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Objective Predicting survival of patients with epithelial ovarian cancer (EOC) is based on prognosis of the population. Combining prognostic factors could facilitate survival prediction on the level of the individual patient. The aim of this study was to develop a prognostic model to predict five-year disease specific survival in patients with EOC, and to evaluate whether this would add to prediction based on prognosis of the population. Patients and methods A retrospective cohort study was performed of all EOC patients treated with primary debulking and adjuvant chemotherapy or neo-adjuvant chemotherapy and interval debulking surgery in three gynaecological-oncologic centres between 1998 and 2010. Primary outcome was 5-year disease-specific survival. We developed a Cox proportional hazard model using the LASSO-method to select the best combination of characteristics from 12 potential predictors and to correct for overfitting. Performance of the model was expressed as calibration and discrimination (c-statistic). A nomogram was developed to increase the clinical applicability of the model. Results Of 840 patients with EOC 462 (55%) died within 5 years due to the disease. A combination of FIGO stage, residual tumour after surgery, primary or interval surgery, histology, performance status, age, amount of ascites and a family history suggestive of breast/ovarian cancer best predicted 5-year survival. The final model showed accurate calibration and the c-statistic was 0.71 (95% CI 0.69-0.74). Conclusions Five-year survival in all stage EOC patients can be predicted accurately using available characteristics. After external validation the model can be used for counselling of patients. [ABSTRACT FROM AUTHOR]

The aim of this study was to validate the flow patterns measured by high-resolution, time-resolved, three-dimensional phase contrast MRI in a real-size intracranial aneurysm phantom. Retrospectively gated three-dimensional phase contrast MRI was performed in an intracranial aneurysm phantom at a resolution of 0.2 × 0.2 × 0.3 mm3 in a solenoid rat coil. Both steady and pulsatile flows were applied. The phase contrast MRI measurements were compared with particle image velocimetry measurements and computational fluid dynamics simulations. A quantitative comparison was performed by calculating the differences between the magnitude of the velocity vectors and angles between the velocity vectors in corresponding voxels. Qualitative analysis of the results was executed by visual inspection and comparison of the flow patterns. The root-mean-square errors of the velocity magnitude in the comparison between phase contrast MRI and computational fluid dynamics were 5% and 4% of the maximum phase contrast MRI velocity, and the medians of the angle distribution between corresponding velocity vectors were 16° and 14° for the steady and pulsatile measurements, respectively. In the phase contrast MRI and particle image velocimetry comparison, the root-mean-square errors were 12% and 10% of the maximum phase contrast MRI velocity, and the medians of the angle distribution between corresponding velocity vectors were 19° and 15° for the steady and pulsatile measurements, respectively. Good agreement was found in the qualitative comparison of flow patterns between the phase contrast MRI measurements and both particle image velocimetry measurements and computational fluid dynamics simulations. High-resolution, time-resolved, three-dimensional phase contrast MRI can accurately measure complex flow patterns in an intracranial aneurysm phantom. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Phenotypic information on individual protein composition of cows is important for many aspects of dairy processing with cheese production as the center of gravity. However, measuring individual protein composition is expensive and time consuming. In this study, we investigated whether protein composition can be predicted based on inexpensive and routinely measured milk Fourier transform infrared (FTIR) spectra. Based on 900 calibration and 900 validation samples that had both capillary zone electrophoresis (CZE)-determined protein composition and FTIR spectra available, low to moderate validation R² were reached (from 0.18 for αS1-casein to 0.56 for β-lactoglobulin). The potential usefulness of this model on the phenotypic level was investigated by means of achieved selection differentials for 25% of the best animals. For α-lactalbumin (R² = 0.20), the selection differential amounted to 0.18 g/100 g and for casein index (R² = 0.50) to 1.24 g/100 g. We concluded that predictions of protein composition were not accurate enough to enable selection of individual animals. However, for specific purposes when, for example, groups of animals that meet a certain threshold are to be selected, the presented model could be useful in practice on the phenotypic level. The potential usefulness of this model on the genetic level was investigated by means of genetic correlations between CZE-determined and FTIR-predicted protein composition traits. The genetic correlations ranged from 0.62 (β-casein) to 0.97 (whey). Thus, predictions of protein composition, when used as input to estimate breeding values, provide an excellent means for genetic improvement of protein composition. In addition, estimated repeatabilities based on 3 repeated observations of predicted protein composition showed that a considerable amount of prediction error can be removed using repeated observations. [ABSTRACT FROM AUTHOR]

β-Lactoglobulin (β-LG) genotypes are associated with differences in bovine milk protein composition. Therefore, β-LG genotypes are of direct relevance for the dairy industry. In this study, we predicted β-lactoglobulin genotypes based on routinely recorded milk Fourier t β ransform infrared spectra using 500 calibration samples. The results show that 76% of the cows carrying the β-LG AA genotype, 80% of the cows carrying the β-LG AB genotype, and 66% of the cows carrying the β-LG BB genotype were predicted correctly. Furthermore, the prediction of β-LG genotypes based on Fourier transform infrared spectra showed a repeatability of 0.85. We discuss how the combined use of predicted β-LG genotypes, pedigree information, and β-LG genotypes derived using other methods could lead to further improvement in the percentage of correctly predicted β-LG genotypes. The presented methodology is easy and inexpensive and could ultimately provide β-LG genotypes at the individual cow level. [ABSTRACT FROM AUTHOR]

