Global data for ecology and epidemiology: a novel algorithm for temporal Fourier processing MODIS data

Background. Remotely-sensed environmental data from earth-orbiting satellites are increasingly used to model the distribution and abundance of both plant and animal species, especially those of economic or conservation importance. Time series of data from the MODerate-resolution Imaging Spectroradiometer (MODIS) sensors on-board NASA's Terra and Aqua satellites offer the potential to capture environmental thermal and vegetation seasonality, through temporal Fourier analysis, more accurately than was previously possible using the NOAA Advanced Very High Resolution Radiometer (AVHRR) sensor data. MODIS data are composited over 8- or 16-day time intervals that pose unique problems for temporal Fourier analysis. Applying standard techniques to MODIS data can introduce errors of up to 30% in the estimation of the amplitudes and phases of the Fourier harmonics. Methodology/Principal Findings. We present a novel spline-based algorithm that overcomes the processing problems of composited MODIS data. The algorithm is tested on artificial data generated using randomly selected values of both amplitudes and phases, and provides an accurate estimate of the input variables under all conditions. The algorithm was then applied to produce layers that capture the seasonality in MODIS data for the period from 2001 to 2005. Conclusions/Significance. Global temporal Fourier processed images of 1 km MODIS data for Middle Infrared Reflectance, day- and night-time Land Surface Temperature (LST), Normalised Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI) are presented for ecological and epidemiological applications. The finer spatial and temporal resolution, combined with the greater geolocational and spectral accuracy of the MODIS instruments, compared with previous multi-temporal data sets, mean that these data may be used with greater confidence in species' distribution modelling

Phylogenetic Relationships of Monocots Based on the Highly Informative Plastid Gene ndhF

We used ndhF sequence variation to reconstruct relationships across 282 taxa representing 78 monocot families and all 12 orders. The resulting tree is highly resolved and places commelinids sister to Asparagales, with both sister to Liliales—Pandanales in the strict consensus; Pandanales are sister to Dioscoreales in the bootstrap majority-rule tree, just above Petrosaviales. Acorales are sister to all other monocots, with Alismatales sister to all but Acorales. Relationships among the four major clades of commelinids remain unresolved. Relationships within orders are consistent with those based on rbcL, alone or in combination with atpB and 18S nrDNA, and generally better supported: ndhF contributes more than twice as many informative characters as rbcL, and nearly as many as rbcL, atpB, and 18S nrDNA combined. Based on functional arguments, we hypothesized that net venation and fleshy fruits should both evolve—and thus undergo concerted convergence—in shaded habitats, and revert to parallel venation and dry, passively dispersed fruits in open, sunny habitats. Our data show that net venation arose at least 26 times and disappeared 9 times, whereas fleshy fruits arose 22 times and disappeared 11 times. Both traits arose together at least 15 times and disappeared together 5 times. They thus show a highly significant pattern of concerted convergence (P \u3c 10-9) and are each even more strongly associated with shaded habitats (P \u3c 10-10 to 10-23); net venation is also associated, as predicted, with broad-leaved aquatic plants. Exceptions to this pattern illustrate the importance of other selective constraints and phylogenetic inertia

Colour reconnection in e+e- -> W+W- at sqrt(s) = 189 - 209 GeV

The effects of the final state interaction phenomenon known as colour reconnection are investigated at centre-of-mass energies in the range sqrt(s) ~ 189-209 GeV using the OPAL detector at LEP. Colour reconnection is expected to affect observables based on charged particles in hadronic decays of W+W-. Measurements of inclusive charged particle multiplicities, and of their angular distribution with respect to the four jet axes of the events, are used to test models of colour reconnection. The data are found to exclude extreme scenarios of the Sjostrand-Khoze Type I (SK-I) model and are compatible with other models, both with and without colour reconnection effects. In the context of the SK-I model, the best agreement with data is obtained for a reconnection probability of 37%. Assuming no colour reconnection, the charged particle multiplicity in hadronically decaying W bosons is measured to be (nqqch) = 19.38+-0.05(stat.)+-0.08 (syst.).Comment: 30 pages, 9 figures, Submitted to Euro. Phys. J.

