Wear particles generated from ultra-high-molecular-weight polyethylene (UHMWPE) joint components play a central role in macrophage-mediated inflammatory responses associated with periprosthetic osteolysis. Although particle size, material modification, and particle load are known to influence biological reactivity, the temporal dynamics of macrophage responses under continuous exposure remain insufficiently understood. In this study, a microchamber-based platform was employed to enable controlled, cumulative, and time-resolved exposure of human monocyte-derived macrophages to clinically relevant UHMWPE wear particles. Wear particles were generated under four material conditions (virgin, γ-irradiated, vitamin-E-blended, and vitamin-E-blended with γ-irradiation) and classified into two size groups enriched in particles smaller or larger than approximately 1 µm. Macrophages were continuously exposed for 24 h under two cumulative particle load conditions corresponding to approximately 5× and 40× the seeded cell number. Culture medium was collected at regular intervals and analyzed for tumor necrosis factor alpha (TNF-α) using an enzyme-linked immunosorbent assay. TNF-α production showed time-dependent changes, including transient early-phase increases followed by declines in some donor-derived macrophages. Higher cumulative particle loading generally resulted in greater TNF-α production than lower loading, indicating that cumulative particle burden influences the inflammatory response profile. In contrast, the effects of particle size and UHMWPE material modification were less distinct under the present conditions, while donor-dependent variation was evident. These findings indicate that cumulative particle load is an important determinant of macrophage inflammatory responses to UHMWPE wear particles. The microchamber-based system provides a useful experimental framework for time-resolved analysis of wear particle–cell interactions and contributes to a better understanding of the mechanisms underlying implant-related inflammation.

The three-dimensional morphogenesis of epithelial tissues is governed by robust physical mechanisms. Examples of this process include the folding of insect imaginal discs and cerebral convolutions. Reaction-diffusion theories have historically focused on chemical aspects to explain these structures. However, recent mechanobiological studies indicate that geometric constraints are equally pivotal. In this study, we investigate how the intrinsic curvature of a tissue substrate directs the buckling morphogenesis driven by cell division. Using a three-dimensional cell-center model, we simulated epithelial proliferation on spherical and ellipsoidal surfaces. Our results reveal a curvature-dependent mode transition on spherical surfaces. Specifically, the buckling pattern shifts from a dot-like state to a labyrinthine state as the radius increases. Crucially, we observed that tissue geometry regulates the spatial orientation of the buckling patterns. On prolate ellipsoids, the tissue spontaneously generates “Yoshimura pattern-like folds” (zig-zag patterns). This topological structure is similar to the folding of beetle horns. Conversely, on oblate ellipsoids, the tissue robustly forms concentric ring patterns. This morphology resembles the folding of Drosophila leg discs. We propose that this physical pattern selection arises from geometric confinement rather than solely from molecular pre-patterning. Specifically, the high-curvature poles of prolate ellipsoids generate effective axial compression. In contrast, the high-curvature equator of oblate ellipsoids induces radial compression. These findings suggest that morphogenetic outcomes are robustly “encoded” in the macroscopic geometry of the developing primordium. Therefore, this macroscopic geometry serves as a geometric bifurcation parameter to regulate the transition between ordered and disordered patterns.

Sound reaches the auditory system through air conduction (AC) via the ear canal or bone conduction (BC) via vibrations of the temporal bone, and both pathways are often activated simultaneously in real environments such as trains and vehicles; environmental sounds are transmitted via AC, while mechanical vibrations may be perceived not only as tactile stimuli but also as BC-like vibrational stimuli. Previous studies have demonstrated AC–BC interference for identical pure tones, but directly measuring cochlear vibrations during simultaneous acoustic and vibrational stimulation remains challenging. Computational simulation can therefore help clarify intracochlear mechanics under such combined stimulation. However, intracochlear mechanical responses under simultaneous AC and vibrational stimulation at different frequencies, which more closely reflect real-world environments, remain insufficiently characterized. In this study, cochlear vibrations under simultaneous AC and vibrational stimulation were simulated using a computational model of human cochlea. Displacement-driven BC stimulation consistently generated basilar-membrane (BM) traveling waves comparable in overall pattern to those induced by AC stimulation. Under same-frequency stimulation, the BM response at the AC-defined CF location varied systematically with AC–BC relative phase and relative magnitude, including marked reductions consistent with destructive interference. Under different-frequency stimulation, the traveling-wave envelope departed from a single spindle-shaped profile and could become bimodal or otherwise non-spindle-shaped, indicating superposition of concurrent response components. These results show that AC–BC interference depends on stimulus magnitude, phase, and frequency, and provide a basis for quantitatively assessing vibroacoustic interactions in the cochlea.

