998 resultados para uncertainty factor
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OBJECTIVES: Growth retardation is a frequent complication of paediatric inflammatory bowel disease (IBD). Only a few studies report the final height of these patients, with controversial results. We compared adult height of patients with paediatric IBD with that of patients with adult-onset disease. METHODS: Height data of 675 women 19-44 years of age and 454 men 23-44 years of age obtained at inclusion in the Swiss IBD cohort study registry were grouped according to the age at diagnosis: (a) prepubertal (men≤13, women≤11 years), (b) pubertal (men 13-22, women 11-18 years) and (c) adult (men>22, women>18 years of age), and compared with each other and with healthy controls. RESULTS: Male patients with prepubertal onset of Crohn's disease (CD) had significantly lower final height (mean 172±6 cm, range 161-182) compared with men with pubertal (179±6 cm, 161-192) or adult (178±7 cm, 162-200) age at onset and the general population (178±7 cm, 142-204). Height z-scores standardized against heights of the normal population were significantly lower in all patients with a prepubertal diagnosis of CD (-0.8±0.9) compared with the other patient groups (-0.1±0.8, P<0.001). Prepubertal onset of CD emerged as a risk factor for reduced final height in patients with prepubertal CD. No difference for final height was found between patients with ulcerative or unclassified IBD diagnosed at prepubertal, pubertal or adult age. CONCLUSION: Prepubertal onset of CD is a risk for lower final height, independent of the initial disease location and the necessity for surgical interventions.
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BACKGROUND/AIM: Both steatosis and insulin resistance have been linked to accelerated fibrosis in chronic hepatitis C. Connective tissue growth factor (CTGF) plays a major role in extracellular matrix production in fibrotic disorders including cirrhosis, and its expression is stimulated in vitro by insulin and glucose. We hypothesized that CTGF may link steatosis, insulin resistance and fibrosis. METHODS: We included 153 chronic hepatitis C patients enrolled in the Swiss Hepatitis C Cohort Study and for whom a liver biopsy and plasma samples were available. CTGF expression was assessed quantitatively by immunohistochemistry. In 94 patients (57 with genotypes non-3), plasma levels of glucose, insulin and leptin were also measured. CTGF synthesis was investigated by immunoblotting on LX-2 stellate cells. RESULTS: Connective tissue growth factor expression was higher in patients with steatosis (P=0.039) and in patients with fibrosis (P=0.008) than those without these features. CTGF levels were neither associated with insulinaemia or with glycaemia, nor with inflammation. By multiple regression analysis, CTGF levels were independently associated with steatosis, a past history of alcohol abuse, plasma leptin and HCV RNA levels; when only patients with genotypes non-3 were considered, CTGF levels were independently associated with a past history of alcohol abuse, plasma leptin levels and steatosis. Leptin stimulated CTGF synthesis in LX-2 cells. CONCLUSIONS: In patients with chronic hepatitis C and steatosis, CTGF may promote fibrosis independently of inflammation. CTGF may link steatosis and fibrosis via increased leptin levels.
