Biology and Ecology of Sand Flies (Diptera: Psychodidae) in the Middle East, with Special Emphasis on Phlebotomus Papatasi and Phlebotomus Alexandri

DTIC Science & Technology

2009-03-06

64 Predicted distribution of Phlebotomus papatasi in the Middle East 85 Jackknife test of training gain for...P. papatasi 86 Predicted distribution of Phlebotomus alexandri in the Middle East 87 Jackknife test of...epithelial cells by approximately 72 hours post ingestion (Sacks and Kamhawi 2001, Bates 2007). Approximately one week after ingestion, the parasites

The Outlier Detection for Ordinal Data Using Scalling Technique of Regression Coefficients

NASA Astrophysics Data System (ADS)

Adnan, Arisman; Sugiarto, Sigit

2017-06-01

The aims of this study is to detect the outliers by using coefficients of Ordinal Logistic Regression (OLR) for the case of k category responses where the score from 1 (the best) to 8 (the worst). We detect them by using the sum of moduli of the ordinal regression coefficients calculated by jackknife technique. This technique is improved by scalling the regression coefficients to their means. R language has been used on a set of ordinal data from reference distribution. Furthermore, we compare this approach by using studentised residual plots of jackknife technique for ANOVA (Analysis of Variance) and OLR. This study shows that the jackknifing technique along with the proper scaling may lead us to reveal outliers in ordinal regression reasonably well.

Sampling effort and estimates of species richness based on prepositioned area electrofisher samples

USGS Publications Warehouse

Bowen, Z.H.; Freeman, Mary C.

1998-01-01

Estimates of species richness based on electrofishing data are commonly used to describe the structure of fish communities. One electrofishing method for sampling riverine fishes that has become popular in the last decade is the prepositioned area electrofisher (PAE). We investigated the relationship between sampling effort and fish species richness at seven sites in the Tallapoosa River system, USA based on 1,400 PAE samples collected during 1994 and 1995. First, we estimated species richness at each site using the first-order jackknife and compared observed values for species richness and jackknife estimates of species richness to estimates based on historical collection data. Second, we used a permutation procedure and nonlinear regression to examine rates of species accumulation. Third, we used regression to predict the number of PAE samples required to collect the jackknife estimate of species richness at each site during 1994 and 1995. We found that jackknife estimates of species richness generally were less than or equal to estimates based on historical collection data. The relationship between PAE electrofishing effort and species richness in the Tallapoosa River was described by a positive asymptotic curve as found in other studies using different electrofishing gears in wadable streams. Results from nonlinear regression analyses indicted that rates of species accumulation were variable among sites and between years. Across sites and years, predictions of sampling effort required to collect jackknife estimates of species richness suggested that doubling sampling effort (to 200 PAEs) would typically increase observed species richness by not more than six species. However, sampling effort beyond about 60 PAE samples typically increased observed species richness by < 10%. We recommend using historical collection data in conjunction with a preliminary sample size of at least 70 PAE samples to evaluate estimates of species richness in medium-sized rivers

Inadequacy of internal covariance estimation for super-sample covariance

NASA Astrophysics Data System (ADS)

Lacasa, Fabien; Kunz, Martin

2017-08-01

We give an analytical interpretation of how subsample-based internal covariance estimators lead to biased estimates of the covariance, due to underestimating the super-sample covariance (SSC). This includes the jackknife and bootstrap methods as estimators for the full survey area, and subsampling as an estimator of the covariance of subsamples. The limitations of the jackknife covariance have been previously presented in the literature because it is effectively a rescaling of the covariance of the subsample area. However we point out that subsampling is also biased, but for a different reason: the subsamples are not independent, and the corresponding lack of power results in SSC underprediction. We develop the formalism in the case of cluster counts that allows the bias of each covariance estimator to be exactly predicted. We find significant effects for a small-scale area or when a low number of subsamples is used, with auto-redshift biases ranging from 0.4% to 15% for subsampling and from 5% to 75% for jackknife covariance estimates. The cross-redshift covariance is even more affected; biases range from 8% to 25% for subsampling and from 50% to 90% for jackknife. Owing to the redshift evolution of the probe, the covariances cannot be debiased by a simple rescaling factor, and an exact debiasing has the same requirements as the full SSC prediction. These results thus disfavour the use of internal covariance estimators on data itself or a single simulation, leaving analytical prediction and simulations suites as possible SSC predictors.

Prediction of resource volumes at untested locations using simple local prediction models

USGS Publications Warehouse

Attanasi, E.D.; Coburn, T.C.; Freeman, P.A.

2006-01-01

This paper shows how local spatial nonparametric prediction models can be applied to estimate volumes of recoverable gas resources at individual undrilled sites, at multiple sites on a regional scale, and to compute confidence bounds for regional volumes based on the distribution of those estimates. An approach that combines cross-validation, the jackknife, and bootstrap procedures is used to accomplish this task. Simulation experiments show that cross-validation can be applied beneficially to select an appropriate prediction model. The cross-validation procedure worked well for a wide range of different states of nature and levels of information. Jackknife procedures are used to compute individual prediction estimation errors at undrilled locations. The jackknife replicates also are used with a bootstrap resampling procedure to compute confidence bounds for the total volume. The method was applied to data (partitioned into a training set and target set) from the Devonian Antrim Shale continuous-type gas play in the Michigan Basin in Otsego County, Michigan. The analysis showed that the model estimate of total recoverable volumes at prediction sites is within 4 percent of the total observed volume. The model predictions also provide frequency distributions of the cell volumes at the production unit scale. Such distributions are the basis for subsequent economic analyses. ?? Springer Science+Business Media, LLC 2007.

Jackknife Variance Estimator for Two Sample Linear Rank Statistics

DTIC Science & Technology

1988-11-01

Accesion For - - ,NTIS GPA&I "TIC TAB Unann c, nc .. [d Keywords: strong consistency; linear rank test’ influence function . i , at L By S- )Distribut...reverse if necessary and identify by block number) FIELD IGROUP SUB-GROUP Strong consistency; linear rank test; influence function . 19. ABSTRACT

HEXT, a software supporting tree-based screens for hybrid taxa in multilocus data sets, and an evaluation of the homoplasy excess test.

PubMed

Schneider, Kevin; Koblmüller, Stephan; Sefc, Kristina M

2015-11-11

The homoplasy excess test (HET) is a tree-based screen for hybrid taxa in multilocus nuclear phylogenies. Homoplasy between a hybrid taxon and the clades containing the parental taxa reduces bootstrap support in the tree. The HET is based on the expectation that excluding the hybrid taxon from the data set increases the bootstrap support for the parental clades, whereas excluding non-hybrid taxa has little effect on statistical node support. To carry out a HET, bootstrap trees are calculated with taxon-jackknife data sets, that is excluding one taxon (species, population) at a time. Excess increase in bootstrap support for certain nodes upon exclusion of a particular taxon indicates the hybrid (the excluded taxon) and its parents (the clades with increased support).We introduce a new software program, hext, which generates the taxon-jackknife data sets, runs the bootstrap tree calculations, and identifies excess bootstrap increases as outlier values in boxplot graphs. hext is written in r language and accepts binary data (0/1; e.g. AFLP) as well as co-dominant SNP and genotype data.We demonstrate the usefulness of hext in large SNP data sets containing putative hybrids and their parents. For instance, using published data of the genus Vitis (~6,000 SNP loci), hext output supports V. × champinii as a hybrid between V. rupestris and V. mustangensis .With simulated SNP and AFLP data sets, excess increases in bootstrap support were not always connected with the hybrid taxon (false positives), whereas the expected bootstrap signal failed to appear on several occasions (false negatives). Potential causes for both types of spurious results are discussed.With both empirical and simulated data sets, the taxon-jackknife output generated by hext provided additional signatures of hybrid taxa, including changes in tree topology across trees, consistent effects of exclusions of the hybrid and the parent taxa, and moderate (rather than excessive) increases in bootstrap support

Whole-genome typing and characterization of blaVIM19-harbouring ST383 Klebsiella pneumoniae by PFGE, whole-genome mapping and WGS.

PubMed

Sabirova, Julia S; Xavier, Basil Britto; Coppens, Jasmine; Zarkotou, Olympia; Lammens, Christine; Janssens, Lore; Burggrave, Ronald; Wagner, Trevor; Goossens, Herman; Malhotra-Kumar, Surbhi

2016-06-01

We utilized whole-genome mapping (WGM) and WGS to characterize 12 clinical carbapenem-resistant Klebsiella pneumoniae strains (TGH1-TGH12). All strains were screened for carbapenemase genes by PCR, and typed by MLST, PFGE (XbaI) and WGM (AflII) (OpGen, USA). WGS (Illumina) was performed on TGH8 and TGH10. Reads were de novo assembled and annotated [SPAdes, Rapid Annotation Subsystem Technology (RAST)]. Contigs were aligned directly, and after in silico AflII restriction, with corresponding WGMs (MapSolver, OpGen; BioNumerics, Applied Maths). All 12 strains were ST383. Of the 12 strains, 11 were carbapenem resistant, 7 harboured blaKPC-2 and 11 harboured blaVIM-19. Varying the parameters for assigning WGM clusters showed that these were comparable to STs and to the eight PFGE types or subtypes (difference of three or more bands). A 95% similarity coefficient assigned all 12 WGMs to a single cluster, whereas a 99% similarity coefficient (or ≥10 unmatched-fragment difference) assigned the 12 WGMs to eight (sub)clusters. Based on a difference of three or more bands between PFGE profiles, the Simpson's diversity indices (SDIs) of WGM (0.94, Jackknife pseudo-values CI: 0.883-0.996) and PFGE (0.93, Jackknife pseudo-values CI: 0.828-1.000) were similar (P = 0.649). However, the discriminatory power of WGM was significantly higher (SDI: 0.94, Jackknife pseudo-values CI: 0.883-0.996) than that of PFGE profiles typed on a difference of seven or more bands (SDI: 0.53, Jackknife pseudo-values CI: 0.212-0.849) (P = 0.007). This study demonstrates the application of WGM to understanding the epidemiology of hospital-associated K. pneumoniae. Utilizing a combination of WGM and WGS, we also present here the first longitudinal genomic characterization of the highly dynamic carbapenem-resistant ST383 K. pneumoniae clone that is rapidly gaining importance in Europe. © The Author 2016. Published by Oxford University Press on behalf of the British Society for Antimicrobial

An improved partial least-squares regression method for Raman spectroscopy

NASA Astrophysics Data System (ADS)

Momenpour Tehran Monfared, Ali; Anis, Hanan

2017-10-01

It is known that the performance of partial least-squares (PLS) regression analysis can be improved using the backward variable selection method (BVSPLS). In this paper, we further improve the BVSPLS based on a novel selection mechanism. The proposed method is based on sorting the weighted regression coefficients, and then the importance of each variable of the sorted list is evaluated using root mean square errors of prediction (RMSEP) criterion in each iteration step. Our Improved BVSPLS (IBVSPLS) method has been applied to leukemia and heparin data sets and led to an improvement in limit of detection of Raman biosensing ranged from 10% to 43% compared to PLS. Our IBVSPLS was also compared to the jack-knifing (simpler) and Genetic Algorithm (more complex) methods. Our method was consistently better than the jack-knifing method and showed either a similar or a better performance compared to the genetic algorithm.

HIV-1 protease cleavage site prediction based on two-stage feature selection method.

PubMed

Niu, Bing; Yuan, Xiao-Cheng; Roeper, Preston; Su, Qiang; Peng, Chun-Rong; Yin, Jing-Yuan; Ding, Juan; Li, HaiPeng; Lu, Wen-Cong

2013-03-01

Knowledge of the mechanism of HIV protease cleavage specificity is critical to the design of specific and effective HIV inhibitors. Searching for an accurate, robust, and rapid method to correctly predict the cleavage sites in proteins is crucial when searching for possible HIV inhibitors. In this article, HIV-1 protease specificity was studied using the correlation-based feature subset (CfsSubset) selection method combined with Genetic Algorithms method. Thirty important biochemical features were found based on a jackknife test from the original data set containing 4,248 features. By using the AdaBoost method with the thirty selected features the prediction model yields an accuracy of 96.7% for the jackknife test and 92.1% for an independent set test, with increased accuracy over the original dataset by 6.7% and 77.4%, respectively. Our feature selection scheme could be a useful technique for finding effective competitive inhibitors of HIV protease.

Use of Empirical Estimates of Shrinkage in Multiple Regression: A Caution.

ERIC Educational Resources Information Center

Kromrey, Jeffrey D.; Hines, Constance V.

1995-01-01

The accuracy of four empirical techniques to estimate shrinkage in multiple regression was studied through Monte Carlo simulation. None of the techniques provided unbiased estimates of the population squared multiple correlation coefficient, but the normalized jackknife and bootstrap techniques demonstrated marginally acceptable performance with…

Variance Estimation Using Replication Methods in Structural Equation Modeling with Complex Sample Data

ERIC Educational Resources Information Center

Stapleton, Laura M.

2008-01-01

This article discusses replication sampling variance estimation techniques that are often applied in analyses using data from complex sampling designs: jackknife repeated replication, balanced repeated replication, and bootstrapping. These techniques are used with traditional analyses such as regression, but are currently not used with structural…

Prediction of rat protein subcellular localization with pseudo amino acid composition based on multiple sequential features.

PubMed

Shi, Ruijia; Xu, Cunshuan

2011-06-01

The study of rat proteins is an indispensable task in experimental medicine and drug development. The function of a rat protein is closely related to its subcellular location. Based on the above concept, we construct the benchmark rat proteins dataset and develop a combined approach for predicting the subcellular localization of rat proteins. From protein primary sequence, the multiple sequential features are obtained by using of discrete Fourier analysis, position conservation scoring function and increment of diversity, and these sequential features are selected as input parameters of the support vector machine. By the jackknife test, the overall success rate of prediction is 95.6% on the rat proteins dataset. Our method are performed on the apoptosis proteins dataset and the Gram-negative bacterial proteins dataset with the jackknife test, the overall success rates are 89.9% and 96.4%, respectively. The above results indicate that our proposed method is quite promising and may play a complementary role to the existing predictors in this area.

Diallel analysis for sex-linked and maternal effects.

PubMed

Zhu, J; Weir, B S

1996-01-01

Genetic models including sex-linked and maternal effects as well as autosomal gene effects are described. Monte Carlo simulations were conducted to compare efficiencies of estimation by minimum norm quadratic unbiased estimation (MINQUE) and restricted maximum likelihood (REML) methods. MINQUE(1), which has 1 for all prior values, has a similar efficiency to MINQUE(θ), which requires prior estimates of parameter values. MINQUE(1) has the advantage over REML of unbiased estimation and convenient computation. An adjusted unbiased prediction (AUP) method is developed for predicting random genetic effects. AUP is desirable for its easy computation and unbiasedness of both mean and variance of predictors. The jackknife procedure is appropriate for estimating the sampling variances of estimated variances (or covariances) and of predicted genetic effects. A t-test based on jackknife variances is applicable for detecting significance of variation. Worked examples from mice and silkworm data are given in order to demonstrate variance and covariance estimation and genetic effect prediction.

29 CFR 1918.54 - Rigging gear.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Relating to Labor (Continued) OCCUPATIONAL SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR (CONTINUED) SAFETY AND HEALTH REGULATIONS FOR LONGSHORING Vessel's Cargo Handling Gear § 1918.54 Rigging gear. (a... provided, the guys shall be so placed as to produce a minimum stress and not permit the boom to jackknife...

speed-ne: Software to simulate and estimate genetic effective population size (Ne ) from linkage disequilibrium observed in single samples.

PubMed

Hamilton, Matthew B; Tartakovsky, Maria; Battocletti, Amy

2018-05-01

The genetic effective population size, N e , can be estimated from the average gametic disequilibrium (r2^) between pairs of loci, but such estimates require evaluation of assumptions and currently have few methods to estimate confidence intervals. speed-ne is a suite of matlab computer code functions to estimate Ne^ from r2^ with a graphical user interface and a rich set of outputs that aid in understanding data patterns and comparing multiple estimators. speed-ne includes functions to either generate or input simulated genotype data to facilitate comparative studies of Ne^ estimators under various population genetic scenarios. speed-ne was validated with data simulated under both time-forward and time-backward coalescent models of genetic drift. Three classes of estimators were compared with simulated data to examine several general questions: what are the impacts of microsatellite null alleles on Ne^, how should missing data be treated, and does disequilibrium contributed by reduced recombination among some loci in a sample impact Ne^. Estimators differed greatly in precision in the scenarios examined, and a widely employed Ne^ estimator exhibited the largest variances among replicate data sets. speed-ne implements several jackknife approaches to estimate confidence intervals, and simulated data showed that jackknifing over loci and jackknifing over individuals provided ~95% confidence interval coverage for some estimators and should be useful for empirical studies. speed-ne provides an open-source extensible tool for estimation of Ne^ from empirical genotype data and to conduct simulations of both microsatellite and single nucleotide polymorphism (SNP) data types to develop expectations and to compare Ne^ estimators. © 2018 John Wiley & Sons Ltd.

Variance Estimation for NAEP Data Using a Resampling-Based Approach: An Application of Cognitive Diagnostic Models. Research Report. ETS RR-10-26

ERIC Educational Resources Information Center

Hsieh, Chueh-an; Xu, Xueli; von Davier, Matthias

2010-01-01

This paper presents an application of a jackknifing approach to variance estimation of ability inferences for groups of students, using a multidimensional discrete model for item response data. The data utilized to demonstrate the approach come from the National Assessment of Educational Progress (NAEP). In contrast to the operational approach…

A comparison of confidence interval methods for the concordance correlation coefficient and intraclass correlation coefficient with small number of raters.

PubMed

Feng, Dai; Svetnik, Vladimir; Coimbra, Alexandre; Baumgartner, Richard

2014-01-01

The intraclass correlation coefficient (ICC) with fixed raters or, equivalently, the concordance correlation coefficient (CCC) for continuous outcomes is a widely accepted aggregate index of agreement in settings with small number of raters. Quantifying the precision of the CCC by constructing its confidence interval (CI) is important in early drug development applications, in particular in qualification of biomarker platforms. In recent years, there have been several new methods proposed for construction of CIs for the CCC, but their comprehensive comparison has not been attempted. The methods consisted of the delta method and jackknifing with and without Fisher's Z-transformation, respectively, and Bayesian methods with vague priors. In this study, we carried out a simulation study, with data simulated from multivariate normal as well as heavier tailed distribution (t-distribution with 5 degrees of freedom), to compare the state-of-the-art methods for assigning CI to the CCC. When the data are normally distributed, the jackknifing with Fisher's Z-transformation (JZ) tended to provide superior coverage and the difference between it and the closest competitor, the Bayesian method with the Jeffreys prior was in general minimal. For the nonnormal data, the jackknife methods, especially the JZ method, provided the coverage probabilities closest to the nominal in contrast to the others which yielded overly liberal coverage. Approaches based upon the delta method and Bayesian method with conjugate prior generally provided slightly narrower intervals and larger lower bounds than others, though this was offset by their poor coverage. Finally, we illustrated the utility of the CIs for the CCC in an example of a wake after sleep onset (WASO) biomarker, which is frequently used in clinical sleep studies of drugs for treatment of insomnia.

Approximation of Confidence Limits on Sample Semivariograms From Single Realizations of Spatially Correlated Random Fields

NASA Astrophysics Data System (ADS)

Shafer, J. M.; Varljen, M. D.

1990-08-01

A fundamental requirement for geostatistical analyses of spatially correlated environmental data is the estimation of the sample semivariogram to characterize spatial correlation. Selecting an underlying theoretical semivariogram based on the sample semivariogram is an extremely important and difficult task that is subject to a great deal of uncertainty. Current standard practice does not involve consideration of the confidence associated with semivariogram estimates, largely because classical statistical theory does not provide the capability to construct confidence limits from single realizations of correlated data, and multiple realizations of environmental fields are not found in nature. The jackknife method is a nonparametric statistical technique for parameter estimation that may be used to estimate the semivariogram. When used in connection with standard confidence procedures, it allows for the calculation of closely approximate confidence limits on the semivariogram from single realizations of spatially correlated data. The accuracy and validity of this technique was verified using a Monte Carlo simulation approach which enabled confidence limits about the semivariogram estimate to be calculated from many synthetically generated realizations of a random field with a known correlation structure. The synthetically derived confidence limits were then compared to jackknife estimates from single realizations with favorable results. Finally, the methodology for applying the jackknife method to a real-world problem and an example of the utility of semivariogram confidence limits were demonstrated by constructing confidence limits on seasonal sample variograms of nitrate-nitrogen concentrations in shallow groundwater in an approximately 12-mi2 (˜30 km2) region in northern Illinois. In this application, the confidence limits on sample semivariograms from different time periods were used to evaluate the significance of temporal change in spatial correlation. This

Possession, Transportation, and Use of Firearms by Older Youth in 4-H Shooting Sports Programs

ERIC Educational Resources Information Center

White, David J.; Williver, S. Todd

2014-01-01

Thirty years ago we would think nothing of driving to school with a jackknife in our pocket or rifle in the gun rack. Since then, the practices of possessing, transporting, and using firearms have been limited by laws, rules, and public perception. Despite restrictions on youth, the Youth Handgun Safety Act does afford 4-H shooting sports members…

The Beginner's Guide to the Bootstrap Method of Resampling.

ERIC Educational Resources Information Center

Lane, Ginny G.

The bootstrap method of resampling can be useful in estimating the replicability of study results. The bootstrap procedure creates a mock population from a given sample of data from which multiple samples are then drawn. The method extends the usefulness of the jackknife procedure as it allows for computation of a given statistic across a maximal…

Captain M. A. Ainslie (1869-1951): his observations and telescopes

NASA Astrophysics Data System (ADS)

Mobberley, M. P.

2010-02-01

The astronomical career of one of the BAA's most enthusiastic planetary observers, who contributed observations in the first five decades of the twentieth century, is described. In addition, his pioneering observation of the occultation of a star by Saturn's rings in 1917 is examined and the full story of his unique 'Jack-Knife telescope', designed by Horace Dall, is given.

Performance of internal covariance estimators for cosmic shear correlation functions

DOE PAGES

Friedrich, O.; Seitz, S.; Eifler, T. F.; ...

2015-12-31

Data re-sampling methods such as the delete-one jackknife are a common tool for estimating the covariance of large scale structure probes. In this paper we investigate the concepts of internal covariance estimation in the context of cosmic shear two-point statistics. We demonstrate how to use log-normal simulations of the convergence field and the corresponding shear field to carry out realistic tests of internal covariance estimators and find that most estimators such as jackknife or sub-sample covariance can reach a satisfactory compromise between bias and variance of the estimated covariance. In a forecast for the complete, 5-year DES survey we show that internally estimated covariance matrices can provide a large fraction of the true uncertainties on cosmological parameters in a 2D cosmic shear analysis. The volume inside contours of constant likelihood in themore » $$\\Omega_m$$-$$\\sigma_8$$ plane as measured with internally estimated covariance matrices is on average $$\\gtrsim 85\\%$$ of the volume derived from the true covariance matrix. The uncertainty on the parameter combination $$\\Sigma_8 \\sim \\sigma_8 \\Omega_m^{0.5}$$ derived from internally estimated covariances is $$\\sim 90\\%$$ of the true uncertainty.« less

The relationship between the number of loci and the statistical support for the topology of UPGMA trees obtained from genetic distance data.

PubMed

Highton, R

1993-12-01

An analysis of the relationship between the number of loci utilized in an electrophoretic study of genetic relationships and the statistical support for the topology of UPGMA trees is reported for two published data sets. These are Highton and Larson (Syst. Zool.28:579-599, 1979), an analysis of the relationships of 28 species of plethodonine salamanders, and Hedges (Syst. Zool., 35:1-21, 1986), a similar study of 30 taxa of Holarctic hylid frogs. As the number of loci increases, the statistical support for the topology at each node in UPGMA trees was determined by both the bootstrap and jackknife methods. The results show that the bootstrap and jackknife probabilities supporting the topology at some nodes of UPGMA trees increase as the number of loci utilized in a study is increased, as expected for nodes that have groupings that reflect phylogenetic relationships. The pattern of increase varies and is especially rapid in the case of groups with no close relatives. At nodes that likely do not represent correct phylogenetic relationships, the bootstrap probabilities do not increase and often decline with the addition of more loci.

swot: Super W Of Theta

NASA Astrophysics Data System (ADS)

Coupon, Jean; Leauthaud, Alexie; Kilbinger, Martin; Medezinski, Elinor

2017-07-01

SWOT (Super W Of Theta) computes two-point statistics for very large data sets, based on “divide and conquer” algorithms, mainly, but not limited to data storage in binary trees, approximation at large scale, parellelization (open MPI), and bootstrap and jackknife resampling methods “on the fly”. It currently supports projected and 3D galaxy auto and cross correlations, galaxy-galaxy lensing, and weighted histograms.

Evaluating species richness: biased ecological inference results from spatial heterogeneity in species detection probabilities

USGS Publications Warehouse

McNew, Lance B.; Handel, Colleen M.

2015-01-01

Accurate estimates of species richness are necessary to test predictions of ecological theory and evaluate biodiversity for conservation purposes. However, species richness is difficult to measure in the field because some species will almost always be overlooked due to their cryptic nature or the observer's failure to perceive their cues. Common measures of species richness that assume consistent observability across species are inviting because they may require only single counts of species at survey sites. Single-visit estimation methods ignore spatial and temporal variation in species detection probabilities related to survey or site conditions that may confound estimates of species richness. We used simulated and empirical data to evaluate the bias and precision of raw species counts, the limiting forms of jackknife and Chao estimators, and multi-species occupancy models when estimating species richness to evaluate whether the choice of estimator can affect inferences about the relationships between environmental conditions and community size under variable detection processes. Four simulated scenarios with realistic and variable detection processes were considered. Results of simulations indicated that (1) raw species counts were always biased low, (2) single-visit jackknife and Chao estimators were significantly biased regardless of detection process, (3) multispecies occupancy models were more precise and generally less biased than the jackknife and Chao estimators, and (4) spatial heterogeneity resulting from the effects of a site covariate on species detection probabilities had significant impacts on the inferred relationships between species richness and a spatially explicit environmental condition. For a real dataset of bird observations in northwestern Alaska, the four estimation methods produced different estimates of local species richness, which severely affected inferences about the effects of shrubs on local avian richness. Overall, our results

Cluster mislocation in kinematic Sunyaev-Zel'dovich (kSZ) effect extraction

NASA Astrophysics Data System (ADS)

Calafut, Victoria Rose; Bean, Rachel; Yu, Byeonghee

2018-01-01

We investigate the impact of a variety of analysis assumptions that influence cluster identification and location on the kSZ pairwise momentum signal and covariance estimation. Photometric and spectroscopic galaxy tracers from SDSS, WISE, and DECaLs, spanning redshifts 0.05jackknife estimator. We also show that jackknife covariance estimates are significantly more conservative than those obtained by CMB rotation methods. Using redMaPPer data, we concurrently compare uncertainties for photometric redshift errors and miscentering and find them comparable for separations <˜ 50 Mpc where the kSZ signal is largest.For the next generation of CMB and LSS surveys the statistical and photometric errors will shrink markedly. Our results demonstrate that uncertainties introduced through using galaxy proxies for cluster locations will need to be fully incorporated, and actively mitigated, for the kSZ to reach its full potential as a cosmological constraining tool for dark energy and neutrino physics.

DNA-DNA hybridization-based phylogeny for "higher" nonpasserines: reevaluating a key portion of the avian family tree.

PubMed

Bleiweiss, R; Kirsch, J A; Lapointe, F J

1994-09-01

A matrix of delta T mode values for 10 birds, including 9 nonpasserines and a suboscine passerine flycatcher, was generated by DNA-DNA hybridization. Within the most derived lineages, all bootstrapped and jackknifed FITCH trees lend strong support to sister-groupings of the two swift families, of hummingbirds to swifts, and of these to a clade containing both owls and night-hawks. The outgroup duck roots the tree between the woodpecker (Piciformes) and the remaining taxa, indicating that Piciformes are among the earliest branches within nonpasserines. However, the succeeding branches to kingfisher, mousebird, and suboscine passerine flycatcher are based on short internodes that are poorly supported by bootstrapping and that give inconsistent results in jackknifing. Although these 3 orders may have arisen through rapid or near-simultaneous divergence, placement of the "advanced" Passeriformes deep within a more "primitive" radiation indicates that nonpasserines are paraphyletic, echoing the same distinction for reptiles with respect to their advanced descendants. Despite significant rate variation among different taxa, these results largely concur with those obtained with the same technique by Sibley and Ahlquist, who used the delta T50H measure and UPGMA analysis. This agreement lends credence to some of their more controversial claims.

Sample Reuse in Statistical Remodeling.

DTIC Science & Technology

1987-08-01

as the jackknife and bootstrap, is an expansion of the functional, T(Fn), or of its distribution function or both. Frangos and Schucany (1987a) used...accelerated bootstrap. In the same report Frangos and Schucany demonstrated the small sample superiority of that approach over the proposals that take...higher order terms of an Edgeworth expansion into account. In a second report Frangos and Schucany (1987b) examined the small sample performance of

Software Supportability Risk Assessment in OT&E (Operational Test and Evaluation): Literature Review, Current Research Review, and Data Base Assemblage.

DTIC Science & Technology

1984-09-28

variables before simula- tion of model - Search for reality checks a, - Express uncertainty as a probability density distribution. a. H2 a, H-22 TWIF... probability that the software con- tains errors. This prior is updated as test failure data are accumulated. Only a p of 1 (software known to contain...discusssed; both parametric and nonparametric versions are presented. It is shown by the author that the bootstrap underlies the jackknife method and

Comparison of variance estimators for meta-analysis of instrumental variable estimates

PubMed Central

Schmidt, AF; Hingorani, AD; Jefferis, BJ; White, J; Groenwold, RHH; Dudbridge, F

2016-01-01

Abstract Background: Mendelian randomization studies perform instrumental variable (IV) analysis using genetic IVs. Results of individual Mendelian randomization studies can be pooled through meta-analysis. We explored how different variance estimators influence the meta-analysed IV estimate. Methods: Two versions of the delta method (IV before or after pooling), four bootstrap estimators, a jack-knife estimator and a heteroscedasticity-consistent (HC) variance estimator were compared using simulation. Two types of meta-analyses were compared, a two-stage meta-analysis pooling results, and a one-stage meta-analysis pooling datasets. Results: Using a two-stage meta-analysis, coverage of the point estimate using bootstrapped estimators deviated from nominal levels at weak instrument settings and/or outcome probabilities ≤ 0.10. The jack-knife estimator was the least biased resampling method, the HC estimator often failed at outcome probabilities ≤ 0.50 and overall the delta method estimators were the least biased. In the presence of between-study heterogeneity, the delta method before meta-analysis performed best. Using a one-stage meta-analysis all methods performed equally well and better than two-stage meta-analysis of greater or equal size. Conclusions: In the presence of between-study heterogeneity, two-stage meta-analyses should preferentially use the delta method before meta-analysis. Weak instrument bias can be reduced by performing a one-stage meta-analysis. PMID:27591262

A simple randomisation procedure for validating discriminant analysis: a methodological note.

PubMed

Wastell, D G

1987-04-01

Because the goal of discriminant analysis (DA) is to optimise classification, it designedly exaggerates between-group differences. This bias complicates validation of DA. Jack-knifing has been used for validation but is inappropriate when stepwise selection (SWDA) is employed. A simple randomisation test is presented which is shown to give correct decisions for SWDA. The general superiority of randomisation tests over orthodox significance tests is discussed. Current work on non-parametric methods of estimating the error rates of prediction rules is briefly reviewed.

Empirical likelihood-based confidence intervals for mean medical cost with censored data.

PubMed

Jeyarajah, Jenny; Qin, Gengsheng

2017-11-10

In this paper, we propose empirical likelihood methods based on influence function and jackknife techniques for constructing confidence intervals for mean medical cost with censored data. We conduct a simulation study to compare the coverage probabilities and interval lengths of our proposed confidence intervals with that of the existing normal approximation-based confidence intervals and bootstrap confidence intervals. The proposed methods have better finite-sample performances than existing methods. Finally, we illustrate our proposed methods with a relevant example. Copyright © 2017 John Wiley & Sons, Ltd.

CLUSFAVOR 5.0: hierarchical cluster and principal-component analysis of microarray-based transcriptional profiles

PubMed Central

Peterson, Leif E

2002-01-01

CLUSFAVOR (CLUSter and Factor Analysis with Varimax Orthogonal Rotation) 5.0 is a Windows-based computer program for hierarchical cluster and principal-component analysis of microarray-based transcriptional profiles. CLUSFAVOR 5.0 standardizes input data; sorts data according to gene-specific coefficient of variation, standard deviation, average and total expression, and Shannon entropy; performs hierarchical cluster analysis using nearest-neighbor, unweighted pair-group method using arithmetic averages (UPGMA), or furthest-neighbor joining methods, and Euclidean, correlation, or jack-knife distances; and performs principal-component analysis. PMID:12184816

Increasing the stability of the articulated lorry at braking by locking the fifth wheel coupling

NASA Astrophysics Data System (ADS)

Skotnikov, G. I.; Jileykin, M. M.; Komissarov, A. I.

2018-02-01

The jackknifing of the articulated lorry is determined by the loss of stability with respect to the vertical axis of the fifth wheel coupling, which can be caused by the failure of the brake system, the displacement of the center of mass of the semitrailer or tractor from the longitudinal axis of the vehicle, the road parameters (longitudinal and transverse slopes), the difference in the friction coefficients under the sides of the articulated lorry. In this regard, the issue of creating devices that prevent the jackknifing, and their control systems is important. A method is proposed for maintaining the stability of the movement of articulated lorry when braking both on a straight line and in a turn by blocking the relative rotation of the tractor and the trailer. Blocking occurs due to the creation of a stabilizing moment in the direction opposite to the angular rate of folding. To test the developed algorithm for locking the fifth wheel coupling, a mathematical model of the spatial motion of the articulated lorry was developed, including the models of interaction of an elastic tire with a rigid terrain, suspension systems, transmission, steering, fifth-wheel coupling. The efficiency and effectiveness of the coupling locking control system is proved by comparing the results of the simulation of a straight-line braking and braking in turn. It is shown that the application of the control system significantly increases the stability of the road train.

ROCView: prototype software for data collection in jackknife alternative free-response receiver operating characteristic analysis

PubMed Central

Thompson, J; Hogg, P; Thompson, S; Manning, D; Szczepura, K

2012-01-01

ROCView has been developed as an image display and response capture (IDRC) solution to image display and consistent recording of reader responses in relation to the free-response receiver operating characteristic paradigm. A web-based solution to IDRC for observer response studies allows observations to be completed from any location, assuming that display performance and viewing conditions are consistent with the study being completed. The simplistic functionality of the software allows observations to be completed without supervision. ROCView can display images from multiple modalities, in a randomised order if required. Following registration, observers are prompted to begin their image evaluation. All data are recorded via mouse clicks, one to localise (mark) and one to score confidence (rate) using either an ordinal or continuous rating scale. Up to nine “mark-rating” pairs can be made per image. Unmarked images are given a default score of zero. Upon completion of the study, both true-positive and false-positive reports can be downloaded and adapted for analysis. ROCView has the potential to be a useful tool in the assessment of modality performance difference for a range of imaging methods. PMID:22573294

Nonparametric Estimation of Distribution and Density Functions with Applications.

DTIC Science & Technology

1982-05-01

8 > Z C.. o i, ,- 4 8 ...S C[ 17 : - j 46 0- IA ~ IL ar’ D rn B- - 4 -4A B- 8 ~a *~jai 188 the jackknife may be found in Gray, et al., and Cressie (Refs 15,28). Analogous to...convergence. 21 =7w; Ul I 0083 q C/) 22S , WJ 8 , J035 224 43 UC I a- 04 14 Q) ’I 4 -4a-Q 23z Let R1 be the real line, the borel field on R 1 and P,

Effect of trapping methods on the estimation of alpha diversity of a phlebotomine sandfly assemblage in southern Mexico.

PubMed

Rodríguez-Rojas, J J; Rebollar-Téllez, E A

2017-12-01

The aims of the study were to (a) investigate the effect of trapping methods on alpha diversity; and (b) enhance the knowledge of the sandfly assemblage in the state of Quintana Roo. Field work was undertaken in a tropical forest of southern Mexico from August 2013 to July 2014. Sampling was conducted monthly during three consecutive nights. For each trapping night, 12 different types of trap were operated from 18.00 to 24.00 hours in four transects. Measures of alpha community diversity were based on the quantification of the number of species (Chao 2, Jackknife 2, Clench's equation, Margalef's index) and the community structure, as well as the dominance (Simpson and Berger-Parker indexes) and evenness (Shannon's entropy index, true diversity of the Jost and Pielou index). With a total sampling effort of 1728 night-traps, 16 101 phlebotomine sandflies were collected; they represented two genera and 13 species. Diversity estimates of 100% (Chao 2 and Clench's equation) and 85% (Jackknife 2) of potential species in the study area were calculated. Shannon traps and CDC light traps indicated the largest number of species, but only Shannon traps showed the greatest abundance. This inventory of sandflies is an important activity to enhance our knowledge of sandfly assemblages and guilds. The ultimate goal of studying alpha diversity in sandflies would be to have a better understanding of the population dynamics and all complex networks of interactions that may, in turn, be associated with the epidemiology of the disease. © 2017 The Royal Entomological Society.

Thin-plate spline analysis of the cranial base in African, Asian and European populations and its relationship with different malocclusions.

PubMed

Rosas, Antonio; Bastir, Markus; Alarcón, Jose Antonio; Kuroe, Kazuto

2008-09-01

To test the hypothesis that midline basicranial orientation and posterior cranial base length are discriminating factors between adults of different populations and its potential maxillo/mandibular disharmonies. Twenty-nine 2D landmarks of the midline cranial base, the face and the mandible of dry skull X-rays from three major populations (45 Asians, 34 Africans, 64 Europeans) were digitized and analysed by geometric morphometrics. We used, first, MANOVA to test for mean shape differences between populations; then, principal components analysis (PCA) to assess the overall variation in the sample and finally, canonical variate analysis (CVA) with jack-knife validations (N=1000) to analyse the anatomical features that best distinguished among populations. Significant mean shapes differences were shown between populations (P<0.001). CVA revealed two significant axes of discrimination (P<0.001). Jack-knife validation correctly identified 92% of 15,000 unknowns. In Africans the whole cranial base is rotated into a forward-downward position, while in Asians it is rotated in the opposite way. The Europeans occupied an intermediate position. African and Asian samples showed a maxillo/mandibular prognathism. African prognathism was produced by an anterior positioned maxilla, Asian prognathism by retruded anterior cranial base and increase of the posterior cranial base length. Europeans showed a trend towards retracted mandibles with relatively shorter posterior cranial bases. The results supported the hypothesis that basicranial orientation and posterior cranial base length are valid factors to distinguish between geographic groups. The whole craniofacial configuration underlying a particular maxillo-facial disharmony must be considered in diagnosis, growth predictions and resulting treatment planning.

Statistical innovations in diagnostic device evaluation.

PubMed

Yu, Tinghui; Li, Qin; Gray, Gerry; Yue, Lilly Q

2016-01-01

Due to rapid technological development, innovations in diagnostic devices are proceeding at an extremely fast pace. Accordingly, the needs for adopting innovative statistical methods have emerged in the evaluation of diagnostic devices. Statisticians in the Center for Devices and Radiological Health at the Food and Drug Administration have provided leadership in implementing statistical innovations. The innovations discussed in this article include: the adoption of bootstrap and Jackknife methods, the implementation of appropriate multiple reader multiple case study design, the application of robustness analyses for missing data, and the development of study designs and data analyses for companion diagnostics.

[Hypobaric 0.15% bupivacaine versus hyperbaric 0.5% bupivacaine for posterior (dorsal) spinal block in outpatient anorectal surgery.].

PubMed

Imbelloni, Luiz Eduardo; Vieira, Eneida Maria; Gouveia, M A; Netinho, João Gomes; Cordeiro, José Antonio

2006-12-01

The aim of this study was to study low dose hypobaric 0.15% bupivacaine and hyperbaric 0.5% bupivacaine in outpatient anorectal surgical procedures. Two groups of 50 patients, physical status ASA I and II, undergoing anorectal surgical procedures in a jackknife position, received 6 mg of hypobaric 0.15% bupivacaine in the surgical position (Group 1) or 6 mg of hyperbaric 0.5% bupivacaine in the sitting position for 5 minutes, after which they were placed in a jackknife position (Group 2). Sensitive and motor blockade, time of first urination, ambulation, complications, and the need for analgesics were evaluated. Patients were followed until the third postoperative day and questioned whether they experienced post-puncture headache or temporary neurological symptoms, and until the 30th day and questioned about permanent neurological complications. The test t Student, Mood's median, and Fisher Exact test were used for statistical analysis, and a p < 0.05 was considered significant. Every patient in Group 1 presented selective blockade of the posterior sacral nerve roots, while patients in Group 2 experienced blockade of the anterior and posterior nerve roots. Blockade was significantly higher in Group 1. Motor blockade was significantly less severe in Group 1. Forty-nine patients in Group 1 transferred to the stretcher unassisted while only 40 patients in Group 2 were able to do so. Recovery in Group 1 occurred in 105 +/- 25 minutes and in 95 +/- 15 minutes in Group 2, and this difference was not statistically significant. There were no hemodynamic changes, nausea or vomiting, urine retention, or post-puncture headache. Anorectal surgical procedures under spinal block with low dose bupivacaine, hyperbaric or hypobaric, can be safely done.

Sensitivity of super-efficient data envelopment analysis results to individual decision-making units: an example of surgical workload by specialty.

PubMed

Dexter, Franklin; O'Neill, Liam; Xin, Lei; Ledolter, Johannes

2008-12-01

We use resampling of data to explore the basic statistical properties of super-efficient data envelopment analysis (DEA) when used as a benchmarking tool by the manager of a single decision-making unit. Our focus is the gaps in the outputs (i.e., slacks adjusted for upward bias), as they reveal which outputs can be increased. The numerical experiments show that the estimates of the gaps fail to exhibit asymptotic consistency, a property expected for standard statistical inference. Specifically, increased sample sizes were not always associated with more accurate forecasts of the output gaps. The baseline DEA's gaps equaled the mode of the jackknife and the mode of resampling with/without replacement from any subset of the population; usually, the baseline DEA's gaps also equaled the median. The quartile deviations of gaps were close to zero when few decision-making units were excluded from the sample and the study unit happened to have few other units contributing to its benchmark. The results for the quartile deviations can be explained in terms of the effective combinations of decision-making units that contribute to the DEA solution. The jackknife can provide all the combinations contributing to the quartile deviation and only needs to be performed for those units that are part of the benchmark set. These results show that there is a strong rationale for examining DEA results with a sensitivity analysis that excludes one benchmark hospital at a time. This analysis enhances the quality of decision support using DEA estimates for the potential ofa decision-making unit to grow one or more of its outputs.

One-shot estimate of MRMC variance: AUC.

PubMed

Gallas, Brandon D

2006-03-01

One popular study design for estimating the area under the receiver operating characteristic curve (AUC) is the one in which a set of readers reads a set of cases: a fully crossed design in which every reader reads every case. The variability of the subsequent reader-averaged AUC has two sources: the multiple readers and the multiple cases (MRMC). In this article, we present a nonparametric estimate for the variance of the reader-averaged AUC that is unbiased and does not use resampling tools. The one-shot estimate is based on the MRMC variance derived by the mechanistic approach of Barrett et al. (2005), as well as the nonparametric variance of a single-reader AUC derived in the literature on U statistics. We investigate the bias and variance properties of the one-shot estimate through a set of Monte Carlo simulations with simulated model observers and images. The different simulation configurations vary numbers of readers and cases, amounts of image noise and internal noise, as well as how the readers are constructed. We compare the one-shot estimate to a method that uses the jackknife resampling technique with an analysis of variance model at its foundation (Dorfman et al. 1992). The name one-shot highlights that resampling is not used. The one-shot and jackknife estimators behave similarly, with the one-shot being marginally more efficient when the number of cases is small. We have derived a one-shot estimate of the MRMC variance of AUC that is based on a probabilistic foundation with limited assumptions, is unbiased, and compares favorably to an established estimate.

DAMBE7: New and Improved Tools for Data Analysis in Molecular Biology and Evolution.

PubMed

Xia, Xuhua

2018-06-01

DAMBE is a comprehensive software package for genomic and phylogenetic data analysis on Windows, Linux, and Macintosh computers. New functions include imputing missing distances and phylogeny simultaneously (paving the way to build large phage and transposon trees), new bootstrapping/jackknifing methods for PhyPA (phylogenetics from pairwise alignments), and an improved function for fast and accurate estimation of the shape parameter of the gamma distribution for fitting rate heterogeneity over sites. Previous method corrects multiple hits for each site independently. DAMBE's new method uses all sites simultaneously for correction. DAMBE, featuring a user-friendly graphic interface, is freely available from http://dambe.bio.uottawa.ca (last accessed, April 17, 2018).

Comparison of different hydrological similarity measures to estimate flow quantiles

NASA Astrophysics Data System (ADS)

Rianna, M.; Ridolfi, E.; Napolitano, F.

2017-07-01

This paper aims to evaluate the influence of hydrological similarity measures on the definition of homogeneous regions. To this end, several attribute sets have been analyzed in the context of the Region of Influence (ROI) procedure. Several combinations of geomorphological, climatological, and geographical characteristics are also used to cluster potentially homogeneous regions. To verify the goodness of the resulting pooled sites, homogeneity tests arecarried out. Through a Monte Carlo simulation and a jack-knife procedure, flow quantiles areestimated for the regions effectively resulting as homogeneous. The analysis areperformed in both the so-called gauged and ungauged scenarios to analyze the effect of hydrological measures on flow quantiles estimation.

Sample size, library composition, and genotypic diversity among natural populations of Escherichia coli from different animals influence accuracy of determining sources of fecal pollution.

