99 resultados para EXTENDED EXPONENTIAL DISTRIBUTION

em Université de Lausanne, Switzerland


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BACKGROUND: Risks of significant infant drug exposurethrough breastmilk are poorly defined for many drugs, and largescalepopulation data are lacking. We used population pharmacokinetics(PK) modeling to predict fluoxetine exposure levels ofinfants via mother's milk in a simulated population of 1000 motherinfantpairs.METHODS: Using our original data on fluoxetine PK of 25breastfeeding women, a population PK model was developed withNONMEM and parameters, including milk concentrations, wereestimated. An exponential distribution model was used to account forindividual variation. Simulation random and distribution-constrainedassignment of doses, dosing time, feeding intervals and milk volumewas conducted to generate 1000 mother-infant pairs with characteristicssuch as the steady-state serum concentrations (Css) and infantdose relative to the maternal weight-adjusted dose (relative infantdose: RID). Full bioavailability and a conservative point estimate of1-month-old infant CYP2D6 activity to be 20% of the adult value(adjusted by weigth) according to a recent study, were assumed forinfant Css calculations.RESULTS: A linear 2-compartment model was selected as thebest model. Derived parameters, including milk-to-plasma ratios(mean: 0.66; SD: 0.34; range, 0 - 1.1) were consistent with the valuesreported in the literature. The estimated RID was below 10% in >95%of infants. The model predicted median infant-mother Css ratio was0.096 (range 0.035 - 0.25); literature reported mean was 0.07 (range0-0.59). Moreover, the predicted incidence of infant-mother Css ratioof >0.2 was less than 1%.CONCLUSION: Our in silico model prediction is consistent withclinical observations, suggesting that substantial systemic fluoxetineexposure in infants through human milk is rare, but further analysisshould include active metabolites. Our approach may be valid forother drugs. [supported by CIHR and Swiss National Science Foundation(SNSF)]

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Preface The starting point for this work and eventually the subject of the whole thesis was the question: how to estimate parameters of the affine stochastic volatility jump-diffusion models. These models are very important for contingent claim pricing. Their major advantage, availability T of analytical solutions for characteristic functions, made them the models of choice for many theoretical constructions and practical applications. At the same time, estimation of parameters of stochastic volatility jump-diffusion models is not a straightforward task. The problem is coming from the variance process, which is non-observable. There are several estimation methodologies that deal with estimation problems of latent variables. One appeared to be particularly interesting. It proposes the estimator that in contrast to the other methods requires neither discretization nor simulation of the process: the Continuous Empirical Characteristic function estimator (EGF) based on the unconditional characteristic function. However, the procedure was derived only for the stochastic volatility models without jumps. Thus, it has become the subject of my research. This thesis consists of three parts. Each one is written as independent and self contained article. At the same time, questions that are answered by the second and third parts of this Work arise naturally from the issues investigated and results obtained in the first one. The first chapter is the theoretical foundation of the thesis. It proposes an estimation procedure for the stochastic volatility models with jumps both in the asset price and variance processes. The estimation procedure is based on the joint unconditional characteristic function for the stochastic process. The major analytical result of this part as well as of the whole thesis is the closed form expression for the joint unconditional characteristic function for the stochastic volatility jump-diffusion models. The empirical part of the chapter suggests that besides a stochastic volatility, jumps both in the mean and the volatility equation are relevant for modelling returns of the S&P500 index, which has been chosen as a general representative of the stock asset class. Hence, the next question is: what jump process to use to model returns of the S&P500. The decision about the jump process in the framework of the affine jump- diffusion models boils down to defining the intensity of the compound Poisson process, a constant or some function of state variables, and to choosing the distribution of the jump size. While the jump in the variance process is usually assumed to be exponential, there are at least three distributions of the jump size which are currently used for the asset log-prices: normal, exponential and double exponential. The second part of this thesis shows that normal jumps in the asset log-returns should be used if we are to model S&P500 index by a stochastic volatility jump-diffusion model. This is a surprising result. Exponential distribution has fatter tails and for this reason either exponential or double exponential jump size was expected to provide the best it of the stochastic volatility jump-diffusion models to the data. The idea of testing the efficiency of the Continuous ECF estimator on the simulated data has already appeared when the first estimation results of the first chapter were obtained. In the absence of a benchmark or any ground for comparison it is unreasonable to be sure that our parameter estimates and the true parameters of the models coincide. The conclusion of the second chapter provides one more reason to do that kind of test. Thus, the third part of this thesis concentrates on the estimation of parameters of stochastic volatility jump- diffusion models on the basis of the asset price time-series simulated from various "true" parameter sets. The goal is to show that the Continuous ECF estimator based on the joint unconditional characteristic function is capable of finding the true parameters. And, the third chapter proves that our estimator indeed has the ability to do so. Once it is clear that the Continuous ECF estimator based on the unconditional characteristic function is working, the next question does not wait to appear. The question is whether the computation effort can be reduced without affecting the efficiency of the estimator, or whether the efficiency of the estimator can be improved without dramatically increasing the computational burden. The efficiency of the Continuous ECF estimator depends on the number of dimensions of the joint unconditional characteristic function which is used for its construction. Theoretically, the more dimensions there are, the more efficient is the estimation procedure. In practice, however, this relationship is not so straightforward due to the increasing computational difficulties. The second chapter, for example, in addition to the choice of the jump process, discusses the possibility of using the marginal, i.e. one-dimensional, unconditional characteristic function in the estimation instead of the joint, bi-dimensional, unconditional characteristic function. As result, the preference for one or the other depends on the model to be estimated. Thus, the computational effort can be reduced in some cases without affecting the efficiency of the estimator. The improvement of the estimator s efficiency by increasing its dimensionality faces more difficulties. The third chapter of this thesis, in addition to what was discussed above, compares the performance of the estimators with bi- and three-dimensional unconditional characteristic functions on the simulated data. It shows that the theoretical efficiency of the Continuous ECF estimator based on the three-dimensional unconditional characteristic function is not attainable in practice, at least for the moment, due to the limitations on the computer power and optimization toolboxes available to the general public. Thus, the Continuous ECF estimator based on the joint, bi-dimensional, unconditional characteristic function has all the reasons to exist and to be used for the estimation of parameters of the stochastic volatility jump-diffusion models.

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Objectives: The study objective was to derive reference pharmacokinetic curves of antiretroviral drugs (ART) based on available population pharmacokinetic (Pop-PK) studies that can be used to optimize therapeutic drug monitoring guided dosage adjustment.¦Methods: A systematic search of Pop-PK studies of 8 ART in adults was performed in PubMed. To simulate reference PK curves, a summary of the PK parameters was obtained for each drug based on meta-analysis approach. Most models used one-compartment model, thus chosen as reference model. Models using bi-exponential disposition were simplified to one-compartment, since the first distribution phase was rapid and not determinant for the description of the terminal elimination phase, mostly relevant for this project. Different absorption were standardized for first-order absorption processes.¦Apparent clearance (CL), apparent volume of distribution of the terminal phase (Vz) and absorption rate constant (ka) and inter-individual variability were pooled into summary mean value, weighted by number of plasma levels; intra-individual variability was weighted by number of individuals in each study.¦Simulations based on summary PK parameters served to construct concentration PK percentiles (NONMEM®).¦Concordance between individual and summary parameters was assessed graphically using Forest-plots. To test robustness, difference in simulated curves based on published and summary parameters was calculated using efavirenz as probe drug.¦Results: CL was readily accessible from all studies. For studies with one-compartment, Vz was central volume of distribution; for two-compartment, Vz was CL/λz. ka was directly used or derived based on the mean absorption time (MAT) for more complicated absorption models, assuming MAT=1/ka.¦The value of CL for each drug was in excellent agreement throughout all Pop-PK models, suggesting that minimal concentration derived from summary models was adequately characterized. The comparison of the concentration vs. time profile for efavirenz between published and summary PK parameters revealed not more than 20% difference. Although our approach appears adequate for estimation of elimination phase, the simplification of absorption phase might lead to small bias shortly after drug intake.¦Conclusions: Simulated reference percentile curves based on such an approach represent a useful tool for interpretating drug concentrations. This Pop-PK meta-analysis approach should be further validated and could be extended to elaborate more sophisticated computerized tool for the Bayesian TDM of ART.

