• Journal of Gastric Cancer
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• v.14 no.2
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• pp.67-86
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• 2014

Gastric cancer is one of the most common cancers in the world. Animal models have been used to elucidate the details of the molecular mechanisms of various cancers. However, most inbred strains of mice have resistance to gastric carcinogenesis. Helicobacter infection and carcinogen treatment have been used to establish mouse models that exhibit phenotypes similar to those of human gastric cancer. A large number of transgenic and knockout mouse models of gastric cancer have been developed using genetic engineering. A combination of carcinogens and gene manipulation has been applied to facilitate development of advanced gastric cancer; however, it is rare for mouse models of gastric cancer to show aggressive, metastatic phenotypes required for preclinical studies. Here, we review current mouse models of gastric carcinogenesis and provide our perspectives on future developments in this field.

• Korean Journal of Biological Psychiatry
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• v.3 no.2
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• pp.211-215
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• 1996

The present study investigated the associations between CT measures and obstetric complications and family history of major mental illnesses. We had the hypothesis of diosthesis-stress model in the etiology of schizophrenia. We had the following findings. 1) Family history of major mental illnesses is inversely related to obstetric complications. 2) Prefrontal sulcal widening and family history of schizophrenia. are inversely related. 3) In female but not in male patients those with family history of schizophrenia tended to have less prefrontal sulcal widening and ventricular brain ratio. These results suggest that more genetic factors contribute to structural brain abnormalities in female than in male patients.

• Journal of Environmental Science International
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• v.26 no.4
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• pp.521-527
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• 2017

Solar radiation forecasts are important for predicting the amount of ice on road and the potential solar energy. In an attempt to improve solar radiation predictability in Jeju, we conducted machine learning with various data mining techniques such as tree models, conditional inference tree, random forest, support vector machines and logistic regression. To validate machine learning models, the results from the simulation was compared with the solar radiation data observed over Jeju observation site. According to the model assesment, it can be seen that the solar radiation prediction using random forest is the most effective method. The error rate proposed by random forest data mining is 17%.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.1427-1428
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• 2015

MEMS(Micro Electro-mechanical System) are getting attention as promising industry in the 21st century. Car air bags, acceleration sensors, and medical, information appliances are being actively applied in MEMS. This paper suggest the electrical electrodes of brain signal applied MEMS model and the prototype design for EEG signal amplification circuit. Also, we suggest an independent BCI(Brain Computer Interface) system with brain electrical signal of electrode models and wireless communication platform.

• The Journal of Korean Medicine
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• v.23 no.4
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• pp.91-97
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• 2002

Objective: This study was conducted to know the survival probability of the patients with cerebrovascular disease. Method: 1,341 patients who were suspected of having cerebrovascular disease clinically were investigated by telephone and NHIC (National Health Insurance Corporation) data. Conclusion: 1. The study population was grouped as 'Negative Brain CT findings' (11.8%), 'Hemorrhage' (12.4%) and 'Infarction' (75.7%). 2. The survival probabilities calculated by the Life Table method were statistically significant among brain CT finding groups (P<0.01). 3. The mean survival time calculated by the Kaplan-Meier method were also statistically significant among brain CT finding groups (P<0.01). 4. The result of Cox regression model was that sex (OR=0.7), age (OR=1.07), diabetes mellitus (OR=1.38), and heart disease (OR=1.69) affected the survival of the patients with cerebrovascular disease.

• International Journal of Knowledge Content Development & Technology
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• v.3 no.1
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• pp.19-29
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• 2013

Insights from the recent wealth of popular books on neuroscience are offered to suggest a strengthening of theory in information science. Information theory has traditionally neglected the human dimension in favour of 'scientific' theory often derived from the Shannon-Weaver model. Neuroscientists argue in excitingly fresh ways from the evidence of case studies, non-intrusive experimentation and the measurements that can be obtained from technologies that include electroencephalography, positron emission tomography (PET), functional magnetic resonance imaging (fMRI), and magnetoencephalography (MEG). The way in which the findings of neuroscience intersect with ideas such as those of Kahneman on fast and slow thinking and Csikszentmihalyi on flow, is tentatively explored as lines of connection with information science. It is argued that the beginnings of a theoretical underpinning for current web-based information searching in relation to established information retrieval methods can be drawn from this.

