著者
松村 靖夫 喜多 紗斗美 森本 史郎 秋元 健吾 古谷 真優美 岡 直美 田中 隆治
出版者
公益社団法人日本薬学会
雑誌
Biological & pharmaceutical bulletin (ISSN:09186158)
巻号頁・発行日
vol.18, no.7, pp.1016-1019, 1995-07-15
被引用文献数
18 93

We investigated the antihypertensive effect of sesamin, a lignan from sesame oil, using deoxycorticosterone acetate (DOCA)-salt hypertensive rats. The animals were unilaterally nephrectomized, and then separated into a sham-operated group (sham group) and a DOCA-salt-treated group. The latter was further separated into a normal diet group (control group) and a sesamin-containing diet group (sesamin group). The systolic blood pressure of control group progressively increased in comparison with that of sham group. This DOCA-salt-induced hypertension was markedly suppressed by feeding a sesamin-containing diet. Systolic blood pressure after 5 weeks was 130.6±1.9mmHg in the sham group, 198.1±7.3mmHg in the control group and 152.5±8.4mmHg in the sesamin group, respectively. The treatment with DOCA and salt for 5 weeks significantly increased the weight of the left ventricle plus the septum. However, this increase was signiflcantly suppressed in the sesamin group. When the degree of vascular hypertrophy of the aorta and superior mesenteric artery was histochemically evaluated, there were significant increases in wall thickness, wall area and the wall-to-lumen ratio in the control group, compared with the sham. Sesamin feeding ameliorated the development of DOCA-salt-induced vascular hypertrophy in both the aorta and mesenteric artery. These findings strongly suggest that sesamin is useful as a prophylactic treatment in the development of hypertension and cardiovascular hypertrophy.
著者
田中 隆治 吉岡 理文
出版者
一般社団法人 電気学会
雑誌
電気学会論文誌C(電子・情報・システム部門誌) (ISSN:03854221)
巻号頁・発行日
vol.131, no.11, pp.1895-1900, 2011-11-01 (Released:2011-11-01)
参考文献数
7

In recent years, Augmented Reality (AR) becomes the focus of attention as a technology for obtaining some information. Most AR systems have used some markers to display any information. However, since markerless AR systems can be used intuitively, they are researched actively.In this paper, we study about the AR system based on the hand recognition as a markerless system. The reason why we used a hand is that we don't need to prepare or carry on any tool, and can easy to watch any information on a hand. Taehee Lee et al. introduced HandyAR which employ the hand recognition. In this method, there are some problems. At first, when the method learns skin model, it needs many learning data. This is because it uses RGB color model. Secondly, it is difficult to get hand because hand images which are extracted by the skin model have noise. Thirdly, the method uses finger positions to estimate the hand coordinate. Therefore it is sensitive to finger state. We improved HandyAR to solve these problems. Experimental result showed that our method had higher performance than conventional methods.