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By interacting with MHC class II molecules, CD4 facilitates lineage development as well as activation of Th cells. Expression of physiological levels of CD4 requires a proximal CD4 enhancer to stimulate basic CD4 promoter activity. T cell factor (TCF)-1/beta-catenin pathway has previously been shown to regulate thymocyte survival via up-regulating antiapoptotic molecule Bcl-xL. By both loss and gain of function studies, in this study we show additional function of TCF-1/beta-catenin pathway in the regulation of CD4 expression in vivo. Mice deficient in TCF-1 displayed significantly reduced protein and mRNA levels of CD4 in CD4+ CD8+ double-positive (DP) thymocytes. A transgene encoding Bcl-2 restored survival but not CD4 levels of TCF-1(-/-) DP cells. Thus, TCF-1-regulated survival and CD4 expression are two separate events. In contrast, CD4 levels were restored on DP TCF-1(-/-) cells by transgenic expression of a wild-type TCF-1, but not a truncated TCF-1 that lacks a domain required for interacting with beta-catenin. Furthermore, forced expression of a stabilized beta-catenin, a coactivator of TCF-1, resulted in up-regulation of CD4. TCF-1 or stabilized beta-catenin greatly stimulated activity of a CD4 reporter gene driven by a basic CD4 promoter and the CD4 enhancer. However, mutation of a potential TCF binding site located within the enhancer abrogated TCF-1 and beta-catenin-mediated activation of CD4 reporter. Finally, recruitment of TCF-1 to CD4 enhancer was detected in wild-type but not TCF-1 null mice by chromatin-immunoprecipitation analysis. Thus, our results demonstrated that TCF/beta-catenin pathway enhances CD4 expression in vivo by recruiting TCF-1 to stimulate CD4 enhancer activity.
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SUMMARY : Eukaryotic DNA interacts with the nuclear proteins using non-covalent ionic interactions. Proteins can recognize specific nucleotide sequences based on the sterical interactions with the DNA and these specific protein-DNA interactions are the basis for many nuclear processes, e.g. gene transcription, chromosomal replication, and recombination. New technology termed ChIP-Seq has been recently developed for the analysis of protein-DNA interactions on a whole genome scale and it is based on immunoprecipitation of chromatin and high-throughput DNA sequencing procedure. ChIP-Seq is a novel technique with a great potential to replace older techniques for mapping of protein-DNA interactions. In this thesis, we bring some new insights into the ChIP-Seq data analysis. First, we point out to some common and so far unknown artifacts of the method. Sequence tag distribution in the genome does not follow uniform distribution and we have found extreme hot-spots of tag accumulation over specific loci in the human and mouse genomes. These artifactual sequence tags accumulations will create false peaks in every ChIP-Seq dataset and we propose different filtering methods to reduce the number of false positives. Next, we propose random sampling as a powerful analytical tool in the ChIP-Seq data analysis that could be used to infer biological knowledge from the massive ChIP-Seq datasets. We created unbiased random sampling algorithm and we used this methodology to reveal some of the important biological properties of Nuclear Factor I DNA binding proteins. Finally, by analyzing the ChIP-Seq data in detail, we revealed that Nuclear Factor I transcription factors mainly act as activators of transcription, and that they are associated with specific chromatin modifications that are markers of open chromatin. We speculate that NFI factors only interact with the DNA wrapped around the nucleosome. We also found multiple loci that indicate possible chromatin barrier activity of NFI proteins, which could suggest the use of NFI binding sequences as chromatin insulators in biotechnology applications. RESUME : L'ADN des eucaryotes interagit avec les protéines nucléaires par des interactions noncovalentes ioniques. Les protéines peuvent reconnaître les séquences nucléotidiques spécifiques basées sur l'interaction stérique avec l'ADN, et des interactions spécifiques contrôlent de nombreux processus nucléaire, p.ex. transcription du gène, la réplication chromosomique, et la recombinaison. Une nouvelle technologie appelée ChIP-Seq a été récemment développée pour l'analyse des interactions protéine-ADN à l'échelle du génome entier et cette approche est basée sur l'immuno-précipitation de la chromatine et sur la procédure de séquençage de l'ADN à haut débit. La nouvelle approche ChIP-Seq a donc un fort potentiel pour remplacer les anciennes techniques de cartographie des interactions protéine-ADN. Dans