Journal of the Mechanical Behavior of Biomedical Materials

The mechanical behavior of right ventricular (RV) myocardium is governed by its anisotropic microstructure, yet constitutive models that account for fiber dispersion and enable reliable parameter identification remain limited. In this study, we propose a physics-embedded constitutive neural network framework for automated discovery of strain energy functions and microstructural parameters from experimental data. The model is formulated within an incompressible, orthotropic hyperelastic setting using invariant-based representations. Fiber, sheet, and normal directions are incorporated through a rotated structural basis, and dispersion effects are modeled using a generalized structure tensor approach. The framework is trained on multi-axial mechanical data from ovine RV myocardium, including uniaxial tension-compression and simple shear tests. We investigate two training scenarios: (i) full datasets containing both tensile and compressive regimes and (ii) datasets restricted to tensile loading. In both cases, the model accurately reproduces the measured stress-strain responses and identifies sparse, interpretable constitutive models which involve isotropic, anisotropic, and coupling invariants. However, the identifiability of microstructural parameters strongly depends on the available loading conditions. While tensile-only data yield higher predictive accuracy, they result in non-unique or biased estimates of fiber dispersion. In contrast, inclusion of compressive data enables consistent identification of dispersion parameters by separating fiber and matrix contributions. These results highlight the importance of multi-axial loading data for robust parameter identification and demonstrate the capability of constitutive neural network-based approaches for data-driven modeling of anisotropic soft tissues.

Patellar osteochondral allograft (OCA) transplantation is widely used to treat large full-thickness cartilage defects, yet long-term failure and reoperation rates remain high. Although surface congruity and osseous integration are emphasized clinically, cartilage thickness and mechanical compatibility between donor and recipient are not considered. Our previous work suggests that cartilage thickness mismatch can amplify local deformation at the graft boundary, potentially compromising graft longevity. This study investigates how combined mismatches in cartilage thickness and mechanical properties influence the local strain environment at the patellar OCA interface. Simplified two-dimensional axisymmetric finite element models of patellar OCA repair were developed in ABAQUS. Donor-to-recipient cartilage thickness ratios ranging from 0.33 to 3.25 were evaluated together with donor-recipient Youngs modulus mismatches (2.5-7.0 MPa). Cartilage was modeled using homogeneous linear elastic and functionally graded material formulations to account for depth-dependent stiffness. A compressive pressure of 1.0 MPa was applied to represent patellofemoral joint loading, and peak compressive and shear strains were quantified at the graft boundary. Cartilage thickness mismatch produced localized high-strain regions (HSR) of compressive and shear strain at the donor-recipient interface that were absent in thickness-matched constructs. Strain amplification increased with both thickness and mechanical property mismatch. Compressive strain exhibited directional asymmetry, with donor-side-thicker configurations producing greater amplification than recipient-side-thicker configurations. Incorporating depth-dependent cartilage stiffness reduced peak strain magnitudes but did not eliminate mismatch-driven strain amplification. These findings demonstrate that cartilage thickness and mechanical disparity can create HSR at the patellar OCA graft boundary that may predispose grafts to impaired integration and long-term failure.

Tissue-level mechanical stimuli are primary drivers of tissue adaptation and can be optimised during conservative treatments to improve treatment outcomes for many highly prevalent musculoskeletal conditions. Current laboratory-based technologies limit our ability to connect conservative interventions such as exercise and movement modification with muscle, joint, and tissue-level mechanics, in natural environments. We introduce a physics-informed neural network (PINN) to estimate clinically relevant biomechanics from smart garments. By accounting for physiological dynamics of neural activation and muscle contraction, the PINN accurately predicted hip joint angles (RMSE <6 degrees), moments (RMSE 0.12 N*m/kg to 0.30 N*m/kg), and joint forces (RMSE 6 to 16%) from three inertial measurement units and four electromyographic sensors. We demonstrated that the trained PINN can be combined with a smart garment to estimate hip biomechanics, in real-time, during a gait retraining intervention aimed at modifying joint loading to treat hip osteoarthritis. The developed PINN and smart garment system may be adapted and generalised for personalised management or rehabilitation of a broad range of musculoskeletal diseases and injuries, in clinical, home, workplace, and sporting environments.

