167 resultados para independent sets

em Université de Lausanne, Switzerland


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Anti-basal ganglia antibodies (ABGAs) have been suggested to be a hallmark of autoimmunity in Gilles de la Tourette's syndrome (GTS), possibly related to prior exposure to streptococcal infection. In order to detect whether the presence of ABGAs was associated with subtle structural changes in GTS, whole-brain analysis using independent sets of T(1) and diffusion tensor imaging MRI-based methods were performed on 22 adults with GTS with (n = 9) and without (n = 13) detectable ABGAs in the serum. Voxel-based morphometry analysis failed to detect any significant difference in grey matter density between ABGA-positive and ABGA-negative groups in caudate nuclei, putamina, thalami and frontal lobes. These results suggest that ABGA synthesis is not related to structural changes in grey and white matter (detectable with these methods) within frontostriatal circuits.

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Galton (1907) first demonstrated the "wisdom of crowds" phenomenon by averaging independent estimates of unknown quantities given by many individuals. Herzog and Hertwig (2009; hereafter H&H in Psychological Science) showed that individuals' own estimates can be improved by asking them to make two estimates at separate times and averaging them. H&H claimed to observe far greater improvement in accuracy when participants received "dialectical" instructions to consider why their first estimate might be wrong before making their second estimates than when they received standard instructions. We reanalyzed H&H's data using measures of accuracy that are unrelated to the frequency of identical first and second responses and found that participants in both conditions improved their accuracy to an equal degree.

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Waveform tomographic imaging of crosshole georadar data is a powerful method to investigate the shallow subsurface because of its ability to provide images of pertinent petrophysical parameters with extremely high spatial resolution. All current crosshole georadar waveform inversion strategies are based on the assumption of frequency-independent electromagnetic constitutive parameters. However, in reality, these parameters are known to be frequency-dependent and complex and thus recorded georadar data may show significant dispersive behavior. In this paper, we evaluate synthetically the reconstruction limits of a recently published crosshole georadar waveform inversion scheme in the presence of varying degrees of dielectric dispersion. Our results indicate that, when combined with a source wavelet estimation procedure that provides a means of partially accounting for the frequency-dependent effects through an "effective" wavelet, the inversion algorithm performs remarkably well in weakly to moderately dispersive environments and has the ability to provide adequate tomographic reconstructions.

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Introduction: As part of the MicroArray Quality Control (MAQC)-II project, this analysis examines how the choice of univariate feature-selection methods and classification algorithms may influence the performance of genomic predictors under varying degrees of prediction difficulty represented by three clinically relevant endpoints. Methods: We used gene-expression data from 230 breast cancers (grouped into training and independent validation sets), and we examined 40 predictors (five univariate feature-selection methods combined with eight different classifiers) for each of the three endpoints. Their classification performance was estimated on the training set by using two different resampling methods and compared with the accuracy observed in the independent validation set. Results: A ranking of the three classification problems was obtained, and the performance of 120 models was estimated and assessed on an independent validation set. The bootstrapping estimates were closer to the validation performance than were the cross-validation estimates. The required sample size for each endpoint was estimated, and both gene-level and pathway-level analyses were performed on the obtained models. Conclusions: We showed that genomic predictor accuracy is determined largely by an interplay between sample size and classification difficulty. Variations on univariate feature-selection methods and choice of classification algorithm have only a modest impact on predictor performance, and several statistically equally good predictors can be developed for any given classification problem.

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Ductal growth of the mammary gland occurs in two distinct stages. The first round of branching morphogenesis occurs during embryogenesis, and the second round commences at the onset of puberty. Currently, relatively little is known about the genetic networks that control the initial phases of ductal expansion, which, unlike pubertal development, proceeds independent of hormonal input in female mice. Here we identify NF-κB downstream of the TNF-like ligand ectodysplasin (Eda) as a unique regulator of embryonic and prepubertal ductal morphogenesis. Loss of Eda, or inhibition of NF-κB, led to smaller ductal trees with fewer branches. On the other hand, overexpression of Eda caused a dramatic NF-κB-dependent phenotype in both female and male mice characterized by precocious and highly increased ductal growth and branching that correlated with enhanced cell proliferation. We have identified several putative transcriptional target genes of Eda/NF-κB, including PTHrP, Wnt10a, and Wnt10b, as well as Egf family ligands amphiregulin and epigen. We developed a mammary bud culture system that allowed us to manipulate mammary development ex vivo and found that recombinant PTHrP, Wnt3A, and Egf family ligands stimulate embryonic branching morphogenesis, suggesting that these pathways may cooperatively mediate the effects of Eda.

