• Gut and Liver
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• v.12 no.6
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• pp.641-647
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• 2018

Background/Aims: Helicobacter pylori eradication rates are decreasing because of increases in clarithromycin resistance. Thus, finding an easy and accurate method of detecting clarithromycin resistance is important. Methods: We evaluated 70 H. pylori isolates from Korean patients. Dual-labeled peptide nucleic acid (PNA) probes were designed to detect resistance associated with point mutations in 23S ribosomal ribonucleic acid gene domain V (A2142G, A2143G, and T2182C). Data were analyzed by probe-based fluorescence melting curve analysis based on probe-target dissociation temperatures and compared with Sanger sequencing. Results: Among 70 H. pylori isolates, 0, 16, and 58 isolates contained A2142G, A2143G, and T2182C mutations, respectively. PNA probe-based analysis exhibited 100.0% positive predictive values for A2142G and A2143G and a 98.3% positive predictive value for T2182C. PNA probe-based analysis results correlated with 98.6% of Sanger sequencing results (${\kappa}$-value=0.990; standard error, 0.010). Conclusions: H. pylori clarithromycin resistance can be easily and accurately assessed by dual-labeled PNA probe-based melting curve analysis if probes are used based on the appropriate resistance-related mutations. This method is fast, simple, accurate, and adaptable for clinical samples. It may help clinicians choose a precise eradication regimen.

• The Korean Journal of Pain
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• v.32 no.2
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• pp.87-96
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• 2019

Background: This study was performed in order to examine the effect of intrathecal sec-O-glucosylhamaudol (SOG), an extract from the root of the Peucedanum japonicum Thunb., on incisional pain in a rat model. Methods: The intrathecal catheter was inserted in male Sprague-Dawley rats (n = 55). The postoperative pain model was made and paw withdrawal thresholds (PWTs) were evaluated. Rats were randomly treated with a vehicle (70% dimethyl sulfoxide) and SOG ($10{\mu}g$, $30{\mu}g$, $100{\mu}g$, and $300{\mu}g$) intrathecally, and PWT was observed for four hours. Dose-responsiveness and ED50 values were calculated. Naloxone was administered 10 min prior to treatment of SOG $300{\mu}g$ in order to assess the involvement of SOG with an opioid receptor. The protein levels of the ${\delta}$-opioid receptor, ${\kappa}$-opioid receptor, and ${\mu}$-opioid receptor (MOR) were analyzed by Western blotting of the spinal cord. Results: Intrathecal SOG significantly increased PWT in a dose-dependent manner. Maximum effects were achieved at a dose of $300{\mu}g$ at 60 min after SOG administration, and the maximal possible effect was 85.35% at that time. The medial effective dose of intrathecal SOG was $191.3{\mu}g$ (95% confidence interval, 102.3-357.8). The antinociceptive effects of SOG ($300{\mu}g$) were significantly reverted until 60 min by naloxone. The protein levels of MOR were decreased by administration of SOG. Conclusions: Intrathecal SOG showed a significant antinociceptive effect on the postoperative pain model and reverted by naloxone. The expression of MOR were changed by SOG. The effects of SOG seem to involve the MOR.

• Imaging Science in Dentistry
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• v.49 no.3
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• pp.191-199
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• 2019

Purpose: To compare the diagnostic ability of undergraduate dental students to detect maxillary sinus abnormalities in panoramic radiographs(PR) and cone-beam computed tomography (CBCT). Materials and Methods: This was a retrospective study based on the evaluation of PR and CBCT images. A pilot study was conducted to determine the number of students eligible to participate in the study. The images were evaluated by 2 students, and 280 maxillary sinuses were assessed using the following categories: normal, mucosal thickening, sinus polyp, antral pseudocyst, nonspecific opacification, periostitis, antrolith, and antrolith associated with mucosal thickening. The reference standard was established by the consensus of 2 oral radiologists based on the CBCT images. The kappa test, receiver operating characteristic curves, and 1-way analysis of variance with the Tukey-Kramer post-hoc test were employed. Results: Intraobserver and interobserver reliability showed agreement ranging from substantial (0.809) to almost perfect (0.922). The agreement between the students' evaluations and the reference standard was reasonable (0.258) for PR and substantial(0.692) for CBCT. Comparisons of values of sensitivity, specificity, and accuracy showed that CBCT was significantly better(P<0.05). Conclusion: CBCT was better than PR for the detection of maxillary sinus abnormalities by dental students. However, CBCT should only be requested after a careful analysis of PR by students and more experienced professionals.

