Recently, a decellularized tissue, which is extracellular matrix assembly, have been focused as one of candidate biomaterials. Recently, decellularized tendon and ligament have been tried as alternative tendon and ligament for tissue regeneration. However, it is difficult to recellularize inside of them. So, in this study, we proposed a method that decellularized membrane was recellularized and fabricated for in vitro reconstruction of ligament-like tissue having living cells. The decellularized pericardiums were prepared by two decellularized methods. Cells such as fibroblast, myoblast, mesenchymal stem cell, were adhered and cultivated on the decellularized pericardiums. The ligament-like tissue was reconstructed by rolling of the recellularized pericardiums with keeping the cellular adhesion in the inside. These results suggest that the ligament-like tissue could be reconstructed by using the recellularized pericardium.

Purpose

The artificial bone is commonly grafted into the cancellous bone. We investigated whether onlay graft contributes to earlier cortical bone formation.

Methods

A gutter is created for 16 femurs (eight rats), followed by putting porous hydroxyapatite/collagen (HAp/Col) onto the bone surface. Control group: only gutter (no HAp/Col), HA group: HAp/Col with saline, HA-PRP group: HAp/Col with PRP, O₃-HA-PRP group: VUV/O₃-treated HAp/Col with PRP. Two and four weeks after the surgery, μCT and histopathological examination are performed.

Results

Both HA-PRP and O₃-HA-PRP groups showed partial bone formation in the superficial gutter. O₃-HA-PRP group showed a more rapid decrease of HAp/Col volume and CT value, compared with HA or HA-PRP group.

Conclusion

Artificial bone with PRP partially stimulated superficial bone formation. Although VUV/O₃-treated HAp/Col with PRP showed neither more rapid nor more amount bone formation, metabolism of the artificial bone might be promoted.

This paper describes Shape retaining and Sacrificial molding (SRS-molding) method for fabrication of ECM-based in vitro vascular model. SRS-molding stabilizes the shape of microchannel better than Sacrificial molding, which is reported in previous research. The author compared the shapes of microchannels made by SRS-molding and Sacrificial molding, and showed that SRS-molding improved the stability of the channel shape. To use the vascular model under mechanical stimuli, stretch stress and shear stress from fluid flow were simulated on the vascular model, and quantitative stress data were obtained. As demonstrations, cells were cultivated with perfusion, and the vascular model was stretched with cells. The author confirmed cell growth in the vascular model and channel deformation without cell separation. From the above, this system could be used to observe the cellular responses to the mechanical stimuli, and the author believes that this system would be a platform for in vitro vascular tissue engineering.

We reproduce chemical reactions of blood vessels by a flexibly deformable collagen tube device. The device is composed of an unfixed collagen hydrogel tube, enabling the reproduction of both macro and micro scale deformation of the vessel tissue. The fabrication of the device is a simple molding process. Also, the device is easily perfused because the collagen hydrogel tube is directly attached to silicone tubes. We succeeded in demonstrating the chemical deformation of vessel tissue and endothelial cells by inflammatory mediators. Moreover, the drug testing was presented by anti-inflammatory chemicals. We believe that our flexible culturing device could help the construction of functional blood vessels reproducing in vivo chemical reactions in high similarity, and contribute to biomedical researches and pharmacokinetic testing.

produce regenerated kidneys by decellularizing the kidneys derived from heterologous animals and recellularizing with patients' own cells. The decellularized kidneys were prepared by a combination of high hydrostatic pressure (HHP) and surfactant (SDS) treatment. The difference in the amount of residual ECM by treatment suggested that various decellularized kidneys with different amounts of residual ECM could be produced by the combination of HHP and SDS. Next, mouse connective tissue cells (L929) were seeded to decellularized kidneys. Calcein-AM and HE staining showed that many cells were distributed in the renal cortex of SDS kidneys and few cells were exist in the interior of HHP-SDS kidneys. These results indicate that cell adhesion varies depending on the amount of ECM remaining in the decellularized kidney, suggesting that cells are also affected by kidney reconstruction.

Twitch stress of a cardiac tissue equivalent reconstructed in vitro is markedly lower than that in native tissue. Polyunsaturated fatty acid (PUFA) has bioactivities, and mediates crucial functions in the heart. We previously elucidated that the supplementation of docosahexaenoic (DHA) and arachidonic (AA) acids elevate contractile fraction in the cultured cardiomyocytes. However, metabolism of PUFA in cardiomyocytes in culture might be insufficient because PUFAs are mainly metabolized in the liver in vivo. In the present study, we evaluated effects of supplementation of 17-HDoHE or 22-HDoHE, which are DHA metabolites, or 8,9-EET or 11,12-EET, which are AA metabolites, on contractile performance of cultured cardiomyocytes. Four days after the onset of supplementation of 17-HDoHE, 22-HDoHE, or 8,9-EET, the contractile fraction was significantly higher (P<0.01) than that in cells without the supplementation. The results suggest that supplementation of DHA and AA metabolites may have beneficial effects on the contractile performance in cultured cardiomyocytes.