cette thèse, nous apportons de nouvelles perspectives dans l'analyse des données ChIP-Seq. Tout d'abord, nous avons identifié des artefacts très communs associés à cette méthode qui étaient jusqu'à présent insoupçonnés. La distribution des séquences dans le génome ne suit pas une distribution uniforme et nous avons constaté des positions extrêmes d'accumulation de séquence à des régions spécifiques, des génomes humains et de la souris. Ces accumulations des séquences artéfactuelles créera de faux pics dans toutes les données ChIP-Seq, et nous proposons différentes méthodes de filtrage pour réduire le nombre de faux positifs. Ensuite, nous proposons un nouvel échantillonnage aléatoire comme un outil puissant d'analyse des données ChIP-Seq, ce qui pourraient augmenter l'acquisition de connaissances biologiques à partir des données ChIP-Seq. Nous avons créé un algorithme d'échantillonnage aléatoire et nous avons utilisé cette méthode pour révéler certaines des propriétés biologiques importantes de protéines liant à l'ADN nommés Facteur Nucléaire I (NFI). Enfin, en analysant en détail les données de ChIP-Seq pour la famille de facteurs de transcription nommés Facteur Nucléaire I, nous avons révélé que ces protéines agissent principalement comme des activateurs de transcription, et qu'elles sont associées à des modifications de la chromatine spécifiques qui sont des marqueurs de la chromatine ouverte. Nous pensons que lés facteurs NFI interagir uniquement avec l'ADN enroulé autour du nucléosome. Nous avons également constaté plusieurs régions génomiques qui indiquent une éventuelle activité de barrière chromatinienne des protéines NFI, ce qui pourrait suggérer l'utilisation de séquences de liaison NFI comme séquences isolatrices dans des applications de la biotechnologie.
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The sequestration of Plasmodium falciparum-infected erythrocytes to the endothelial cells of brain capillaries is believed to represent one of the determining factors in the pathogenesis of cerebral malaria. In vitro studies of cytoadherence provide an experimental approach to understand the mechanism of sequestration and the respective roles played by parasite and host components in this interaction. This paper critically reviews current studies on cytoadherence, with particular emphasis on the nature of the information provided by such studies and their limitations. The paper also describes how cytoadherence studies using the patient's own monocytes can provide original information on the level of receptor up-regulation in the course of malarial infection.
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Pseudomonas fluorescens CHA0 produces a variety of secondary metabolites, in particular the antibiotics pyoluteorin and 2,4-diacetylphloroglucinol, and protects various plants from diseases caused by soilborne pathogenic fungi. The rpoD gene encoding the housekeeping sigma factor sigma 70 of P. fluorescens was sequenced. The deduced RpoD protein showed 83% identity with RpoD of Pseudomonas aeruginosa and 67% identity with RpoD of Escherichia coli. Attempts to inactivate the single chromosomal rpoD gene of strain CHA0 were unsuccessful, indicating an essential role of this gene. When rpoD was carried by an IncP vector in strain CHA0, the production of both antibiotics was increased severalfold and, in parallel, protection of cucumber against disease caused by Pythium ultimum was improved, in comparison with strain CHA0.
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In Pseudomonas fluorescens biocontrol strain CHA0, the two-component system GacS/GacA positively controls the synthesis of extracellular products such as hydrogen cyanide, protease, and 2,4-diacetylphloroglucinol, by upregulating the transcription of small regulatory RNAs which relieve RsmA-mediated translational repression of target genes. The expression of the stress sigma factor sigmaS (RpoS) was controlled positively by GacA and negatively by RsmA. By comparison with the wild-type CHA0, both a gacS and an rpoS null mutant were more sensitive to H2O2 in stationary phase. Overexpression of rpoS or of rsmZ, encoding a small RNA antagonistic to RsmA, restored peroxide resistance to a gacS mutant. By contrast, the rpoS mutant showed a slight increase in the expression of the hcnA (HCN synthase subunit) gene and of the aprA (major exoprotease) gene, whereas overexpression of sigmaS strongly reduced the expression of these genes. These results suggest that in strain CHA0, regulation of exoproduct synthesis does not involve sigmaS as an intermediate in the Gac/Rsm signal transduction pathway whereas sigmaS participates in Gac/Rsm-mediated resistance to oxidative stress.
