250 resultados para Potential Kernel
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PURPOSE: Hypertriglyceridemia (hyperTG) is common among intensive care unit (ICU) patients, but knowledge about hyperTG risk factors is scarce. The present study aims to identify risk factors favoring its development in patients requiring prolonged ICU treatment. METHODS: Prospective observational study in the medicosurgical ICU of a university teaching hospital. All consecutive patients staying ≥4 days were enrolled. Potential risk factors were recorded: pathology, energy intake, amount and type of nutritional lipids, intake of propofol, glucose intake, laboratory parameters, and drugs. Triglyceride (TG) levels were assessed three times weekly. Statistics was based on two-way analysis of variance (ANOVA) and linear regression with potential risk factors. RESULTS: Out of 1,301 consecutive admissions, 220 patients were eligible, of whom 99 (45 %) presented hyperTG (triglycerides >2 mmol/L). HyperTG patients were younger, heavier, with more brain injury and multiple trauma. Intake of propofol (mg/kg/h) and lipids' propofol had the highest correlation with plasma TG (r (2) = 0.28 and 0.26, respectively, both p < 0.001). Infection and inflammation were associated with development of hyperTG [C-reactive protein (CRP), r (2) = 0.19, p = 0.004]. No strong association could be found with nutritional lipids or other risk factors. Outcome was similar in normo- and hyperTG patients. CONCLUSIONS: HyperTG is frequent in the ICU but is not associated with adverse outcome. Propofol and accompanying lipid emulsion are the strongest risk factors. Our results suggest that plasma TG should be monitored at least twice weekly in patients on propofol. The clinical consequences of propofol-related hyperTG should be investigated in further studies.
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Neural tissue has historically been regarded as having poor regenerative capacity but recent advances in the growing fields of tissue engineering and regenerative medicine have opened new hopes for the treatment of nerve injuries and neurodegenerative disorders. Adipose tissue has been shown to contain a large quantity of adult stem cells (ASC). These cells can be easily harvested with low associated morbidity and because of their potential to differentiate into multiple cell types, their use has been suggested for a wide variety of therapeutic applications. In this review we examine the evidence indicating that ASC can stimulate nerve regeneration by both undergoing neural differentiation and through the release of a range of growth factors. We also discuss some of the issues that need to be addressed before ASC can be developed as an effective cellular therapy for the treatment of neural tissue disorders.
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The heat shock response (HSR) is a highly conserved molecular response to various types of stresses, including heat shock, during which heat-shock proteins (Hsps) are produced to prevent and repair damages in labile proteins and membranes. In cells, protein unfolding in the cytoplasm is thought to directly enable the activation of the heat shock factor 1 (HSF-1), however, recent work supports the activation of the HSR via an increase in the fluidity of specific membrane domains, leading to activation of heat-shock genes. Our findings support the existence of a plasma membrane-dependent mechanism of HSF-1 activation in animal cells, which is initiated by a membrane-associated transient receptor potential vanilloid receptor (TRPV). We found in various non-cancerous and cancerous mammalian epithelial cells that the TRPV1 agonists, capsaicin and resiniferatoxin (RTX), upregulated the accumulation of Hsp70, Hsp90 and Hsp27 and Hsp70 and Hsp90 respectively, while the TRPV1 antagonists, capsazepine and AMG-9810, attenuated the accumulation of Hsp70, Hsp90 and Hsp27 and Hsp70, Hsp90, respectively. Capsaicin was also shown to activate HSF-1. These findings suggest that heat-sensing and signaling in mammalian cells is dependent on TRPV channels in the plasma membrane. Thus, TRPV channels may be important drug targets to inhibit or restore the cellular stress response in diseases with defective cellular proteins, such as cancer, inflammation and aging.
