• Clinical Endoscopy
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• v.56 no.4
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• pp.446-452
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• 2023

Background/Aims: Colonoscopy for screening is associated with unpleasant experiences for patients, and abdominal compression devices have been developed to minimize these problems. However, there is a paucity of data supporting the therapeutic benefits of this strategy. This study examined the effects of using an abdominal compression device during colonoscopy on the cecal intubation time (CIT), abdominal compression, patient comfort, and postural changes. Methods: We searched PubMed and Scopus (from inception to November 2021) for randomized controlled trials that assessed the effects of an abdominal compression device during colonoscopy on CIT, abdominal compression, patient comfort, and postural change. A random-effects meta-analysis was performed. Weighted mean differences (WMDs) and Mantel-Haenszel odds ratios (ORs) were calculated. Results: Our pooled analysis of seven randomized controlled trials revealed that abdominal compression devices significantly reduced CIT (WMD, -0.76 [-1.49 to -0.03] minutes; p=0.04), abdominal compression (OR, 0.52; 95% confidence interval [CI], 0.28-0.94; p=0.03), and postural changes (OR, 0.46; 95% CI, 0.27-0.78; p=0.004) during colonoscopy. However, our results did not show a significant change in patient comfort (WMD, -0.48; 95% CI, -1.05 to 0.08; p=0.09) when using an abdominal compression device. Conclusions: Our findings demonstrate that employing an abdominal compression device may reduce CIT, abdominal compression, and postural change but have no impact on patient comfort.

• Clinical Nutrition Research
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• v.12 no.1
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• pp.54-64
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• 2023

A systematic review and meta-analysis were designed to summarize studies conducted on the effects of raspberry and blackcurrant consumption on blood pressure (BP). Eligible studies were detected by searching numerous five online databases including PubMed, Scopus, Web of Science, Cochrane Library, and Google Scholar, until December 17, 2022. We pooled the mean difference and its 95% confidence interval (CI) by applying a random-effects model. Overall, the impact of raspberry and blackcurrant on BP was reported in ten randomized controlled trials (RCTs) (420 subjects). Pooled analysis of six clinical trials revealed that raspberry consumption has no significant reduction in systolic blood pressure (SBP) (weighted mean differences [WMDs], -1.42; 95% CI, -3.27 to 0.87; p = 0.224) and diastolic blood pressure (DBP) (WMD, -0.53; 95% CI, -1.77 to 0.71; p = 0.401), in comparison with placebo. Moreover, pooled analysis of four clinical trials indicated that blackcurrant consumption did not reduce SBP (WMD, -1.46; 95% CI, -6.62 to 3.7; p = 0.579), and DBP (WMD, -2.09; 95% CI, -4.38 to 0.20; p = 0.07). Raspberry and blackcurrant consumption elicited no significant reductions in BP. More accurate RCTs are required to clarify the impact of raspberry and blackcurrant intake on BP.

• Clinical Endoscopy
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• v.57 no.1
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• pp.36-47
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• 2024

Background/Aims: Scissor-type endoscopic submucosal dissection (ST-ESD) knives can reduce the adverse events associated with ESDs. This study aimed to compare ST-ESD and non-scissor-type (NST)-ESD knives. Methods: We identified ten studies that compared the performance characteristics and safety profiles of ST-ESD and NST-ESD knives. Fixed- and random-effects models were used to calculate the pooled proportions. Heterogeneity was assessed using the I² test. Results: On comparing ST-ESD knives to NST-ESD knives, the weighted odds of en bloc resection was 1.61 (95% confidence interval [CI], 0.90-2.90; p=0.14), R0 resection was 1.10 (95% CI, 0.71-1.71; p=0.73), delayed bleeding was 0.40 (95% CI, 0.17-0.90; p=0.03), perforation was 0.35 (95% CI, 0.18-0.70; p<0.01) and ESD self-completion by non-experts was 1.89 (95% CI, 1.20-2.95; p<0.01). There was no heterogeneity, with an I² score of 0% (95% CI, 0%-54.40%). Conclusions: The findings of reduced odds of perforation, a trend toward reduced delayed bleeding, and an improvement in the rates of en bloc and R0 resection with ST-ESD knives compared to NST-ESD knives support the use of ST-ESD knives when non-experts perform ESDs or as an adjunct tool for challenging ESD procedures.

• Clinical Nutrition Research
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• v.11 no.2
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• pp.120-132
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• 2022

Numerous clinical trials have examined the beneficial effects of Juglans regia leaf extract (JRLE) in patients with type 2 diabetes mellitus (T2DM); however, the results of these studies are inconsistent. Therefore, we conducted the current systematic review and meta-analysis to evaluate the effect of JRLE on glycemic control and lipid profile in T2DM patients. We searched online databases including PubMed, Scopus, EMBASE, and Web of Science for randomized controlled clinical trials that examined the effect of JRLE on glycemic and lipid indices in T2DM patients. Data were pooled using both fixed and random-effect models and weighted mean difference (WMD) was considered as the overall effect size. Of the total records, 4 eligible studies, with a total sample size of 195 subjects, were included. The meta-analysis revealed that JRLE supplementation significantly reduces fasting blood glucose (WMD, -18.04; 95% confidence interval [CI], -32.88 mg/dL, -3.21 mg/dL; p = 0.017) and significantly increases fasting insulin level (WMD, 1.93; 95% CI, 0.40 U/L, 3.45 U/L; p = 0.014). Although the overall effect of JRLE supplementation on hemoglobin A1c was not significant, a significant reduction was seen in studies with an intervention duration of > 8 weeks (WMD, -0.64; 95% CI, -1.16%, -0.11%; p = 0.018). Moreover, we also found no significant change in lipid parameters. Our findings revealed a beneficial effect of JRLE supplementation on glycemic indices in T2DM patients, but no significant improvement was found for lipid profile parameters.

• Clinical Nutrition Research
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• v.11 no.2
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• pp.133-145
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• 2022

The aim of this systematic review and meta-analysis was to summarize all the existing randomized controlled trials (RCTs) evidence and to evaluate the effects of magnesium supplementation on serum magnesium, calcium and urinary magnesium concentrations in patients with type 2 diabetes compared with the control. Two independent authors systematically searched online databases including Embase, Scopus, PubMed, and Web of Science from inception until 30th January 2022. RCTs complying with the inclusion criteria were included in this meta-analysis. The heterogeneity among the included studies was assessed using Cochrane's Q test and I-square (I²) statistic. Data were pooled using a random-effects model and weighted mean difference (WMD) was considered as the overall effect size. Sixteen trials were included in this meta-analysis. Serum magnesium (mean difference, 0.15 mg/dL; 95% confidence interval [CI], 0.06 to 0.23; p = 0.001) and urinary magnesium (WMD, 1.99 mg/dL; 95% CI, 0.36 to 3.62; p = 0.017) concentrations were significantly increased after magnesium supplementation when compared with the control group. However, magnesium supplementation did not have any significant effect on serum calcium (WMD, -0.09 mg/dL; 95% CI, -0.27 to 0.08; p = 0.294) level when compared with the control group. This meta-analysis demonstrated that magnesium supplementation significantly increased Serum magnesium levels which may have played an indirect role in improved clinical symptoms in patients with type 2 diabetes.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.979-995
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• 2023

As wildfires are difficult to predict, real-time monitoring is crucial for a timely response. Geostationary satellite images are very useful for active fire detection because they can monitor a vast area with high temporal resolution (e.g., 2 min). Existing satellite-based active fire detection algorithms detect thermal outliers using threshold values based on the statistical analysis of brightness temperature. However, the difficulty in establishing suitable thresholds for such threshold-based methods hinders their ability to detect fires with low intensity and achieve generalized performance. In light of these challenges, machine learning has emerged as a potential-solution. Until now, relatively simple techniques such as random forest, Vanilla convolutional neural network (CNN), and U-net have been applied for active fire detection. Therefore, this study proposed an active fire detection algorithm using state-of-the-art (SOTA) deep learning techniques using data from the Advanced Himawari Imager and evaluated it over East Asia and Australia. The SOTA model was developed by applying EfficientNet and lion optimizer, and the results were compared with the model using the Vanilla CNN structure. EfficientNet outperformed CNN with F1-scores of 0.88 and 0.83 in East Asia and Australia, respectively. The performance was better after using weighted loss, equal sampling, and image augmentation techniques to fix data imbalance issues compared to before the techniques were used, resulting in F1-scores of 0.92 in East Asia and 0.84 in Australia. It is anticipated that timely responses facilitated by the SOTA deep learning-based approach for active fire detection will effectively mitigate the damage caused by wildfires.

