Biomechanics and Modeling in Mechanobiology

Endothelial cells integrate biomechanical and biochemical cues to regulate vascular function, which can be modeled using cell signaling networks. Yet, the extent to which their signaling behavior is determined by network topology versus reaction-specific parameterization remains unclear. We developed a continuous logic-based ordinary differential equation model of vascular endothelial signaling containing 70 species and 123 regulatory reactions assembled from the literature. Model predictions were evaluated against 78 literature-defined directional responses to increased wall stress, wall shear stress, hypoxia, and TNF. We first tested whether a single global parameter triplet describing reaction weight (w), Hill coefficient (n), and half-maximal activation (EC50) could reproduce these observations. Investigator-selected global parameters reproduced 62 of 78 responses (79.49%). Monte Carlo sampling of 100,000 globally constant parameter sets improved agreement to 69 of 78 responses (88.46%), indicating that network topology alone captured most qualitative signaling behavior but remained sensitive to parameter choice. Allowing reaction-specific parameters increased the best agreement to 75 of 78 responses (96.15%). We then used a genetic algorithm to identify the smallest subset of reactions requiring reaction-specific specification while retaining a common constant-parameter spine for the remainder of the network. Complete agreement (100%) with all 78 literature-defined responses was achieved with reaction-specific parameterization of only 10 of 123 reactions. The optimized model was subsequently used to simulate continuous changes in wall shear stress, revealing pathway-dependent nonlinear responses, including monotonic increases in nitric oxide and pSmad1/5, nonmonotonic responses in endothelin-1 and NF-{kappa}B, and a biphasic pSmad2/3 response. These findings show that most observed endothelial signaling behavior can be reproduced by a fixed network topology with broadly shared reaction parameters with only a limited subset of interactions requiring quantitative specialization. This framework provides a compact endothelial signaling model for investigating mechanobiological regulation and for future integration with multiscale models of vascular adaptation and disease.

Predictive biomechanical models of the tricuspid valve require accurate representation of the chordae tendineae, yet subject-specific chordal geometry is difficult to reconstruct from non-invasive imaging. Here, we adopt a framework for generating functionally equivalent synthetic chordae without prior knowledge of in vivo chordal attachments. To this end, we first adapt an anatomy-informed hyperelastic shape-matching method that establishes correspondence between end-diastolic and end-systolic leaflet configurations using chordal-mimicking forces, a rigid contact template, and a Gaussian-smoothed locally corrective pressure field. We then generate synthetic chordal insertion sites using zone-based rejection sampling and calibrate the unloaded length of each chord by combining reaction forces with the chordal stress-stretch relationship. The framework was evaluated using Texas TriValve 1.1, a high-fidelity finite element model of a human tricuspid valve validated against beating-heart echocardiography. We found that shape matching reproduced the target end-systolic geometry with a mean inter-surface distance of 0.29 {+/-} 0.35 mm. Moreover, synthetic chordal insertions faithfully reproduce end-systolic leaflet deformations. We subsequently examined synthetic chordal configurations containing 202, 225, and 450 insertions, informed by measurements from eight explanted human tricuspid valves. Here, increasing insertion number reduced mean inter-surface distance from 0.63 {+/-} 0.52 mm to 0.49 {+/-} 0.44 mm and reduced contact area errors from 3.52% to 0.59%. Across all configurations, mean maximum principal stretch errors in leaflet belly regions remained below 2.4%, while areal strain errors ranged from 0.34% to 10.01%. These results demonstrate that anatomically informed shape matching coupled with stress-based chordal calibration can reproduce tricuspid valve closure without explicit subject-specific chordal geometry. This framework provides a foundation for generating synthetic subvalvular anatomy for future imaging-derived, predictive tricuspid valve models.

