Three-dimensional aspects of fluid flows in channels. I. Meniscus and thin film regimes

We study the forced displacement of a fluid-fluid interface in a three-dimensional channel formed by two parallel solid plates. Using a lattice-Boltzmann method, we study situations in which a slip velocity arises from diffusion effects near the contact line. The difference between the slip and channel velocities determines whether the interface advances as a meniscus or a thin film of fluid is left adhered to the plates. We find that this effect is controlled by the capillary and Péclet numbers. We estimate the crossover from a meniscus to a thin film and find good agreement with numerical results. The penetration regime is examined in the steady state. We find that the occupation fraction of the advancing finger relative to the channel thickness is controlled by the capillary number and the viscosity contrast between the fluids. For high viscosity contrast, lattice-Boltzmann results agree with previous results. For zero viscosity contrast, we observe remarkably narrow fingers. The shape of the finger is found to be universal.

High-resolution ultrasonography of subretinal structure and assessment of retina degeneration in rat.

The purpose of this work was to evaluate the ability of 80 MHz ultrasonography to differentiate intra-retinal layers and quantitatively assess photoreceptor dystrophy in small animal models. Four groups of 10 RCS rats each (five dystrophic and five controls) were explored at 25, 35, 45 and 55 days post-natal (PN). A series of retina cross-sections were obtained ex vivo from outside intact eyes using an 80 MHz three-dimensional ultrasound backscatter microscope (20-microm-axial resolution). Ultrasound features of normal retina were correlated to those of corresponding histology and thickness measurements of photoreceptor segment and nuclear layers were performed on all groups. To show the ability of 80 MHz ultrasonography to distinguish the retinal degeneration in vivo, one RCS rat was explored at 25 and 55 days post-natal. Ultrasound image of normal retina displayed four distinct layers marked by reflections at neurites/nuclei interfaces and permitted to differentiate the photoreceptor segment and nuclear layers. The backscatter level from the retina was shown to be related to the size, density and organization of the intra-layer structure. Ultrasound thickness measurements highly correlated with histologic measurements. A thinning (p<0.05) of outer nuclear layer (ONL) was detected over time for controls and was thought to be assigned to retina maturation. Retinal degeneration started at PN35 and resulted in a more pronounced ONL thinning (p<0.05) over time. ONL degeneration was accompanied by segment layer thickening (p<0.05) at PN35 and thinning thereafter. These changes may indicate accumulation of outer segment debris at PN35 then progressive destruction. In vivo images of rat intra-retinal structure showed the ability of the method to distinguish the photoreceptor layer changes. Our results indicate that 80 MHz ultrasonography reveals intra-retinal layers and is sensitive to age and degenerative changes of photoreceptors. This technique has great potential to follow-up retinal dystrophy and therapeutic effects in vivo.

Individual prediction of cognitive decline in mild cognitive impairment using support vector machine-based analysis of diffusion tensor imaging data.

Although cross-sectional diffusion tensor imaging (DTI) studies revealed significant white matter changes in mild cognitive impairment (MCI), the utility of this technique in predicting further cognitive decline is debated. Thirty-five healthy controls (HC) and 67 MCI subjects with DTI baseline data were neuropsychologically assessed at one year. Among them, there were 40 stable (sMCI; 9 single domain amnestic, 7 single domain frontal, 24 multiple domain) and 27 were progressive (pMCI; 7 single domain amnestic, 4 single domain frontal, 16 multiple domain). Fractional anisotropy (FA) and longitudinal, radial, and mean diffusivity were measured using Tract-Based Spatial Statistics. Statistics included group comparisons and individual classification of MCI cases using support vector machines (SVM). FA was significantly higher in HC compared to MCI in a distributed network including the ventral part of the corpus callosum, right temporal and frontal pathways. There were no significant group-level differences between sMCI versus pMCI or between MCI subtypes after correction for multiple comparisons. However, SVM analysis allowed for an individual classification with accuracies up to 91.4% (HC versus MCI) and 98.4% (sMCI versus pMCI). When considering the MCI subgroups separately, the minimum SVM classification accuracy for stable versus progressive cognitive decline was 97.5% in the multiple domain MCI group. SVM analysis of DTI data provided highly accurate individual classification of stable versus progressive MCI regardless of MCI subtype, indicating that this method may become an easily applicable tool for early individual detection of MCI subjects evolving to dementia.

