The pulsed laser used in URS (ureteroscopy) is used effectively in the treatment of urologic diseases such as lithotripsy and benign prostatic hyperplasia. In the case of lithotripsy in a relatively narrow area or prostatectomy, since it is necessary to irradiate the laser near or directly into the tissue through an optical fiber, it is pointed out that thermal damage may be caused to areas other than the affected area. The authors have measured the temperature near the fiber tip and attempted to evaluate the damage to biological tissues using an evaluation method called CEM43℃ (cumulative equivalent minutes at 43℃). In this report, we measured the time-averaged temperature distribution on the wall surface around the bubbles using thermocouples flush-mounted on the wall, and examined the range where the tissue wall is expected to be damaged using CEM43℃. As a result, we found that the possibility of thermal damage could occur in the area in front of the fiber tip. In addition, the thermal damage area is closely related to the contact between the bubbles and the wall surface associated with the characteristic collapse behavior of the bubbles formed near the wall surface.
The thrombus formation process has yet to be fully simulated, which necessitates the design of a novel method for the quantitative assessment of device thrombogenicity that complements animal experiments/ex vivo experiments using animal blood and computational fluid dynamics analysis. This study aimed to develop a model blood capable of simulating the formation of red thrombus owing to stagnation of blood flow by applying the phenomenon of milk clot formation. To render the rheological properties of skim milk solution used as a model blood closer to those of human blood, the ratio of the amounts of casein in skim milk, calcium chloride, and rennet (constituents of the solution of the model blood) was varied and the rheological properties of the clot formation process of human blood and skim milk solution were measured using a cone-plate viscometer. Comparisons of the rheological properties of human blood and skim milk solutions during clotting revealed that during clot formation of human blood, four characteristic quantities of the time-series change in rheological properties were observed: the viscosity before clotting, coagulation start time, viscosity increase rate, and first yield viscosity. Further, hypercoagulable skim milk solutions with rheological properties similar to those of human blood were prepared by adjusting the solution composition ratio. When this model blood was circulated in a closed-loop circuit with a saccular aneurysm model, the growth rate of skim milk clot formation in the aneurysm model was significantly different in a flow diverter stent model and a micro-porous covered stent. The variation in porosity between these two stent models has a direct impact on the rate of embolisation. The proposed blood model can effectively replicate the formation of red thrombus, providing a valuable means to accurately and quantitatively assess the therapeutic efficacy of embolisation devices.
The evaluation of tactile sensitivity involving frictional behavior via computational models can further accelerate the development of industrial products in terms of usability. This study aimed to confirm the capability of a previously proposed mechano-neurophysiological model, representing the basic mechanical (i.e., finger skin deformation) and neurophysiological (i.e., neural activities of slowly adapting type-1 (SA1) afferents) functions in the tactile sensation process, for simulating tactile responses during Braille reading under multiple frictional conditions. A previous psychophysical experiment on tactile recognition during Braille reading reported that the misread rate was significantly higher at frictional coefficient (μ) = 2.62 than at μ = 0.56, whereas no significant differences were observed between the misread rates at μ = 0.25 and 0.77. The Braille reading experiment was simulated using the mechano-neurophysiological model to achieve the present aim. The simulation results revealed marginal differences in the SA1 responses between μ = 0.25 and 0.77, and the correlation coefficients between the SA1 responses and Braille patterns were 0.98 at μ = 0.25 and 0.96 at μ = 0.77, suggesting a limited influence of friction on Braille recognition. However, the SA1 responses varied considerably between μ = 0.56 and 2.62, and the correlation coefficients were 0.97 at μ = 0.56 and 0.49 at μ = 2.62, implying a relatively strong influence of friction. The simulation results supported the above-mentioned findings of the previous psychophysical experiment, thereby demonstrating that the mechano-neurophysiological model qualitatively determined the tendency of influence of friction on Braille recognition.