PubMed

Johnson, LeeAnn K; Brown, Mary B; Carruthers, Ethan A; Ferguson, John A; Dombek, Priscilla E; Sadowsky, Michael J

2004-08-01

A horizontal, fluorophore-enhanced, repetitive extragenic palindromic-PCR (rep-PCR) DNA fingerprinting technique (HFERP) was developed and evaluated as a means to differentiate human from animal sources of Escherichia coli. Box A1R primers and PCR were used to generate 2,466 rep-PCR and 1,531 HFERP DNA fingerprints from E. coli strains isolated from fecal material from known human and 12 animal sources: dogs, cats, horses, deer, geese, ducks, chickens, turkeys, cows, pigs, goats, and sheep. HFERP DNA fingerprinting reduced within-gel grouping of DNA fingerprints and improved alignment of DNA fingerprints between gels, relative to that achieved using rep-PCR DNA fingerprinting. Jackknife analysis of the complete rep-PCR DNA fingerprint library, done using Pearson's product-moment correlation coefficient, indicated that animal and human isolates were assigned to the correct source groups with an 82.2% average rate of correct classification. However, when only unique isolates were examined, isolates from a single animal having a unique DNA fingerprint, Jackknife analysis showed that isolates were assigned to the correct source groups with a 60.5% average rate of correct classification. The percentages of correctly classified isolates were about 15 and 17% greater for rep-PCR and HFERP, respectively, when analyses were done using the curve-based Pearson's product-moment correlation coefficient, rather than the band-based Jaccard algorithm. Rarefaction analysis indicated that, despite the relatively large size of the known-source database, genetic diversity in E. coli was very great and is most likely accounting for our inability to correctly classify many environmental E. coli isolates. Our data indicate that removal of duplicate genotypes within DNA fingerprint libraries, increased database size, proper methods of statistical analysis, and correct alignment of band data within and between gels improve the accuracy of microbial source tracking methods.

Comparing performances of logistic regression and neural networks for predicting melatonin excretion patterns in the rat exposed to ELF magnetic fields.

PubMed

Jahandideh, Samad; Abdolmaleki, Parviz; Movahedi, Mohammad Mehdi

2010-02-01

Various studies have been reported on the bioeffects of magnetic field exposure; however, no consensus or guideline is available for experimental designs relating to exposure conditions as yet. In this study, logistic regression (LR) and artificial neural networks (ANNs) were used in order to analyze and predict the melatonin excretion patterns in the rat exposed to extremely low frequency magnetic fields (ELF-MF). Subsequently, on a database containing 33 experiments, performances of LR and ANNs were compared through resubstitution and jackknife tests. Predictor variables were more effective parameters and included frequency, polarization, exposure duration, and strength of magnetic fields. Also, five performance measures including accuracy, sensitivity, specificity, Matthew's Correlation Coefficient (MCC) and normalized percentage, better than random (S) were used to evaluate the performance of models. The LR as a conventional model obtained poor prediction performance. Nonetheless, LR distinguished the duration of magnetic fields as a statistically significant parameter. Also, horizontal polarization of magnetic fields with the highest logit coefficient (or parameter estimate) with negative sign was found to be the strongest indicator for experimental designs relating to exposure conditions. This means that each experiment with horizontal polarization of magnetic fields has a higher probability to result in "not changed melatonin level" pattern. On the other hand, ANNs, a more powerful model which has not been introduced in predicting melatonin excretion patterns in the rat exposed to ELF-MF, showed high performance measure values and higher reliability, especially obtaining 0.55 value of MCC through jackknife tests. Obtained results showed that such predictor models are promising and may play a useful role in defining guidelines for experimental designs relating to exposure conditions. In conclusion, analysis of the bioelectromagnetic data could result in

Assessing the Reliability of Regional Depth-Duration-Frequency Equations for Gauged and Ungauged Sites

NASA Astrophysics Data System (ADS)

Castellarin, A.; Montanari, A.; Brath, A.

2002-12-01

The study derives Regional Depth-Duration-Frequency (RDDF) equations for a wide region of northern-central Italy (37,200 km 2) by following an adaptation of the approach originally proposed by Alila [WRR, 36(7), 2000]. The proposed RDDF equations have a rather simple structure and allow an estimation of the design storm, defined as the rainfall depth expected for a given storm duration and recurrence interval, in any location of the study area for storm durations from 1 to 24 hours and for recurrence intervals up to 100 years. The reliability of the proposed RDDF equations represents the main concern of the study and it is assessed at two different levels. The first level considers the gauged sites and compares estimates of the design storm obtained with the RDDF equations with at-site estimates based upon the observed annual maximum series of rainfall depth and with design storm estimates resulting from a regional estimator recently developed for the study area through a Hierarchical Regional Approach (HRA) [Gabriele and Arnell, WRR, 27(6), 1991]. The second level performs a reliability assessment of the RDDF equations for ungauged sites by means of a jack-knife procedure. Using the HRA estimator as a reference term, the jack-knife procedure assesses the reliability of design storm estimates provided by the RDDF equations for a given location when dealing with the complete absence of pluviometric information. The results of the analysis show that the proposed RDDF equations represent practical and effective computational means for producing a first guess of the design storm at the available raingauges and reliable design storm estimates for ungauged locations. The first author gratefully acknowledges D.H. Burn for sponsoring the submission of the present abstract.

Integrating local pastoral knowledge, participatory mapping, and species distribution modeling for risk assessment of invasive rubber vine (Cryptostegia grandiflora) in Ethiopia’s Afar region

USGS Publications Warehouse

Luizza, Matthew; Wakie, Tewodros; Evangelista, Paul; Jarnevich, Catherine S.

2016-01-01

The threats posed by invasive plants span ecosystems and economies worldwide. Local knowledge of biological invasions has proven beneficial for invasive species research, but to date no work has integrated this knowledge with species distribution modeling for invasion risk assessments. In this study, we integrated pastoral knowledge with Maxent modeling to assess the suitable habitat and potential impacts of invasive Cryptostegia grandiflora Robx. Ex R.Br. (rubber vine) in Ethiopia’s Afar region. We conducted focus groups with seven villages across the Amibara and Awash-Fentale districts. Pastoral knowledge revealed the growing threat of rubber vine, which to date has received limited attention in Ethiopia, and whose presence in Afar was previously unknown to our team. Rubber vine occurrence points were collected in the field with pastoralists and processed in Maxent with MODIS-derived vegetation indices, topographic data, and anthropogenic variables. We tested model fit using a jackknife procedure and validated the final model with an independent occurrence data set collected through participatory mapping activities with pastoralists. A Multivariate Environmental Similarity Surface analysis revealed areas with novel environmental conditions for future targeted surveys. Model performance was evaluated using area under the receiver-operating characteristic curve (AUC) and showed good fit across the jackknife models (average AUC = 0.80) and the final model (test AUC = 0.96). Our results reveal the growing threat rubber vine poses to Afar, with suitable habitat extending downstream of its current known location in the middle Awash River basin. Local pastoral knowledge provided important context for its rapid expansion due to acute changes in seasonality and habitat alteration, in addition to threats posed to numerous endemic tree species that provide critical provisioning ecosystem services. This work demonstrates the utility of integrating local ecological

Predicting Presynaptic and Postsynaptic Neurotoxins by Developing Feature Selection Technique

PubMed Central

Yang, Yunchun; Zhang, Chunmei; Chen, Rong; Huang, Po

2017-01-01

Presynaptic and postsynaptic neurotoxins are proteins which act at the presynaptic and postsynaptic membrane. Correctly predicting presynaptic and postsynaptic neurotoxins will provide important clues for drug-target discovery and drug design. In this study, we developed a theoretical method to discriminate presynaptic neurotoxins from postsynaptic neurotoxins. A strict and objective benchmark dataset was constructed to train and test our proposed model. The dipeptide composition was used to formulate neurotoxin samples. The analysis of variance (ANOVA) was proposed to find out the optimal feature set which can produce the maximum accuracy. In the jackknife cross-validation test, the overall accuracy of 94.9% was achieved. We believe that the proposed model will provide important information to study neurotoxins. PMID:28303250

Latency as a region contrast: Measuring ERP latency differences with Dynamic Time Warping.

PubMed

Zoumpoulaki, A; Alsufyani, A; Filetti, M; Brammer, M; Bowman, H

2015-12-01

Methods for measuring onset latency contrasts are evaluated against a new method utilizing the dynamic time warping (DTW) algorithm. This new method allows latency to be measured across a region instead of single point. We use computer simulations to compare the methods' power and Type I error rates under different scenarios. We perform per-participant analysis for different signal-to-noise ratios and two sizes of window (broad vs. narrow). In addition, the methods are tested in combination with single-participant and jackknife average waveforms for different effect sizes, at the group level. DTW performs better than the other methods, being less sensitive to noise as well as to placement and width of the window selected. © 2015 Society for Psychophysiological Research.

Random forests of interaction trees for estimating individualized treatment effects in randomized trials.

PubMed

Su, Xiaogang; Peña, Annette T; Liu, Lei; Levine, Richard A

2018-04-29

Assessing heterogeneous treatment effects is a growing interest in advancing precision medicine. Individualized treatment effects (ITEs) play a critical role in such an endeavor. Concerning experimental data collected from randomized trials, we put forward a method, termed random forests of interaction trees (RFIT), for estimating ITE on the basis of interaction trees. To this end, we propose a smooth sigmoid surrogate method, as an alternative to greedy search, to speed up tree construction. The RFIT outperforms the "separate regression" approach in estimating ITE. Furthermore, standard errors for the estimated ITE via RFIT are obtained with the infinitesimal jackknife method. We assess and illustrate the use of RFIT via both simulation and the analysis of data from an acupuncture headache trial. Copyright © 2018 John Wiley & Sons, Ltd.

Fast Computation of the Two-Point Correlation Function in the Age of Big Data

NASA Astrophysics Data System (ADS)

Pellegrino, Andrew; Timlin, John

2018-01-01

We present a new code which quickly computes the two-point correlation function for large sets of astronomical data. This code combines the ease of use of Python with the speed of parallel shared libraries written in C. We include the capability to compute the auto- and cross-correlation statistics, and allow the user to calculate the three-dimensional and angular correlation functions. Additionally, the code automatically divides the user-provided sky masks into contiguous subsamples of similar size, using the HEALPix pixelization scheme, for the purpose of resampling. Errors are computed using jackknife and bootstrap resampling in a way that adds negligible extra runtime, even with many subsamples. We demonstrate comparable speed with other clustering codes, and code accuracy compared to known and analytic results.

Exponentially Decelerated Contrast Media Injection Rate Combined With a Novel Patient-Specific Contrast Formula Reduces Contrast Volume Administration and Radiation Dose During Computed Tomography Pulmonary Angiography.

PubMed

Saade, Charbel; Mayat, Ahmad; El-Merhi, Fadi

2016-01-01

Matching contrast injection timing with vessel dynamics significantly improves vessel opacification and reduces contrast dose in the assessment of pulmonary embolism during computed tomography (CT) pulmonary angiography. The aim of this study was to investigate opacification of the pulmonary vasculature (PV) during CT pulmonary angiography using a patient-specific contrast formula (PSCF) and exponentially decelerated contrast media (EDCM) injection rate. Institutional review board approved this retrospective study. Computed tomography pulmonary angiography was performed on 200 patients with suspected pulmonary embolism using a 64-channel CT scanner. Patient demographics were equally distributed. Patients were randomly assigned to 2 equal protocol groups: protocol A used a PSCF, and protocol B involved the use of a PSCF combined with EDCM. The mean cross-sectional opacification profile of 8 central and 11 peripheral PVs were measured for each patient, and arteriovenous contrast ratio was calculated. Protocols were compared using Mann-Whitney U nonparametric statistics. Jackknife alternative free-response receiver operating characteristic analyses were used to assess diagnostic efficacy. Interobserver variations were investigated using kappa methods. A number of pulmonary arteries demonstrated increases in opacification (P < 0.02) for protocol B compared with A, whereas opacification in all veins was reduced in protocol B (P < 0.03). Subsequently, increased arteriovenous contrast ratio in protocol B compared with A was observed at all anatomic locations (P < 0.0002). An increase in jackknife alternative free-response receiver operating characteristic figure of merit (P < 0.0002) and interobserver variation was observed with protocol B compared with protocol A (κ = 0.3-0.73). Mean contrast volume was reduced in protocol B (29 [4] mL) compared with protocol A (33 [9] mL). Mean effective radiation dose in protocol B (1.2 [0.4] mSv) was reduced by 14% compared with

Search for Long Period Solar Normal Modes in Ambient Seismic Noise

NASA Astrophysics Data System (ADS)

Caton, R.; Pavlis, G. L.

2016-12-01

We search for evidence of solar free oscillations (normal modes) in long period seismic data through multitaper spectral analysis of array stacks. This analysis is similar to that of Thomson & Vernon (2015), who used data from the most quiet single stations of the global seismic network. Our approach is to use stacks of large arrays of noisier stations to reduce noise. Arrays have the added advantage of permitting the use of nonparametic statistics (jackknife errors) to provide objective error estimates. We used data from the Transportable Array, the broadband borehole array at Pinyon Flat, and the 3D broadband array in Homestake Mine in Lead, SD. The Homestake Mine array has 15 STS-2 sensors deployed in the mine that are extremely quiet at long periods due to stable temperatures and stable piers anchored to hard rock. The length of time series used ranged from 50 days to 85 days. We processed the data by low-pass filtering with a corner frequency of 10 mHz, followed by an autoregressive prewhitening filter and median stack. We elected to use the median instead of the mean in order to get a more robust stack. We then used G. Prieto's mtspec library to compute multitaper spectrum estimates on the data. We produce delete-one jackknife error estimates of the uncertainty at each frequency by computing median stacks of all data with one station removed. The results from the TA data show tentative evidence for several lines between 290 μHz and 400 μHz, including a recurring line near 379 μHz. This 379 μHz line is near the Earth mode 0T2 and the solar mode 5g5, suggesting that 5g5 could be coupling into the Earth mode. Current results suggest more statistically significant lines may be present in Pinyon Flat data, but additional processing of the data is underway to confirm this observation.

Statistical inference based on the nonparametric maximum likelihood estimator under double-truncation.

PubMed

Emura, Takeshi; Konno, Yoshihiko; Michimae, Hirofumi

2015-07-01

Doubly truncated data consist of samples whose observed values fall between the right- and left- truncation limits. With such samples, the distribution function of interest is estimated using the nonparametric maximum likelihood estimator (NPMLE) that is obtained through a self-consistency algorithm. Owing to the complicated asymptotic distribution of the NPMLE, the bootstrap method has been suggested for statistical inference. This paper proposes a closed-form estimator for the asymptotic covariance function of the NPMLE, which is computationally attractive alternative to bootstrapping. Furthermore, we develop various statistical inference procedures, such as confidence interval, goodness-of-fit tests, and confidence bands to demonstrate the usefulness of the proposed covariance estimator. Simulations are performed to compare the proposed method with both the bootstrap and jackknife methods. The methods are illustrated using the childhood cancer dataset.

Using the concept of pseudo amino acid composition to predict resistance gene against Xanthomonas oryzae pv. oryzae in rice: an approach from chaos games representation.

PubMed

Jingbo, Xia; Silan, Zhang; Feng, Shi; Huijuan, Xiong; Xuehai, Hu; Xiaohui, Niu; Zhi, Li

2011-09-07

To evaluate the possibility of an unknown protein to be a resistant gene against Xanthomonas oryzae pv. oryzae, a different mode of pseudo amino acid composition (PseAAC) is proposed to formulate the protein samples by integrating the amino acid composition, as well as the Chaos games representation (CGR) method. Some numerical comparisons of triangle, quadrangle and 12-vertex polygon CGR are carried to evaluate the efficiency of using these fractal figures in classifiers. The numerical results show that among the three polygon methods, triangle method owns a good fractal visualization and performs the best in the classifier construction. By using triangle + 12-vertex polygon CGR as the mathematical feature, the classifier achieves 98.13% in Jackknife test and MCC achieves 0.8462. Copyright © 2011 Elsevier Ltd. All rights reserved.

Avian community response to small-scale habitat disturbance in Maine

USGS Publications Warehouse

Derleth, E.L.; McAuley, D.G.; Dwyer, T.J.

1989-01-01

The effects of small clearcuts (1 - 8 ha) on avian communities in the forest of eastern Maine were studied using point counts during spring 1978 - 1981. Surveys were conducted in uncut (control) and clear-cut (treatment) plots in three stand types: conifer, hardwood, and mixed growth. We used a mark-recapture model and its associated jackknife species richness estimator (N), as an indicator of avian community structure. Increases in estimated richness (N) and Shannon - Weaver diversity (H') were noted in the treated hardwood and mixed growth, but not in the conifer stands. Seventeen avian species increased in relative abundance, whereas two species declined. Stand treatment was associated with important changes in bird species composition. Increased habitat patchiness and the creation of forest edge are hypothesized as causes for the greater estimates of richness and diversity.

Persistent topographic quantitative EEG sequelae of chronic marihuana use: a replication study and initial discriminant function analysis.

PubMed

Struve, F A; Straumanis, J J; Patrick, G

1994-04-01

In a previous pilot study using psychiatric patients we reported that daily marihuana users had significant elevations of (1) Absolute Alpha Power, (2) Relative Alpha Power, and (3) Interhemispheric Alpha Coherence over both frontal and frontal-central areas when contrasted with subjects who did not use marihuana. We referred to this phenomenon as Hyperfrontality of Alpha. The study presented here is a successful replication of our previous findings using new samples of subjects and identical methods. Post hoc analyses based on the combined sample from both studies suggest that variables of psychiatric diagnoses and medication did not bias our results. In addition, a discriminant function analysis using quantitative EEG variables as candidate predictors generated a 95% correct THC user versus nonuser classification accuracy which received a successful jackknife replication.

Alignment-free microbial phylogenomics under scenarios of sequence divergence, genome rearrangement and lateral genetic transfer.

PubMed

Bernard, Guillaume; Chan, Cheong Xin; Ragan, Mark A

2016-07-01

Alignment-free (AF) approaches have recently been highlighted as alternatives to methods based on multiple sequence alignment in phylogenetic inference. However, the sensitivity of AF methods to genome-scale evolutionary scenarios is little known. Here, using simulated microbial genome data we systematically assess the sensitivity of nine AF methods to three important evolutionary scenarios: sequence divergence, lateral genetic transfer (LGT) and genome rearrangement. Among these, AF methods are most sensitive to the extent of sequence divergence, less sensitive to low and moderate frequencies of LGT, and most robust against genome rearrangement. We describe the application of AF methods to three well-studied empirical genome datasets, and introduce a new application of the jackknife to assess node support. Our results demonstrate that AF phylogenomics is computationally scalable to multi-genome data and can generate biologically meaningful phylogenies and insights into microbial evolution.

Prediction of beta-turns with learning machines.

PubMed

Cai, Yu-Dong; Liu, Xiao-Jun; Li, Yi-Xue; Xu, Xue-biao; Chou, Kuo-Chen

2003-05-01

The support vector machine approach was introduced to predict the beta-turns in proteins. The overall self-consistency rate by the re-substitution test for the training or learning dataset reached 100%. Both the training dataset and independent testing dataset were taken from Chou [J. Pept. Res. 49 (1997) 120]. The success prediction rates by the jackknife test for the beta-turn subset of 455 tetrapeptides and non-beta-turn subset of 3807 tetrapeptides in the training dataset were 58.1 and 98.4%, respectively. The success rates with the independent dataset test for the beta-turn subset of 110 tetrapeptides and non-beta-turn subset of 30,231 tetrapeptides were 69.1 and 97.3%, respectively. The results obtained from this study support the conclusion that the residue-coupled effect along a tetrapeptide is important for the formation of a beta-turn.

Optimal subset selection of primary sequence features using the genetic algorithm for thermophilic proteins identification.

PubMed

Wang, LiQiang; Li, CuiFeng

2014-10-01

A genetic algorithm (GA) coupled with multiple linear regression (MLR) was used to extract useful features from amino acids and g-gap dipeptides for distinguishing between thermophilic and non-thermophilic proteins. The method was trained by a benchmark dataset of 915 thermophilic and 793 non-thermophilic proteins. The method reached an overall accuracy of 95.4 % in a Jackknife test using nine amino acids, 38 0-gap dipeptides and 29 1-gap dipeptides. The accuracy as a function of protein size ranged between 85.8 and 96.9 %. The overall accuracies of three independent tests were 93, 93.4 and 91.8 %. The observed results of detecting thermophilic proteins suggest that the GA-MLR approach described herein should be a powerful method for selecting features that describe thermostabile machines and be an aid in the design of more stable proteins.

Hierarchical Bayes estimation of species richness and occupancy in spatially replicated surveys

USGS Publications Warehouse

Kery, M.; Royle, J. Andrew

2008-01-01

1. Species richness is the most widely used biodiversity metric, but cannot be observed directly as, typically, some species are overlooked. Imperfect detectability must therefore be accounted for to obtain unbiased species-richness estimates. When richness is assessed at multiple sites, two approaches can be used to estimate species richness: either estimating for each site separately, or pooling all samples. The first approach produces imprecise estimates, while the second loses site-specific information. 2. In contrast, a hierarchical Bayes (HB) multispecies site-occupancy model benefits from the combination of information across sites without losing site-specific information and also yields occupancy estimates for each species. The heart of the model is an estimate of the incompletely observed presence-absence matrix, a centrepiece of biogeography and monitoring studies. We illustrate the model using Swiss breeding bird survey data, and compare its estimates with the widely used jackknife species-richness estimator and raw species counts. 3. Two independent observers each conducted three surveys in 26 1-km(2) quadrats, and detected 27-56 (total 103) species. The average estimated proportion of species detected after three surveys was 0.87 under the HB model. Jackknife estimates were less precise (less repeatable between observers) than raw counts, but HB estimates were as repeatable as raw counts. The combination of information in the HB model thus resulted in species-richness estimates presumably at least as unbiased as previous approaches that correct for detectability, but without costs in precision relative to uncorrected, biased species counts. 4. Total species richness in the entire region sampled was estimated at 113.1 (CI 106-123); species detectability ranged from 0.08 to 0.99, illustrating very heterogeneous species detectability; and species occupancy was 0.06-0.96. Even after six surveys, absolute bias in observed occupancy was estimated at up to 0

Linear regression in astronomy. II

NASA Technical Reports Server (NTRS)

Feigelson, Eric D.; Babu, Gutti J.

1992-01-01

A wide variety of least-squares linear regression procedures used in observational astronomy, particularly investigations of the cosmic distance scale, are presented and discussed. The classes of linear models considered are (1) unweighted regression lines, with bootstrap and jackknife resampling; (2) regression solutions when measurement error, in one or both variables, dominates the scatter; (3) methods to apply a calibration line to new data; (4) truncated regression models, which apply to flux-limited data sets; and (5) censored regression models, which apply when nondetections are present. For the calibration problem we develop two new procedures: a formula for the intercept offset between two parallel data sets, which propagates slope errors from one regression to the other; and a generalization of the Working-Hotelling confidence bands to nonstandard least-squares lines. They can provide improved error analysis for Faber-Jackson, Tully-Fisher, and similar cosmic distance scale relations.

Geary autocorrelation and DCCA coefficient: Application to predict apoptosis protein subcellular localization via PSSM

NASA Astrophysics Data System (ADS)

Liang, Yunyun; Liu, Sanyang; Zhang, Shengli

2017-02-01

Apoptosis is a fundamental process controlling normal tissue homeostasis by regulating a balance between cell proliferation and death. Predicting subcellular location of apoptosis proteins is very helpful for understanding its mechanism of programmed cell death. Prediction of apoptosis protein subcellular location is still a challenging and complicated task, and existing methods mainly based on protein primary sequences. In this paper, we propose a new position-specific scoring matrix (PSSM)-based model by using Geary autocorrelation function and detrended cross-correlation coefficient (DCCA coefficient). Then a 270-dimensional (270D) feature vector is constructed on three widely used datasets: ZD98, ZW225 and CL317, and support vector machine is adopted as classifier. The overall prediction accuracies are significantly improved by rigorous jackknife test. The results show that our model offers a reliable and effective PSSM-based tool for prediction of apoptosis protein subcellular localization.

Quantitative Structure-Activity Relationship of Insecticidal Activity of Benzyl Ether Diamidine Derivatives

NASA Astrophysics Data System (ADS)

Zhai, Mengting; Chen, Yan; Li, Jing; Zhou, Jun

2017-12-01

The molecular electrongativity distance vector (MEDV-13) was used to describe the molecular structure of benzyl ether diamidine derivatives in this paper, Based on MEDV-13, The three-parameter (M 3, M 15, M 47) QSAR model of insecticidal activity (pIC 50) for 60 benzyl ether diamidine derivatives was constructed by leaps-and-bounds regression (LBR) . The traditional correlation coefficient (R) and the cross-validation correlation coefficient (R CV ) were 0.975 and 0.971, respectively. The robustness of the regression model was validated by Jackknife method, the correlation coefficient R were between 0.971 and 0.983. Meanwhile, the independent variables in the model were tested to be no autocorrelation. The regression results indicate that the model has good robust and predictive capabilities. The research would provide theoretical guidance for the development of new generation of anti African trypanosomiasis drugs with efficiency and low toxicity.

Parametric, bootstrap, and jackknife variance estimators for the k-Nearest Neighbors technique with illustrations using forest inventory and satellite image data

Treesearch

Ronald E. McRoberts; Steen Magnussen; Erkki O. Tomppo; Gherardo Chirici

2011-01-01

Nearest neighbors techniques have been shown to be useful for estimating forest attributes, particularly when used with forest inventory and satellite image data. Published reports of positive results have been truly international in scope. However, for these techniques to be more useful, they must be able to contribute to scientific inference which, for sample-based...

Gulls identified as major source of fecal pollution in coastal waters: a microbial source tracking study.

PubMed

Araújo, Susana; Henriques, Isabel S; Leandro, Sérgio Miguel; Alves, Artur; Pereira, Anabela; Correia, António

2014-02-01

Gulls were reported as sources of fecal pollution in coastal environments and potential vectors of human infections. Microbial source tracking (MST) methods were rarely tested to identify this pollution origin. This study was conducted to ascertain the source of water fecal contamination in the Berlenga Island, Portugal. A total of 169 Escherichia coli isolates from human sewage, 423 isolates from gull feces and 334 water isolates were analyzed by BOX-PCR. An average correct classification of 79.3% was achieved. When an 85% similarity cutoff was applied 24% of water isolates were present in gull feces against 2.7% detected in sewage. Jackknifing resulted in 29.3% of water isolates classified as gull, and 10.8% classified as human. Results indicate that gulls constitute a major source of water contamination in the Berlenga Island. This study validated a methodology to differentiate human and gull fecal pollution sources in a real case of a contaminated beach. © 2013.

Authentication of the botanical and geographical origin of honey by mid-infrared spectroscopy.

PubMed

Ruoff, Kaspar; Luginbühl, Werner; Künzli, Raphael; Iglesias, María Teresa; Bogdanov, Stefan; Bosset, Jacques Olivier; von der Ohe, Katharina; von der Ohe, Werner; Amado, Renato

2006-09-06

The potential of Fourier transform mid-infrared spectroscopy (FT-MIR) using an attenuated total reflectance (ATR) cell was evaluated for the authentication of 11 unifloral (acacia, alpine rose, chestnut, dandelion, heather, lime, rape, fir honeydew, metcalfa honeydew, oak honeydew) and polyfloral honey types (n = 411 samples) previously classified with traditional methods such as chemical, pollen, and sensory analysis. Chemometric evaluation of the spectra was carried out by applying principal component analysis and linear discriminant analysis, the error rates of the discriminant models being calculated by using Bayes' theorem. The error rates ranged from <0.1% (polyfloral and heather honeys as well as honeydew honeys from metcalfa, oak, and fir) to 8.3% (alpine rose honey) in both jackknife classification and validation, depending on the honey type considered. This study indicates that ATR-MIR spectroscopy is a valuable tool for the authentication of the botanical origin and quality control and may also be useful for the determination of the geographical origin of honey.

Mixed model approaches for diallel analysis based on a bio-model.

PubMed

Zhu, J; Weir, B S

1996-12-01

A MINQUE(1) procedure, which is minimum norm quadratic unbiased estimation (MINQUE) method with 1 for all the prior values, is suggested for estimating variance and covariance components in a bio-model for diallel crosses. Unbiasedness and efficiency of estimation were compared for MINQUE(1), restricted maximum likelihood (REML) and MINQUE theta which has parameter values for the prior values. MINQUE(1) is almost as efficient as MINQUE theta for unbiased estimation of genetic variance and covariance components. The bio-model is efficient and robust for estimating variance and covariance components for maternal and paternal effects as well as for nuclear effects. A procedure of adjusted unbiased prediction (AUP) is proposed for predicting random genetic effects in the bio-model. The jack-knife procedure is suggested for estimation of sampling variances of estimated variance and covariance components and of predicted genetic effects. Worked examples are given for estimation of variance and covariance components and for prediction of genetic merits.

Dirichlet Component Regression and its Applications to Psychiatric Data.

PubMed

Gueorguieva, Ralitza; Rosenheck, Robert; Zelterman, Daniel

2008-08-15

We describe a Dirichlet multivariable regression method useful for modeling data representing components as a percentage of a total. This model is motivated by the unmet need in psychiatry and other areas to simultaneously assess the effects of covariates on the relative contributions of different components of a measure. The model is illustrated using the Positive and Negative Syndrome Scale (PANSS) for assessment of schizophrenia symptoms which, like many other metrics in psychiatry, is composed of a sum of scores on several components, each in turn, made up of sums of evaluations on several questions. We simultaneously examine the effects of baseline socio-demographic and co-morbid correlates on all of the components of the total PANSS score of patients from a schizophrenia clinical trial and identify variables associated with increasing or decreasing relative contributions of each component. Several definitions of residuals are provided. Diagnostics include measures of overdispersion, Cook's distance, and a local jackknife influence metric.

Dirichlet Component Regression and its Applications to Psychiatric Data

PubMed Central

Gueorguieva, Ralitza; Rosenheck, Robert; Zelterman, Daniel

2011-01-01

Summary We describe a Dirichlet multivariable regression method useful for modeling data representing components as a percentage of a total. This model is motivated by the unmet need in psychiatry and other areas to simultaneously assess the effects of covariates on the relative contributions of different components of a measure. The model is illustrated using the Positive and Negative Syndrome Scale (PANSS) for assessment of schizophrenia symptoms which, like many other metrics in psychiatry, is composed of a sum of scores on several components, each in turn, made up of sums of evaluations on several questions. We simultaneously examine the effects of baseline socio-demographic and co-morbid correlates on all of the components of the total PANSS score of patients from a schizophrenia clinical trial and identify variables associated with increasing or decreasing relative contributions of each component. Several definitions of residuals are provided. Diagnostics include measures of overdispersion, Cook’s distance, and a local jackknife influence metric. PMID:22058582

Dissociable executive functions in behavioral variant frontotemporal and Alzheimer dementias

PubMed Central

Feigenbaum, Dana; Rankin, Katherine P.; Smith, Glenn E.; Boxer, Adam L.; Wood, Kristie; Hanna, Sherrie M.; Miller, Bruce L.; Kramer, Joel H.

2013-01-01

Objective: The objective of this study was to determine which aspects of executive functions are most affected in behavioral variant frontotemporal dementia (bvFTD) and best differentiate this syndrome from Alzheimer disease (AD). Methods: We compared executive functions in 22 patients diagnosed with bvFTD, 26 with AD, and 31 neurologically healthy controls using a conceptually driven and comprehensive battery of executive function tests, the NIH EXAMINER battery (http://examiner.ucsf.edu). Results: The bvFTD and the AD patients were similarly impaired compared with controls on tests of working memory, category fluency, and attention, but the patients with bvFTD showed significantly more severe impairments than the patients with AD on tests of letter fluency, antisaccade accuracy, social decision-making, and social behavior. Discriminant function analysis with jackknifed cross-validation classified the bvFTD and AD patient groups with 73% accuracy. Conclusions: Executive function assessment can support bvFTD diagnosis when measures are carefully selected to emphasize frontally specific functions. PMID:23658382

A novel representation for apoptosis protein subcellular localization prediction using support vector machine.

PubMed

Zhang, Li; Liao, Bo; Li, Dachao; Zhu, Wen

2009-07-21

Apoptosis, or programmed cell death, plays an important role in development of an organism. Obtaining information on subcellular location of apoptosis proteins is very helpful to understand the apoptosis mechanism. In this paper, based on the concept that the position distribution information of amino acids is closely related with the structure and function of proteins, we introduce the concept of distance frequency [Matsuda, S., Vert, J.P., Ueda, N., Toh, H., Akutsu, T., 2005. A novel representation of protein sequences for prediction of subcellular location using support vector machines. Protein Sci. 14, 2804-2813] and propose a novel way to calculate distance frequencies. In order to calculate the local features, each protein sequence is separated into p parts with the same length in our paper. Then we use the novel representation of protein sequences and adopt support vector machine to predict subcellular location. The overall prediction accuracy is significantly improved by jackknife test.

Estimating biogas production of biologically treated municipal solid waste.

PubMed

Scaglia, Barbara; Confalonieri, Roberto; D'Imporzano, Giuliana; Adani, Fabrizio

2010-02-01

In this work, a respirometric approach, i.e., Dynamic Respiration Index (DRI), was used to predict the anaerobic biogas potential (ABP), studying 46 waste samples coming directly from MBT full-scale plants. A significant linear regression model was obtained by a jackknife approach: ABP=(34.4+/-2.5)+(0.109+/-0.003).DRI. The comparison of the model of this work with those of the previous works using a different respirometric approach (Sapromat-AT(4)), allowed obtaining similar results and carrying out direct comparison of different limits to accept treated waste in landfill, proposed in the literature. The results indicated that on an average, MBT treatment allowed 56% of ABP reduction after 4weeks of treatment, and 79% reduction after 12weeks of treatment. The obtainment of another regression model allowed transforming Sapromat-AT(4) limit in DRI units, and achieving a description of the kinetics of DRI and the corresponding ABP reductions vs. MBT treatment-time.

Overcoming confounded controls in the analysis of gene expression data from microarray experiments.

PubMed

Bhattacharya, Soumyaroop; Long, Dang; Lyons-Weiler, James

2003-01-01

A potential limitation of data from microarray experiments exists when improper control samples are used. In cancer research, comparisons of tumour expression profiles to those from normal samples is challenging due to tissue heterogeneity (mixed cell populations). A specific example exists in a published colon cancer dataset, in which tissue heterogeneity was reported among the normal samples. In this paper, we show how to overcome or avoid the problem of using normal samples that do not derive from the same tissue of origin as the tumour. We advocate an exploratory unsupervised bootstrap analysis that can reveal unexpected and undesired, but strongly supported, clusters of samples that reflect tissue differences instead of tumour versus normal differences. All of the algorithms used in the analysis, including the maximum difference subset algorithm, unsupervised bootstrap analysis, pooled variance t-test for finding differentially expressed genes and the jackknife to reduce false positives, are incorporated into our online Gene Expression Data Analyzer ( http:// bioinformatics.upmc.edu/GE2/GEDA.html ).

A Method for WD40 Repeat Detection and Secondary Structure Prediction

PubMed Central

Wang, Yang; Jiang, Fan; Zhuo, Zhu; Wu, Xian-Hui; Wu, Yun-Dong

2013-01-01

WD40-repeat proteins (WD40s), as one of the largest protein families in eukaryotes, play vital roles in assembling protein-protein/DNA/RNA complexes. WD40s fold into similar β-propeller structures despite diversified sequences. A program WDSP (WD40 repeat protein Structure Predictor) has been developed to accurately identify WD40 repeats and predict their secondary structures. The method is designed specifically for WD40 proteins by incorporating both local residue information and non-local family-specific structural features. It overcomes the problem of highly diversified protein sequences and variable loops. In addition, WDSP achieves a better prediction in identifying multiple WD40-domain proteins by taking the global combination of repeats into consideration. In secondary structure prediction, the average Q3 accuracy of WDSP in jack-knife test reaches 93.7%. A disease related protein LRRK2 was used as a representive example to demonstrate the structure prediction. PMID:23776530

Detrended cross-correlation coefficient: Application to predict apoptosis protein subcellular localization.

PubMed

Liang, Yunyun; Liu, Sanyang; Zhang, Shengli

2016-12-01

Apoptosis, or programed cell death, plays a central role in the development and homeostasis of an organism. Obtaining information on subcellular location of apoptosis proteins is very helpful for understanding the apoptosis mechanism. The prediction of subcellular localization of an apoptosis protein is still a challenging task, and existing methods mainly based on protein primary sequences. In this paper, we introduce a new position-specific scoring matrix (PSSM)-based method by using detrended cross-correlation (DCCA) coefficient of non-overlapping windows. Then a 190-dimensional (190D) feature vector is constructed on two widely used datasets: CL317 and ZD98, and support vector machine is adopted as classifier. To evaluate the proposed method, objective and rigorous jackknife cross-validation tests are performed on the two datasets. The results show that our approach offers a novel and reliable PSSM-based tool for prediction of apoptosis protein subcellular localization. Copyright © 2016 Elsevier Inc. All rights reserved.

Phylogeny of sipunculan worms: A combined analysis of four gene regions and morphology.

PubMed

Schulze, Anja; Cutler, Edward B; Giribet, Gonzalo

2007-01-01

The intra-phyletic relationships of sipunculan worms were analyzed based on DNA sequence data from four gene regions and 58 morphological characters. Initially we analyzed the data under direct optimization using parsimony as optimality criterion. An implied alignment resulting from the direct optimization analysis was subsequently utilized to perform a Bayesian analysis with mixed models for the different data partitions. For this we applied a doublet model for the stem regions of the 18S rRNA. Both analyses support monophyly of Sipuncula and most of the same clades within the phylum. The analyses differ with respect to the relationships among the major groups but whereas the deep nodes in the direct optimization analysis generally show low jackknife support, they are supported by 100% posterior probability in the Bayesian analysis. Direct optimization has been useful for handling sequences of unequal length and generating conservative phylogenetic hypotheses whereas the Bayesian analysis under mixed models provided high resolution in the basal nodes of the tree.

Spider diversity (Arachnida: Araneae) in Atlantic Forest areas at Pedra Branca State Park, Rio de Janeiro, Brazil

PubMed Central

Pérez-González, Abel; Baptista, Renner L. C.

2016-01-01

Abstract Background There has never been any published work about the diversity of spiders in the city of Rio de Janeiro using analytical tools to measure diversity. The only available records for spider communities in nearby areas indicate 308 species in the National Park of Tijuca and 159 species in Marapendi Municipal Park. These numbers are based on a rapid survey and on an one-year survey respectively. New information This study provides a more thorough understanding of how the spider species are distributed at Pedra Branca State Park. We report a total of 14,626 spider specimens recorded from this park, representing 49 families and 373 species or morphospecies, including at least 73 undescribed species. Also, the distribution range of 45 species was expanded, and species accumulation curves estimate that there is a minimum of 388 (Bootstrap) and a maximum of 468 species (Jackknife2) for the sampled areas. These estimates indicates that the spider diversity may be higher than observed. PMID:26929710

A Hybrid Classification System for Heart Disease Diagnosis Based on the RFRS Method.

PubMed

Liu, Xiao; Wang, Xiaoli; Su, Qiang; Zhang, Mo; Zhu, Yanhong; Wang, Qiugen; Wang, Qian

2017-01-01

Heart disease is one of the most common diseases in the world. The objective of this study is to aid the diagnosis of heart disease using a hybrid classification system based on the ReliefF and Rough Set (RFRS) method. The proposed system contains two subsystems: the RFRS feature selection system and a classification system with an ensemble classifier. The first system includes three stages: (i) data discretization, (ii) feature extraction using the ReliefF algorithm, and (iii) feature reduction using the heuristic Rough Set reduction algorithm that we developed. In the second system, an ensemble classifier is proposed based on the C4.5 classifier. The Statlog (Heart) dataset, obtained from the UCI database, was used for experiments. A maximum classification accuracy of 92.59% was achieved according to a jackknife cross-validation scheme. The results demonstrate that the performance of the proposed system is superior to the performances of previously reported classification techniques.

Estimating contaminant loads in rivers: An application of adjusted maximum likelihood to type 1 censored data

USGS Publications Warehouse

Cohn, Timothy A.

2005-01-01

This paper presents an adjusted maximum likelihood estimator (AMLE) that can be used to estimate fluvial transport of contaminants, like phosphorus, that are subject to censoring because of analytical detection limits. The AMLE is a generalization of the widely accepted minimum variance unbiased estimator (MVUE), and Monte Carlo experiments confirm that it shares essentially all of the MVUE's desirable properties, including high efficiency and negligible bias. In particular, the AMLE exhibits substantially less bias than alternative censored‐data estimators such as the MLE (Tobit) or the MLE followed by a jackknife. As with the MLE and the MVUE the AMLE comes close to achieving the theoretical Frechet‐Cramér‐Rao bounds on its variance. This paper also presents a statistical framework, applicable to both censored and complete data, for understanding and estimating the components of uncertainty associated with load estimates. This can serve to lower the cost and improve the efficiency of both traditional and real‐time water quality monitoring.

Jackknife Estimation of Sampling Variance of Ratio Estimators in Complex Samples: Bias and the Coefficient of Variation. Research Report. ETS RR-06-19

ERIC Educational Resources Information Center

Oranje, Andreas

2006-01-01

A multitude of methods has been proposed to estimate the sampling variance of ratio estimates in complex samples (Wolter, 1985). Hansen and Tepping (1985) studied some of those variance estimators and found that a high coefficient of variation (CV) of the denominator of a ratio estimate is indicative of a biased estimate of the standard error of a…

Estimation of age at death from the pubic symphysis and the auricular surface of the ilium using a smoothing procedure.

PubMed

Martins, Rui; Oliveira, Paulo Eduardo; Schmitt, Aurore

2012-06-10

We discuss here the estimation of age at death from two indicators (pubic symphysis and the sacro-pelvic surface of the ilium) based on four different osteological series from Portugal, Great-Britain, South Africa or USA (European origin). These samples and the scoring system of the two indicators were used by Schmitt et al. (2002), applying the methodology proposed by Lucy et al. (1996). In the present work, the same data was processed using a modification of the empirical method proposed by Lucy et al. (2002). The various probability distributions are estimated from training data by using kernel density procedures and Jackknife methodology. Bayes's theorem is then used to produce the posterior distribution from which point and interval estimates may be made. This statistical approach reduces the bias of the estimates to less than 70% of what was obtained by the initial method. This reduction going up to 52% if knowledge of sex of the individual is available, and produces an age for all the individuals that improves age at death assessment. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

An integrated multi-label classifier with chemical-chemical interactions for prediction of chemical toxicity effects.

PubMed

Liu, Tao; Chen, Lei; Pan, Xiaoyong

2018-05-31

Chemical toxicity effect is one of the major reasons for declining candidate drugs. Detecting the toxicity effects of all chemicals can accelerate the procedures of drug discovery. However, it is time-consuming and expensive to identify the toxicity effects of a given chemical through traditional experiments. Designing quick, reliable and non-animal-involved computational methods is an alternative way. In this study, a novel integrated multi-label classifier was proposed. First, based on five types of chemical-chemical interactions retrieved from STITCH, each of which is derived from one aspect of chemicals, five individual classifiers were built. Then, several integrated classifiers were built by integrating some or all individual classifiers. By testing the integrated classifiers on a dataset with chemicals and their toxicity effects in Accelrys Toxicity database and non-toxic chemicals with their performance evaluated by jackknife test, an optimal integrated classifier was selected as the proposed classifier, which provided quite high prediction accuracies and wide applications. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Predicting subcellular location of apoptosis proteins based on wavelet transform and support vector machine.

PubMed

Qiu, Jian-Ding; Luo, San-Hua; Huang, Jian-Hua; Sun, Xing-Yu; Liang, Ru-Ping

2010-04-01

Apoptosis proteins have a central role in the development and homeostasis of an organism. These proteins are very important for understanding the mechanism of programmed cell death. As a result of genome and other sequencing projects, the gap between the number of known apoptosis protein sequences and the number of known apoptosis protein structures is widening rapidly. Because of this extremely unbalanced state, it would be worthwhile to develop a fast and reliable method to identify their subcellular locations so as to gain better insight into their biological functions. In view of this, a new method, in which the support vector machine combines with discrete wavelet transform, has been developed to predict the subcellular location of apoptosis proteins. The results obtained by the jackknife test were quite promising, and indicated that the proposed method can remarkably improve the prediction accuracy of subcellular locations, and might also become a useful high-throughput tool in characterizing other attributes of proteins, such as enzyme class, membrane protein type, and nuclear receptor subfamily according to their sequences.

Limited sampling hampers “big data” estimation of species richness in a tropical biodiversity hotspot

PubMed Central

Engemann, Kristine; Enquist, Brian J; Sandel, Brody; Boyle, Brad; Jørgensen, Peter M; Morueta-Holme, Naia; Peet, Robert K; Violle, Cyrille; Svenning, Jens-Christian

2015-01-01

Macro-scale species richness studies often use museum specimens as their main source of information. However, such datasets are often strongly biased due to variation in sampling effort in space and time. These biases may strongly affect diversity estimates and may, thereby, obstruct solid inference on the underlying diversity drivers, as well as mislead conservation prioritization. In recent years, this has resulted in an increased focus on developing methods to correct for sampling bias. In this study, we use sample-size-correcting methods to examine patterns of tropical plant diversity in Ecuador, one of the most species-rich and climatically heterogeneous biodiversity hotspots. Species richness estimates were calculated based on 205,735 georeferenced specimens of 15,788 species using the Margalef diversity index, the Chao estimator, the second-order Jackknife and Bootstrapping resampling methods, and Hill numbers and rarefaction. Species richness was heavily correlated with sampling effort, and only rarefaction was able to remove this effect, and we recommend this method for estimation of species richness with “big data” collections. PMID:25692000

Spinal hemianesthesia: Unilateral and posterior

PubMed Central

Imbelloni, Luiz Eduardo

2014-01-01

The injection of a non-isobaric local anesthetic should induce a unilateral spinal anesthesia in patients in a lateral decubitus position. The posterior spinal hemianesthesia only be obtained with hypobaric solutions injected in the jackknife position. The most important factors to be considered when performing a spinal hemianesthesia are: type and gauge of the needle, density of the local anesthetic relative to the CSF, position of the patient, speed of administration of the solution, time of stay in position, and dose/concentration/volume of the anesthetic solution. The distance between the spinal roots on the right-left sides and anterior-posterior is, approximately, 10-15 mm. This distance allows performing unilateral spinal anesthesia or posterior spinal anesthesia. The great advantage of obtaining spinal hemianesthesia is the reduction of cardiovascular changes. Likewise, both the dorsal and unilateral sensory block predominates in relation to the motor block. Because of the numerous advantages of producing spinal hemianesthesia, anesthesiologists should apply this technique more often. This review considers the factors which are relevant, plausible and proven to obtain spinal hemianesthesia. PMID:25886320

COMDYN: Software to study the dynamics of animal communities using a capture-recapture approach

USGS Publications Warehouse

Hines, J.E.; Boulinier, T.; Nichols, J.D.; Sauer, J.R.; Pollock, K.H.

