• BMB Reports
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• v.43 no.8
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• pp.513-523
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• 2010

Cytokines that bind to and signal through the gp130 co-receptor subunit include interleukin (IL)-6, IL-11, oncostatin M (OSM), leukemia inhibitory factor (LIF), cardiotrophin-1 (CT-1), and ciliary neutrophic factor (CNTF). Apart from contributing to inflammation, gp130 signalling cytokines also function in the maintenance of bone homeostasis. Expression of each of these cytokines and their ligand-specific receptors is observed in bone and joint cells, and bone-active hormones and inflammatory cytokines regulate their expression. gp130 signalling cytokines have been shown to regulate the differentiation and activity of osteoblasts, osteoclasts and chondrocytes. Furthermore, cytokine and receptor specific gene-knockout mouse models have identified distinct roles for each of these cytokines in regulating bone resorption, bone formation and bone growth. This review will discuss the current models of paracrine and endocrine actions of gp130-signalling cytokines in bone remodelling and growth, as well as their impact in pathologic bone remodelling evident in periodontal disease, rheumatoid arthritis, spondylarthropathies and osteoarthritis.

• Reproductive and Developmental Biology
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• v.37 no.1
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• pp.41-49
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• 2013

Ovarian cancer is the most lethal world-wide gynecological disease among women due to the lack of molecular biomarkers to diagnose the disease at an early stage. In addition, there are few well established relevant animal models for research on human ovarian cancer. For instance, rodent models have been established through highly specialized genetic manipulations, but they are not an excellent model for human ovarian cancer because histological features are not comparable to those of women, mice have a low incidence of tumorigenesis, and they experience a protracted period of tumor development. However, the laying hen is a unique and highly relevant animal model for research on human ovarian cancer because they spontaneously develop epithelial cell-derived ovarian cancer (EOC) as occurs in women. Our research group has identified common histological and physiological aspects of ovarian tumors from women and laying hens, and we have provided evidence for several potential biomarkers to detect, monitor and target for treatment of human ovarian cancers based on the use of both genetic and epigenetic factors. Therefore, this review focuses on ovarian cancer of laying hens and relevant regulatory mechanisms, based on genetic and epigenetic aspects of the disease in order to provide new information and to highlight the advantages of the laying hen model for research in ovarian carcinogenesis.

• Journal of The Korean Society of Inherited Metabolic disease
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• v.5 no.1
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• pp.116-125
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• 2005

Orthotopic liver transplantation is the treatment of choice for inherited metabolic diseases. However, the supply of donor organs is limiting and therefore many patients cannot benefit from this therapy. In contrast, hepatocytes can be isolated from a single donor liver. They can be transplanted into several recipients, and this procedure may help overcome the shortage of donor livers. A great deal of work with animal models indicates that hepatocytes transplanted into the liver or spleen can survive, function, and participate in the normal regenerative process. Recent clinical studies suggest that hepatocyte transplantation may be useful for bridging patients to whole organ transplantation and for providing metabolic support during liver failure and for replacing whole organ transplantation in certain inherited metabolic diseases. Nowadays, hepatocytes from various stem cells have been regarded as an another cell source for treatment of inherited metabolic diseases. Although cell therapy using stem cells for inherited metabolic disease patient has been accepted only as an experimental trial yet, hepatocytes from stem cells can solve a lot of obstacles in the treatment of inherited metabolic diseases.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.10
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• pp.229-238
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• 2021

The article applies the ECM - ARDL model to examine the relationship between economic indicators and the existence of the disease in the long run of 10 ASEAN countries from 2000 to 2019. There are two models: The first model investigates the impact of GDP per capita, net inflow FDI, unemployment rate, and inflation rate on the proportion of export to GDP of ASEAN countries, the second model is similar to the first one but adds one more variable to the independent variable list - 'the variable for disease'. The results prove the long-run effect of GDP per capita, FDI, unemployment and inflation rate on export of the selected countries, though individual country shows differences in the sign and magnitude of these impacts. Surprisingly, the number of people suffering from disease does not affect the export of all selected countries as expected. The results of the two models also indicate that the disequilibrium in the short run converges to the equilibrium in the long run with a high proportion, especially in the case of Cambodia and the Philippines, with the rate of 95.65% and 151.94%, respectively. The findings can be useful for policymakers in promulgating efficient policies to enhance the trading activities of the selected countries.

• Journal of Applied Biological Chemistry
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• v.61 no.4
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• pp.341-349
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• 2018

The aim of this study was to evaluate autophagy-enhancing and neuroprotective effects of Wonji-Gobon mixture (WGM), a traditional Chinese prescription medication, in Parkinson's disease (PD) mouse models. Our investigation found that WGM increased the expression of both Beclin1 and LC3b-II proteins as measured with western blot in the BV2 cell line; both proteins play a role in autophagy. WGM also increased the autophagy expression as measured by fluorescence-activated cell-sorting analysis in the BV2 cell line. In 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine-induced PD models, WGM significantly increased the amount of dopamine in a striatum-substantia nigra suspension, produced notable results in the forced swim test, and increased serotonin as measured by high-performance liquid chromatography analysis; these results are indicative of neuroprotective effects. In summary, our findings indicate that WGM treatment has neuroprotective effects that are partially mediated by autophagy enhancement.