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OBJECTIVE: The purpose of this article is to assess the effect of the adaptive statistical iterative reconstruction (ASIR) technique on image quality in hip MDCT arthrography and to evaluate its potential for reducing radiation dose. SUBJECTS AND METHODS: Thirty-seven patients examined with hip MDCT arthrography were prospectively randomized into three different protocols: one with a regular dose (volume CT dose index [CTDIvol], 38.4 mGy) and two with a reduced dose (CTDIvol, 24.6 or 15.4 mGy). Images were reconstructed using filtered back projection (FBP) and four increasing percentages of ASIR (30%, 50%, 70%, and 90%). Image noise and contrast-to-noise ratio (CNR) were measured. Two musculoskeletal radiologists independently evaluated several anatomic structures and image quality parameters using a 4-point scale. They also jointly assessed acetabular labrum tears and articular cartilage lesions. RESULTS: With decreasing radiation dose level, image noise statistically significantly increased (p=0.0009) and CNR statistically significantly decreased (p=0.001). We also found a statistically significant reduction in noise (p=0.0001) and increase in CNR (p≤0.003) with increasing percentage of ASIR; in addition, we noted statistically significant increases in image quality scores for the labrum and cartilage, subchondral bone, overall diagnostic quality (up to 50% ASIR), and subjective noise (p≤0.04), and statistically significant reductions for the trabecular bone and muscles (p≤0.03). Regardless of the radiation dose level, there were no statistically significant differences in the detection and characterization of labral tears (n=24; p=1) and cartilage lesions (n=40; p≥0.89) depending on the ASIR percentage. CONCLUSION: The use of up to 50% ASIR in hip MDCT arthrography helps to reduce radiation dose by approximately 35-60%, while maintaining diagnostic image quality comparable to that of a regular-dose protocol using FBP.
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African clawed frogs of the widespread polytypic species Xenopus laevis Daudin, 1802 (ranging large parts of sub-Saharan Africa) have been spreading since the 1940s, and have established reproductive populations in Europe, Asia and the Americas, where they can have negative impact as competitors of native amphibians and as disease vectors for chytridomycosis or ranaviruses. Here we use two mitochondrial (cytochrome b, 16S rDNA) and one nuclear (RAG 1: Recombination Associated Gene 1) DNA markers to infer the potential origin of invasive clawed frogs from Sicily that represent the largest invasive population in Europe. Identical mtDNA haplotypes match with those of Xenopus laevis, and Sicilian clawed frogs very probably belong to a lineage from the Cape Region of South Africa, most likely originating from a laboratory stock. Nuclear data support this conclusion. Identical mtDNA sequences (cyt b, 16S) of frogs sampled across their range in Sicily suggest the occurrence of a single source population and a potential bottleneck at their release, but faster evolving multilocus nuclear data (microsatellites, SNPs) on the population genetics would be important in the future to better support this hypothesis
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The paper presents the Multiple Kernel Learning (MKL) approach as a modelling and data exploratory tool and applies it to the problem of wind speed mapping. Support Vector Regression (SVR) is used to predict spatial variations of the mean wind speed from terrain features (slopes, terrain curvature, directional derivatives) generated at different spatial scales. Multiple Kernel Learning is applied to learn kernels for individual features and thematic feature subsets, both in the context of feature selection and optimal parameters determination. An empirical study on real-life data confirms the usefulness of MKL as a tool that enhances the interpretability of data-driven models.
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Collectively, research aimed to understand the regeneration of certain tissues has unveiled the existence of common key regulators. Knockout studies of the murine Nuclear Factor I-C (NFI-C) transcription factor revealed a misregulation of growth factor signaling, in particular that of transforming growth factor ß-1 (TGF-ßl), which led to alterations of skin wound healing and the growth of its appendages, suggesting it may be a general regulator of regenerative processes. We sought to investigate this further by determining whether NFI-C played a role in liver regeneration. Liver regeneration following two-thirds removal of the liver by partial hepatectomy (PH) is a well-established regenerative model whereby changes elicited in hepatocytes following injury lead to a rapid, phased proliferation. However, mechanisms controlling the action of liver proliferative factors such as transforming growth factor-ßl (TGF-ß1) and plasminogen activator inhibitor-1 (PAI-1) remain largely unknown. We show that the absence of NFI-C impaired hepatocyte proliferation due to an overexpression of PAI-1 and the subsequent suppression of urokinase plasminogen (uPA) activity and hepatocyte growth factor (HGF) signaling, a potent hepatocyte mitogen. This