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Suggests that much of the trouble people have with numbers is linguistic. Points out differences between language and mathematical dimensions of math terms. Gives tips concerning reading of math problems, finding out what messages children are receiving, and the importance of basic number facts and estimation. (RH)

Dorset HealthCare NHS Trust is a three-star specialist mental health and learning disability trust, serving a population of 450,000 people living in east Dorset and also providing some services across [...]

Abstract Background This paper examines the cost and benefits, both financial and environmental, of two leading forms of solar power generation, grid-tied photovoltaic cells and Dish Stirling Systems, using conventional carbon-based fuel as a benchmark. Methods First we define how these solar technologies will be implemented and why. Then we delineate a model city and its characteristics, which will be used to test the two methods of solar-powered electric distribution. Then we set the constraining assumptions for each technology, which serve as parameters for our calculations. Finally, we calculate the present value of the total cost of conventional energy needed to power our model city and use this as a benchmark when analyzing both solar models’ benefits and costs. Results The preeminent form of distributed electricity generation, grid-tied photovoltaic cells under net-metering, allow individual homeowners a degree of electric self-sufficiency while often turning a profit. However, substantial subsidies are required to make the investment sensible. Meanwhile, large dish Stirling engine installations have a significantly higher potential rate of return, but face a number of pragmatic limitations. Conclusions This paper concludes that both technologies are a sensible investment for consumers, but given that the dish Stirling consumer receives 6.37 dollars per watt while the home photovoltaic system consumer receives between 0.9 and 1.70 dollars per watt, the former appears to be a superior option. Despite the large investment, this paper deduces that it is far more feasible to get few strong investors to develop a solar farm of this magnitude, than to get 150,000 households to install photovoltaic arrays in their roofs. Potential implications of the solar farm construction include an environmental impact given the size of land require for this endeavour. However, the positive aspects, which include a large CO2 emission reduction aggregated over the lifespan of the farm, outweigh any minor concerns or potential externalities.

Abstract Background Molecular dynamics (MD) simulation is a powerful technique for sampling the meta-stable and transitional conformations of proteins and other biomolecules. Computational data clustering has emerged as a useful, automated technique for extracting conformational states from MD simulation data. Despite extensive application, relatively little work has been done to determine if the clustering algorithms are actually extracting useful information. A primary goal of this paper therefore is to provide such an understanding through a detailed analysis of data clustering applied to a series of increasingly complex biopolymer models. Results We develop a novel series of models using basic polymer theory that have intuitive, clearly-defined dynamics and exhibit the essential properties that we are seeking to identify in MD simulations of real biomolecules. We then apply spectral clustering, an algorithm particularly well-suited for clustering polymer structures, to our models and MD simulations of several intrinsically disordered proteins. Clustering results for the polymer models provide clear evidence that the meta-stable and transitional conformations are detected by the algorithm. The results for the polymer models also help guide the analysis of the disordered protein simulations by comparing and contrasting the statistical properties of the extracted clusters. Conclusions We have developed a framework for validating the performance and utility of clustering algorithms for studying molecular biopolymer simulations that utilizes several analytic and dynamic polymer models which exhibit well-behaved dynamics including: meta-stable states, transition states, helical structures, and stochastic dynamics. We show that spectral clustering is robust to anomalies introduced by structural alignment and that different structural classes of intrinsically disordered proteins can be reliably discriminated from the clustering results. To our knowledge, our framework is the first to utilize model polymers to rigorously test the utility of clustering algorithms for studying biopolymers.

Abstract Background The HL7 Clinical Document Architecture (CDA) constrains the HL7 Reference Information model (RIM) to specify the format of HL7-compliant clinical documents, dubbed CDA documents. The use of clinical terminologies such as SNOMED CT® further improves interoperability as they provide a shared understanding of concepts used in clinical documents. However, despite the use of the RIM and of shared terminologies such as SNOMED CT®, gaps remain as to how to use both the RIM and SNOMED CT® in HL7 clinical documents. The HL7 implementation guide on Using SNOMED CT in HL7 Version 3 is an effort to close this gap. It is, however, a human-readable document that is not suited for automatic processing. As such, health care professionals designing clinical documents need to ensure validity of documents manually. Results We represent the CDA using the Ontology Web Language OWL and further use the OWL version of SNOMED CT® to enable the translation of CDA documents to so-called OWL ontologies. We formalize a subset of the constraints in the implementation guide on Using SNOMED CT in HL7 Version 3 as OWL Integrity Constraints and show that we can automatically validate CDA documents using OWL reasoners such as Pellet. Finally, we evaluate our approach via a prototype implementation that plugs in the Open Health Workbench. Conclusions We present a methodology to automatically check the validity of CDA documents which make reference to SNOMED CT® terminology. The methodology relies on semantic technologies such as OWL. As such it removes the burden from IT health care professionals of having to manually implement such guidelines in systems that use HL7 Version 3 documents.

