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Abstract Beauty is related to our lives in various ways and examining it from an interdisciplinary approach is essential. People are very concerned with their appearance. A widely accepted beauty ideal is that the thinner an individual is, the more beautiful they are. However, the effect of continuous motion on body form aesthetics is unclear. Additionally, an upright pelvic posture in the sagittal plane during walking seems to affect the aesthetic judgments of female appearance. We directly analyzed the influence of body form and walking pattern on aesthetic visual impressions from a third-person perspective with a two-way analysis of variance. Captured motion data for three conditions—upright pelvis, normal pelvis, and posteriorly tilted pelvic posture—were applied to each of three mannequins, representing thin, standard, and obese body forms. When participants watched stimulus videos of the mannequins walking with various postures, a significantly higher score for aesthetic visual impression was noted for an upright pelvic posture than for a posteriorly tilted pelvic posture, irrespective of body form (F (2, 119) = 79.89, p

Pathological gait in patients with Hakim’s disease (HD, synonymous with idiopathic normal-pressure hydrocephalus; iNPH), Parkinson’s disease (PD), and cervical myelopathy (CM) has been subjectively evaluated in this study. We quantified the characteristics of upper and lower limb movements in patients with pathological gait. We analyzed 1491 measurements of 1 m diameter circular walking from 122, 12, and 93 patients with HD, PD, and CM, respectively, and 200 healthy volunteers using the Three-Dimensional Pose Tracker for Gait Test. Upper and lower limb movements of 2D coordinates projected onto body axis sections were derived from estimated 3D relative coordinates. The hip and knee joint angle ranges on the sagittal plane were significantly smaller in the following order: healthy > CM > PD > HD, whereas the shoulder and elbow joint angle ranges were significantly smaller, as follows: healthy > CM > HD > PD. The outward shift of the leg on the axial plane was significantly greater, as follows: healthy < CM < PD < HD, whereas the outward shift of the upper limb followed the order of healthy > CM > HD > PD. The strongest correlation between the upper and lower limb movements was identified in the angle ranges of the hip and elbow joints on the sagittal plane. The lower and upper limb movements during circular walking were correlated. Patients with HD and PD exhibited reduced back-and-forth swings of the upper and lower limbs.

The accurate estimation of lower-limb joint angles and moments is crucial for assessing the progression of orthopedic diseases, with continuous monitoring during daily walking being essential. An inertial measurement unit (IMU) attached to the lower back has been used for this purpose, but the effect of IMU misalignment in the frontal plane on estimation accuracy remains unclear. This study investigated the impact of virtual IMU misalignment in the frontal plane on estimation errors of lower-limb joint angles and moments during walking. Motion capture data were recorded from 278 healthy adults walking at a comfortable speed. An estimation model was developed using principal component analysis and linear regression, with pelvic accelerations as independent variables and lower-limb joint angles and moments as dependent variables. Virtual IMU misalignments of −20°, −10°, 0°, 10°, and 20° in the frontal plane (five conditions) were simulated. The joint angles and moments were estimated and compared across these conditions. The results indicated that increasing virtual IMU misalignment in the frontal plane led to greater errors in the estimation of pelvis and hip angles, particularly in the frontal plane. For misalignments of ±20°, the errors in pelvis and hip angles were significantly amplified compared to well-aligned conditions. These findings underscore the importance of accounting for IMU misalignment when estimating these variables.

BackgroundA distal radius fracture (DRF) is a common initial fragility fracture among women in their early postmenopausal period, which is associated with an increased risk of subsequent fractures. Gait assessments are valuable for evaluating fracture risk; inertial measurement units (IMUs) have been widely used to assess gait under free-living conditions. However, little is known about long-term changes in patients with DRF, especially concerning daily-life gait. We hypothesized that, in the long term, the daily-life gait parameters in patients with DRF could enable us to reveal future risk factors for falls and fractures. ObjectiveThis study assessed the spatiotemporal characteristics of patients with DRF at 4 weeks and 6 months of recovery. MethodsWe recruited 16 women in their postmenopausal period with DRF as their first fragility fracture (mean age 62.3, SD 7.0 years) and 28 matched healthy controls (mean age 65.6, SD 8.0 years). Daily-life gait assessments and physical assessments, such as hand grip strength (HGS), were performed using an in-shoe IMU sensor. Participants’ results were compared with those of the control group, and their recovery was assessed for 6 months after the fracture. ResultsIn the fracture group, at 4 weeks after DRF, lower foot height in the swing phase (P=.049) and higher variability of stride length (P=.03) were observed, which improved gradually. However, the dorsiflexion angle in the fracture group tended to be lower consistently during 6 months (at 4 weeks: P=.06; during 6 months: P=.07). As for the physical assessments, the fracture group showed lower HGS at all time points (at 4 weeks: P

