Dinesen Guldbrandsen (karateroom92)

ETHNOPHARMACOLOGICAL RELEVANCE Paeoniae Radix Alba (PRA, called baishao in China), the root of Paeonia lactiflora Pall., has shown a rich medicinal value for more than 2000 years. PRA is used in local medicine and traditional medicine for autoimmune diseases associated with inflammation. At present, total glucosides of paeony (TGP), the main active ingredient of PRA, has been developed into a preparation for the treatment of autoimmune diseases, as TGP exhibits the effect of regulating immunity, anti-inflammatory, and analgesic effects. AIM OF THE REVIEW TGP was developed and applied to inflammation-related autoimmune diseases in modern clinical practice. selleck chemicals llc Based on its application in traditional prescriptions, this article reviews PRA's botany and phytochemistry (including its extraction process and quality control), and discusses the clinical application and pharmacological research of TGP as an anti-inflammatory drug from the perspective of ethnopharmacology. Additionally, we review modern pharmacological an pharmacological research on TGP is based on the traditional usage of PRA, and its folk medicinal value in the treatment of autoimmune diseases has now been verified. In particular, TGP has been developed into a formulation used clinically for the treatment of autoimmune diseases. The combination of TGP capsules and chemicals to treat autoimmune diseases has the effect of increasing efficacy and reducing toxicity. Based on further research on its preparation, quality control, and mechanisms of action, TGP is expected to eventually play a greater role in the treatment of autoimmune diseases. V.An open-source library of implementations for deep-learning-based image segmentation and outcomes models based on radiotherapy and radiomics is presented. As oncology treatment planning becomes increasingly driven by automation, such a library of model implementations is crucial to (i) validate existing models on datasets collected at different institutions, (ii) automate segmentation, (iii) create ensembles for improving performance and (iv) incorporate validated models in the clinical workflow. Inclusion of deep-learning-based image segmentation and outcomes models in the same library provides a fully automated and reproduceable pipeline to estimate prognosis. The library was developed with the Computational Environment for Radiological Research (CERR) software platform. Centralizing model implementations in CERR builds upon its rich set of radiotherapy and radiomics tools and caters to the world-wide user base. CERR provides well-validated feature extraction pipelines for radiotherapy dosimetry and radiomics with fine control over the calculation settings, allowing users to select appropriate parameters used in model derivation. Models for automatic image segmentation are distributed via containers, allowing them to be deployed with a variety of scientific computing architectures. The library includes implementations of popular DVH-based models outlined in the Quantitative Analysis of Normal Tissue Effects in the Clinic effort and recently published literature. Radiomics models include features from the Image Biomarker Standardization Initiative and application-specific features found to be relevant across multiple sites and image modalities. The library is distributed as a module within CERR at https// under the GNU-GPL copyleft with additional restrictions on clinical and commercial use and provision to dual license in future. PURPOSE The aim of this study is to introduce a novel DWI-MRI phantom and to compare Apparent Diffusion Coefficient (ADC) measurements, utilizing EPI-DWI and HASTE-DWI sequences and two different fitting algorithms. MATERIALS AND METHODS 23 test tubes with different sucrose concentrations and polyacrylamide gels were used as a phantom for ADC measurements. The phantom was scanned on a clinical MRI system (1.5 T) over a two-month period utilizing an EPI-