Abstract Background Autosomal dominant inheritance of germline mutations in the bone morphogenetic protein receptor type 2 (BMPR2) gene are a major risk factor for pulmonary arterial hypertension (PAH). While previous studies demonstrated a difference in severity between BMPR2 mutation carriers and noncarriers, it is likely disease severity is not equal among BMPR2 mutations. We hypothesized that patients with missense BMPR2 mutations have more severe disease than those with truncating mutations. Methods Testing for BMPR2 mutations was performed in 169 patients with PAH (125 with a family history of PAH and 44 with sporadic disease). Of the 106 patients with a detectable BMPR2 mutation, lymphocytes were available in 96 to functionally assess the nonsense-mediated decay pathway of RNA surveillance. Phenotypic characteristics were compared between BMPR2 mutation carriers and noncarriers, as well as between those carriers with a missense versus truncating mutation. Results While there was a statistically significant difference in age at diagnosis between carriers and noncarriers, subgroup analysis revealed this to be the case only for females. Among carriers, there was no difference in age at diagnosis, death, or survival according to exonic location of the BMPR2 mutation. However, patients with missense mutations had statistically significant younger ages at diagnosis and death, as well as shorter survival from diagnosis to death or lung transplantation than those with truncating mutations. Consistent with this data, the majority of missense mutations were penetrant prior to age 36 years, while the majority of truncating mutations were penetrant after age 36 years. Conclusion In this cohort, BMPR2 mutation carriers have more severe PAH disease than noncarriers, but this is only the case for females. Among carriers, patients with missense mutations that escape nonsense-mediated decay have more severe disease than those with truncating mutations. These findings suggest that treatment and prevention strategies directed specifically at BMPR2 pathway defects may need to vary according to the type of mutation.

Abstract Background While BMPR2 mutation strongly predisposes to pulmonary arterial hypertension (PAH), only 20% of mutation carriers develop clinical disease. This finding suggests that modifier genes contribute to FPAH clinical expression. Since modifiers are likely to be common alleles, this problem is not tractable by traditional genetic approaches. Furthermore, examination of gene expression is complicated by confounding effects attributable to drugs and the disease process itself. Methods To resolve these problems, B-cells were isolated, EBV-immortalized, and cultured from familial PAH patients with BMPR2 mutations, mutation positive but disease-free family members, and family members without mutation. This allows examination of differences in gene expression without drug or disease-related effects. These differences were assayed by Affymetrix array, with follow-up by quantitative RT-PCR and additional statistical analyses. Results By gene array, we found consistent alterations in multiple pathways with known relationship to PAH, including actin organization, immune function, calcium balance, growth, and apoptosis. Selected genes were verified by quantitative RT-PCR using a larger sample set. One of these, CYP1B1, had tenfold lower expression than control groups in female but not male PAH patients. Analysis of overrepresented gene ontology groups suggests that risk of disease correlates with alterations in pathways more strongly than with any specific gene within those pathways. Conclusion Disease status in BMPR2 mutation carriers was correlated with alterations in proliferation, GTP signaling, and stress response pathway expression. The estrogen metabolizing gene CYP1B1 is a strong candidate as a modifier gene in female PAH patients.

Abstract Background Robust, programmatically accessible biomedical information services that syntactically and semantically interoperate with other resources are challenging to construct. Such systems require the adoption of common information models, data representations and terminology standards as well as documented application programming interfaces (APIs). The National Cancer Institute (NCI) developed the cancer common ontologic representation environment (caCORE) to provide the infrastructure necessary to achieve interoperability across the systems it develops or sponsors. The caCORE Software Development Kit (SDK) was designed to provide developers both within and outside the NCI with the tools needed to construct such interoperable software systems. Results The caCORE SDK requires a Unified Modeling Language (UML) tool to begin the development workflow with the construction of a domain information model in the form of a UML Class Diagram. Models are annotated with concepts and definitions from a description logic terminology source using the Semantic Connector component. The annotated model is registered in the Cancer Data Standards Repository (caDSR) using the UML Loader component. System software is automatically generated using the Codegen component, which produces middleware that runs on an application server. The caCORE SDK was initially tested and validated using a seven-class UML model, and has been used to generate the caCORE production system, which includes models with dozens of classes. The deployed system supports access through object-oriented APIs with consistent syntax for retrieval of any type of data object across all classes in the original UML model. The caCORE SDK is currently being used by several development teams, including by participants in the cancer biomedical informatics grid (caBIG) program, to create compatible data services. caBIG compatibility standards are based upon caCORE resources, and thus the caCORE SDK has emerged as a key enabling technology for caBIG. Conclusion The caCORE SDK substantially lowers the barrier to implementing systems that are syntactically and semantically interoperable by providing workflow and automation tools that standardize and expedite modeling, development, and deployment. It has gained acceptance among developers in the caBIG program, and is expected to provide a common mechanism for creating data service nodes on the data grid that is under development.