1999-01-01

COMDYN is a set of programs developed for estimation of parameters associated with community dynamics using count data from two locations or time periods. It is Internet-based, allowing remote users either to input their own data, or to use data from the North American Breeding Bird Survey for analysis. COMDYN allows probability of detection to vary among species and among locations and time periods. The basic estimator for species richness underlying all estimators is the jackknife estimator proposed by Burnham and Overton. Estimators are presented for quantities associated with temporal change in species richness, including rate of change in species richness over time, local extinction probability, local species turnover and number of local colonizing species. Estimators are also presented for quantities associated with spatial variation in species richness, including relative richness at two locations and proportion of species present in one location that are also present at a second location. Application of the estimators to species richness estimation has been previously described and justified. The potential applications of these programs are discussed.

Limited sampling hampers "big data" estimation of species richness in a tropical biodiversity hotspot.

PubMed

Engemann, Kristine; Enquist, Brian J; Sandel, Brody; Boyle, Brad; Jørgensen, Peter M; Morueta-Holme, Naia; Peet, Robert K; Violle, Cyrille; Svenning, Jens-Christian

2015-02-01

Macro-scale species richness studies often use museum specimens as their main source of information. However, such datasets are often strongly biased due to variation in sampling effort in space and time. These biases may strongly affect diversity estimates and may, thereby, obstruct solid inference on the underlying diversity drivers, as well as mislead conservation prioritization. In recent years, this has resulted in an increased focus on developing methods to correct for sampling bias. In this study, we use sample-size-correcting methods to examine patterns of tropical plant diversity in Ecuador, one of the most species-rich and climatically heterogeneous biodiversity hotspots. Species richness estimates were calculated based on 205,735 georeferenced specimens of 15,788 species using the Margalef diversity index, the Chao estimator, the second-order Jackknife and Bootstrapping resampling methods, and Hill numbers and rarefaction. Species richness was heavily correlated with sampling effort, and only rarefaction was able to remove this effect, and we recommend this method for estimation of species richness with "big data" collections.

Nonparametric methods for drought severity estimation at ungauged sites

NASA Astrophysics Data System (ADS)

Sadri, S.; Burn, D. H.

2012-12-01

The objective in frequency analysis is, given extreme events such as drought severity or duration, to estimate the relationship between that event and the associated return periods at a catchment. Neural networks and other artificial intelligence approaches in function estimation and regression analysis are relatively new techniques in engineering, providing an attractive alternative to traditional statistical models. There are, however, few applications of neural networks and support vector machines in the area of severity quantile estimation for drought frequency analysis. In this paper, we compare three methods for this task: multiple linear regression, radial basis function neural networks, and least squares support vector regression (LS-SVR). The area selected for this study includes 32 catchments in the Canadian Prairies. From each catchment drought severities are extracted and fitted to a Pearson type III distribution, which act as observed values. For each method-duration pair, we use a jackknife algorithm to produce estimated values at each site. The results from these three approaches are compared and analyzed, and it is found that LS-SVR provides the best quantile estimates and extrapolating capacity.

Optimal Bandwidth for Multitaper Spectrum Estimation

DOE PAGES

Haley, Charlotte L.; Anitescu, Mihai

2017-07-04

A systematic method for bandwidth parameter selection is desired for Thomson multitaper spectrum estimation. We give a method for determining the optimal bandwidth based on a mean squared error (MSE) criterion. When the true spectrum has a second-order Taylor series expansion, one can express quadratic local bias as a function of the curvature of the spectrum, which can be estimated by using a simple spline approximation. This is combined with a variance estimate, obtained by jackknifing over individual spectrum estimates, to produce an estimated MSE for the log spectrum estimate for each choice of time-bandwidth product. The bandwidth that minimizesmore » the estimated MSE then gives the desired spectrum estimate. Additionally, the bandwidth obtained using our method is also optimal for cepstrum estimates. We give an example of a damped oscillatory (Lorentzian) process in which the approximate optimal bandwidth can be written as a function of the damping parameter. Furthermore, the true optimal bandwidth agrees well with that given by minimizing estimated the MSE in these examples.« less

Fusing face-verification algorithms and humans.

PubMed

O'Toole, Alice J; Abdi, Hervé; Jiang, Fang; Phillips, P Jonathon

2007-10-01

It has been demonstrated recently that state-of-the-art face-recognition algorithms can surpass human accuracy at matching faces over changes in illumination. The ranking of algorithms and humans by accuracy, however, does not provide information about whether algorithms and humans perform the task comparably or whether algorithms and humans can be fused to improve performance. In this paper, we fused humans and algorithms using partial least square regression (PLSR). In the first experiment, we applied PLSR to face-pair similarity scores generated by seven algorithms participating in the Face Recognition Grand Challenge. The PLSR produced an optimal weighting of the similarity scores, which we tested for generality with a jackknife procedure. Fusing the algorithms' similarity scores using the optimal weights produced a twofold reduction of error rate over the most accurate algorithm. Next, human-subject-generated similarity scores were added to the PLSR analysis. Fusing humans and algorithms increased the performance to near-perfect classification accuracy. These results are discussed in terms of maximizing face-verification accuracy with hybrid systems consisting of multiple algorithms and humans.

Recent developments in the Dorfman-Berbaum-Metz procedure for multireader ROC study analysis.

PubMed

Hillis, Stephen L; Berbaum, Kevin S; Metz, Charles E

2008-05-01

The Dorfman-Berbaum-Metz (DBM) method has been one of the most popular methods for analyzing multireader receiver-operating characteristic (ROC) studies since it was proposed in 1992. Despite its popularity, the original procedure has several drawbacks: it is limited to jackknife accuracy estimates, it is substantially conservative, and it is not based on a satisfactory conceptual or theoretical model. Recently, solutions to these problems have been presented in three papers. Our purpose is to summarize and provide an overview of these recent developments. We present and discuss the recently proposed solutions for the various drawbacks of the original DBM method. We compare the solutions in a simulation study and find that they result in improved performance for the DBM procedure. We also compare the solutions using two real data studies and find that the modified DBM procedure that incorporates these solutions yields more significant results and clearer interpretations of the variance component parameters than the original DBM procedure. We recommend using the modified DBM procedure that incorporates the recent developments.

Order-restricted inference for means with missing values.

PubMed

Wang, Heng; Zhong, Ping-Shou

2017-09-01

Missing values appear very often in many applications, but the problem of missing values has not received much attention in testing order-restricted alternatives. Under the missing at random (MAR) assumption, we impute the missing values nonparametrically using kernel regression. For data with imputation, the classical likelihood ratio test designed for testing the order-restricted means is no longer applicable since the likelihood does not exist. This article proposes a novel method for constructing test statistics for assessing means with an increasing order or a decreasing order based on jackknife empirical likelihood (JEL) ratio. It is shown that the JEL ratio statistic evaluated under the null hypothesis converges to a chi-bar-square distribution, whose weights depend on missing probabilities and nonparametric imputation. Simulation study shows that the proposed test performs well under various missing scenarios and is robust for normally and nonnormally distributed data. The proposed method is applied to an Alzheimer's disease neuroimaging initiative data set for finding a biomarker for the diagnosis of the Alzheimer's disease. © 2017, The International Biometric Society.

Predicting cancerlectins by the optimal g-gap dipeptides

NASA Astrophysics Data System (ADS)

Lin, Hao; Liu, Wei-Xin; He, Jiao; Liu, Xin-Hui; Ding, Hui; Chen, Wei

2015-12-01

The cancerlectin plays a key role in the process of tumor cell differentiation. Thus, to fully understand the function of cancerlectin is significant because it sheds light on the future direction for the cancer therapy. However, the traditional wet-experimental methods were money- and time-consuming. It is highly desirable to develop an effective and efficient computational tool to identify cancerlectins. In this study, we developed a sequence-based method to discriminate between cancerlectins and non-cancerlectins. The analysis of variance (ANOVA) was used to choose the optimal feature set derived from the g-gap dipeptide composition. The jackknife cross-validated results showed that the proposed method achieved the accuracy of 75.19%, which is superior to other published methods. For the convenience of other researchers, an online web-server CaLecPred was established and can be freely accessed from the website http://lin.uestc.edu.cn/server/CalecPred. We believe that the CaLecPred is a powerful tool to study cancerlectins and to guide the related experimental validations.

Identification of immunoglobulins using Chou's pseudo amino acid composition with feature selection technique.

PubMed

Tang, Hua; Chen, Wei; Lin, Hao

2016-04-01

Immunoglobulins, also called antibodies, are a group of cell surface proteins which are produced by the immune system in response to the presence of a foreign substance (called antigen). They play key roles in many medical, diagnostic and biotechnological applications. Correct identification of immunoglobulins is crucial to the comprehension of humoral immune function. With the avalanche of protein sequences identified in postgenomic age, it is highly desirable to develop computational methods to timely identify immunoglobulins. In view of this, we designed a predictor called "IGPred" by formulating protein sequences with the pseudo amino acid composition into which nine physiochemical properties of amino acids were incorporated. Jackknife cross-validated results showed that 96.3% of immunoglobulins and 97.5% of non-immunoglobulins can be correctly predicted, indicating that IGPred holds very high potential to become a useful tool for antibody analysis. For the convenience of most experimental scientists, a web-server for IGPred was established at http://lin.uestc.edu.cn/server/IGPred. We believe that the web-server will become a powerful tool to study immunoglobulins and to guide related experimental validations.

Technical note: comparing von Luschan skin color tiles and modern spectrophotometry for measuring human skin pigmentation.

PubMed

Swiatoniowski, Anna K; Quillen, Ellen E; Shriver, Mark D; Jablonski, Nina G

2013-06-01

Prior to the introduction of reflectance spectrophotometry into anthropological field research during the 1950s, human skin color was most commonly classified by visual skin color matching using the von Luschan tiles, a set of 36 standardized, opaque glass tiles arranged in a chromatic scale. Our goal was to establish a conversion formula between the tile-based color matching method and modern reflectance spectrophotometry to make historical and contemporary data comparable. Skin pigmentation measurements were taken on the forehead, inner upper arms, and backs of the hands using both the tiles and a spectrophotometer on 246 participants showing a broad range of skin pigmentation. From these data, a second-order polynomial conversion formula was derived by jackknife analysis to estimate melanin index (M-index) based on tile values. This conversion formula provides a means for comparing modern data to von Luschan tile measurements recorded in historical reports. This is particularly important for populations now extinct, extirpated, or admixed for which tile-based measures of skin pigmentation are the only data available. Copyright © 2013 Wiley Periodicals, Inc.

Distinguishing centrarchid genera by use of lateral line scales

USGS Publications Warehouse

Roberts, N.M.; Rabeni, C.F.; Stanovick, J.S.

2007-01-01

Predator-prey relations involving fishes are often evaluated using scales remaining in gut contents or feces. While several reliable keys help identify North American freshwater fish scales to the family level, none attempt to separate the family Centrarchidae to the genus level. Centrarchidae is of particular concern in the midwestern United States because it contains several popular sport fishes, such as smallmouth bass Micropterus dolomieu, largemouth bass M. salmoides, and rock bass Ambloplites rupestris, as well as less-sought-after species of sunfishes Lepomis spp. and crappies Pomoxis spp. Differentiating sport fish from non-sport fish has important management implications. Morphological characteristics of lateral line scales (n = 1,581) from known centrarchid fishes were analyzed. The variability of measurements within and between genera was examined to select variables that were the most useful in further classifying unknown centrarchid scales. A linear discriminant analysis model was developed using 10 variables. Based on this model, 84.4% of Ambloplites scales, 81.2% of Lepomis scales, and 86.6% of Micropterus scales were classified correctly using a jackknife procedure. ?? Copyright by the American Fisheries Society 2007.

Accurate prediction of subcellular location of apoptosis proteins combining Chou's PseAAC and PsePSSM based on wavelet denoising.

PubMed

Yu, Bin; Li, Shan; Qiu, Wen-Ying; Chen, Cheng; Chen, Rui-Xin; Wang, Lei; Wang, Ming-Hui; Zhang, Yan

2017-12-08

Apoptosis proteins subcellular localization information are very important for understanding the mechanism of programmed cell death and the development of drugs. The prediction of subcellular localization of an apoptosis protein is still a challenging task because the prediction of apoptosis proteins subcellular localization can help to understand their function and the role of metabolic processes. In this paper, we propose a novel method for protein subcellular localization prediction. Firstly, the features of the protein sequence are extracted by combining Chou's pseudo amino acid composition (PseAAC) and pseudo-position specific scoring matrix (PsePSSM), then the feature information of the extracted is denoised by two-dimensional (2-D) wavelet denoising. Finally, the optimal feature vectors are input to the SVM classifier to predict subcellular location of apoptosis proteins. Quite promising predictions are obtained using the jackknife test on three widely used datasets and compared with other state-of-the-art methods. The results indicate that the method proposed in this paper can remarkably improve the prediction accuracy of apoptosis protein subcellular localization, which will be a supplementary tool for future proteomics research.

Differentiation of fecal Escherichia coli from poultry and free-living birds by (GTG)5-PCR genomic fingerprinting.

PubMed

Mohapatra, Bidyut R; Broersma, Klaas; Mazumder, Asit

2008-04-01

Determination of the non-point sources of fecal pollution is essential for the assessment of potential public health risk and development of appropriate management practices for prevention of further contamination. Repetitive extragenic palindromic-PCR coupled with (GTG)(5) primer [(GTG)(5)-PCR] was performed on 573 Escherichia coli isolates obtained from the feces of poultry (chicken, duck and turkey) and free-living (Canada goose, hawk, magpie, seagull and songbird) birds to evaluate the efficacy of (GTG)(5)-PCR genomic fingerprinting in the prediction of the correct source of fecal pollution. A discriminant analysis with the jack-knife algorithm of (GTG)(5)-PCR DNA fingerprints revealed that 95%, 94.1%, 93.2%, 84.6%, 79.7%, 76.7%, 75.3% and 70.7% of magpie, hawk, turkey, seagull, Canada goose, chicken, duck and songbird fecal E. coli isolates classified into the correct host source, respectively. The results of this study indicate that (GTG)(5)-PCR can be considered to be a complementary molecular tool for the rapid determination of E. coli isolates identity and tracking the non-point sources of fecal pollution.

Sequence-based predictive modeling to identify cancerlectins

PubMed Central

Lai, Hong-Yan; Chen, Xin-Xin; Chen, Wei; Tang, Hua; Lin, Hao

2017-01-01

Lectins are a diverse type of glycoproteins or carbohydrate-binding proteins that have a wide distribution to various species. They can specially identify and exclusively bind to a certain kind of saccharide groups. Cancerlectins are a group of lectins that are closely related to cancer and play a major role in the initiation, survival, growth, metastasis and spread of tumor. Several computational methods have emerged to discriminate cancerlectins from non-cancerlectins, which promote the study on pathogenic mechanisms and clinical treatment of cancer. However, the predictive accuracies of most of these techniques are very limited. In this work, by constructing a benchmark dataset based on the CancerLectinDB database, a new amino acid sequence-based strategy for feature description was developed, and then the binomial distribution was applied to screen the optimal feature set. Ultimately, an SVM-based predictor was performed to distinguish cancerlectins from non-cancerlectins, and achieved an accuracy of 77.48% with AUC of 85.52% in jackknife cross-validation. The results revealed that our prediction model could perform better comparing with published predictive tools. PMID:28423655

Inferring the shallow phylogeny of true salamanders (Salamandra) by multiple phylogenomic approaches.

PubMed

Rodríguez, Ariel; Burgon, James D; Lyra, Mariana; Irisarri, Iker; Baurain, Denis; Blaustein, Leon; Göçmen, Bayram; Künzel, Sven; Mable, Barbara K; Nolte, Arne W; Veith, Michael; Steinfartz, Sebastian; Elmer, Kathryn R; Philippe, Hervé; Vences, Miguel

2017-10-01

The rise of high-throughput sequencing techniques provides the unprecedented opportunity to analyse controversial phylogenetic relationships in great depth, but also introduces a risk of being misinterpreted by high node support values influenced by unevenly distributed missing data or unrealistic model assumptions. Here, we use three largely independent phylogenomic data sets to reconstruct the controversial phylogeny of true salamanders of the genus Salamandra, a group of amphibians providing an intriguing model to study the evolution of aposematism and viviparity. For all six species of the genus Salamandra, and two outgroup species from its sister genus Lyciasalamandra, we used RNA sequencing (RNAseq) and restriction site associated DNA sequencing (RADseq) to obtain data for: (1) 3070 nuclear protein-coding genes from RNAseq; (2) 7440 loci obtained by RADseq; and (3) full mitochondrial genomes. The RNAseq and RADseq data sets retrieved fully congruent topologies when each of them was analyzed in a concatenation approach, with high support for: (1) S. infraimmaculata being sister group to all other Salamandra species; (2) S. algira being sister to S. salamandra; (3) these two species being the sister group to a clade containing S. atra, S. corsica and S. lanzai; and (4) the alpine species S. atra and S. lanzai being sister taxa. The phylogeny inferred from the mitochondrial genome sequences differed from these results, most notably by strongly supporting a clade containing S. atra and S. corsica as sister taxa. A different placement of S. corsica was also retrieved when analysing the RNAseq and RADseq data under species tree approaches. Closer examination of gene trees derived from RNAseq revealed that only a low number of them supported each of the alternative placements of S. atra. Furthermore, gene jackknife support for the S. atra - S. lanzai node stabilized only with very large concatenated data sets. The phylogeny of true salamanders thus provides a

Tracing the pathways of neotropical migratory shorebirds using stable isotopes: a pilot study.

PubMed

Farmer, A; Rye, R; Landis, G; Bern, C; Kester, C; Ridley, I

2003-09-01

We evaluated the potential use of stable isotopes to establish linkages between the wintering grounds and the breeding grounds of the Pectoral Sandpiper (Calidris melanotos), the White-rumped Sandpiper (Calidris fuscicollis), the Baird's Sandpiper (Calidris bairdii), and other Neotropical migratory shorebird species (e.g., Tringa spp.). These species molt their flight feathers on the wintering grounds and hence their flight feathers carry chemical signatures that are characteristic of their winter habitat. The objective of our pilot study was to assess the feasibility of identifying the winter origin of individual birds by: (1) collecting shorebird flight feathers from several widely separated Argentine sites and analyzing these for a suite of stable isotopes; and 2) analyzing the deuterium and 18O isotope data that were available from precipitation measurement stations in Argentina. Isotopic ratios (delta13C, delta15N and delta34S) of flight feathers were significantly different among three widely separated sites in Argentina during January 2001. In terms of relative importance in separating the sites, delta34S was most important, followed by delta15N, and then delta13C. In the complete discriminant analysis, the classification function correctly predicted group membership in 85% of the cases (jackknifed classification matrix). In a stepwise analysis delta13C was dropped from the solution, and site membership was correctly predicted in 92% of cases (jackknifed matrix). Analysis of precipitation data showed that both deltaD and delta18O were significantly related to both latitude and longitude on a countrywide scale (p < 0.001). Other variables, month, altitude, explained little additional variation in these isotope ratios. Several issues were identified that will likely constrain the degree of accuracy one can expect in predicting the geographic origin of birds from Argentina. There was unexplained variation in isotope ratios within and among the different wing

Tracing the pathways of Neotropical migratory shorebirds using stable isotopes: A pilot study

USGS Publications Warehouse

Farmer, A.H.; Rye, R.; Landis, G.; Bern, C.; Kester, C.; Ridley, I.

2003-01-01

We evaluated the potential use of stable isotopes to establish linkages between the wintering grounds and the breeding grounds of the Pectoral Sandpiper (Calidris melanotos), the White-rumped Sandpiper (Calidris fuscicollis), the Baird's Sandpiper (Calidris bairdii), and other Neotropical migratory shorebird species (e.g., Tringa spp.). These species molt their flight feathers on the wintering grounds and hence their flight feathers carry chemical signatures that are characteristic of their winter habitat. The objective of our pilot study was to assess the feasibility of identifying the winter origin of individual birds by: (1) collecting shorebird flight feathers from several widely separated Argentine sites and analyzing these for a suite of stable isotopes; and (2) analyzing the deuterium and 18O isotope data that were available from precipitation measurement stations in Argentina. Isotopic ratios (δ13C, δ15N and δ34S) of flight feathers were significantly different among three widely separated sites in Argentina during January 2001. In terms of relative importance in separating the sites, δ34S was most important, followed by δ15N, and then δ13C. In the complete discriminant analysis, the classification function correctly predicted group membership in 85% of the cases (jackknifed classification matrix). In a stepwise analysis δ13C was dropped from the solution, and site membership was correctly predicted in 92% of cases (jackknifed matrix). Analysis of precipitation data showed that both δD and δ18O were significantly related to both latitude and longitude on a countrywide scale (p < 0.001). Other variables, month, altitude, explained little additional variation in these isotope ratios. Several issues were identified that will likely constrain the degree of accuracy one can expect in predicting the geographic origin of birds from Argentina. There was unexplained variation in isotope ratios within and among the different wing feathers from individual

Adolescent Ecstasy and other drug use in the National Survey of Parents and Youth: the role of sensation-seeking, parental monitoring and peer’s drug use

PubMed Central

Martins, Silvia S.; Storr, Carla L.; Alexandre, Pierre K.; Chilcoat, Howard D.

2008-01-01

The association between high sensation-seeking, close friends’ drug use and low parental monitoring with Ecstasy (MDMA) use in adolescence was examined in a sample of US household-dwelling adolescents aged 12–18 years (N=5,049). We also tested whether associations were of stronger magnitude than associations between these correlates and marijuana or alcohol/tobacco use in adolescence. Data from Round 2 of the National Survey of Parents and Youth (NSPY) Restricted Use Files (RUF) was analyzed via Jackknife weighted multinomial logistic regression models. High sensation-seekers were more likely to be ecstasy, marijuana, and alcohol/tobacco users, respectively, as compared to low sensation-seekers. High sensation-seeking and close friends’ drug use were more strongly associated with ecstasy as compared to marijuana and alcohol/tobacco use. Low parental monitoring was associated with marijuana use and alcohol/tobacco use and there was a trend for it to be associated with ecstasy use. Ecstasy use is strongly associated with peer drug use and more modestly associated with high sensation-seeking. School prevention programs should target high-sensation-seeking adolescents and also encourage them to affiliate with non-drug using peers. PMID:18355973

Prediction of change in protein unfolding rates upon point mutations in two state proteins.

PubMed

Chaudhary, Priyashree; Naganathan, Athi N; Gromiha, M Michael

2016-09-01

Studies on protein unfolding rates are limited and challenging due to the complexity of unfolding mechanism and the larger dynamic range of the experimental data. Though attempts have been made to predict unfolding rates using protein sequence-structure information there is no available method for predicting the unfolding rates of proteins upon specific point mutations. In this work, we have systematically analyzed a set of 790 single mutants and developed a robust method for predicting protein unfolding rates upon mutations (Δlnku) in two-state proteins by combining amino acid properties and knowledge-based classification of mutants with multiple linear regression technique. We obtain a mean absolute error (MAE) of 0.79/s and a Pearson correlation coefficient (PCC) of 0.71 between predicted unfolding rates and experimental observations using jack-knife test. We have developed a web server for predicting protein unfolding rates upon mutation and it is freely available at https://www.iitm.ac.in/bioinfo/proteinunfolding/unfoldingrace.html. Prominent features that determine unfolding kinetics as well as plausible reasons for the observed outliers are also discussed. Copyright © 2016 Elsevier B.V. All rights reserved.

Driver assistance system for passive multi-trailer vehicles with haptic steering limitations on the leading unit.

PubMed

Morales, Jesús; Mandow, Anthony; Martínez, Jorge L; Reina, Antonio J; García-Cerezo, Alfonso

2013-04-03

Driving vehicles with one or more passive trailers has difficulties in both forward and backward motion due to inter-unit collisions, jackknife, and lack of visibility. Consequently, advanced driver assistance systems (ADAS) for multi-trailer combinations can be beneficial to accident avoidance as well as to driver comfort. The ADAS proposed in this paper aims to prevent unsafe steering commands by means of a haptic handwheel. Furthermore, when driving in reverse, the steering-wheel and pedals can be used as if the vehicle was driven from the back of the last trailer with visual aid from a rear-view camera. This solution, which can be implemented in drive-by-wire vehicles with hitch angle sensors, profits from two methods previously developed by the authors: safe steering by applying a curvature limitation to the leading unit, and a virtual tractor concept for backward motion that includes the complex case of set-point propagation through on-axle hitches. The paper addresses system requirements and provides implementation details to tele-operate two different off- and on-axle combinations of a tracked mobile robot pulling and pushing two dissimilar trailers.

Composition of soil microbiome along elevation gradients in southwestern highlands of Saudi Arabia.

PubMed

Yasir, Muhammad; Azhar, Esam I; Khan, Imran; Bibi, Fehmida; Baabdullah, Rnda; Al-Zahrani, Ibrahim A; Al-Ghamdi, Ahmed K

2015-03-14

Saudi Arabia is mostly barren except the southwestern highlands that are susceptible to environmental changes, a hotspot for biodiversity, but poorly studied for microbial diversity and composition. In this study, 454-pyrosequencing of 16S rRNA gene hypervariable region V6 was used to analyze soil bacterial community along elevation gradients of the southwestern highlands. In general, lower percentage of total soil organic matter (SOM) and nitrogen were detected in the analyzed soil samples. Total 33 different phyla were identified across the samples, including dominant phyla Proteobacteria, Actinobacteria and Acidobacteria. Representative OTUs were grouped into 329 and 508 different taxa at family and genus level taxonomic classification, respectively. The identified OTUs unique to each sample were very low irrespective of the altitude. Jackknifed principal coordinates analysis (PCoA) revealed, overall differences in the bacterial community were more related to the quantity of specific OTUs than to their diversity among the studied samples. Bacterial diversity and soil physicochemical properties did not show consistent changes along the elevation gradients. The large number of OTUs shared between the studied samples suggest the presence of a core soil bacterial community in the southwestern highlands of Saudi Arabia.

Human DNA ligase III recognizes DNA ends by dynamic switching between two DNA-bound states.

PubMed

Cotner-Gohara, Elizabeth; Kim, In-Kwon; Hammel, Michal; Tainer, John A; Tomkinson, Alan E; Ellenberger, Tom

2010-07-27

Human DNA ligase III has essential functions in nuclear and mitochondrial DNA replication and repair and contains a PARP-like zinc finger (ZnF) that increases the extent of DNA nick joining and intermolecular DNA ligation, yet the bases for ligase III specificity and structural variation among human ligases are not understood. Here combined crystal structure and small-angle X-ray scattering results reveal dynamic switching between two nick-binding components of ligase III: the ZnF-DNA binding domain (DBD) forms a crescent-shaped surface used for DNA end recognition which switches to a ring formed by the nucleotidyl transferase (NTase) and OB-fold (OBD) domains for catalysis. Structural and mutational analyses indicate that high flexibility and distinct DNA binding domain features in ligase III assist both nick sensing and the transition from nick sensing by the ZnF to nick joining by the catalytic core. The collective results support a "jackknife model" in which the ZnF loads ligase III onto nicked DNA and conformational changes deliver DNA into the active site. This work has implications for the biological specificity of DNA ligases and functions of PARP-like zinc fingers.

The Link Between Nutrition and Physical Activity in Increasing Academic Achievement.

PubMed

Asigbee, Fiona M; Whitney, Stephen D; Peterson, Catherine E

2018-06-01

Research demonstrates a link between decreased cognitive function in overweight school-aged children and improved cognitive function among students with high fitness levels and children engaging in regular physical activity (PA). The purpose of this study was to examine whether regular PA and proper nutrition together had a significant effect on academic achievement. Using the seventh wave of the Early Childhood Longitudinal Study, Kindergarten Class 1998-99 (ECLS-K) dataset, linear regression analysis with a Jackknife resampling correction was conducted to analyze the relationship among nutrition, PA, and academic achievement, while controlling for socioeconomic status, age, and sex. A nonactive, unhealthy nutrition group and a physically active, healthy nutrition group were compared on standardized tests of academic achievement. Findings indicated that PA levels and proper nutrition significantly predicted achievement scores. Thus, the active, healthy nutrition group scored higher on reading, math, and science standardized achievement tests scores. There is a strong connection between healthy nutrition and adequate PA, and the average performance within the population. Thus, results from this study suggest a supporting relationship between students' health and academic achievement. Findings also provide implications for school and district policy changes. © 2018, American School Health Association.

On the value of nuclear and mitochondrial gene sequences for reconstructing the phylogeny of vanilloid orchids (Vanilloideae, Orchidaceae)

PubMed Central

Cameron, Kenneth M.

2009-01-01

Background and Aims Most molecular phylogenetic studies of Orchidaceae have relied heavily on DNA sequences from the plastid genome. Nuclear and mitochondrial loci have only been superficially examined for their systematic value. Since 40% of the genera within Vanilloideae are achlorophyllous mycoheterotrophs, this is an ideal group of orchids in which to evaluate non-plastid gene sequences. Methods Phylogenetic reconstructions for Vanilloideae were produced using independent and combined data from the nuclear 18S, 5·8S and 26S rDNA genes and the mitochondrial atpA gene and nad1b-c intron. Key Results These new data indicate placements for genera such as Lecanorchis and Galeola, for which plastid gene sequences have been mostly unavailable. Nuclear and mitochondrial parsimony jackknife trees are congruent with each other and previously published trees based solely on plastid data. Because of high rates of sequence divergence among vanilloid orchids, even the short 5·8S rDNA gene provides impressive levels of resolution and support. Conclusions Orchid systematists are encouraged to sequence nuclear and mitochondrial gene regions along with the growing number of plastid loci available. PMID:19251715

Estimating survival probabilities by exposure levels: utilizing vital statistics and complex survey data with mortality follow-up.

PubMed

Landsman, V; Lou, W Y W; Graubard, B I

2015-05-20

We present a two-step approach for estimating hazard rates and, consequently, survival probabilities, by levels of general categorical exposure. The resulting estimator utilizes three sources of data: vital statistics data and census data are used at the first step to estimate the overall hazard rate for a given combination of gender and age group, and cohort data constructed from a nationally representative complex survey with linked mortality records, are used at the second step to divide the overall hazard rate by exposure levels. We present an explicit expression for the resulting estimator and consider two methods for variance estimation that account for complex multistage sample design: (1) the leaving-one-out jackknife method, and (2) the Taylor linearization method, which provides an analytic formula for the variance estimator. The methods are illustrated with smoking and all-cause mortality data from the US National Health Interview Survey Linked Mortality Files, and the proposed estimator is compared with a previously studied crude hazard rate estimator that uses survey data only. The advantages of a two-step approach and possible extensions of the proposed estimator are discussed. Copyright © 2015 John Wiley & Sons, Ltd.

Predicting risk of nonmelanoma skin cancer and premalignant skin lesions in renal transplant recipients.

PubMed

Urwin, Helen R; Jones, Peter W; Harden, Paul N; Ramsay, Helen M; Hawley, Carmel M; Nicol, David L; Fryer, Anthony A

2009-06-15

Nonmelanoma skin cancer (NMSC) and associated premalignant lesions represent a major complication after transplantation, particularly in areas with high ultraviolet radiation (UVR) exposure. The American Society of Transplantation has proposed annual NMSC screening for all renal transplant recipients. The aim of this study was to develop a predictive index (PI) that could be used in targeted screening. Data on patient demographics, UVR exposure, and other clinical parameters were collected on 398 adult recipients recruited from the Princess Alexandra Hospital, Brisbane. Structured interview, skin examination, biopsy of lesions, and review of medical/pathologic records were performed. Time to presentation with the first NMSC was assessed using Cox's regression models and Kaplan-Meier estimates used to assess detection of NMSC during screening. Stepwise selection identified age, outdoor UVR exposure, living in a hot climate, pretransplant NMSC, childhood sunburning, and skin type as predictors. The PI generated was used to allocate patients into three screening groups (6 months, 2 years, and 5 years). The survival curves of these groups were significantly different (P<0.0001). Jack-knife validation correctly allocated all patients into the appropriate group. We have developed a simple PI to enable development of targeted NMSC surveillance strategies.

Earthquake source properties of a shallow induced seismic sequence in SE Brazil

NASA Astrophysics Data System (ADS)

Agurto-Detzel, Hans; Bianchi, Marcelo; Prieto, Germán. A.; Assumpção, Marcelo

2017-04-01

We study source parameters of a cluster of 21 very shallow (<1 km depth) small-magnitude (Mw < 2) earthquakes induced by percolation of water by gravity in SE Brazil. Using a multiple empirical Green's functions (meGf) approach, we estimate seismic moments, corner frequencies, and static stress drops of these events by inversion of their spectral ratios. For the studied magnitude range (-0.3 < Mw < 1.9), we found an increase of stress drop with seismic moment. We assess associated uncertainties by considering different signal time windows and by performing a jackknife resampling of the spectral ratios. We also calculate seismic moments by full waveform inversion to independently validate our moments from spectral analysis. We propose repeated rupture on a fault patch at shallow depth, following continuous inflow of water, as the cause for the observed low absolute stress drop values (<1 MPa) and earthquake size dependency. To our knowledge, no other study on earthquake source properties of shallow events induced by water injection with no added pressure is available in the literature. Our study suggests that source parameter characterization may provide additional information of induced seismicity by hydraulic stimulation.

Calibration plots for risk prediction models in the presence of competing risks.

PubMed

Gerds, Thomas A; Andersen, Per K; Kattan, Michael W

2014-08-15

A predicted risk of 17% can be called reliable if it can be expected that the event will occur to about 17 of 100 patients who all received a predicted risk of 17%. Statistical models can predict the absolute risk of an event such as cardiovascular death in the presence of competing risks such as death due to other causes. For personalized medicine and patient counseling, it is necessary to check that the model is calibrated in the sense that it provides reliable predictions for all subjects. There are three often encountered practical problems when the aim is to display or test if a risk prediction model is well calibrated. The first is lack of independent validation data, the second is right censoring, and the third is that when the risk scale is continuous, the estimation problem is as difficult as density estimation. To deal with these problems, we propose to estimate calibration curves for competing risks models based on jackknife pseudo-values that are combined with a nearest neighborhood smoother and a cross-validation approach to deal with all three problems. Copyright © 2014 John Wiley & Sons, Ltd.

Driver Assistance System for Passive Multi-Trailer Vehicles with Haptic Steering Limitations on the Leading Unit

PubMed Central

Morales, Jesús; Mandow, Anthony; Martínez, Jorge L.; Reina, Antonio J.; García-Cerezo, Alfonso

2013-01-01

Driving vehicles with one or more passive trailers has difficulties in both forward and backward motion due to inter-unit collisions, jackknife, and lack of visibility. Consequently, advanced driver assistance systems (ADAS) for multi-trailer combinations can be beneficial to accident avoidance as well as to driver comfort. The ADAS proposed in this paper aims to prevent unsafe steering commands by means of a haptic handwheel. Furthermore, when driving in reverse, the steering-wheel and pedals can be used as if the vehicle was driven from the back of the last trailer with visual aid from a rear-view camera. This solution, which can be implemented in drive-by-wire vehicles with hitch angle sensors, profits from two methods previously developed by the authors: safe steering by applying a curvature limitation to the leading unit, and a virtual tractor concept for backward motion that includes the complex case of set-point propagation through on-axle hitches. The paper addresses system requirements and provides implementation details to tele-operate two different off- and on-axle combinations of a tracked mobile robot pulling and pushing two dissimilar trailers. PMID:23552102

SLLE for predicting membrane protein types.

PubMed

Wang, Meng; Yang, Jie; Xu, Zhi-Jie; Chou, Kuo-Chen

2005-01-07

Introduction of the concept of pseudo amino acid composition (PROTEINS: Structure, Function, and Genetics 43 (2001) 246; Erratum: ibid. 44 (2001) 60) has made it possible to incorporate a considerable amount of sequence-order effects by representing a protein sample in terms of a set of discrete numbers, and hence can significantly enhance the prediction quality of membrane protein type. As a continuous effort along such a line, the Supervised Locally Linear Embedding (SLLE) technique for nonlinear dimensionality reduction is introduced (Science 22 (2000) 2323). The advantage of using SLLE is that it can reduce the operational space by extracting the essential features from the high-dimensional pseudo amino acid composition space, and that the cluster-tolerant capacity can be increased accordingly. As a consequence by combining these two approaches, high success rates have been observed during the tests of self-consistency, jackknife and independent data set, respectively, by using the simplest nearest neighbour classifier. The current approach represents a new strategy to deal with the problems of protein attribute prediction, and hence may become a useful vehicle in the area of bioinformatics and proteomics.

Predicting Drug-Target Interaction Networks Based on Functional Groups and Biological Features

PubMed Central

Shi, Xiao-He; Hu, Le-Le; Kong, Xiangyin; Cai, Yu-Dong; Chou, Kuo-Chen

2010-01-01

Background Study of drug-target interaction networks is an important topic for drug development. It is both time-consuming and costly to determine compound-protein interactions or potential drug-target interactions by experiments alone. As a complement, the in silico prediction methods can provide us with very useful information in a timely manner. Methods/Principal Findings To realize this, drug compounds are encoded with functional groups and proteins encoded by biological features including biochemical and physicochemical properties. The optimal feature selection procedures are adopted by means of the mRMR (Maximum Relevance Minimum Redundancy) method. Instead of classifying the proteins as a whole family, target proteins are divided into four groups: enzymes, ion channels, G-protein- coupled receptors and nuclear receptors. Thus, four independent predictors are established using the Nearest Neighbor algorithm as their operation engine, with each to predict the interactions between drugs and one of the four protein groups. As a result, the overall success rates by the jackknife cross-validation tests achieved with the four predictors are 85.48%, 80.78%, 78.49%, and 85.66%, respectively. Conclusion/Significance Our results indicate that the network prediction system thus established is quite promising and encouraging. PMID:20300175

Standard errors and confidence intervals for variable importance in random forest regression, classification, and survival.

PubMed

Ishwaran, Hemant; Lu, Min

2018-06-04

Random forests are a popular nonparametric tree ensemble procedure with broad applications to data analysis. While its widespread popularity stems from its prediction performance, an equally important feature is that it provides a fully nonparametric measure of variable importance (VIMP). A current limitation of VIMP, however, is that no systematic method exists for estimating its variance. As a solution, we propose a subsampling approach that can be used to estimate the variance of VIMP and for constructing confidence intervals. The method is general enough that it can be applied to many useful settings, including regression, classification, and survival problems. Using extensive simulations, we demonstrate the effectiveness of the subsampling estimator and in particular find that the delete-d jackknife variance estimator, a close cousin, is especially effective under low subsampling rates due to its bias correction properties. These 2 estimators are highly competitive when compared with the .164 bootstrap estimator, a modified bootstrap procedure designed to deal with ties in out-of-sample data. Most importantly, subsampling is computationally fast, thus making it especially attractive for big data settings. Copyright © 2018 John Wiley & Sons, Ltd.

Predicting DNA binding proteins using support vector machine with hybrid fractal features.

PubMed

Niu, Xiao-Hui; Hu, Xue-Hai; Shi, Feng; Xia, Jing-Bo

2014-02-21

DNA-binding proteins play a vitally important role in many biological processes. Prediction of DNA-binding proteins from amino acid sequence is a significant but not fairly resolved scientific problem. Chaos game representation (CGR) investigates the patterns hidden in protein sequences, and visually reveals previously unknown structure. Fractal dimensions (FD) are good tools to measure sizes of complex, highly irregular geometric objects. In order to extract the intrinsic correlation with DNA-binding property from protein sequences, CGR algorithm, fractal dimension and amino acid composition are applied to formulate the numerical features of protein samples in this paper. Seven groups of features are extracted, which can be computed directly from the primary sequence, and each group is evaluated by the 10-fold cross-validation test and Jackknife test. Comparing the results of numerical experiments, the group of amino acid composition and fractal dimension (21-dimension vector) gets the best result, the average accuracy is 81.82% and average Matthew's correlation coefficient (MCC) is 0.6017. This resulting predictor is also compared with existing method DNA-Prot and shows better performances. © 2013 The Authors. Published by Elsevier Ltd All rights reserved.

Prediction of protein subcellular locations by GO-FunD-PseAA predictor.

PubMed

Chou, Kuo-Chen; Cai, Yu-Dong

2004-08-06

The localization of a protein in a cell is closely correlated with its biological function. With the explosion of protein sequences entering into DataBanks, it is highly desired to develop an automated method that can fast identify their subcellular location. This will expedite the annotation process, providing timely useful information for both basic research and industrial application. In view of this, a powerful predictor has been developed by hybridizing the gene ontology approach [Nat. Genet. 25 (2000) 25], functional domain composition approach [J. Biol. Chem. 277 (2002) 45765], and the pseudo-amino acid composition approach [Proteins Struct. Funct. Genet. 43 (2001) 246; Erratum: ibid. 44 (2001) 60]. As a showcase, the recently constructed dataset [Bioinformatics 19 (2003) 1656] was used for demonstration. The dataset contains 7589 proteins classified into 12 subcellular locations: chloroplast, cytoplasmic, cytoskeleton, endoplasmic reticulum, extracellular, Golgi apparatus, lysosomal, mitochondrial, nuclear, peroxisomal, plasma membrane, and vacuolar. The overall success rate of prediction obtained by the jackknife cross-validation was 92%. This is so far the highest success rate performed on this dataset by following an objective and rigorous cross-validation procedure.

OH-PRED: prediction of protein hydroxylation sites by incorporating adapted normal distribution bi-profile Bayes feature extraction and physicochemical properties of amino acids.

PubMed

Jia, Cang-Zhi; He, Wen-Ying; Yao, Yu-Hua

2017-03-01

Hydroxylation of proline or lysine residues in proteins is a common post-translational modification event, and such modifications are found in many physiological and pathological processes. Nonetheless, the exact molecular mechanism of hydroxylation remains under investigation. Because experimental identification of hydroxylation is time-consuming and expensive, bioinformatics tools with high accuracy represent desirable alternatives for large-scale rapid identification of protein hydroxylation sites. In view of this, we developed a supporter vector machine-based tool, OH-PRED, for the prediction of protein hydroxylation sites using the adapted normal distribution bi-profile Bayes feature extraction in combination with the physicochemical property indexes of the amino acids. In a jackknife cross validation, OH-PRED yields an accuracy of 91.88% and a Matthew's correlation coefficient (MCC) of 0.838 for the prediction of hydroxyproline sites, and yields an accuracy of 97.42% and a MCC of 0.949 for the prediction of hydroxylysine sites. These results demonstrate that OH-PRED increased significantly the prediction accuracy of hydroxyproline and hydroxylysine sites by 7.37 and 14.09%, respectively, when compared with the latest predictor PredHydroxy. In independent tests, OH-PRED also outperforms previously published methods.

Accurate prediction of subcellular location of apoptosis proteins combining Chou’s PseAAC and PsePSSM based on wavelet denoising

PubMed Central

Chen, Cheng; Chen, Rui-Xin; Wang, Lei; Wang, Ming-Hui; Zhang, Yan

2017-01-01

Apoptosis proteins subcellular localization information are very important for understanding the mechanism of programmed cell death and the development of drugs. The prediction of subcellular localization of an apoptosis protein is still a challenging task because the prediction of apoptosis proteins subcellular localization can help to understand their function and the role of metabolic processes. In this paper, we propose a novel method for protein subcellular localization prediction. Firstly, the features of the protein sequence are extracted by combining Chou's pseudo amino acid composition (PseAAC) and pseudo-position specific scoring matrix (PsePSSM), then the feature information of the extracted is denoised by two-dimensional (2-D) wavelet denoising. Finally, the optimal feature vectors are input to the SVM classifier to predict subcellular location of apoptosis proteins. Quite promising predictions are obtained using the jackknife test on three widely used datasets and compared with other state-of-the-art methods. The results indicate that the method proposed in this paper can remarkably improve the prediction accuracy of apoptosis protein subcellular localization, which will be a supplementary tool for future proteomics research. PMID:29296195

Prediction of Protein Structural Classes for Low-Similarity Sequences Based on Consensus Sequence and Segmented PSSM.

PubMed

Liang, Yunyun; Liu, Sanyang; Zhang, Shengli

2015-01-01

Prediction of protein structural classes for low-similarity sequences is useful for understanding fold patterns, regulation, functions, and interactions of proteins. It is well known that feature extraction is significant to prediction of protein structural class and it mainly uses protein primary sequence, predicted secondary structure sequence, and position-specific scoring matrix (PSSM). Currently, prediction solely based on the PSSM has played a key role in improving the prediction accuracy. In this paper, we propose a novel method called CSP-SegPseP-SegACP by fusing consensus sequence (CS), segmented PsePSSM, and segmented autocovariance transformation (ACT) based on PSSM. Three widely used low-similarity datasets (1189, 25PDB, and 640) are adopted in this paper. Then a 700-dimensional (700D) feature vector is constructed and the dimension is decreased to 224D by using principal component analysis (PCA). To verify the performance of our method, rigorous jackknife cross-validation tests are performed on 1189, 25PDB, and 640 datasets. Comparison of our results with the existing PSSM-based methods demonstrates that our method achieves the favorable and competitive performance. This will offer an important complementary to other PSSM-based methods for prediction of protein structural classes for low-similarity sequences.

Predicting bacteriophage proteins located in host cell with feature selection technique.

PubMed

Ding, Hui; Liang, Zhi-Yong; Guo, Feng-Biao; Huang, Jian; Chen, Wei; Lin, Hao

2016-04-01

A bacteriophage is a virus that can infect a bacterium. The fate of an infected bacterium is determined by the bacteriophage proteins located in the host cell. Thus, reliably identifying bacteriophage proteins located in the host cell is extremely important to understand their functions and discover potential anti-bacterial drugs. Thus, in this paper, a computational method was developed to recognize bacteriophage proteins located in host cells based only on their amino acid sequences. The analysis of variance (ANOVA) combined with incremental feature selection (IFS) was proposed to optimize the feature set. Using a jackknife cross-validation, our method can discriminate between bacteriophage proteins located in a host cell and the bacteriophage proteins not located in a host cell with a maximum overall accuracy of 84.2%, and can further classify bacteriophage proteins located in host cell cytoplasm and in host cell membranes with a maximum overall accuracy of 92.4%. To enhance the value of the practical applications of the method, we built a web server called PHPred (〈http://lin.uestc.edu.cn/server/PHPred〉). We believe that the PHPred will become a powerful tool to study bacteriophage proteins located in host cells and to guide related drug discovery. Copyright © 2016 Elsevier Ltd. All rights reserved.

Potential use of ionic species for identifying source land-uses of stormwater runoff.

