Biomechanics and Modeling in Mechanobiology

Residual stresses in arteries are commonly revealed by the opening of a ring after a radial cut. Glycosaminoglycans (GAGs) contribute to this response, but fixed-charge-density (FCD)-driven Donnan swelling alone does not fully explain the opening-angle reduction measured after enzymatic GAG depletion. We therefore tested whether the transmural FCD profile defines a removable preferred-stretch field superposed on a structural field retained after GAG depletion. A reduced analytical-computational axisymmetric closure framework was applied to regional-average measurements from the ascending aorta, arch, and descending porcine thoracic aorta. Each control state was fitted using its measured circumferential opening angle, geometry, material properties, and through-wall FCD profile. GAG depletion was represented by removing the FCD-linked preferred-stretch component. One coefficient governing this removable component was selected jointly from the three measured regional post-depletion angles. A one-layer wall was the primary parsimonious model; a two-layer wall tested anatomical robustness. The one-layer model fitted a shared coefficient of -1.4226 x 10-3 (mEq/L)-1 and predicted depleted angles of 82.639{degrees}, 44.032{degrees}, and 19.979{degrees}, compared with measured values of 85{degrees}, 41{degrees}, and 18{degrees} (three-region RMSE 2.50{degrees}). The two-layer model fitted -1.51746 x 10-3 (mEq/L)-1 and predicted 82.972{degrees}, 44.273{degrees}, and 18.534{degrees} (RMSE 2.24{degrees}). Thus, layer differentiation improved aggregate fit only modestly. These findings support a parsimonious mechanism in which GAG depletion removes an FCD-shaped circumferential preferred-stretch component while most residual-stress architecture remains in a structural field retained after depletion. Donnan swelling remains mechanically relevant, but it is insufficient alone to explain the measured regional response. Statement of SignificanceGlycosaminoglycans are charged extracellular-matrix constituents that influence arterial residual stresses through osmotic effects and interactions with the fibrous matrix. We tested whether the through-wall FCD pattern also plays a role in the development of residual stresses and can be modeled as a removable circumferential preferred-stretch component. One coefficient linking that pattern to the GAG depletion response explained the post-depletion opening angles of the ascending aorta, arch, and descending aorta within 3.3{degrees} using a one-layer model. A two-layer model improved aggregate error only modestly. The result provides a compact mechanistic link between extracellular-matrix composition and residual opening without requiring a separately fitted GAG effect in each region.

Constitutive models of myocardial mechanics form a cornerstone of personalized cardiac simulations and cardiac digital twins. Researchers traditionally prescribe these models a priori and calibrate them from ex vivo tissue experiments, even though tissue excision alters loading conditions, removes residual stresses, and eliminates important physiological interactions. Multimodal cardiac MRI now provides subject-specific ventricular geometry, deformation, and myocardial microstructure, yet current inverse approaches still rely on predefined constitutive laws. Here we present the first framework to discover constitutive models of passive myocardial mechanics directly from in vivo cardiac imaging data by embedding a constitutive artificial neural network within a nonlinear finite element model of ventricular filling. Using multimodal cardiac MRI that combines ventricular geometry, deformation, and microstructure from a representative healthy individual, the framework identifies sparse, mechanically admissible strain-energy functions without prescribing their form a priori. The best-performing model contains only two fiber- and two sheet-invariant terms, achieves a mean displacement error of 1.62 mm, and reduces the error of the widely used Guccione and Holzapfel models by 34.14% and 26.01%. The discovered models indicate that fiber- and sheet-related anisotropic mechanisms dominate the passive mechanical response during physiological ventricular filling. More broadly, this work establishes a non-invasive strategy for subject-specific constitutive discovery from cardiac imaging data and lays the foundation for personalized cardiac simulations and cardiac digital twins.

