• Korean Journal of Clinical Pharmacy
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• v.18 no.1
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• pp.6-10
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• 2008

This study investigated the effect of long-term administration of pioglitazone on the pharmacokinetics of verapamil in rats. Pharmacokinetic parameters of verapamil were determined after oral administration of verapamil (9 mg/kg) in rats coadministered pioglitazone (0.5 mg/kg) or pretreated with pioglitazone (0.5 mg/kg) for 3 and 9 days. Compared to oral control group, the presence of pioglitazone significantly (p<0.05) increased the area under the plasma concentration-time curve (AUC) of verapamil by 48.6% (coad), 61.1% (3 days) and 56.5% (9 days), and the peak concentration($C_{max}$) by 65.1% (coad), 76.8% (3 days) and 66.4% (9 days). The absolute bioavailability (AB%) of verapamil was significantly (p<0.05) higher by 6.2% (coad), 6.7% (3 days), 6.5% (9 days) compared to control (4.2%), and presence of pioglitazone was no significant change in the terminal half-life ($t_{1/2}$) and the time to reach the peak concentration($T_{max}$) of verapamil. Our results indicate that pioglitazone significantly enhanced oral bioavailability of verapamil in rats, implying that presence of pioglitazone could be effective to inhibit the CYP3A4-mediated metabolism of verapamil in the intestine. Drug interactions should be considered in the clinical setting when verapamil is coadministrated with pioglitazone.

• Tuberculosis and Respiratory Diseases
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• v.81 no.1
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• pp.13-18
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• 2018

Bronchodilator therapy is central to the management of chronic obstructive pulmonary disease and are recommended as the preferred treatment by the Global Obstructive Lung Disease Initiative (GOLD). Long acting anti-muscarinics (LAMA) and long acting ${\beta}_2$ agonists (LABA) are both more effective than regular short-acting drugs but many patients remain symptomatic despite monotherapy with these drugs. Combination therapy with LAMA and LABA increases the therapeutic benefit while minimizing dose-dependent side effects of long-acting bronchodilator therapy. The TOviTO programme has investigated the benefits of treatment with a combination of tiotropium and olodaterol administered via a single inhaler. Tiotropium+olodaterol $5/5{\mu}g$ significantly improved forced expiratory volume in 1 second ($FEV_1$) area under the curve from 0 to 3 hours, trough $FEV_1$ health status and breathlessness versus the mono-components and placebo. Tiotropium+olodaterol $5/5{\mu}g$ also increased endurance time and reduced dynamic hyperinflation during constant work rate cycle ergometry. On the basis of these and other studies the 2017 GOLD report recommends escalating to dual bronchodilator therapy in patients in groups B and C if they remain symptomatic or continue to have exacerbations and as initial therapy for patients in group D.

• Economic and Environmental Geology
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• v.34 no.5
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• pp.499-506
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• 2001

The geophysical monitoring technique using the high resolution time-domain electromagnetic (TEM) method with a coincident loop away was applied for determination of an underground seawater flow in the coastal areas. In comparison of the TEM monitoring to direct current (DC) resistivity monitoring, the TEM response to the under ground seawater flow is less sensitive than the DC resistivity response. However, the TEM monitoring is more effective in terms of measuring time, survey expense, and real-time data processing than the DC monitoring thor evaluating the spatial distribution of the fresh water-seawater transition zone in a regional area.

• Biomedical Science Letters
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• v.23 no.4
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• pp.348-354
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• 2017

TyG (triglyceride and glucose) index using triglyceride and fasting blood glucose is recommended as a useful marker for insulin resistance. The present study evaluated the usefulness of TyG index in diagnosing metabolic syndrome and suggested an optimal cut-off value. The subjects of this study were adult 4,415 adults aged 20 to 80 years who underwent health screening at J General Hospital from January 2016 to January 2017. Metabolic syndrome was based on AHA/NHLBI (American Heart Association/National Heart, Lung, and Blood Institute) criteria. TyG index correlated with metabolic syndrome risk factors including HOMA-IR. Compared with the participants in the lowest quartile of TyG index, odds ratios and 95% confidence intervals for metabolic syndrome were 8.5 (3.005~23.903), 20.0 (17.190~23.407) for those in the third, and the fourth quartile of TyG index. The optimal cut-off value of the metabolic syndrome was 8.81 for TyG index (sensitivity 86.7%, specificity 80.1%) and area under the ROC curve (AUC) was 0.894. In conclusion, TyG index is effective to identify individuals at risk for metabolic syndrome.

