158 resultados para Stochastic processes--Computer simulation.
Resumo:
Adequate in-vitro training in valved stents deployment as well as testing of the latter devices requires compliant real-size models of the human aortic root. The casting methods utilized up to now are multi-step, time consuming and complicated. We pursued a goal of building a flexible 3D model in a single-step procedure. We created a precise 3D CAD model of a human aortic root using previously published anatomical and geometrical data and printed it using a novel rapid prototyping system developed by the Fab@Home project. As a material for 3D fabrication we used common house-hold silicone and afterwards dip-coated several models with dispersion silicone one or two times. To assess the production precision we compared the size of the final product with the CAD model. Compliance of the models was measured and compared with native porcine aortic root. Total fabrication time was 3 h and 20 min. Dip-coating one or two times with dispersion silicone if applied took one or two extra days, respectively. The error in dimensions of non-coated aortic root model compared to the CAD design was <3.0% along X, Y-axes and 4.1% along Z-axis. Compliance of a non-coated model as judged by the changes of radius values in the radial direction by 16.39% is significantly different (P<0.001) from native aortic tissue--23.54% at the pressure of 80-100 mmHg. Rapid prototyping of compliant, life-size anatomical models with the Fab@Home 3D printer is feasible--it is very quick compared to previous casting methods.
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We propose a method for brain atlas deformation in the presence of large space-occupying tumors, based on an a priori model of lesion growth that assumes radial expansion of the lesion from its starting point. Our approach involves three steps. First, an affine registration brings the atlas and the patient into global correspondence. Then, the seeding of a synthetic tumor into the brain atlas provides a template for the lesion. The last step is the deformation of the seeded atlas, combining a method derived from optical flow principles and a model of lesion growth. Results show that a good registration is performed and that the method can be applied to automatic segmentation of structures and substructures in brains with gross deformation, with important medical applications in neurosurgery, radiosurgery, and radiotherapy.
Resumo:
SIMULIT est un programme permettant la simulation de l'occupation des lits des hôpitaux de soins aigus. La mise en oeuvre de SIMULIT et des programmes annexes requiert de l'utilisateur qu'il sache créer et modifier un fichier à l'aide d'un éditeur, et lancer l'exécution d'un programme sur la machine dont il dispose. Le schéma général de la mise en oeuvre se trouve à l'annexe 1 de ce cahier.
Resumo:
La nomenclature des diagnostics est celle de la Classification internationale des maladies (9e révision), utilisée par la Statistique médicale VESKA depuis 1980. Les trois premiers chiffres du code ont été utilisés; seul le premier diagnostic a été retenu.
Resumo:
When sex determination in a species is predominantly genetic but environmentally reversible, exposure to (anthropogenic) changes in the environment can lead to shifts in a population's sex ratio. Such scenarios may be common in many fishes and amphibians, yet their ramifications remain largely unexplored. We used a simple model to study the (short-term) population consequences of environmental sex reversal (ESR). We examined the effects on sex ratios, sex chromosome frequencies, and population growth and persistence after exposure to environmental forces with feminizing or masculinizing tendencies. When environmental feminization was strong, X chromosomes were driven to extinction. Analogously, extinction of normally male-linked genetic factors (e.g., Y chromosomes) was caused by continuous environmental masculinization. Although moderate feminization was beneficial for population growth in the absence of large viability effects, our results suggest that the consequences of ESR are generally negative in terms of population size and the persistence of sex chromosomes. Extreme sex ratios resulting from high rates of ESR also reduced effective population sizes considerably. This may limit any evolutionary response to the deleterious effects of ESR. Our findings suggest that ESR changes population growth and sex ratios in some counter-intuitive ways and can change the predominant factor in sex determination from genetic to fully environmental, often within only a few tens of generations. Populations that lose genetic sex determination may quickly go extinct if the environmental forces that cause sex reversal cease.
Resumo:
Lesions of anatomical brain networks result in functional disturbances of brain systems and behavior which depend sensitively, often unpredictably, on the lesion site. The availability of whole-brain maps of structural connections within the human cerebrum and our increased understanding of the physiology and large-scale dynamics of cortical networks allow us to investigate the functional consequences of focal brain lesions in a computational model. We simulate the dynamic effects of lesions placed in different regions of the cerebral cortex by recording changes in the pattern of endogenous ("resting-state") neural activity. We find that lesions produce specific patterns of altered functional connectivity among distant regions of cortex, often affecting both cortical hemispheres. The magnitude of these dynamic effects depends on the lesion location and is partly predicted by structural network properties of the lesion site. In the model, lesions along the cortical midline and in the vicinity of the temporo-parietal junction result in large and widely distributed changes in functional connectivity, while lesions of primary sensory or motor regions remain more localized. The model suggests that dynamic lesion effects can be predicted on the basis of specific network measures of structural brain networks and that these effects may be related to known behavioral and cognitive consequences of brain lesions.