Bone material properties in the femur exhibit marked spatial heterogeneity, which may influence stress distribution after total hip arthroplasty (THA). However, many finite element (FE) studies have relied on homogeneous material assumptions, potentially overlooking patient-specific femoral mechanical behavior. The objectives of this study were to investigate the influence of heterogeneous bone material properties on stress distribution in THA femurs and to clarify the relationship between local bone stiffness and stress distribution across Gruen zones. Subject-specific FE models of three femurs with different Dorr classifications (A-C) were constructed using computed tomography (CT) images. Heterogeneous material properties were assigned based on Hounsfield unit-derived density and elastic modulus, and two cementless stem designs (short and long stems) were analyzed under physiological walking loads. Average von Mises stress was evaluated in each Gruen zone and compared with composite elastic modulus calculated using a rule-of-mixtures approach. The results showed that overall stress distribution patterns were qualitatively similar to those obtained using homogeneous material models, exhibiting stress shielding and distal stress concentration regardless of stem type or femoral morphology. However, within the same Gruen zones, an inverse relationship was observed between composite elastic modulus and average von Mises stress, particularly in mid-to-distal regions. Compared with homogeneous models, heterogeneous models exhibited lower stress magnitudes due to reduced bending deformation. These findings indicate that while homogeneous models may be sufficient for comparative parametric analyses, heterogeneous material modeling provides important insights into local stress-stiffness relationships and patient-specific bone quality. Incorporating material heterogeneity is considered essential for accurate prediction of local mechanical behavior and for future simulations of bone remodeling and fracture risk after THA.

Physics-informed neural networks (PINNs) offer a promising framework by embedding partial differential equations (PDEs) into the loss function together with measurement data, making them well-suited for inverse problems. However, plain PINNs face challenges with time-dependent PDEs due to the high computational cost of space-time training and the risk of convergence to local minima. These limitations are particularly pronounced in hemodynamic analysis, where 4D-flow magnetic resonance imaging (4D-flow MRI) yields temporally sparse velocity snapshots over the cardiac cycle. To address this challenge, we propose a PINN framework that reconstructs instantaneous flow fields from transient velocity snapshots by inferring the acceleration term in the incompressible Navier-Stokes equations. By designing the network without explicit time as an input, the proposed approach enables physics enforcement using spatial evaluations alone, improving training efficiency while maintaining physical consistency with transient flow characteristics. In addition, we introduce an acceleration-mismatch loss that penalizes discrepancies between predicted and measured accelerations, which improves prediction accuracy through regularization. Numerical examples on pulsatile flow behind a stenosis using temporally and spatially downsampled synthetic data generated from time-resolved CFD demonstrate that the proposed framework reliably reconstructs velocity fields even under sparse temporal sampling, and appropriate regularization for acceleration improves predictions of pressure-gradient and acceleration fields.

Traditional stopwatch-based assessments such as the Timed Up and Go (TUG) test may lack sensitivity for high-functioning older adults because of ceiling effects. This study evaluated the potential of a markerless motion capture (MMC) framework using a single monocular camera to quantify subtle trunk kinematics during TUG and to explore motor control deficits that may be imperceptible to human observation. Thirty-four community-dwelling older adults (17 fallers and 17 non-fallers) performed TUG under a maximal-effort condition to impose biomechanical stress. MediaPipe-based pose estimation was used to extract the trunk center-of-mass (COM) trajectory, and a systematic screening of 18 metrics spanning temporal, variability, and smoothness domains was conducted to identify candidate biomarkers. Total time did not distinguish between groups, whereas the Log Cumulative Jerk (LCJ) in the return walk phase showed the largest effect size (Cohen's d = 0.68), although the between-group difference was not statistically significant under non-parametric testing (Mann-Whitney U, p = 0.130). In this context, lower LCJ may reflect a more constrained movement pattern consistent with a possible “stiffening strategy,” rather than improved coordination. LCJ yielded the highest classification performance among the tested parameters (AUC = 0.65), indicating modest relative discrimination in this sample. These exploratory findings suggest that markerless assessment of movement smoothness may provide complementary information beyond conventional time-based measures and may support hypothesis-generating, non-contact fall-risk screening in community settings.

This study investigated the low-dimensional spatiotemporal structure of overground walking using displacement-based principal component analysis (PCA). Four healthy young male subjects participated in the walking measurement experiment. Three-dimensional marker trajectories were collected during overground walking at three different walking rates, and marker displacements were analyzed to reduce the influence of translational components. Cumulative variance of the first two principal components (PC1 and PC2) consistently accounted for more than 85% of the total variance across all walking rates. Temporal analysis showed that PC1 exhibited a regular sinusoidal waveform corresponding to the fundamental gait frequency, whereas PC2 showed a periodic structure at approximately twice that frequency. In contrast, higher-order components displayed complex composite waveforms. Principal component loadings indicated that PC1 primarily represented alternating anterior–posterior displacements of the left and right lower limbs, while PC2 reflected coordinated in-phase displacements associated with the double-support phase. The variance explained by PC1 slightly increased with walking rate, likely due to increased step length. Sinusoidal models of PC1 and PC2 were used to successfully reconstruct walking movements with high temporal fidelity. The temporal and spatial characteristics of these components were preserved across all walking rates. Within this preliminary dataset of four healthy young males, overground walking was characterized by low-dimensional periodic coordination patterns that were relatively consistent across individuals. These findings highlight the effectiveness of displacement-based PCA for revealing fundamental walking movement organization.