• Journal of Nutrition and Health
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• v.43 no.3
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• pp.215-223
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• 2010

Sasa borealis leaf has been known to have anti-diabetic properties. In this study, we tried to evaluate the effects of Sasa borealis leaf extract (SBE) on the inhibition of $\alpha$-glucosidase activity and postprandial glycemic response following ingestion of four carbohydrate-rich foods; cooked rice, ramen (instant noodle), noodle, and bread. Fourteen healthy female adults consumed 50 g of glucose (control) or one of the four foods containing 50 g of available carbohydrate with or without 2,000 mg of SBE. The activity of $\alpha$-glucosidase was inhibited dose-dependently by SBE. With SBE, blood glucose concentration at 15 min and the positive area under the curve (AUC) of postprandial glycemic response at 15 min and 30 min after consuming each of the four foods were reduced significantly. As the result, total positive AUC during 120 min was decreased in case of taking cooked rice or bread. Glycemic index and glycemic load of the four foods were declined from 13% to 23% with SBE. The results of this study suggest that SBE may be effective for postprandial glucose control by inhibiting $\alpha$-glucosidase activity.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1293-1308
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• 2020

In fine-tuning-based transfer learning, the size of the dataset may affect learning accuracy. When a dataset scale is small, fine-tuning-based transfer-learning methods use high computing costs, similar to a large-scale dataset. We propose a mid-level feature extractor that retrains only the mid-level convolutional layers, resulting in increased efficiency and reduced computing costs. This mid-level feature extractor is likely to provide an effective alternative in training a small-scale medical image dataset. The performance of the mid-level feature extractor is compared with the performance of low- and high-level feature extractors, as well as the fine-tuning method. First, the mid-level feature extractor takes a shorter time to converge than other methods do. Second, it shows good accuracy in validation loss evaluation. Third, it obtains an area under the ROC curve (AUC) of 0.87 in an untrained test dataset that is very different from the training dataset. Fourth, it extracts more clear feature maps about shape and part of the chest in the X-ray than fine-tuning method.

• BMB Reports
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• v.43 no.12
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• pp.836-841
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• 2010

In the era of personal genomics, predicting the individual response to drug-treatment is a challenge of biomedical research. The aim of this study was to validate whether interaction information between genetic and transcriptional signatures are promising features to predict a drug response. Because drug resistance/susceptibilities result from the complex associations of genetic and transcriptional activities, we predicted the inter-relationships between genetic and transcriptional signatures. With this concept, captured genetic polymorphisms and transcriptional profiles were prepared in cancer samples. By splitting ninety-nine samples into a trial set (n = 30) and a test set (n = 69), the outperformance of relationship-focused model (0.84 of area under the curve in trial set, P = $2.90{\times}10^{-4}$) was presented in the trial set and validated in the test set, respectively. The prediction results of modeling show that considering the relationships between genetic and transcriptional features is an effective approach to determine outcome predictions of drug-treatment.