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The high complexity of cortical convolutions in humans is very challenging both for engineers to measure and compare it, and for biologists and physicians to understand it. In this paper, we propose a surface-based method for the quantification of cortical gyrification. Our method uses accurate 3-D cortical reconstruction and computes local measurements of gyrification at thousands of points over the whole cortical surface. The potential of our method to identify and localize precisely gyral abnormalities is illustrated by a clinical study on a group of children affected by 22q11 Deletion Syndrome, compared to control individuals.
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Functionally relevant large scale brain dynamics operates within the framework imposed by anatomical connectivity and time delays due to finite transmission speeds. To gain insight on the reliability and comparability of large scale brain network simulations, we investigate the effects of variations in the anatomical connectivity. Two different sets of detailed global connectivity structures are explored, the first extracted from the CoCoMac database and rescaled to the spatial extent of the human brain, the second derived from white-matter tractography applied to diffusion spectrum imaging (DSI) for a human subject. We use the combination of graph theoretical measures of the connection matrices and numerical simulations to explicate the importance of both connectivity strength and delays in shaping dynamic behaviour. Our results demonstrate that the brain dynamics derived from the CoCoMac database are more complex and biologically more realistic than the one based on the DSI database. We propose that the reason for this difference is the absence of directed weights in the DSI connectivity matrix.
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Understanding tree recruitment is needed to forecast future forest distribution. Many studies have reported the relevant ecological factors that affect recruitment success in trees, but the potential for genetic-based differences in recruitment has often been neglected. In this study, we established a semi-natural reciprocal sowing experiment to test for local adaptation and microenvironment effects (evaluated here by canopy cover) in the emergence and early survival of maritime pine (Pinus pinaster Aiton), an emblematic Mediterranean forest tree. A novel application of molecular markers was also developed to test for family selection and, thus, for potential genetic change over generations. Overall, we did not find evidence to support local adaptation at the recruitment stage in our semi-natural experiment. Moreover, only weak family selection (if any) was found, suggesting that in stressful environments with low survival, stochastic processes and among-year climate variability may drive recruitment. Nevertheless, our study revealed that, at early stages of recruitment, microenvironments may favor the population with the best adapted life strategy, irrespectively of its (local or non-local) origin. We also found that emergence time is a key factor for seedling survival in stressful Mediterranean environments. Our study highlights the complexity of the factors influencing the early stages of establishment of maritime pine and provides insights into possible management actions aimed at environmental change impact mitigation. In particular, we found that the high stochasticity of the recruitment process in stressful environments and the differences in population-specific adaptive strategies may difficult assisted migration schemes.
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We have recently shown that at isotopic steady state (13)C NMR can provide a direct measurement of glycogen concentration changes, but that the turnover of glycogen was not accessible with this protocol. The aim of the present study was to design, implement and apply a novel dual-tracer infusion protocol to simultaneously measure glycogen concentration and turnover. After reaching isotopic steady state for glycogen C1 using [1-(13)C] glucose administration, [1,6-(13)C(2)] glucose was infused such that isotopic steady state was maintained at the C1 position, but the C6 position reflected (13)C label incorporation. To overcome the large chemical shift displacement error between the C1 and C6 resonances of glycogen, we implemented 2D gradient based localization using the Fourier series window approach, in conjunction with time-domain analysis of the resulting FIDs using jMRUI. The glycogen concentration of 5.1 +/- 1.6 mM measured from the C1 position was in excellent agreement with concomitant biochemical determinations. Glycogen turnover measured from the rate of label incorporation into the C6 position of glycogen in the alpha-chloralose anesthetized rat was 0.7 micromol/g/h.
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Protein-ligand docking has made important progress during the last decade and has become a powerful tool for drug development, opening the way to virtual high throughput screening and in silico structure-based ligand design. Despite the flattering picture that has been drawn, recent publications have shown that the docking problem is far from being solved, and that more developments are still needed to achieve high successful prediction rates and accuracy. Introducing an accurate description of the solvation effect upon binding is thought to be essential to achieve this goal. In particular, EADock uses the Generalized Born Molecular Volume 2 (GBMV2) solvent model, which has been shown to reproduce accurately the desolvation energies calculated by solving the Poisson equation. Here, the implementation of the Fast Analytical Continuum Treatment of Solvation (FACTS) as an implicit solvation model in small molecules docking calculations has been assessed using the EADock docking program. Our results strongly support the use of FACTS for docking. The success rates of EADock/FACTS and EADock/GBMV2 are similar, i.e. around 75% for local docking and 65% for blind docking. However, these results come at a much lower computational cost: FACTS is 10 times faster than GBMV2 in calculating the total electrostatic energy, and allows a speed up of EADock by a factor of 4. This study also supports the EADock development strategy relying on the CHARMM package for energy calculations, which enables straightforward implementation and testing of the latest developments in the field of Molecular Modeling.