Abstract Background Gait decline in older adults is related to falling risk, some of which contribute to injurious falls requiring medical attention or restriction of activity of daily living. Among injurious falls, distal radius fracture (DRF) is a common initial fragility fracture associated with the subsequent fracture risk in postmenopausal females. The recent invention of an inertial measurement unit (IMU) facilitates the assessment of free-living gait; however, little is known about the daily gait characteristics related to the risk of subsequent fractures. We hypothesized that females with DRF might have early changes in foot kinematics in daily gait. The aim of this study was to evaluate the daily-life gait characteristics related to the risk of falls and fracture. Methods In this cross-sectional study, we recruited 27 postmenopausal females with DRF as their first fragility fracture and 28 age-matched females without a history of fragility fractures. The participants underwent daily gait assessments for several weeks using in-shoe IMU sensors. Eight gait parameters and each coefficient of variance were calculated. Some physical tests, such as hand grip strength and Timed Up and Go tests, were performed to check the baseline functional ability. Results The fracture group showed lower foot angles of dorsiflexion and plantarflexion in the swing phase. The receiver operating characteristic curve analyses revealed that a total foot movement angle (TFMA)

Understanding past and current trends is crucial in the fashion industry to forecast future market demands. This study quantifies and reports the characteristics of the trendy walking styles of fashion models during real-world runway performances using three cutting-edge technologies: (a) publicly available video resources, (b) human pose detection technology, and (c) multivariate human-movement analysis techniques. The skeletal coordinates of the whole body during one gait cycle, extracted from publicly available video resources of 69 fashion models, underwent principal component analysis to reduce the dimensionality of the data. Then, hierarchical cluster analysis was used to classify the data. The results revealed that (1) the gaits of the fashion models analyzed in this study could be classified into five clusters, (2) there were significant differences in the median years in which the shows were held between the clusters, and (3) reconstructed stick-figure animations representing the walking styles of each cluster indicate that an exaggerated leg-crossing gait has become less common over recent years. Accordingly, we concluded that the level of leg crossing while walking is one of the major changes in trendy walking styles, from the past to the present, directed by the world’s leading brands.

We aimed to capture the fluctuations in the dynamics of body positions and find the characteristics of them in patients with idiopathic normal pressure hydrocephalus (iNPH) and Parkinson’s disease (PD). With the motion-capture application (TDPT-GT) generating 30 Hz coordinates at 27 points on the body, walking in a circle 1 m in diameter was recorded for 23 of iNPH, 23 of PD, and 92 controls. For 128 frames of calculated distances from the navel to the other points, after the Fourier transforms, the slopes (the representatives of fractality) were obtained from the graph plotting the power spectral density against the frequency in log–log coordinates. Differences in the average slopes were tested by one-way ANOVA and multiple comparisons between every two groups. A decrease in the absolute slope value indicates a departure from the 1/f noise characteristic observed in healthy variations. Significant differences in the patient groups and controls were found in all body positions, where patients always showed smaller absolute values. Our system could measure the whole body’s movement and temporal variations during walking. The impaired fluctuations of body movement in the upper and lower body may contribute to gait and balance disorders in patients.

Identifying the characteristics of fallers is important for preventing falls because such events may reduce quality of life. It has been reported that several variables related to foot positions and angles during gait (e.g., sagittal foot angle and minimum toe clearance) differ between fallers and non-fallers. However, examining such representative discrete variables may not be sufficient to detect crucial information, which may be contained in the large portions of unanalyzed data. Therefore, we aimed to identify the comprehensive characteristics of foot position and angle during the swing phase of gait in non-fallers and fallers using principal component analysis (PCA). Thirty non-fallers and 30 fallers were recruited for this study. We performed PCA to reduce the dimensions of foot positions and angles during the swing phase and obtained principal component scores (PCSs) for each principal component vector (PCV), which were then compared between groups. The results revealed that the PCS of PCV3 in fallers was significantly larger than that in non-fallers (p = 0.003, Cohen’s d = 0.80). We reconstructed waveforms of foot positions and angles during the swing phase using PCV3 and our main findings can be summarized as follows. Compared to non-fallers, fallers have a 1) low average foot position in the z-axis (i.e., height) during the initial swing phase 2) small average foot angle in the x-axis (i.e., rotation in the sagittal plane), during the initial swing phase, and 3) large variability in foot position in the y-axis (i.e., anterior/posterior position) during the initial swing phase. We can conclude that these are characteristics of gait related to fallers. Therefore, our findings may be beneficial for evaluating fall risk during gait using a device such as a shoe- or insole-embedded inertial measurement unit.

