• Journal of Medicine and Life Science
• /
• v.15 no.2
• /
• pp.46-50
• /
• 2018

Cancer, a leading mortality disease following cardiovascular disease worldwide, has high incidence as one out of every four adults in Korea. It was known to be caused by several reasons including somatic mutation, activation of oncogene and chromosome aneuploidy. Cancer cells show a faster growth rate and have metastatic and heterogeneous cell populations compared to normal cells. Cancer stem cells, the most invested field in cancer biology, is a theory to explain heterogeneous cell populations of cancer cells among several characteristics of cancer cells, which is providing the theoretical background for incidence of cancer and treatment failure by drug resistance. Cancer stem cells initially explain heterogeneous cell populations of cancer cells based on the same markers of normal stem cells in cancer, in which only cancer stem cells showed heterogeneity of cancer cells and tumor initiating ability of leukemia. Based on these results, cancer stem cells were reported in various solid cancers such as breast cancer, liver cancer, and lung cancer. Breast cancer stem cells were first reported in solid cancer which had tumor initiating ability and further identified as anti-cancer drug resistance. There were several identification methods in breast cancer stem cells such as specific surface markers and culture methods. The discovery of cancer stem cells not only explains heterogeneity of cancer cells, but it also provides theoretical background for targeting cancer stem cells to complete elimination of cancer cells. Many institutes have been developing new anticancer drugs targeting cancer stem cells, but there have not been noticeable results yet. Many researchers also reported a necessity for improvement of current concepts and methods of research on cancer stem cells. Herein, we discuss the limitations and the perspectives of breast cancer stem cells based on the current concept and history.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.57 no.6
• /
• pp.1058-1062
• /
• 2008

In clinical decision support system(CDSS), unlike rule-based expert method, appropriate data-driven machine learning method can easily provide the information of individual feature(clinical test) for disease classification. However, currently developed methods focus on the improvement of the classification accuracy for diagnosis. With the analysis of feature importance in classification, one may infer the novel clinical test sets which highly differentiate the specific diseases or disease states. In this background, we introduce a novel CDSS that integrate a classifier and feature selection module together. Random forest algorithm is applied for the classifier and the feature importance measure. The system selects the significant clinical tests discriminating the diseases by examining the classification error during backward elimination of the features. The superior performance of random forest algorithm in clinical classification was assessed against artificial neural network and decision tree algorithm by using breast cancer, diabetes and heart disease data in UCI Machine Learning Repository. The test with the same data sets shows that the proposed system can successfully select the significant clinical test set for each disease.

• Korean Journal of Veterinary Research
• /
• v.29 no.3
• /
• pp.407-416
• /
• 1989

The prospect of live vaccines consisting of genetically modified vaccinia virus expressing foreign genes is exciting, but important issues concerning safety and efficacy need to resolved. Vaccinia virus (VV) is an efficient expression vector with broad host range infectivity and large DNA capacity. This vector has been particularly useful for identifying target antigens for humoral and cell-mediated immunity. The WHO smallpox eradication program, involving the extensive use of VV vaccines, resulted in the late 1970s in the elimination of one of the world's most feared diseases. This achievement is a triumph for preventive medicine and for international collaboration in public health. In 1980, WHO recommended that the routine use of smallpox vaccine should be stopped. Against this background, the prospect of li ve vaccines consisting of genetically modified VV expressing foreign antigens arising from the work of Moss, and Paoletti and their colleagues in 1982 has been greeted with enthusiasm. These investigators have shown that genes coding for immunogenic proteins can be inserted into VV DNA without impairing the ability of the virus to grow in cell culture. Moreover experimental animals infected with VV recombinants containing genes coding for a variety of immunizing proteins have been shown to be protected against challenge infection with the corresponding infectious agent. In this communication, I describe current progress in the construction of a novel plasmid vector that facilitate the insertion and expression of foreign genes in VV as well as the selection of recombinants.

• Journal of Electrical Engineering and Technology
• /
• v.8 no.5
• /
• pp.1188-1193
• /
• 2013

In content based image retrieval (CBIR) system, the images are represented based upon its feature such as color, texture, shape, and spatial relationship etc. In this paper, we propose a MRI Image Retrieval using wavelet transform with mahalanobis distance measurement. Wavelet transformation can also be easily extended to 2-D (image) or 3-D (volume) data by successively applying 1-D transformation on different dimensions. The proposed algorithm has tested using wavelet transform and performance analysis have done with HH and $H^*$ elimination methods. The retrieval image is the relevance between a query image and any database image, the relevance similarity is ranked according to the closest similar measures computed by the mahalanobis distance measurement. An adaptive similarity synthesis approach based on a linear combination of individual feature level similarities are analyzed and presented in this paper. The feature weights are calculated by considering both the precision and recall rate of the top retrieved relevant images as predicted by our enhanced technique. Hence, to produce effective results the weights are dynamically updated for robust searching process. The experimental results show that the proposed algorithm is easily identifies target object and reduces the influence of background in the image and thus improves the performance of MRI image retrieval.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.13 no.3
• /
• pp.237-245
• /
• 2008

Recently, multilevel H-bridge inverters have become popular in medium to high power ac drive applications. One of significant advantages of them is low harmonic contents in their input line currents thanks to the transformer with multiple phase-shifted secondary windings. This paper attempts to provide basic guidelines for the design of the phase shifting transformer windings and theoretical analysis of input line current harmonics of H-bridge inverters. The part II is devoted to the analysis of the harmonic characteristics of the input line current, providing mathematical background for the equidistant phase-shifting angle distribution policy for harmonic elimination.