indicated that NFI-C first acts to promote hepatocyte proliferation at the onset of liver regeneration in wildtype mice. The subsequent transient down regulation of NFI-C, as can be explained by a self- regulatory feedback loop with TGF-ßl, may limit the number of hepatocytes entering the first wave of cell division and/or prevent late initiations of mitosis. Overall, we conclude that NFI-C acts as a regulator of the phased hepatocyte proliferation during liver regeneration. Taken together with NFI-C's actions in other in vivo models of (re)generation, it is plausible that NFI-C may be a general regulator of regenerative processes. - L'ensemble des recherches visant à comprendre la régénération de certains tissus a permis de mettre en évidence l'existence de régulateurs-clés communs. L'étude des souris, dépourvues du gène codant pour le facteur de transcription NFI-C (Nuclear Factor I-C), a montré des dérèglements dans la signalisation de certains facteurs croissance, en particulier du TGF-ßl (transforming growth factor-ßl), ce qui conduit à des altérations de la cicatrisation de la peau et de la croissance des poils et des dents chez ces souris, suggérant que NFI-C pourrait être un régulateur général du processus de régénération. Nous avons cherché à approfondir cette question en déterminant si NFI-C joue un rôle dans la régénération du foie. La régénération du foie, induite par une hépatectomie partielle correspondant à l'ablation des deux-tiers du foie, constitue un modèle de régénération bien établi dans lequel la lésion induite conduit à la prolifération rapide des hépatocytes de façon synchronisée. Cependant, les mécanismes contrôlant l'action de facteurs de prolifération du foie, comme le facteur de croissance TGF-ßl et l'inhibiteur de l'activateur du plasminogène PAI-1 (plasminogen activator inhibitor-1), restent encore très méconnus. Nous avons pu montrer que l'absence de NFI-C affecte la prolifération des hépatocytes, occasionnée par la surexpression de PAI-1 et par la subséquente suppression de l'activité de la protéine uPA (urokinase plasminogen) et de la signalisation du facteur de croissance des hépatocytes HGF (hepatocyte growth factor), un mitogène puissant des hépatocytes. Cela indique que NFI-C agit en premier lieu pour promouvoir la prolifération des hépatocytes au début de la régénération du foie chez les souris de type sauvage. La subséquente baisse transitoire de NFI-C, pouvant s'expliquer par une boucle rétroactive d'autorégulation avec le facteur TGF-ßl, pourrait limiter le nombre d'hépatocytes qui entrent dans la première vague de division cellulaire et/ou inhiber l'initiation de la mitose tardive. L'ensemble de ces résultats nous a permis de conclure que NFI-C agit comme un régulateur de la prolifération des hépatocytes synchrones au cours de la régénération du foie.
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Over the past few years, the therapeutic potential of Treg has been highlighted in the field of autoimmune diseases and after allogeneic transplantation. The first hurdle for the therapeutic use of Treg is their insufficient numbers in non-manipulated individuals, in particular when facing strong immune activation and expanding effector cells, such as in response to an allograft. Here we review current approaches being explored for Treg expansion in the perspective of clinical therapeutic protocols. We describe different Treg subsets that could be suitable for clinical application, as well as discuss factors such as the required dose of Treg, their antigen-specificity and in vivo stability, that have to be considered for optimal Treg-based immunotherapy in transplantation. Since Treg may not be sufficient as stand-alone therapy for solid organ transplantation in humans, we draw attention to possible hurdles and combination therapy with immunomodulatory drugs that could possibly improve the in vivo efficacy of Treg.
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We describe herein some immunological properties of human fetal bone cells recently tested for bone tissue-engineering applications. Adult mesenchymal stem cells (MSCs) and osteoblasts were included in the study for comparison. Surface markers involved in bone metabolism and immune recognition were analyzed using flow cytometry before and after differentiation or treatment with cytokines. Immunomodulatory properties were studied on activated peripheral blood mononuclear cells (PBMCs). The immuno-profile of fetal bone cells was further investigated at the gene expression level. Fetal bone cells and adult MSCs were positive for Stro-1, alkaline phosphatase, CD10, CD44, CD54, and beta2-microglobulin, but human leukocyte antigen (HLA)-I and CD80 were less present than on adult osteoblasts. All cells were negative for HLA-II. Treatment with recombinant human interferon gamma increased the presence of HLA-I in adult cells much more than in fetal cells. In the presence of activated PBMCs, fetal cells had antiproliferative effects, although with patterns not always comparable with those of adult MSCs and osteoblasts. Because of the immunological profile, and with their more-differentiated phenotype than of stem cells, fetal bone cells present an interesting potential for allogeneic cell source in tissue-engineering applications.
