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https://www.selleckchem.com/products/rocilinostat-acy-1215.html RESULTS Kidney damage induced by CIS was confirmed by the increase of creatinine, urea and uric acid levels in the blood of juvenile rats. The renal oxidative disturbance was characterized by an increase in the levels of thiobarbituric acid reactive substances (TBARS), protein carbonyl, and nitrogen oxides (Nox), as well as the decrease in non-protein thiol content (NPSH), glutathione-S-transferase (GST), catalase (CAT) and superoxide dismutase (SOD) activities. CIS inhibited the activities of δ-aminolevulinic acid dehydratase (δ-ALA-D) and Na+, K+-ATPase and down-regulated the Nrf2/Keap-1/HO-1 pathway in the kidney of juvenile rats. CONCLUSION Both Ebselen and (PhSe)2 modulated back to the normal levels all parameters altered by the CIS administration in the kidney of juvenile rats. Thus, this study shows that (PhSe)2 was as effective as Ebselen in protecting the kidney against oxidative damage caused by CIS in rats. PURPOSE To design and evaluate a self-trainable natural language processing (NLP)-based procedure to classify unstructured radiology reports. The method enabling the generation of curated datasets is exemplified on CT pulmonary angiogram (CTPA) reports. METHOD We extracted the impressions of CTPA reports created at our institution from 2016 to 2018 (n = 4397; language German). The status (pulmonary embolism yes/no) was manually labelled for all exams. Data from 2016/2017 (n = 2801) served as a ground truth to train three NLP architectures that only require a subset of reference datasets for training to be operative. The three architectures were as follows a convolutional neural network (CNN), a support vector machine (SVM) and a random forest (RF) classifier. Impressions of 2018 (n = 1377) were kept aside and used for general performance measurements. Furthermore, we investigated the dependence of classification performance on the amount of training data with multiple simulations. RESULTS

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