Abstract Emojis are frequently used by people worldwide as a tool to express one’s emotional states and have recently been considered for assessment in research. However, details regarding the ways in which they correspond to human emotional states remain unidentified. Thus, this study aimed to understand how emojis are classified on the valence and arousal axes and to examine the relationship between the former and human emotional states. In an online survey involving 1082 participants, a nine-point scale was employed to evaluate the valence and arousal levels of 74 facial emojis. Results from the cluster analysis revealed these emojis to be categorized into six different clusters on the two axes of valence and arousal. Further, the one-way analysis of variance indicated that these clusters have six valence and four arousal levels. From the results, each cluster was interpreted as (1) a strong negative sentiment, (2) a moderately negative sentiment, (3) a neutral sentiment with a negative bias, (4) a neutral sentiment with a positive bias, (5) a moderately positive sentiment, and (6) a strong positive sentiment. Therefore, facial emojis were found to comprehensively express the human emotional states.

Abstract Frailty is associated with gait variability in several quantitative parameters, including high stride time variability. However, the associations between joint kinematics during walking and increased gait variability with frailty remain unclear. In the current study, principal component analysis was used to identify the key joint kinematics characteristics of gait related to frailty. We analyzed whole kinematic waveforms during the entire gait cycle obtained from the pelvis and lower limb joint angle in 30 older women (frail/prefrail: 15 participants; non-frail: 15 participants). Principal component analysis was conducted using a 60 × 1224 input matrix constructed from participants’ time-normalized pelvic and lower-limb-joint angles along three axes (each leg of 30 participants, 51 time points, four angles, three axes, and two variables). Statistical analyses revealed that only principal component vectors 6 and 9 were related to frailty. Recombining the joint kinematics corresponding to these principal component vectors revealed that frail older women tended to exhibit greater variability of knee- and ankle-joint angles in the sagittal plane while walking compared with non-frail older women. We concluded that greater variability of knee- and ankle-joint angles in the sagittal plane are joint kinematic characteristics of gait related to frailty.

BackgroundThe Sustaining Health by Integrating Next-generation Ecosystems (SHINE) Study was developed as a data platform that incorporates personal health records (PHRs) into health-related data at the municipal level in Japan. This platform allows analyses of the associations between PHRs and future health statuses, and supports the production of evidence for developing preventive care interventions. Herein, we introduce the SHINE Study's profile and describe its use in preliminary analyses.MethodsThe SHINE Study involves the collection of participants' health measurements and their addition to various health-related data from the Longevity Improvement & Fair Evidence (LIFE) Study. With cooperation from municipal governments, measurements can be acquired from persons enrolled in government-led long-term care prevention classes and health checkups who consent to participate in the SHINE Study. For preliminary analyses, we collected salivary test measurements, lifelog measurements, and gait measurements; these were linked with the LIFE Study's database. We analyzed the correlations between these measurements and the previous year's health care expenditures.ResultsWe successfully linked PHR data of 33 participants for salivary test measurements, 44 participants for lifelog measurements, and 32 participants for gait measurements. Only mean torso speed in the gait measurements was significantly correlated with health care expenditures (r = -0.387, P = 0.029).ConclusionThe SHINE Study was developed as a data platform to collect and link PHRs with the LIFE Study's database. The analyses undertaken with this platform are expected to contribute to the development of preventive care tools and promote health in Japan.

Herein, we report two paediatric cases of ovarian teratoma-associated anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis. We performed surgical resection of the teratomas—enucleation in case 1 and salpingo-oophorectomy in case 2. The pathological diagnoses were immature teratomas with a small number of neuroglial elements, and cerebrospinal fluid (CSF) anti-NMDAR antibody test was positive in both cases. In case 1, the patient showed excellent recovery, and in case 2, neurological symptoms gradually improved. Paediatric cases of ovarian teratoma-associated anti-NMDAR encephalitis are rare, and early surgical resection and immunotherapy are important for good prognosis. We highlight the occurrence of paediatric cases of ovarian teratoma-associated anti-NMDAR encephalitis to create awareness and highlight the importance of surgical resection despite severe neurological symptoms.

