http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
천연물 추출물이 대식세포 및 호염구 활성 억제에 미치는 영향
박재현,장지민,차상률,백효신,이주연,이유희,류세민,양세란,Park, Jaehyun,Jang, Jimin,Cha, Sang-Ryul,Baek, Hyosin,Lee, Jooyeon,Lee, You-Hui,Ryu, Semin,Yang, Se-Ran 한국식품위생안전성학회 2022 한국식품위생안전성학회지 Vol.37 No.3
Asthma is a chronic inflammatory disease characterized by recurring symptoms, airflow obstruction, and bronchial hyper-responsiveness. The onset of asthma for most patients begins early in life, and current asthma treatment with anti-inflammatory agents can have adverse effects, eventually leading to impaired quality of life. In the pathogenesis of asthma, macrophages and basophils play a vital role during progression. Macrophages not only induce inflammation by secreting inflammatory cytokines but also promote DNA damage and mucus production through nitric oxide (NO) production. Basophils enhance eosinophil recruitment and aggravate asthma through the FcεRIα receptor with high affinity for histamine and IgE. Therefore, in this study, we investigated whether the activation of macrophages and basophils is suppressed by the individual extracts of 28 natural products. RAW 264.7 cells (mouse macrophages) were treated with the natural products in LPS, and 4 natural product extracts resulted in decreased NO production. In β-hexosaminidase assay using RBL-2H3 cells (rat basophils), 19 natural product extracts decreased β-hexosaminidase production. In NO production and β-hexosaminidase assay using macrophages and basophils, 3 natural product extracts (Plantago asiatica, Centella asiatica, and Perilla frutescens var. japonica) significantly inhibited NO production and β-hexosaminidase release. Overall, we examined the inhibitory effects of 28 natural product extracts on macrophage and basophil activity, and the findings demonstrated the potential of natural product extracts for treating asthma and macrophage- and basophil-related diseases.
김진원(Jinwon Kim),박웅(Ung Park),이성한(Sunghan Lee),류세민(Semin Ryu),정인철(In cheol Jeong) 대한전자공학회 2024 대한전자공학회 학술대회 Vol.2024 No.6
This research aims to develop a non-contact system for detecting bed falls using four load cells installed on the legs of a bed. The proposed system is non-invasive and does not disrupt the user. Experiments were conducted with five adult participants, and simulated bed fall data were collected. A one-dimensional convolutional neural network (1-D CNN) model was employed to analyze the processed data, utilizing subject-independent training. The model achieved an accuracy of 87% in classifying falls, which was validated with test data. These results indicate that the load cell-based bed fall detection system has significant potential for practical applications in real-world environments.