• Clinical and Experimental Reproductive Medicine
• /
• v.28 no.3
• /
• pp.199-207
• /
• 2001

Objective: The present study was undertaken to examine the effects of magnesium ion in the culture medium on the development of mouse fertilized oocytes either before or after pronuclear formation, and to investigate whether the effect of magnesium ion is related with the redistributional change of mitochondria. Methods : Fertilized oocytes obtained from the oviducts of mice at 15 hr after hCG injection before pronuclear formation (pre-PN) or 21 hr after hCG injection after pronuclear formation (post-PN) were used. The embryos were cultured for 3 days with basic T6 medium-magnesium free and various concentrations of magnesium ion, 0.0, 0.5, 1.0, 2.0, 4.0 or 8.0 mM, respectively. After culture, the developmental stages of embryos and the number of nuclei were evaluated. To observe the effects of magnesium ion on the mitochondrial distribution, fertilized oocytes were collected at 21 hr after hCG injection and cultured for 6 hr with various concentration of magnesium ion. As a control, fertilized oocytes with pronuclei at 27 hr after hCG injection were used. Results: The concentration of magnesium ion to accelerate the in vitro development of mouse fertilized oocytes appeared to be at 2.0 mM for the pre-PN and the post-PN stage embryos. In the mitochondrial redistribution patterns, the embryos cultured in 2.0 mM concentration of magnesium ion showed the highest percentage (22.6%) of distinct perinuclear clustering pattern comparing to other experimental group. Conclusion: The effect of magnesium ion may be related to the cytoplasmic redistribution of mitochondria. This relationship seems to connect the developmental competence of preimplantation mouse embryos in vitro. These results can suggest that higher concentration of magnesium ion (2.0 mM) than those of conventional culture medium ($0.2{\sim}1.2\;mM$) is more suitable for in vitro culture of preimplantation mouse embryos.

• Investigative Magnetic Resonance Imaging
• /
• v.3 no.2
• /
• pp.179-187
• /
• 1999

Purpose : This paper introduces a computationally inexpensive context-dependent classification of multi-echo MRI with Bayes compound decision model. In order to produce accurate region segmentation especially in homogeneous area and along boundaries of the regions, we propose a classification method that uses contextual information of local enighborhood system in the image. Material and Methods : The performance of the context free classifier over a statistically heterogeneous image can be improved if the local stationary regions in the image are disassociated from each other through the mechanism of the interaction parameters defined at he local neighborhood level. In order to improve the classification accuracy, we use the contextual information which resolves ambiguities in the class assignment of a pattern based on the labels of the neighboring patterns in classifying the image. Since the data immediately surrounding a given pixel is intimately associated with this given pixel., then if the true nature of the surrounding pixel is known this can be used to extract the true nature of the given pixel. The proposed context-dependent compound decision model uses the compound Bayes decision rule with the contextual information. As for the contextual information in the model, the directional transition probabilities estimated from the local neighborhood system are used for the interaction parameters. Results : The context-dependent classification paradigm with compound Bayesian model for multi-echo MR images is developed. Compared to context free classification which does not consider contextual information, context-dependent classifier show improved classification results especially in homogeneous and along boundaries of regions since contextual information is used during the classification. Conclusion : We introduce a new paradigm to classify multi-echo MRI using clustering analysis and Bayesian compound decision model to improve the classification results.

• Journal of Gifted/Talented Education
• /
• v.21 no.3
• /
• pp.773-796
• /
• 2011

This study examined the thinking styles of scientifically gifted students on the basis of Sternberg's theory of mental self-government, and the relationship between thinking styles and self-regulated learning ability of the students and their scientific inquiry ability by the different types of thinking styles. 110 middle school students who belonging to the university science-gifted education center participated in this study. 13 thinking styles were postulated that fall along 5 dimensions which are functions, forms, levels, scopes and leanings of the mental self-government. Scientifically gifted students responded to the Thinking Style Inventory (TSI) that standardized Korean version, Self-regulated Ability Inventory and Test of Science Inquiry Skills Inventory (TSIS). The results indicated that scientifically gifted students prefer legislative, liberal, external, hierarchical and judical thinking styles, rather than conservative style. This result also showed that subscales of thinking styles were significantly correlated with self-regulated learning ability and scientific inquiry ability. The legislative style, hierarchical style, local style and liberal style were significant predictors of self-regulation learning ability. The legislative style was significant predictor, whereas oligarchic style was negative predictor of scientific inquiry ability. The results of k-means clustering analysis and MANOVA showed that the self-regulated learning ability and scientific inquiry ability were significantly correlated with the pattern and level of thinking style.