PubMed

Lee, Dong Hoon; Kim, Jin Hwi; Mendoza, Joseph A; Lee, Chang-Hee; Kang, Joo-Hyon

2017-02-01

Identifying critical land-uses or source areas is important to prioritize resources for cost-effective stormwater management. This study investigated the use of information on ionic composition as a fingerprint to identify the source land-use of stormwater runoff. We used 12 ionic species in stormwater runoff monitored for a total of 20 storm events at five sites with different land-use compositions during the 2012-2014 wet seasons. A stepwise forward discriminant function analysis (DFA) with the jack-knifed cross validation approach was used to select ionic species that better discriminate the land-use of its source. Of the 12 ionic species, 9 species (K + , Mg 2+ , Na + , NH 4 + , Br - , Cl - , F - , NO 2 - , and SO 4 2- ) were selected for better performance of the DFA. The DFA successfully differentiated stormwater samples from urban, rural, and construction sites using concentrations of the ionic species (70%, 95%, and 91% of correct classification, respectively). Over 80% of the new data cases were correctly classified by the trained DFA model. When applied to data cases from a mixed land-use catchment and downstream, the DFA model showed the greater impact of urban areas and rural areas respectively in the earlier and later parts of a storm event.

A Direct Comparison of Two Densely Sampled HIV Epidemics: The UK and Switzerland

NASA Astrophysics Data System (ADS)

Ragonnet-Cronin, Manon L.; Shilaih, Mohaned; Günthard, Huldrych F.; Hodcroft, Emma B.; Böni, Jürg; Fearnhill, Esther; Dunn, David; Yerly, Sabine; Klimkait, Thomas; Aubert, Vincent; Yang, Wan-Lin; Brown, Alison E.; Lycett, Samantha J.; Kouyos, Roger; Brown, Andrew J. Leigh

2016-09-01

Phylogenetic clustering approaches can elucidate HIV transmission dynamics. Comparisons across countries are essential for evaluating public health policies. Here, we used a standardised approach to compare the UK HIV Drug Resistance Database and the Swiss HIV Cohort Study while maintaining data-protection requirements. Clusters were identified in subtype A1, B and C pol phylogenies. We generated degree distributions for each risk group and compared distributions between countries using Kolmogorov-Smirnov (KS) tests, Degree Distribution Quantification and Comparison (DDQC) and bootstrapping. We used logistic regression to predict cluster membership based on country, sampling date, risk group, ethnicity and sex. We analysed >8,000 Swiss and >30,000 UK subtype B sequences. At 4.5% genetic distance, the UK was more clustered and MSM and heterosexual degree distributions differed significantly by the KS test. The KS test is sensitive to variation in network scale, and jackknifing the UK MSM dataset to the size of the Swiss dataset removed the difference. Only heterosexuals varied based on the DDQC, due to UK male heterosexuals who clustered exclusively with MSM. Their removal eliminated this difference. In conclusion, the UK and Swiss HIV epidemics have similar underlying dynamics and observed differences in clustering are mainly due to different population sizes.

Prediction of beta-turns from amino acid sequences using the residue-coupled model.

PubMed

Guruprasad, K; Shukla, S

2003-04-01

We evaluated the prediction of beta-turns from amino acid sequences using the residue-coupled model with an enlarged representative protein data set selected from the Protein Data Bank. Our results show that the probability values derived from a data set comprising 425 protein chains yielded an overall beta-turn prediction accuracy 68.74%, compared with 94.7% reported earlier on a data set of 30 proteins using the same method. However, we noted that the overall beta-turn prediction accuracy using probability values derived from the 30-protein data set reduces to 40.74% when tested on the data set comprising 425 protein chains. In contrast, using probability values derived from the 425 data set used in this analysis, the overall beta-turn prediction accuracy yielded consistent results when tested on either the 30-protein data set (64.62%) used earlier or a more recent representative data set comprising 619 protein chains (64.66%) or on a jackknife data set comprising 476 representative protein chains (63.38%). We therefore recommend the use of probability values derived from the 425 representative protein chains data set reported here, which gives more realistic and consistent predictions of beta-turns from amino acid sequences.

Predicting red wolf release success in the southeastern United States

USGS Publications Warehouse

van Manen, Frank T.; Crawford, Barron A.; Clark, Joseph D.

2000-01-01

Although the red wolf (Canis rufus) was once found throughout the southeastern United States, indiscriminate killing and habitat destruction reduced its range to a small section of coastal Texas and Louisiana. Wolves trapped from 1973 to 1980 were taken to establish a captive breeding program that was used to repatriate 2 mainland and 3 island red wolf populations. We collected data from 320 red wolf releases in these areas and classified each as a success or failure based on survival and reproductive criteria, and whether recaptures were necessary to resolve conflicts with humans. We evaluated the relations between release success and conditions at the release sites, characteristics of released wolves, and release procedures. Although <44% of the variation in release success was explained, model performance based on jackknife tests indicated a 72-80% correct prediction rate for the 4 operational models we developed. The models indicated that success was associated with human influences on the landscape and the level of wolf habituation to humans prior to release. We applied the models to 31 prospective areas for wolf repatriation and calculated an index of release success for each area. Decision-makers can use these models to objectively rank prospective release areas and compare strengths and weaknesses of each.

The potential distribution of Phlebotomus papatasi (Diptera: Psychodidae) in Libya based on ecological niche model.

PubMed

Abdel-Dayem, M S; Annajar, B B; Hanafi, H A; Obenauer, P J

2012-05-01

The increased cases of cutaneous leishmaniasis vectored by Phlebotomus papatasi (Scopoli) in Libya have driven considerable effort to develop a predictive model for the potential geographical distribution of this disease. We collected adult P. papatasi from 17 sites in Musrata and Yefern regions of Libya using four different attraction traps. Our trap results and literature records describing the distribution of P. papatasi were incorporated into a MaxEnt algorithm prediction model that used 22 environmental variables. The model showed a high performance (AUC = 0.992 and 0.990 for training and test data, respectively). High suitability for P. papatasi was predicted to be largely confined to the coast at altitudes <600 m. Regions south of 300 degrees N latitude were calculated as unsuitable for this species. Jackknife analysis identified precipitation as having the most significant predictive power, while temperature and elevation variables were less influential. The National Leishmaniasis Control Program in Libya may find this information useful in their efforts to control zoonotic cutaneous leishmaniasis. Existing records are strongly biased toward a few geographical regions, and therefore, further sand fly collections are warranted that should include documentation of such factors as soil texture and humidity, land cover, and normalized difference vegetation index (NDVI) data to increase the model's predictive power.

Detection of the pairwise kinematic Sunyaev-Zel'dovich effect with BOSS DR11 and the Atacama Cosmology Telescope

NASA Astrophysics Data System (ADS)

De Bernardis, F.; Aiola, S.; Vavagiakis, E. M.; Battaglia, N.; Niemack, M. D.; Beall, J.; Becker, D. T.; Bond, J. R.; Calabrese, E.; Cho, H.; Coughlin, K.; Datta, R.; Devlin, M.; Dunkley, J.; Dunner, R.; Ferraro, S.; Fox, A.; Gallardo, P. A.; Halpern, M.; Hand, N.; Hasselfield, M.; Henderson, S. W.; Hill, J. C.; Hilton, G. C.; Hilton, M.; Hincks, A. D.; Hlozek, R.; Hubmayr, J.; Huffenberger, K.; Hughes, J. P.; Irwin, K. D.; Koopman, B. J.; Kosowsky, A.; Li, D.; Louis, T.; Lungu, M.; Madhavacheril, M. S.; Maurin, L.; McMahon, J.; Moodley, K.; Naess, S.; Nati, F.; Newburgh, L.; Nibarger, J. P.; Page, L. A.; Partridge, B.; Schaan, E.; Schmitt, B. L.; Sehgal, N.; Sievers, J.; Simon, S. M.; Spergel, D. N.; Staggs, S. T.; Stevens, J. R.; Thornton, R. J.; van Engelen, A.; Van Lanen, J.; Wollack, E. J.

2017-03-01

We present a new measurement of the kinematic Sunyaev-Zel'dovich effect using data from the Atacama Cosmology Telescope (ACT) and the Baryon Oscillation Spectroscopic Survey (BOSS). Using 600 square degrees of overlapping sky area, we evaluate the mean pairwise baryon momentum associated with the positions of 50,000 bright galaxies in the BOSS DR11 Large Scale Structure catalog. A non-zero signal arises from the large-scale motions of halos containing the sample galaxies. The data fits an analytical signal model well, with the optical depth to microwave photon scattering as a free parameter determining the overall signal amplitude. We estimate the covariance matrix of the mean pairwise momentum as a function of galaxy separation, using microwave sky simulations, jackknife evaluation, and bootstrap estimates. The most conservative simulation-based errors give signal-to-noise estimates between 3.6 and 4.1 for varying galaxy luminosity cuts. We discuss how the other error determinations can lead to higher signal-to-noise values, and consider the impact of several possible systematic errors. Estimates of the optical depth from the average thermal Sunyaev-Zel'dovich signal at the sample galaxy positions are broadly consistent with those obtained from the mean pairwise momentum signal.

Hybridisation and diversification in the adaptive radiation of clownfishes.

PubMed

Litsios, Glenn; Salamin, Nicolas

2014-11-30

The importance of hybridisation during species diversification has long been debated among evolutionary biologists. It is increasingly recognised that hybridisation events occurred during the evolutionary history of numerous species, especially during the early stages of adaptive radiation. We study the effect of hybridisation on diversification in the clownfishes, a clade of coral reef fish that diversified through an adaptive radiation process. While two species of clownfish are likely to have been described from hybrid specimens, the occurrence and effect of hybridisation on the clade diversification is yet unknown. We generate sequences of three mitochondrial genes to complete an existing dataset of nuclear sequences and document cytonuclear discordance at a node, which shows a drastic increase of diversification rate. Then, using a tree-based jack-knife method, we identify clownfish species likely stemming from hybridisation events. Finally, we use molecular cloning and identify the putative parental species of four clownfish specimens that display the morphological characteristics of hybrids. Our results show that consistently with the syngameon hypothesis, hybridisation events are linked with a burst of diversification in the clownfishes. Moreover, several recently diverged clownfish lineages likely originated through hybridisation, which indicates that diversification, catalysed by hybridisation events, may still be happening.

Estimation of abbreviated mycophenolic acid area under the concentration-time curve during early posttransplant period by limited sampling strategy.

PubMed

Mohammadpour, A-H; Nazemian, F; Abtahi, B; Naghibi, M; Gholami, K; Rezaee, S; Nazari, M-R A; Rajabi, O

2008-12-01

Area under the concentration curve (AUC) of mycophenolic acid (MPA) could help to optimize therapeutic drug monitoring during the early post-renal transplant period. The aim of this study was to develop a limited sampling strategy to estimate an abbreviated MPA AUC within the first month after renal transplantation. In this study we selected 19 patients in the early posttransplant period with normal renal graft function (glomerular filtration rate > 70 mL/min). Plasma MPA concentrations were measured using reverse-phase high-performance liquid chromatography. MPA AUC(0-12h) was calculated using the linear trapezoidal rule. Multiple stepwise regression analysis was used to determine the minimal and convenient time points of MPA levels that could be used to derive model equations best fitted to MPA AUC(0-12h). The regression equation for AUC estimation that gave the best performance was AUC = 14.46 C(10) + 15.547 (r(2) = .882). The validation of the method was performed using the jackknife method. Mean prediction error of this model was not different from zero (P > .05) and had a high root mean square prediction error (8.06). In conclusion, this limited sampling strategy provided an effective approach for therapeutic drug monitoring during the early posttransplant period.

Variables influencing the presence of subyearling fall Chinook salmon in shoreline habitats of the Hanford Reach, Columbia River

USGS Publications Warehouse

Tiffan, K.F.; Clark, L.O.; Garland, R.D.; Rondorf, D.W.

2006-01-01

Little information currently exists on habitat use by subyearling fall Chinook salmon Oncorhynchus tshawytscha rearing in large, main-stem habitats. We collected habitat use information on subyearlings in the Hanford Reach of the Columbia River during May 1994 and April-May 1995 using point abundance electrofishing. We analyzed measures of physical habitat using logistic regression to predict fish presence and absence in shoreline habitats. The difference between water temperature at the point of sampling and in the main river channel was the most important variable for predicting the presence and absence of subyearlings. Mean water velocities of 45 cm/s or less and habitats with low lateral bank slopes were also associated with a greater likelihood of subyearling presence. Intermediate-sized gravel and cobble substrates were significant predictors of fish presence, but small (<32-mm) and boulder-sized (>256-mm) substrates were not. Our rearing model was accurate at predicting fish presence and absence using jackknifing (80% correct) and classification of observations from an independent data set (76% correct). The habitat requirements of fall Chinook salmon in the Hanford Reach are similar to those reported for juvenile Chinook salmon in smaller systems but are met in functionally different ways in a large river.

Predicting the Potential Distribution of Polygala tenuifolia Willd. under Climate Change in China

PubMed Central

Li, Lin; Zhao, Yao; Pei, Lin; Zhao, Jiancheng

2016-01-01

Global warming has created opportunities and challenges for the survival and development of species. Determining how climate change may impact multiple ecosystem levels and lead to various species adaptations is necessary for both biodiversity conservation and sustainable biological resource utilization. In this study, we employed Maxent to predict changes in the habitat range and altitude of Polygala tenuifolia Willd. under current and future climate scenarios in China. Four representative concentration pathways (RCP2.6, RCP4.5, RCP6.0, and RCP8.5) were modeled for two time periods (2050 and 2070). The model inputs included 732 presence points and nine sets of environmental variables under the current conditions and the four RCPs in 2050 and 2070. The area under the receiver-operating characteristic (ROC) curve (AUC) was used to evaluate model performance. All of the AUCs were greater than 0.80, thereby placing these models in the “very good” category. Using a jackknife analysis, the precipitation in the warmest quarter, annual mean temperature, and altitude were found to be the top three variables that affect the range of P. tenuifolia. Additionally, we found that the predicted highly suitable habitat was in reasonable agreement with its actual distribution. Furthermore, the highly suitable habitat area was slowly reduced over time. PMID:27661983

Mapping the climatic suitable habitat of oriental arborvitae (Platycladus orientalis) for introduction and cultivation at a global scale.

PubMed

Li, Guoqing; Du, Sheng; Wen, Zhongming

2016-07-21

Oriental arborvitae (Platycladus orientalis) is an important afforestation and ornamental tree species, which is native in eastern Asian. Therefore, a global suitable habitat map for oriental arborvitae is urgently needed for global promotion and cultivation. Here, the potential habitat and climatic requirements of oriental arborvitae at global scale were simulated using herbariums data and 13 thermal-moisture variables as input data for maximum entropy model (MaxEnt). The simulation performance of MaxEnt is evaluated by ten-fold cross-validation and a jackknife procedure. Results show that the potential habitat and climate envelop of oriental arborvitae can be successfully simulated by MaxEnt at global scale, with a mean test AUC value of 0.93 and mean training AUC value of 0.95. Thermal factors play more important roles than moisture factors in controlling the distribution boundary of oriental arborvitae's potential ranges. There are about 50 countries suitable for introduction and cultivation of oriental arborvitae with an area of 2.0 × 10(7) km(2), which occupied 13.8% of land area on the earth. This unique study will provide valuable information and insights needed to identify new regions with climatically suitable habitats for cultivation and introduction of oriental arborvitae around the world.

Inverse probability weighting estimation of the volume under the ROC surface in the presence of verification bias.

PubMed

Zhang, Ying; Alonzo, Todd A

2016-11-01

In diagnostic medicine, the volume under the receiver operating characteristic (ROC) surface (VUS) is a commonly used index to quantify the ability of a continuous diagnostic test to discriminate between three disease states. In practice, verification of the true disease status may be performed only for a subset of subjects under study since the verification procedure is invasive, risky, or expensive. The selection for disease examination might depend on the results of the diagnostic test and other clinical characteristics of the patients, which in turn can cause bias in estimates of the VUS. This bias is referred to as verification bias. Existing verification bias correction in three-way ROC analysis focuses on ordinal tests. We propose verification bias-correction methods to construct ROC surface and estimate the VUS for a continuous diagnostic test, based on inverse probability weighting. By applying U-statistics theory, we develop asymptotic properties for the estimator. A Jackknife estimator of variance is also derived. Extensive simulation studies are performed to evaluate the performance of the new estimators in terms of bias correction and variance. The proposed methods are used to assess the ability of a biomarker to accurately identify stages of Alzheimer's disease. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Phylotranscriptomic consolidation of the jawed vertebrate timetree.

PubMed

Irisarri, Iker; Baurain, Denis; Brinkmann, Henner; Delsuc, Frédéric; Sire, Jean-Yves; Kupfer, Alexander; Petersen, Jörn; Jarek, Michael; Meyer, Axel; Vences, Miguel; Philippe, Hervé

2017-09-01

Phylogenomics is extremely powerful but introduces new challenges as no agreement exists on "standards" for data selection, curation and tree inference. We use jawed vertebrates (Gnathostomata) as model to address these issues. Despite considerable efforts in resolving their evolutionary history and macroevolution, few studies have included a full phylogenetic diversity of gnathostomes and some relationships remain controversial. We tested a novel bioinformatic pipeline to assemble large and accurate phylogenomic datasets from RNA sequencing and find this phylotranscriptomic approach successful and highly cost-effective. Increased sequencing effort up to ca. 10Gbp allows recovering more genes, but shallower sequencing (1.5Gbp) is sufficient to obtain thousands of full-length orthologous transcripts. We reconstruct a robust and strongly supported timetree of jawed vertebrates using 7,189 nuclear genes from 100 taxa, including 23 new transcriptomes from previously unsampled key species. Gene jackknifing of genomic data corroborates the robustness of our tree and allows calculating genome-wide divergence times by overcoming gene sampling bias. Mitochondrial genomes prove insufficient to resolve the deepest relationships because of limited signal and among-lineage rate heterogeneity. Our analyses emphasize the importance of large curated nuclear datasets to increase the accuracy of phylogenomics and provide a reference framework for the evolutionary history of jawed vertebrates.

Estimation of local extreme suspended sediment concentrations in California Rivers.

PubMed

Tramblay, Yves; Saint-Hilaire, André; Ouarda, Taha B M J; Moatar, Florentina; Hecht, Barry

2010-09-01

The total amount of suspended sediment load carried by a stream during a year is usually transported during one or several extreme events related to high river flow and intense rainfall, leading to very high suspended sediment concentrations (SSCs). In this study quantiles of SSC derived from annual maximums and the 99th percentile of SSC series are considered to be estimated locally in a site-specific approach using regional information. Analyses of relationships between physiographic characteristics and the selected indicators were undertaken using the localities of 5-km radius draining of each sampling site. Multiple regression models were built to test the regional estimation for these indicators of suspended sediment transport. To assess the accuracy of the estimates, a Jack-Knife re-sampling procedure was used to compute the relative bias and root mean square error of the models. Results show that for the 19 stations considered in California, the extreme SSCs can be estimated with 40-60% uncertainty, depending on the presence of flow regulation in the basin. This modelling approach is likely to prove functional in other Mediterranean climate watersheds since they appear useful in California, where geologic, climatic, physiographic, and land-use conditions are highly variable. Copyright 2010 Elsevier B.V. All rights reserved.

Mapping the climatic suitable habitat of oriental arborvitae (Platycladus orientalis) for introduction and cultivation at a global scale

PubMed Central

Li, Guoqing; Du, Sheng; Wen, Zhongming

2016-01-01

Oriental arborvitae (Platycladus orientalis) is an important afforestation and ornamental tree species, which is native in eastern Asian. Therefore, a global suitable habitat map for oriental arborvitae is urgently needed for global promotion and cultivation. Here, the potential habitat and climatic requirements of oriental arborvitae at global scale were simulated using herbariums data and 13 thermal-moisture variables as input data for maximum entropy model (MaxEnt). The simulation performance of MaxEnt is evaluated by ten-fold cross-validation and a jackknife procedure. Results show that the potential habitat and climate envelop of oriental arborvitae can be successfully simulated by MaxEnt at global scale, with a mean test AUC value of 0.93 and mean training AUC value of 0.95. Thermal factors play more important roles than moisture factors in controlling the distribution boundary of oriental arborvitae’s potential ranges. There are about 50 countries suitable for introduction and cultivation of oriental arborvitae with an area of 2.0 × 107 km2, which occupied 13.8% of land area on the earth. This unique study will provide valuable information and insights needed to identify new regions with climatically suitable habitats for cultivation and introduction of oriental arborvitae around the world. PMID:27443221

A Computational Model for Predicting RNase H Domain of Retrovirus.

PubMed

Wu, Sijia; Zhang, Xinman; Han, Jiuqiang

2016-01-01

RNase H (RNH) is a pivotal domain in retrovirus to cleave the DNA-RNA hybrid for continuing retroviral replication. The crucial role indicates that RNH is a promising drug target for therapeutic intervention. However, annotated RNHs in UniProtKB database have still been insufficient for a good understanding of their statistical characteristics so far. In this work, a computational RNH model was proposed to annotate new putative RNHs (np-RNHs) in the retroviruses. It basically predicts RNH domains through recognizing their start and end sites separately with SVM method. The classification accuracy rates are 100%, 99.01% and 97.52% respectively corresponding to jack-knife, 10-fold cross-validation and 5-fold cross-validation test. Subsequently, this model discovered 14,033 np-RNHs after scanning sequences without RNH annotations. All these predicted np-RNHs and annotated RNHs were employed to analyze the length, hydrophobicity and evolutionary relationship of RNH domains. They are all related to retroviral genera, which validates the classification of retroviruses to a certain degree. In the end, a software tool was designed for the application of our prediction model. The software together with datasets involved in this paper can be available for free download at https://sourceforge.net/projects/rhtool/files/?source=navbar.

Prediction of Antimicrobial Peptides Based on Sequence Alignment and Feature Selection Methods

PubMed Central

Wang, Ping; Hu, Lele; Liu, Guiyou; Jiang, Nan; Chen, Xiaoyun; Xu, Jianyong; Zheng, Wen; Li, Li; Tan, Ming; Chen, Zugen; Song, Hui; Cai, Yu-Dong; Chou, Kuo-Chen

2011-01-01

Antimicrobial peptides (AMPs) represent a class of natural peptides that form a part of the innate immune system, and this kind of ‘nature's antibiotics’ is quite promising for solving the problem of increasing antibiotic resistance. In view of this, it is highly desired to develop an effective computational method for accurately predicting novel AMPs because it can provide us with more candidates and useful insights for drug design. In this study, a new method for predicting AMPs was implemented by integrating the sequence alignment method and the feature selection method. It was observed that, the overall jackknife success rate by the new predictor on a newly constructed benchmark dataset was over 80.23%, and the Mathews correlation coefficient is 0.73, indicating a good prediction. Moreover, it is indicated by an in-depth feature analysis that the results are quite consistent with the previously known knowledge that some amino acids are preferential in AMPs and that these amino acids do play an important role for the antimicrobial activity. For the convenience of most experimental scientists who want to use the prediction method without the interest to follow the mathematical details, a user-friendly web-server is provided at http://amp.biosino.org/. PMID:21533231

Atypical feeding behavior of Long-tailed Ducks in the wake of a commercial fishing boat while clamming

USGS Publications Warehouse

Perry, Matthew; Osenton, Peter C.; White, Timothy P.

2017-01-01

A foraging group of Clangula hyemalis (Long-tailed Duck) was observed on 10 February 2010 diving behind a commercial boat that was clamming near Monomoy Island, Nantucket Sound, MA. We used a shotgun to collect 9 of the ducks, and our analyses of gizzard and gullet (esophagus and proventriculus) revealed 37 food items in the gizzard and 16 in the gullet. Mollusca were the dominant food in the gizzard (49%), whereas Crustacea were dominant in the gullet (57%). Crustacea were the second most important food in the gizzard (38%), whereas Mollusca were the second most important food in the gullet (31%). Relatively high volumes of the Amphipoda Caprella sp. (skeleton shrimp) and the Decopoda Crangon septemspinosa (Sand Shrimp) were recorded in the gullet and gizzard. Ensis directus (Atlantic Jackknife Clam) formed the greatest volume of Mollusca in the gizzard (15%) and in the gullet (15%). Long-tailed Ducks had fed on this Bivalvia and several other species of Mollusca that had no shell or broken shell when consumed. Many of the food organisms were apparently dislodged and some damaged by the clamming operation creating an opportunistic feeding strategy for the Long-tailed Ducks.

Accurate RNA 5-methylcytosine site prediction based on heuristic physical-chemical properties reduction and classifier ensemble.

PubMed

Zhang, Ming; Xu, Yan; Li, Lei; Liu, Zi; Yang, Xibei; Yu, Dong-Jun

2018-06-01

RNA 5-methylcytosine (m 5 C) is an important post-transcriptional modification that plays an indispensable role in biological processes. The accurate identification of m 5 C sites from primary RNA sequences is especially useful for deeply understanding the mechanisms and functions of m 5 C. Due to the difficulty and expensive costs of identifying m 5 C sites with wet-lab techniques, developing fast and accurate machine-learning-based prediction methods is urgently needed. In this study, we proposed a new m 5 C site predictor, called M5C-HPCR, by introducing a novel heuristic nucleotide physicochemical property reduction (HPCR) algorithm and classifier ensemble. HPCR extracts multiple reducts of physical-chemical properties for encoding discriminative features, while the classifier ensemble is applied to integrate multiple base predictors, each of which is trained based on a separate reduct of the physical-chemical properties obtained from HPCR. Rigorous jackknife tests on two benchmark datasets demonstrate that M5C-HPCR outperforms state-of-the-art m 5 C site predictors, with the highest values of MCC (0.859) and AUC (0.962). We also implemented the webserver of M5C-HPCR, which is freely available at http://cslab.just.edu.cn:8080/M5C-HPCR/. Copyright © 2018 Elsevier Inc. All rights reserved.

Japan unified hIgh-resolution relocated catalog for earthquakes (JUICE): Crustal seismicity beneath the Japanese Islands

NASA Astrophysics Data System (ADS)

Yano, Tomoko E.; Takeda, Tetsuya; Matsubara, Makoto; Shiomi, Katsuhiko

2017-04-01

We have generated a high-resolution catalog called the ;Japan Unified hIgh-resolution relocated Catalog for Earthquakes; (JUICE), which can be used to evaluate the geometry and seismogenic depth of active faults in Japan. We relocated > 1.1 million hypocenters from the NIED Hi-net catalog for events which occurred between January 2001 and December 2012, to a depth of 40 km. We apply a relative hypocenter determination method to the data in each grid square, in which entire Japan is divided into 1257 grid squares to parallelize the relocation procedure. We used a double-difference method, incorporating cross-correlating differential times as well as catalog differential times. This allows us to resolve, in detail, a seismicity distribution for the entire Japanese Islands. We estimated location uncertainty by a statistical resampling method, using Jackknife samples, and show that the uncertainty can be within 0.37 km in the horizontal and 0.85 km in the vertical direction with a 90% confidence interval for areas with good station coverage. Our seismogenic depth estimate agrees with the lower limit of the hypocenter distribution for a recent earthquake on the Kamishiro fault (2014, Mj 6.7), which suggests that the new catalog should be useful for estimating the size of future earthquakes for inland active faults.

MultiP-Apo: A Multilabel Predictor for Identifying Subcellular Locations of Apoptosis Proteins

PubMed Central

Li, Hui; Wang, Rong; Gan, Yong

2017-01-01

Apoptosis proteins play an important role in the mechanism of programmed cell death. Predicting subcellular localization of apoptosis proteins is an essential step to understand their functions and identify drugs target. Many computational prediction methods have been developed for apoptosis protein subcellular localization. However, these existing works only focus on the proteins that have one location; proteins with multiple locations are either not considered or assumed as not existing when constructing prediction models, so that they cannot completely predict all the locations of the apoptosis proteins with multiple locations. To address this problem, this paper proposes a novel multilabel predictor named MultiP-Apo, which can predict not only apoptosis proteins with single subcellular location but also those with multiple subcellular locations. Specifically, given a query protein, GO-based feature extraction method is used to extract its feature vector. Subsequently, the GO feature vector is classified by a new multilabel classifier based on the label-specific features. It is the first multilabel predictor ever established for identifying subcellular locations of multilocation apoptosis proteins. As an initial study, MultiP-Apo achieves an overall accuracy of 58.49% by jackknife test, which indicates that our proposed predictor may become a very useful high-throughput tool in this area. PMID:28744305

Real-time eye tracking for the assessment of driver fatigue.

PubMed

Xu, Junli; Min, Jianliang; Hu, Jianfeng

2018-04-01

Eye-tracking is an important approach to collect evidence regarding some participants' driving fatigue. In this contribution, the authors present a non-intrusive system for evaluating driver fatigue by tracking eye movement behaviours. A real-time eye-tracker was used to monitor participants' eye state for collecting eye-movement data. These data are useful to get insights into assessing participants' fatigue state during monotonous driving. Ten healthy subjects performed continuous simulated driving for 1-2 h with eye state monitoring on a driving simulator in this study, and these measured features of the fixation time and the pupil area were recorded via using eye movement tracking device. For achieving a good cost-performance ratio and fast computation time, the fuzzy K -nearest neighbour was employed to evaluate and analyse the influence of different participants on the variations in the fixation duration and pupil area of drivers. The findings of this study indicated that there are significant differences in domain value distribution of the pupil area under the condition with normal and fatigue driving state. Result also suggests that the recognition accuracy by jackknife validation reaches to about 89% in average, implying that show a significant potential of real-time applicability of the proposed approach and is capable of detecting driver fatigue.

Real-time eye tracking for the assessment of driver fatigue

PubMed Central

Xu, Junli; Min, Jianliang

2018-01-01

Eye-tracking is an important approach to collect evidence regarding some participants’ driving fatigue. In this contribution, the authors present a non-intrusive system for evaluating driver fatigue by tracking eye movement behaviours. A real-time eye-tracker was used to monitor participants’ eye state for collecting eye-movement data. These data are useful to get insights into assessing participants’ fatigue state during monotonous driving. Ten healthy subjects performed continuous simulated driving for 1–2 h with eye state monitoring on a driving simulator in this study, and these measured features of the fixation time and the pupil area were recorded via using eye movement tracking device. For achieving a good cost-performance ratio and fast computation time, the fuzzy K-nearest neighbour was employed to evaluate and analyse the influence of different participants on the variations in the fixation duration and pupil area of drivers. The findings of this study indicated that there are significant differences in domain value distribution of the pupil area under the condition with normal and fatigue driving state. Result also suggests that the recognition accuracy by jackknife validation reaches to about 89% in average, implying that show a significant potential of real-time applicability of the proposed approach and is capable of detecting driver fatigue. PMID:29750113

Detection of the pairwise kinematic Sunyaev-Zel'dovich effect with BOSS DR11 and the Atacama Cosmology Telescope

DOE PAGES

Bernardis, F. De; Aiola, S.; Vavagiakis, E. M.; ...

2017-03-07

Here, we present a new measurement of the kinematic Sunyaev-Zel'dovich effect using data from the Atacama Cosmology Telescope (ACT) and the Baryon Oscillation Spectroscopic Survey (BOSS). Using 600 square degrees of overlapping sky area, we evaluate the mean pairwise baryon momentum associated with the positions of 50,000 bright galaxies in the BOSS DR11 Large Scale Structure catalog. A non-zero signal arises from the large-scale motions of halos containing the sample galaxies. The data fits an analytical signal model well, with the optical depth to microwave photon scattering as a free parameter determining the overall signal amplitude. We estimate the covariancemore » matrix of the mean pairwise momentum as a function of galaxy separation, using microwave sky simulations, jackknife evaluation, and bootstrap estimates. The most conservative simulation-based errors give signal-to-noise estimates between 3.6 and 4.1 for varying galaxy luminosity cuts. We discuss how the other error determinations can lead to higher signal-to-noise values, and consider the impact of several possible systematic errors. Estimates of the optical depth from the average thermal Sunyaev-Zel'dovich signal at the sample galaxy positions are broadly consistent with those obtained from the mean pairwise momentum signal.« less

BICEP2 / Keck Array V: Measurements of B-mode polarization at degree angular scales and 150 GHz by the Keck Array

DOE PAGES

Ade, P. A. R.; Ahmed, Z.; Aikin, R. W.; ...

2015-09-29

Here, the Keck Array is a system of cosmic microwave background polarimeters, each similar to the Bicep2 experiment. In this paper we report results from the 2012 to 2013 observing seasons, during which the Keck Array consisted of five receivers all operating in the same (150 GHz) frequency band and observing field as Bicep2. We again find an excess of B-mode power over the lensed-ΛCDM expectation of >5σ in the range 30 < ℓ < 150 and confirm that this is not due to systematics using jackknife tests and simulations based on detailed calibration measurements. In map difference and spectralmore » difference tests these new data are shown to be consistent with Bicep2. Finally, we combine the maps from the two experiments to produce final Q and U maps which have a depth of 57 nK deg (3.4 μK arcmin) over an effective area of 400 deg 2 for an equivalent survey weight of 250,000 μK –2. The final BB band powers have noise uncertainty a factor of 2.3 times better than the previous results, and a significance of detection of excess power of >6σ.« less

Neuropsychological dysfunction in schizophrenia and affective disease.

PubMed

Taylor, M A; Redfield, J; Abrams, R

1981-05-01

We used Smith's neuropsychological test battery to study the cortical functioning of 52 patients with affective disorders, 17 schizophrenics, and 8 patients with coarse brain disease (CBD), all diagnosed according to research criteria. Testing and diagnoses were made independently and blindly. After accounting for the variance due to age, sex, handedness, educational level, and psychotropic drugs, we found that on tests of dominant hemisphere function schizophrenics performed significantly worse than patients with affective disorder but were no different from patients with CBD. On tests of nondominant hemisphere function the performance of the schizophrenics was similar to that of the other two groups, which were different from each other in that patients with CBD had poorer performance than affectives. A discriminant function analysis of the test scores applied to a jackknifed classification matrix successfully predicted research diagnosis in 86.5% of the affectively ill patients and 76.5% of the schizophrenics, for an overall hit rate of 84.1%. A canonical plot of the discriminant scores further showed distinct groups, with manics and depressives most alike but quite different from schizophrenics and patients with CBD. These findings are consistent with those derived from other neuropsychological studies, as well as EEG and CT scan studies.

EGS hydraulic stimulation monitoring by surface arrays - location accuracy and completeness magnitude: the Basel Deep Heat Mining Project case study

NASA Astrophysics Data System (ADS)

Häge, Martin; Blascheck, Patrick; Joswig, Manfred

2013-01-01

The potential and limits of monitoring induced seismicity by surface-based mini arrays was evaluated for the hydraulic stimulation of the Basel Deep Heat Mining Project. This project aimed at the exploitation of geothermal heat from a depth of about 4,630 m. As reference for our results, a network of borehole stations by Geothermal Explorers Ltd. provided ground truth information. We utilized array processing, sonogram event detection and outlier-resistant, graphical jackknife location procedures to compensate for the decrease in signal-to-noise ratio at the surface. We could correctly resolve the NNW-SSE striking fault plane by relative master event locations. Statistical analysis of our catalog data resulted in M L 0.36 as completeness magnitude, but with significant day-to-night dependency. To compare to the performance of borehole data with M W 0.9 as completeness magnitude, we applied two methods for converting M L to M W which raised our M C to M W in the range of 0.99-1.13. Further, the b value for the duration of our measurement was calculated to 1.14 (related to M L), respectively 1.66 (related to M W), but changes over time could not be resolved from the error bars.

BICEP2/KECK ARRAY V: MEASUREMENTS OF B-MODE POLARIZATION AT DEGREE ANGULAR SCALES AND 150 GHz BY THE KECK ARRAY

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ade, P. A. R.; Ahmed, Z.; Aikin, R. W.

2015-10-01

The Keck Array is a system of cosmic microwave background polarimeters, each similar to the Bicep2 experiment. In this paper we report results from the 2012 to 2013 observing seasons, during which the Keck Array consisted of five receivers all operating in the same (150 GHz) frequency band and observing field as Bicep2. We again find an excess of B-mode power over the lensed-ΛCDM expectation of >5σ in the range 30 < ℓ < 150 and confirm that this is not due to systematics using jackknife tests and simulations based on detailed calibration measurements. In map difference and spectral differencemore » tests these new data are shown to be consistent with Bicep2. Finally, we combine the maps from the two experiments to produce final Q and U maps which have a depth of 57 nK deg (3.4 μK arcmin) over an effective area of 400 deg{sup 2} for an equivalent survey weight of 250,000 μK{sup −2}. The final BB band powers have noise uncertainty a factor of 2.3 times better than the previous results, and a significance of detection of excess power of >6σ.« less

Prediction of lysine ubiquitylation with ensemble classifier and feature selection.

PubMed

Zhao, Xiaowei; Li, Xiangtao; Ma, Zhiqiang; Yin, Minghao

2011-01-01

Ubiquitylation is an important process of post-translational modification. Correct identification of protein lysine ubiquitylation sites is of fundamental importance to understand the molecular mechanism of lysine ubiquitylation in biological systems. This paper develops a novel computational method to effectively identify the lysine ubiquitylation sites based on the ensemble approach. In the proposed method, 468 ubiquitylation sites from 323 proteins retrieved from the Swiss-Prot database were encoded into feature vectors by using four kinds of protein sequences information. An effective feature selection method was then applied to extract informative feature subsets. After different feature subsets were obtained by setting different starting points in the search procedure, they were used to train multiple random forests classifiers and then aggregated into a consensus classifier by majority voting. Evaluated by jackknife tests and independent tests respectively, the accuracy of the proposed predictor reached 76.82% for the training dataset and 79.16% for the test dataset, indicating that this predictor is a useful tool to predict lysine ubiquitylation sites. Furthermore, site-specific feature analysis was performed and it was shown that ubiquitylation is intimately correlated with the features of its surrounding sites in addition to features derived from the lysine site itself. The feature selection method is available upon request.

Stock structure of Lake Baikal omul as determined by whole-body morphology

USGS Publications Warehouse

Bronte, Charles R.; Fleischer, G.W.; Maistrenko, S.G.; Pronin, N.M.

1999-01-01

In Lake Baikal, three morphotypes of omul Coregonus autumnalis migratorius are recognized; the littoral, pelagic, and deep-water forms. Morphotype assignment is difficult, and similar to that encountered in pelagic and deep-water coregonines in the Laurentian Great Lakes. Principal component analysis revealed separation of all three morphotypes based on caudal peduncle length and depth, length and depth of the body between the dorsal and anal fin, and distance between the pectoral and the pelvic fins. Strong negative loadings were associated with head measurements. Omul of the same morphotype captured at different locations were classified to location of capture using step-wise discriminant function analysis. Jackknife correct classifications ranged from 43 to 78% for littoral omul from five locations, and 45–86% for pelagic omul from four locations. Patterns of location misclassification of littoral omul suggested that the sub-population structure, hence stock affinity, may be influenced by movements and intermixing of individuals among areas that are joined bathymetrically. Pelagic omul were more distinguishable by site and may support a previous hypothesis of a spawning-based rather than a foraging-based sub-population structure. Omul morphotypes may reflect adaptations to both ecological and local environmental conditions, and may have a genetic basis.

MultiP-Apo: A Multilabel Predictor for Identifying Subcellular Locations of Apoptosis Proteins.

PubMed

Wang, Xiao; Li, Hui; Wang, Rong; Zhang, Qiuwen; Zhang, Weiwei; Gan, Yong

2017-01-01

Apoptosis proteins play an important role in the mechanism of programmed cell death. Predicting subcellular localization of apoptosis proteins is an essential step to understand their functions and identify drugs target. Many computational prediction methods have been developed for apoptosis protein subcellular localization. However, these existing works only focus on the proteins that have one location; proteins with multiple locations are either not considered or assumed as not existing when constructing prediction models, so that they cannot completely predict all the locations of the apoptosis proteins with multiple locations. To address this problem, this paper proposes a novel multilabel predictor named MultiP-Apo, which can predict not only apoptosis proteins with single subcellular location but also those with multiple subcellular locations. Specifically, given a query protein, GO-based feature extraction method is used to extract its feature vector. Subsequently, the GO feature vector is classified by a new multilabel classifier based on the label-specific features. It is the first multilabel predictor ever established for identifying subcellular locations of multilocation apoptosis proteins. As an initial study, MultiP-Apo achieves an overall accuracy of 58.49% by jackknife test, which indicates that our proposed predictor may become a very useful high-throughput tool in this area.

Detection of the pairwise kinematic Sunyaev-Zel'dovich effect with BOSS DR11 and the Atacama Cosmology Telescope

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bernardis, F. De; Aiola, S.; Vavagiakis, E. M.

Here, we present a new measurement of the kinematic Sunyaev-Zel'dovich effect using data from the Atacama Cosmology Telescope (ACT) and the Baryon Oscillation Spectroscopic Survey (BOSS). Using 600 square degrees of overlapping sky area, we evaluate the mean pairwise baryon momentum associated with the positions of 50,000 bright galaxies in the BOSS DR11 Large Scale Structure catalog. A non-zero signal arises from the large-scale motions of halos containing the sample galaxies. The data fits an analytical signal model well, with the optical depth to microwave photon scattering as a free parameter determining the overall signal amplitude. We estimate the covariancemore » matrix of the mean pairwise momentum as a function of galaxy separation, using microwave sky simulations, jackknife evaluation, and bootstrap estimates. The most conservative simulation-based errors give signal-to-noise estimates between 3.6 and 4.1 for varying galaxy luminosity cuts. We discuss how the other error determinations can lead to higher signal-to-noise values, and consider the impact of several possible systematic errors. Estimates of the optical depth from the average thermal Sunyaev-Zel'dovich signal at the sample galaxy positions are broadly consistent with those obtained from the mean pairwise momentum signal.« less

Detection of the pairwise kinematic Sunyaev-Zel'dovich effect with BOSS DR11 and the Atacama Cosmology Telescope

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bernardis, F. De; Vavagiakis, E.M.; Niemack, M.D.

We present a new measurement of the kinematic Sunyaev-Zel'dovich effect using data from the Atacama Cosmology Telescope (ACT) and the Baryon Oscillation Spectroscopic Survey (BOSS). Using 600 square degrees of overlapping sky area, we evaluate the mean pairwise baryon momentum associated with the positions of 50,000 bright galaxies in the BOSS DR11 Large Scale Structure catalog. A non-zero signal arises from the large-scale motions of halos containing the sample galaxies. The data fits an analytical signal model well, with the optical depth to microwave photon scattering as a free parameter determining the overall signal amplitude. We estimate the covariance matrixmore » of the mean pairwise momentum as a function of galaxy separation, using microwave sky simulations, jackknife evaluation, and bootstrap estimates. The most conservative simulation-based errors give signal-to-noise estimates between 3.6 and 4.1 for varying galaxy luminosity cuts. We discuss how the other error determinations can lead to higher signal-to-noise values, and consider the impact of several possible systematic errors. Estimates of the optical depth from the average thermal Sunyaev-Zel'dovich signal at the sample galaxy positions are broadly consistent with those obtained from the mean pairwise momentum signal.« less

Detection of the Pairwise Kinematic Sunyaev-Zel'dovich Effect with BOSS DR11 and the Atacama Cosmology Telescope

NASA Technical Reports Server (NTRS)

De Bernardis, F.; Aiola, S.; Vavagiakis, E. M.; Battaglia, N.; Niemack, M. D.; Beall, J.; Becker, D. T.; Bond, J. R.; Calabrese, E.; Cho, H.;

Protein location prediction using atomic composition and global features of the amino acid sequence

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cherian, Betsy Sheena, E-mail: betsy.skb@gmail.com; Nair, Achuthsankar S.

2010-01-22

Subcellular location of protein is constructive information in determining its function, screening for drug candidates, vaccine design, annotation of gene products and in selecting relevant proteins for further studies. Computational prediction of subcellular localization deals with predicting the location of a protein from its amino acid sequence. For a computational localization prediction method to be more accurate, it should exploit all possible relevant biological features that contribute to the subcellular localization. In this work, we extracted the biological features from the full length protein sequence to incorporate more biological information. A new biological feature, distribution of atomic composition is effectivelymore » used with, multiple physiochemical properties, amino acid composition, three part amino acid composition, and sequence similarity for predicting the subcellular location of the protein. Support Vector Machines are designed for four modules and prediction is made by a weighted voting system. Our system makes prediction with an accuracy of 100, 82.47, 88.81 for self-consistency test, jackknife test and independent data test respectively. Our results provide evidence that the prediction based on the biological features derived from the full length amino acid sequence gives better accuracy than those derived from N-terminal alone. Considering the features as a distribution within the entire sequence will bring out underlying property distribution to a greater detail to enhance the prediction accuracy.« less

Computing camera heading: A study

NASA Astrophysics Data System (ADS)

Zhang, John Jiaxiang

2000-08-01

An accurate estimate of the motion of a camera is a crucial first step for the 3D reconstruction of sites, objects, and buildings from video. Solutions to the camera heading problem can be readily applied to many areas, such as robotic navigation, surgical operation, video special effects, multimedia, and lately even in internet commerce. From image sequences of a real world scene, the problem is to calculate the directions of the camera translations. The presence of rotations makes this problem very hard. This is because rotations and translations can have similar effects on the images, and are thus hard to tell apart. However, the visual angles between the projection rays of point pairs are unaffected by rotations, and their changes over time contain sufficient information to determine the direction of camera translation. We developed a new formulation of the visual angle disparity approach, first introduced by Tomasi, to the camera heading problem. Our new derivation makes theoretical analysis possible. Most notably, a theorem is obtained that locates all possible singularities of the residual function for the underlying optimization problem. This allows identifying all computation trouble spots beforehand, and to design reliable and accurate computational optimization methods. A bootstrap-jackknife resampling method simultaneously reduces complexity and tolerates outliers well. Experiments with image sequences show accurate results when compared with the true camera motion as measured with mechanical devices.

Comparing two correlated C indices with right-censored survival outcome: a one-shot nonparametric approach

PubMed Central

Kang, Le; Chen, Weijie; Petrick, Nicholas A.; Gallas, Brandon D.

2014-01-01

The area under the receiver operating characteristic (ROC) curve (AUC) is often used as a summary index of the diagnostic ability in evaluating biomarkers when the clinical outcome (truth) is binary. When the clinical outcome is right-censored survival time, the C index, motivated as an extension of AUC, has been proposed by Harrell as a measure of concordance between a predictive biomarker and the right-censored survival outcome. In this work, we investigate methods for statistical comparison of two diagnostic or predictive systems, of which they could either be two biomarkers or two fixed algorithms, in terms of their C indices. We adopt a U-statistics based C estimator that is asymptotically normal and develop a nonparametric analytical approach to estimate the variance of the C estimator and the covariance of two C estimators. A z-score test is then constructed to compare the two C indices. We validate our one-shot nonparametric method via simulation studies in terms of the type I error rate and power. We also compare our one-shot method with resampling methods including the jackknife and the bootstrap. Simulation results show that the proposed one-shot method provides almost unbiased variance estimations and has satisfactory type I error control and power. Finally, we illustrate the use of the proposed method with an example from the Framingham Heart Study. PMID:25399736

Galaxy-galaxy lensing in the Dark Energy Survey Science Verification data

DOE PAGES

Clampitt, J.; S?nchez, C.; Kwan, J.; ...