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The interfacial micromotion is closely associated to the long-term success of cementless hip prostheses. Various techniques have been proposed to measure them, but only a few number of points over the stem surface can be measured simultaneously. In this paper, we propose a new technique based on micro-Computer Tomography (μCT) to measure locally the relative interfacial micromotions between the metallic stem and the surrounding femoral bone. Tantalum beads were stuck at the stem surface and spread at the endosteal surface. Relative micromotions between the stem and the endosteal bone surfaces were measured at different loading amplitudes. The estimated error was 10μm and the maximal micromotion was 60μm, in the loading direction, at 1400N. This pilot study provided a local measurement of the micromotions in the 3 direction and at 8 locations on the stem surface simultaneously. This technique could be easily extended to higher loads and a much larger number of points, covering the entire stem surface and providing a quasi-continuous distribution of the 3D interfacial micromotions around the stem. The new measurement method would be very useful to compare the induced micromotions of different stem designs and to optimize the primary stability of cementless total hip arthroplasty.

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In Quantitative Microbial Risk Assessment, it is vital to understand how lag times of individual cells are distributed over a bacterial population. Such identified distributions can be used to predict the time by which, in a growth-supporting environment, a few pathogenic cells can multiply to a poisoning concentration level. We model the lag time of a single cell, inoculated into a new environment, by the delay of the growth function characterizing the generated subpopulation. We introduce an easy-to-implement procedure, based on the method of moments, to estimate the parameters of the distribution of single cell lag times. The advantage of the method is especially apparent for cases where the initial number of cells is small and random, and the culture is detectable only in the exponential growth phase.

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During the last 2 years, several novel genes that encode glucose transporter-like proteins have been identified and characterized. Because of their sequence similarity with GLUT1, these genes appear to belong to the family of solute carriers 2A (SLC2A, protein symbol GLUT). Sequence comparisons of all 13 family members allow the definition of characteristic sugar/polyol transporter signatures: (1) the presence of 12 membrane-spanning helices, (2) seven conserved glycine residues in the helices, (3) several basic and acidic residues at the intracellular surface of the proteins, (4) two conserved tryptophan residues, and (5) two conserved tyrosine residues. On the basis of sequence similarities and characteristic elements, the extended GLUT family can be divided into three subfamilies, namely class I (the previously known glucose transporters GLUT1-4), class II (the previously known fructose transporter GLUT5, the GLUT7, GLUT9 and GLUT11), and class III (GLUT6, 8, 10, 12, and the myo-inositol transporter HMIT1). Functional characteristics have been reported for some of the novel GLUTs. Like GLUT1-4, they exhibit a tissue/cell-specific expression (GLUT6, leukocytes, brain; GLUT8, testis, blastocysts, brain, muscle, adipocytes; GLUT9, liver, kidney; GLUT10, liver, pancreas; GLUT11, heart, skeletal muscle). GLUT6 and GLUT8 appear to be regulated by sub-cellular redistribution, because they are targeted to intra-cellular compartments by dileucine motifs in a dynamin dependent manner. Sugar transport has been reported for GLUT6, 8, and 11; HMIT1 has been shown to be a H+/myo-inositol co-transporter. Thus, the members of the extended GLUT family exhibit a surprisingly diverse substrate specificity, and the definition of sequence elements determining this substrate specificity will require a full functional characterization of all members.

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BACKGROUND: Aminoglycosides are mandatory in the treatment of severe infections in burns. However, their pharmacokinetics are difficult to predict in critically ill patients. Our objective was to describe the pharmacokinetic parameters of high doses of tobramycin administered at extended intervals in severely burned patients. METHODS: We prospectively enrolled 23 burned patients receiving tobramycin in combination therapy for Pseudomonas species infections in a burn ICU over 2 years in a therapeutic drug monitoring program. Trough and post peak tobramycin levels were measured to adjust drug dosage. Pharmacokinetic parameters were derived from two points first order kinetics. RESULTS: Tobramycin peak concentration was 7.4 (3.1-19.6)microg/ml and Cmax/MIC ratio 14.8 (2.8-39.2). Half-life was 6.9 (range 1.8-24.6)h with a distribution volume of 0.4 (0.2-1.0)l/kg. Clearance was 35 (14-121)ml/min and was weakly but significantly correlated with creatinine clearance. CONCLUSION: Tobramycin had a normal clearance, but an increased volume of distribution and a prolonged half-life in burned patients. However, the pharmacokinetic parameters of tobramycin are highly variable in burned patients. These data support extended interval administration and strongly suggest that aminoglycosides should only be used within a structured pharmacokinetic monitoring program.

