Effect of Geijibokryunghwan and each constituent herb on inhibition of platelet aggregation (계지복령환(桂枝茯笭丸) 및 그 구성약물(構成藥物)의 혈소판응집억제(血小板凝集抑制)에 관(關)한 연구(硏究))
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- The Journal of Dong Guk Oriental Medicine
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- v.8 no.2
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- pp.115-129
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- 2000
The cause that the increase of animality fat intakes, under exercise, fatness, adding the stress, advanced age etc., the occurrence rate of the circulation system disease has been increased. And the thrombosis importantly came to the front as the risk factor of these circulation system's disease. Nowadays, the ischemic disease has especially discussed, for example the angina or myocardial infarction, originated in thrombosis that came from the platelet aggregation. In the western medicine, as the cure and prevention, using the aspirin or ticlopidine for platelet aggregation suppressant. But in the
By the activation of ovary hormone, many morphological changes occur in the epithelial cell lines and muscle cells in rat uterus. These two cells in uterus are important to the implantation of embryo, maintaining pregnancy and starting parturition. One important change associated with the morphological change of these two cells in uterus is the change on prostaglandin(PG) metabolism. Its presence and synthesis in endometriurn and myometrium in uterus affects estrous cycle and the start of embryo implantation in uterus. It also performs as an important modulator in parturition. So the abnormally weak expression of PG causes difficulty during labor and over-expression causes pre-term labor. PG biosynthesis starts from either free or liberated arachidonic acids from membrane phospholipid by phospholipase. Such arachidonic acids are converted into PG catalyzed by Cyclooxygenase. Under normal physiological condition, Cyclooxygenase-1(COX-1) having 602 units of amino acids controls the synthesis of PG. It acts as a local hormone regulating vasomodulation of blood flow, flexible muscle movement, increasing the blood permeability and contributing the protective role in preserving integrity of the stomach lining and Cyclooxygenase-2 (COX-2) is induced by the inflammation, pregnancy and increased its expression until parturition. Lipid metabolite like PG is located in uterine and expression of COX-2 increased with pregnancy. Increased expression of COX proteins in epithelial cells and myometrial cells are told to increase the muscle contractility in uterus but decreased right after the labor in rat. It is a good sign indicating that COX proteins are deeply related to the start of labor. Currently, Several studies report the use of PG and COX-2 inhibitor as medication for controlled abortion or to prevent pre-term labor but they entail various side-effects. Our study proposed to suggest use of acupuncture as an another mediator to control abortion or pre-term labor without causing unnecessary side-effects by those medicines. Two acupuncture sites, LI-4 & SP-6 were selected due to their known efficacy. From the immunohistochemical staining of COX-2, normal expression of COX-2 protein in nonpregnant SD rat's uterus revealed that COX-2 protein was primarily detected in the lumina epithelial lining and in the epithelial cell lining contacting the stromal cells. High resolution optical microscopic scanning revealed distinguishable staining in the myometrial mucosa. LI-4 acupuncture administered nonpregnant rat's uterus showed strong expression for COX-2 in endometrium contacted with lumina epithelial lining of rat uterus and in myometrial mucosa. Stromal cells showed more staining than untreated nonpregnant rat's uterus and stronger staining in stromal cells contacting myometrial layer compared to untreated nonpregnant rat's uterus. SP-6 acupuncture administered nonpregnant rat's uterus showed weak expression for COX-2 in myometrial layers and stromal cells but no staining was visible in lumina epitheliai and glandular epithelial cells. Few stromal cells and myometrial mucosa were positively stained for COX-2. Pregnant SD rat's uterus was also immunostained for COX-2 expression after 18 days of pregnancy. Unlike to untreated nonpregnant rat's uterus, luminal epithelial cells were not positively stained for COX-2 but stronger staining for COX-2 was revealed in stromal cells. LI-4 acupunctured SD rat's uterus had very strong expression of COX-2 in luminal epithelial lining. Few stromal cells showed stronger positive COX-2 staining and myometrial layers also showed more expression than untreated pregnant rat. SP-6 acupuncture administered pregnant SD rat's uterus showed positive expression of COX-2 in epithelial cells of luminal mucosa layer but weaker than that of LI-4 acupuncture treatment's case. However, strong positive staining was revealed in stromal mucosa and myometrial layers. Virgin SD rat's uterus motility index during LI-4 acupuncture was 66.52 % (Prob〉T = 0.0197) compared to its motility before the acupuncture treatment but the motility index was slighdy elevated up to 79.58 % (Prob〉T = 0.1175) after the acupuncture. During the SP-6 acupuncture treatment for 30 minutes, uterus motility index was 90.52 % (Prob〉T = 0.1832) showing lesser decrement but consequently reached similar motility index decreasal to 79.95 % (Prob〉T = 0.0215) after the acupuncture treatment as LI-4 showed. LI-4 acupuncture tend to be a quick treatment to reducing the uterus motility in a virgin rat but eventually both two acupuncture administration created very similar reduction of uterus motility seeing the index after the both acupunctures. The uterus movement monitored during the LI-4 acupuncture administered for 30 minutes, Pregnant SD rat showed decreased motility down to 77.90 % (Prob〉 T = 0.0076) compared to uterus motility before the acupuncture and it continuously decreased down to 71.81 %(Prob〉T = 0.0214) after the removal of needle. The statistical analysis using paired t-test showed significance difference for both two motility indexs at =0.05. SP-6 acupuncture administered to pregnant SD rat also had similar pattern of decreasing uterus motility index down to 74.70 % (Prob〉T = 0.1730) during the initial 30 minutes acupuncture administration and it was continuously lowered to 71.52 % (Prob〉T = 0.0155) after the acupuncture. The paired t-test resuit for SP-6 suggest prompt response of uterus motility index to the SP-6 acupuncture treatment but consequently reached same level of inducing the motility reduction as LI-4 at =0.05 level.
According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.
The thermal analysis by mathematical model simulation makes it possible to reasonably predict heating and/or cooling requirements of certain greenhouses located under various geographical and climatic environment. It is another advantages of model simulation technique to be able to make it possible to select appropriate heating system, to set up energy utilization strategy, to schedule seasonal crop pattern, as well as to determine new greenhouse ranges. In this study, the control pattern for greenhouse microclimate is categorized as cooling and heating. Dynamic model was adopted to simulate heating requirements and/or energy conservation effectiveness such as energy saving by night-time thermal curtain, estimation of Heating Degree-Hours(HDH), long time prediction of greenhouse thermal behavior, etc. On the other hand, the cooling effects of ventilation, shading, and pad ||||&|||| fan system were partly analyzed by static model. By the experimental work with small size model greenhouse of 1.2m