Background: Ascending thoracic aortic aneurysm (ATAA) is characterized by progressive biomechanical remodeling that is incompletely captured by maximum aortic diameter. The relationships between age, sex, aortic valve phenotype (BAV vs TAV), and aneurysmal mechanics remains incompletely understood. Methods: Ascending aortic specimens from 54 patients undergoing elective ATAA repair were evaluated. Biaxial testing quantified Green strain and local stiffness at membrane tensions of 60 and 120 N/m. Opening angle was used to assess circumferential residual stress and stretch. Associations with age were evaluated using Pearson correlations, and differences between sex and valve phenotype were also explored. Multivariable linear regression models including age, sex, and valve phenotype were used to evaluate their adjusted associations with each mechanical outcome. Results: Increasing age was associated with increased local stiffness and reduced Green strain and remained the strongest determinant of biaxial mechanical properties after adjustment. Compared with tricuspid aortic valve specimens, BAV specimens exhibited lower Green strain together with lower local stiffness. Females demonstrated greater Green strain in unadjusted analyses; however, after adjustment, sex remained associated only with longitudinal Green strain at 60 N/m. None of the evaluated clinical characteristics consistently explained opening angle or residual stretch. Conclusions: Age was the predominant clinical determinant of biaxial mechanical remodeling in ATAA, whereas valve phenotype demonstrated selective associations and sex contributed comparatively little after adjustment. Circumferential residual stress appeared largely independent of these clinical characteristics, suggesting that residual stress and biaxial mechanics capture complementary aspects of aneurysmal remodeling.

Purpose: Atrial fibrosis is associated with thromboembolic risk in atrial fibrillation, but how fibrosis-related contractile impairment alters blood transport in the left atrium (LA) and left atrial appendage (LAA) remains unclear. Prior multi-physics simulations coupled electromechanical (EM) and computational fluid dynamics (CFD) models to show that fibrosis impairs LA function and flow, but were limited to booster-only contraction and could not separate the effects of fibrosis burden from its spatial distribution. Here we examined how fibrosis burden and spatial pattern independently relate to long-term LA and LAA hemodynamics in full-cycle, multi-beat simulations on a common LA anatomy. Methods: Three fibrosis patterns derived from late gadolinium enhancement MRI were considered: one from the patient providing the common anatomy and two from additional patients, with the latter mapped onto the common anatomy via universal atrial coordinates. All three patterns were applied globally at matched burdens of 15.6% and 31.2%, yielding six global-fibrosis cases and a non-fibrotic reference. Two patterns were also confined to the LAA at three local burdens (10%, 25%, and 50%), yielding six LAA-fibrosis cases. A 3D EM model for the LA anatomy was coupled to a 0D circulatory model, so that the simulations resolved the reservoir, conduit, and booster phases. Full-cycle EM-derived wall motion drove subsequent multi-beat CFD simulations. Region-specific emptying fraction (EF), non-dimensional kinetic energy (KE), and the 90th percentile of blood residence time (TR) were evaluated for the LA and LAA. Results: Left ventricular stroke volume remained nearly constant across cases, while increasing global fibrosis burden progressively reduced LA and LAA EF (LA: 36% to 30-31%; LAA: 44% to 28-38%) and monotonically increased LA TR across all patterns. Non-dimensional LA KE showed an approximately quadratic association with LA EF across patterns, whereas LAA KE was more scattered but still increased with LAA EF. In contrast, the relationship between the 90th percentile of LAA TR and LAA EF showed pattern-specific, non-monotonic trends. Conclusions: Fibrosis burden and spatial distribution jointly shape LA and LAA hemodynamics, but through different mechanisms. LAA EF is a robust functional descriptor of chamber-averaged kinetic energy regardless of fibrosis pattern, whereas LAA blood stasis depends additionally on the spatial distribution of fibrosis beyond what bulk emptying fraction predicts. These findings support incorporating imaging-derived fibrosis pattern, and not only burden, alongside functional metrics when assessing thrombogenic risk in the LAA.