Distinguishing pathological gait is challenging in neurology because of the difficulty of capturing total body movement and its analysis. We aimed to obtain a convenient recording with an iPhone and establish an algorithm based on deep learning. From May 2021 to November 2022 at Yamagata University Hospital, Shiga University, and Takahata Town, patients with idiopathic normal pressure hydrocephalus (n = 48), Parkinson’s disease (n = 21), and other neuromuscular diseases (n = 45) comprised the pathological gait group (n = 114), and the control group consisted of 160 healthy volunteers. iPhone application TDPT-GT captured the subjects walking in a circular path of about 1 meter in diameter, a markerless motion capture system, with an iPhone camera, which generated the three-axis 30 frames per second (fps) relative coordinates of 27 body points. A light gradient boosting machine (Light GBM) with stratified k-fold cross-validation (k = 5) was applied for gait collection for about 1 min per person. The median ability model tested 200 frames of each person’s data for its distinction capability, which resulted in the area under a curve of 0.719. The pathological gait captured by the iPhone could be distinguished by artificial intelligence.

Abstract Background Walking speed is an important measure associated with health outcomes in older individuals, such as dependency and death. This study aimed to examine whether the walking speed of community-dwelling older adults varies between time periods within a day, as measured outdoors in daily life. We aimed to determine the types of walking speed variations and examine the factors associated with them. Methods Daily life outdoor walking speed was measured in 92 participants (average age 71.9 years±5.64) using a GPS smartphone app for 1 month. Average walking speeds for five time periods were analyzed with a linear mixed model. Intra-day walking speed variation patterns were classified by latent class analysis. Factors associated with the class were identified by logistic regression analysis. Results A statistically significant difference in average walking speed was found between early morning (1.33 m/s), and afternoon (1.27 m/s) and evening (1.26 m/s) (p

Emojis are universal tools that are frequently used to express people’s emotional states throughout daily communications. They are often applied in various fields of research, such as consumer surveys, as indicators of users’ emotional states. Further analyses of emoji interpretation among people with age are required to ensure the validity of emojis as a metric in such fields of research, thereby reducing misunderstandings. However, details regarding the effect of age on both arousal and valence, as they pertain to the interpretation of emojis, remain unclear. Therefore, in this study, we investigate the effects of the interpretation of facial emojis on the arousal-valence space among people of varying age groups. We conducted an online survey involving 2,000 participants, whereby we employed a nine-point scale to evaluate the valence and arousal levels associated with 74 facial emojis. Based on the two axes of valence and arousal among the age groups involved in this study, emojis are categorized into six similar clusters. For the two negative clusters, i.e., strongly negative and moderately negative sentiments, the group involving middle-aged participants showed significantly higher levels of arousal compared to the group involving young participants. Additionally, not all emojis classified into the aforementioned negative clusters indicate age difference. Based on these results, this study recommends using emojis with no age-related effects on the negative clusters as indices for evaluating human emotions.

This paper describes the application of micro-Doppler radar (MDR) to gait classification based on fall risk-related differences using deep learning and gait parameter-based approaches. Two classification problems were considered in this study: elderly non-fallers and multiple fallers were classified to investigate the detection of fall risk-related gait differences, and middle-aged (50s) and elderly (70s) adults were classified to detect aging-related gait differences. The MDR signal data of the participants were simulated using an open motion capture gait dataset. The classification results obtained using the deep learning and gait parameter-based approaches showed that the classification accuracy achieved using a support vector machine with the gait parameters extracted from the MDR signals was better than that resulting from the deep learning of spectrogram (time-velocity distribution) images of the MDR signals for both classification problems. The gait parameter-based approach achieved the classification rates of 79 % for faller/non-faller classification and 82 % for 50s/70s classification, whereas the corresponding accuracies were 73 % and 76 %, respectively, using the deep learning approach. These results reveal that the gait parameters extracted via MDR measurements include sufficient information on gait to detect individuals with a high risk of falls and the gait parameter-based approaches are thus effective for both classification problems.

To assess pathological gaits quantitatively, three-dimensional coordinates estimated with a deep learning model were converted into body axis plane projections. First, 15 healthy volunteers performed four gait patterns; that is, normal, shuffling, short-stepped, and wide-based gaits, with the Three-Dimensional Pose Tracker for Gait Test (TDPT-GT) application. Second, gaits of 47 patients with idiopathic normal pressure hydrocephalus (iNPH) and 92 healthy elderly individuals in the Takahata cohort were assessed with the TDPT-GT. Two-dimensional relative coordinates were calculated from the three-dimensional coordinates by projecting the sagittal, coronal, and axial planes. Indices of the two-dimensional relative coordinates associated with a pathological gait were comprehensively explored. The candidate indices for the shuffling gait were the angle range of the hip joint < 30° and relative vertical amplitude of the heel < 0.1 on the sagittal projection plane. For the short-stepped gait, the angle range of the knee joint < 45° on the sagittal projection plane was a candidate index. The candidate index for the wide-based gait was the leg outward shift > 0.1 on the axial projection plane. In conclusion, the two-dimensional coordinates on the body axis projection planes calculated from the 3D relative coordinates estimated by the TDPT-GT application enabled the quantification of pathological gait features.