BackgroundBone graft biomaterials play a critical role in bone regeneration by influencing osteoblast differentiation and mineralization. However, comparative data regarding the osteogenic potential of commonly used graft materials under standardized conditions remain limited. Method and materialIn this in vitro experimental study, osteoblast-like cells (MG-63) were cultured with four bone graft materials, including Bio-Oss, Cerasorb, Bio-Tiss Cerabone, and Pro Osteon. The relative mRNA expression of osteogenic markers (COL1 and OPN) was evaluated at 1, 7, 14, and 21 days using real-time PCR. Alkaline phosphatase (ALP) activity and mineralization capacity were also assessed using colorimetric assay and Alizarin Red staining. Data were analyzed using one-way ANOVA and Tukey post hoc test (P < 0.05). ResultsSignificant differences were observed among the tested materials across all evaluated parameters. Bio-Oss and Cerasorb demonstrated higher gene expression levels and ALP activity compared to Bio-Tiss Cerabone and Pro Osteon (P < 0.05). Mineralization analysis showed significantly greater calcium deposition in the Bio-Oss and Cerasorb groups, whereas Pro Osteon consistently exhibited the lowest osteogenic performance. ConclusionBone graft biomaterials significantly influence osteogenic activity in osteoblast-like cells. Bio-Oss and Cerasorb showed superior osteogenic potential, while Pro Osteon demonstrated weaker performance. These findings highlight the importance of material properties in optimizing bone regeneration.

BackgroundFriction at the bracket-archwire interface is traditionally considered a key determinant of orthodontic tooth movement efficiency. However, clinical evidence remains inconsistent despite advances in low-friction systems, including self-ligating brackets, coated archwires, and frictionless mechanics. ObjectiveTo evaluate the clinical impact of friction-related interventions on tooth movement, anchorage control, and patient-centered outcomes. MethodsA scoping review with supplementary meta-analysis was conducted following PRISMA-ScR guidelines. Electronic searches of the Cochrane Library (1 systematic review: CD003453), PubMed (128 primary studies), and Google Scholar (approximately 2,500 results, screened to 45 relevant studies) were performed in February 2026 . Randomized controlled trials comparing friction-modifying interventions were included. Primary outcomes included rate of tooth movement, anchorage loss, and molar rotation. Secondary outcomes included pain and treatment duration. Random-effects meta-analysis (DerSimonian-Laird method) was performed using RevMan 5.4; this method was chosen due to expected clinical heterogeneity . Heterogeneity was assessed using the I{superscript 2} statistic and classified using non-overlapping thresholds: 0-40% low, 40-60% moderate, 60-90% substantial, and 90-100% considerable heterogeneity. Risk of bias was assessed using Cochrane RoB 2, and certainty of evidence was evaluated using GRADE. Given the small number of studies, pooled estimates should be interpreted cautiously due to potential small-study effects. ResultsNineteen RCTs were included in quantitative synthesis. Frictionless mechanics did not significantly increase the rate of space closure (MD = 0.15 mm/month; 95% CI: -0.08 to 0.38; P = 0.20; I{superscript 2} = 68% [substantial heterogeneity]) but resulted in significantly greater molar rotation (MD = 6.1 degrees; 95% CI: 4.8 to 7.4; P < 0.001; I{superscript 2} = 45% [moderate heterogeneity]) . Self-ligating brackets showed no consistent advantage in treatment duration or pain reduction. Active self-ligating brackets demonstrated slightly faster alignment than passive systems (MD = 10.24 days; 95% CI: 2.80 to 17.68). Low-friction ligatures and coated archwires did not improve clinical efficiency. Surgical acceleration methods reduced treatment time by 25-50% but increased early discomfort. Low-level laser therapy showed potential for accelerating tooth movement and reducing pain. ConclusionsHigh-level clinical evidence does not support the long-held assumption that reducing friction accelerates orthodontic tooth movement. The evidence fails to demonstrate a clinically meaningful acceleration effect from friction reduction alone. Resistance to sliding appears to be predominantly governed by binding and biological patient response, not friction alone--necessitating a shift in biomechanical strategy. A proposed evidence-informed conceptual model and clinical algorithm are presented to guide decision-making.

