前立腺癌における血清γ-セミノプロティンの測定

前立腺癌の新しいマーカーとして, γ-セミノプロテイン(γ-Sm)と前立腺性酸性ホスファターゼ(PAP)とを比較評価した.未治療前立腺癌におけるγ-SMおよびPAPのsensitivityは, それぞれ81%, 67%であった.γ-Smはすべての病期で前立腺肥大症と比較して陽性率が高かった.前立腺癌ではγ-SmとPAPは相関を示さなかった.γ-SmとPAPを同時に測定することにより, 感度が上昇した.γ-SmおよびPAPのspecificityはそれぞれ87%と90%であった.内分泌療法を施行した病期D2において, γ-SmはPAPよりもより多く正常化した.以上より, γ-Smは前立腺癌のもう1つの有用なマーカーであるといえるSerum gamma-seminoprotein (gamma-Sm) was evaluated as a new marker for prostatic cancer in comparison with prostatic acid phosphatase (PAP). The sensitivity of gamma-Sm and PAP for untreated prostatic cancer was 81% and 67%, respectively. gamma-Sm showed a higher positive rate over all stages than in benign prostatic hypertrophy (BPH). There was no correlation between gamma-Sm and PAP in prostatic cancer. Improved sensitivity was obtained by simultaneous measurement of gamma-Sm and PAP. Specificity of gamma-Sm and PAP for BPH was 87% and 90%, respectively. gamma-Sm normalized after endocrine therapy for stage D2 more often than did PAP. These results indicate that gamma-Sm is another useful marker to evaluate prostatic cancer

The β1-integrin-dependent function of RECK in physiologic and tumor angiogenesis

金沢大学がん研究所Vascular endothelial cells produce considerable amounts of matrix metalloproteinases (MMP), including MMP-2, MMP-9, and membrane type 1 (MT1)-MMP. However, little is known about the regulatory mechanisms of these protease activities exhibited during vascular development. A glycosylphosphatidylinositol-anchored glycoprotein, reversion-inducing cysteine-rich protein with Kazal motifs (RECK), has been shown to attenuate MMP-2 maturation by directly interacting with MT1-MMP. Here, we show that an angiogenic factor angiopoietin-1 induces RECK expression in human umbilical vein endothelial cells (HUVEC), and RECK depletion in these cells results in defective vascular tube formation and cellular senescence. We further observed that RECK depletion downregulates β1-integrin activation, which was associated with decreased autophosphorylation of focal adhesion kinase and increased expression of a cyclin-dependent kinase inhibitor p21CIP1. In agreement, significant downregulation of β1-integrin activity was observed in vascular endothelial cells in Reck-/- mouse embryos. In HUVECs, specific inhibition of MMP-2 significantly antagonized the effect of RECK depletion on β1-integrin signaling, cell proliferation, and tube elongation. Furthermore, we observed that hypervascular tumor-derived cell lines can induce high RECK expression in convoluted vascular endothelial cells, and this in turn supports tumor growth. Targeting RECK specifically in tumor-associated vascular endothelial cells resulted in tumor regression. Therefore, we propose that RECK in tumor vascular endothelial cells can be an interesting target of cancer treatment via abortion of tumor angiogenesis. ©2010 AACR

Tricks and treats: designing technology to support mobility assistance dogs

Assistance dogs are a key intervention to support the autonomy of people with tetraplegia. Previous research on assistive technologies have investigated ways to, ultimately, replace their labour using technology, for instance through the design of smart home environments. However, both the disability studies literature and our interviews suggest there is an immediate need to support these relationships, both in terms of training and bonding. Through a case study of an accessible dog treats dispenser, we investigate a technological intervention responding to these needs, detailing an appropriate design methodology and contributing insights into user requirements and preferences

チ ノ ネットワーク セイチョウ モデル

知の創造プロセスに関する先行研究では、これまでいくつかのモデルが提唱されてきた。本稿で我々は、知の創造プロセスについて「増殖段階」「混在段階」「創造段階」の3段階からなる【知のネットワーク成長モデル】を新たに提唱する。本モデルが従来のモデルと異なる点は、知の創造理論について、数学の一分野であるノード(点)とエッジ(線)で結ばれた「グラフ」を用いたグラフ理論や、ライフサイエンスの分野である「タンパク質相互作用ネットワーク(PPI: Protein-Protein Interaction)」などを援用して、知の創造プロセスを提唱している点にある。さらに「混在段階」と「創造段階」の溝(キャズム)を越え、混在させた知に新しい価値を付加するためのセレンディピティの必要性についても言及している点にある。In this paper we describe a novel knowledge creation model, the "three-step knowledge network model," which comprises the propagation step, the mixing step, and the creation step. This model uses knowledge networks first proposed by Willard Van Orman Quine\u27s, and graph theory to describe the knowledge creation process. We use higher education as a example of knowledge creation that this model can describe, and in the future hope to apply this model to other phenomena