Regulation of peptidase activity in a three-dimensional aggregate model of brain tumor vasculature.

The abnormal vascular system of brain cancers inappropriately expresses membrane proteins, including proteolytic enzymes, ultimately resulting in blood extravasation. The production of inflammatory mediators, such as cytokines and nitric oxide, and tumor hypoxia have been implicated in these effects. We have previously shown that the activity of aminopeptidase A is increased in the abnormal vascular system of human and rat brain tumors. To study the mechanisms regulating the activities of peptidases in cerebral vasculature in brain tumors, we have developed a three-dimensional model of differentiated rat brain cells in aggregate cultures in which rat brain microvessels were incorporated. The secretion of interleukin-6 (IL-6) in the culture medium of aggregates was used as an indicator of inflammatory activation. Addition to these aggregates of C6 glioma cell medium (C6-CM) conditioned under hypoxic or normoxic conditions or serum mimicked tumor-dependent hypoxia or conditions of dysfunction of brain tumor vasculature. Hypoxic and normoxic C6-CM, but not serum, regulated peptidase activity in aggregates, and in particular it increased the activity of aminopeptidase A determined using histoenzymography. Serum, but not C6-CM, increased IL-6 production, but did not increase aminopeptidase A activity in aggregates. Thus soluble glioma-derived factors, but not serum-derived factors, induce dysfunctions of cerebral vasculature by directly regulating the activity of peptidases, not involving inflammatory activation. Tumor hypoxia is not necessary to modulate peptidase activity.

Assessing the epidemiology and pattern of care of colorectal cancer in Valais, Switzerland

Background: The Valais's cancer registry (RVsT) of the Observatoire valaisan de le santé (OVS) and the department of oncology of Valais's Hospital conducted a study on the epidemiology and pattern of care of colorectal cancer in Valais. Colorectal cancer is the third cause of death by cancer in Switzerland with about 1600 deaths per year. It is the third most frequent cancer for males and the second most frequent for females in Valais. The number of new colorectal cancer cases (average per year) increased between 1989 and 2009 for males as well as for females in Valais. The number of colorectal cancer death cases (average per year) slightly increased between 1989 and 2009 for males as well as for females in Valais. Age-standardized rates of incidence were stable for males and females in Valais and in Switzerland between 1989 and 2009, while age-standardized rates of mortality decreased for males and females in Valais and Switzerland. Results: 774 cases were recorded (59% males). Median age at diagnosis was 70 years old. Most of cancers were invasive (79%) and the main localization was the colon (71%). The most frequent mode of detection was a consultation for non emergency symptoms (75%), but almost 10% of patients consulted in emergency. 82% of patients were treated within 30 days from diagnosis. 90% of the patients were treated by surgery alone or with combined treatment. The first treatment was surgery, including endoscopic resection in 86% of the cases. The treatment was different according to the localization and the stage of the cancer. Survival rate was 95% at 30 days and 79% at one year. The survival was dependent on the stage and the age at diagnosis. Cox model shows an association between mortality and age (better survival for young people) and between mortality and stage (better survival for the lower stages). Methods: RVsT collects information on all cancer cases since 1989 for people registered in the communes of Valais. RVsT has an authorization to collect non anonymized data. All new incident cancers are coded according to the International Classification of Diseases for Oncology (ICD-O-3) and the stages are coded according to the TNM classification. We studied all cases of in situ and invasive colorectal cancers diagnosed between 2006 and 2009 and registered routinely at the RVsT. We checked for data completeness and if necessary sent questionnaires to avoid missing data. A distance of 15 cm has been chosen to delimitate the colon (sigmoid) and the rectal cancers. We made an active follow-up for vital status to have a valid survival analysis. We analyzed the characteristics of the tumors according to age, sex, localization and stage with stata 9 software. Kaplan-Meier curves were generated and Cox model were fitted to analyze survival. Conclusion: The characteristics of patients and tumors and the one year survival were similar to those observed in Switzerland and some European countries. Patterns of care were close to those recommended in guidelines. Routine data recorded in a cancer registry can be used, not only to provide general statistics, but also to help clinicians assess local practices.

