Purpose: Unnecessary prostate biopsies for detecting prostate cancer (PCa) should be minimized. Therefore, this study developed a machine learning (ML) model to predict PCa in Korean men and evaluated its usability. Materials and Methods: We retrospectively analyzed clinical data from 928 patients who underwent prostate biopsies at Kangwon National University Hospital between May 2013 and May 2023. Of these, 377 (41.6%) were diagnosed with PCa, and 551 (59.4%) did not have cancer. For external validation, clinical data from 385 patients aged 48–89 years who underwent prostate biopsies from September 2005 to September 2023 at Wonju Severance Christian Hospital were also included. Twenty-two clinical features were used to develop an ML model to predict PCa. Features were selected based on their contributions to model performance, leading to the inclusion of 15 features. A meta-learner was constructed using logistic regression to predict the probability of PCa, and the classifier was trained and validated on randomly extracted training and test sets at an 8:2 ratio. Results: The prostate health index, prostate volume, age, nodule on digital rectal examination, and prostate-specific antigen were the top 5 features for predicting PCa. The area under the receiver operating characteristic curve (AUC) of the meta-learner logistic regression model was 0.89, and the accuracy, sensitivity, and specificity were 0.828, 0.711, and 0.909, respectively. Our model also showed excellent prediction performance for high-grade PCa, with a Gleason score of 7 or higher and an AUC of 0.903. Furthermore, we evaluated the performance of the model using external cohort clinical data and achieved an AUC of 0.863. Conclusions Our ML model excelled in predicting PCa, specifically clinically significant PCa. Although extensive cross-validation in other clinical cohorts is needed, this ML model is a promising option for future diagnostics.

Purpose: Unnecessary prostate biopsies for detecting prostate cancer (PCa) should be minimized. Therefore, this study developed a machine learning (ML) model to predict PCa in Korean men and evaluated its usability. Materials and Methods: We retrospectively analyzed clinical data from 928 patients who underwent prostate biopsies at Kangwon National University Hospital between May 2013 and May 2023. Of these, 377 (41.6%) were diagnosed with PCa, and 551 (59.4%) did not have cancer. For external validation, clinical data from 385 patients aged 48–89 years who underwent prostate biopsies from September 2005 to September 2023 at Wonju Severance Christian Hospital were also included. Twenty-two clinical features were used to develop an ML model to predict PCa. Features were selected based on their contributions to model performance, leading to the inclusion of 15 features. A meta-learner was constructed using logistic regression to predict the probability of PCa, and the classifier was trained and validated on randomly extracted training and test sets at an 8:2 ratio. Results: The prostate health index, prostate volume, age, nodule on digital rectal examination, and prostate-specific antigen were the top 5 features for predicting PCa. The area under the receiver operating characteristic curve (AUC) of the meta-learner logistic regression model was 0.89, and the accuracy, sensitivity, and specificity were 0.828, 0.711, and 0.909, respectively. Our model also showed excellent prediction performance for high-grade PCa, with a Gleason score of 7 or higher and an AUC of 0.903. Furthermore, we evaluated the performance of the model using external cohort clinical data and achieved an AUC of 0.863. Conclusions Our ML model excelled in predicting PCa, specifically clinically significant PCa. Although extensive cross-validation in other clinical cohorts is needed, this ML model is a promising option for future diagnostics.

Purpose: Unnecessary prostate biopsies for detecting prostate cancer (PCa) should be minimized. Therefore, this study developed a machine learning (ML) model to predict PCa in Korean men and evaluated its usability. Materials and Methods: We retrospectively analyzed clinical data from 928 patients who underwent prostate biopsies at Kangwon National University Hospital between May 2013 and May 2023. Of these, 377 (41.6%) were diagnosed with PCa, and 551 (59.4%) did not have cancer. For external validation, clinical data from 385 patients aged 48–89 years who underwent prostate biopsies from September 2005 to September 2023 at Wonju Severance Christian Hospital were also included. Twenty-two clinical features were used to develop an ML model to predict PCa. Features were selected based on their contributions to model performance, leading to the inclusion of 15 features. A meta-learner was constructed using logistic regression to predict the probability of PCa, and the classifier was trained and validated on randomly extracted training and test sets at an 8:2 ratio. Results: The prostate health index, prostate volume, age, nodule on digital rectal examination, and prostate-specific antigen were the top 5 features for predicting PCa. The area under the receiver operating characteristic curve (AUC) of the meta-learner logistic regression model was 0.89, and the accuracy, sensitivity, and specificity were 0.828, 0.711, and 0.909, respectively. Our model also showed excellent prediction performance for high-grade PCa, with a Gleason score of 7 or higher and an AUC of 0.903. Furthermore, we evaluated the performance of the model using external cohort clinical data and achieved an AUC of 0.863. Conclusions Our ML model excelled in predicting PCa, specifically clinically significant PCa. Although extensive cross-validation in other clinical cohorts is needed, this ML model is a promising option for future diagnostics.

