246 resultados para geographical patterns
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OBJECTIVES: Recombinant erythropoietin has a strong impact on aerobic power and is therefore one of the most potent doping agents in endurance sports. The anti-doping control of this synthetic hormone relies on the detection, in the urine, of its isoelectric pattern, which differs from that of the corresponding natural hormone, the latter being typically more acidic than the former. However, a small number of natural urinary patterns, referred to as "atypical patterns," are less acidic than the dominant form. Based on anecdotal evidence, the occurrence of such patterns seems to be related to particular strenuous exercises. This study aimed to demonstrate this relation using a strenuous exercise protocol. DESIGN: Seven athletes took part in a training protocol including a series of supramaximal short-duration exercises. Urine and blood samples were collected throughout the protocols. SETTINGS: World Cycling Center, Aigle, Switzerland, and research laboratories. PARTICIPANTS: Seven top-level athletes (cyclists) were involved in this study. MAIN OUTCOME MEASURES: Erythropoietin (EPO) isoelectric patterns were obtained by submitting blood and urine samples to isoelectric focusing. Additional protein dosages were performed. RESULTS: Supramaximal short-duration exercises induced the transformation of typical urinary natural EPO patterns into atypical ones. None of the obtained atypical patterns fulfilled the 3 criteria mandatory for reporting an adverse analytical finding. Serum EPO patterns were not affected by the exercises that caused the transformation of urinary patterns. CONCLUSION: An exercise-induced transient renal dysfunction is proposed as a hypothetic explanation for these observations that rely on parallel investigations of proteinuria in the same samples.
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Aims: To describe the drinking patterns and their baseline predictive factors during a 12-month period after an initial evaluation for alcohol treatment. Methods CONTROL is a single-center, prospective, observational study evaluating consecutive alcohol-dependent patients. Using a curve clustering methodology based on a polynomial regression mixture model, we identified three clusters of patients with dominant alcohol use patterns described as mostly abstainers, mostly moderate drinkers and mostly heavy drinkers. Multinomial logistic regression analysis was used to identify baseline factors (socio-demographic, alcohol dependence consequences and related factors) predictive of belonging to each drinking cluster. ResultsThe sample included 143 alcohol-dependent adults (63.6% males), mean age 44.6 ± 11.8 years. The clustering method identified 47 (32.9%) mostly abstainers, 56 (39.2%) mostly moderate drinkers and 40 (28.0%) mostly heavy drinkers. Multivariate analyses indicated that mild or severe depression at baseline predicted belonging to the mostly moderate drinkers cluster during follow-up (relative risk ratio (RRR) 2.42, CI [1.02-5.73, P = 0.045] P = 0.045), while living alone (RRR 2.78, CI [1.03-7.50], P = 0.044) and reporting more alcohol-related consequences (RRR 1.03, CI [1.01-1.05], P = 0.004) predicted belonging to the mostly heavy drinkers cluster during follow-up. Conclusion In this sample, the drinking patterns of alcohol-dependent patients were predicted by baseline factors, i.e. depression, living alone or alcohol-related consequences and findings that may inform clinicians about the likely drinking patterns of their alcohol-dependent patient over the year following the initial evaluation for alcohol treatment.
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Reductive evolution and massive pseudogene formation have shaped the 3.31-Mb genome of Mycobacterium leprae, an unculturable obligate pathogen that causes leprosy in humans. The complete genome sequence of M. leprae strain Br4923 from Brazil was obtained by conventional methods (6x coverage), and Illumina resequencing technology was used to obtain the sequences of strains Thai53 (38x coverage) and NHDP63 (46x coverage) from Thailand and the United States, respectively. Whole-genome comparisons with the previously sequenced TN strain from India revealed that the four strains share 99.995% sequence identity and differ only in 215 polymorphic sites, mainly SNPs, and by 5 pseudogenes. Sixteen interrelated SNP subtypes were defined by genotyping both extant and extinct strains of M. leprae from around the world. The 16 SNP subtypes showed a strong geographical association that reflects the migration patterns of early humans and trade routes, with the Silk Road linking Europe to China having contributed to the spread of leprosy.
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The reliable and objective assessment of chronic disease state has been and still is a very significant challenge in clinical medicine. An essential feature of human behavior related to the health status, the functional capacity, and the quality of life is the physical activity during daily life. A common way to assess physical activity is to measure the quantity of body movement. Since human activity is controlled by various factors both extrinsic and intrinsic to the body, quantitative parameters only provide a partial assessment and do not allow for a clear distinction between normal and abnormal activity. In this paper, we propose a methodology for the analysis of human activity pattern based on the definition of different physical activity time series with the appropriate analysis methods. The temporal pattern of postures, movements, and transitions between postures was quantified using fractal analysis and symbolic dynamics statistics. The derived nonlinear metrics were able to discriminate patterns of daily activity generated from healthy and chronic pain states.
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Colour pattern diversity can be due to random processes or to natural or sexual selection. Consequently, similarities in colour patterns are not always correlated with common ancestry, but may result from convergent evolution under shared selection pressures or drift. Neolamprologus brichardi and Neolamprologus pulcher have been described as two distinct species based on differences in the arrangement of two dark bars on the operculum. Our study uses DNA sequences of the mitochondrial control region to show that relatedness of haplotypes disagrees with species assignment based on head colour pattern. This suggests repeated parallel evolution of particular stripe patterns. The complete lack of shared haplotypes between populations of the same or different phenotypes reflects strong philopatric behaviour, possibly induced by the cooperative breeding mode in which offspring remain in their natal territory and serve as helpers until they disperse to nearby territories or take over a breeding position. Concordant phylogeographic patterns between N. brichardi/N. pulcher populations and other rock-dwelling cichlids suggest that the same colonization routes have been taken by sympatric species and that these routes were affected by lake level fluctuations in the past.
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Object The goal of this study was to establish whether clear patterns of initial pain freedom could be identified when treating patients with classic trigeminal neuralgia (TN) by using Gamma Knife surgery (GKS). The authors compared hypesthesia and pain recurrence rates to see if statistically significant differences could be found. Methods Between July 1992 and November 2010, 737 patients presenting with TN underwent GKS and prospective evaluation at Timone University Hospital in Marseille, France. In this study the authors analyzed the cases of 497 of these patients, who participated in follow-up longer than 1 year, did not have megadolichobasilar artery- or multiple sclerosis-related TN, and underwent GKS only once; in other words, the focus was on cases of classic TN with a single radiosurgical treatment. Radiosurgery was performed with a Leksell Gamma Knife (model B, C, or Perfexion) using both MR and CT imaging targeting. A single 4-mm isocenter was positioned in the cisternal portion of the trigeminal nerve at a median distance of 7.8 mm (range 4.5-14 mm) anterior to the emergence of the nerve. A median maximum dose of 85 Gy (range 70-90 Gy) was delivered. Using empirical methods and assisted by a chart with clear cut-off periods of pain free distribution, the authors were able to divide patients who experienced freedom from pain into 3 separate groups: patients who became pain free within the first 48 hours post-GKS; those who became pain free between 48 hours and 30 days post-GKS; and those who became pain free more than 30 days after GKS. Results The median age in the 497 patients was 68.3 years (range 28.1-93.2 years). The median follow-up period was 43.75 months (range 12-174.41 months). Four hundred fifty-four patients (91.34%) were initially pain free within a median time of 10 days (range 1-459 days) after GKS. One hundred sixty-nine patients (37.2%) became pain free within the first 48 hours (Group PF(≤ 48 hours)), 194 patients (42.8%) between posttreatment Day 3 and Day 30 (Group PF((>48 hours, ≤ 30 days))), and 91 patients (20%) after 30 days post-GKS (Group PF(>30 days)). Differences in postoperative hypesthesia were found: in Group PF(≤ 48 hours) 18 patients (13.7%) developed postoperative hypesthesia, compared with 30 patients (19%) in Group PF((>48 hours, ≤ 30 days)) and 22 patients (30.6%) in Group PF(>30 days) (p = 0.014). One hundred fifty-seven patients (34.4%) who initially became free from pain experienced a recurrence of pain with a median delay of 24 months (range 0.62-150.06 months). There were no statistically significant differences between the patient groups with respect to pain recurrence: 66 patients (39%) in Group PF(≤ 48 hours) experienced pain recurrence, compared with 71 patients (36.6%) in Group PF((>48 hours, ≤ 30 days)) and 27 patients (29.7%) in Group PF(>30 days) (p = 0.515). Conclusions A substantial number of patients (169 cases, 37.2%) became pain free within the first 48 hours. The rate of hypesthesia was higher in patients who became pain free more than 30 days after GKS, with a statistically significant difference between patient groups (p = 0.014).
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Only a very small fraction of long noncoding RNAs (lncRNAs) are well characterized. The evolutionary history of lncRNAs can provide insights into their functionality, but the absence of lncRNA annotations in non-model organisms has precluded comparative analyses. Here we present a large-scale evolutionary study of lncRNA repertoires and expression patterns, in 11 tetrapod species. We identify approximately 11,000 primate-specific lncRNAs and 2,500 highly conserved lncRNAs, including approximately 400 genes that are likely to have originated more than 300 million years ago. We find that lncRNAs, in particular ancient ones, are in general actively regulated and may function predominantly in embryonic development. Most lncRNAs evolve rapidly in terms of sequence and expression levels, but tissue specificities are often conserved. We compared expression patterns of homologous lncRNA and protein-coding families across tetrapods to reconstruct an evolutionarily conserved co-expression network. This network suggests potential functions for lncRNAs in fundamental processes such as spermatogenesis and synaptic transmission, but also in more specific mechanisms such as placenta development through microRNA production.