While polyunsaturated fatty acids play essential roles in the physiology of myocardium, conventional culture medium contains little lipid. We previously revealed that the contents of docosahexaenoic (DHA) and arachidonic (AA) acids in cultured cardiomyocytes derived from fetal rats were markedly lower than those in the neonatal myocardium, and the contractile fraction was maximized as DHA (20 μM) or AA (50 μM) supplemented in the medium. In this study, we evaluated the effects of DHA or AA supplementation on mRNA expression and further measured the contractile force of cardiomyocytes with the supplementations. Significant upregulation of the mRNA expression related to cell adhesion was unveiled in the cultured cardiomyocytes with the supplementation of DHA or AA; however, no significant enhancement in the contractile force was measured out. These results suggest that the supplementation of DHA or AA may strongly promote intercellular adhesion, but do not directly reinforce the contractile force.

Because ultrasound irradiation causes damage on cells, we analyzed the damage on cells under ultrasound exposure by varying its parameters. We examined the suspension of CD8-OVA1.3 cells, which are T-cells of mice, in a well plate on the surface of the degassed water at a water temperature of 37 ^oC. From the bottom of a water tank, ultrasound irradiation was performed by targeting a suspension of cells. After irradiation, fluorescent reagents were used to calculate the cell viability.As a result, the survival rate was the lowest at a frequency of 3 MHz, when a continuous wave (100% of duty ratio) was applied with a sound pressure of 400 kPa-pp. On the other hand, when only the duty ratio is less than 20% without changing other parameters, the survival rate raised 100%. From the results, cell damage complexly related to various ultrasound parameters.

The use of experimental animals has two problems: animal ethics and the inaccuracy in extrapolating data to humans. To solve these problems, we used two-channel organ chips made of polydimethylsiloxane to mimic human heart. We seeded human umbilical vein endothelial cells, gingival fibroblasts, and the induced pluripotent stem cells (iPSC) on the chips, and then perfused culture medium. After the three-week differentiation protocol, iPSCs were differentiated into cardiomyocytes. They showed spontaneous contraction and synchronized fluctuation of intracellular calcium level, demonstrating successful cardiac differentiation. Furthermore, the heart rate of the cardiomyocytes differentiated from iPS cells increased in response to noradrenalin in a dose-dependent manner, suggesting the development of the functional β-adrenergic receptor signaling system. These results demonstrate that the organ-on-a-chip system is useful for mimicking the human heart and testing the effect of drugs on the heart.

Cellular functions have often been studied in 2D cell culture, but those in 3D conditions including gels made of extracellular matrix have not yet been fully investigated. Most studies on the stress field to date have been addressed by tracing marker beads or staining the collagen gels. However, these methods must take into account the potential side effects of the staining on the cells. To overcome these issues, here we develop a label-free method for measuring the deformation field of the cells within 3D collagen gels by using second harmonic generation (SHG) microscopy. As a preliminary step to the calculation of the stress field, the strain tensor was calculated using the obtained deformation field, and the strain field was visualized. Based on these results, we have opened up the possibility of observing the mechanical behavior of cells in detail in a three-dimensional environment.

Analyzing the mechanics of intracellular diffusion forwards the understanding of the inner workings of living cells and their rheological properties. Conventional Brownian diffusion is insufficient in describing this diffusion not only due to the complexity of the cell, but also because of macromolecular crowding caused by immobile obstacles such as the actin cytoskeleton. We investigate the effects of crowding on the diffusion rates in three distinct locations of mesenchymal cells, namely the cytoplasm, stress fibers, and those below the nucleus using inert green fluorescent proteins (GFPs). We analyze the fluorescence intensity of the GFPs using fluorescence correlation spectroscopy (FCS) to determine the diffusion coefficient and show that diffusion tends to be slower on average in stress fibers and is significantly slower in those located below the nucleus due to extensive crowding in the cell bottom. Our data suggests that the diffusive properties of GFP, are hindered by the macromolecular crowding.