Deep-learning-based gait classification of young and elderly adults using micro-Doppler radar (MDR) is presented in this paper. The MDR signal data were accurately simulated using an open motion-capture gait dataset, and deep-learning classification of the time-velocity distribution (i.e., spectrogram) images calculated with the generated data are presented. Utilizing a simulation, we also investigated the body parts deemed most efficient for classification based on their generation of good MDR data. As a result, the classification rate using whole-body data was 74%. However, this classification rate of using only leg data showed an accuracy of 91%, which indicates that the thighs and shanks are efficient target body parts for the gait classification of both young and elderly adults.

AIM: To investigate the regulation and mechanisms of periostin expression in retinal Müller glia, and to explore the relevance to retinal neovascularization. METHODS: The oxygen-induced retinopathy (OIR) mouse model and the human Moorfield/Institute of Ophthalmology-Müller 1 (MIO-M1) cell line were used in the study. Immunofluorescence staining was used to determine the distribution and expression of periostin and a Müller glial cell marker glutamine synthetase (GS). Cytokines TNF-α and IFN-γ were added to stimulate the MIO-M1 cells. ShRNA was used to knockdown periostin expression in MIO-M1 cells. Quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) was conducted to assess the mRNA expression of periostin. RESULTS: Immunofluorescence staining showed that periostin was expressed by MIO-M1 Müller glia. GS-positive Müller glia and periostin increased in OIR retinas, and were partially overlaid. The stimulation of TNF-α and IFN-γ reduced the mRNA expression of periostin significantly and dose-dependently in MIO-M1 cells. Knockdown of periostin reduced mRNA expression of vascular endothelial growth factor A (VEGFA) in MIO-M1 cells, while VEGFA expression was not changed in periostin knock-out OIR retinas. CONCLUSION: Müller glia could be one of the main sources of periostin in the retina, and might contribute to the pathogenesis of retinal neovascularization. Proinflammatory cytokines TNF-α and IFN-γ attenuate the periostin expression in retinal Müller glia, which provides a potential and novel method in treating retinal neovascular diseases.

To quantitatively assess pathological gait, we developed a novel smartphone application for full-body human motion tracking in real time from markerless video-based images using a smartphone monocular camera and deep learning. As training data for deep learning, the original three-dimensional (3D) dataset comprising more than 1 million captured images from the 3D motion of 90 humanoid characters and the two-dimensional dataset of COCO 2017 were prepared. The 3D heatmap offset data consisting of 28 × 28 × 28 blocks with three red–green–blue colors at the 24 key points of the entire body motion were learned using the convolutional neural network, modified ResNet34. At each key point, the hottest spot deviating from the center of the cell was learned using the tanh function. Our new iOS application could detect the relative tri-axial coordinates of the 24 whole-body key points centered on the navel in real time without any markers for motion capture. By using the relative coordinates, the 3D angles of the neck, lumbar, bilateral hip, knee, and ankle joints were estimated. Any human motion could be quantitatively and easily assessed using a new smartphone application named Three-Dimensional Pose Tracker for Gait Test (TDPT-GT) without any body markers or multipoint cameras.

To evaluate the postures in ergonomics applications, studies have proposed the use of low-cost, marker-less, and portable depth camera-based motion tracking systems (DCMTSs) as a potential alternative to conventional marker-based motion tracking systems (MMTSs). However, a simple but systematic method for examining the estimation errors of various DCMTSs is lacking. This paper proposes a benchmarking method for assessing the estimation accuracy of depth cameras for full-body landmark location estimation. A novel alignment board was fabricated to align the coordinate systems of the DCMTSs and MMTSs. The data from an MMTS were used as a reference to quantify the error of using a DCMTS to identify target locations in a 3-D space. To demonstrate the proposed method, the full-body landmark location tracking errors were evaluated for a static upright posture using two different DCMTSs. For each landmark, we compared each DCMTS (Kinect system and RealSense system) with an MMTS by calculating the Euclidean distances between symmetrical landmarks. The evaluation trials were performed twice. The agreement between the tracking errors of the two evaluation trials was assessed using intraclass correlation coefficient (ICC). The results indicate that the proposed method can effectively assess the tracking performance of DCMTSs. The average errors (standard deviation) for the Kinect system and RealSense system were 2.80 (1.03) cm and 5.14 (1.49) cm, respectively. The highest average error values were observed in the depth orientation for both DCMTSs. The proposed method achieved high reliability with ICCs of 0.97 and 0.92 for the Kinect system and RealSense system, respectively.