PurposeComputational models of the uterus during pregnancy enable analysis of electro-chemo-mechanical pathways to predict labor timing and guide treatment planning. We aim to develop a robust image-based modeling pipeline to investigate uterine passive mechanics during late pregnancy. MethodsA parametric model of the uterus and cervix was created using a patients MRI measurements at 38 weeks of gestation. Inspired by advances in cardiac mechanics models, we created Laplace-Dirichlet solutions to inform tissue domains, fiber structure within the uterus and cervix, and spatially varying Robin boundary conditions. Prior imaging and mechanical testing data were used to fit material parameters. Boundary condition parameters were tuned to match the displacements of a previously established approach that employed contact with surrounding tissue. The tissue mechanical response to a physiologic load was assessed across varying material properties and fiber architectures. ResultsDiscrepancies in nodal displacements between the current approach and the contact-based model were limited to 3.4 {+/-} 1.8 mm, yielding nearly 90 % computational savings. Uterine tensile strains were more sensitive to ground substance elastic modulus (E) compared to fiber properties. Reduced E and fiber stiffness increased cervical strains and compression. Fiber dispersion and architecture modulated the opening of the cervical internal ostium but had a reduced impact on compression. ConclusionWe developed a novel workflow for modeling passive uterine mechanics, informed by patient-specific measurements and in vitro mechanical tests. The robust workflow may prove useful for studying labor progression and conducting longitudinal studies to enhance our understanding of normal and pathological pregnancies.

Tumor spheroid mechanics arise from both the mechanical properties of individual cells and the adhesive interactions that organize them into tissues. The relative contribution of these two factors to the bulk mechanical behavior, however, remains difficult to disentangle experimentally. Here, we develop a computational model of micropipette aspiration to compare the mechanical response of isolated cells and multicellular spheroids within a common computational framework. By independently varying single-cell stiffness and cell-cell adhesion, we quantify their effects on aspiration dynamics, effective elastic modulus, and viscoelastic relaxation. Our results show that increasing single-cell stiffness substantially alters the mechanics of isolated cells but has limited influence on the effective elastic modulus of multicellular spheroids. In contrast, changes in cell-cell adhesion produce pronounced effects on spheroid effective elastic modulus. Nevertheless, both parameters increase the retardation time governing the transition from the initial elastic response to long-time viscous deformation. These findings suggest that multicellular elasticity is governed primarily by intercellular mechanical coupling, whereas the dynamical response to applied stress depends jointly on cell-scale mechanics and cell-cell adhesion.

Cerebral aneurysms are abnormal outpouchings of arteries within the brain and occur in [~]1 in 30 adults. Their initiation, growth, and rupture have been linked to focal blood flow abnormalities--often termed "disturbed" or "hostile" hemodynamics--but commonly-used hemodynamic metrics yield conflicting associations with pathology and lack a unifying mechanistic interpretation. Building on a theoretically-grounded link between wall shear stress and near-wall vorticity, we hypothesized that a topology-based description of near-wall flow can operationalize the concept of hostile hemodynamics in a reproducible way. Inspired by atmospheric tornadic phenomena, we sought a principled taxonomy of coherent near-wall fluid structures with potential mechanobiological and clinical implications. Using high-fidelity computational fluid dynamics simulations in anatomically realistic geometries, we identified coherent near-wall fluid structures whose organization mirrors well-studied atmospheric phenomena: tornado-like columnar rotating cores; downburst-like nonrotating wall-impinging jets with tangential outflow, roll-cloud-like tangential vortices; and mixed configurations. These tornadic events on the aneurysm luminal surface were identified from wall shear stress topology, consistent with its theoretical connection to near-wall vorticity kinematics. The presence of tornadic phenomena--and their imprints on the aneurysm wall--was independently observed in vivo using 4D flow magnetic resonance imaging. By translating concepts from atmospheric physics into vascular biomechanics, this topology-based framework yields a unified mechanistic language for describing near-wall hemodynamics, resolving blood flow complexity into interpretable and reproducible coherent fluid structures, enabling standardized hemodynamic phenotyping, and supporting hypothesis-driven studies of aneurysms and other cardiovascular diseases where greater fluid-mechanical specificity and interpretability may strengthen links between mechanobiology and clinical risk.