Focal Adhesions (FAs) sense the mechanical stresses acting on cells and induce biochemical reactions within the cells. This phenomenon is called as mechanotransduction. There are many studies on the mechanism of mechamotransduciton, and most of them have suggested that it is caused by the stretching of FA proteins. However, such a stretching phenomenon is not observed in cells. Therefore, we hypothesized that mechaontransduction is caused by changes in the fluctuations of FAs. We performed Fluorescence Correlation Spectroscopy at an almost fixed point, at the location of FAs. We thought that the change in the fluorescence fluctuation obtained by this method could be regarded as representing the structural fluctuation of FAs. In order to apply mechanical stresses to FAs, we administered blebbistatin and compared the results before and after. The results suggest that the structural fluctuations of FAs could be significantly affected by reducing the mechanical stresses.

The measurements of conventional SQUID-MEG system is performed with the head fixed, but it is influenced by the size and shape of the head. Therefore, we studied the usefulness of a planar sensor array MEG system with optically pumped magnetometers (OPMs) by taking advantage of OPMs.By simulation, it is assumed that the OPM modules surface with a first-order gradiometer structure arranged in a plane is in contact with the back of the head of the subject. At first, we calculated the evoked response in the primary visual cortex by visual stimulation in the shield room while changing the number of sensors. Next, for each number of sensors, we analyzed whether the signal source could be reconstructed using the generalized least squares method.The results show that it was possible to reconstruct the signal source activities with high accuracy even in OPM-MEG measurement with fewer sensors than those of SQUID-MEG.

Wearable intelligent devices for improved safety and comfort have become a hot topic in recent years. The brain-computer interface (BCI) method is typically based on electroencephalography (EEG), enabling users' direct interaction with devices in real time. However, rigid contact through EEG is inconvenient for daily applications. Magnetoencephalography (MEG), a noncontact brain signal measurement with high temporal and spatial resolutions, can be an excellent alternative for developing the BCI. In this study, we investigated the feasibility of wearable magnetometers, such as diamond nitrogen-vacancy centers, and optically pumped magnetometers for potential applications in on-board MEG. For the stimulation setting, we considered the steady-state visual-evoked response (SSVER), which is an essential brain activity for users. To investigate the presence of SSVER and denoising, we optimized the sensor array position and orientation. The results show the potential of intelligent devices for user interaction.

In the previous study, the method of extracting brain region from the MR brain image was proposed. That uses snake to detect the scalp and remove scalp and skull automatically. In this study, we propose an automatic placement method of the initial contour of a snake. The divided small areas were classified into no object, brain parenchyma, and composite area with the average and the standard deviation of the histogram of the image. The position of snake could be initialized automatically by place it in no object area. In the diagnosis of cerebral atrophy, it is necessary to distinguish between cerebrospinal fluid, gray matter, and white matter. However, it is difficult to classify tissues with ambiguous boundaries, such as white matter and gray matter, with histograms. Then, we applied an automatic region segmentation method, called self-organization map (SOM). As a result, we could classify tissues successfully.

Realistic volume conductor models generate three-component voxel lead field matrices. However, three columns of these matrices are not independent and spatially correlated, which is represented by the covariance structure of the voxel lead field matrix. This paper investigates beamformer performance degradation due to the spatial correlation of the lead field columns. We find that the column spatial correlation can cause orientation inaccuracy in scalar beamformers, while it can cause power inaccuracy in vector beamformers. These orientation and power inaccuracies also depend on the signal-to-noise ratio (SNR), as well as the window size in the data measurements. We present theoretical analysis describing how these three factors, i.e., the lead-field covariance structure, SNR, and data window size, affect the beamformer source estimation process. The results of computer simulation that validates our analysis are also presented.

EEG has high temporal resolution, but spatial resolution is low due to the influence of the low conductivity of the skull and the limited number of the electrodes. Cortical dipole imaging has been developed to visualize brain electrical activity in high spatial resolution. It is necessary to solve an inverse problem to estimate the cortical dipole distribution from scalp EEG. In this study, we paid attention to Lasso regression using L1 norm as a solution for the inverse problem, and compared the accuracy with the conventional Ridge regression using L2 norm (Tikhonov regularization). We simulated the cortical dipole imaging using dipole sources on a 2D head model. After that we estimated the dipole distribution by performing Ridge and Lasso regression from the scalp potential. As a result, the localized dipole distribution was obtained using Lasso regression and it was better than that Ridge regression.

The ERP can be estimated by averaging the responses to multiple target stimuli and suppressing background EEG and artifacts. As the number of responses used for averaging increases, the effect of suppressing components other than EPR becomes higher, but the longer the measurement time, the greater the mental and physical burden on the subject. Therefore, we aim to shorten the measurement time by using EEGNet, which is one of the deep learning networks. Here, by learning so that the network outputs 1 for the input of the response of the target stimulus and 0 for the response of the non-target stimulus, the ERP is estimated by the weighted averaging using the output value as the weight for the response. As a result, compared to the conventional averaging, the P300 showed a 14% larger amplitude with a 13% smaller number of responses while maintaining the waveform shape and the peak latency.

