Subjective Experience on Virtual Reality-Assisted Mental Health Promotion Program.

OBJECTIVE: Mental health promotion programs using virtual reality (VR) technology have been developed in various forms. This study aimed to investigate the subjective experience of a VR-assisted mental health promotion program for the community population, which was provided in the form of VR experience on a bus to increase accessibility. METHODS: Ninety-six people participated in this study. The relationship between the subjective experience and mental health states such as depression, anxiety, perceived stress, and quality of life was explored. The subjective experience on depression and stress before and after VR program treatment was compared using the Wilcoxon signed-rank test. The satisfaction with the VR-assisted mental health promotion program was examined after using the VR program. RESULTS: The VR-assisted mental health promotion program on a bus significantly improved subjective symptoms such as depression (p=0.036) and perceived stress (p=0.010) among all the participants. Among the high-risk group, this VR program significantly relieved subjective depressive feeling score (p=0.033), and subjective stressful feeling score (p=0.035). In contrast, there were no significant changes in subjective depressive feelings (p=0.182) and subjective stressful feelings (p=0.058) among the healthy group. Seventy-two percent of the participants reported a high level of satisfaction, scoring 80 points or more. CONCLUSION: The findings of this study suggest that the VR-assisted mental health promotion program may effectively improve the subjective depressive and stressful feelings. The use of VR programs on buses to increase of accessibility for the community could be a useful approach for promoting mental health among the population.

Applications of artificial intelligence in urologic oncology.

PURPOSE: With the recent rising interest in artificial intelligence (AI) in medicine, many studies have explored the potential and usefulness of AI in urological diseases. This study aimed to comprehensively review recent applications of AI in urologic oncology. MATERIALS AND METHODS: We searched the PubMed-MEDLINE databases for articles in English on machine learning (ML) and deep learning (DL) models related to general surgery and prostate, bladder, and kidney cancer. The search terms were a combination of keywords, including both "urology" and "artificial intelligence" with one of the following: "machine learning," "deep learning," "neural network," "renal cell carcinoma," "kidney cancer," "urothelial carcinoma," "bladder cancer," "prostate cancer," and "robotic surgery." RESULTS: A total of 58 articles were included. The studies on prostate cancer were related to grade prediction, improved diagnosis, and predicting outcomes and recurrence. The studies on bladder cancer mainly used radiomics to identify aggressive tumors and predict treatment outcomes, recurrence, and survival rates. Most studies on the application of ML and DL in kidney cancer were focused on the differentiation of benign and malignant tumors as well as prediction of their grade and subtype. Most studies suggested that methods using AI may be better than or similar to existing traditional methods. CONCLUSIONS: AI technology is actively being investigated in the field of urological cancers as a tool for diagnosis, prediction of prognosis, and decision-making and is expected to be applied in additional clinical areas soon. Despite technological, legal, and ethical concerns, AI will change the landscape of urological cancer management.

Deep Learning Model for Real­time Semantic Segmentation During Intraoperative Robotic Prostatectomy.

Background and objective: Recently, deep learning algorithms, including convolutional neural networks (CNNs), have shown remarkable progress in medical imaging analysis. Semantic segmentation, which segments an unknown image into different parts and objects, has potential applications in robotic surgery in areas where artificial intelligence (AI) can be applied, such as in AI-assisted surgery, surgeon training, and skill assessment. We aimed to investigate the performance of a CNN-based deep learning model in real-time segmentation in robot-assisted radical prostatectomy (RALP). Methods: Intraoperative videos of RALP procedures were obtained. The reinforcement U-Net model was used for segmentation. Segmentation of the images of instruments, bladder, prostate, and seminal vesicle-vas deferens was performed. The dataset was preprocessed and split randomly into training, validation, and test data in a 7:2:1 ratio. Dice coefficient, intersection over union (IoU), and accuracy by class, which are commonly used in medical image segmentation, were calculated to evaluate the performance of the model. Key findings and limitations: From 120 patient videos, 2400 images were selected for RALP procedures. The mean Dice scores for the identification of the instruments, bladder, prostate, and seminal vesicle-vas deferens were 0.96, 0.74, 0.85, and 0.84, respectively. Overall, when applied to the test data, the model had a mean Dice coefficient value of 0.85, IoU of 0.77, and accuracy of 0.85. Limitations included the sample size, lack of diversity in the methods of surgery, incomplete surgical processes, and lack of external validation. Conclusions and clinical implications: The CNN-based segmentation provides accurate real-time recognition of surgical instruments and anatomy in RALP. Deep learning algorithms can be used to identify anatomy within the surgical field and could potentially be used to provide real-time guidance in robotic surgery. Patient summary: We demonstrate the potential effectiveness of deep learning segmentation in robotic prostatectomy procedures. Deep learning algorithms could be used to identify anatomical structures within the surgical field and may provide real-time guidance in robotic surgery.

