• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.1
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• pp.138-142
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• 2010

Purpose: PTH (parathyroid hormone) level is a useful index for prediction of hypocalcemia after thyroidectomy. The fast results are required for an early diagnosis of hypocalcemia. In this study, we evaluated the PTH change according to incubation time, and investigated the usefulness of hypocalcemia diagnosis of PTH results in early incubation time. Materials and Methods: The subjects were 131 patients who had taken the PTH test from July to August in 2009. All experiments were used IRMA method. PTH value were evaluated with the correlation between precision (10 times repeat) and recovery rate and at 0.5, 3, 6 and $18{\pm}2$ (below overnight) hours following incubation time. Data analysis was investigated with relationship of the sensitivity, specificity, PPV (positive predictive value) and accuracy. Results: The correlation was time-dependent with levels reaching $R^2$=0.987 at 0.5 hours, $R^2$=0.993 at 3 hours and $R^2$=0.996 at 6 hours compare to overnight levels. The precision (%CV${\pm}$SD) were $15.92{\pm}15.54$ at 0.5 hours, $6.91{\pm}7.38$ at 3 hours, $4.30{\pm}4.69$ at 6 hours and $4.59{\pm}2.59$ at overnight. The recovery rate (%Mean${\pm}$SD) were $96.8{\pm}5.44$ at 0.5 hours, $102.6{\pm}4.35$ at 3 hours, $100.7{\pm}2.56$ at 6 hours and $102.2{\pm}5.98$ at overnight. When 15 pg/ml of overnight density was set up as criteria, we measured the sensitivity, specificity and PPV, accuracy at 0.5, 3, 6 hours. The sensitivity was shown to 97.5% at all times. The specificity was 96.0% at 0.5 hours, 100% at 3 hours and 92.3% at 6 hours for control, respectively. The PPV was 86.6% at 0.5 hours, 100% at 3 hours and 92.8% at 6 hours. The accuracy was shown to 84.7% at 0.5 hours, 97.5% at 3 hours and 90.6% at 6 hours. These data were accompanied by a corresponding PTH value of overnight incubation time, which significantly correlated with early time results. Conclusion: The values of PTH at 3 hours has favorable the rate of concordance of 94.1% and may be useful for prediction of hypocalcemia, and it responses to overnight incubation PTH values. Therefore, This method may be an attractive alternative to proper treatment to stop symptom revelation by giving a calcium agent to the patient.

• Journal of Life Science
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• v.24 no.12
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• pp.1339-1344
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• 2014

Inflammatory bowel disease is an immune disorder associated with chronic mucosal inflammation and severe ulceration in the gastrointestinal tract. Antibodies against proinflammatory cytokines, including TNF${\alpha}$, are currently used as promising therapeutic agents against the disease. Stabilization of the transcript is a crucial post-transcriptional process in the expression of proinflammatory cytokines. In the present study, we assessed the expression and histological distribution of the HuR protein, an important transcript stabilizer, in tissues from experimental animals and patients with Crohn's disease. The total and cytosolic levels of the HuR protein were enhanced in the intestinal epithelia from dextran sodium sulfate (DSS)-treated mice compared to those in control tissues from normal mice. Moreover, the expression of HuR was very high only in the mucosal and glandular epithelium, and the relative localization of the protein was sequestered in the lower parts of the villus during the DSS insult. The expression of HuR was significantly higher in mucosal lesions than in normal-looking areas. Consistent with the data from the animal model, the expression of HuR was confined to the mucosal and glandular epithelium. These results suggest that HuR may contribute to the post-transcriptional regulation of proinflammatory genes during early mucosal insults. More mechanistic investigations are warranted to determine the potential use of HuR as a predictive biomarker or a promising target against IBD.

• Clinical and Experimental Pediatrics
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• v.45 no.5
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• pp.654-658
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• 2002

Purpose : Endocrine and immune systems are connected and interdependent. Adrenal glands play an important role in this network and control the balance between serum levels of dehydroepiandrosterone sulfate(DHEAS) and cortisol. These steroids have an antagonistic effect on the T cell progression into Th1 and Th2 cells and on the induction of correlated interleukins. Therefore we evaluated the role of adrenal androgen and cortisol as immune modulators in Kawasaki disease( KD) with changes of T cell immunity. Methods : From April to August in 2001, we examined serum DHEAS and 24 hour urine free cortisol(F) before administration of immunoglobulin and steroids by radioimmunoassay in 14 KD patients. It's clinical severity was determined by Harada score and coronary lesion. Results : The age of the patient group ranged from 4 months to 4 years; its average age was 2.3 years. Three patients(21.4%) were below 1 year, 2(14.3%) between 1 and 2 years, 5(35.7%) between 2 and 3 years, 4(28.6%) between 3 and 4 years of age. Male to female ratio was 1:1.3. DHEAS was significantly decreased in patients($11.1{\pm}6.0{\mu}g/dL$) more than controls($81.6{\pm}13.3{\mu}g/dL$)(P<0.05). Twenty-four hour urine free cortisol was significantly increased in patients($36.9{\pm}21.9{\mu}g/dL$) more than controls($13.6{\pm}5.5{\mu}g/dL$)(P<0.05). Ratio of DHEAS/F was decreased remarkably in patients($0.33{\pm}0.20$) more than controls($6.65{\pm}2.56$)(P=0.016). There was no difference between ratio of DHEAS/F and Harada score, but its ratio was very low in patients with coronary aneurysm. Conclusion : These data demonstrate that there are changes of DHEAS and cortisol in acute stage of KD and the dis-equilibrium between two steroids may be relevant in the T cell immune response induction of Kawasaki disease. These changes support the use of DHEAS/F ratio as one of the predictive factors of coronary arteries complication.