• Preventive Nutrition and Food Science
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• v.21 no.3
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• pp.181-186
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• 2016

This study was designed to investigate the inhibitory effect of Gynura procumbens extract against carbohydrate digesting enzymes and its ability to ameliorate postprandial hyperglycemia in streptozotocin (STZ)-induced diabetic mice. G. procumbens extract showed prominent ${\alpha}$-glucosidase and ${\alpha}$-amylase inhibitory effects. The half-maximal inhibitory concentration ($IC_{50}$) of G. procumbens extract against ${\alpha}$-glucosidase and ${\alpha}$-amylase was $0.092{\pm}0.018$ and $0.084{\pm}0.027mg/mL$, respectively, suggesting that the ${\alpha}$-amylase inhibition activity of the G. procumbens extract was more effective than that of the positive control, acarbose ($IC_{50}=0.164mg/mL$). The increase in postprandial blood glucose levels was more significantly alleviated in the G. procumbens extract group than in the control group of STZ-induced diabetic mice. Moreover, the area under the curve significantly decreased with G. procumbens extract administration in STZ-induced diabetic mice. These results suggest that G. procumbens extract may help alleviate postprandial hyperglycemia by inhibiting carbohydrate digesting enzymes.

• Clinical and Experimental Pediatrics
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• v.57 no.10
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• pp.451-456
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• 2014

Purpose: We evaluated serum procalcitonin (PCT) as a diagnostic marker of neonatal sepsis, and compared PCT levels with C-reactive protein (CRP) levels. Methods: We retrospectively reviewed the medical records of 269 neonates with a suspected infection, admitted to Wonkwang University School of Medicine & Hospital between January 2011 and December 2012, for whom PCT and CRP values had been obtained. Neonates were categorized into 4 groups according to infection severity. CRP and PCT values were analyzed and compared, and their effectiveness as diagnostic markers was determined by using receiver operating characteristic (ROC) curve analysis. We also calculated the sensitivity, specificity, and positive, and negative predictive values. Results: The mean PCT and CRP concentrations were respectively $56.27{\pm}81.89$ and $71.14{\pm}37.17mg/L$ in the "confirmed sepsis" group; $15.64{\pm}32.64$ and $39.23{\pm}41.41mg/L$ in the "suspected sepsis" group; $9.49{\pm}4.30$ and $0.97{\pm}1.16mg/L$ in the "mild infection" group; and $0.21{\pm}0.12$ and $0.72{\pm}0.7mg/L$ in the control group. High concentrations indicated greater severity of infection (P<0.001). Five of 18 patients with confirmed sepsis had low PCT levels (<1.0 mg/L) despite high CRP levels. In the ROC analysis, the area under the curve was 0.951 for CRP and 0.803 for PCT. The cutoff concentrations of 0.5 mg/L for PCT and 1.0 mg/L for CRP were optimal for diagnosing neonatal sepsis (sensitivity, 88.29% vs. 100%; specificity, 58.17% vs. 85.66%; positive predictive value, 13.2% vs. 33.3%; negative predictive value, 98.6% vs. 100%, respectively). Conclusion: PCT is a highly effective early diagnostic marker of neonatal infection. However, it may not be as reliable as CRP.

• Geomechanics and Engineering
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• v.34 no.3
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• pp.267-284
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• 2023

Landslides are one of the most dangerous phenomena and natural disasters. Landslides cause many human and financial losses in most parts of the world, especially in mountainous areas. Due to the climatic conditions and topography, people in the northern and western regions of Iran live with the risk of landslides. One of the measures that can effectively reduce the possible risks of landslides and their crisis management is to identify potential areas prone to landslides through multi-criteria modeling approach. This research aims to model landslide potential area in the Oshvand watershed using a support vector machine algorithm. For this purpose, evidence maps of seven effective factors in the occurrence of landslides namely slope, slope direction, height, distance from the fault, the density of waterways, rainfall, and geology, were prepared. The maps were generated and weighted using the continuous fuzzification method and logistic functions, resulting values in zero and one range as weights. The weighted maps were then combined using the support vector machine algorithm. For the training and testing of the machine, 81 slippery ground points and 81 non-sliding points were used. Modeling procedure was done using four linear, polynomial, Gaussian, and sigmoid kernels. The efficiency of each model was compared using the area under the receiver operating characteristic curve; the root means square error, and the correlation coefficient . Finally, the landslide potential model that was obtained using Gaussian's kernel was selected as the best one for susceptibility of landslides in the Oshvand watershed.