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We present a combined shape and mechanical anisotropy evolution model for a two-phase inclusion-bearing rock subject to large deformation. A single elliptical inclusion embedded in a homogeneous but anisotropic matrix is used to represent a simplified shape evolution enforced on all inclusions. The mechanical anisotropy develops due to the alignment of elongated inclusions. The effective anisotropy is quantified using the differential effective medium (DEM) approach. The model can be run for any deformation path and an arbitrary viscosity ratio between the inclusion and host phase. We focus on the case of simple shear and weak inclusions. The shape evolution of the representative inclusion is largely insensitive to the anisotropy development and to parameter variations in the studied range. An initial hardening stage is observed up to a shear strain of gamma = 1 irrespective of the inclusion fraction. The hardening is followed by a softening stage related to the developing anisotropy and its progressive rotation toward the shear direction. The traction needed to maintain a constant shear rate exhibits a fivefold drop at gamma = 5 in the limiting case of an inviscid inclusion. Numerical simulations show that our analytical model provides a good approximation to the actual evolution of a two-phase inclusion-host composite. However, the inclusions develop complex sigmoidal shapes resulting in the formation of an S-C fabric. We attribute the observed drop in the effective normal viscosity to this structural development. We study the localization potential in a rock column bearing varying fraction of inclusions. In the inviscid inclusion case, a strain jump from gamma = 3 to gamma = 100 is observed for a change of the inclusion fraction from 20% to 33%.
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It is estimated that around 230 people die each year due to radon (222Rn) exposure in Switzerland. 222Rn occurs mainly in closed environments like buildings and originates primarily from the subjacent ground. Therefore it depends strongly on geology and shows substantial regional variations. Correct identification of these regional variations would lead to substantial reduction of 222Rn exposure of the population based on appropriate construction of new and mitigation of already existing buildings. Prediction of indoor 222Rn concentrations (IRC) and identification of 222Rn prone areas is however difficult since IRC depend on a variety of different variables like building characteristics, meteorology, geology and anthropogenic factors. The present work aims at the development of predictive models and the understanding of IRC in Switzerland, taking into account a maximum of information in order to minimize the prediction uncertainty. The predictive maps will be used as a decision-support tool for 222Rn risk management. The construction of these models is based on different data-driven statistical methods, in combination with geographical information systems (GIS). In a first phase we performed univariate analysis of IRC for different variables, namely the detector type, building category, foundation, year of construction, the average outdoor temperature during measurement, altitude and lithology. All variables showed significant associations to IRC. Buildings constructed after 1900 showed significantly lower IRC compared to earlier constructions. We observed a further drop of IRC after 1970. In addition to that, we found an association of IRC with altitude. With regard to lithology, we observed the lowest IRC in sedimentary rocks (excluding carbonates) and sediments and the highest IRC in the Jura carbonates and igneous rock. The IRC data was systematically analyzed for potential bias due to spatially unbalanced sampling of measurements. In order to facilitate the modeling and the interpretation of the influence of geology on IRC, we developed an algorithm based on k-medoids clustering which permits to define coherent geological classes in terms of IRC. We performed a soil gas 222Rn concentration (SRC) measurement campaign in order to determine the predictive power of SRC with respect to IRC. We found that the use of SRC is limited for IRC prediction. The second part of the project was dedicated to predictive mapping of IRC using models which take into account the multidimensionality of the process of 222Rn entry into buildings. We used kernel regression and ensemble regression tree for this purpose. We could explain up to 33% of the variance of the log transformed IRC all over Switzerland. This is a good performance compared to former attempts of IRC modeling in Switzerland. As predictor variables we considered geographical coordinates, altitude, outdoor temperature, building type, foundation, year of construction and detector type. Ensemble regression trees like random forests allow to determine the role of each IRC predictor in a multidimensional setting. We found spatial information like geology, altitude and coordinates to have stronger influences on IRC than building related variables like foundation type, building type and year of construction. Based on kernel estimation we developed an approach to determine the local probability of IRC to exceed 300 Bq/m3. In addition to that we developed a confidence index in order to provide an estimate of uncertainty of the map. All methods allow an easy creation of tailor-made maps for different building characteristics. Our work is an essential step towards a 222Rn risk assessment which accounts at the same time for different architectural situations as well as geological and geographical conditions. For the communication of 222Rn hazard to the population we recommend to make use of the probability map based on kernel estimation. The communication of 222Rn hazard could for example be implemented via a web interface where the users specify the characteristics and coordinates of their home in order to obtain the probability to be above a given IRC with a corresponding index of confidence. Taking into account the health effects of 222Rn, our results have the potential to substantially improve the estimation of the effective dose from 222Rn delivered to the Swiss population.