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Microsatellite instability (MSI) occurs in 10-20% of colorectal tumours and is associated with good prognosis. Here we describe the development and validation of a genomic signature that identifies colorectal cancer patients with MSI caused by DNA mismatch repair deficiency with high accuracy. Microsatellite status for 276 stage II and III colorectal tumours has been determined. Full-genome expression data was used to identify genes that correlate with MSI status. A subset of these samples (n = 73) had sequencing data for 615 genes available. An MSI gene signature of 64 genes was developed and validated in two independent validation sets: the first consisting of frozen samples from 132 stage II patients; and the second consisting of FFPE samples from the PETACC-3 trial (n = 625). The 64-gene MSI signature identified MSI patients in the first validation set with a sensitivity of 90.3% and an overall accuracy of 84.8%, with an AUC of 0.942 (95% CI, 0.888-0.975). In the second validation, the signature also showed excellent performance, with a sensitivity 94.3% and an overall accuracy of 90.6%, with an AUC of 0.965 (95% CI, 0.943-0.988). Besides correct identification of MSI patients, the gene signature identified a group of MSI-like patients that were MSS by standard assessment but MSI by signature assessment. The MSI-signature could be linked to a deficient MMR phenotype, as both MSI and MSI-like patients showed a high mutation frequency (8.2% and 6.4% of 615 genes assayed, respectively) as compared to patients classified as MSS (1.6% mutation frequency). The MSI signature showed prognostic power in stage II patients (n = 215) with a hazard ratio of 0.252 (p = 0.0145). Patients with an MSI-like phenotype had also an improved survival when compared to MSS patients. The MSI signature was translated to a diagnostic microarray and technically and clinically validated in FFPE and frozen samples.

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To compare the impact of meeting specific classification criteria [modified New York (mNY), European Spondyloarthropathy Study Group (ESSG), and Assessment of SpondyloArthritis international Society (ASAS) criteria] on anti-tumor necrosis factor (anti-TNF) drug retention, and to determine predictive factors of better drug survival. All patients fulfilling the ESSG criteria for axial spondyloarthritis (SpA) with available data on the axial ASAS and mNY criteria, and who had received at least one anti-TNF treatment were retrospectively retrieved in a single academic institution in Switzerland. Drug retention was computed using survival analysis (Kaplan-Meier), adjusted for potential confounders. Of the 137 patients classified as having axial SpA using the ESSG criteria, 112 also met the ASAS axial SpA criteria, and 77 fulfilled the mNY criteria. Drug retention rates at 12 and 24 months for the first biologic therapy were not significantly different between the diagnostic groups. Only the small ASAS non-classified axial SpA group (25 patients) showed a nonsignificant trend toward shorter drug survival. Elevated CRP level, but not the presence of bone marrow edema on magnetic resonance imaging (MRI) scans, was associated with significantly better drug retention (OR 7.9, ICR 4-14). In this cohort, anti-TNF drug survival was independent of the classification criteria. Elevated CRP level, but not positive MRI, was associated with better drug retention.

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Dendritic cells (DCs) are professional APCs that have a role in the initiation of adaptive immune responses and tolerance. Among the tolerogenic mechanisms, the expression of the enzyme IDO1 represents an effective tool to generate T regulatory cells. In humans, different DC subsets express IDO1, but less is known about the IDO1-related enzyme IDO2. In this study, we found a different pattern of expression and regulation between IDO1 and IDO2 in human circulating DCs. At the protein level, IDO1 is expressed only in circulating myeloid DCs (mDCs) and is modulated by PGE2, whereas IDO2 is expressed in both mDCs and plasmacytoid DCs and is not modulated by PGE2. In healthy subjects, IDO1 expression requires the presence of PGE2 and needs continuous transcription and translation, whereas IDO2 expression is constitutive, independent from suppressor of cytokine signaling 3 activity. Conversely, in patients suffering from inflammatory arthritis, circulating DCs express both IDO1 and IDO2. At the functional level, both mDCs and plasmacytoid DCs generate T regulatory cells through an IDO1/IDO2-dependent mechanism. We conclude that, in humans, whereas IDO1 provides an additional mechanism of tolerance induced by proinflammatory mediators, IDO2 is stably expressed in steady-state conditions and may contribute to the homeostatic tolerogenic capacity of DCs.

