853 resultados para height partition clustering
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AIMS/HYPOTHESIS: The metabolic syndrome comprises a clustering of cardiovascular risk factors but the underlying mechanism is not known. Mice with targeted disruption of endothelial nitric oxide synthase (eNOS) are hypertensive and insulin resistant. We wondered, whether eNOS deficiency in mice is associated with a phenotype mimicking the human metabolic syndrome. METHODS AND RESULTS: In addition to arterial pressure and insulin sensitivity (euglycaemic hyperinsulinaemic clamp), we measured the plasma concentration of leptin, insulin, cholesterol, triglycerides, free fatty acids, fibrinogen and uric acid in 10 to 12 week old eNOS-/- and wild type mice. We also assessed glucose tolerance under basal conditions and following a metabolic stress with a high fat diet. As expected eNOS-/- mice were hypertensive and insulin resistant, as evidenced by fasting hyperinsulinaemia and a roughly 30 percent lower steady state glucose infusion rate during the clamp. eNOS-/- mice had a 1.5 to 2-fold elevation of the cholesterol, triglyceride and free fatty acid plasma concentration. Even though body weight was comparable, the leptin plasma level was 30% higher in eNOS-/- than in wild type mice. Finally, uric acid and fibrinogen were elevated in the eNOS-/- mice. Whereas under basal conditions, glucose tolerance was comparable in knock out and control mice, on a high fat diet, knock out mice became significantly more glucose intolerant than control mice. CONCLUSIONS: A single gene defect, eNOS deficiency, causes a clustering of cardiovascular risk factors in young mice. We speculate that defective nitric oxide synthesis could trigger many of the abnormalities making up the metabolic syndrome in humans.
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The article examines the structure of the collaboration networks of research groups where Slovenian and Spanish PhD students are pursuing their doctorate. The units of analysis are student-supervisor dyads. We use duocentred networks, a novel network structure appropriate for networks which are centred around a dyad. A cluster analysis reveals three typical clusters of research groups. Those which are large and belong to several institutions are labelled under a bridging social capital label. Those which are small, centred in a single institution but have high cohesion are labelled as bonding social capital. Those which are small and with low cohesion are called weak social capital groups. Academic performance of both PhD students and supervisors are highest in bridging groups and lowest in weak groups. Other variables are also found to differ according to the type of research group. At the end, some recommendations regarding academic and research policy are drawn
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The African Republic of Cape Verde consists of nine inhabited and several uninhabited volcanic islands set out in the Atlantic Ocean, about 500 km off the most westerly point of the African mainland and 1500 km south of the Canary Islands @g. 2). Most are rugged and mountainous; three (Sal, Maio, and Boavista) are flat, desert islands with sand beaches. Precipitation is meagre and very erratic; indeed Cape Verde can be seen as an island extension of the arid Sahel zone. Three species of the genus Phoenix are recorded from the Cape Verde Islands, P. akzctyli&a L., P. canariensis Chabaud and P. atlantica A. Chev. While the former two species have almost certainly been introduced by man, the latter is said to be endemic to the islands. Perhaps because the Cape Verdes are a particularly isolated set of islands or because palms are notoriously awkward to collect, little is known about the taxonomy, origins and natural history of this species. Phoenix atlantica was described by the French botanist Auguste Chevalier (1935a) following field exploration in the Cape Verdes in 1934 (Chevalier 1934: 1153). Chevalier provided limited diagnostic characters, defining the species as a clustering palm with 2-6 trunks, 5-15 m in height with dark green leaves 2-3 m in length. He considered it to be most similar in form to P. &ctyZzjkra and P. canariensis, possessing characters of both (Chevalier 1935a). Chevalier’s description indicates that Phoenix atlantica can be distinguished easily from P. canariensis by its clustering growth form (P. canariensis always has a single, stout trunk) and its shorter, straighter leaves. However, the differences between P. atlantica and P. dactylzjkra appear much more subtle. For example, while P. dacfylifera is usually observed as single-stemmed, when left undisturbed for a number of years it becomes clustering like the Cape Verde Phoenix, so this character on its own is unreliable. Further alleged distinctions include acuminate (P. atlantica) versus rounded (P. dactylzjkra) petals in the male flowers (Chevalier 1935a, b, Greuter 1967: 249, and Brochmann et al. 1997), fruit 2 cm long (P. atlantica) versus fruit more than 2.5 cm long (P. dactyl&a) (Brochmann et al.