• Journal of the Korean Society of Radiology
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• v.83 no.5
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• pp.1059-1070
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• 2022

Purpose To compare the sensitivity of tumor detection and inter-observer agreement between acquired diffusion-weighted imaging (aDWI) b2000 and computed DWI (cDWI) b2000 in patients with prostate cancer (PCa). Materials and Methods Eighty-eight patients diagnosed with PCa by radical prostatectomy and having undergone pre-operative 3 Tesla-MRI, including DWI (b, 0, 100, 1000, 2000 s/mm²), were included in the study. cDWI b2000 was obtained from aDWI b0, b100, and b1000. Two independent reviewers performed a review of the aDWI b2000 and cDWI b2000 images in random order at 4-week intervals. A region of interest was drawn for the largest tumor on each dataset, and a Prostate Imaging-Reporting and Data System (PI-RADS) score based on PI-RADS v2.1 was recorded. Histologic topographic maps served as the reference standard. Results The study population's Gleason scores were 6 (n = 16), 7 (n = 53), 8 (n = 9), and 9 (n = 10). According to the reviewers, the sensitivities of cDWI b2000 and aDWI b2000 showed no significant differences (for reviewer 1, both 94% [83/88]; for reviewer 2, both 90% [79/88]; p = 1.000, respectively). The kappa values of cDWI b2000 and aDWI b2000 for the PI-RADS score were 0.422 (95% confidence interval [CI], 0.240-0.603) and 0.495 (95% CI, 0.308-0.683), respectively. Conclusion cDWI b2000 showed comparable sensitivity with aDWI b2000, in addition to sustained moderate inter-observer agreement, in the detection of PCa.

• Journal of Korea Water Resources Association
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• v.45 no.8
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• pp.827-837
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• 2012

The estimation of the rainfall quantile is of great importance in designing hydrologic structures. Conventionally, the rainfall quantile is estimated by univariate frequency analysis with an appropriate probability distribution. There is a limitation in which duration of rainfall is restrictive. To overcome this limitation, bivariate frequency analysis by using 3 copula models is performed in this study. Annual maximum rainfall events in 5 stations are used for frequency analysis and rainfall depth and duration are used as random variables. Gumbel (GUM), generalized logistic (GLO) distributions are applied for rainfall depth and generalized extreme value (GEV), GUM, GLO distributions are applied for rainfall duration. Copula models used in this study are Frank, Joe, and Gumbel-Hougaard models. Maximum pseudo-likelihood estimation method is used to estimate the parameter of copula, and the method of probability weighted moments is used to estimate the parameters of marginal distributions. Rainfall quantile from this procedure is compared with various marginal distributions and copula models. As a result, in change of marginal distribution, distribution of duration does not significantly affect on rainfall quantile. There are slight differences depending on the distribution of rainfall depth. In the case which the marginal distribution of rainfall depth is GUM, there is more significantly increasing along the return period than GLO. Comparing with rainfall quantiles from each copula model, Joe and Gumbel-Hougaard models show similar trend while Frank model shows rapidly increasing trend with increment of return period.