2016-11-22

We present galaxy-galaxy lensing results from 139 square degrees of Dark Energy Survey (DES) Science Verification (SV) data. Our lens sample consists of red galaxies, known as redMaGiC, which are specifically selected to have a low photometric redshift error and outlier rate. The lensing measurement has a total signal-to-noise of 29 over scales $0.09 < R < 15$ Mpc/$h$, including all lenses over a wide redshift range $0.2 < z < 0.8$. Dividing the lenses into three redshift bins for this constant moving number density sample, we find no evidence for evolution in the halo mass with redshift. We obtainmore » consistent results for the lensing measurement with two independent shear pipelines, ngmix and im3shape. We perform a number of null tests on the shear and photometric redshift catalogs and quantify resulting systematic uncertainties. Covariances from jackknife subsamples of the data are validated with a suite of 50 mock surveys. The results and systematics checks in this work provide a critical input for future cosmological and galaxy evolution studies with the DES data and redMaGiC galaxy samples. We fit a Halo Occupation Distribution (HOD) model, and demonstrate that our data constrains the mean halo mass of the lens galaxies, despite strong degeneracies between individual HOD parameters.« less

Cosmic shear measurements with Dark Energy Survey Science Verification data

DOE PAGES

Becker, M. R.

2016-07-06

Here, we present measurements of weak gravitational lensing cosmic shear two-point statistics using Dark Energy Survey Science Verification data. We demonstrate that our results are robust to the choice of shear measurement pipeline, either ngmix or im3shape, and robust to the choice of two-point statistic, including both real and Fourier-space statistics. Our results pass a suite of null tests including tests for B-mode contamination and direct tests for any dependence of the two-point functions on a set of 16 observing conditions and galaxy properties, such as seeing, airmass, galaxy color, galaxy magnitude, etc. We use a large suite of simulationsmore » to compute the covariance matrix of the cosmic shear measurements and assign statistical significance to our null tests. We find that our covariance matrix is consistent with the halo model prediction, indicating that it has the appropriate level of halo sample variance. We also compare the same jackknife procedure applied to the data and the simulations in order to search for additional sources of noise not captured by the simulations. We find no statistically significant extra sources of noise in the data. The overall detection significance with tomography for our highest source density catalog is 9.7σ. Cosmological constraints from the measurements in this work are presented in a companion paper.« less

Using Chou's pseudo amino acid composition based on approximate entropy and an ensemble of AdaBoost classifiers to predict protein subnuclear location.

PubMed

Jiang, Xiaoying; Wei, Rong; Zhao, Yanjun; Zhang, Tongliang

2008-05-01

The knowledge of subnuclear localization in eukaryotic cells is essential for understanding the life function of nucleus. Developing prediction methods and tools for proteins subnuclear localization become important research fields in protein science for special characteristics in cell nuclear. In this study, a novel approach has been proposed to predict protein subnuclear localization. Sample of protein is represented by Pseudo Amino Acid (PseAA) composition based on approximate entropy (ApEn) concept, which reflects the complexity of time series. A novel ensemble classifier is designed incorporating three AdaBoost classifiers. The base classifier algorithms in three AdaBoost are decision stumps, fuzzy K nearest neighbors classifier, and radial basis-support vector machines, respectively. Different PseAA compositions are used as input data of different AdaBoost classifier in ensemble. Genetic algorithm is used to optimize the dimension and weight factor of PseAA composition. Two datasets often used in published works are used to validate the performance of the proposed approach. The obtained results of Jackknife cross-validation test are higher and more balance than them of other methods on same datasets. The promising results indicate that the proposed approach is effective and practical. It might become a useful tool in protein subnuclear localization. The software in Matlab and supplementary materials are available freely by contacting the corresponding author.

Predicting structural classes of proteins by incorporating their global and local physicochemical and conformational properties into general Chou's PseAAC.

PubMed

Contreras-Torres, Ernesto

2018-06-02

In this study, I introduce novel global and local 0D-protein descriptors based on a statistical quantity named Total Sum of Squares (TSS). This quantity represents the sum of the squares differences of amino acid properties from the arithmetic mean property. As an extension, the amino acid-types and amino acid-groups formalisms are used for describing zones of interest in proteins. To assess the effectiveness of the proposed descriptors, a Nearest Neighbor model for predicting the major four protein structural classes was built. This model has a success rate of 98.53% on the jackknife cross-validation test; this performance being superior to other reported methods despite the simplicity of the predictor. Additionally, this predictor has an average success rate of 98.35% in different cross-validation tests performed. A value of 0.98 for the Kappa statistic clearly discriminates this model from a random predictor. The results obtained by the Nearest Neighbor model demonstrated the ability of the proposed descriptors not only to reflect relevant biochemical information related to the structural classes of proteins but also to allow appropriate interpretability. It can thus be expected that the current method may play a supplementary role to other existing approaches for protein structural class prediction and other protein attributes. Copyright © 2018 Elsevier Ltd. All rights reserved.

Full Moment Tensor Analysis Using First Motion Data at The Geysers Geothermal Field

NASA Astrophysics Data System (ADS)

Boyd, O.; Dreger, D. S.; Lai, V. H.; Gritto, R.

2012-12-01

Seismicity associated with geothermal energy production at The Geysers Geothermal Field in northern California has been increasing during the last forty years. We investigate source models of over fifty earthquakes with magnitudes ranging from Mw 3.5 up to Mw 4.5. We invert three-component, complete waveform data from broadband stations of the Berkeley Digital Seismic Network, the Northern California Seismic Network and the USA Array deployment (2005-2007) for the complete, six-element moment tensor. Some solutions are double-couple while others have substantial non-double-couple components. To assess the stability and significance of non-double-couple components, we use a suite of diagnostic tools including the F-test, Jackknife test, bootstrap and network sensitivity solution (NSS). The full moment tensor solutions of the studied events tend to plot in the upper half of the Hudson source type diagram where the fundamental source types include +CLVD, +LVD, tensile-crack, DC and explosion. Using the F-test to compare the goodness-of-fit values between the full and deviatoric moment tensor solutions, most of the full moment tensor solutions do not show a statistically significant improvement in fit over the deviatoric solutions. Because a small isotropic component may not significantly improve the fit, we include first motion polarity data to better constrain the full moment tensor solutions.

Identification of DNA-binding proteins by combining auto-cross covariance transformation and ensemble learning.

PubMed

Liu, Bin; Wang, Shanyi; Dong, Qiwen; Li, Shumin; Liu, Xuan

2016-04-20

DNA-binding proteins play a pivotal role in various intra- and extra-cellular activities ranging from DNA replication to gene expression control. With the rapid development of next generation of sequencing technique, the number of protein sequences is unprecedentedly increasing. Thus it is necessary to develop computational methods to identify the DNA-binding proteins only based on the protein sequence information. In this study, a novel method called iDNA-KACC is presented, which combines the Support Vector Machine (SVM) and the auto-cross covariance transformation. The protein sequences are first converted into profile-based protein representation, and then converted into a series of fixed-length vectors by the auto-cross covariance transformation with Kmer composition. The sequence order effect can be effectively captured by this scheme. These vectors are then fed into Support Vector Machine (SVM) to discriminate the DNA-binding proteins from the non DNA-binding ones. iDNA-KACC achieves an overall accuracy of 75.16% and Matthew correlation coefficient of 0.5 by a rigorous jackknife test. Its performance is further improved by employing an ensemble learning approach, and the improved predictor is called iDNA-KACC-EL. Experimental results on an independent dataset shows that iDNA-KACC-EL outperforms all the other state-of-the-art predictors, indicating that it would be a useful computational tool for DNA binding protein identification. .

Analysis and prediction of presynaptic and postsynaptic neurotoxins by Chou's general pseudo amino acid composition and motif features.

PubMed

Mei, Juan; Zhao, Ji

2018-06-14

Presynaptic neurotoxins and postsynaptic neurotoxins are two important neurotoxins isolated from venoms of venomous animals and have been proven to be potential effective in neurosciences and pharmacology. With the number of toxin sequences appeared in the public databases, there was a need for developing a computational method for fast and accurate identification and classification of the novel presynaptic neurotoxins and postsynaptic neurotoxins in the large databases. In this study, the Multinomial Naive Bayes Classifier (MNBC) had been developed to discriminate the presynaptic neurotoxins and postsynaptic neurotoxins based on the different kinds of features. The Minimum Redundancy Maximum Relevance (MRMR) feature selection method was used for ranking 400 pseudo amino acid (PseAA) compositions and 50 top ranked PseAA compositions were selected for improving the prediction results. The motif features, 400 PseAA compositions and 50 PseAA compositions were combined together, and selected as the input parameters of MNBC. The best correlation coefficient (CC) value of 0.8213 was obtained when the prediction quality was evaluated by the jackknife test. It was anticipated that the algorithm presented in this study may become a useful tool for identification of presynaptic neurotoxin and postsynaptic neurotoxin sequences and may provide some useful help for in-depth investigation into the biological mechanism of presynaptic neurotoxins and postsynaptic neurotoxins. Copyright © 2018 Elsevier Ltd. All rights reserved.

Prediction of small molecule binding property of protein domains with Bayesian classifiers based on Markov chains.

PubMed

Bulashevska, Alla; Stein, Martin; Jackson, David; Eils, Roland

2009-12-01

Accurate computational methods that can help to predict biological function of a protein from its sequence are of great interest to research biologists and pharmaceutical companies. One approach to assume the function of proteins is to predict the interactions between proteins and other molecules. In this work, we propose a machine learning method that uses a primary sequence of a domain to predict its propensity for interaction with small molecules. By curating the Pfam database with respect to the small molecule binding ability of its component domains, we have constructed a dataset of small molecule binding and non-binding domains. This dataset was then used as training set to learn a Bayesian classifier, which should distinguish members of each class. The domain sequences of both classes are modelled with Markov chains. In a Jack-knife test, our classification procedure achieved the predictive accuracies of 77.2% and 66.7% for binding and non-binding classes respectively. We demonstrate the applicability of our classifier by using it to identify previously unknown small molecule binding domains. Our predictions are available as supplementary material and can provide very useful information to drug discovery specialists. Given the ubiquitous and essential role small molecules play in biological processes, our method is important for identifying pharmaceutically relevant components of complete proteomes. The software is available from the author upon request.

Perturbative approach to covariance matrix of the matter power spectrum

NASA Astrophysics Data System (ADS)

Mohammed, Irshad; Seljak, Uroš; Vlah, Zvonimir

2017-04-01

We evaluate the covariance matrix of the matter power spectrum using perturbation theory up to dominant terms at 1-loop order and compare it to numerical simulations. We decompose the covariance matrix into the disconnected (Gaussian) part, trispectrum from the modes outside the survey (supersample variance) and trispectrum from the modes inside the survey, and show how the different components contribute to the overall covariance matrix. We find the agreement with the simulations is at a 10 per cent level up to k ˜ 1 h Mpc-1. We show that all the connected components are dominated by the large-scale modes (k < 0.1 h Mpc-1), regardless of the value of the wave vectors k, k΄ of the covariance matrix, suggesting that one must be careful in applying the jackknife or bootstrap methods to the covariance matrix. We perform an eigenmode decomposition of the connected part of the covariance matrix, showing that at higher k, it is dominated by a single eigenmode. The full covariance matrix can be approximated as the disconnected part only, with the connected part being treated as an external nuisance parameter with a known scale dependence, and a known prior on its variance for a given survey volume. Finally, we provide a prescription for how to evaluate the covariance matrix from small box simulations without the need to simulate large volumes.

Identifying 5-methylcytosine sites in RNA sequence using composite encoding feature into Chou's PseKNC.

PubMed

Sabooh, M Fazli; Iqbal, Nadeem; Khan, Mukhtaj; Khan, Muslim; Maqbool, H F

2018-05-01

This study examines accurate and efficient computational method for identification of 5-methylcytosine sites in RNA modification. The occurrence of 5-methylcytosine (m 5 C) plays a vital role in a number of biological processes. For better comprehension of the biological functions and mechanism it is necessary to recognize m 5 C sites in RNA precisely. The laboratory techniques and procedures are available to identify m 5 C sites in RNA, but these procedures require a lot of time and resources. This study develops a new computational method for extracting the features of RNA sequence. In this method, first the RNA sequence is encoded via composite feature vector, then, for the selection of discriminate features, the minimum-redundancy-maximum-relevance algorithm was used. Secondly, the classification method used has been based on a support vector machine by using jackknife cross validation test. The suggested method efficiently identifies m 5 C sites from non- m 5 C sites and the outcome of the suggested algorithm is 93.33% with sensitivity of 90.0 and specificity of 96.66 on bench mark datasets. The result exhibits that proposed algorithm shown significant identification performance compared to the existing computational techniques. This study extends the knowledge about the occurrence sites of RNA modification which paves the way for better comprehension of the biological uses and mechanism. Copyright © 2018 Elsevier Ltd. All rights reserved.

Prediction of Body Fluids where Proteins are Secreted into Based on Protein Interaction Network

PubMed Central

Hu, Le-Le; Huang, Tao; Cai, Yu-Dong; Chou, Kuo-Chen

2011-01-01

Determining the body fluids where secreted proteins can be secreted into is important for protein function annotation and disease biomarker discovery. In this study, we developed a network-based method to predict which kind of body fluids human proteins can be secreted into. For a newly constructed benchmark dataset that consists of 529 human-secreted proteins, the prediction accuracy for the most possible body fluid location predicted by our method via the jackknife test was 79.02%, significantly higher than the success rate by a random guess (29.36%). The likelihood that the predicted body fluids of the first four orders contain all the true body fluids where the proteins can be secreted into is 62.94%. Our method was further demonstrated with two independent datasets: one contains 57 proteins that can be secreted into blood; while the other contains 61 proteins that can be secreted into plasma/serum and were possible biomarkers associated with various cancers. For the 57 proteins in first dataset, 55 were correctly predicted as blood-secrete proteins. For the 61 proteins in the second dataset, 58 were predicted to be most possible in plasma/serum. These encouraging results indicate that the network-based prediction method is quite promising. It is anticipated that the method will benefit the relevant areas for both basic research and drug development. PMID:21829572

Increased binding of 5-HT1A receptors in a dissociative amnesic patient after the recovery process.

PubMed

Kitamura, Soichiro; Yasuno, Fumihiko; Inoue, Makoto; Kosaka, Jun; Kiuchi, Kuniaki; Matsuoka, Kiwamu; Kishimoto, Toshifumi; Suhara, Tetsuya

2014-10-30

Dissociative amnesia is characterized by an inability to retrieve information already saved in memories. 5-HT has some role in neural regulatory control and may be related to the recovery from dissociative amnesia. To examine the role of 5-HT1A receptors in the recovery from dissociative amnesia, we performed two positron emission tomography (PET) scans on a 30-year-old patient of dissociative amnesia using [(11)C]WAY-100635, the first at amnesic state, and the second at the time he had recovered. Exploratory voxel-based analysis (VBA) was performed using SPM software. 5-HT1A BPND images were compared between the patient at amnesic and recovery states and healthy subjects (14 males, mean age 29.8 ± 6.45) with Jack-knife analysis. 5-HT1A receptor bindings of the patient at the recovery state were significantly higher than those of healthy subjects in the right superior and middle frontal cortex, left inferior frontal and orbitofrontal cortex and bilateral inferior temporal cortex. The increase in BPND values of recovery state was beyond 10% of those of amnesia state in these regions except in the right superior frontal cortex. We considered that neural regulatory control by the increase of 5-HT1A receptors in cortical regions played a role in the recovery from dissociative amnesia. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Phylogeny of the Asparagales based on three plastid and two mitochondrial genes.

PubMed

Seberg, Ole; Petersen, Gitte; Davis, Jerrold I; Pires, J Chris; Stevenson, Dennis W; Chase, Mark W; Fay, Michael F; Devey, Dion S; Jørgensen, Tina; Sytsma, Kenneth J; Pillon, Yohan

2012-05-01

The Asparagales, with ca. 40% of all monocotyledons, include a host of commercially important ornamentals in families such as Orchidaceae, Alliaceae, and Iridaceae, and several important crop species in genera such as Allium, Aloe, Asparagus, Crocus, and Vanilla. Though the order is well defined, the number of recognized families, their circumscription, and relationships are somewhat controversial. Phylogenetic analyses of Asparagales were based on parsimony and maximum likelihood using nucleotide sequence variation in three plastid genes (matK, ndhF, and rbcL) and two mitochondrial genes (atp1 and cob). Branch support was assessed using both jackknife analysis implementing strict-consensus (SC) and bootstrap analysis implementing frequency-within-replicates (FWR). The contribution of edited sites in the mitochondrial genes to topology and branch support was investigated. The topologies recovered largely agree with previous results, though some clades remain poorly resolved (e.g., Ruscaceae). When the edited sites were included in the analysis, the plastid and mitochondrial genes were highly incongruent. However, when the edited sites were removed, the two partitions became congruent. Some deeper nodes in the Asparagales tree remain poorly resolved or unresolved as do the relationships of certain monogeneric families (e.g., Aphyllanthaceae, Ixioliriaceae, Doryanthaceae), whereas support for many families increases. However, the increased support is dominated by plastid data, and the potential influence of mitochondrial and biparentially inherited single or low-copy nuclear genes should be investigated.

Trophic ecology of largemouth bass and northern pike in allopatric and sympatric assemblages in northern boreal lakes

USGS Publications Warehouse

Soupir, Craig A.; Brown, Michael L.; Kallemeyn, Larry W.

2000-01-01

Largemouth bass (Micropterus salmoides) and northern pike (Esox lucius) are top predators in the food chain in most aquatic environments that they occupy; however, limited information exists on species interactions in the northern reaches of largemouth bass distribution. We investigated the seasonal food habits of allopatric and sympatric assemblages of largemouth bass and northern pike in six interior lakes within Voyageurs National Park, Minnesota. Percentages of empty stomachs were variable for largemouth bass (38-54%) and northern pike (34.7-66.7%). Fishes (mainly yellow perch, Perca flavescens) comprised greater than 60% (mean percent mass, MPM) of the northern pike diet during all seasons in both allopatric and sympatric assemblages. Aquatic insects (primarily Odonata and Hemiptera) were important in the diets of largemouth bass in all communities (0.0-79.7 MPM). Although largemouth bass were observed in the diet of northern pike, largemouth bass apparently did not prey on northern pike. Seasonal differences were observed in the proportion of aquatic insects (P = 0.010) and fishes (P = 0.023) in the diets of northern pike and largemouth bass. Based on three food categories, jackknifed classifications correctly classified 77 and 92% of northern pike and largemouth bass values, respectively. Percent resource overlap values were biologically significant (greater than 60%) during at least one season in each sympatric assemblage, suggesting some diet overlap.

Gastrointestinal Parasites of Ecuadorian Mantled Howler Monkeys (Alouatta palliata aequatorialis) Based on Fecal Analysis.

PubMed

Helenbrook, William D; Wade, Susan E; Shields, William M; Stehman, Stephen V; Whipps, Christopher M

2015-06-01

An analysis of gastrointestinal parasites of Ecuadorian mantled howler monkeys, Alouatta palliata aequatorialis, was conducted based on examination of fecal smears, flotations, and sedimentations. At least 1 type of parasite was detected in 97% of the 96 fecal samples screened across 19 howler monkey groups using these techniques. Samples averaged 3.6 parasite species per individual (±1.4 SD). Parasites included species representing genera of 2 apicomplexans: Cyclospora sp. (18% of individual samples) and Isospora sp. (3%); 6 other protozoa: Balantidium sp. (9%), Blastocystis sp. (60%), Chilomastix sp. (4%), Dientamoeba sp. (3%), Entamoeba species (56%), Iodamoeba sp. (5%); 4 nematodes: Enterobius sp. (3%), Capillaria sp. (78%), Strongyloides spp. (88%) which included 2 morphotypes, Trypanoxyuris sp. (12%); and the platyhelminth Controrchis sp. (15%). A statistically significant positive correlation was found between group size and each of 3 different estimators of parasite species richness adjusted for sampling effort (ICE: r(2) = 0.24, P = 0.05; Chao2: r(2) = 0.25, P = 0.05, and Jackknife: r(2) = 0.31, P = 0.03). Two significant associations between co-infecting parasites were identified. Based on the prevalence data, individuals infected with Balantidium sp. were more likely to also be infected with Isospora sp. (χ(2) = 6.02, P = 0.01), while individuals harboring Chilomastix sp. were less likely to have Capillaria sp. present (χ(2) = 4.03, P = 0.04).

Classification of protein quaternary structure by functional domain composition

PubMed Central

Yu, Xiaojing; Wang, Chuan; Li, Yixue

2006-01-01

Background The number and the arrangement of subunits that form a protein are referred to as quaternary structure. Quaternary structure is an important protein attribute that is closely related to its function. Proteins with quaternary structure are called oligomeric proteins. Oligomeric proteins are involved in various biological processes, such as metabolism, signal transduction, and chromosome replication. Thus, it is highly desirable to develop some computational methods to automatically classify the quaternary structure of proteins from their sequences. Results To explore this problem, we adopted an approach based on the functional domain composition of proteins. Every protein was represented by a vector calculated from the domains in the PFAM database. The nearest neighbor algorithm (NNA) was used for classifying the quaternary structure of proteins from this information. The jackknife cross-validation test was performed on the non-redundant protein dataset in which the sequence identity was less than 25%. The overall success rate obtained is 75.17%. Additionally, to demonstrate the effectiveness of this method, we predicted the proteins in an independent dataset and achieved an overall success rate of 84.11% Conclusion Compared with the amino acid composition method and Blast, the results indicate that the domain composition approach may be a more effective and promising high-throughput method in dealing with this complicated problem in bioinformatics. PMID:16584572

Evaluation of the potential of Raman microspectroscopy for prediction of chemotherapeutic response to cisplatin in lung adenocarcinoma.

PubMed

Nawaz, Haq; Bonnier, Franck; Knief, Peter; Howe, Orla; Lyng, Fiona M; Meade, Aidan D; Byrne, Hugh J

2010-12-01

The study of the interaction of anticancer drugs with mammalian cells in vitro is important to elucidate the mechanisms of action of the drug on its biological targets. In this context, Raman spectroscopy is a potential candidate for high throughput, non-invasive analysis. To explore this potential, the interaction of cis-diamminedichloroplatinum(II) (cisplatin) with a human lung adenocarcinoma cell line (A549) was investigated using Raman microspectroscopy. The results were correlated with parallel measurements from the MTT cytotoxicity assay, which yielded an IC(50) value of 1.2 ± 0.2 µM. To further confirm the spectral results, Raman spectra were also acquired from DNA extracted from A549 cells exposed to cisplatin and from unexposed controls. Partial least squares (PLS) multivariate regression and PLS Jackknifing were employed to highlight spectral regions which varied in a statistically significant manner with exposure to cisplatin and with the resultant changes in cellular physiology measured by the MTT assay. The results demonstrate the potential of the cellular Raman spectrum to non-invasively elucidate spectral changes that have their origin either in the biochemical interaction of external agents with the cell or its physiological response, allowing the prediction of the cellular response and the identification of the origin of the chemotherapeutic response at a molecular level in the cell.

HyspIRI Measurements of Agricultural Systems in California: 2013-2015

NASA Astrophysics Data System (ADS)

Townsend, P. A.; Kruger, E. L.; Singh, A.; Jablonski, A. D.; Kochaver, S.; Serbin, S.

2015-12-01

During 2013-2015, NASA collected high-altitude AVIRIS hyperspectral and MASTER thermal infrared imagery across large swaths of California in support of the HyspIRI planning and prototyping activities. During these campaigns, we made extensive measurements of photosynthetic capacity—Vcmax and Jmax—and their temperature sensitivities across a range of sites, crop types and environmental conditions. Our objectives were to characterize the physiological diversity of agricultural vegetation in California and develop generalizable algorithms to map these physiological parameters across several image acquisitions, regardless of crop type and canopy temperatures. We employed AVIRIS imagery to scale and estimate the vegetation parameters and MASTER surface temperature to provide context, since physiology responds exponentially to leaf temperature. We demonstrate a segmentation approach to disentangling leaf and background soil temperature, and then illustrate our retrievals of Vcmax and Jmax during overflight conditions across a large number of the 2013-2015 HyspIRI acquisitions. Our results show >80% repeatability (R2) across split sample jack-knifing, with RMSEs within 15% of the range of our data. The approach was robust across crop types (e.g., grape, almond, pistachio, avocado, pomegranate, oats, peppers, citrus, date palm, alfalfa, melons, beets) and leaf temperatures. A global imaging spectroscopy system such as HyspIRI will offer unprecedented ability to monitor agricultural crop performance under widely varying surface conditions.

Influence of land use and meteorological factors on the spatial distribution of Toxocara canis and Toxocara cati eggs in soil in urban areas.

PubMed

Gao, Xiang; Wang, Hongbin; Li, Jianxin; Qin, Hongyu; Xiao, Jianhua

2017-01-15

Soil which has been contaminated by Toxocara spp. eggs is considered as one of the main infection sources of Toxocariasis in animals and humans. The present study conducted a detailed investigation into the spatial patterns of Toxocara canis (T. canis) and Toxocara cati (T. cati) eggs in soil in urban area of northeastern Mainland China, and assessed the inter-relationships between meteorological factors, land use and the distribution of the Toxocara spp. eggs. Polymerase chain reaction (PCR) was used for the determination of T. canis and T. cati eggs contamination in soil samples. Between April 2014 and May 2015, 9420 soil samples were subjected to PCR examination and 7027 sheep (74.6%) were determined to be positive for T. canis and T. cati eggs. Subsequently, we evaluated the effect of land use, and meteorological factors on the spatial distribution of T. canis and T. cati eggs based on a maximum entropy model. Jackknife analysis revealed that the area of residential land, wood and grass land and precipitation may influence the occurrence of T. canis and T. cati eggs in soil. Our findings indicate that land use and meteorological factors may be important variables affecting transmission of Toxocariasis and should be taken into account in the development of future surveillance programmes for Toxocariasis. Copyright © 2016 Elsevier B.V. All rights reserved.

Limited sampling strategy models for estimating the AUC of gliclazide in Chinese healthy volunteers.

PubMed

Huang, Ji-Han; Wang, Kun; Huang, Xiao-Hui; He, Ying-Chun; Li, Lu-Jin; Sheng, Yu-Cheng; Yang, Juan; Zheng, Qing-Shan

2013-06-01

The aim of this work is to reduce the cost of required sampling for the estimation of the area under the gliclazide plasma concentration versus time curve within 60 h (AUC0-60t ). The limited sampling strategy (LSS) models were established and validated by the multiple regression model within 4 or fewer gliclazide concentration values. Absolute prediction error (APE), root of mean square error (RMSE) and visual prediction check were used as criterion. The results of Jack-Knife validation showed that 10 (25.0 %) of the 40 LSS based on the regression analysis were not within an APE of 15 % using one concentration-time point. 90.2, 91.5 and 92.4 % of the 40 LSS models were capable of prediction using 2, 3 and 4 points, respectively. Limited sampling strategies were developed and validated for estimating AUC0-60t of gliclazide. This study indicates that the implementation of an 80 mg dosage regimen enabled accurate predictions of AUC0-60t by the LSS model. This study shows that 12, 6, 4, 2 h after administration are the key sampling times. The combination of (12, 2 h), (12, 8, 2 h) or (12, 8, 4, 2 h) can be chosen as sampling hours for predicting AUC0-60t in practical application according to requirement.

iHyd-PseCp: Identify hydroxyproline and hydroxylysine in proteins by incorporating sequence-coupled effects into general PseAAC.

PubMed

Qiu, Wang-Ren; Sun, Bi-Qian; Xiao, Xuan; Xu, Zhao-Chun; Chou, Kuo-Chen

2016-07-12

Protein hydroxylation is a posttranslational modification (PTM), in which a CH group in Pro (P) or Lys (K) residue has been converted into a COH group, or a hydroxyl group (-OH) is converted into an organic compound. Closely associated with cellular signaling activities, this type of PTM is also involved in some major diseases, such as stomach cancer and lung cancer. Therefore, from the angles of both basic research and drug development, we are facing a challenging problem: for an uncharacterized protein sequence containing many residues of P or K, which ones can be hydroxylated, and which ones cannot? With the explosive growth of protein sequences in the post-genomic age, the problem has become even more urgent. To address such a problem, we have developed a predictor called iHyd-PseCp by incorporating the sequence-coupled information into the general pseudo amino acid composition (PseAAC) and introducing the "Random Forest" algorithm to operate the calculation. Rigorous jackknife tests indicated that the new predictor remarkably outperformed the existing state-of-the-art prediction method for the same purpose. For the convenience of most experimental scientists, a user-friendly web-server for iHyd-PseCp has been established at http://www.jci-bioinfo.cn/iHyd-PseCp, by which users can easily obtain their desired results without the need to go through the complicated mathematical equations involved.

Galaxy-galaxy lensing in the Dark Energy Survey Science Verification data

NASA Astrophysics Data System (ADS)

Clampitt, J.; Sánchez, C.; Kwan, J.; Krause, E.; MacCrann, N.; Park, Y.; Troxel, M. A.; Jain, B.; Rozo, E.; Rykoff, E. S.; Wechsler, R. H.; Blazek, J.; Bonnett, C.; Crocce, M.; Fang, Y.; Gaztanaga, E.; Gruen, D.; Jarvis, M.; Miquel, R.; Prat, J.; Ross, A. J.; Sheldon, E.; Zuntz, J.; Abbott, T. M. C.; Abdalla, F. B.; Armstrong, R.; Becker, M. R.; Benoit-Lévy, A.; Bernstein, G. M.; Bertin, E.; Brooks, D.; Burke, D. L.; Carnero Rosell, A.; Carrasco Kind, M.; Cunha, C. E.; D'Andrea, C. B.; da Costa, L. N.; Desai, S.; Diehl, H. T.; Dietrich, J. P.; Doel, P.; Estrada, J.; Evrard, A. E.; Fausti Neto, A.; Flaugher, B.; Fosalba, P.; Frieman, J.; Gruendl, R. A.; Honscheid, K.; James, D. J.; Kuehn, K.; Kuropatkin, N.; Lahav, O.; Lima, M.; March, M.; Marshall, J. L.; Martini, P.; Melchior, P.; Mohr, J. J.; Nichol, R. C.; Nord, B.; Plazas, A. A.; Romer, A. K.; Sanchez, E.; Scarpine, V.; Schubnell, M.; Sevilla-Noarbe, I.; Smith, R. C.; Soares-Santos, M.; Sobreira, F.; Suchyta, E.; Swanson, M. E. C.; Tarle, G.; Thomas, D.; Vikram, V.; Walker, A. R.

2017-03-01

We present galaxy-galaxy lensing results from 139 deg2 of Dark Energy Survey (DES) Science Verification (SV) data. Our lens sample consists of red galaxies, known as redMaGiC, which are specifically selected to have a low photometric redshift error and outlier rate. The lensing measurement has a total signal-to-noise ratio of 29 over scales 0.09 < R < 15 Mpc h-1, including all lenses over a wide redshift range 0.2 < z < 0.8. Dividing the lenses into three redshift bins for this constant moving number density sample, we find no evidence for evolution in the halo mass with redshift. We obtain consistent results for the lensing measurement with two independent shear pipelines, NGMIX and IM3SHAPE. We perform a number of null tests on the shear and photometric redshift catalogues and quantify resulting systematic uncertainties. Covariances from jackknife subsamples of the data are validated with a suite of 50 mock surveys. The result and systematic checks in this work provide a critical input for future cosmological and galaxy evolution studies with the DES data and redMaGiC galaxy samples. We fit a halo occupation distribution (HOD) model, and demonstrate that our data constrain the mean halo mass of the lens galaxies, despite strong degeneracies between individual HOD parameters.

Galaxy-galaxy lensing in the Dark Energy Survey Science Verification data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clampitt, J.; S?nchez, C.; Kwan, J.

We present galaxy-galaxy lensing results from 139 square degrees of Dark Energy Survey (DES) Science Verification (SV) data. Our lens sample consists of red galaxies, known as redMaGiC, which are specifically selected to have a low photometric redshift error and outlier rate. The lensing measurement has a total signal-to-noise of 29 over scales $0.09 < R < 15$ Mpc/$h$, including all lenses over a wide redshift range $0.2 < z < 0.8$. Dividing the lenses into three redshift bins for this constant moving number density sample, we find no evidence for evolution in the halo mass with redshift. We obtainmore » consistent results for the lensing measurement with two independent shear pipelines, ngmix and im3shape. We perform a number of null tests on the shear and photometric redshift catalogs and quantify resulting systematic uncertainties. Covariances from jackknife subsamples of the data are validated with a suite of 50 mock surveys. The results and systematics checks in this work provide a critical input for future cosmological and galaxy evolution studies with the DES data and redMaGiC galaxy samples. We fit a Halo Occupation Distribution (HOD) model, and demonstrate that our data constrains the mean halo mass of the lens galaxies, despite strong degeneracies between individual HOD parameters.« less

Activation of CO2-reducing methanogens in oil reservoir after addition of nutrient.

PubMed

Yang, Guang-Chao; Zhou, Lei; Mbadinga, Serge Maurice; You, Jing; Yang, Hua-Zhen; Liu, Jin-Feng; Yang, Shi-Zhong; Gu, Ji-Dong; Mu, Bo-Zhong

2016-12-01

Nutrient addition as part of microbial enhanced oil recovery (MEOR) operations have important implications for more energy recovery from oil reservoirs, but very little is known about the in situ response of microorganisms after intervention. An analysis of two genes as biomarkers, mcrA encoding the key enzyme in methanogenesis and fthfs encoding the key enzyme in acetogenesis, was conducted during nutrient addition in oil reservoir. Clone library data showed that dominant mcrA sequences changed from acetoclastic (Methanosaetaceae) to CO 2 -reducing methanogens (Methanomicrobiales and Methanobacteriales), and the authentic acetogens affiliated to Firmicutes decreased after the intervention. Principal coordinates analysis (PCoA) and Jackknife environment clusters revealed evidence on the shift of the microbial community structure among the samples. Quantitative analysis of methanogens via qPCR showed that Methanobacteriales and Methanomicrobiales increased after nutrient addition, while acetoclastic methanogens (Methanosaetaceae) changed slightly. Nutrient treatment activated native CO 2 -reducing methanogens in oil reservoir. The high frequency of Methanobacteriales and Methanomicrobiales (CO 2 -reducers) after nutrient addition in this petroleum system suggested that CO 2 -reducing methanogenesis was involved in methane production. The nutrient addition could promote the methane production. The results will likely improve strategies of utilizing microorganisms in subsurface environments. Copyright © 2016 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Prostate cancer detection using machine learning techniques by employing combination of features extracting strategies.

PubMed

Hussain, Lal; Ahmed, Adeel; Saeed, Sharjil; Rathore, Saima; Awan, Imtiaz Ahmed; Shah, Saeed Arif; Majid, Abdul; Idris, Adnan; Awan, Anees Ahmed

2018-02-06

Prostate is a second leading causes of cancer deaths among men. Early detection of cancer can effectively reduce the rate of mortality caused by Prostate cancer. Due to high and multiresolution of MRIs from prostate cancer require a proper diagnostic systems and tools. In the past researchers developed Computer aided diagnosis (CAD) systems that help the radiologist to detect the abnormalities. In this research paper, we have employed novel Machine learning techniques such as Bayesian approach, Support vector machine (SVM) kernels: polynomial, radial base function (RBF) and Gaussian and Decision Tree for detecting prostate cancer. Moreover, different features extracting strategies are proposed to improve the detection performance. The features extracting strategies are based on texture, morphological, scale invariant feature transform (SIFT), and elliptic Fourier descriptors (EFDs) features. The performance was evaluated based on single as well as combination of features using Machine Learning Classification techniques. The Cross validation (Jack-knife k-fold) was performed and performance was evaluated in term of receiver operating curve (ROC) and specificity, sensitivity, Positive predictive value (PPV), negative predictive value (NPV), false positive rate (FPR). Based on single features extracting strategies, SVM Gaussian Kernel gives the highest accuracy of 98.34% with AUC of 0.999. While, using combination of features extracting strategies, SVM Gaussian kernel with texture + morphological, and EFDs + morphological features give the highest accuracy of 99.71% and AUC of 1.00.

LOCSVMPSI: a web server for subcellular localization of eukaryotic proteins using SVM and profile of PSI-BLAST

PubMed Central

Xie, Dan; Li, Ao; Wang, Minghui; Fan, Zhewen; Feng, Huanqing

2005-01-01

Subcellular location of a protein is one of the key functional characters as proteins must be localized correctly at the subcellular level to have normal biological function. In this paper, a novel method named LOCSVMPSI has been introduced, which is based on the support vector machine (SVM) and the position-specific scoring matrix generated from profiles of PSI-BLAST. With a jackknife test on the RH2427 data set, LOCSVMPSI achieved a high overall prediction accuracy of 90.2%, which is higher than the prediction results by SubLoc and ESLpred on this data set. In addition, prediction performance of LOCSVMPSI was evaluated with 5-fold cross validation test on the PK7579 data set and the prediction results were consistently better than the previous method based on several SVMs using composition of both amino acids and amino acid pairs. Further test on the SWISSPROT new-unique data set showed that LOCSVMPSI also performed better than some widely used prediction methods, such as PSORTII, TargetP and LOCnet. All these results indicate that LOCSVMPSI is a powerful tool for the prediction of eukaryotic protein subcellular localization. An online web server (current version is 1.3) based on this method has been developed and is freely available to both academic and commercial users, which can be accessed by at . PMID:15980436

Improved detection of DNA-binding proteins via compression technology on PSSM information.

PubMed

Wang, Yubo; Ding, Yijie; Guo, Fei; Wei, Leyi; Tang, Jijun

2017-01-01

Since the importance of DNA-binding proteins in multiple biomolecular functions has been recognized, an increasing number of researchers are attempting to identify DNA-binding proteins. In recent years, the machine learning methods have become more and more compelling in the case of protein sequence data soaring, because of their favorable speed and accuracy. In this paper, we extract three features from the protein sequence, namely NMBAC (Normalized Moreau-Broto Autocorrelation), PSSM-DWT (Position-specific scoring matrix-Discrete Wavelet Transform), and PSSM-DCT (Position-specific scoring matrix-Discrete Cosine Transform). We also employ feature selection algorithm on these feature vectors. Then, these features are fed into the training SVM (support vector machine) model as classifier to predict DNA-binding proteins. Our method applys three datasets, namely PDB1075, PDB594 and PDB186, to evaluate the performance of our approach. The PDB1075 and PDB594 datasets are employed for Jackknife test and the PDB186 dataset is used for the independent test. Our method achieves the best accuracy in the Jacknife test, from 79.20% to 86.23% and 80.5% to 86.20% on PDB1075 and PDB594 datasets, respectively. In the independent test, the accuracy of our method comes to 76.3%. The performance of independent test also shows that our method has a certain ability to be effectively used for DNA-binding protein prediction. The data and source code are at https://doi.org/10.6084/m9.figshare.5104084.

Prediction of protein structural classes by recurrence quantification analysis based on chaos game representation.

PubMed

Yang, Jian-Yi; Peng, Zhen-Ling; Yu, Zu-Guo; Zhang, Rui-Jie; Anh, Vo; Wang, Desheng

2009-04-21

In this paper, we intend to predict protein structural classes (alpha, beta, alpha+beta, or alpha/beta) for low-homology data sets. Two data sets were used widely, 1189 (containing 1092 proteins) and 25PDB (containing 1673 proteins) with sequence homology being 40% and 25%, respectively. We propose to decompose the chaos game representation of proteins into two kinds of time series. Then, a novel and powerful nonlinear analysis technique, recurrence quantification analysis (RQA), is applied to analyze these time series. For a given protein sequence, a total of 16 characteristic parameters can be calculated with RQA, which are treated as feature representation of protein sequences. Based on such feature representation, the structural class for each protein is predicted with Fisher's linear discriminant algorithm. The jackknife test is used to test and compare our method with other existing methods. The overall accuracies with step-by-step procedure are 65.8% and 64.2% for 1189 and 25PDB data sets, respectively. With one-against-others procedure used widely, we compare our method with five other existing methods. Especially, the overall accuracies of our method are 6.3% and 4.1% higher for the two data sets, respectively. Furthermore, only 16 parameters are used in our method, which is less than that used by other methods. This suggests that the current method may play a complementary role to the existing methods and is promising to perform the prediction of protein structural classes.

Cluster mislocation in kinematic Sunyaev-Zel'dovich effect extraction

NASA Astrophysics Data System (ADS)

Calafut, Victoria; Bean, Rachel; Yu, Byeonghee

2017-12-01

We investigate the impact of a variety of analysis assumptions that influence cluster identification and location on the kinematic Sunyaev-Zel'dovich (kSZ) pairwise momentum signal and covariance estimation. Photometric and spectroscopic galaxy tracers from SDSS, WISE, and DECaLs, spanning redshifts 0.05 jackknife (JK) estimator. We also find that JK covariance estimates are significantly more conservative than those obtained by cosmic microwave background (CMB) rotation methods. Using redMaPPer data, we concurrently compare the impact of photometric redshift errors and miscentering. At separations <˜50 Mpc , where the kSZ signal is largest, miscentering uncertainties can be comparable to JK errors, while photometric redshifts are lower but still significant. For the next generation of CMB and large scale structure surveys the statistical and photometric errors will shrink markedly. Our results demonstrate that uncertainties introduced through using galaxy proxies for cluster locations will need to be fully incorporated, and actively mitigated, for the kSZ to reach its full potential as a cosmological constraining tool for dark energy and neutrino physics.

Perturbative approach to covariance matrix of the matter power spectrum

DOE PAGES

Mohammed, Irshad; Seljak, Uros; Vlah, Zvonimir

2016-12-14

Here, we evaluate the covariance matrix of the matter power spectrum using perturbation theory up to dominant terms at 1-loop order and compare it to numerical simulations. We decompose the covariance matrix into the disconnected (Gaussian) part, trispectrum from the modes outside the survey (beat coupling or super-sample variance), and trispectrum from the modes inside the survey, and show how the different components contribute to the overall covariance matrix. We find the agreement with the simulations is at a 10\\% level up tomore » $$k \\sim 1 h {\\rm Mpc^{-1}}$$. We also show that all the connected components are dominated by the large-scale modes ($$k<0.1 h {\\rm Mpc^{-1}}$$), regardless of the value of the wavevectors $$k,\\, k'$$ of the covariance matrix, suggesting that one must be careful in applying the jackknife or bootstrap methods to the covariance matrix. We perform an eigenmode decomposition of the connected part of the covariance matrix, showing that at higher $k$ it is dominated by a single eigenmode. Furthermore, the full covariance matrix can be approximated as the disconnected part only, with the connected part being treated as an external nuisance parameter with a known scale dependence, and a known prior on its variance for a given survey volume. Finally, we provide a prescription for how to evaluate the covariance matrix from small box simulations without the need to simulate large volumes.« less

Predicting discovery rates of genomic features.

PubMed

Gravel, Simon

2014-06-01

Successful sequencing experiments require judicious sample selection. However, this selection must often be performed on the basis of limited preliminary data. Predicting the statistical properties of the final sample based on preliminary data can be challenging, because numerous uncertain model assumptions may be involved. Here, we ask whether we can predict "omics" variation across many samples by sequencing only a fraction of them. In the infinite-genome limit, we find that a pilot study sequencing 5% of a population is sufficient to predict the number of genetic variants in the entire population within 6% of the correct value, using an estimator agnostic to demography, selection, or population structure. To reach similar accuracy in a finite genome with millions of polymorphisms, the pilot study would require ∼15% of the population. We present computationally efficient jackknife and linear programming methods that exhibit substantially less bias than the state of the art when applied to simulated data and subsampled 1000 Genomes Project data. Extrapolating based on the National Heart, Lung, and Blood Institute Exome Sequencing Project data, we predict that 7.2% of sites in the capture region would be variable in a sample of 50,000 African Americans and 8.8% in a European sample of equal size. Finally, we show how the linear programming method can also predict discovery rates of various genomic features, such as the number of transcription factor binding sites across different cell types. Copyright © 2014 by the Genetics Society of America.

Estimation of distribution overlap of urn models.

PubMed

Hampton, Jerrad; Lladser, Manuel E

2012-01-01

A classical problem in statistics is estimating the expected coverage of a sample, which has had applications in gene expression, microbial ecology, optimization, and even numismatics. Here we consider a related extension of this problem to random samples of two discrete distributions. Specifically, we estimate what we call the dissimilarity probability of a sample, i.e., the probability of a draw from one distribution not being observed in [Formula: see text] draws from another distribution. We show our estimator of dissimilarity to be a [Formula: see text]-statistic and a uniformly minimum variance unbiased estimator of dissimilarity over the largest appropriate range of [Formula: see text]. Furthermore, despite the non-Markovian nature of our estimator when applied sequentially over [Formula: see text], we show it converges uniformly in probability to the dissimilarity parameter, and we present criteria when it is approximately normally distributed and admits a consistent jackknife estimator of its variance. As proof of concept, we analyze V35 16S rRNA data to discern between various microbial environments. Other potential applications concern any situation where dissimilarity of two discrete distributions may be of interest. For instance, in SELEX experiments, each urn could represent a random RNA pool and each draw a possible solution to a particular binding site problem over that pool. The dissimilarity of these pools is then related to the probability of finding binding site solutions in one pool that are absent in the other.

Fast and Accurate Construction of Ultra-Dense Consensus Genetic Maps Using Evolution Strategy Optimization

PubMed Central

Mester, David; Ronin, Yefim; Schnable, Patrick; Aluru, Srinivas; Korol, Abraham

2015-01-01

Our aim was to develop a fast and accurate algorithm for constructing consensus genetic maps for chip-based SNP genotyping data with a high proportion of shared markers between mapping populations. Chip-based genotyping of SNP markers allows producing high-density genetic maps with a relatively standardized set of marker loci for different mapping populations. The availability of a standard high-throughput mapping platform simplifies consensus analysis by ignoring unique markers at the stage of consensus mapping thereby reducing mathematical complicity of the problem and in turn analyzing bigger size mapping data using global optimization criteria instead of local ones. Our three-phase analytical scheme includes automatic selection of ~100-300 of the most informative (resolvable by recombination) markers per linkage group, building a stable skeletal marker order for each data set and its verification using jackknife re-sampling, and consensus mapping analysis based on global optimization criterion. A novel Evolution Strategy optimization algorithm with a global optimization criterion presented in this paper is able to generate high quality, ultra-dense consensus maps, with many thousands of markers per genome. This algorithm utilizes "potentially good orders" in the initial solution and in the new mutation procedures that generate trial solutions, enabling to obtain a consensus order in reasonable time. The developed algorithm, tested on a wide range of simulated data and real world data (Arabidopsis), outperformed two tested state-of-the-art algorithms by mapping accuracy and computation time. PMID:25867943

Determination of biodiesel content in biodiesel/diesel blends using NIR and visible spectroscopy with variable selection.

PubMed

Fernandes, David Douglas Sousa; Gomes, Adriano A; Costa, Gean Bezerra da; Silva, Gildo William B da; Véras, Germano

2011-12-15

This work is concerned of evaluate the use of visible and near-infrared (NIR) range, separately and combined, to determine the biodiesel content in biodiesel/diesel blends using Multiple Linear Regression (MLR) and variable selection by Successive Projections Algorithm (SPA). Full spectrum models employing Partial Least Squares (PLS) and variables selection by Stepwise (SW) regression coupled with Multiple Linear Regression (MLR) and PLS models also with variable selection by Jack-Knife (Jk) were compared the proposed methodology. Several preprocessing were evaluated, being chosen derivative Savitzky-Golay with second-order polynomial and 17-point window for NIR and visible-NIR range, with offset correction. A total of 100 blends with biodiesel content between 5 and 50% (v/v) prepared starting from ten sample of biodiesel. In the NIR and visible region the best model was the SPA-MLR using only two and eight wavelengths with RMSEP of 0.6439% (v/v) and 0.5741 respectively, while in the visible-NIR region the best model was the SW-MLR using five wavelengths and RMSEP of 0.9533% (v/v). Results indicate that both spectral ranges evaluated showed potential for developing a rapid and nondestructive method to quantify biodiesel in blends with mineral diesel. Finally, one can still mention that the improvement in terms of prediction error obtained with the procedure for variables selection was significant. Copyright © 2011 Elsevier B.V. All rights reserved.

Image processing can cause some malignant soft-tissue lesions to be missed in digital mammography images.

PubMed

Warren, L M; Halling-Brown, M D; Looney, P T; Dance, D R; Wallis, M G; Given-Wilson, R M; Wilkinson, L; McAvinchey, R; Young, K C

2017-09-01

To investigate the effect of image processing on cancer detection in mammography. An observer study was performed using 349 digital mammography images of women with normal breasts, calcification clusters, or soft-tissue lesions including 191 subtle cancers. Images underwent two types of processing: FlavourA (standard) and FlavourB (added enhancement). Six observers located features in the breast they suspected to be cancerous (4,188 observations). Data were analysed using jackknife alternative free-response receiver operating characteristic (JAFROC) analysis. Characteristics of the cancers detected with each image processing type were investigated. For calcifications, the JAFROC figure of merit (FOM) was equal to 0.86 for both types of image processing. For soft-tissue lesions, the JAFROC FOM were better for FlavourA (0.81) than FlavourB (0.78); this difference was significant (p=0.001). Using FlavourA a greater number of cancers of all grades and sizes were detected than with FlavourB. FlavourA improved soft-tissue lesion detection in denser breasts (p=0.04 when volumetric density was over 7.5%) CONCLUSIONS: The detection of malignant soft-tissue lesions (which were primarily invasive) was significantly better with FlavourA than FlavourB image processing. This is despite FlavourB having a higher contrast appearance often preferred by radiologists. It is important that clinical choice of image processing is based on objective measures. Copyright © 2017 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Spatio-Temporal Distribution of Vector-Host Contact (VHC) Ratios and Ecological Niche Modeling of the West Nile Virus Mosquito Vector, Culex quinquefasciatus, in the City of New Orleans, LA, USA

PubMed Central

Michaels, Sarah R.; Riegel, Claudia; Pereira, Roberto M.; Zipperer, Wayne; Lockaby, B. Graeme; Koehler, Philip G.

2017-01-01

The consistent sporadic transmission of West Nile Virus (WNV) in the city of New Orleans justifies the need for distribution risk maps highlighting human risk of mosquito bites. We modeled the influence of biophysical and socioeconomic metrics on the spatio-temporal distributions of presence/vector-host contact (VHC) ratios of WNV vector, Culex quinquefasciatus, within their flight range. Biophysical and socioeconomic data were extracted within 5-km buffer radii around sampling localities of gravid female Culex quinquefasciatus. The spatio-temporal correlations between VHC data and 33 variables, including climate, land use-land cover (LULC), socioeconomic, and land surface terrain were analyzed using stepwise linear regression models (RM). Using MaxEnt, we developed a distribution model using the correlated predicting variables. Only 12 factors showed significant correlations with spatial distribution of VHC ratios (R2 = 81.62, p < 0.01). Non-forested wetland (NFWL), tree density (TD) and residential-urban (RU) settings demonstrated the strongest relationship. The VHC ratios showed monthly environmental resilience in terms of number and type of influential factors. The highest prediction power of RU and other urban and built up land (OUBL), was demonstrated during May–August. This association was positively correlated with the onset of the mosquito WNV infection rate during June. These findings were confirmed by the Jackknife analysis in MaxEnt and independently collected field validation points. The spatial and temporal correlations of VHC ratios and their response to the predicting variables are discussed. PMID:28786934

Spatio-Temporal Distribution of Vector-Host Contact (VHC) Ratios and Ecological Niche Modeling of the West Nile Virus Mosquito Vector, Culex quinquefasciatus, in the City of New Orleans, LA, USA.

PubMed

Sallam, Mohamed F; Michaels, Sarah R; Riegel, Claudia; Pereira, Roberto M; Zipperer, Wayne; Lockaby, B Graeme; Koehler, Philip G

2017-08-08

The consistent sporadic transmission of West Nile Virus (WNV) in the city of New Orleans justifies the need for distribution risk maps highlighting human risk of mosquito bites. We modeled the influence of biophysical and socioeconomic metrics on the spatio-temporal distributions of presence/vector-host contact (VHC) ratios of WNV vector, Culex quinquefasciatus , within their flight range . Biophysical and socioeconomic data were extracted within 5-km buffer radii around sampling localities of gravid female Culex quinquefasciatus . The spatio-temporal correlations between VHC data and 33 variables, including climate, land use-land cover (LULC), socioeconomic, and land surface terrain were analyzed using stepwise linear regression models (RM). Using MaxEnt, we developed a distribution model using the correlated predicting variables. Only 12 factors showed significant correlations with spatial distribution of VHC ratios ( R ² = 81.62, p < 0.01). Non-forested wetland (NFWL), tree density (TD) and residential-urban (RU) settings demonstrated the strongest relationship. The VHC ratios showed monthly environmental resilience in terms of number and type of influential factors. The highest prediction power of RU and other urban and built up land (OUBL), was demonstrated during May-August. This association was positively correlated with the onset of the mosquito WNV infection rate during June. These findings were confirmed by the Jackknife analysis in MaxEnt and independently collected field validation points. The spatial and temporal correlations of VHC ratios and their response to the predicting variables are discussed.

Thrips species (Insecta: Thysanoptera) associated with flowers in a restinga fragment in northeastern Brazil.

PubMed

Lima, I M B; Almeida-Filho, M A; Lima, M G A; Bonilla, O H; Lima, E F B

2018-03-22

With the growing volume of research involving Thysanoptera in Brazil, studies were carried out to improve our understanding of the diversity of thrips in areas where the fauna has historically been neglected. Accordingly, we recorded the diversity of thrips (Insecta: Thysanoptera) associated with a restinga fragment located on the campus of the State University of Ceará (UECE), Fortaleza, Ceará state, and computed the estimated richness and diversity indices. Samples were collected from 2011 through 2013 from flowers of 86 plant species. The material was taken to the Laboratory of Insect-Plant Interaction, where thrips were screened under stereomicroscope. We collected 456 adults and 58 immatures, representing 14 species, in addition to one unidentified species of Treherniella. Microcephalothrips abdominalis was found on a large number of host plants, and Frankliniella insularis was the most common species. About two-thirds of the total richness of thrips species was associated with three plant families (Amaranthaceae, Caesalpiniaceae and Poaceae); six thrips species were each associated with only one plant species. The richness of the species collected was close to that estimated by Bootstrap and Jackknife 1 analysis. The Shannon-Wiener (H') and Simpson (D) diversity indexes were 1,7607 and 0.7769, respectively. Although the species are common, 46 new associations between plant species and thrips were established, 13 of which are true host associations, which demonstrates the importance of coastal vegetation in maintaining populations of thrips.

Identification of pathogenic fungi with an optoelectronic nose

PubMed Central

Zhang, Yinan; Askim, Jon R.; Zhong, Wenxuan; Orlean, Peter; Suslick, Kenneth S.

2014-01-01

Human fungal infections have gained recent notoriety following contamination of pharmaceuticals in the compounding process. Such invasive infections are a more serious global problem, especially for immunocompromised patients. While superficial fungal infections are common and generally curable, invasive fungal infections are often life-threatening and much harder to diagnose and treat. Despite the increasing awareness of the situation’s severity, currently available fungal diagnostic methods cannot always meet diagnostic needs, especially for invasive fungal infections. Volatile organic compounds produced by fungi provide an alternative diagnostic approach for identification of fungal strains. We report here an optoelectronic nose based on a disposable colorimetric sensor array capable of rapid differentiation and identification of pathogenic fungi based on their metabolic profiles of emitted volatiles. The sensor arrays were tested with 12 human pathogenic fungal strains grown on standard agar medium. Array responses were monitored with an ordinary flatbed scanner. All fungal strains gave unique composite responses within 3 hours and were correctly clustered using hierarchical cluster analysis. A standard jackknifed linear discriminant analysis gave a classification accuracy of 94% for 155 trials. Tensor discriminant analysis, which takes better advantage of the high dimensionality of the sensor array data, gave a classification accuracy of 98.1%. The sensor array is also able to observe metabolic changes in growth patterns upon the addition of fungicides, and this provides a facile screening tool for determining fungicide efficacy for various fungal strains in real time. PMID:24570999

iPro54-PseKNC: a sequence-based predictor for identifying sigma-54 promoters in prokaryote with pseudo k-tuple nucleotide composition

PubMed Central

Lin, Hao; Deng, En-Ze; Ding, Hui; Chen, Wei; Chou, Kuo-Chen

2014-01-01

The σ54 promoters are unique in prokaryotic genome and responsible for transcripting carbon and nitrogen-related genes. With the avalanche of genome sequences generated in the postgenomic age, it is highly desired to develop automated methods for rapidly and effectively identifying the σ54 promoters. Here, a predictor called ‘iPro54-PseKNC’ was developed. In the predictor, the samples of DNA sequences were formulated by a novel feature vector called ‘pseudo k-tuple nucleotide composition’, which was further optimized by the incremental feature selection procedure. The performance of iPro54-PseKNC was examined by the rigorous jackknife cross-validation tests on a stringent benchmark data set. As a user-friendly web-server, iPro54-PseKNC is freely accessible at http://lin.uestc.edu.cn/server/iPro54-PseKNC. For the convenience of the vast majority of experimental scientists, a step-by-step protocol guide was provided on how to use the web-server to get the desired results without the need to follow the complicated mathematics that were presented in this paper just for its integrity. Meanwhile, we also discovered through an in-depth statistical analysis that the distribution of distances between the transcription start sites and the translation initiation sites were governed by the gamma distribution, which may provide a fundamental physical principle for studying the σ54 promoters. PMID:25361964

Modeling spatial risk of zoonotic cutaneous leishmaniasis in Central Iran.

PubMed

Shiravand, Babak; Tafti, Abbas Ali Dehghani; Hanafi-Bojd, Ahmad Ali; Almodaresi, S Ali; Mirzaei, Masoud; Abai, Mohammad Reza

2018-06-18

Zoonotic Cutaneous Leishmaniasis (ZCL) is one of the endemic diseases in central part of Iran. The aim of this cross-sectional study was to find the areas with a higher risk of infection considering the distribution of vector, reservoir hosts and human infection. Passive data recorded the positive cases of cutaneous leishmaniasis in Yazd province health center were collected for 10 years, from 2007 to 2016 at the County level. Considering all earlier studies conducted in Yazd province, records of Phlebotomus papatasi, the main vector of ZCL, and Rhombomys opimus, the main reservoir of ZCL, were collected and entered in a database. ArcGIS and MaxEnt model were used to map and predict the best ecological niches for both vector and reservoir. The most cumulative incidence of the disease was found to be in Khatam County, south of Yazd province. The area under curve (AUC) for R. opimus and P. papatasi was 0.955 and 0.914, respectively. We found higher presence probability of both vector and reservoir in central and eastern parts of the province. The jackknife test indicated that temperature and normalized difference vegetation index (NDVI) had the most effect on the model for the vector and reservoir, respectively. The areas with higher presence probability for the reservoirs and vectors were considered having the higher potential for ZCL transmission. These findings can be used to prevent and control the disease. Copyright © 2018 Elsevier B.V. All rights reserved.

Test-Retest Intervisit Variability of Functional and Structural Parameters in X-Linked Retinoschisis.

PubMed

Jeffrey, Brett G; Cukras, Catherine A; Vitale, Susan; Turriff, Amy; Bowles, Kristin; Sieving, Paul A

2014-09-01

To examine the variability of four outcome measures that could be used to address safety and efficacy in therapeutic trials with X-linked juvenile retinoschisis. Seven men with confirmed mutations in the RS1 gene were evaluated over four visits spanning 6 months. Assessments included visual acuity, full-field electroretinograms (ERG), microperimetric macular sensitivity, and retinal thickness measured by optical coherence tomography (OCT). Eyes were separated into Better or Worse Eye groups based on acuity at baseline. Repeatability coefficients were calculated for each parameter and jackknife resampling used to derive 95% confidence intervals (CIs). The threshold for statistically significant change in visual acuity ranged from three to eight letters. For ERG a-wave, an amplitude reduction greater than 56% would be considered significant. For other parameters, variabilities were lower in the Worse Eye group, likely a result of floor effects due to collapse of the schisis pockets and/or retinal atrophy. The criteria for significant change (Better/Worse Eye) for three important parameters were: ERG b/a-wave ratio (0.44/0.23), point wise sensitivity (10.4/7.0 dB), and central retinal thickness (31%/18%). The 95% CI range for visual acuity, ERG, retinal sensitivity, and central retinal thickness relative to baseline are described for this cohort of participants with X-linked juvenile retinoschisis (XLRS). A quantitative understanding of the variability of outcome measures is vital to establishing the safety and efficacy limits for therapeutic trials of XLRS patients.

Source Characterization of Underground Explosions from Combined Regional Moment Tensor and First-Motion Analysis

DOE PAGES

Chiang, Andrea; Dreger, Douglas S.; Ford, Sean R.; ...

2014-07-08

Here in this study, we investigate the 14 September 1988 U.S.–Soviet Joint Verification Experiment nuclear test at the Semipalatinsk test site in eastern Kazakhstan and two nuclear explosions conducted less than 10 years later at the Chinese Lop Nor test site. These events were very sparsely recorded by stations located within 1600 km, and in each case only three or four stations were available in the regional distance range. We have utilized a regional distance seismic waveform method fitting long-period, complete, three-component waveforms jointly with first-motion observations from regional stations and teleseismic arrays. The combination of long-period waveforms and first-motionmore » observations provides a unique discrimination of these sparsely recorded events in the context of the Hudson et al. (1989) source-type diagram. We demonstrate through a series of jackknife tests and sensitivity analyses that the source type of the explosions is well constrained. One event, a 1996 Lop Nor shaft explosion, displays large Love waves and possibly reversed Rayleigh waves at one station, indicative of a large F-factor. We show the combination of long-period waveforms and P-wave first motions are able to discriminate this event as explosion-like and distinct from earthquakes and collapses. We further demonstrate the behavior of network sensitivity solutions for models of tectonic release and spall-based tensile damage over a range of F-factors and K-factors.« less

Source Characterization of Underground Explosions from Combined Regional Moment Tensor and First-Motion Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chiang, Andrea; Dreger, Douglas S.; Ford, Sean R.

Here in this study, we investigate the 14 September 1988 U.S.–Soviet Joint Verification Experiment nuclear test at the Semipalatinsk test site in eastern Kazakhstan and two nuclear explosions conducted less than 10 years later at the Chinese Lop Nor test site. These events were very sparsely recorded by stations located within 1600 km, and in each case only three or four stations were available in the regional distance range. We have utilized a regional distance seismic waveform method fitting long-period, complete, three-component waveforms jointly with first-motion observations from regional stations and teleseismic arrays. The combination of long-period waveforms and first-motionmore » observations provides a unique discrimination of these sparsely recorded events in the context of the Hudson et al. (1989) source-type diagram. We demonstrate through a series of jackknife tests and sensitivity analyses that the source type of the explosions is well constrained. One event, a 1996 Lop Nor shaft explosion, displays large Love waves and possibly reversed Rayleigh waves at one station, indicative of a large F-factor. We show the combination of long-period waveforms and P-wave first motions are able to discriminate this event as explosion-like and distinct from earthquakes and collapses. We further demonstrate the behavior of network sensitivity solutions for models of tectonic release and spall-based tensile damage over a range of F-factors and K-factors.« less

Robust power spectral estimation for EEG data.

PubMed

Melman, Tamar; Victor, Jonathan D

2016-08-01

Typical electroencephalogram (EEG) recordings often contain substantial artifact. These artifacts, often large and intermittent, can interfere with quantification of the EEG via its power spectrum. To reduce the impact of artifact, EEG records are typically cleaned by a preprocessing stage that removes individual segments or components of the recording. However, such preprocessing can introduce bias, discard available signal, and be labor-intensive. With this motivation, we present a method that uses robust statistics to reduce dependence on preprocessing by minimizing the effect of large intermittent outliers on the spectral estimates. Using the multitaper method (Thomson, 1982) as a starting point, we replaced the final step of the standard power spectrum calculation with a quantile-based estimator, and the Jackknife approach to confidence intervals with a Bayesian approach. The method is implemented in provided MATLAB modules, which extend the widely used Chronux toolbox. Using both simulated and human data, we show that in the presence of large intermittent outliers, the robust method produces improved estimates of the power spectrum, and that the Bayesian confidence intervals yield close-to-veridical coverage factors. The robust method, as compared to the standard method, is less affected by artifact: inclusion of outliers produces fewer changes in the shape of the power spectrum as well as in the coverage factor. In the presence of large intermittent outliers, the robust method can reduce dependence on data preprocessing as compared to standard methods of spectral estimation. Copyright © 2016 Elsevier B.V. All rights reserved.

Behavioral phenomenology in Alzheimer's disease, frontotemporal dementia, and late-life depression: a retrospective analysis.

PubMed

Swartz, J R; Miller, B L; Lesser, I M; Booth, R; Darby, A; Wohl, M; Benson, D F

1997-04-01

Often patients in the early stages of Alzheimer's disease (AD), frontotemporal dementia (FTD), and late-life depression can be difficult to differentiate clinically. Although subtle cognitive distinctions exist between these disorders, noncognitive behavioral phenomenology may provide additional discriminating power. In 19 subjects with AD, 19 with FTD, 16 with late-life psychotic depression (LLPD), and 19 with late-life nonpsychotic depression (LLNPD), noncognitive behavioral symptoms were quantified retrospectively using the Schedules for Clinical Assessment in Neuropsychiatry (SCAN) and compared using both a one-way ANOVA and a multivariate stepwise discriminant analysis, which utilized a jackknife procedure. The FTD group showed the highest mean total SCAN score, while the AD group showed the lowest. ANOVA showed significant differences in the mean total SCAN scores between the four diagnostic groups (P < .0001). With the discriminant analysis, the four disorders demonstrated different clusters of behavioral abnormalities and were differentiated by these symptoms (P < .0001). A subset of 14 SCAN item group symptoms was identified that collectively classified the following percentages of subjects in each diagnostic category: AD 94.7%, FTD 100%, LLPD 87.5%, and LLNPD 100%. These results indicate that AD, FTD, LLPD, and LLNPD were distinguished retrospectively by the SCAN without using cognitive data. Better definition of the longitudinal course of noncognitive behavioral symptoms in different dementias and psychiatric disorders will be valuable both for diagnosis and to help define behavioral syndromes that are associated with selective neuroanatomic and neurochemical brain pathology.

US adult tobacco users' absolute harm perceptions of traditional and alternative tobacco products, information-seeking behaviors, and (mis)beliefs about chemicals in tobacco products.

PubMed

Bernat, Jennifer K; Ferrer, Rebecca A; Margolis, Katherine A; Blake, Kelly D

2017-08-01

Harm perceptions about tobacco products may influence initiation, continued use, and cessation efforts. We assessed associations between adult traditional tobacco product use and absolute harm perceptions of traditional and alternative tobacco products. We also described the topics individuals looked for during their last search for information, their beliefs about chemicals in cigarettes/cigarette smoke, and how both relate to harm perceptions. We ran multivariable models with jackknife replicate weights to analyze data from the 2015 administration of the National Cancer Institute's Health Information National Trends Survey (N=3376). Compared to never users, individuals reported lower perceived levels of harm for products they use. Among current tobacco users, ethnicity, thinking about chemicals in tobacco, and information-seeking were all factors associated with tobacco product harm perceptions. In the full sample, some respondents reported searching for information about health effects and cessation and held misperceptions about the source of chemicals in tobacco. This study fills a gap in the literature by assessing the absolute harm perceptions of a variety of traditional and alternative tobacco products. Harm perceptions vary among tobacco products, and the relationship among tobacco use, information seeking, thoughts about chemicals in tobacco products, and harm perceptions is complex. Data suggest that some individuals search for information about health effects and cessation and hold misperceptions about chemicals in tobacco products. Future inquiry could seek to understand the mechanisms that contribute to forming harm perceptions and beliefs about chemicals in tobacco products. Published by Elsevier Ltd.

Prediction of space sickness in astronauts from preflight fluid, electrolyte, and cardiovascular variables and Weightless Environmental Training Facility (WETF) training

NASA Technical Reports Server (NTRS)

Simanonok, K.; Mosely, E.; Charles, J.

1992-01-01

Nine preflight variables related to fluid, electrolyte, and cardiovascular status from 64 first-time Shuttle crewmembers were differentially weighted by discrimination analysis to predict the incidence and severity of each crewmember's space sickness as rated by NASA flight surgeons. The nine variables are serum uric acid, red cell count, environmental temperature at the launch site, serum phosphate, urine osmolality, serum thyroxine, sitting systolic blood pressure, calculated blood volume, and serum chloride. Using two methods of cross-validation on the original samples (jackknife and a stratefied random subsample), these variables enable the prediction of space sickness incidence (NONE or SICK) with 80 percent sickness and space severity (NONE, MILD, MODERATE, of SEVERE) with 59 percent success by one method of cross-validation and 67 percent by another method. Addition of a tenth variable, hours spent in the Weightlessness Environment Training Facility (WETF) did not improve the prediction of space sickness incidences but did improve the prediction of space sickness severity to 66 percent success by the first method of cross-validation of original samples and to 71 percent by the second method. Results to date suggest the presence of predisposing physiologic factors to space sickness that implicate fluid shift etiology. The data also suggest that prior exposure to fluid shift during WETF training may produce some circulatory pre-adaption to fluid shifts in weightlessness that results in a reduction of space sickness severity.

Neutral Kaon Mixing from Lattice QCD

NASA Astrophysics Data System (ADS)

Bai, Ziyuan

In this work, we report the lattice calculation of two important quantities which emerge from second order, K0 - K¯0 mixing : DeltaMK and epsilonK. The RBC-UKQCD collaboration has performed the first calculation of DeltaMK with unphysical kinematics [1]. We now extend this calculation to near-physical and physical ensembles. In these physical or near-physical calculations, the two-pion energies are below the kaon threshold, and we have to examine the two-pion intermediate states contribution to DeltaMK, as well as the enhanced finite volume corrections arising from these two-pion intermediate states. We also report the ?rst lattice calculation of the long-distance contribution to the indirect CP violation parameter, the epsilonK. This calculation involves the treatment of a short-distance, ultra-violet divergence that is absent in the calculation of DeltaMK, and we will report our techniques for correcting this divergence on the lattice. In this calculation, we used unphysical quark masses on the same ensemble that we used in [1]. Therefore, rather than providing a physical result, this calculation demonstrates the technique for calculating epsilonK, and provides an approximate understanding the size of the long-distance contributions. Various new techniques are employed in this work, such as the use of All-Mode-Averaging (AMA), the All-to-All (A2A) propagators and the use of super-jackknife method in analyzing the data.

A revision of chiggers of the minuta species-group (Acari: Trombiculidae: Neotrombicula Hirst, 1925) using multivariate morphometrics.

PubMed

Stekolnikov, Alexandr A; Klimov, Pavel B

2010-09-01

We revise chiggers belonging to the minuta-species group (genus Neotrombicula Hirst, 1925) from the Palaearctic using size-free multivariate morphometrics. This approach allowed us to resolve several diagnostic problems. We show that the widely distributed Neotrombicula scrupulosa Kudryashova, 1993 forms three spatially and ecologically isolated groups different from each other in size or shape (morphometric property) only: specimens from the Caucasus are distinct from those from Asia in shape, whereas the Asian specimens from plains and mountains are different from each other in size. We developed a multivariate classification model to separate three closely related species: N. scrupulosa, N. lubrica Kudryashova, 1993 and N. minuta Schluger, 1966. This model is based on five shape variables selected from an initial 17 variables by a best subset analysis using a custom size-correction subroutine. The variable selection procedure slightly improved the predictive power of the model, suggesting that it not only removed redundancy but also reduced 'noise' in the dataset. The overall classification accuracy of this model is 96.2, 96.2 and 95.5%, as estimated by internal validation, external validation and jackknife statistics, respectively. Our analyses resulted in one new synonymy: N. dimidiata Stekolnikov, 1995 is considered to be a synonym of N. lubrica. Both N. scrupulosa and N. lubrica are recorded from new localities. A key to species of the minuta-group incorporating results from our multivariate analyses is presented.

Bacterial community structure and soil properties of a subarctic tundra soil in Council, Alaska.

PubMed

Kim, Hye Min; Jung, Ji Young; Yergeau, Etienne; Hwang, Chung Yeon; Hinzman, Larry; Nam, Sungjin; Hong, Soon Gyu; Kim, Ok-Sun; Chun, Jongsik; Lee, Yoo Kyung

2014-08-01

The subarctic region is highly responsive and vulnerable to climate change. Understanding the structure of subarctic soil microbial communities is essential for predicting the response of the subarctic soil environment to climate change. To determine the composition of the bacterial community and its relationship with soil properties, we investigated the bacterial community structure and properties of surface soil from the moist acidic tussock tundra in Council, Alaska. We collected 70 soil samples with 25-m intervals between sampling points from 0-10 cm to 10-20 cm depths. The bacterial community was analyzed by pyrosequencing of 16S rRNA genes, and the following soil properties were analyzed: soil moisture content (MC), pH, total carbon (TC), total nitrogen (TN), and inorganic nitrogen (NH4+ and NO3-). The community compositions of the two different depths showed that Alphaproteobacteria decreased with soil depth. Among the soil properties measured, soil pH was the most significant factor correlating with bacterial community in both upper and lower-layer soils. Bacterial community similarity based on jackknifed unweighted unifrac distance showed greater similarity across horizontal layers than through the vertical depth. This study showed that soil depth and pH were the most important soil properties determining bacterial community structure of the subarctic tundra soil in Council, Alaska. © 2014 The Authors. FEMS Microbiology Ecology published by John Wiley & Sons Ltd on behalf of the Federation of European Microbiological Societies.

Ecomorphological analysis of bovid mandibles from Laetoli Tanzania using 3D geometric morphometrics: Implications for hominin paleoenvironmental reconstruction.

PubMed

Forrest, Frances L; Plummer, Thomas W; Raaum, Ryan L

2018-01-01

The current study describes a new method of mandibular ecological morphology (ecomorphology). Three-dimensional geometric morphometrics (3D GM) was used to quantify mandibular shape variation between extant bovids with different feeding preferences. Landmark data were subjected to generalized Procrustes analysis (GPA), principal components analysis (PCA), and discriminant function analysis (DFA). The PCA resulted in a continuum from grazers to browsers along PC1 and DFA classified 88% or more of the modern specimens to the correct feeding category. The protocol was reduced to a subset of landmarks on the mandibular corpus in order to make it applicable to incomplete fossils. The reduced landmark set resulted in greater overlap between feeding categories but maintained the same continuum as the complete landmark model. The DFA resubstitution and jackknife analyses resulted in classification success rates of 85% and 80%, respectively. The reduced landmark model was applied to fossil mandibles from the Upper Laetolil Beds (∼4.3-3.5 Ma) and Upper Ndolanya Beds (∼2.7-2.6 Ma) at Laetoli, Tanzania in order to assess antelope diet, and indirectly evaluate paleo-vegetation structure. The majority of the fossils were classified by the DFA as browsers or mixed feeders preferring browse. Our results indicate a continuous presence of wooded habitats and are congruent with recent environmental studies at Laetoli indicating a mosaic woodland-bushland-grassland savanna ecosystem. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparing two correlated C indices with right-censored survival outcome: a one-shot nonparametric approach.

PubMed

Kang, Le; Chen, Weijie; Petrick, Nicholas A; Gallas, Brandon D

2015-02-20

The area under the receiver operating characteristic curve is often used as a summary index of the diagnostic ability in evaluating biomarkers when the clinical outcome (truth) is binary. When the clinical outcome is right-censored survival time, the C index, motivated as an extension of area under the receiver operating characteristic curve, has been proposed by Harrell as a measure of concordance between a predictive biomarker and the right-censored survival outcome. In this work, we investigate methods for statistical comparison of two diagnostic or predictive systems, of which they could either be two biomarkers or two fixed algorithms, in terms of their C indices. We adopt a U-statistics-based C estimator that is asymptotically normal and develop a nonparametric analytical approach to estimate the variance of the C estimator and the covariance of two C estimators. A z-score test is then constructed to compare the two C indices. We validate our one-shot nonparametric method via simulation studies in terms of the type I error rate and power. We also compare our one-shot method with resampling methods including the jackknife and the bootstrap. Simulation results show that the proposed one-shot method provides almost unbiased variance estimations and has satisfactory type I error control and power. Finally, we illustrate the use of the proposed method with an example from the Framingham Heart Study. Copyright © 2014 John Wiley & Sons, Ltd.

Galaxy-galaxy lensing estimators and their covariance properties

NASA Astrophysics Data System (ADS)

Singh, Sukhdeep; Mandelbaum, Rachel; Seljak, Uroš; Slosar, Anže; Vazquez Gonzalez, Jose

2017-11-01

We study the covariance properties of real space correlation function estimators - primarily galaxy-shear correlations, or galaxy-galaxy lensing - using SDSS data for both shear catalogues and lenses (specifically the BOSS LOWZ sample). Using mock catalogues of lenses and sources, we disentangle the various contributions to the covariance matrix and compare them with a simple analytical model. We show that not subtracting the lensing measurement around random points from the measurement around the lens sample is equivalent to performing the measurement using the lens density field instead of the lens overdensity field. While the measurement using the lens density field is unbiased (in the absence of systematics), its error is significantly larger due to an additional term in the covariance. Therefore, this subtraction should be performed regardless of its beneficial effects on systematics. Comparing the error estimates from data and mocks for estimators that involve the overdensity, we find that the errors are dominated by the shape noise and lens clustering, which empirically estimated covariances (jackknife and standard deviation across mocks) that are consistent with theoretical estimates, and that both the connected parts of the four-point function and the supersample covariance can be neglected for the current levels of noise. While the trade-off between different terms in the covariance depends on the survey configuration (area, source number density), the diagnostics that we use in this work should be useful for future works to test their empirically determined covariances.

North American Tropical Cyclone Landfall and SST: A Statistical Model Study

NASA Technical Reports Server (NTRS)

Hall, Timothy; Yonekura, Emmi

2013-01-01

A statistical-stochastic model of the complete life cycle of North Atlantic (NA) tropical cyclones (TCs) is used to examine the relationship between climate and landfall rates along the North American Atlantic and Gulf Coasts. The model draws on archived data of TCs throughout the North Atlantic to estimate landfall rates at high geographic resolution as a function of the ENSO state and one of two different measures of sea surface temperature (SST): 1) SST averaged over the NA subtropics and the hurricane season and 2) this SST relative to the seasonal global subtropical mean SST (termed relSST). Here, the authors focus on SST by holding ENSO to a neutral state. Jackknife uncertainty tests are employed to test the significance of SST and relSST landfall relationships. There are more TC and major hurricane landfalls overall in warm years than cold, using either SST or relSST, primarily due to a basinwide increase in the number of storms. The signal along the coast, however, is complex. Some regions have large and significant sensitivity (e.g., an approximate doubling of annual major hurricane landfall probability on Texas from -2 to +2 standard deviations in relSST), while other regions have no significant sensitivity (e.g., the U.S. mid-Atlantic and Northeast coasts). This geographic structure is due to both shifts in the regions of primary TC genesis and shifts in TC propagation.

Prediction of protein S-nitrosylation sites based on adapted normal distribution bi-profile Bayes and Chou's pseudo amino acid composition.

PubMed

Jia, Cangzhi; Lin, Xin; Wang, Zhiping

2014-06-10

Protein S-nitrosylation is a reversible post-translational modification by covalent modification on the thiol group of cysteine residues by nitric oxide. Growing evidence shows that protein S-nitrosylation plays an important role in normal cellular function as well as in various pathophysiologic conditions. Because of the inherent chemical instability of the S-NO bond and the low abundance of endogenous S-nitrosylated proteins, the unambiguous identification of S-nitrosylation sites by commonly used proteomic approaches remains challenging. Therefore, computational prediction of S-nitrosylation sites has been considered as a powerful auxiliary tool. In this work, we mainly adopted an adapted normal distribution bi-profile Bayes (ANBPB) feature extraction model to characterize the distinction of position-specific amino acids in 784 S-nitrosylated and 1568 non-S-nitrosylated peptide sequences. We developed a support vector machine prediction model, iSNO-ANBPB, by incorporating ANBPB with the Chou's pseudo amino acid composition. In jackknife cross-validation experiments, iSNO-ANBPB yielded an accuracy of 65.39% and a Matthew's correlation coefficient (MCC) of 0.3014. When tested on an independent dataset, iSNO-ANBPB achieved an accuracy of 63.41% and a MCC of 0.2984, which are much higher than the values achieved by the existing predictors SNOSite, iSNO-PseAAC, the Li et al. algorithm, and iSNO-AAPair. On another training dataset, iSNO-ANBPB also outperformed GPS-SNO and iSNO-PseAAC in the 10-fold crossvalidation test.

PSSP-RFE: accurate prediction of protein structural class by recursive feature extraction from PSI-BLAST profile, physical-chemical property and functional annotations.

PubMed

Li, Liqi; Cui, Xiang; Yu, Sanjiu; Zhang, Yuan; Luo, Zhong; Yang, Hua; Zhou, Yue; Zheng, Xiaoqi

2014-01-01

Protein structure prediction is critical to functional annotation of the massively accumulated biological sequences, which prompts an imperative need for the development of high-throughput technologies. As a first and key step in protein structure prediction, protein structural class prediction becomes an increasingly challenging task. Amongst most homological-based approaches, the accuracies of protein structural class prediction are sufficiently high for high similarity datasets, but still far from being satisfactory for low similarity datasets, i.e., below 40% in pairwise sequence similarity. Therefore, we present a novel method for accurate and reliable protein structural class prediction for both high and low similarity datasets. This method is based on Support Vector Machine (SVM) in conjunction with integrated features from position-specific score matrix (PSSM), PROFEAT and Gene Ontology (GO). A feature selection approach, SVM-RFE, is also used to rank the integrated feature vectors through recursively removing the feature with the lowest ranking score. The definitive top features selected by SVM-RFE are input into the SVM engines to predict the structural class of a query protein. To validate our method, jackknife tests were applied to seven widely used benchmark datasets, reaching overall accuracies between 84.61% and 99.79%, which are significantly higher than those achieved by state-of-the-art tools. These results suggest that our method could serve as an accurate and cost-effective alternative to existing methods in protein structural classification, especially for low similarity datasets.

Predicting membrane protein types by the LLDA algorithm.

PubMed

Wang, Tong; Yang, Jie; Shen, Hong-Bin; Chou, Kuo-Chen

2008-01-01

Membrane proteins are generally classified into the following eight types: (1) type I transmembrane, (2) type II, (3) type III, (4) type IV, (5) multipass transmembrane, (6) lipid-chain-anchored membrane, (7) GPI-anchored membrane, and (8) peripheral membrane (K.C. Chou and H.B. Shen: BBRC, 2007, 360: 339-345). Knowing the type of an uncharacterized membrane protein often provides useful clues for finding its biological function and interaction process with other molecules in a biological system. With the explosion of protein sequences generated in the Post-Genomic Age, it is urgent to develop an automated method to deal with such a challenge. Recently, the PsePSSM (Pseudo Position-Specific Score Matrix) descriptor is proposed by Chou and Shen (Biochem. Biophys. Res. Comm. 2007, 360, 339-345) to represent a protein sample. The advantage of the PsePSSM descriptor is that it can combine the evolution information and sequence-correlated information. However, incorporating all these effects into a descriptor may cause the "high dimension disaster". To overcome such a problem, the fusion approach was adopted by Chou and Shen. Here, a completely different approach, the so-called LLDA (Local Linear Discriminant Analysis) is introduced to extract the key features from the high-dimensional PsePSSM space. The dimension-reduced descriptor vector thus obtained is a compact representation of the original high dimensional vector. Our jackknife and independent dataset test results indicate that it is very promising to use the LLDA approach to cope with complicated problems in biological systems, such as predicting the membrane protein type.

Characteristics of the group of radiologists that benefits the most using Breast Screen Reader Assessment Strategy (BREAST)

NASA Astrophysics Data System (ADS)

Ganesan, A.; Alakhras, M.; Brennan, P. C.; Lee, W.; Tapia, K.; Mello-Thoms, C.

2018-03-01

Purpose: To determine the impact of Breast Screen Reader Assessment Strategy (BREAST) over time in improving radiologists' breast cancer detection performance, and to identify the group of radiologists that benefit the most by using BREAST as a training tool. Materials and Methods: Thirty-six radiologists who completed three case-sets offered by BREAST were included in this study. The case-sets were arranged in radiologists' chronological order of completion and five performance measures (sensitivity, specificity, location sensitivity, receiver operating characteristics area under the curve (ROC AUC) and jackknife alternative free-response receiver operating characteristic (JAFROC) figure-of-merit (FOM)), available from BREAST, were compared between case-sets to determine the level of improvement achieved. The radiologists were then grouped based on their characteristics and the above performance measures between the case-sets were compared. Paired t-tests or Wilcoxon signed-rank tests with statistical significance set at p < 0.05 were used to compare the performance measures. Results: Significant improvement was demonstrated in radiologists' case-set performance in terms of location sensitivity and JAFROC FOM over the years, and radiologists' location sensitivity and JAFROC FOM showed significant improvement irrespective of their characteristics. In terms of ROC AUC, significant improvement was shown for radiologists who were reading screen mammograms for more than 7 years and spent more than 9 hours per week reading mammograms. Conclusion: Engaging with case-sets appears to enhance radiologists' performance suggesting the important value of initiatives such as BREAST. However, such performance enhancement was not shown for everyone, highlighting the need to tailor the BREAST platform to benefit all radiologists.

A software system for the simulation of chest lesions

NASA Astrophysics Data System (ADS)

Ryan, John T.; McEntee, Mark; Barrett, Saoirse; Evanoff, Michael; Manning, David; Brennan, Patrick

2007-03-01

We report on the development of a novel software tool for the simulation of chest lesions. This software tool was developed for use in our study to attain optimal ambient lighting conditions for chest radiology. This study involved 61 consultant radiologists from the American Board of Radiology. Because of its success, we intend to use the same tool for future studies. The software has two main functions: the simulation of lesions and retrieval of information for ROC (Receiver Operating Characteristic) and JAFROC (Jack-Knife Free Response ROC) analysis. The simulation layer operates by randomly selecting an image from a bank of reportedly normal chest x-rays. A random location is then generated for each lesion, which is checked against a reference lung-map. If the location is within the lung fields, as derived from the lung-map, a lesion is superimposed. Lesions are also randomly selected from a bank of manually created chest lesion images. A blending algorithm determines which are the best intensity levels for the lesion to sit naturally within the chest x-ray. The same software was used to run a study for all 61 radiologists. A sequence of images is displayed in random order. Half of these images had simulated lesions, ranging from subtle to obvious, and half of the images were normal. The operator then selects locations where he/she thinks lesions exist and grades the lesion accordingly. We have found that this software was very effective in this study and intend to use the same principles for future studies.

Reader characteristics linked to detection of pulmonary nodules on radiographs: ROC vs. JAFROC analyses of performance

NASA Astrophysics Data System (ADS)

Kohli, Akshay; Robinson, John W.; Ryan, John; McEntee, Mark F.; Brennan, Patrick C.

2011-03-01

The purpose of this study is to explore whether reader characteristics are linked to heightened levels of diagnostic performance in chest radiology using receiver operating characteristic (ROC) and jackknife free response ROC (JAFROC) methodologies. A set of 40 postero-anterior chest radiographs was developed, of which 20 were abnormal containing one or more simulated nodules, of varying subtlety. Images were independently reviewed by 12 boardcertified radiologists including six chest specialists. The observer performance was measured in terms of ROC and JAFROC scores. For the ROC analysis, readers were asked to rate their degree of suspicion for the presence of nodules by using a confidence rating scale (1-6). JAFROC analysis required the readers to locate and rate as many suspicious areas as they wished using the same scale and resultant data were used to generate Az and FOM scores for ROC and JAFROC analyses respectively. Using Pearson methods, scores of performance were correlated with 7 reader characteristics recorded using a questionnaire. JAFROC analysis showed that improved reader performance was significantly (p<=0.05) linked with chest specialty (p<0.03), hours per week reading chest radiographs (p<0.03) and chest readings per year (p<0.04). ROC analyses demonstrated only one significant relationship, hours per week reading chest radiographs (p<0.02).The results of this study have shown that radiologist's performance in the detection of pulmonary nodules on radiographs is significantly linked to chest specialty, hours reading per week and number of radiographs read per year. Also, JAFROC is a more powerful predictor of performance as compared to ROC.

Evaluation of chest tomosynthesis for the detection of pulmonary nodules: effect of clinical experience and comparison with chest radiography

NASA Astrophysics Data System (ADS)

Zachrisson, Sara; Vikgren, Jenny; Svalkvist, Angelica; Johnsson, Åse A.; Boijsen, Marianne; Flinck, Agneta; Månsson, Lars Gunnar; Kheddache, Susanne; Båth, Magnus

2009-02-01

Chest tomosynthesis refers to the technique of collecting low-dose projections of the chest at different angles and using these projections to reconstruct section images of the chest. In this study, a comparison of chest tomosynthesis and chest radiography in the detection of pulmonary nodules was performed and the effect of clinical experience of chest tomosynthesis was evaluated. Three senior thoracic radiologists, with more than ten years of experience of chest radiology and 6 months of clinical experience of chest tomosynthesis, acted as observers in a jackknife free-response receiver operating characteristics (JAFROC-1) study, performed on 42 patients with and 47 patients without pulmonary nodules examined with both chest tomosynthesis and chest radiography. MDCT was used as reference and the total number of nodules found using MDCT was 131. To investigate the effect of additional clinical experience of chest tomosynthesis, a second reading session of the tomosynthesis images was performed one year after the initial one. The JAFROC-1 figure of merit (FOM) was used as the principal measure of detectability. In comparison with chest radiography, chest tomosynthesis performed significantly better with regard to detectability. The observer-averaged JAFROC-1 FOM was 0.61 for tomosynthesis and 0.40 for radiography, giving a statistically significant difference between the techniques of 0.21 (p<0.0001). The observer-averaged JAFROC-1 FOM of the second reading of the tomosynthesis cases was not significantly higher than that of the first reading, indicating no improvement in detectability due to additional clinical experience of tomosynthesis.

Prediction of apoptosis protein locations with genetic algorithms and support vector machines through a new mode of pseudo amino acid composition.

PubMed

Kandaswamy, Krishna Kumar; Pugalenthi, Ganesan; Möller, Steffen; Hartmann, Enno; Kalies, Kai-Uwe; Suganthan, P N; Martinetz, Thomas

2010-12-01

Apoptosis is an essential process for controlling tissue homeostasis by regulating a physiological balance between cell proliferation and cell death. The subcellular locations of proteins performing the cell death are determined by mostly independent cellular mechanisms. The regular bioinformatics tools to predict the subcellular locations of such apoptotic proteins do often fail. This work proposes a model for the sorting of proteins that are involved in apoptosis, allowing us to both the prediction of their subcellular locations as well as the molecular properties that contributed to it. We report a novel hybrid Genetic Algorithm (GA)/Support Vector Machine (SVM) approach to predict apoptotic protein sequences using 119 sequence derived properties like frequency of amino acid groups, secondary structure, and physicochemical properties. GA is used for selecting a near-optimal subset of informative features that is most relevant for the classification. Jackknife cross-validation is applied to test the predictive capability of the proposed method on 317 apoptosis proteins. Our method achieved 85.80% accuracy using all 119 features and 89.91% accuracy for 25 features selected by GA. Our models were examined by a test dataset of 98 apoptosis proteins and obtained an overall accuracy of 90.34%. The results show that the proposed approach is promising; it is able to select small subsets of features and still improves the classification accuracy. Our model can contribute to the understanding of programmed cell death and drug discovery. The software and dataset are available at http://www.inb.uni-luebeck.de/tools-demos/apoptosis/GASVM.

A hybrid orographic plus statistical model for downscaling daily precipitation in Northern California

USGS Publications Warehouse

Pandey, G.R.; Cayan, D.R.; Dettinger, M.D.; Georgakakos, K.P.

