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Liddle syndrome (LS) is an autosomal dominant genetic disorder characterized by early onset hypertension, hypokalemia, and low plasma aldosterone or renin concentration. It is caused by mutations in subunits of the epithelial sodium channel (ENaC). The clinical phenotypes of LS are variable and nonspecific, making it prone to both misdiagnosis and missed diagnosis. Genetic analysis is necessary to confirm the diagnosis of LS. Herein, we report the case of a 42-year-old male with LS and a 30-year history of hypertension. He was being treated for possible primary aldosteronism (PA) over the preceding 7 years; however, his hypertension was poorly controlled despite intensive combination therapy. His 13-year-old son served as a proband for a diagnosis of LS, as he had hypertension, hypokalemia, and a significant family history of hypertension. Genetic testing revealed a heterozygous pathological variant in the SCNN1B gene. This led to a diagnosis of LS, as the father was found to harbor the same mutation. Both were treated with ENaC inhibitors and a salt-restricted diet, which improved their symptoms markedly. The son’s genetic diagnosis facilitated the subsequent proper diagnosis and treatment of his father. LS causes early onset hypertension; hence, its early diagnosis and treatment can prevent complications. Hereditary hypertension should be considered in cases of early onset hypertension with a significant family history. Patients diagnosed with PA using outdated criteria may have concomitant LS and require careful evaluation of biochemical and endocrine tests according to the current criteria.

Gaussian process Bayesian optimization (GPBO) based on the upper confidence bound is a method for finding the approximate maximum solution using observations maximizing $E + \beta V^{1/2}$ consisting of the estimated average E and variance V obtained by Gaussian process regression. The exploration weight $\beta $ is the coefficient for adjusting the exploration-exploitation trade-off, which affects search performance. In previous studies, constant value, logarithmic decay, and probabilistic value as the exploration weight have been proposed, and they exhibit good search performance. For better search performance, we propose a method for setting the exploration weight using estimated variance integration (EVI) as a novel meta-heuristics algorithm. Because the integration of the estimated variance V represents the total amount of uncertainty in an entire search space, using it as the exploration weight, we can expect the search performance to be higher than that of previous methods. In this study, an exact analytical solution for integrating the estimated variance in the Gaussian kernel case was provided to realize EVI-GPBO. Experiments on searching for the global optimum using benchmark functions for evaluating approximate search algorithms were conducted to evaluate EVI-GPBO. The results indicate that EVI-GPBO can find optimal solutions with a high percentage compared to the existing methods. In a more realistic setting, an experiment on hyperparameter tuning for a support vector machine was conducted. The results indicate that EVI-GPBO obtained a higher score than the other existing methods. In summary, we conclude that EVI-GPBO is an effective search algorithm.

Location data collected from mobile devices via global positioning system often lack semantic information and can form sparse trajectories in space and time. This study investigates whether user age groups can be accurately classified solely from such sparse spatial–temporal trajectories. We propose a feature extraction method based on a Gaussian mixture model (GMM), which assigns representative points (RPs) by clustering the location data and aggregating user trajectories into these RPs. We then construct three machine learning (ML) models—support vector classifier (SVC), random forest (RF), and deep neural network (DNN)—using the GMM-based features and compare their performance with that of the improved DNN (IDNN), which is an existing feature extraction approach. In our experiments, we introduced a missing value ratio θth to quantify trajectory sparsity and analyzed the effect of trajectory sparsity on the classification accuracy and generalizability performance of the ML models. The results indicate that GMM-based features outperform IDNN-based features in both classification accuracy and generalization performance. Notably, the RF model achieved the highest accuracy, whereas the SVC model displayed stable generalizability. As the missing value ratio θth increases, the IDNN becomes more susceptible to overfitting, whereas the GMM-based approach preserves accuracy and robustness. These findings suggest that sparse trajectories can still offer meaningful classification performance with appropriate feature design and model selection even without semantic information. This approach holds promise for domains where large-scale, sparse trajectory data are common, including urban planning, marketing analysis, and public policy.

The concept of multisource energy harvesting has attracted attention in order to harvest multiple types of energy in a single material. In this work, Pb‐free (Ba,Ca)(Zr,Ti)O3 (BCZT) ceramics were used to investigate a combination of piezoelectric and pyroelectric energy harvesting behavior. The temperature dependence of the permittivity and the pyroelectric coefficient was measured, and the pyroelectric properties of BCZT were expected to improve near its orthorhombic–tetragonal phase transition temperature TO–T (∼40°C). The output voltage and current were measured using a BCZT plate, where the BCZT was oscillated under a temperature gradient to apply mechanical stress and temperature fluctuation simultaneously. The measured output voltage from the combined piezo‐ and pyroelectric contributions at a frequency of 2 Hz and with a load resistance of 10 MΩ was 1.4 times higher than the sole piezoelectric output voltage. The resulting combined output voltage was confirmed by finite element simulation. [ABSTRACT FROM AUTHOR]

