management. Prospective multicenter validation is warranted to confirm the generalizability and clinical utility of this approach.

Head rotation is the leading cause of diffuse brain injuries from cycling accidents, with severe, long-term or even fatal consequences. Here, we present a novel helmet safety technology, the Release Layer System (RLS), designed to enhance conventional helmets and reduce the likelihood of such injuries. RLS is located on the outer side of the helmet and thus gets impacted first. The force of the impact activates a rolling mechanism triggering the release of an outer polycarbonate panel, thereby dispersing and transforming a substantial portion of the incident rotational energy. To evaluate the effectiveness of the technology, we conducted oblique impact tests on three popular helmet types, in conventional and RLS-equipped configurations, at three impact locations. RLS-equipped helmets reduced Peak Angular Velocity (PAV) by 57-66%, averaged across impact locations, compared to their conventional counterparts. This corresponds to a 68-86% reduction in the probability of an AIS2+ brain injury, as estimated by the Brain Injury Criterion. The most notable improvement was observed at the pYrot location (front impacts, mid-sagittal plane), with up to 85% PAV reduction. Testing across headforms further demonstrated the effectiveness of the technology in mitigating head rotation irrespective of variations in evaluation setups. This work introduces a novel mechanism for rotational impact mitigation and provides evidence of its potential benefits compared with conventional helmets. As an outer-layer approach, RLS may offer an alternative pathway for managing rotational kinematics in future helmet designs.

Wearable devices for gravity balancing have high potential for impact across domains, including neuromotor rehabilitation and occupational systems. Devices made from compliant mechanisms, optimized to achieve specific compensation moments at target joints, have proven effective, but thus far have solely been optimized towards gravity compensation and not other wearability criteria. In this work, we propose a multi-objective optimization framework, based on particle swarm optimization, to design a soft, gravity balancing shoulder orthosis, while taking into account wearability constraints such as undesired loading directions and device size. Using this custom framework, we pursued multiple stages of orthosis design and optimization, selecting multiple solutions to be translated to real-world prototypes. These solutions were realized via 3D printing with thermoplastic polyurethane and evaluated for mechanical performance on benchtop and in-vivo. In-vivo testing on 6 healthy individuals demonstrated relative reductions in muscle activity for the anterior deltoid and upper trapezius, by 53 % and 71 % respectively when operating the orthosis for static tasks within functional shoulder ranges of motion. Changes in muscle activation were also were observed across other muscles, including the posterior deltoid, as well as in dynamic tasks at different speeds.

Background: Deep brain stimulation (DBS) is a treatment option for Parkinson disease (PD). However, the effect of DBS on the arterial pressure (AP) remains unexplored. We aimed to develop an artificial baroreflex system for treating orthostatic hypotension (OH) due to central baroreflex failure in patients with PD. To achieve this, we developed an appropriate algorithm after estimating the dynamic responses of the AP to DBS using a white noise system identification method. Methods: We randomly performed DBS while measuring the AP tonometrically in 3 trials involving 3 patients with PD treated with DBS. We calculated the frequency response of the AP to the DBS using a fast Fourier transform algorithm. Finally, the feedback correction factors were determined via numerical simulation. Results: The frequency responses of the systolic AP to random DBS were identifiable in all 3 trials, and the steady state gain was 8.24 mmHg/STM. Based on these results, the proportional correction factor was set to 0.12, and the integral correction factor was set to 0.018. The computer simulation revealed that the system could quickly and effectively attenuate a sudden AP drop induced by external disturbances such as head-up tilting. Conclusion: An artificial baroreflex system with DBS may be a novel therapeutic approach for OH caused by central baroreflex failure.

Domestic dogs (Canis familiaris) display more morphological variation than any other mammal. Cranial morphology has been extensively studied, as have the relationships with function, development, genetics, veterinary medicine, and breed welfare. Postcrania remain comparatively understudied, despite well-documented breed-specific predispositions to musculoskeletal disease. Here, we apply three-dimensional landmark-free morphometrics to quantify the shape of 743 elements from 213 dogs, including the scapula, humerus, radius, ulna, pelvic girdle, femur, tibia, and fibula. We assess integration among limb elements and investigate drivers of shape variation within and between breeds. Across most breeds, limb bone shape is strikingly similar. Dachshunds, however, exhibit distinct morphology across all elements and one to two orders of magnitude greater variation than any other breed. Despite this disparity, integration remains high between all element pairs. Remarkably, we find no significant relationship between bone shape and body mass, age, or pathology, but comparison with historic specimens reveals marked changes in dachshund long bone shape over the past [~]150 years. These extreme differences are not shared by other sampled chondrodysplastic breeds, underscoring the need to understand morphological diversity beyond simple categorisation. These findings provide a quantitative framework for linking postcranial morphology with function, disease risk, and evidence-based improvements to canine welfare.