Evaluating the Suitability of the Plantaris Tendon for Sports Trauma Reconstruction and a Predictive Model of Tendon Length Based on Height and Leg Length.

This study evaluates the suitability of the plantaris tendon (PT) as a tendon graft donor for sports trauma reconstruction and proposes a predictive model for estimating PT length by using an individual's height and leg length. Anatomical dissection of 50 cadavers (32 males and 18 females) yielded precise measurements of PT length and width while also recording height and leg length. Among the lower limbs, 89% were suitable for at least one recommended graft suitability criterion. In addition, PT length exhibited robust positive correlations with height and leg length. Predictive equations were established for estimating the PT length based on leg length and height with consistency across sexes and sides: PT length = 0.605 + 0.396 × leg length (r = 0.721) and PT length = 1.480 + 0.193 × height (r = 0.626). This study underscores the grafting potential of the PT, providing a predictive tool that can aid surgeons in addressing tendon graft challenges within sports trauma scenarios.

Changes of Locomotor Activity by Dopamine D2, D3 Agonist Quinpirole in Mice Using Home-cage Monitoring System.

Objective: : As dopamine is closely linked to locomotor activities, animal studies on locomotor activities using dopaminergic agents were widely done. However, most of animal studies were performed for a short period that there is a lack of longitudinal study on the effects of dopaminergic agents on locomotor activities. This study aimed to examine the longterm effect of a dopamine D2, D3 agonist quinpirole on locomotor activities in mice using a home-cage monitoring system. Methods: : The locomotor activities of Institute Cancer Research mice were measured by infrared motion detectors in home-cages under the 12-hour dark and 12-hour light condition for three days after the quinpirole injection. Quinpirole was injected at a concentration of 0.5 mg/kg intraperitoneally in the beginning of the dark phase. The locomotor activities before and after the quinpirole administration were compared by the Wilcoxon signed-rank test and one-way repeated measures ANOVA. Results: : After the quinpirole administration, the 24-hour total locomotor activity did not change (p = 0.169), but activities were significantly increased in the 12-hour dark phase sum (p = 0.013) and decreased in the 12-hour light phase sum (p = 0.009). Significant increases in the activities were observed in the dark-light difference (p = 0.005) and dark-light ratio (p = 0.005) as well. Conclusion: : This study suggests that quinpirole injection entrains the circadian rest-activity rhythm of locomotor activities. Therefore, quinpirole can be a drug that mediates locomotor activity as a dopamine agonist as well as a modulator of the circadian rhythms.

The Effect of Porosity on the Thermal Conductivity of Highly Thermally Conductive Adhesives for Advanced Semiconductor Packages.

This study suggests promising candidates as highly thermally conductive adhesives for advanced semiconductor packaging processes such as flip chip ball grid array (fcBGA), flip chip chip scale package (fcCSP), and package on package (PoP). To achieve an extremely high thermal conductivity (TC) of thermally conductive adhesives of around 10 Wm-1K-1, several technical methods have been tried. However, there are few ways to achieve such a high TC value except by using spherical aluminum nitride (AlN) and 99.99% purified aluminum oxide (Al2O3) fillers. Herein, by adapting highly sophisticated blending and dispersion techniques with spherical AlN fillers, the highest TC of 9.83 Wm-1K-1 was achieved. However, there were big differences between theoretically calculated TCs that were based on the conventional Bruggeman asymmetric model and experimentally measured TCs due to the presence of voids or pores in the composites. To narrow the gaps between these two TC values, this study also suggests a new experimental model that contains the porosity effect on the effective TC of composites in high filler loading ranges over 80 vol%, which modifies the conventional Bruggeman asymmetric model.

A Validation Study of Mental Health Monitoring Through a Mobile Application.