Location data collected from mobile devices via global positioning system often lack semantic information and can form sparse trajectories in space and time. This study investigates whether user age groups can be accurately classified solely from such sparse spatial–temporal trajectories. We propose a feature extraction method based on a Gaussian mixture model (GMM), which assigns representative points (RPs) by clustering the location data and aggregating user trajectories into these RPs. We then construct three machine learning (ML) models—support vector classifier (SVC), random forest (RF), and deep neural network (DNN)—using the GMM-based features and compare their performance with that of the improved DNN (IDNN), which is an existing feature extraction approach. In our experiments, we introduced a missing value ratio θ th to quantify trajectory sparsity and analyzed the effect of trajectory sparsity on the classification accuracy and generalizability performance of the ML models. The results indicate that GMM-based features outperform IDNN-based features in both classification accuracy and generalization performance. Notably, the RF model achieved the highest accuracy, whereas the SVC model displayed stable generalizability. As the missing value ratio θ th increases, the IDNN becomes more susceptible to overfitting, whereas the GMM-based approach preserves accuracy and robustness. These findings suggest that sparse trajectories can still offer meaningful classification performance with appropriate feature design and model selection even without semantic information. This approach holds promise for domains where large-scale, sparse trajectory data are common, including urban planning, marketing analysis, and public policy. [ABSTRACT FROM AUTHOR]

Congenital cystic eye (CCE) is a rare congenital ocular disease, which has been suggested to be caused by problems with optic vesicle invagination. This is characterized by the formation of intraorbital cystic lesions lined by undifferentiated neuroepithelium. However, cases involving ocular structures with varying degrees of differentiation have also been reported as CCE in humans and animals. In horses, CCE have only been reported as a case presenting as neuroepithelial-lined cysts without the formation of ocular structures. This paper describes large bilateral intraorbital cysts in a 1-day-old horse. The histopathological findings revealed that the cysts were covered by neuroepithelium with formation of the lens, ciliary body, and optic nerve, and it was diagnosed as CCE. This report provides further variations of CCE in horses. [ABSTRACT FROM AUTHOR]

The Japan Gastroenterological Association published the first version of its clinical guidelines for chronic constipation 2023. Based on the latest evidence, these guidelines describe the definition, classification, diagnostic criteria, diagnostic testing methods, epidemiology, pathophysiology, and treatment of chronic constipation. They include flowcharts for both diagnosis and treatment of chronic constipation. In the treatment of chronic constipation, the first step involves differentiating between secondary forms, such as organic disease-associated constipation, systemic disease-associated constipation, and drug-induced constipation. The next step is to determine whether the chronic constipation stems from a motility disorder, a form of primary chronic constipation. For functional constipation and constipation-predominant irritable bowel syndrome, treatment should be initiated after evaluating symptoms like reduced bowel movement frequency type or defecation difficulty type. The first line of treatment includes the improvement of lifestyle habits and diet therapy. The first drugs to consider for oral treatment are osmotic laxatives. If these are ineffective, secretagogues and ileal bile acid transporter inhibitors are candidates. However, stimulant laxatives are exclusively designated for as-needed use. Probiotics, bulk-forming laxatives, prokinetics, and Kampo medicines, for which there is insufficient evidence, are considered alternative or complementary therapy. Providing the best clinical strategies for chronic constipation therapy in Japan, these clinical guidelines for chronic constipation 2023 should prove useful for its treatment worldwide. The Japan Gastroenterological Association published the first version of its clinical guidelines for chronic constipation 2023. Based on the latest evidence, these guidelines describe the definition, classification, diagnostic criteria, diagnostic testing methods, epidemiology, pathophysiology, and treatment of chronic constipation. They include flowcharts for both diagnosis and treatment of chronic constipation. In the treatment of chronic constipation, the first step involves differentiating between secondary forms, such as organic disease-associated constipation, systemic disease-associated constipation, and drug-induced constipation. The next step is to determine whether the chronic constipation stems from a motility disorder, a form of primary chronic constipation. For functional constipation and constipation-predominant irritable bowel syndrome, treatment should be initiated after evaluating symptoms like reduced bowel movement frequency type or defecation difficulty type. The first line of treatment includes the improvement of lifestyle habits and diet therapy. The first drugs to consider for oral treatment are osmotic laxatives. If these are ineffective, secretagogues and ileal bile acid transporter inhibitors are candidates. However, stimulant laxatives are exclusively designated for as-needed use. Probiotics, bulk-forming laxatives, prokinetics, and Kampo medicines, for which there is insufficient evidence, are considered alternative or complementary therapy. Providing the best clinical strategies for chronic constipation therapy in Japan, these clinical guidelines for chronic constipation 2023 should prove useful for its treatment worldwide. [ABSTRACT FROM AUTHOR]

The present study aimed to investigate the impact of cancer-associated thromboembolism (CAT) on the survival and biomarkers of ovarian clear cell carcinoma (OCCC). Patients with OCCC who underwent surgery at the National Defense Medical College Hospital (Tokorozawa, Japan) between January 2000 and December 2019 were included in the current study. Associations among CAT, clinicopathological features and prognosis were retrospectively compared. Furthermore, immunohistochemical staining was conducted in all patients to compare differences between patients with and without CAT. Among 111 patients with OCCC, 20 patients (18.0%) had CAT complications. CAT was detected in 12 patients (10.8%) before primary treatment and in 8 patients (7.2%) after primary surgery. Patients with CAT experienced more tumor recurrence (P=0.048) and platinum resistance (P=0.025), had worse progression-free survival (PFS; P<0.01) and overall survival (OS; P<0.01), and multivariate analysis showed that CAT was a prognostic factor for worse PFS [hazard ratio (HR)=2.10, P=0.039] and OS (HR=4.26, P<0.01). Moreover, immunohistochemical analysis revealed that more OCCC cases with CAT were positive for tissue factor (TF; P=0.030) and phosphorylated-Janus kinase 2 (JAK2; P=0.034) expression than those without CAT. In conclusion, CAT may be associated with platinum resistance and poor prognosis in patients with OCCC. Furthermore, TF and JAK2 could be considered potential novel therapeutic targets for OCCC complicated by CAT. [ABSTRACT FROM AUTHOR]