• Korean Journal of Clinical Laboratory Science
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• v.54 no.4
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• pp.279-284
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• 2022

Certain pre-transfusion tests are not commonly performed during emergency blood transfusion. In this study, we reviewed and analyzed the data of post-blood transfusion antibody screening tests to establish the effects of unexpected antibodies causing hemolytic transfusion reactions. We reviewed information published domestically and internationally, and selected the data of 68,602 antibody screening tests and 528 antibody identification tests conducted at P hospital. We found that unexpected antibody positive (1198,1.74%), Rh type (161, 30.49%), Lewis type (67, 12.69%), others (Di (a), 28, 5.30%). The anti-E type positive was 93 (17.61%), and that of the cases with anti-C (13, 2.46%). Only data of domestic cases were included for analysis that were published before 2007, which established the presence of antibodies of the following types and numbers of cases: anti-E (196, 22.45%), anti-Le a (82, 9.39%), and anti-E+C (60, 6.87%). In 2018, anti-E (107, 17.12%), anti-E+Canti-E+C (56, 8.96%), and anti-Di a (28, 4.48%) were detected. In other domestic cases, S hospital was detect to anti-E, anti-Le a, anti-E+C. The Anti-E, anti-D, anti-E+C, and anti-C+E were detected in D hospital. In Saudi Arabia, Anti-D, anti-E, and anti-Jka was detected. The Anti-M, Anti-N, Anti-Le (a), and Anti-D were detected in India. Requests for emergency blood transfusion increased 1.8 times after the opening of the trauma center. This study has the disadvantage of being a cross-sectional study. additional studies are needed to provide basic information on alternative treatments that can increase the safety and reduce the side effects of hemolytic transfusion in emergency transfusion situations.

• Journal of Life Science
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• v.34 no.7
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• pp.476-484
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• 2024

Although two-dimensional (2D) monolayer cell culture models are still widely used as the optimal models for anticancer activity research, three-dimensional (3D) multicellular tumor spheroid (3D MTS) models that can better approximate the tumor environment can offer an alternative to bridge the gap between in vitro and animal model studies. Isoalantolactone is among the sesquiterpene lactones found in medicinal plants, including the roots of Elecampane (Inula helenium L.), and is known to have various pharmacological activities, including anticancer activity. In this study, we investigated whether the anticancer activity of isoalantolactone observed in 2D models could be reproduced in a 3D MTS model derived from human hepatocellular carcinoma (HCC) Hep3B cells. According to our results, isoalantolactone inhibited the formation of MTSs in a manner dependent on the treatment concentration, which was accompanied by an increase in reactive oxygen species (ROS) generation. In particular, as isoalantolactone treatment and the culture time increased, the area of proliferating cells was replaced by cells in which apoptosis was induced. Additionally, in MTSs, isoalantolactone increased the expression of death-receptor-related proteins and the activity of caspase-3, and it decreased the expression of the Bax/Bcl-2 expression ratio and total poly(ADP-ribose) polymerase. However, when the production of ROS was artificially blocked, all these changes caused by isoalantolactone were attenuated and the cell survival rate of MTS cells was restored. Therefore, the results of this study suggest that the induction of apoptosis in Hep3B cell-derived MTSs by isoalantolactone is achieved through the activation of extrinsic and intrinsic pathways and is ROS-dependent.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.167-194
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• 2019

This research starts from the four basic concepts of incentive incompatibility, limited information, myopia and decision variable which are confronted when making decisions in keyword bidding. In order to make these concept concrete, four framework approaches are designed as follows; Strategic approach for the incentive incompatibility, Statistical approach for the limited information, Alternative optimization for myopia, and New model approach for decision variable. The purpose of this research is to propose the statistical optimization model in constructing the portfolio of Sponsored Search Advertising (SSA) in the Sponsor's perspective through empirical tests which can be used in portfolio decision making. Previous research up to date formulates the CTR estimation model using CPC, Rank, Impression, CVR, etc., individually or collectively as the independent variables. However, many of the variables are not controllable in keyword bidding. Only CPC and Rank can be used as decision variables in the bidding system. Classical SSA model is designed on the basic assumption that the CPC is the decision variable and CTR is the response variable. However, this classical model has so many huddles in the estimation of CTR. The main problem is the uncertainty between CPC and Rank. In keyword bid, CPC is continuously fluctuating even at the same Rank. This uncertainty usually raises questions about the credibility of CTR, along with the practical management problems. Sponsors make decisions in keyword bids under the limited information, and the strategic portfolio approach based on statistical models is necessary. In order to solve the problem in Classical SSA model, the New SSA model frame is designed on the basic assumption that Rank is the decision variable. Rank is proposed as the best decision variable in predicting the CTR in many papers. Further, most of the search engine platforms provide the options and algorithms to make it possible to bid with Rank. Sponsors can participate in the keyword bidding with Rank. Therefore, this paper tries to test the validity of this new SSA model and the applicability to construct the optimal portfolio in keyword bidding. Research process is as follows; In order to perform the optimization analysis in constructing the keyword portfolio under the New SSA model, this study proposes the criteria for categorizing the keywords, selects the representing keywords for each category, shows the non-linearity relationship, screens the scenarios for CTR and CPC estimation, selects the best fit model through Goodness-of-Fit (GOF) test, formulates the optimization models, confirms the Spillover effects, and suggests the modified optimization model reflecting Spillover and some strategic recommendations. Tests of Optimization models using these CTR/CPC estimation models are empirically performed with the objective functions of (1) maximizing CTR (CTR optimization model) and of (2) maximizing expected profit reflecting CVR (namely, CVR optimization model). Both of the CTR and CVR optimization test result show that the suggested SSA model confirms the significant improvements and this model is valid in constructing the keyword portfolio using the CTR/CPC estimation models suggested in this study. However, one critical problem is found in the CVR optimization model. Important keywords are excluded from the keyword portfolio due to the myopia of the immediate low profit at present. In order to solve this problem, Markov Chain analysis is carried out and the concept of Core Transit Keyword (CTK) and Expected Opportunity Profit (EOP) are introduced. The Revised CVR Optimization model is proposed and is tested and shows validity in constructing the portfolio. Strategic guidelines and insights are as follows; Brand keywords are usually dominant in almost every aspects of CTR, CVR, the expected profit, etc. Now, it is found that the Generic keywords are the CTK and have the spillover potentials which might increase consumers awareness and lead them to Brand keyword. That's why the Generic keyword should be focused in the keyword bidding. The contribution of the thesis is to propose the novel SSA model based on Rank as decision variable, to propose to manage the keyword portfolio by categories according to the characteristics of keywords, to propose the statistical modelling and managing based on the Rank in constructing the keyword portfolio, and to perform empirical tests and propose a new strategic guidelines to focus on the CTK and to propose the modified CVR optimization objective function reflecting the spillover effect in stead of the previous expected profit models.