988 resultados para ESTABLISHED POPULATIONS
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Background In an agreement assay, it is of interest to evaluate the degree of agreement between the different methods (devices, instruments or observers) used to measure the same characteristic. We propose in this study a technical simplification for inference about the total deviation index (TDI) estimate to assess agreement between two devices of normally-distributed measurements and describe its utility to evaluate inter- and intra-rater agreement if more than one reading per subject is available for each device. Methods We propose to estimate the TDI by constructing a probability interval of the difference in paired measurements between devices, and thereafter, we derive a tolerance interval (TI) procedure as a natural way to make inferences about probability limit estimates. We also describe how the proposed method can be used to compute bounds of the coverage probability. Results The approach is illustrated in a real case example where the agreement between two instruments, a handle mercury sphygmomanometer device and an OMRON 711 automatic device, is assessed in a sample of 384 subjects where measures of systolic blood pressure were taken twice by each device. A simulation study procedure is implemented to evaluate and compare the accuracy of the approach to two already established methods, showing that the TI approximation produces accurate empirical confidence levels which are reasonably close to the nominal confidence level. Conclusions The method proposed is straightforward since the TDI estimate is derived directly from a probability interval of a normally-distributed variable in its original scale, without further transformations. Thereafter, a natural way of making inferences about this estimate is to derive the appropriate TI. Constructions of TI based on normal populations are implemented in most standard statistical packages, thus making it simpler for any practitioner to implement our proposal to assess agreement.
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UNLABELLED: Honeybees harbor well-defined bacterial communities in their guts. The major members of these communities appear to benefit the host, but little is known about how they interact with the host and specifically how they interface with the host immune system. In the pylorus, a short region between the midgut and hindgut, honeybees frequently exhibit scab-like structures on the epithelial gut surface. These structures are reminiscent of a melanization response of the insect immune system. Despite the wide distribution of this phenotype in honeybee populations, its cause has remained elusive. Here, we show that the presence of a common member of the bee gut microbiota, the gammaproteobacterium Frischella perrara, correlates with the appearance of the scab phenotype. Bacterial colonization precedes scab formation, and F. perrara specifically localizes to the melanized regions of the host epithelium. Under controlled laboratory conditions, we demonstrate that exposure of microbiota-free bees to F. perrara but not to other bacteria results in scab formation. This shows that F. perrara can become established in a spatially restricted niche in the gut and triggers a morphological change of the epithelial surface, potentially due to a host immune response. As an intermittent colonizer, this bacterium holds promise for addressing questions of community invasion in a simple yet relevant model system. Moreover, our results show that gut symbionts of bees engage in differential host interactions that are likely to affect gut homeostasis. Future studies should focus on how these different gut bacteria impact honeybee health. IMPORTANCE: As pollinators, honeybees are key species for agricultural and natural ecosystems. Their guts harbor simple communities composed of characteristic bacterial species. Because of these features, bees are ideal systems for studying fundamental aspects of gut microbiota-host interactions. However, little is known about how these bacteria interact with their host. Here, we show that a common member of the bee gut microbiota causes the formation of a scab-like structure on the gut epithelium of its host. This phenotype was first described in 1946, but since then it has not been much further characterized, despite being found in bee populations worldwide. The scab phenotype is reminiscent of melanization, a conserved innate immune response of insects. Our results show that high abundance of one member of the bee gut microbiota triggers this specific phenotype, suggesting that the gut microbiota composition can affect the immune status of this key pollinator species.
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Reaching a consensus in terms of interchangeability and utility (i.e., disease detection/monitoring) of a medical device is the eventual aim of repeatability and agreement studies. The aim of the tolerance and relative utility indices described in this report is to provide a methodology to compare change in clinical measurement noise between different populations (repeatability) or measurement methods (agreement), so as to highlight problematic areas. No longitudinal data are required to calculate these indices. Both indices establish a metric of least to most effected across all parameters to facilitate comparison. If validated, these indices may prove useful tools when combining reports and forming the consensus required in the validation process for software updates and new medical devices.
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Background: TILLING (Targeting Induced Local Lesions IN Genomes) is a reverse genetic method that combines chemical mutagenesis with high-throughput genome-wide screening for point mutation detection in genes of interest. However, this mutation discovery approach faces a particular problem which is how to obtain a mutant population with a sufficiently high mutation density. Furthermore, plant mutagenesis protocols require two successive generations (M1, M2) for mutation fixation to occur before the analysis of the genotype can begin. Results: Here, we describe a new TILLING approach for rice based on ethyl methanesulfonate (EMS) mutagenesis of mature seed-derived calli and direct screening of in vitro regenerated plants. A high mutagenesis rate was obtained (i.e. one mutation in every 451 Kb) when plants were screened for two senescence-related genes. Screening was carried out in 2400 individuals from a mutant population of 6912. Seven sense change mutations out of 15 point mutations were identified. Conclusions: This new strategy represents a significant advantage in terms of time-savings (i.e. more than eight months), greenhouse space and work during the generation of mutant plant populations. Furthermore, this effective chemical mutagenesis protocol ensures high mutagenesis rates thereby saving in waste removal costs and the total amount of mutagen needed thanks to the mutagenesis volume reduction.
