917 resultados para Approach to CSR development
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The prostate cancer is a complex pathology involving oncological, functional and psychosocial items. The prostate's center of CHUV harmonize the know-how of urologists, oncologist, radiotherapists and clinical nurses to offer a global management to patients attempts by prostate cancer, from diagnosis to therapy and follow-up.
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Background In recent years, planaria have emerged as an important model system for research into stem cells and regeneration. Attention is focused on their unique stem cells, the neoblasts, which can differentiate into any cell type present in the adult organism. Sequencing of the Schmidtea mediterranea genome and some expressed sequence tag projects have generated extensive data on the genetic profile of these cells. However, little information is available on their protein dynamics. Results We developed a proteomic strategy to identify neoblast-specific proteins. Here we describe the method and discuss the results in comparison to the genomic high-throughput analyses carried out in planaria and to proteomic studies using other stem cell systems. We also show functional data for some of the candidate genes selected in our proteomic approach. Conclusions We have developed an accurate and reliable mass-spectra-based proteomics approach to complement previous genomic studies and to further achieve a more accurate understanding and description of the molecular and cellular processes related to the neoblasts.
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Surgical extirpation is the treatment of choice for symptomatic mullerian duct remnants (prostatic utricle, PU), and several surgical approaches have been described for the treatment of this pathology. A group of 11 patients with symptomatic PU were observed and treated. Associated anomalies included proximal or penoscrotal hypospadias in all patients and cryptorchidism in 9 (81.8%). In all cases the PU needed surgical correction, as the patients had recurring symptomatology. Surgery was carried out transvesically in 10 (91%) cases and in 1 a perineal approach was used. There were no surgical complications, and at follow-up all patients showed complete resolution of the symptoms. We believe the transvesical approach, compared to other techniques, is more advantageous in the treatment of this pathology, as it permits excellent exposure, ease of surgery, good reconstruction, and good functional results with no sequelae.
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Background: Elevated levels of g-glutamyl transferase (GGT) have been associated with subsequent risk of elevated blood pressure (BP), hypertension and diabetes. However, the causality of these relationships has not been addressed. Mendelian randomization refers to the random allocation of alleles at the time of gamete formation. Such allocation is expected to be independent of any behavioural and environmental factors (known or unknown), allowing the analysis of largely unconfounded risk associations that are not due to reverse causation. Methods: We performed a cross-sectional analysis among 4361 participants to the population based CoLaus study. Associations of sex-specific GGT quartiles with systolic BP, diastolic BP and insulin levels were assessed using multivariable linear regression analyses. The rs2017869 GGT1 variant, which explained 1.6% of the variance in GGT levels, was used as an instrument to perform a Mendelian randomization analysis. Results: Median age of the study population was 53 years. After age and sex adjustment, GGT quartiles were strongly associated with systolic and diastolic BP (all p for linear trend <0.0001). After multivariable adjustment, these relationships were significantly attenuated, but remained significant for systolic (b(95%CI)¼1.30 (0.32;2.03), p¼0.007) and diastolic BP (b (95%CI)¼0.57 (0.02;1.13), p¼0.04). Using Mendelian randomization, we observed no positive association of GGT with either systolic BP (b (95%CI)¼-5.68 (-11.51-0.16), p¼0.06) or diastolic BP (b (95%CI)¼ -2.24 (-5.98;1.49) p¼0.24). The association of GGT with insulin was also attenuated after multivariable adjustment. Nevertheless, a strong linear trend persisted in the fully adjusted model (b (95%CI)¼0.07 (0.04;0.09), p<0.0001). Using Mendelian randomization, we observed a similar positive association of GGT with insulin (b (95%CI)¼0.19 (0.01-0.37), p¼0.04). Conclusion: In this study, we found evidence for a direct causal relationship between GGT and insulin, suggesting that oxidative stress may be causally implicated in the pathogenesis of type 2 diabetes mellitus.
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The major objective of this study was to investigate the effects of several days of intense exercise on the growth hormone marker approach to detect doping with human growth hormone (hGH). In addition we investigated the effect of changes in plasma volume on the test. Fifteen male athletes performed a simulated nine-day cycling stage race. Blood samples were collected twice daily over a period of 15 days (stage race + three days before and after). Plasma volumes were estimated by the optimized CO Rebreathing method. IGF-1 and P-III-NP were analyzed by Siemens Immulite and Cisbio Assays, respectively. All measured GH 2000 scores were far below the published decision limits for an adverse analytical finding. The period of exercise did not increase the GH-scores; however the accompanying effect of the increase in Plasma Volume yielded in essentially lower GH-scores. We could demonstrate that a period of heavy, long-term exercise with changes in plasma volume does not interfere with the decision limits for an adverse analytical finding. Copyright © 2014 John Wiley & Sons, Ltd.
