963 resultados para population pattern
Resumo:
The blue shark, Prionace glauca, is one of the most vagile shark species worldwide distributed. The particular body shape allows blue sharks make transoceanic movements, leading to a circumglobal distribution. Due to its reproductive cycle, an extraordinarily high number of specimens is globally registered but, even if it is still a major bycatch of longline fishery rather than a commercial target, it is characterized by a high vulnerability. In this perspective it is important to increase the amount of informations regarding its population extent in the different worldwide areas, evaluating the possible phylogeographic patterns between different locations. This study, included in the "MedBlueSGen" European project, aims exactly at filling a gap in knowledges regarding the genetic population structure of the Mediterranean blue sharks, which has never been investigated before, with a comparison with the North-Eastern Atlantic blue shark population. To reach this objective, we used a dataset of samples from different Mediterranean areas implementing it with some samples from North-Eastern Atlantic. Analyzing the variability of the two mitochondrial markers control region and cytochrome b, with the design of new species-specific primer pairs, we assessed the mitochondrial genetic structure of Mediterranean and North-Eastern Atlantic samples, focusing on the analysis of their possible connectivity, and we tried to reconstruct their demographic history and population size. Data analyses highlighted the absence of a genetic structuring within the Mediterranean and among it and North-Eastern Atlantic, suggesting that the Strait of Gibraltar doesn't represent a phylogeographic barrier. These results are coherent to what has been found in similar investigations on other worldwide blue shark populations. Analysis of the historical demographic trend revealed a general stable pattern for the cytochrome-b and a slightly population expansion for the control region marker.
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P>1. There are a number of models describing population structure, many of which have the capacity to incorporate spatial habitat effects. One such model is the source-sink model, that describes a system where some habitats have a natality that is higher than mortality (source) and others have a mortality that exceeds natality (sink). A source can be maintained in the absence of migration, whereas a sink will go extinct. 2. However, the interaction between population dynamics and habitat quality is complex, and concerns have been raised about the validity of published empirical studies addressing source-sink dynamics. In particular, some of these studies fail to provide data on survival, a significant component in disentangling a sink from a low quality source. Moreover, failing to account for a density-dependent increase in mortality, or decrease in fecundity, can result in a territory being falsely assigned as a sink, when in fact, this density-dependent suppression only decreases the population size to a lower level, hence indicating a 'pseudo-sink'. 3. In this study, we investigate a long-term data set for key components of territory-specific demography (mortality and reproduction) and their relationship to habitat characteristics in the territorial, group-living Siberian jay (Perisoreus infaustus). We also assess territory-specific population growth rates (r), to test whether spatial population dynamics are consistent with the ideas of source-sink dynamics. 4. Although average mortality did not differ between sexes, habitat-specific mortality did. Female mortality was higher in older forests, a pattern not observed in males. Male mortality only increased with an increasing amount of open areas. Moreover, reproductive success was higher further away from human settlement, indicating a strong effect of human-associated nest predators. 5. Averaged over all years, 76% of the territories were sources. These territories generally consisted of less open areas, and were located further away from human settlement. 6. The source-sink model provides a tool for modelling demography in distinct habitat patches of different quality, which can aid in identifying key habitats within the landscape, and thus, reduce the risk of implementing unsound management decisions.
