Serum erythropoietin levels in paroxysmal nocturnal haemoglobinuria: Implications for therapy

In order to assess the rationale and possible indications for the use of recombinant erythropoietin in paroxysmal nocturnal haemoglobinuria (PNH), we have measured endogenous erythropoietin (Epo) levels in 18 patients with PNH and in 44 patients with iron deficiency anaemia (IDA), In both groups of patients we found a significant inverse correlation between Epo and haemoglobin (Hb). However, the mean Epo level was significantly higher in the PNH group (385 mU/ml) than in the IDA group (136 mU/ml), The range of Epo levels at any given Hb was greater in the PNH group than in the IDA group. There was a significant positive correlation between Epo and absolute reticulocyte count, Since Epo administration is unlikely to benefit patients with high levels of endogenous Epo, we conclude that in the majority of patients with PNH there is no indication for treatment with Epo.

A constraints-based resource discovery model for multi-provider cloud environments

Increasingly infrastructure providers are supplying the cloud marketplace with storage and on-demand compute resources to host cloud applications. From an application user's point of view, it is desirable to identify the most appropriate set of available resources on which to execute an application. Resource choice can be complex and may involve comparing available hardware specifications, operating systems, value-added services, such as network configuration or data replication, and operating costs, such as hosting cost and data throughput. Providers' cost models often change and new commodity cost models, such as spot pricing, have been introduced to offer significant savings. In this paper, a software abstraction layer is used to discover infrastructure resources for a particular application, across multiple providers, by using a two-phase constraints-based approach. In the first phase, a set of possible infrastructure resources are identified for a given application. In the second phase, a heuristic is used to select the most appropriate resources from the initial set. For some applications a cost-based heuristic is most appropriate; for others a performance-based heuristic may be used. A financial services application and a high performance computing application are used to illustrate the execution of the proposed resource discovery mechanism. The experimental result shows the proposed model could dynamically select an appropriate set of resouces that match the application's requirements.