• Smart Media Journal
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• v.12 no.3
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• pp.30-37
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• 2023

Alzheimer's disease (AD) symptoms are being treated by early diagnosis, where we can only slow the symptoms and research is still undergoing. In consideration, using T1-weighted images several classification models are proposed in Machine learning to identify AD. In this paper, we consider the improvised feature selection, to reduce the complexity by using wrapping techniques and Restricted Boltzmann Machine (RBM). This present work used the subcortical and cortical features of 278 subjects from the ADNI dataset to identify AD and sMRI. Multi-class classification is used for the experiment i.e., AD, EMCI, LMCI, HC. The proposed feature selection consists of Forward feature selection, Backward feature selection, and Combined PCA & RBM. Forward and backward feature selection methods use an iterative method starting being no features in the forward feature selection and backward feature selection with all features included in the technique. PCA is used to reduce the dimensions and RBM is used to select the best feature without interpreting the features. We have compared the three models with PCA to analysis. The following experiment shows that combined PCA &RBM, and backward feature selection give the best accuracy with respective classification model RF i.e., 88.65, 88.56% respectively.

• Korean Journal of Biological Psychiatry
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• v.30 no.1
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• pp.24-30
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• 2023

Objectives Alzheimer's disease (AD) is the most common form of dementia in older adults, damaging the brain and resulting in impaired memory, thinking, and behavior. The identification of differentially expressed genes and related pathways among affected brain regions can provide more information on the mechanisms of AD. The aim of our study was to identify differentially expressed genes associated with AD and combined biomarkers among them to improve AD risk prediction accuracy. Methods Machine learning methods were used to compare the performance of the identified combined biomarkers. In this study, three publicly available gene expression datasets from the hippocampal brain region were used. Results We detected 31 significant common genes from two different microarray datasets using the limma package. Some of them belonged to 11 biological pathways. Combined biomarkers were identified in two microarray datasets and were evaluated in a different dataset. The performance of the predictive models using the combined biomarkers was superior to those of models using a single gene. When two genes were combined, the most predictive gene set in the evaluation dataset was ATR and PRKCB when linear discriminant analysis was applied. Conclusions Combined biomarkers showed good performance in predicting the risk of AD. The constructed predictive nomogram using combined biomarkers could easily be used by clinicians to identify high-risk individuals so that more efficient trials could be designed to reduce the incidence of AD.

• Korean Journal of Veterinary Research
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• v.32 no.3
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• pp.377-380
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• 1992

The value of the cell enzyme-linked immunosorbent assay as a possible replacement for the indirect immunofluorescence antibody test for the estimation of antibodies against BD virus was assessed in four animal models. The serum antibody response was measured by both assay systems;the variability of both tests was less than one diluent step, and correlation of the two tests was assessed using regression analysis. The study showed that the all four animal models gave satisfactory correlation of CELISA and IFA. There, CELISA is acceptable for use in mouse, rabbit, chicken and rat models.

• Journal of the Korean Data and Information Science Society
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• v.26 no.5
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• pp.1087-1095
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• 2015

Influenza, commonly known as "the flu", is an infectious disease caused by the influenza virus. We consider, in this paper, regression models as a prediction model of influenza disease. While most of previous researches use mainly the meteorological variables as a predictive variables, we consider social media information in the models. As a result, we found that the contributions of two-type of informations are comparable. We used the medical treatment data of influenza provided by Natioal Health Insurance Survice (NHIS) and the meteorological data provided by Korea Meteorological Administration (KMA). We collect social media information (twitter buzz amount) from Twitter. Time series model is also considered for comparison.

• BMB Reports
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• v.57 no.1
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• pp.50-59
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• 2024

The application of gene engineering in livestock is necessary for various reasons, such as increasing productivity and producing disease resistance and biomedicine models. Overall, gene engineering provides benefits to the agricultural and research aspects, and humans. In particular, productivity can be increased by producing livestock with enhanced growth and improved feed conversion efficiency. In addition, the application of the disease resistance models prevents the spread of infectious diseases, which reduces the need for treatment, such as the use of antibiotics; consequently, it promotes the overall health of the herd and reduces unexpected economic losses. The application of biomedicine could be a valuable tool for understanding specific livestock diseases and improving human welfare through the development and testing of new vaccines, research on human physiology, such as human metabolism or immune response, and research and development of xenotransplantation models. Gene engineering technology has been evolving, from random, time-consuming, and laborious methods to specific, time-saving, convenient, and stable methods. This paper reviews the overall trend of genetic engineering technologies development and their application for efficient production of genetically engineered livestock, and provides examples of technologies approved by the United States (US) Food and Drug Administration (FDA) for application in humans.