992 resultados para GENETIC-RECOMBINATION


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Methods for generating a new population are a fundamental component of estimation of distribution algorithms (EDAs). They serve to transfer the information contained in the probabilistic model to the new generated population. In EDAs based on Markov networks, methods for generating new populations usually discard information contained in the model to gain in efficiency. Other methods like Gibbs sampling use information about all interactions in the model but are computationally very costly. In this paper we propose new methods for generating new solutions in EDAs based on Markov networks. We introduce approaches based on inference methods for computing the most probable configurations and model-based template recombination. We show that the application of different variants of inference methods can increase the EDAs’ convergence rate and reduce the number of function evaluations needed to find the optimum of binary and non-binary discrete functions.

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A shock tube method is introduced to study the ionization–recombination kinetics of high temperature gas, in which a test gas is heated and ionized by a reflected shock wave and subsequently quenched by a strong rarefaction wave reflected on the end wall of the driver section as the main cooling wave associated with a rarefaction wave incident back into region 5 when the reflected shock wave interacts with the contact surface. As the quenching rate of the strong rarefaction wave reaches 106 K/s, a nonequilibrium ionization-recombination process occurs, during which the ion recombination with electrons dominates.

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La Leucemia Linfoblástica Aguda (LLA) es el cáncer pediátrico más común. Es un desorden de las células linfoblásticas, que son las precursoras de las células linfáticas, y se caracteriza por la acumulación en médula ósea y sangre de pequeñas células blásticas con poco citoplasma y cromatina dispersa. En las últimas décadas, se ha conseguido aumentar la supervivencia del 10% al 80% pero todavía hay un 20% de pacientes que no responden al tratamiento. Esta mejoría se ha conseguido mediante la implantación de terapias combinadas y la adecuación de la terapia a grupos de riesgo. Los pacientes se separan en tres grupos de riesgo, Riesgo Estándar (RE), Alto Riesgo (AR) y Muy Alto Riesgo (MAR), en base a marcadores pronósticos, entre los que se incluyen alteraciones citogenéticas. Sin embargo, a lo largo del tratamiento, nos encontramos con dos problemas:1) Por un lado, algunos de los pacientes incluidos en el grupo de RE y AR no responden bien al tratamiento y pasan AR y MAR respectivamente. Esto quiere decir que los grupos de riesgo no están bien definidos. Por lo tanto, sería de interés poder caracterizar los pacientes que realmente son RE y AR y aquéllos que desde un principio deberían haber sido considerados como de mayor riesgo.2) Por otro lado, un alto porcentaje de pacientes experimenta toxicidad, que puede llegar a ser muy grave en algunos casos, siendo necesario parar el tratamiento. Por este motivo, sería altamente beneficioso poder reconocer a los pacientes que van a ser más sensibles al tratamiento para, de ese modo, poder ajustar la dosis.Por todo esto, creemos que una mejor asignación de los pacientes de LLA a grupos de riesgo y la personalización de la dosis, mediante nuevos marcadores genéticos, permitiría mejorar la respuesta al tratamiento.En este estudio nos planteamos, por lo tanto, dos objetivos: 1) Llevar a cabo la identificación de nuevas alteraciones genéticas presentes en el tumor para una mejor caracterización del riesgo y 2) Realizar una caracterización genética del individuo que permita predecir la respuesta al tratamiento.

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Background:Human papillomavirus (HPV) variants differ in their biological and chemical properties, and therefore, may present differences in pathogenicity. Most authors classified variants based on the phylogenetic analysis of L1 region. Nevertheless, recombination in HPV samples is becoming a usual finding and thus, characterizing genetic variability in other regions should be essential. Objectives:We aimed to characterize the genetic variability of HPV 18 in 5 genomic regions: E6, E7, E4, L1 and the Upstream Regulatory Region (URR), working with both single infection and multiple HPV infection samples. Furthermore, we aimed to assess the prevalence of HPV 18 variants in our region and look for possible existence of recombination as well as analyze the relationship between these variants and the type of lesion. Methods: From 2007 to 2010, Clinical Microbiology and Infection Control Department analyzed 44 samples which were positive for HPV 18. Genetic variability was determined in PCR products and variants were assigned to European, Asian-amerindian or African lineage. Recombination and association of variants with different types of lesion was studied. Results: Genetic analysis of the regions revealed a total of 56 nucleotide variations. European, African and Asian-amerindian variants were found in 25/44 (56.8%), 10/44 (22.7%) and 5/44 (11.4%) samples, respectively. We detected the presence of recombinant variants in 2/44 (4.5%) cases. Samples taken from high-grade squamous intraepithelial lesions (H-SIL) only presented variants with specific-african substitutions. Conclusions: Multiple HPV infection, non-european HPV variants prevalence and existence of recombination are considered risk factors for HPV persistence and progression of intraepithelial abnormalities, and therefore, should be taken into consideration in order to help to design and optimize diagnostics protocols as well as improve epidemiologic studies. Our study is one of the few studies in Spain which analyses the genetic variability of HPV18 and we showed the importance of characterizing more than one genomic region in order to detect recombination and classify HPV variants properly