968 resultados para Reflect Array


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Objective:The most difficult thyroid tumors to be diagnosed by cytology and histology are conventional follicular carcinomas (cFTCs) and oncocytic follicular carcinomas (oFTCs). Several microRNAs (miRNAs) have been previously found to be consistently deregulated in papillary thyroid carcinomas; however, very limited information is available for cFTC and oFTC. The aim of this study was to explore miRNA deregulation and find candidate miRNA markers for follicular carcinomas that can be used diagnostically.Design:Thirty-eight follicular thyroid carcinomas (21 cFTCs, 17 oFTCs) and 10 normal thyroid tissue samples were studied for expression of 381 miRNAs using human microarray assays. Expression of deregulated miRNAs was confirmed by individual RT-PCR assays in all samples. In addition, 11 follicular adenomas, two hyperplastic nodules (HNs), and 19 fine-needle aspiration samples were studied for expression of novel miRNA markers detected in this study.Results:The unsupervised hierarchical clustering analysis demonstrated individual clusters for cFTC and oFTC, indicating the difference in miRNA expression between these tumor types. Both cFTCs and oFTCs showed an up-regulation of miR-182/-183/-221/-222/-125a-3p and a down-regulation of miR-542-5p/-574-3p/-455/-199a. Novel miRNA (miR-885-5p) was found to be strongly up-regulated (>40-fold) in oFTCs but not in cFTCs, follicular adenomas, and HNs. The classification and regression tree algorithm applied to fine-needle aspiration samples demonstrated that three dysregulated miRNAs (miR-885-5p/-221/-574-3p) allowed distinguishing follicular thyroid carcinomas from benign HNs with high accuracy.Conclusions:In this study we demonstrate that different histopathological types of follicular thyroid carcinomas have distinct miRNA expression profiles. MiR-885-5p is highly up-regulated in oncocytic follicular carcinomas and may serve as a diagnostic marker for these tumors. A small set of deregulated miRNAs allows for an accurate discrimination between follicular carcinomas and hyperplastic nodules and can be used diagnostically in fine-needle aspiration biopsies.

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Certain magnetic resonance (MR) enhancement patterns are often considered to be associated with a specific diagnosis but experience shows that this association is not always consistent. Therefore, it is not clear how reliably contrast enhancement patterns correlate with specific tissue changes. We investigated the detailed histomorphologic findings of intracranial lesions in relation to Gadodiamide contrast enhancement in 55 lesions from 55 patients, nine cats, and 46 dogs. Lesions were divided into areas according to their contrast enhancement; therefore 81 areas resulted from the 55 lesions which were directly compared with histopathology. In 40 of 55 lesions (73%), the histomorphologic features explained the contrast enhancement pattern. In particular, vascular proliferation and dilated vessels occurred significantly more often in areas with enhancement than in areas without enhancement (P = 0.044). In 15 lesions, there was no association between MR images and histologic findings. In particular, contrast enhancement was found within necrotic areas (10 areas) and ring enhancement was seen in lesions without central necrosis (five lesions). These findings imply that necrosis cannot be differentiated reliably from viable tissue based on postcontrast images. Diffusion of contrast medium within lesions and time delays after contrast medium administration probably play important roles in the presence and patterns of contrast enhancement. Thus, histologic features of lesions cannot be predicted solely by contrast enhancement patterns.