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Understanding levels of population differentiation and inbreeding are important issues in conservation biology, especially for social Hymenoptera with fragmented and small population sizes. Isolated populations are more vulnerable to genetic loss and extinction than those with extended continuous distributions. However, small populations are not always a consequence of a recent reduction of their habitat. Thus, determining the history of population isolation and current patterns of genetic variation of a species is crucial for its conservation. Rossomyrmex minuchae is a slave-making ant with patchy distribution in South Eastern Spain and is classified as vulnerable by the IUCN. In contrast, the other three known species of the genus are presumed to show more uniform distributions. Here we investigate the genetic diversity and population structure of R. minuchae and compare it with that found in two other species of the genus: R. anatolicus and R. quandratinodum. We conclude that although genetic diversity of R. minuchae is low, there is no evidence of a recent bottleneck, suggesting a gradual and natural fragmentation process. We also show extreme population differentiation at nuclear and mitochondrial markers, and isolation by distance at a local scale. Despite some evidence for inbreeding and low genetic variation within populations, we found almost no diploid males, a finding which contrasts with that expected in inbred Hymenoptera with single locus complementary sex determination. This could mean that sex is determined by another mechanism. We argue that continued low population size means that detrimental effects of inbreeding and low genetic variation are likely in the future. We suggest that a policy of artificial gene flow aimed at increasing within population variation is considered as a management option.

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Much of the analytical modeling of morphogen profiles is based on simplistic scenarios, where the source is abstracted to be point-like and fixed in time, and where only the steady state solution of the morphogen gradient in one dimension is considered. Here we develop a general formalism allowing to model diffusive gradient formation from an arbitrary source. This mathematical framework, based on the Green's function method, applies to various diffusion problems. In this paper, we illustrate our theory with the explicit example of the Bicoid gradient establishment in Drosophila embryos. The gradient formation arises by protein translation from a mRNA distribution followed by morphogen diffusion with linear degradation. We investigate quantitatively the influence of spatial extension and time evolution of the source on the morphogen profile. For different biologically meaningful cases, we obtain explicit analytical expressions for both the steady state and time-dependent 1D problems. We show that extended sources, whether of finite size or normally distributed, give rise to more realistic gradients compared to a single point-source at the origin. Furthermore, the steady state solutions are fully compatible with a decreasing exponential behavior of the profile. We also consider the case of a dynamic source (e.g. bicoid mRNA diffusion) for which a protein profile similar to the ones obtained from static sources can be achieved.

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Ovalbumin-like serine protease inhibitors are mainly localized intracellularly and their in vivo functions are largely unknown. To elucidate their physiological role(s), we studied the expression of one of these inhibitors, protease inhibitor 8 (PI-8), in normal human tissues by immunohistochemistry using a PI-8-specific monoclonal antibody. PI-8 was strongly expressed in the nuclei of squamous epithelium of mouth, pharynx, esophagus, and epidermis, and by the epithelial layer of skin appendages, particularly by more differentiated epithelial cells. PI-8 was also expressed by monocytes and by neuroendocrine cells in the pituitary gland, pancreas, and digestive tract. Monocytes showed nuclear and cytoplasmic localization of PI-8, whereas neuroendocrine cells showed only cytoplasmic staining. In vitro nuclear localization of PI-8 was confirmed by confocal analysis using serpin-transfected HeLa cells. Furthermore, mutation of the P(1) residue did not affect the subcellular distribution pattern of PI-8, indicating that its nuclear localization is independent of the interaction with its target protease. We conclude that PI-8 has a unique distribution pattern in human tissues compared to the distribution patterns of other intracellular serpins. Additional studies must be performed to elucidate its physiological role.

