The Radial Structure of the Cygnus Loop Supernova Remnant --- Possible evidence of a cavity explosion ---

We observed the North-East (NE) Limb toward the center region of the Cygnus Loop with the ASCA Observatory. We found a radial variation of electron temperature (kTe) and ionization timescale (log(\tau)) whereas no variation could be found for the abundances of heavy elements. In this paper, we re-analyzed the same data set and new observations with the latest calibration files. Then we constructed the precise spatial variations of kTe, log(\tau), and abundances of O, Ne, Mg, Si, and Fe over the field of view (FOV). We found a spatial variation not only in kTe and in log(\tau) but also in most of heavy elements. As described in Miyata et al. (1994), values of kTe increase and those of log(\tau) decrease toward the inner region. We found that the abundance of heavy elements increases toward the inner region. The radial profiles of O, Ne, and Fe show clear jump structures at a radius of 0.9 Rs, where Rs is the shock radius. Outside of 0.9 Rs, abundances of all elements are constant. On the contrary, inside of 0.9 Rs, abundances of these elements are 20--30 % larger than those obtained outside of 0.9 Rs. The radial profile of kTe also shows the jump structure at 0.9 Rs. This means that the hot and metal rich plasma fills the volume inside of 0.9 Rs. We concluded that this jump structure was the possible evidence for the pre-existing cavity produced by the precursor. If the ejecta fills inside of 0.9 Rs, the total mass of the ejecta was roughly 4\Msun. We then estimated the main-sequence mass to be roughly 15\Msun, which supports the massive star in origin of the Cygnus Loop supernova remnant and the existence of a pre-existing cavity.Comment: 37 pages, 14 figures. Accepted for publication of Ap

Thrombospondins in the heart: potential functions in cardiac remodeling

Cardiac remodeling after myocardial injury involves inflammation, angiogenesis, left ventricular hypertrophy and matrix remodeling. Thrombospondins (TSPs) belong to the group of matricellular proteins, which are non-structural extracellular matrix proteins that modulate cell–matrix interactions and cell function in injured tissues or tumors. They interact with different matrix and membrane-bound proteins due to their diverse functional domains. That the expression of TSPs strongly increases during cardiac stress or injury indicates an important role for them during cardiac remodeling. Recently, the protective properties of TSP expression against heart failure have been acknowledged. The current review will focus on the biological role of TSPs in the ischemic and hypertensive heart, and will describe the functional consequences of TSP polymorphisms in cardiac disease

Strategic research agenda for biomedical imaging

This Strategic Research Agenda identifies current challenges and needs in healthcare, illustrates how biomedical imaging and derived data can help to address these, and aims to stimulate dedicated research funding efforts. Medicine is currently moving towards a more tailored, patient-centric approach by providing personalised solutions for the individual patient. Innovation in biomedical imaging plays a key role in this process as it addresses the current needs for individualised prevention, treatment, therapy response monitoring, and image-guided surgery. The use of non-invasive biomarkers facilitates better therapy prediction and monitoring, leading to improved patient outcomes. Innovative diagnostic imaging technologies provide information about disease characteristics which, coupled with biological, genetic and -omics data, will contribute to an individualised diagnosis and therapy approach. In the emerging field of theranostics, imaging tools together with therapeutic agents enable the selection of best treatments and allow tailored therapeutic interventions. For prenatal monitoring, the use of innovative imaging technologies can ensure an early detection of malfunctions or disease. The application of biomedical imaging for diagnosis and management of lifestyle-induced diseases will help to avoid disease development through lifestyle changes. Artificial intelligence and machine learning in imaging will facilitate the improvement of image interpretation and lead to better disease prediction and therapy planning. As biomedical imaging technologies and analysis of existing imaging data provide solutions to current challenges and needs in healthcare, appropriate funding for dedicated research is needed to implement the innovative approaches for the wellbeing of citizens and patients

Untersuchung kathodenrelevanter Prozesse in Pseudofunkenschaltern mit emissionsspektroskopischen und elektrischen Messmethoden

SIGLEAvailable from TIB Hannover: DW 7026 / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman