249 resultados para Code bias variation
Resumo:
This study represents the most extensive analysis of batch-to-batch variations in spray paint samples to date. The survey was performed as a collaborative project of the ENFSI (European Network of Forensic Science Institutes) Paint and Glass Working Group (EPG) and involved 11 laboratories. Several studies have already shown that paint samples of similar color but from different manufacturers can usually be differentiated using an appropriate analytical sequence. The discrimination of paints from the same manufacturer and color (batch-to-batch variations) is of great interest and these data are seldom found in the literature. This survey concerns the analysis of batches from different color groups (white, papaya (special shade of orange), red and black) with a wide range of analytical techniques and leads to the following conclusions. Colored batch samples are more likely to be differentiated since their pigment composition is more complex (pigment mixtures, added pigments) and therefore subject to variations. These variations may occur during the paint production but may also occur when checking the paint shade in quality control processes. For these samples, techniques aimed at color/pigment(s) characterization (optical microscopy, microspectrophotometry (MSP), Raman spectroscopy) provide better discrimination than techniques aimed at the organic (binder) or inorganic composition (fourier transform infrared spectroscopy (FTIR) or elemental analysis (SEM - scanning electron microscopy and XRF - X-ray fluorescence)). White samples contain mainly titanium dioxide as a pigment and the main differentiation is based on the binder composition (Csingle bondH stretches) detected either by FTIR or Raman. The inorganic composition (elemental analysis) also provides some discrimination. Black samples contain mainly carbon black as a pigment and are problematic with most of the spectroscopic techniques. In this case, pyrolysis-GC/MS represents the best technique to detect differences. Globally, Py-GC/MS may show a high potential of discrimination on all samples but the results are highly dependent on the specific instrumental conditions used. Finally, the discrimination of samples when data was interpreted visually as compared to statistically using principal component analysis (PCA) yielded very similar results. PCA increases sensitivity and could perform better on specific samples, but one first has to ensure that all non-informative variation (baseline deviation) is eliminated by applying correct pre-treatments. Statistical treatments can be used on a large data set and, when combined with an expert's opinion, will provide more objective criteria for decision making.
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The neuro-peptide hormone oxytocin regulates several reproductive mechanisms in mammals, such as uterine contractions during parturition and milk ejection in the lactating mammary gland. Oxytocin may also influence behavior and behavioral strategies, e.g. pair bonding, social recognition, maternal behavior, trust building, or anxiety. Teasing oestrous mares by a stallion provokes the release of oxytocin. We therefore tested whether such elevated oxytocin levels reveal possible mate preferences as determined in typical preference tests.
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PURPOSE: The objective was to explore whether a satellite-based navigation system, global positioning system used in differential mode (DGPS), could accurately assess the speed of running in humans. METHODS: A subject was equipped with a portable GPS receptor coupled to a receiver for differential corrections, while running outdoors on a straight asphalt road at 27 different speeds. Actual speed (reference method) was assessed by chronometry. RESULTS: The accuracy of speed prediction had a standard deviation (SD) of 0.08 km x h(-1) for walking, 0.11 km x h(-1) for running, yielding a coefficient of variation (SD/mean) of 1.38% and 0.82%, respectively. There was a highly significant linear relationship between actual and DGPS speed assessment (r2 = 0.999) with little bias in the prediction equation, because the slope of the regression line was close to unity (0.997). CONCLUSION: the DGPS technique appears to be a valid and inconspicuous tool for "on line" monitoring of the speed of displacement of individuals located on any field on earth, for prolonged periods of time and unlimited distance, but only in specific environmental conditions ("open sky"). Furthermore, the accuracy of speed assessment using the differential GPS mode was improved by a factor of 10 as compared to non-differential GPS.
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The analysis of conservation between the human and mouse genomes resulted in the identification of a large number of conserved nongenic sequences (CNGs). The functional significance of this nongenic conservation remains unknown, however. The availability of the sequence of a third mammalian genome, the dog, allows for a large-scale analysis of evolutionary attributes of CNGs in mammals. We have aligned 1638 previously identified CNGs and 976 conserved exons (CODs) from human chromosome 21 (Hsa21) with their orthologous sequences in mouse and dog. Attributes of selective constraint, such as sequence conservation, clustering, and direction of substitutions were compared between CNGs and CODs, showing a clear distinction between the two classes. We subsequently performed a chromosome-wide analysis of CNGs by correlating selective constraint metrics with their position on the chromosome and relative to their distance from genes. We found that CNGs appear to be randomly arranged in intergenic regions, with no bias to be closer or farther from genes. Moreover, conservation and clustering of substitutions of CNGs appear to be completely independent of their distance from genes. These results suggest that the majority of CNGs are not typical of previously described regulatory elements in terms of their location. We propose models for a global role of CNGs in genome function and regulation, through long-distance cis or trans chromosomal interactions.