Aortic stiffness is both heterogenous and anisotropic. Current non-invasive methods to estimate aortic stiffness are limited to characterizing the aortic tissue as isotropic due to the lack the techniques required to extract multi-axial strain from 3D dynamic images. Vascular deformation mapping (VDM) is a nonrigid image registration technique which has thus far been applied to map aortic growth using longitudinal imaging. In this study, we propose to use VDM to assess 3D aortic deformation by mapping diastolic and systolic images. During image registration process, penalty parameters are employed to fine-tune image alignment and penalize non-physiological deformations. These penalty parameters must be calibrated to ensure that VDM successfully reproduces multi-axial aortic motion patterns in health and disease. In this paper, we developed a calibration pipeline for these parameters using synthetic data. A rotation-free shell model was used to generate physics-based synthetic data on aortic motion incorporating patient-specific geometries, root motion, and blood pressure from a cohort of 14 subjects (healthy, Marfans syndrome and thoracic aortic aneurysm). An error metric was defined to quantify the quality of the VDM results. Furthermore, a k-means clustering technique was used to categorize the subjects into three clusters based on ascending aortic motion. Optimal penalty parameters were identified for each of the three clusters. The results indicated that patient clusters with smaller aortic root motion required larger rigidity penalty values. The calibrated parameters successively reduced errors in 3D displacement and multi-axial stretch compared to un-optimized VDM predictions, enhancing the accuracy of capturing aortic deformation from dynamic images. Among the different aortic regions, the ascending thoracic aorta exhibits the largest error reduction.

Dissection of the thoracic aorta includes delamination of medial lamellae and permeation of blood within the media. Quantifying how biaxial loading of a vulnerable wall and fluid mechanics interact to drive dissection remains a central challenge. Here we combine controlled distension-extension testing of intact porcine descending thoracic aortas with forced intramural fluid injection to investigate how axial stretch, injection rate, and needle gauge modulate the initiation and propagation of intramural delamination. Across experiments, injection pressure-volume curves exhibited nonlinear responses characterized by pressure peaks followed by stepwise pressure drops, suggesting progressive micro-delamination events within the medial lamellar networks. Increasing axial stretch significantly elevated peak injection pressure and promoted preferential axial propagation of the permeation / delamination front. Higher injection rates induced abrupt lamellar separation and larger dissected areas, whereas smaller needle gauges generated higher upstream pressures due to increased hydraulic resistance. Synchrotron imaging revealed the microstructural transition from intralamellar fluid permeation and wall swelling to the formation of a large fluid-filled delamination cavity. These results support a mechanistic framework in which the introduction of pressurized fluid within the aortic media behaves as a hydraulic fracture process in a layered poroelastic tissue, governed by balance across fluid pressurization, wall loading, and interlamellar strength. The findings provide quantitative insight into the biomechanical conditions that contribute to the initiation and propagation of aortic dissection.

Tissue engineered constructs are increasingly used for both modeling organs and disease in vitro as well as for therapeutic intervention. In addition to collagen, these constructs commonly include native extracellular matrix proteins (ECM), such as fibronectin and laminin. Given the critical role of inflammatory pathways in disease and in response to implanted materials, it is important to understand the role these proteins play in regulating the inflammatory environment. Fibronectin and laminin influence neutrophil function and endothelial activation in 2D, but their regulation of the inflammatory environment in 3D engineered constructs is not clear. For this study, we used an inflammation-on-a-chip device that includes a model blood vessel surrounded by a collagen I hydrogel with fibronectin and/or laminin. We investigated the additive effects of both proteins and a range of concentrations for each protein to determine concentration dependence. Both fibronectin and laminin have concertation dependent effects on neutrophils and the endothelium. High concentrations (50 {micro}g/mL) of fibronectin reduced neutrophil migration, while 20 {micro}g/mL laminin reduced neutrophil extravasation and migration, potentially due to lower ICAM-1 expression by the endothelium. Interestingly, 50 {micro}g/mL of laminin significantly disrupted endothelial vessel formation and reduced ICAM-1 and VE-cadherin expression, likely due to significant changes in the collagen architecture. The inclusion of fibronectin and laminin, even at physiological levels, results in significant effects on neutrophil behavior, endothelial vessel formation, and collagen architecture. These proteins impact the inflammatory environment and thus need to be considered when modeling diseases and designing therapeutics, especially when neutrophils or an endothelium are involved. Translational Impact StatementThis work uses an inflammation-on-a-chip device to study how fibronectin and laminin impact neutrophil behavior and vascular inflammation as these proteins are commonly used in engineered constructs. We found that fibronectin impairs neutrophil migration, while laminin decreases neutrophil extravasation and migration and at higher concentrations also prevents endothelial vessel formation. Therefore, researchers should be aware that these proteins will alter the inflammatory environment when including them in engineered constructs.

