Photochemical and thermal decomposition of solids

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Pure Red Cell Aplasia Caused by Acute Hepatitis A

Pure red cell aplasia is characterized as a normocytic anemia associated with reticulocytopenia and the absence of erythroblasts in the bone marrow. Pure red cell aplasia can be induced by various causes such as thymoma, connective tissue disease, viral infection, lymphoma, and adverse drug reactions. There have been only a few reports of pure red cell aplasia associated with acute viral hepatitis A. In Korea, no case of pure red cell aplasia caused by acute hepatitis A has yet been reported. We recently experienced a case of acute viral hepatitis A complicated by pure red cell aplasia. The patient was successfully treated with corticosteroids. Here we report this case and review the literature

Acquired pure red cell aplasia: updated review of treatment

Pure red cell aplasia (PRCA) is a syndrome characterized by a severe normocytic anaemia, reticulocytopenia, and absence of erythroblasts from an otherwise normal bone marrow. Primary PRCA, or secondary PRCA which has not responded to treatment of the underlying disease, is treated as an immunologically-mediated disease. Although vigorous immunosuppressive treatments induce and maintain remissions in a majority of patients, they carry an increased risk of serious complications. Corticosteroids were used in the treatment of PRCA and this has been considered the treatment of first choice although relapse is not uncommon. Cyclosporine A (CsA) has become established as one of the leading drugs for treatment of PRCA. However, common concerns have been the number of patients treated with CsA who achieve sustained remissions and the number that relapse. This article reviews the current status of CsA therapy and compares it to other treatments for diverse PRCAs

Epstein-Barr virus-positive recipient type B-cells survive in a "complete chimera" after allogeneic bone-marrow transplantation

Latency of Epstein-Barr virus infection may be generated by surviving immortalized B cells or by continuous re-infection. EBV-positive B-cell tumors have been found following bone-marrow transplantation (BMT) and were of donor type in the few cases investigated. We established a B-cell line from the bone marrow of a patient in complete remission following allogeneic BMT for aplastic anemia 18 months post-grafting. Differences in sex and isoenzymes allowed an exact determination of chimerism in our case. While the patient showed persistent complete chimerism of all cell lineages, cells grown in culture were of recipient type. They expressed B-cell markers, showed a monoclonal rearrangement of the immunoglobulin genes and carried EBV-associated antigens. As direct preparations of cells from the patient did not contain detectable recipient-type cells, it appeared likely that small numbers of EBV-transformed B cells of the recipient survived for long periods in this patient. For the development of secondary B-cell neoplasms in vivo, additional patho-physiological steps like severe graft versus host disease or T-cell suppression are obviously required because the patient was still free of lymphoma 3 years post-grafting

Performance Modeling using a Genetic Programming Based Model Error Correction Procedure

Application performance models provide insight to designers of high performance computing (HPC) systems on the role of subsystems such as the processor or the network in determining application performance and allow HPC centers to more accurately target procurements to resource requirements. Performance models can also be used to identify application performance bottlenecks and to provide insights about scalability issues. The suitability of a performance model, however, for a particular performance investigation is a function of both the accuracy and the cost of the model. A semi-empirical model developed in an earlier publication for an astrophysics application was shown to be inaccurate when predicting communication cost for large numbers of processors. It was hypothesized that this deficiency is due to the inability of the model to adequately capture communication contention (threshold effects) as well as other un-modeled components such as noise and I⁄O contention. This thesis demonstrates a new approach to capture these unknown features to improve the predictive capabilities of the model. This approach uses a systematic model error correction procedure that uses evolutionary algorithms to find an error correction term to augment the existing model. Four variations of this procedure were investigated and all were shown to produce improved results than the old model. Successful cross-platform application of this approach showed that it adequately captures machine dependent characteristics. This approach was then extended to a second application, which too showed improved results than the standard semi-empirical modeling approach