OBJECTIVE: Face-to-face evaluation is the most important in psychiatric evaluation, but smart healthcare, including non-face-to-face evaluation, can be beneficial considering the situation in which face-to-face evaluation is limited or the preventive aspect of mental illness. In this paper, we aimed to check whether mental health screening tests have the same significance as paper-based tests even when collected through mobile applications. METHODS: A smart mental healthcare screening test was conducted on the 1,327 community subjects. We measured two indicators of depression (Patient Health Questionnaire 9-item scale, PHQ-9) and anxiety (Generalized Anxiety Disorder 7-item scale, GAD-7) to check mental health conditions. RESULTS: The average Cronbach's alpha value of the PHQ-9 questionnaire was good at 0.870. As a result of PHQ-9's principal component analysis, one component with an eigenvalue of 1 or more was identified, which is suitable to be described as a single factor. The average Cronbach's alpha value of the GAD-7 was 0.919. The structural validity of the GAD-7 was confirmed through principal component analysis. CONCLUSION: Our results show that PHQ-9 and GAD-7 scales performed through mobile applications can have the same meaning as paper-based tests. Surveys using a tablet PC, or smartphone application can monitor residents' mental health and accumulate data. Based on these data, smart mental health management can check the mental health of residents and treat mental illness in connection with medical services.

Cluster Analysis on the Mental Health States in a Community Sample of Young Women During Pre-Pregnancy, Pregnancy, or the Postpartum Period.

OBJECTIVE: It is necessary to identify the mental health types of young women considering the importance of the mental health during the peripartum period. This study aimed to classify the mental health types in a community sample of young women with pre-pregnancy, pregnancy, or the postpartum period. METHODS: A total of 293 young women during pre-pregnancy, pregnancy, or the postpartum period were included in this study. The clinical characteristics of depression, anxiety, perceived stress, and quality of life were assessed. The clinical characteristics of the subject were classified by cluster analysis and compared by analysis of variance. RESULTS: From the cluster analysis, the subjects were classified into three groups. Cluster 1 showed significantly lower depression and anxiety and higher quality of life than those of cluster 2 and 3. Cluster 2 demonstrated significantly higher depression and anxiety and lower quality of life than those of cluster 3 and 1. Cluster 3 represented the intermediate levels between cluster 2 and 1. CONCLUSION: This study suggested that young women during pre-pregnancy, pregnancy, or the postpartum period might be in a good mental health group, a high-risk group requiring active monitoring, or a group in need of treatment. By monitoring mental health, the groups with high risk or requiring treatment could be discovered and proper management for prevention or improvement of mental health and quality of life can be provided.

Machine Learning Algorithms for the Prediction of Locomotor Activity by an Infrared Motion Detector on the Sleep-wake States in Mice.

Objective: Even though studies using machine learning on sleep-wake states have been performed, studies in various conditions are still necessary. This study aimed to examine the performance of the prediction model of locomotor activities on sleep-wake states using machine learning algorithms. Methods: The processed data using moving average of locomotor activities were used as predicting features. The sleep-wake states were used as true labels. The prediction models were established by machine learning classifiers such as support vector machine with radial basis function (SVM-RBF), linear discriminant analysis (LDA), naïve Bayes, and random forest (RF). The prediction model was evaluated by a six-fold cross validation. Results: The SVM-RBF and RF showed acceptable performance within a window of moving average from 480 to 1,200 seconds. The highest accuracy (0.869) was shown by the RF at the interval of 480 seconds. Meanwhile, the highest area under the curve (0.939) was shown by LDA at the interval of 870 seconds. Conclusion: This study suggested that the prediction model on sleep-wake state using machine learning could show an improvement of the model performance when using moving average with raw data. The prediction model using locomotor activity can be useful in research on sleep-wake state.

Unilateral Myoclonus as an initial manifestation in Moyamoya disease with asymmetric vasculature.

Movement disorders have been identified as a rare early manifestation of the Moyamoya disease. Herein, we present a case of a 34-year-old man with a genetically confirmed Moyamoya disease who showed unilateral myoclonus as an initial manifestation. Neuroimaging studies showed prominent asymmetrically developed Moyamoya disease on the right hemisphere with near-complete loss of normal vessels while the left hemisphere was adjunctively fed with extension of posterior cerebral artery: uneven progression of vasculature. 99mTc-hexamethylpropylene amine oxime single-photon emission computed tomography demonstrated impaired vascular reserve. Electroencephalography showed occasional sharp waves on right temporal area. The phenomenon of this patient could be explained in the context of excitable cortex and hypoactive subcortical substrate that might imply putative contradictory neurobiology in Moyamoya disease.

Normal Distal Tibiofibular Syndesmosis Assessment Using Postmortem Computed Tomography (PMCT).