Atomic force microscopy (AFM) has been extensively used to measure the mechanical properties of single cells and tissues with a high force sensitivity. AFM has been established to quantify mechanical differences between cells, e.g., between normal and disease cells, and between untreated (controlled) and treated cells. However, since these biological samples are intrinsically heterogeneous and hierarchical materials, AFM often suffers from the quantification of cell and tissue mechanics due to the high spatial resolution of AFM from the nanoscale to the microscale, comparable to the spatial variation and fluctuation of living systems. Thus, it is still challenging to elucidate universal nano- and micro-mechanical features of living systems using AFM data. This review addresses how AFM can quantify the heterogeneities and hierarchies of cell systems. For single-cell mechanical analysis, AFM has been combined with micropatterned substrate to control cell shape and precisely define the AFM measurement within cells, allowing us to analyze the cell-to-cell mechanical variation. For tissue mechanical analysis, we introduce AFM with a wide-scan range to map multicellular samples from a few hundred to millimeter scales, depending on the type of scanner, allowing us to quantify the spatial mechanical variation in multicellular systems. The reliability and the possibility of AFM to apply mechanics studies on cells and tissues with a range of Pascal (Pa) to MPa are addressed.
Cell adhesion to the extracellular matrix critically influences essential cellular functions such as proliferation, motility, and differentiation, all of which are crucial for maintaining tissue homeostasis. Achieving precise control over cell adhesion to artificial substrates is a pivotal challenge in biomaterials engineering. This minireview aims to elucidate the multifaceted considerations for substrate surface design, grounded in the detailed molecular mechanisms of the cell adhesion complex. We systematically outline key design variables for controlling cell adhesion, such as the spatial arrangement of adhesion ligands, matrix stiffness, and surface lateral deformation. The review also delves into the emerging role of mechanobiology of membrane glycocalyx, with a particular focus on the impact on the formation of focal adhesion complexes. Collectively, these considerations offer a methodology for fine-tuned control of cell adhesion and its subsequent cellular functions on engineered biomaterials.
Despite considerable advancements in biological measurement technologies, capturing the simultaneous temporal changes in various biomolecular concentrations remains a challenge. Overcoming this technical difficulty via data preprocessing could not only clarify the principles of biological functions but also reduce the costs associated with advancing measurement technologies. This review introduces a novel approach to harmonizing heterogeneous time-series data related to molecular signaling and cellular movement. In response to this challenge, we developed and employed a motion-trigger average (MTA) algorithm. The MTA comprehensively screens and averages intracellular molecular activities that coincide with targeted velocity patterns of the moving cell edge. Given that the MTA filters out cell individuality-dependent noise from the data, a straightforward regression equation can correlate edge moving velocities with the molecular activities of various species within the cell. This methodology not only integrates fragmented datasets but also enables the reuse of past data for new analyses. The crux of our discovery is the elucidation of the role that Rho GTPases play in regulating cellular edge dynamics, a finding made possible by adopting the MTA algorithm. Our study suggests that the MTA could become an indispensable tool in data-driven biology, potentially paving the way for considerable insights into dynamic cellular behaviors and the underlying biological principles.
The Young’s modulus of normal lung tissues ranges from 1 to 5 kPa, whereas fibrotic or lung tumor tissues can be ~30 times stiffer. However, the lung parenchyma microscopically consists of various tissues, and cancer cells in tumors contact stiff collagen-containing fibers during invasion. In this study, we investigated the effect of stiff substrates on A549 cell migration. We fabricated stiff polydimethylsiloxane (PDMS) substrates with different stiffness levels (1.4, 3.4, and 18.3 MPa) by adjusting the cross-linking agent ratio. We examined the distance and the trajectory orientation of A549 cell migration on PDMS substrates and much stiffer 7.7 GPa glass with scratch-wound assays. A549 cells exhibited a collective sheet-like migration pattern toward the wounded area on stiff substrates. The migration range at 18.3 MPa was significantly higher than at 1.4 and 3.4 MPa, and that on glass was significantly higher than that at 18.3 MPa. The cell trajectory orientation on stiff PDMS substrates gradually increased and became constant, whereas that on glass was constant from the initial migration. Our results revealed that stiff substrates affect A549 cells migration in this range.