Background: Hand hygiene is considered the simplest and most cost-effective method of infection prevention. Regular observation and feedback on hand hygiene compliance are key strategies for its enhancement. This study evaluated the effectiveness of hand hygiene surveillance, including direct observation and feedback, by comprehensively analyzing the reported hand hygiene compliance within the Korean National Healthcare-Associated Infections Surveillance System from 2019 to 2022. Methods: Participating medical institutions included general hospitals and hospitals with infection control departments that consented to participate. Hand hygiene surveillance was conducted using direct observation. Collected data, including healthcare workers, clinical areas, hand hygiene moments, and hand hygiene compliance, were recorded to calculate hand hygiene compliance rates. Additionally, the volume of alcohol-based hand sanitizers used per patient per day was investigated as an indirect indicator of hand hygiene compliance. The study was conducted from July 2019 to December 2022. Results: Hand hygiene compliance increased from 87.2% in Q3 2019 to 89.9% in 2022. Nurses and medical technologists showed the highest compliance rates, whereas doctors showed the lowest compliance rates. Intensive care units excelled in compliance, whereas emergency de partments lagged. Compliance was highest after patient contact and lowest when the patient’s surroundings were touched. Larger hospitals consumed more alcohol-based hand sanitizers than smaller hospitals did. Conclusion This study confirmed an improvement in hand hygiene compliance through sustained surveillance, indicating its contribution not only to preventing infection transfer within healthcare facilities but also to fostering a culture of hand hygiene in the country.

Purpose: This single-arm phase II trial investigate the efficacy and safety of S-1 plus oxaliplatin (SOX) in patients with metastatic breast cancer. Materials and Methods: Patients with metastatic breast cancer previously treated with anthracyclines and taxanes were enrolled. Patients received S-1 (40-60 mg depending on patient’s body surface area, twice a day, day 1-14) and oxaliplatin (130 mg/m2, day 1) in 3 weeks cycle until disease progression or unacceptable toxicity. The primary endpoint was objective response rate (ORR) according to Response Evaluation Criteria in Solid Tumor 1.1. Secondary endpoints included time-to-progression (TTP), duration-of-response (DoR), overall survival (OS), and adverse events. Results: A total of 87 patients were enrolled from 11 institutions in Korea. Hormone receptor was positive in 54 (62.1%) patients and six (6.9%) had human epidermal growth factor receptor 2–positive disease. Forty-eight patients (85.1%) had visceral metastasis and 74 (55.2%) had more than three sites of metastases. The ORR of SOX regimen was 38.5% (95% confidence interval [CI], 26.9 to 50.0) with a median TTP of 6.0 months (95% CI, 5.1 to 6.9). Median DoR and OS were 10.3 months (95% CI, 5.5 to 15.1) and 19.4 (95% CI, not estimated) months, respectively. Grade 3 or 4 neutropenia was reported in 28 patients (32.1%) and thrombocytopenia was observed in 23 patients (26.6%). Conclusion This phase II study showed that SOX regimen is a reasonable option in metastatic breast cancer previously treated with anthracyclines and taxanes.

Kikuchi-Fujimoto disease (KFD) is an acute febrile disease that mainly involves histiocytic necrotizing lymphadenitis in children and young adults. Diagnosis of KFD is even more difficult if image-guided percutaneous biopsy is technically challenging. We present a case of clinically diagnosed KFD in an 11-year-old boy who presented with fever, abdominal pain, and mesenteric lymphadenopathy, resulting in a diagnostic challenge. Additionally, we conducted a systematic review, and our goal was to describe the spectrum of disease, therapy, and outcomes. We identified 15 cases of KFD with symptoms that mimicked mesenteric lymphadenitis. Reports from the Americas, Europe, and Asia were also included. Most patients were male, exhibited leukopenia and elevated inflammatory markers, and recovered without significant sequelae or complications. A high index of suspicion of KFD should be maintained in children presenting with prolonged fever and unusual manifestations, such as mesenteric lymphadenitis.

