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ObjectiveWe compared the efficacy and postoperative complications of tension-free vaginal tape (TVT)-abbrevo® (TVT-A) and TVT-obturator® (TVT-O) surgeries for the treatment of stress urinary incontinence (SUI).MethodsWe retrospectively analyzed the medical records of 143 female patients with SUI who underwent TVT-A or TVT-O surgery between January 2010 and December 2019 at the Asan Medical Center in Seoul. We evaluated intra- and postoperative complications such as bladder injury, groin pain, urinary retention, and mesh exposure. We also checked the success rate at 6 months after surgery.ResultsThere were no complications, including fever, hematuria, hematoma of the vulva, or bladder injury, immediately after surgery in either group. Postoperative complications 2 weeks post-surgery were groin pain (11.3%), urinary retention (4.9%), and mesh exposure (0.7%). Groin pain was not significantly different between the two groups at 2 weeks, 3 months, and 6 months after surgery (TVT-O vs. TVT-A after 2 weeks: 12.5% vs. 10.3%, P=0.791; 3 months: 0.0% vs. 1.4%, P=0.999; and 6 months: 0.0% vs. 0.0%, P=0.999). Over 90% of the patients reported cure or improved symptoms in both groups. In the univariate logistic analysis, the type of TVT (TVT-O or TVT-A) was not associated with the success rate (odds ratio, 3.21; 95% confidence interval, 0.59-17.40; P=0.175).ConclusionTVT-A surgery is comparable with TVT-O in terms of high success rate and low frequency of complications, including bladder injury and groin pain.

This study aimed to analyze the use of Korean medicine treatments for alopecia in among clinical studies. We identified and analyzed 22 studies from Korean databases; Oriental Medicine Advanced Searching Integrated System (OASIS), Science ON, Korean Studies Information Service System (KISS), and Research Information Sharing Service (RISS) and international database; PubMed. We analyzed the Korean medical treatment in each case and determined the tendency to use each intervention. We analyzed 1,464 patients from 22 selected studies. Herbal medicine, acupuncture, external medicine or products, pharmacopuncture, and phototherapy were used for alopecia treatment. The herbal medicines mainly used to treat alopecia were Gagam Cheongyoung-tang, Gagam Hwajung-hwan, and Yukmijihwang-tang·hwan. The acupoints primarily used were GV20, EX-HN1, GB5, KI3, PC6, ST36, GV22, and A-shi. The most commonly used pharmacopuncture therapies were Hwangryunhaedoktang (HH), Carthami Fructus (CF), Bee Venom (BV), and Hominis placenta (HP). The Korean medical treatment for alopecia improved the condition of patients. However, seven studies reported the occurrence of side effects such as pruritus, dazed, drowsiness, headache, pain, and diarrhea. This study shows the potential of Korean medicine for the treatment of alopecia. Further studies with a large sample size and long-term follow-up are warranted to establish the primary treatment guidelines and objective out-come measures for alopecia.

Knowledge drives business innovation. However, even if companies have the same knowledge element in the business ecosystem, innovation performance varies depending on the structural position of the technical knowledge network. This study investigated whether there is a difference in exploitative innovation according to the structural position of the AI technical knowledge network. We collected patents from the top 100 digital companies registered with the US Patent Office from 2015 to 2019 and classified the companies into knowledge producer-based brokers, knowledge absorber-based brokers, knowledge absorbers, and knowledge producers from the perspective of knowledge creation and flow. The analysis results are as follows. First, a few of the top 100 digital companies disseminate, absorb, and mediate knowledge, while the majority do not. Second, exploitative innovation is the largest, in the order of knowledge producer, knowledge absorber-based broker, knowledge absorber, and knowledge producer-based broker. Finally, patents for industrial intelligence occupy a large proportion, and knowledge producers are leading exploitative innovation. Therefore, latecomers need to expand their resources and capabilities by citing patents owned by leading companies and converge with existing industries into AI-based industries.

Introduction The aim of this study was to assess the efficacy and safety of switching to teneligliptin from other dipeptidyl peptidase-4 (DPP-4) inhibitors in patients with type 2 diabetes mellitus (T2DM) inadequately controlled despite treatment with a stable dose of other DPP-4 inhibitors. Methods Patients with glycosylated hemoglobin (HbA1c) ≥ 7% despite taking DPP-4 inhibitors other than teneligliptin, with or without other antidiabetic agents, for at least 3 months were enrolled in this study. Patients on DPP-4 inhibitors administered prior to participation in this study were switched to 20 mg teneligliptin once daily and the dose was maintained for the 52-week study period. The primary endpoint was the change in HbA1c at week 12. Fasting plasma glucose (FPG) and the blood lipid profile were also evaluated. Adverse events were monitored for safety assessment. Results At weeks 12, 24, and 52, the HbA1c values significantly decreased by − 0.39, − 0.44, and − 0.52%, respectively, compared to the baseline value (p

BackgroundCommon neural underpinning of Parkinson’s Disease (PD) psychosis across different structural magnetic resonance imaging (MRI) studies remains unclear to this day with few studies and even fewer meta-analyses available.ObjectivesOur meta-analysis aimed to identify and summarise studies using MRI approach to identify PD psychosis-specific brain regions and examine the relation between cortical volume loss and dopaminergic and serotonergic receptor density.MethodsPubMed, Web of Science and Embase were searched for MRI studies of PD psychosis (PDP) compared to PD patients without psychosis (PDnP). Seed-baseddMapping with Permutation of Subject Images was applied in the meta-analysis where coordinates were available. Multiple linear regressions to examine the relationship between grey matter volume loss in PDP and receptor gene expression density (extracted from the Allen Human Brain Atlas) were conducted in R.ResultsWe observed lower grey matter volume in parietal-temporo-occipital regions from our meta-analysis (N studies =10, PDP n=211, PDnP, n=298). These results remained significant after adjusting for PD medications and for cognitive scores. Grey matter volume loss in PDP was associated with local expression of 5-HT1a (b=0.109,p=0.012) and 5-HT2a receptors (b=-0.106,p=0.002) also after adjusting for PD medications (5-HT1a,p= 0.005; 5-HT2a,p= 0.001).ConclusionsWidespread cortical volume loss in the parieto-temporo-occipital regions involved in information processing and integration, as well as attention, could result in PD psychosis symptoms. Neurobiological mechanisms implicating serotonergic receptors may also contribute to this condition.

The neurobiological substrates underlying the relationship of circadian rest-activity rhythm (RAR) alteration with accelerated late-life cognitive decline are not clearly understood. In the present study, the longitudinal relationship of objectively measured circadian RAR with in vivo Alzheimer's disease (AD) pathologies and cerebrovascular injury was investigated in non-demented older adults.The present study included 129 participants without dementia who participated in the Korean Brain Aging Study for Early DiagnosisPrediction of Alzheimer's Disease cohort. All participants underwent actigraphy at baseline and two consecutive [Delayed acrophase at baseline was significantly associated with greater annualized decline of AD-CM over a 2-year period, but not with that of other neuroimaging measures. In contrast, other circadian RAR parameters at baseline had no association with annualized change of any neuroimaging measures. Annualized decline of AD-CM was also significantly positively associated with the annual change in MMSE scores. Furthermore, a mediation analysis showed that greater reduction in AD-CM mediated the effect of delayed acrophase at baseline on faster decline of MMSE score.The findings indicates that delayed acrophase in late-life may cause or predict hypometabolism at AD-signature brain regions, which underlies cognitive decline in the near future. This article is protected by copyright. All rights reserved.

Social anxiety disorder (SAD) is a mental disorder characterized by excessive anxiety in social situations. This study aimed to examine the alteration of resting-state functional connectivity in SAD patients related to the virtual reality-based self-training (VRS) which enables exposure to social situations in a controlled environment. Fifty-two SAD patients were randomly assigned to the experimental group who received the VRS, or the control group who did not. Self-report questionnaires and resting-state functional magnetic resonance imaging (fMRI) were performed to assess clinical symptoms and analyze the resting-state network properties, respectively. Significant decrease in social anxiety and an increase in self-esteem was found in the experimental group. From the resting-state fMRI analysis, alteration of local network properties in the left dorsolateral prefrontal gyrus (-10.0%, p = 0.025), left inferior frontal gyrus (-32.3%, p = 0.044), left insula (-17.2%, p = 0.046), left Heschl's gyrus (-21.2%, p = 0.011), bilateral inferior temporal gyrus (right: +122.6%, p = 0.045; left:−46.7%, p = 0.015), and right calcarine sulcus (+17.0%, p = 0.010) were found in the experimental group. Average shortest path length (+8.3%, p = 0.008) and network efficiency (-7.6%, p = 0.011) are found to be altered from the global network property analysis. In addition, the experimental group displayed more positive and more negative changes in the correlation trend of average shortest path length (p = 0.004) and global network efficiency (p = 0.014) with the severity of social anxiety, respectively. These results suggest potential effectiveness of the VRS, which is possibly related to the change of aberrant processing and control of visual and auditory linguistic stimuli and the adaptive change in rumination pattern.

Objective: We investigated the association between dual decline (DD) (loss of memory and gait speed) and the instrumental activities of daily living (IADL) degeneration in older adults. Methods: Data were drawn from the National Social Life, Health, and Aging Project (NSHAP) reflecting changes over 5 years. This study used the NSHAP data set wave 2 (2010–2011, N = 3196) and wave 3 (2015–2016, N = 4377). Results: Data from 1640 participants were retrieved. There were 601 people with DD and 1039 people without-DD. The DD group had a 28.4% (95% CI = 1.013–1.626) greater risk of degrading in IADL than the without-DD group (odds ratio = 1.284, p < .05). Conclusion: Current research can be used when establishing intervention programs or policies that can prevent IADL degradation through simple memory training and walking activities for older adults living in the community.

This study focuses on how teachers’ pedagogical content knowledge (PCK) of mathematics may differ depending on teacher interactions in an online teacher community of practice (CoP). The study utilizes data from 26,857 posts collected from the South Korean self-generated online teacher CoP, ‘Indischool’. This data was then analyzed using natural language processing techniques; specifically, text classification with word2vec, BERT, and machine learning classifiers was used. The results indicate that the texts of posts can predict the level of teacher interactions in the online CoP. BERT embedding and classifier exhibited the best performance, ultimately achieving an F1 score of .756. Moreover, topic modeling utilizing BERT embedding is used to uncover the specific PCK of teachers through high- and low-interaction posts. The results reveal that high-interaction posts with numerous likes and replies demonstrate more in-depth reflections on teaching mathematics and refined PCK. This study makes two significant contributions. First, it applies a data science framework that allows for the analysis of real data from an actual online teacher community. Secondly, it sheds light on the intricacies of knowledge management in an online teacher CoP, an area that has to this point received limited empirical attention.

세계적인 전자상거래 기업들은 지속 가능한 경쟁력을 확보하기 위해 사용자 맞춤형 추천 서비스를 제공하고 있다. 기존 관련 연구에서는 주로 평점, 구매 여부 등 정량적 선호도 정보를 사용하여 개인화 추천 서비스를 제공하였다. 하지만 이와 같은 정량적 선호도 정보를 사용하여 개인화 추천 서비스를 제공하면 추천 성능이 저하될 수 있다는 문제점이 제기되고 있다. 호텔을 이용한 사용자가 호텔 서비스, 청결 상태 등에 대하여 만족하지 못한다고 리뷰를 작성하였으나 선호도 평점 5점을 부여했을 때 정량적 선호도(평점)와 정성적 선호도(리뷰)가 불일치한 문제가 발생할 수 있다. 따라서 본 연구에서는 정량적 선호도 정보와 정성적 선호도 정보가 일치하는지를 확인하고 이를 바탕으로 선호도 정보가 일치하는 사용자를 바탕으로 새로운 프로파일을 구축하여 개인화 추천 서비스를 제공하고자 한다. 리뷰에서 정성적 선호도를 추출하기 위해 자연어 처리 관련 연구에서 널리 사용되고 있는 CNN, LSTM, CNN + LSTM 등 딥러닝 기법을 사용하여 감성분석 모델을 구축하였다. 이를 통해 사용자가 작성한 리뷰에서 정성적 선호도 정보를 정교하게 추출하여 정량적 선호도 정보와 비교하였다. 본 연구에서 제안한 추천 방법론의 성능을 평가하기 위해 세계 최대 여행 플랫폼 TripAdvisor에서 실제 호텔을 이용한 사용자 선호도 정보를 수집하여 사용하였다. 실험 결과 본 연구에서 제안한 추천 방법론이 기존의 정량적 선호도만을 고려하는 추천 방법론보다 우수한 추천 성능을 나타냄을 확인할 수 있었다.

Fourteen azaphilone-type polyketides (1-14), including nine new ones (1-6 and 8-10), were isolated from cultures of Vitex rotundifolia-associated Penicillium sp. JVF17, and their structures were determined by spectroscopic analysis together with computational methods and chemical reactions. Neuroprotective effects of the isolated compounds were evaluated against glutamate-induced neurotoxicity. Treatment with compounds 3, 6, 7, and 11-14 increased cell viabilities of hippocampal neuronal cells damaged by glutamate, with compound 12 being the most potent. Compound 12 markedly decreased intracellular Ca2+ and nuclear condensation levels. Mechanistically, molecular markers of apoptosis induced by treatment with glutamate, i.e., phosphorylation of MAPKs and elevated Bax/Bcl-2 expression ratio, were significantly lowered by compound 12. The azaphilones with an isoquinoline core structure were more active than those with pyranoquinones, but N-substitution decreased the activity. This study, including the structure-activity relationship, indicates that the azaphilone scaffold is a promising lead toward the development of novel neuroprotective agents.

Objectives: On February 26, 2021, coronavirus disease 2019 (COVID-19) vaccination was started for high-priority groups based on the recommendation of the Advisory Committee on Immunization Practices with 2 available COVID-19 vaccines (AstraZeneca and Pfizer-BioNTech) in Korea. This report provides a summary of adverse events following COVID-19 vaccination as of April 30, 2021.Methods: Adverse events following immunization are notifiable by medical doctors to the Korea Immunization Management System (KIMS) under the national surveillance system. We analyzed all adverse events reports following COVID-19 vaccination to the KIMS from February 26 to April 30, 2021. Results: In total, 16,196 adverse events following 3,586,814 administered doses of COVID-19 vaccines were reported in approximately 2 months (February 26 to April 30, 2021). Of these, 15,658 (96.7%) were non-serious adverse events, and 538 (3.3%) were serious adverse events, including 73 (0.5%) deaths. The majority of adverse events (n=13,063, 80.7%) were observed in women, and the most frequently reported adverse events were myalgia (52.2%), fever (44.9%), and headache (34.9%). Of the 73 deaths following the COVID-19 vaccination, none were related to the vaccines.Conclusion: By April 30, 3.6 million doses of the COVID 19 vaccine had been given in Korea, and the overwhelming majority of reports were for non-serious events. The Korea Disease Control and Prevention Agency continues to monitor the safety of COVID-19 vaccination.

Artificial neural network models were developed to classify road pavement types into the transverse-tined, the longitudinal-tined, NGCS(Next Generation Concrete Surface), Diamond Grinding, and Stone Mastic Asphalt by utilizing tire-pavement noise and road surface images. Tire-pavement noise data were collected by OBSI(On-Board Sound Intensity) method, and analyzed to obtain sound intensity level, sound pressure level, and sound quality indices. Road surface image data was analyzed through image feature extraction algorithms of Hough transformation and HOG(Histogram of gradient). The important features among the acoustic and image characteristics were selected by a random forest model. The acoustic features selected by the random forest algorithm are the overall sound intensity level of 400~5kHz 1/3-octave bands, the sound intensities (W/m2) of 800~2kHz 1/3-octave bands, loudness, fluctuation strength and tonality. The image features selected are the number of longitudinal lines extracted from Hough transform algorithm and HOG of the central cell. The two groups of the selected features were applied separately or together to an artificial neural network model to find classification performance. The classification accuracy rates of the models using acoustic features only, image features only and both acoustic and image features combined were 90.8%, 88.8%, and 97.3%, respectively.

Objective The distinction between idiopathic normal pressure hydrocephalus (iNPH) and hydrocephalus ex vacuo caused by encephalic volume loss remains to be established. This study aims to investigate radiological parameters as clinically useful tools to discriminate iNPH from hydrocephalus ex vacuo caused by Alzheimer’s disease (AD).Methods A total of 54 patients with ventriculomegaly (iNPH, 25; hydrocephalus ex vacuo, 29) were recruited in this study. Consequently, nine radiological parameters were compared between iNPH and hydrocephalus ex vacuo using magnetic resonance imaging (MRI).Results A small callosal angle (CA), the Sylvian fissure dilatation, and absence of narrowing of superior parietal sulci discriminated the iNPH group from the hydrocephalus ex vacuo group (p

Background Personalized warfarin dosing is influenced by various factors including genetic and non-genetic factors. Multiple linear regression (LR) is known as a conventional method to develop predictive models. Recently, machine learning approaches have been extensively implemented for warfarin dosing due to the hypothesis of non-linear association between covariates and stable warfarin dose. Objective To extend the multiple linear regression algorithm for personalized warfarin dosing in a Korean population and compare with a machine learning--based algorithm. Method From this cohort study, we collected information on 650 patients taking warfarin who achieved steady state including demographic information, indications, comorbidities, comedications, habits, and genetic factors. The dataset was randomly split into training set (90%) and test set (10%). The LR and machine learning (gradient boosting machine [GBM]) models were developed on the training set and were evaluated on the test set. Result LR and GBM models were comparable in terms of accuracy of ideal dose (75.38% and 73.85%), correlation (0.77 and 0.73), mean absolute error (0.58 mg/day and 0.64 mg/day), and root mean square error (0.82 mg/day and 0.9 mg/day), respectively. VKORC1 genotype, CYP2C9 genotype, age, and weight were the highest contributors and could obtain 80% of maximum performance in both models. Conclusion This study shows that our LR and GMB models are satisfactory to predict warfarin dose in our dataset. Both models showed similar performance and feature contribution characteristics. LR may be the appropriate model due to its simplicity and interpretability.