Devireddy et al. [1] previously showed that an enthalpy-based, macroscale model simulated tissue freezing histories are in close agreement with a coupled model incorporating cellular water transport and intracellular ice formation (IIF). That comparison, however, was performed for a limited set of tissue geometries, cooling conditions, and biophysical parameters. Here, we revisit that conclusion by reimplementing the published model from its governing equations and systematically expanding the parameter space to determine when microscale processes alter the predicted macroscale freezing response. We incorporate both surface catalyzed nucleation (SCN) and volume catalyzed nucleation (VCN) of intracellular ice with cellular osmotic dehydration and examine a broad range of tissue dimensions, cooling rates, convective boundary conditions, membrane permeabilities, cell sizes, activation energies, intracellular water fractions, and nucleation rates. Linearization of the cellular water transport equation about osmotic equilibrium yields an osmotic relaxation timethat can be compared with the local residence time of tissue undergoing phase change. Their ratio defines a dimensionless group, that organizes the transition between regimes in which the uncoupled enthalpy formulation and the coupled micro and macroscale formulation produce similar or substantially different results. Across the one-dimensional parameter space examined here, the two models remain within a prescribed thermal-error bound for the dimensionless group below approximately 0.1, whereas the discrepancy increases systematically above this threshold. Model divergence also depends on intracellular ice nucleation, i.e., when nucleation is sufficiently slow, cellular water transport can become rate limiting for latent heat release. Conversely, sufficiently rapid intracellular ice formation reduces the macroscopic discrepancy by providing an additional pathway for latent-heat release. Multidimensional simulations further show that geometry alone can move a nominally conventional freezing protocol into the coupled regime. In particular, multidirectional cooling can reduce the local residence time sufficiently to produce substantial differences in predicted frozen volume even when the corresponding thermal histories appear similar. Finally, we formulate an inverse approach for estimating IIF parameters from tissue scale thermal histories. Synthetic simulations indicate that parameter recovery is feasible within a finite range of cooling conditions, providing a testable strategy for future experimental measurements. Together, these results provide a mechanistic criterion for deciding when microscale biophysical processes must be retained in macroscale tissue-freezing models.

Fibrotic strictures are among the most disabling complications of Crohn's disease, permanently narrowing the bowel and impairing motility, yet no approved therapy reverses them. Chronic inflammation alters pacemaker-network coupling, smooth-muscle excitability, and calcium-dependent contractility, while fibrosis thickens the bowel wall, narrows the lumen, and changes tissue mechanics. The relative contributions of these coupled electrical, contractile, and structural alterations to motility loss remain unclear. To address this gap, we develop an integrated electromechanical finite-element framework for fibrostenosing Crohn's disease that couples a fibrosis-driven growth model with a FitzHugh-Nagumo electromechanical model. A full-factorial 25 design of experiments is used to quantify the relative effects of electrical diffusivity, excitation threshold, peak active stress, wall stiffness, and hypertrophic remodeling on cyclic lumen-volume deformation. Motility is quantified by the standard deviation of lumen volume over one contraction cycle. Within the parameter ranges examined, increased wall stiffness emerged as the dominant contributor to motility loss, followed by impaired smooth-muscle contractility. Changes in excitation threshold, hypertrophic remodeling, and electrical diffusivity produced substantially smaller effects. Pairwise interactions were small relative to the dominant main effects, indicating that the mechanisms contributed largely through their individual effects. Our findings suggest that limiting wall stiffening while preserving smooth-muscle contractile function may provide a therapeutic strategy for maintaining intestinal motility in fibrostenosing Crohn's disease.

