• Asian Pacific Journal of Cancer Prevention
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• v.14 no.2
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• pp.923-927
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• 2013

Objective: This work aims to investigate the therapeutic regimen of brain metastatic cancers and the relationship between clinical features and prognosis. Methods: Clinical data of 184 patients with brain metastatic cancers were collected and analysed for the relationship between survival time and age, gender, primary diseases, quantity of brain metastatic foci, their position, extra cranial lesions, and therapeutic regimens. Results: The average age of onset was 59.1 years old. The median survival time (MST) was 15.0 months, and the patients with breast cancer as the primary disease had the longest survival time. Females had a longer survival time than males. Patients with meningeal metastasis had extremely short survival time. Those with less than 3 brain metastatic foci survived longer than patients with more than 3. The MST of patients receiving radiotherapy only and the patients receiving chemotherapy only were all 10.0 months while the MST of patients receiving combination therapy was 16.0 months. Multiple COX regression analysis demonstrated that gender, primary diseases, and quantity of brain metastatic foci were independent prognostic factors for brain metastatic cancers. Conclusions: Chemotherapy is as important as radiotherapy in the treatment of brain metastatic cancer. Combination therapy is the best treatment mode. Male gender, brain metastatic cancers originating in the gastrointestinal tract, more than 3 metastatic foci, and involvement of meninges indicate a worse prognosis.

• Journal of Neurogastroenterology and Motility
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• v.24 no.4
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• pp.512-527
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• 2018

This review provides a comprehensive overview of brain imaging studies of the brain-gut interaction in functional gastrointestinal disorders (FGIDs). Functional neuroimaging studies during gut stimulation have shown enhanced brain responses in regions related to sensory processing of the homeostatic condition of the gut (homeostatic afferent) and responses to salience stimuli (salience network), as well as increased and decreased brain activity in the emotional response areas and reduced activation in areas associated with the top-down modulation of visceral afferent signals. Altered central regulation of the endocrine and autonomic nervous responses, the key mediators of the brain-gut axis, has been demonstrated. Studies using resting-state functional magnetic resonance imaging reported abnormal local and global connectivity in the areas related to pain processing and the default mode network (a physiological baseline of brain activity at rest associated with self-awareness and memory) in FGIDs. Structural imaging with brain morphometry and diffusion imaging demonstrated altered gray- and white-matter structures in areas that also showed changes in functional imaging studies, although this requires replication. Molecular imaging by magnetic resonance spectroscopy and positron emission tomography in FGIDs remains relatively sparse. Progress using analytical methods such as machine learning algorithms may shift neuroimaging studies from brain mapping to predicting clinical outcomes. Because several factors contribute to the pathophysiology of FGIDs and because its population is quite heterogeneous, a new model is needed in future studies to assess the importance of the factors and brain functions that are responsible for an optimal homeostatic state.

• English Language & Literature Teaching
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• no.5
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• pp.103-122
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• 1999

In this paper, I will argue that in teaching L2, it is important to take a holistic teaching method considering various learning styles of the learners and the nature of L2 learning. Under the situation that most of the school education is centered on the left brain activity, learners with the right brain preference tend to get only to the lower proficiency than they really can. To prove this, I conducted a experiment on two classes of high school students. I decided the hemispheric preference of each students using HMI (hemispheric mode indicator) Then I compared the hemispheric preferences of students with their scores in English tests. The students with right hemispheric preference show significantly lower scores than the ones with left preference. It is implied that the current English education should adapted to address various learning and cognitive styles and whole-brain L2 teaching method should replace the left-centered instruction in the learning environment.

• Journal of Biomedical Engineering Research
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• v.32 no.4
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• pp.295-304
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• 2011

In this study, we evaluated the EEG based BCI algorithm using common spatial pattern to find realistic applicability using neurofeedback EEG based BCI algorithm - EEG mode, feature vector calculation, the number of selected channels, 3 types of classifier, window size is evaluated for 10 subjects. The experimental results have been evaluated depending on conditioned experiment whether neurofeedback is used or not In case of using neurofeedback, a few subjects presented exceptional but general tendency presented the performance improvement Through this study, we found a motivation of development for the specific classifier based BCI system and the assessment evaluation system. We proposed a need for an optimized algorithm applicable to the robust motor imagery evaluation system with more useful functionalities.

