STUDY OF URANIUM SORPTION AND DESORPTION ON SOME TURKISH CLAYS

The sorption and desorption of uranium on two different clay samples which are obtained from the deposit located in Turgutlu and Kula have been studied by application of a batch technique. The two types of clay materials are Ca-montmorillonite. The uranium concentration range was between 200-3000 ppm. Experimental procedures are outlined and results for uranium contacted with montmorillonite are reported and discussed. The sorption/desorption isotherms were reversible and non-linear for this concentration range. The relative importance of test parameters e.g., pH, clay particle size, temperature, ground water composition, contact - time, solid/water ratio which require definition in order to arrive at meaningful distribution coefficients were carried out. The sorption coefficients varied between 0.65-1.45 and 0.45-1.14 for Kula clay and for Turgutlu clay, respectively. The data could be fitted to Freundlich and Langmuir isotherms. The quantity of the sorbed and desorbed uranium ions was much lower than its theoretical CEC's. This was attributed to a blocking of montmorillonite's CEC by uranium islands sorbed in interlayer. The results have shown that the test parameters can have a marked effect on sorption and the present work provides further evidence of the need to take account of the presence of such materials in safety assessment modeling

Severe osteomalacia in a patient with idiopathic chronic pancreatitis

We report a 30-year-old woman who was confined to a wheelchair because of severe myopatly. She was first seen by a neurologist because of a convulsive syndrome of unknown etiology when she was nine. She was started on anticonvulsive drugs but the drug was stopped when her serum calcium level was found to be very low. She had a history from childhood of steatorrhea and abdominal pain after a fatty meal and became vegetarian at age five years. She worked in a hospital as a nurse and at home her living room received no direct sunlight. As a result of these conditions osteomalacia progressed. We believe an awareness of chronic pancreatitis (CP) during childhood could have prevented the consequences of the disease in this case

Natural language processing for structuring clinical text data on depression using UK-CRIS

Background Utilisation of routinely collected electronic health records from secondary care offers unprecedented possibilities for medical science research but can also present difficulties. One key issue is that medical information is presented as free-form text and, therefore, requires time commitment from clinicians to manually extract salient information. Natural language processing (NLP) methods can be used to automatically extract clinically relevant information. Objective Our aim is to use natural language processing (NLP) to capture real-world data on individuals with depression from the Clinical Record Interactive Search (CRIS) clinical text to foster the use of electronic healthcare data in mental health research. Methods We used a combination of methods to extract salient information from electronic health records. First, clinical experts define the information of interest and subsequently build the training and testing corpora for statistical models. Second, we built and fine-tuned the statistical models using active learning procedures. Findings Results show a high degree of accuracy in the extraction of drug-related information. Contrastingly, a much lower degree of accuracy is demonstrated in relation to auxiliary variables. In combination with state-of-the-art active learning paradigms, the performance of the model increases considerably. Conclusions This study illustrates the feasibility of using the natural language processing models and proposes a research pipeline to be used for accurately extracting information from electronic health records. Clinical implications Real-world, individual patient data are an invaluable source of information, which can be used to better personalise treatment.</p