Large shear deformation in cartilage can lead to tissue failure and injury, which are often precursors to diseases such as post-traumatic osteoarthritis. Under shear, cartilage strain-stiffens prior to failure, which makes stiffening an important indicator of changes to the loading of the extracellular matrix that gives rise to this tissue's properties. While a variety of stiffening mechanisms ranging from uncrimping to fiber-alignment have been explored, whether such mechanisms apply to the depth dependent shear strain stiffening in articular cartilage remains poorly understood. Here, we present experiments and theory that support the idea that the strain-stiffening behavior is caused by a mechanical phase transition from a random isotropic network whose mechanics arise primarily from bending-dominated modes to one where the mechanics arise from stretching-dominated modes. Indeed, consistent with network model predictions, we find that stress-strain data for all depths can be collapsed onto a single universal curve that diverges at a depth-dependent critical strain. These results show that increasing the local concentration of collagen, which constitutes the primary load-bearing network in cartilage, decreases the critical strain at which the strain-stiffening transition occurs, while increasing the low-strain elastic modulus. Furthermore, we demonstrate that bulk compression leads to a higher critical strain and decreased low-strain elastic modulus. Network simulations capture this rich behavior, and indicate that under compression the network collapses, which allows for larger strains before the transition from bending-dominated to stretching-dominated mechanics occurs. Collectively, these findings shed light on the roles that tissue composition and axial strain play in the mechanisms that organize how articular cartilage stiffens during the lead-up to injury.

Healing of the gastrointestinal (GI) tract following surgical interventions is governed by coupled mechanobiological processes and may lead to severe complications such as perforation or stricture formation. A first comprehensive mechanobiological modeling framework of GI healing is herein proposed. The framework addresses two clinically relevant applications of bioprinting: endoscopic treatment of GI tissue defects and bioprinting-assisted surgical anastomosis. Tissue remodeling is based upon a hyperelastic material model with fiber dispersion coupling the spatiotemporal reaction diffusion dynamics of fibroblasts and cytokines with collagen deposition, reorientation, and plastic deformation. An active stress formulation drives fibroblasts and myofibroblast contraction while a multiplicative decomposition approach is adopted for collagen remodeling as a permanent change. The governing equations are discretised in time with an implicit Euler scheme, finite element in space and solved by a staggered algorithm implemented in the open-source platform FEniCS. Numerical simulations show that the initial collagen fibers content and orientation strongly influence fibroblast infiltration and scar contracture formation. The study quantifies the advantage of having a collagen bioprinted architecture aligned with tissue fibers, to reduce structural remodeling distortion. The model also predicts a strong correlation between collagen deposition and luminal burst pressure during the recovery of mechanical integrity in GI anastomosis.

Allergic conjunctivitis is an inflammation of the conjunctiva caused by allergen; it is common disorder affecting up to 40% of the population. In this work, we study seasonal allergic conjunctivitis (SAC), also called "hay fever eyes", which is caused by exposure to airborne pollens. We develop a mathematical model quantifying the ocular immune system response to the allergens. First, we present a simplified qualitative description of the immunopathogenesis of SAC. Then, we express each chosen immunopathological mechanism mathematically to construct a system of thirty-one ordinary differential equations. We compare summary statistics of the predicted observable immune signals to experimental measurements and find our model captures key qualitative features of SAC progression. We then compare our predicted time series of histamine concentration to symptom scores and find a strong correlation suggesting the model predicts relevant clinically trends. Next, we calibrate the model through multi-step process. We find the most influential parameters are the production and depletion rates of IL-4, and the production rates of IL-5 and IL-8. These cytokines are targeted in treatments for asthma, atopic dermatitis, and severe eosinophilic associated disorder and suggest potential therapeutic targets for SAC. Our calibrated model mimics most of the summary statistics of the experimentally observable immune signals with discrepancies for IL-5 and IL-13 indicating that additional immunopathological mechanisms could be important.