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ABSTRACT:: Adherence patterns and their influence on virologic outcome are well characterized for protease inhibitor (PI)- and non-nucleoside reverse transcriptase inhibitor (NNRTI)-based regimens. We aimed to determine how patterns of adherence to raltegravir influence the risk of virological failure. We conducted a prospective multicenter cohort following 81 HIV-infected antiretroviral-naive or experienced subjects receiving or starting twice-a-day raltegravir-based antiretroviral therapy. Their adherence patterns were monitored using the Medication Events Monitoring System. During follow-up (188 days, ±77), 12 (15%) of 81 subjects experienced virological failure. Longer treatment interruption [adjusted odds ratio per 24-hour increase: 2.4; 95% confidence interval: 1.2 to 6.9; P < 0.02] and average adherence (odds ratio per 5% increase: 0.68; 95% confidence interval: 0.46 to 1.00, P < 0.05) were both independently associated with virological failure controlling for prior duration of viral suppression. Timely interdose intervals and high levels of adherence to raltegravir are both necessary to control HIV replication.
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Individuals with depression process information in an overly negative or biased way (e.g., Henriques & Leitenberg, 2002) and demonstrate significant interpersonal dysfunction (e.g., Zlotnick, Kohn, Keitner, & Della Grotta, 2000). This study examined the relationship between cognitive errors (CEs) and interpersonal interactions in early psychotherapy sessions of 25 female patients with major depression. Transcripts were rated for CEs using the Cognitive Error Rating Scale (Drapeau, Perry, & Dunkley, 2008). Interpersonal patterns were assessed using the Structural Analysis of Social Behavior (Benjamin, 1974). Significant associations were found between CEs and markers of interpersonal functioning in selected contexts. The implications of these findings in bridging the gap between research and practice, enhancing treatment outcome, and improving therapist training are discussed. (PsycINFO Database Record (c) 2012 APA, all rights reserved).
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BACKGROUND: Intraabdominal adipose tissue (IAAT) is the body fat depot most strongly related to disease risk. Weight reduction is advocated for overweight people to reduce total body fat and IAAT, although little is known about the effect of weight loss on abdominal fat distribution in different races. OBJECTIVE: We compared the effects of diet-induced weight loss on changes in abdominal fat distribution in white and black women. DESIGN: We studied 23 white and 23 black women, similar in age and body composition, in the overweight state [mean body mass index (BMI; in kg/m(2)): 28.8] and the normal-weight state (mean BMI: 24.0) and 38 never-overweight control women (mean BMI: 23.4). We measured total body fat by using a 4-compartment model, trunk fat by using dual-energy X-ray absorptiometry, and cross-sectional areas of IAAT (at the fourth and fifth lumbar vertebrae) and subcutaneous abdominal adipose tissue (SAAT) by using computed tomography. RESULTS: Weight loss was similar in white and black women (13.1 and 12.6 kg, respectively), as were losses of total fat, trunk fat, and waist circumference. However, white women lost more IAAT (P < 0.001) and less SAAT (P < 0.03) than did black women. Fat patterns regressed toward those of their respective control groups. Changes in waist circumference correlated with changes in IAAT in white women (r = 0.54, P < 0.05) but not in black women (r = 0.19, NS). CONCLUSIONS: Despite comparable decreases in total and trunk fat, white women lost more IAAT and less SAAT than did black women. Waist circumference was not a suitable surrogate marker for tracking changes in the visceral fat compartment in black women.
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BACKGROUND: The advent of highly active antiretroviral therapy (HAART) in 1996 led to a decrease in the incidence of Kaposi's sarcoma (KS) and non-Hodgkin's lymphoma (NHL), but not of other cancers, among people with HIV or AIDS (PWHA). It also led to marked increases in their life expectancy. METHODS: We conducted a record-linkage study between the Swiss HIV Cohort Study and nine Swiss cantonal cancer registries. In total, 9429 PWHA provided 20,615, 17,690, and 15,410 person-years in the pre-, early-, and late-HAART periods, respectively. Standardised incidence ratios in PWHA vs the general population, as well as age-standardised, and age-specific incidence rates were computed for different periods. RESULTS: Incidence of KS and NHL decreased by several fold between the pre- and early-HAART periods, and additionally declined from the early- to the late-HAART period. Incidence of cancers of the anus, liver, non-melanomatous skin, and Hodgkin's lymphoma increased in the early- compared with the pre-HAART period, but not during the late-HAART period. The incidence of all non-AIDS-defining cancers (NADCs) combined was similar in all periods, and approximately double that in the general population. CONCLUSIONS: Increases in the incidence of selected NADCs after the introduction of HAART were largely accounted for by the ageing of PWHA.