This study aims to investigate the changes in metamorphopsia after administering the treat-and-extend regimen of anti-vascular endothelial growth factor therapy for branch retinal vein occlusion-associated macular edema. We retrospectively examined 27 patients (27 eyes) with macula edema due to branch retinal vein occlusion who received intravitreal injections of anti-vascular endothelial growth factor agents using the treat-and-extend regimen for ≥18 months. We evaluated best-corrected visual acuity, central macular thickness, macular edema recurrence, and amount of metamorphopsia quantified by M-CHARTS. The best-corrected visual acuity (logarithm of minimum angle of resolution) and central macular thickness significantly improved at 18 months compared to baseline, the median value (interquartile range [IQR]), 0.30 (0.15-0.52) and 459 (373-542) μm at baseline, and 0 (-0.08-0.16) and 267 (232-306) μm at 18 months. The M-CHARTS score (the mean of vertical and horizontal scores) significantly decreased at 1, 6, and 12 months compared to baseline, but worsened at 18 month, the median value (IQR), 0.45 (0.250-0.925), 0.4 (0.15-0.70), 0.4 (0.150-0.625), 0.4 (0.225-0.550) and 0.45 (0.225-0.750) at baseline, 1 month, 6 months, 12 months and 18 months, respectively. The median cumulative number of macular edema recurrences was 2 (IQR, 0.5-3.0) at 18 months. Simple linear regression and multivariate analyses revealed that the change in the mean M-CHARTS score at 18 months was significantly correlated with the baseline score and the cumulative number of macular edema recurrences. Anti-vascular endothelial growth factor therapy using the treat-and-extend regimen improved metamorphopsia in branch retinal vein occlusion-related macular edema in the short to mid-term follow-up period, but not in the long term. Macular edema recurrence may be associated with persistent metamorphopsia.

In a previous study, we developed a classification model to detect fall risk for elderly adults with a history of falls (fallers) using micro-Doppler radar (MDR) gait measurements via simulation. The objective was to create daily monitoring systems that can identify elderly people with a high risk of falls. This study aimed to verify the effectiveness of our model by collecting actual MDR data from community-dwelling elderly people. First, MDR gait measurements were performed in a community setting, and the efficient gait parameters for the classification of fallers were extracted. Then, a support vector machine model that was trained and validated using the simulated MDR data was tested for the gait parameters extracted from the actual MDR data. A classification accuracy of 78.8% was achieved for the actual MDR data. The validity of the experimental results was confirmed based on a comparison with the results of our previous simulation study. Thus, the practicality of the faller classification model constructed using the simulated MDR data was verified for the actual MDR data.

Abstract Surpassing the world record in athletic performance requires extensive use of kinematic and dynamic motion analyses to develop novel body usage skills and training methods. Performance beyond the current world record has not been realized or measured; therefore, we need to generate it with dynamics consistency using forward dynamics simulation, although it is technologically difficult because of the complexity of the human structure and its dynamics. This research develops a multilayered kinodynamics simulation that uses a detailed digital human model and a simple motion-representation model to generate the detailed sprinting performances of individuals with lower extremity amputations (ILEAs) aided by carbon-fiber running-specific prostheses (RSPs), which have complex interactions with humans. First, we developed a digital human model of an ILEA using an RSP. We analyzed ILEA sprinting based on experimental motion measurements and kinematics/dynamics computations. We modeled the RSP-aided ILEA sprinting using a simple spring-loaded inverted pendulum model, comprising a linear massless spring, damper, and mass, and we identified the relevant parameters from experimentally measured motion data. Finally, we modified the sprint motion by varying the parameters corresponding to the RSP characteristics. Here, the forward dynamics have been utilized to simulate detailed whole-body sprinting with different RSP types (including simulated RSPs not worn by the subject). Our simulations show good correspondence with the experimentally measured data and further indicate that the sprint time can be improved by reducing the RSP viscosity and increasing stiffness. These simulation results are validated by the experimentally measured motion modifications obtained with different types of RSPs. These results show that the multilayered kinodynamics simulation using the detailed digital human model and the simple motion-representation model has the capacity to generate complex phenomena such as RSP-aided ILEA sprinting that contains complex interactions between the human and the RSP. This simulation technique can be applied to RSP design optimization for ILEA sprinting.

Abstract Background The Two-Step test is one of three official tests authorized by the Japanese Orthopedic Association to evaluate the risk of locomotive syndrome (a condition of reduced mobility caused by an impairment of the locomotive organs). It has been reported that the Two-Step test score has a good correlation with one’s walking ability; however, its association with the gait pattern of older people during normal walking is still unknown. Therefore, this study aims to clarify the associations between the gait patterns of older people observed during normal walking and their Two-Step test scores. Methods We analyzed the whole waveforms obtained from the lower-extremity joint angles and joint moments of 26 older people in various stages of locomotive syndrome using principal component analysis (PCA). The PCA was conducted using a 260 × 2424 input matrix constructed from the participants’ time-normalized pelvic and right-lower-limb-joint angles along three axes (ten trials of 26 participants, 101 time points, 4 angles, 3 axes, and 2 variable types per trial). Results The Pearson product-moment correlation coefficient between the scores of the principal component vectors (PCVs) and the scores of the Two-Step test revealed that only one PCV (PCV 2) among the 61 obtained relevant PCVs is significantly related to the score of the Two-Step test. Conclusions We therefore concluded that the joint angles and joint moments related to PCV 2—ankle plantar-flexion, ankle plantar-flexor moments during the late stance phase, ranges of motion and moments on the hip, knee, and ankle joints in the sagittal plane during the entire stance phase—are the motions associated with the Two-Step test.

Abstract Background Malignancy during pregnancy has become a significant cause of maternal death in developed countries, likely due to both an older pregnant population, and increases of cervical cancer in younger women. Our aim is to investigate the clinical aspects of malignancy during pregnancy in Japan and to use this information to identify opportunities for earlier detection and treatment. Methods We provided a questionnaire to 1508 secondary or tertiary care hospitals in Japan. We reviewed the clinical characteristics of cases with malignancy during pregnancy for the period of January to December, 2008. From the 760 institutions which responded, we obtained clinical information for 227 unique cases. The questionnaire provided clinical information, including disease site, pregnancy outcome and how the disease was detected. Results The most common type of malignancy was cervical cancer (n = 162, 71.4%) followed by ovarian (n = 16, 7.0%) and breast cancer (n = 15, 6.6%). Leukemia (n = 7, 3.1%), colon cancer (n = 5, 2.2%), gastric cancer (n = 5, 2.2%), malignant lymphoma (n = 4, 1.8%), thyroid cancer (n = 3, 1.3%), brain cancer (n = 3, 1.3%), endometrial cancer (n = 2, 0.9%), and head and neck cancer (n = 2, 0.9%) accounted for the remaining cases. Overall, gynecological malignancies accounted for 79.3% (95% confidence interval 74.0–84.6) of pregnancy associated malignancies diagnosed in the present study. The majority of cervical cancers, 149 (92.0%) of 162, were diagnosed by a Pap (Papanicolaou) smear during early gestation. Ten (62.5%) of the ovarian cancer cases were diagnosed by ultrasonography during a prenatal checkup or at the time of initial pregnancy diagnosis. Out of 14 breast cancers, only one (7.1%) was diagnosed by screening breast exam. Conclusions From this study, we reaffirm the clear and significant benefits of prenatal checkups starting at an early gestational age for the detection of gynecological cancers during pregnancy. Conversely, breast cancer detection during pregnancy was poor, suggesting new strategies for early identification of this disease are required.

Ovarian dermoid cysts (ODCs) are the most common benign tumors in young women, but autoimmune hemolytic anemia (AIHA) induced by ODC is rare. We report the first case of ODC-associated AIHA with improvement after laparoscopic oophorocystectomy. An 18-year-old nulliparous woman was diagnosed with a left ODC that was 7 cm in diameter. Preoperative blood tests showed macrocytic anemia, reticulocytosis, high serum lactate dehydrogenase activity, hyperbilirubinemia, and low haptoglobin. Direct and indirect Coombs tests were positive. We diagnosed AIHA. Prednisolone therapy did not result in improvement, so it seemed that AIHA was being induced by the ODC. After laparoscopic oophorocystectomy, the patient's condition improved without blood transfusion. Resection of ODC should be performed first for ODC-associated AIHA; laparoscopic surgery may be superior to laparotomy from the standpoint of hemorrhage given the underlying anemia.