• Sleep Medicine and Psychophysiology
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• v.21 no.1
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• pp.5-13
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• 2014

Objectives: Depression, sleep complaints and cognitive impairments are commonly observed in the elderly. Elderly subjects with depressive symptoms have been found to show both poor cognitive performances and sleep disturbances. However, the relationship between sleep complaints and cognitive dysfunction in elderly depression is not clear. The aim of this study is to identify the association between sleep disturbances and cognitive decline in late-life depression. Methods: A total of 282 elderly people who underwent nocturnal polysomnography in a sleep laboratory were enrolled in the study. The Korean version of the Neuropsychological Assessment Battery developed by the Consortium to Establish a Registry for Alzheimer's Disease (CERAD-K) was applied to evaluate cognitive function. Depressive symptoms were assessed with the geriatric depression scale (GDS) and subjective sleep quality was measured using the Pittsburg sleep quality index (PSQI). Results: The control group ($GDS{\leq}9$) when compared with mild ($10{\leq}GDS{\leq}16$) and severe ($17{\leq}GDS$) depression groups, had significantly different scores in the Trail making test part B (TMT-B), Benton visual retention test part A (BVRT-A), and Stroop color and word test (SCWT)(all tests p<0.05). The PSQI score, REM sleep duration, apnea-hypopnea index and oxygen desaturation index were significantly different across the three groups (all indices, p<0.05). A stepwise multiple regression model showed that educational level, age and GDS score were predictive for both TMT-B time (adjusted $R^2$=35.6%, p<0.001) and BVRT-A score (adjusted $R^2$=28.3%, p<0.001). SCWT score was predicted by educational level, age, apnea-hypopnea index (AHI) and GDS score (adjusted $R^2$=20.6%, p<0.001). Poor sleep quality and sleep structure alterations observed in depression did not have any significant effects on cognitive deterioration. Conclusion: Older adults with depressive symptoms showed mild sleep alterations and poor cognitive performances. However, we found no association between sleep disturbances (except sleep apnea) and cognitive difficulties in elderly subjects with depressive symptoms. It is possible that the impact of sleep disruptions on cognitive abilities was hindered by the confounding effect of age, education and depressive symptoms.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.39-57
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• 2012

Recently, due to the introduction of high-tech equipment in interactive exhibits, many people's attention has been concentrated on Interactive exhibits that can double the exhibition effect through the interaction with the audience. In addition, it is also possible to measure a variety of audience reaction in the interactive exhibition. Among various audience reactions, this research uses the change of the facial features that can be collected in an interactive exhibition space. This research develops an artificial neural network-based prediction model to predict the response of the audience by measuring the change of the facial features when the audience is given stimulation from the non-excited state. To present the emotion state of the audience, this research uses a Valence-Arousal model. So, this research suggests an overall framework composed of the following six steps. The first step is a step of collecting data for modeling. The data was collected from people participated in the 2012 Seoul DMC Culture Open, and the collected data was used for the experiments. The second step extracts 64 facial features from the collected data and compensates the facial feature values. The third step generates independent and dependent variables of an artificial neural network model. The fourth step extracts the independent variable that affects the dependent variable using the statistical technique. The fifth step builds an artificial neural network model and performs a learning process using train set and test set. Finally the last sixth step is to validate the prediction performance of artificial neural network model using the validation data set. The proposed model is compared with statistical predictive model to see whether it had better performance or not. As a result, although the data set in this experiment had much noise, the proposed model showed better results when the model was compared with multiple regression analysis model. If the prediction model of audience reaction was used in the real exhibition, it will be able to provide countermeasures and services appropriate to the audience's reaction viewing the exhibits. Specifically, if the arousal of audience about Exhibits is low, Action to increase arousal of the audience will be taken. For instance, we recommend the audience another preferred contents or using a light or sound to focus on these exhibits. In other words, when planning future exhibitions, planning the exhibition to satisfy various audience preferences would be possible. And it is expected to foster a personalized environment to concentrate on the exhibits. But, the proposed model in this research still shows the low prediction accuracy. The cause is in some parts as follows : First, the data covers diverse visitors of real exhibitions, so it was difficult to control the optimized experimental environment. So, the collected data has much noise, and it would results a lower accuracy. In further research, the data collection will be conducted in a more optimized experimental environment. The further research to increase the accuracy of the predictions of the model will be conducted. Second, using changes of facial expression only is thought to be not enough to extract audience emotions. If facial expression is combined with other responses, such as the sound, audience behavior, it would result a better result.

