Search

Objectives Tegoprazan, a novel potassium-competitive acid blocker with rapid and effective antisecretory activity, was approved for the treatment of Helicobacter pylori infections in Korea in March 2020. However, real-world data regarding tegoprazan-based therapies are scarce. We compared the efficacies of tegoprazan- and lansoprazole-based triple therapies (TTs). Methods Between March 2020 and February 2023, this study enrolled patients diagnosed with H. pylori infections who were prescribed either 14-day tegoprazan- or lansoprazole-based TTs as first-line treatments. Their medical records were retrospectively reviewed to compare H. pylori eradication rates and the rates of patient adherence to the recommended therapy. Results A total of 670 patients diagnosed with H. pylori infections were prescribed 14-day TT regimens between March 2020 and February 2023 at Ilsan Paik Hospital (Goyang, Korea). Of those enrolled in the study, 64 received tegoprazan-based TT and 295 received lansoprazole-based TT as their first-line treatment. The H. pylori eradication rates for tegoprazan- and lansoprazole-based TTs were 76.6% and 75.6%, respectively, in the intent-to-treat population; the rates were 88.9% and 88.4%, respectively, in the per-protocol population (non-inferiority test, p=0.03 and p=0.01 in the respective populations). No significant differences were observed between the two groups with regards to treatment adherence rates (84.4% vs. 85.1%, p=0.78). Conclusions As a first-line treatment for H. pylori eradication, 14-day tegoprazan-based TT demonstrated non-inferior efficacy compared with 14-day lansoprazole-based TT.

This study introduces a novel concept for axial-flow fans with winglets featuring gradually decreasing curvature along the chordwise direction. The objective is to mitigate the formation of leakage vortices in the gap flow region between the fan blade tip and the shroud. Two types of axial-flow fans, denoted as VR-A and VR-B, are designed, each incorporating variable winglets with differing rates of curvature reduction compared to the baseline CR fan with constant winglet curvature. The research encompasses a comprehensive approach involving computational fluid dynamics (CFD) simulations and experimental analyses. Numerical simulations employ incompressible Unsteady Reynolds-averaged Navier-Stokes (URANS) equations to capture intricate flow behaviors, while a virtual fan performance tester is used for flow performance predictions. Furthermore, the Ffowcs Williams & Hawking (FW–H) integral equation is utilized to estimate the radiated aerodynamic noise. Experimental measurements include flow performance assessments and noise evaluations, yielding data on flow rate, efficiency, and sound pressure spectrum. Comparisons between numerical and experimental results validate the numerical methods. Subsequent evaluations highlight the advantages of the VR fans over the CR fan, showing increased flow rates and reduced noise levels. These enhancements are attributed to the weakened leakage vortex in the gap flow region. The findings provide valuable insights for optimizing axial-flow fans partially covered by shrouds, offering improved flow performance and decreased noise radiation.

Immunoglobulin G4-related disease (IgG4-RD) is an immune-mediated fibroinflammatory disease. IgG4-RD can affect any organ system, including the pancreas, bile ducts, salivary glands, mesentery, and retroperitoneum. On the other hand, small intestine involvement is extremely rare. This paper describes a case of IgG4-RD involving the small bowel, particularly at the distal ileum. An 81-year-old female was admitted to the authors’ hospital complaining of abdominal pain, dyspepsia, and hematochezia. The laboratory tests, including tumor markers and IgG4, were within normal limits. A colonoscopy did not show any abnormal findings. Abdominal computed tomography revealed segmental aneurysmal dilatation and wall thickening at the distal ileum, suggesting malignant conditions, such as small bowel lymphoma. The patient underwent an exploratory laparoscopy and ileocecectomy to differentiate a malignancy. A histopathology examination revealed dense lymphoplasmacytic infiltration, storiform fibrosis, and IgG4-positive plasma cells (>50 per high power field). The patient was finally diagnosed with IgG4-RD. The patient was followed up in the outpatient clinic for five years without recurrence. This paper suggests that a radical resection without maintenance therapy can be a treatment option, particularly when the IgG4-RD manifests as a localized gastrointestinal tract lesion.

IntroductionPreterm birth is a leading cause of infant mortality and morbidity. Despite the improvement in the overall mortality in premature infants, the intact survival of these infants remains a significant challenge. Screening the physical growth of infants is fundamental to potentially reducing the escalation of this disorder. Recently, machine learning models have been used to predict the growth restrictions of infants; however, they frequently rely on conventional risk factors and cross-sectional data and do not leverage the longitudinal database associated with medical data from laboratory tests.MethodsThis study aimed to present an automated interpretable ML-based approach for the prediction and classification of short-term growth outcomes in preterm infants. We prepared four datasets based on weight and length including weight baseline, length baseline, weight follow-up, and length follow-up. The CHA Bundang Medical Center Neonatal Intensive Care Unit dataset was classified using two well-known supervised machine learning algorithms, namely support vector machine (SVM) and logistic regression (LR). A five-fold cross-validation, and several performance measures, including accuracy, precision, recall and F1-score were used to compare classifier performances. We further illustrated the models’ trustworthiness using calibration and cumulative curves. The visualized global interpretations using Shapley additive explanation (SHAP) is provided for analyzing variables’ contribution to final prediction.ResultsBased on the experimental results with area under the curve, the discrimination ability of the SVM algorithm was found to better than that of the LR model on three of the four datasets with 81%, 76% and 72% in weight follow-up, length baseline and length follow-up dataset respectively. The LR classifier achieved a better ROC score only on the weight baseline dataset with 83%. The global interpretability results revealed that pregnancy-induced hypertension, gestational age, twin birth, birth weight, antenatal corticosteroid use, premature rupture of membranes, sex, and birth length were consistently ranked as important variables in both the baseline and follow-up datasets.DiscussionThe application of machine learning models to the early detection and automated classification of short-term growth outcomes in preterm infants achieved high accuracy and may provide an efficient framework for clinical decision systems enabling more effective monitoring and facilitating timely intervention.

The prognosis of a patient’s re-admission and the forecast of future diagnoses is a critical task in the process of inferring clinical outcomes. The discharge summaries recorded in the Electronic Health Records (EHR) are stinking rich, but they are also heterogeneous, sparse, noisy, and biased, and hinder the learning algorithms that aim to extract actionable insights from them. The existing approaches use the current admission’s International Classification of Diseases (ICD) codes as the input features, but they do not fully describe the progression of the patient. Other systems apply the attention mechanisms directly to these notes without the guidance of domain knowledge, resulting in distorted predictions. In this work, we propose a hybrid LSTM-CNN self-guided attention model that aims to predict the ICD diagnosis that is likely to cause the next readmission within 90 days since the current discharge using the discharge narratives. Since the notes contain unnecessary tokens, the model leverages the recent advances in deep learning to predict the patient’s future diagnosis by reducing the number of tokens from the notes to be considered for prediction. We use a 1D CNN (1-Dimensional Convolutional Neural Network) to capture all features from the note and concurrently an LSTM (Long Short-Term Memory) is used to extract the features of clinically meaningful Concept Unique Identifiers (CUI) that are fetched from the note itself to build a knowledge base. The textual knowledge base guides the learning module about which n-grams from the note to focus on for prediction. We consider 3 prediction scenarios: diagnosis category prediction, the probability of the occurrence of one of the top 20 disease conditions, and ICD9 codes prediction. For the diagnosis category prediction, our proposed model achieves a macro-average ROC of 0.82 and a micro-average ROC of 0.79, an AUROC of 0.87 for the top 20 most appearing diseases prediction, and a macro-average Recall of 0.8 and a micro-average Recall of 0.84 for ICD9 codes prediction respectively. The predictive accuracy of the model is assessed through the prediction of heart failure onset and for all these prediction scenarios, the results show that the hybrid approach outperforms the existing baselines.

