Dynamics of Gompertzian tumour growth under environmental fluctuations

We investigate the effect of correlated additive and multiplicative Gaussian white noise oil the Gompertzian growth of tumours. Our results are obtained by Solving numerically the time-dependent Fokker-Planck equation (FPE) associated with the stochastic dynamics. In Our numerical approach we have adopted B-spline functions as a truncated basis to expand the approximated eigenfunctions. The eigenfunctions and eigenvalues obtained using this method are used to derive approximate solutions of the dynamics under Study. We perform simulations to analyze various aspects, of the probability distribution. of the tumour cell populations in the transient- and steady-state regimes. More precisely, we are concerned mainly with the behaviour of the relaxation time (tau) to the steady-state distribution as a function of (i) of the correlation strength (lambda) between the additive noise and the multiplicative noise and (ii) as a function of the multiplicative noise intensity (D) and additive noise intensity (alpha). It is observed that both the correlation strength and the intensities of additive and multiplicative noise, affect the relaxation time.

Positron scattering and annihilation in hydrogenlike ions

Diagrammatic many-body theory is used to calculate the scattering phase shifts, normalized annihilation rates Zeff, and annihilation ? spectra for positron collisions with the hydrogenlike ions He+, Li2+, B4+, and F8+. Short-range electron-positron correlations and longer-range positron-ion correlations are accounted for by evaluating nonlocal corrections to the annihilation vertex and the exact positron self-energy. The numerical calculation of the many-body theory diagrams is performed using B-spline basis sets. To elucidate the role of the positron-ion repulsion, the annihilation rate is also estimated analytically in the Coulomb-Born approximation. It is found that the energy dependence and magnitude of Zeff are governed by the Gamow factor that characterizes the suppression of the positron wave function near the ion. For all of the H-like ions, the correlation enhancement of the annihilation rate is found to be predominantly due to corrections to the annihilation vertex, while the corrections to the positron wave function play only a minor role. Results of the calculations for s-, p-, and d-wave incident positrons of energies up to the positronium-formation threshold are presented. Where comparison is possible, our values are in excellent agreement with the results obtained using other, e.g., variational, methods. The annihilation-vertex enhancement factors obtained in the present calculations are found to scale approximately as 1+(1.6+0.46l)/Zi, where Zi is the net charge of the ion and l is the positron orbital angular momentum. Our results for positron annihilation in H-like ions provide insights into the problem of positron annihilation with core electrons in atoms and condensed matter systems, which have similar binding energies.

Time-dependent R-matrix theory applied to two-photon double ionization of He

We introduce a time-dependent R-matrix theory generalized to describe double-ionization processes. The method is used to investigate two-photon double ionization of He by intense XUV laser radiation. We combine a detailed B-spline-based wave-function description in an extended inner region with a single-electron outer region containing channels representing both single ionization and double ionization. A comparison of wave-function densities for different box sizes demonstrates that the flow between the two regions is described with excellent accuracy. The obtained two-photon double-ionization cross sections are in excellent agreement with other cross sections available. Compared to calculations fully contained within a finite inner region, the present calculations can be propagated over the time it takes the slowest electron to reach the boundary.

Validation des modèles statistiques tenant compte des variables dépendantes du temps en prévention primaire des maladies cérébrovasculaires

L’intérêt principal de cette recherche porte sur la validation d’une méthode statistique en pharmaco-épidémiologie. Plus précisément, nous allons comparer les résultats d’une étude précédente réalisée avec un devis cas-témoins niché dans la cohorte utilisé pour tenir compte de l’exposition moyenne au traitement : – aux résultats obtenus dans un devis cohorte, en utilisant la variable exposition variant dans le temps, sans faire d’ajustement pour le temps passé depuis l’exposition ; – aux résultats obtenus en utilisant l’exposition cumulative pondérée par le passé récent ; – aux résultats obtenus selon la méthode bayésienne. Les covariables seront estimées par l’approche classique ainsi qu’en utilisant l’approche non paramétrique bayésienne. Pour la deuxième le moyennage bayésien des modèles sera utilisé pour modéliser l’incertitude face au choix des modèles. La technique utilisée dans l’approche bayésienne a été proposée en 1997 mais selon notre connaissance elle n’a pas été utilisée avec une variable dépendante du temps. Afin de modéliser l’effet cumulatif de l’exposition variant dans le temps, dans l’approche classique la fonction assignant les poids selon le passé récent sera estimée en utilisant des splines de régression. Afin de pouvoir comparer les résultats avec une étude précédemment réalisée, une cohorte de personnes ayant un diagnostique d’hypertension sera construite en utilisant les bases des données de la RAMQ et de Med-Echo. Le modèle de Cox incluant deux variables qui varient dans le temps sera utilisé. Les variables qui varient dans le temps considérées dans ce mémoire sont iv la variable dépendante (premier évènement cérébrovasculaire) et une des variables indépendantes, notamment l’exposition

