Caracterización preliminar de razas y biovares de Rolstonia solanacearum (E.F. Smith) Yabuuchi et-al, en Nicaragua

Ralstonia solanacearum (E.F.Smith) Yabuuchi et al., causa la marchites bacteriana de un amplio rango de cultivos en muchas regiones tropicales y subtropicales y en algunas zonas calientes de paises con clima templado. Esta bacteria es una especie altamente variable, por consiguiente, el estudio de su diversidad poblacional es un importante factor a considerar para su control. El objetivo principal de este estudio fue el de caracterizar la estructura poblacional de R. solanacearum al determinar sus razas y biovares en diferentes sitios de Nicaragua. El muestreo se llevó a cabo en cuatro departamentos de Nicaragua (Esteli, Matagalpa, Jinotega y Rivas). Se recolectaron y purificaron 33 aislamientos. De estos, 27 aislamientos fueron confirmados que eran R. solanacearum. A través de pruebas bioquímicas se identificaron veinte aislamientos pertenecientes a la Raza 1, Biovar 3 y 7 pertenecientes a la Raza 2, Biovar 3. El biovar 3 es el más prevalente en los sitios muestreados.

A-SCALA: an age-structured statistical catch-at-length analysis for assessing tuna stocks in the eastern tropical Pacific Ocean

English: We describe an age-structured statistical catch-at-length analysis (A-SCALA) based on the MULTIFAN-CL model of Fournier et al. (1998). The analysis is applied independently to both the yellowfin and the bigeye tuna populations of the eastern Pacific Ocean (EPO). We model the populations from 1975 to 1999, based on quarterly time steps. Only a single stock for each species is assumed for each analysis, but multiple fisheries that are spatially separate are modeled to allow for spatial differences in catchability and selectivity. The analysis allows for error in the effort-fishing mortality relationship, temporal trends in catchability, temporal variation in recruitment, relationships between the environment and recruitment and between the environment and catchability, and differences in selectivity and catchability among fisheries. The model is fit to total catch data and proportional catch-at-length data conditioned on effort. The A-SCALA method is a statistical approach, and therefore recognizes that the data collected from the fishery do not perfectly represent the population. Also, there is uncertainty in our knowledge about the dynamics of the system and uncertainty about how the observed data relate to the real population. The use of likelihood functions allow us to model the uncertainty in the data collected from the population, and the inclusion of estimable process error allows us to model the uncertainties in the dynamics of the system. The statistical approach allows for the calculation of confidence intervals and the testing of hypotheses. We use a Bayesian version of the maximum likelihood framework that includes distributional constraints on temporal variation in recruitment, the effort-fishing mortality relationship, and catchability. Curvature penalties for selectivity parameters and penalties on extreme fishing mortality rates are also included in the objective function. The mode of the joint posterior distribution is used as an estimate of the model parameters. Confidence intervals are calculated using the normal approximation method. It should be noted that the estimation method includes constraints and priors and therefore the confidence intervals are different from traditionally calculated confidence intervals. Management reference points are calculated, and forward projections are carried out to provide advice for making management decisions for the yellowfin and bigeye populations. Spanish: Describimos un análisis estadístico de captura a talla estructurado por edad, A-SCALA (del inglés age-structured statistical catch-at-length analysis), basado en el modelo MULTIFAN- CL de Fournier et al. (1998). Se aplica el análisis independientemente a las poblaciones de atunes aleta amarilla y patudo del Océano Pacífico oriental (OPO). Modelamos las poblaciones de 1975 a 1999, en pasos trimestrales. Se supone solamente una sola población para cada especie para cada análisis, pero se modelan pesquerías múltiples espacialmente separadas para tomar en cuenta diferencias espaciales en la capturabilidad y selectividad. El análisis toma en cuenta error en la relación esfuerzo-mortalidad por pesca, tendencias temporales en la capturabilidad, variación temporal en el reclutamiento, relaciones entre el medio ambiente y el reclutamiento y entre el medio ambiente y la capturabilidad, y diferencias en selectividad y capturabilidad entre pesquerías. Se ajusta el modelo a datos de captura total y a datos de captura a talla proporcional condicionados sobre esfuerzo. El método A-SCALA es un enfoque estadístico, y reconoce por lo tanto que los datos obtenidos de la pesca no representan la población perfectamente. Además, hay incertidumbre en nuestros conocimientos de la dinámica del sistema e incertidumbre sobre la relación entre los datos observados y la población real. El uso de funciones de verosimilitud nos permite modelar la incertidumbre en los datos obtenidos de la población, y la inclusión de un error de proceso estimable nos permite modelar las incertidumbres en la dinámica del sistema. El enfoque estadístico permite calcular intervalos de confianza y comprobar hipótesis. Usamos una versión bayesiana del marco de verosimilitud máxima que incluye constreñimientos distribucionales sobre la variación temporal en el reclutamiento, la relación esfuerzo-mortalidad por pesca, y la capturabilidad. Se incluyen también en la función objetivo penalidades por curvatura para los parámetros de selectividad y penalidades por tasas extremas de mortalidad por pesca. Se usa la moda de la distribución posterior conjunta como estimación de los parámetros del modelo. Se calculan los intervalos de confianza usando el método de aproximación normal. Cabe destacar que el método de estimación incluye constreñimientos y distribuciones previas y por lo tanto los intervalos de confianza son diferentes de los intervalos de confianza calculados de forma tradicional. Se calculan puntos de referencia para el ordenamiento, y se realizan proyecciones a futuro para asesorar la toma de decisiones para el ordenamiento de las poblaciones de aleta amarilla y patudo.

