High-resolution numerical modelling of flow-vegetation interactions

In this paper, we present and apply a new three-dimensional model for the prediction of canopy-flow and turbulence dynamics in open-channel flow. The approach uses a dynamic immersed boundary technique that is coupled in a sequentially staggered manner to a large eddy simulation. Two different biomechanical models are developed depending on whether the vegetation is dominated by bending or tensile forces. For bending plants, a model structured on the Euler-Bernoulli beam equation has been developed, whilst for tensile plants, an N-pendula model has been developed. Validation against flume data shows good agreement and demonstrates that for a given stem density, the models are able to simulate the extraction of energy from the mean flow at the stem-scale which leads to the drag discontinuity and associated mixing layer.

Computational fluid dynamics of the right ventricular outflow tract and of the pulmonary artery: a bench model of flow dynamics.

OBJECTIVES: The reconstruction of the right ventricular outflow tract (RVOT) with valved conduits remains a challenge. The reoperation rate at 5 years can be as high as 25% and depends on age, type of conduit, conduit diameter and principal heart malformation. The aim of this study is to provide a bench model with computer fluid dynamics to analyse the haemodynamics of the RVOT, pulmonary artery, its bifurcation, and left and right pulmonary arteries that in the future may serve as a tool for analysis and prediction of outcome following RVOT reconstruction. METHODS: Pressure, flow and diameter at the RVOT, pulmonary artery, bifurcation of the pulmonary artery, and left and right pulmonary arteries were measured in five normal pigs with a mean weight of 24.6 ± 0.89 kg. Data obtained were used for a 3D computer fluid-dynamics simulation of flow conditions, focusing on the pressure, flow and shear stress profile of the pulmonary trunk to the level of the left and right pulmonary arteries. RESULTS: Three inlet steady flow profiles were obtained at 0.2, 0.29 and 0.36 m/s that correspond to the flow rates of 1.5, 2.0 and 2.5 l/min flow at the RVOT. The flow velocity profile was constant at the RVOT down to the bifurcation and decreased at the left and right pulmonary arteries. In all three inlet velocity profiles, low sheer stress and low-velocity areas were detected along the left wall of the pulmonary artery, at the pulmonary artery bifurcation and at the ostia of both pulmonary arteries. CONCLUSIONS: This computed fluid real-time model provides us with a realistic picture of fluid dynamics in the pulmonary tract area. Deep shear stress areas correspond to a turbulent flow profile that is a predictive factor for the development of vessel wall arteriosclerosis. We believe that this bench model may be a useful tool for further evaluation of RVOT pathology following surgical reconstructions.

Use of flow cytometric methods for single-cell analysis in environmental microbiology

Flow cytometry (FCM) is emerging as an important tool in environmental microbiology. Although flow cytometry applications have to date largely been restricted to certain specialized fields of microbiology, such as the bacterial cell cycle and marine phytoplankton communities, technical advances in instrumentation and methodology are leading to its increased popularity and extending its range of applications. Here we will focus on a number of recent flow cytometry developments important for addressing questions in environmental microbiology. These include (i) the study of microbial physiology under environmentally relevant conditions, (ii) new methods to identify active microbial populations and to isolate previously uncultured microorganisms, and (iii) the development of high-throughput autofluorescence bioreporter assays

Passive knee-extension test to measure hamstring tightness: influence of gravity correction

CONTEXT: A passive knee-extension test has been shown to be a reliable method of assessing hamstring tightness, but this method does not take into account the potential effect of gravity on the tested leg. OBJECTIVE: To compare an original passive knee-extension test with 2 adapted methods including gravity's effect on the lower leg. DESIGN: Repeated measures. SETTING: Laboratory. PARTICIPANTS: 20 young track and field athletes (16.6 ± 1.6 y, 177.6 ± 9.2 cm, 75.9 ± 24.8 kg). INTERVENTION: Each subject was tested in a randomized order with 3 different methods: In the original one (M1), passive knee angle was measured with a standard force of 68.7 N (7 kg) applied proximal to the lateral malleolus. The second (M2) and third (M3) methods took into account the relative lower-leg weight (measured respectively by handheld dynamometer and anthropometrical table) to individualize the force applied to assess passive knee angle. MAIN OUTCOME MEASURES: Passive knee angles measured with video-analysis software. RESULTS: No difference in mean individualized applied force was found between M2 and M3, so the authors assessed passive knee angle only with M2. The mean knee angle was different between M1 and M2 (68.8 ± 12.4 vs 73.1 ± 10.6, P < .001). Knee angles in M1 and M2 were correlated (r = .93, P < .001). CONCLUSIONS: Differences in knee angle were found between the original passive knee-extension test and a method with gravity correction. M2 is an improved version of the original method (M1) since it minimizes the effect of gravity. Therefore, we recommend using it rather than M1.