Introduction Obstructive lung diseases (OLDs) are responsible for high rates of illness and death worldwide. Inflammation, chronic airflow limitation, and bronchial remodeling occur in OLD and eventually result in the unique respiratory sounds. Despite its subjective and having low reproducibility, still traditional auscultation using a manual stethoscope is the main method used to identify the lung sounds. Nevertheless, the combination of recent advancements in digital stethoscopes and AI (Artificial Intelligence) has permitted the objective measurement of lung sounds. Nevertheless, there is a lack of standardized, region-specific databases for AI training and validation. Even though lung sound classification is an emerging aspect in research and telerehabilitation the lobar wise acoustic pattern is still novel due to lack of prevailing database to train AI models. Identifying this gap this study aims to develop an acoustic repository and analyze the data using segmental lung sounds from patients with OLDs and healthy controls through an electronic stethoscope. Methods and analysis This is a cross sectional observational study involving 120 participants (60 OLD patients and 60 healthy controls). Lobar wise acoustic signals will be captured using an electronic stethoscope in healthy and diseases population. The data will be analyzed using Audacity software for annotations and then it will be used for feature extraction and statistical analysis. The acoustic features extracted through Audacity, will include frequency, intensity, pitch, and root mean square (RMS) energy. Repeated measures ANOVA will be applied to compare mean sound intensities across lung segments while Pearson correlation will be used to assess associations with body composition parameters. The data will then be standardized for AI-based diagnostic applications. Ethics and dissemination The study is being reviewed from the Ethics Review Committee, Faculty of Medicine, University of Peradeniya (2025/EC/87) will be sought. Informed consent will be obtained in writing. The dissemination of results will take place through peer-reviewed publications and the creation of a public database containing lung sounds from the region.

Abstract Purpose: MyotonPRO (MTP) and time-harmonic elastography (THE) are increasingly used to assess muscle mechanical properties, yet they operate on fundamentally different physical principles. MTP measures composite MTP stiffness (N/m) through surface oscillations, while THE quantifies intrinsic shear modulus (THE stiffness, kPa) via propagating shear waves. This study aimed at systematically compare MTP and THE measurements in the vastus lateralis muscle across different contraction intensities and examine how the skin layer and subcutaneous fat (SLSF) thickness influence their relationship. Methods: Twenty-six healthy adults (15 males, 11 females; age 25 [SD 4] years) underwent MTP and THE measurements of the vastus lateralis at rest and during isometric contractions at 15% and 30% maximal voluntary contraction (MVC). Effects of contraction intensities on tissue properties were assessed using univariate analyses of variance with repeated measures. Associations between the different outcomes of THE and MTP technologies were explored using Pearson's correlations and partial correlation coefficients separately for each contraction intensity with adjustment of the SLSF thickness of participants. Results: Both technologies detected contraction intensity-dependent stiffening across all outcomes (p < 0.001). THE stiffness increased from 5.3 [1.2] kPa at rest to 15.6 [6.1] kPa at 30% MVC; THE wave attenuation increased from 0.83 [0.19] to 1.42 [0.36] s/m while MTP stiffness increased from 337.3 [49.3] N/m at rest to 529.4 [160.7] N/m at 30% MVC. Correlations between modalities were weak and condition-dependent. THE wave attenuation did not significantly correlate with any MTP outcome across conditions. Conclusion: MTP and THE detect contraction-induced stiffening through fundamentally different physical mechanisms and should not be regarded as interchangeable. Their correlation is modest at rest and breaks down (or reverses) during active contraction, with subcutaneous fat as a key modifying factor. Clinical trial number: Not applicable.

Collagens are key components of the extracellular matrix (ECM) that play a crucial role in maintaining structure, strength, and function of the lungs. Fibrillar collagens are crosslinked by enzymes such as lysyl oxidases and transglutaminases and organized into networks by proteoglycans and glycoproteins. Collagens are the main load-bearing components and along with elastin may impart a non-linear strain hardening behavior to the lung. In disease, collagen crosslinking and organization can be disrupted, possibly due to abnormal levels of enzymes or ECM components. Few studies have examined collagen crosslinking and organization in healthy and diseased human lungs. In this study, alterations in collagen crosslinking and organization were investigated in human lung control, fibrotic and chronic obstructive pulmonary disease (COPD) tissue sections. Ultra-performance liquid chromatography and second harmonic generation microscopy measured pyridinoline crosslinks and the distribution of mature and immature collagens within the decellularized scaffolds, respectively. Fibrotic scaffolds had higher total collagen but less crosslinking per mole of collagen compared with COPD donors. Image analysis by second harmonic generation microscopy showed mature collagens populated airway or blood vessel walls in all three groups and in the parenchyma of fibrotic scaffolds. Immature collagens, on the other hand, were mainly localized to parenchymal regions in control and COPD scaffolds, with fewer immature collagens in fibrotic parenchyma. Additionally, quantification of the mature to immature collagen ratio in defined regions of control and diseased scaffolds showed increased organized collagen in fibrotic tissue. Our study shows that collagen crosslinking and organization are disrupted in fibrotic and COPD lungs and these changes may be compartment specific and can contribute to aberrant mechanical properties of diseased lungs. Our findings highlight that along with total collagen content, collagen crosslinking and organization are equally important while investigating collagen-mediated pathological changes in lung tissue. These changes may have implications for developing ECM-based therapeutics for patients with lung diseases.

Background and ObjectiveThe foot-ankle complex is a highly articulated and mechanically constrained system, often simplified as a chain of few rigid segments, neglecting many bone-to-bone motions and raising questions about the accurate representation of interaction with ground. This study proposes a new reduced-order multibody formulation that captures intrinsic kinematic constraints of the foot through motion synergies. MethodsBones kinematic coupling, or motion synergies, were experimentally derived from weight-bearing CT scans using principal component analysis. These couplings were embedded in a synergy-based multibody kinematic optimization framework describing the foot-ankle with five degrees of freedom: ankle flexion; foot adduction, pronation, and arching; and toe flexion. Model accuracy was evaluated against bone-level experimental kinematics. The model was applied to gait data from healthy, flat, and diabetic feet and compared with a standard multi-segment foot model, assessing robustness by progressively reducing the number of skin markers. ResultsAverage errors were about 1{degrees} and 0.5 mm when using subject-specific synergies and below 7{degrees} and 4 mm when scaling the generic model, matching or exceeding the accuracy of existing models. Reliable reconstruction was obtained using only four foot markers. In clinical gait analysis, the model showed superior discrimination between populations and enabled assessment of transverse arch deformation, not accessible with conventional models. ConclusionThe proposed synergy-based model provides an accurate, low-complexity framework for reconstructing bone-level foot and ankle kinematics, substantially simplifying gait analysis while improving biomechanical interpretability. This framework supports future integration with dynamic models aimed at studying load transmission in the foot.

Adult hippocampal neurogenesis plays a central role in learning, memory formation, and adaptive neural plasticity, making it an attractive target for noninvasive neuromodulation strategies. Low-intensity focused ultrasound (LIFU) has emerged as a promising modality for modulating brain function, yet its effects on adult neurogenesis and the role of stimulation frequency remain incompletely understood. In this study, we evaluated whether transcranial LIFU applied to the dentate gyrus influences neurogenic and cognitive outcomes in a frequency-dependent manner. Adult rats received twice-weekly ultrasound stimulation for four weeks at 0.5, 1, or 5 MHz. Neurogenesis was assessed through BrdU incorporation and neuronal differentiation by BrdU/NeuN co-labeling, while expression of neurogenesis-associated markers (BDNF, FGF-2, and Sox-2) was quantified using qRT-PCR. Behavioral effects were examined using the novel object recognition task. Among the tested conditions, 0.5 MHz stimulation produced the most pronounced neurogenic response, with increased cellular proliferation in the dentate gyrus, elevated expression of neurogenic markers, and improved recognition memory relative to sham-treated animals. Higher stimulation frequencies yielded comparatively weaker effects. These findings identify stimulation frequency as a critical determinant of LIFU-driven neuroplastic responses and support the potential of focused ultrasound as a noninvasive approach for promoting hippocampal regeneration and functional recovery.