• Korean Journal of Psychosomatic Medicine
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• v.27 no.1
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• pp.42-49
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• 2019

Objectives : Living donor liver transplantation (LDLT) is a life-saving therapy for patients with terminal liver disease. Many studies have focused on recipients rather than donors. The aim of this study was to assess the emotional status and personality characteristics of LDLT donors. Methods : We evaluated 218 subjects (126 male, 92 female) who visited Daegu Catholic University Medical Center from August 2012 to July 2018. A retrospective review of their preoperative psychological evaluation was done. We investigated epidemiological data and the Minnesota Multiphasic Personality Inventory-2 questionnaire. Subanalysis was done depending on whether subjects actually underwent surgery, relationship with the recipient, and their gender. Results : Mean age of subjects was $32.19{\pm}10.91years$. 187 subjects received LDLT surgery (actual donors) while 31 subjects didn't (potential donors). Donor-recipient relationship included husband-wife, parent-children, brother-sister etc. Subjects had statistical significance on validity scale L, F, K and all clinical scales compared to the control group. Potential donors had significant difference in F(b), F(p), K, S, Pa, AGGR, PSYC, DISC and NEGE scales compared to actual donors. F, D and NEGE scales were found to be predictive for actual donation. Subanalysis on donor-recipient relationship and gender also showed significant difference in certain scales. Conclusions : Under-reporting of psychological problems should be considered when evaluating living-liver donors. Information about the donor's overall psychosocial background, mental status and donation process should also be acquired.

• Radiation Oncology Journal
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• v.22 no.2
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• pp.115-123
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• 2004

Purpose : This retrospective study was conducted to compare early preliminary results of breast conservation therapy (BCT) with mastectomy In early breast cancer. Materials and Methods : We evaluated 171 women with AJCC stage I and II breast cancer who had been treated at Kangnam St. Mary's Hospital from March 1989 to August 1996. Eighty-eight patients underwent mastectomy and 85 patients did conservative surgery with breast irradiation. in the BCT group, all patients received whole breast irradiation to a total dose of 45$\~$50 Gy/5$\~$6 wks, followed by a boost to the original tumor site at least 60 Gy. Chemotherapy was administered to 29 (34.1$\%$) patients in BCT and 40 (45.5$\%$) in mastectomy, with various sequencing of surgery and/or radiation. We compared survival rate, patterns of failure in each treatment group and the prognostic factors that had a significant effect on treatment failure. The median follow-up time was 63 months (19$\~$111 months). Log rank test was used to estimate the prognostic factors for treatment failure. Results : Overall survival, disease free survival, locoregional recurrence and distant metastasis rates were not significantly different between the two treatment groups. During the follow-up period, 11 patients (12.5$\%$)in the mastectomy group and 10 patients (11.8%$\%$ in the BCT group were failed. Six local recurrences occurred after mastectomy and 5 after BCT Five patients fatted at distant site in mastectomy and 4 in BCT. Of the local recurrence cases, five of 6 mastectomy patients and 3 of S BCT patients were alive with no evidence of disease after salvage surgery and/or chemoirradiation. Our results indicated that the major influence on survival was distant metastasis. Unfortunately, control of distant metastasisis was not frequently achieved. Even with salvage systemic therapy or radiotherapy, most of distant metastasis patients died or had uncontrolled disease in both treatment groups: only one of 4 BCT patients and none of mastectomy patients were alive without disease. There was no apparent difference in the incidence rate of contralateral breast cancer and non-breast 2$^{nd}$ primary tumor between the two treatment groups. Univariate Log-rank test identified the N stage and the involved axillary LN number as distinct prognostic factors that were highly predictive of treatment failure in both treatment groups. Additionally, marginal status in BCT and histologic nuclear grade In the mastectomy group were risk factors for treatment fallure (p < 0.05). Concousion : Although further careful follow-up is necessary to confirm the trends evident In this serles, it would appear that patterns of failure and survival rate following conservative surgery and radiotherapy in early breast cancer are similar to those following mastectomy. The great majority of patients with local recurrence had an exellent salvage rate in both treatment groups. Therefore, these preliminary short term results support BCT as an equally effective management for early breast cancer as an alternative to mastectomy.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.