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Background: Reconstructing the evolutionary history of a species is challenging. It often depends not only on the past biogeographic and climatic events but also the contemporary and ecological factors, such as current connectivity and habitat heterogeneity. In fact, these factors might interact with each other and shape the current species distribution. However, to what extent the current population genetic structure reflects the past and the contemporary factors is largely unknown. Here we investigated spatio-temporal genetic structures of Nile tilapia (Oreochromis niloticus) populations, across their natural distribution in Africa. While its large biogeographic distribution can cause genetic differentiation at the paleo-biogeographic scales, its restricted dispersal capacity might induce a strong genetic structure at micro-geographic scales. Results: Using nine microsatellite loci and 350 samples from ten natural populations, we found the highest genetic differentiation among the three ichthyofaunal provinces and regions (Ethiopian, Nilotic and Sudano-Sahelian) (R(ST) = 0.38 - 0.69). This result suggests the predominant effect of paleo-geographic events at macro-geographic scale. In addition, intermediate divergences were found between rivers and lakes within the regions, presumably reflecting relatively recent interruptions of gene flow between hydrographic basins (R(ST) = 0.24 - 0.32). The lowest differentiations were observed among connected populations within a basin (R(ST) = 0.015 in the Volta basin). Comparison of temporal sample series revealed subtle changes in the gene pools in a few generations (F = 0 - 0.053). The estimated effective population sizes were 23 - 143 and the estimated migration rate was moderate (m similar to 0.094 - 0.097) in the Volta populations. Conclusions: This study revealed clear hierarchical patterns of the population genetic structuring of O. niloticus in Africa. The effects of paleo-geographic and climatic events were predominant at macro-geographic scale, and the significant effect of geographic connectivity was detected at micro-geographic scale. The estimated effective population size, the moderate level of dispersal and the rapid temporal change in genetic composition might reflect a potential effect of life history strategy on population dynamics. This hypothesis deserves further investigation. The dynamic pattern revealed at micro-geographic and temporal scales appears important from a genetic resource management as well as from a biodiversity conservation point of view.
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The relation between residential magnetic field exposure from power lines and mortality from neurodegenerative conditions was analyzed among 4.7 million persons of the Swiss National Cohort (linking mortality and census data), covering the period 2000-2005. Cox proportional hazard models were used to analyze the relation of living in the proximity of 220-380 kV power lines and the risk of death from neurodegenerative diseases, with adjustment for a range of potential confounders. Overall, the adjusted hazard ratio for Alzheimer's disease in persons living within 50 m of a 220-380 kV power line was 1.24 (95% confidence interval (CI): 0.80, 1.92) compared with persons who lived at a distance of 600 m or more. There was a dose-response relation with respect to years of residence in the immediate vicinity of power lines and Alzheimer's disease: Persons living at least 5 years within 50 m had an adjusted hazard ratio of 1.51 (95% CI: 0.91, 2.51), increasing to 1.78 (95% CI: 1.07, 2.96) with at least 10 years and to 2.00 (95% CI: 1.21, 3.33) with at least 15 years. The pattern was similar for senile dementia. There was little evidence for an increased risk of amyotrophic lateral sclerosis, Parkinson's disease, or multiple sclerosis.
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This dissertation has three separate parts: the first part deals with the general pedigree association testing incorporating continuous covariates; the second part deals with the association tests under population stratification using the conditional likelihood tests; the third part deals with the genome-wide association studies based on the real rheumatoid arthritis (RA) disease data sets from Genetic Analysis Workshop 16 (GAW16) problem 1. Many statistical tests are developed to test the linkage and association using either case-control status or phenotype covariates for family data structure, separately. Those univariate analyses might not use all the information coming from the family members in practical studies. On the other hand, the human complex disease do not have a clear inheritance pattern, there might exist the gene interactions or act independently. In part I, the new proposed approach MPDT is focused on how to use both the case control information as well as the phenotype covariates. This approach can be applied to detect multiple marker effects. Based on the two existing popular statistics in family studies for case-control and quantitative traits respectively, the new approach could be used in the simple family structure data set as well as general pedigree structure. The combined statistics are calculated using the two statistics; A permutation procedure is applied for assessing the p-value with adjustment from the Bonferroni for the multiple markers. We use simulation studies to evaluate the type I error rates and the powers of the proposed approach. Our results show that the combined test using both case-control information and phenotype covariates not only has the correct type I error rates but also is more powerful than