• Journal of Life Science
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• v.23 no.11
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• pp.1351-1359
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• 2013

The anti-proliferative activity of ${\beta}$-ionone was investigated on human non-small lung cancer A-549 cells (designated A-549 cells). A-549 cells were treated with various concentrations of ${\beta}$-ionone (1, 5, 10, and 15 ${\mu}M$) for two, four, and six days. Biochemical markers related to the growth inhibition of A-549 cells by ${\beta}$-ionone were measured at the second day of incubation. ${\beta}$-Ionone inhibited the growth of A-549 cells by dose-and time-dependent manners, resulting in an $IC_{50}$ of 5.0 ${\mu}g/ml$ at the second day of incubation. ${\beta}$-Ionone induced apoptosis by a dose-dependent manner. ${\beta}$-Ionone increased levels of p53, p21, and Bax proteins, but suppressed expression of the Bcl-2 protein. Similarly, ${\beta}$-ionone enhanced cytochrome c release from the mitochondria to the cytosol, and induced activation of caspase-9 and -3. Additionally, ${\beta}$-ion-one reduced $cPLA_2$ and COX-2 protein levels. These results suggest that the ${\beta}$-ionone inhibits the proliferation of A-549 cells through reciprocal regulation of Bax and Bcl-2 gene expression and suppression of $cPLA_2$ and COX-2 protein expressions.

• The Korean Journal of Nuclear Medicine
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• v.36 no.6
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• pp.317-324
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• 2002

Purpose: The use of statistical parametric mapping (SPM) program has increased for the analysis of brain PET and SPECT images. Montreal Neurological Institute (MNI) coordinate is used in SPM program as a standard anatomical framework. While the most researchers look up Talairach atlas to report the localization of the activations detected in SPM program, there is significant disparity between MNI templates and Talairach atlas. That disparity between Talairach and MNI coordinates makes the interpretation of SPM result time consuming, subjective and inaccurate. The purpose of this study was to develop a program to provide objective anatomical information of each x-y-z position in ICBM coordinate. Materials and Methods: Program was designed to provide the anatomical information for the given x-y-z position in MNI coordinate based on the Statistical Probabilistic Anatomical Map (SPAM) images of ICBM. When x-y-z position was given to the program, names of the anatomical structures with non-zero probability and the probabilities that the given position belongs to the structures were tabulated. The program was coded using IDL and JAVA language for 4he easy transplantation to any operating system or platform. Utility of this program was shown by comparing the results of this program to those of SPM program. Preliminary validation study was peformed by applying this program to the analysis of PET brain activation study of human memory in which the anatomical information on the activated areas are previously known. Results: Real time retrieval of probabilistic information with 1 mm spatial resolution was archived using the programs. Validation study showed the relevance of this program: probability that the activated area for memory belonged to hippocampal formation was more than 80%. Conclusion: These programs will be useful for the result interpretation of the image analysis peformed on MNI coordinate, as done in SPM program.

• Journal of fish pathology
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• v.26 no.3
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• pp.255-263
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• 2013

The innate immune response is fundamental defense response of vertebrates and invertebrates. Especially, the innate immune response important for larvae that lack of resistance to infectious diseases in the early stages. Galectin is one of the kinds of lectin and presents in the fish mucous that involves innate immune response. Galectin have been studied from various fishing species, but expression analysis of galectin is still unclear during early developmental stage in olive flounder. In this study, we investigated gene expression of galectin-1 from various developmental stage and tissues. We excised several tissues including the muscle, fin, eye, gill, brain, stomach, intestine, kidney, spleen and liver from adult olive flounder and confirmed gene expression of galectin-1 using RT-PCR and quantitative real-time PCR. Expression of galectin-1 was significantly higher in muscle, stomach and intestinal tissue than other tissue in adult fish (5 and 29 months). Also, galectin-1 gene was detected from 0 DAH and gradually increased to 35 DAH and since then decreased after stomach development period. Induction of galectin-1 during the early developmental stage suggest that muscle, fin and eye tissue is formed and begins the secretion of galectin this period. In addition, increased expression levels at 35 DAH suggest that due to complete formation of stomach and intestine, increase of secretion and activation of enzyme. This study shows that expression of galectin-1 during early developmental stages and adult period in olive flounder and can be expect that galectin-1 play essental role in the innate immune system throughout the whole life time. Galectin-1 is primary barrier such as skin and digestive tissue against pathogen infection, also digestive tract developmental period is important for pathogen invasion can be expected that it will serve. Mass mortality due to the disease in seed production is continuing damage, therefore these result will be meaningful about infectious disease during early developmental stages as a basic data for the study.