Smooth muscle differentiation identifies two classes of poorly differentiated pleomorphic sarcomas with distinct outcome.

The clinical relevance of accurately diagnosing pleomorphic sarcomas has been shown, especially in cases of undifferentiated pleomorphic sarcomas with myogenic differentiation, which appear significantly more aggressive. To establish a new smooth muscle differentiation classification and to test its prognostic value, 412 sarcomas with complex genetics were examined by immunohistochemistry using four smooth muscle markers (calponin, h-caldesmon, transgelin and smooth muscle actin). Two tumor categories were first defined: tumors with positivity for all four markers and tumors with no or incomplete phenotypes. Multivariate analysis demonstrated that this classification method exhibited the strongest prognostic value compared with other prognostic factors, including histological classification. Secondly, incomplete or absent smooth muscle phenotype tumor group was then divided into subgroups by summing for each tumor the labeling intensities of all four markers for each tumors. A subgroup of tumors with an incomplete but strong smooth muscle differentiation phenotype presenting an intermediate metastatic risk was thus identified. Collectively, our results show that the smooth muscle differentiation classification method may be a useful diagnostic tool as well as a relevant prognostic tool for undifferentiated pleomorphic sarcomas.

Topographic forcing of flow partition and flow structures at river bifurcations

This paper presents the predicted flow dynamics from the application of a Reynolds-averaged NavierStokes model to a series of bifurcation geometries with morphologies measured during previous flume experiments. The topography of the bifurcations consists of either plane or bedform-dominated beds which may or may not possess discordance between the two bifurcation distributaries. Numerical predictions are compared with experimental results to assess the ability of the numerical model to reproduce the division of flow into the bifurcation distributaries. The hydrodynamic model predicts: (1) diverting fluxes in the upstream channel which direct water into the distributaries; (2) super-elevation of the free surface induced at the bifurcation edge by pressure differences; and (3) counter-rotating secondary circulation cells which develop upstream of the apex of the bifurcation and move into the downstream channels, with water converging at the surface and diverging at the bed. When bedforms are not present, weak transversal fluxes characterize the upstream channel for almost its entire length, associated with clearly distinguishable secondary circulation cells, although these may be under-estimated by the turbulence model used in the solution. In the bedform dominated case, the same hydrodynamic conditions were not observed, with the bifurcation influence restricted and depth scale secondary circulation cells not forming. The results also demonstrate the dominant effect bed discordance has upon flow division between the two distributaries. Finally, results indicate that in bedform dominated rivers. Consequently, we suggest that sand-bed river bifurcations are more likely to have an influence that extends much further upstream and have a greater impact upon water distribution. This may contribute to observed morphological differences between sand-bedded and gravel-bedded braided river networks. Copyright (C) 2012 John Wiley & Sons, Ltd.

Identification and characterization of novel classes of macrophage migration inhibitory factor (MIF) inhibitors with distinct mechanisms of action.