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To test whether quantitative traits are under directional or homogenizing selection, it is common practice to compare population differentiation estimates at molecular markers (F(ST)) and quantitative traits (Q(ST)). If the trait is neutral and its determinism is additive, then theory predicts that Q(ST) = F(ST), while Q(ST) > F(ST) is predicted under directional selection for different local optima, and Q(ST) < F(ST) is predicted under homogenizing selection. However, nonadditive effects can alter these predictions. Here, we investigate the influence of dominance on the relation between Q(ST) and F(ST) for neutral traits. Using analytical results and computer simulations, we show that dominance generally deflates Q(ST) relative to F(ST). Under inbreeding, the effect of dominance vanishes, and we show that for selfing species, a better estimate of Q(ST) is obtained from selfed families than from half-sib families. We also compare several sampling designs and find that it is always best to sample many populations (>20) with few families (five) rather than few populations with many families. Provided that estimates of Q(ST) are derived from individuals originating from many populations, we conclude that the pattern Q(ST) > F(ST), and hence the inference of directional selection for different local optima, is robust to the effect of nonadditive gene actions.
Resumo:
BACKGROUND: The increasing use of erythropoietins with long half-lives and the tendency to lengthen the administration interval to monthly injections call for raising awareness on the pharmacokinetics and risks of new erythropoietin stimulating agents (ESA). Their pharmacodynamic complexity and individual variability limit the possibility of attaining comprehensive clinical experience. In order to help physicians acquiring prescription abilities, we have built a prescription computer model to be used both as a simulator and education tool. METHODS: The pharmacokinetic computer model was developed using Visual Basic on Excel and tested with 3 different ESA half-lives (24, 48 and 138 hours) and 2 administration intervals (weekly vs. monthly). Two groups of 25 nephrologists were exposed to the six randomised combinations of half-life and administration interval. They were asked to achieve and maintain, as precisely as possible, the haemoglobin target of 11-12 g/dL in a simulated naïve patient. Each simulation was repeated twice, with or without randomly generated bleeding episodes. RESULTS: The simulation using an ESA with a half-life of 138 hours, administered monthly, compared to the other combinations of half-lives and administration intervals, showed an overshooting tendency (percentages of Hb values > 13 g/dL 15.8 ± 18.3 vs. 6.9 ± 12.2; P < 0.01), which was quickly corrected with experience. The prescription ability appeared to be optimal with a 24 hour half-life and weekly administration (ability score indexing values in the target 1.52 ± 0.70 vs. 1.24 ± 0.37; P < 0.05). The monthly prescription interval, as suggested in the literature, was accompanied by less therapeutic adjustments (4.9 ± 2.2 vs. 8.2 ± 4.9; P < 0.001); a direct correlation between haemoglobin variability and number of therapy modifications was found (P < 0.01). CONCLUSIONS: Computer-based simulations can be a useful tool for improving ESA prescription abilities among nephrologists by raising awareness about the pharmacokinetic characteristics of the various ESAs and recognizing the factors that influence haemoglobin variability.
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In this study, a quantitative approach was used to investigate the role of D142, which belongs to the highly conserved E/DRY sequence, in the activation process of the alpha1B-adrenergic receptor (alpha1B-AR). Experimental and computer-simulated mutagenesis were performed by substituting all possible natural amino acids at the D142 site. The resulting congeneric set of proteins together with the finding that all the receptor mutants show various levels of constitutive (agonist-independent) activity enabled us to quantitatively analyze the relationships between structural/dynamic features and the extent of constitutive activity. Our results suggest that the hydrophobic/hydrophilic character of D142, which could be regulated by protonation/deprotonation of this residue, is an important modulator of the transition between the inactive (R) and active (R*) state of the alpha1B-AR. Our study represents an example of quantitative structure-activity relationship analysis of the activation process of a G protein-coupled receptor.
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The method of stochastic dynamic programming is widely used in ecology of behavior, but has some imperfections because of use of temporal limits. The authors presented an alternative approach based on the methods of the theory of restoration. Suggested method uses cumulative energy reserves per time unit as a criterium, that leads to stationary cycles in the area of states. This approach allows to study the optimal feeding by analytic methods.