Predicting the ground reaction force (GRF) and ground reaction moment (GRM) with a biomechanical model-based approach has an advantage for biomechanical gait analysis in situations where a statistical model cannot be used due to a lack of training data. However, the current prediction methods using a biomechanical model have some issues for clinical application. The present study developed a new inertial measurement unit (IMU)-based method to predict the GRF, the GRM, and the joint kinematics and kinetics with a 3D biomechanical model and simple system. The present method predicts them using a 3D forward dynamics model that computationally generates human movements that minimize the hybrid cost function defined by physical loads and errors between the motion of the model and that of the participants recorded by six IMUs, which allows the prediction system to use only a relatively small number of IMUs. We investigated the prediction accuracy during walking by comparing the new method with a conventional analysis using a force plate and motion capture system. As a result, we observed strong and excellent correlations between the prediction and measurement of the anterior GRF, vertical GRF, sagittal GRM, hip flexion angle, knee flexion angle, hip flexion torque, and ankle dorsiflexion torque. Considering the accuracy of previous studies and that required for gait analysis, the present method could predict them with practical accuracy due to estimated biomechanically valid motions based on optimization using the hybrid cost function that includes a biomechanical evaluation. Moreover, the prediction system has an advantage for clinical applications because the present method observed practical accuracy that has the potential to be applied to some sports analysis and can analyze 3D motion with a simple system consisting of a small number of hardware components and a software.
This study aims to confirm the effects of a neck pillow on the postural stability of the head and neck and the variance of center of mass in a sitting position. Experiments were conducted on keeping a sitting posture at rest with and without the use of two types of neck pillows; the neck wrap pillow and the front neck pillow. During experiments, whole body posture was recorded by a motion capture system. Differences in head-and-neck postural stability and center of mass variance in the resting sitting position were statistically compared among the neck pillow conditions. As a result, it was confirmed that the front neck pillow increases the postural stability of the head and neck in a resting sitting position and reduces the variation of the center of mass.
The margin of stability (MoS) is a gait stability index with good validity. MoS is computed in the anterior and mediolateral directions. However, their relationship has not been well investigated. Furthermore, previous studies have little investigated the differences in MoS between distinct age groups. Inter-age comparisons reveal age-specific walking characteristics and their effects on stability. In this study, we used multiple indicators and multiple causes model, which is a type of structural equation modeling, to investigate the statistical relationships between various types of gait parameters and MoSs for each of the healthy participant groups over 60 and in their 20s. For the analysis, data from 120 individuals were obtained from a gait database. The model for the younger group showed that the MoSs in the anterior and mediolateral directions were mostly separated. The stability in the anterior direction was independent of the stability in the mediolateral direction. In contrast, some gait parameters simultaneously affected the two MoSs in the elderly group. The stability in the anterior and mediolateral directions was interdependent. For example, forward walking speed influenced the anterior and mediolateral MoSs in the elderly group, whereas it influenced only the anterior MoS in the younger group. These findings suggest that the age of people must be considered when discussing gait characteristics that contribute to stability.
Intracellular proteins are continuously replaced over time by chemical reaction called molecular turnover. Fluorescence recovery after photobleaching (FRAP) is a powerful technique to evaluate the turnover in living cells. In short-term FRAP measurements, individual proteins involved in the turnover are transported by the Brownian motion-based diffusion. In long-term measurements, by contrast, intracellular flow can no longer be ignored, which transports proteins in specific directions within cells and accordingly shifts the spatial distribution of the local chemical equilibrium state. In addition to that, regions initially marked by photobleaching are subject to not only the spatial movement but also microscopic deformations in the presence of contractility produced by active dynamics of motor proteins. Evaluating the complex molecular turnover composed of these multiple physicochemical factors remains an open challenge. Motivated by this situation, FRAP-based novel approaches have been extensively developed to unveil unknown quantities associated with turnover. In other words, advance in FRAP method can potentially open up new ways in cell biology and related physics, in which turnover is critically involved. In this paper aiming at reviewing recent advances in FRAP analysis, we categorize the turnover-associated timescale into (i) the short-term case (~sec) composed of molecular diffusion and the long-term one (~sec–min) driven by (ii) flow-like movement or by (iii) structural deformation. In the case of (i), FRAP combined with a reaction-diffusion model and genetic engineering allows us to distinguish between the pure diffusion-related quantities and the domain-level equilibrium constant. In the case of (ii) and (iii), continuum mechanics-based FRAP (CM-FRAP) model allows for simultaneously quantifying chemical and mechanical behaviors such as the off-rate of fluorescently labeled proteins, the spatially directed movements, and the microscopic deformation. Thus, we describe these recent advances in FRAP analysis as well as conventional techniques, which have greatly contributed to deciphering the complicated intracellular turnover.