Effects of starvation on larval growth, survival and metamorphosis of Ivory shell Babylonia formosae habei Altena et al., 1981 (Neogastropoda : Buccinidae)

The impact of starvation on larvae of Ivory shell Babylonia formosae habei was studied in a laboratory experiment. Newly hatched veligers showed considerable tolerance to starvation due to their endogenous yolk material, and time to the point-of-no-return (PNR; the threshold point during starvation after which larvae can longer metamorphose even if food is provided) was calculated to be 104.5 h. However, starvation still affected larval growth, survival, and metamorphosis. Mean shell length of larvae increased 49.77 mum day(-1) for nonstarved, but only 11.13 mum day (-1) for larvae starved for 108 h. After larvae began feeding, their growth rates rapidly recovered to the level of the nonstarved following short periods of starvation (less than 48 h), but were inhibited and unable to ever reach the level of the nonstarved when being starved beyond 48 h. Percent metamorphosis was 53.75% for the nonstarved, but all larvae died before 10 days for those starved for 108 h. Starvation not only affected larval time to reach metamorphosis, but also caused the delay in the time to metamorphosis. For the nonstarved, larvae took only 11.5 days to reach spontaneous metamorphosis, but they took 20 days to reach spontaneous metamorphosis when starved for 96 h, and this duration of delayed metamorphosis reached 8.5 days. Furthermore, the importance of yolk material for maintaining larval survival of B. formosae habei during starvation periods is also discussed. (C) 2004 Elsevier B.V. All rights reserved.

The role of the dopaminergic neurotrophin growth/differentiation factor-5 in the developing rat ventral midbrain

Growth differentiation factor-5 (GDF-5) is a member of the transforming growth factor-β superfamily, a family of proteins that play diverse roles in many aspects of cell growth, proliferation and differentiation. GDF-5 has also been shown to be a trophic factor for embryonic midbrain dopaminergic neurons in vitro (Krieglstein et al. 1995) and after transplantation to adult rats in vivo (Sullivan et al. 1998). GDF-5 has also been shown to have neuroprotective and neurorestorative effects on adult dopaminergic neurons in the substantia nigra in animal models of Parkinson’s disease (Sullivan et al. 1997, 1999; Hurley et al. 2004). This experimental evidence has lead to GDF-5 being proposed as a neurotrophic factor with potential for use in the treatment of Parkinson’s disease. However, it is not know if GDF-5 is expressed in the brain and whether it plays a role in dopaminergic neuron development. The experiments presented here aim to address these questions. To that end this thesis is divided into five separate studies each addressing a particular question associated with GDF-5 and its expression patterns and roles during the development of the rat midbrain. Expression of the GDF-5 in the developing rat ventral mesencephalon (VM) was found to begin at E12 and peak on E14, the day that dopaminergic neurons undergo terminal differentiation. In the adult rat, GDF-5 was found to be restricted to heart and brain, being expressed in many areas of the brain, including striatum and midbrain. This indicated a role for GDF-5 in the development and maintenance of dopaminergic neurons. The appropriate receptors for GDF-5 (BMPR-II and BMPR-Ib) were found to be expressed at high levels in the rat VM at E14 and BMPR-II expression was demonstrated on dopaminergic neurons in the E13 mouse VM. GDF-5 resulted in a three-fold increase in the numbers of dopaminergic neurons in cultures of E14 rat VM, without affecting the numbers of neurones or total cells. GDF-5 was found to increase the proportion of neurons that were dopaminergic. The numbers of Nurr1-positive cells were not affected by GDF-5 treatment, but GDF-5 did increase the numbers of Nurr1- positive cells that expressed tyrosine hydroxylase (TH). Taken together this data indicated that GDF-5 increases the conversion of Nurr1-positive, TH-negative cells to Nurr1-positive, TH-positive cells. In GDF-5 treated cultures, total neurite length, neurite arborisation and somal area of dopaminergic were all significantly increased compared to control cultures. Thus this study showed that GDF-5 increased the numbers and morphological differentiation of VM dopaminergic neurones in vitro. In order to examine if GDF-5 could induce a dopaminergic phenotype in neural progenitor cells, neurosphere cultures prepared from embryonic rat VM were established. The effect of the gestational age of the donor VM on the proportion of cell types generated from neurospheres from E12, E13 and E14 VM was examined. Dopaminergic neurons could only be generated from neurospheres which were prepared from E12 VM. Thus in subsequent studies the effect of GDF-5 on dopaminergic induction was examined in progentior cell cultures prepared from the E12 rat VM. In primary cultures of E12 rat VM, GDF-5 increased the numbers of TH-positive cells without affecting the proliferation or survival of these cells. In cultures of expanded neural progenitor cells from the E12 rat VM, GDF-5 increased the expression of Nurr1 and TH, an action that was dependent on signalling through the BMPR-Ib receptor. Taken together, these experiments provide evidence that GDF-5 is expressed in the developing rat VM, is involved in both the induction of a dopaminergic phenotype in cells of the VM and in the subsequent morphological development of these dopaminergic neurons

Naturalis historie libri XXXVII : nuper studiose recogniti ([Reprod.]) / atque impressi adiectis variis Antonii Sabellici, Raphaelis Volaterrani, Beroaldi, [et al.]... adnotationibus ; ed. Nicolaus Beraldus

[Histoire naturelle (latin). 1516]

Inglés III Sara Alicia Ancira Arechiga...[et al.]

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Manual de unidades de inglés Sara Alicia Ancira Aréchiga ... [et al.]

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Manual de unidades de inglés Sara Alicia Ancira Aréchiga ... [et al.]

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Manual de unidades inglés coord. Sara Alicia Ancira Aréchiga... [et al.]

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