• KSBB Journal
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• v.14 no.5
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• pp.593-599
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• 1999

In this study, optimal conditions to infect CD34 positive cells containing hematopoietic stem cells obtained from cord blood and bone marrow were found using two different retroviral vectors expressing human growth hormone (hGH) and $\beta$-galactosidase. CD34 positive cells were successfully infected with recombinant retroviruses only when the CD34 positive cells were co-cultured with packaging cells secreting recombinant retroviruses. To find the highest infection efficiency for the gene transfer, CD34 positive cells from cord blood were co-cultured with packaging cells secreting recombinant retroviruses encoding E. coli lacZ gene. The highest infection efficiency was obtained when CD34 positive cells were cultured for 3 days, and then co-culturing was done for another 2 days. When CD34 positive cells from bone marrow were co-cultured with packaging cells secreting recombinant retroviruses encoding hGH gene, the maximum amount of hGH was also secreted at the same conditions found above, i.e. 3 days of culture and 2 days of co-culture. These results show that there are optimal conditions for the gene transfer into hematopoietic stem cells regardless of sources of target cells or retroviral vectors used to infect.

• The Journal of the Acoustical Society of Korea
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• v.20 no.4
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• pp.35-41
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• 2001

This paper describes Linear Discriminant Analysis and common vector extraction for speech recognition. Voice signal contains psychological and physiological properties of the speaker as well as dialect differences, acoustical environment effects, and phase differences. For these reasons, the same word spelled out by different speakers can be very different heard. This property of speech signal make it very difficult to extract common properties in the same speech class (word or phoneme). Linear algebra method like BT (Karhunen-Loeve Transformation) is generally used for common properties extraction In the speech signals, but common vector extraction which is suggested by M. Bilginer et at. is used in this paper. The method of M. Bilginer et al. extracts the optimized common vector from the speech signals used for training. And it has 100％ recognition accuracy in the trained data which is used for common vector extraction. In spite of these characteristics, the method has some drawback-we cannot use numbers of speech signal for training and the discriminant information among common vectors is not defined. This paper suggests advanced method which can reduce error rate by maximizing the discriminant information among common vectors. And novel method to normalize the size of common vector also added. The result shows improved performance of algorithm and better recognition accuracy of 2％ than conventional method.

• Tuberculosis and Respiratory Diseases
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• v.50 no.1
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• pp.52-66
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• 2001

Background : NF-${\kappa}B$ is the most important transcriptional factor in IL-8 gene expression. Triptolide is a new compound that recently has been shown to inhibit NF-${\kappa}B$ activation. The purpose of this study is to investigate how triptolide inhibits NF-${\kappa}B$-dependent IL-8 gene transcription in lung epithelial cells and to pilot the potential for the clinical application of triptolide in inflammatory lung diseases. Methods : A549 cells were used and triptolide was provided from Pharmagenesis Company (Palo Alto, CA). In order to examine NF-${\kappa}B$-dependent IL-8 transcriptional activity, we established stable A549 IL-8-NF-${\kappa}B$-luc. cells and performed luciferase assays. IL-8 gene expression was measured by RT-PCR and ELISA. A Western blot was done for the study of $I{\kappa}B{\alpha}$ degradation and an electromobility shift assay was done to analyze NF-${\kappa}B$ DNA binding. p65 specific transactivation was analyzed by a cotransfection study using a Gal4-p65 fusion protein expression system. To investigate the involvement of transcriptional coactivators, we perfomed a transfection study with CBP and SRC-1 expression vectors. Results : We observed that triptolide significantly suppresses NF-${\kappa}B$-dependent IL-8 transcriptional activity induced by IL-$1{\beta}$ and PMA. RT-PCR showed that triptolide represses both IL-$1{\beta}$ and PMA-induced IL-8 mRNA expression and ELISA confirmed this triptolide-mediated IL-8 suppression at the protein level. However, triptolide did not affect $I{\kappa}B{\alpha}$ degradation and NF-$_{\kappa}B$ DNA binding. In a p65-specific transactivation study, triptolide significantly suppressed Gal4-p65T Al and Gal4-p65T A2 activity suggesting that triptolide inhibits NF-${\kappa}B$ activation by inhibiting p65 transactivation. However, this triptolide-mediated inhibition of p65 transactivation was not rescued by the overexpression of CBP or SRC-1, thereby excluding the role of transcriptional coactivators. Conclusions : Triptolide is a new compound that inhibits NF-${\kappa}B$-dependent IL-8 transcriptional activation by inhibiting p65 transactivation, but not by an $I{\kappa}B{\alpha}$-dependent mechanism. This suggests that triptolide may have a therapeutic potential for inflammatory lung diseases.

