• Journal of Korean Society of Forest Science
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• v.47 no.1
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• pp.16-26
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• 1980

Soluble carbohydrates and free amino acids in the terminal buds of Pinus elliottii were analyzed to understand the nutritional status of the buds during the period of female strobilus initiation. Grafted, 18-year-old slash pine trees in a seed orchard were divided into two groups, abundant-flowering (AFG) and poor-flowering group (PFG) according to their flowering history. Four types of terminal buds, with two types from each group, were examined: (1) large buds in upper crown (female-producing buds) and small buds in lower crown (male-producing) in AFG, (2) large buds in upper crown (vegetative buds) and small buds in lower crown (male-producing) in PFG. Bud samples were collected four times from late July to early September. Free sugars and free amino acids (75% ethanol-soluble) were determined by gas chromatography and automatic analysis, respectively. Sugar content in the large buds of both groups was greater than in the small buds of the same group. Fructose and glucose were major sugars found in the bud tissue. Arginine was the most abundant amino acid in all four types of buds, with the concentration increased from 23% in late July to 60% in early September. Arginine and total amino acid content in the female-producing buds of AFG was much lower than three other types of buds. When female-producing buds and male-producing buds of AFG were compared in their arginine content, the former contained about same amount as the latter in late July, but showed one-fourth of the latter in early September. The low level of argining in the female-producing buds suggested a minimal or negative role of arginine in the initiation of female flower primordia. A higher sugar to amino acid ratio was observed with female-producing buds of AFG than with vegetative or male-producing buds of either flowering group. The low amino acid content in the female­producing buds suggested that initiation of female strobilus primordia was associated with temporary reduction in the metabolic activity of the buds.

• Journal of Bio-Environment Control
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• v.28 no.3
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• pp.234-242
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• 2019

We analyzed the anthocyanin accumulation, abscisic acid (ABA), gibberellic acid (GA) contents and metabolic genes expression in berry skins under high temperature (High T) at veraison, in order to investigate the cause of bad coloration of 'Kyoho' grape due to High T in summer season. The coloration of 'Kyoho' grapes was stopped by High T for 10 days from veraison, and the fruit quality was not affected except skin color. Total anthocyanin of skins was decreased by High T treatment and malvidin and peonidin were decreased compared to control. In berry skins, ABA content did not decrease by High T treatment, but it was rather higher than that of control. GA content was increased about two times compared to the control after 10 days of High T treatment, which caused decreased ratio of ABA/GA. Analysis of expression of anthocyanin biosynthetic genes showed that the early biosynthetic genes were not affected by High T and the expression of UFGT was decreased by temperature treatment. ABA biosynthetic gene expressions were not affected by High T and the expression of GA20ox1 and GA2ox1/2, which are known to regulate the biosynthesis and inactivation of GA, were increased and decreased by High T, respectively. Therefore, the bad coloration of 'Kyoho' grapes under the High T at veraison was due to inhibition of anthocyanin biosynthesis of skin, and it was suggested that the anthocyanin biosynthesis was controlled by the ratio of ABA and GA rather than ABA content.

• Korean Journal of Psychosomatic Medicine
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• v.26 no.2
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• pp.188-193
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• 2018