Colonoscopic polypectomy is effective in decreasing the incidence and mortality of colorectal cancer (CRC). Premalignant polyps discovered during colonoscopy are associated with the risk of metachronous advanced neoplasia. Postpolypectomy surveillance is the most important method for managing advanced metachronous neoplasia. A more efficient and evidence-based guideline for postpolypectomy surveillance is required because of the limited medical resources and concerns regarding colonoscopy complications. In these consensus guidelines, an analytic approach was used to address all reliable evidence to interpret the predictors of CRC or advanced neoplasia during surveillance colonoscopy. The key recommendations state that the high-risk findings for metachronous CRC following polypectomy are as follows: adenoma ≥10 mm in size; 3 to 5 (or more) adenomas; tubulovillous or villous adenoma; adenoma containing high-grade dysplasia; traditional serrated adenoma; sessile serrated lesion containing any grade of dysplasia; serrated polyp of at least 10 mm in size; and 3 to 5 (or more) sessile serrated lesions. More studies are needed to fully comprehend the patients who are most likely to benefit from surveillance colonoscopy and the ideal surveillance interval to prevent metachronous CRC.

Colonoscopic polypectomy is effective in decreasing the incidence and mortality of colorectal cancer (CRC). Premalignant polyps discovered during colonoscopy are associated with the risk of metachronous advanced neoplasia. Postpolypectomy surveillance is the most important method for the management of advanced metachronous neoplasia. A more efficient and evidence-based guideline for postpolypectomy surveillance is required because of limited medical resources and concerns regarding colonoscopy complications. In these consensus guidelines, an analytic approach was used to address all reliable evidence to interpret the predictors of CRC or advanced neoplasia during surveillance colonoscopy. The key recommendations state that the high-risk findings for metachronous CRC following polypectomy are as follows: (1) adenoma ≥10 mm in size; (2) 3 to 5 (or more) adenomas; (3) tubulovillous or villous adenoma; (4) adenoma containing high-grade dysplasia; (5) traditional serrated adenoma; (6) sessile serrated lesion (SSL) containing any grade of dysplasia; (7) serrated polyp of at least 10 mm in size; and (8) 3 to 5 (or more) SSLs. More studies are needed to fully comprehend the patients most likely to benefit from surveillance colonoscopy and the ideal surveillance interval to prevent metachronous CRC.

Axial-flow fans are widely used as cooling fans in the outdoor units of split-type air conditioners. The design of an axial-flow fan blade involves stacking several airfoils that can be differently designed for each spanwise section. However, the complex flow field around the fan blade, including circumferential and axial flows, presents challenges when applying the single airfoil theory. This study proposed a systematic performance-based design method for axial-flow fans using a cascade of airfoils based on the blade strip theory. The theory characterized the complex three-dimensional flow field driven by an axial-flow fan in terms of a two-dimensional cascade of airfoil flows. Computational fluid dynamics based on finite volume methods were used to predict the flow field and aerodynamic sound sources of an existing low-pressure axial-flow fan partially covered by a fan shroud, and the results were validated against experimental measurements. Three radial locations in the spanwise region from the hub to the blade tip that have a significant impact on aerodynamic performance were selected, and the two-dimensional flow field on a cylindrical surface with a constant radius was extracted from the three-dimensional flow field to characterize the performance of an axial fan. Then, the airfoils at the targeted span locations were optimized for a higher flow rate and greater efficiency via two-dimensional simulations using the cascades of the airfoil, and the selected optimized airfoils were applied to existing fan blades. The effectiveness of the proposed performance-based design method for low-pressure axial-flow fans was validated by the results, which showed that the redesigned fan blades with cascades of airfoils performed as predicted, increasing the intended higher flow rate by about 1%, improving power consumption by 8%, and lowering the overall sound pressure level by 1.5 dBA.

The objectives of this study were to assess the effects of ginseng on erectile dysfunction. We searched multiple electronic databases from their inceptions to 30 January 2021 without restrictions by language. We included randomized or quasirandomized controlled trials that evaluated the use of any type of ginseng as a treatment for erectile dysfunction compared to placebo or conventional treatment. The authors independently screened the literature, extracted data, assessed risk of bias, and rated the certainty of evidence (CoE) according to the GRADE approach. We included nine studies, and all compared ginseng to placebo. Ginseng appears to have a trivial effect on erectile dysfunction when compared to placebo based on the Erectile Function Domain of the International Index of Erectile Function (IIEF)-15 instrument (mean difference [MD] 3.52, 95% confidence interval [CI] 1.79 to 5.25; I²=0%; 3 studies; low CoE). Ginseng may have little to no effect on adverse events compared to placebo (risk ratio [RR] 1.45, 95% CI 0.69 to 3.03; I²=0%; 7 studies; low CoE). While ginseng may improve men's self-reported ability to have intercourse (RR 2.55, 95% CI 1.76 to 3.69; I²=23%; 6 studies; low CoE), it may have a trivial effect on men's satisfaction with intercourse based on the Intercourse Satisfaction Domain of the IIEF-15 (MD 1.19, 95% CI 0.41 to 1.97; I²=0%; 3 studies; low CoE). No study reported quality of life as an outcome.

Deep learning has progressively been the spotlight of innovations that aim to leverage the clinical time-series data that are longitudinally recorded in the Electronic Health Records(EHR) to forecast the patient’s survival and vital signs deterioration. However, their recording velocity, as well as their noisiness, hinder the proper adoption of the recently proposed benchmarks. The Recurrent Neural Networks (RNN) especially the Long-short Term Memory (LSTMs) have achieved better results in recent studies but they are hard to train and interpret and fail to properly capture the long-term dependencies. Moreover, the RNNs suffer greatly with clinical time series due to their sequential processing which cripples the prospect of parallel processing. Recently the Transformer approach was proposed for Natural Language Processing (NLP) tasks and achieved state-of-the-art results. Hence to tackle the drawbacks that are suffered by the RNNs we propose a clinical time series Multi-head Transformer (MHT), which is a transformer-based model that forecasts the patient’s future time series variables using the vitals signs. To prove the generalization of the model we use the same model for other critical tasks that describe the Intensive Care Unit (ICU) patient’s progression and the associated risks like the remaining Length Of Stay(LoS), the In-hospital Mortality as well as the 24 hours mortality. Our model achieves an Area Under The Curve-Receiver Operating Characteristics(AUC-ROC) of 0.98 and an Area Under the Curve, Precision-Recall (AUC-PR) of 0.424 for vital time series prediction, and an AUC-ROC of 0.875 in the mortality prediction. The model performs well for the frequently recorded variables like the Heart Rate (HR) and performs barely like the LSTM counterparts for the intermittently captured records such as the White Blood Count (WBC).

Purpose: Treatment options for urinary tract infection (UTI) caused by extended-spectrum beta-lactamase (ESBL)-producing organisms are limited other than carbapenem. Accordingly, clinicians should investigate alternative antimicrobial options for limited infection. This study was performed to assess the efficacy of single-dose amikacin and a 7-day oral regimen of amoxicillin/clavulanate for the treatment of acute cystitis caused by ESBL-producing Escherichia coli and Klebsiella pneumoniae. Materials and Methods: A single-dose amikacin and 7-day oral amoxicillin/clavulanate regimen was given to all patients with acute cystitis or recurrent cystitis between May 2016 and October 2018. We conducted a retrospective cohort study assessing the efficacy of this regimen for the treatment of UTI due to ESBL-producing organisms. Both clinical and laboratory efficacy were assessed a minimum of 7 days and a maximum of 14 days after the completion of treatment. Results: A total of 47 patients were enrolled in this study. E. coli and K. pneumoniae were isolated in 44 patients (93.6%) and 3 patients (6.4%), respectively. Of the 47 enrolled, 39 patients (83.0%) showed sterile culture results on follow-up. Thirty-seven patients (78.7%) showed improvement of symptoms. Of 8 patients who showed bacterial persistence, 4 patients showed ESBL-producing E. coli, whereas 4 patients showed non-ESBL E. coli on follow-up cultures. During follow-up, 12 patients experienced the recurrence of acute cystitis with a median recurrence period of 2.5 months. Conclusions: The combination of amoxicillin/clavulanate and amikacin may be an alternative to carbapenem treatment in patients with acute cystitis caused by ESBL-producing Enterobacteriaceae.

Purpose: This study aimed to understand the characteristics of sexual behaviors among Korean adults to facilitate the development of strategies and policies focused on sexual health in groups categorized by sociodemographic characteristics. Materials and Methods: A nationally representative probability sample of 2,500 individuals (1,273 men and 1,227 women) aged 18–69 years obtained using a stratified multiple-stage sampling method based on Statistics Korea (KOSTAT) participated in a cross-sectional online survey. The survey consisted of structured questionnaires comprising questions on demographic information, lifetime sexual behavior, and sexual behavior in the previous 12 months. Results: The mean age at first sexual intercourse was lower in men than in women (21.9±4.4 vs. 24.1±4.4 years, p=0.001). The overall prevalence rate of sexual events with casual partners within previous 12 months was 13.1% (95% confidence interval [CI], 11.6%–14.5%). It was found to more commonly exist among lower age groups and men. The overall regular condom use rates with relationship partner and casual partner were 14.8% (95% CI, 13.2%–16.4%) and 39.6% (95% CI, 33.9%–45.3%), respectively. Condom use rate with casual partners among 20s and 30s men was 51.2%. Overall, only 10.4% of the respondents had received sexual education about sexually transmitted infections. Conclusions: This study provided contemporary sexual behaviors in Korean adults, and identified socio-demographic factors that seem to influence sexual behaviors. Low condom use rates and low rate of receiving sexual education were concerns. The result of this study would be useful to health professionals to formulate policies and strategies related to sexual health.

Although surgery was the standard treatment for early gastrointestinal cancers, endoscopic resection is now a standard treatment for early gastrointestinal cancers without regional lymph node metastasis. High-definition white light endoscopy, chromoendoscopy, and image-enhanced endoscopy such as narrow band imaging are performed to assess the edge and depth of early gastrointestinal cancers for delineation of resection boundaries and prediction of the possibility of lymph node metastasis before the decision of endoscopic resection. Endoscopic mucosal resection and/or endoscopic submucosal dissection can be performed to remove early gastrointestinal cancers completely by en bloc fashion. Histopathological evaluation should be carefully made to investigate the presence of risk factors for lymph node metastasis such as depth of cancer invasion and lymphovascular invasion. Additional treatment such as radical surgery with regional lymphadenectomy should be considered if the endoscopically resected specimen shows risk factors for lymph node metastasis. This is the first Korean clinical practice guideline for endoscopic resection of early gastrointestinal cancer. This guideline was developed by using mainly de novo methods and encompasses endoscopic management of superficial esophageal squamous cell carcinoma, early gastric cancer, and early colorectal cancer. This guideline will be revised as new data on early gastrointestinal cancer are collected.

A point-of-interest (POI) recommendation system performs an important role in location-based services because it can help people to explore new locations and promote advertisers to launch advertisements at appropriate locations. The existing POI recommendation systems require raw check-in history of users, which might cause location privacy violations. Although there have been several matrix factorization (MF) based privacy-preserving recommendation systems, they can only focus on user-POI relationships without considering the human movements in check-in history. To tackle this problem, we design a successive POI recommendation framework with local differential privacy, named SPIREL. SPIREL uses two types of information derived from the check-in history as input for the factorization: a transition pattern between two POIs and the visit counts of POIs. We propose a novel objective function for learning the user-POI and POI-POI relationships simultaneously. We further integrate local differential privacy mechanisms in our proposed framework to prevent potential location privacy breaches. Experiments using four public datasets demonstrate that SPIREL achieves better POI recommendation quality while accomplishing stronger privacy preservation.

Purpose: To validate a novel arteriogenic erectile dysfunction (ED) model with atherosclerosis (AS) based on molecular and histologic evidence induced by chronic pelvic ischemia (CPI) and determine effect of phosphodiesterase-5 inhibitor treatment. Materials and Methods: Twenty 16-week-old male Sprague–Dawley rats were divided into three experimental groups (Group I, untreated sham-operated rats with regular diet; Group II, CPI with cholesterol diet; Group III, CPI model with cholesterol diet and mirodenafil). Erectile function was accessed using maximum intracavernous pressure (ICP) and ICP/mean arterial pressure (MAP). Molecular changes were examined by western blot analysis using hypoxia inducible factor 1-alpha (HIF-1α), endothelial nitric oxide synthase (eNOS), and transforming growth factor beta-1 (TGF-β1) antibodies. Collagen change was evaluated by Masson’s trichrome staining. Results: In vivo measurements of ICP and ICP/MAP in Group II were significantly lower than those in Group I (p

Although surgery was the standard treatment for early gastrointestinal cancers, endoscopic resection is now a standard treatment for early gastrointestinal cancers without regional lymph node metastasis. High-definition white light endoscopy, chromoendoscopy, and image-enhanced endoscopy such as narrow band imaging are performed to assess the edge and depth of early gastrointestinal cancers for delineation of resection boundaries and prediction of the possibility of lymph node metastasis before the decision of endoscopic resection. Endoscopic mucosal resection and/or endoscopic submucosal dissection can be performed to remove early gastrointestinal cancers completely by en bloc fashion. Histopathological evaluation should be carefully made to investigate the presence of risk factors for lymph node metastasis such as depth of cancer invasion and lymphovascular invasion. Additional treatment such as radical surgery with regional lymphadenectomy should be considered if the endoscopically resected specimen shows risk factors for lymph node metastasis. This is the first Korean clinical practice guideline for endoscopic resection of early gastrointestinal cancer. This guideline was developed by using mainly de novo methods and encompasses endoscopic management of superficial esophageal squamous cell carcinoma, early gastric cancer, and early colorectal cancer. This guideline will be revised as new data on early gastrointestinal cancer are collected.

Purpose: To evaluate the efficacy and safety of penile elongation featuring simple scrotal septum detachment from the penile base to compensate for the loss of penile length during penile plication in patients with Peyronie's disease compared with conventional penile plication. Materials and Methods: We conducted a retrospective analysis of 38 patients (24–75 years of age) with Peyronie's disease who underwent penile plication with or without our novel technique from January 2009 to May 2018. Penile elongation was achieved by release and detachment of the scrotal septum from the penile base to the level of the scrotal fat tissue. The objective outcome of change in stretched penile length (SPL) and the subjective outcome of patient perception of postoperative penile length were compared between groups. Any postoperative complications were recorded. Results: Of the 38 patients, 16 underwent penile plication with scrotal septum detachment (elongation group) and 22 underwent penile plication only (conventional group). The postoperative mean SPL was increased in the elongation group and decreased in the conventional group (1.2±1.3 cm vs. −0.5±0.3 cm, p

With the advancement of information and communication technology (ICT), the medical sector is undergoing a massive transformation. Health records are being digitized, stored remotely in the cloud and shared with different stakeholders. However, the use of the cloud for personal health record (PHR) storage presents data security and privacy challenges. Ciphertext-policy attribute-based encryption (CP-ABE) is being widely studied for fine-grained access control of PHRs in the cloud. Expressiveness, efficiency and attribute revocation, among others, are some key requirements of a cloud based health systems. But, many of the proposed CP-ABE schemes rely on access structures that are either restrictive or cumbersome and thus result in less expressive and efficient schemes. Many of the schemes also lack mechanisms for efficient and immediate attribute/user revocation. In this work, we propose an expressive and efficient access control scheme with attribute/user revocation based on ordered binary decision diagram (OBDD) access structure. We use the attribute group approach to achieve the attribute/user revocation in our work. Additionally, the ciphertexts and private keys are assigned version numbers to prevent the revoked group members from colluding with non-revoked members. Security and efficiency analysis show that our proposed scheme is secure, expressive and efficient.

Purpose: To evaluate if preoperative sterile pyuria can be a prognostic factor for intravesical recurrence (IVR) and overall survival (OS)in patients with upper tract urothelial carcinoma (UTUC) undergoing surgery. Materials and Methods: We retrospectively reviewed the medical records of patients who were diagnosed with UTUC from October 2003 to December 2016 at Korea University Medical Center. Sterile pyuria was defined as urine containing five or more white blood cells per high-power field in the absence of bacteria in urine culture. We used a stepwise multivariable Cox proportional hazards model to assess the independent effects of the prognostic factors for IVR and OS. Results: We investigated a total of 176 patients who were diagnosed with UTUC. Among them, 91 (51.7%) patients had preoperative sterile pyuria. There were no significant differences in the baseline characteristics between the pyuria and non-pyuria groups concerning tumor grade, T stage, tumor multiplicity, and recurrence history. However, there was a significant difference in the IVR between the two groups. In the multivariable analysis, preoperative sterile pyuria, diabetes mellitus, high-grade tumor, and lymphovascular invasion were revealed as independent risk factors for IVR, and only lymphovascular invasion was identified as an independent risk factor for OS. Conclusions: Preoperative sterile pyuria is significantly associated with IVR in patients with UTUC undergoing surgery, but it is not associated with OS. Furthermore, diabetes mellitus, high-grade tumor, and lymphovascular invasion are also independent prognostic factors for these patients.

Purpose: The primary aim of this study was to assess treatment persistence with a fixed-dose combination (FDC) of tadalafil (5 mg) and tamsulosin (0.4 mg). This study also evaluated the reasons for early treatment discontinuation. Materials and Methods: This retrospective observational study included patients with benign prostatic hyperplasia and erectile dysfunction who started an FDC treatment of tadalafil (5 mg) and tamsulosin (0.4 mg) between July 2017 and February 2018. Treatment persistence and reasons for early discontinuation were evaluated during the first 6 months. The cumulative discontinuation rate and differences in various parameters were assessed using Kaplan–Meier analysis and the log-rank test, respectively. Factors related to persistence were analyzed using a Cox proportional hazard model. Results: Overall, 97 patients were included in the study. The cumulative persistence rate at 30, 90, and 180 days was 88.7%, 66.0%, and 54.6%, respectively. The cumulative persistence over 6 months differed significantly according to the administration of FDC therapy (log-rank p=0.005) and age (log-rank p=0.024). Younger patients (odds ratio, 2.049; p=0.021) and treatment-naive patients (odds ratio, 2.461; p=0.006) were more likely to discontinue therapy within 6 months. The common reasons for discontinuing therapy were side effects (63.6%) and perceived poor efficacy (22.7%). Conclusions: Side effects were reported to be the main reason for treatment discontinuation. Thus, to improve compliance for a once-daily FDC of tadalafil (5 mg) and tamsulosin (0.4 mg), it is recommended to select patients who show adaptation to a combination of α-blockers and phosphodiesterase type 5 inhibitors prior to FDC treatment.

Recent advances in positioning techniques, along with the widespread use of mobile devices, make it easier to monitor and collect user trajectory information during their daily activities. An ever-growing abundance of data about trajectories of individual users paves the way for various applications that utilize user mobility information. One of the most common analysis tasks in these new applications is to extract the sequential transition patterns between two consecutive timestamps from a collection of trajectories. Such patterns have been widely exploited in diverse applications to predict and recommend next user locations based on the current position. Thus, in this paper, we explore the computation of the transition patterns, especially with a trajectory dataset collected using differential privacy, which is a de facto standard for privacy-preserving data collection and processing. Specifically, the proposed scheme relies on geo-indistinguishability, which is a variant of the well-known differential privacy, to collect trajectory data from users in a privacy-preserving manner, and exploits the functionality of the expectation-maximization algorithm to precisely estimate hidden transition patterns based on perturbed trajectory datasets collected under geo-indistinguishability. Experimental results using real trajectory datasets confirm that a good estimation of transition pattern can be achieved with the proposed method.

Many estuaries have been damaged by such material movements as marine debris, suspended sediment, and pollutants. Understanding the estuarine circulation system is necessary to solve such problems. Salt transport analysis provides an insight into hydrodynamic processes about material circulation in the estuary. In this study, to understand the mechanisms of salt transport, a three-dimensional hydrodynamic model was applied in the hypertidal estuary system—Yeomha Channel in Gyeonggi Bay. The simulation period of the model was a total of 245 days (20 January to 20 September 2020), including the dry and wet seasons. The model results for the temporal variation in tide, current velocity, and salinity were validated by comparing them with the observed in-situ data. The total salt transport (FS) was calculated in three cross sections of the Yeomha Channel and was decomposed into three components (QfS0: advective salt transport; FE: steady shear dispersion; FT: tidal oscillatory salt transport). During the dry season with strong tidal forces, the total salt transport patterns were mainly dominated by QfS0. During the wet season with high river discharge, the total salt transport patterns were determined by the balance between QfS0, FE, and FT. The long-term tidal constituents (MSf and Mm) were the main mechanisms causing QfS0 with the spring–neap variation during the dry season. The tidal trapping effect, caused by a phase difference of less than 90° between tidal current and salinity, generated landward FT in the dry and wet seasons. In addition, the high river discharge during the wet season decreased the phase difference between tidal current and salinity to less than 70°, resulting in a much stronger landward FT. This study suggests that the long-term tidal constituents and tidal trapping effect are unique characteristics that contribute to material circulation in the hypertidal estuary.

Esophageal cancer is one of the lethal malignant tumors because it is often diagnosed in the advanced stage with lymph node or distant metastasis. The recurrence rate of esophageal cancer is known to be about 40% to 50% even in the patients who underwent curative esophageal resection. Most frequent sites of metastases are known to be the liver. Furthermore, other distant metastases also could be developed in lung, bone, brain, kidney, adrenal, abdominal cavity, and skin. However, ampulla of Vater (AoV) metastasis rarely occurs from esophageal cancer. Therefore, we report herein a case of AoV metastasis from squamous cell carcinoma of the esophagus.

A map-based infectious disease outbreak information system, called PEACOCK, that provides three types of necessary infectious disease outbreak information is presented. The system first collects the infectious disease outbreak statistics from the government agencies and displays the number of infected people and infection indices on the map. Then, it crawls online news articles for each infectious disease and displays the number of mentions of each disease on the map. Users can also search for news articles regarding the disease. Finally, it retrieves the portal search query data and plots the graphs of the trends. It divides the risk into three levels (i.e., normal, caution, and danger) and visualizes them using different colors on the map. Users can access infectious disease outbreak information accurately and quickly using the system. As the system visualizes the information using both a map and various types of graphs, users can check the information at a glance. This system is in live at http://www.epidemic.co.kr/map.

Collaborative eHealth that enables the collection and sharing of patients' data is eliminating the location and accessibility barriers in healthcare service delivery. With advances in technology, patients' data can be collected from anywhere, at any time, stored in a central location, and shared across multiple service providers to improve the quality of healthcare service delivery. Maintaining patients' data privacy during the storage and sharing process is critical for collaborative eHealth success. The attribute-based encryption, which has shown potential in data privacy protection in the cloud, has the necessary ingredients to be used in guarding against privacy violations in collaborative eHealth. In this paper, we survey the different attribute-based encryption schemes for usage in collaborative eHealth. We discuss some challenges associated with the use of attribute-based encryption schemes in collaborative eHealth and point out some future research directions. Also, we perform a comparative analysis of the surveyed schemes in terms of security, revocation ability, and efficiency.

With the development of smart healthcare services, there is a growing demand for healthcare environments in which a patient can be collaboratively treated by multiple healthcare providers. To enable such collaborative treatments, it is essential to have a collaborative eHealth system that is capable of storing and managing large-scale health data generated by multiple healthcare providers as well as patients themselves in one place. However, this system may raise serious privacy concerns because of unauthorized access to sensitive health data of a data owner by other users. Usually, such privacy concerns can be resolved using attribute-based encryption (ABE), which provides fine-grained data access control mechanisms. Through ABE, in which access control is expressed by a set of attributes, the sensitive data of a data owner can be selectively shared with a set of data users by encrypting it with a set of attributes. However, with the growing popularity of smart healthcare services, which are enabled by analyzing large-scale health data collected from diverse populations, a binary access control policy akin to this is not sufficient for supporting the ever-growing request for sharing health data. Hence, in this paper, we develop a novel collaborative eHealth system that supports Multilevel Privacy-Preserving Data Sharing, MPPDS. In MPPDS, a data owner is able to share his or her health data with various data users within a collaborative eHealth system, under different levels of privacy protections. Specifically, our approach leverages local differential privacy to preserve the privacy of data owners in the process of data sharing and relies on ABE to support multilevel privacy guarantee mechanisms depending on the degree of trust between data owners and data users. We also present a method to effectively estimate aggregate statistics based on the collection of health data shared by different data owners under MPPDS. Experimental results with real and synthetic data sets demonstrate that the proposed MPPDS scheme enables more trusted data users to compute more accurate aggregate statistics than less trusted data users in a collaborative eHealth system.

Recent technological advancements have led to a deluge of medical data from various domains. However, the recorded data from divergent sources comes poorly annotated, noisy, and unstructured. Hence, the data is not fully leveraged to establish actionable insights that can be used in clinical applications. These data recorded in hospital's Electronic Health Records (EHR) consists of patient information, clinical notes, charted events, medications, procedures, laboratory test results, diagnosis codes, and so on. Traditional machine learning and statistical methods have failed to offer insights that can be used by physicians to treat patients as they need to obtain an expert opinion assisted features before building a benchmark task model. With the rise of deep learning methods, there is a need to understand how deep learning can save lives. The purpose of this study was to offer an intuitive explanation for possible use cases of deep learning with EHR. We reflect on techniques that can be applied by health informatics professionals by giving technical intuitions and blue prints on how each clinical task can be approached by a deep learning algorithm.

Q-learning is arguably one of the most applied representative reinforcement learning approaches and one of the off-policy strategies. Since the emergence of Q-learning, many studies have described its uses in reinforcement learning and artificial intelligence problems. However, there is an information gap as to how these powerful algorithms can be leveraged and incorporated into general artificial intelligence workflow. Early Q-learning algorithms were unsatisfactory in several aspects and covered a narrow range of applications. It has also been observed that sometimes, this rather powerful algorithm learns unrealistically and overestimates the action values hence abating the overall performance. Recently with the general advances of machine learning, more variants of Q-learning like Deep Q-learning which combines basic Q learning with deep neural networks have been discovered and applied extensively. In this paper, we thoroughly explain how Q-learning evolved by unraveling the mathematical complexities behind it as well its flow from reinforcement learning family of algorithms. Improved variants are fully described, and we categorize Q-learning algorithms into single-agent and multi-agent approaches. Finally, we thoroughly investigate up-to-date research trends and key applications that leverage Q-learning algorithms.

Due to privacy concerns, multi-party gradient tree boosting algorithms have become widely popular amongst machine learning researchers and practitioners. However, limited existing works have focused on vertically partitioned datasets, and the few existing works are either not scalable or tend to leak information. Thus, in this work, we propose SSXGB, which is a scalable and acceptably secure multi-party gradient tree boosting framework for vertically partitioned datasets with partially outsourced computations. Specifically, we employ an additive homomorphic encryption (HE) scheme for security. We design two sub-protocols based on the HE scheme to perform non-linear operations associated with gradient tree boosting algorithms. Next, we propose secure training and prediction algorithms under the SSXGB framework. Then, we provide theoretical security and communication analysis for the proposed framework. Finally, we evaluate the performance of the framework with experiments using two real-world datasets.

Introduction: Glans penis augmentation (GPA) using hyaluronic acid (HA) gel has been developed for treating premature ejaculation (PE) with penile hypersensitivity. The injected HA filler creates a barrier that reduces the tactile stimuli to the hypersensitive dorsal nerve. Although the HA filler is biodegradable and is believed to not cause permanent loss of sexual function, the current International Society for Sexual Medicine guideline for PE does not recommend this procedure owing to concerns regarding sexual dysfunction. Aim: To investigate the practice patterns for GPA using HA filler among Korean urologists, and to identify whether urologist experienced patient reports of sexual dysfunction post-treatment. Methods: Between March 2016 and July 2016, a specially designed questionnaire was mailed to 86 selected Korean urologists who had used injectable materials to treat PE. Main Outcome Measures: The prevalence and awareness of sexual dysfunction after GPA using HA filler were evaluated. Results: Overall, 56 urologists completed the survey (response rate: 69.2%), of which 36 (64.3%) had performed GPA using HA filler. They reported having performed a combined total of 4,344 such GPA procedures. Most urologists (72.7%) performed GPA using HA filler in patients who benefit from topical anesthetics. Patients with a history of failed pharmacotherapy (59.1%) and selective dorsal nerve neurotomy (45.5%) were selected for GPA using HA filler. The respondents (44.4%) encountered overall 206 (4.7%) cases of patients reports of recurrence of PE. Interestingly, only 36 (0.8%) cases of glans pain or paresthesia and no cases of erectile dysfunction post-treatment were reported. Conclusion: Korean urologists performed GPA using HA filler when pharmacotherapy failed or if there was a response to topical treatment. Paresthesia and hypoesthesia after GPA using HA filler are rare, and no cases of erectile dysfunction were encountered by Korean urologists.Jeong HG, Ahn ST, Kim JW, et al. Practice Patterns Among Korean Urologists for Glans Penis Augmentation Using Hyaluronic Acid Filler in the Management of Premature Ejaculation. Sex Med 2018;6:297–301. Key Words: Pre-Mature Ejaculation, Glans Penis Augmentation, Hyaluronic Acid Gel, Sexual Function Loss

AimThis study evaluated the prognosis and survival predictors for bladder urachal carcinoma (UC), based on large scale multicenter cohort with long term follow-up database.MethodsA total 203 patients with bladder UC treated at 19 hospitals were enrolled. Clinical parameters on carcinoma presentation, diagnosis, and therapeutic methods were reviewed for the primary cancer and for all subsequent recurrences. The stage of UC was stratified by Mayo and Sheldon pathological staging system. Oncological outcomes and the possible clinicopathological parameters associated with survival outcomes were investigated.ResultsThe mean age of the patients was 54.2 years. Among the total of 203 patients, stages I, II, III, and IV (Mayo stage) were 48 (23.8%), 108 (53.5%), 23 (11.4%), and 23 (11.4%), respectively. Gross hematuria and bladder irritation symptoms were the two most common initial symptoms. The mean follow-up period was 65 months, and 5-year overall survival rates (OS), cancer-specific survival rates (CSS), and recurrence-free survival rates (RFS) were 88.3, 83.1, and 63.9%, respectively. For the patients with Mayo stage ≥III, OS, CSS, and RFS were significantly decreased to 38.0, 35.2, and 28.4%, respectively. The higher pathological stage (Mayo stage ≥III, Sheldon stage ≥IIIc), positive surgical margin (PSM), and positive lymphovascular invasion (PLM) were independent predictors of shorter OS, CSS, and RFS.ConclusionThe pathological stage, PSM, and PLM were significantly associated with the survival of UC patients, emphasizing an importance of the complete surgical resection of tumor lesion.

With the rapid advancement of information and communication technologies, there is a growing transformation of healthcare systems. A patient's health data can now be centrally stored in the cloud and be shared with multiple healthcare stakeholders, enabling the patient to be collaboratively treated by more than one healthcare institution. However, several issues, including data security and privacy concerns still remain unresolved. Ciphertext-policy attribute-based encryption (CP-ABE) has shown promising potential in providing data security and privacy in cloud-based systems. Nevertheless, the conventional CP-ABE scheme is inadequate for direct adoption in a collaborative ehealth system. For one, its expressiveness is limited as it is based on a monotonic access structure. Second, it lacks an attribute/user revocation mechanism. Third, the computational burden on both the data owner and data users is linear with the number of attributes in the ciphertext. To address these inadequacies, we propose CESCR, a CP-ABE for efficient and secure sharing of health data in collaborative ehealth systems with immediate and efficient attribute/user revocation. The CESCR scheme is unbounded, i.e., it does not bind the size of the attribute universe to the security parameter, it is based on the expressive and non-restrictive ordered binary decision diagram (OBDD) access structure, and it securely outsources the computationally demanding attribute operations of both encryption and decryption processes without requiring a dummy attribute. Security analysis shows that the CESCR scheme is secure in the selective model. Simulation and performance comparisons with related schemes also demonstrate that the CESCR scheme is expressive and efficient.

This study investigated the flow patterns and affecting factors in the North Port of Incheon, South Korea, to understand the inner-port circulation characteristics by applying an unstructured grid finite volume community ocean model (FVCOM) together with a field survey. The FVCOM considered the tide, river discharge, surface winds, and atmospheric pressure with the highest resolution of 50 m around the port. The model results were validated with current velocity and salinity observations. In the main channel, the difference in salinity between the sea surface and bottom increased during the neap tide due to weakened tidal currents, thus strengthening the stratification. However, at the inner port, strong stratification was observed during spring tide as the near-surface freshwater from upstream of the estuary moved relatively farther south of the port than that during the neap tide. Freshwater flowed into the port during the flood current and was trapped in the semi-closed geometry of the inner port. The horizontal salinity gradient between the trapped fresher water in the port and saltier water in the main channel increased during the flood current. As a result, density-driven circulations associated with near-bed currents towards the port were maintained for more than 3 h after high tide. This result implies that the baroclinic effect, mainly due to the salinity gradient in the North Port, could significantly affect residual circulation at the inner harbor in a macro-tidal environment and the mass transport mechanism, such as sediment transport. In general, such enhanced baroclinic effects due to salinity and tides are not limited to the North Port and can have greater effects on inner-port circulation in other macro-tidal harbors that suffer from severe sedimentation problems.

Alterations involving serine-threonine phosphatase PP2A subunits occur in a range of human cancers, and partial loss of PP2A function contributes to cell transformation. Displacement of regulatory B subunits by the SV40 Small T antigen (ST) or mutation/deletion of PP2A subunits alters the abundance and types of PP2A complexes in cells, leading to transformation. Here, we show that ST not only displaces common PP2A B subunits but also promotes A-C subunit interactions with alternative B subunits (B’’’, striatins) that are components of the Striatin-interacting phosphatase and kinase (STRIPAK) complex. We found that STRN4, a member of STRIPAK, is associated with ST and is required for ST-PP2A-induced cell transformation. ST recruitment of STRIPAK facilitates PP2A-mediated dephosphorylation of MAP4K4 and induces cell transformation through the activation of the Hippo pathway effector YAP1. These observations identify an unanticipated role of MAP4K4 in transformation and show that the STRIPAK complex regulates PP2A specificity and activity.

Background: Testosterone action is mediated through the androgen receptor (AR), whose sensitivity is influenced by the AR CAG repeat polymorphism. However, the relation between late-onset hypogonadism (LOH) and AR CAG repeat length is unclear and studies of Asian populations are limited. Aim: To investigate the relation between AR CAG repeat length and LOH in Korean men. Methods: 263 Korean men (mean age = 63.43 ± 10.9 years) were enrolled from 2014 to 2015. LOH diagnosis was based on a serum testosterone level lower than 3.5 ng/mL and positive androgen deficiency according to the Aging Males’ Symptom Scale (AMS). Total testosterone levels and answers to the LOH-related questionnaire were analyzed. Outcomes: The relation between AR CAG repeat length and LOH was determined. Results: Mean CAG repeat length was 22.1 ± 4.6 and mean serum testosterone levels were 2.6 ± 0.7 and 6.0 ± 2.0 ng/mL in men with and without LOH, respectively. Men with LOH showed significantly longer AR CAG repeat lengths than men without LOH (26.1 vs 21.6, P < .001). Longer CAG repeat lengths were correlated with higher AMS total scores (r = 0.454, P = .001) and AMS psychotic, somatic, and sexual sub-scores (r = 0.276, 0.246, and 0.571, P = .006, .007, .001, respectively) and significantly lower 5-item International Index of Erectile Function scores (r = −0.261, P = .001). Multivariate analysis showed that patient age and CAG repeat length were independently associated with LOH (odds ratio = 1.05 and 1.29, P = .041 and

Big data, which is being explosively generated in various areas, is considered as a new growth engine for diverse industries. In recent years, analysis of big data has attracted attention because it exhibits the potential to generate high value. In addition, with the advent of the IoT era, wherein each object is connected to all the others in a system, the importance of big data is likely to continue to be emphasized, due to the availability of data generated from diverse devices. With the increasing importance of indoor space in which most city dwellers spend over 80% of daily life, big data containing users' indoor positioning information is a critical asset for understanding the indoor behavior pattern of users, such as the shopping behavior pattern of customers in a large department store. However, there is also a risk of leakage of personal information, because it is feasible to infer the users' sensitive information by tracking and analyzing the users' indoor positions. Local differential privacy (LDP) is the state-of-the-art approach that is used to protect individual privacy in the process of data collection. LDP ensures that the privacy of the data contributor is protected by perturbing her/his original data at the data contributor's side; thus, the data collector cannot access the original data, but is still able to obtain population statistics. This paper focuses on the application of LDP to the collection of indoor positioning data. In particular, we experimentally evaluated the utilization of indoor positioning big data collected by leveraging LDP for estimating the density of the specified indoor area. Experimental results with both synthetic and actual data sets demonstrate that LDP is well applicable to the collection of indoor positioning data for the purpose of inferring population statistics.

Most of us live our daily lives in various types of indoor environments. With the rapidly increasing air pollution and abnormal weather conditions occurring all over the world, the importance of indoor space is expected to increase in the future. As the importance of indoor spaces has increased, there have been extensive efforts to understand the indoor behavior patterns of individuals by collecting and analyzing their indoor positioning data. However, indiscriminate collection of indoor location information may raise significant privacy issues, because it is possible to infer sensitive information by analyzing their indoor location data. Thus, there is a need to develop a technology capable of: 1) collecting individuals' indoor positioning data while not violating privacy requirements and 2) analyzing their movement patterns, based on the indoor positioning data set collected in a privacy-preserving manner. Recently, there has been a growing interest in local difference privacy (LDP) that can protect individual privacy in the process of data collection. The main concept of LDP is adding carefully designed noise to sensitive data at the data contributor's side and directly sending the noisy data to a data collector, guaranteeing that the original data are not exposed to the outside. In this paper, we first develop a method to collect individuals' indoor positioning information by leveraging LDP, and then, we introduce an effective approach to compute top-k routes between two points in indoor environments by leveraging the indoor positioning data sets collected in an LDP manner. Experimental results show that the proposed approach well exploits the indoor positioning data collected in an LDP-compliant manner, and a good estimation of top-k routes can be achieved with the proposed method and a large data set.

Humans are susceptible to various infectious diseases. However, humanity still has limited responses to emergent and recurrent infectious diseases. Recent developments in medical technology have led to various vaccines being developed, but these vaccines typically require a considerable amount of time to counter infectious diseases. Therefore, one of the best methods to prevent infectious diseases is to continuously update our knowledge with useful information from infectious disease information systems and taking active steps to safeguard ourselves against infectious diseases. Some existing infectious disease information systems simply present infectious disease information in the form of text or transmit it via e-mail. Other systems provide data in the form of files or maps. Most existing systems display text-centric information regarding infectious disease outbreaks. Therefore, understanding infectious disease outbreak information at a glance is difficult for users. In this paper, we propose the infectious disease outbreak statistics visualization system, called to DOVE, which collects infectious disease outbreak statistics from the Korea Centers for Disease Control & Prevention and provides statistical charts with district, time, infectious disease, gender, and age data. Users can easily identify infectious disease outbreak statistics at a glance by simply entering the district, time, and name of an infectious disease into our system. Additionally, each statistical chart allows users to recognize the characteristics of an infectious disease and predict outbreaks by investigating the outbreak trends of that disease. We believe that our system provides effective information to help prevent infectious disease outbreaks. Our system is currently available on the web at http://www.epidemic.co.kr/statistics.

Because of the vast availability of data, there has been an additional focus on the health industry and an increasing number of studies that aim to leverage the data to improve healthcare have been conducted. The health data are growing increasingly large, more complex, and its sources have increased tremendously to include computerized physician order entry, electronic medical records, clinical notes, medical images, cyber-physical systems, medical Internet of Things, genomic data, and clinical decision support systems. New types of data from sources like social network services and genomic data are used to build personalized healthcare systems, hence health data are obtained in various forms, from varied sources, contexts, technologies, and their nature can impede a proper analysis. Any analytical research must overcome these obstacles to mine data and produce meaningful insights to save lives. In this paper, we investigate the key challenges, data sources, techniques, technologies, as well as future directions in the field of big data analytics in healthcare. We provide a do-it-yourself review that delivers a holistic, simplified, and easily understandable view of various technologies that are used to develop an integrated health analytic application.

There is no safe and effective standard method for glans penis augmentation. Furthermore, there has been scant research on glans penis augmentation due to a poor understanding of glans anatomy, technical difficulty, and a lack of suitable substances for augmentation. Cross-linked dextran gel is a newly developed filler for soft-tissue augmentation. We evaluated the efficacy and safety of using a novel technique to inject cross-linked dextran gel for glans penis augmentation during a 24-week follow-up study. This prospective, single-arm, multicenter study enrolled twenty healthy adult men who underwent glans penis augmentation between June and August 2013. Cross-linked dextran gel was injected into the glans penis using a simple and easy technique. The sizes of the glans penis and individual satisfaction were assessed. Any adverse event was also reported. A total of 18 individuals were analyzed; two of them were lost to follow-up. The mean procedure time and injected volume were about 30 min and 6.6 ± 0.9 ml, respectively. The mean surface areas of the glans at baseline and 24 weeks were 20.0 ± 3.5 cm2 and 33.6 ± 5.4 cm2 , respectively, representing a mean increase of 68.7% ± 14.0% (P < 0.001). Sixteen individuals (88.9%) were satisfied with the outcomes, and none were dissatisfied. There were no serious adverse events during the study. Cross-linked dextran gel injection for glans penis augmentation was easy and showed a significant augmentative effect on the glans penis, good durability, and was well tolerated without serious adverse events. Therefore, cross-linked dextran gel injection may be an effective, new technique for glans penis augmentation.

Purpose: In epidemiological studies, there are various associations of androgen receptor (AR) CAG with several diseases or phenotypes. However, the relationship between CAG repeat length and metabolic syndrome (MS) remains unclear, especially in Asian populations. This study was designed to evaluate the relationship between AR CAG repeat length polymorphism and MS in a Korean male population. Materials and Methods: We explored the relationship between AR CAG repeat length polymorphism and MS in a Korean male population (n=337) from 2013 to 2014. AR CAG repeat were determined by microsatellite fragment sizing. Components of MS and laboratory data (lipid profile, fasting glucose, and glycated hemoglobin [HbA1c]) were analyzed with AR CAG repeat length. Results: The mean AR CAG repeat length was 22.3±4.7. Sixty-nine men (20.5%) were diagnosed with MS. Men with MS showed significantly longer AR CAG repeat lengths compared with men without MS (26.2 vs. 21.4, p＜0.001). With increasing CAG repeat, the number of components meeting the NCEP criteria increased significantly. AR CAG repeat length was associated significantly with high density lipoprotein (HDL), triglyceride, and HbA1c levels. In the multivariate analysis, CAG repeat length, waist circumference, and levels of HDL were independently associated with MS. (odds ratio (OR)=1.37, 1.19 and 0.90, p ＜0.001, 0.045, and 0.001, respectively). Conclusions: AR CAG repeat length was associated with MS and laboratory test results, such as those for HDL, triglycerides, and HbA1c, in Korean males. Longer CAG repeat length was identified as a risk factor for MS in Korean males.

