101 resultados para Permutation-Symmetric Covariance


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ABSTRACT Fat oxidation kinetics: effect of exercise. During graded exercise, absolute whole body fat oxidation rates increase from low to moderate intensities, and then markedly decline at high intensities, implying an exercise intensity (Fatmax) at which the fat oxidation rate is maximal (MFO). The main aim of the present work was to examine the effect of exercise on whole body fat oxidation kinetics. For this purpose, a sinusoidal mathematical model (SIN) has been developped in the first study to provide an accurate description of the shape of fat oxidation kinetics during graded exercise, represented as a function of exercise intensity, and to determine Fatmax and MFO. The SIN model incorporates three independent variables (i.e., dilatation, symmetry, and translation) that correspond to main expected modulations of the basic fat oxidation curve because of factors such as mode of exercise or training status. The results of study 1 showed that the SIN model was a valuable tool to determine Fatmax and MFO, and to precisely characterize and quantify the different shape of fat oxidation kinetics through its three variables. The effectiveness of the SIN model to detect differences in fat oxidation kinetics induced by a specific factor was then confirmed in the second study, which quantitatively described and compared fat oxidation kinetics in two different popular modes of exercise: running and cycling. It was found that the mean fat oxidation kinetics during running was characterized by a greater dilatation and a rightward asymmetry compared with the symmetric parabolic curve in cycling. In the two subsequent studies, the effect of a prior endurance exercise of different intensities and durations on whole body fat oxidation kinetics was examined. Study 3 determined the impact of a 1-h continuous exercise bout at an exercise intensity corresponding to Fatmax on fat oxidation kinetics during a subsequent graded test, while study 4 investigated the effect of an exercise leading to a more pronounced muscle glycogen depletion. The results of these two latter studies showed that fat oxidation rates, MFO, and Fatmax were enhanced following endurance exercise, but were increased to a greater extent with a more severe mucle glycogen depletion, inducing therefore modifications in the postexercise fat oxidation kinetics (i.e., greater dilatation and rightward asymmetry). In perspective, further studies have been suggested 1) to assess physiological meaning of the three independent variables of the SIN model; and 2) to compare the effect of two different training programs on fat oxidation kinetics in obese subjects.

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Take-off, the most important phase in ski jumping, has been primarily studied in terms of spatio-temporal parameters; little is known about its motor control aspects. This study aims to assess the inter-segment coordination of the shank-thigh and thigh-sacrum pairs using the continuous relative phase (CRP). In total 87 jumps were recorded from 33 athletes with an inertial sensor-based system. The CRP curves indicated that the thighs lead the shanks during the first part of take-off extension and that the shanks rotated faster at the take-off extension end. The thighs and sacrum first rotated synchronously, with the sacrum then taking lead, with finally the thighs rotating faster. Five characteristic features were extracted from the CRP and their relationship with jump length was tested. Three features of the shank-thigh pair and one of the thigh-sacrum pair reported a significant association with jump length. It was observed that athletes who achieved longer jumps had their thighs leading their shanks during a longer time, with these athletes also having a more symmetric movement between thighs and sacrum. This study shows that inter-segment coordination during the take-off extension is related to performance and further studies are necessary to contrast its importance with other ski jumping aspects.

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OBJECTIVE: To test if enhancing maternal skin-to-skin contact, or kangaroo mother care (KMC) by adding rocking, singing and sucking is more efficacious than simple KMC for procedural pain in preterm neonates. STUDY DESIGN: Preterm neonates (n=90) between 32 0/7 and 36 0/7 weeks' gestational age participated in a single-blind randomized crossover design. The infant was held in KMC with the addition of rocking, singing and sucking or the infant was held in KMC without additional stimulation. The Premature Infant Pain Profile was the primary outcome with time to recover as the secondary outcome. A repeated-measures analysis of covariance was employed for analyses. RESULT: There were no significant differences in any of the 30 s time periods over the 2 min of blood sampling nor in time to return to baseline. Compared to historical controls of the same age in incubator, the pain scores were lower and comparable to other studies of KMC. There were site differences related to lower scores with the use of sucrose in one site and higher scores in younger, sicker infants in another site. CONCLUSION: The sensorial stimulations from skin-to-skin contact that include tactile, olfactory sensations from the mother are sufficient to decrease pain response in premature neonates. Other studies showing that rocking, sucking and music were efficacious were independent of skin-to-skin contact, which, when used alone has been shown to be effective as reported across studies.