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Homozygosity has long been associated with rare, often devastating, Mendelian disorders, and Darwin was one of the first to recognize that inbreeding reduces evolutionary fitness. However, the effect of the more distant parental relatedness that is common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power. Here we use runs of homozygosity to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts, and find statistically significant associations between summed runs of homozygosity and four complex traits: height, forced expiratory lung volume in one second, general cognitive ability and educational attainment (P < 1 × 10(-300), 2.1 × 10(-6), 2.5 × 10(-10) and 1.8 × 10(-10), respectively). In each case, increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months' less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing evidence that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been.
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Prof. Dr. Antonio Prevosti was born on the 15th of February, 1919, at Barcelona where he grew up and lived with his wife Maria Monclús and his family until his death. Between the years 1939 and 1942 he registered at the University of Barcelona and finished his studies there with the"University Degree in Natural Science" obtaining the extraordinary award of his promotion. Immediately afterwards he started his research about the growth rate of Barcelona school children from two very different social groups at the Anthropology Laboratory of the University of Barcelona. The obtained results were published in his Doctoral Thesis (1948). Further investigations on quantitative traits in human populations improved his knowledge of statistical analyses and provided the basis for a scholarship from the Italian Ministry of Foreign Affairs to work at the Institute of Statistical and Demographical Sciences in Rome directed by Prof. C. Gini.
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Many models proposed to study the evolution of collective action rely on a formalism that represents social interactions as n-player games between individuals adopting discrete actions such as cooperate and defect. Despite the importance of spatial structure in biological collective action, the analysis of n-player games games in spatially structured populations has so far proved elusive. We address this problem by considering mixed strategies and by integrating discrete-action n-player games into the direct fitness approach of social evolution theory. This allows to conveniently identify convergence stable strategies and to capture the effect of population structure by a single structure coefficient, namely, the pairwise (scaled) relatedness among interacting individuals. As an application, we use our mathematical framework to investigate collective action problems associated with the provision of three different kinds of collective goods, paradigmatic of a vast array of helping traits in nature: "public goods" (both providers and shirkers can use the good, e.g., alarm calls), "club goods" (only providers can use the good, e.g., participation in collective hunting), and "charity goods" (only shirkers can use the good, e.g., altruistic sacrifice). We show that relatedness promotes the evolution of collective action in different ways depending on the kind of collective good and its economies of scale. Our findings highlight the importance of explicitly accounting for relatedness, the kind of collective good, and the economies of scale in theoretical and empirical studies of the evolution of collective action.
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Background: Differences in the distribution of genotypes between individuals of the same ethnicity are an important confounder factor commonly undervalued in typical association studies conducted in radiogenomics. Objective: To evaluate the genotypic distribution of SNPs in a wide set of Spanish prostate cancer patients for determine the homogeneity of the population and to disclose potential bias. Design, Setting, and Participants: A total of 601 prostate cancer patients from Andalusia, Basque Country, Canary and Catalonia were genotyped for 10 SNPs located in 6 different genes associated to DNA repair: XRCC1 (rs25487, rs25489, rs1799782), ERCC2 (rs13181), ERCC1 (rs11615), LIG4 (rs1805388, rs1805386), ATM (rs17503908, rs1800057) and P53 (rs1042522). The SNP genotyping was made in a Biotrove OpenArrayH NT Cycler. Outcome Measurements and Statistical Analysis: Comparisons of genotypic and allelic frequencies among populations, as well as haplotype analyses were determined using the web-based environment SNPator. Principal component analysis was made using the SnpMatrix and XSnpMatrix classes and methods implemented as an R package. Non-supervised hierarchical cluster of SNP was made using MultiExperiment Viewer. Results and Limitations: We observed that genotype distribution of 4 out 10 SNPs was statistically different among the studied populations, showing the greatest differences between Andalusia and Catalonia. These observations were confirmed in cluster analysis, principal component analysis and in the differential distribution of haplotypes among the populations. Because tumor characteristics have not been taken into account, it is possible that some polymorphisms may influence tumor characteristics in the same way that it may pose a risk factor for other disease characteristics. Conclusion: Differences in distribution of genotypes within different populations of the same ethnicity could be an important confounding factor responsible for the lack of validation of SNPs associated with radiation-induced toxicity, especially when extensive meta-analysis with subjects from different countries are carried out.
