Introduction: Nonmuscle-invasive bladder cancer has a relatively high postoperative recurrence rate despite the implementation of conventional treatment methods. Cystoscopy is essential for diagnosing and monitoring bladder cancer, but lesions are overlooked while using white-light imaging. Using cystoscopy, tumors with a small diameter; flat tumors, such as carcinoma in situ ; and the extent of flat lesions associated with the elevated lesions are difficult to identify. In addition, the accuracy of diagnosis and treatment using cystoscopy varies according to the skill and experience of physicians. Therefore, to improve the quality of bladder cancer diagnosis, we aimed to support the cystoscopic diagnosis of bladder cancer using artificial intelligence (AI). Materials and Methods: A total of 2102 cystoscopic images, consisting of 1671 images of normal tissue and 431 images of tumor lesions, were used to create a dataset with an 8:2 ratio of training and test images. We constructed a tumor classifier based on a convolutional neural network (CNN). The performance of the trained classifier was evaluated using test data. True-positive rate and false-positive rate were plotted when the threshold was changed as the receiver operating characteristic (ROC) curve. Results: In the test data (tumor image: 87, normal image: 335), 78 images were true positive, 315 true negative, 20 false positive, and 9 false negative. The area under the ROC curve was 0.98, with a maximum Youden index of 0.837, sensitivity of 89.7%, and specificity of 94.0%. Conclusion: By objectively evaluating the cystoscopic image with CNN, it was possible to classify the image, including tumor lesions and normality. The objective evaluation of cystoscopic images using AI is expected to contribute to improvement in the accuracy of the diagnosis and treatment of bladder cancer.

Background: Nonmuscle-invasive bladder cancer is diagnosed, treated, and monitored using cystoscopy. Artificial intelligence (AI) is increasingly used to augment tumor detection, but its performance is hindered by the limited availability of cystoscopic images required to form a large training data set. This study aimed to determine whether stepwise transfer learning with general images followed by gastroscopic images can improve the accuracy of bladder tumor detection on cystoscopic imaging. Materials and Methods: We trained a convolutional neural network with 1.2 million general images, followed by 8728 gastroscopic images. In the final step of the transfer learning process, the model was additionally trained with 2102 cystoscopic images of normal bladder tissue and bladder tumors collected at the University of Tsukuba Hospital. The diagnostic accuracy was evaluated using a receiver operating characteristic curve. The diagnostic performance of the models trained with cystoscopic images with or without stepwise organic transfer learning was compared with that of medical students and urologists with varying levels of experience. Results: The model developed by stepwise organic transfer learning had 95.4% sensitivity and 97.6% specificity. This performance was better than that of the other models and comparable with that of expert urologists. Notably, it showed superior diagnostic accuracy when tumors occupied >10% of the image. Conclusions: Our findings demonstrate the value of stepwise organic transfer learning in applications with limited data sets for training and further confirm the value of AI in medical diagnostics. Here, we applied deep learning to develop a tool to detect bladder tumors with an accuracy comparable with that of a urologist. To address the limitation that few bladder tumor images are available to train the model, we demonstrate that pretraining with general and gastroscopic images yields superior results.

Evidence on laparoscopic sacrocolpopexy (LSC) is lacking. Herein, we describe the complications and outcomes of LSC. This single-centre, retrospective cohort study included women with pelvic organ prolapse (POP) who underwent LSC between 2015 and 2017. Preoperative, intraoperative, postoperative, and demographic data were collected. We evaluated patients using the Pelvic Organ Prolapse Quantification system and questionnaires. The primary outcomes were operative characteristics, perioperative complications, early postoperative complications, and anatomical results at 12 months. Forty-six patients (median age: 71 years) underwent LSC. The median follow-up period was 12.0 ± 5.0 (range: 11–26) months. The perioperative complications were bladder perforation and vaginal injury (2.2%). Two (4.3%) patients required reoperation for port-site hernia. One (2.2%) patient developed a retroperitoneal abscess, and one (2.2%) had worsened stress urinary incontinence after LSC. Three (6.5%) patients presented with recurrence of prolapse. LSC is safe and effective for POP.

An Antarctic wintering-over station is a unique environment, as a small isolated society facing extreme survival margins. Psychological surveys have been done over ten years, including the Baum test, the Positive and Negative Affect Schedule (PANAS), the Coping Orientation to Problems Experienced (COPE), Subjective Health Complaints Inventory (SHC), the Two-Sided Personality Scale (TSPS) and medical consultations in Syowa Station, a Japanese Antarctic station to reveal the mental status of team members. Team members experienced fewer physical health risks in Antarctica than in Japan. Wintering-over team members reinterpreted situations positively and accepted their environment, sought instrumental social support, planned ahead, and used active coping skills and humour to overcome difficulties. They did not act out emotionally or deny problems. Individuals exhibited two types of coping, either stability through maintaining a previous lifestyle or flexible adjustment to a new way of life. Positive affect remained constant during the wintering-over period. In living through a harsh reality, team members drew support from the subjective feelings of an “internal relationship” with home or family in their minds. Thus, an Antarctic wintering-over station is an ideal isolated environment for psychological surveys, which can help understand future space travel and group managements in everyday societies.

This study aimed to evaluate disease and injury trends among wintering members of the Japanese Antarctic Research Expedition. Obtained information is indispensable to the advancement of medical system and research. Summation was performed based on medical records of reports prepared by each expedition over the period 1956–2016. The clinical department’s classification methods of the names of injuries and diseases varied among expeditions, but the names were integrated following the same classification. Of 1734 members (29 women), 6837 disease or injury cases (4 cases/person) were recorded. The rates of cases were as follows: surgical-orthopaedic (45.3%), internal medical (21.7%), dental (11.6%), dermatological (8.4%), ophthalmological (5.8%), otorhinolaryngological (5.3%), psychiatric (1.6%), and urological (0.1%) cases. There was no major change in rates by type of medical case in each expedition. This analysis made it possible to prepare medical facilities, content of physical examinations to select members, training of physicians before departure, preventive hygiene at sites, and medical research themes.

Background: Inductively coupled plasma mass spectrometry (ICP‐MS) is widely used for the accurate measurement of minerals. However, its application to serum essential mineral measurement has not been fully evaluated. The present study aimed to assess the performance of ICP‐MS for serum minerals by comparing its measurements to those obtained using standard quantification methods.Methods: Cross‐sectional data were collected from 282 participants from a single facility in Japan. Serum concentrations of eight key minerals, namely sodium, potassium, calcium, phosphorus, magnesium, iron, zinc, and copper, measured via ICP‐MS and standard methods were compared using Passing–Bablok regression and Bland–Altman plots.Results: All minerals, except phosphorus, exhibited good agreement with standard methods, with more stable regression coefficients observed for minerals with greater interindividual variability. After systematically filtering outliers, the mean relative errors were approximately −3% for sodium, potassium, calcium, and magnesium; +5% for iron; 0% for zinc; and −19% for copper. The outliers for iron were primarily due to mild hemolysis, whereas those for zinc were largely attributed to nonhemolysis factors. For phosphorus, the serum total phosphorus concentration measured using ICP‐MS was approximately 3.5 times higher than the serum inorganic phosphorus concentration measured using standard methods, with a weak correlation observed between the two methods.Conclusion: This study provides a practical foundation for future research. Understanding ICP‐MS characteristics will facilitate the development of new approaches in clinical diagnostics.