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BACKGROUND: Little is known about engagement in multiple health behaviours in childhood cancer survivors. METHODS: Using latent class analysis, we identified health behaviour patterns in 835 adult survivors of childhood cancer (age 20-35 years) and 1670 age- and sex-matched controls from the general population. Behaviour groups were determined from replies to questions on smoking, drinking, cannabis use, sporting activities, diet, sun protection and skin examination. RESULTS: The model identified four health behaviour patterns: 'risk-avoidance', with a generally healthy behaviour; 'moderate drinking', with higher levels of sporting activities, but moderate alcohol-consumption; 'risk-taking', engaging in several risk behaviours; and 'smoking', smoking but not drinking. Similar proportions of survivors and controls fell into the 'risk-avoiding' (42% vs 44%) and the 'risk-taking' cluster (14% vs 12%), but more survivors were in the 'moderate drinking' (39% vs 28%) and fewer in the 'smoking' cluster (5% vs 16%). Determinants of health behaviour clusters were gender, migration background, income and therapy. CONCLUSION: A comparable proportion of childhood cancer survivors as in the general population engage in multiple health-compromising behaviours. Because of increased vulnerability of survivors, multiple risk behaviours should be addressed in targeted health interventions.
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This paper presents new evidence on the evolution of adult height in 10 Europeancountries for cohorts born between 1950 and 1980 using the European CommunityHousehold Panel (ECHP), which collects height data from Austria, Belgium, Denmark,Finland, Greece, Ireland, Italy, Portugal, Spain and Sweden. Our findings show agradual increase in adult height across all countries. However, countries from SouthernEurope (Greece, Italy, Portugal, Spain) experienced higher gains in stature than thoselocated in Northern Europe (Austria, Belgium, Denmark, Finland, Ireland and Sweden).
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The n-octanol/water partition coefficient (log Po/w) is a key physicochemical parameter for drug discovery, design, and development. Here, we present a physics-based approach that shows a strong linear correlation between the computed solvation free energy in implicit solvents and the experimental log Po/w on a cleansed data set of more than 17,500 molecules. After internal validation by five-fold cross-validation and data randomization, the predictive power of the most interesting multiple linear model, based on two GB/SA parameters solely, was tested on two different external sets of molecules. On the Martel druglike test set, the predictive power of the best model (N = 706, r = 0.64, MAE = 1.18, and RMSE = 1.40) is similar to six well-established empirical methods. On the 17-drug test set, our model outperformed all compared empirical methodologies (N = 17, r = 0.94, MAE = 0.38, and RMSE = 0.52). The physical basis of our original GB/SA approach together with its predictive capacity, computational efficiency (1 to 2 s per molecule), and tridimensional molecular graphics capability lay the foundations for a promising predictor, the implicit log P method (iLOGP), to complement the portfolio of drug design tools developed and provided by the SIB Swiss Institute of Bioinformatics.
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AIM: Inulin clearance (Cin) is the gold standard for assessing glomerular filtration rate (GFR). Other methods are based on the plasma creatinine concentration (Pcreat), creatinine clearance (Ccreat), the Haycock-Schwartz formula and the plasma concentration of cystatin C (PcysC), a 13 kDa basic protein produced at a constant rate by all nucleated cells. The present prospective study was thus designed to evaluate the reliability of PcysC as a marker of GFR in comparison with that of Pcreat, Ccreat and the Haycock-Schwartz formula, using Cin as the gold standard. METHODS: Ninety-nine children (51 m/48 f), with a median age of 8.3 y (1.0-17.9) were studied. Using a cut-off for Cin of 100 ml/min per 1.73 m2, 54 children (54.5%) had impaired GFR. Those with normal GFR were comparable for age, height, weight and body mass index. RESULTS: Logistic regression, ROC analysis and linear regression all showed that Ccreat was the best parameter to discriminate between impaired and normal GFR, followed by the Haycock-Schwartz formula, PcysC, and finally Pcreat, each one being significantly more predictive than the next. CONCLUSION: GFR is better assessed by the Haycock-Schwartz formula than by PcysC or Pcreat alone. It is therefore concluded that when urine collection is not possible, simply measuring the child's Pcreat and height is the best, easiest and cheapest way to assess GFR.
