Overexpression of mitofusin-2 (MFN2), a mitochondrial fusion protein, is frequently associated with poor prognosis in cervical cancer patients. Here, I aimed to investigate the involvement of MFN2 in cervical cancer progression and determine the effect of MFN2 on prognosis in cervical cancer patients. After generating MFN2-knockdown SiHa cells derived from squamous cell carcinoma, I investigated the effect of MFN2 on SiHa cell proliferation using the Cell Counting Kit-8 assay and determined the mRNA levels of proliferation markers. Colony-forming ability and tumorigenesis were evaluated using a colony-formation assay and tumor xenograft mouse models. The migratory and invasive abilities associated with MFN2 were measured using wound-healing and invasion assays. Wnt/β-catenin-mediated epithelial-mesenchymal transition (EMT) markers related to MFN2 were assessed through quantitative RT-PCR. MFN2-knockdown SiHa cells exhibited reduced proliferation, colony formation, migration, invasion, and tumor formation in vivo. The motility of SiHa cells with MFN2 knockdown was reduced through Wnt/β-catenin-mediated EMT inhibition. MFN2 promoted cancer progression and tumorigenesis in SiHa cells. Overall, MFN2 could serve as a therapeutic target and a novel biomarker for cervical cancer.
The purpose of this study was to identify differences in learning patterns according to content complexity in video-based learning environments and to derive variables that have an important effect on learning achievement within particular learning contexts. To achieve our aims, we observed and collected data on learners' cognitive processes through perceived affordances, using behavioral logs and eye movements as specific indicators. These two types of reaction data were collected from 67 male and female university students who watched two learning videos classified according to their task complexity through the video learning player. The results showed that when the content complexity level was low, learners tended to navigate using other learners' digital logs, but when it was high, students tended to control the learning process and directly generate their own logs. In addition, using derived prediction models according to the degree of content complexity level, we identified the important variables influencing learning achievement in the low content complexity group as those related to video playback and annotation. In comparison, in the high content complexity group, the important variables were related to active navigation of the learning video. This study tried not only to apply the novel variables in the field of educational technology, but also attempt to provide qualitative observations on the learning process based on a quantitative approach.
Field experiments were conducted in the 101 tobacco fields(51 fields in 1985 and 50 fields in 1986) of chief tobacco producing counties of Chungbuk province(Jincheon, Eumseong, Goesan, and Joongweon counties), Chungnam province(Cheonweon county), and Kyongbuk province (Cheongdo, Seongju, and Andong counties) for two years from 1985 to 1986 in order to evaluate soil fertility using chemical properties and soil map database. Pot experiments also on the same soils were conducted and the results were compared to those of field experiments. The yield of tobacco in the plots of no fertilization was considered as a basic factor representing the soil fertility and was evaluated by nineteen independent variables, that was 9 chemical properties and 10 soil map databases. These independent variables were classified into two groups, 11 quantitative indexes and 9 qualitative indexes, and were analyzed by multiple linear regression(MLR) of SAS by REG and GLM models. The yield of tobacco in the plot of no fertilization showed high variations, e.g. the difference between minimum and maximum yields was about 5.0-5.5 times in the pot experiment and 8.2-14.9 times in the field experiment. The indexes indicating close link between yield of tobacco and soil chemical indexes, was selected but it was not well matched by the years or between pot and field experiments. Also, the standardized partial regression coefficients of quantitative indexes for the yield of field were less than 1.0, suggesting that it is difficult to develop an available single index for the evaluation of soil fertility. Evaluation for the soil fertility of field by MLR was better than that of single regression and it was gradually improved by adding chemical properties, quantitative indexes, and qualitative indexes of soil map. For example, the coefficient of determination ($R^2$) of MLR for the yield of 1985 was increased to 0.422 with chemical indexes, 0.503 by addition of quantitative indexes, and 0.633 by the additional adding of qualitative indexes of soil map, compared to 0.244 of single index, $NO_3-N$ content of soil. Consequently, it is assumed that this approach by MLR with quantitative and qualitative indexes including chemical properties and soil map databases was available as an evaluation model of soil fertility for tobacco field.