• Molecules and Cells
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• v.45 no.2
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• pp.53-64
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• 2022

Three-dimensional cultures of human neural tissue/organlike structures in vitro can be achieved by mimicking the developmental processes occurring in vivo. Rapid progress in the field of neural organoids has fueled the hope (and hype) for improved understanding of brain development and functions, modeling of neural diseases, discovery of new drugs, and supply of surrogate sources of transplantation. In this short review, we summarize the state-of-the-art applications of this fascinating tool in various research fields and discuss the reality of the technique hoping that the current limitations will soon be overcome by the efforts of ingenious researchers.

• Annual Conference of KIPS
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• 2023.05a
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• pp.574-575
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• 2023

뇌종양은 인체에 발생하는 여러 종양 중 세 번째로 많이 나타난다. 뇌종양 환자 수는 지속해서 증가하고 있으며, 별도의 예방법이 존재하지 않아 빠른 진단 및 종양 종류에 따른 치료가 매우 중요하다. 현재 뇌종양 진료는 전문의가 전용 소프트웨어로 뇌 Magnetic Resonance Imaging(MRI) 이미지를 확대, 축소하여 자세히 살펴보면서 종양의 크기, 위치, 양성/악성 여부 등을 판단한다. 이 방식은 의사의 숙련도에 따라 진료 시간과 판독의 차이가 크고 오진 가능성이 있다. 본 논문은 뇌종양 종류별 MRI 이미지가 학습된 CNN 모델을 사용한 의사의 뇌종양 진단 시간 단축, 진단 정확도 향상을 통해 환자 치료의 효율성을 높이는 방안으로 Brain Tumor X를 제안한다.

• Proceedings of the KSAR Conference
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• 2002.06a
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• pp.19-19
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• 2002

This study was to examine whether the in vitro differentiated neural cells derived from human embryonic stem (hES, MB03) cells can be survived and expressed tyrosin hydroxylase(TH) in grafted normal or PD rat brain. To differentiate in vitro into neural cells, embryoid bodies (EB: for 5 days, without mitogen) were formed from hES cells, neural progenitor cells(neurosphere, for 7-10 days, 20 ng/㎖ of bFGF added N2 medium) were produced from EB, and then finally neurospheres were differentiated into mature neuron cells in N2 medium(without bFGF) for 2 weeks. In normal rat brain, neural progenitor cells or mature neuron cells (1×10/sup 7/ cells/㎖) were grafted to the striatum of normal rats. After 2 weeks, when the survival of grafted hES cells was examined by immunohistochemical analysis, the neural progenitor cell group indicated higher BrdU, NeuN＋, MAP2＋ and GFAP＋ than mature neuron cell group in grafted sites of normal rats. This result demonstrated that the in vivo differentiation of grafted hES cells be increased simultaneously in both of neuronal and glial cell type. Also, neural progenitor cell grafted normal rats expressed more TH pattern than mature neuron cells. Based on this data, as a preliminary test, when the neural progenitor cells were grafted into the striatum of 6-hydroxydopamine lesioned PD rats, we confirmed the cell survival (by double staining of Nissl and NeuN) and TH expression. This result suggested that in vitro differentiated neural progenitor cells derived from hES cells are more usable than mature neuron cells for the neural cell grafting in animal model and those grafted cells were survived and expressed TH in normal or PD rat brain.

• Science of Emotion and Sensibility
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• v.21 no.3
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• pp.83-102
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• 2018

The process model of emotion regulation suggests that cognitive reappraisal and expressive suppression engage at different time points in the regulation process. Although multiple brain regions and networks have been identified for each strategy, no articles have explored changes in network characteristics or network connectivity over time. The present study examined (a) the whole-brain network and six other resting-state networks, (b) their modularity and global efficiency, which is an index of the efficiency of information exchange across the network, (c) the degree and betweenness centrality for 160 brain regions to identify the hub nodes with the most control over the entire network, and (d) the intra-network and inter-network functional connectivity (FC). Such investigations were performed using a traditional large-scale FC analysis and a relatively recent sliding window correlation analysis. The results showed that the right inferior orbitofrontal cortex was the hub region of the whole-brain network for both strategies. The present findings of temporally altering functional activity of the networks revealed that the default mode network (DMN) activated at the early stage of reappraisal, followed by the task-positive networks (cingulo-opercular network and fronto-parietal network), emotion-processing networks (the cerebellar network and DMN), and sensorimotor network (SMN) that activated at the early stage of suppression, followed by the greater recruitment of task-positive networks and their functional connection with the emotional response-related networks (SMN and occipital network). This is the first study that provides neuroimaging evidence supporting the process model of emotion regulation by revealing the temporally varying network efficiency and intra- and inter-network functional connections of reappraisal and suppression.