• Journal of IKEEE
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• v.25 no.3
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• pp.493-500
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• 2021

In this paper, we propose the development of deep learning structure to improve quality of polygonal containers. The deep learning structure consists of a convolution layer, a bottleneck layer, a fully connect layer, and a softmax layer. The convolution layer is a layer that obtains a feature image by performing a convolution 3x3 operation on the input image or the feature image of the previous layer with several feature filters. The bottleneck layer selects only the optimal features among the features on the feature image extracted through the convolution layer, reduces the channel to a convolution 1x1 ReLU, and performs a convolution 3x3 ReLU. The global average pooling operation performed after going through the bottleneck layer reduces the size of the feature image by selecting only the optimal features among the features of the feature image extracted through the convolution layer. The fully connect layer outputs the output data through 6 fully connect layers. The softmax layer multiplies and multiplies the value between the value of the input layer node and the target node to be calculated, and converts it into a value between 0 and 1 through an activation function. After the learning is completed, the recognition process classifies non-circular glass bottles by performing image acquisition using a camera, measuring position detection, and non-circular glass bottle classification using deep learning as in the learning process. In order to evaluate the performance of the deep learning structure to improve quality of polygonal containers, as a result of an experiment at an authorized testing institute, it was calculated to be at the same level as the world's highest level with 99% good/defective discrimination accuracy. Inspection time averaged 1.7 seconds, which was calculated within the operating time standards of production processes using non-circular machine vision systems. Therefore, the effectiveness of the performance of the deep learning structure to improve quality of polygonal containers proposed in this paper was proven.

• Korean Chemical Engineering Research
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• v.59 no.4
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• pp.584-595
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• 2021

In this study, the correlation between operating stages of waste air-treating system composed of two alternatively-operating UV/photocatalytic reactors, and the deactivation of photocatalyst used in each operating stage, was investigated by instrumental analysis thereon. The repeated deactivation and subsequent re-generation of photocatalyst used in the waste air treating system of previous investigation performed by Lee and Lim (Korean Chem. Eng. Research, 59(4), 574-583(2021)), were characterized on virgin photocatalyst-carrying porous SiO₂ media (A4), used photocatalyst-carrying porous SiO₂ media (A1, A2 and A3) collected from the corresponding photocatalytic reactor upon 1^st, 2^nd, and 3^rd run, respectively, regenerated photocatalyst-carrying porous SiO₂ media upon 1 time-run (AD1) and 3 times regenerated photocatalyst-carrying porous SiO₂ media upon 3 time-runs (AD3) by instrumental analysis including BET analysis, SEM, XPS, SEM-EDS and FT-IR. As a result, the proper regeneration-temperature for deactivated photocatalyst to be regenerated several times (more than 3 times), was suggested below 200 ℃. Such temperature of deactivated photocatalyst-regeneration was almost consistent to the one, according to BET analysis, at which tiny nano-pores blocked by adsorbed ethanol-oxidative and degraded intermediates (AEODI), were regenerated to be reopened through almost complete mineralization of AEODI. In particular, the results of XPS analysis indicated an incurrence of insignificant deactivation of photocatalysis upon 1^st run of UV/photocatalytic reactor (A or C) of the previous investigation. In addition, the results of XPS analysis were consistent with the experimental results of the previous investigation in that 1) deactivation of photocatalyst incurred during 2^nd run of the UV/photocatalytic reactor (A or C) resulted in decreased removal efficiency, by ca. 5% and 5%, of ethanol and hydrogen sulfide, respectively, compared with its 1^st run; 2) there was insignificant difference between the removal efficiencies of its 2^nd run and 3^rd run. Furthermore, the removal efficiencies of ethanol and hydrogen sulfide for hypothetical 4^th run of photocatalytic reactor in the previous investigation, using AD3, were expected to decrease, compared with its 3^rd run, by much more than those for 2^nd run in the previous investigation did, compared with its 1^st run.