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BACKGROUND: Globally, Africans and African Americans experience a disproportionate burden of type 2 diabetes, compared to other race and ethnic groups. The aim of the study was to examine the association of plasma glucose with indices of glucose metabolism in young adults of African origin from 5 different countries. METHODS: We identified participants from the Modeling the Epidemiologic Transition Study, an international study of weight change and cardiovascular disease (CVD) risk in five populations of African origin: USA (US), Jamaica, Ghana, South Africa, and Seychelles. For the current study, we included 667 participants (34.8 ± 6.3 years), with measures of plasma glucose, insulin, leptin, and adiponectin, as well as moderate and vigorous physical activity (MVPA, minutes/day [min/day]), daily sedentary time (min/day), anthropometrics, and body composition. RESULTS: Among the 282 men, body mass index (BMI) ranged from 22.1 to 29.6 kg/m(2) in men and from 25.8 to 34.8 kg/m(2) in 385 women. MVPA ranged from 26.2 to 47.1 min/day in men, and from 14.3 to 27.3 min/day in women and correlated with adiposity (BMI, waist size, and % body fat) only among US males after controlling for age. Plasma glucose ranged from 4.6 ± 0.8 mmol/L in the South African men to 5.8 mmol/L US men, while the overall prevalence for diabetes was very low, except in the US men and women (6.7 and 12 %, respectively). Using multivariate linear regression, glucose was associated with BMI, age, sex, smoking hypertension, daily sedentary time but not daily MVPA. CONCLUSION: Obesity, metabolic risk, and other potential determinants vary significantly between populations at differing stages of the epidemiologic transition, requiring tailored public health policies to address local population characteristics.
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An important aspect of immune monitoring for vaccine development, clinical trials, and research is the detection, measurement, and comparison of antigen-specific T-cells from subject samples under different conditions. Antigen-specific T-cells compose a very small fraction of total T-cells. Developments in cytometry technology over the past five years have enabled the measurement of single-cells in a multivariate and high-throughput manner. This growth in both dimensionality and quantity of data continues to pose a challenge for effective identification and visualization of rare cell subsets, such as antigen-specific T-cells. Dimension reduction and feature extraction play pivotal role in both identifying and visualizing cell populations of interest in large, multi-dimensional cytometry datasets. However, the automated identification and visualization of rare, high-dimensional cell subsets remains challenging. Here we demonstrate how a systematic and integrated approach combining targeted feature extraction with dimension reduction can be used to identify and visualize biological differences in rare, antigen-specific cell populations. By using OpenCyto to perform semi-automated gating and features extraction of flow cytometry data, followed by dimensionality reduction with t-SNE we are able to identify polyfunctional subpopulations of antigen-specific T-cells and visualize treatment-specific differences between them.
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BACKGROUND: Biomarkers are a promising tool for the management of patients with atherosclerosis, but their variation is largely unknown. We assessed within-subject and between-subject biological variation of biomarkers in peripheral artery disease (PAD) patients and healthy controls, and defined which biomarkers have a favorable variation profile for future studies. METHODS: Prospective, parallel-group cohort study, including 62 patients with stable PAD (79% men, 65±7years) and 18 healthy control subjects (44% men, 57±7years). Blood samples were taken at baseline, and after 3-, 6-, and 12-months. We calculated within-subject (CVI) and between-subject (CVG) coefficients of variation and intra-class correlation coefficient (ICC). RESULTS: Mean levels of D-dimer, hs-CRP, IL-6, IL-8, MMP-9, MMP-3, S100A8/A9, PAI-1, sICAM-1, and sP-selectin levels were higher in PAD patients than in healthy controls (P≤.05 for all). CVI and CVG of the different biomarkers varied considerably in both groups. An ICC≥0.5 (indicating moderate-to-good reliability) was found for hs-CRP, D-Dimer, E-selectin, IL-10, MCP-1, MMP-3, oxLDL, sICAM-1 and sP-selectin in both groups, for sVCAM in healthy controls and for MMP-9, PAI-1 and sCD40L in PAD patients. CONCLUSIONS: Single biomarker measurements are of limited utility due to large within-subject variation, both in PAD patients and healthy subjects. D-dimer, hs-CRP, MMP-9, MMP-3, PAI-1, sP-selectin and sICAM-1 are biomarkers with both higher mean levels in PAD patients and a favorable variation profile making them most suitable for future studies.
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The pumpkinseed Lepomis gibbosus, an omnivorous, nest guarding North American sunfish, was introduced into European waters about 100 years ago. To assess growth performance following introduction, we reviewed the available data for North American and European populations of pumpkinseed and compared the back-calculated age-specific growth for juveniles (standard length, SL, at age two) and adults (age two to five increment) as well as adult body size (SL at age five), von Bertalanffy growth model parameters and the index of growth (in length) performance (φ′). For continental comparisons of growth trajectory, mean growth curves for North American and Europe were calculated with the von Bertalanffy model using pooled data sets for each continent. Juvenile growth rate did not differ between European and North American pumpkinseed, but mean adult body size and adult growth rate were both significantly greater in North American than European populations. Adult body size decreased with increasing latitude (ANOVA) in North American populations, but this was not observed with adult growth rate. In contrast, adult body size tended to increase with latitude in European populations. Adult body size correlated significantly with φ′. The von Bertalanffy model described the overall growth patterns of North American and European populations reasonably well, but on the individual population level, length asymptotes were unrealistic (estimates that were > 20 % of the mean back-calculated size for the oldest age class) for a third of European populations and 80% of the North American populations. In contrast to North American pumpkinseed populations, somatic growth in European populations appears to be compromised by limited, but adequate, food resources, probably due to strong intraspecific interactions. This appears to be especially acute in adults, having potential ramifications for life span and reproductive allocation