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BACKGROUND: Non-response is a major concern among substance use epidemiologists. When differences exist between respondents and non-respondents, survey estimates may be biased. Therefore, researchers have developed time-consuming strategies to convert non-respondents to respondents. The present study examines whether late respondents (converted former non-participants) differ from early respondents, non-consenters or silent refusers (consent givers but non-participants) in a cohort study, and whether non-response bias can be reduced by converting former non-respondents. METHODS: 6099 French- and 5720 German-speaking Swiss 20-year-old males (more than 94% of the source population) completed a short questionnaire on substance use outcomes and socio-demographics, independent of any further participation in a cohort study. Early respondents were those participating in the cohort study after standard recruitment procedures. Late respondents were non-respondents that were converted through individual encouraging telephone contact. Early respondents, non-consenters and silent refusers were compared to late respondents using logistic regressions. Relative non-response biases for early respondents only, for respondents only (early and late) and for consenters (respondents and silent refusers) were also computed. RESULTS: Late respondents showed generally higher patterns of substance use than did early respondents, but lower patterns than did non-consenters and silent refusers. Converting initial non-respondents to respondents reduced the non-response bias, which might be further reduced if silent refusers were converted to respondents. CONCLUSION: Efforts to convert refusers are effective in reducing non-response bias. However, converted late respondents cannot be seen as proxies of non-respondents, and are at best only indicative of existing response bias due to persistent non-respondents.
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Large, rare copy number variants (CNVs) have been implicated in a variety of psychiatric disorders, but the role of CNVs in recurrent depression is unclear. We performed a genome-wide analysis of large, rare CNVs in 3106 cases of recurrent depression, 459 controls screened for lifetime-absence of psychiatric disorder and 5619 unscreened controls from phase 2 of the Wellcome Trust Case Control Consortium (WTCCC2). We compared the frequency of cases with CNVs against the frequency observed in each control group, analysing CNVs over the whole genome, genic, intergenic, intronic and exonic regions. We found that deletion CNVs were associated with recurrent depression, whereas duplications were not. The effect was significant when comparing cases with WTCCC2 controls (P=7.7 × 10(-6), odds ratio (OR) =1.25 (95% confidence interval (CI) 1.13-1.37)) and to screened controls (P=5.6 × 10(-4), OR=1.52 (95% CI 1.20-1.93). Further analysis showed that CNVs deleting protein coding regions were largely responsible for the association. Within an analysis of regions previously implicated in schizophrenia, we found an overall enrichment of CNVs in our cases when compared with screened controls (P=0.019). We observe an ordered increase of samples with deletion CNVs, with the lowest proportion seen in screened controls, the next highest in unscreened controls and the highest in cases. This may suggest that the absence of deletion CNVs, especially in genes, is associated with resilience to recurrent depression.
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Geographical body size variation has long interested evolutionary biologists, and a range of mechanisms have been proposed to explain the observed patterns. It is considered to be more puzzling in ectotherms than in endotherms, and integrative approaches are necessary for testing non-exclusive alternative mechanisms. Using lacertid lizards as a model, we adopted an integrative approach, testing different hypotheses for both sexes while incorporating temporal, spatial, and phylogenetic autocorrelation at the individual level. We used data on the Spanish Sand Racer species group from a field survey to disentangle different sources of body size variation through environmental and individual genetic data, while accounting for temporal and spatial autocorrelation. A variation partitioning method was applied to separate independent and shared components of ecology and phylogeny, and estimated their significance. Then, we fed-back our models by controlling for relevant independent components. The pattern was consistent with the geographical Bergmann's cline and the experimental temperature-size rule: adults were larger at lower temperatures (and/or higher elevations). This result was confirmed with additional multi-year independent data-set derived from the literature. Variation partitioning showed no sex differences in phylogenetic inertia but showed sex differences in the independent component of ecology; primarily due to growth differences. Interestingly, only after controlling for independent components did primary productivity also emerge as an important predictor explaining size variation in both sexes. This study highlights the importance of integrating individual-based genetic information, relevant ecological parameters, and temporal and spatial autocorrelation in sex-specific models to detect potentially important hidden effects. Our individual-based approach devoted to extract and control for independent components was useful to reveal hidden effects linked with alternative non-exclusive hypothesis, such as those of primary productivity. Also, including measurement date allowed disentangling and controlling for short-term temporal autocorrelation reflecting sex-specific growth plasticity.