2000-01-01

A hybrid (physical-statistical) scheme is developed to resolve the finescale distribution of daily precipitation over complex terrain. The scheme generates precipitation by combining information from the upper-air conditions and from sparsely distributed station measurements; thus, it proceeds in two steps. First, an initial estimate of the precipitation is made using a simplified orographic precipitation model. It is a steady-state, multilayer, and two-dimensional model following the concepts of Rhea. The model is driven by the 2.5?? ?? 2.5?? gridded National Oceanic and Atmospheric Administration-National Centers for Environmental Prediction upper-air profiles, and its parameters are tuned using the observed precipitation structure of the region. Precipitation is generated assuming a forced lifting of the air parcels as they cross the mountain barrier following a straight trajectory. Second, the precipitation is adjusted using errors between derived precipitation and observations from nearby sites. The study area covers the northern half of California, including coastal mountains, central valley, and the Sierra Nevada. The model is run for a 5-km rendition of terrain for days of January-March over the period of 1988-95. A jackknife analysis demonstrates the validity of the approach. The spatial and temporal distributions of the simulated precipitation field agree well with the observed precipitation. Further, a mapping of model performance indices (correlation coefficients, model bias, root-mean-square error, and threat scores) from an array of stations from the region indicates that the model performs satisfactorily in resolving daily precipitation at 5-km resolution.

Galaxy–galaxy lensing estimators and their covariance properties

DOE PAGES

Singh, Sukhdeep; Mandelbaum, Rachel; Seljak, Uros; ...

2017-07-21

Here, we study the covariance properties of real space correlation function estimators – primarily galaxy–shear correlations, or galaxy–galaxy lensing – using SDSS data for both shear catalogues and lenses (specifically the BOSS LOWZ sample). Using mock catalogues of lenses and sources, we disentangle the various contributions to the covariance matrix and compare them with a simple analytical model. We show that not subtracting the lensing measurement around random points from the measurement around the lens sample is equivalent to performing the measurement using the lens density field instead of the lens overdensity field. While the measurement using the lens densitymore » field is unbiased (in the absence of systematics), its error is significantly larger due to an additional term in the covariance. Therefore, this subtraction should be performed regardless of its beneficial effects on systematics. Comparing the error estimates from data and mocks for estimators that involve the overdensity, we find that the errors are dominated by the shape noise and lens clustering, which empirically estimated covariances (jackknife and standard deviation across mocks) that are consistent with theoretical estimates, and that both the connected parts of the four-point function and the supersample covariance can be neglected for the current levels of noise. While the trade-off between different terms in the covariance depends on the survey configuration (area, source number density), the diagnostics that we use in this work should be useful for future works to test their empirically determined covariances.« less

A Novel Feature Extraction Method with Feature Selection to Identify Golgi-Resident Protein Types from Imbalanced Data

PubMed Central

Yang, Runtao; Zhang, Chengjin; Gao, Rui; Zhang, Lina

2016-01-01

The Golgi Apparatus (GA) is a major collection and dispatch station for numerous proteins destined for secretion, plasma membranes and lysosomes. The dysfunction of GA proteins can result in neurodegenerative diseases. Therefore, accurate identification of protein subGolgi localizations may assist in drug development and understanding the mechanisms of the GA involved in various cellular processes. In this paper, a new computational method is proposed for identifying cis-Golgi proteins from trans-Golgi proteins. Based on the concept of Common Spatial Patterns (CSP), a novel feature extraction technique is developed to extract evolutionary information from protein sequences. To deal with the imbalanced benchmark dataset, the Synthetic Minority Over-sampling Technique (SMOTE) is adopted. A feature selection method called Random Forest-Recursive Feature Elimination (RF-RFE) is employed to search the optimal features from the CSP based features and g-gap dipeptide composition. Based on the optimal features, a Random Forest (RF) module is used to distinguish cis-Golgi proteins from trans-Golgi proteins. Through the jackknife cross-validation, the proposed method achieves a promising performance with a sensitivity of 0.889, a specificity of 0.880, an accuracy of 0.885, and a Matthew’s Correlation Coefficient (MCC) of 0.765, which remarkably outperforms previous methods. Moreover, when tested on a common independent dataset, our method also achieves a significantly improved performance. These results highlight the promising performance of the proposed method to identify Golgi-resident protein types. Furthermore, the CSP based feature extraction method may provide guidelines for protein function predictions. PMID:26861308

How are multifactorial beliefs about the role of genetics and behavior in cancer causation associated with cancer risk cognitions and emotions in the US population?

PubMed

Hamilton, Jada G; Waters, Erika A

2018-02-01

People who believe that cancer has both genetic and behavioral risk factors have more accurate mental models of cancer causation and may be more likely to engage in cancer screening behaviors than people who do not hold such multifactorial causal beliefs. This research explored possible health cognitions and emotions that might produce such differences. Using nationally representative cross-sectional data from the US Health Information National Trends Survey (N = 2719), we examined whether endorsing a multifactorial model of cancer causation was associated with perceptions of risk and other cancer-related cognitions and affect. Data were analyzed using linear regression with jackknife variance estimation and procedures to account for the complex survey design and weightings. Bivariate and multivariable analyses indicated that people who endorsed multifactorial beliefs about cancer had higher absolute risk perceptions, lower pessimism about cancer prevention, and higher worry about harm from environmental toxins that could be ingested or that emanate from consumer products (Ps < .05). Bivariate analyses indicated that multifactorial beliefs were also associated with higher feelings of risk, but multivariable analyses suggested that this effect was accounted for by the negative affect associated with reporting a family history of cancer. Multifactorial beliefs were not associated with believing that everything causes cancer or that there are too many cancer recommendations to follow (Ps > .05). Holding multifactorial causal beliefs about cancer are associated with a constellation of risk perceptions, health cognitions, and affect that may motivate cancer prevention and detection behavior. Copyright © 2017 John Wiley & Sons, Ltd.

Do adolescent Ecstasy users have different attitudes towards drugs when compared to Marijuana users?

PubMed Central

Martins, Silvia S.; Storr, Carla L.; Alexandre, Pierre K.; Chilcoat, Howard D.

2008-01-01

Background Perceived risk and attitudes about the consequences of drug use, perceptions of others expectations and self-efficacy influence the intent to try drugs and continue drug use once use has started. We examine associations between adolescents’ attitudes and beliefs towards ecstasy use; because most ecstasy users have a history of marijuana use, we estimate the association for three groups of adolescents: non-marijuana/ecstasy users, marijuana users (used marijuana at least once but never used ecstasy) and ecstasy users (used ecstasy at least once). Methods Data from 5,049 adolescents aged 12–18 years old who had complete weighted data information in Round 2 of the Restricted Use Files (RUF) of the National Survey of Parents and Youth (NSPY). Data were analyzed using jackknife weighted multinomial logistic regression models. Results Adolescent marijuana and ecstasy users were more likely to approve of marijuana and ecstasy use as compared to non-drug using youth. Adolescent marijuana and ecstasy users were more likely to have close friends who approved of ecstasy as compared to non-drug using youth. The magnitudes of these two associations were stronger for ecstasy use than for marijuana use in the final adjusted model. Our final adjusted model shows that approval of marijuana and ecstasy use was more strongly associated with marijuana and ecstasy use in adolescence than perceived risk in using both drugs. Conclusion Information about the risks and consequences of ecstasy use need to be presented to adolescents in order to attempt to reduce adolescents’ approval of ecstasy use as well as ecstasy experimentation. PMID:18068314

iRNA-2methyl: Identify RNA 2'-O-methylation Sites by Incorporating Sequence-Coupled Effects into General PseKNC and Ensemble Classifier.

PubMed

Qiu, Wang-Ren; Jiang, Shi-Yu; Sun, Bi-Qian; Xiao, Xuan; Cheng, Xiang; Chou, Kuo-Chen

2017-01-01

Being a kind of post-transcriptional modification (PTCM) in RNA, the 2'-Omethylation modification occurs in the processes of life development and disease formation as well. Accordingly, from the angles of both basic research and drug development, we are facing a challenging problem: given an uncharacterized RNA sequence formed by many nucleotides of A (adenine), C (cytosine), G (guanine), and U (uracil), which one can be of 2-O'-methylation modification, and which one cannot? Unfortunately, so far no computational method whatsoever has been developed to address such a problem. To fill this empty area, we propose a predictor called iRNA-2methyl. It is formed by incorporating a series of sequence-coupled factors into the general PseKNC (pseudo nucleotide composition), followed by fusing 12 basic random forest classifier into four ensemble predictors, with each aimed to identify the cases of A, C, G, and U along the RNA sequence concerned, respectively. Rigorous jackknife cross-validations have indicated that the success rates are very high (>93%). For the convenience of most experimental scientists, a user-friendly web-server for iRNA-2methyl has been established at http://www.jci-bioinfo.cn/iRNA-2methyl, by which users can easily obtain their desired results without the need to go through the complicated mathematical equations involved. The proposed predictor iRNA-2methyl will become a very useful bioinformatics tool for medicinal chemistry, helping to design effective drugs against the diseases related to the 2'-Omethylation modification. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Posterior Retroperitoneoscopic Resection of Extra-adrenal Paraganglioma Located in the Aorto-caval Space.

PubMed

Kang, Sang-Wook; Kandil, Emad; Kim, Min Jhi; Kim, Kwang Soon; Lee, Cho Rok; Jeong, Jong Ju; Nam, Kee-Hyun; Chung, Woong Youn; Park, Cheong Soo

2018-04-01

The posterior retroperitoneoscopic adrenalec tomy has several advantages compared with the transperitoneal approach such as a shorter and more direct route to the target organ, no breach of the intraperitoneal space, and no required retraction of the adjacent organs. It also is a safe procedure with a short learning curve.1 - 5 This report presents a challenging case of an extra-adrenal paraganglioma located in the aorto-caval space and managed using the retroperitoneal approach. A 39-year-old man was placed in the prone jackknife position, and three incisions were made in the right posterior abdominal wall for placement of the laparoscopic ports. The retroperitoneal space was entered with diathermy and blunt finger dissection, and retropneumoperitoneum was achieved with carbon dioxide insufflation pressure up to 18 mmHg. After identification of the right kidney and vessels, the tumor was meticulously dissected and excised with an energy device. The specimen was removed using a laparoscopic specimen retrieval bag, and the port sites were closed in layers. The operative time was 130 min, and the total blood loss was 30 ml. The tumor was diagnosed as a moderately differentiated extra-adrenal paraganglioma. The Von Hippel-Lindau gene mutation was detected using next-generation sequencing. The posterior retroperitoneoscopic approach is a safe, feasible, and effective method for excising an extra-adrenal paraganglioma even in the aorto-caval space. The authors suggest that this procedure is a useful surgical option for treatment of an aorto-caval paraganglioma for selected patients and by experienced surgeons.

Using the concept of Chou's pseudo amino acid composition to predict apoptosis proteins subcellular location: an approach by approximate entropy.

PubMed

Jiang, Xiaoying; Wei, Rong; Zhang, Tongliang; Gu, Quan

2008-01-01

The function of protein is closely correlated with it subcellular location. Prediction of subcellular location of apoptosis proteins is an important research area in post-genetic era because the knowledge of apoptosis proteins is useful to understand the mechanism of programmed cell death. Compared with the conventional amino acid composition (AAC), the Pseudo Amino Acid composition (PseAA) as originally introduced by Chou can incorporate much more information of a protein sequence so as to remarkably enhance the power of using a discrete model to predict various attributes of a protein. In this study, a novel approach is presented to predict apoptosis protein solely from sequence based on the concept of Chou's PseAA composition. The concept of approximate entropy (ApEn), which is a parameter denoting complexity of time series, is used to construct PseAA composition as additional features. Fuzzy K-nearest neighbor (FKNN) classifier is selected as prediction engine. Particle swarm optimization (PSO) algorithm is adopted for optimizing the weight factors which are important in PseAA composition. Two datasets are used to validate the performance of the proposed approach, which incorporate six subcellular location and four subcellular locations, respectively. The results obtained by jackknife test are quite encouraging. It indicates that the ApEn of protein sequence could represent effectively the information of apoptosis proteins subcellular locations. It can at least play a complimentary role to many of the existing methods, and might become potentially useful tool for protein function prediction. The software in Matlab is available freely by contacting the corresponding author.

Testing the equivalence of modern human cranial covariance structure: Implications for bioarchaeological applications.

PubMed

von Cramon-Taubadel, Noreen; Schroeder, Lauren

2016-10-01

Estimation of the variance-covariance (V/CV) structure of fragmentary bioarchaeological populations requires the use of proxy extant V/CV parameters. However, it is currently unclear whether extant human populations exhibit equivalent V/CV structures. Random skewers (RS) and hierarchical analyses of common principal components (CPC) were applied to a modern human cranial dataset. Cranial V/CV similarity was assessed globally for samples of individual populations (jackknifed method) and for pairwise population sample contrasts. The results were examined in light of potential explanatory factors for covariance difference, such as geographic region, among-group distance, and sample size. RS analyses showed that population samples exhibited highly correlated multivariate responses to selection, and that differences in RS results were primarily a consequence of differences in sample size. The CPC method yielded mixed results, depending upon the statistical criterion used to evaluate the hierarchy. The hypothesis-testing (step-up) approach was deemed problematic due to sensitivity to low statistical power and elevated Type I errors. In contrast, the model-fitting (lowest AIC) approach suggested that V/CV matrices were proportional and/or shared a large number of CPCs. Pairwise population sample CPC results were correlated with cranial distance, suggesting that population history explains some of the variability in V/CV structure among groups. The results indicate that patterns of covariance in human craniometric samples are broadly similar but not identical. These findings have important implications for choosing extant covariance matrices to use as proxy V/CV parameters in evolutionary analyses of past populations. © 2016 Wiley Periodicals, Inc.

Predictive performance of rainfall thresholds for shallow landslides in Switzerland from gridded daily data

NASA Astrophysics Data System (ADS)

Leonarduzzi, Elena; Molnar, Peter; McArdell, Brian W.

2017-08-01

A high-resolution gridded daily precipitation data set was combined with a landslide inventory containing over 2000 events in the period 1972-2012 to analyze rainfall thresholds which lead to landsliding in Switzerland. We colocated triggering rainfall to landslides, developed distributions of triggering and nontriggering rainfall event properties, and determined rainfall thresholds and intensity-duration ID curves and validated their performance. The best predictive performance was obtained by the intensity-duration ID threshold curve, followed by peak daily intensity Imax and mean event intensity Imean. Event duration by itself had very low predictive power. A single country-wide threshold of Imax = 28 mm/d was extended into space by regionalization based on surface erodibility and local climate (mean daily precipitation). It was found that wetter local climate and lower erodibility led to significantly higher rainfall thresholds required to trigger landslides. However, we showed that the improvement in model performance due to regionalization was marginal and much lower than what can be achieved by having a high-quality landslide database. Reference cases in which the landslide locations and timing were randomized and the landslide sample size was reduced showed the sensitivity of the Imax rainfall threshold model. Jack-knife and cross-validation experiments demonstrated that the model was robust. The results reported here highlight the potential of using rainfall ID threshold curves and rainfall threshold values for predicting the occurrence of landslides on a country or regional scale with possible applications in landslide warning systems, even with daily data.

Detection of calcification clusters in digital breast tomosynthesis slices at different dose levels utilizing a SRSAR reconstruction and JAFROC

NASA Astrophysics Data System (ADS)

Timberg, P.; Dustler, M.; Petersson, H.; Tingberg, A.; Zackrisson, S.

2015-03-01

Purpose: To investigate detection performance for calcification clusters in reconstructed digital breast tomosynthesis (DBT) slices at different dose levels using a Super Resolution and Statistical Artifact Reduction (SRSAR) reconstruction method. Method: Simulated calcifications with irregular profile (0.2 mm diameter) where combined to form clusters that were added to projection images (1-3 per abnormal image) acquired on a DBT system (Mammomat Inspiration, Siemens). The projection images were dose reduced by software to form 35 abnormal cases and 25 normal cases as if acquired at 100%, 75% and 50% dose level (AGD of approximately 1.6 mGy for a 53 mm standard breast, measured according to EUREF v0.15). A standard FBP and a SRSAR reconstruction method (utilizing IRIS (iterative reconstruction filters), and outlier detection using Maximum-Intensity Projections and Average-Intensity Projections) were used to reconstruct single central slices to be used in a Free-response task (60 images per observer and dose level). Six observers participated and their task was to detect the clusters and assign confidence rating in randomly presented images from the whole image set (balanced by dose level). Each trial was separated by one weeks to reduce possible memory bias. The outcome was analyzed for statistical differences using Jackknifed Alternative Free-response Receiver Operating Characteristics. Results: The results indicate that it is possible reduce the dose by 50% with SRSAR without jeopardizing cluster detection. Conclusions: The detection performance for clusters can be maintained at a lower dose level by using SRSAR reconstruction.

Predictive value of hippocampal MR imaging-based high-dimensional mapping in mesial temporal epilepsy: preliminary findings.

PubMed

Hogan, R E; Wang, L; Bertrand, M E; Willmore, L J; Bucholz, R D; Nassif, A S; Csernansky, J G

2006-01-01

We objectively assessed surface structural changes of the hippocampus in mesial temporal sclerosis (MTS) and assessed the ability of large-deformation high-dimensional mapping (HDM-LD) to demonstrate hippocampal surface symmetry and predict group classification of MTS in right and left MTS groups compared with control subjects. Using eigenvector field analysis of HDM-LD segmentations of the hippocampus, we compared the symmetry of changes in the right and left MTS groups with a group of 15 matched controls. To assess the ability of HDM-LD to predict group classification, eigenvectors were selected by a logistic regression procedure when comparing the MTS group with control subjects. Multivariate analysis of variance on the coefficients from the first 9 eigenvectors accounted for 75% of the total variance between groups. The first 3 eigenvectors showed the largest differences between the control group and each of the MTS groups, but with eigenvector 2 showing the greatest difference in the MTS groups. Reconstruction of the hippocampal deformation vector fields due solely to eigenvector 2 shows symmetrical patterns in the right and left MTS groups. A "leave-one-out" (jackknife) procedure correctly predicted group classification in 14 of 15 (93.3%) left MTS subjects and all 15 right MTS subjects. Analysis of principal dimensions of hippocampal shape change suggests that MTS, after accounting for normal right-left asymmetries, affects the right and left hippocampal surface structure very symmetrically. Preliminary analysis using HDM-LD shows it can predict group classification of MTS and control hippocampi in this well-defined population of patients with MTS and mesial temporal lobe epilepsy (MTLE).

Prefrontoparietal dysfunction during emotion regulation in anxiety disorder: a meta-analysis of functional magnetic resonance imaging studies.

PubMed

Wang, Hai-Yang; Zhang, Xiao-Xia; Si, Cui-Ping; Xu, Yang; Liu, Qian; Bian, He-Tao; Zhang, Bing-Wei; Li, Xue-Lin; Yan, Zhong-Rui

2018-01-01

Impairments in emotion regulation, and more specifically in cognitive reappraisal, are thought to play a key role in the pathogenesis of anxiety disorders. However, the available evidence on such deficits is inconsistent. To further illustrate the neurobiological underpinnings of anxiety disorder, the present meta-analysis summarizes functional magnetic resonance imaging (fMRI) findings for cognitive reappraisal tasks and investigates related brain areas. We performed a comprehensive series of meta-analyses of cognitive reappraisal fMRI studies contrasting patients with anxiety disorder with healthy control (HC) subjects, employing an anisotropic effect-size signed differential mapping approach. We also conducted a subgroup analysis of medication status, anxiety disorder subtype, data-processing software, and MRI field strengths. Meta-regression was used to explore the effects of demographics and clinical characteristics. Eight studies, with 11 datasets including 219 patients with anxiety disorder and 227 HC, were identified. Compared with HC, patients with anxiety disorder showed relatively decreased activation of the bilateral dorsomedial prefrontal cortex (dmPFC), bilateral dorsal anterior cingulate cortex (dACC), bilateral supplementary motor area (SMA), left ventromedial prefrontal cortex (vmPFC), bilateral parietal cortex, and left fusiform gyrus during cognitive reappraisal. The subgroup analysis, jackknife sensitivity analysis, heterogeneity analysis, and Egger's tests further confirmed these findings. Impaired cognitive reappraisal in anxiety disorder may be the consequence of hypo-activation of the prefrontoparietal network, consistent with insufficient top-down control. Our findings provide robust evidence that functional impairment in prefrontoparietal neuronal circuits may have a significant role in the pathogenesis of anxiety disorder.

Estimating individual glomerular volume in the human kidney: clinical perspectives.

PubMed

Puelles, Victor G; Zimanyi, Monika A; Samuel, Terence; Hughson, Michael D; Douglas-Denton, Rebecca N; Bertram, John F; Armitage, James A

2012-05-01

Measurement of individual glomerular volumes (IGV) has allowed the identification of drivers of glomerular hypertrophy in subjects without overt renal pathology. This study aims to highlight the relevance of IGV measurements with possible clinical implications and determine how many profiles must be measured in order to achieve stable size distribution estimates. We re-analysed 2250 IGV estimates obtained using the disector/Cavalieri method in 41 African and 34 Caucasian Americans. Pooled IGV analysis of mean and variance was conducted. Monte-Carlo (Jackknife) simulations determined the effect of the number of sampled glomeruli on mean IGV. Lin's concordance coefficient (R(C)), coefficient of variation (CV) and coefficient of error (CE) measured reliability. IGV mean and variance increased with overweight and hypertensive status. Superficial glomeruli were significantly smaller than juxtamedullary glomeruli in all subjects (P < 0.01), by race (P < 0.05) and in obese individuals (P < 0.01). Subjects with multiple chronic kidney disease (CKD) comorbidities showed significant increases in IGV mean and variability. Overall, mean IGV was particularly reliable with nine or more sampled glomeruli (R(C) > 0.95, <5% difference in CV and CE). These observations were not affected by a reduced sample size and did not disrupt the inverse linear correlation between mean IGV and estimated total glomerular number. Multiple comorbidities for CKD are associated with increased IGV mean and variance within subjects, including overweight, obesity and hypertension. Zonal selection and the number of sampled glomeruli do not represent drawbacks for future longitudinal biopsy-based studies of glomerular size and distribution.

Estimating individual glomerular volume in the human kidney: clinical perspectives

PubMed Central

Puelles, Victor G.; Zimanyi, Monika A.; Samuel, Terence; Hughson, Michael D.; Douglas-Denton, Rebecca N.; Bertram, John F.

2012-01-01

Background. Measurement of individual glomerular volumes (IGV) has allowed the identification of drivers of glomerular hypertrophy in subjects without overt renal pathology. This study aims to highlight the relevance of IGV measurements with possible clinical implications and determine how many profiles must be measured in order to achieve stable size distribution estimates. Methods. We re-analysed 2250 IGV estimates obtained using the disector/Cavalieri method in 41 African and 34 Caucasian Americans. Pooled IGV analysis of mean and variance was conducted. Monte-Carlo (Jackknife) simulations determined the effect of the number of sampled glomeruli on mean IGV. Lin’s concordance coefficient (RC), coefficient of variation (CV) and coefficient of error (CE) measured reliability. Results. IGV mean and variance increased with overweight and hypertensive status. Superficial glomeruli were significantly smaller than juxtamedullary glomeruli in all subjects (P < 0.01), by race (P < 0.05) and in obese individuals (P < 0.01). Subjects with multiple chronic kidney disease (CKD) comorbidities showed significant increases in IGV mean and variability. Overall, mean IGV was particularly reliable with nine or more sampled glomeruli (RC > 0.95, <5% difference in CV and CE). These observations were not affected by a reduced sample size and did not disrupt the inverse linear correlation between mean IGV and estimated total glomerular number. Conclusions. Multiple comorbidities for CKD are associated with increased IGV mean and variance within subjects, including overweight, obesity and hypertension. Zonal selection and the number of sampled glomeruli do not represent drawbacks for future longitudinal biopsy-based studies of glomerular size and distribution. PMID:21984554

Evaluation of Limiting Climatic Factors and Simulation of a Climatically Suitable Habitat for Chinese Sea Buckthorn

PubMed Central

Li, Guoqing; Du, Sheng; Guo, Ke

2015-01-01

Chinese sea buckthorn (Hippophae rhamnoides subsp. sinensis) has considerable economic potential and plays an important role in reclamation and soil and water conservation. For scientific cultivation of this species across China, we identified the key climatic factors and explored climatically suitable habitat in order to maximize survival of Chinese sea buckthorn using MaxEnt and GIS tools, based on 98 occurrence records from herbarium and publications and 13 climatic factors from Bioclim, Holdridge life zone and Kria' index variables. Our simulation showed that the MaxEnt model performance was significantly better than random, with an average test AUC value of 0.93 with 10-fold cross validation. A jackknife test and the regularized gain change, which were applied to the training algorithm, showed that precipitation of the driest month (PDM), annual precipitation (AP), coldness index (CI) and annual range of temperature (ART) were the most influential climatic factors in limiting the distribution of Chinese sea buckthorn, which explained 70.1% of the variation. The predicted map showed that the core of climatically suitable habitat was distributed from the southwest to northwest of Gansu, Ningxia, Shaanxi and Shanxi provinces, where the most influential climate variables were PDM of 1.0–7.0 mm, AP of 344.0–1089.0 mm, CI of -47.7–0.0°C, and ART of 26.1–45.0°C. We conclude that the distribution patterns of Chinese sea buckthorn are related to the northwest winter monsoon, the southwest summer monsoon and the southeast summer monsoon systems in China. PMID:26177033

[Forest lighting fire forecasting for Daxing'anling Mountains based on MAXENT model].

PubMed

Sun, Yu; Shi, Ming-Chang; Peng, Huan; Zhu, Pei-Lin; Liu, Si-Lin; Wu, Shi-Lei; He, Cheng; Chen, Feng

2014-04-01

Daxing'anling Mountains is one of the areas with the highest occurrence of forest lighting fire in Heilongjiang Province, and developing a lightning fire forecast model to accurately predict the forest fires in this area is of importance. Based on the data of forest lightning fires and environment variables, the MAXENT model was used to predict the lightning fire in Daxing' anling region. Firstly, we studied the collinear diagnostic of each environment variable, evaluated the importance of the environmental variables using training gain and the Jackknife method, and then evaluated the prediction accuracy of the MAXENT model using the max Kappa value and the AUC value. The results showed that the variance inflation factor (VIF) values of lightning energy and neutralized charge were 5.012 and 6.230, respectively. They were collinear with the other variables, so the model could not be used for training. Daily rainfall, the number of cloud-to-ground lightning, and current intensity of cloud-to-ground lightning were the three most important factors affecting the lightning fires in the forest, while the daily average wind speed and the slope was of less importance. With the increase of the proportion of test data, the max Kappa and AUC values were increased. The max Kappa values were above 0.75 and the average value was 0.772, while all of the AUC values were above 0.5 and the average value was 0. 859. With a moderate level of prediction accuracy being achieved, the MAXENT model could be used to predict forest lightning fire in Daxing'anling Mountains.

Differentiating prenatal exposure to methamphetamine and alcohol versus alcohol and not methamphetamine using tensor based brain morphometry and discriminant analysis

PubMed Central

Sowell, Elizabeth R.; Leow, Alex D.; Bookheimer, Susan Y.; Smith, Lynne M.; O’Connor, Mary J.; Kan, Eric; Rosso, Carly; Houston, Suzanne; Dinov, Ivo D.; Thompson, Paul M.

2010-01-01

Here we investigate the effects of prenatal exposure to methamphetamine (MA) on local brain volume using magnetic resonance imaging. Because many who use MA during pregnancy also use alcohol, a known teratogen, we examined whether local brain volumes differed among 61 children (ages 5 to 15), 21 with prenatal MA exposure, 18 with concomitant prenatal alcohol exposure (the MAA group), 13 with heavy prenatal alcohol but not MA exposure (ALC group), and 27 unexposed controls (CON group). Volume reductions were observed in both exposure groups relative to controls in striatal and thalamic regions bilaterally, and right prefrontal and left occipitoparietal cortices. Striatal volume reductions were more severe in the MAA group than in the ALC group, and within the MAA group, a negative correlation between full-scale IQ (FSIQ) scores and caudate volume was observed. Limbic structures including the anterior and posterior cingulate, the inferior frontal gyrus (IFG) and ventral and lateral temporal lobes bilaterally were increased in volume in both exposure groups. Further, cingulate and right IFG volume increases were more pronounced in the MAA than ALC group. Discriminant function analyses using local volume measurements and FSIQ were used to predict group membership, yielding factor scores that correctly classified 72% of participants in jackknife analyses. These findings suggest that striatal and limbic structures, known to be sites of neurotoxicity in adult MA abusers, may be more vulnerable to prenatal MA exposure than alcohol exposure, and that more severe striatal damage is associated with more severe cognitive deficit. PMID:20237258

An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea.

PubMed

McDonald, Daniel; Price, Morgan N; Goodrich, Julia; Nawrocki, Eric P; DeSantis, Todd Z; Probst, Alexander; Andersen, Gary L; Knight, Rob; Hugenholtz, Philip

2012-03-01

Reference phylogenies are crucial for providing a taxonomic framework for interpretation of marker gene and metagenomic surveys, which continue to reveal novel species at a remarkable rate. Greengenes is a dedicated full-length 16S rRNA gene database that provides users with a curated taxonomy based on de novo tree inference. We developed a 'taxonomy to tree' approach for transferring group names from an existing taxonomy to a tree topology, and used it to apply the Greengenes, National Center for Biotechnology Information (NCBI) and cyanoDB (Cyanobacteria only) taxonomies to a de novo tree comprising 408,315 sequences. We also incorporated explicit rank information provided by the NCBI taxonomy to group names (by prefixing rank designations) for better user orientation and classification consistency. The resulting merged taxonomy improved the classification of 75% of the sequences by one or more ranks relative to the original NCBI taxonomy with the most pronounced improvements occurring in under-classified environmental sequences. We also assessed candidate phyla (divisions) currently defined by NCBI and present recommendations for consolidation of 34 redundantly named groups. All intermediate results from the pipeline, which includes tree inference, jackknifing and transfer of a donor taxonomy to a recipient tree (tax2tree) are available for download. The improved Greengenes taxonomy should provide important infrastructure for a wide range of megasequencing projects studying ecosystems on scales ranging from our own bodies (the Human Microbiome Project) to the entire planet (the Earth Microbiome Project). The implementation of the software can be obtained from http://sourceforge.net/projects/tax2tree/.

An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea

PubMed Central

McDonald, Daniel; Price, Morgan N; Goodrich, Julia; Nawrocki, Eric P; DeSantis, Todd Z; Probst, Alexander; Andersen, Gary L; Knight, Rob; Hugenholtz, Philip

2012-01-01

Reference phylogenies are crucial for providing a taxonomic framework for interpretation of marker gene and metagenomic surveys, which continue to reveal novel species at a remarkable rate. Greengenes is a dedicated full-length 16S rRNA gene database that provides users with a curated taxonomy based on de novo tree inference. We developed a ‘taxonomy to tree' approach for transferring group names from an existing taxonomy to a tree topology, and used it to apply the Greengenes, National Center for Biotechnology Information (NCBI) and cyanoDB (Cyanobacteria only) taxonomies to a de novo tree comprising 408 315 sequences. We also incorporated explicit rank information provided by the NCBI taxonomy to group names (by prefixing rank designations) for better user orientation and classification consistency. The resulting merged taxonomy improved the classification of 75% of the sequences by one or more ranks relative to the original NCBI taxonomy with the most pronounced improvements occurring in under-classified environmental sequences. We also assessed candidate phyla (divisions) currently defined by NCBI and present recommendations for consolidation of 34 redundantly named groups. All intermediate results from the pipeline, which includes tree inference, jackknifing and transfer of a donor taxonomy to a recipient tree (tax2tree) are available for download. The improved Greengenes taxonomy should provide important infrastructure for a wide range of megasequencing projects studying ecosystems on scales ranging from our own bodies (the Human Microbiome Project) to the entire planet (the Earth Microbiome Project). The implementation of the software can be obtained from http://sourceforge.net/projects/tax2tree/. PMID:22134646

Geology of the Cooper Ridge NE Quadrangle, Sweetwater County, Wyoming

USGS Publications Warehouse

Roehler, Henry W.

1979-01-01

The Cooper Ridge NE 7?-minute quadrangle is 18 miles southeast of Rock Springs, Wyo., on the east flank of the Rock Springs uplift. Upper Cretaceous rocks composing the Rock Springs Formation, Ericson Sandstone, Almond Formation, Lewis Shale, Fox Hills Sandstone, and Lance Formation, Paleocene rocks composing the Fort Union Formation, and Eocene rocks composing the Wasatch Formation are exposed and dip 5?-8? southeast. Outcrops are unfaulted and generally homoclinal, but a minor cross-trending fold, the Jackknife Spring anticline, plunges southeastward and interrupts the northeast strike of beds. Older rocks in the subsurface are faulted and folded, especially near the Brady oil and gas field. Coal beds are present in the Almond, Lance, and Fort Union Formations. Coal resources are estimated to be more than 762 million short tons in 16 beds more than 2.5 feet thick, under less than 3,000 ft of overburden. Nearly 166 million tons are under less than 200 ft of overburden and are recoverable by strip mining. Unknown quantities of oil and gas are present in the Cretaceous Rock Springs, Blair, and Dakota Formations, Jurassic sandstone (Entrada Sandstone of drillers), Jurassic(?) and Triassic(?) Nugget Sandstone, Permian Park City Formation, and Pennsylvanian and Permian Weber Sandstone at the Brady field, part of which is in the southeast corner of the quadrangle, and in the Dakota Sandstone at the Prenalta Corp. Bluewater 33-32 well near the northern edge of the quadrangle. Other minerals include uranium in the Almond Formation and titanium in the Rock Springs Formation.

Evaluation of Limiting Climatic Factors and Simulation of a Climatically Suitable Habitat for Chinese Sea Buckthorn.

PubMed

Li, Guoqing; Du, Sheng; Guo, Ke

2015-01-01

Chinese sea buckthorn (Hippophae rhamnoides subsp. sinensis) has considerable economic potential and plays an important role in reclamation and soil and water conservation. For scientific cultivation of this species across China, we identified the key climatic factors and explored climatically suitable habitat in order to maximize survival of Chinese sea buckthorn using MaxEnt and GIS tools, based on 98 occurrence records from herbarium and publications and 13 climatic factors from Bioclim, Holdridge life zone and Kria' index variables. Our simulation showed that the MaxEnt model performance was significantly better than random, with an average test AUC value of 0.93 with 10-fold cross validation. A jackknife test and the regularized gain change, which were applied to the training algorithm, showed that precipitation of the driest month (PDM), annual precipitation (AP), coldness index (CI) and annual range of temperature (ART) were the most influential climatic factors in limiting the distribution of Chinese sea buckthorn, which explained 70.1% of the variation. The predicted map showed that the core of climatically suitable habitat was distributed from the southwest to northwest of Gansu, Ningxia, Shaanxi and Shanxi provinces, where the most influential climate variables were PDM of 1.0-7.0 mm, AP of 344.0-1089.0 mm, CI of -47.7-0.0°C, and ART of 26.1-45.0°C. We conclude that the distribution patterns of Chinese sea buckthorn are related to the northwest winter monsoon, the southwest summer monsoon and the southeast summer monsoon systems in China.

Robust power spectral estimation for EEG data

PubMed Central

Melman, Tamar; Victor, Jonathan D.

2016-01-01

Background Typical electroencephalogram (EEG) recordings often contain substantial artifact. These artifacts, often large and intermittent, can interfere with quantification of the EEG via its power spectrum. To reduce the impact of artifact, EEG records are typically cleaned by a preprocessing stage that removes individual segments or components of the recording. However, such preprocessing can introduce bias, discard available signal, and be labor-intensive. With this motivation, we present a method that uses robust statistics to reduce dependence on preprocessing by minimizing the effect of large intermittent outliers on the spectral estimates. New method Using the multitaper method[1] as a starting point, we replaced the final step of the standard power spectrum calculation with a quantile-based estimator, and the Jackknife approach to confidence intervals with a Bayesian approach. The method is implemented in provided MATLAB modules, which extend the widely used Chronux toolbox. Results Using both simulated and human data, we show that in the presence of large intermittent outliers, the robust method produces improved estimates of the power spectrum, and that the Bayesian confidence intervals yield close-to-veridical coverage factors. Comparison to existing method The robust method, as compared to the standard method, is less affected by artifact: inclusion of outliers produces fewer changes in the shape of the power spectrum as well as in the coverage factor. Conclusion In the presence of large intermittent outliers, the robust method can reduce dependence on data preprocessing as compared to standard methods of spectral estimation. PMID:27102041

A multi-scale study of Orthoptera species richness and human population size controlling for sampling effort

NASA Astrophysics Data System (ADS)

Cantarello, Elena; Steck, Claude E.; Fontana, Paolo; Fontaneto, Diego; Marini, Lorenzo; Pautasso, Marco

2010-03-01

Recent large-scale studies have shown that biodiversity-rich regions also tend to be densely populated areas. The most obvious explanation is that biodiversity and human beings tend to match the distribution of energy availability, environmental stability and/or habitat heterogeneity. However, the species-people correlation can also be an artefact, as more populated regions could show more species because of a more thorough sampling. Few studies have tested this sampling bias hypothesis. Using a newly collated dataset, we studied whether Orthoptera species richness is related to human population size in Italy’s regions (average area 15,000 km2) and provinces (2,900 km2). As expected, the observed number of species increases significantly with increasing human population size for both grain sizes, although the proportion of variance explained is minimal at the provincial level. However, variations in observed Orthoptera species richness are primarily associated with the available number of records, which is in turn well correlated with human population size (at least at the regional level). Estimated Orthoptera species richness (Chao2 and Jackknife) also increases with human population size both for regions and provinces. Both for regions and provinces, this increase is not significant when controlling for variation in area and number of records. Our study confirms the hypothesis that broad-scale human population-biodiversity correlations can in some cases be artefactual. More systematic sampling of less studied taxa such as invertebrates is necessary to ascertain whether biogeographical patterns persist when sampling effort is kept constant or included in models.

iPhos-PseEvo: Identifying Human Phosphorylated Proteins by Incorporating Evolutionary Information into General PseAAC via Grey System Theory.

PubMed

Qiu, Wang-Ren; Sun, Bi-Qian; Xiao, Xuan; Xu, Dong; Chou, Kuo-Chen

2017-05-01

Protein phosphorylation plays a critical role in human body by altering the structural conformation of a protein, causing it to become activated/deactivated, or functional modification. Given an uncharacterized protein sequence, can we predict whether it may be phosphorylated or may not? This is no doubt a very meaningful problem for both basic research and drug development. Unfortunately, to our best knowledge, so far no high throughput bioinformatics tool whatsoever has been developed to address such a very basic but important problem due to its extremely complexity and lacking sufficient training data. Here we proposed a predictor called iPhos-PseEvo by (1) incorporating the protein sequence evolutionary information into the general pseudo amino acid composition (PseAAC) via the grey system theory, (2) balancing out the skewed training datasets by the asymmetric bootstrap approach, and (3) constructing an ensemble predictor by fusing an array of individual random forest classifiers thru a voting system. Rigorous jackknife tests have indicated that very promising success rates have been achieved by iPhos-PseEvo even for such a difficult problem. A user-friendly web-server for iPhos-PseEvo has been established at http://www.jci-bioinfo.cn/iPhos-PseEvo, by which users can easily obtain their desired results without the need to go through the complicated mathematical equations involved. It has not escaped our notice that the formulation and approach presented here can be used to analyze many other problems in protein science as well. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

The index gage method to develop a flow duration curve from short-term streamflow records

NASA Astrophysics Data System (ADS)

Zhang, Zhenxing

2017-10-01

The flow duration curve (FDC) is one of the most commonly used graphical tools in hydrology and provides a comprehensive graphical view of streamflow variability at a particular site. For a gaged site, an FDC can be easily estimated with frequency analysis. When no streamflow records are available, regional FDCs are used to synthesize FDCs. However, studies on how to develop FDCs for sites with short-term records have been very limited. Deriving representative FDC when there are short-term hydrologic records is important. For instance, 43% of the 394 streamflow gages in Illinois have records of 20 years or fewer, and these short-term gages are often distributed in headwaters and contain valuable hydrologic information. In this study, the index gage method is proposed to develop FDCs using short-term hydrologic records via an information transfer technique from a nearby hydrologically similar index gage. There are three steps: (1) select an index gage; (2) determine changes of FDC; and (3) develop representative FDCs. The approach is tested using records from 92 U.S. Geological Survey streamflow gages in Illinois. A jackknife experiment is conducted to assess the performance. Bootstrap resampling is used to simulate various periods of records, i.e., 1, 2, 5, 10, 15, and 20 years of records. The results demonstrated that the index gage method is capable of developing a representative FDC using short-term records. Generally, the approach performance is improved when more hydrologic records are available, but the improvement appears to level off when the short-term gage has 10 years or more records.

Detecting taxonomic signal in an under-utilised character system: geometric morphometrics of the forcipular coxae of Scutigeromorpha (Chilopoda)

PubMed Central

Gutierrez, Beatriz Lopez; MacLeod, Norman; Edgecombe, Gregory D.

2011-01-01

Abstract To date, the forcipules have played almost no role in determining the systematics of scutigeromorph centipedes though in his 1974 review of taxonomic characters Markus Würmli suggested some potentially informative variation might be found in these structures. Geometric morphometric analyses were used to evaluate Würmli’s suggestion, specifically to determine whether the shape of the forcipular coxa contains information useful for diagnosing species. The geometry of the coxae of eight species from the genera Sphendononema, Scutigera, Dendrothereua, Thereuonema, Thereuopoda, Thereuopodina, Allothereua and Parascutigera was characterised using a combination of landmark- and semi-landmark-based sampling methods to summarize group-specific morphological variation. Canonical variates analysis of shape data characterizing the forcipular coxae indicates that these structures differ significantly between taxa at various systematic levels. Models calculated for the canonical variates space facilitate identification of the main shape differences between genera, including overall length/width, curvature of the external coxal margin, and the extent to which the coxofemoral condyle projects laterally. Jackknifed discriminant function analysis demonstrates that forcipular coxal training-set specimens were assigned to correct species in 61% of cases on average, the most accurate assignments being those of Parascutigera (Parascutigera guttata) and Thereuonema (Thereuonema microstoma). The geographically widespread species Thereuopoda longicornis, Sphendononema guildingii, Scutigera coleoptrata, and Dendrothereua linceci exhibit the least diagnostic coxae in our dataset. Thereuopoda longicornis populations sampled from different parts of East and Southeast Asia were significantly discriminated from each other, suggesting that, in this case, extensive synonymy may be obscuring diagnosable inter-species coxal shape differences. PMID:22303095

Identification of microRNA precursor with the degenerate K-tuple or Kmer strategy.

PubMed

Liu, Bin; Fang, Longyun; Wang, Shanyi; Wang, Xiaolong; Li, Hongtao; Chou, Kuo-Chen

2015-11-21

The microRNA (miRNA), a small non-coding RNA molecule, plays an important role in transcriptional and post-transcriptional regulation of gene expression. Its abnormal expression, however, has been observed in many cancers and other disease states, implying that the miRNA molecules are also deeply involved in these diseases, particularly in carcinogenesis. Therefore, it is important for both basic research and miRNA-based therapy to discriminate the real pre-miRNAs from the false ones (such as hairpin sequences with similar stem-loops). Most existing methods in this regard were based on the strategy in which RNA samples were formulated by a vector formed by their Kmer components. But the length of Kmers must be very short; otherwise, the vector's dimension would be extremely large, leading to the "high-dimension disaster" or overfitting problem. Inspired by the concept of "degenerate energy levels" in quantum mechanics, we introduced the "degenerate Kmer" (deKmer) to represent RNA samples. By doing so, not only we can accommodate long-range coupling effects but also we can avoid the high-dimension problem. Rigorous jackknife tests and cross-species experiments indicated that our approach is very promising. It has not escaped our notice that the deKmer approach can also be applied to many other areas of computational biology. A user-friendly web-server for the new predictor has been established at http://bioinformatics.hitsz.edu.cn/miRNA-deKmer/, by which users can easily get their desired results. Copyright © 2015 Elsevier Ltd. All rights reserved.

Population pharmacokinetics of caffeine and its metabolites theobromine, paraxanthine and theophylline after inhalation in combination with diacetylmorphine.

PubMed

Zandvliet, Anthe S; Huitema, Alwin D R; de Jonge, Milly E; den Hoed, Rob; Sparidans, Rolf W; Hendriks, Vincent M; van den Brink, Wim; van Ree, Jan M; Beijnen, Jos H

2005-01-01

The stimulant effect of caffeine, as an additive in diacetylmorphine preparations for study purposes, may interfere with the pharmacodynamic effects of diacetylmorphine. In order to obtain insight into the pharmacology of caffeine after inhalation in heroin users, the pharmacokinetics of caffeine and its dimethylxanthine metabolites were studied. The objectives were to establish the population pharmacokinetics under these exceptional circumstances and to compare the results to published data regarding intravenous and oral administration in healthy volunteers. Diacetylmorphine preparations containing 100 mg of caffeine were used by 10 persons by inhalation. Plasma concentrations of caffeine, theobromine, paraxanthine and theophylline were measured by high performance liquid chromatography. Non-linear mixed effects modelling was used to estimate population pharmacokinetic parameters. The model was evaluated by the jack-knife procedure. Caffeine was rapidly and effectively absorbed after inhalation. Population pharmacokinetics of caffeine and its dimethylxanthine metabolites could adequately and simultaneously be described by a linear multi-compartment model. The volume of distribution for the central compartment was estimated to be 45.7 l and the apparent elimination rate constant of caffeine at 8 hr after inhalation was 0.150 hr(-1) for a typical individual. The bioavailability was approximately 60%. The presented model adequately describes the population pharmacokinetics of caffeine and its dimethylxanthine metabolites after inhalation of the caffeine sublimate of a 100 mg tablet. Validation proved the stability of the model. Pharmacokinetics of caffeine after inhalation and intravenous administration are to a large extent similar. The bioavailability of inhaled caffeine is approximately 60% in experienced smokers.

