71 research outputs found

    Considerations on the Castrop formula for calculation of intraocular lens power

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    Background: To explain the concept of the Castrop lens power calculation formula and show the application and results from a large dataset compared to classical formulae. Methods: The Castrop vergence formula is based on a pseudophakic model eye with 4 refractive surfaces. This was compared against the SRKT, Hoffer-Q, Holladay1, simplified Haigis with 1 optimized constant and Haigis formula with 3 optimized constants. A large dataset of preoperative biometric values, lens power data and postoperative refraction data was split into training and test sets. The training data were used for formula constant optimization, and the test data for cross-validation. Constant optimization was performed for all formulae using nonlinear optimization, minimising root mean squared prediction error. Results: The constants for all formulae were derived with the Levenberg-Marquardt algorithm. Applying these constants to the test data, the Castrop formula showed a slightly better performance compared to the classical formulae in terms of prediction error and absolute prediction error. Using the Castrop formula, the standard deviation of the prediction error was lowest at 0.45 dpt, and 95% of all eyes in the test data were within the limit of 0.9 dpt of prediction error. Conclusion: The calculation concept of the Castrop formula and one potential option for optimization of the 3 Castrop formula constants (C, H, and R) are presented. In a large dataset of 1452 data points the performance of the Castrop formula was slightly superior to the respective results of the classical formulae such as SRKT, Hoffer-Q, Holladay1 or Haigis

    Spatiotemporal scaling of North American continental interior wetlands: implications for shorebird conservation

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    Within interior North America, erratic weather patterns and heterogeneous wetland complexes cause wide spatio-temporal variation in the resources available to migrating shorebirds. Identifying the pattern-generating components of landscape-level resources and the scales at which shorebirds respond to these patterns will better facilitate conservation efforts for these species. We constructed descriptive models that identified weather variables associated with creating the spatio-temporal patterns of shorebird habitat in ten landscapes in north-central Oklahoma. We developed a metric capable of measuring the dynamic composition and configuration of shorebird habitat in the region and used field data to empirically estimate the spatial scale at which shorebirds respond to the amount and configuration of habitat. Precipitation, temperature, solar radiation and wind speed best explained the incidence of wetland habitat, but relationships varied among wetland types. Shorebird occurrence patterns were best explained by habitat density estimates at a 1.5 km scale. This model correctly classified 86 % of shorebird observations. At this scale, when habitat density was low, shorebirds occurred in 5 % of surveyed habitat patches but occurrence reached 60 % when habitat density was high. Our results suggest scale dependence in the habitat-use patterns of migratory shorebirds. We discuss potential implications of our results and how integrating this information into conservation efforts may improve conservation strategies and management practices

    Avian Use of Perennial Biomass Feedstocks as Post-Breeding and Migratory Stopover Habitat

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    Increased production of biomass crops in North America will require new agricultural land, intensify the cultivation of land already under production and introduce new types of biomass crops. Assessing the potential biodiversity impacts of novel agricultural systems is fundamental to the maintenance of biodiversity in agricultural landscapes, yet the consequences of expanded biomass production remain unclear. We evaluate the ability of two candidate second generation biomass feedstocks (switchgrass, Panicum virgatum, and mixed-grass prairie) not currently managed as crops to act as post-breeding and fall migratory stopover habitat for birds. In total, we detected 41 bird species, including grassland specialists and species of state and national conservation concern (e.g. Henslow's Sparrow, Ammodramus henslowii). Avian species richness was generally comparable in switchgrass and prairie and increased with patch size in both patch types. Grassland specialists were less abundant and less likely to occur in patches within highly forested landscapes and were more common and likely to occur in larger patches, indicating that this group is also area-sensitive outside of the breeding season. Variation in the biomass and richness of arthropod food within patches was generally unrelated to richness and abundance metrics. Total bird abundance and that of grassland specialists was higher in patches with greater vegetation structural heterogeneity. Collectively, we find that perennial biomass feedstocks have potential to provide post-breeding and migratory stopover habitat for birds, but that the placement and management of crops will be critical factors in determining their suitability for species of conservation concern. Industrialization of cellulosic bioenergy production that results in reduced crop structural heterogeneity is likely to dramatically reduce the suitability of perennial biomass crops for birds

