657 resultados para Adjuvante de Freund
Resumo:
Variantti A.
Resumo:
Variantti B.
Resumo:
Variantti A.
Resumo:
Orofacial pain is a prevalent symptom in modern society. Some musculoskeletal orofacial pain is caused by temporomandibular disorders (TMDs). This condition has a multi-factorial etiology, including emotional factors and alteration of the masticator muscle and temporomandibular joints (TMJs). TMJ inflammation is considered to be a cause of pain in patients with TMD. Extracellular proteolytic enzymes, specifically the matrix metalloproteinases (MMPs), have been shown to modulate inflammation and pain. The purpose of this investigation was to determine whether the expression and level of gelatinolytic activity of MMP-2 and MMP-9 in the trigeminal ganglion are altered during different stages of temporomandibular inflammation, as determined by gelatin zymography. This study also evaluated whether mechanical allodynia and orofacial hyperalgesia, induced by the injection of complete Freund's adjuvant into the TMJ capsule, were altered by an MMP inhibitor (doxycycline, DOX). TMJ inflammation was measured by plasma extravasation in the periarticular tissue (Evans blue test) and infiltration of polymorphonuclear neutrophils into the synovial fluid (myeloperoxidase enzyme quantification). MMP expression in the trigeminal ganglion was shown to vary during the phases of the inflammatory process. MMP-9 regulated the early phase and MMP-2 participated in the late phase of this process. Furthermore, increases in plasma extravasation in periarticular tissue and myeloperoxidase activity in the joint tissue, which occurred throughout the inflammation process, were diminished by treatment with DOX, a nonspecific MMP inhibitor. Additionally, the increases of mechanical allodynia and orofacial hyperalgesia were attenuated by the same treatment.
Resumo:
Invokaatio Jehova adjuvante.
Resumo:
Invokaatio: Adjuvante Deo!
Resumo:
Invokaatio: Deo adjuvante.
Resumo:
Communication présentée au congrès de l’ACFAS, Mai 2001
Resumo:
Die Fachgruppe AFS (früher Fachgruppe 0.1.5) der Gesellschaft für Informatik veranstaltet seit 1991 einmal im Jahr ein Treffen der Fachgruppe im Rahmen eines Theorietags, der traditionell eineinhalb Tage dauert. Seit dem Jahr 1996 wird dem eigentlichen Theorietag noch ein eintägiger Workshop zu speziellen Themen der theoretischen Informatik vorangestellt. In diesem Jahr wurde der Theorietag vom Fachgebiet "Theoretische Informatik" des Fachbereichs Elektrotechnik/Informatik der Universität Kassel organisiert. Er fand vom 29.9. bis 1.10.2010 in Baunatal bei Kassel statt. Dabei stand der begleitende Workshop unter dem allgemeinen Thema "Ausgewählte Themen der Theoretischen Informatik". Als Vortragende für diesen Workshop konnten Carsten Damm (Göttingen), Markus Holzer (Giessen), Peter Leupold (Kassel), Martin Plátek (Prag) und Heribert Vollmer (Hannover) gewonnen werden. Das Programm des eigentlichen Theorietags bestand aus 20 Vorträgen sowie der Sitzung der Fachgruppe AFS. In diesem Band finden sich die Zusammenfassungen aller Vorträge sowohl des Workshops als auch des Theorietags. Desweiteren enthält er das Programm und die Liste aller Teilnehmer.
Resumo:
The Support Vector Machine (SVM) is a new and very promising classification technique developed by Vapnik and his group at AT&T Bell Labs. This new learning algorithm can be seen as an alternative training technique for Polynomial, Radial Basis Function and Multi-Layer Perceptron classifiers. An interesting property of this approach is that it is an approximate implementation of the Structural Risk Minimization (SRM) induction principle. The derivation of Support Vector Machines, its relationship with SRM, and its geometrical insight, are discussed in this paper. Training a SVM is equivalent to solve a quadratic programming problem with linear and box constraints in a number of variables equal to the number of data points. When the number of data points exceeds few thousands the problem is very challenging, because the quadratic form is completely dense, so the memory needed to store the problem grows with the square of the number of data points. Therefore, training problems arising in some real applications with large data sets are impossible to load into memory, and cannot be solved using standard non-linear constrained optimization algorithms. We present a decomposition algorithm that can be used to train SVM's over large data sets. The main idea behind the decomposition is the iterative solution of sub-problems and the evaluation of, and also establish the stopping criteria for the algorithm. We present previous approaches, as well as results and important details of our implementation of the algorithm using a second-order variant of the Reduced Gradient Method as the solver of the sub-problems. As an application of SVM's, we present preliminary results we obtained applying SVM to the problem of detecting frontal human faces in real images.