Objectives : Clozapine is a widely prescribed antipsychotic drug for schizophrenia and is known to increase the risk of cardiovascular disease due to its metabolic side effects. However, little is known about the effect of clozapine on the platelet activation, another important factor in the development of cardiovascular disease. In this study, we tried to investigate the effect of clozapine on platelet activity in patients with schizophrenia by comparing the mean platelet component (MPC) values before and after the clozapine administration. Methods : A retrospective review of medical records of patients with schizophrenia, who newly started clozapine treatment from September 1st, 2003 to April 30th, 2007 at the Department of Psychiatry, Konyang University Hospital in Republic of Korea was performed. The final statistical analysis included 14 participants. Bayer ADVIA $120^{(R)}$ system was used to measure MPC. Results : Among the 14 participants, five subjects were males (28.60%), and ten subjects were females (71.40%). The mean age of participants was $37.50{\pm}11.64years$. Average of duration of illness was $91.00{\pm}93.96months$, with the mean dosage of clozapine taken by participants at the time of the last blood test was $337.50{\pm}109.52mg$. The mean MPC measurement before and after receiving clozapine was $26.12{\pm}2.22g/dL$ and $25.14{\pm}2.08g/dL$ respectively. Wilcoxon signed rank test showed that there was a statistically significant decrease in MPC levels after clozapine administration (V=16, p=0.024). Conclusions : Decreased MPC levels after clozapine administration implies that clozapine may increase platelet activation which could have an adverse effect on the occurrence of thromboembolic disease. Our findings also suggest that careful monitoring of the risk factors of cardiovascular diseases, such as platelets activity, is necessary when administering clozapine.

• Journal of Life Science
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• v.31 no.6
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• pp.603-608
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• 2021

The purpose of this perspective research is to discuss the potential role of exercise-interventions in COVID-19, terms of prevention and prognosis in the periods of the COVID-19 vaccine. SARCO-CoV-2. COVID-19 was detected as a new virus causing severe cardiovascular and respiratory complications. It emerged as a global public health emergency and national pandemic. It caused more than 1 million deaths in the first 6 months of the pandemic and resulted in huge social and economic fluctuations internationally. Unprecedented stressful situations, such as COVID-19 blue and COVID-19 red impact on many health problems. In healthy individuals, COVID-19 infection may induced no symptoms (i.e., asymptomatic), whereas others may experience flu-like symptoms, such as ARDS, pneumonia, and death. Poor health status, such as obesity and cardiovascular and respiratory complications, are high risk factors for COVID-19 prevention, occurrence, and prognosis. Several COVID-19 vaccines are currently in human trials. However, the efficacy and safety of COVID-19 vaccines, including potential side effects, such as anaphylaxis (a life-threatening allergic reaction) and rare blood clots, still need to be investigated. On the basis of direct and indirect evidence, it seems that regular and moderate physical exercise can be recommended as a nonpharmacological, efficient, and safe way to cope with COVID-19. Physical inactivity and metabolic abnormalities are directly associated with reduced immune responses, including reduced innate, CMI, and AMI responses. Due to prolonged viral shedding, quarantine in inactive, obese and disease people should likely be longer than physical active people. Multicomponent and systemic exercise should be considered for the obese, disease, and elderly people. More mechanism research is needed in this area.

• Journal of Korea Entertainment Industry Association
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• v.13 no.7
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• pp.375-384
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• 2019

The purpose of this study was to investigate the effects of long-term aerobic dancing exercise on body composition, physical fitness and mental function in older women over 70 years old. All subjects were limited to older women aged 70 to under 85. The experimental group performed aerobic exercise of 2-3 times a week for 9.2 ± 4.6 yrs, and the control group did not perform any regular exercise and spent 3-4 times a week mainly in the relaxing facility for older. As a results in this study, the weight, muscle mass and body fat percentage of the aerobic group were not significantly different from those of the control group, but there were significantly positive effects of aerobic group in visceral fat mass, abdominal obesity rate(%), body water content and systolic blood pressure(p < .05). In terms of physical fitness, Sit & reach, one-legged stand (right) and TUG of the aerobic group were significantly higher than those of the control group(p < .05), but there were no significant differences between two groups in the shoulder flexibilities and grip strength. MMSE as a cognitive function was not significantly different between the two groups, but GDS was significantly lower in the aerobic group than in the control group(p < .05). According to the correlation analysis between all variables and MMSE and GDS, MMSE was significantly inversely correlated with height (r = -0.425)(p < .05), and no correlation was detected with other variables. However, GDS have signitively negative correlations with resting heart rate(r = -0.464), sit & reach(r = -0.525) left(r = -0.491) and right grip strengths(r = -0.635) as well as positive correlation systolic blood pressure(r = 0.482) and TUG (r = 0.479), respectively(p < .05). In conclusion, long-term aerobic exercise of elderly women over 70 older had positive effects on variables related to metabolic disease (visceral fat and resting heart rate), silver fitness variables related to falls, and depression level in the elderly.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.111-124
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• 2018