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The cytokine macrophage migration inhibitory factor (MIF) is an important component of the early proinflammatory response of the innate immune system. However, the antimicrobial defense mechanisms mediated by MIF remain fairly mysterious. In the present study, we examined whether MIF controls bacterial uptake and clearance by professional phagocytes, using wild-type and MIF-deficient macrophages. MIF deficiency did not affect bacterial phagocytosis, but it strongly impaired the killing of gram-negative bacteria by macrophages and host defenses against gram-negative bacterial infection, as shown by increased mortality in a Klebsiella pneumonia model. Consistent with MIF's regulatory role of Toll-like 4 expression in macrophages, MIF-deficient cells stimulated with lipopolysaccharide or Escherichia coli exhibited reduced nuclear factor κB activity and tumor necrosis factor (TNF) production. Addition of recombinant MIF or TNF corrected the killing defect of MIF-deficient macrophages. Together, these data show that MIF is a key mediator of host responses against gram-negative bacteria, acting in part via a modulation of bacterial killing by macrophages.
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1. Species distribution modelling is used increasingly in both applied and theoretical research to predict how species are distributed and to understand attributes of species' environmental requirements. In species distribution modelling, various statistical methods are used that combine species occurrence data with environmental spatial data layers to predict the suitability of any site for that species. While the number of data sharing initiatives involving species' occurrences in the scientific community has increased dramatically over the past few years, various data quality and methodological concerns related to using these data for species distribution modelling have not been addressed adequately. 2. We evaluated how uncertainty in georeferences and associated locational error in occurrences influence species distribution modelling using two treatments: (1) a control treatment where models were calibrated with original, accurate data and (2) an error treatment where data were first degraded spatially to simulate locational error. To incorporate error into the coordinates, we moved each coordinate with a random number drawn from the normal distribution with a mean of zero and a standard deviation of 5 km. We evaluated the influence of error on the performance of 10 commonly used distributional modelling techniques applied to 40 species in four distinct geographical regions. 3. Locational error in occurrences reduced model performance in three of these regions; relatively accurate predictions of species distributions were possible for most species, even with degraded occurrences. Two species distribution modelling techniques, boosted regression trees and maximum entropy, were the best performing models in the face of locational errors. The results obtained with boosted regression trees were only slightly degraded by errors in location, and the results obtained with the maximum entropy approach were not affected by such errors. 4. Synthesis and applications. To use the vast array of occurrence data that exists currently for research and management relating to the geographical ranges of species, modellers need to know the influence of locational error on model quality and whether some modelling techniques are particularly robust to error. We show that certain modelling techniques are particularly robust to a moderate level of locational error and that useful predictions of species distributions can be made even when occurrence data include some error.
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The benefit of bevacizumab (Bv) has been shown in different tumors including colorectal cancer, renal cancer, pulmonary non-small cell cancer and also breast cancer. However to date, there is no established test evaluating the angiogenic status of a patient and monitoring the effects of anti-angiogenic treatments. Tumor angiogenesis is the result of a balance between multiple pro- and anti¬angiogenic molecules. There is very little published clinical data exploring the impact of the anti-angiogenic therapy on the different angiogenesis-related molecules and the potential role of these molecules as prognostic or predictive factors.