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Aim Conservation strategies are in need of predictions that capture spatial community composition and structure. Currently, the methods used to generate these predictions generally focus on deterministic processes and omit important stochastic processes and other unexplained variation in model outputs. Here we test a novel approach of community models that accounts for this variation and determine how well it reproduces observed properties of alpine butterfly communities. Location The western Swiss Alps. Methods We propose a new approach to process probabilistic predictions derived from stacked species distribution models (S-SDMs) in order to predict and assess the uncertainty in the predictions of community properties. We test the utility of our novel approach against a traditional threshold-based approach. We used mountain butterfly communities spanning a large elevation gradient as a case study and evaluated the ability of our approach to model species richness and phylogenetic diversity of communities. Results S-SDMs reproduced the observed decrease in phylogenetic diversity and species richness with elevation, syndromes of environmental filtering. The prediction accuracy of community properties vary along environmental gradient: variability in predictions of species richness was higher at low elevation, while it was lower for phylogenetic diversity. Our approach allowed mapping the variability in species richness and phylogenetic diversity projections. Main conclusion Using our probabilistic approach to process species distribution models outputs to reconstruct communities furnishes an improved picture of the range of possible assemblage realisations under similar environmental conditions given stochastic processes and help inform manager of the uncertainty in the modelling results
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We present an analytical scheme, easily implemented numerically, to generate synthetic Gaussian turbulent flows by using a linear Langevin equation, where the noise term acts as a stochastic stirring force. The characteristic parameters of the velocity field are well introduced, in particular the kinematic viscosity and the spectrum of energy. As an application, the diffusion of a passive scalar is studied for two different energy spectra. Numerical results are compared favorably with analytical calculations.
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Coma after cardiac arrest (CA) is an important cause of admission to the ICU. Prognosis of post-CA coma has significantly improved over the past decade, particularly because of aggressive postresuscitation care and the use of therapeutic targeted temperature management (TTM). TTM and sedatives used to maintain controlled cooling might delay neurologic reflexes and reduce the accuracy of clinical examination. In the early ICU phase, patients' good recovery may often be indistinguishable (based on neurologic examination alone) from patients who eventually will have a poor prognosis. Prognostication of post-CA coma, therefore, has evolved toward a multimodal approach that combines neurologic examination with EEG and evoked potentials. Blood biomarkers (eg, neuron-specific enolase [NSE] and soluble 100-β protein) are useful complements for coma prognostication; however, results vary among commercial laboratory assays, and applying one single cutoff level (eg, > 33 μg/L for NSE) for poor prognostication is not recommended. Neuroimaging, mainly diffusion MRI, is emerging as a promising tool for prognostication, but its precise role needs further study before it can be widely used. This multimodal approach might reduce false-positive rates of poor prognosis, thereby providing optimal prognostication of comatose CA survivors. The aim of this review is to summarize studies and the principal tools presently available for outcome prediction and to describe a practical approach to the multimodal prognostication of coma after CA, with a particular focus on neuromonitoring tools. We also propose an algorithm for the optimal use of such multimodal tools during the early ICU phase of post-CA coma.
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Needle fiber calcite (NFC) is an ubiquitous terrestrial secondary calcium carbonate mineral often associated with calcitic nanofibers. NFC's origin has been debated for a long time and a fungal origin is often proposed. Fungi are known to be involved in mineral weathering and production of metal oxalate, but little information exists regarding the genesis of other minerals, such as calcite. In this study, a comparison of similar ultrastructural characteristics of fungal hyphae and NFC has been performed to highlight analogies between both features. These analogies clearly demonstrate the probable close relationship between fungal filaments (hyphae and rhizomorphs) and NFC and its associated nanofibers.
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A theoretical density-functional study has been carried out to analyze the exchange coupling in the chains of CuGeO3 using discrete models. The results show a good agreement with the experimental exchange coupling constant (J) together with a strong dependence of J with the Cu-O-Cu angle. The calculation of the J values for a distorted model indicates a larger degree of dimerization than those reported previously.
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A theoretical density-functional study has been carried out to analyze the exchange coupling in the chains of CuGeO3 using discrete models. The results show a good agreement with the experimental exchange coupling constant (J) together with a strong dependence of J with the Cu-O-Cu angle. The calculation of the J values for a distorted model indicates a larger degree of dimerization than those reported previously.
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Background: MLPA method is a potentially useful semi-quantitative method to detect copy number alterations in targeted regions. In this paper, we propose a method for the normalization procedure based on a non-linear mixed-model, as well as a new approach for determining the statistical significance of altered probes based on linear mixed-model. This method establishes a threshold by using different tolerance intervals that accommodates the specific random error variability observed in each test sample.Results: Through simulation studies we have shown that our proposed method outperforms two existing methods that are based on simple threshold rules or iterative regression. We have illustrated the method using a controlled MLPA assay in which targeted regions are variable in copy number in individuals suffering from different disorders such as Prader-Willi, DiGeorge or Autism showing the best performace.Conclusion: Using the proposed mixed-model, we are able to determine thresholds to decide whether a region is altered. These threholds are specific for each individual, incorporating experimental variability, resulting in improved sensitivity and specificity as the examples with real data have revealed.