6 research outputs found
Hypoxia-mediated mechanism of MUC5AC production in human nasal epithelial and its implication in rhinosinusitis
BACKGROUND:
Excessive mucus production is typical in various upper airway diseases. In sinusitis, the expression of MUC5AC, a major respiratory mucin gene, increases. However, the mechanisms leading to mucus hypersecretion in sinusitis have not been characterized. Hypoxia due to occlusion of the sinus ostium is one of the major pathologic mechanisms of sinusitis, but there have been no reports regarding the mechanism of hypoxia-induced mucus hypersecretion.
METHODS AND FINDINGS:
This study aims to identify whether hypoxia may induce mucus hypersecretion and elucidate its mechanism. Normal human nasal epithelial (NHNE) cells and human lung mucoepidermoid carcinoma cell line (NCI-H292) were used. Sinus mucosa from patients was also tested. Anoxic condition was in an anaerobic chamber with a 95% N2/5% CO2 atmosphere. The regulatory mechanism of MUC5AC by anoxia was investigated using RT-PCR, real-time PCR, western blot, ChIP, electrophoretic mobility shift, and luciferase assay. We show that levels of MUC5AC mRNA and the corresponding secreted protein increase in anoxic cultured NHNE cells. The major transcription factor for hypoxia-related signaling, HIF-1α, is induced during hypoxia, and transfection of a mammalian expression vector encoding HIF-1α results in increased MUC5AC mRNA levels under normoxic conditions. Moreover, hypoxia-induced expression of MUC5AC mRNA is down-regulated by transfected HIF-1α siRNA. We found increased MUC5AC promoter activity under anoxic conditions, as indicated by a luciferase reporter assay, and mutation of the putative hypoxia-response element in MUC5AC promoter attenuated this activity. Binding of over-expressed HIF-1α to the hypoxia-response element in the MUC5AC promoter was confirmed. In human sinusitis mucosa, which is supposed to be hypoxic, expression of MUC5AC and HIF-1α is higher than in control mucosa.
CONCLUSION:
The results indicate that anoxia up-regulates MUC5AC by the HIF-1α signaling pathway in human nasal epithelia and suggest that hypoxia might be a pathogenic mechanism of mucus hypersecretion in sinusitis.ope
Delphi study on public company policies for SMEs' supports
학위논문 (석사)-- 서울대학교 대학원 : 공기업정책학과, 2011.8. 박정훈.Maste
뇌 인지 과정을 모방한 계층적 정보 처리 모델 - 계층적 다단계 비음수행렬분해법
학위논문(석사) - 한국과학기술원 : 전기및전자공학과, 2013.2, [ vi, 92 p. ]How to train a machine well so that it can develop intelligence like human has been a big issue of arti-ficial intelligence industry. Recently, deep learning has been a hot topic in this field. It is proven by several researches that deep learning, which resembles hierarchical data processing mechanism of our brain, actually does help learning process and improves the performance. In this thesis, we introduce another type of deep learning network, hierarchical multi-layer NMF, where each unit consists of non-negative matrix factorization algorithm, NMF; we extend single unit of learning algorithm NMF into multi-layered structure. With our pro-posed network, we aim to achieve two goals. One is to mimic and model how our brain processes information and represent data in hierarchical manner. The other is to observe the behavior of our multi-layered hierar-chical network and analyze its characteristics compared to shallow structure. Our demonstration shows that proposed multi-layered structure successfully models hierarchical learning mechanism; in the lower layer, very simple and sparse features are extracted at first, and as it proceeds to upper layer, the features develop into complex features by making combinations of simple features. By observing the hierarchical feature ex-traction process of our proposed algorithm, we are able to understand the underlying structure of complex data; we can understand the basic building blocks and how they come together in stages to finally represent data characteristics. With the analysis on image and document data sets, experimental results show that our brain-like information processing model has some strong points in reconstruction and classification tasks compared to single layered structure. Furthermore, our proposed multi-layer network seems to display charac-teristics different from that of shallow architecture in aspect of distribution of data representation. Our pro-posed multi-layer network is expected to demonstra...한국과학기술원 : 전기및전자공학과