• Journal of Magnetics
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• v.16 no.3
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• pp.246-252
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• 2011

A high-voltage power supply has been built for activation of the brain via stimulation using a Full Wave Cockroft-Walton Circuit (FWCW). A resonant half-bridge inverter was applied (with half plus/half minus DC voltage) through a bidirectional power transistor to a magnetic stimulation device with the capability of producing a variety of pulse forms. The energy obtained from the previous stage runs the transformer and FW-CW, and the current pulse coming from the pulse-forming circuit is transmitted to a stimulation coil device. In addition, the residual energy in each circuit will again generate stimulation pulses through the transformer. In particular, the bidirectional device modifies the control mode of the stimulation coil to which the current that exceeds the rated current is applied, consequently controlling the output voltage as a constant current mode. Since a serial resonant half-bridge has less switching loss and is able to reduce parasitic capacitance, a device, which can simultaneously change the charging voltage of the energy-storage condenser and the pulse repetition rate, could be implemented. Image processing of the brain activity was implemented using a graphical user interface (GUI) through a data mining technique (data mining) after measuring the vital signs separated from the frequencies of EEG and ECG spectra obtained from the pulse stimulation using a 90S8535 chip (AMTEL Corporation).

• The Korean Journal of Nuclear Medicine Technology
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• v.23 no.1
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• pp.69-74
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• 2019

Purpose $^{18}F$-FDOPA using amino acid is particularly attractive for imaging of brain tumors because of the high uptake in tumor tissue and the low uptake in normal brain tissue. But, on the other hand, $^{18}F$-FDG is highly uptake in both tumor tissue and normal brain tissue. The purpose of study is to evaluate comparison of contrasts in $^{18}F$-FDOPA Brain PET/CT and $^{18}F$-FDG Brain PET/CT and to find out optimal scan time by analysis of variation in SUV with the passage of uptake time. Materials and Methods A region of interest of approximately $350mm^2$ at the center of the tumor and cerebellum in 12 patients ($51.4{\pm}12.8yrs$) who $^{18}F$-FDG Brain PET/CT and $^{18}F$-FDOPA Brain PET/CT were examined more than once each. The $SUV_{max}$ was measured, and the $SUV_{max}$ ratio (T/C ratio) of the tumor cerebellum was calculated. In the analysis of SUV, T/C ratio was calculated for each frame after dividing into 15 frames of 2 minutes each using List mode data in 25 patients ($49.{\pm}10.3yrs$). SPSS 21 was used to compare T/C ratio of $^{18}F$-FDOPA and T/C ratio of $^{18}F$-FDG. Results The T/C ratio of $^{18}F$-FDOPA Brain PET/CT was higher than the T/C ratio of $^{18}F$-FDG Brain, and show a significant difference according to a paired t-test(t=-5.214, p=0.000). As a result of analyzing changes in $SUV_{max}$ and T/C ratio, the peak point of $SUV_{max}$ was $5.6{\pm}2.9$ and appeared in the fourth frame (6 to 8 minutes), and the peak of T/C ratio also appeared in the fourth frame (6 to 8 minutes). Taking this into consideration and comparing the existing 10 to 30 minutes image and 6 to 26 minutes image, the $SUV_{max}$ and T/C ratio increased by 0.2 and 0.1 each, compared to the 10 to 30 minutes image for 6 to 26 minutes image. Conclusion From this study, $^{18}F$-FDOPA Brain PET/CT is effective when reading the image, because the T/C ratio of $^{18}F$-FDOPA Brain PET/CT was higher than T/C ratio of $^{18}F$-FDG Brain PET/CT. In addition, in the case of $^{18}F$-FDOPA Brain PET/CT, there was no difference between the existing 10 to 30 minutes image and 6 to 26 minutes image. Through continuous research, we can find possibility of shortening examination time in $^{18}F$-FDOPA Brain PET/CT. Also, we can help physician to accurate reading using additional scan data.

• Bulletin of the Korean Chemical Society
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• v.32 no.6
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• pp.2015-2020
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• 2011

A series of isoxazol-indolin-2-one was designed for GSK-3${\beta}$ inhibitors as novel anticancer agents based on their binding mode analysis in GSK-3${\beta}$ crystal structure. Total 21 compounds were synthesized and evaluated for their inhibitory activity against two tumor cell lines (DU145 and HT29). Most of the synthesized compounds were potent with above 80% inhibitory activity at 100 ${\mu}M$, and several compounds were examined for inhibitory activity against GSK-3${\beta}$. Among them, 15(Z) ($R_1$=H, $R_2$=3-Cl-phenyl) was most active with 78% inhibition of tumor cell line (HT29) at 20 ${\mu}M$ and 72% inhibition of GSK-3${\beta}$ at 20 ${\mu}M$.

