Pure iron grains are rare in the universe

The abundant forms in which the major elements in the universe exist have been determined from numerous astronomical observations and meteoritic analyses. Iron (Fe) is an exception, in that only depletion of gaseous Fe has been detected in the interstellar medium, suggesting that Fe is condensed into a solid, possibly the astronomically invisible metal. To determine the primary form of Fe, we replicated the formation of Fe grains in gaseous ejecta of evolved stars by means of microgravity experiments. We found that the sticking probability for formation of Fe grains is extremely small; only several atoms will stick per hundred thousand collisions, so that homogeneous nucleation of metallic Fe grains is highly ineffective, even in the Fe-rich ejecta of Type Ia supernovae. This implies that most Fe is locked up as grains of Fe compounds or as impurities accreted onto other grains in the interstellar medium

Non-linear Attributed Graph Clustering by Symmetric NMF with PU Learning

We consider the clustering problem of attributed graphs. Our challenge is how we can design an effective and efficient clustering method that precisely captures the hidden relationship between the topology and the attributes in real-world graphs. We propose Non-linear Attributed Graph Clustering by Symmetric Non-negative Matrix Factorization with Positive Unlabeled Learning. The features of our method are three holds. 1) it learns a non-linear projection function between the different cluster assignments of the topology and the attributes of graphs so as to capture the complicated relationship between the topology and the attributes in real-world graphs, 2) it leverages the positive unlabeled learning to take the effect of partially observed positive edges into the cluster assignment, and 3) it achieves efficient computational complexity, $O((n^2+mn)kt)$, where $n$ is the vertex size, $m$ is the attribute size, $k$ is the number of clusters, and $t$ is the number of iterations for learning the cluster assignment. We conducted experiments extensively for various clustering methods with various real datasets to validate that our method outperforms the former clustering methods regarding the clustering quality

糖転移化合物の新規医薬品添加剤への応用を目指した製剤設計及び処方検討に関する研究

開発段階での医薬品候補化合物の水溶性が極端に低下する中、候補となる難水溶性薬物の溶解性の改善かつ吸収性の増大が、医薬品開発の継続や製品化において鍵となる。しかし、既存の製剤技術や処方設計では十分な結果が得られない場合も多く、新たな製剤技術や処方設計による溶解性の改善が強く望まれている。我々は、近年の酵素合成技術の革新によって開発され、機能性食品添加剤として使用され始めた糖転移化合物に着目した。糖転移化合物は、既存の化合物に糖を転移することで、水溶性を増大させた化合物の総称であり、食品分野においては広く使用され、安全性が確保されている。本研究の目的は、糖転移化合物α-glucosyl hesperidin (Hsp-G) 及び α-glucosyl Stevia (Stevia-G)を用いて、難水溶性化合物の溶解性及び吸収性改善効果を目指した新規の処方検討を行い、改善効果の評価、メカニズムの解明、新規処方設計の提案により、糖転移化合物の医薬品添加剤や機能性食品添加剤としての可能性を見出すことにある。While the water solubility of new drug candidates in the development phase is often extremely poor, the improvement ofthe dissolution and absorption of poorly water soluble drug candidates is a key factor in the continuation of drug development andmaking new drugs. Since the existing technology and formulation design cannot produce acceptable results for poorly water solubledrugs in many cases, improvement in dissolution with new techniques and formulation designs is essential. We focused ontransglycosylated compounds which were recently developed by innovation of enzyme synthesis technology and have begun to beused as functional food additives. A transglycosylated compound is the general term for compounds which increase water solubilityby the addition of sugar to an existing compound making it safe and widely used in the food industry. The purpose of this study wasto evaluate the potential of Hsp-G and Stevia-G as pharmaceutical excipients and functional food additives to enhance the dissolutionand absorption of poorly water soluble drugs using a new formulation, as well as an evaluation of the improvement and mechanismof dissolution enhancement effect

A Morphometric Study on Pituitary Pars Intermedia Cells of Male Mice Fed a Liquid Diet Supplemented with Urea(Endocrinology)

Volume: 8Start Page: 899End Page: 90