• Geomechanics and Engineering
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• v.30 no.3
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• pp.259-272
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• 2022

Rockburst is a dynamic, multivariate, and non-linear phenomenon that occurs in underground mining and civil engineering structures. Predicting rockburst is challenging since conventional models are not standardized. Hence, machine learning techniques would improve the prediction accuracies. This study describes decision based uncertainty models to predict rockburst in underground engineering structures using gradient boosting algorithms (GBM). The model input variables were uniaxial compressive strength (UCS), uniaxial tensile strength (UTS), maximum tangential stress (MTS), excavation depth (D), stress ratio (SR), and brittleness coefficient (BC). Several models were trained using different combinations of the input variables and a 3-fold cross-validation resampling procedure. The hyperparameters comprising learning rate, number of boosting iterations, tree depth, and number of minimum observations were tuned to attain the optimum models. The performance of the models was tested using classification accuracy, Cohen's kappa coefficient (k), sensitivity and specificity. The best-performing model showed a classification accuracy, k, sensitivity and specificity values of 98%, 93%, 1.00 and 0.957 respectively by optimizing model ROC metrics. The most and least influential input variables were MTS and BC, respectively. The partial dependence plots revealed the relationship between the changes in the input variables and model predictions. The findings reveal that GBM can be used to anticipate rockburst and guide decisions about support requirements before mining development.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.48 no.3
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• pp.167-173
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• 2022

Objectives: The purpose of this study was to estimate the minimal clinically important difference (MCID) of mouth opening (MO) and patient satisfaction in surgically treated oral submucous fibrosis (OSMF) patients. Materials and Methods: The status of MO was collected preoperatively (T0), postoperatively at 3 months (T1), and at a minimum of 6 months postoperatively (T2). MCID was determined through the anchor-based approach with the change difference method, mean change method, and receiver operator characteristic curve (ROC) method. Results: In this study, 35 patients enrolled and completed postoperative follow-up (T2) averaging a duration of 18.1 months. At T1, using the change difference method, MO was 14.89 mm and the ROC curve exhibited a 11.5 gain in MO (sensitivity 81.8% and specificity 100%, area under the curve [AUC] of 0.902) and was classified as MCID as reported by patients. At T2, MCID of MO was 9.75 mm using the change difference method and 11.75 mm by the mean change method. The ROC curve revealed that the MCID of MO at T2 was 10.5 mm with 73.9% sensitivity and 83.3% specificity (AUC of 0.873). The kappa value was 0.91, confirming reliability of the data. Conclusion: This study demonstrated MCID values that indicate the clinical relevance of surgical treatment of OSMF if the minimum possible gain in MO is approximately 10 mm.

• Korean Journal of Remote Sensing
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• v.39 no.4
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• pp.425-440
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• 2023

Monitoring water surface has become one of the most prominent areas of research in addressing environmental challenges.Accurate and automated detection of watersurface in remote sensing imagesis crucial for disaster prevention, urban planning, and water resource management, particularly for a country where water plays a vital role in human life. However, achieving precise detection poses challenges. Previous studies have explored different approaches,such as analyzing water indexes, like normalized difference water index (NDWI) derived from satellite imagery's visible or infrared bands and using k-means clustering analysis to identify land cover patterns and segment regions based on similar attributes. Nonetheless, challenges persist, notably distinguishing between waterspectralsignatures and cloud shadow or terrain shadow. In thisstudy, our objective is to enhance the precision of water surface detection by constructing a comprehensive water database (DB) using existing digital and land cover maps. This database serves as an initial assumption for automated water index analysis. We utilized 1:5,000 and 1:25,000 digital maps of Korea to extract water surface, specifically rivers, lakes, and reservoirs. Additionally, the 1:50,000 and 1:5,000 land cover maps of Korea aided in the extraction process. Our research demonstrates the effectiveness of utilizing a water DB product as our first approach for efficient water surface extraction from satellite images, complemented by our second and third approachesinvolving NDWI analysis and k-means analysis. The image segmentation and binary mask methods were employed for image analysis during the water extraction process. To evaluate the accuracy of our approach, we conducted two assessments using reference and ground truth data that we made during this research. Visual interpretation involved comparing our results with the global surface water (GSW) mask 60 m resolution, revealing significant improvements in quality and resolution. Additionally, accuracy assessment measures, including an overall accuracy of 90% and kappa values exceeding 0.8, further support the efficacy of our methodology. In conclusion, thisstudy'sresults demonstrate enhanced extraction quality and resolution. Through comprehensive assessment, our approach proves effective in achieving high accuracy in delineating watersurfaces from satellite images.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.57-69
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• 2024

