{Twisted Poincar\'e Series and Geometric Factorization of Affine Weyl Groups

We study the relation between the alternating product of twisted Poincar'e series of parabolic subgroups of affine Weyl groups and hyperbolic stabilizers of geodesic tubes. Moreover, from such relation, we find a length-preserving factorization of affine Weyl groups of type $\tilde{A}_n$ and $\tilde{C}_n$

Оценка квалификации выпускника фармацевтического факультета с позиций компетентностного подхода

конкурентоспособностьОБРАЗОВАНИЕ ФАРМАЦЕВТИЧЕСКОЕпровизорыПРОФЕССИОНАЛЬНАЯ КОМПЕТЕНТНОСТ

Direct growth of ultra-long platinum nanolawns on a semiconductor photocatalyst

A template- and surfactant-free process, thermally assisted photoreduction, is developed to prepare vertically grown ultra-long Pt nanowires (NWs) (about 30-40 nm in diameter, 5-6 μm in length, and up to 80 NWs/100 μm2 in the wire density) on TiO2 coated substrates, including Si wafers and carbon fibers, with the assistance of the photocatalytic ability and semiconductor characteristics of TiO2. A remarkable aspect ratio of up to 200 can be achieved. TEM analytical results suggest that the Pt NWs are single-crystalline with a preferred 〈111〉 growth direction. The precursor adopted and the heat treatment conditions are crucial for the yield of NWs. The photoelectrons supplied by TiO2 gives rise to the formation of nano-sized Pt nuclei from salt melt or solution. The subsequent growth of NWs is supported by the thermal electrons which also generated from TiO2 during the post thermal treatment. The interactions between the ions and the electrons in the Pt/TiO2 junction are discussed in this study

Development of a deep learning-based tool to assist wound classification

This paper presents a deep learning-based wound classification tool that can assist medical personnel in non-wound care specialization to classify five key wound conditions, namely deep wound, infected wound, arterial wound, venous wound, and pressure wound, given color images captured using readily available cameras. The accuracy of the classification is vital for appropriate wound management. The proposed wound classification method adopts a multi-task deep learning framework that leverages the relationships among the five key wound conditions for a unified wound classification architecture. With differences in Cohen's kappa coefficients as the metrics to compare our proposed model with humans, the performance of our model was better or non-inferior to those of all human medical personnel. Our convolutional neural network-based model is the first to classify five tasks of deep, infected, arterial, venous, and pressure wounds simultaneously with good accuracy. The proposed model is compact and matches or exceeds the performance of human doctors and nurses. Medical personnel who do not specialize in wound care can potentially benefit from an app equipped with the proposed deep learning model

Transgenic Expression of Decoy Receptor 3 Protects Islets from Spontaneous and Chemical-induced Autoimmune Destruction in Nonobese Diabetic Mice

Decoy receptor 3 (DCR3) halts both Fas ligand– and LIGHT-induced cell deaths, which are required for pancreatic β cell damage in autoimmune diabetes. To directly investigate the therapeutic potential of DCR3 in preventing this disease, we generated transgenic nonobese diabetic mice, which overexpressed DCR3 in β cells. Transgenic DCR3 protected mice from autoimmune and cyclophosphamide-induced diabetes in a dose-dependent manner and significantly reduced the severity of insulitis. Local expression of the transgene did not alter the diabetogenic properties of systemic lymphocytes or the development of T helper 1 or T regulatory cells. The transgenic islets had a higher transplantation success rate and survived for longer than wild-type islets. We have demonstrated for the first time that the immune-evasion function of DCR3 inhibits autoimmunity and that genetic manipulation of grafts may improve the success and survival of islet transplants

Combined Phytochemistry and Chemotaxis Assays for Identification and Mechanistic Analysis of Anti-Inflammatory Phytochemicals in Fallopia japonica

Plants provide a rich source of lead compounds for a variety of diseases. A novel approach combining phytochemistry and chemotaxis assays was developed and used to identify and study the mechanisms of action of the active compounds in F. japonica, a medicinal herb traditionally used to treat inflammation. Based on a bioactivity-guided purification strategy, two anthranoids, emodin and physcion, were identified from F. japonica. Spectroscopic techniques were used to characterize its crude extract, fractions and phytochemicals. The crude extract, chloroform fraction, and anthranoids of F. japonica significantly inhibited CXCR4-mediated chemotaxis. Mechanistic studies showed that emodin and physcion inhibited chemotaxis via inactivating the MEK/ERK pathway. Moreover, the crude extract and emodin could prevent or treat type 1 diabetes in non-obese diabetic (NOD) mice. This study illustrates the applicability of a combinational approach for the study of anti-inflammatory medicine and shows the potential of F. japonica and its anthranoids for anti-inflammatory therapy