• Journal of Microbiology and Biotechnology
• /
• v.28 no.2
• /
• pp.199-209
• /
• 2018

Volatile organic compounds (VOCs) are increasingly been recognized as the chemical mediators of mold interactions, shaping their community dynamics, growth, and metabolism. Herein, we selectively examined the time-correlated (0 D-11 D, where D = incubation days) effects of intraspecies VOC-mediated interactions (VMI) on Aspergillus oryzae KCCM 60345 (S1), following co-cultivation with partner strain A. oryzae KACC 44967 (S2), in a specially designed twin plate assembly. The comparative evaluation of $S1_{VMI}$ (S1 subjected to VMI with S2) and its control ($S1_{Con}$) showed a notable disparity in their radial growth ($S1_{VMI}$ < $S1_{Con}$) at 5 D, protease activity ($S1_{VMI}$ > $S1_{Con}$) at 3-5 D, amylase activity ($S1_{VMI}$ < $S1_{Con}$) at 3-5 D, and antioxidant levels ($S1_{VMI}$ > $S1_{Con}$) at 3 D. Furthermore, we observed a distinct clustering pattern for gas chromatography-time of flight-mass spectrometry datasets from 5 D extracts of $S1_{VMI}$ and $S1_{Con}$ in principle component analysis (PC1: 30.85%; PC2: 10.31%) and partial least squares discriminant analysis (PLS-DA) (PLS1: 30.77; PLS2: 10.15%). Overall, 43 significantly discriminant metabolites were determined for engendering the metabolic variance based on the PLS-DA model (VIP > 0.7, p < 0.05). In general, a marked disparity in the relative abundance of amino acids ($S1_{VMI}$ > $S1_{Con}$) at 5 D, organic acids ($S1_{VMI}$ > $S1_{Con}$) at 5 D, and kojic acid ($S1_{VMI}$ < $S1_{Con}$) at 5-7 D were observed. Examining the headspace VOCs shared between S1 and S2 in the twin plate for 5 D incubated samples, we observed the relatively higher abundance of C-8 VOCs (1-octen-3-ol, (5Z)-octa-1,5-dien-3-ol, 3-octanone, 1-octen-3-ol acetate) having known semiochemical functions. The present study potentially illuminates the effects of VMI on commercially important A. oryzae's growth and biochemical phenotypes with subtle details of altered metabolomes.

• Journal of KIISE:Software and Applications
• /
• v.36 no.10
• /
• pp.836-850
• /
• 2009

Human posture recognition has attracted tremendous attention in ubiquitous environment, performing arts and robot control so that, recently, many researchers in pattern recognition and computer vision are working to make efficient posture recognition system. However the most of existing studies is very sensitive to human variations such as the rotation or the translation of body. This is why the feature, which is extracted from the feature extraction part as the first step of general posture recognition system, is influenced by these variations. To alleviate these human variations and improve the posture recognition result, this paper presents 3D Star Skeleton and Principle Component Analysis (PCA) based feature extraction methods in the multi-view environment. The proposed system use the 8 projection maps, a kind of depth map, as an input data. And the projection maps are extracted from the visual hull generation process. Though these data, the system constructs 3D Star Skeleton and extracts the rotation invariant feature using PCA. In experimental result, we extract the feature from the 3D Star Skeleton and recognize the human posture using the feature. Finally we prove that the proposed method is robust to human variations.

• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.3
• /
• pp.1149-1154
• /
• 2014

Background: In Malaysia, data from the Malaysian Health Ministry showed colorectal cancer (CRC) to be the second most common type of cancer in 2007-2009, after breast cancer. The same was apparent after looking at males and females cases separately. In the present study, the Geographic Information System (GIS) was employed to describe the distribution of CRC cases in Kuala Lumpur (KL), Malaysia, according to socio-demographic factors (age, gender, ethnicity and district). Materials and Methods: This retrospective review concerned data for patients diagnosed with colorectal cancer in the years 1995 to 2011 collected from the Wilayah Persekutuan Health Office, taken from the cancer notification form (NCR-2), and patient medical records from the Surgical Department, Universiti Kebangsaan Malaysia Medical Centre (UKMMC). A total of 146 cases were analyzed. All the data collected were analysed using ArcGIS version 10.0 and SPSS version 19.0. Results: Patients aged 60 to 69 years accounted for the highest proportion of cases (34.2%) and males slightly predominated 76 (52.1%), Chinese had the highest number of registered cases at 108 (74.0%) and staging revealed most cases in the 3rd and 4th stages. Kernel density analysis showed more cases are concentrated up in the northern area of Petaling and Kuala Lumpur subdistricts. Spatial global pattern analysis by average nearest neighbour resulted in nearest neighbour ratio of 0.75, with Z-score of -5.59, p value of <0.01 and the z-score of -5.59. Spatial autocorrelation (Moran's I) showed clustering significant with p<0.01, Z score 3.14 and Moran's Index of 0.007. When mapping clusters with hotspot analysis (Getis-Ord Gi), hot and cold spots were identified. Hot spot areas fell on the northeast side of KL. Conclusions: This study demonstrated significant spatial patterns of cancer incidence in KL. Knowledge about these spatial patterns can provide useful information to policymakers in the planning of screening of CRC in the targeted population and improvement of healthcare facilities to provide better treatment for CRC patients.