Vital Statistics of Iowa in Brief, 2007

This publication is an historical recording of the most requested statistics on vital events and is a source of information that can be used in further analysis.

Vital Statistics of Iowa in Brief, 2008

This publication is an historical recording of the most requested statistics on vital events and is a source of information that can be used in further analysis.

Vital Statistics of Iowa in Brief, 2009

This publication is an historical recording of the most requested statistics on vital events and is a source of information that can be used in further analysis.

Vital Statistics of Iowa in Brief, 2010

This publication is an historical recording of the most requested statistics on vital events and is a source of information that can be used in further analysis.

Vital Statistics of Iowa in Brief, 2011

This publication is an historical recording of the most requested statistics on vital events and is a source of information that can be used in further analysis.

Vital Statistics of Iowa in Brief, 2012

This publication is an historical recording of the most requested statistics on vital events and is a source of information that can be used in further analysis.

Vital Statistics of Iowa in Brief, 2013

This publication is an historical recording of the most requested statistics on vital events and is a source of information that can be used in further analysis.

Kernel-based Mapping of Meteorological Fields in Complex Orography

Due to the advances in sensor networks and remote sensing technologies, the acquisition and storage rates of meteorological and climatological data increases every day and ask for novel and efficient processing algorithms. A fundamental problem of data analysis and modeling is the spatial prediction of meteorological variables in complex orography, which serves among others to extended climatological analyses, for the assimilation of data into numerical weather prediction models, for preparing inputs to hydrological models and for real time monitoring and short-term forecasting of weather.In this thesis, a new framework for spatial estimation is proposed by taking advantage of a class of algorithms emerging from the statistical learning theory. Nonparametric kernel-based methods for nonlinear data classification, regression and target detection, known as support vector machines (SVM), are adapted for mapping of meteorological variables in complex orography.With the advent of high resolution digital elevation models, the field of spatial prediction met new horizons. In fact, by exploiting image processing tools along with physical heuristics, an incredible number of terrain features which account for the topographic conditions at multiple spatial scales can be extracted. Such features are highly relevant for the mapping of meteorological variables because they control a considerable part of the spatial variability of meteorological fields in the complex Alpine orography. For instance, patterns of orographic rainfall, wind speed and cold air pools are known to be correlated with particular terrain forms, e.g. convex/concave surfaces and upwind sides of mountain slopes.Kernel-based methods are employed to learn the nonlinear statistical dependence which links the multidimensional space of geographical and topographic explanatory variables to the variable of interest, that is the wind speed as measured at the weather stations or the occurrence of orographic rainfall patterns as extracted from sequences of radar images. Compared to low dimensional models integrating only the geographical coordinates, the proposed framework opens a way to regionalize meteorological variables which are multidimensional in nature and rarely show spatial auto-correlation in the original space making the use of classical geostatistics tangled.The challenges which are explored during the thesis are manifolds. First, the complexity of models is optimized to impose appropriate smoothness properties and reduce the impact of noisy measurements. Secondly, a multiple kernel extension of SVM is considered to select the multiscale features which explain most of the spatial variability of wind speed. Then, SVM target detection methods are implemented to describe the orographic conditions which cause persistent and stationary rainfall patterns. Finally, the optimal splitting of the data is studied to estimate realistic performances and confidence intervals characterizing the uncertainty of predictions.The resulting maps of average wind speeds find applications within renewable resources assessment and opens a route to decrease the temporal scale of analysis to meet hydrological requirements. Furthermore, the maps depicting the susceptibility to orographic rainfall enhancement can be used to improve current radar-based quantitative precipitation estimation and forecasting systems and to generate stochastic ensembles of precipitation fields conditioned upon the orography.