3D scanners have revolutionised how podiatrists capture foot morphology in order to design custom orthoses (insoles). While various 3D scanning technologies are used in clinical practice, they vary greatly in cost and ease of use and many of these are not specifically designed for podiatry applications. There is limited literature comparing accuracy between scanners, and many approaches require prolonged scan times during which the patient must remain still. Multicamera photogrammetry offers a promising solution by enabling high-quality, rapid 3D scanning which other devices cannot provide. This study compared the accuracy and clinical utility of four 3D scanners. One was a high accuracy reference scanner (Artec Spider) which was used as a gold standard. Two further scanners which are commonly used in the clinic were also investigated (Apple iPad 6 with Structure Sensor attachment 'iPad', and Envisic VeriScan Podiatric Scanner 'laser') and these were directly compared with a novel prototype multicamera photogrammetry 3D scanner. The left feet of 20 healthy volunteers were scanned using each of the four devices and scans were evaluated for accuracy, completeness, and acquisition and processing times. All scanners produced clinically acceptable scans, with the novel photogrammetry scanner demonstrating superior accuracy. Scan times varied significantly between scanners, with the photogrammetry device capturing scans much faster. All scanners had acceptable levels of completeness, though the iPad and photogrammetry outperformed the laser scanner. These results provide a valuable tool for clinics seeking guidance on scanner selection and highlight the benefits of instantaneous photogrammetry scanning to improve workflow efficiency and accessibility.

Various ankle-foot conditions (e.g., fractures, diabetic foot ulcers, and post-surgical recovery) require periods of complete non-weightbearing followed by gradually increasing partial loadings. However, existing assistive devices often provide inconsistent or uncomfortable offloading during gait. Additionally, prolonged proximal leg offloading can contribute to muscle atrophy, reduced bone density, and overuse of other body segments. We present a novel offloading ankle-foot orthosis (OLAFO) designed to overcome these limitations. The OLAFO features a patient-specific load-bearing shank brace, designed through a digital workflow and fabricated from a 3D-printed core reinforced with carbon-fiber composite lamination. Interlocking serrated side struts, adjustable in 2 mm increments, modulate load sharing between the shank and plantar surfaces. Furthermore, the OLAFO incorporates contact plates with a rocker profile informed by roll-over-shape measurements to support forward progression and gait symmetry. Proof-of-concept biomechanical verification in one able-bodied participant evaluated complete offloading, five partial-loading levels, and normal gait using a pressure walkway to compute vertical ground reaction forces and impulses. In complete offloading, the affected foot generated no contact pressures. Across partial-loading levels, the foot impulse increased from 14% to 53% of the total load and scaled linearly with strut height adjustments, supporting clinician-prescribed loading increments. Contralateral stance duration increased only modestly compared to commonly used assistive devices, indicating reduced compensatory loading on the intact limb. These findings demonstrate the proof-of-concept feasibility of the OLAFO, highlighting its potential for verifying full offloading and prescribing partial-loading targets during rehabilitation. Future research will evaluate performance across patient populations and clinical rehabilitation tasks.

Background Delineating the cellular origins of extracellular vesicles (EVs) enables the detection of clinically relevant changes in dynamic and complex tissues, such as the endometrium, which are not characterizable through single biomarker assays. Transcriptome deconvolution into cellular composition using deep learning methods provides a means to explore this complexity. However, such computational methods have not been previously applied to EV bulk transcriptomes, and their efficacy in profiling EV population changes and concordance to tissue throughout the menstrual cycle remains unknown. Methods This observational cross-sectional study utilized a deconvolutional generative deep learning algorithm, BulkTrajBlend, trained on a comprehensive human endometrial single-cell RNA sequencing (scRNA-seq) atlas. The model was applied to deconvolve paired bulk transcriptomes from endometrial tissue and uterine fluid EVs (UF-EVs) across the proliferative (P, n=4), early-secretory (ES, n=5), mid-secretory (MS, n=5), and late-secretory (LS, n=5) phases from healthy, fertile women. To validate generalizability, independent UF-EV datasets (ES, n=12; MS, n=12) obtained via different laboratory protocols were included. Deconvolved pseudo-single-cell (pSC) profiles from UF-EV data were subsequently integrated with Visium spatial transcriptomics slides of human endometrium (P, n=2; MS, n=4; ES, n=2). Results We developed a foundation model-based approach utilizing self-supervised learning to determine the cellular origin of EVs from their transcriptomic profiles. By mapping the generated pSC profiles to spatial transcriptomic data, we evaluated spatial origins of EVs. The statistical analysis demonstrated that UF-EV transcriptome deconvolution reflects the dynamic changes in the cellular composition of endometrial tissue across the menstrual cycle phases. The ability to distinguish accurately between proliferative and decidualizing menstrual cycle phases (ROC-AUC = 0.98) using cellular profile of deconvoluted UF-EVs transcriptome enables non-invasive profiling of endometrial tissue. Conclusions Our findings indicate the feasibility of determining endometrial tissue cellular composition using UF-EV transcriptomics. This methodology enables refined, non-invasive endometrial testing, avoiding invasive biopsy procedures. Based on deconvolution results, we are able to correlate UF-EV content to tissue, and distinguish between menstrual cycle phases. These results build toward a multifactorial screening method for abnormalities within the endometrium.