• Korean Journal of Biological Psychiatry
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• v.24 no.2
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• pp.68-74
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• 2017

Objectives It is well known that problem drinking is associated with alterations of brain structures and functions. Brain functions related to alcohol consumption can be determined by the resting state functional connectivity in various resting state networks (RSNs). This study aims to ascertain the alcohol effect on the structures forming predetermined RSNs by assessing their cortical thickness. Methods Twenty-six abstinent male patients with alcohol dependence and the same number of age-matched healthy control were recruited from an inpatient mental hospital and community. All participants underwent a 3T MRI scan. Averaged cortical thickness of areas constituting 7 RSNs were determined by using FreeSurfer with Yeo atlas derived from cortical parcellation estimated by intrinsic functional connectivity. Results There were significant group differences of mean cortical thicknesses (Cohen's d, corrected p) in ventral attention (1.01, < 0.01), dorsal attention (0.93, 0.01), somatomotor (0.90, 0.01), and visual (0.88, 0.02) networks. We could not find significant group differences in the default mode network. There were also significant group differences of gray matter volumes corrected by head size across the all networks. However, there were no group differences of surface area in each network. Conclusions There are differences in degree and pattern of structural recovery after abstinence across areas forming RSNs. Considering the previous observation that group differences of functional connectivity were significant only in networks related to task-positive networks such as dorsal attention and cognitive control networks, we can explain recovery pattern of cognition and emotion related to the default mode network and the mechanisms for craving and relapse associated with task-positive networks.

• Journal of Korean Academy of Nursing
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• v.52 no.1
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• pp.36-51
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• 2022

Purpose: The purpose of this study was to examine the effects of electroencephalogram (EEG) biofeedback training for emotion regulation and brain homeostasis on anxiety about COVID-19 infection, impulsivity, anger rumination, meta-mood, and self-regulation ability of late adolescents in the prolonged COVID-19 pandemic situation. Methods: A non-equivalent control group pretest-posttest design was used. The participants included 55 late adolescents in the experimental and control groups. The variables were evaluated using quantitative EEG at pre-post time points in the experimental group. The experimental groups received 10 sessions using the three-band protocol for five weeks. The collected data were analyzed using the Shapiro-Wilk test, Wilcoxon rank sum test, Wilcoxon signed-rank test, t-test and paired t-test using the SAS 9.3 program. The collected EEG data used a frequency series power spectrum analysis method through fast Fourier transform. Results: Significant differences in emotion regulation between the two groups were observed in the anxiety about COVID-19 infection (W = 585.50, p = .002), mood repair of meta-mood (W = 889.50, p = .024), self-regulation ability (t = - 5.02, p < .001), self-regulation mode (t = - 4.74, p < .001), and volitional inhibition mode (t = - 2.61, p = .012). Neurofeedback training for brain homeostasis was effected on enhanced sensory-motor rhythm (S = 177.00, p < .001) and inhibited theta (S = - 166.00, p < .001). Conclusion: The results demonstrate the potential of EEG biofeedback training as an independent nursing intervention that can markedly improve anxiety, mood-repair, and self-regulation ability for emotional distress during the COVID-19 pandemic.

• Journal of KIISE
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• v.41 no.12
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• pp.1050-1057
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• 2014

Electroencephalogram (EEG)-based brain-computer interfaces (BCI) can be used for a number of purposes in a variety of industries, such as to replace body parts like hands and feet or to improve user convenience. In this paper, we propose a method to decompose and extract motor imagery EEG signal using Empirical Mode Decomposition (EMD) and Fast Fourier Transforms (FFT). The EEG signal classification consists of the following three steps. First, during signal decomposition, the EMD is used to generate Intrinsic Mode Functions (IMFs) from the EEG signal. Then during feature extraction, the power spectral density (PSD) is used to identify the frequency band of the IMFs generated. The FFT is used to extract the features for motor imagery from an IMF that includes mu rhythm. Finally, during classification, the Support Vector Machine (SVM) is used to classify the features of the motor imagery EEG signal. 10-fold cross-validation was then used to estimate the generalization capability of the given classifier., and the results show that the proposed method has an accuracy of 84.50% which is higher than that of other methods.