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The strength of interactions between T cell receptors and the peptide-major histocompatibility complex (pMHC) directly modulates T cell fitness, clonal expansion, and acquisition of effector properties. Here we show that asymmetric T cell division is an important mechanistic link between increased signal strength, effector differentiation, and the ability to induce tissue pathology. Recognition of pMHC above a threshold affinity drove responding T cells into asymmetric cell division. The ensuing proximal daughters underwent extensive division and differentiated into short-lived effector cells expressing the integrin VLA-4, allowing the activated T cell to infiltrate and mediate destruction of peripheral target tissues. In contrast, T cells activated by below-threshold antigens underwent symmetric division, leading to abortive clonal expansion and failure to fully differentiate into tissue-infiltrating effector cells. Antigen affinity and asymmetric division are important factors that regulate fate specification in CD8(+) T cells and predict the potential of a self-reactive T cell to mediate tissue pathology.

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The ability to determine the location and relative strength of all transcription-factor binding sites in a genome is important both for a comprehensive understanding of gene regulation and for effective promoter engineering in biotechnological applications. Here we present a bioinformatically driven experimental method to accurately define the DNA-binding sequence specificity of transcription factors. A generalized profile was used as a predictive quantitative model for binding sites, and its parameters were estimated from in vitro-selected ligands using standard hidden Markov model training algorithms. Computer simulations showed that several thousand low- to medium-affinity sequences are required to generate a profile of desired accuracy. To produce data on this scale, we applied high-throughput genomics methods to the biochemical problem addressed here. A method combining systematic evolution of ligands by exponential enrichment (SELEX) and serial analysis of gene expression (SAGE) protocols was coupled to an automated quality-controlled sequence extraction procedure based on Phred quality scores. This allowed the sequencing of a database of more than 10,000 potential DNA ligands for the CTF/NFI transcription factor. The resulting binding-site model defines the sequence specificity of this protein with a high degree of accuracy not achieved earlier and thereby makes it possible to identify previously unknown regulatory sequences in genomic DNA. A covariance analysis of the selected sites revealed non-independent base preferences at different nucleotide positions, providing insight into the binding mechanism.

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This paper introduces a nonlinear measure of dependence between random variables in the context of remote sensing data analysis. The Hilbert-Schmidt Independence Criterion (HSIC) is a kernel method for evaluating statistical dependence. HSIC is based on computing the Hilbert-Schmidt norm of the cross-covariance operator of mapped samples in the corresponding Hilbert spaces. The HSIC empirical estimator is very easy to compute and has good theoretical and practical properties. We exploit the capabilities of HSIC to explain nonlinear dependences in two remote sensing problems: temperature estimation and chlorophyll concentration prediction from spectra. Results show that, when the relationship between random variables is nonlinear or when few data are available, the HSIC criterion outperforms other standard methods, such as the linear correlation or mutual information.

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Background. Efficient therapy for both limb and gait ataxia is required. Climbing, a complex task for the whole motor system involving balance, body stabilization, and the simultaneous coordination of all 4 limbs, may have therapeutic potential. Objective. To investigate whether long-term climbing training improves motor function in patients with cerebellar ataxia. Methods. Four patients suffering from limb and gait ataxia underwent a 6-week climbing training. Its effect on ataxia was evaluated with validated clinical balance and manual dexterity tests and with a kinematic analysis of multijoint arm and leg pointing movements. Results. The patients increased their movement velocity and achieved a more symmetric movement speed profile in both arm and leg pointing movements. Furthermore, the 2 patients who suffered the most from gait ataxia improved their balance and 2 of the 4 patients improved manual dexterity. Conclusion. Climbing training has the potential to serve as a new rehabilitation method for patients with upper and lower limb ataxia.

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Human tumors often contain slowly proliferating cancer cells that resist treatment, but we do not know precisely how these cells arise. We show that rapidly proliferating cancer cells can divide asymmetrically to produce slowly proliferating "G0-like" progeny that are enriched following chemotherapy in breast cancer patients. Asymmetric cancer cell division results from asymmetric suppression of AKT/PKB kinase signaling in one daughter cell during telophase of mitosis. Moreover, inhibition of AKT signaling with small-molecule drugs can induce asymmetric cancer cell division and the production of slow proliferators. Cancer cells therefore appear to continuously flux between symmetric and asymmetric division depending on the precise state of their AKT signaling network. This model may have significant implications for understanding how tumors grow, evade treatment, and recur.

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In a prospective study the functional results after dissection or preservation of the serratus anterior muscle in the postero-lateral standard thoracotomy were evaluated. In 14 patients of our clinic with dissection and suture and in 14 patients with preservation of the serratus muscle the muscle function was assessed and compared preoperatively, within the first two post-operative weeks, and three months after the operation by the same physiotherapists. The two groups were blinded in regard to age, original disease, and mode of intervention. We compared the wing position of the scapula in the sitting position and the positioning of the scapula at fixation of the shoulder joint in the sitting and in the supine position. Using a four-grade function assessment scheme, both groups obtained the same functional results. There was no seroma in either group. After 2.8 (2.5 to 3.0) years all the surviving patients described symmetric functional conditions. We therefore conclude that in order to achieve a better view of the operative field the serratus muscle may be dissected close to the origin if it is then readapted.

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Robust estimators for accelerated failure time models with asymmetric (or symmetric) error distribution and censored observations are proposed. It is assumed that the error model belongs to a log-location-scale family of distributions and that the mean response is the parameter of interest. Since scale is a main component of mean, scale is not treated as a nuisance parameter. A three steps procedure is proposed. In the first step, an initial high breakdown point S estimate is computed. In the second step, observations that are unlikely under the estimated model are rejected or down weighted. Finally, a weighted maximum likelihood estimate is computed. To define the estimates, functions of censored residuals are replaced by their estimated conditional expectation given that the response is larger than the observed censored value. The rejection rule in the second step is based on an adaptive cut-off that, asymptotically, does not reject any observation when the data are generat ed according to the model. Therefore, the final estimate attains full efficiency at the model, with respect to the maximum likelihood estimate, while maintaining the breakdown point of the initial estimator. Asymptotic results are provided. The new procedure is evaluated with the help of Monte Carlo simulations. Two examples with real data are discussed.

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INTRODUCTION: Adaptive statistical iterative reconstruction (ASIR) can decrease image noise, thereby generating CT images of comparable diagnostic quality with less radiation. The purpose of this study is to quantify the effect of systematic use of ASIR versus filtered back projection (FBP) for neuroradiology CT protocols on patients' radiation dose and image quality. METHODS: We evaluated the effect of ASIR on six types of neuroradiologic CT studies: adult and pediatric unenhanced head CT, adult cervical spine CT, adult cervical and intracranial CT angiography, adult soft tissue neck CT with contrast, and adult lumbar spine CT. For each type of CT study, two groups of 100 consecutive studies were retrospectively reviewed: 100 studies performed with FBP and 100 studies performed with ASIR/FBP blending factor of 40 %/60 % with appropriate noise indices. The weighted volume CT dose index (CTDIvol), dose-length product (DLP) and noise were recorded. Each study was also reviewed for image quality by two reviewers. Continuous and categorical variables were compared by t test and free permutation test, respectively. RESULTS: For adult unenhanced brain CT, CT cervical myelography, cervical and intracranial CT angiography and lumbar spine CT both CTDIvol and DLP were lowered by up to 10.9 % (p < 0.001), 17.9 % (p = 0.005), 20.9 % (p < 0.001), and 21.7 % (p = 0.001), respectively, by using ASIR compared with FBP alone. Image quality and noise were similar for both FBP and ASIR. CONCLUSION: We recommend routine use of iterative reconstruction for neuroradiology CT examinations because this approach affords a significant dose reduction while preserving image quality.

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Background: Bone health is a concern when treating early stage breast cancer patients with adjuvant aromatase inhibitors. Early detection of patients (pts) at risk of osteoporosis and fractures may be helpful for starting preventive therapies and selecting the most appropriate endocrine therapy schedule. We present statistical models describing the evolution of lumbar and hip bone mineral density (BMD) in pts treated with tamoxifen (T), letrozole (L) and sequences of T and L. Methods: Available dual-energy x-ray absorptiometry exams (DXA) of pts treated in trial BIG 1-98 were retrospectively collected from Swiss centers. Treatment arms: A) T for 5 years, B) L for 5 years, C) 2 years of T followed by 3 years of L and, D) 2 years of L followed by 3 years of T. Pts without DXA were used as a control for detecting selection biases. Patients randomized to arm A were subsequently allowed an unplanned switch from T to L. Allowing for variations between DXA machines and centres, two repeated measures models, using a covariance structure that allow for different times between DXA, were used to estimate changes in hip and lumbar BMD (g/cm2) from trial randomization. Prospectively defined covariates, considered as fixed effects in the multivariable models in an intention to treat analysis, at the time of trial randomization were: age, height, weight, hysterectomy, race, known osteoporosis, tobacco use, prior bone fracture, prior hormone replacement therapy (HRT), bisphosphonate use and previous neo-/adjuvant chemotherapy (ChT). Similarly, the T-scores for lumbar and hip BMD measurements were modeled using a per-protocol approach (allowing for treatment switch in arm A), specifically studying the effect of each therapy upon T-score percentage. Results: A total of 247 out of 546 pts had between 1 and 5 DXA; a total of 576 DXA were collected. Number of DXA measurements per arm were; arm A 133, B 137, C 141 and D 135. The median follow-up time was 5.8 years. Significant factors positively correlated with lumbar and hip BMD in the multivariate analysis were weight, previous HRT use, neo-/adjuvant ChT, hysterectomy and height. Significant negatively correlated factors in the models were osteoporosis, treatment arm (B/C/D vs. A), time since endocrine therapy start, age and smoking (current vs. never).Modeling the T-score percentage, differences from T to L were -4.199% (p = 0.036) and -4.907% (p = 0.025) for the hip and lumbar measurements respectively, before any treatment switch occurred. Conclusions: Our statistical models describe the lumbar and hip BMD evolution for pts treated with L and/or T. The results of both localisations confirm that, contrary to expectation, the sequential schedules do not seem less detrimental for the BMD than L monotherapy. The estimated difference in BMD T-score percent is at least 4% from T to L.