Neurokinin-B transcription in erythroid cells - Direct activation by the hematopoietic transcription factor GATA-1

The GATA family of transcription factors establishes genetic networks that control developmental processes including hematopoiesis, vasculogenesis, and cardiogenesis. We found that GATA-1 strongly activates transcription of the Tac-2 gene, which encodes proneurokinin-B, a precursor of neurokinin-B (NK-B). Neurokinins function through G protein-coupled transmembrane receptors to mediate diverse physiological responses including pain perception and the control of vascular tone. Whereas an elevated level of NK-B was implicated in pregnancy-associated pre-eclampsia ( Page, N. M., Woods, R. J., Gardiner, S. M., Lomthaisong, K., Gladwell, R. T., Butlin, D. J., Manyonda, I. T., and Lowry, P. J. ( 2000) Nature 405, 797 - 800), the regulation of NK-B synthesis and function are poorly understood. Tac-2 was expressed in normal murine erythroid cells and was induced upon ex vivo erythropoiesis. An estrogen receptor fusion to GATA-1 (ER-GATA-1) and endogenous GATA-1 both occupied a region of Tac-2 intron-7, which contains two conserved GATA motifs. Genetic complementation analysis in GATA-1-null G1E cells revealed that endogenous GATA-2 occupied the same region of intron-7, and expression of ER-GATA-1 displaced GATA-2 and activated Tac-2 transcription. Erythroid cells did not express neurokinin receptors, whereas aortic and yolk sac endothelial cells differentially expressed neurokinin receptor subtypes. Since NK-B induced cAMP accumulation in yolk sac endothelial cells, these results suggest a new mode of vascular regulation in which GATA-1 controls NK-B synthesis in erythroid cells.

Neurofuzzy network model construction using Bézier-Bernstein polynomial functions

Neurofuzzy modelling systems combine fuzzy logic with quantitative artificial neural networks via a concept of fuzzification by using a fuzzy membership function usually based on B-splines and algebraic operators for inference, etc. The paper introduces a neurofuzzy model construction algorithm using Bezier-Bernstein polynomial functions as basis functions. The new network maintains most of the properties of the B-spline expansion based neurofuzzy system, such as the non-negativity of the basis functions, and unity of support but with the additional advantages of structural parsimony and Delaunay input space partitioning, avoiding the inherent computational problems of lattice networks. This new modelling network is based on the idea that an input vector can be mapped into barycentric co-ordinates with respect to a set of predetermined knots as vertices of a polygon (a set of tiled Delaunay triangles) over the input space. The network is expressed as the Bezier-Bernstein polynomial function of barycentric co-ordinates of the input vector. An inverse de Casteljau procedure using backpropagation is developed to obtain the input vector's barycentric co-ordinates that form the basis functions. Extension of the Bezier-Bernstein neurofuzzy algorithm to n-dimensional inputs is discussed followed by numerical examples to demonstrate the effectiveness of this new data based modelling approach.

Generalized neurofuzzy network modeling algorithms using Bezier-Bernstein polynomial functions and additive decomposition

This paper introduces a new neurofuzzy model construction algorithm for nonlinear dynamic systems based upon basis functions that are Bezier-Bernstein polynomial functions. This paper is generalized in that it copes with n-dimensional inputs by utilising an additive decomposition construction to overcome the curse of dimensionality associated with high n. This new construction algorithm also introduces univariate Bezier-Bernstein polynomial functions for the completeness of the generalized procedure. Like the B-spline expansion based neurofuzzy systems, Bezier-Bernstein polynomial function based neurofuzzy networks hold desirable properties such as nonnegativity of the basis functions, unity of support, and interpretability of basis function as fuzzy membership functions, moreover with the additional advantages of structural parsimony and Delaunay input space partition, essentially overcoming the curse of dimensionality associated with conventional fuzzy and RBF networks. This new modeling network is based on additive decomposition approach together with two separate basis function formation approaches for both univariate and bivariate Bezier-Bernstein polynomial functions used in model construction. The overall network weights are then learnt using conventional least squares methods. Numerical examples are included to demonstrate the effectiveness of this new data based modeling approach.