The podocyte foot process network forms the final barrier of the kidneys glomerular filtration system. Under mechanical stress this network is prone to injury in which podocytes lose connectivity to their neighbors and begin the progression toward effacement, but what governs its mechanical resilience is unknown. We show that the network is built like a lap joint: two major processes coupled through interdigitating foot processes, a configuration that behaves as a classical shear lag system, with force concentrating at the joint ends and decaying over a characteristic transfer length set by geometry and stiffness. A discrete network model reproduces the continuum shear lag solution and identifies a hierarchy among governing parameters, with cytoskeletal stiffening of the major process amplifying foot process force more potently than basement membrane stiffness. Applying the model to morphometric data from puromycin aminonucleoside nephrosis, a model of human minimal change disease and early focal segmental glomerulosclerosis, reveals a mechanical positive feedback loop: force concentration drives foot process loss, which raises force on surviving segments and accelerates further loss. This nonlinear amplification implies a threshold beyond which failure becomes self-sustaining, analogous to the critical crack length in fracture mechanics.

Acute subdural hematoma (ASDH) is a prevalent injury with high mortality and morbidity, often resulting from bridging vein (BV) disruption secondary to cortical relative motion. As a thin membrane enveloping the brain surface and anchoring BVs, the pia mater is hypothesized to play a critical mechanical role in cortical response and hence ASDH pathogenesis. Finite element (FE) head models are valuable tools to predict ASDH occurrence during impacts. However, the pia mater is often represented as an elastic material in existing FE head models, despite experimental evidence reporting its nonlinear mechanical behavior. In this study, both linear (Young's modulus of 11.5 MPa) and nonlinear (the stress-strain curve derived from pial tension tests) material models of the pia mater were implemented in one FE head model. The models were subjected to three experimental impact loadings, one of which was known to cause ASDH and two of which were not. Results demonstrated that, across all simulated impacts, the model with nonlinear pia mater properties predicted larger cortical displacements and BV responses than the linear model. For the impact with known ASDH occurrence, the predicted BV strain was 0.17 for the nonlinear model and 0.094 for the linear model, with only the former approaching the reported rupture strain range of the BV-superior sagittal sinus complex (0.29 {+/-} 0.13). These findings verified the mechanical importance of the pia mater in cortical responses and hence the prediction of ASDH, suggesting that conventional linear pia modeling might over-constrain cortical motion, leading to underestimation of BV strain and ASDH risk. The current study supported the adoption of experimentally derived nonlinear pia mater properties in FE head models to improve the reliability of ASDH prediction.

The cytoskeleton is a dynamic biopolymer network whose shear rheological properties are crucial for cellular physiology and pathology. However, its mechanical behavior spans multiple spatiotemporal scales, and the coupling of dynamic remodeling and viscoelastic dissipation mechanisms poses a challenge for traditional models to comprehensively capture complex cellular responses. This study aims to establish a multiscale cytoskeletal network model that integrates the bio-chemo-mechanical properties of local linked proteins, the viscoelasticity of actin filaments, and their deformation states. Developing a boundary-modified finite element method with an incremental iterative algorithm, we demonstrated the dynamic remodeling of network and the resultant rheological properties of cytoskeleton by extending the predictive time scale to one thousand seconds. The results not only reproduced the short- and intermediate-term power-law creep behavior and long-term strain plateau response of the cytoskeletal network observed in shear rheological experiments, but also indicate that the synergy among the chemo-mechanical coupling of cross-linked proteins and the bending-to-tension transition of actin filaments govern both the network remodeling and its power-law response evolutionary, whereas the steady-state properties of actin filaments determine the long-term network behavior. Simulations of cancerous and drug effects show that cancer-induced softening and reduced filament viscosity lead to accelerated cytoskeletal responses and decreased apparent shear modulus, respectively; and drug-enhanced filament prestress, along with promoting association or inhibiting dissociation of cross-linked proteins, can effectively increase the steady-state shear modulus. These findings advance the understanding of the spatiotemporal evolution and pathological mechanisms of cellular mechanical responses and provide insights for regulating polymer network performance.