    A knowledge-based taxonomy of critical factors for adopting electronic health record systems by physicians: a systematic literature review

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    <p>Abstract</p> <p>Background</p> <p>The health care sector is an area of social and economic interest in several countries; therefore, there have been lots of efforts in the use of electronic health records. Nevertheless, there is evidence suggesting that these systems have not been adopted as it was expected, and although there are some proposals to support their adoption, the proposed support is not by means of information and communication technology which can provide automatic tools of support. The aim of this study is to identify the critical adoption factors for electronic health records by physicians and to use them as a guide to support their adoption process automatically.</p> <p>Methods</p> <p>This paper presents, based on the PRISMA statement, a systematic literature review in electronic databases with adoption studies of electronic health records published in English. Software applications that manage and process the data in the electronic health record have been considered, i.e.: computerized physician prescription, electronic medical records, and electronic capture of clinical data. Our review was conducted with the purpose of obtaining a taxonomy of the physicians main barriers for adopting electronic health records, that can be addressed by means of information and communication technology; in particular with the information technology roles of the knowledge management processes. Which take us to the question that we want to address in this work: "What are the critical adoption factors of electronic health records that can be supported by information and communication technology?". Reports from eight databases covering electronic health records adoption studies in the medical domain, in particular those focused on physicians, were analyzed.</p> <p>Results</p> <p>The review identifies two main issues: 1) a knowledge-based classification of critical factors for adopting electronic health records by physicians; and 2) the definition of a base for the design of a conceptual framework for supporting the design of knowledge-based systems, to assist the adoption process of electronic health records in an automatic fashion. From our review, six critical adoption factors have been identified: user attitude towards information systems, workflow impact, interoperability, technical support, communication among users, and expert support. The main limitation of the taxonomy is the different impact of the adoption factors of electronic health records reported by some studies depending on the type of practice, setting, or attention level; however, these features are a determinant aspect with regard to the adoption rate for the latter rather than the presence of a specific critical adoption factor.</p> <p>Conclusions</p> <p>The critical adoption factors established here provide a sound theoretical basis for research to understand, support, and facilitate the adoption of electronic health records to physicians in benefit of patients.</p

    Genome-wide association study and meta-analysis in multiple populations identifies new loci for peanut allergy and establishes C11orf30/EMSY as a genetic risk factor for food allergy

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    BACKGROUND: Peanut allergy (PA) is a complex disease with both environmental and genetic risk factors. Previously PA loci were identified in FLG and HLA in candidate gene studies, and loci in HLA in a genome-wide association study and meta-analysis. OBJECTIVE: To investigate genetic susceptibility to PA. METHODS: Eight hundred and fifty cases and 926 hyper-controls and >7.8 million genotyped and imputed single nucleotide polymorphisms (SNPs) were analyzed in a genome-wide association study to identify susceptibility variants for PA in the Canadian population. Meta-analysis of two phenotypes (PA and food allergy) was conducted using 7 studies from the Canadian, American (2), Australian, German and Dutch (2) populations. RESULTS: A SNP near ITGA6 reached genome-wide significance with PA (p=1.80×10(-8)), while SNPs associated with SKAP1, MMP12/MMP13, CTNNA3, ARHGAP24, ANGPT4, c11orf30 (EMSY), and EXOC4 reached a threshold suggestive of association (p≤1.49×10(-6)). In the meta-analysis of PA, loci in or near ITGA6, ANGPT4, MMP12/MMP13, c11orf30 and EXOC4 were significant (p≤1.49×10(-6)). When a phenotype of any food allergy was used for meta-analysis, the c11orf30 locus reached genome-wide significance (p=7.50×10(-11)), while SNPs associated with ITGA6, ANGPT4, MMP12/MMP13, EXOC4 and additional c11orf30 SNPs were suggestive (p≤1.49×10(-6)). Functional annotation indicated SKAP1 regulates expression of CBX1, which co-localizes with the EMSY protein coded by c11orf30. CONCLUSION: This study identifies multiple novel loci as risk factors for PA and food allergy and establishes c11orf30 as a risk locus for both peanut and food allergy. Multiple genes (c11orf30/EMSY, SKAP1 and CTNNA3) identified by this study are involved in epigenetic regulation of gene expression
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