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AbstractBreast cancer is one of the most common cancers affecting one in eight women during their lives. Survival rates have increased steadily thanks to early diagnosis with mammography screening and more efficient treatment strategies. Post-operative radiation therapy is a standard of care in the management of breast cancer and has been shown to reduce efficiently both local recurrence rate and breast cancer mortality. Radiation therapy is however associated with some late effects for long-term survivors. Radiation-induced secondary cancer is a relatively rare but severe late effect of radiation therapy. Currently, radiotherapy plans are essentially optimized to maximize tumor control and minimize late deterministic effects (tissue reactions) that are mainly associated with high doses (» 1 Gy). With improved cure rates and new radiation therapy technologies, it is also important to evaluate and minimize secondary cancer risks for different treatment techniques. This is a particularly challenging task due to the large uncertainties in the dose-response relationship.In contrast with late deterministic effects, secondary cancers may be associated with much lower doses and therefore out-of-field doses (also called peripheral doses) that are typically inferior to 1 Gy need to be determined accurately. Out-of-field doses result from patient scatter and head scatter from the treatment unit. These doses are particularly challenging to compute and we characterized it by Monte Carlo (MC) calculation. A detailed MC model of the Siemens Primus linear accelerator has been thoroughly validated with measurements. We investigated the accuracy of such a model for retrospective dosimetry in epidemiological studies on secondary cancers. Considering that patients in such large studies could be treated on a variety of machines, we assessed the uncertainty in reconstructed peripheral dose due to the variability of peripheral dose among various linac geometries. For large open fields (> 10x10 cm2), the uncertainty would be less than 50%, but for small fields and wedged fields the uncertainty in reconstructed dose could rise up to a factor of 10. It was concluded that such a model could be used for conventional treatments using large open fields only.The MC model of the Siemens Primus linac was then used to compare out-of-field doses for different treatment techniques in a female whole-body CT-based phantom. Current techniques such as conformai wedged-based radiotherapy and hybrid IMRT were investigated and compared to older two-dimensional radiotherapy techniques. MC doses were also compared to those of a commercial Treatment Planning System (TPS). While the TPS is routinely used to determine the dose to the contralateral breast and the ipsilateral lung which are mostly out of the treatment fields, we have shown that these doses may be highly inaccurate depending on the treatment technique investigated. MC shows that hybrid IMRT is dosimetrically similar to three-dimensional wedge-based radiotherapy within the field, but offers substantially reduced doses to out-of-field healthy organs.Finally, many different approaches to risk estimations extracted from the literature were applied to the calculated MC dose distribution. Absolute risks varied substantially as did the ratio of risk between two treatment techniques, reflecting the large uncertainties involved with current risk models. Despite all these uncertainties, the hybrid IMRT investigated resulted in systematically lower cancer risks than any of the other treatment techniques. More epidemiological studies with accurate dosimetry are required in the future to construct robust risk models. In the meantime, any treatment strategy that reduces out-of-field doses to healthy organs should be investigated. Electron radiotherapy might offer interesting possibilities with this regard.RésuméLe cancer du sein affecte une femme sur huit au cours de sa vie. Grâce au dépistage précoce et à des thérapies de plus en plus efficaces, le taux de guérison a augmenté au cours du temps. La radiothérapie postopératoire joue un rôle important dans le traitement du cancer du sein en réduisant le taux de récidive et la mortalité. Malheureusement, la radiothérapie peut aussi induire des toxicités tardives chez les patients guéris. En particulier, les cancers secondaires radio-induits sont une complication rare mais sévère de la radiothérapie. En routine clinique, les plans de radiothérapie sont essentiellement optimisées pour un contrôle local le plus élevé possible tout en minimisant les réactions tissulaires tardives qui sont essentiellement associées avec des hautes doses (» 1 Gy). Toutefois, avec l'introduction de différentes nouvelles techniques et avec l'augmentation des taux de survie, il devient impératif d'évaluer et de minimiser les risques de cancer secondaire pour différentes techniques de traitement. Une telle évaluation du risque est