Sphingosine-1-phosphate (S1P) is an important lipid mediator that regulates a diverse range of intracellular cell signaling pathways that are relevant to tissue engineering and regenerative medicine. However, the precise function of S1P in dental pulp stem cells (DPSCs) and its osteogenic differentiation remains unclear. We here investigated the function of S1P/S1P receptor (S1PR)-mediated cellular signaling in the osteogenic differentiation of DPSCs and clarified the fundamental signaling pathway. Our results showed that S1P-treated DPSCs exhibited a low rate of differentiation toward the osteogenic phenotype in association with a marked reduction in osteogenesis-related gene expression and AKT activation. Of note, both S1PR1/S1PR3 and S1PR2 agonists significantly downregulated the expression of osteogenic genes and suppressed AKT activation, resulting in an attenuated osteogenic capacity of DPSCs. Most importantly, an AKT activator completely abrogated the S1P-mediated downregulation of osteoblastic markers and partially prevented S1P-mediated attenuation effects during osteogenesis. Intriguingly, the pro-inflammatory TNF-α cytokine promoted the infiltration of macrophages toward DPSCs and induced S1P production in both DPSCs and macrophages. Our findings indicate that the elevation of S1P under inflammatory conditions suppresses the osteogenic capacity of the DPSCs responsible for regenerative endodontics.
Cell Differentiation ; Cell Proliferation ; Cells, Cultured ; Dental Pulp/metabolism* ; Lysophospholipids ; Osteogenesis ; Proto-Oncogene Proteins c-akt/metabolism* ; Signal Transduction ; Sphingosine/analogs & derivatives* ; Stem Cells

The generation and maintenance of consciousness are fundamental but difficult subjects in the fields of psychology, philosophy, neuroscience, and medicine. However, recent developments in neuro-imaging techniques coupled with network analysis have greatly advanced our understanding of consciousness. The present review focuses on large-scale functional brain networks based on neuro-imaging data to explain the awareness (contents) and wakefulness of consciousness.Despite limitations, neuroimaging data suggests brain maps for important psychological and cognitive processes such as attention, language, self-referential, emotion, motivation, social behavior, and wakefulness. We considered a review of these advancements would provide new insights into research on the neural correlates of consciousness.

Purpose: To report a rare case of differentiation syndrome with ocular manifestations in a patient with acute promyelocytic leukemia treated with all-trans retinoic acid (ATRA).Case summary: A 27-year-old female complained of yellowing of vision and decreased visual acuity during an ATRA medication course for acute promyelocytic leukemia. Bilateral diffuse drusen-like lesions were found at the posterior pole along with multiple pigment epithelial detachment on optical coherence tomography (OCT) scans. Fluorescein angiography showed multiple hyperfluorescent lesions with leakage at the late phase corresponding to drusen-like lesions in fundus photography. Indocyanine green angiography revealed multiple hypocyanescent lesions. ATRA treatment was discontinued and replaced with high-dose dexamethasone. Accordingly, the patient experienced a rapid improvement in visual symptoms and the chorioretinal lesions on OCT scans showed marked resolution. Conclusions Differentiation syndrome-associated chorioretinopathy may occur in patients with acute promyelocytic leukemia treated with ATRA. Because the occurrence of chorioretinopathy may be associated with systemic aggravation of the ATRA syndrome, preemptive treatment with early detection is required.

Purpose: To compare the refractive measurements from a wavefront aberrometer, autorefractor, and retinoscopy after cycloplegia in evaluating the usefulness and validity of refractive measurements by a wavefront aberrometer in children. Methods: A total of 130 eyes of 65 children, aged from 3 to 16 years, were examined using retinoscopy, a wavefront aberrometer (OPD-Scan III), and an autorefractor (KR-1) after cycloplegia. Refractive measurements were converted to power vectors (M, J0, and J45) and cylindrical absolute values for statistical analysis. The agreement between instruments was assessed and the correlations of measurements were evaluated. Subgroup analysis was performed on two subgroups: one representing less refractive error (|M| < 2 D on cycloplegic retinoscopy) and the other with larger refractive error (|M| ≥ 2 D on cycloplegic retinoscopy). Results: Compared with retinoscopy readings, the aberrometer and autorefractor yielded more myopic values (p = 0.007, p < 0.001). In the less refractive error group, the autorefractor results showed statistically significant differences from retinoscopy readings for M, J0, and J45 and the cylindrical absolute value (all p < 0.05); there were no statistically significant differences between M, J0, and J45 vectors of the aberrometer and those obtained using retinoscopy (p = 0.674, p = 0.699, p = 0.766). With the larger refractive error group, the M vectors of the aberrometer and autorefractor showed more myopic values than the M vector retinoscopy readings; the differences were statistically significant (all p < 0.001). Conclusions The wavefront aberrometer yielded refraction readings closer to those obtained with retinoscopy than the automated refraction in the less refractive error group. With a larger refractive error, statistically significant differences (all p < 0.001) were found among the aberrometer, autorefractor, and retinoscopy readings.