• Near Infrared Analysis
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• v.2 no.1
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• pp.59-66
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• 2001

Nowadays, medical diagnostics is efficiently supported by clinical chemistry and near infrared spectroscopy is becoming a new dimension, which has shown high potential to provide valuable information for diagnosis. The investigation was carried out to study the influence of mammary gland inflammation, called mastitis, on cow´s milk spectra and milk composition measured by near infrared spectroscopy (NIRS). Milk somatic cell counts (SCC) in milk were used as a measure of mammary gland inflammation. Naturally occurred variations with milk composition within lactation and in the process of milking were included in the experimental design of this study. Time series of unhomogenized, raw milk spectral data were collected from 3 cow along morning and evening milking, for 5 consecutive months, within their second lactation. In the time of the trial, the investigated cows had periods with mammary gland inflammation. Transmittance spectra of 258 milk samples were obtained by NIRSystem 6500 spectrophotometer in 1100-2400 nm region. Calibration equations for the examined milk components were developed by PLS regression using 3 different sets of samples: samples with low somatic cell count (SCC), samples with high SCC and combined data set. The NIR calibration and prediction of individual cow´s milk fat, protein, and lactose were highly influenced by the presence of mil samples from animals with mammary gland inflammation in the data set. The best accuracy of prediction (i.e. the lower SEP and the higher correlation coefficient) for fat, protein and lactose was obtained for equations, developed when using only “healthy” samples, with low SCC. The standard error of prediction increased and correlation coefficient decreased significantly when equations for low SCC milk were used to predict examined components in “mastitis” samples with high SCC, and vice versa. Combined data set that included samples from healthy and mastitis animals could be used to build up regression models for screening. Further use of separate model for healthy samples improved milk composition measurement. Regression vectors for NIR mild protein measurement obtained for “healthy” and “mastitic” group were compared and revealed differences in 1390-1450 nm, 1500-1740 nm and 1900-2200 nm regions and thus illustrated post-secretory breakdown of milk proteins by hydrolytic enzymes that occurred with mastitis. For the first time it has been found that monitoring the spectral differences in water bands at 1440 nm and 1912 nm could provide valuable information for inflammation diagnosis.

• IMMUNE NETWORK
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• v.5 no.2
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• pp.89-98
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• 2005

Background: DNA vaccination represents an anticipated approach for the control of numerous infectious diseases. Used alone, however, DNA vaccine is weak immunogen inferior to viral vectors. In recent, heterologous prime-boost vaccination leads DNA vaccines to practical reality. Methods: We assessed prime-boost immunization strategies with a DNA vaccine (minigene, $gB_{498-505}$ DNA) and recombinant vaccinia virus $(vvgB_{498-505})$ expressing epitope $gB_{498-505}$ (SSIEF ARL) of CD8+ T cells specific for glycoprotein B (gB) of herpes simplex virus (HSV). Animals were immunized primarily with $gB_{498-505}$ epitope-expressing DNA vaccine/recombinant vaccinia virus and boosted with alternative vaccine type expressing entire Ag. Results: In prime-boost protocols using vvgBw (recombinant vaccinia virus expressing entire Ag) and $vvgB_{498-505}$, CD8+ T cell-mediated immunity was induced maximally at both acute and memory stages if primed with vvgBw and boosted with $vvgB_{498-505}$ as evaluated by CTL activity, intracellular IFN-staining, and MHC class I tetramer staining. Similarly $gB_{498-505}$ DNA prime-gBw DNA (DNA vaccine expressing entire Ag) boost immunization elicited the strongest CD8+ T cell responses in protocols based on DNA vaccine. However, the level of CD8+ T cell-mediated immunity induced with prime-boost vaccination using DNA vaccine expressing epitope or entire Ag was inferior to those based on vvgBw and $vvgB_{498-505}$. Of particular interest CD8+ T cell-mediated immunity was optimally induced when $vvgB_{498-505}$ was used to prime and gB DNA was used as alternative boost. Especially CD7+ T cell responses induced by such protocol was longer lasted than other protocols. Conclusion: These facts direct to search for the effective strategy to induce optimal CD8+ T cell-mediated immunity against cancer and viral infection.

