Nature of light correlations in ghost imaging

We investigate the nature of correlations in Gaussian light sources used for ghost imaging. We adopt methods from quantum information theory to distinguish genuinely quantum from classical correlations. Combining a microscopic analysis of speckle-speckle correlations with an effective coarse-grained description of the beams, we show that quantum correlations exist even in `classical'-like thermal light sources, and appear relevant for the implementation of ghost imaging in the regime of low illumination. We further demonstrate that the total correlations in the thermal source beams effectively determine the quality of the imaging, as quantified by the signal-to-noise ratio.Comment: 12 pages, 5 figures. To appear in Scientific Reports (NPG

Agent based modelling helps in understanding the rules by which fibroblasts support keratinocyte colony formation

Background: Autologous keratincoytes are routinely expanded using irradiated mouse fibroblasts and bovine serum for clinical use. With growing concerns about the safety of these xenobiotic materials, it is desirable to culture keratinocytes in media without animal derived products. An improved understanding of epithelial/mesenchymal interactions could assist in this. Methodology/Principal Findings: A keratincyte/fibroblast o-culture model was developed by extending an agent-based keratinocyte colony formation model to include the response of keratinocytes to both fibroblasts and serum. The model was validated by comparison of the in virtuo and in vitro multicellular behaviour of keratinocytes and fibroblasts in single and co-culture in Greens medium. To test the robustness of the model, several properties of the fibroblasts were changed to investigate their influence on the multicellular morphogenesis of keratinocyes and fibroblasts. The model was then used to generate hypotheses to explore the interactions of both proliferative and growth arrested fibroblasts with keratinocytes. The key predictions arising from the model which were confirmed by in vitro experiments were that 1) the ratio of fibroblasts to keratinocytes would critically influence keratinocyte colony expansion, 2) this ratio needed to be optimum at the beginning of the co-culture, 3) proliferative fibroblasts would be more effective than irradiated cells in expanding keratinocytes and 4) in the presence of an adequate number of fibroblasts, keratinocyte expansion would be independent of serum. Conclusions: A closely associated computational and biological approach is a powerful tool for understanding complex biological systems such as the interactions between keratinocytes and fibroblasts. The key outcome of this study is the finding that the early addition of a critical ratio of proliferative fibroblasts can give rapid keratinocyte expansion without the use of irradiated mouse fibroblasts and bovine serum

Reciprocity as a foundation of financial economics

This paper argues that the subsistence of the fundamental theorem of contemporary financial mathematics is the ethical concept ‘reciprocity’. The argument is based on identifying an equivalence between the contemporary, and ostensibly ‘value neutral’, Fundamental Theory of Asset Pricing with theories of mathematical probability that emerged in the seventeenth century in the context of the ethical assessment of commercial contracts in a framework of Aristotelian ethics. This observation, the main claim of the paper, is justified on the basis of results from the Ultimatum Game and is analysed within a framework of Pragmatic philosophy. The analysis leads to the explanatory hypothesis that markets are centres of communicative action with reciprocity as a rule of discourse. The purpose of the paper is to reorientate financial economics to emphasise the objectives of cooperation and social cohesion and to this end, we offer specific policy advice

SimHap GUI: An intuitive graphical user interface for genetic association analysis

<p>Abstract</p> <p>Background</p> <p>Researchers wishing to conduct genetic association analysis involving single nucleotide polymorphisms (SNPs) or haplotypes are often confronted with the lack of user-friendly graphical analysis tools, requiring sophisticated statistical and informatics expertise to perform relatively straightforward tasks. Tools, such as the <it>SimHap </it>package for the R statistics language, provide the necessary statistical operations to conduct sophisticated genetic analysis, but lacks a graphical user interface that allows anyone but a professional statistician to effectively utilise the tool.</p> <p>Results</p> <p>We have developed SimHap GUI, a cross-platform integrated graphical analysis tool for conducting epidemiological, single SNP and haplotype-based association analysis. SimHap GUI features a novel workflow interface that guides the user through each logical step of the analysis process, making it accessible to both novice and advanced users. This tool provides a seamless interface to the <it>SimHap </it>R package, while providing enhanced functionality such as sophisticated data checking, automated data conversion, and real-time estimations of haplotype simulation progress.</p> <p>Conclusion</p> <p>SimHap GUI provides a novel, easy-to-use, cross-platform solution for conducting a range of genetic and non-genetic association analyses. This provides a free alternative to commercial statistics packages that is specifically designed for genetic association analysis.</p

Delay Of Insulin Addition To Oral Combination Therapy Despite Inadequate Glycemic Control: Delay of Insulin Therapy

BACKGROUND: Patients and providers may be reluctant to escalate to insulin therapy despite inadequate glycemic control. OBJECTIVES: To determine the proportion of patients attaining and maintaining glycemic targets after initiating sulfonylurea and metformin oral combination therapy (SU/MET); to assess insulin initiation among patients failing SU/MET; and to estimate the glycemic burden incurred, stratified by whether HbA(1c) goal was attained and maintained. DESIGN: Longitudinal observational cohort study. SUBJECTS: Type 2 diabetes patients, 3,891, who newly initiated SU/MET between 1 January 1996 and 31 December 2000. MEASUREMENTS: Subjects were followed until insulin was added, health plan disenrolment, or until 31 December 2005. We calculated the number of months subjects continued SU/MET therapy alone, in total, and during periods of inadequate glycemic control; the A1C reached during those time periods; and total glycemic burden, defined as the estimated cumulative monthly difference between measured A1C and 8%. RESULTS: During a mean follow-up of 54.6 ± 28.6 months, 41.9% of the subjects added insulin, and 11.8% received maximal doses of both oral agents. Over half of SU/MET patients attained but failed to maintain A1C of 8%, yet continued SU/MET therapy for an average of nearly 3 years, sustaining glycemic burden equivalent to nearly 32 months of A1C levels of 9%. Another 18% of patients never attained the 8% goal with SU/MET, yet continued that therapy for an average of 30 months, reaching mean A1C levels of 10%. CONCLUSIONS: Despite inadequate glycemic control, a minority of patients added insulin or maximized oral agent doses, thus, incurring substantial glycemic burden on SU/MET. Additional studies are needed to examine the benefits of rapid titration to maximum doses and earlier initiation of insulin therapy

Segmentation of epidermal tissue with histopathological damage in images of haematoxylin and eosin stained human skin.