Evaluation method of soil fertility by application of geographic information system (GIS) which includes landscape characteristics and soil map data was investigated from productivities of red pepper and tobacco grown on the fields with no fertilization. Total 131 fields experiments, 64 fields of red pepper and 67 fields of tobacco were conducted from 22 and 23 fields for red pepper and tobacco, respectively, located at Cheangweon and Eumseong counties in 1996, from 20 and 25 fields at Boeun and Goesan counties in 1997, and 22 and 19 fields at Jincheon and Chungju counties in 1998. All the experimental sites were selected on the basis of wide range of distribution in landscape and soil attributes. Dry weights and nutrients (N, P and K) uptakes by red pepper plant and tobacco leaves were considered as basic fertility of the soil (BFS). The BFS was estimated by twenty-five independent variables including 13 chemical properties and 12 GIS data. Twenty-five independent variables were classified by two groups, 15 quantitative variables and 10 qualitative variables, and were analyzed by multiple linear regression (MLR) of REG and GLM models of SAS. Dry weight of red pepper (DWRP) and dry weight of tobacco leaves (DWTL) every year showed high variations by five times in difference plots with minimum yield and maximum yield indicating the diverse soil fertility among the experimental fields. Evaluation for the BFS by the MLR including independent variables was better than that by simple regression showing gradual improvement by adding chemical properties, quantitative variables, and qualitative variables of the GIS. However the evaluation for the BFS by the MLR showed the better result for tobacco than red pepper. For example the variability in the DWTL by MLR was explained 34.2% by only chemical properties, 35.0% by adding quantitative variables, and 72.5% by adding both the quantitative and qualitative variables of the GIS compared with 21.7% by simple regression with $NO_3-N$ content in soil. Consequently, it is assumed that this approach by the MLR including both the quantitative and qualitative variables was available as an evaluation model of soil fertility for upland field.
With the transition of archaeological recording method's transition from analog to digital, the 3D scanning technology has been actively adopted within the field. Research on the digital archaeological digital data gathered from 3D scanning and photogrammetry is continuously being conducted. However, due to cost and manpower issues, most buried cultural heritage organizations are hesitating to adopt such digital technology. This paper aims to present a digital recording method of relics utilizing open-source software and photogrammetry technology, which is believed to be the most efficient method among 3D scanning methods. The digital recording process of relics consists of three stages: acquiring a 3D model, creating a joining map with the edited 3D model, and creating an digital drawing. In order to enhance the accessibility, this method only utilizes open-source software throughout the entire process. The results of this study confirms that in terms of quantitative evaluation, the deviation of numerical measurement between the actual artifact and the 3D model was minimal. In addition, the results of quantitative quality analysis from the open-source software and the commercial software showed high similarity. However, the data processing time was overwhelmingly fast for commercial software, which is believed to be a result of high computational speed from the improved algorithm. In qualitative evaluation, some differences in mesh and texture quality occurred. In the 3D model generated by opensource software, following problems occurred: noise on the mesh surface, harsh surface of the mesh, and difficulty in confirming the production marks of relics and the expression of patterns. However, some of the open source software did generate the quality comparable to that of commercial software in quantitative and qualitative evaluations. Open-source software for editing 3D models was able to not only post-process, match, and merge the 3D model, but also scale adjustment, join surface production, and render image necessary for the actual measurement of relics. The final completed drawing was tracked by the CAD program, which is also an open-source software. In archaeological research, photogrammetry is very applicable to various processes, including excavation, writing reports, and research on numerical data from 3D models. With the breakthrough development of computer vision, the types of open-source software have been diversified and the performance has significantly improved. With the high accessibility to such digital technology, the acquisition of 3D model data in archaeology will be used as basic data for preservation and active research of cultural heritage.
The purpose of this study is to quantitatively and empirically investigate whether cartoon-realism, which is referred to as a guideline for avoiding the uncanny valley phenomenon, is actually effective. An experiment was carried out to investigate whether or not methods that try to realistically express the texture of human skin while making 3D models whose outward appearance abstract like a cartoon actually reduce the negative sentiments associated with the uncanny valley phenomenon. The results found that when human skin textures were applied to cartoon-type 3D models, the degree of eeriness significantly increased (p<0.05), while there was no change in the degree of human likeness. When cartoon-style skin textures were applied to human-type 3D models, there was no significant difference in the degree of eeriness, but the degree of human likeness significantly decreased (p<0.05). These results show that, cartoon realism is not actually effective, and rather creates a perceptual conflict and induces the uncanny valley phenomenon. The results of this study are expected to be used as quantitative and empirical data for developing design guidelines that will overcome the uncanny valley phenomenon in the future.