The P300 is widely used in character input by EEG. Generally, a computer algorithm that accurately detects P300 is used to identify a target character with high accuracy. However, there are no reports of approaches that cause subjects to generate prominent P300 for easy detection. We use feedback that informs the subject of the evaluation score inside the computer in real time. Therefore, when the score of the target character is high, the subject tries to maintain the state, and when the score is low, the subject pays more attention to the stimulus to raise the score, thereby promoting the prominent appearance of P300. In this study, the font size of the presented characters was changed according to the score, and the accuracy was evaluated with and without feedback. As for the results, 7 out of 10 subjects gave better results with feedback.

Visual environmental changes dynamically, which causes change of object image reflected in the retina. However, we can identify an object from others effortlessly in daily life. This study focused on the change in viewing angle and aimed to elucidate the underlying neural processing for view-invariant object recognition. Inferotemporal cortex locates at the end of ventral cortical pathway which is critical for object recognition and discrimination. We have previously investigated the inferotemporal cell stimulus selectivity to the training object images and its change during object discrimination learning. In the present study, we generated response vectors using the firing frequency data of a cell population in inferotemporal cortex, and created object discrimination classifiers by training with the set of vectors with machine learning algorithm. Furthermore, we proposed a method with much higher temporal resolution to visualize the formation process of view-invariant object recognition, by shortening analysis window.

Diffusion MRI is a group of methods that track water diffusion in vivo. Among them, diffusional kurtosis imaging (DKI) can quantify water diffusion using a few parameters. One of the parameters, diffusional kurtosis (K) statistically expresses how sharp the peak of a probability density function of water diffusion is. Parameters are inferred by various methods, such as the closed-form expressions and the least-squares method. While DKI is useful for quantifying non-Gaussian water diffusion, it is also sensitive to noise on diffusion-weighted images (DWIs). This noise-sensitivity can cause inference errors, which appears as black or white pixels. The purpose of this study was to investigate how K inference can be improved by applying denoising filters on DWIs. Through experiments using clinical data, we examined four filters such as PCA using the Marcenko-Pastur distribution, local PCA, non-local means, and convolutional neural networks.

Recent advances in optics and genetical engineering open new doors for developing novel sensory prostheses. Optogenetic stimulation has an advantage in targeting selective neural populations. However, fundamental neural dynamics is not well known. Here, with high-density neural probes under the anesthetized conditions, we addressed electrophysiological characterization in the activity of V1 neurons in the primary visual cortex (V1) where suppressing parvalbumin-positive inhibitory neurons using PV-cre transgenic rats and cre-dependent adeno associate virus for highly targeted expression of the optogenetic silencer, eNpHR-3.0. Optical stimulation was focused to the surface of the brain with collimating lenses and controlled with one-board microcomputer. A shot-term increase in spiking rate at the time of optical stimulation was found in about 20% of excitatory neurons. The analysis of local field potentials and spiking activity revealed that the optically evoked spiking activity were highly synchronized to the specific ranges of oscillations resembling normal visual responses.

We examined the phase of steady-state visual evoked potentials (SSVEPs) to evaluate binocular vision in 17 healthy subjects (39.5±10.2 years old, 15 men). VEP signals were recorded by a headset-type EEG device (TOKAI Orb, TOKAI OPTICAL CO., LTD.). Visual stimuli were presented at 15 Hz to the lower half of the visual field under three conditions, dominant eye, non-dominant eye, and both. The 15-Hz SSVEPs were obtained by Fourier transform at five electrodes PO7, O1, Oz, O2, and PO8 linked to A1A2. The phase of 15-Hz SSVEP was compared among three conditions. Results showed that the phase of the binocular condition was significantly advanced than that of the dominant eye condition by 2.1 ms and the non-dominant eye condition by 1.5 ms at O1, and than that of the dominant eye condition by 2.5 ms at Oz. It was suggested that binocular vision could be evaluated using the SSVEP phase.

Pain management is one of the important treatments of cancer patients. This study aims to develop a classifier of chronic cancer pain patients from their brain metabolic activity measured by FDG-PET. We compared FDG-PET brain images of 74 painful and 29 painless cancer patients to clarify the brain activity specific to chronic pain of cancer. Using the detected brain activity pattern, we further developed a classifier that determines the presence or absence of chronic pain from PET brain images by machine learning methods. The painful cancer patients showed significantly increased activity in the amygdala, hippocampus, and decreased activity in the cingulate gyrus and precuneus (p<0.001, uncorrected). The proposed classifier was able to identify patients with chronic pain with a sensitivity of approximately 90%, while the specificity was approximately 60%. Further research is required to improve the specificity by selecting better regions of interest and classification algorithms.