• The KIPS Transactions:PartB
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• v.11B no.1
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• pp.27-34
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• 2004

This paper proposes a method to trace and interpret a moving object based on the information which can be directly obtained from MPEG-2 compressed video stream without decoding process. In the proposed method, the motion flow is constructed from the motion vectors included in compressed video. We calculate the amount of pan, tilt, and zoom associated with camera operations using generalized Hough transform. The local object motion can be extracted from the motion flow after the compensation with the parameters related to the global camera motion. Initially, a moving object to be traced is designated by user via bounding box. After then automatic tracking Is performed based on the accumulated motion flows according to the area contributions. Also, in order to reduce the cumulative tracking error, the object area is reshaped in the first I-frame of a GOP by matching the DCT coefficients. The proposed method can improve the computation speed because the information can be directly obtained from the MPEG-2 compressed video, but the object boundary is limited by macro-blocks rather than pixels. Also, the proposed method is proper for approximate object tracking rather than accurate tracing of an object because of limited information available in the compressed video data.

• Korean Journal of Poultry Science
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• v.35 no.3
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• pp.241-245
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• 2008

Lentiviral vector system is efficient vehicles for the delivery of exogenous genes, and it is generally used in the generation of transgenic chickens. In this study, we used recombinant lentiviral vectors to generate transgenic chicks that express the human superoxide dismutase-3 gene driven by the chicken ovalbumin promoter. It is well known that superoxide dismutases(SODs) are believed to play a crucial role in protecting cells against oxygen toxicity. There are three forms of SOD proteins: cytosolic Cu-Zn SOD, mitochondrial Mn SOD, and extracellular SOD(SOD-3). The recombinant lentivirus containing the human SOD-3 gene was injected into the subgerminal cavity of freshly laid eggs. Subsequently, the embryos were incubated to hatch using phases II and III of the surrogate shell ex vivo culture system. From 341 injected embryos, the 78 chicks hatched after 21 days incubation. The hatched chicks were screened for the human SOD-3 gene by using PCR. Two of 47 male chickens that survived to sexual maturity contained the human SOD-3 gene in their semen. These results showed that our transgenic chicken generation system was completely established.

• Journal of Plant Biotechnology
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• v.32 no.4
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• pp.233-241
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• 2005

Plants have considerable advantages for the production of antigenic proteins because they provide an inexpensive source of protein and an easy administration of vaccine. Since a publication describing edible plant vaccine of HBsAg in 1992, a number of laboratories around the world have studied the use of plants as the bioreactor to produce antigenic proteins of human or animal pathogens. Over the last ten years, these works have been mainly focused on three major strategies for the production of antigenic proteins in plants: stable genetic transformation of either the nuclear or plastid genome, or transient expression in plants using viral vectors. As many antigenic proteins have been expressed in tobacco, also several laboratories have succeeded to express genes encoding antigenic proteins in other crop plants: potato, tomato, maize, carrot, soybean and spinach. At present many works for the production of edible plant vaccine against bacteria-mediated diseases have mostly performed the studies of enterotoxins and adhesion proteins. Also the development of new-type antigens (pili, flagella, surface protein, other enterotoxin and exotoxin etc.) is required for various targets and more efficacy to immunize against microorganism pathogens. Many works mostly studied in experimental animals had good results, and phase I clinical trial of LTB clearly indicated its immunogenic ability. On the other hand, edible plant vaccines have still problems remained to be solved. In addition to the accumulation of sufficient antigen in plants, human health, environment and agriculture regulation should be proven. Also oral tolerance, the physiological response to food antigens and commensal flora is the induction of a state of specific immunological unresponsiveness, needs to be addressed before plant-derived vaccine becomes a therapeutic option.