Pulmonary hypertension (PH) is characterized by progressive structural and mechanical remodeling of the pulmonary vasculature, yet few computational frameworks directly link disease mechanisms to longitudinal progression and therapeutic response. In this study, we utilized a multiscale pulmonary arterial growth and remodeling (G&R) framework to capture evolving functional metrics from rat models of PH. This framework couples morphometric tree hemodynamics, constrained mixture theory-based wall mechanics, and maladaptive cellular remodeling. Disease progression was driven by three mechanistically interpretable parameters governing excess smooth muscle production, remodeling activation, and passive stiffening. These parameters were calibrated to longitudinal monocrotaline (MCT) measurements of pressure, wall thickness, and stiffness from prior work using a multiobjective optimization. To show the predictive value of this model, we simulated therapeutic intervention within the same disease-specific framework by using functional cell-level responses to therapy to inform changes in parameter values. Calibration to the study-specific MCT dataset reproduced the temporal increases in pressure, wall thickness, and stiffness, demonstrating that the model could capture multiple features of vascular remodeling simultaneously, with R2 values of 0.81, 0.83, and 0.95, respectively. Simulated treatment reduced pressure, wall thickness, and stiffness. Predicted pressure and wall-thickness responses agreed closely with the corresponding experimental treatment effects, whereas stiffness recovery was overpredicted, suggesting that additional mechanisms may contribute to persistent vascular stiffening after intervention. The framework also captured the overall progression of pulmonary pressure increases across both aggregated MCT and Sugen-hypoxia datasets, suggesting utility across studies and animal models. This work outlines a physics-based, multiscale framework that simulated quantities of direct clinical interest in a mechanistically interpretable platform for linking pulmonary vascular remodeling and treatment response. It supports comparisons across experimental phenotypes and interventions while identifying where constitutive refinements are needed to improve predictive capability across phenotypes.

Integrins are adhesion proteins that diffuse along the cell membrane, bind to ligands, and cluster with each other in the early stage of cell adhesion. Integrin clustering and its specific spatial distribution play important roles in subsequent biological processes; however, the mechanisms that give rise to their characteristic spatial distribution remain poorly understood. To address this issue, we developed a cell adhesion model that incorporates cell membrane deformation and integrin dynamics. A hybrid continuous/discrete model was applied to represent membrane deformation, whereas Brownian dynamics combined with a transition state model was used to describe integrin dynamics and binding kinetics. Comparison of numerical simulations of cell adhesion to a substrate with experimental observations at the early stage of adhesion successfully reproduced the characteristic spatial distribution of integrin clusters, in which high-density clusters formed at the periphery of the region adhering to the substrate. These results suggest that the cellular-scale distribution of integrin clusters can be reproduced using only minimal elements, such as adhesion-driven membrane deformation and integrin-ligand binding. In addition, we found that the strength of integrin-ligand binding regulates the degree of clustering by changing the size of the part of the membrane that is deformed, thereby mechanically supporting the mechanical involvement of the actin cytoskeleton in integrin clustering. Furthermore, the formation and spatial distribution of integrin clusters were shown to be determined not only by the static mechanical equilibrium of membrane deformation and physical adsorption, but also by membrane spreading/deformation and the dynamic behavior of integrins. This suggests that the size and spatial distribution of integrin clusters may be controllable by modulating the speed of membrane spreading.