Mammalian spermatozoa navigating through the female reproductive tract to reach the egg comprises a fundamental step in achieving successful fertilization. Within the oviduct, sperms encounter oviductal mucus, which is a highly viscous and shear-thinning non-Newtonian fluid whose rheological characteristics strongly influence sperm motility and guidance. During their journey, sperms are subjected to fluid flow generated by the peristaltic motion of the oviductal wall, prompting them to employ behavioral mechanisms such as thigmotaxis and rheotaxis to efficiently migrate toward the oocyte. In the present study, we experimentally examined the interplay between rheotactic behavior and collective swimming of sperm in shear-thinning fluids. To reproduce the physiological flow conditions in the oviduct, we designed and fabricated microchannels. These microchannels mimic the geometry and flow environment of the oviduct using a combination of high-resolution 3D printing and soft lithography techniques. These microfluidic systems allow precise control of the flow field and viscosity distribution, thereby enabling quantitative analysis of sperm motility under conditions relevant to in vivo reproduction. Our results demonstrate that spermatozoa exhibit pronounced rheotaxis within regions near the channel wall, where strong velocity gradients are present. The shear-thinning nature of the medium enhances this orientation response, which results in improved alignment of swimming directions and spontaneous formation of sperm clusters. Furthermore, sperms engaged in collective motion exhibit significantly higher swimming velocities than those swimming individually, suggesting hydrodynamic cooperation among neighboring cells. These findings provide new insights into the physical and biological mechanisms underlying sperm transport in complex reproductive environments. The enhanced rheotactic alignment and collective behavior observed in shear-thinning fluids may confer evolutionary advantages by increasing the probability of successful fertilization under physiological flow conditions.

A number of studies have been conducted on the relationship between plant growth and external stimuli. There has been, however, little research on the effects of wind stimuli that are one of the major stress factors acting on plants in natural environments. Understanding how mechanical properties and morphologies of plants respond to external stimuli is essential for elucidating plant growth mechanisms. This study, therefore, focused on wind-induced changes in mechanical, histological and cellular properties of plants. Mini sunflowers (Helianthus annuus L.) were grown in a wind tunnel with wind speeds of 3.0 m/s and no-wind (control), while room temperature and light-dark conditions were kept consistent between the two groups. After approximately one month of growth under each condition, measurements of the length of stem, the Young’s modulus of stem, the length of cells, the lignified cell area ratio and the cell cycle were conducted. Compared with the control group, the wind-stimulated group exhibited a 67% decrease in the Young’s modulus, a 38% reduction in the stem length, and a 64% reduction in the lignified area ratio, whereas no significant difference in the cell length was observed. In addition, cell cycle progression was inhibited under the wind-stimulated condition. The results indicate that a reduction in cell number contributes to decreased stem length, while a lower ratio of lignified cell area contributes to decreased Young’s modulus. These findings suggest that plants adapt to wind stimuli by maintaining shorter and more flexible stems, thereby reducing the risk of mechanical failure.

The periodic motion of the lower trunk region during human locomotion is analyzed from a kinematic perspective for different gaits using inertial measurement units (IMUs). Experiments are performed on subjects who walked or ran on a treadmill, each equipped with an IMU attached to their lower trunk. The treadmill speed was externally controlled according to a fixed protocol consisting of speed-up and speed-down phases. Time-series data of acceleration and angular velocity were collected and analyzed. We propose a method to estimate the initial elevation angle and velocity associated with the periodic motion, and we focus on the three dynamical aspects of the subject’s movements: the trajectory of the lower trunk in the sagittal plane, the excess kinetic energy ratio, and the position of the least acceleration fluctuation point. The results revealed that the rotation direction of the trajectory in the sagittal plane in the moving frame differed between walking and running for almost all subjects. This difference is interpreted kinematically in terms of the direction and timing of the ground reaction force. The excess kinetic energy ratio as a function of Froude number also well characterizes the gait differences. Furthermore, it is found that the point of least acceleration fluctuation is located consistently behind the body during running.

In both engineered and living systems composed of mechanically interacting elastic bodies, variational modeling, which assigns an energy function to a system, has effectively captured the shape evolution in the elastic body system in response to the mechanical interactions. However, to make an energy function represent component-level shape evolution, the energy function should account for the evolution of mechanical interactions along with the shape evolution of the individual elastic bodies. In this study, we develop an energy function-based model that assigns an energy function with landscape evolution to each elastic body in a system. This model formulates the shape evolution of individual elastic bodies and the evolution of their contact forces, based on the shape gradients of the assigned energy functions and the landscape evolution, respectively. To clarify a characteristic of the system dynamics, we implement this formulation on finite element simulations for a simple two-dimensional system with concave-convex joint-like geometry under axial and oblique loading conditions. Under axial loading, the contact force distribution remains substantially constant, and the energy values decrease as expected from the shape gradients. Under oblique loading, localized increases in the contact force at specific corners generate landscape evolution that increases the energy. Consequently, our formulation has clarified that the energy increase of the components emerges as a characteristic of system dynamics associated with the landscape evolution of the energy functions.