The biomechanical properties of the human aorta play a key role in cardiovascular function and disease, yet their population-wide trends and variations remain largely unknown. To fill this crucial gap, we quantified variations in aortic size, stiffness and stresses across 57,434 individuals from the UK Biobank using two-dimensional cine MR imaging and a combined deep-learning, probabilistic and biomechanical modelling framework. Aortic diameter and distensibility (inverse of stiffness) were calculated for the ascending and descending aorta, and their conditional distributions were characterised as a function of age, sex, body size and blood pressure. These observations were integrated with ex-vivo tissue mechanics to infer stress distributions across the aortic wall and the associated uncertainty. Our analysis revealed several new relationships. Larger aortas were found to be stiffer, and greater body size (height and/or weight) was associated with larger aortas with no change in stiffness. Aortic distensibility was negatively associated with systolic, but not diastolic, blood pressure. Apparent sex differences in aortic size were substantially reduced after accounting for body size. Importantly, the maximum stress was found to depend not only on aortic size, as previously thought, but also on distensibility, with lower distensibility associated with higher stresses. The results provide first-of-their-kind population-scale reference distributions for human aortic stiffness, which will improve the personalisation of computational models and digital twins. The correlation between stress and distensibility strongly supports progressing beyond the current diameter-based criteria (based on the law of Laplace) and for the inclusion of stiffness in the clinical risk assessment of aortic diseases. Overall, this study forms the foundation for personalised quantitative medicine and biomechanically informed risk stratification of aortic aneurysms and dissections.

Cardiomyocyte contraction is essential for the pumping action of the heart and deteriorates after myocardial damage, either as a consequence of irreversible cardiomyocyte injury or stiffening of the extracellular matrix, a process described as fibrosis. Cell geometry and substrate stiffness not only influence sarcomere architecture and contractility, they also determine how much work the cardiomyocytes can transfer to their environment. Human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes provide a model system to examine these effects in a controlled manner, enabling us to mimic key features of the cardiac environment in vitro. Here we show that geometric confinement and substrate stiffness influence different aspects of cardiomyocyte force generation. By combining traction force microscopy and live-cell imaging of hiPSC-derived cardiomyocytes on soft and patterned substrates, we find that geometric confinement leads to longer resting sarcomeres and more pronounced sarcomere shortening on substrates with both physiological (10 kPa) and fibrotic (30 kPa) stiffness. Interestingly, the substrate stiffness itself has little effect on resting sarcomere length, but influences the peak contractile stress. On 10 kPa substrates, confined cells generate higher peak contractile stresses than unconfined cells, whereas this difference is not observed at 30 kPa. Confinement also results in faster mechanical relaxation at 10 kPa, with no detectable difference at 30 kPa. The combination of defined cell geometry and physiological stiffness leads to longer resting sarcomere lengths, more pronounced sarcomere shortening, higher peak contractile stress, and faster relaxation, features associated with a more mature cardiomyocyte phenotype. These findings show that the mechanical consequences of cell geometry depend on substrate stiffness and, therefore, both aspects have to be considered when employing hiPSC-derived cardiomyocytes as a model system in mechanobiology research, disease modeling and drug testing.

A densely vascularized tissue can still be starved of oxygen. Tissue oxygenation depends heavily on vessel arrangement, blood flow distributions, and cellular metabolism. Resolving these effects from individual constituent vessels to whole organs has historically been computationally prohibitive. We introduce the Cardiovascular Analysis and Simulation of Circulatory Advection, Diffusion, and Exchange (CASCADE) toolkit, which makes vessel-resolved oxygen transport tractable at the organ scale through a novel screened Green's-function formulation. On laptop-class hardware, CASCADE simulates networks containing thousands of vessels in under one second and a full biventricular human heart model in about two minutes. We validate spatial oxygen and cell-survival predictions against experiments in perfused engineered tissues and matched finite-element simulations. In engineered tissues, sweeps across thousands of network designs and physiological conditions reveal when vessel density, oxygen supply, or network architecture limits viability, establishing design rules for sustaining thick constructs. In a human heart model, CASCADE translates coronary occlusion, anemia, polycythemia, and hypoxemia into distinct myocardial oxygenation patterns, revealing where oxygen delivery fails and how much tissue is at risk.