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Abstract Background. In children, waist-for-height ratio (WHtR) has been proposed to identify subjects at higher risk of cardiovascular diseases. The utility of WHtR to identify children with elevated blood pressure (BP) is unclear. Design. Cross-sectional population-based study of schoolchildren. Methods. Weight, height, waist circumference and BP were measured in all sixth-grade schoolchildren of the canton de Vaud (Switzerland) in 2005/06. WHtR was computed as waist [cm]/height [cm]. Elevated BP was defined according to sex-, age- and height-specific US reference data. The area under the receiver operating characteristic curve (AUC) statistic was computed to compare the ability of body mass index (BMI) z-score and WHtR, alone or in combination, to identify children with elevated BP. Results. 5207 children participated (76% response) [2621 boys, 2586 girls; mean (± SD) age, 12.3 ± 0.5 years; range: 10.1-14.9]. The prevalence of elevated BP was 11%. Mean WHtR was 0.44 ± 0.05 (range: 0.29- 0.77) and 11% had high WHtR (> 0.5). BMI z-score and WHtR were strongly correlated (Spearman correlation coefficient r = 0.76). Both indices were positively associated with elevated BP. AUCs for elevated BP was relatively low for BMI z-score (0.62) or for WHtR (0.62), and was not substantially improved when both indices were considered together (0.63). Conclusions. The ability of BMI z-score or WHtR to identify children aged 10-14 with elevated BP was weak. Adding WHtR did not confer additional discriminative power to BMI alone. These findings do not support the measurement of WHtR in addition to BMI to identify children with elevated BP.
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Average physical stature has increased dramatically during the 20th century in many populations across the world with few exceptions. It remains unclear if social inequalities in height persist despite improvements in living standards in the welfare economies of Western Europe. We examined trends in the association between height and socioeconomic indicators in adults over three decades in France. The data were drawn from the French Decennial Health Surveys: a multistage, stratified, random survey of households, representative of the population, conducted in 1970, 1980, 1991, and 2003. We categorised age into 10-year bands, 25-34, 35-44, 45-54 and 55-64 years. Education and income were the two socioeconomic measures used. The slope index of inequality (SII) was used as a summary index of absolute social inequalities in height. The results show that average height increased over this period; men and women aged 25-34 years were 171.9 and 161.2 cm tall in 1970 and 177.0 and 164.0 cm in 2003, respectively. However, education-related inequalities in height remained unchanged over this period and in men were 4.48 cm (1970), 4.71 cm (1980), 5.58 cm (1991) and 4.69 cm (2003), the corresponding figures in women were 2.41, 2.37, 3.14 and 2.96 cm. Income-related inequalities in height were smaller and much attenuated after adjustment for education. These results suggest that in France, social inequalities in adult height in absolute terms have remained unchanged across the three decades under examination.
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As adult height is a well-established retrospective measure of health and standard of living, it is important to understand the factors that determine it. Among them, the influence of socio-environmental factors has been subjected to empirical scrutiny. This paper explores the influence of generational (or environmental) effects and individual and gender-specific heterogeneity on adult height. Our data set is from contemporary Spain, a country governed by an authoritarian regime between 1939 and 1977. First, we use normal position and quantile regression analysis to identify the determinants of self-reported adult height and to measure the influence of individual heterogeneity. Second, we use a Blinder-Oaxaca decomposition approach to explain the `gender height gap¿ and its distribution, so as to measure the influence on this gap of individual heterogeneity. Our findings suggest a significant increase in adult height in the generations that benefited from the country¿s economic liberalization in the 1950s, and especially those brought up after the transition to democracy in the 1970s. In contrast, distributional effects on height suggest that only in recent generations has ¿height increased more among the tallest¿. Although the mean gender height gap is 11 cm, generational effects and other controls such as individual capabilities explain on average roughly 5% of this difference, a figure that rises to 10% in the lowest 10% quantile.
