• Journal of Physiology & Pathology in Korean Medicine
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• v.17 no.4
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• pp.1101-1111
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• 2003

Our study shows that EC extract has inhibitory effect on pro-inflammatory cytokines such as TNF-α, IL-1, IL-6, iNOS and COX2 in hFLSs. IL-1β, IL-6, iNOS and COX2 mRNA expression is suppressed at a low dasage (1㎍/ml) of EC extract. TNF-α was also suppressed at higher dosages (10 ㎍/ml, 100㎍/ml). EC extract also inhibited TNF-α, IL-1β and IL-6 production in pro-inflammatory cytokine stimulated-hFLSs. Expecially IL-1β(p<0.05) production are suppressed significantly. On the other hand, EC extract did not show any cytotoxicity. Thses data suggest that EC extract has anti-inflammatory effect mostly by inhibiting IL-1β production, and thus could be used to prevent or treat some inflammatory disease such as RA. It remains to be known what are the major components responsible for anti-inflammatory effect and what is the main mechanism.

• Toxicological Research
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• v.30 no.4
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• pp.277-282
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• 2014

To develop a composition for enhancing immunity, based on alcohol extracts of the bumblebee as an active ingredient, bumblebee ethanol extracts were evaluated for their protective effect in chronic models of inflammation, adjuvant induced rat arthritis. B. terrestris worker extract (SDIEX) and, B. hypocrita sapporoensis lava and pupa extract (SPDYBEX), significantly decreased paw edema in arthritic rats, at a dose 100 mg/kg, respectively. The cytokine levels related inflammation of COX-2, $sPLA_2$, VEGF, and TNF-${\alpha}$, were decreased, compared to positive control, indomethacin (5 mg/kg). Histopathological data demonstrated decreases inflammatory activity, hind paw edema, and repaired hyaline articular cartilage in DRG over a 2 wk administration. HPLC and GC-MS analysis of SDIEX and SPDYBEX revealed the presence of cantharidin.

• Food Science and Biotechnology
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• v.17 no.4
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• pp.846-849
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• 2008

This study employed high performance liquid chromatography (HPLC) coupled to an on-line $ABTS^+$ radical scavenging detection (RSD) system along with HPLC-electro spin impact/mass spectrometry (ESI/MS), to rapidly determine and identify antioxidant compounds occurring in blueberry extract. The extract was separated by HPLC, and then the radical scavenging activities of the separated compounds were evaluated by the on-line coupled $ABTS^+$-RSD system. The negative peaks of the $ABTS^+$-RSD system, which indicates the presence of antioxidant activity, were monitored by measuring the decrease in absorbance at 734 nm. The active components in the blueberry extract were identified by HPLC-ESI/MS using their MS spectra and retention times. According to the data acquired from the on-line HPLC-$ABTS^+$-based assay and HPLC-ESI/MS systems, the antioxidant compounds detected in the blueberry extract were identified as chlorogenic acid and 11 anthocyanins.

• Biomedical Science Letters
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• v.30 no.3
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• pp.137-142
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• 2024

The aim of this study was to investigate the inhibitory effects of Alismatis rhizoma extract on breast cancer cell growth and elucidate the underlying mechanisms. The growth inhibitory effects of Alismatis rhizoma extract on breast cancer cells were measured using the WST-1 assay, while its impact on relevant proteins and genes was analyzed using real-time polymerase chain reaction. The results demonstrated significant inhibition of breast cancer cell growth by Alismatis rhizoma, with the inhibitory effect showing a positive correlation with the dosage, treatment duration, and quantity. Furthermore, Alismatis rhizoma extract markedly decreased the expression levels of cell cycle protein D1 and suppressed cell migration and invasion. In conclusion, Alismatis rhizoma exhibits the potential to inhibit breast cancer cell growth, possibly by regulating cell cycle progression and inhibiting cell migration and invasion. These findings suggest that Alismatis rhizoma extract possesses anticancer properties against human breast cancer cells. Further investigation of its reuglation of action will provide foundational data, potentially paving the way for its development as an anticancer therapeutic agent.