Modelling and inverting complex-valued Wiener systems

We develop a complex-valued (CV) B-spline neural network approach for efficient identification and inversion of CV Wiener systems. The CV nonlinear static function in the Wiener system is represented using the tensor product of two univariate B-spline neural networks. With the aid of a least squares parameter initialisation, the Gauss-Newton algorithm effectively estimates the model parameters that include the CV linear dynamic model coefficients and B-spline neural network weights. The identification algorithm naturally incorporates the efficient De Boor algorithm with both the B-spline curve and first order derivative recursions. An accurate inverse of the CV Wiener system is then obtained, in which the inverse of the CV nonlinear static function of the Wiener system is calculated efficiently using the Gaussian-Newton algorithm based on the estimated B-spline neural network model, with the aid of the De Boor recursions. The effectiveness of our approach for identification and inversion of CV Wiener systems is demonstrated using the application of digital predistorter design for high power amplifiers with memory

Bayesian analysis of random regression models using B-splines to model test-day milk yield of Holstein cattle in Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Breeding value accuracy estimates for growth traits using random regression and multi-trait models in Nelore cattle

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Acompanhamento laboratorial da função renal de cães sadios tratados experimentalmente com doses terapêuticas de anfotericina B

O presente trabalho objetivou avaliar a função renal de dez cães adultos saudáveis submetidos à administração de doses terapêuticas do antifúngico anfotericina B, cuja utilização tem sido limitada pelo seu elevado potencial nefrotóxico, e avaliar o método laboratorial mais sensível e precoce de diagnóstico de lesão renal. Foram realizadas, diariamente, urinálise, excreção fracionada de sódio e potássio, dosagem sérica de creatinina e uréia e atividade urinária de gama-glutamiltransferase (GGT). Concluiu-se que a anfotericina B provoca lesões nos túbulos proximal e distal, induzindo acidose tubular renal do tipo I e Diabetes insipidus nefrogênico em cães. Avaliação da função renal, preferencialmente por dosagens de creatinina, uréia e potássio séricos, é recomendada antes de cada aplicação do fármaco. A densidade urinária foi o parâmetro mais precocemente alterado pela lesão renal. A GGT urinária não foi eficaz para o diagnóstico precoce de lesão induzida por anfotericina B.

Diferentes abordagens para modelar a produção de leite de bovinos da raça Guzerá

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Lovastatin protects mithochondrial and renal function in kidney ischemia-reperfusion in rats

PURPOSE: To investigate the effect of lovastatin on renal ischemia followed by reperfusion. METHODS: Thirty one Wistar rats submitted to left renal ischemia for 60 minutes followed by contralateral nephrectomy were divided into two groups: A (n = 17, control, no treatment), and B (n = 14, lovastatin 15 mg/kg/day p.o. ten days before ischemia). The animals were sacrificed at the end of ischemia, after 24 hours and at seven days after reperfusion. Survival, serum urea and creatinine levels and renal mitochondrial function were evaluated. RESULTS: Mortality was 29.4% in group A and 0.7% in group B. Urea and creatinine levels were increased in both groups, but the values were significantly lower in group B. Mitochondrial function showed decoupling in 83.4% of group A, as opposed to 38.4/% of group B. CONCLUSIONS: The result shows a protective action of renal function by lovastatin administered before ischemia/reperfusion. Since most of the mitochondrial fraction presented membranes with the ability to maintain ATP production in group B, stabilization of the mitochondrial membrane should be considered as part of the protective action of lovastatin on renal function in ischemia/reperfusion.

Bayesian analysis of random regression models using B-splines to model test-day milk yield of Holstein cattle in Brazil

The objective of this paper is to model variations in test-day milk yields of first lactations of Holstein cows by RR using B-spline functions and Bayesian inference in order to fit adequate and parsimonious models for the estimation of genetic parameters. They used 152,145 test day milk yield records from 7317 first lactations of Holstein cows. The model established in this study was additive, permanent environmental and residual random effects. In addition, contemporary group and linear and quadratic effects of the age of cow at calving were included as fixed effects. Authors modeled the average lactation curve of the population with a fourth-order orthogonal Legendre polynomial. They concluded that a cubic B-spline with seven random regression coefficients for both the additive genetic and permanent environment effects was to be the best according to residual mean square and residual variance estimates. Moreover they urged a lower order model (quadratic B-spline with seven random regression coefficients for both random effects) could be adopted because it yielded practically the same genetic parameter estimates with parsimony. (C) 2012 Elsevier B.V. All rights reserved.