• Journal of Applied Biological Chemistry
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• v.64 no.2
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• pp.113-119
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• 2021

Olive (Olea europaea L.) leaves, a raw material for health functional foods and cosmetics have abundant polyphenols including oleuropein (major bioactive compound) with various biological activities: antioxidant, antibacterial, antiviral, anticancer activity, and inhibit platelet activation. Oleuropein has been reported as skin protectant, antioxidant, anti-ageing, anti-cancer, anti-inflammation, anti-atherogenic, anti-viral, and anti-microbial activity. Despite oleuropein is the important compound in olive leaves, there is still no quantitative approach to reveal oleuropein content in commercial products. Therefore, a validated method of analysis has to develop for oleuropein. In this study, the components and oleuropein content in 10 types of products were analyzed using a developed method with ultra-performance liquid chromatography to quadrupole time-of-flight mass spectrometry, charge of aerosol detector, and photodiode array. The total of 18 compounds including iridoids (1, 3, 4, 14, and 16-18), coumarin (2), phenylethanoids (5, 9, and 11), flavonoids (6-8, 10, 12, and 13), lignan (15), were tentatively identified in the leaves extract based high resolution mass spectrometry data, and the content of oleuropein in each product was almost identical between two detection methods. The oleuropein in three commercial product (A, G, H) was contained more over the suggested content, and it of five products (B, E, H, I, J) were analyzed within 5-10% error range. However, the two products (C, D) were found far lower than suggested contents. This study provides that analytical results of oleuropein could be a potential information for the quality control of leaf extract for a manufactured functional food.

• Science of Emotion and Sensibility
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• v.26 no.3
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• pp.149-160
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• 2023

This study develops a time-varying system-based noncontact fabric sensor that can measure cerebral blood-flow signals to explore the possibility of brain blood-signal detection and emotional evaluation. The textile sensor was implemented as a coil-type sensor by combining 30 silver threads of 40 deniers and then embroidering it with the computer machine. For the cerebral blood-flow measurement experiment, subjects were asked to attach a coil-type sensor to the carotid artery area, wear an electrocardiogram (ECG) electrode and a respiration (RSP) measurement belt. In addition, Doppler ultrasonography was performed using an ultrasonic diagnostic device to measure the speed of blood flow. The subject was asked to wear Meta Quest 2, measure the blood-flow change signal when viewing the manipulated image visual stimulus, and fill out an emotional-evaluation questionnaire. The measurement results show that the textile-sensor-measured signal also changes with a change in the blood-flow rate signal measured using the Doppler ultrasonography. These findings verify that the cerebral blood-flow signal can be measured using a coil-type textile sensor. In addition, the HRV extracted from ECG and PLL signals (textile sensor signals) are calculated and compared for emotional evaluation. The comparison results show that for the change in the ratio because of the activation of the sympathetic and parasympathetic nervous systems due to visual stimulation, the values calculated using the textile sensor and ECG signals tend to be similar. In conclusion, a the proposed time-varying system-based coil-type textile sensor can be used to study changes in the cerebral blood flow and monitor emotions.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.69-94
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• 2017