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The coverage and volume of geo-referenced datasets are extensive and incessantly¦growing. The systematic capture of geo-referenced information generates large volumes¦of spatio-temporal data to be analyzed. Clustering and visualization play a key¦role in the exploratory data analysis and the extraction of knowledge embedded in¦these data. However, new challenges in visualization and clustering are posed when¦dealing with the special characteristics of this data. For instance, its complex structures,¦large quantity of samples, variables involved in a temporal context, high dimensionality¦and large variability in cluster shapes.¦The central aim of my thesis is to propose new algorithms and methodologies for¦clustering and visualization, in order to assist the knowledge extraction from spatiotemporal¦geo-referenced data, thus improving making decision processes.¦I present two original algorithms, one for clustering: the Fuzzy Growing Hierarchical¦Self-Organizing Networks (FGHSON), and the second for exploratory visual data analysis:¦the Tree-structured Self-organizing Maps Component Planes. In addition, I present¦methodologies that combined with FGHSON and the Tree-structured SOM Component¦Planes allow the integration of space and time seamlessly and simultaneously in¦order to extract knowledge embedded in a temporal context.¦The originality of the FGHSON lies in its capability to reflect the underlying structure¦of a dataset in a hierarchical fuzzy way. A hierarchical fuzzy representation of¦clusters is crucial when data include complex structures with large variability of cluster¦shapes, variances, densities and number of clusters. The most important characteristics¦of the FGHSON include: (1) It does not require an a-priori setup of the number¦of clusters. (2) The algorithm executes several self-organizing processes in parallel.¦Hence, when dealing with large datasets the processes can be distributed reducing the¦computational cost. (3) Only three parameters are necessary to set up the algorithm.¦In the case of the Tree-structured SOM Component Planes, the novelty of this algorithm¦lies in its ability to create a structure that allows the visual exploratory data analysis¦of large high-dimensional datasets. This algorithm creates a hierarchical structure¦of Self-Organizing Map Component Planes, arranging similar variables' projections in¦the same branches of the tree. Hence, similarities on variables' behavior can be easily¦detected (e.g. local correlations, maximal and minimal values and outliers).¦Both FGHSON and the Tree-structured SOM Component Planes were applied in¦several agroecological problems proving to be very efficient in the exploratory analysis¦and clustering of spatio-temporal datasets.¦In this thesis I also tested three soft competitive learning algorithms. Two of them¦well-known non supervised soft competitive algorithms, namely the Self-Organizing¦Maps (SOMs) and the Growing Hierarchical Self-Organizing Maps (GHSOMs); and the¦third was our original contribution, the FGHSON. Although the algorithms presented¦here have been used in several areas, to my knowledge there is not any work applying¦and comparing the performance of those techniques when dealing with spatiotemporal¦geospatial data, as it is presented in this thesis.¦I propose original methodologies to explore spatio-temporal geo-referenced datasets¦through time. Our approach uses time windows to capture temporal similarities and¦variations by using the FGHSON clustering algorithm. The developed methodologies¦are used in two case studies. In the first, the objective was to find similar agroecozones¦through time and in the second one it was to find similar environmental patterns¦shifted in time.¦Several results presented in this thesis have led to new contributions to agroecological¦knowledge, for instance, in sugar cane, and blackberry production.¦Finally, in the framework of this thesis we developed several software tools: (1)¦a Matlab toolbox that implements the FGHSON algorithm, and (2) a program called¦BIS (Bio-inspired Identification of Similar agroecozones) an interactive graphical user¦interface tool which integrates the FGHSON algorithm with Google Earth in order to¦show zones with similar agroecological characteristics.
