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Background: Complex care management is seen as an approach to face the challenges of an ageing society with increasing numbers of patients with complex care needs. The Medical Research Council in the United Kingdom has proposed a framework for the development and evaluation of complex interventions that will be used to develop and evaluate a primary care-based complex care management program for chronically ill patients at high risk for future hospitalization in Germany. Methods and design: We present a multi-method procedure to develop a complex care management program to implement interventions aimed at reducing potentially avoidable hospitalizations for primary care patients with type 2 diabetes mellitus, chronic obstructive pulmonary disease, or chronic heart failure and a high likelihood of hospitalization. The procedure will start with reflection about underlying precipitating factors of hospitalizations and how they may be targeted by the planned intervention (pre-clinical phase). An intervention model will then be developed (phase I) based on theory, literature, and exploratory studies (phase II). Exploratory studies are planned that entail the recruitment of 200 patients from 10 general practices. Eligible patients will be identified using two ways of 'case finding': software based predictive modelling and physicians' proposal of patients based on clinical experience. The resulting subpopulations will be compared regarding healthcare utilization, care needs and resources using insurance claims data, a patient survey, and chart review. Qualitative studies with healthcare professionals and patients will be undertaken to identify potential barriers and enablers for optimal performance of the complex care management program. Discussion: This multi-method procedure will support the development of a primary care-based care management program enabling the implementation of interventions that will potentially reduce avoidable hospitalizations.
Background: Pythium ultimum (P. ultimum) is a ubiquitous oomycete plant pathogen responsible for a variety of diseases on a broad range of crop and ornamental species. Results: The P. ultimum genome (42.8 Mb) encodes 15,290 genes and has extensive sequence similarity and synteny with related Phytophthora species, including the potato blight pathogen Phytophthora infestans. Whole transcriptome sequencing revealed expression of 86% of genes, with detectable differential expression of suites of genes under abiotic stress and in the presence of a host. The predicted proteome includes a large repertoire of proteins involved in plant pathogen interactions although surprisingly, the P. ultimum genome does not encode any classical RXLR effectors and relatively few Crinkler genes in comparison to related phytopathogenic oomycetes. A lower number of enzymes involved in carbohydrate metabolism were present compared to Phytophthora species, with the notable absence of cutinases, suggesting a significant difference in virulence mechanisms between P. ultimum and more host specific oomycete species. Although we observed a high degree of orthology with Phytophthora genomes, there were novel features of the P. ultimum proteome including an expansion of genes involved in proteolysis and genes unique to Pythium. We identified a small gene family of cadherins, proteins involved in cell adhesion, the first report in a genome outside the metazoans. Conclusions: Access to the P. ultimum genome has revealed not only core pathogenic mechanisms within the oomycetes but also lineage specific genes associated with the alternative virulence and lifestyles found within the pythiaceous lineages compared to the Peronosporaceae.
During a 4-week run in October–November 2006, a pilot experiment was performed at the CERN Proton Synchrotron in preparation for the Cosmics Leaving OUtdoor Droplets (CLOUD) experiment, whose aim is to study the possible influence of cosmic rays on clouds. The purpose of the pilot experiment was firstly to carry out exploratory measurements of the effect of ionising particle radiation on aerosol formation from trace H2SO4 vapour and secondly to provide technical input for the CLOUD design. A total of 44 nucleation bursts were produced and recorded, with formation rates of particles above the 3 nm detection threshold of between 0.1 and 100 cm -3 s -1, and growth rates between 2 and 37 nm h -1. The corresponding H2O concentrations were typically around 106 cm -3 or less. The experimentally-measured formation rates and htwosofour concentrations are comparable to those found in the atmosphere, supporting the idea that sulphuric acid is involved in the nucleation of atmospheric aerosols. However, sulphuric acid alone is not able to explain the observed rapid growth rates, which suggests the presence of additional trace vapours in the aerosol chamber, whose identity is unknown. By analysing the charged fraction, a few of the aerosol bursts appear to have a contribution from ion-induced nucleation and ion-ion recombination to form neutral clusters. Some indications were also found for the accelerator beam timing and intensity to influence the aerosol particle formation rate at the highest experimental SO2 concentrations of 6 ppb, although none was found at lower concentrations. Overall, the exploratory measurements provide suggestive evidence for ion-induced nucleation or ion-ion recombination as sources of aerosol particles. However in order to quantify the conditions under which ion processes become significant, improvements are needed in controlling the experimental variables and in the reproducibility of the experiments. Finally, concerning technical aspects, the most important lessons for the CLOUD design include the stringent requirement of internal cleanliness of the aerosol chamber, as well as maintenance of extremely stable temperatures (variations below 0.1 °C)