BACKGROUND: Distal tibiofibular syndesmotic injuries, often misdiagnosed, can lead to substantial morbidity. This study utilized postmortem computed tomography (PMCT) to define normal syndesmotic relationships in 131 subjects. METHODS: Three parameters were measured: fibular rotation (FR), sagittal translation (ST), and incisura depth (ID). RESULTS: Interobserver reliability was excellent for FR and ID but moderate for ST. Anatomical variability was wide, with FR ranging from -0.4° to 16.6°, ST from 0.33 mm to 3.49 mm, and ID from 1.89 mm to 6.05 mm. Side-to-side variability within subjects was minimal. Gender-specific differences were observed in ST, possibly due to size variations, highlighting the need for gender-specific diagnostic criteria. CONCLUSIONS: Although establishing universal reference values is challenging, using contralateral ankles for comparison can enhance diagnostic accuracy in syndesmotic injuries. This study, the first of its kind, offers valuable insights into normal distal tibiofibular syndesmotic relationships based on PMCT data. Future validation studies in patients with syndesmotic injuries can further improve diagnostic accuracy.

Estimating Adult Stature Using Metatarsal Length in the Korean Population: A Cadaveric Study.

This study aims to propose a regression equation for estimating stature in the Korean population using metatarsal bones from cadavers and to validate the appropriateness of the Korean-specific equation by comparing it to equations from other populations. A total of 81 adult formalin-fixed cadavers (51 males and 30 females) were evaluated. The first and second metatarsal bones' physiological and maximal lengths were measured, and the cadaveric stature of the subjects was determined as the distance from the vertex to the plantar face of the heel. In all measurements, the correlation coefficient between real stature and metatarsal length was statistically significant (p < 0.001). Additionally, both sexes showed a correlation between stature and metatarsal bone length. For unknown sex, M1 (first metatarsal maximal length) showed the strongest association between stature and metatarsal length. The following is the appropriate regression equation: 1172.4913 + 7.3275M1 (R = 0.703). The current equation demonstrated a statistically significant appropriateness for the Korean population when compared to equations for other populations (p < 0.001). In conclusion, we proposed a Korean-specific regression equation for estimating stature using metatarsal length, and this formula may be more appropriate and useful in forensic science for the Korean population.

Design of EM Sensor for Non-Contact Detection of Defective Wire Harness in Conveyor System.

For a non-contact detection of defective wire harness in conveyor system, a new method using the electromagnetic (EM) sensor is proposed in this paper. A dual-feed and multi array microstrip patch antenna operating at 5.8 GHz is utilized to design the EM sensor. When the wire harness is located above patch antenna, the equivalent circuit of each patch antenna and wire harness can be modeled as shunt resistor, capacitor, and inductor. Moreover, a capacitive coupling between the patch antenna and the wire harness is generated. Next, the shunt resistor of wire harness increases due to the defect of the wire so that the reflection coefficient of the patch antenna is lower than that of the wire without defect; thus, the defect of wire harness can be detected by magnitude of reflection coefficient at resonant frequency. The performances of the designed EM sensor are verified and compared by the equivalent circuit modeling, full-wave simulation, and measurement.

Design of an Intermediate Die for the Multi-Pass Shape Drawing Process.

The multi-pass shape drawing process is mainly used in metal forming processes to manufacture long components with constant arbitrary cross-sectional shapes along their lengths. The cross-roller guide is a typical component that is manufactured by a multi-pass shape drawing process. The cross-roller guide is mostly used in optical measurement equipment where high-precision movement is required. Therefore, the dimensional accuracy of the cross-roller guide is very important since it can influence precision linear motion. However, the unfilled defects can occur in a case where the product has a complex cross-sectional shape. In this study, a new design method for an intermediate die is suggested by using an equal-radial-velocity variation method in order to reduce the unfilled defects. The proposed design method can reduce the unfilled defects by minimizing the radial velocity variation in the deformation zone of the drawing die. The intermediate die was designed by geometrical information of the final product without prior finite element (FE) analysis. The suggested method was applied to design the multi-pass shape drawing process for manufacturing the cross-roller guide. FE analysis was performed to validate the effectiveness of the proposed method in comparison to the conventional design method that uses equipotential lines in the multi-pass shape drawing process. Finally, a shape drawing experiment was performed to compare the target shape and the FE analysis with the experimental data.

Energetic Contributions Including Gender Differences and Metabolic Flexibility in the General Population and Athletes.