Macrophages are involved in angiogenesis, and might also contribute to the pathogenesis of intraocular neovascular diseases. Recent studies indicated that macrophages exert different functions in the process of intraocular neovascularization, and the polarization of M1 and M2 phenotypes plays extremely essential roles in the diverse functions of macrophages. Moreover, a large number of cytokines released by macrophages not only participate in macrophage polarization, but also associate with retinal and choroidal neovascular diseases. Therefore, macrophage might be considered as a novel therapeutic target to the treatment of pathological neovascularization in the eye. This review mainly summarizes diverse roles of macrophages and discusses the possible mechanisms in retinal and choroidal neovascularization.

Retinal neovascularization (NV) due to retinal ischemia remains one of the principal causes of vision impairment in patients with ischemic retinal diseases. We recently reported that periostin (POSTN) may play a role in the development of preretinal fibrovascular membranes, but its role in retinal NV has not been determined. The purpose of this study was to examine the expression of POSTN in the ischemic retinas of a mouse model of oxygen-induced retinal NV. We also studied the function of POSTN on retinal NV using Postn KO mice and human retinal endothelial cells (HRECs) in culture. In addition, we used a novel RNAi agent, NK0144, which targets POSTN to determine its effect on the development of retinal NV. Our results showed that the expression of POSTN was increased in the vascular endothelial cells, pericytes, and M2 macrophages in ischemic retinas. POSTN promoted the ischemia-induced retinal NV by Akt phosphorylation through integrin αvβ3. NK0144 had a greater inhibitory effect than canonical double-stranded siRNA on preretinal pathological NV in vivo and in vitro. These findings suggest a causal relationship between POSTN and retinal NV, and indicate a potential therapeutic role of intravitreal injection of NK0144 for retinal neovascular diseases. Keywords: periostin, RNAi, neovascularization, diabetic retinopathy

Knowledge of joint moments will provide greater insight into the manner in which lower-extremity amputees wearing running-specific prostheses regain running capacity and compensate for replacement of an active leg with a passive prosthetic implement. Thus, the purpose of this study was to investigate three-dimensional joint moments during sprinting for unilateral transfemoral amputees wearing running-specific prostheses. Ten sprinters with unilateral transfemoral amputation performed maximal sprinting at the 22 m mark while wearing running-specific prostheses. Joint moments were calculated through an inverse dynamics approach. All peak flexion and extension moments in the prosthetic leg were found to be lower than those of the intact leg, except for the peak plantar flexion moment. In the frontal plane, the peak adduction and abduction moments in the prosthetic leg were generally lower than those of the intact leg. The peak internal rotation moments differed significantly between the legs, but the peak external rotation moments did not. The results of the present study suggest that asymmetric joint moment adaptations occur for unilateral transfemoral amputees to compensate for replacement of the biological leg with a passive prosthetic knee joint and running-specific prosthesis.

The aim of this study was to clarify the major differences in the electromyographic (EMG) activities in the hip joint required to achieve a non-rotational (NR) shot as compared with an instep kick from the spatiotemporal data. For this purpose, simulated EMG activities obtained from NR shots and instep kicks were analyzed using principal component analysis (PCA). The PCA was conducted using an input matrix constructed from the time-normalized average and the standard deviation of the EMG activities (101 data x (15 muscles; iliacus, gluteus maximus, rectus femoris, biceos femoris, vastus lateralis, vastus medialis, vastus intermedius, semimembranosus, semitendinosus, sartorius, tensor fasciae latae muscle, adductor magnus muscle, adductor longus muscle, gasctrocnemius, and tibialis anterior)). The PCA revealed that the 3rd, 4th and 8th principal component vectors (PCVs) of the 10 generated PCVs were related to achieving the NR shot (p < 0.05).

The aim of this study was to investigate differences of the spatiotemporal parameters in a 100-m sprint among elite, sub-elite, and non-elite sprinters with a unilateral transtibial amputation. Using publicly available Internet broadcasts, we analyzed 125, 19, and 33 records from 30 elite, 12 sub-elite, and 22 non-elite sprinters, respectively. For each sprinter's run, the average velocity, step frequency, and step length were calculated using the number of steps in conjunction with the official race time. Average velocity was greatest in elite sprinters (8.71±0.32 m/s), followed by the sub-elite (8.09±0.06 m/s) and non-elite groups (7.72±0.27 m/s). Although there was a significant difference in average step frequency between the three groups, the effect size was small and the relative difference among the three groups was 3.1%. Statistical analysis also revealed that the average step length was longest in elite sprinters, followed by the sub-elite and non-elite groups. These results suggest that the differences in sprint performance between the three groups is mainly due to the average step length rather than step frequency.