Mu rhythm, which is one of the characteristic waves of EEG, has been studied for applying EEG-based brain-computer interfaces (BCI) because it is attenuated when he or she visualizes performing a motor action. However, even now, the accuracy of the classification of intention is not sufficient for practical use. To improve the accuracy of BCI using mu rhythm, we investigated the effects of background colors on stimulating movies. In the experiment, the subjects were asked to visualize hand motor action following the movie of hand motions. Four colors, blue, red, green, and achromatic color, were used for the background of the movie, and each power of mu rhythm was measured. As a result, it was revealed that green and achromatic colors are effective to BCI using mu rhythm because the powers of these colors were more attenuated than that of other colors.

A 4-class BCI system presenting two oddball tone sequences each of which has two kinds of deviant tones was tested. The BCI has been studied as an effective communication tool for those who have neuromuscular disorders. Among many types of BCI systems, the system uses the auditory stimuli can be operated by those who visually impaired. The authors proposed the auditory BCI system based on auditory stream segregation that alternatively presented tones with different frequencies are perceived as segregated auditory streams. To increase selections of this system, it is required to increase the number of auditory streams. However, the maximum number of the selection is limited since the limitation of the auditory sensation area. In this study, the system detects 4-selections from two auditory streams was proposed. Each stream involves oddball paradigm which has two deviant stimuli. subjects were requested to attend to one out of the four deviant tones.

The authors have been studying techniques for diagnosing diseases from patients' voices. In this study, we propose a method for accurately detecting mild cognitive impairment (MCI) through voice analysis.

We recruited forty-five elderly subjects (twenty-five males and twenty females, aged sixty-five years or older), conducted a cognitive function test through mini-mental state examination (MMSE) , and collected their voice recordings of reading thirteen types of fixed phrases. The subjects were categorized into the healthy group (MMSE-score > 27) and the MCI group (23 < MMSE-score < 28), and 6552 features were determined from their voices. Subsequently, we applied logistic regression analysis on these features for creating a discriminator.

Consequently, a discriminator comprising eight voice features was obtained, which can distinguish between the healthy group and MCI group with 78% accuracy.

Although the resultant accuracy is based on the analyzed data, it suggests that MCI can be detected from subjects' voices.

The purpose of this study is to clarify the difference in sleep EEG irregularities between PD with SAS patient group and non-PD with SAS patient group. We analyzed the EEG data (the first 3-min long data with same sleep stage) of the patients from both groups and calculated the sample entropy (SpEn) for each sleep stage. SpEn quantifies the irregularity of the time series. We also analyzed the EEG data of healthy subjects from the Sleep-EDF database (PhysioNet). Both PD with SAS group and non-PD with SAS group showed significantly lower values of SpEn of EEG measured around Pz-Oz than healthy subjects in non-REM1. On the contrary, they showed significantly higher values of SpEn of EEG measured around Fz-Cz than healthy subjects in non-REM3. These results imply that irregularities of EEG time series patterns during sleep are affected by SAS, while PD has no effect on it.

Our brain works with a complex network of hundreds of millions of cells and their components. With recent advances in measurement technology, the size of data on brain connectivity is becoming larger, and more efficient compression methods are needed. In this study, we applied a Neural Embedding methods based on Deep AutoEncoder (DAE) to compress the data into small data that can be recovered naturally. We then analized what features of the brain were captured by the compressed data, comparing it to several network variables and principal components (PC). We also compared its performance with that of Principal Component Analysis (PCA), which is a linear classical dimensional compression. Here, we targeted the interaction networks among neurons derived from neuronal spikes. This compression scheme will help us to interpret the properties of the connectivity architecture between neurons associated with diseases in a simple and automatic way.

In our brain, spikes, steep potential changes, emitted by a group of neurons interact with each other with temporal dynamics.Neuronal spike data is essential information for understanding the function and structure of the brain's nerves, but acquiring the data involves animal experiments, and it is especially difficult to acquire large amounts of data for a group of diseases. Therefore, this study proposes artificial generation of neuronal spike data, assuming its significance in terms of Replace in the 3Rs of animal experiments in the future.We generated artificial spike data based on real spike data obtained from the cerebral cortex or rodents and learned its characteristics by machine learning. We evaluated the generated data in terms of not only the firing rate but also of the synchronous firing probability between cells, and successfully observed that both the real data and the training using simulated data correctly captured their characteristics.