Mechanical properties of epithelial tissues play essential roles in morphogenesis and physiological function. In this study, we analytically derived the in-plane bulk modulus, shear modulus, and Poissons ratio of a three-dimensional cell vertex model of epithelial monolayers. We showed that the model can robustly reproduce a near-zero in-plane Poissons ratio, a mechanical feature reported in cultured epithelial tissues. Numerical simulations further confirmed that the theoretically predicted Poissons ratio accurately describes the response of the model under finite, biologically relevant strains. In addition, the model exhibits not only morphological bistability between squamous-like and columnar-like states, but also mechanical bistability characterized by distinct elastic responses. Together, these results provide a minimal three-dimensional framework that links cell-scale mechanical interactions and epithelial morphology to tissue-scale elastic properties.

Mass is a fundamental aspect of muscle contractile function, yet the inertial effects of inactive muscle mass is generally neglected in modeling and not quantified in studies on small muscles or isolated fibers. However, during submaximal contractions, inactive muscle tissue may take longer to be accelerated by active fibers, and may be subject to prolonged deceleration, both of which may potentially reduce force development and work output. We sought to test if inactive tissue mass imposes an inertial penalty on muscle performance, using in situ sinusoidal work-loop experiments on rat plantaris muscles. Regional fascicle dynamics, measured across supramaximal and submaximal levels of activation, showed that decreasing activation significantly reduced fascicle strain and increased both shortening and lengthening latency. Contrary to our predictions, however, reductions in work, beyond those explained by decreased fascicle strain, were negligible. Normalized work did not decline disproportionately relative to force, suggesting no clear inertial penalty on work at this muscle size. Our findings suggest that while inactive muscle mass influences the dynamics of submaximal contractions, its impact on work during submaximal contractions at small muscle sizes is limited.

The aorta, normally resilient to hemodynamic stresses, becomes vulnerable to structural failure due to diverse conditions that weaken the wall. We injected fluid into excised specimens of human ascending aorta with pressure monitoring to quantify the impact of clinical and histological factors on mural damage. Two modes of medial injury emerged with distinct pressure tracings. Extravasation was characterized by diffuse infiltration of fluid with widespread damage of smooth muscle cells and collagen fibers but limited separation of elastic lamellae. By contrast, delamination was characterized by marked separation of elastic lamellae along a single plane with damage to cells and fibrillar matrix restricted to adjacent laminae. Aging, aortic dilatation, and family history associated with lower pressures causing delamination, whereas a diagnosis of hypertension associated with higher pressures suggesting resilience to dissection. Collagen fraction adjacent to delamination correlated with higher pressures as did decreased smooth muscle cell density and increased glycosaminoglycan fraction, although several clinical and histological variables were interrelated. Protein cross-linking strengthened and enzymatic digestion of collagen weakened the aortic wall, while acute cell lysis with detergent had no effect. We conclude that increased functional medial collagen has an adaptive protective role in aortic remodeling rather than signifying medial degeneration.

Hemodynamic forces play a key role in early cardiac morphogenesis, yet many computational studies assume Newtonian blood behavior. Here, we evaluate the impact of nonNewtonian shearthinning rheology on flow patterns, pressure distributions, and wall shear stress (WSS) during cardiac looping using idealized threedimensional models of the embryonic heart tube. Five geometries representing progressive looping stages, from a linear tube to an Sshaped configuration with ventricular ballooning, were analyzed under pulsatile flow using both Newtonian and powerlaw viscosity models. Across all stages, Reynolds numbers (Re {approx} 1-7) and Womersley numbers (Wo {approx} 0.3) indicated laminar, quasisteady flow consistent with embryonic conditions. Incorporating shearthinning rheology produced substantial deviations from Newtonian predictions, with peak systolic WSS differing by up to [~]40% and pressure drops by up to [~]20%. These effects were most pronounced in regions of increased curvature and geometric complexity. These findings demonstrate that nonNewtonian rheology significantly influences predicted hemodynamic environments during cardiac looping and should be incorporated into computational models aimed at understanding mechanobiological regulation of early heart development.