Search for the Standard Model Higgs Boson with the OPAL Detector at LEP

This paper summarises the search for the Standard Model Higgs boson in e+e- collisions at centre-of-mass energies up to 209 GeV performed by the OPAL Collaboration at LEP. The consistency of the data with the background hypothesis and various Higgs boson mass hypotheses is examined. No indication of a signal is found in the data and a lower bound of 112.7GeV/C^2 is obtained on the mass of the Standard Model Higgs boson at the 95% CL.Comment: 51 pages, 21 figure

Search for R-Parity Violating Decays of Scalar Fermions at LEP

A search for pair-produced scalar fermions under the assumption that R-parity is not conserved has been performed using data collected with the OPAL detector at LEP. The data samples analysed correspond to an integrated luminosity of about 610 pb-1 collected at centre-of-mass energies of sqrt(s) 189-209 GeV. An important consequence of R-parity violation is that the lightest supersymmetric particle is expected to be unstable. Searches of R-parity violating decays of charged sleptons, sneutrinos and squarks have been performed under the assumptions that the lightest supersymmetric particle decays promptly and that only one of the R-parity violating couplings is dominant for each of the decay modes considered. Such processes would yield final states consisting of leptons, jets, or both with or without missing energy. No significant single-like excess of events has been observed with respect to the Standard Model expectations. Limits on the production cross- section of scalar fermions in R-parity violating scenarios are obtained. Constraints on the supersymmetric particle masses are also presented in an R-parity violating framework analogous to the Constrained Minimal Supersymmetric Standard Model.Comment: 51 pages, 24 figures, Submitted to Eur. Phys. J.

Measurement of the Hadronic Photon Structure Function F_2^gamma at LEP2

The hadronic structure function of the photon F_2^gamma is measured as a function of Bjorken x and of the factorisation scale Q^2 using data taken by the OPAL detector at LEP. Previous OPAL measurements of the x dependence of F_2^gamma are extended to an average Q^2 of 767 GeV^2. The Q^2 evolution of F_2^gamma is studied for average Q^2 between 11.9 and 1051 GeV^2. As predicted by QCD, the data show positive scaling violations in F_2^gamma. Several parameterisations of F_2^gamma are in agreement with the measurements whereas the quark-parton model prediction fails to describe the data.Comment: 4 pages, 2 figures, to appear in the proceedings of Photon 2001, Ascona, Switzerlan

Development of a blood-based gene expression algorithm for assessment of obstructive coronary artery disease in non-diabetic patients

<p>Abstract</p> <p>Background</p> <p>Alterations in gene expression in peripheral blood cells have been shown to be sensitive to the presence and extent of coronary artery disease (CAD). A non-invasive blood test that could reliably assess obstructive CAD likelihood would have diagnostic utility.</p> <p>Results</p> <p>Microarray analysis of RNA samples from a 195 patient Duke CATHGEN registry case:control cohort yielded 2,438 genes with significant CAD association (p < 0.05), and identified the clinical/demographic factors with the largest effects on gene expression as age, sex, and diabetic status. RT-PCR analysis of 88 CAD classifier genes confirmed that diabetic status was the largest clinical factor affecting CAD associated gene expression changes. A second microarray cohort analysis limited to non-diabetics from the multi-center PREDICT study (198 patients; 99 case: control pairs matched for age and sex) evaluated gene expression, clinical, and cell population predictors of CAD and yielded 5,935 CAD genes (p < 0.05) with an intersection of 655 genes with the CATHGEN results. Biological pathway (gene ontology and literature) and statistical analyses (hierarchical clustering and logistic regression) were used in combination to select 113 genes for RT-PCR analysis including CAD classifiers, cell-type specific markers, and normalization genes.</p> <p>RT-PCR analysis of these 113 genes in a PREDICT cohort of 640 non-diabetic subject samples was used for algorithm development. Gene expression correlations identified clusters of CAD classifier genes which were reduced to meta-genes using LASSO. The final classifier for assessment of obstructive CAD was derived by Ridge Regression and contained sex-specific age functions and 6 meta-gene terms, comprising 23 genes. This algorithm showed a cross-validated estimated AUC = 0.77 (95% CI 0.73-0.81) in ROC analysis.</p> <p>Conclusions</p> <p>We have developed a whole blood classifier based on gene expression, age and sex for the assessment of obstructive CAD in non-diabetic patients from a combination of microarray and RT-PCR data derived from studies of patients clinically indicated for invasive angiography.</p> <p>Clinical trial registration information</p> <p>PREDICT, Personalized Risk Evaluation and Diagnosis in the Coronary Tree, <url>http://www.clinicaltrials.gov</url>, <a href="http://www.clinicaltrials.gov/ct2/show/NCT00500617">NCT00500617</a></p

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin