• Information Systems Review
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• v.24 no.1
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• pp.21-37
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• 2022

Drug repositioning, one of the methods of developing new drugs, is a useful way to discover new indications by allowing drugs that have already been approved for use in people to be used for other purposes. Recently, with the development of machine learning technology, the case of analyzing vast amounts of biological information and using it to develop new drugs is increasing. The use of machine learning technology to drug repositioning will help quickly find effective treatments. Currently, the world is having a difficult time due to a new disease caused by coronavirus (COVID-19), a severe acute respiratory syndrome. Drug repositioning that repurposes drugsthat have already been clinically approved could be an alternative to therapeutics to treat COVID-19 patients. This study intends to examine research trends in the field of drug repositioning using machine learning techniques. In Pub Med, a total of 4,821 papers were collected with the keyword 'Drug Repositioning'using the web scraping technique. After data preprocessing, frequency analysis, LDA-based topic modeling, random forest classification analysis, and prediction performance evaluation were performed on 4,419 papers. Associated words were analyzed based on the Word2vec model, and after reducing the PCA dimension, K-Means clustered to generate labels, and then the structured organization of the literature was visualized using the t-SNE algorithm. Hierarchical clustering was applied to the LDA results and visualized as a heat map. This study identified the research topics related to drug repositioning, and presented a method to derive and visualize meaningful topics from a large amount of literature using a machine learning algorithm. It is expected that it will help to be used as basic data for establishing research or development strategies in the field of drug repositioning in the future.

• Korean Journal of Radiology
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• v.22 no.12
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• pp.1985-1995
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• 2021

Objective: Although the liver-to-spleen volume ratio (LSVR) based on CT reflects portal hypertension, its prognostic role in cirrhotic patients has not been proven. We evaluated the utility of LSVR, automatically measured from CT images using a deep learning algorithm, as a predictor of hepatic decompensation and transplantation-free survival in patients with hepatitis B viral (HBV)-compensated cirrhosis. Materials and Methods: A deep learning algorithm was used to measure the LSVR in a cohort of 1027 consecutive patients (mean age, 50.5 years; 675 male and 352 female) with HBV-compensated cirrhosis who underwent liver CT (2007-2010). Associations of LSVR with hepatic decompensation and transplantation-free survival were evaluated using multivariable Cox proportional hazards and competing risk analyses, accounting for either the Child-Pugh score (CPS) or Model for End Stage Liver Disease (MELD) score and other variables. The risk of the liver-related events was estimated using Kaplan-Meier analysis and the Aalen-Johansen estimator. Results: After adjustment for either CPS or MELD and other variables, LSVR was identified as a significant independent predictor of hepatic decompensation (hazard ratio for LSVR increase by 1, 0.71 and 0.68 for CPS and MELD models, respectively; p < 0.001) and transplantation-free survival (hazard ratio for LSVR increase by 1, 0.8 and 0.77, respectively; p < 0.001). Patients with an LSVR of < 2.9 (n = 381) had significantly higher 3-year risks of hepatic decompensation (16.7% vs. 2.5%, p < 0.001) and liver-related death or transplantation (10.0% vs. 1.1%, p < 0.001) than those with an LSVR ≥ 2.9 (n = 646). When patients were stratified according to CPS (Child-Pugh A vs. B-C) and MELD (< 10 vs. ≥ 10), an LSVR of < 2.9 was still associated with a higher risk of liver-related events than an LSVR of ≥ 2.9 for all Child-Pugh (p ≤ 0.045) and MELD (p ≤ 0.009) stratifications. Conclusion: The LSVR measured on CT can predict hepatic decompensation and transplantation-free survival in patients with HBV-compensated cirrhosis.

• Korean Journal of Radiology
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• v.22 no.6
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• pp.994-1004
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• 2021

Objective: To extract pulmonary and cardiovascular metrics from chest CTs of patients with coronavirus disease 2019 (COVID-19) using a fully automated deep learning-based approach and assess their potential to predict patient management. Materials and Methods: All initial chest CTs of patients who tested positive for severe acute respiratory syndrome coronavirus 2 at our emergency department between March 25 and April 25, 2020, were identified (n = 120). Three patient management groups were defined: group 1 (outpatient), group 2 (general ward), and group 3 (intensive care unit [ICU]). Multiple pulmonary and cardiovascular metrics were extracted from the chest CT images using deep learning. Additionally, six laboratory findings indicating inflammation and cellular damage were considered. Differences in CT metrics, laboratory findings, and demographics between the patient management groups were assessed. The potential of these parameters to predict patients' needs for intensive care (yes/no) was analyzed using logistic regression and receiver operating characteristic curves. Internal and external validity were assessed using 109 independent chest CT scans. Results: While demographic parameters alone (sex and age) were not sufficient to predict ICU management status, both CT metrics alone (including both pulmonary and cardiovascular metrics; area under the curve [AUC] = 0.88; 95% confidence interval [CI] = 0.79-0.97) and laboratory findings alone (C-reactive protein, lactate dehydrogenase, white blood cell count, and albumin; AUC = 0.86; 95% CI = 0.77-0.94) were good classifiers. Excellent performance was achieved by a combination of demographic parameters, CT metrics, and laboratory findings (AUC = 0.91; 95% CI = 0.85-0.98). Application of a model that combined both pulmonary CT metrics and demographic parameters on a dataset from another hospital indicated its external validity (AUC = 0.77; 95% CI = 0.66-0.88). Conclusion: Chest CT of patients with COVID-19 contains valuable information that can be accessed using automated image analysis. These metrics are useful for the prediction of patient management.

• Korean Journal of Radiology
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• v.22 no.2
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• pp.189-197
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• 2021

Objective: Muscle depletion in patients undergoing liver transplantation affects the recipients' prognosis and therefore cannot be overlooked. We aimed to evaluate whether changes in muscle and fat mass during the preoperative period are associated with prognosis after deceased donor liver transplantation (DDLT). Materials and Methods: This study included 72 patients who underwent DDLT and serial computed tomography (CT) scans. Skeletal muscle index (SMI) and fat mass index (FMI) were calculated using the muscle and fat area in CT performed 1 year prior to surgery (1 yr Pre-LT), just before surgery (Pre-LT), and after transplantation (Post-LT). Simple aspects of serial changes in muscle and fat mass were analyzed during three measurement time points. The rate of preoperative changes in body composition parameters were calculated (preoperative ΔSMI [%] = [SMI at Pre-LT - SMI at 1 yr Pre-LT] / SMI at Pre-LT x 100; preoperative ΔFMI [%] = [FMI at Pre-LT - FMI at 1 yr Pre-LT] / FMI at Pre-LT x 100) and assessed for correlation with patient survival. Results: SMI significantly decreased during the preoperative period (mean preoperative ΔSMI, -13.04%, p < 0.001). In the multivariable analysis, preoperative ΔSMI (p = 0.016) and model for end-stage liver disease score (p = 0.011) were independent prognostic factors for overall survival. The mean survival time for patients with a threshold decrease in the preoperative ΔSMI (≤ -30%) was significantly shorter than for other patients (p = 0.007). Preoperative ΔFMI was not a prognostic factor but FMI increased during the postoperative period (p = 0.009) in all patients. Conclusion: A large reduction in preoperative SMI was significantly associated with reduced survival after DDLT. Therefore, changes in muscle mass during the preoperative period can be considered as a prognostic factor for survival after DDLT.

• Korean Journal of Radiology
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• v.22 no.2
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• pp.233-242
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• 2021

Objective: To evaluate the association of MRI features with the major genomic profiles and prognosis of World Health Organization grade III (G3) gliomas compared with those of glioblastomas (GBMs). Materials and Methods: We enrolled 76 G3 glioma and 155 GBM patients with pathologically confirmed disease who had pretreatment brain MRI and major genetic information of tumors. Qualitative and quantitative imaging features, including volumetrics and histogram parameters, such as normalized cerebral blood volume (nCBV), cerebral blood flow (nCBF), and apparent diffusion coefficient (nADC) were evaluated. The G3 gliomas were divided into three groups for the analysis: with this isocitrate dehydrogenase (IDH)-mutation, IDH mutation and a chromosome arm 1p/19q-codeleted (IDHmut1p/19qdel), IDH mutation, 1p/19q-nondeleted (IDHmut1p/19qnondel), and IDH wildtype (IDHwt). A prediction model for the genetic profiles of G3 gliomas was developed and validated on a separate cohort. Both the quantitative and qualitative imaging parameters and progression-free survival (PFS) of G3 gliomas were compared and survival analysis was performed. Moreover, the imaging parameters and PFS between IDHwt G3 gliomas and GBMs were compared. Results: IDHmut G3 gliomas showed a larger volume (p = 0.017), lower nCBF (p = 0.048), and higher nADC (p = 0.007) than IDHwt. Between the IDHmut tumors, IDHmut1p/19qdel G3 gliomas had higher nCBV (p = 0.024) and lower nADC (p = 0.002) than IDHmut1p/19qnondel G3 gliomas. Moreover, IDHmut1p/19qdel tumors had the best prognosis and IDHwt tumors had the worst prognosis among G3 gliomas (p < 0.001). PFS was significantly associated with the 95th percentile values of nCBV and nCBF in G3 gliomas. There was no significant difference in neither PFS nor imaging features between IDHwt G3 gliomas and IDHwt GBMs. Conclusion: We found significant differences in MRI features, including volumetrics, CBV, and ADC, in G3 gliomas, according to IDH mutation and 1p/19q codeletion status, which can be utilized for the prediction of genomic profiles and the prognosis of G3 glioma patients. The MRI signatures and prognosis of IDHwt G3 gliomas tend to follow those of IDHwt GBMs.

• Korean Journal of Radiology
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• v.21 no.5
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• pp.588-597
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• 2020

Objective: To investigate the value of combined chemical exchange saturation transfer (CEST) and conventional magnetization transfer imaging (MT) in detecting metabolic and structural changes of renal fibrosis in rats with unilateral ureteral obstruction (UUO) at 3T MRI. Materials and Methods: Thirty-five Sprague-Dawley rats underwent UUO surgery (n = 25) or sham surgery (n = 10). The obstructed and contralateral kidneys were evaluated on days 1, 3, 5, and 7 after surgery. After CEST and MT examinations, ¹⁸F-labeled fluoro-2-deoxyglucose positron emission tomography was performed to quantify glucose metabolism. Fibrosis was measured by histology and western blots. Correlations were compared between asymmetrical magnetization transfer ratio at 1.2 ppm (MTR_asym(1.2ppm)) derived from CEST and maximum standard uptake value (SUV_max) and between magnetization transfer ratio (MTR) derived from MT and alpha-smooth muscle actin (α-SMA). Results: On days 3 and 7, MTR_asym(1.2ppm) and MTR of UUO renal cortex and medulla were significantly different from those of contralateral kidneys (p < 0.05). On day 7, MTR_asym(1.2ppm) and MTR of UUO renal cortex and medulla were significantly different from those of sham-operated kidneys (p < 0.05). The MTR_asym(1.2ppm) of UUO renal medulla was fairly negatively correlated with SUV_max (r = -0.350, p = 0.021), whereas MTR of UUO renal medulla was strongly negatively correlated with α-SMA (r = -0.744, p < 0.001). Conclusion: CEST and MT could provide metabolic and structural information for comprehensive assessment of renal fibrosis in UUO rats in 3T MRI and may aid in clinical monitoring of renal fibrosis in patients with chronic kidney disease.

• Journal of The Korean Society of Integrative Medicine
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• v.12 no.1
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• pp.27-39
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• 2024

Purpose : Smoking is a major factor in chronic obstructive pulmonary disease (COPD), but the effect of electrical cigarette smoking on COPD development is still uncertain. This study aimed to compare the functions of airways and lungs exposed to combustible cigarettes and electrical cigarettes based on the pulmonary function test (PFT) results from the Korean National Health and Nutrition Examination Survey (NHANES). Methods : This study used data from 8,942 participants with PFT results out of 47,309 total subjects from the 6th to 8th Korean NHANES (2014-2015, 2016-2018, and 2019, respectively). Individuals with diseases such as cancer, ex-smokers, and dual tobacco users were excluded. The PFT results were analyzed according to the COPD diagnostic criteria. After adjusting for confounding variables, a complex sample generalized linear model ANOVA test was performed to investigate the association between PFT results and combustible smoker or electrical cigarette user groups. Results : In an analysis based on the obstructive ventilatory disorders (forced expiratory volume in 1 second[FEV₁]/forced vital capacity[FVC]<.7), combustible cigarette smokers showed a 3.46 times higher risk of COPD compared to non-smokers, while electrical cigarette smokers exhibited no significant difference in terms of COPD-related risks compared to non-smokers. FEV₁ showed a negative relation with combustible cigarette smokers as reported elsewhere (B=-.07, p<.001). FEV₁/FVC was negatively related to both combustible cigarette smokers (B=-.03, p<.001) and electrical cigarette smokers (B=-.02, p<.001). Conclusion : FEV₁/FVC decreases were observed in the long-term exposure to both combustible and electrical cigarettes. The lower FEV₁ in the combustible cigarette group implies the worsening of the severity of COPD, suggesting more damage to the airways and lungs in the short term. Therefore, the temporary electrical cigarettes use for the transition period in order to smoking cessation potentially aids to reduce the harmful effect of combustible cigarettes in COPD development.

• Journal of Industrial Convergence
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• v.22 no.6
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• pp.51-59
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• 2024

The purpose of the paper is to suggest government policies that are practically helpful to small business owners in pandemic situations such as COVID-19. To this end, keyword frequency analysis and word cloud analysis of text mining analysis were performed by crawling news articles centered on the keywords "COVID-19 Support for Small Businesses", "The Impact of Small Businesses by Response System to COVID-19 Infectious Diseases", and "COVID-19 Small Business Economic Policy", and major issues were identified through LDA topic modeling analysis. As a result of conducting LDA topic modeling, the support policy for small business owners formed a topic label with government cash and financial support, and the impact of small business owners according to the COVID-19 infectious disease response system formed a topic label with a government-led quarantine system and an individual-led quarantine system, and the COVID-19 economic policy formed a topic label with a policy for small business owners to acquire economic crisis and self-sustainability. Focusing on the organized topic label, it was intended to provide basic data for small business owners to understand the damage reduction policy for small business owners and the policy for enhancing market competitiveness in the future pandemic situation.

• Journal of Korean society of Dental Hygiene
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• v.24 no.3
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• pp.219-227
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• 2024

Objectives: The pulp is the center of the tooth containing nerves and blood vessels. The condition in which the pulp becomes inflamed due to caries or periodontitis is called pulpitis. Pulpitis is a difficult-to-treat disease and causes peripheral nerve tissue changes and severe pain; however, the relationship between neuronal activity and voltage-gated sodium channel 1.7 (Nav1.7) expression in the trigeminal ganglion (TG) during pulpitis has not been well studied. In this study, we found that experimentally induced pulpitis activates Nav1.7 expression in the periphery, leading to neuronal overexpression in the TG. Thus, we sought to identify ways to regulate this process. Methods: Acute pulpitis was induced in rat maxillary molars by treating the pulp with allyl isothiocyanate (AITC). Three days later, in vivo optical imaging was used to record and compare neural activities in the TG. Western blotting was used to identify molecular changes in terms of the expression of extracellular signal-regulated kinase (ERK), c-Fos, transient receptor potential ankyrin 1 (TRPA1), and collapsin response mediator protein-2 (CRMP2) in the brain stem. Results: The results confirmed the neurological changes in the TGs of the pulpitis model, and histological and molecular biological evidence confirmed that increased Nav1.7 expression induced by pulpitis leads to pain. Furthermore, selective inhibition of Nav1.7 resulted in changes in neural activity, suggesting that pulpitis induces increased Nav1.7 expression, and that effective control of Nav1.7 could potentially reduce pain. Conclusions: The inhibition of overexpressed Nav1.7 channels may modulate nociceptive signal processing in the brain and effectively control pain associated with pulpitis.

• IMMUNE NETWORK
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• v.21 no.5
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• pp.34.1-34.16
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• 2021

Sjögren's syndrome (SS) is an autoimmune disease characterized by dryness of the mouth and eyes. The glandular dysfunction in SS involves not only T cell-mediated destruction of the glands but also autoantibodies against the type 3 muscarinic acetylcholine receptor or aquaporin 5 (AQP5) that interfere with the secretion process. Studies on the breakage of tolerance and induction of autoantibodies to these autoantigens could benefit SS patients. To break tolerance, we utilized a PmE-L peptide derived from the AQP5-homologous aquaporin of Prevotella melaninogenica (PmAqp) that contained both a B cell "E" epitope and a T cell epitope. Repeated subcutaneous immunization of C57BL/6 mice with the PmE-L peptide efficiently induced the production of Abs against the "E" epitope of mouse/human AQP5 (AQP5E), and we aimed to characterize the antigen specificity, the sequences of AQP5E-specific B cell receptors, and salivary gland phenotypes of these mice. Sera containing anti-AQP5E IgG not only stained mouse Aqp5 expressed in the submandibular glands but also detected PmApq and PmE-L by immunoblotting, suggesting molecular mimicry. Characterization of the AQP5E-specific autoantibodies selected from the screening of phage display Ab libraries and mapping of the B cell receptor repertoires revealed that the AQP5E-specific B cells acquired the ability to bind to the Ag through cumulative somatic hypermutation. Importantly, animals with anti-AQP5E Abs had decreased salivary flow rates without immune cell infiltration into the salivary glands. This model will be useful for investigating the role of anti-AQP5 autoantibodies in glandular dysfunction in SS and testing new therapeutics targeting autoantibody production.