Atherosclerosis is one of the factors that cause serious diseases such as myocardial infarction and cerebral infarction, but the early diagnosis is difficult because there are no subjective symptoms of atherosclerosis. In order to enable early diagnosis, there are researches that uses mathematical models that represents the progression of atherosclerosis in terms of plaque accumulation in blood vessels. These models include many variables based on biochemistry, such as pro-inflammatory mediators in the blood, and it is difficult to obtain these variables in clinical practice. Therefore, if it is possible to construct a mathematical model using non-invasive variables, it will be of great clinical value. OCT is one of the technologies that have high enough spatial resolution to observe micro-vessels in the fundus without invasion. Doppler OCT is capable of measuring retinal blood flow. In this study, we construct a mathematical model of plaque accumulation that incorporates retinal blood flow information.

You often find a target symbol quickly. According to Hick's law, the search time is proportional to the logarithm of the number of symbols. In other words, the visual search is optimized in the sense that the search time does not become longer proportional to the increase of symbols. The visual mechanism enabling the target symbol to be found quickly is under investigation. In order to clarify what factor affects the search time, we analyzed the data which the participants were able to find the target out in visual search experiments. As a result, it was clarified that the distance between the initial point of gaze before search and the target position seldom affect the search time. The correlation coefficient was almost zero.

Total hip arthroplasty used by an artificial hip joint is frequently performed to treat hip joint diseases such as the osteoarthritis and the osteonecrosis of the femoral head. However, the joint dislocation easily occurs due to the muscle resection after the surgery. An artificial hip joint with a structure for preventing dislocation was proposed in this study. The acetabular cup of the joint has an inset part which is defined as the cup part over hemisphere line of the artificial head. In the present study, the dislocation moment was estimated using the finite element method. The rotational displacement was applied to the artificial head to obtain the relationship between the dislocation moment and inset height. Analytical results showed that dislocation moment increased with the increase of the inset height. We have an insight into the optimal structure of artificial hip joint to prevent dislocation under moments.

In pre-operative planning of sagittal split ramus osteotomy, it is desirable to consider three-dimensional contact pressure analysis of a patient's temporomandibular joint in order to determine fixation position of divided bone fragments. Additionally, it is required to construct a three-dimensional surface model of a patient's mandible including teeth region in pre-processing of the contact pressure analysis. Since these become time-consuming tasks for surgeons, we propose a convolutional neural network-based automated segmentation method of the mandible including teeth region from 3D head CT images. In this study, we compare the segmentation accuracy on cross-sectional images in order to achieve accurate shape extraction of the temporomandibular joint.

The plantar fascia is tensed by the dorsiflexion of the MTP joint. The longitudinal arch is elevated by the windlass mechanism (WM). We aimed to analyze WM by measuring the height of the navicular in three-dimensionally.17 feet were examined. The foot CT in the middle and dorsiflexion positions was taken by non-weightbearing and full weightbearing. The height of the navicular was measured from the board of the foot to the most plantar point of navicular bone.The height increased an average of 2.63 mm in non-weightbearing and an average of 2.12 mm in the full weightbearing. There was no significant difference between each condition.This study indicates that the height increased in both conditions and the effect of WM was confirmed. The elevation of the arch tended to be lower than in the non-weightbearing, due to the stretched plantar fascia by weightbearing.

The purpose of this study is to analyze the behavior of bubble-surrounded cells (BSCs) by considering the non-linearity and surface characteristics of bubbles under ultrasound exposure. First, the oscillation of bubbles were analyzed using the Rayleigh-Plesset equation, which describes time variation of bubble radius. Next, acoustic radiation force on a BSC was calculated with time average of the volume of bubbles, spatial distribution of sound pressure, viscosity coefficient representing the surface condition of bubbles, and the number of bubbles attached on a cell. Finally, the behavior of a BSC was reproduced by the acoustic force and drag force received from the fluid. By implementing the above factors, we found that the magnitude of the viscosity coefficient greatly affected the acoustic radiation force. As a result, it was theoretically shown that the behavior of BSCs could be affected greatly depending on the parameters of bubbles and acoustic conditions.

Electrical excitation of the heart initiates from the sinoatrial node which is a physiological pacemaker in the normal heart. Premature excitation generated from an abnormal heart could be related to the arrhythmia. In clinically, to distinguish a location of premature excitation is important to treat the heart using ablation therapy. In this study, we investigated relationships between the location of premature excitation in the ventricles and characteristics of vectorcardiogram (VCG) which relates to pattern of excitation propagation in the heart. We simulated excitation propagation in the whole ventricles in physiological and abnormal conditions using supercomputer and calculated the VCG theoretically. Characteristics of VCG in abnormal beats were obviously different compared to that of normal beat and reflected the location of premature excitation in the heart. The method used in this study might be useful to predict the location of the premature excitation theoretically.