Introduction: The femoropopliteal artery undergoes substantial axial compression, bending, torsion, and pinching during limb flexion. When an implanted stent does not accommodate these deformations, repetitive biomechanical mismatch may alter the vascular response to implantation and contribute to restenosis. We tested whether designing a peripheral stent to better accommodate physiologic limb-flexion deformation reduces the subsequent inflammatory and neointimal response. Methods: A nitinol stent was developed using multi-objective computational optimization to maintain arterial apposition while reducing wall stress and luminal pinching during physiologic deformation. Sixteen Yucatan minipigs were studied in independent 3- and 6-month cohorts (n=8 each). Each animal received the optimized stent in one limb and a commercial stent with representative biomechanical behavior contralaterally. CTA quantified in vivo limb-flexion deformation, while CT and histology assessed stenosis, neointimal accumulation, inflammatory-cell burden, SMA-positive tissue, and extracellular-matrix composition. Results: The optimized stent accommodated greater axial shortening than the commercial comparator at both 3 months (11.2{+/-}2.7% vs. 6.6{+/-}2.1%, p=0.003) and 6 months (13.7{+/-}4.4% vs. 6.8{+/-}2.3%, p=0.004). Intimal hyperplasia volume was lower with the optimized stent at 3 months (227.5{+/-}85.2 vs. 350.0{+/-}130.5 mm3, p=0.002) and 6 months (183.6{+/-}46.2 vs. 261.2{+/-}60.6 mm3, p=0.001), with significantly lower maximum, mean, and median stenosis at both timepoints. At 3 months, macrophage and total inflammatory-cell counts were 51% and 45% lower, respectively, with the optimized stent. Histologic tissue area was 28% lower at 3 months and 12% lower at 6 months. SMA-positive tissue fraction was higher with the optimized stent at both timepoints, whereas elastin, glycosaminoglycan, and collagen fractions were similar between devices. Discussion: Improved accommodation of limb-flexion deformation was associated with a smaller inflammatory and neointimal response to stent implantation through 6 months, while overall neointimal matrix composition remained largely unchanged. These findings provide in vivo evidence that biomechanical compatibility with the dynamic lower-limb environment can influence vascular healing and should be considered a mechanistic design criterion for peripheral artery stents.

Mitochondrial reactive oxygen species (ROS) are implicated in cardiac dysfunction, but complex dynamic interactions between ROS, intracellular calcium, and electrophysiology make it difficult to resolve mechanisms experimentally. We developed the Zukowski excitation-contraction-mitochondrial-ROS (ECM-ROS) model, a computational model that couples human ventricular electrophysiology with mitochondrial calcium handling, energetics, ROS production, and ROS dependent modulation of the ryanodine receptor, SERCA, L-type calcium current, and late sodium current. Model predictions were evaluated against independent experimental measurements of ROS induced changes in action potential duration and intracellular calcium. We then used the model to characterize ROS calcium feedback across physiological pacing rates and applied it to doxorubicin induced oxidative stress. Increasing cytosolic calcium produced nonlinear amplification of mitochondrial activity and cytosolic ROS, with greater amplification at faster pacing rates. Moderate ROS elevation initially enhanced calcium release, whereas greater oxidative stress depleted sarcoplasmic reticulum calcium stores. During simulated doxorubicin exposure, faster pacing lowered the level of oxidative stress required to produce calcium dysregulation and action potential prolongation. Mitochondrial ROS and calcium accumulation preceded detectable electrophysiological remodeling. In populations incorporating variability in ion channel expression, neither doxorubicin induced oxidative stress nor subtle pharmacological IKr block alone produced early afterdepolarizations. However, early afterdepolarizations were predicted to emerge with combined perturbations. These findings establish a computational framework for investigating bidirectional coupling among mitochondrial function, ROS, calcium handling, and human cardiac electrophysiology. The model generates testable predictions regarding the early detection of oxidative cardiac injury and the physiological conditions that increase susceptibility to arrhythmia.