The behaviour of a miniature calorimetric sensor, which is under consideration for catheter-based coronary-artery-flow assessment, is investigated in both steady and pulsatile tube flows. The sensor is composed of a heating element operated at constant power and two thermopiles that measure flow-induced temperature differences over the sensor surface. An analytical sensor model is developed, which includes axial heat conduction in the fluid and a simple representation of the solid wall, assuming a quasi-steady sensor response to the pulsatile flow. To reduce the mathematical problem, described by a two-dimensional advection–diffusion equation, a spectral method is applied. A Fourier transform is then used to solve the resulting set of ordinary differential equations and an analytical expression for the fluid temperature is found. To validate the analytical model, experiments with the sensor mounted in a tube have been performed in steady and pulsatile water flows with various amplitudes and Strouhal numbers. Experimental results are generally in good agreement with theory and show a quasi-steady sensor response in the coronary-flow regime. The model can therefore be used to optimize the sensor design for coronary-flow assessment. [ABSTRACT FROM AUTHOR]

It has recently been shown that Fourier transform infrared spectroscopy has potential for the prediction of detailed milk fat composition, even based on a limited number of observations. Therefore, there seems to be an opportunity for improvement by means of using more observations. The objective of this study was to verify whether the use of more data would add to the accuracy of predicting milk fat composition. In addition, the effect of season on modeling was quantified because large differences in milk fat composition between winter and summer samples exist. We concluded that the use of 3,622 observations does increase predictability of milk fat composition based on infrared spectroscopy. However, for fatty acids with low concentrations, the use of many observations does not increase predictability to a level at which application of the model becomes obvious. Furthermore, the effect of season on validation r-square was limited but was occasionally large on prediction bias. For fatty acids that show large differences in level and standard deviation between winter and summer, a representative sample that includes observations collected in various seasons is critical for unbiased prediction. This research shows that all major fatty acids, combined groups of fatty acids, and the ratio of saturated to unsaturated fatty acids can be predicted accurately. [ABSTRACT FROM AUTHOR]

Background Up to one-third of labouring women will experience painful ‘back labour’. Sterile water injected lateral to the lumbosacral spine is a simple and well-researched approach to this pain. Objective To determine if sterile water injection for low back pain compared to placebo or alternative therapy increased or decreased the rate of Caesarean section. Search strategy We performed a literature search with no language restriction in four databases: the Cochrane library, EMBASE (1980–2009), Ovid Medline (1950–2009) and CINAHL (1982–2009). Selection criteria We included all randomised controlled trials (RCTs) of sterile water injection for labour pain that included outcomes of interest and original data. Data collection and analysis We compared Caesarean section rates among women who received sterile water injection in labour with those who received either placebo treatment or another non-pharmacological treatment modality. Other outcomes included pain scores, use of regional analgesia and women’s assessment of treatment. We used Revman 5 for the meta-analysis. Data were entered by one reviewer and independently cross-checked. Pooled outcomes were reported as Relative Risk (RR) or Weighted Mean Difference using Mantel–Haenszel fixed-effects model except when the I2 value >50% indicated significant heterogeneity in which case random-effects model was used. Main results We included eight RCTs. The Caesarean section rate was 4.6% in the sterile water injection group and 9.9% in the comparison group ( n = 828) (RR 0.51, 95% CI: 0.30, 0.87). Conclusion We believe that a large RCT should be mounted to validate our findings regarding the impact of sterile water injections on mode of delivery. [ABSTRACT FROM AUTHOR]

This paper seeks to determine the macro-economic impacts of changes in health care provision. The resource allocation issues have been explored in theory, by applying the Rybczynski theorem, and empirically, using a computable general equilibrium (CGE) model for the UK with a detailed health component. From the theory, changes in non-health outputs are shown to depend on factor-bias and scale effects, the net effects generally being indeterminate. From the applied model, a rise in the National Health Service (NHS) budget is shown to yield overall welfare gains, which fall by two-thirds assuming health care-specific factors. A nominally equivalent migration policy yields even higher welfare gains. [ABSTRACT FROM AUTHOR]

A particle-based track-before-detect filtering algorithm is presented. This algorithm incorporates the Swerling family of target amplitude fluctuation models in order to capture the effect of radar cross-section changes that a target would present to a sensor over time. The filter is designed with an existence variable, to determine the presence of a target in the data, and an efficient method of incorporating this variable in a particle filter scheme is developed. Results of the algorithm on simulated data show a significant gain in detection performance through accurately modelling the target amplitude fluctuations. [ABSTRACT FROM AUTHOR]