Background: Atrial fibrillation (AF) is a high prevalence arrhythmia causing heart failure and/or cerebral infarction. To improve the treatment, understanding the complicated excitation propagation during AF is required. However, the biological information obtained from the electrocardiograms is limited. Objectives: To investigate the excitation propagation during sinus rhythm and AF, computer simulation was performed in a 3D model of human atria.Methods: The 3D atrial model was constructed based on human MRI data, and simulated atrial excitation propagation was visualized.Results and Discussion: In the human atrial model, the excitation propagation during sinus rhythm was virtually reproduced. In the next step, we plan to increase the number of myocardial units and to perform large-scale AF simulation. In addition, we will try to improve the software visualizing AF observed in clinical practice. In the near future, more effective visualization technique will be required for proposing novel strategy for refractory non-paroxysmal AF treatment.

Recently, transcatheter aortic valve implantation (TAVI) has been performed with good results in patients with severe aortic stenosis who are considered to be at high risk or difficult to attempt surgical aortic valve replacement. However, if there is a gap between the aorta and the artificial valve, paravalvular leakage (PVL) is generated, so wake and recirculation area occurs. In their areas, they are high risks for thrombosis. But the details of the formation mechanism have not been clarified yet.In this study, thrombus formation around PVL model was quantified, and flow field using model of artificial valve was also analyzed by CFD. Thrombus formation around the PVL model is visualized. In addition, the effect of the gap size on thrombus formation is investigated. The effect of the flow field on the mechanism of thrombus formation is also evaluated by comparing the CFD results with the experimental results.

Computational simulation of blood flow through the microvascular networks relies on precise image reconstruction of the microvascular networks. We previously proposed a novel quantification method for vessel diameters along centerlines of the single vessels. However, it has been difficult to determine vessel diameters in the branch areas where three vessels merged. The present study therefore aimed to propose an image analysis method for quantification and 3D reconstruction of the microvascular images. Because of the asymmetric structure of the vessel branches, a radius (i.e., the minimum distance from the center points to the vascular wall) was automatically measured. To determine the accuracy of the image reconstruction, binarized raw images were used as a grand truth, and a ratio for truly and falsely reconstructed vascular regions was compared. The conventional method overestimated about 20% relative to the ground truth, while it was about 2% for the proposed method.

Currently, iPS cell-derived cardiomyocytes are important as cell materials, and a high-speed, automated quality evaluation method is required for their practical application. Focusing on the fact that magnetic field measurement is non-invasive, non-contact, and non-destructive, we investigated a method for evaluating cells by measuring the magnetic field with SQUID magnetometer. In this study, we developed an effective method for detecting small biological signals of cultured cells from measurement data. First, mathematical models that reproduce the action potentials of mouse iPS cell-derived cardiomyocytes were developed. Next, we simulated the magnetic field generated from the cultured cell population. Furthermore, deep learning was performed using the simulated magnetic field waveforms, and measurement data from cardiomyocytes were analyzed by the trained network. As a result, we succeeded in detecting magnetic signals that periodically correspond to the beats observed with an optical microscope and the field potentials, thus demonstrating the effectiveness of this method.

We have developed a novel deep learning network model to predict the hemodynamics in a short time from the aorta shape. However this network model needs a location registration in advance. The aim of this study is to find out relations between the location gap of the input data and prediction accuracy.Prediction accuracy was evaluated by the mean square error(MSE) of the velocity. The area where the training data exists was called the training range. One test data was located inside and outside of this range. Within the training range, there is the position where the prediction accuracy becomes higher than the original position. Outside of the range, there is non-linear tendency of sudden drop in accuracy. The errors become particularly large in the part where the patient-specific flow is observed.This study showed the importance of the location registration for the prediction accuracy on our network model.

We have previously proposed a system CellCompiler that generates simulation program from combination of cell model written in CellML format and numerical solution file written in TecML 2.0 format. TecML file describes numerical solution of differential equations with recurrence relation equations, however the CellCompiler had limitations in TecML file, for example proper values for the indices of variables have to be assigned with which the recurrence relation equations becomes computable. We proposed an algorithm that converts TecML 3.0 recurrence relation equations which do not have these limitations into TecML 2.0 format which can be used by CellCompiler.