the other existing methods. For multiple marker interactions, our proposed method is also very powerful. Selective genotyping is an economical strategy in detecting and mapping quantitative trait loci in the genetic dissection of complex disease. When the samples arise from different ethnic groups or an admixture population, all the existing selective genotyping methods may result in spurious association due to different ancestry distributions. The problem can be more serious when the sample size is large, a general requirement to obtain sufficient power to detect modest genetic effects for most complex traits. In part II, I describe a useful strategy in selective genotyping while population stratification is present. Our procedure used a principal component based approach to eliminate any effect of population stratification. The paper evaluates the performance of our procedure using both simulated data from an early study data sets and also the HapMap data sets in a variety of population admixture models generated from empirical data. There are one binary trait and two continuous traits in the rheumatoid arthritis dataset of Problem 1 in the Genetic Analysis Workshop 16 (GAW16): RA status, AntiCCP and IgM. To allow multiple traits, we suggest a set of SNP-level F statistics by the concept of multiple-correlation to measure the genetic association between multiple trait values and SNP-specific genotypic scores and obtain their null distributions. Hereby, we perform 6 genome-wide association analyses using the novel one- and two-stage approaches which are based on single, double and triple traits. Incorporating all these 6 analyses, we successfully validate the SNPs which have been identified to be responsible for rheumatoid arthritis in the literature and detect more disease susceptibility SNPs for follow-up studies in the future. Except for chromosome 13 and 18, each of the others is found to harbour susceptible genetic regions for rheumatoid arthritis or related diseases, i.e., lupus erythematosus. This topic is discussed in part III.
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The expression pattern of angiotensin AT2 receptors with predominance during fetal life and upregulation under pathological conditions during tissue injury/repair process suggests that AT2 receptors may exert an important action in injury/repair adaptive mechanisms. Less is known about AT2 receptors in acute ischemia-induced cardiac injury. We aimed here to elucidate the role of AT2 receptors after acute myocardial infarction. Double immunofluorescence staining showed that cardiac AT2 receptors were mainly detected in clusters of small c-kit+ cells accumulating in peri-infarct zone and c-kit+AT2+ cells increased in response to acute cardiac injury. Further, we isolated cardiac c-kit+AT2+ cell population by modified magnetic activated cell sorting and fluorescence activated cell sorting. These cardiac c-kit+AT2+ cells, represented approximately 0.19% of total cardiac cells in infarcted heart, were characterized by upregulated transcription factors implicated in cardiogenic differentiation (Gata-4, Notch-2, Nkx-2.5) and genes required for self-renewal (Tbx-3, c-Myc, Akt). When adult cardiomyocytes and cardiac c-kit+AT2+ cells isolated from infarcted rat hearts were cocultured, AT2 receptor stimulation in vitro inhibited apoptosis of these cocultured cardiomyocytes. Moreover, in vivo AT2 receptor stimulation led to an increased c-kit+AT2+ cell population in the infarcted myocardium and reduced apoptosis of cardiomyocytes in rats with acute myocardial infarction. These data suggest that cardiac c-kit+AT2+ cell population exists and increases after acute ischemic injury. AT2 receptor activation supports performance of cardiomyocytes, thus contributing to cardioprotection via cardiac c-kit+AT2+ cell population.
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According to life-history theory age-dependent investments into reproduction are thought to co-vary with survival and growth of animals. In polygynous species, in which size is an important determinant of reproductive success, male reproduction via alternative mating tactics at young age are consequently expected to be the less frequent in species with higher survival. We tested this hypothesis in male Alpine ibex (Capra ibex), a highly sexually dimorphic mountain ungulate whose males have been reported to exhibit extremely high adult survival rates. Using data from two offspring cohorts in a population in the Swiss Alps, the effects of age, dominance and mating tactic on the likelihood of paternity were inferred within a Bayesian framework. In accordance with our hypothesis, reproductive success in male Alpine ibex was heavily biased towards older, dominant males that monopolized access to receptive females by adopting the 'tending' tactic, while success among young, subordinate males via the sneaking tactic 'coursing' was in general low and rare. In addition, we detected a high reproductive skew in male Alpine ibex, suggesting a large opportunity for selection. Compared with other ungulates with higher mortality rates, reproduction among young male Alpine ibex was much lower and more sporadic. Consistent with that, further examinations on the species level indicated that in polygynous ungulates the significance of early reproduction appears to decrease with increasing survival. Overall, this study supports the theory that survival prospects of males modulate the investments into reproduction via alternative mating tactics early in life. In the case of male Alpine ibex, the results indicate that their life-history strategy targets for long life, slow and prolonged growth and late reproduction.