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The presence of a calling and career development are assumed to be closely related. However, the nature of and reason for this relationship have not been thoroughly investigated. We hypothesized the existence of reciprocal effects between calling and three dimensions of career preparation and assessed the change of the presence of a calling, career planning, decidedness, and self-efficacy with three waves of a diverse sample of German university students (N = 846) over one year. Latent growth analyses revealed that the intercepts of calling showed a significant positive correlation with the intercepts of all career preparation measures. The slope of calling was positively related to those of decidedness and self-efficacy but not to planning. Cross-lagged analyses showed that calling predicted a subsequent increase in planning and self-efficacy. Planning and decidedness predicted an increase in the presence of a calling. The results suggest that calling and career preparation are related due to mutual effects but that effects differ for different career preparation dimensions.
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Community-level patterns of functional traits relate to community assembly and ecosystem functioning. By modelling the changes of different indices describing such patterns - trait means, extremes and diversity in communities - as a function of abiotic gradients, we could understand their drivers and build projections of the impact of global change on the functional components of biodiversity. We used five plant functional traits (vegetative height, specific leaf area, leaf dry matter content, leaf nitrogen content and seed mass) and non-woody vegetation plots to model several indices depicting community-level patterns of functional traits from a set of abiotic environmental variables (topographic, climatic and edaphic) over contrasting environmental conditions in a mountainous landscape. We performed a variation partitioning analysis to assess the relative importance of these variables for predicting patterns of functional traits in communities, and projected the best models under several climate change scenarios to examine future potential changes in vegetation functional properties. Not all indices of trait patterns within communities could be modelled with the same level of accuracy: the models for mean and extreme values of functional traits provided substantially better predictive accuracy than the models calibrated for diversity indices. Topographic and climatic factors were more important predictors of functional trait patterns within communities than edaphic predictors. Overall, model projections forecast an increase in mean vegetation height and in mean specific leaf area following climate warming. This trend was important at mid elevation particularly between 1000 and 2000 m asl. With this study we showed that topographic, climatic and edaphic variables can successfully model descriptors of community-level patterns of plant functional traits such as mean and extreme trait values. However, which factors determine the diversity of functional traits in plant communities remains unclear and requires more investigations.
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Due to the advances in sensor networks and remote sensing technologies, the acquisition and storage rates of meteorological and climatological data increases every day and ask for novel and efficient processing algorithms. A fundamental problem of data analysis and modeling is the spatial prediction of meteorological variables in complex orography, which serves among others to extended climatological analyses, for the assimilation of data into numerical weather prediction models, for preparing inputs to hydrological models and for real time monitoring and short-term forecasting of weather.In this thesis, a new framework for spatial estimation is proposed by taking advantage of a class of algorithms emerging from the statistical learning theory. Nonparametric kernel-based methods for nonlinear data classification, regression and target detection, known as support vector machines (SVM), are adapted for mapping of meteorological variables in complex orography.With the advent of high resolution digital elevation models, the field of spatial prediction met new horizons. In fact, by exploiting image processing tools along with physical heuristics, an incredible number of terrain features which account for the topographic conditions at multiple spatial scales can be extracted. Such features are highly relevant for the mapping of meteorological variables because they control a considerable part of the spatial variability of meteorological fields in the complex Alpine orography. For instance, patterns of orographic rainfall, wind speed and cold air pools are known to be correlated with particular terrain forms, e.g. convex/concave surfaces and upwind sides of mountain slopes.Kernel-based methods are employed to learn the nonlinear statistical dependence which links the multidimensional space of geographical and topographic explanatory variables to the variable of interest, that is the wind speed as measured at the weather stations or the occurrence of orographic rainfall patterns as extracted from sequences of radar images. Compared to low dimensional models integrating only the geographical coordinates, the proposed framework opens a way to regionalize meteorological variables which are multidimensional in nature and rarely show spatial auto-correlation in the original space making the use of classical geostatistics tangled.The challenges which are explored during the thesis are manifolds. First, the complexity of models is optimized to impose appropriate smoothness properties and reduce the impact of noisy measurements. Secondly, a multiple kernel extension of SVM is considered to select the multiscale features which explain most of the spatial variability of wind speed. Then, SVM target detection methods are implemented to describe the orographic conditions which cause persistent and stationary rainfall patterns. Finally, the optimal splitting of the data is studied to estimate realistic performances and confidence intervals characterizing the uncertainty of predictions.The resulting maps of average wind speeds find applications within renewable resources assessment and opens a route to decrease the temporal scale of analysis to meet hydrological requirements. Furthermore, the maps depicting the susceptibility to orographic rainfall enhancement can be used to improve current radar-based quantitative precipitation estimation and forecasting systems and to generate stochastic ensembles of precipitation fields conditioned upon the orography.