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REASONS FOR PERFORMING STUDY: Sarcoids are nonmetastasising, yet locally aggressive skin tumours that constitute the most frequent neoplasm in equids. Infection by bovine papillomaviruses types 1 and 2 (BPV-1, BPV-2) has been recognised as major causative factor in sarcoid pathogenesis, but a possible correlation of intralesional virus load with disease severity has not been established thus far. HYPOTHESIS: Given the pathogenic role of BPV-1 and BPV-2 in sarcoid disease, we suggest that intralesional viral DNA concentration may reflect the degree of affection. METHODS: Severity of disease was addressed by recording the tumour growth kinetics, lesion number and tumour type for 37 sarcoid-bearing horses and one donkey. Viral load was estimated via quantitative real-time PCR (qPCR) of the E2, E5, L1 and L2 genes from the BPV-1/-2 genome for one randomly selected lesion per horse and correlated with disease severity. RESULTS: Quantitative PCR against E2 identified viral DNA concentrations ranging from 0-556 copies/tumour cell. Of 16 horses affected by quiescent, slowly growing single tumours or multiple mild-type lesions, 15 showed a viral load up to 1.4 copies per cell. In stark contrast, all equids (22/22) bearing rapidly growing and/or multiple aggressive sarcoids had a viral load between 3 and 569 copies per cell. Consistent results were obtained with qPCR against E5, L1 and L2. CONCLUSIONS: While tumours of the same clinical type carried variable virus load, confirming that viral titre does not determine clinical appearance, we identified a highly significant correlation between intralesional viral load and disease severity. POTENTIAL RELEVANCE: The rapid determination of BPV viral load will give a reliable marker for disease severity and may also be considered when establishing a therapeutic strategy.

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Little is known about the neurobiology of hypokinesia in schizophrenia. Therefore, the aim of this study was to investigate alterations of white matter motor pathways in schizophrenia and to relate our findings to objectively measured motor activity. We examined 21 schizophrenia patients and 21 healthy controls using diffusion tensor imaging and actigraphy. We applied a probabilistic fibre tracking approach to investigate pathways connecting the dorsolateral prefrontal cortex (dlPFC), the rostral anterior cingulate cortex (rACC), the pre-supplementary motor area (pre-SMA), the supplementary motor area proper (SMA-proper), the primary motor cortex (M1), the caudate nucleus, the striatum, the pallidum and the thalamus. Schizophrenia patients had lower activity levels than controls. In schizophrenia we found higher probability indices forming part of a bundle of interest (PIBI) in pathways connecting rACC, pre-SMA and SMA-proper as well as in pathways connecting M1 and pre-SMA with caudate nucleus, putamen, pallidum and thalamus and a reduced spatial extension of motor pathways in schizophrenia. There was a positive correlation between PIBI and activity level in the right pre-SMA-pallidum and the left M1-thalamus connection in healthy controls, and in the left pre-SMA-SMA-proper pathway in schizophrenia. Our results point to reduced volitional motor activity and altered motor pathway organisation in schizophrenia. The identified associations between the amount of movement and structural connectivity of motor pathways suggest dysfunction of cortico-basal ganglia pathways in the pathophysiology of hypokinesia in schizophrenia. Schizophrenia patients may use cortical pathways involving the supplementary motor area to compensate for basal ganglia dysfunction.

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Childhood adrenocortical tumors (ACT) are rare malignancies, except in southern Brazil, where a higher incidence rate is associated to a high frequency of the founder R337H TP53 mutation. To date, copy number alterations in these tumors have only been analyzed by low-resolution comparative genomic hybridization.

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Motivation: Array CGH technologies enable the simultaneous measurement of DNA copy number for thousands of sites on a genome. We developed the circular binary segmentation (CBS) algorithm to divide the genome into regions of equal copy number (Olshen {\it et~al}, 2004). The algorithm tests for change-points using a maximal $t$-statistic with a permutation reference distribution to obtain the corresponding $p$-value. The number of computations required for the maximal test statistic is $O(N^2),$ where $N$ is the number of markers. This makes the full permutation approach computationally prohibitive for the newer arrays that contain tens of thousands markers and highlights the need for a faster. algorithm. Results: We present a hybrid approach to obtain the $p$-value of the test statistic in linear time. We also introduce a rule for stopping early when there is strong evidence for the presence of a change. We show through simulations that the hybrid approach provides a substantial gain in speed with only a negligible loss in accuracy and that the stopping rule further increases speed. We also present the analysis of array CGH data from a breast cancer cell line to show the impact of the new approaches on the analysis of real data. Availability: An R (R Development Core Team, 2006) version of the CBS algorithm has been implemented in the ``DNAcopy'' package of the Bioconductor project (Gentleman {\it et~al}, 2004). The proposed hybrid method for the $p$-value is available in version 1.2.1 or higher and the stopping rule for declaring a change early is available in version 1.5.1 or higher.