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Aim: When planning SIRT using 90Y microspheres, the partition model is used to refine the activity calculated by the body surface area (BSA) method to potentially improve the safety and efficacy of treatment. For this partition model dosimetry, accurate determination of mean tumor-to-normal liver ratio (TNR) is critical since it directly impacts absorbed dose estimates. This work aimed at developing and assessing a reliable methodology for the calculation of 99mTc-MAA SPECT/CT-derived TNR ratios based on phantom studies. Materials and methods: IQ NEMA (6 hot spheres) and Kyoto liver phantoms with different hot/background activity concentration ratios were imaged on a SPECT/CT (GE Infinia Hawkeye 4). For each reconstruction with the IQ phantom, TNR quantification was assessed in terms of relative recovery coefficients (RC) and image noise was evaluated in terms of coefficient of variation (COV) in the filled background. RCs were compared using OSEM with Hann, Butterworth and Gaussian filters, as well as FBP reconstruction algorithms. Regarding OSEM, RCs were assessed by varying different parameters independently, such as the number of iterations (i) and subsets (s) and the cut-off frequency of the filter (fc). The influence of the attenuation and diffusion corrections was also investigated. Furthermore, both 2D-ROIs and 3D-VOIs contouring were compared. For this purpose, dedicated Matlab© routines were developed in-house for automatic 2D-ROI/3D-VOI determination to reduce intra-user and intra-slice variability. Best reconstruction parameters and RCs obtained with the IQ phantom were used to recover corrected TNR in case of the Kyoto phantom for arbitrary hot-lesion size. In addition, we computed TNR volume histograms to better assess uptake heterogeneityResults: The highest RCs were obtained with OSEM (i=2, s=10) coupled with the Butterworth filter (fc=0.8). Indeed, we observed a global 20% RC improvement over other OSEM settings and a 50% increase as compared to the best FBP reconstruction. In any case, both attenuation and diffusion corrections must be applied, thus improving RC while preserving good image noise (COV<10%). Both 2D-ROI and 3D-VOI analysis lead to similar results. Nevertheless, we recommend using 3D-VOI since tumor uptake regions are intrinsically 3D. RC-corrected TNR values lie within 17% around the true value, substantially improving the evaluation of small volume (<15 mL) regions. Conclusions: This study reports the multi-parameter optimization of 99mTc MAA SPECT/CT images reconstruction in planning 90Y dosimetry for SIRT. In phantoms, accurate quantification of TNR was obtained using OSEM coupled with Butterworth and RC correction.
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Birth weight within the normal range is associated with a variety of adult-onset diseases, but the mechanisms behind these associations are poorly understood. Previous genome-wide association studies of birth weight identified a variant in the ADCY5 gene associated both with birth weight and type 2 diabetes and a second variant, near CCNL1, with no obvious link to adult traits. In an expanded genome-wide association meta-analysis and follow-up study of birth weight (of up to 69,308 individuals of European descent from 43 studies), we have now extended the number of loci associated at genome-wide significance to 7, accounting for a similar proportion of variance as maternal smoking. Five of the loci are known to be associated with other phenotypes: ADCY5 and CDKAL1 with type 2 diabetes, ADRB1 with adult blood pressure and HMGA2 and LCORL with adult height. Our findings highlight genetic links between fetal growth and postnatal growth and metabolism.
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A recurring task in the analysis of mass genome annotation data from high-throughput technologies is the identification of peaks or clusters in a noisy signal profile. Examples of such applications are the definition of promoters on the basis of transcription start site profiles, the mapping of transcription factor binding sites based on ChIP-chip data and the identification of quantitative trait loci (QTL) from whole genome SNP profiles. Input to such an analysis is a set of genome coordinates associated with counts or intensities. The output consists of a discrete number of peaks with respective volumes, extensions and center positions. We have developed for this purpose a flexible one-dimensional clustering tool, called MADAP, which we make available as a web server and as standalone program. A set of parameters enables the user to customize the procedure to a specific problem. The web server, which returns results in textual and graphical form, is useful for small to medium-scale applications, as well as for evaluation and parameter tuning in view of large-scale applications, requiring a local installation. The program written in C++ can be freely downloaded from ftp://ftp.epd.unil.ch/pub/software/unix/madap. The MADAP web server can be accessed at http://www.isrec.isb-sib.ch/madap/.