Bone strain and remodeling are important factors for bone health. Improved characterization of relationships between these factors in response to acute loading will improve our understanding of bone maintenance, adaptation to load, and pathophysiology. The purpose of this study was to evaluate colocalization between finite-element-estimated bone strain and [18F]sodium fluoride positron emission tomography imaging-estimated subchondral bone remodeling in the tibial diaphysis in response to acute exercise. We hypothesized that the exercise-induced change in standardized uptake values would be greatest in regions of higher strain. 26 participants underwent bilateral positron emission tomography/magnetic resonance scans before and after a bout of stair ascent and descent exercise. Finite element analysis was performed to calculate principal strain distributions in the tibial diaphysis. [18F]sodium fluoride standardized uptake values were calculated from pre- and post-exercise positron emission tomography data and mapped to the tibial surface. Mean pre-exercise and exercise-induced change in standardized uptake values were calculated and compared between regions defined by strain percentile. Both normalized mean pre-exercise and exercise-induced change in standardized uptake values increased with maximum principal strain in a pattern suggesting an exponential relationship. Pre-exercise and exercise-induced change in standardized uptake value were notably much greater in the region of highest maximum principal strains (estimated marginal means = 76.9 and 71.0 percentile, respectively) when compared to all other regions of the tibial diaphysis ([&le;] 61.1 and [&le;] 57.0 percentile, respectively, p < 0.001). This study is the first to directly show a relationship between bone mechanical loads and acute [18F]sodium fluoride uptake in humans in vivo. Our results highlight the influence of tensile strain magnitude on bone metabolic activity in response to acute loading. Furthermore, we demonstrate the utility of a combined finite element analysis and positron emission tomography approach to interrogate relationships between bone loading and bone metabolic response to acute exercise.

Computational models of the middle ear are typically developed within the linear range of the middle ear's response, which corresponds to typical sounds in daily life. Understanding middle-ear biomechanics under high-intensity sounds is also important for assessing potential auditory damage under adverse conditions. In this study, a finite-element (FE) model of the human middle ear plus the external ear canal is presented, employing a first-order Ogden hyperelastic material formulation and time-domain nonlinear analysis to capture nonlinear deformation of soft tissues and the resulting middle-ear response. The model was analyzed using pure-tone pressure excitations applied at the ear canal entrance over the 80 Hz to 8 kHz frequency range and 110 to 180 dB sound pressure levels (SPL). The ear canal pressure near the tympanic membrane (TM) and full-field three-dimensional response of the middle ear structures were examined. Across the investigated frequency range, the simulated middle-ear motion exhibited a transition from predominantly piston-like behavior at low frequencies, up to 1 kHz, to increasingly intricate multi-modal and multi-directional vibration patterns at higher frequencies. Nonlinear behaviors became increasingly significant at high frequencies and high stimulus levels, including compressive/expansive pressure-displacement relationships, waveform distortions, and the emergence of non-harmonic spectral components. The model developed in this study provides a computational framework for studying nonlinear sound transmission through the middle ear and its implications for high-intensity acoustic exposure. The findings contribute to a better understanding of middle-ear mechanics under adverse conditions and support future investigations of acoustic trauma and hearing protection strategies.

Understanding the relationship between weather conditions and infectious disease transmission has important public health implications; nevertheless, the functional form of this relationship often remains poorly understood. Humidity has previously been suggested to have a U-shaped effect on the transmission of respiratory pathogens, with optimal transmission occurring at both low and high levels. Here, to assess the impact of this functional form and of its potential misspecification, we first simulate transmission rates based on the U-shaped relationship and then test whether an exponential function accurately estimates these rates across a range of climates. We further use a transmission model to simulate case count data for a range of hypothetical pathogens, comparing outbreak dynamics under the U-shaped forcing function to those under the best-fit exponential approximation. In our simulations, the model fit for the exponential function is climate-dependent, performing best in very dry and very humid environments. In locations where specific humidity values centre around the vertex of the U-shaped function, the exponential model underestimates the amplitude and frequency of incidence peaks. These findings demonstrate the potential consequences of assuming an incorrect functional form for weather-infectious disease relationships and highlight the need for more careful consideration of this functional form in modelling practice.

