966 resultados para Climate Leaf Analysis Multivariate Program (CLAMP)


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The use of bone mineral density (BMD) for fracture discrimination may be improved by considering bone microarchitecture. Texture parameters such as trabecular bone score (TBS) or mean Hurst parameter (H) could help to find women who are at high risk of fracture in the non-osteoporotic group. The purpose of this study was to combine BMD and microarchitectural texture parameters (spine TBS and calcaneus H) for the detection of osteoporotic fractures. Two hundred and fifty five women had a lumbar spine (LS), total hip (TH), and femoral neck (FN) DXA. Additionally, texture analyses were performed with TBS on spine DXA and with H on calcaneus radiographs. Seventy-nine women had prevalent fragility fractures. The association with fracture was evaluated by multivariate logistic regressions. The diagnostic value of each parameter alone and together was evaluated by odds ratios (OR). The area under curve (AUC) of the receiver operating characteristics (ROC) were assessed in models including BMD, H, and TBS. Women were also classified above and under the lowest tertile of H or TBS according to their BMD status. Women with prevalent fracture were older and had lower TBS, H, LS-BMD, and TH-BMD than women without fracture. Age-adjusted ORs were 1.66, 1.70, and 1.93 for LS, FN, and TH-BMD, respectively. Both TBS and H remained significantly associated with fracture after adjustment for age and TH-BMD: OR 2.07 [1.43; 3.05] and 1.47 [1.04; 2.11], respectively. The addition of texture parameters in the multivariate models didn't show a significant improvement of the ROC-AUC. However, women with normal or osteopenic BMD in the lowest range of TBS or H had significantly more fractures than women above the TBS or the H threshold. We have shown the potential interest of texture parameters such as TBS and H in addition to BMD to discriminate patients with or without osteoporotic fractures. However, their clinical added values should be evaluated relative to other risk factors.

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Background: Cells have the ability to respond and adapt to environmental changes through activation of stress-activated protein kinases (SAPKs). Although p38 SAPK signalling is known to participate in the regulation of gene expression little is known on the molecular mechanisms used by this SAPK to regulate stress-responsive genes and the overall set of genes regulated by p38 in response to different stimuli.Results: Here, we report a whole genome expression analyses on mouse embryonic fibroblasts (MEFs) treated with three different p38 SAPK activating-stimuli, namely osmostress, the cytokine TNFα and the protein synthesis inhibitor anisomycin. We have found that the activation kinetics of p38α SAPK in response to these insults is different and also leads to a complex gene pattern response specific for a given stress with a restricted set of overlapping genes. In addition, we have analysed the contribution of p38α the major p38 family member present in MEFs, to the overall stress-induced transcriptional response by using both a chemical inhibitor (SB203580) and p38α deficient (p38α-/-) MEFs. We show here that p38 SAPK dependency ranged between 60% and 88% depending on the treatments and that there is a very good overlap between the inhibitor treatment and the ko cells. Furthermore, we have found that the dependency of SAPK varies depending on the time the cells are subjected to osmostress. Conclusions: Our genome-wide transcriptional analyses shows a selective response to specific stimuli and a restricted common response of up to 20% of the stress up-regulated early genes that involves an important set of transcription factors, which might be critical for either cell adaptation or preparation for continuous extra-cellular changes. Interestingly, up to 85% of the up-regulated genes are under the transcriptional control of p38 SAPK. Thus, activation of p38 SAPK is critical to elicit the early gene expression program required for cell adaptation to stress.