• Science of Emotion and Sensibility
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• v.15 no.4
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• pp.503-516
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• 2012

According to the researches of robot and software agent until now, computational emotion model is dependent on system, so it is hard task that emotion models is separated from existing systems and then recycled into new systems. Therefore, I introduce the Engine of computational Emotion model (shall hereafter appear as EE) to integrate with any robots or agents. This is the engine, ie a software for independent form from inputs and outputs, so the EE is Emotion Generation to control only generation and processing of emotions without both phases of Inputs(Perception) and Outputs(Expression). The EE can be interfaced with any inputs and outputs, and produce emotions from not only emotion itself but also personality and emotions of person. In addition, the EE can be existed in any robot or agent by a kind of software library, or be used as a separate system to communicate. In EE, emotions is the Primary Emotions, ie Joy, Surprise, Disgust, Fear, Sadness, and Anger. It is vector that consist of string and coefficient about emotion, and EE receives this vectors from input interface and then sends its to output interface. In EE, each emotions are connected to lists of emotional experiences, and the lists consisted of string and coefficient of each emotional experiences are used to generate and process emotional states. The emotional experiences are consisted of emotion vocabulary understanding various emotional experiences of human. This study EE is available to use to make interaction products to response the appropriate reaction of human emotions. The significance of the study is on development of a system to induce that person feel that product has your sympathy. Therefore, the EE can help give an efficient service of emotional sympathy to products of HRI, HCI area.

• Asian-Australasian Journal of Animal Sciences
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• v.14 no.6
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• pp.880-884
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• 2001

Rumen microbiology research has undergone several evolutionary steps: the isolation and nutritional characterization of readily cultivated microbes; followed by the cloning and sequence analysis of individual genes relevant to key digestive processes; through to the use of small subunit ribosomal RNA (SSU rRNA) sequences for a cultivation-independent examination of microbial diversity. Our knowledge of rumen microbiology has expanded as a result, but the translation of this information into productive alterations of ruminal function has been rather limited. For instance, the cloning and characterization of cellulase genes in Escherichia coli has yielded some valuable information about this complex enzyme system in ruminal bacteria. SSU rRNA analyses have also confirmed that a considerable amount of the microbial diversity in the rumen is not represented in existing culture collections. However, we still have little idea of whether the key, and potentially rate-limiting, gene products and (or) microbial interactions have been identified. Technologies allowing high throughput nucleotide and protein sequence analysis have led to the emergence of two new fields of investigation, genomics and proteomics. Both disciplines can be further subdivided into functional and comparative lines of investigation. The massive accumulation of microbial DNA and protein sequence data, including complete genome sequences, is revolutionizing the way we examine microbial physiology and diversity. We describe here some examples of our use of genomics- and proteomics-based methods, to analyze the cellulase system of Ruminococcus flavefaciens FD-1 and explore the genome of Ruminococcus albus 8. At Illinois, we are using bacterial artificial chromosome (BAC) vectors to create libraries containing large (>75 kbases), contiguous segments of DNA from R. flavefaciens FD-1. Considering that every bacterium is not a candidate for whole genome sequencing, BAC libraries offer an attractive, alternative method to perform physical and functional analyses of a bacterium's genome. Our first plan is to use these BAC clones to determine whether or not cellulases and accessory genes in R. flavefaciens exist in clusters of orthologous genes (COGs). Proteomics is also being used to complement the BAC library/DNA sequencing approach. Proteins differentially expressed in response to carbon source are being identified by 2-D SDS-PAGE, followed by in-gel-digests and peptide mass mapping by MALDI-TOF Mass Spectrometry, as well as peptide sequencing by Edman degradation. At Ohio State, we have used a combination of functional proteomics, mutational analysis and differential display RT-PCR to obtain evidence suggesting that in addition to a cellulosome-like mechanism, R. albus 8 possesses other mechanisms for adhesion to plant surfaces. Genome walking on either side of these differentially expressed transcripts has also resulted in two interesting observations: i) a relatively large number of genes with no matches in the current databases and; ii) the identification of genes with a high level of sequence identity to those identified, until now, in the archaebacteria. Genomics and proteomics will also accelerate our understanding of microbial interactions, and allow a greater degree of in situ analyses in the future. The challenge is to utilize genomics and proteomics to improve our fundamental understanding of microbial physiology, diversity and ecology, and overcome constraints to ruminal function.