This study aims to develop a classification model for predicting the occurrence of hyperlipidemia, one of the chronic diseases. Prior studies applying data mining techniques for predicting disease can be classified into a model design study for predicting cardiovascular disease and a study comparing disease prediction research results. In the case of foreign literatures, studies predicting cardiovascular disease were predominant in predicting disease using data mining techniques. Although domestic studies were not much different from those of foreign countries, studies focusing on hypertension and diabetes were mainly conducted. Since hypertension and diabetes as well as chronic diseases, hyperlipidemia, are also of high importance, this study selected hyperlipidemia as the disease to be analyzed. We also developed a model for predicting hyperlipidemia using SVM and meta learning algorithms, which are already known to have excellent predictive power. In order to achieve the purpose of this study, we used data set from Korea Health Panel 2012. The Korean Health Panel produces basic data on the level of health expenditure, health level and health behavior, and has conducted an annual survey since 2008. In this study, 1,088 patients with hyperlipidemia were randomly selected from the hospitalized, outpatient, emergency, and chronic disease data of the Korean Health Panel in 2012, and 1,088 nonpatients were also randomly extracted. A total of 2,176 people were selected for the study. Three methods were used to select input variables for predicting hyperlipidemia. First, stepwise method was performed using logistic regression. Among the 17 variables, the categorical variables(except for length of smoking) are expressed as dummy variables, which are assumed to be separate variables on the basis of the reference group, and these variables were analyzed. Six variables (age, BMI, education level, marital status, smoking status, gender) excluding income level and smoking period were selected based on significance level 0.1. Second, C4.5 as a decision tree algorithm is used. The significant input variables were age, smoking status, and education level. Finally, C4.5 as a decision tree algorithm is used. In SVM, the input variables selected by genetic algorithms consisted of 6 variables such as age, marital status, education level, economic activity, smoking period, and physical activity status, and the input variables selected by genetic algorithms in artificial neural network consist of 3 variables such as age, marital status, and education level. Based on the selected parameters, we compared SVM, meta learning algorithm and other prediction models for hyperlipidemia patients, and compared the classification performances using TP rate and precision. The main results of the analysis are as follows. First, the accuracy of the SVM was 88.4% and the accuracy of the artificial neural network was 86.7%. Second, the accuracy of classification models using the selected input variables through stepwise method was slightly higher than that of classification models using the whole variables. Third, the precision of artificial neural network was higher than that of SVM when only three variables as input variables were selected by decision trees. As a result of classification models based on the input variables selected through the genetic algorithm, classification accuracy of SVM was 88.5% and that of artificial neural network was 87.9%. Finally, this study indicated that stacking as the meta learning algorithm proposed in this study, has the best performance when it uses the predicted outputs of SVM and MLP as input variables of SVM, which is a meta classifier. The purpose of this study was to predict hyperlipidemia, one of the representative chronic diseases. To do this, we used SVM and meta-learning algorithms, which is known to have high accuracy. As a result, the accuracy of classification of hyperlipidemia in the stacking as a meta learner was higher than other meta-learning algorithms. However, the predictive performance of the meta-learning algorithm proposed in this study is the same as that of SVM with the best performance (88.6%) among the single models. The limitations of this study are as follows. First, various variable selection methods were tried, but most variables used in the study were categorical dummy variables. In the case with a large number of categorical variables, the results may be different if continuous variables are used because the model can be better suited to categorical variables such as decision trees than general models such as neural networks. Despite these limitations, this study has significance in predicting hyperlipidemia with hybrid models such as met learning algorithms which have not been studied previously. It can be said that the result of improving the model accuracy by applying various variable selection techniques is meaningful. In addition, it is expected that our proposed model will be effective for the prevention and management of hyperlipidemia.