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Background Following the discovery that mutant KRAS is associated with resistance to anti-epidermal growth factor receptor (EGFR) antibodies, the tumours of patients with metastatic colorectal cancer are now profiled for seven KRAS mutations before receiving cetuximab or panitumumab. However, most patients with KRAS wild-type tumours still do not respond. We studied the effect of other downstream mutations on the efficacy of cetuximab in, to our knowledge, the largest cohort to date of patients with chemotherapy-refractory metastatic colorectal cancer treated with cetuximab plus chemotherapy in the pre-KRAS selection era. Methods 1022 tumour DNA samples (73 from fresh-frozen and 949 from formalin-fixed, paraffin-embedded tissue) from patients treated with cetuximab between 2001 and 2008 were gathered from 11 centres in seven European countries. 773 primary tumour samples had sufficient quality DNA and were included in mutation frequency analyses; mass spectrometry genotyping of tumour samples for KRAS, BRAF, NRAS, and PIK3CA was done centrally. We analysed objective response, progression-free survival (PFS), and overall survival in molecularly defined subgroups of the 649 chemotherapy-refractory patients treated with cetuximab plus chemotherapy. Findings 40.0% (299/747) of the tumours harboured a KRAS mutation, 14.5% (108/743) harboured a PIK3CA mutation (of which 68.5% [74/108] were located in exon 9 and 20.4% [22/108] in exon 20), 4.7% (36/761) harboured a BRAF mutation, and 2.6% (17/644) harboured an NRAS mutation. KRAS mutants did not derive benefit compared with wild types, with a response rate of 6.7% (17/253) versus 35.8% (126/352; odds ratio [OR] 0.13, 95% CI 0.07-0.22; p<0.0001), a median PFS of 12. weeks versus 24 weeks (hazard ratio [HR] 1 98, 1.66-2.36; p<0.0001), and a median overall survival of 32 weeks versus 50 weeks (1.75, 1.47-2.09; p<0.0001). In KRAS wild types, carriers of BRAF and NRAS mutations had a significantly lower response rate than did BRAF and NRAS wild types, with a response rate of 8.3% (2/24) in carriers of BRAF mutations versus 38.0% in BRAF wild types (124/326; OR 0.15, 95% CI 0.02-0.51; p=0.0012); and 7.7% (1/13) in carriers of NRAS mutations versus 38.1% in NRAS wild types (110/289; OR 0.14, 0.007-0.70; p=0.013). PIK3CA exon 9 mutations had no effect, whereas exon 20 mutations were associated with a worse outcome compared with wild types, with a response rate of 0.0% (0/9) versus 36.8% (121/329; OR 0.00,0.00-0.89; p=0.029), a median PFS of 11.5 weeks versus 24 weeks (HR 2.52, 1.33-4.78; p=0.013), and a median overall survival of 34 weeks versus 51 weeks (3.29, 1.60-6.74; p=0.0057). Multivariate analysis and conditional inference trees confirmed that, if KRAS is not mutated, assessing BRAF, NRAS, and PIK3CA exon 20 mutations (in that order) gives additional information about outcome. Objective response rates in our series were 24.4% in the unselected population, 36.3% in the KRAS wild-type selected population, and 41.2% in the KRAS, BRAF, NRAS, and PIK3CA exon 20 wild-type population. Interpretation While confirming the negative effect of KRAS mutations on outcome after cetuximab, we show that BRAF, NRAS, and PIK3CA,exon 20 mutations are significantly associated with a low response rate. Objective response rates could be improved by additional genotyping of BRAF, NRAS, and PIK3CA exon 20 mutations in a KRAS wild-type population.

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Morphological descriptors are practical and essential biomarkers for diagnosis andtreatment selection for intracranial aneurysm management according to the current guidelinesin use. Nevertheless, relatively little work has been dedicated to improve the three-dimensionalquanti cation of aneurysmal morphology, automate the analysis, and hence reduce the inherentintra- and inter-observer variability of manual analysis. In this paper we propose a methodologyfor the automated isolation and morphological quanti cation of saccular intracranial aneurysmsbased on a 3D representation of the vascular anatomy.

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We study the minimum mean square error (MMSE) and the multiuser efficiency η of large dynamic multiple access communication systems in which optimal multiuser detection is performed at the receiver as the number and the identities of active users is allowed to change at each transmission time. The system dynamics are ruled by a Markov model describing the evolution of the channel occupancy and a large-system analysis is performed when the number of observations grow large. Starting on the equivalent scalar channel and the fixed-point equation tying multiuser efficiency and MMSE, we extend it to the case of a dynamic channel, and derive lower and upper bounds for the MMSE (and, thus, for η as well) holding true in the limit of large signalâtoânoise ratios and increasingly large observation time T.

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User generated content shared in online communities is often described using collaborative tagging systems where users assign labels to content resources. As a result, a folksonomy emerges that relates a number of tags with the resources they label and the users that have used them. In this paper we analyze the folksonomy of Freesound, an online audio clip sharing site which contains more than two million users and 150,000 user-contributed sound samplescovering a wide variety of sounds. By following methodologies taken from similar studies, we compute some metrics that characterize the folksonomy both at the globallevel and at the tag level. In this manner, we are able to betterunderstand the behavior of the folksonomy as a whole, and also obtain some indicators that can be used as metadata for describing tags themselves. We expect that such a methodology for characterizing folksonomies can be useful to support processes such as tag recommendation or automatic annotation of online resources.