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The purpose of this study was to assess the cross-cultural validity of the Marlowe-Crowne Social Desirability scale short form C, in a large sample of French-speaking participants from eight African countries and Switzerland. Exploratory and confirmatory analyses suggested retaining a two-factor structure. Item bias detection according to country was conducted for all 13 items and effect was calculated with R2. For the two-factor solution, 9 items were associated with a negligible effect size, 3 items with a moderate one, and 1 item with a large one. A series of analyses of covariance considering the acquiescence variable as a covariate showed that the acquiescence tendency does not contribute to the bias at item level. This research indicates that the psychometric properties of this instrument do not reach a scalar equivalence but that a culturally reliable measurement of social desirability could be developed.

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Despite the considerable evidence showing that dispersal between habitat patches is often asymmetric, most of the metapopulation models assume symmetric dispersal. In this paper, we develop a Monte Carlo simulation model to quantify the effect of asymmetric dispersal on metapopulation persistence. Our results suggest that metapopulation extinctions are more likely when dispersal is asymmetric. Metapopulation viability in systems with symmetric dispersal mirrors results from a mean field approximation, where the system persists if the expected per patch colonization probability exceeds the expected per patch local extinction rate. For asymmetric cases, the mean field approximation underestimates the number of patches necessary for maintaining population persistence. If we use a model assuming symmetric dispersal when dispersal is actually asymmetric, the estimation of metapopulation persistence is wrong in more than 50% of the cases. Metapopulation viability depends on patch connectivity in symmetric systems, whereas in the asymmetric case the number of patches is more important. These results have important implications for managing spatially structured populations, when asymmetric dispersal may occur. Future metapopulation models should account for asymmetric dispersal, while empirical work is needed to quantify the patterns and the consequences of asymmetric dispersal in natural metapopulations.

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Simulated-annealing-based conditional simulations provide a flexible means of quantitatively integrating diverse types of subsurface data. Although such techniques are being increasingly used in hydrocarbon reservoir characterization studies, their potential in environmental, engineering and hydrological investigations is still largely unexploited. Here, we introduce a novel simulated annealing (SA) algorithm geared towards the integration of high-resolution geophysical and hydrological data which, compared to more conventional approaches, provides significant advancements in the way that large-scale structural information in the geophysical data is accounted for. Model perturbations in the annealing procedure are made by drawing from a probability distribution for the target parameter conditioned to the geophysical data. This is the only place where geophysical information is utilized in our algorithm, which is in marked contrast to other approaches where model perturbations are made through the swapping of values in the simulation grid and agreement with soft data is enforced through a correlation coefficient constraint. Another major feature of our algorithm is the way in which available geostatistical information is utilized. Instead of constraining realizations to match a parametric target covariance model over a wide range of spatial lags, we constrain the realizations only at smaller lags where the available geophysical data cannot provide enough information. Thus we allow the larger-scale subsurface features resolved by the geophysical data to have much more due control on the output realizations. Further, since the only component of the SA objective function required in our approach is a covariance constraint at small lags, our method has improved convergence and computational efficiency over more traditional methods. Here, we present the results of applying our algorithm to the integration of porosity log and tomographic crosshole georadar data to generate stochastic realizations of the local-scale porosity structure. Our procedure is first tested on a synthetic data set, and then applied to data collected at the Boise Hydrogeophysical Research Site.