Cerebrovascular pulsatility drives measurable brain tissue deformation and has been associated with ageing and a range of neurological disorders. Yet how pulsatile haemodynamic forces are transmitted through deformable cerebral arteries into the surrounding brain remains poorly understood, particularly in anatomically realistic vascular geometries. Existing computational approaches have largely treated cerebral fluid and tissue mechanics separately or relied on idealised geometries, limiting our ability to determine how vascular anatomy simultaneously governs intraluminal haemodynamics and extravascular mechanical loading. Here, we develop an image-derived three-dimensional computational framework that jointly resolves pulsatile blood flow, arterial wall deformation and surrounding brain tissue motion in representative cerebral arteries. Four arterial segments, including the middle cerebral artery, middle cerebral artery bifurcation, basilar artery and internal carotid artery, are reconstructed from high-field (5 Tesla) magnetic resonance imaging data of a healthy subject. A finite-deformation fluid-structure interaction model is established by coupling non-Newtonian blood flow, hyperelastic arterial wall and hyper-viscoelastic brain tissue. The predicted tissue response is benchmarked against in vivo magnetic resonance elastography measurements of cardiac-induced volumetric strain over a cardiac cycle. Results reveal spatially localised arterial and tissue deformation whose magnitude and distribution are strongly governed by vascular geometry and wall thickness. Among the segments examined, the internal carotid artery exhibits the largest deformation response, while reduced wall thickness increases strain transmission into the surrounding tissue. Geometrically complex regions also exhibit greater spatial heterogeneity in near-wall haemodynamic metrics. These findings demonstrate that cerebral vascular anatomy simultaneously shapes intraluminal haemodynamics and extravascular mechanical loading. By integrating image-derived vascular anatomy, coupled blood-vessel-brain mechanics and in vivo benchmarking within a unified framework, this study provides a mechanically consistent reference for healthy cerebral pulsatility and establishes a foundation for quantifying how blood-vessel-brain interactions are altered under pathological conditions.

In the current clinical practice, the diagnosis of spinal disorders and their surgical planning are critically based on imaging data. To complement this data, patient-specific finite element models have been developed and showed to be powerful tools for evaluating spine mechanics. Most of them rely on Computational Tomography (CT) scans - which have a high resolution but are seldom available in routine clinical practice - while only a recent few models are on less invasive Magnetic Resonance Imaging (MRI). Yet, despite the proliferation of these computational models, encompassing detailed anatomical and functional information, the rheological assumptions they are built upon are based on tissue-sample mechanical response data, which leaves a gap in the quantitative analysis on how such assumptions influence the macroscopic response of a functional spinal unit. Aiming at addressing these shortcomings, the main purpose of this work is to introduce a quantitative computational assessment of the macroscopic impact of commonly adopted rheological models - from linear elasticity to fiber-reinforced nonlinear hyperelasticity - in several loading conditions, focusing on a lumbar unit which is considered as a typical benchmark system. We also propose a reconstruction procedure to accurately describe subject-specific anatomy from MRI data, including the intervertebral disc and its nucleus pulposus. Bones are modeled as linear elastic media, whereas for the AF, we consider three different mechanical models - namely, isotropic linear elasticity and the Holzapfel-Gasser-Ogden model with and without fiber reinforcement. Model verification on an idealized geometry demonstrates numerical consistency, while parametric orthostatic simulations highlight the need for nonlinear formulations to capture anisotropy and strain-stiffening behavior of the intervertebral disc. Then, we carry out flexion, lateral bending, and torsion tests on a subject-specific reconstructed functional unit, for which we provide parametric analysis in terms of momentum magnitude and resulting range of motion. These tests further confirm the need for a nonlinear rheology of the annulus fibrosus and provide a quantitative assessment of the differences between the constitutive laws considered. Moreover, successful comparisons with the literature, in terms of macroscopic deformation under several loading conditions, serve as partial validation for our computational model.