• Journal of Chest Surgery
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• v.35 no.6
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• pp.420-429
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• 2002

Moderate hypothermic cardiopulmonary bypass (CPB) has commonly been used in cardiac surgery. Several cardiac centers recently practice normothermic CPB in cardiac surgery, However, the clinical effect and safety of normothermic CPB on cerebral metabolism are not established and not fully understood. This study was prospectively designed to evaluate the clinical influence of normothermic CPB on brain metabolism and to compare it with that of moderate hypothermic CPB. Material and Method: Thirty-six adult patients scheduled for elective cardiac surgery were randomized to receive normothermic (nasopharyngeal temperature ＞34.5 $^{\circ}C$, n=18) or hypothermic (nasopharyngeal temperature 29~3$0^{\circ}C$, n=18) CPB with nonpulsatile pump. Middle cerebral artery blood flow velocity (VMCA), cerebral arteriovenous oxygen content difference (CAVO$_{2}$), cerebral oxygen extraction (COE), modified cerebral metabolic rate for oxygen (MCMRO$_{2}$), cerebral oxygen transport (TEO$_{2}$), cerebral venous desaturation (oxygen saturation in internal jugular bulb blood$\leq$50 %), and arterial and internal jugular bulb blood gas analysis were measured during six phases of the operation： Pre-CPB (control), CPB-10 min, Rewarm-1 (nasopharyngeal temperature 34 $^{\circ}C$ in the hypothermic group), Rewarm-2 (nasopharyngeal temperature 37 $^{\circ}C$ in the both groups), CPB-off and Post-CPB (skin closure after CPB-off). Postoperaitve neuropsychologic complications were observed in all patients. All variables were compared between the two groups. Result： VMCA at Rewarm-2 was higher in the hypothermic group (153.11$\pm$8.98%) than in the normothermic group (131.18$\pm$6.94%) (p＜0.05). CAVO$_{2}$ (3.47$\pm$0.21 vs 4.28$\pm$0.29 mL/dL, p＜0.05), COE (0.30$\pm$0.02 vs 0.39$\pm$0.02, p＜0.05) and MCMRO$_{2}$ (4.71 $\pm$0.42 vs 5.36$\pm$0.45, p<0.05) at CPB-10 min were lower in the hypothermic group than in the normothermic group. The hypothermic group had higher TEO$_{2}$ than the normothermic group at CPB-10 (1,527.60$\pm$25.84 vs 1,368.74$\pm$20.03, p＜0.05), Rewarm-2 (1,757.50$\pm$32.30 vs 1,478.60$\pm$27.41, p＜0.05) and Post-CPB (1,734.37$\pm$41.45 vs 1,597.68$\pm$27.50, p＜0.05). Internal jugular bulb oxygen tension (40.96$\pm$1.16 vs 34.79$\pm$2.18 mmHg, p＜0.05), saturation (72.63$\pm$2.68 vs 64.76$\pm$2.49 %, p＜0.05) and content (8.08$\pm$0.34 vs 6.78$\pm$0.43 mL/dL, p<0.05) at CPB-10 were higher in the hypothermic group than in the normothermic group. The hypothermic group had less incidence of postoperative neurologic complication (delirium) than the normothermic group (2 vs 4 patients, p＜0.05). Lasting periods of postoperative delirium were shorter in the hypothermic group than in the normothermic group (60 vs 160 hrs, p<0.01). Conclusion: These results indicate that normothermic CPB should not be routinely applied in all cardiac surgery, especially advanced age or the clinical situations that require prolonged operative time. Moderate hypothermic CPB may have beneficial influences relatively on brain metabolism and postoperative neuropsychologic outcomes when compared with normothermic CPB.