Macrophage migration inhibitory factor (MIF), a proinflammatory cytokine, is considered an attractive therapeutic target in multiple inflammatory and autoimmune disorders. In addition to its known biologic activities, MIF can also function as a tautomerase. Several small molecules have been reported to be effective inhibitors of MIF tautomerase activity in vitro. Herein we employed a robust activity-based assay to identify different classes of novel inhibitors of the catalytic and biological activities of MIF. Several novel chemical classes of inhibitors of the catalytic activity of MIF with IC(50) values in the range of 0.2-15.5 microm were identified and validated. The interaction site and mechanism of action of these inhibitors were defined using structure-activity studies and a battery of biochemical and biophysical methods. MIF inhibitors emerging from these studies could be divided into three categories based on their mechanism of action: 1) molecules that covalently modify the catalytic site at the N-terminal proline residue, Pro(1); 2) a novel class of catalytic site inhibitors; and finally 3) molecules that disrupt the trimeric structure of MIF. Importantly, all inhibitors demonstrated total inhibition of MIF-mediated glucocorticoid overriding and AKT phosphorylation, whereas ebselen, a trimer-disrupting inhibitor, additionally acted as a potent hyperagonist in MIF-mediated chemotactic migration. The identification of biologically active compounds with known toxicity, pharmacokinetic properties, and biological activities in vivo should accelerate the development of clinically relevant MIF inhibitors. Furthermore, the diversity of chemical structures and mechanisms of action of our inhibitors makes them ideal mechanistic probes for elucidating the structure-function relationships of MIF and to further determine the role of the oligomerization state and catalytic activity of MIF in regulating the function(s) of MIF in health and disease.

Analysis of flow dynamics in right ventricular outflow tract.

BACKGROUND: The mechanism behind early graft failure after right ventricular outflow tract (RVOT) reconstruction is not fully understood. Our aim was to establish a three-dimensional computational fluid dynamics (CFD) model of RVOT to investigate the hemodynamic conditions that may trigger the development of intimal hyperplasia and arteriosclerosis. METHODS: Pressure, flow, and diameter at the RVOT, pulmonary artery (PA), bifurcation of the PA, and left and right PAs were measured in 10 normal pigs with a mean weight of 24.8 ± 0.78 kg. Data obtained from the experimental scenario were used for CFD simulation of pressure, flow, and shear stress profile from the RVOT to the left and right PAs. RESULTS: Using experimental data, a CFD model was obtained for 2.0 and 2.5-L/min pulsatile inflow profiles. In both velocity profiles, time and space averaged in the low-shear stress profile range from 0-6.0 Pa at the pulmonary trunk, its bifurcation, and at the openings of both PAs. These low-shear stress areas were accompanied to high-pressure regions 14.0-20.0 mm Hg (1866.2-2666 Pa). Flow analysis revealed a turbulent flow at the PA bifurcation and ostia of both PAs. CONCLUSIONS: Identified local low-shear stress, high pressure, and turbulent flow correspond to a well-defined trigger pattern for the development of intimal hyperplasia and arteriosclerosis. As such, this real-time three-dimensional CFD model may in the future serve as a tool for the planning of RVOT reconstruction, its analysis, and prediction of outcome.

Restricted gene flow at specific parts of the shrew genome in chromosomal hybrid zones.

The species and races of the shrews of the Sorex araneus group exhibit a broad range of chromosomal polymorphisms. European taxa of this group are parapatric and form contact or hybrid zones that span an extraordinary variety of situations, ranging from absolute genetic isolation to almost free gene flow. This variety seems to depend for a large part on the chromosome composition of populations, which are primarily differentiated by various Robertsonian fusions of a subset of acrocentric chromosomes. Previous studies suggested that chromosomal rearrangements play a causative role in the speciation process. In such models, gene flow should be more restricted for markers on chromosomes involved in rearrangements than on chromosomes common in both parent species. In the present study, we address the possibility of such differential gene flow in the context of two genetically very similar but karyotypically different hybrid zones between species of the S. araneus group using microsatellite loci mapped to the chromosome arm level. Interspecific genetic structure across rearranged chromosomes was in general larger than across common chromosomes. However, the difference between the two classes of chromosomes was only significant in the hybrid zone where the complexity of hybrids is expected to be larger. These differences did not distinguish populations within species. Therefore, the rearranged chromosomes appear to affect the reproductive barrier between karyotypic species, although the strength of this effect depends on the complexity of the hybrids produced.

Quantification of aortic flow by phase-contrast magnetic resonance in patients with bicuspid aortic valve.