Purpose: Fibrotic remodeling of the uterus, associated with aging, disease, and environmental exposures, alters collagen organization and tissue stiffness, yet how these changes influence organ-level mechanical behavior remains poorly understood. Glutaraldehyde (GA)-induced collagen crosslinking was used as a controlled surrogate for fibrotic remodeling to determine whether image-informed inverse finite element analysis (iFEA), combined with inflation testing and micro-computed tomography (microCT), could detect and quantify the resulting changes in uterine constitutive behavior. Methods: Murine uteri (n = 6 untreated, n = 6 GA-crosslinked) underwent volume-controlled balloon inflation with simultaneous microCT imaging to quantify deformation of the inner and outer wall boundaries for iFEA. Specimen-specific Gasser-Ogden-Holzapfel (GOH) finite element models were optimized by adjusting model parameters to reproduce experimentally measured wall contours throughout inflation. Model performance was evaluated using contour root mean square error (RMSE), and parameter identifiability was assessed through sensitivity analyses. Results: GA treatment significantly increased inflation work, linear stiffness, and maximum inflation resistance (p < 0.001). The iFEA framework accurately reproduced experimental deformation (RMSE < 3%) and revealed significant increases in the estimated GOH parameters C10 (9.2-fold), k1 (2.0-fold), and k2 (2.7-fold), consistent with increased effective tissue stiffness and a shift toward earlier collagen fiber recruitment. Sensitivity analyses demonstrated unique, well-defined minima for all parameter combinations. Conclusion: Image-informed iFEA provides a quantitative framework for relating collagen remodeling to organ-level uterine mechanics through specimen-specific constitutive parameter estimation. This approach establishes a foundation for investigating the mechanical consequences of uterine fibrosis and other remodeling processes.

Background and objectiveMusculoskeletal joint disorders often show inconsistent relationships between structural degeneration and nociceptive pain. Temporomandibular joint (TMJ) disc displacement represents a clinically relevant model for investigating the structure-function-pain relationship. This study aimed to develop a multiscale computational framework integrating biomechanics, three-dimensional (3D) neural morphology, and electrophysiology to quantitatively link TMJ structural alterations, biomechanical loading, and peripheral nociceptive activation. MethodsStrain distributions in the TMJ disc and retrodiscal tissue during mouth opening and clenching were computed in ArtiSynth under varying degrees of displacement. Human TMJ 3D nerve architecture was reconstructed using porcine TMJ nerve mapping data as an anatomical reference, and ion channel dynamics were implemented in NEURON. Model coupling was achieved by mapping biomechanical strain fields onto nociceptor membranes to simulate mechanosensitive currents and action potential propagation to the trigeminal ganglion. ResultsAnterior DDwoR induced a severity dependent strain pattern in the TMJ disc and retrodiscal tissue, including posterior redistribution, increased strain magnitude, prolonged activation, and broader retrodiscal tissue involvement. Displacements of 4, 6, and 8 mm produced larger mechanosensitive currents, broader terminal depolarization, and higher trigeminal firing rates during mouth opening (6, 18, and 28 Hz) and clenching (8, 20, and 28 Hz), whereas 0- and 2-mm displacements produced negligible neural activation. ConclusionsThis study establishes a multiscale biomechanical-electrophysiological framework linking TMJ structural alterations to peripheral nociceptive activation. The framework quantitatively connects macroscale strain patterns with microscale neural activation, suggesting that anterior disc displacement may amplify peripheral nociceptive signaling by increasing the overlap between elevated strain and densely innervated retrodiscal tissue.