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As a noninvasive method, exhaled breath condensate (EBC) has gained importance to improve monitoring of lung diseases and to detect biomarkers. The aim of the study was to investigate, whether erythropoietin (EPO) is detectable in EBC. EBC was collected from 22 consecutive patients as well as from healthy individuals. Using a multiplex fluorescent bead immunoassay, we detected EPO in EBC, as well as tumour necrosis factor-alpha (TNF-alpha) in 13 out of 22 patients simultaneously (EPO 0.21 +/- 0.03 in U/mL and TNF-alpha 34.6 +/- 4.2 in pg/mL, mean +/- SEM). No significant differences for EPO levels or correlation between EPO and TNF-alpha were found but TNF-alpha was significantly higher in patients with chronic obstructive pulmonary disease (COPD) than in non-COPD (obstructive sleep apnoea, OSA, and lung healthy patients). This is the first report of detection of EPO in EBC. Due to the small study size more data is needed to clarify the role of EPO in EBC.

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Genomic alterations have been linked to the development and progression of cancer. The technique of Comparative Genomic Hybridization (CGH) yields data consisting of fluorescence intensity ratios of test and reference DNA samples. The intensity ratios provide information about the number of copies in DNA. Practical issues such as the contamination of tumor cells in tissue specimens and normalization errors necessitate the use of statistics for learning about the genomic alterations from array-CGH data. As increasing amounts of array CGH data become available, there is a growing need for automated algorithms for characterizing genomic profiles. Specifically, there is a need for algorithms that can identify gains and losses in the number of copies based on statistical considerations, rather than merely detect trends in the data. We adopt a Bayesian approach, relying on the hidden Markov model to account for the inherent dependence in the intensity ratios. Posterior inferences are made about gains and losses in copy number. Localized amplifications (associated with oncogene mutations) and deletions (associated with mutations of tumor suppressors) are identified using posterior probabilities. Global trends such as extended regions of altered copy number are detected. Since the posterior distribution is analytically intractable, we implement a Metropolis-within-Gibbs algorithm for efficient simulation-based inference. Publicly available data on pancreatic adenocarcinoma, glioblastoma multiforme and breast cancer are analyzed, and comparisons are made with some widely-used algorithms to illustrate the reliability and success of the technique.

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DNA sequence copy number has been shown to be associated with cancer development and progression. Array-based Comparative Genomic Hybridization (aCGH) is a recent development that seeks to identify the copy number ratio at large numbers of markers across the genome. Due to experimental and biological variations across chromosomes and across hybridizations, current methods are limited to analyses of single chromosomes. We propose a more powerful approach that borrows strength across chromosomes and across hybridizations. We assume a Gaussian mixture model, with a hidden Markov dependence structure, and with random effects to allow for intertumoral variation, as well as intratumoral clonal variation. For ease of computation, we base estimation on a pseudolikelihood function. The method produces quantitative assessments of the likelihood of genetic alterations at each clone, along with a graphical display for simple visual interpretation. We assess the characteristics of the method through simulation studies and through analysis of a brain tumor aCGH data set. We show that the pseudolikelihood approach is superior to existing methods both in detecting small regions of copy number alteration and in accurately classifying regions of change when intratumoral clonal variation is present.

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In most microarray technologies, a number of critical steps are required to convert raw intensity measurements into the data relied upon by data analysts, biologists and clinicians. These data manipulations, referred to as preprocessing, can influence the quality of the ultimate measurements. In the last few years, the high-throughput measurement of gene expression is the most popular application of microarray technology. For this application, various groups have demonstrated that the use of modern statistical methodology can substantially improve accuracy and precision of gene expression measurements, relative to ad-hoc procedures introduced by designers and manufacturers of the technology. Currently, other applications of microarrays are becoming more and more popular. In this paper we describe a preprocessing methodology for a technology designed for the identification of DNA sequence variants in specific genes or regions of the human genome that are associated with phenotypes of interest such as disease. In particular we describe methodology useful for preprocessing Affymetrix SNP chips and obtaining genotype calls with the preprocessed data. We demonstrate how our procedure improves existing approaches using data from three relatively large studies including one in which large number independent calls are available. Software implementing these ideas are avialble from the Bioconductor oligo package.