997 resultados para Nuclear models
Resumo:
The evolution of a quantitative phenotype is often envisioned as a trait substitution sequence where mutant alleles repeatedly replace resident ones. In infinite populations, the invasion fitness of a mutant in this two-allele representation of the evolutionary process is used to characterize features about long-term phenotypic evolution, such as singular points, convergence stability (established from first-order effects of selection), branching points, and evolutionary stability (established from second-order effects of selection). Here, we try to characterize long-term phenotypic evolution in finite populations from this two-allele representation of the evolutionary process. We construct a stochastic model describing evolutionary dynamics at non-rare mutant allele frequency. We then derive stability conditions based on stationary average mutant frequencies in the presence of vanishing mutation rates. We find that the second-order stability condition obtained from second-order effects of selection is identical to convergence stability. Thus, in two-allele systems in finite populations, convergence stability is enough to characterize long-term evolution under the trait substitution sequence assumption. We perform individual-based simulations to confirm our analytic results.
Resumo:
Adherens junctions (AJs) and cell polarity complexes are key players in the establishment and maintenance of apical-basal cell polarity. Loss of AJs or basolateral polarity components promotes tumor formation and metastasis. Recent studies in vertebrate models show that loss of AJs or loss of the basolateral component Scribble (Scrib) cause deregulation of the Hippo tumor suppressor pathway and hyperactivation of its downstream effectors Yes-associated protein (YAP) and Transcriptional coactivator with PDZ-binding motif (TAZ). However, whether AJs and Scrib act through the same or independent mechanisms to regulate Hippo pathway activity is not known. Here, we dissect how disruption of AJs or loss of basolateral components affect the activity of the Drosophila YAP homolog Yorkie (Yki) during imaginal disc development. Surprisingly, disruption of AJs and loss of basolateral proteins produced very different effects on Yki activity. Yki activity was cell-autonomously decreased but non-cell-autonomously elevated in tissues where the AJ components E-cadherin (E-cad) or α-catenin (α-cat) were knocked down. In contrast, scrib knockdown caused a predominantly cell-autonomous activation of Yki. Moreover, disruption of AJs or basolateral proteins had different effects on cell polarity and tissue size. Simultaneous knockdown of α-cat and scrib induced both cell-autonomous and non-cell-autonomous Yki activity. In mammalian cells, knockdown of E-cad or α-cat caused nuclear accumulation and activation of YAP without overt effects on Scrib localization and vice versa. Therefore, our results indicate the existence of multiple, genetically separable inputs from AJs and cell polarity complexes into Yki/YAP regulation.
Resumo:
Network airlines have been increasingly focusing their operations on hub airports through the exploitation of connecting traffic, allowing them to take advantage of economies of traffic density, which are unequivocal in the airline industry. Less attention has been devoted to airlines' decisions on point-to-point thin routes, which could be served using different aircraft technologies and different business models. This paper examines, both theoretically and empirically, the impact on airlines' networks of the two major innovations in the airline industry in the last two decades: the regional jet technology and the low-cost business model. We show that, under certain circumstances, direct services on point-to-point thin routes can be viable and thus airlines may be interested in deviating passengers out of the hub. Keywords: regional jet technology; low-cost business model; point-to-point network; hub-and-spoke network JEL Classi…fication Numbers: L13; L2; L93
Resumo:
By using improved pulsed field gel electrophoresis conditions, the molecular karyotype of the reference clone CL Brener selected for Trypanosoma cruzi genome project was established. A total of 20 uniform chromosomal bands ranging in size from 0.45 to 3.5 Megabase pairs (Mbp) were resolved in a single run. The weighted sum of the chromosomal bands was approximately 87 Mbp. Chromoblots were hybridized with 39 different homologous probes, 13 of which identified single chromosomes. Several markers showed linkage and four different linkage groups were identified, each comprising two markers. Densitometric analysis suggests that most of the chromosomal bands contain two or more chromosomes representing either homologous chromosomes and/or heterologous chromosomes with similar sizes
Resumo:
Strategies to construct the physical map of the Trypanosoma cruzi nuclear genome have to capitalize on three main advantages of the parasite genome, namely (a) its small size, (b) the fact that all chromosomes can be defined, and many of them can be isolated by pulse field gel electrophoresis, and (c) the fact that simple Southern blots of electrophoretic karyotypes can be used to map sequence tagged sites and expressed sequence tags to chromosomal bands. A major drawback to cope with is the complexity of T. cruzi genetics, that hinders the construction of a comprehensive genetic map. As a first step towards physical mapping, we report the construction and partial characterization of a T. cruzi CL-Brener genomic library in yeast artificial chromosomes (YACs) that consists of 2,770 individual YACs with a mean insert size of 365 kb encompassing around 10 genomic equivalents. Two libraries in bacterial artificial chromosomes (BACs) have been constructed, BACI and BACII. Both libraries represent about three genome equivalents. A third BAC library (BAC III) is being constructed. YACs and BACs are invaluable tools for physical mapping. More generally, they have to be considered as a common resource for research in Chagas disease
Resumo:
This paper presents an analysis of motor vehicle insurance claims relating to vehicle damage and to associated medical expenses. We use univariate severity distributions estimated with parametric and non-parametric methods. The methods are implemented using the statistical package R. Parametric analysis is limited to estimation of normal and lognormal distributions for each of the two claim types. The nonparametric analysis presented involves kernel density estimation. We illustrate the benefits of applying transformations to data prior to employing kernel based methods. We use a log-transformation and an optimal transformation amongst a class of transformations that produces symmetry in the data. The central aim of this paper is to provide educators with material that can be used in the classroom to teach statistical estimation methods, goodness of fit analysis and importantly statistical computing in the context of insurance and risk management. To this end, we have included in the Appendix of this paper all the R code that has been used in the analysis so that readers, both students and educators, can fully explore the techniques described
Resumo:
Brown adipose tissue and liver of hibernating, arousing and euthermic individuals of the dormouse Muscardinus avellanarius were studies using ultrastructural cytochemistry and immunocytochemistry with the aim to investigate possible fine structural modifications of the cell nucleus during the seasonal cycle. The general morphology of brown adipocyte and hepatocyte nuclei was similar in the three experimental groups. However, three nuclear structural constituents were identified only in hibernating individuals: coiled bodies (CBs) and amorphous bodies (ABs) were observed in hepatocytes and, together with bundles of nucleoplasmic fibrils (NF), were present in brown adipocytes of hibernating dormice. In arousing animals only some structural constituents suggestive of poorly structured CBs were found. The latter showed the same immunocytochemical features as CBs of hibernating individuals, suggesting that they are disappearing CBs. A possible involvement of CBs in storing and/or processing RNA which must be rapidly and abundantly released upon arousal is discussed. ABs similarly to CBs contain RNA and nucleoplasmic ribonucleoproteins (RNPs) and could also be involved in mRNA pathways. NF do not contain nucleic acids or RNPs and seem to be composed of protein-aceous material; their functional role in the nuclear metabolism of hibernating brown adipocytes remains unclear.
Resumo:
Species distribution models (SDMs) are widely used to explain and predict species ranges and environmental niches. They are most commonly constructed by inferring species' occurrence-environment relationships using statistical and machine-learning methods. The variety of methods that can be used to construct SDMs (e.g. generalized linear/additive models, tree-based models, maximum entropy, etc.), and the variety of ways that such models can be implemented, permits substantial flexibility in SDM complexity. Building models with an appropriate amount of complexity for the study objectives is critical for robust inference. We characterize complexity as the shape of the inferred occurrence-environment relationships and the number of parameters used to describe them, and search for insights into whether additional complexity is informative or superfluous. By building 'under fit' models, having insufficient flexibility to describe observed occurrence-environment relationships, we risk misunderstanding the factors shaping species distributions. By building 'over fit' models, with excessive flexibility, we risk inadvertently ascribing pattern to noise or building opaque models. However, model selection can be challenging, especially when comparing models constructed under different modeling approaches. Here we argue for a more pragmatic approach: researchers should constrain the complexity of their models based on study objective, attributes of the data, and an understanding of how these interact with the underlying biological processes. We discuss guidelines for balancing under fitting with over fitting and consequently how complexity affects decisions made during model building. Although some generalities are possible, our discussion reflects differences in opinions that favor simpler versus more complex models. We conclude that combining insights from both simple and complex SDM building approaches best advances our knowledge of current and future species ranges.
Resumo:
There are several experimental models describing in vivo eosinophil (EO) migration, including ip injection of a large volume of saline (SAL) or Sephadex beads (SEP). The aim of this study was to investigate the mechanisms involved in the EO migration in these two models. Two consecutive injections of SAL given 48 hr apart, induced a selective recruitment of EO into peritoneal cavity of rats, which peaked 48 hr after the last injection. SEP, when injected ip, promoted EO accumulation in rats. The phenomenom was dose-related and peaked 48 hr after SEP injection. To investigate the mediators involved in this process we showed that BW A4C, MK 886 and dexamethasone (DXA) inhibited the EO migration induced by SAL and SEP. To investigate the source of the EO chemotactic factor we showed that mast cells, macrophages (MO), but not lymphocytes, incubated in vitro in presence of SAL released a factor which induced EO migration. With SEP, only mast cells release a factor that induced EO migration, which was inhibited by BW A4C, MK 886 and DXA. Furthermore, the chemotactic activity of SAL-stimulated mast cells was inhibited by antisera against IL-5 and IL-8 (interleukin). SAL-stimulated MO were only inhibited by anti-IL-8 antibodies as well SEP-stimulated mast cells. These results suggest that the EO migration induced by SAL may be dependent on resident mast cells and MO and mediated by LTB4, IL-5 and IL-8. SEP-induced EO migration was dependent on mast cells and may be mediated by LTB4 and IL-8. Furthermore, IL-5 and IL-8 induced EO migration, which was also dependent on resident cells and mediated by LTB4 . In conclusion, EO migration induced by SAL is dependent on mast cells and MO, whereas that induced by SEP is dependent on mast cells alone. Stimulated mast cells release LTB4, IL-5 and IL-8 while MO release LTB4 and IL-8. The IL-5 and IL-8 release by the SAL or SEP-stimulated resident cells may act in an autocrine fashion, thus potentiating LTB4 release.