• Progress in Superconductivity
• /
• v.4 no.1
• /
• pp.53-58
• /
• 2002

Noise from electronic instrumentation is invariably present in biomedical signals, although the art of instrumentation design is such that this noise source may be negligible. And sometimes signals of interest are contaminated or degraded by signals of similar type from another source. Biomedical signals are omni-presently contaminated by these background noises that span nearly all frequency bandwidths. In the magneto-cardiogram (MCG), several digital filters have been designed for the elimination of the power-line interference, broadband white noise, surrounding magnetic noise, and baseline wondering. In addition to the introduced FIR filter, notch, adaptive filter using the least mean square (LMS) algorithm, and recurrent neural network (RNN) filter, a new filtering method for effective noise canceling in MCG signals is proposed in this paper, which is realized by the wavelet packets. The experimental results show that the proposed filter using wavelet packet performs efficiently with respect to noise rejection. To verify this, two characteristics were analyzed and compared with LMS adaptive filter, SNR of filtered signal and attractor pattern using the nonlinear dynamics.

• 한국정보컨버전스학회:학술대회논문집
• /
• 2008.06a
• /
• pp.113-116
• /
• 2008

In this paper we suggest two novel methods for an implementation of the spot detection phase in the 2-DE gel image analysis program. The one is the adaptive thresholding method for eliminating noises and the other is the asymmetric diffusion model for spot matching. Remained noises after the preprocessing phase cause the over-segmentation problem by the next segmentation phase. To identify and exclude the over-segmented background regions, il we use a fixed thresholding method that is choosing an intensity value for the threshold, the spots that are invisible by one's human eyes but mean very small amount proteins which have important role in the biological samples could be eliminated. Accordingly we suggest the adaptive thresholding method which comes from an idea that is got on statistical analysis for the prominences of the peaks. There are the Gaussian model and the diffusion model for the spot shape model. The diffusion model is the closer to the real spot shapes than the Gaussian model, but spots have very various and irregular shapes and especially asymmetric formation in x-coordinate and y-coordinate. The reason for irregularity of spot shape is that spots could not be diffused perfectly across gel medium because of the characteristics of 2-DE process. Accordingly we suggest the asymmetric diffusion model for modeling spot shapes. In this paper we present a brief explanation ol the two methods and experimental results.

• Journal of Digital Contents Society
• /
• v.14 no.1
• /
• pp.117-124
• /
• 2013

This paper suggests the robust method of extraction for moving objects in illumination variation by using image sequence from an immovable camera. The most difficult part of the implication is the effect by illumination and noise. The object area is hardly estimated when the dusky area occurs in illumination variation by time change. This thesis describes the extraction of moving objects employed by Gaussian mixture model which is noise robust measure. Also, the report suggests the elimination method of illumination part in input image by the representative illumination image which is defined to minimize the illumination influence.

• Proceedings of the Korean Vacuum Society Conference
• /
• 2013.08a
• /
• pp.152-152
• /
• 2013

Mechanism of energy conversion from chemical to electrical during exothermic catalytic reactions at the metal surfaces has been a fascinating and crucial subject in heterogeneous catalysis. A metal-semiconductor Schottky nanodiode is novel device for direct detection of chemically induced hot electrons which have sufficient energy to surmount the Schottky barrier. We measured a continuous chemicurrent during the hydrogen oxidation under of 760 Torr of O2 and 6 Torr of H2 by using Pt/Si and Pt/TiO2 nanodiodes at reaction temperatures and compared the chemicurrent with the reaction turnover rate. The thermoelectric current was measured by carrying out an experiment under O2 condition for elimination of the background current. Gas chromatograph and source meter were used for measurement of the chemical turnover rate and the chemicurrent, respectively. The correlation between the chemicurrent and the chemical turnover rate under hydrogen oxidation implies how hot electrons generated on the metal surface affect hydrogen oxidation.

• Nuclear Medicine and Molecular Imaging
• /
• v.40 no.2
• /
• pp.74-81
• /
• 2006

Molecular targeting may be defined as the specific concentration of a diagnostic or therapeutic tracer by its Interaction with a molecular species that is distinctly present or absent in a disease state. Monoclonal antibody (mAb) is one of the successful agents for targeted therapy in cancer. To enhance the therapeutic effect, the concept of targeting radionuclides to tumors using radiolabeled mAbs against tumor-associated antigens, radioimmunotherapy, was proposed. The efficacy of radioimmunotherapy, however, has to be further optimized. Several strategies to improve targeting of tumors with radiolabeled mAbs have been developed, such as the use of mAb fragments, the use of high-affinity mAbs, the use of labeling techniques that are stable in vivo, active removal of the radiolabeled mAb from the circulation, and pretargeting strategies. Until now, however, there are many kinds of obstacles to be solved in the use of mAb for the targeted therapy. Major technical challenges to molecular targeting are related to the rapid and specific delivery of tracers to the target, the elimination of unwanted background activity, and the development of more specific targets to create a cytocidal effect. further development of this field will be determined by success in solving these challenges.