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Abiotic factors are considered strong drivers of species distribution and assemblages. Yet these spatial patterns are also influenced by biotic interactions. Accounting for competitors or facilitators may improve both the fit and the predictive power of species distribution models (SDMs). We investigated the influence of a dominant species, Empetrum nigrum ssp. hermaphroditum, on the distribution of 34 subordinate species in the tundra of northern Norway. We related SDM parameters of those subordinate species to their functional traits and their co-occurrence patterns with E. hermaphroditum across three spatial scales. By combining both approaches, we sought to understand whether these species may be limited by competitive interactions and/or benefit from habitat conditions created by the dominant species. The model fit and predictive power increased for most species when the frequency of occurrence of E. hermaphroditum was included in the SDMs as a predictor. The largest increase was found for species that 1) co-occur most of the time with E. hermaphroditum, both at large (i.e. 750 m) and small spatial scale (i.e. 2 m) or co-occur with E. hermaphroditum at large scale but not at small scale and 2) have particularly low or high leaf dry matter content (LDMC). Species that do not co-occur with E. hermaphroditum at the smallest scale are generally palatable herbaceous species with low LDMC, thus showing a weak ability to tolerate resource depletion that is directly or indirectly induced by E. hermaphroditum. Species with high LDMC, showing a better aptitude to face resource depletion and grazing, are often found in the proximity of E. hermaphroditum. Our results are consistent with previous findings that both competition and facilitation structure plant distribution and assemblages in the Arctic tundra. The functional and co-occurrence approaches used were complementary and provided a deeper understanding of the observed patterns by refinement of the pool of potential direct and indirect ecological effects of E. hermaphroditum on the distribution of subordinate species. Our correlative study would benefit being complemented by experimental approaches.

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INTRODUCTION: Solid tumors are known to have an abnormal vasculature that limits the distribution of chemotherapy. We have recently shown that tumor vessel modulation by low-dose photodynamic therapy (L-PDT) could improve the uptake of macromolecular chemotherapeutic agents such as liposomal doxorubicin (Liporubicin) administered subsequently. However, how this occurs is unknown. Convection, the main mechanism for drug transport between the intravascular and extravascular spaces, is mostly related to interstitial fluid pressure (IFP) and tumor blood flow (TBF). Here, we determined the changes of tumor and surrounding lung IFP and TBF before, during, and after vascular L-PDT. We also evaluated the effect of these changes on the distribution of Liporubicin administered intravenously (IV) in a lung sarcoma metastasis model. MATERIALS AND METHODS: A syngeneic methylcholanthrene-induced sarcoma cell line was implanted subpleurally in the lung of Fischer rats. Tumor/surrounding lung IFP and TBF changes induced by L-PDT were determined using the wick-in-needle technique and laser Doppler flowmetry, respectively. The spatial distribution of Liporubicin in tumor and lung tissues following IV drug administration was then assessed in L-PDT-pretreated animals and controls (no L-PDT) by epifluorescence microscopy. RESULTS: L-PDT significantly decreased tumor but not lung IFP compared to controls (no L-PDT) without affecting TBF. These conditions were associated with a significant improvement in Liporubicin distribution in tumor tissues compared to controls (P < .05). DISCUSSION: L-PDT specifically enhanced convection in blood vessels of tumor but not of normal lung tissue, which was associated with a significant improvement of Liporubicin distribution in tumors compared to controls.

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Dispersal mechanisms and competition together play a key role in the spatial distribution of a population. Species that disperse via fission are likely to experience high levels of localized competitive pressure from conspecifics relative to species that disperse in other ways. Although fission dispersal occurs in many species, its ecological and behavioural effects remain unclear. We compared foraging effort, nest spatial distribution and aggression of two sympatric ant species that differ in reproductive dispersal: Streblognathus peetersi, which disperse by group fission, and Plectroctena mandibularis, which disperse by solitary wingless queens. We found that although both species share space and have similar foraging strategies, they differ in nest distribution and aggressive behaviour. The spatial distribution of S. peetersi nests was extremely aggregated, and workers were less aggressive towards conspecifics from nearby nests than towards distant conspecifics and all heterospecific workers. By contrast, the spatial distribution of P. mandibularis nests was overdispersed, and workers were equally aggressive towards conspecific and heterospecific competitors regardless of nest distance. Finally, laboratory experiments showed that familiarity led to the positive relationship between aggression and nest distance in S. peetersi. While unfamiliar individuals were initially aggressive, the level of aggression decreased within 1 h of contact, and continued to decrease over 24 h. Furthermore, individuals from near nests that were not aggressive could be induced to aggression after prolonged isolation. Overall, these results suggest that low aggression mediated by familiarity could provide benefits for a species with fission reproduction and an aggregated spatial distribution.