AIMS: Bicuspid aortic valve (BAV) causes complex flow patterns in the ascending aorta (AAo), which may compromise the accuracy of flow measurement by phase-contrast magnetic resonance (PC-MR). Therefore, we aimed to assess and compare the accuracy of forward flow measurement in the AAo, where complex flow is more dominant in BAV patients, with flow quantification in the left ventricular outflow tract (LVOT) and the aortic valve orifice (AV), where complex flow is less important, in BAV patients and controls. METHODS AND RESULTS: Flow was measured by PC-MR in 22 BAV patients and 20 controls at the following positions: (i) LVOT, (ii) AV, and (iii) AAo, and compared with the left ventricular stroke volume (LVSV). The correlation between the LVSV and the forward flow in the LVOT, the AV, and the AAo was good in BAV patients (r = 0.97/0.96/0.93; P < 0.01) and controls (r = 0.96/0.93/0.93; P < 0.01). However, in relation with the LVSV, the forward flow in the AAo was mildly underestimated in controls and much more in BAV patients [median (inter-quartile range): 9% (4%/15%) vs. 22% (8%/30%); P < 0.01]. This was not the case in the LVOT and the AV. The severity of flow underestimation in the AAo was associated with flow eccentricity. CONCLUSION: Flow measurement in the AAo leads to an underestimation of the forward flow in BAV patients. Measurement in the LVOT or the AV, where complex flow is less prominent, is an alternative means for quantifying the systolic forward flow in BAV patients.

Quantitative integration of geophysical and hydraulic data : from the local towards the regional scale range