Recently, increase of demand for big data analysis has been driving the vigorous development of related technologies and tools. In addition, development of IT and increased penetration rate of smart devices are producing a large amount of data. According to this phenomenon, data analysis technology is rapidly becoming popular. Also, attempts to acquire insights through data analysis have been continuously increasing. It means that the big data analysis will be more important in various industries for the foreseeable future. Big data analysis is generally performed by a small number of experts and delivered to each demander of analysis. However, increase of interest about big data analysis arouses activation of computer programming education and development of many programs for data analysis. Accordingly, the entry barriers of big data analysis are gradually lowering and data analysis technology being spread out. As the result, big data analysis is expected to be performed by demanders of analysis themselves. Along with this, interest about various unstructured data is continually increasing. Especially, a lot of attention is focused on using text data. Emergence of new platforms and techniques using the web bring about mass production of text data and active attempt to analyze text data. Furthermore, result of text analysis has been utilized in various fields. Text mining is a concept that embraces various theories and techniques for text analysis. Many text mining techniques are utilized in this field for various research purposes, topic modeling is one of the most widely used and studied. Topic modeling is a technique that extracts the major issues from a lot of documents, identifies the documents that correspond to each issue and provides identified documents as a cluster. It is evaluated as a very useful technique in that reflect the semantic elements of the document. Traditional topic modeling is based on the distribution of key terms across the entire document. Thus, it is essential to analyze the entire document at once to identify topic of each document. This condition causes a long time in analysis process when topic modeling is applied to a lot of documents. In addition, it has a scalability problem that is an exponential increase in the processing time with the increase of analysis objects. This problem is particularly noticeable when the documents are distributed across multiple systems or regions. To overcome these problems, divide and conquer approach can be applied to topic modeling. It means dividing a large number of documents into sub-units and deriving topics through repetition of topic modeling to each unit. This method can be used for topic modeling on a large number of documents with limited system resources, and can improve processing speed of topic modeling. It also can significantly reduce analysis time and cost through ability to analyze documents in each location or place without combining analysis object documents. However, despite many advantages, this method has two major problems. First, the relationship between local topics derived from each unit and global topics derived from entire document is unclear. It means that in each document, local topics can be identified, but global topics cannot be identified. Second, a method for measuring the accuracy of the proposed methodology should be established. That is to say, assuming that global topic is ideal answer, the difference in a local topic on a global topic needs to be measured. By those difficulties, the study in this method is not performed sufficiently, compare with other studies dealing with topic modeling. In this paper, we propose a topic modeling approach to solve the above two problems. First of all, we divide the entire document cluster(Global set) into sub-clusters(Local set), and generate the reduced entire document cluster(RGS, Reduced global set) that consist of delegated documents extracted from each local set. We try to solve the first problem by mapping RGS topics and local topics. Along with this, we verify the accuracy of the proposed methodology by detecting documents, whether to be discerned as the same topic at result of global and local set. Using 24,000 news articles, we conduct experiments to evaluate practical applicability of the proposed methodology. In addition, through additional experiment, we confirmed that the proposed methodology can provide similar results to the entire topic modeling. We also proposed a reasonable method for comparing the result of both methods.

• Journal of Life Science
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• v.19 no.5
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• pp.593-597
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• 2009

The uterus plays a critical role in pregnancy and steroid hormones, and both estrogen (E2) and progesterone (P4) especially play important roles in the cross-talk between embryos and uterus to support the pregnancy. E2 stimulates uterine growth during early pregnancy to prepare for implantation of embryos. This cross-talk during the implantation period involves hormones (E2 and P4) and growth factors, including insulin-like growth factor-I (IGF-I). In the uterus of a pregnant pig, the action of E2 is mediated by estrogen receptor-${\beta}$ (ER-${\beta}$). The expression of ER-a was much higher in early pregnancy than in mid- and late- pregnancy, suggesting E2 secretion from embryos enhances transcription of ER-a during early pregnancy. In order to prove whether IGF-I is an E2 target gene, quantitative real-time PCR was performed on ovariectomized murine uterus with E2 and/or P4 treatment(s). Increased IGF-I mRNA expression was observed with E2 treatment, however, it was not significantly induced by P4 treatment, which clearly demonstrates that, in mice, E2 depends on the activation of uterine IGF-I gene expression. The expression of IGF-I in the uterus of pigs was much higher in early pregnancy than in mid- and late- pregnancy and these data exhibited the same expression pattern with the ER-${\beta}$ gene expression in the uterus. It suggests that a positive co-relationship between IGF-I and ER-${\beta}$ expression exists in the uterus, and that both gene expressions of IGF-I and ER-${\beta}$ are regulated by E2. It further suggests that uterine the IGF-I gene expression might be initiated by E2 secreted from embryos to increase ER-${\beta}$ gene expression, and that this increased ER-${\beta}$ further stimulates the expression of IGF-I in the uterus during early pregnancy.