Resumo:
Eosinophils play a central role in the establishment and outcome of bronchial inflammation in asthma. Animal models of allergy are useful to answer questions related to mechanisms of allergic inflammation. We have used models of sensitized and boosted guinea pigs to investigate the nature of bronchial inflammation in allergic conditions. These animals develop marked bronchial infiltration composed mainly of CD4+ T-lymphocytes and eosinophils. Further provocation with antigen leads to degranulation of eosinophils and ulceration of the bronchial mucosa. Eosinophils are the first cells to increase in numbers in the mucosa after antigen challenge and depend on the expression of alpha 4 integrin to adhere to the vascular endothelium and transmigrate to the mucosa. Blockage of alpha4 integrin expression with specific antibody prevents not only the transmigration of eosinophils but also the development of bronchial hyperresponsiveness (BHR) to agonists in sensitized and challenged animals, clearly suggesting a role for this cell type in this altered functional state. Moreover, introduction of antibody against Major Basic Protein into the airways also prevents the development of BHR in similar model. BHR can also be suppressed by the use of FK506, an immunosuppressor that reduces in almost 100% the infiltration of eosinophils into the bronchi of allergic animals. These data support the concept that eosinophil is the most important pro-inflammatory factor in bronchial inflammation associated with allergy.
Resumo:
In a recent paper Bermúdez [2009] used bivariate Poisson regression models for ratemaking in car insurance, and included zero-inflated models to account for the excess of zeros and the overdispersion in the data set. In the present paper, we revisit this model in order to consider alternatives. We propose a 2-finite mixture of bivariate Poisson regression models to demonstrate that the overdispersion in the data requires more structure if it is to be taken into account, and that a simple zero-inflated bivariate Poisson model does not suffice. At the same time, we show that a finite mixture of bivariate Poisson regression models embraces zero-inflated bivariate Poisson regression models as a special case. Additionally, we describe a model in which the mixing proportions are dependent on covariates when modelling the way in which each individual belongs to a separate cluster. Finally, an EM algorithm is provided in order to ensure the models’ ease-of-fit. These models are applied to the same automobile insurance claims data set as used in Bermúdez [2009] and it is shown that the modelling of the data set can be improved considerably.
Resumo:
Obesity is an increasingly serious health problem, and is highly associated with insulin-resistance and dyslipidemia. The mechanisms involved in the development of this disorder are still poorly understood, although significant progress has been recently made in the elucidation of their molecular basis. The major causes leading to obesity are defects in the regulation of fat metabolism. Several mutations identified in different animal models have unveiled the roles of a number of genes in the regulation of energy balance. These dicoveries, together with the fact that some of these mutations have been found in humans, have lead to the conclusion that obesity is due to nutritional or environmental factors, but also involves genetic factors. A number of important peripheric factors participate in the regulation processes, such as the adipocyte-specific hormone leptin, and the nuclear homone receptors PPARs. A general scheme can now be drawn which includes some key factors and their respective interactions.
Resumo:
A better understanding of the factors that mould ecological community structure is required to accurately predict community composition and to anticipate threats to ecosystems due to global changes. We tested how well stacked climate-based species distribution models (S-SDMs) could predict butterfly communities in a mountain region. It has been suggested that climate is the main force driving butterfly distribution and community structure in mountain environments, and that, as a consequence, climate-based S-SDMs should yield unbiased predictions. In contrast to this expectation, at lower altitudes, climate-based S-SDMs overpredicted butterfly species richness at sites with low plant species richness and underpredicted species richness at sites with high plant species richness. According to two indices of composition accuracy, the Sorensen index and a matching coefficient considering both absences and presences, S-SDMs were more accurate in plant-rich grasslands. Butterflies display strong and often specialised trophic interactions with plants. At lower altitudes, where land use is more intense, considering climate alone without accounting for land use influences on grassland plant richness leads to erroneous predictions of butterfly presences and absences. In contrast, at higher altitudes, where climate is the main force filtering communities, there were fewer differences between observed and predicted butterfly richness. At high altitudes, even if stochastic processes decrease the accuracy of predictions of presence, climate-based S-SDMs are able to better filter out butterfly species that are unable to cope with severe climatic conditions, providing more accurate predictions of absences. Our results suggest that predictions should account for plants in disturbed habitats at lower altitudes but that stochastic processes and heterogeneity at high altitudes may limit prediction success of climate-based S-SDMs.