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The investigation of perceptual and cognitive functions with non-invasive brain imaging methods critically depends on the careful selection of stimuli for use in experiments. For example, it must be verified that any observed effects follow from the parameter of interest (e.g. semantic category) rather than other low-level physical features (e.g. luminance, or spectral properties). Otherwise, interpretation of results is confounded. Often, researchers circumvent this issue by including additional control conditions or tasks, both of which are flawed and also prolong experiments. Here, we present some new approaches for controlling classes of stimuli intended for use in cognitive neuroscience, however these methods can be readily extrapolated to other applications and stimulus modalities. Our approach is comprised of two levels. The first level aims at equalizing individual stimuli in terms of their mean luminance. Each data point in the stimulus is adjusted to a standardized value based on a standard value across the stimulus battery. The second level analyzes two populations of stimuli along their spectral properties (i.e. spatial frequency) using a dissimilarity metric that equals the root mean square of the distance between two populations of objects as a function of spatial frequency along x- and y-dimensions of the image. Randomized permutations are used to obtain a minimal value between the populations to minimize, in a completely data-driven manner, the spectral differences between image sets. While another paper in this issue applies these methods in the case of acoustic stimuli (Aeschlimann et al., Brain Topogr 2008), we illustrate this approach here in detail for complex visual stimuli.

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We have previously demonstrated that the bZIP transcription factor CREB-2, also called ATF-4, trans-activates, in association with the viral protein Tax, the human T-cell leukemia virus type I (HTLV-I) promoter. In this study, we have examined whether CREB-2 acetylation affects transcriptional activation mediated by Tax. We present evidence that CREB-2 is acetylated in vitro and in vivo. CREB-2 is acetylated in two regions: the basic domain of the bZIP (from amino acid residue 270 to 300) and the short basic domain (from 342 to 351) located downstream from the bZIP. We also demonstrate that CREB-2 is acetylated by p300/CBP but not by p/CAF. Moreover, replacement of lysine by arginine in the basic domains decreases the trans-activating capacity of CREB-2. However, in the presence of Tax, the HTLV-I transcription remains fully activated by these CREB-2 mutants. Although we cannot totally exclude that the mutations could also affect CREB-2 structure and activity independent of acetylation, our results suggest that activation of the viral promoter in the presence of Tax is independent of the CREB-2 acetylation.

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NKT cells, defined as T cells expressing the NK cell marker NK1.1, are involved in tumor rejection and regulation of autoimmunity via the production of cytokines. We show in this study that two types of NKT cells can be defined on the basis of their reactivity to the monomorphic MHC class I-like molecule CD1d. One type of NKT cell is positively selected by CD1d and expresses a biased TCR repertoire together with a phenotype found on activated T cells. A second type of NKT cell, in contrast, develops in the absence of CD1d, and expresses a diverse TCR repertoire and a phenotype found on naive T cells and NK cells. Importantly, the two types of NKT cells segregate in distinct tissues. Whereas thymus and liver contain primarily CD1d-dependent NKT cells, spleen and bone marrow are enriched in CD1d-independent NKT cells. Collectively, our data suggest that recognition of tissue-specific ligands by the TCR controls localization and activation of NKT cells.

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Background Individual signs and symptoms are of limited value for the diagnosis of influenza. Objective To develop a decision tree for the diagnosis of influenza based on a classification and regression tree (CART) analysis. Methods Data from two previous similar cohort studies were assembled into a single dataset. The data were randomly divided into a development set (70%) and a validation set (30%). We used CART analysis to develop three models that maximize the number of patients who do not require diagnostic testing prior to treatment decisions. The validation set was used to evaluate overfitting of the model to the training set. Results Model 1 has seven terminal nodes based on temperature, the onset of symptoms and the presence of chills, cough and myalgia. Model 2 was a simpler tree with only two splits based on temperature and the presence of chills. Model 3 was developed with temperature as a dichotomous variable (≥38°C) and had only two splits based on the presence of fever and myalgia. The area under the receiver operating characteristic curves (AUROCC) for the development and validation sets, respectively, were 0.82 and 0.80 for Model 1, 0.75 and 0.76 for Model 2 and 0.76 and 0.77 for Model 3. Model 2 classified 67% of patients in the validation group into a high- or low-risk group compared with only 38% for Model 1 and 54% for Model 3. Conclusions A simple decision tree (Model 2) classified two-thirds of patients as low or high risk and had an AUROCC of 0.76. After further validation in an independent population, this CART model could support clinical decision making regarding influenza, with low-risk patients requiring no further evaluation for influenza and high-risk patients being candidates for empiric symptomatic or drug therapy.