Des progrès significatifs ont été réalisés dans le domaine de l'intégration quantitative des données géophysique et hydrologique l'échelle locale. Cependant, l'extension à de plus grandes échelles des approches correspondantes constitue encore un défi majeur. Il est néanmoins extrêmement important de relever ce défi pour développer des modèles fiables de flux des eaux souterraines et de transport de contaminant. Pour résoudre ce problème, j'ai développé une technique d'intégration des données hydrogéophysiques basée sur une procédure bayésienne de simulation séquentielle en deux étapes. Cette procédure vise des problèmes à plus grande échelle. L'objectif est de simuler la distribution d'un paramètre hydraulique cible à partir, d'une part, de mesures d'un paramètre géophysique pertinent qui couvrent l'espace de manière exhaustive, mais avec une faible résolution (spatiale) et, d'autre part, de mesures locales de très haute résolution des mêmes paramètres géophysique et hydraulique. Pour cela, mon algorithme lie dans un premier temps les données géophysiques de faible et de haute résolution à travers une procédure de réduction déchelle. Les données géophysiques régionales réduites sont ensuite reliées au champ du paramètre hydraulique à haute résolution. J'illustre d'abord l'application de cette nouvelle approche dintégration des données à une base de données synthétiques réaliste. Celle-ci est constituée de mesures de conductivité hydraulique et électrique de haute résolution réalisées dans les mêmes forages ainsi que destimations des conductivités électriques obtenues à partir de mesures de tomographic de résistivité électrique (ERT) sur l'ensemble de l'espace. Ces dernières mesures ont une faible résolution spatiale. La viabilité globale de cette méthode est testée en effectuant les simulations de flux et de transport au travers du modèle original du champ de conductivité hydraulique ainsi que du modèle simulé. Les simulations sont alors comparées. Les résultats obtenus indiquent que la procédure dintégration des données proposée permet d'obtenir des estimations de la conductivité en adéquation avec la structure à grande échelle ainsi que des predictions fiables des caractéristiques de transports sur des distances de moyenne à grande échelle. Les résultats correspondant au scénario de terrain indiquent que l'approche d'intégration des données nouvellement mise au point est capable d'appréhender correctement les hétérogénéitées à petite échelle aussi bien que les tendances à gande échelle du champ hydraulique prévalent. Les résultats montrent également une flexibilté remarquable et une robustesse de cette nouvelle approche dintégration des données. De ce fait, elle est susceptible d'être appliquée à un large éventail de données géophysiques et hydrologiques, à toutes les gammes déchelles. Dans la deuxième partie de ma thèse, j'évalue en détail la viabilité du réechantillonnage geostatique séquentiel comme mécanisme de proposition pour les méthodes Markov Chain Monte Carlo (MCMC) appliquées à des probmes inverses géophysiques et hydrologiques de grande dimension . L'objectif est de permettre une quantification plus précise et plus réaliste des incertitudes associées aux modèles obtenus. En considérant une série dexemples de tomographic radar puits à puits, j'étudie deux classes de stratégies de rééchantillonnage spatial en considérant leur habilité à générer efficacement et précisément des réalisations de la distribution postérieure bayésienne. Les résultats obtenus montrent que, malgré sa popularité, le réechantillonnage séquentiel est plutôt inefficace à générer des échantillons postérieurs indépendants pour des études de cas synthétiques réalistes, notamment pour le cas assez communs et importants où il existe de fortes corrélations spatiales entre le modèle et les paramètres. Pour résoudre ce problème, j'ai développé un nouvelle approche de perturbation basée sur une déformation progressive. Cette approche est flexible en ce qui concerne le nombre de paramètres du modèle et lintensité de la perturbation. Par rapport au rééchantillonage séquentiel, cette nouvelle approche s'avère être très efficace pour diminuer le nombre requis d'itérations pour générer des échantillons indépendants à partir de la distribution postérieure bayésienne. - Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending corresponding approaches beyond the local scale still represents a major challenge, yet is critically important for the development of reliable groundwater flow and contaminant transport models. To address this issue, I have developed a hydrogeophysical data integration technique based on a two-step Bayesian sequential simulation procedure that is specifically targeted towards larger-scale problems. The objective is to simulate the distribution of a target hydraulic parameter based on spatially exhaustive, but poorly resolved, measurements of a pertinent geophysical parameter and locally highly resolved, but spatially sparse, measurements of the considered geophysical and hydraulic parameters. To this end, my algorithm links the low- and high-resolution geophysical data via a downscaling procedure before relating the downscaled regional-scale geophysical data to the high-resolution hydraulic parameter field. I first illustrate the application of this novel data integration approach to a realistic synthetic database consisting of collocated high-resolution borehole measurements of the hydraulic and electrical conductivities and spatially exhaustive, low-resolution electrical conductivity estimates obtained from electrical resistivity tomography (ERT). The overall viability of this method is tested and verified by performing and comparing flow and transport simulations through the original and simulated hydraulic conductivity fields. The corresponding results indicate that the proposed data integration procedure does indeed allow for obtaining faithful estimates of the larger-scale hydraulic conductivity structure and reliable predictions of the transport characteristics over medium- to regional-scale distances. The approach is then applied to a corresponding field scenario consisting of collocated high- resolution measurements of the electrical conductivity, as measured using a cone penetrometer testing (CPT) system, and the hydraulic conductivity, as estimated from electromagnetic flowmeter and slug test measurements, in combination with spatially exhaustive low-resolution electrical conductivity estimates obtained from surface-based electrical resistivity tomography (ERT). The corresponding results indicate that the newly developed data integration approach is indeed capable of adequately capturing both the small-scale heterogeneity as well as the larger-scale trend of the prevailing hydraulic conductivity field. The results also indicate that this novel data integration approach is remarkably flexible and robust and hence can be expected to be applicable to a wide range of geophysical and hydrological data at all scale ranges. In the second part of my thesis, I evaluate in detail the viability of sequential geostatistical resampling as a proposal mechanism for Markov Chain Monte Carlo (MCMC) methods applied to high-dimensional geophysical and hydrological inverse problems in order to allow for a more accurate and realistic quantification of the uncertainty associated with the thus inferred models. Focusing on a series of pertinent crosshole georadar tomographic examples, I investigated two classes of geostatistical resampling strategies with regard to their ability to efficiently and accurately generate independent realizations from the Bayesian posterior distribution. The corresponding results indicate that, despite its popularity, sequential resampling is rather inefficient at drawing independent posterior samples for realistic synthetic case studies, notably for the practically common and important scenario of pronounced spatial correlation between model parameters. To address this issue, I have developed a new gradual-deformation-based perturbation approach, which is flexible with regard to the number of model parameters as well as the perturbation strength. Compared to sequential resampling, this newly proposed approach was proven to be highly effective in decreasing the number of iterations required for drawing independent samples from the Bayesian posterior distribution.