une tâche ardue étant donné les nombreuses incertitudes liées à la relation dose-risque.Contrairement aux effets tissulaires, les cancers secondaires peuvent aussi être induits par des basses doses dans des organes qui se trouvent hors des champs d'irradiation. Ces organes reçoivent des doses périphériques typiquement inférieures à 1 Gy qui résultent du diffusé du patient et du diffusé de l'accélérateur. Ces doses sont difficiles à calculer précisément, mais les algorithmes Monte Carlo (MC) permettent de les estimer avec une bonne précision. Un modèle MC détaillé de l'accélérateur Primus de Siemens a été élaboré et validé avec des mesures. La précision de ce modèle a également été déterminée pour la reconstruction de dose en épidémiologie. Si on considère que les patients inclus dans de larges cohortes sont traités sur une variété de machines, l'incertitude dans la reconstruction de dose périphérique a été étudiée en fonction de la variabilité de la dose périphérique pour différents types d'accélérateurs. Pour de grands champs (> 10x10 cm ), l'incertitude est inférieure à 50%, mais pour de petits champs et des champs filtrés, l'incertitude de la dose peut monter jusqu'à un facteur 10. En conclusion, un tel modèle ne peut être utilisé que pour les traitements conventionnels utilisant des grands champs.Le modèle MC de l'accélérateur Primus a été utilisé ensuite pour déterminer la dose périphérique pour différentes techniques dans un fantôme corps entier basé sur des coupes CT d'une patiente. Les techniques actuelles utilisant des champs filtrés ou encore l'IMRT hybride ont été étudiées et comparées par rapport aux techniques plus anciennes. Les doses calculées par MC ont été comparées à celles obtenues d'un logiciel de planification commercial (TPS). Alors que le TPS est utilisé en routine pour déterminer la dose au sein contralatéral et au poumon ipsilatéral qui sont principalement hors des faisceaux, nous avons montré que ces doses peuvent être plus ou moins précises selon la technTque étudiée. Les calculs MC montrent que la technique IMRT est dosimétriquement équivalente à celle basée sur des champs filtrés à l'intérieur des champs de traitement, mais offre une réduction importante de la dose aux organes périphériques.Finalement différents modèles de risque ont été étudiés sur la base des distributions de dose calculées par MC. Les risques absolus et le rapport des risques entre deux techniques de traitement varient grandement, ce qui reflète les grandes incertitudes liées aux différents modèles de risque. Malgré ces incertitudes, on a pu montrer que la technique IMRT offrait une réduction du risque systématique par rapport aux autres techniques. En attendant des données épidémiologiques supplémentaires sur la relation dose-risque, toute technique offrant une réduction des doses périphériques aux organes sains mérite d'être étudiée. La radiothérapie avec des électrons offre à ce titre des possibilités intéressantes.
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Seven young men spent three nights and 2 d in a respiration chamber where their rates of energy expenditure and substrate oxidation were continuously measured by indirect calorimetry. During the first 24 h they ingested a mixed maintenance diet containing 35% of calories as fat. An additional amount of 106 +/- 6 g fat/24 h (means +/- SD) was added to this diet during the following 36 h. The fat supplement (987 +/- 55 kcal/d) did not alter 24-h energy expenditure (2783 +/- 232 vs 2820 +/- 284 kcal/d) and failed to promote the use of fat as a metabolic fuel (fat oxidation 1032 +/- 205 vs 1042 +/- 205 kcal/d). The overall energy balance was closely correlated with the fat balance (r = 0.96, p less than 0.001) but not with the carbohydrate balance (r = -0.12, NS). These data indicate that substantial imbalances between intake and oxidation are much more likely for fat than for carbohydrate.
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This paper studies optimal monetary policy in a framework that explicitly accounts for policymakers' uncertainty about the channels of transmission of oil prices into the economy. More specfically, I examine the robust response to the real price of oil that US monetary authorities would have been recommended to implement in the period 1970 2009; had they used the approach proposed by Cogley and Sargent (2005b) to incorporate model uncertainty and learning into policy decisions. In this context, I investigate the extent to which regulator' changing beliefs over different models of the economy play a role in the policy selection process. The main conclusion of this work is that, in the specific environment under analysis, one of the underlying models dominates the optimal interest rate response to oil prices. This result persists even when alternative assumptions on the model's priors change the pattern of the relative posterior probabilities, and can thus be attributed to the presence of model uncertainty itself.