Untersuchung zur Bestimmung quantitativer Parameter der Lungenventilation mittels CT und MRT

Die zuverlässige Berechnung von quantitativen Parametern der Lungenventilation ist für ein Verständnis des Verhaltens der Lunge und insbesondere für die Diagnostik von Lungenerkrankungen von großer Bedeutung. Nur durch quantitative Parameter sind verlässliche und reproduzierbare diagnostische Aussagen über den Gesundheitszustand der Lunge möglich. Im Rahmen dieser Arbeit wurden neue quantitative Verfahren zur Erfassung der Lungenventilation basierend auf der dynamischen Computer- (CT) und Magnetresonanztomographie (MRT) entwickelt. Im ersten Teil dieser Arbeit wurde die Frage untersucht, ob das Aufblähen der Lunge in gesunden Schweinelungen und Lungen mit Akutem Lungenversagen (ARDS) durch einzelne, diskrete Zeitkonstanten beschrieben werden kann, oder ob kontinuierliche Verteilungen von Zeitkonstanten die Realität besser beschreiben. Hierzu wurden Serien dynamischer CT-Aufnahmen während definierter Beatmungsmanöver (Drucksprünge) aufgenommen und anschließend aus den Messdaten mittels inverser Laplace-Transformation die zugehörigen Verteilungen der Zeitkonstanten berechnet. Um die Qualität der Ergebnisse zu analysieren, wurde der Algorithmus im Rahmen von Simulationsrechnungen systematisch untersucht und anschließend in-vivo an gesunden und ARDS-Schweinelungen eingesetzt. Während in den gesunden Lungen mono- und biexponentielle Verteilungen bestimmt wurden, waren in den ARDS-Lungen Verteilungen um zwei dominante Zeitkonstanten notwendig, um die gemessenen Daten auf der Basis des verwendeten Modells verlässlich zu beschreiben. Es wurden sowohl diskrete als auch kontinuierliche Verteilungen gefunden. Die CT liefert Informationen über das solide Lungengewebe, während die MRT von hyperpolarisiertem 3He in der Lage ist, direkt das eingeatmete Gas abzubilden. Im zweiten Teil der Arbeit wurde zeitlich hochaufgelöst das Einströmen eines 3He-Bolus in die Lunge erfasst. Über eine Entfaltungsanalyse wurde anschließend das Einströmverhalten unter Idealbedingungen (unendlich kurzer 3He-Bolus), also die Gewebeantwortfunktion, berechnet und so eine Messtechnik-unabhängige Erfassung des Einströmens von 3He in die Lunge ermöglicht. Zentrale Fragestellung war hier, wie schnell das Gas in die Lunge einströmt. Im Rahmen von Simulationsrechnungen wurde das Verhalten eines Entfaltungsalgorithmus (basierend auf B-Spline Repräsentationen) systematisch analysiert. Zusätzlich wurde ein iteratives Entfaltungsverfahren eingesetzt. Aus zeitlich hochaufgelösten Messungen (7ms) an einer gesunden und einer ARDS-Schweinelunge konnte erstmals nachgewiesen werden, dass das Einströmen in-vivo in weniger als 0,1s geschieht. Die Ergebnisse zeigen Zeitkonstanten im Bereich von 4ms–50ms, wobei zwischen der gesunden Lungen und der ARDS-Lunge deutliche Unterschiede beobachtet wurden. Zusammenfassend ermöglichen daher die in dieser Arbeit vorgestellten Algorithmen eine objektivere Bestimmung quantitativer Parameter der Lungenventilation. Dies ist für die eindeutige Beschreibung ventilatorischer Vorgänge in der Lunge und somit für die Lungendiagnostik unerlässlich. Damit stehen quantitative Methoden für die Lungenfunktionsdiagnostik zur Verfügung, deren diagnostische Relevanz im Rahmen wissenschaftlicher und klinischer Studien untersucht werden kann.