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The interpretation of data on genetic variation with regard to the relative roles of different evolutionary factors that produce and maintain genetic variation depends critically on our assumptions concerning effective population size and the level of migration between neighboring populations. In humans, recent population growth and movements of specific ethnic groups across wide geographic areas mean that any theory based on assumptions of constant population size and absence of substructure is generally untenable. We examine the effects of population subdivision on the pattern of protein genetic variation in a total sample drawn from an artificial agglomerate of 12 tribal populations of Central and South America, analyzing the pooled sample as though it were a single population. Several striking findings emerge. (1) Mean heterozygosity is not sensitive to agglomeration, but the number of different alleles (allele count) is inflated, relative to neutral mutation/drift/equilibrium expectation. (2) The inflation is most serious for rare alleles, especially those which originally occurred as tribally restricted "private" polymorphisms. (3) The degree of inflation is an increasing function of both the number of populations encompassed by the sample and of the genetic divergence among them. (4) Treating an agglomerated population as though it were a panmictic unit of long standing can lead to serious biases in estimates of mutation rates, selection pressures, and effective population sizes. Current DNA studies indicate the presence of numerous genetic variants in human populations. The findings and conclusions of this paper are all fully applicable to the study of genetic variation at the DNA level as well.
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Demographic composition and dynamics of animal and human populations are important determinants for the transmission dynamics of infectious disease and for the effect of infectious disease or environmental disasters on productivity. In many circumstances, demographic data are not available or of poor quality. Since 1999 Switzerland has been recording cattle movements, births, deaths and slaughter in an animal movement database (AMD). The data present in the AMD offers the opportunity for analysing and understanding the dynamic of the Swiss cattle population. A dynamic population model can serve as a building block for future disease transmission models and help policy makers in developing strategies regarding animal health, animal welfare, livestock management and productivity. The Swiss cattle population was therefore modelled using a system of ordinary differential equations. The model was stratified by production type (dairy or beef), age and gender (male and female calves: 0-1 year, heifers and young bulls: 1-2 years, cows and bulls: older than 2 years). The simulation of the Swiss cattle population reflects the observed pattern accurately. Parameters were optimized on the basis of the goodness-of-fit (using the Powell algorithm). The fitted rates were compared with calculated rates from the AMD and differed only marginally. This gives confidence in the fitted rates of parameters that are not directly deductible from the AMD (e.g. the proportion of calves that are moved from the dairy system to fattening plants).
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Survivors of childhood cancer have a higher mortality than the general population. We describe cause-specific long-term mortality in a population-based cohort of childhood cancer survivors. We included all children diagnosed with cancer in Switzerland (1976-2007) at age 0-14 years, who survived ≥5 years after diagnosis and followed survivors until December 31, 2012. We obtained causes of death (COD) from the Swiss mortality statistics and used data from the Swiss general population to calculate age-, calendar year- and sex-standardized mortality ratios (SMR), and absolute excess risks (AER) for different COD, by Poisson regression. We included 3'965 survivors and 49'704 person years at risk. Of these, 246 (6.2%) died, which was 11 times higher than expected (SMR 11.0). Mortality was particularly high for diseases of the respiratory (SMR 14.8) and circulatory system (SMR 12.7), and for second cancers (SMR 11.6). The pattern of cause-specific mortality differed by primary cancer diagnosis, and changed with time since diagnosis. In the first 10 years after 5-year survival, 78.9% of excess deaths were caused by recurrence of the original cancer (AER 46.1). Twenty-five years after diagnosis, only 36.5% (AER 9.1) were caused by recurrence, 21.3% by second cancers (AER 5.3) and 33.3% by circulatory diseases (AER 8.3). Our study confirms an elevated mortality in survivors of childhood cancer for at least 30 years after diagnosis with an increased proportion of deaths caused by late toxicities of the treatment. The results underline the importance of clinical follow-up continuing years after the end of treatment for childhood cancer. This article is protected by copyright. All rights reserved.
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Patterns of size inequality in crowded plant populations are often taken to be indicative of the degree of size asymmetry of competition, but recent research suggests that some of the patterns attributed to size‐asymmetric competition could be due to spatial structure. To investigate the theoretical relationships between plant density, spatial pattern, and competitive size asymmetry in determining size variation in crowded plant populations, we developed a spatially explicit, individual‐based plant competition model based on overlapping zones of influence. The zone of influence of each plant is modeled as a circle, growing in two dimensions, and is allometrically related to plant biomass. The area of the circle represents resources potentially available to the plant, and plants compete for resources in areas in which they overlap. The size asymmetry of competition is reflected in the rules for dividing up the overlapping areas. Theoretical plant populations were grown in random and in perfectly uniform spatial patterns at four densities under size‐asymmetric and size‐symmetric competition. Both spatial pattern and size asymmetry contributed to size variation, but their relative importance varied greatly over density and over time. Early in stand development, spatial pattern was more important than the symmetry of competition in determining the degree of size variation within the population, but after plants grew and competition intensified, the size asymmetry of competition became a much more important source of size variation. Size variability was slightly higher at higher densities when competition was symmetric and plants were distributed nonuniformly in space. In a uniform spatial pattern, size variation increased with density only when competition was size asymmetric. Our results suggest that when competition is size asymmetric and intense, it will be more important in generating size variation than is local variation in density. Our results and the available data are consistent with the hypothesis that high levels of size inequality commonly observed within crowded plant populations are largely due to size‐asymmetric competition, not to variation in local density.
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This paper forms part of a broader overview of biodiversity of marine life in the Gulf of Maine area (GoMA), facilitated by the GoMA Census of Marine Life program. It synthesizes current data on species diversity of zooplankton and pelagic nekton, including compilation of observed species and descriptions of seasonal, regional and cross-shelf diversity patterns. Zooplankton diversity in the GoMA is characterized by spatial differences in community composition among the neritic environment, the coastal shelf, and deep offshore waters. Copepod diversity increased with depth on the Scotian Shelf. On the coastal shelf of the western Gulf of Maine, the number of higher-level taxonomic groups declined with distance from shore, reflecting more nearshore meroplankton. Copepod diversity increased in late summer, and interdecadal diversity shifts were observed, including a period of higher diversity in the 1990s. Changes in species diversity were greatest on interannual scales, intermediate on seasonal scales, and smallest across regions, in contrast to abundance patterns, suggesting that zooplankton diversity may be a more sensitive indicator of ecosystem response to interannual climate variation than zooplankton abundance. Local factors such as bathymetry, proximity of the coast, and advection probably drive zooplankton and pelagic nekton diversity patterns in the GoMA, while ocean-basin-scale diversity patterns probably contribute to the increase in diversity at the Scotian Shelf break, a zone of mixing between the cold-temperate community of the shelf and the warm-water community offshore. Pressing research needs include establishment of a comprehensive system for observing change in zooplankton and pelagic nekton diversity, enhanced observations of "underknown'' but important functional components of the ecosystem, population and metapopulation studies, and development of analytical modeling tools to enhance understanding of diversity patterns and drivers. Ultimately, sustained observations and modeling analysis of biodiversity must be effectively communicated to managers and incorporated into ecosystem approaches for management of GoMA living marine resources.
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Physical activity has been, and remains, a significant public health issue. Thus, increasing physical activity has been identified as a top priority according to Healthy People 2010. Various behavioral variables have been associated with participation in physical activity, including the Type A behavior pattern (TABP). This study was a secondary data analysis of the Women On The Move pilot study data and examined the relationship between Type A behavior with physical activity. The study population consisted of fifty-six (56) adult minority women 40 years of age and above. The Thurstone Activity Scale was adapted for use in this study to measure TABP. Physical activity behavior was measured using an accelerometer (Computer Science Application, [CSA]) and a physical activity diary. All study questions were examined using multiple linear regression analysis. In all analyses age, household income, and level of education were entered as covariates. The results found no association with TABP and exercise or physical activity. More research involving a larger, more active study population is recommended in order to more precisely determine the relationship of TABP and physical activity. ^
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Uncertainty has been found to be a major component of the cancer experience and can dramatically affect psychosocial adaptation and outcomes of a patient's disease state (McCormick, 2002). Patients with a diagnosis of Carcinoma of Unknown Primary (CUP) may experience higher levels of uncertainty due to the unpredictability of current and future symptoms, limited treatment options and an undetermined life expectancy. To date, only one study has touched upon uncertainty and its' effects on those with CUP but no information exists concerning the effects of uncertainty regarding diagnosis and treatment on the distress level and psychosocial adjustment of this population (Parker & Lenzi, 2003). ^ Mishel's Uncertainty in Illness Theory (1984) proposes that uncertainty is preceded by three variables, one of which being Structure Providers. Structure Providers include credible authority, the degree of trust and confidence the patient has with their doctor, education and social support. It was the goal of this study to examine the relationship between uncertainty and Structure Providers to support the following hypotheses: (1) There will be a negative association between credible authority and uncertainty, (2) There will be a negative association between education level and uncertainty, and (3) There will be a negative association between social support and uncertainty. ^ This cross-sectional analysis utilized data from 219 patients following their initial consultation with their oncologist. Data included the Mishel Uncertainty in Illness Scale (MUIS) which was used to determine patients' uncertainty levels, the Medical Outcomes Study-Social Support Scale (MOSS-SSS) to assess patients, levels of social support, the Patient Satisfaction Questionnaire (PSQ-18) and the Cancer Diagnostic Interview Scale (CDIS) to measure credible authority and general demographic information to assess age, education, marital status and ethnicity. ^ In this study we found that uncertainty levels were generally higher in this sample as compared to other types of cancer populations. And while our results seemed to support most of our hypothesis, we were only able to show significant associations between two. The analyses indicated that credible authority measured by both the CDIS and the PSQ was a significant predictor of uncertainty as was social support measured by the MOSS-SS. Education has shown to have an inconsistent pattern of effect in relation to uncertainty and in the current study there was not enough data to significantly support our hypothesis. ^ The results of this study generally support Mishel's Theory of Uncertainty in Illness and highlight the importance of taking into consideration patients, psychosocial factors as well as employing proper communication practices between physicians and their patients.^
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The purpose of this study was to exam the relationship between internet use and depression among a population of individuals who have sustained spinal cord injury. This was cross-sectional survey design conducted among spinal cord injury (SCI) patients in the Model Spinal Cord Injury System. We included a total of 1,011 SCI-patients who were interviewed face-to-face or by telephone interview over approximately a three year time period (2004–2006). All data were collected through a telephone survey which included the Patient Health Questionnaire-9 (PHQ-9) to assess depression. We examined various scales of this survey, included a reduced 3-item scale (items 1, 2 and 6) to avoid the presence of somatic symptoms among SCI patients from influencing classification of depression. The frequency of internet usage was grouped as daily/weekly/monthly/non user. Covariates examined as possible confounders included demographic characteristics, occupational status, educational level, injury type, daily function of living, pain level, self-perceived health status and satisfaction with life. We observed a negative association between the frequency of internet use and the level of depression. Daily use of internet was associated with lower PHQ-9 score and depression; however this association did not reach statistical significance after for the mentioned covariates. In conclusion, the factors related to lower depression in SCI patients who use the internet are complicated. Daily internet usage was associated with lower levels of depression. The accuracy of 3-item scale needs further validation and investigation. Further study of internet usage pattern in SCI patient is recommended. ^