PurposeFunctional tricuspid regurgitation (FTR) is driven by right ventricular (RV) remodeling, annular dilation, and papillary muscle dislocation. Free wall approximation (FWA) has been proposed to treat FTR by addressing RV dilation, but its effects on tricuspid valve (TV) biomechanics remain unclear. We present a real-time 3D echocardiographic (rt3DE)-based finite element framework to quantify TV biomechanics under FTR, and preliminarily apply it to assess FWA effects. MethodsSubject-specific models were developed from rt3DE data of three dilated porcine hearts in an ex-vivo mock-loop. TV geometries at end-diastole and peak systole (PS) were complemented by parametric chordae tendineae and hyperelastic tissue properties. TV closure was simulated under a standard pressure load and image-based annular motion. After tuning chordae length to replicate the PS ground truth in FTR, FWA was simulated as 30% and 60% approximations along three anatomical directions (anterior-posterior, A-P; anterior-septal, A-S; anterior-septal wall, A-SW). ResultsIn FTR simulations, median geometric errors ranged from 1.16 to 1.26 mm; median stress ranged from 56.4 to 74.7 kPa. FWA simulations predicted regurgitant orifice area (ROA) reductions by 53-99%, albeit overestimating the residual ROA vs. in vitro ground truth when starting from particularly extreme FTR conditions; concomitantly, a median stress reduction by 8-43% vs. FTR conditions was predicted. ConclusionPreliminary data suggest that our rt3DE-based framework can reliably quantify FTR-related TV biomechanics and that post-FWA biomechanics depends on initial FTR conditions. A larger cohort is required to verify the method and obtain statistically significant results.

PurposePatient-specific models of left atrial (LA) mechanics often assume uniform left atrial wall thickness (LAWT), but the effect of LAWT on the mechanics and hemodynamics remains less quantified. MethodsFour LA myocardium models were built from gated CTA images: a baseline variable thickness (VT#0), two reduced-dilation variants, and a 2mm uniform thickness model. Multi-scale mechanics and blood flow simulations were performed across all the thickness variants using model parameters personalized on the baseline model. Predicted displacements, wall stresses and strains, and hemodynamics were compared. ResultsAcross all LAWT variants, myocardial volume spanned 14.4-19.9mL (38%), while cavity volume remained mostly within 5% of image data throughout the cardiac cycle. Circulatory system output, myocardial displacements, and strains varied by 5-6% relative to the baseline model. Instantaneous stresses increased by up to 19% in the thinner variable thickness models and decreased by up to 16% in the uniformly thick case. Globally, the area under low time-averaged wall shear stress (TAWSS) varied between 23% and 30% across all thickness variants, while LA exposed to elevated oscillatory shear index (OSI) increased from nearly 6% to 19%. Over 90% of LAA was exposed to low shear, but the high-OSI area increased from 7% in VT#0 to over 30% in Uniform. ConclusionA personalized multiscale modeling framework was leveraged to demonstrate that the left atrial myocardial stresses and oscillatory shear had a greater sensitivity to local wall thickness representation compared to cavity volumes, tissue displacements, strains, and mean blood shear.

The osteocyte network in bone is believed to play an important role for how bone tissues sense and respond to mechanical stimulation. Yet, bone adaptation to mechanical loads is often conceptualised as a simple response to mechanical stimuli, such as Wolffs law, which is based on mechanical variables only and takes no account of the cellular basis of mechanosensation. Wolffs law presumes the existence of a reference mechanical stimulus, the mechanical setpoint, above which bone is consolidated, and under which bone is removed. In this paper, we develop a theory of bone tissue sensing and adaptation based on osteocytes to provide new understanding of the role played by osteocyte signals in mechanical adaptation. In this theory, the mechanical setpoint of Frosts mechanostat is explicitly embodied as osteocyte properties involved in mechanotransduction. The mechanical setpoint is allowed to adapt due to the replacement of osteocytes during remodelling, making the setpoint space and time dependent. We propose a mathematical model to implement this new theory of bone adapation and present numerical simulations of this model to explore how mechanobiological response curves (effective Wolffs laws) are modulated by setpoint adaptation during remodelling. By accounting for varying osteocyte populations within bone tissue, we explore bone adaptation under osteocyte disruptions, which is particularly relevant to age-related bone loss. Our model suggests that biological disruptions of remodelling balance cannot always be compensated by mechanical feedback, and that setpoint adaptation during remodelling may have significant observable consequences, such as hysteresis in bone response signatures that resemble lazy zones.