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Public opposition to antiracism laws-an expression of prejudice toward immigrants-is widespread in Switzerland as well as in other European countries. Using data from the European Social Survey 2002 (N = 1,711), the present study examined across Swiss municipalities individual and contextual predictors of opposition to such laws and of two well-established antecedents of prejudice: perceived threat and intergroup contact. The study extends multilevel research on immigration attitudes by investigating the role of the ideological climate prevailing in municipalities (conservative vs. progressive), in addition to structural features of municipalities. Controlling for individual-level determinants, stronger opposition to antiracism laws was found in more conservative municipalities, while the proportion of immigrants was positively related to intergroup contact. Furthermore, in conservative municipalities with a low proportion of immigrants, fewer intergroup contacts were reported. In line with prior research, intergroup contact decreased prejudiced policy stances through a reduction of perceived threat. Overall, this study highlights the need to include normative and ideological features of local contexts in the analysis of public reactions toward immigrants.

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One of the most important issues in portland cement concrete pavement research today is surface characteristics. The issue is one of balancing surface texture construction with the need for durability, skid resistance, and noise reduction. The National Concrete Pavement Technology Center at Iowa State University, in conjunction with the Federal Highway Administration, American Concrete Pavement Association, International Grinding and Grooving Association, Iowa Highway Research Board, and other states, have entered into a three-part National Surface Characteristics Program to resolve the balancing problem. As a portion of Part 2, this report documents the construction of 18 separate pavement surfaces for use in the first level of testing for the national project. It identifies the testing to be done and the limitations observed in the construction process. The results of the actual tests will be included in the subsequent national study reports.

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Meta-analysis of genome-wide association studies (GWASs) has led to the discoveries of many common variants associated with complex human diseases. There is a growing recognition that identifying "causal" rare variants also requires large-scale meta-analysis. The fact that association tests with rare variants are performed at the gene level rather than at the variant level poses unprecedented challenges in the meta-analysis. First, different studies may adopt different gene-level tests, so the results are not compatible. Second, gene-level tests require multivariate statistics (i.e., components of the test statistic and their covariance matrix), which are difficult to obtain. To overcome these challenges, we propose to perform gene-level tests for rare variants by combining the results of single-variant analysis (i.e., p values of association tests and effect estimates) from participating studies. This simple strategy is possible because of an insight that multivariate statistics can be recovered from single-variant statistics, together with the correlation matrix of the single-variant test statistics, which can be estimated from one of the participating studies or from a publicly available database. We show both theoretically and numerically that the proposed meta-analysis approach provides accurate control of the type I error and is as powerful as joint analysis of individual participant data. This approach accommodates any disease phenotype and any study design and produces all commonly used gene-level tests. An application to the GWAS summary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare and low-frequency variants associated with human height. The relevant software is freely available.

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Objective To analyze innovative contents on Early Child Development Promotion. Method This action-research involves nine faculties from four Higher Education Institutions at inner-state of São Paulo, Brazil.Data were collected by syllabi analyses (2009-2011), interviews and focus group. We have adopted an ECDP underpinning from international consensus, thus evaluating KT Results We have found relevant incorporation between teaching and extension in Nursing (87,5%) and Psychology (75%) undergraduate courses, while Pedagogy was restricted to teaching. Conclusion This KT evaluation has evinced innovative potential of extension, regardless teaching and research, for a better Early Childhood.


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One of the disadvantages of old age is that there is more past than future: this,however, may be turned into an advantage if the wealth of experience and, hopefully,wisdom gained in the past can be reflected upon and throw some light on possiblefuture trends. To an extent, then, this talk is necessarily personal, certainly nostalgic,but also self critical and inquisitive about our understanding of the discipline ofstatistics. A number of almost philosophical themes will run through the talk: searchfor appropriate modelling in relation to the real problem envisaged, emphasis onsensible balances between simplicity and complexity, the relative roles of theory andpractice, the nature of communication of inferential ideas to the statistical layman, theinter-related roles of teaching, consultation and research. A list of keywords might be:identification of sample space and its mathematical structure, choices betweentransform and stay, the role of parametric modelling, the role of a sample spacemetric, the underused hypothesis lattice, the nature of compositional change,particularly in relation to the modelling of processes. While the main theme will berelevance to compositional data analysis we shall point to substantial implications forgeneral multivariate analysis arising from experience of the development ofcompositional data analysisâ¦

