99mTc generator using molybdenum nanoparticles

The version of record of this article, first published in Journal of Radioanalytical and Nuclear Chemistry, is available online at Publisher’s website: https://doi.org/10.1007/s10967-023-09173-

Biochemical characterization of reactive nitrogen species by eosinophil peroxidase in tyrosine nitration

It is well known that eosinophils are involved in tyrosine nitration. In this study, we evaluated tyrosine nitration by rat eosinophils isolated from peritoneal fl uid and constituent eosinophils in the stomach. Rat peritoneal eosinophils activated with 1 &#956;M phorbol myristate acetate (PMA) and 50 &#956;M NO2 &#65437; showed immunostaining for nitrotyrosine only in smaller cells, despite the fact that eosinophils are capable of producing superoxide (O2·&#65437;). Free tyrosine nitrating capacity after incubation with PMA and NO2 &#65437; was 4-fold higher in eosinophils than in neutrophils. Catalase and &#65400;- and &#65402; -tocopherol inhibited free tyrosine nitration by reactive nitrogen species from eosinophils but not that by peroxynitrite. Superoxide dismutase augmented free tyrosine nitration by activated eosinophils and peroxynitrite. The concentration of nitric oxide released from eosinophils was relatively low (0.32 &#956;M/106 cells/h) and did not contribute to the formation of nitrotyrosine. On the other hand, most constituent eosinophils constituent in the rat stomach stimulated by PMA and NO2 &#65437; showed tyrosine nitration capacity. These results suggest that intact cells other than apoptotic-like eosinophils eluted in the intraperitoneal cavity could not generate reactive species responsible for nitration by a peroxidase-dependent mechanism. In contrast, normal eosinophils in the stomach were capable of nitration, suggesting that the characteristics of eosinophils in gastric mucosa are diff erent from those eluted in the peritoneal cavity.</p

Research Activities in the Department of Medical Engineering

The Department of Medical Engineering is dedicated to the research and educational activities to fulfill its mission as educating medical professionals in medical engineering under the diploma policy and curriculum policy, that is, "research and education aiming for fostering professionals competent in comprehensive resolving capacity based upon a wide field of knowledge and vision in clinical engineering, which can be attained by wearing the basic knowledge of medical science and engineering." For this reason, the Faculty of the Department of Medical Engineering is composed of the two areas; PhDs in engineering-based clinical medicine, and mainly MDs in medical sciences and clinical medicine. To summarize the research activities at the Department of Medical Engineering, the authors will describe the overview of research activities being performed in the Department of Medical Engineering Fields, by dividing into 1) Research in Biomedical Engineering Fields, and 2) Research in Medical Science and Clinical Engineering Fields

Research Promotion in Nursing, Physiotherapy, Occupational Therapy and Medical Engineering - Appeal and Recommendation to the Colleague -

[Summary] Despite of the severe situations of insufficient money, labor, time, and communication, we want to promote the research activity in our university to the level of major institutions. The first step we propose is to acquire the external research grants from public resources. The specific proposal is described in grant application to increase the probability of successful adoption of the grant from the Ministry of Education and Science of Japan

Extraction of Error Detection Rules without Supervised Information from Log Files Using Automatically Defined Groups

Abstract- Our main aim is to extract multiple rules from log files in the computer systems, to detect various levels of errors, and to inform these errors or configuration mistakes to the system administrators automatically, in order to manage them without expert knowledge. To satisfy this aim, we performed an extraction experiment from the log files of a system using Automatically Defined Groups (ADG), which is based on Genetic Programming. Moreover, we focused on &quot;System State Pattern &quot; related to the difference between normal daily state and abnormal state that some errors occur in the system. In this experiment, then, we tried to extract rules without any manually managed and supervised information, by using simple translation technique: regular expressions. As a result, 50 agents in the best individual were divided into 16 groups from 322 log files. This means that 16 rules were acquired. We confirmed these rules could detect some errors such as DNS configuration error. We could also find the importance of the rules because the rule with more agents tended to have a higher adopted frequency by evolutionary computation. Therefore, we consider that our method using ADG is useful for the diagnosis of computer systems, and helps administrators manage their systems without expert knowledge about their systems. I