Recent biological function models are often constructed from large number of functional elements, that have complex interactions each other. To understand the mechanisms of these models, bifurcation analysis or lead potential analysis methods are applied, however, these methods have problem that the mechanism of the target system have to be at least roughly known. We proposed a method which use Jacobian Matrix of the biological function models that are written by differential equations, to visualize the interactions between the functional elements by directed graphs. By using the method, we could visualize the ion current system at depolarizing phase and at early afterdepolarization phase of cardiac cell model.

EAD is suggested as one of the causes of ventricular fibrillation. We examined the mechanisms of generation and propagation of EADs by using a one-dimensional unit model, which was composed of two types of human ventricular cell models; normal and EAD-prone cells. In the EAD-prone cells, EAD was evoked by retarding the slow inactivation of the slow component of the Na+ current. We found that EADs were evoked repetitively because of Ca2+-dependent activation of the Na+-Ca2+ exchangers and reduction of the Na+- K+ pump current and/or propagation of the excitations through gap junction channels to adjacent repolarized cells. By blocking the gap junction currents, it was revealed that each EAD-prone cell generates EADs independently. The boundary between EAD-prone cells and normal cells was one of the factors that evoked repetitive EAD discharges. In the present study, the comprehensive ionic mechanisms underlying the repetitive discharge and propagation of EADs were revealed.

It is known that the incidence of pulmonary cysts after surgery differs depending on the shape of the staple line. We have created two simple models in which the lung is cut along the horizontal line on the lung surface (type I) or in convex toward the lung's deep part (type V) and analyzed using the finite element method. We reported that higher stress was generated in type I at the staple line's endpoint in the past meeting. A stress-strain diagram of the pulmonary pleura measured for the porcine pleura was used in the present work. As a result, the stress distribution and deformation are similar to the previous results for both type I and type V. It implies that the shape of the staple line is an important factor of the stress concentration along the staple line.

In video-assisted thoracoscopic surgeries, the precise estimation of lung deformation between the inflated lung in the computed tomography (CT) images during preoperative planning and the deflated lung in the treatment views during surgery is expected. The purpose of this study is to develop a deformation estimation method of the 3D surface of a deflated lung from a few partial observations. To estimate deformations for a largely deformed lung, a kernel regression-based solution was introduced. The proposed method used a few landmarks to capture the partial deformation between the 3D surface mesh obtained from preoperative CT and the intraoperative anatomical positions. The method was applied on nine datasets of the left lungs of live Beagle dogs. Contrast-enhanced CT images of the lungs were acquired. The proposed method achieved a local positional error of vertices of 2.74 mm, Hausdorff distance of 6.11 mm, and Dice similarity coefficient of 0.94.

The purpose of this study is elucidating the mechanism of acoustic radiation force, which acts on a thin catheter to be bend, by referring a theory of previous research considering an elastic tube. To reproduce the behavior of thin catheter, acoustic radiation function, acoustic intensity, and the size of the catheter should be taken into account to calculate acoustic radiation force. We found that there was a condition to obtain stable acoustic radiation force when the tube was filled with a specific gas according to the wall thickness. In addition, we succeeded to reproduce similar tendencies as the preceding experimental results in our laboratory. In this study, we were able to theoretically confirm the conditions to obtain acoustic radiation force on thin catheter more effectively.

Hemodialysis is a type of the renal replacement therapies for patients with renal failure. Treatment efficiency of hemodialysis is affected by stenosis of vessels and blood flow. Treatment efficiency decreases when recirculation occurs, so recirculation should be avoided. But, because the shape of blood vessels and blood flow are different for each patient, there is no effective measure for all cases. So, I used Computational Fluid Dynamics (CFD) analysis to simulate blood flow. This time, I used a tube and a glycerin solution to measure recirculation rate in 15 patterns of vascular models. Then, the values obtained in the experiment were compared with the recirculation rate estimated by CFD analysis. The recirculation rates estimated by the two methods were in good agreement. CFD analysis was able to simulate blood flow during hemodialysis. In addition, it may be able to suggest needle positions and vessel shapes to suppress recirculation.

Model Predictive Control (MPC) is an optimal control technique where control action is obtained by minimizing the objective (cost) function subject to the model equation of the plant. In this basic study, the feasibility of MPC for Functional Electrical Stimulation (FES) using a simple identified model was investigated. The MPC-FES controller was examined in controlling the 1-D OF movement of the wrist joint through computer simulation. The dynamic models of the wrist joint movements were developed by using the step response of an electrically stimulated musculoskeletal system for each subject. The average model of the step responses of several subjects has also been used to test the feasibility of the MPC for FES. Computer simulation tests showed that the MPC-FES controller with a simple model based on step response of each subject as well as the average model was able to follow the desired movement trajectory with small error.