Adherent cells must continuously adapt to rapid environmental fluctuations to preserve mechanical integrity. However, conventional theoretical frameworks predominantly rely on quasi-static assumptions, thereby limiting their ability to capture the transient dynamics of cellular responses to high-rate perturbations, such as acute osmotic shocks. To address this limitation, we developed a biophysical model incorporating a Hill-type law that couples active cytoskeletal mechanics to cell-edge velocity, explaining the counterintuitive experimental observation that traction forces transiently decrease during rapid hypotonic swelling despite an increase in cell size. We further construct a kinematic-geometric phase diagram that connects classical quasi-static theories with our dynamic model. Moreover, we show that traction-force dynamics are sensitive to the loading rate and amplitude of osmotic shock. In addition, stiffness-associated simulations and supporting perturbation evidence suggest a cellular stiffness-associated recovery trend in which stiffer cells exhibit faster volume recovery driven by stronger recoil of hydrostatic pressure.

Background: Hypertension is a major risk factor for type B aortic dissections and rupture, with guidelines recommending systolic blood pressure (SBP) control below 130 mmHg to improve outcomes. While post-TEVAR blood pressure is often managed with a focus on mean SBP, little is known about temporal hemodynamic patterns and their association with surgical success. This study investigates blood pressure and heart rate (HR) time-series metrics within 24 hours post-TEVAR and their predictive potential for outcomes. Methods: Blood pressure (n = 560) and HR (n = 680) time-series data from 31 patients were analyzed alongside preoperative aortic geometry metrics. Exploratory data analysis identified correlations between BP variability and outcomes. Stationarity tests were performed on time-series data to assess statistical properties. Logistic regression models incorporating hemodynamic metrics, along with CT-derived features, were used to predict TEVAR outcomes. Results: Successful outcomes correlated with greater diastolic blood pressure variability and strictly stationary SBP. Logistic regression models combining these metrics along with heart rate standard deviation and preoperative aortic geometry achieved 96.67% 5-fold cross-validation accuracy in predicting outcomes. Conclusion: Post-TEVAR behaviors of hemodynamic variables are critical predictors of TEVAR success, with higher DBP standard deviation and strict stationarity of SBP significantly associated with favorable outcomes. These findings highlight the importance of hemodynamic variability and stationarity in optimizing post-TEVAR patient care.

Crank length affects the geometry of the bicycle-rider system and influences the motion of the lower limb throughout the pedal cycle. Conventional crank selection has largely relied on rider stature and mechanical power, yet mechanical power and cycling economy remain remarkably insensitive to crank length across a broad range. Yet, elite cyclists and triathletes increasingly adopt shorter cranks, particularly in disciplines where aerodynamic drag strongly affects cycling performance. However, the mechanisms that connect crank length to mechanical power and aerodynamic drag remain unclear. Here we show that crank length couples rider anthropometry, hip kinematics, and aerodynamic drag. Population anthropometry of 6,068 individuals reveals that stature alone poorly predicts personalized crank length, while geometric analysis identifies a nearly linear relationship between crank length and minimum lower hip angle: a 10-mm reduction in crank length increases hip-angle margin by approximately 1.42 degrees with little mechanical penalty. This geometric freedom permits more flexion of the torso and a more aerodynamic posture; the resulting aerodynamic advantage grows rapidly with cycling speed because aerodynamic power scales with velocity cubed. Data from 150 elite cyclists and triathletes support this shift toward shorter cranks, with triathletes adopting shorter relative crank lengths than cyclists. Our results establish crank length as a personalized design variable that connects lower-limb geometry to aerodynamics. These insights enable personalized crank selection, integrated rider-bicycle design, and performance optimization for the increased aerodynamic demands of high-speed cycling.