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Growing demand for corn due to the expansion of ethanol has increased concerns that environmentally sensitive lands retired from agricultural production into the Conservation Reserve Program (CRP) will be cropped again. Iowa produces more ethanol than any other state in the United States, and it also produces the most corn. Thus, an examination of the impacts of higher crop prices on CRP land in Iowa can give insight into what we might expect nationally in the years ahead if crop prices remain high. We construct CRP land supply curves for various corn prices and then estimate the environmental impacts of cropping CRP land through the Environmental Policy Integrated Climate (EPIC) model. EPIC provides edge-of-field estimates of soil erosion, nutrient loss, and carbon sequestration. We find that incremental impacts increase dramatically as higher corn prices bring into production more and more environmentally fragile land. Maintaining current levels of environmental quality will require substantially higher spending levels. Even allowing for the cost savings that would accrue as CRP land leaves the program, a change in targeting strategies will likely be required to ensure that the most sensitive land does not leave the program.

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The human brainstem is a densely packed, complex but highly organised structure. It not only serves as a conduit for long projecting axons conveying motor and sensory information, but also is the location of multiple primary nuclei that control or modulate a vast array of functions, including homeostasis, consciousness, locomotion, and reflexive and emotive behaviours. Despite its importance, both in understanding normal brain function as well as neurodegenerative processes, it remains a sparsely studied structure in the neuroimaging literature. In part, this is due to the difficulties in imaging the internal architecture of the brainstem in vivo in a reliable and repeatable fashion. A modified multivariate mixture of Gaussians (mmMoG) was applied to the problem of multichannel tissue segmentation. By using quantitative magnetisation transfer and proton density maps acquired at 3 T with 0.8 mm isotropic resolution, tissue probability maps for four distinct tissue classes within the human brainstem were created. These were compared against an ex vivo fixated human brain, imaged at 0.5 mm, with excellent anatomical correspondence. These probability maps were used within SPM8 to create accurate individual subject segmentations, which were then used for further quantitative analysis. As an example, brainstem asymmetries were assessed across 34 right-handed individuals using voxel based morphometry (VBM) and tensor based morphometry (TBM), demonstrating highly significant differences within localised regions that corresponded to motor and vocalisation networks. This method may have important implications for future research into MRI biomarkers of pre-clinical neurodegenerative diseases such as Parkinson's disease.

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The use of simple and multiple correspondence analysis is well-established in socialscience research for understanding relationships between two or more categorical variables.By contrast, canonical correspondence analysis, which is a correspondence analysis with linearrestrictions on the solution, has become one of the most popular multivariate techniques inecological research. Multivariate ecological data typically consist of frequencies of observedspecies across a set of sampling locations, as well as a set of observed environmental variablesat the same locations. In this context the principal dimensions of the biological variables aresought in a space that is constrained to be related to the environmental variables. Thisrestricted form of correspondence analysis has many uses in social science research as well,as is demonstrated in this paper. We first illustrate the result that canonical correspondenceanalysis of an indicator matrix, restricted to be related an external categorical variable, reducesto a simple correspondence analysis of a set of concatenated (or stacked ) tables. Then weshow how canonical correspondence analysis can be used to focus on, or partial out, aparticular set of response categories in sample survey data. For example, the method can beused to partial out the influence of missing responses, which usually dominate the results of amultiple correspondence analysis.

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We consider the application of normal theory methods to the estimation and testing of a general type of multivariate regressionmodels with errors--in--variables, in the case where various data setsare merged into a single analysis and the observable variables deviatepossibly from normality. The various samples to be merged can differ on the set of observable variables available. We show that there is a convenient way to parameterize the model so that, despite the possiblenon--normality of the data, normal--theory methods yield correct inferencesfor the parameters of interest and for the goodness--of--fit test. Thetheory described encompasses both the functional and structural modelcases, and can be implemented using standard software for structuralequations models, such as LISREL, EQS, LISCOMP, among others. An illustration with Monte Carlo data is presented.