Collaborative soft object manipulation for game engine-based virtual reality surgery simulators

In this paper we analyse and evaluate the capabilities of popular game engines to simulate and interact with soft objects. We discuss how these engines can be used for simulated surgical training applications, determine their shortcomings and make suggestions how game engines can be extended to make them more suitable for such applications

Polymorphism in TGFB1 is associated with worse non-relapse mortality and overall survival after stem cell transplantation with unrelated donors.

Transforming growth factor beta-1, encoded by the TGFB1 gene, is a cytokine that plays a central role in many physiological and pathogenic processes. We have sequenced TGFB1 regulatory region and assigned allelic genotypes in a large cohort of hematopoietic stem cell transplantation patients and donors. In this study, we analyzed 522 unrelated donor-patient pairs and examined the combined effect of all the common polymorphisms in this genomic region. In univariate analysis, we found that patients carrying a specific allele, 'p001', showed significantly reduced overall survival (5-year overall survival 30.7% for p001/ p001 patients vs. 41.6% others; P=0.032) and increased non-relapse mortality (1-year nonrelapse mortality: 39.0% vs. 25.4%; P=0.039) after transplantation. In multivariate analysis, the presence of a p001/ p001 genotype in patients was confirmed as an independent factor for reduced overall survival [hazard ratio=1.53 (1.04-2.24); P=0.031], and increased non-relapse mortality [hazard ratio=1.73 (1.06-2.83); P=0.030]. In functional experiments we found a trend towards a higher percentage of surface transforming growth factor beta-1-positive regulatory T cells after activation when the cells had a p001 allele (P=0.07). Higher or lower production of transforming growth factor beta-1 in the inflammatory context of hematopoietic stem cell transplantation may influence the development of complications in these patients. Findings indicate that TGFB1 genotype could potentially be of use as a prognostic factor in hematopoietic stem cell transplantation risk assessment algorithms

Attachment styles and personal growth following romantic breakups: The mediating roles of distress, rumination, and tendency to rebound

© 2013 Marshall et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.This article has been made available through the Brunel Open Access Publishing Fund.The purpose of this research was to examine the associations of attachment anxiety and avoidance with personal growth following relationship dissolution, and to test breakup distress, rumination, and tendency to rebound with new partners as mediators of these associations. Study 1 (N = 411) and Study 2 (N = 465) measured attachment style, breakup distress, and personal growth; Study 2 additionally measured ruminative reflection, brooding, and proclivity to rebound with new partners. Structural equation modelling revealed in both studies that anxiety was indirectly associated with greater personal growth through heightened breakup distress, whereas avoidance was indirectly associated with lower personal growth through inhibited breakup distress. Study 2 further showed that the positive association of breakup distress with personal growth was accounted for by enhanced reflection and brooding, and that anxious individuals’ greater personal growth was also explained by their proclivity to rebound. These findings suggest that anxious individuals’ hyperactivated breakup distress may act as a catalyst for personal growth by promoting the cognitive processing of breakup-related thoughts and emotions, whereas avoidant individuals’ deactivated distress may inhibit personal growth by suppressing this cognitive work

Mathematical Modelling of Optical Coherence Tomography

In this chapter a general mathematical model of Optical Coherence Tomography (OCT) is presented on the basis of the electromagnetic theory. OCT produces high resolution images of the inner structure of biological tissues. Images are obtained by measuring the time delay and the intensity of the backscattered light from the sample considering also the coherence properties of light. The scattering problem is considered for a weakly scattering medium located far enough from the detector. The inverse problem is to reconstruct the susceptibility of the medium given the measurements for different positions of the mirror. Different approaches are addressed depending on the different assumptions made about the optical properties of the sample. This procedure is applied to a full field OCT system and an extension to standard (time and frequency domain) OCT is briefly presented.Comment: 28 pages, 5 figures, book chapte