• Journal of Korean Society for Atmospheric Environment
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• v.17 no.5
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• pp.425-437
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• 2001

This study is based on the uses meta-analysis methodology to examine the statistical consistency and importance of random variation among results of epidemiologic studies between air pollutants exposure and childhood asthma. Studies for this meta-analysis were conducted by reviewing previous results and by asking researcher active in this field for recommendations. Overall, 10 cases of air pollutants exposures and childhood asthma were reviewed. A variety of statistical methods for meta-analysis have been used to assess the combined effects, to identify heterogeneity, and to provide a single summary risk estimate based on a set of simiar epidemiologic studies. In this study, classification of exposure metircs on air environmental epidemiologic studies are reported for (1) aggravation of childhood asthma by a 50 ppb increase SO$_2$(6 individual studies); (2) aggravation of childhood asthma by a 50 ppb increase NO$_2$(5 individual studies); (3) aggravation of childhood asthma by a 50 ppb increase $O_3$(7 individual studies); (4) aggravation of childhood asthma by a 10$\mu\textrm{g}$/m$^3$increase PM$_{10}$ (4 individual studies); (5) aggravation of childhood asthma by a 1 ppm increase CO (2 individual studies); and (6) comparison of results between a Korean study results and this meta-analytic study. Results of this study indicated that an inverse-variance weighted pooling of the hospital admission risk at a 1ppm increment of CO levels was 1.12% (95% CI : 1.01 ~ 1.24). The hospital admission risk was estimated to increase 5% (95% CI : 1.02~1.08), 6%(95% CI : 1.04~1.09), and 5% (95% CI : 1.02~1.09) with each 50ppb increase of SO$_2$, NO$_2$, and $O_3$, respectively. In addition, our results lead to a small but significant elevation in risk of 2% (RR = 1.02, 95% CI = 1.01~1.04) with each 10$\mu\textrm{g}$/m$^3$increase of PM$_{10}$ among 4 individual studies. We found a small elevation in risk of childhood asthma, and pooled results of 10 epidemiologic studies of childhood asthma using increase a cut-off-point levels of air pollutants showed a few pieces of evidence. The results of this meta-analysis suggested that air pollution associated with an increased incidence of childhood asthma. According to this study, relationship between exposure to air pollutants and childhood asthma in Korea seem to be high than results of this meta-analysis.sis.

• Journal of Animal Science and Technology
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• v.58 no.11
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• pp.40.1-40.5
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• 2016

Background: Currently about 26,000 horses are breeding in Korea and 57.2% (14,776 horses) of them are breeding in Jeju island. According to the statistics published in 2010, the horses breeding in Jeju island are subdivided into Jeju horse (6.1%), Thoroughbred (18.8%) and Halla horse (75.1%). Halla horses are defined as a crossbreed between Jeju and Thoroughbred horses and are used for horse racing, horse riding and horse meat production. However, little research has been conducted on Halla horses because of the perception of crossbreed and people's weighted interest toward Jeju horses. Method: Using 17 Microsatellite (MS) Markers recommended by International Society for Animal Genetics (ISAG), genomic DNAs were extracted from the hair roots of 3,880 Halla horses breeding in Korea and genetic diversity was identified by genotyping after PCR was performed. Results and conclusion: In average, 10.41 alleles (from 6 alleles in HTG7 to 17 alleles in ASB17) were identified after the analysis using 17 MS Markers. The mean value of $H_{obs}$ was 0.749 with a range from 0.612(HMS1) to 0. 857(ASB2). Also, it was found that $H_{\exp}$ and PIC values were lowest in HMS1 (0.607 and 0.548, respectively), and highest in LEX3(0.859 and 0.843, respectively), and the mean value of $H_{\exp}$ was 0.760 and that of PIC was 0.728. 17 MS markers used in this studies were considered as appropriate markers for the polymorphism analysis of Halla horses. The frequency for the appearance of identical individuals was $5.90{\times}10^{-20}$ when assumed as random mating population and when assumed as half-sib and full-sib population, frequencies were $4.08{\times}10^{-15}$ and $3.56{\times}10^{-8}$, respectively. Based on these results, the 17 MS markers can be used adequately for the Individual Identification and Parentage Verification of Halla horses. Remarkably, allele M and Q of ASB23 marker, G of HMS2 marker, H and L of HTG6 marker, L of HTG7 marker, E of LEX3 marker were the specific alleles unique to Halla horses.