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We have prepared transgenic mice whose T cells constitutively express a chimeric receptor combining extracellular human IL-4R and intracellular IL-2Rbeta segments. This receptor can transmit IL-2/IL-15-like signals in response to human, but not mouse, IL-4. We used these animals to explore to what extent functional IL-2R/IL-15R expression controls the capacity of T cells to proliferate in response to IL-2/IL-15-like signals. After activation with Con A, naive transgenic CD8+ and CD4+ T cells respond to human IL-4 as well as to IL-2. Without prior activation, they failed to proliferate in response to human IL-4, although human IL-4 did prolong their survival. Thus, IL-2-induced proliferation of activated T cells requires at least one other Ag-induced change apart from the induction of a functional IL-2R. However, a fraction of CD8+CD44high T cells proliferate in human IL-4 without antigenic stimulation or syngeneic feeder cells. In contrast, CD4+CD44high T cells are not constitutively responsive to human IL-4. We conclude that although all transgenic T cells express a functional chimeric receptor, only some CD8+CD44high T cells contain all molecules required for entry into the cell cycle in response to human IL-4 or IL-15.

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AIM: The clinical relevance of sentinel lymph node (SLN) analysis was evaluated prospectively and compared with other known risk factors of relapse in early stage melanoma. METHODS: Surgery was guided by lymphoscintigraphy, blue dye and gamma probe detection. SLN were analysed by haematoxylin eosin (HE) histochemistry and multimarker immunohistochemistry (IHC). Disease free survival (DFS) was evaluated with Kaplan-Meier plots according to different parameters and Cox analyses of variance. RESULTS: From 210 patients a total of 381 SLN were excised. Lymphoscintigraphy identified all excised SLN with only 2 false positive lymphatic lakes. Fifty patients (24%) had tumour positive SLN. With a mean follow-up of 31.3 months, 29 tumour recurrences were observed, 19 (38%) in 50 SLN positive and 10 (6%) in 160 SLN negative patients. Strong predictive factors for early relapse (p < 0.0005) were SLN positivity and a high Breslow index. CONCLUSION: SLN tumour positivity is an independent factor of high risk for early relapse with a higher power of discrimination than the Breslow index.

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Mammary carcinomas developing in SV40 transgenic WAP-T mice arise in two distinct histological phenotypes: as differentiated low-grade and undifferentiated high-grade tumors. We integrated different types of information such as histological grading, analysis of aCGH-based gene copy number and gene expression profiling to provide a comprehensive molecular description of mammary tumors in WAP-T mice. Applying a novel procedure for the correlation of gene copy number with gene expression on a global scale, we observed in tumor samples a global coherence between genotype and transcription. This coherence can be interpreted as a matched transcriptional regulation inherited from the cells of tumor origin and determined by the activity of cancer driver genes. Despite common recurrent genomic aberrations, e.g. gain of chr. 15 in most WAP-T tumors, loss of chr. 19 frequently occurs only in low-grade tumors. These tumors show features of "basal-like" epithelial differentiation, particularly expression of keratin 14. The high-grade tumors are clearly separated from the low-grade tumors by strong expression of the Met gene and by coexpression of epithelial (e.g. keratin 18) and mesenchymal (e.g. vimentin) markers. In high-grade tumors, the expression of the nonmutated Met protein is associated with Met-locus amplification and Met activity. The role of Met as a cancer driver gene is supported by the contribution of active Met signaling to motility and growth of mammary tumor-derived cells. Finally, we discuss the independent origin of low- and high-grade tumors from distinct cells of tumor origin, possibly luminal progenitors, distinguished by Met gene expression and Met signaling.