• Korean Journal of Ecology and Environment
• /
• v.46 no.4
• /
• pp.581-587
• /
• 2013

The amounts of carbon (C), nitrogen (N) and phosphorus (P) in relation to dry weight (D.W.) were measured in zooplankton from the large four rivers (Han R., Geum R., Yeongsan R. and Seomjin R.) during 2004~2008. The stoichiometry of total zooplankton in four river systems was highly variable. The ranges of average C, N and P-contents were $70{\sim}620mgC\;mg^{-1}$ D.W., $7.1{\sim}85.5{\mu}gN\;mg^{-1}$ D.W. and $2.5{\sim}7.4{\mu}gP\;mg^{-1}$ D.W., respectively. The mean C :N: P atomic ratios reflected large spatial differences. The C : P and N : P ratios of the zooplankton community ranged from 38 to 392 : 1 and from 4 to 65 : 1 in all sampling sites. Self-Organizing Map (SOM) was applied to the survey data, and the study sites were clearly classified into 3 clusters. Clustering was largely affected by the distribution pattern of C, N, P-contents, which is related with characteristics of river systems on the basis of stoichiometry.

• Korean Journal of Plant Resources
• /
• v.29 no.5
• /
• pp.555-563
• /
• 2016

The morphological characteristics and genetic relationships among 32 germplasms of Zanthoxylum schinifolium and Zanthoxylum piperitum collected from two farms in Korea were investigated. The traits with the most variability were seed color, leaf size, and spine size. The intraspecific polymorphism of Z. schinifolium and Z. piperitum was 96.5% and 60.3%, respectively. The genetic diversity and Shannon’s information index values ranged from 0.11 to 0.33 and 0.19 to 0.50, with average values of 0.26 and 0.42, respectively. Two ISSR primers (UBC861 and UBC862) were able to distinguish the different species. The genetic similarity matrix (GSM) revealed variability among the accessions ranging from 0.116 to 0.816. The intraspecific GSM for Z. schinifolium and Z. piperitum was 0.177-0.780 and 0.250-0.816, respectively. The GSM findings indicate that Z. schinifolium and Z. piperitum accessions have high genetic diversity and possess germplasms qualifying as good genetic resources for cross breeding. The clustering analysis separated Z. schinifolium and Z. piperitum into independent groups, and all accessions could be classified into three categories. Z. Schinifolium var. nermis belonged to independent groups. Comparison of the clusters based on morphological analysis with those based on ISSR data resulted in an unclear pattern of division among the accessions. The study findings indicate that Z. schinifolium and Z. piperitum accessions have genetic diversity, and ISSR markers were useful for identifying Z. schinifolium and Z. piperitum.

• Molecular & Cellular Toxicology
• /
• v.3 no.3
• /
• pp.190-194
• /
• 2007

Gastric adenocarcinoma (GA) is a major tumor type of gastric cancers and subdivides into several different tumors such as papillary, tubular mucinous, signet-ring cell and adenosquamous carcinoma according to histopatholigical determination. In other hand, GA is also subdivided into intestinal and diffuse type of adenocarcinoma by the Lauren?fs classification. In this study, we have examined differential gene expression pattern analysis of three histologically different GAs of 24 samples by using DNA microarray containing approximately 19000 genetic elements. The hierarchical clustering analysis of 24 gastric adenocarcinomas (12 of intestinal type, 7 of diffuse type and 5 of mixed type) resulted in two major subgroup on dendrogram, and two subgroups included most of intestinal and diffused type of GAs respectively. Supervised analysis of 19 intestinal and diffuse type GAs by using Wilcoxon rank T-test (P<0.01) resulted in 100 outlier genes which exactly separated intestinal and diffuse type of GA by differential gene expression. In conclusion, genome-wide analysis of gene expression of GAs suggested that GAs may subclassify as intestinal and diffused type of GA by their characteristic molecular expression. Our results also provide large-scale genetic elements which reflect molecular differences of intestinal and diffuse type of GAs, and this may facilitate to understand different molecular carcinogenesis of gastric cancer.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.26 no.1
• /
• pp.56-63
• /
• 2016

In this study, we introduce a design of Fuzzy RBFNNs-based digit recognition system using the incremental-PCA in order to recognize the handwritten digits. The Principal Component Analysis (PCA) is a widely-adopted dimensional reduction algorithm, but it needs high computing overhead for feature extraction in case of using high dimensional images or a large amount of training data. To alleviate such problem, the incremental-PCA is proposed for the computationally efficient processing as well as the incremental learning of high dimensional data in the feature extraction stage. The architecture of Fuzzy Radial Basis Function Neural Networks (RBFNN) consists of three functional modules such as condition, conclusion, and inference part. In the condition part, the input space is partitioned with the use of fuzzy clustering realized by means of the Fuzzy C-Means (FCM) algorithm. Also, it is used instead of gaussian function to consider the characteristic of input data. In the conclusion part, connection weights are used as the extended diverse types in polynomial expression such as constant, linear, quadratic and modified quadratic. Experimental results conducted on the benchmarking MNIST handwritten digit database demonstrate the effectiveness and efficiency of the proposed digit recognition system when compared with other studies.