• Korea Journal of Hospital Management
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• v.10 no.1
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• pp.93-114
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• 2005

The prenatal care is the preventive medical service to help the pregnant mother deliver the healthy baby. It's regular examines give some chances to check-up the healthy conditions. This thesis concentrates on the CRM system to support an effective prenatal care system and prove the effectiveness of it. As CRM is the adapted management related to the customer's own information, it is important to develop the CRM model classified by the patients characteristics. A general hospital in Busan operated the CRM system to carry out the effective prenatal care and there is an analysis to ensure the effectiveness of CRM system for the pregnant women in our maternity ward. The results can be summarized as follows: 1) According to the comparisons with the CRM system, we can conclude the system is desirable. (1) Maternal Age : In the age distribution, the prenatal visit frequency, triple marker freqency, oral GTT and targeted ultrasonography in the experimental group in 30 to 34 years old is higher on the whole. For over 35 years old group, the higher frequency comes out in the oral GTT and targeted ultrasonography and for 25 to 29 years old group the different figure shows just in the targeted ultrasonography. (2) Area of residence: There is a clear difference in all the items in Busan and near area but no sign of difference in prenatal visits and oral GTT in other residencial area. Especially in the targeted ultrasonography the higher figure shows in the experimental group located in the both areas. The targeted ultrasonography is known as the specific examination which should be examined by the specialists, on the contrary the other examinations can be operated in the small clinic. So the public information and seminars related with ultrasonography increases the check-up frequency. The clinic requests some ultrasonographical examinations to the specialists in general hospital. (3) Parity: The clear difference shows that the CRM system causes the prenatal visit frequency to become higher in experimental group. The figure is 9.7 times and 8.6 times each. This is opposite that the past study said multiparity reduced the average prenatal visits. But the result of CRM is considered as the method to help the multiparity understand the importance of the prenatal care. (4) Obstetrical history: In the experimental group of the spontaneous delivery group, the figure is higher in the prenatal visit frequency, triple marker, oral GTT and targeted ultrasonography but the Caesarean section delivery group has higher figure in targeted ultrasonography. (5) In the first check-up, the rate of targeted ultrasonography in under 16 week pregnancy, in the 16 week pregnancy to 32 week pregnancy and the over 32 week pregnancy in the experimental group is upper than the compared one. For the oral GTT, there is a difference in under 16 week pregnancy but no difference in prenatal visits and triple marker. 2) The analysis of characteristics of prenatal care through the decision tree resulted in the fact that the most important variable is the residential area. After the delivery frequency is following, the obstetrical history and maternal age are in order. It is the same result in the triple marker and oral GTT. Consequently it is the same order of important variables in CRM system. The effectiveness of CRM system is proved in this study. The CRM system is a marketing method to control and lead the customers through the segmentation of customer data. It increases the new customer aquisition, maintenance of loyal customers, augmentation of customers value, activation of potential customers and creation of life time customers. So eventually it can enlarge the customers value. The medical institution should make efforts to establish the data base enforced by the customer's information on the underlying ordinary data system to carry out the CRM system effectively. In addition, it should develop the a variety of marketing strategy in order to set up one to one marketing satisfying the needs of individual patients.