Crop classification plays a vitalrole in monitoring agricultural landscapes and enhancing food production. In this study, we explore the effectiveness of Long Short-Term Memory (LSTM) models for crop classification, focusing on distinguishing between apple and rice crops. The aim wasto overcome the challenges associatedwith finding phenology-based classification thresholds by utilizing LSTM to capture the entire Normalized Difference Vegetation Index (NDVI)trend. Our methodology involvestraining the LSTM model using a reference site and applying it to three separate three test sites. Firstly, we generated 25 NDVI imagesfrom the Sentinel-2A data. Aftersegmenting study areas, we calculated the mean NDVI values for each segment. For the reference area, employed a training approach utilizing the NDVI trend line. This trend line served as the basis for training our crop classification model. Following the training phase, we applied the trained model to three separate test sites. The results demonstrated a high overall accuracy of 0.92 and a kappa coefficient of 0.85 for the reference site. The overall accuracies for the test sites were also favorable, ranging from 0.88 to 0.92, indicating successful classification outcomes. We also found that certain phenological metrics can be less effective in crop classification therefore limitations of relying solely on phenological map thresholds and emphasizes the challenges in detecting phenology in real-time, particularly in the early stages of crops. Our study demonstrates the potential of LSTM models in crop classification tasks, showcasing their ability to capture temporal dependencies and analyze timeseriesremote sensing data.While limitations exist in capturing specific phenological events, the integration of alternative approaches holds promise for enhancing classification accuracy. By leveraging advanced techniques and considering the specific challenges of agricultural landscapes, we can continue to refine crop classification models and support agricultural management practices.

• Imaging Science in Dentistry
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• v.53 no.4
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• pp.375-381
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• 2023

Purpose: This study assessed the diagnostic performance of stitched and non-stitched cross-sectional cone-beam computed tomography (CBCT) images of non-displaced ovine mandibular fractures. Materials and Methods: In this ex vivo study, non-displaced fractures were artificially created in 10 ovine mandibles (20 hemi-mandibles) using a hammer. The control group comprised 8 hemi-mandibles. The non-displaced fracture lines were oblique or vertical, <0.5 mm wide, 10-20 mm long, and only in the buccal or lingual cortex. Fracture lines in the ramus and posterior mandible were created to be at the interface or borders of the 2 stitched images. CBCT images were obtained from the specimens with an 80 mm×80 mm field of view before and after fracture induction. OnDemand software (Cybermed, Seoul, Korea) was used for stitching the CBCT images. Four observers evaluated 56 (28 stitched and 28 non-stitched) images to detect fracture lines. The diagnostic performance of stitched and non-stitched images was assessed by calculating the area under the receiver operating characteristic curve (AUC). Sensitivity and specificity values were also calculated (alpha=0.05). Results: The AUC was calculated to be 0.862 and 0.825 for the stitched and non-stitched images, respectively (P=0.747). The sensitivity and specificity were 90% and 75% for the non-stitched images and 85% and 87% for the stitched images, respectively. The inter-observer reliability was shown by a Fleiss kappa coefficient of 0.79, indicating good agreement. Conclusion: No significant difference was found in the diagnostic performance of stitched and non-stitched cross-sectional CBCT images of non-displaced fractures of the ovine mandible.

• Investigative Magnetic Resonance Imaging
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• v.18 no.4
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• pp.314-322
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• 2014

Purpose: Diastolic dysfunction is a common problem in patients with hypertrophic cardiomyopathy (HCM). The purpose of this study was to assess the role of MRI in the assessment of diastolic function using mitral valve and pulmonary vein flow velocities in HCM patients. Methods and Results: Phase-contrast MRI (mitral valve and pulmonary vein) and transthoracic echocardiography was successfully performed for 59 HCM patients (44 men and 15 women; mean age, 51 years). Forty-nine patients had a diastolic dysfunction; grade 1 (n = 20), grade 2 (n = 27), and grade 3 (n = 2) using echocardiography, and ten patients had normal diastolic function. The transmitral inflow parameters (E, A, and E/A ratios) obtained by MRI showed positive correlation with the same parameters measured by echocardiography (Pearson's r values were 0.47, 0.60, and 0.75 for E, A, E/A, respectively, all P < 0.001). With the flow information of the pulmonary vein from cardiac MRI, pseudo-normalized pattern (n = 8) could be distinguished from true normal filling pattern (n = 17), and the diastolic function grades by cardiac MRI showed moderate agreement with those of echocardiography (kappa value = 0.45, P < 0.001). Conclusions: Assessment of left ventricle diastolic function is feasible using phase-contrast MRI in HCM patients. Analysis of pulmonary vein flow velocity on MRI is useful for differentiating pseudo-normal from normal diastolic function in HCM patients.

• Korean Journal of Food Science and Technology
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• v.41 no.3
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• pp.265-271
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• 2009

The quality attributes of bread made with milk protein (casein, C; whey protein, W) and polysaccharide (sodium alginate, A; ${\kappa}$-carrageenan, K) mixtures were investigated to study the method to suppressing quality deterioration during storage. Bread prepared with the CA mixture had a higher specific loaf volume compared to the control. And bread made with the WA mixture had reduced moisture loss during storage compared to the control. The hardness of control and breads containing protein-polysaccharide mixtures increased during storage, but hardness increased more in the control than the treatments. In terms of crumb color, the breads containing protein-polysaccharide mixtures had higher $L^{\ast}$ values, but lower $a^{\ast}$ and $b^{\ast}$ values than the control. Finally, there were no significant differences in sensory quality among the control and treatment breads. Overall, data indicate that the addition of CA and WA improved the baking quality of bread and retarded staling.