Resumo:
We compare a broad range of optimal product line design methods. The comparisons take advantage of recent advances that make it possible to identify the optimal solution to problems that are too large for complete enumeration. Several of the methods perform surprisingly well, including Simulated Annealing, Product-Swapping and Genetic Algorithms. The Product-Swapping heuristic is remarkable for its simplicity. The performance of this heuristic suggests that the optimal product line design problem may be far easier to solve in practice than indicated by complexity theory.
Resumo:
We study four measures of problem instance behavior that might account for the observed differences in interior-point method (IPM) iterations when these methods are used to solve semidefinite programming (SDP) problem instances: (i) an aggregate geometry measure related to the primal and dual feasible regions (aspect ratios) and norms of the optimal solutions, (ii) the (Renegar-) condition measure C(d) of the data instance, (iii) a measure of the near-absence of strict complementarity of the optimal solution, and (iv) the level of degeneracy of the optimal solution. We compute these measures for the SDPLIB suite problem instances and measure the correlation between these measures and IPM iteration counts (solved using the software SDPT3) when the measures have finite values. Our conclusions are roughly as follows: the aggregate geometry measure is highly correlated with IPM iterations (CORR = 0.896), and is a very good predictor of IPM iterations, particularly for problem instances with solutions of small norm and aspect ratio. The condition measure C(d) is also correlated with IPM iterations, but less so than the aggregate geometry measure (CORR = 0.630). The near-absence of strict complementarity is weakly correlated with IPM iterations (CORR = 0.423). The level of degeneracy of the optimal solution is essentially uncorrelated with IPM iterations.
Resumo:
La butirilcolinesterasa humana (BChE; EC 3.1.1.8) es una enzima polimórfica sintetizada en el hígado y en el tejido adiposo, ampliamente distribuida en el organismo y encargada de hidrolizar algunos ésteres de colina como la procaína, ésteres alifáticos como el ácido acetilsalicílico, fármacos como la metilprednisolona, el mivacurium y la succinilcolina y drogas de uso y/o abuso como la heroína y la cocaína. Es codificada por el gen BCHE (OMIM 177400), habiéndose identificado más de 100 variantes, algunas no estudiadas plenamente, además de la forma más frecuente, llamada usual o silvestre. Diferentes polimorfismos del gen BCHE se han relacionado con la síntesis de enzimas con niveles variados de actividad catalítica. Las bases moleculares de algunas de esas variantes genéticas han sido reportadas, entre las que se encuentra las variantes Atípica (A), fluoruro-resistente del tipo 1 y 2 (F-1 y F-2), silente (S), Kalow (K), James (J) y Hammersmith (H). En este estudio, en un grupo de pacientes se aplicó el instrumento validado Lifetime Severity Index for Cocaine Use Disorder (LSI-C) para evaluar la gravedad del consumo de “cocaína” a lo largo de la vida. Además, se determinaron Polimorfismos de Nucleótido Simple (SNPs) en el gen BCHE conocidos como responsables de reacciones adversas en pacientes consumidores de “cocaína” mediante secuenciación del gen y se predijo el efecto delos SNPs sobre la función y la estructura de la proteína, mediante el uso de herramientas bio-informáticas. El instrumento LSI-C ofreció resultados en cuatro dimensiones: consumo a lo largo de la vida, consumo reciente, dependencia psicológica e intento de abandono del consumo. Los estudios de análisis molecular permitieron observar dos SNPs codificantes (cSNPs) no sinónimos en el 27.3% de la muestra, c.293A>G (p.Asp98Gly) y c.1699G>A (p.Ala567Thr), localizados en los exones 2 y 4, que corresponden, desde el punto de vista funcional, a la variante Atípica (A) [dbSNP: rs1799807] y a la variante Kalow (K) [dbSNP: rs1803274] de la enzima BChE, respectivamente. Los estudios de predicción In silico establecieron para el SNP p.Asp98Gly un carácter patogénico, mientras que para el SNP p.Ala567Thr, mostraron un comportamiento neutro. El análisis de los resultados permite proponer la existencia de una relación entre polimorfismos o variantes genéticas responsables de una baja actividad catalítica y/o baja concentración plasmática de la enzima BChE y algunas de las reacciones adversas ocurridas en pacientes consumidores de cocaína.
Resumo:
El desplazamiento forzado de población en la zona del Alto Sinú durante los años 1998 – 2002 responde al interés de los grupos armados ilegales por dominar el territorio y reconfigurar el orden socioeconómico en el mismo.
Resumo:
Esto texto examina cuatro conceptos de vida que se consideran notables en el siglo XX, los contrasta y propone algunos aspectos que pueden enriquecer el concepto.