Metabolic flexibility includes the ability to perform fat and carbohydrate oxidation, as well as oxidative capacity, which is associated with mitochondrial function, energetic contributions, and physical health and performance. During a session of graded incremental exercise testing (GIET), we investigated metabolic flexibility, the contributions of three energy systems, and performances of individuals with different metabolic characteristics. Fifteen general population (GP; n = 15, male n = 7, female n = 8) and 15 national-level half-marathon and triathlon athletes (A; n = 15, male n = 7, female n = 8) participated in this study. During GIET, heart rate (HR), oxygen uptake (V˙O2mean and V˙CO2mean), metabolic equivalents (METs) in V˙O2mean, and blood glucose and lactate concentrations (La-) were measured. Furthermore, jogging/running speeds (S) at specific La-, fat and carbohydrate oxidations (FATox and CHOox), and energetic contributions (oxidative; WOxi, glycolytic; WGly, and phosphagen; WPCr) were calculated. The percentages of HRmax, relative V˙O2mean, V˙CO2mean, and METs in V˙O2mean were all lower in A than they were in GP. FATox values were lower in GP than in A, while CHOox and La- were higher in GP than in A. Negative correlations between La- and FATox were also observed in both groups. Contributions of WOxi, WGly, and WPCr were higher in GP than in A during GIET. Moreover, values of WGly, and WPCr were significantly lower and higher, respectively, in male GP than in female GP. Furthermore, S at specific La- were higher in A than in GP. It is suggested that an individualized low-intensity recovery exercise program be established, to achieve increased metabolic flexibility and oxidative capacity (aerobic base), such as public health improvements and a greater volume of higher exercise intensities; this is the type of exercise that elite athletes worldwide mostly perform during their training period and progression. This may prevent cardiac/metabolic diseases in GP.

Anatomical Characteristics of Extensor Hallucis Longus Tendon Variations and Its Clinical Implications: A Korean Cadaveric Study.

The purpose of this study is to ascertain the morphological characteristics of the extensor hallucis longus (EHL) tendon variation using larger-scale dissection of Korean cadavers and to classify the types of variation along with incidence. A total of 158 feet from adult formalin-fixed cadavers (50 males, 29 females) were dissected. The morphological characteristics and measurements of the EHL tendon variants were evaluated. Three types of the EHL tendon variation were classified, wherein the most common type was Type 2 (106 feet, 67.1%), Type 3 (3 feet, 1.9%) was the rarest type, and Type 1 without accessory tendon was found in 49 feet (31.0%). Type 2K (11 feet, 7%) and Type 3K (1 foot, 0.6%) were described as new subtypes. The present study suggests morphological characteristics of the EHL tendon variation in Korean populations and high morphological variability of the EHL tendon along with the possibility of differences according to race or ethnicity and gender. Furthermore, a newly updated classification complemented by new subtypes of variation will help foot and ankle surgeons in diagnosis and surgical planning with hallux problems.

Optimization of Analysis of Circadian Rest-Activity Rhythm Using Cosinor Analysis in Mice.

OBJECTIVE: Data processing in analysis of circadian rhythm was performed in various ways. However, there was a lack of evidence for the optimal analysis of circadian rest-activity rhythm. Therefore, we aimed to perform mathematical simulations of data processing to investigate proper evidence for the optimal analysis of circadian rest-activity rhythm. METHODS: Locomotor activities of 20 ICR male mice were measured by infrared motion detectors. The data of locomotor activities was processed using data summation, data average, and data moving average methods for cosinor analysis. Circadian indices were estimated according to time block, respectively. Also, statistical F and p-values were calculated by zero-amplitude test. RESULTS: The data moving average result showed well-fitted cosine curves independent of data processing time. Meanwhile, the amplitude, MESOR, and acrophase were properly estimated within 800 seconds in data summation and data average methods. CONCLUSION: These findings suggest that data moving average would be an optimal method for data processing in a cosinor analysis and data average within 800-second data processing time might be adaptable. The results of this study can be helpful to analyze circadian restactivity rhythms and integrate the results of the studies using different data processing methods.

Anatomical Classification for Plantaris Tendon Insertion and Its Clinical Implications: A Cadaveric Study.

The purposes of this study were to ascertain the morphological characteristics of a plantaris tendon (PT) insertion using a larger-scale dissection of Korean cadavers and to classify the types of PT insertion related to the calcaneal tendon (CT). A total of 108 feet from adult formalin-fixed cadavers (34 males, 20 females) were dissected. The morphological characteristics and measurements of the PT insertion were evaluated. Five types of PT insertion were classified, wherein the most common type was Type 1 (39 feet, 63.1%). Type 2 and Type 3 were similar, with 16 feet (14.8%) and 15 feet (13.9%), respectively. Type 4 (6 feet, 5.6%) was the rarest type, and Type 5 had 25 feet (23.1%). The case of an absent PT was noted in 7 feet (6.5%). In the proximal portion, the tendon had a thick and narrow shape, became thin and wide in the middle portion, and then changed to thick and narrow again just before the insertion into the calcaneal tuberosity. This study confirmed the five types according to the location of the PT and the area of its insertion-related CT. The morphology of the PT insertion may be anatomically likely to influence the occurrence of tendinopathy in the CT.