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Induction of allergic contact dermatitis by astigmatid mite-derived monoterpene, α-acaridial
Toshio Sasai,Yunosuke Hirano,Sayaka Maeda,Isamu Matsunaga,Atsushi Otsuka,Daisuke Morita,Ritsuo Nishida,Hideo Nakayama,Yasumasa Kuwahara,Masahiko Sugita,Naoki Mori 한국응용곤충학회 2008 한국응용곤충학회 학술대회논문집 Vol.2008 No.10
α-Acaridial [2(E)-(4-methyl-3-pentenyl)butenedial] is a novel monoterpene secreted from the house dust mites. Because of its molecular nature of a highly reactive, small lipidic compound, we addressed whether α-acaridial might function as a haptenic allergen that induced allergic contact dermatitis. Mice sensitized with α-acaridial were challenged by the same antigen on the ear skin. After 2 days, significant ear swelling with a prominent infiltration of CD4+ T lymphocytes was observed. In vitro, α-acaridial exhibited an outstanding ability to quickly interact with and chemically modify a reference protein. Virtually all cysteine residues and a sizable fraction of lysine residues were found to be selectively modified, suggesting that α-acaridial could potentially interact with any proteins. Previously, numerous mite-derived proteinaceous allergens have been associated with contact dermatitis. Our study now emphasizes that small lipidic compounds released from mites comprise a new class of mite allergens, and therefore, is of significant medical implications.
Portable Life Support System Using Wearable Biosensor Worn by the Elderly
Syunji Yazaki,Toshio Matsunaga 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
We describe the development of a portable life support system called the Abnormal Condition Detection System(ACDS) involving the use of a wireless wearable biosensor that can be used to simultaneously observe triaxial acceleration, ECGs, and the temperature at the surface of the body. A prototype ACDS previously implemented by us and has been described in some papers. This prototype system can detect falls and abnormal heart rates as abnormal conditions. We implemented a new feature that displays the intensity of exercise to the user to encourage the use of the system even under normal conditions. We then implemented the new method for detecting falls and comparedit with the previous version. We found that the new method could achieve a detection rate of 93.9% with a missed alarm rate of 7.9%.