There has recently been an increasing need for the collection and sharing of microdata containing information regarding an individual entity. Because microdata typically contain sensitive information on an individual, releasing it directly for public use may violate existing privacy requirements. Thus, extensive studies have been conducted on privacy-preserving data publishing (PPDP), which ensures that any microdata released satisfy the privacy policy requirements. Most existing privacy-preserving data publishing algorithms consider a scenario in which a data publisher, receiving a request for the release of data containing personal information, anonymizes the data prior to publishing—a process that is usually conducted offline. However, with the increasing demand for the sharing of data among various parties, it is more desirable to integrate the data anonymization functionality into existing systems that are capable of supporting online query processing. Thus, we developed a novel scheme that is able to efficiently anonymize the query results on the fly, and thus support efficient online privacy-preserving data publishing. In particular, given a user’s query, the proposed approach effectively estimates the generalization level of each quasi-identifier attribute, thereby achieving the k-anonymity property in the query result datasets based on the statistical information without applying k-anonymity on all actual datasets, which is a costly procedure. The experiment results show that, through the proposed method, significant gains in processing time can be achieved.

Due to the prevalence of globalization and the surge in people’s traffic, diseases are spreading more rapidly than ever and the risks of sporadic contamination are becoming higher than before. Disease warnings continue to rely on censored data, but these warning systems have failed to cope with the speed of disease proliferation. Due to the risks associated with the problem, there have been many studies on disease outbreak surveillance systems, but existing systems have limitations in monitoring disease-related topics and internationalization. With the advent of online news, social media and search engines, social and web data contain rich unexplored data that can be leveraged to provide accurate, timely disease activities and risks. In this study, we develop an infectious disease surveillance system for extracting information related to emerging diseases from a variety of Internet-sourced data. We also propose an effective deep learning-based data filtering and ranking algorithm. This system provides nation-specific disease outbreak information, disease-related topic ranking, a number of reports per district and disease through various visualization techniques such as a map, graph, chart, correlation and coefficient, and word cloud. Our system provides an automated web-based service, and it is free for all users and live in operation.

Acute renal failure can be the result of acute renal cortical necrosis (RCN), which commonly occurs from complications occurring during pregnancy. RCN is rarely caused by medications, although tranexamic acid, which is used in patients with acute bleeding for its antifibrinolytic effects, reportedly causes acute RCN in rare cases. An 82-year-old woman experienced gastrointestinal bleeding after endoscopic papillectomy of an ampullary adenoma. The bleeding was controlled with tranexamic acid administration; however, 4 days later, her urine volume decreased and she developed pulmonary edema and dyspnea. Serum creatinine levels increased from 0.8 to 3.9 mg/dL and dialysis was performed. Abdominal pelvic computed tomography with contrast enhancement revealed bilateral RCN with no renal cortex enhancement. Renal dysfunction and oliguria persisted and hemodialysis was continued. Clinicians must be aware that acute RCN can occur after tranexamic acid administration to control bleeding.

Abstract Background Publishing raw electronic health records (EHRs) may be considered as a breach of the privacy of individuals because they usually contain sensitive information. A common practice for the privacy-preserving data publishing is to anonymize the data before publishing, and thus satisfy privacy models such as k-anonymity. Among various anonymization techniques, generalization is the most commonly used in medical/health data processing. Generalization inevitably causes information loss, and thus, various methods have been proposed to reduce information loss. However, existing generalization-based data anonymization methods cannot avoid excessive information loss and preserve data utility. Methods We propose a utility-preserving anonymization for privacy preserving data publishing (PPDP). To preserve data utility, the proposed method comprises three parts: (1) utility-preserving model, (2) counterfeit record insertion, (3) catalog of the counterfeit records. We also propose an anonymization algorithm using the proposed method. Our anonymization algorithm applies full-domain generalization algorithm. We evaluate our method in comparison with existence method on two aspects, information loss measured through various quality metrics and error rate of analysis result. Results With all different types of quality metrics, our proposed method show the lower information loss than the existing method. In the real-world EHRs analysis, analysis results show small portion of error between the anonymized data through the proposed method and original data. Conclusions We propose a new utility-preserving anonymization method and an anonymization algorithm using the proposed method. Through experiments on various datasets, we show that the utility of EHRs anonymized by the proposed method is significantly better than those anonymized by previous approaches.

Background/Aims: To date, the best therapeutic modality for gastric adenoma, especially low-grade adenoma, has not been established. The aim of this study was to assess the usefulness of argon plasma coagulation (APC) in treating gastric adenoma compared with endoscopic submucosal dissection (ESD). Methods: We included 210 patients with gastric adenoma, who underwent treatment with either APC (97 patients) or ESD (113 patients). The clinical and pathologic characteristics, mean duration of hospital stay, complications, and recurrence rates between the two groups were compared. Results: The mean adenoma size was 0.9 cm and 1.1 cm in the APC group and ESD group, respectively (p

Granulomatous reaction associated with clear cell renal cell carcinoma (CCRCC) is a rare finding, and only a few cases have been described in the literature. It is postulated to occur due to cancer-related antigenic factors such as cancer cells themselves or soluble tumor antigens shed into the blood. Herein, we describe a case of a 56-year-old male patient diagnosed with CCRCC with intratumoral granulomatous inflammation.

Crohn's disease (CD) is a chronic, progressive, and disabling inflammatory bowel disease (IBD) with an uncertain etiopathogenesis. CD can involve any site of the gastrointestinal tract from the mouth to the anus, and is associated with serious complications, such as bowel strictures, perforations, and fistula formation. The incidence and prevalence rates of CD in Korea are still lower compared with those in Western countries, but they have been rapidly increasing during the recent decades. Although there are no definitive curative modalities for CD, various medical and surgical therapies have been applied for the treatment of this disease. Concerning CD management, there have been substantial discrepancies among clinicians according to their personal experience and preference. To suggest recommendable approaches to the diverse problems of CD and to minimize the variations in treatment among physicians, guidelines for the management of CD were first published in 2012 by the IBD Study Group of the Korean Association for the Study of Intestinal Diseases. These are the revised guidelines based on updated evidence, accumulated since 2012. These guidelines were developed by using mainly adaptation methods, and encompass induction and maintenance treatment of CD, treatment based on disease location, treatment of CD complications, including stricture and fistula, surgical treatment, and prevention of postoperative recurrence. These are the second Korean guidelines for the management of CD and will be continuously revised as new evidence is collected.

Big web data from sources including online news and Twitter are good resources for investigating deep learning. However, collected news articles and tweets almost certainly contain data unnecessary for learning, and this disturbs accurate learning. This paper explores the performance of word2vec Convolutional Neural Networks (CNNs) to classify news articles and tweets into related and unrelated ones. Using two word embedding algorithms of word2vec, Continuous Bag-of-Word (CBOW) and Skip-gram, we constructed CNN with the CBOW model and CNN with the Skip-gram model. We measured the classification accuracy of CNN with CBOW, CNN with Skip-gram, and CNN without word2vec models for real news articles and tweets. The experimental results indicated that word2vec significantly improved the accuracy of the classification model. The accuracy of the CBOW model was higher and more stable when compared to that of the Skip-gram model. The CBOW model exhibited better performance on news articles, and the Skip-gram model exhibited better performance on tweets. Specifically, CNN with word2vec models was more effective on news articles when compared to that on tweets because news articles are typically more uniform when compared to tweets.