The mechanical properties of the nucleus are critical for maintaining nuclear integrity and function. We previously showed that chromatin dominates short-extension mechanics whereas lamins provide long-extension strain stiffening. To distinguish the roles of lamin isoforms, micromanipulation nucleus force measurements were performed on isolated nuclei from lamin A/C (Lmna-/-) and lamin B1 (Lmnb1-/-) knockout mouse embryonic fibroblast cells. Lamin A/C knockout does not alter short-extension nuclear stiffness but is essential for strain stiffening at longer extensions. Oppositely, lamin B1 loss reduced short-extension stiffness due to facultative heterochromatin loss while long-extension strain stiffening was slightly increased. Loss of lamin A/C and B1 resulted in similar lamin-chromatin linkers effects as LBR did not change and LAP2{beta} decreased in both. A simulation model of a polymeric lamin shell with stiff lamin A/C and softer lamin B1 subunits can qualitatively recapitulate experimental measurements of lamin knockout cells. Lamin A/C knockout resulted in abnormal nuclear shape but not nuclear blebbing or rupture whereas lamin B1 knockout, similar to other perturbations that cause heterochromatin loss, resulted in increased nuclear blebbing and rupture. This work illuminates the distinct mechanical roles of lamin A/C and B1 in determining nuclear structure and integrity.

Computational analysis of physiological and biomedical systems necessitate efficient geometry representations for high fidelity model predictions, including patient or device specificity. Particle-based Lagrangian computational approaches comprise a valuable approach to gain insights from quantitative velocity and pressure data from computational models. Examples include particle dynamics and transport in human vasculature for diseases such as stroke, thrombosis, and embolisms; and modern targeted drug delivery systems in the vascular network and respiratory airways. However, current particle simulation approaches can bear significant computational expense that scales with both number of particles and background fluid mesh resolution. A significant determinant of this computational expense is the contact resolution between particles and anatomically realistic vessel wall. Here, we develop an efficient particle dynamics model that leverages an implicit representation of real anatomical features using a signed distance field to efficiently resolve particle-wall contact. We outline the underlying algorithmic details, followed by a systematic illustration of performance and accuracy using simplified and analytically defined geometries and flow fields. Subsequently, we present a representative simulation of embolic particles along a human vascular segment where we compare our distance field-based approach against classical wall-contact checks based on assessing particle boundary intersection with triangulated surface mesh. Our approach transforms the underlying Lagrangian contact detection operation into an equivalent Eulerian operation, significantly speeding up bulk particle dynamics computations without significantly impacting accuracy or geometric fidelity.

Repetitive low-intensity blast (LIB) exposure has been identified as a probable cause of mild blast-induced traumatic brain injury (mbTBI) and a chronic injury risk to U.S. military personnel. However, the human brains biomechanical response to this loading regime remains poorly characterized. Using blast-exposure-validated 3D models of human anatomy, we simulated the intracranial tissue response to blast pressure typically experienced by Warfighters during weapons training. Two scenarios were evaluated, a single-dose exposure and a repetitive-dose exposure, to study intracranial pressure (ICP), shear strains, and spectral content. Ansys LS-DYNA was used to generate planar blast waves with peak overpressures of 4-90 kPa and positive phase durations of 2.2-10 ms. Single exposures produced ICP ranging from 4.7-112.7 kPa, dependent on dose and positive phase duration. Under repetitive LIB exposure, peak ICP increased by 8-26% relative to single exposures, with an increase of high-frequency components (>2 kHz). These results demonstrate that LIB can produce measurable intracranial responses that are amplified through repetition, producing pronounced spectral content and elevated pressures despite low strain levels. This study underscores the need to further investigate cumulative dose effects and the value of computational approaches to clarify hypothesized mbTBI mechanisms in operationally relevant conditions.