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Summary points: - The bias introduced by random measurement error will be different depending on whether the error is in an exposure variable (risk factor) or outcome variable (disease) - Random measurement error in an exposure variable will bias the estimates of regression slope coefficients towards the null - Random measurement error in an outcome variable will instead increase the standard error of the estimates and widen the corresponding confidence intervals, making results less likely to be statistically significant - Increasing sample size will help minimise the impact of measurement error in an outcome variable but will only make estimates more precisely wrong when the error is in an exposure variable
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[Abstract] Reading volume and mammography screening performance appear positively correlated. Performance was compared across organised Swiss screening programmes, which target relatively small populations. Except for accreditation of 2nd readers radiologists (restrictive vs non-restrictive strategy), Swiss programmes have similar screening regimen/procedures and duration, which maximises comparability. Variation in performance was explored in order to improve mammography practice and optimise screening performance. Indicators of quality and effectiveness were evaluated for about 200,000 screens performed over 4 screening rounds in the 3 longest-standing Swiss cantonal programmes (of Vaud, Geneva and Valais). Interval cancers were identified by linkage with cancer registries records. Most European standards of performance were met with a favourable cancer stage shift. Several performance indicators showed substantial variation across programmes. In subsequent rounds, compared with programmes (Vaud and Geneva) which accredited few 2nd readers to increase their individual reading volume, proportions of in situ lesions and of small cancers (? 1cm) were one third lower and halved, respectively, and the proportion of advanced lesions (stage II+) nearly 50% higher in the programme without a restrictive selection strategy. Discrepancy in second-year proportional incidence of interval cancers appears to be multicausal. Differences in performance could partly be explained by a selective strategy for 2nd readers and a prior experience in service screening, but not by the levels of opportunistic screening and programme attendance. This study provides clues for enhancing mammography screening performance in low-volume Swiss programmes.
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Understanding the factors that drive geographic variation in life history is an important challenge in evolutionary ecology. Here, we analyze what predicts geographic variation in life-history traits of the common lizard, Zootoca vivipara, which has the globally largest distribution range of all terrestrial reptile species. Variation in body size was predicted by differences in the length of activity season, while we found no effects of environmental temperature per se. Females experiencing relatively short activity season mature at a larger size and remain larger on average than females in populations with relatively long activity seasons. Interpopulation variation in fecundity was largely explained by mean body size of females and reproductive mode, with viviparous populations having larger clutch size than oviparous populations. Finally, body size-fecundity relationship differs between viviparous and oviparous populations, with relatively lower reproductive investment for a given body size in oviparous populations. While the phylogenetic signal was weak overall, the patterns of variation showed spatial effects, perhaps reflecting genetic divergence or geographic variation in additional biotic and abiotic factors. Our findings emphasize that time constraints imposed by the environment rather than ambient temperature play a major role in shaping life histories in the common lizard. This might be attributed to the fact that lizards can attain their preferred body temperature via behavioral thermoregulation across different thermal environments. Length of activity season, defining the maximum time available for lizards to maintain optimal performance, is thus the main environmental factor constraining growth rate and annual rates of mortality. Our results suggest that this factor may partly explain variation in the extent to which different taxa follow ecogeographic rules.
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In pediatric echocardiography, cardiac dimensions are often normalized for weight, height, or body surface area (BSA). The combined influence of height and weight on cardiac size is complex and likely varies with age. We hypothesized that increasing weight for height, as represented by body mass index (BMI) adjusted for age, is poorly accounted for in Z scores normalized for weight, height, or BSA. We aimed to evaluate whether a bias related to BMI was introduced when proximal aorta diameter Z scores are derived from bivariate models (only one normalizing variable), and whether such a bias was reduced when multivariable models are used. We analyzed 1,422 echocardiograms read as normal in children ≤18 years. We computed Z scores of the proximal aorta using allometric, polynomial, and multivariable models with four body size variables. We then assessed the level of residual association of Z scores and BMI adjusted for age and sex. In children ≥6 years, we found a significant residual linear association with BMI-for-age and Z scores for most regression models. Only a multivariable model including weight and height as independent predictors produced a Z score free of linear association with BMI. We concluded that a bias related to BMI was present in Z scores of proximal aorta diameter when normalization was done using bivariate models, regardless of the regression model or the normalizing variable. The use of multivariable models with weight and height as independent predictors should be explored to reduce this potential pitfall when pediatric echocardiography reference values are evaluated.
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Ultra-high-throughput sequencing (UHTS) techniques are evolving rapidly and may soon become an affordable and routine tool for sequencing plant DNA, even in smaller plant biology labs. Here we review recent insights into intraspecific genome variation gained from UHTS, which offers a glimpse of the rather unexpected levels of structural variability among Arabidopsis thaliana accessions. The challenges that will need to be addressed to efficiently assemble and exploit this information are also discussed.