Background: Digital image analysis has the potential to address issues surrounding traditional histological techniques including a lack of objectivity and high variability, through the application of quantitative analysis. A key initial step in image analysis is the identification of regions of interest. A widely applied methodology is that of segmentation. This paper proposes the application of image analysis techniques to segment skin tissue with varying degrees of histopathological damage. The segmentation of human tissue is challenging as a consequence of the complexity of the tissue structures and inconsistencies in tissue preparation, hence there is a need for a new robust method with the capability to handle the additional challenges materialising from histopathological damage.Methods: A new algorithm has been developed which combines enhanced colour information, created following a transformation to the L*a*b* colourspace, with general image intensity information. A colour normalisation step is included to enhance the algorithm's robustness to variations in the lighting and staining of the input images. The resulting optimised image is subjected to thresholding and the segmentation is fine-tuned using a combination of morphological processing and object classification rules. The segmentation algorithm was tested on 40 digital images of haematoxylin & eosin (H&E) stained skin biopsies. Accuracy, sensitivity and specificity of the algorithmic procedure were assessed through the comparison of the proposed methodology against manual methods.Results: Experimental results show the proposed fully automated methodology segments the epidermis with a mean specificity of 97.7%, a mean sensitivity of 89.4% and a mean accuracy of 96.5%. When a simple user interaction step is included, the specificity increases to 98.0%, the sensitivity to 91.0% and the accuracy to 96.8%. The algorithm segments effectively for different severities of tissue damage.Conclusions: Epidermal segmentation is a crucial first step in a range of applications including melanoma detection and the assessment of histopathological damage in skin. The proposed methodology is able to segment the epidermis with different levels of histological damage. The basic method framework could be applied to segmentation of other epithelial tissues

Epstein-Barr virus infection and chronic lymphocytic leukemia: a possible progression factor?

Epstein-Barr virus is pathogenically associated with a well defined group of lymphoid and epithelial tumors in which the virus directly drives transformation of infected cells. Recent evidence however indicates that this virus may infect a subpopulation of tumor cells in patients with chronic lymphocytic leukemia (CLL) and EBV infection has been also associated with Richter transformation in a fraction of cases. We herein review available data suggesting a possible role of EBV as a direct or micro-environmental progression factor in a subset of CLL

Variable selection under multiple imputation using the bootstrap in a prognostic study

Background: Missing data is a challenging problem in many prognostic studies. Multiple imputation (MI) accounts for imputation uncertainty that allows for adequate statistical testing. We developed and tested a methodology combining MI with bootstrapping techniques for studying prognostic variable selection. Method: In our prospective cohort study we merged data from three different randomized controlled trials (RCTs) to assess prognostic variables for chronicity of low back pain. Among the outcome and prognostic variables data were missing in the range of 0 and 48.1%. We used four methods to investigate the influence of respectively sampling and imputation variation: MI only, bootstrap only, and two methods that combine MI and bootstrapping. Variables were selected based on the inclusion frequency of each prognostic variable, i.e. the proportion of times that the variable appeared in the model. The discriminative and calibrative abilities of prognostic models developed by the four methods were assessed at different inclusion levels. Results: We found that the effect of imputation variation on the inclusion frequency was larger than the effect of sampling variation. When MI and bootstrapping were combined at the range of 0% (full model) to 90% of variable selection, bootstrap corrected c-index values of 0.70 to 0.71 and slope values of 0.64 to 0.86 were found. Conclusion: We recommend to account for both imputation and sampling variation in sets of missing data. The new procedure of combining MI with bootstrapping for variable selection, results in multivariable prognostic models with good performance and is therefore attractive to apply on data sets with missing values

Self-rated health and factors influencing responses among young Egyptian type 1 diabetes patients

<p>Abstract</p> <p>Background</p> <p>Patients diagnosed with type 1 diabetes mellitus (T1DM) face major daily challenges. Self-rated health (SRH) is a global measure of an individual's health related quality of life (HRQoL) and is based on the question, "In general, how would you rate your health?" Subjects rate their health as excellent, very good, good, poor or very poor. Our objective was to determine the HRQoL using the SRH measure and determine factors influencing responses. We hypothesized that better SRH responses were associated with shorter diabetes duration, better compliance and better glycemic control.</p> <p>Methods</p> <p>The standardized SRH measure was the instrument used for health related quality of life assessment. Logistic regression analysis was used to examine the association between SRH responses and selected variables.</p> <p>Results</p> <p>124 subjects, 64 females (51.6%) and 60 males (48.4%) were included. Average age was 13.08 (±3.19) and average diabetes duration was 5.82 (±1.60), while the mean HbA₁C was 8.02 (±1.60). The majority rated their health as good (31%), 29% rated it as excellent, 11% as very good, 14% as poor and 15% as very poor. Regression analysis showed that regular exercise was the only predictor that was independently and significantly associated with a "better" self-health rating, with an OR of 12.84, CI of 1.425-115.727 and a <it>p </it>value of 0.023.</p> <p>Conclusion</p> <p>Regular exercise among Egyptian children with T1DM is strongly associated with a "better" overall health related quality of life and should be repeatedly encouraged.</p