Pulsed electromagnetic energy treatment offers no clinical benefit in reducing the pain of knee osteoarthritis: a systematic review

Background The rehabilitation of knee osteoarthritis often includes electrotherapeutic modalities as well as advice and exercise. One commonly used modality is pulsed electromagnetic field therapy (PEMF). PEMF uses electro magnetically generated fields to promote tissue repair and healing rates. Its equivocal benefit over placebo treatment has been previously suggested however recently a number of randomised controlled trials have been published that have allowed a systematic review to be conducted. Methods A systematic review of the literature from 1966 to 2005 was undertaken. Relevant computerised bibliographic databases were searched and papers reviewed independently by two reviewers for quality using validated criteria for assessment. The key outcomes of pain and functional disability were analysed with weighted and standardised mean differences being calculated. Results Five randomised controlled trials comparing PEMF with placebo were identified. The weighted mean differences of the five papers for improvement in pain and function, were small and their 95% confidence intervals included the null. Conclusion This systematic review provides further evidence that PEMF has little value in the management of knee osteoarthritis. There appears to be clear evidence for the recommendation that PEMF does not significantly reduce the pain of knee osteoarthritis

Hip fracture risk assessment: Artificial neural network outperforms conditional logistic regression in an age- and sex-matched case control study

Copyright @ 2013 Tseng et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background - Osteoporotic hip fractures with a significant morbidity and excess mortality among the elderly have imposed huge health and economic burdens on societies worldwide. In this age- and sex-matched case control study, we examined the risk factors of hip fractures and assessed the fracture risk by conditional logistic regression (CLR) and ensemble artificial neural network (ANN). The performances of these two classifiers were compared. Methods - The study population consisted of 217 pairs (149 women and 68 men) of fractures and controls with an age older than 60 years. All the participants were interviewed with the same standardized questionnaire including questions on 66 risk factors in 12 categories. Univariate CLR analysis was initially conducted to examine the unadjusted odds ratio of all potential risk factors. The significant risk factors were then tested by multivariate analyses. For fracture risk assessment, the participants were randomly divided into modeling and testing datasets for 10-fold cross validation analyses. The predicting models built by CLR and ANN in modeling datasets were applied to testing datasets for generalization study. The performances, including discrimination and calibration, were compared with non-parametric Wilcoxon tests. Results - In univariate CLR analyses, 16 variables achieved significant level, and six of them remained significant in multivariate analyses, including low T score, low BMI, low MMSE score, milk intake, walking difficulty, and significant fall at home. For discrimination, ANN outperformed CLR in both 16- and 6-variable analyses in modeling and testing datasets (p?<?0.005). For calibration, ANN outperformed CLR only in 16-variable analyses in modeling and testing datasets (p?=?0.013 and 0.047, respectively). Conclusions - The risk factors of hip fracture are more personal than environmental. With adequate model construction, ANN may outperform CLR in both discrimination and calibration. ANN seems to have not been developed to its full potential and efforts should be made to improve its performance.National Health Research Institutes in Taiwa

Visual parameter optimisation for biomedical image processing

Background: Biomedical image processing methods require users to optimise input parameters to ensure high quality output. This presents two challenges. First, it is difficult to optimise multiple input parameters for multiple input images. Second, it is difficult to achieve an understanding of underlying algorithms, in particular, relationships between input and output. Results: We present a visualisation method that transforms users’ ability to understand algorithm behaviour by integrating input and output, and by supporting exploration of their relationships. We discuss its application to a colour deconvolution technique for stained histology images and show how it enabled a domain expert to identify suitable parameter values for the deconvolution of two types of images, and metrics to quantify deconvolution performance. It also enabled a breakthrough in understanding by invalidating an underlying assumption about the algorithm. Conclusions: The visualisation method presented here provides analysis capability for multiple inputs and outputs in biomedical image processing that is not supported by previous analysis software. The analysis supported by our method is not feasible with conventional trial-and-error approaches