• The Korea Genome Conference
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• 2005.09a
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• pp.74-74
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• 2005

• Journal of Digital Convergence
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• v.13 no.9
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• pp.235-242
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• 2015

Social network technology has been increasing interest in the big data service and development. However, the data stored in the distributed server and not on the central server technology is easy enough to find and extract. In this paper, we propose a big data management techniques to minimize the processing time of information you want from the content server and the management server that provides big data services. The proposed method is to link the in-group data, classified data and groups according to the type, feature, characteristic of big data and the attribute information applied to a hash chain. Further, the data generated to extract the stored data in the distributed server to record time for improving the data index information processing speed of the data classification of the multi-attribute information imparted to the data. As experimental result, The average seek time of the data through the number of cluster groups was increased an average of 14.6% and the data processing time through the number of keywords was reduced an average of 13%.

• Korean Journal of Plant Resources
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• v.24 no.2
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• pp.150-159
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• 2011

This study was conducted to gather the basic data on the alpine leek (Allium victorialis) for the expand of consumption and the production of its manufactured goods. Amino acid content in alpine leek leaves and various physiological activities were examined. Seventeen component amino acids and 38 free amino acids from alpine leek leaves were analyzed, and the total contents were 2,693.28 mg/100g for component amino acids and 535.39 mg/100g for free amino acids. Total phenolic compounds in the leaves of alpine leek showed the highest level from the methanol extract (37.7 mg/l), and followed by ethanol extract (31.9 mg/l) and hot water extract (25.4 mg/l). Total flavonoid contents in 1,000 mg/l extract was the highest in the methanol extract (22.2 mg/l). DPPH radical scavenging activity at 1,000 mg/l extract was high in the order of ethanol extract (51.6%), methanol extract (47.3%) and hot water extract (37.2%). nitrite radical scavenging activity Methanol extract from Allium victorialis leaves was the highest nitrite radical scavenging activity (79.5%). Hyperplasia suppression of lung cancer cells (Calu-6) and gastric cancer cells (SNU-601) by the methanol extract from the bulb of alpine leek were 99.9% in the extracting concentration of over 200 mg/l. No significant difference in antimicrobial activity among the 3 different solvents and extract concentrations was observed, and the inhibition zones against the gram-positive and negative microorganisms were ranged from 8.23 to 10.15 mm. It was concluded that physiological activities in a human body could be improved by the intake of alpine leek as a pharmaceutical material, and that it would be useful for the prevention of health risk such as lung and gastric cancers.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.1
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• pp.39-44
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• 2013

Trees are important ground objects that cause oxygen and reduce carbon dioxide in urban areas. For management of the trees, many studies using LIDAR data have been conducted. But, they rely on overseas developed LIDAR data processing software applications because there is a lack of domestically developed software applications. Therefore, this work was intended to propose an automation process that helps to extract trees automatically from LIDAR data. The proposed process has the function to classify LIDAR data and to extract building regions and trees automatically. It was applied to a study place in Yongin to conduct a test. As a result, about 88% of trees were extracted from the automation process.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.179-190
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• 2017

Hand Accelerometers are widely used to detect human motion patterns in real-time. It is essential to reliably identify which type of activity is performed by human subjects. This rests on having accurate template of each activity. Many human activities are represented as a set of multiple time-series data from such sensors, which are mostly non-stationary and non-linear in nature. This requires a method which can effectively extract patterns from non-stationary and non-linear data. To achieve such a goal, we propose the method to apply Hilbert-Huang Transform which is known to be an effective way of extracting non-stationary and non-linear components from time-series data. It is applied on samples of accelerometer data to determine its effectiveness.

• Industrial Engineering and Management Systems
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• v.11 no.4
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• pp.371-384
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• 2012

This study proposes a multi-level data analysis approach to identify both superficial and latent relationships among variables in the data set obtained from a vocational rehabilitation (VR) services program of people with significant disabilities. At the first layer, data mining and statistical predictive models are used to extract the superficial relationships between dependent and independent variables. To supplement the findings and relationships from the analysis at the first layer, association rule mining algorithms at the second layer are employed to extract additional sets of interesting associative relationships among variables. Finally, nonlinear nonparametric canonical correlation analysis (NLCCA) along with clustering algorithm is employed to identify latent nonlinear relationships. Experimental outputs validate the usefulness of the proposed approach. In particular, the identified latent relationship indicates that disability types (i.e., physical and mental) and severity (i.e., severe, most severe, not severe) have a significant impact on the levels of self-esteem and self-confidence of people with disabilities. The identified superficial and latent relationships can be used to train education program designers and policy developers to maximize the outcomes of VR training programs.