Chemical Exchange Saturation Transfer (CEST) imaging is a method to detect solutes based on the chemical exchange of mobile protons with water. The solute protons exchange with three different patterns, which are fast, slow, and intermediate rates. The CEST contrast can be obtained from the exchangeable protons, which are hydroxyl protons, amine protons, and amide protons. The CEST MR imaging is useful to evaluate tumors, strokes, and other diseases. The purpose of this study is to review the mathematical model for CEST imaging and for measurement of the chemical exchange rate, and to measure the chemical exchange rate using a 3T MRI system on several amino acids. We reviewed the mathematical models for the proton exchange. Several physical models are proposed to demonstrate a two-pool, three-pool, and four-pool models. The CEST signals are also evaluated by taking account of the exchange rate, pH and the saturation efficiency. Although researchers have used most commonly in the calculation of CEST asymmetry, a quantitative analysis is also developed by using Lorentzian fitting. The chemical exchange rate was measured in the phantoms made of asparagine (Asn), glutamate (Glu), ${\gamma}-aminobutyric$ acid (GABA), glycine (Gly), and myoinositol (MI). The experiment was performed at a 3T human MRI system with three different acidity conditions (pH 5.6, 6.2, and 7.4) at a concentration of 50 mM. To identify the chemical exchange rate, the "lsqcurvefit" built-in function in MATLAB was used to fit the pseudo-first exchange rate model. The pseudo-first exchange rate of Asn and Gly was increased with decreasing acidity. In the case of GABA, the largest result was observed at pH 6.2. For Glu, the results at pH 5.6 and 6.2 did not show a significant difference, and the results at pH 7.4 were almost zero. For MI, there was no significant difference at pH 5.6 or 7.4, however, the results at pH 6.2 were smaller than at the other pH values. For the experiment at 3T, we were only able to apply 1 s as the maximum saturation duration due to the limitations of the MRI system. The measurement of the chemical exchange rate was limited in a clinical 3T MRI system because of a hardware limitation.
Three dimensional quantitative structure-activity relationships (3D-QSARs) for the fungicidal activities against Rhizoctonia solani (RS) and Phytophthora capsici (PC) by N-phenyl substituents(X) of N-phenylthionocarbamate derivatives were studied quantitatively using comparative molecular field analysis (CoMFA) methodology based on different alignment approaches. Statistical quality of CoMFA models with field fit alignment were slightly higher than that of atom based fit alignment. The optimized CoMFA models (RS: RF2 & PC: PF2) were derived from field fit alignment and combination of CoMFA fields. And the statistical results of the two models showed the best predictability of the fungicidal activities based on the cross-validated value $q^2$ ($r^2_{cv.}$ =RS: 0.557 & PC: 0.676) and non-cross-validated value ($r^2_{ncv.}$ =RS: 0.954 & PC: 0.968), respectively. The selective fungicidal activities between two fungi were dependence upon the electrostatic field of substrate molecule. Therefore, the fungicidal activities from CoMFA contour maps showed that the fungicidal activity will be able to increased according to the modification of X-substituents on the substrate molecules.
The purpose of this study was to analyze chemistry textbooks and teachers' guidebooks from the perspective of 'Ignorance', one of the important features of model. This is because the emphasis is on developing modeling capabilities for students in the 2015 Revised Curriculum. For this, Arrhenius model and Brønsted-Lowry model were selected as acid and base models in neutralization reaction which are important contents in chemistry curriculum. The analysis criteria of this study were extracted by analyzing previous studies and four general chemistry textbooks dealing with 'Ignorance' related to acid and base neutralization reaction. Based on the analysis criteria, we analyzed nine chemistry I textbooks and teacher's guides and six chemistry II textbooks and teacher's guides of the 2015 revised curriculum. In addition, we analyzed contents of four chemistry I textbooks and teacher's guides and three chemistry II textbooks and teacher's guides in the 2009 revised curriculum for comparison according to revised curriculums. We analyzed the contents related to the concept of 'neutralization reaction', 'neutrality', 'quantitative relation of neutralization reaction', 'degree of ionization', and 'ionization constant'. Based on the results of this study, we proposed a way to present 'Ignorance' of the models in teachers' guidebooks that chemistry teachers can understand 'Ignorance' of model and teach modeling capabilities for students.
It is used water quality data that was measured at Pyeongchanggang real time monitoring stations in Namhan river. These characteristics were analyzed with the water qualify of rainy and nonrainy periods. TOC (Total Organic Carbon) data of rainy periods has correlation with discharge and shows high values of mean, maximum, and standard deviation. DO (Dissolved Oxygen) value of rainy periods is lower than those of nonrainy periods. Input data of the water quality forecasting models that they were constructed by neural network and neuro-fuzzy was chosen as the reasonable data, and water qualify forecasting models were applied. LMNN, MDNN, and ANFIS models have achieved the highest overall accuracy of TOC data. LMNN (Levenberg-Marquardt Neural Network) and MDNN (MoDular Neural Network) model which are applied for DO forecasting shows better results than ANFIS (Adaptive Neuro-Fuzzy Inference System). MDNN model shows the lowest estimation error when using daily time, which is qualitative data trained with quantitative data. The observation of discharge and water quality are effective at same point as well as same time for real time management. But there are some of real time water quality monitoring stations far from the T/M water stage. Pyeongchanggang station is one of them. So discharge on Pyeongchanggang station was calculated by developed runoff neural network model, and the water quality forecasting model is linked to the runoff forecasting model. That linked model shows the improvement of waterquality forecasting.
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