Galaxy–galaxy lensing estimators and their covariance properties

DOE Office of Scientific and Technical Information (OSTI.GOV)

Singh, Sukhdeep; Mandelbaum, Rachel; Seljak, Uros

Here, we study the covariance properties of real space correlation function estimators – primarily galaxy–shear correlations, or galaxy–galaxy lensing – using SDSS data for both shear catalogues and lenses (specifically the BOSS LOWZ sample). Using mock catalogues of lenses and sources, we disentangle the various contributions to the covariance matrix and compare them with a simple analytical model. We show that not subtracting the lensing measurement around random points from the measurement around the lens sample is equivalent to performing the measurement using the lens density field instead of the lens overdensity field. While the measurement using the lens densitymore » field is unbiased (in the absence of systematics), its error is significantly larger due to an additional term in the covariance. Therefore, this subtraction should be performed regardless of its beneficial effects on systematics. Comparing the error estimates from data and mocks for estimators that involve the overdensity, we find that the errors are dominated by the shape noise and lens clustering, which empirically estimated covariances (jackknife and standard deviation across mocks) that are consistent with theoretical estimates, and that both the connected parts of the four-point function and the supersample covariance can be neglected for the current levels of noise. While the trade-off between different terms in the covariance depends on the survey configuration (area, source number density), the diagnostics that we use in this work should be useful for future works to test their empirically determined covariances.« less

Applying a social network analysis (SNA) approach to understanding radiologists' performance in reading mammograms

NASA Astrophysics Data System (ADS)

Tavakoli Taba, Seyedamir; Hossain, Liaquat; Heard, Robert; Brennan, Patrick; Lee, Warwick; Lewis, Sarah

2017-03-01

Rationale and objectives: Observer performance has been widely studied through examining the characteristics of individuals. Applying a systems perspective, while understanding of the system's output, requires a study of the interactions between observers. This research explains a mixed methods approach to applying a social network analysis (SNA), together with a more traditional approach of examining personal/ individual characteristics in understanding observer performance in mammography. Materials and Methods: Using social networks theories and measures in order to understand observer performance, we designed a social networks survey instrument for collecting personal and network data about observers involved in mammography performance studies. We present the results of a study by our group where 31 Australian breast radiologists originally reviewed 60 mammographic cases (comprising of 20 abnormal and 40 normal cases) and then completed an online questionnaire about their social networks and personal characteristics. A jackknife free response operating characteristic (JAFROC) method was used to measure performance of radiologists. JAFROC was tested against various personal and network measures to verify the theoretical model. Results: The results from this study suggest a strong association between social networks and observer performance for Australian radiologists. Network factors accounted for 48% of variance in observer performance, in comparison to 15.5% for the personal characteristics for this study group. Conclusion: This study suggest a strong new direction for research into improving observer performance. Future studies in observer performance should consider social networks' influence as part of their research paradigm, with equal or greater vigour than traditional constructs of personal characteristics.

Prediction of protein structural classes by Chou's pseudo amino acid composition: approached using continuous wavelet transform and principal component analysis.

PubMed

Li, Zhan-Chao; Zhou, Xi-Bin; Dai, Zong; Zou, Xiao-Yong

2009-07-01

A prior knowledge of protein structural classes can provide useful information about its overall structure, so it is very important for quick and accurate determination of protein structural class with computation method in protein science. One of the key for computation method is accurate protein sample representation. Here, based on the concept of Chou's pseudo-amino acid composition (AAC, Chou, Proteins: structure, function, and genetics, 43:246-255, 2001), a novel method of feature extraction that combined continuous wavelet transform (CWT) with principal component analysis (PCA) was introduced for the prediction of protein structural classes. Firstly, the digital signal was obtained by mapping each amino acid according to various physicochemical properties. Secondly, CWT was utilized to extract new feature vector based on wavelet power spectrum (WPS), which contains more abundant information of sequence order in frequency domain and time domain, and PCA was then used to reorganize the feature vector to decrease information redundancy and computational complexity. Finally, a pseudo-amino acid composition feature vector was further formed to represent primary sequence by coupling AAC vector with a set of new feature vector of WPS in an orthogonal space by PCA. As a showcase, the rigorous jackknife cross-validation test was performed on the working datasets. The results indicated that prediction quality has been improved, and the current approach of protein representation may serve as a useful complementary vehicle in classifying other attributes of proteins, such as enzyme family class, subcellular localization, membrane protein types and protein secondary structure, etc.

Visual search for tropical web spiders: the influence of plot length, sampling effort, and phase of the day on species richness.

PubMed

Pinto-Leite, C M; Rocha, P L B

2012-12-01

Empirical studies using visual search methods to investigate spider communities were conducted with different sampling protocols, including a variety of plot sizes, sampling efforts, and diurnal periods for sampling. We sampled 11 plots ranging in size from 5 by 10 m to 5 by 60 m. In each plot, we computed the total number of species detected every 10 min during 1 hr during the daytime and during the nighttime (0630 hours to 1100 hours, both a.m. and p.m.). We measured the influence of time effort on the measurement of species richness by comparing the curves produced by sample-based rarefaction and species richness estimation (first-order jackknife). We used a general linear model with repeated measures to assess whether the phase of the day during which sampling occurred and the differences in the plot lengths influenced the number of species observed and the number of species estimated. To measure the differences in species composition between the phases of the day, we used a multiresponse permutation procedure and a graphical representation based on nonmetric multidimensional scaling. After 50 min of sampling, we noted a decreased rate of species accumulation and a tendency of the estimated richness curves to reach an asymptote. We did not detect an effect of plot size on the number of species sampled. However, differences in observed species richness and species composition were found between phases of the day. Based on these results, we propose guidelines for visual search for tropical web spiders.

TargetM6A: Identifying N6-Methyladenosine Sites From RNA Sequences via Position-Specific Nucleotide Propensities and a Support Vector Machine.

PubMed

Li, Guang-Qing; Liu, Zi; Shen, Hong-Bin; Yu, Dong-Jun

2016-10-01

As one of the most ubiquitous post-transcriptional modifications of RNA, N 6 -methyladenosine ( [Formula: see text]) plays an essential role in many vital biological processes. The identification of [Formula: see text] sites in RNAs is significantly important for both basic biomedical research and practical drug development. In this study, we designed a computational-based method, called TargetM6A, to rapidly and accurately target [Formula: see text] sites solely from the primary RNA sequences. Two new features, i.e., position-specific nucleotide/dinucleotide propensities (PSNP/PSDP), are introduced and combined with the traditional nucleotide composition (NC) feature to formulate RNA sequences. The extracted features are further optimized to obtain a much more compact and discriminative feature subset by applying an incremental feature selection (IFS) procedure. Based on the optimized feature subset, we trained TargetM6A on the training dataset with a support vector machine (SVM) as the prediction engine. We compared the proposed TargetM6A method with existing methods for predicting [Formula: see text] sites by performing stringent jackknife tests and independent validation tests on benchmark datasets. The experimental results show that the proposed TargetM6A method outperformed the existing methods for predicting [Formula: see text] sites and remarkably improved the prediction performances, with MCC = 0.526 and AUC = 0.818. We also provided a user-friendly web server for TargetM6A, which is publicly accessible for academic use at http://csbio.njust.edu.cn/bioinf/TargetM6A.

Clinical validation of a medical grade color monitor for chest radiology

NASA Astrophysics Data System (ADS)

Jacobs, J.; Zanca, F.; Verschakelen, J.; Marchal, G.; Bosmans, H.

2009-02-01

Until recently, the specifications of medical grade monochrome LCD monitors outperformed those of color LCD monitors. New generations of color LCD monitors, however, show specifications that are in many respects similar to those of monochrome monitors typically used in diagnostic workstations. The aim of present study was to evaluate the impact of different medical grade monitors in terms of detection of simulated lung nodules in chest x-ray images. Specifically, we wanted to compare a new medical grade color monitor (Barco Coronis 6MP color) to a medical grade grayscale monitor (Barco Coronis 3MP monochrome) and a consumer color monitor (Philips 200VW 1.7MP color) by means of an observer performance experiment. Using the free-response acquisition data paradigm, seven radiologists were asked to detect and locate lung nodules (170 in total), simulated in half of the 200 chest X-ray images used in the experiment. The jackknife free-response receiver operating characteristic (JAFROC) analysis of the data showed a statistically significant difference between at least two monitors, F-value=3.77 and p-value =0.0481. The different Figure of Merit values were 0.727, 0.723 and 0.697 for the new color LCD monitor, the medical grade monitor and the consumer color monitor respectively. There was no difference between the needed reading times but there was a difference between the mean calculated Euclidian distances between the position marked by the observers and the center of the simulated nodule, indicating a better accuracy with both medical grade monitors. Present data suggests that the new generation of medical grade color monitors could be used as diagnostic workstations.

A comparison of ROC inferred from FROC and conventional ROC

NASA Astrophysics Data System (ADS)

McEntee, Mark F.; Littlefair, Stephen; Pietrzyk, Mariusz W.

2014-03-01

This study aims to determine whether receiver operating characteristic (ROC) scores inferred from free-response receiver operating characteristic (FROC) were equivalent to conventional ROC scores for the same readers and cases. Forty-five examining radiologists of the American Board of Radiology independently reviewed 47 PA chest radiographs under at least two conditions. Thirty-seven cases had abnormal findings and 10 cases had normal findings. Half the readers were asked to first locate any visualized lung nodules, mark them and assign a level of confidence [the FROC mark-rating pair] and second give an overall to the entire image on the same scale [the ROC score]. The second half of readers gave the ROC rating first followed by the FROC mark-rating pairs. A normal image was represented with number 1 and malignant lesions with numbers 2-5. A jackknife free-response receiver operating characteristic (JAFROC), and inferred ROC (infROC) was calculated from the mark-rating pairs using JAFROC V4.1 software. ROC based on the overall rating of the image calculated using DBM MRMC software, which was also used to compare infROC and ROC AUCs treating the methods as modalities. Pearson's correlations coefficient and linear regression were used to examine their relationship using SPSS, version 21.0; (SPSS, Chicago, IL). The results of this study showed no significant difference between the ROC and Inferred ROC AUCs (p≤0.25). While Pearson's correlation coefficient was 0.7 (p≤0.01). Inter-reader correlation calculated from Obuchowski- Rockette covariance's ranged from 0.43-0.86 while intra-reader agreement was greater than previously reported ranging from 0.68-0.82.

A hybrid method for prediction and repositioning of drug Anatomical Therapeutic Chemical classes.

PubMed

Chen, Lei; Lu, Jing; Zhang, Ning; Huang, Tao; Cai, Yu-Dong

2014-04-01

In the Anatomical Therapeutic Chemical (ATC) classification system, therapeutic drugs are divided into 14 main classes according to the organ or system on which they act and their chemical, pharmacological and therapeutic properties. This system, recommended by the World Health Organization (WHO), provides a global standard for classifying medical substances and serves as a tool for international drug utilization research to improve quality of drug use. In view of this, it is necessary to develop effective computational prediction methods to identify the ATC-class of a given drug, which thereby could facilitate further analysis of this system. In this study, we initiated an attempt to develop a prediction method and to gain insights from it by utilizing ontology information of drug compounds. Since only about one-fourth of drugs in the ATC classification system have ontology information, a hybrid prediction method combining the ontology information, chemical interaction information and chemical structure information of drug compounds was proposed for the prediction of drug ATC-classes. As a result, by using the Jackknife test, the 1st prediction accuracies for identifying the 14 main ATC-classes in the training dataset, the internal validation dataset and the external validation dataset were 75.90%, 75.70% and 66.36%, respectively. Analysis of some samples with false-positive predictions in the internal and external validation datasets indicated that some of them may even have a relationship with the false-positive predicted ATC-class, suggesting novel uses of these drugs. It was conceivable that the proposed method could be used as an efficient tool to identify ATC-classes of novel drugs or to discover novel uses of known drugs.

Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classes.

PubMed

Chou, Kuo-Chen

2005-01-01

With protein sequences entering into databanks at an explosive pace, the early determination of the family or subfamily class for a newly found enzyme molecule becomes important because this is directly related to the detailed information about which specific target it acts on, as well as to its catalytic process and biological function. Unfortunately, it is both time-consuming and costly to do so by experiments alone. In a previous study, the covariant-discriminant algorithm was introduced to identify the 16 subfamily classes of oxidoreductases. Although the results were quite encouraging, the entire prediction process was based on the amino acid composition alone without including any sequence-order information. Therefore, it is worthy of further investigation. To incorporate the sequence-order effects into the predictor, the 'amphiphilic pseudo amino acid composition' is introduced to represent the statistical sample of a protein. The novel representation contains 20 + 2lambda discrete numbers: the first 20 numbers are the components of the conventional amino acid composition; the next 2lambda numbers are a set of correlation factors that reflect different hydrophobicity and hydrophilicity distribution patterns along a protein chain. Based on such a concept and formulation scheme, a new predictor is developed. It is shown by the self-consistency test, jackknife test and independent dataset tests that the success rates obtained by the new predictor are all significantly higher than those by the previous predictors. The significant enhancement in success rates also implies that the distribution of hydrophobicity and hydrophilicity of the amino acid residues along a protein chain plays a very important role to its structure and function.

Demographic history and rare allele sharing among human populations.

PubMed

Gravel, Simon; Henn, Brenna M; Gutenkunst, Ryan N; Indap, Amit R; Marth, Gabor T; Clark, Andrew G; Yu, Fuli; Gibbs, Richard A; Bustamante, Carlos D

2011-07-19

High-throughput sequencing technology enables population-level surveys of human genomic variation. Here, we examine the joint allele frequency distributions across continental human populations and present an approach for combining complementary aspects of whole-genome, low-coverage data and targeted high-coverage data. We apply this approach to data generated by the pilot phase of the Thousand Genomes Project, including whole-genome 2-4× coverage data for 179 samples from HapMap European, Asian, and African panels as well as high-coverage target sequencing of the exons of 800 genes from 697 individuals in seven populations. We use the site frequency spectra obtained from these data to infer demographic parameters for an Out-of-Africa model for populations of African, European, and Asian descent and to predict, by a jackknife-based approach, the amount of genetic diversity that will be discovered as sample sizes are increased. We predict that the number of discovered nonsynonymous coding variants will reach 100,000 in each population after ∼1,000 sequenced chromosomes per population, whereas ∼2,500 chromosomes will be needed for the same number of synonymous variants. Beyond this point, the number of segregating sites in the European and Asian panel populations is expected to overcome that of the African panel because of faster recent population growth. Overall, we find that the majority of human genomic variable sites are rare and exhibit little sharing among diverged populations. Our results emphasize that replication of disease association for specific rare genetic variants across diverged populations must overcome both reduced statistical power because of rarity and higher population divergence.

Predicting membrane protein types by incorporating protein topology, domains, signal peptides, and physicochemical properties into the general form of Chou's pseudo amino acid composition.

PubMed

Chen, Yen-Kuang; Li, Kuo-Bin

2013-02-07

The type information of un-annotated membrane proteins provides an important hint for their biological functions. The experimental determination of membrane protein types, despite being more accurate and reliable, is not always feasible due to the costly laboratory procedures, thereby creating a need for the development of bioinformatics methods. This article describes a novel computational classifier for the prediction of membrane protein types using proteins' sequences. The classifier, comprising a collection of one-versus-one support vector machines, makes use of the following sequence attributes: (1) the cationic patch sizes, the orientation, and the topology of transmembrane segments; (2) the amino acid physicochemical properties; (3) the presence of signal peptides or anchors; and (4) the specific protein motifs. A new voting scheme was implemented to cope with the multi-class prediction. Both the training and the testing sequences were collected from SwissProt. Homologous proteins were removed such that there is no pair of sequences left in the datasets with a sequence identity higher than 40%. The performance of the classifier was evaluated by a Jackknife cross-validation and an independent testing experiments. Results show that the proposed classifier outperforms earlier predictors in prediction accuracy in seven of the eight membrane protein types. The overall accuracy was increased from 78.3% to 88.2%. Unlike earlier approaches which largely depend on position-specific substitution matrices and amino acid compositions, most of the sequence attributes implemented in the proposed classifier have supported literature evidences. The classifier has been deployed as a web server and can be accessed at http://bsaltools.ym.edu.tw/predmpt. Copyright © 2012 Elsevier Ltd. All rights reserved.

Estimation of sex from the anthropometric ear measurements of a Sudanese population.

PubMed

Ahmed, Altayeb Abdalla; Omer, Nosyba

2015-09-01

The external ear and its prints have multifaceted roles in medico-legal practice, e.g., identification and facial reconstruction. Furthermore, its norms are essential in the diagnosis of congenital anomalies and the design of hearing aids. Body part dimensions vary in different ethnic groups, so the most accurate statistical estimations of biological attributes are developed using population-specific standards. Sudan lacks comprehensive data about ear norms; moreover, there is a universal rarity in assessing the possibility of sex estimation from ear dimensions using robust statistical techniques. Therefore, this study attempts to establish data for normal adult Sudanese Arabs, assessing the existence of asymmetry and developing a population-specific equation for sex estimation. The study sample comprised 200 healthy Sudanese Arab volunteers (100 males and 100 females) in the age range of 18-30years. The physiognomic ear length and width, lobule length and width, and conchal length and width measurements were obtained by direct anthropometry, using a digital sliding caliper. Moreover, indices and asymmetry were assessed. Data were analyzed using basic descriptive statistics and discriminant function analyses employing jackknife validations of classification results. All linear dimensions used were sexually dimorphic except lobular lengths. Some of the variables and indices show asymmetry. Ear dimensions showed cross-validated sex classification accuracy ranging between 60.5% and 72%. Hence, the ear measurements cannot be used as an effective tool in the estimation of sex. However, in the absence of other more reliable means, it still can be considered a supportive trait in sex estimation. Further, asymmetry should be considered in identification from the ear measurements. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Characteristics of Induced and Tectonic Seismicity in Oklahoma Based on High-precision Earthquake Relocations and Focal mechanisms

NASA Astrophysics Data System (ADS)

Aziz Zanjani, F.; Lin, G.

2016-12-01

Seismic activity in Oklahoma has greatly increased since 2013, when the number of wastewater disposal wells associated with oil and gas production was significantly increased in the area. An M5.8 earthquake at about 5 km depth struck near Pawnee, Oklahoma on September 3, 2016. This earthquake is postulated to be related with the anthropogenic activity in Oklahoma. In this study, we investigate the seismic characteristics in Oklahoma by using high-precision earthquake relocations and focal mechanisms. We acquire the seismic data between January 2013 and October 2016 recorded by the local and regional (within 200 km distance from the Pawnee mainshock) seismic stations from the Incorporated Research Institutions for Seismology (IRIS). We relocate all the earthquakes by applying the source-specific station term method and a differential time relocation method based on waveform cross-correlation data. The high-precision earthquake relocation catalog is then used to perform full-waveform modeling. We use Muller's reflection method for Green's function construction and the mtinvers program for moment tensor inversion. The sensitivity of the solution to the station and component distribution is evaluated by carrying out the Jackknife resampling. These earthquake relocation and focal mechanism results will help constrain the fault orientation and the earthquake rupture length. In order to examine the static Coulomb stress change due to the 2016 Pawnee earthquake, we utilize the Coulomb 3 software in the vicinity of the mainshock and compare the aftershock pattern with the calculated stress variation. The stress change in the study area can be translated into probability of seismic failure on other parts of the designated fault.

Classification of Birds and Bats Using Flight Tracks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cullinan, Valerie I.; Matzner, Shari; Duberstein, Corey A.

Classification of birds and bats that use areas targeted for offshore wind farm development and the inference of their behavior is essential to evaluating the potential effects of development. The current approach to assessing the number and distribution of birds at sea involves transect surveys using trained individuals in boats or airplanes or using high-resolution imagery. These approaches are costly and have safety concerns. Based on a limited annotated library extracted from a single-camera thermal video, we provide a framework for building models that classify birds and bats and their associated behaviors. As an example, we developed a discriminant modelmore » for theoretical flight paths and applied it to data (N = 64 tracks) extracted from 5-min video clips. The agreement between model- and observer-classified path types was initially only 41%, but it increased to 73% when small-scale jitter was censored and path types were combined. Classification of 46 tracks of bats, swallows, gulls, and terns on average was 82% accurate, based on a jackknife cross-validation. Model classification of bats and terns (N = 4 and 2, respectively) was 94% and 91% correct, respectively; however, the variance associated with the tracks from these targets is poorly estimated. Model classification of gulls and swallows (N ≥ 18) was on average 73% and 85% correct, respectively. The models developed here should be considered preliminary because they are based on a small data set both in terms of the numbers of species and the identified flight tracks. Future classification models would be greatly improved by including a measure of distance between the camera and the target.« less

Modeling and predicting tumor response in radioligand therapy.

PubMed

Kletting, Peter; Thieme, Anne; Eberhardt, Nina; Rinscheid, Andreas; D'Alessandria, Calogero; Allmann, Jakob; Wester, Hans-Jürgen; Tauber, Robert; Beer, Ambros J; Glatting, Gerhard; Eiber, Matthias

2018-05-10

The aim of this work was to develop a theranostic method that allows predicting PSMA-positive tumor volume after radioligand therapy (RLT) based on a pre-therapeutic PET/CT measurement and physiologically based pharmacokinetic/dynamic (PBPK/PD) modeling at the example of RLT using 177 Lu-labeled PSMA for imaging and therapy (PSMA I&T). Methods: A recently developed PBPK model for 177 Lu PSMA I&T RLT was extended to account for tumor (exponential) growth and reduction due to irradiation (linear quadratic model). Data of 13 patients with metastatic castration-resistant prostate cancer (mCRPC) were retrospectively analyzed. Pharmacokinetic/dynamic parameters were simultaneously fitted in a Bayesian framework to PET/CT activity concentrations, planar scintigraphy data and tumor volumes prior and post (6 weeks) therapy. The method was validated using the leave-one-out Jackknife method. The tumor volume post therapy was predicted based on pre-therapy PET/CT imaging and PBPK/PD modeling. Results: The relative deviation of the predicted and measured tumor volume for PSMA-positive tumor cells (6 weeks post therapy) was 1±40% excluding one patient (PSA negative) from the population. The radiosensitivity for the PSA positive patients was determined to be 0.0172±0.0084 Gy-1. Conclusion: The proposed method is the first attempt to solely use PET/CT and modeling methods to predict the PSMA-positive tumor volume after radioligand therapy. Internal validation shows that this is feasible with an acceptable accuracy. Improvement of the method and external validation of the model is ongoing. Copyright © 2018 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Remote Sensing of Miombo Woodland's Aboveground Biomass and LAI using RADARSAT and Landsat ETM+ Data

NASA Astrophysics Data System (ADS)

Ribeiro, N. S.; Saatchi, S. S.; Shugart, H. H.; Wshington-Allen, R. A.

2007-05-01

Estimations of biomass are critical in Miombo Woodlands because they represent a primary source of food, fiber, and fuel for 340 million rural peoples and another 15 million urban dwellers in southern Africa. The purpose of this study is to estimate woody aboveground biomass and Leaf Area Index (LAI) in Niassa Reserve, northern Mozambique. The objective of this study is to use optical and microwave satellite data with contemporaneous field data to estimate biomass and LAI. Fifty field plots were surveyed across the Niassa Reserve for biomass and LAI in July and December 2004, respectively. Remote sensing data consisting of RADARSAT backscatter (C- band, ë=5.6 cm) and a June 2004 Landsat ETM+ were acquired. Normalized Difference Vegetation Index (NDVI), Simple Ratio (SR), and a land-cover map (72% total accuracy) were derived from the Landsat scene. Field measurements of biomass and LAI correlated with Radarsat backscatter (Rsqbiomass=0.45, RsqLAI = 0.35, P<0.0001 ), NDVI (Rsqbiomass =0.15, RsqLAI=0.14-, p <0.0001 ) and SR (Rsqbiomass=-0.14, RsqLAI= 0.17, p <0.0001). A jackknife stepwise regression technique was used to develop the best predictive models for biomass (biomass = -5.19 +0.074*radarsat+1.56*SR, Rsq=0.53) and LAI (LAI= -0.66+0.01*radarsat+0.22*SR, Rsq=0.45). The addition of NDVI did not improve the model. Forest biomass and LAI maps were then produced for Niassa Reserve with an estimated peak total biomass of 18 kg/hm2 and a mean LAI of 2.8 m2/m2. In the east both biomass and LAI are lower than the western Niassa Reserve.

Aboveground biomass and leaf area index (LAI) mapping for Niassa Reserve, northern Mozambique

NASA Astrophysics Data System (ADS)

Ribeiro, Natasha S.; Saatchi, Sassan S.; Shugart, Herman H.; Washington-Allen, Robert A.

2008-09-01

Estimations of biomass are critical in miombo woodlands because they represent the primary source of goods and services for over 80% of the population in southern Africa. This study was carried out in Niassa Reserve, northern Mozambique. The main objectives were first to estimate woody biomass and Leaf Area Index (LAI) using remotely sensed data [RADARSAT (C-band, λ = 5.7-cm)] and Landsat ETM+ derived Normalized Difference Vegetation Index (NDVI) and Simple Ratio (SR) calibrated by field measurements and, second to determine, at both landscape and plot scales, the environmental controls (precipitation, woody cover density, fire and elephants) of biomass and LAI. A land-cover map (72% overall accuracy) was derived from the June 2004 ETM+ mosaic. Field biomass and LAI were correlated with RADARSAT backscatter (rbiomass = 0.65, rLAI = 0.57, p < 0.0001) from July 2004, NDVI (rbiomass = 0.30, rLAI = 0.35; p < 0.0001) and SR (rbiomass = 0.36, rLAI = 0.40, p < 0.0001). A jackknife stepwise regression technique was used to develop the best predictive models for biomass (biomass = -5.19 + 0.074 * radarsat + 1.56 * SR, r2 = 0.55) and LAI (LAI = -0.66 + 0.01 * radarsat + 0.22 * SR, r2 = 0.45). Biomass and LAI maps were produced with an estimated peak of 18 kg m-2 and 2.80 m2 m-2, respectively. On the landscape-scale, both biomass and LAI were strongly determined by mean annual precipitation (F = 13.91, p = 0.0002). On the plot spatial scale, woody biomass was significantly determined by fire frequency, and LAI by vegetation type.

The effect of image processing on the detection of cancers in digital mammography.

PubMed

Warren, Lucy M; Given-Wilson, Rosalind M; Wallis, Matthew G; Cooke, Julie; Halling-Brown, Mark D; Mackenzie, Alistair; Chakraborty, Dev P; Bosmans, Hilde; Dance, David R; Young, Kenneth C

2014-08-01

OBJECTIVE. The objective of our study was to investigate the effect of image processing on the detection of cancers in digital mammography images. MATERIALS AND METHODS. Two hundred seventy pairs of breast images (both breasts, one view) were collected from eight systems using Hologic amorphous selenium detectors: 80 image pairs showed breasts containing subtle malignant masses; 30 image pairs, biopsy-proven benign lesions; 80 image pairs, simulated calcification clusters; and 80 image pairs, no cancer (normal). The 270 image pairs were processed with three types of image processing: standard (full enhancement), low contrast (intermediate enhancement), and pseudo-film-screen (no enhancement). Seven experienced observers inspected the images, locating and rating regions they suspected to be cancer for likelihood of malignancy. The results were analyzed using a jackknife-alternative free-response receiver operating characteristic (JAFROC) analysis. RESULTS. The detection of calcification clusters was significantly affected by the type of image processing: The JAFROC figure of merit (FOM) decreased from 0.65 with standard image processing to 0.63 with low-contrast image processing (p = 0.04) and from 0.65 with standard image processing to 0.61 with film-screen image processing (p = 0.0005). The detection of noncalcification cancers was not significantly different among the image-processing types investigated (p > 0.40). CONCLUSION. These results suggest that image processing has a significant impact on the detection of calcification clusters in digital mammography. For the three image-processing versions and the system investigated, standard image processing was optimal for the detection of calcification clusters. The effect on cancer detection should be considered when selecting the type of image processing in the future.

Sodium and potassium intakes among US adults: NHANES 2003–20081234

PubMed Central

Zhang, Zefeng; Carriquiry, Alicia L; Gunn, Janelle P; Kuklina, Elena V; Saydah, Sharon H; Yang, Quanhe; Moshfegh, Alanna J

2012-01-01

Background: The American Heart Association (AHA), Institute of Medicine (IOM), and US Departments of Health and Human Services and Agriculture (USDA) Dietary Guidelines for Americans all recommend that Americans limit sodium intake and choose foods that contain potassium to decrease the risk of hypertension and other adverse health outcomes. Objective: We estimated the distributions of usual daily sodium and potassium intakes by sociodemographic and health characteristics relative to current recommendations. Design: We used 24-h dietary recalls and other data from 12,581 adults aged ≥20 y who participated in NHANES in 2003–2008. Estimates of sodium and potassium intakes were adjusted for within-individual day-to-day variation by using measurement error models. SEs and 95% CIs were assessed by using jackknife replicate weights. Results: Overall, 99.4% (95% CI: 99.3%, 99.5%) of US adults consumed more sodium daily than recommended by the AHA (<1500 mg), and 90.7% (89.6%, 91.8%) consumed more than the IOM Tolerable Upper Intake Level (2300 mg). In US adults who are recommended by the Dietary Guidelines to further reduce sodium intake to 1500 mg/d (ie, African Americans aged ≥51 y or persons with hypertension, diabetes, or chronic kidney disease), 98.8% (98.4%, 99.2%) overall consumed >1500 mg/d, and 60.4% consumed >3000 mg/d—more than double the recommendation. Overall, <2% of US adults and ∼5% of US men consumed ≥4700 mg K/d (ie, met recommendations for potassium). Conclusion: Regardless of recommendations or sociodemographic or health characteristics, the vast majority of US adults consume too much sodium and too little potassium. PMID:22854410

Flexible Meta-Regression to Assess the Shape of the Benzene–Leukemia Exposure–Response Curve

PubMed Central

Vlaanderen, Jelle; Portengen, Lützen; Rothman, Nathaniel; Lan, Qing; Kromhout, Hans; Vermeulen, Roel

2010-01-01

Background Previous evaluations of the shape of the benzene–leukemia exposure–response curve (ERC) were based on a single set or on small sets of human occupational studies. Integrating evidence from all available studies that are of sufficient quality combined with flexible meta-regression models is likely to provide better insight into the functional relation between benzene exposure and risk of leukemia. Objectives We used natural splines in a flexible meta-regression method to assess the shape of the benzene–leukemia ERC. Methods We fitted meta-regression models to 30 aggregated risk estimates extracted from nine human observational studies and performed sensitivity analyses to assess the impact of a priori assessed study characteristics on the predicted ERC. Results The natural spline showed a supralinear shape at cumulative exposures less than 100 ppm-years, although this model fitted the data only marginally better than a linear model (p = 0.06). Stratification based on study design and jackknifing indicated that the cohort studies had a considerable impact on the shape of the ERC at high exposure levels (> 100 ppm-years) but that predicted risks for the low exposure range (< 50 ppm-years) were robust. Conclusions Although limited by the small number of studies and the large heterogeneity between studies, the inclusion of all studies of sufficient quality combined with a flexible meta-regression method provides the most comprehensive evaluation of the benzene–leukemia ERC to date. The natural spline based on all data indicates a significantly increased risk of leukemia [relative risk (RR) = 1.14; 95% confidence interval (CI), 1.04–1.26] at an exposure level as low as 10 ppm-years. PMID:20064779

Demographic history and rare allele sharing among human populations

PubMed Central

Gravel, Simon; Henn, Brenna M.; Gutenkunst, Ryan N.; Indap, Amit R.; Marth, Gabor T.; Clark, Andrew G.; Yu, Fuli; Gibbs, Richard A.; Bustamante, Carlos D.; Altshuler, David L.; Durbin, Richard M.; Abecasis, Gonçalo R.; Bentley, David R.; Chakravarti, Aravinda; Clark, Andrew G.; Collins, Francis S.; De La Vega, Francisco M.; Donnelly, Peter; Egholm, Michael; Flicek, Paul; Gabriel, Stacey B.; Gibbs, Richard A.; Knoppers, Bartha M.; Lander, Eric S.; Lehrach, Hans; Mardis, Elaine R.; McVean, Gil A.; Nickerson, Debbie A.; Peltonen, Leena; Schafer, Alan J.; Sherry, Stephen T.; Wang, Jun; Wilson, Richard K.; Gibbs, Richard A.; Deiros, David; Metzker, Mike; Muzny, Donna; Reid, Jeff; Wheeler, David; Wang, Jun; Li, Jingxiang; Jian, Min; Li, Guoqing; Li, Ruiqiang; Liang, Huiqing; Tian, Geng; Wang, Bo; Wang, Jian; Wang, Wei; Yang, Huanming; Zhang, Xiuqing; Zheng, Huisong; Lander, Eric S.; Altshuler, David L.; Ambrogio, Lauren; Bloom, Toby; Cibulskis, Kristian; Fennell, Tim J.; Gabriel, Stacey B.; Jaffe, David B.; Shefler, Erica; Sougnez, Carrie L.; Bentley, David R.; Gormley, Niall; Humphray, Sean; Kingsbury, Zoya; Koko-Gonzales, Paula; Stone, Jennifer; McKernan, Kevin J.; Costa, Gina L.; Ichikawa, Jeffry K.; Lee, Clarence C.; Sudbrak, Ralf; Lehrach, Hans; Borodina, Tatiana A.; Dahl, Andreas; Davydov, Alexey N.; Marquardt, Peter; Mertes, Florian; Nietfeld, Wilfiried; Rosenstiel, Philip; Schreiber, Stefan; Soldatov, Aleksey V.; Timmermann, Bernd; Tolzmann, Marius; Egholm, Michael; Affourtit, Jason; Ashworth, Dana; Attiya, Said; Bachorski, Melissa; Buglione, Eli; Burke, Adam; Caprio, Amanda; Celone, Christopher; Clark, Shauna; Conners, David; Desany, Brian; Gu, Lisa; Guccione, Lorri; Kao, Kalvin; Kebbel, Andrew; Knowlton, Jennifer; Labrecque, Matthew; McDade, Louise; Mealmaker, Craig; Minderman, Melissa; Nawrocki, Anne; Niazi, Faheem; Pareja, Kristen; Ramenani, Ravi; Riches, David; Song, Wanmin; Turcotte, Cynthia; Wang, Shally; Mardis, Elaine R.; Wilson, Richard K.; Dooling, David; Fulton, Lucinda; Fulton, Robert; Weinstock, George; Durbin, Richard M.; Burton, John; Carter, David M.; Churcher, Carol; Coffey, Alison; Cox, Anthony; Palotie, Aarno; Quail, Michael; Skelly, Tom; Stalker, James; Swerdlow, Harold P.; Turner, Daniel; De Witte, Anniek; Giles, Shane; Gibbs, Richard A.; Wheeler, David; Bainbridge, Matthew; Challis, Danny; Sabo, Aniko; Yu, Fuli; Yu, Jin; Wang, Jun; Fang, Xiaodong; Guo, Xiaosen; Li, Ruiqiang; Li, Yingrui; Luo, Ruibang; Tai, Shuaishuai; Wu, Honglong; Zheng, Hancheng; Zheng, Xiaole; Zhou, Yan; Li, Guoqing; Wang, Jian; Yang, Huanming; Marth, Gabor T.; Garrison, Erik P.; Huang, Weichun; Indap, Amit; Kural, Deniz; Lee, Wan-Ping; Leong, Wen Fung; Quinlan, Aaron R.; Stewart, Chip; Stromberg, Michael P.; Ward, Alistair N.; Wu, Jiantao; Lee, Charles; Mills, Ryan E.; Shi, Xinghua; Daly, Mark J.; DePristo, Mark A.; Altshuler, David L.; Ball, Aaron D.; Banks, Eric; Bloom, Toby; Browning, Brian L.; Cibulskis, Kristian; Fennell, Tim J.; Garimella, Kiran V.; Grossman, Sharon R.; Handsaker, Robert E.; Hanna, Matt; Hartl, Chris; Jaffe, David B.; Kernytsky, Andrew M.; Korn, Joshua M.; Li, Heng; Maguire, Jared R.; McCarroll, Steven A.; McKenna, Aaron; Nemesh, James C.; Philippakis, Anthony A.; Poplin, Ryan E.; Price, Alkes; Rivas, Manuel A.; Sabeti, Pardis C.; Schaffner, Stephen F.; Shefler, Erica; Shlyakhter, Ilya A.; Cooper, David N.; Ball, Edward V.; Mort, Matthew; Phillips, Andrew D.; Stenson, Peter D.; Sebat, Jonathan; Makarov, Vladimir; Ye, Kenny; Yoon, Seungtai C.; Bustamante, Carlos D.; Clark, Andrew G.; Boyko, Adam; Degenhardt, Jeremiah; Gravel, Simon; Gutenkunst, Ryan N.; Kaganovich, Mark; Keinan, Alon; Lacroute, Phil; Ma, Xin; Reynolds, Andy; Clarke, Laura; Flicek, Paul; Cunningham, Fiona; Herrero, Javier; Keenen, Stephen; Kulesha, Eugene; Leinonen, Rasko; McLaren, William M.; Radhakrishnan, Rajesh; Smith, Richard E.; Zalunin, Vadim; Zheng-Bradley, Xiangqun; Korbel, Jan O.; Stütz, Adrian M.; Humphray, Sean; Bauer, Markus; Cheetham, R. Keira; Cox, Tony; Eberle, Michael; James, Terena; Kahn, Scott; Murray, Lisa; Chakravarti, Aravinda; Ye, Kai; De La Vega, Francisco M.; Fu, Yutao; Hyland, Fiona C. L.; Manning, Jonathan M.; McLaughlin, Stephen F.; Peckham, Heather E.; Sakarya, Onur; Sun, Yongming A.; Tsung, Eric F.; Batzer, Mark A.; Konkel, Miriam K.; Walker, Jerilyn A.; Sudbrak, Ralf; Albrecht, Marcus W.; Amstislavskiy, Vyacheslav S.; Herwig, Ralf; Parkhomchuk, Dimitri V.; Sherry, Stephen T.; Agarwala, Richa; Khouri, Hoda M.; Morgulis, Aleksandr O.; Paschall, Justin E.; Phan, Lon D.; Rotmistrovsky, Kirill E.; Sanders, Robert D.; Shumway, Martin F.; Xiao, Chunlin; McVean, Gil A.; Auton, Adam; Iqbal, Zamin; Lunter, Gerton; Marchini, Jonathan L.; Moutsianas, Loukas; Myers, Simon; Tumian, Afidalina; Desany, Brian; Knight, James; Winer, Roger; Craig, David W.; Beckstrom-Sternberg, Steve M.; Christoforides, Alexis; Kurdoglu, Ahmet A.; Pearson, John V.; Sinari, Shripad A.; Tembe, Waibhav D.; Haussler, David; Hinrichs, Angie S.; Katzman, Sol J.; Kern, Andrew; Kuhn, Robert M.; Przeworski, Molly; Hernandez, Ryan D.; Howie, Bryan; Kelley, Joanna L.; Melton, S. Cord; Abecasis, Gonçalo R.; Li, Yun; Anderson, Paul; Blackwell, Tom; Chen, Wei; Cookson, William O.; Ding, Jun; Kang, Hyun Min; Lathrop, Mark; Liang, Liming; Moffatt, Miriam F.; Scheet, Paul; Sidore, Carlo; Snyder, Matthew; Zhan, Xiaowei; Zöllner, Sebastian; Awadalla, Philip; Casals, Ferran; Idaghdour, Youssef; Keebler, John; Stone, Eric A.; Zilversmit, Martine; Jorde, Lynn; Xing, Jinchuan; Eichler, Evan E.; Aksay, Gozde; Alkan, Can; Hajirasouliha, Iman; Hormozdiari, Fereydoun; Kidd, Jeffrey M.; Sahinalp, S. Cenk; Sudmant, Peter H.; Mardis, Elaine R.; Chen, Ken; Chinwalla, Asif; Ding, Li; Koboldt, Daniel C.; McLellan, Mike D.; Dooling, David; Weinstock, George; Wallis, John W.; Wendl, Michael C.; Zhang, Qunyuan; Durbin, Richard M.; Albers, Cornelis A.; Ayub, Qasim; Balasubramaniam, Senduran; Barrett, Jeffrey C.; Carter, David M.; Chen, Yuan; Conrad, Donald F.; Danecek, Petr; Dermitzakis, Emmanouil T.; Hu, Min; Huang, Ni; Hurles, Matt E.; Jin, Hanjun; Jostins, Luke; Keane, Thomas M.; Le, Si Quang; Lindsay, Sarah; Long, Quan; MacArthur, Daniel G.; Montgomery, Stephen B.; Parts, Leopold; Stalker, James; Tyler-Smith, Chris; Walter, Klaudia; Zhang, Yujun; Gerstein, Mark B.; Snyder, Michael; Abyzov, Alexej; Balasubramanian, Suganthi; Bjornson, Robert; Du, Jiang; Grubert, Fabian; Habegger, Lukas; Haraksingh, Rajini; Jee, Justin; Khurana, Ekta; Lam, Hugo Y. K.; Leng, Jing; Mu, Xinmeng Jasmine; Urban, Alexander E.; Zhang, Zhengdong; Li, Yingrui; Luo, Ruibang; Marth, Gabor T.; Garrison, Erik P.; Kural, Deniz; Quinlan, Aaron R.; Stewart, Chip; Stromberg, Michael P.; Ward, Alistair N.; Wu, Jiantao; Lee, Charles; Mills, Ryan E.; Shi, Xinghua; McCarroll, Steven A.; Banks, Eric; DePristo, Mark A.; Handsaker, Robert E.; Hartl, Chris; Korn, Joshua M.; Li, Heng; Nemesh, James C.; Sebat, Jonathan; Makarov, Vladimir; Ye, Kenny; Yoon, Seungtai C.; Degenhardt, Jeremiah; Kaganovich, Mark; Clarke, Laura; Smith, Richard E.; Zheng-Bradley, Xiangqun; Korbel, Jan O.; Humphray, Sean; Cheetham, R. Keira; Eberle, Michael; Kahn, Scott; Murray, Lisa; Ye, Kai; De La Vega, Francisco M.; Fu, Yutao; Peckham, Heather E.; Sun, Yongming A.; Batzer, Mark A.; Konkel, Miriam K.; Walker, Jerilyn A.; Xiao, Chunlin; Iqbal, Zamin; Desany, Brian; Blackwell, Tom; Snyder, Matthew; Xing, Jinchuan; Eichler, Evan E.; Aksay, Gozde; Alkan, Can; Hajirasouliha, Iman; Hormozdiari, Fereydoun; Kidd, Jeffrey M.; Chen, Ken; Chinwalla, Asif; Ding, Li; McLellan, Mike D.; Wallis, John W.; Hurles, Matt E.; Conrad, Donald F.; Walter, Klaudia; Zhang, Yujun; Gerstein, Mark B.; Snyder, Michael; Abyzov, Alexej; Du, Jiang; Grubert, Fabian; Haraksingh, Rajini; Jee, Justin; Khurana, Ekta; Lam, Hugo Y. K.; Leng, Jing; Mu, Xinmeng Jasmine; Urban, Alexander E.; Zhang, Zhengdong; Gibbs, Richard A.; Bainbridge, Matthew; Challis, Danny; Coafra, Cristian; Dinh, Huyen; Kovar, Christie; Lee, Sandy; Muzny, Donna; Nazareth, Lynne; Reid, Jeff; Sabo, Aniko; Yu, Fuli; Yu, Jin; Marth, Gabor T.; Garrison, Erik P.; Indap, Amit; Leong, Wen Fung; Quinlan, Aaron R.; Stewart, Chip; Ward, Alistair N.; Wu, Jiantao; Cibulskis, Kristian; Fennell, Tim J.; Gabriel, Stacey B.; Garimella, Kiran V.; Hartl, Chris; Shefler, Erica; Sougnez, Carrie L.; Wilkinson, Jane; Clark, Andrew G.; Gravel, Simon; Grubert, Fabian; Clarke, Laura; Flicek, Paul; Smith, Richard E.; Zheng-Bradley, Xiangqun; Sherry, Stephen T.; Khouri, Hoda M.; Paschall, Justin E.; Shumway, Martin F.; Xiao, Chunlin; McVean, Gil A.; Katzman, Sol J.; Abecasis, Gonçalo R.; Blackwell, Tom; Mardis, Elaine R.; Dooling, David; Fulton, Lucinda; Fulton, Robert; Koboldt, Daniel C.; Durbin, Richard M.; Balasubramaniam, Senduran; Coffey, Allison; Keane, Thomas M.; MacArthur, Daniel G.; Palotie, Aarno; Scott, Carol; Stalker, James; Tyler-Smith, Chris; Gerstein, Mark B.; Balasubramanian, Suganthi; Chakravarti, Aravinda; Knoppers, Bartha M.; Abecasis, Gonçalo R.; Bustamante, Carlos D.; Gharani, Neda; Gibbs, Richard A.; Jorde, Lynn; Kaye, Jane S.; Kent, Alastair; Li, Taosha; McGuire, Amy L.; McVean, Gil A.; Ossorio, Pilar N.; Rotimi, Charles N.; Su, Yeyang; Toji, Lorraine H.; TylerSmith, Chris; Brooks, Lisa D.; Felsenfeld, Adam L.; McEwen, Jean E.; Abdallah, Assya; Juenger, Christopher R.; Clemm, Nicholas C.; Collins, Francis S.; Duncanson, Audrey; Green, Eric D.; Guyer, Mark S.; Peterson, Jane L.; Schafer, Alan J.; Abecasis, Gonçalo R.; Altshuler, David L.; Auton, Adam; Brooks, Lisa D.; Durbin, Richard M.; Gibbs, Richard A.; Hurles, Matt E.; McVean, Gil A.

2011-01-01

High-throughput sequencing technology enables population-level surveys of human genomic variation. Here, we examine the joint allele frequency distributions across continental human populations and present an approach for combining complementary aspects of whole-genome, low-coverage data and targeted high-coverage data. We apply this approach to data generated by the pilot phase of the Thousand Genomes Project, including whole-genome 2–4× coverage data for 179 samples from HapMap European, Asian, and African panels as well as high-coverage target sequencing of the exons of 800 genes from 697 individuals in seven populations. We use the site frequency spectra obtained from these data to infer demographic parameters for an Out-of-Africa model for populations of African, European, and Asian descent and to predict, by a jackknife-based approach, the amount of genetic diversity that will be discovered as sample sizes are increased. We predict that the number of discovered nonsynonymous coding variants will reach 100,000 in each population after ∼1,000 sequenced chromosomes per population, whereas ∼2,500 chromosomes will be needed for the same number of synonymous variants. Beyond this point, the number of segregating sites in the European and Asian panel populations is expected to overcome that of the African panel because of faster recent population growth. Overall, we find that the majority of human genomic variable sites are rare and exhibit little sharing among diverged populations. Our results emphasize that replication of disease association for specific rare genetic variants across diverged populations must overcome both reduced statistical power because of rarity and higher population divergence. PMID:21730125

Predicting radiologists' true and false positive decisions in reading mammograms by using gaze parameters and image-based features

NASA Astrophysics Data System (ADS)

Gandomkar, Ziba; Tay, Kevin; Ryder, Will; Brennan, Patrick C.; Mello-Thoms, Claudia

2016-03-01

Radiologists' gaze-related parameters combined with image-based features were utilized to classify suspicious mammographic areas ultimately scored as True Positives (TP) and False Positives (FP). Eight breast radiologists read 120 two-view digital mammograms of which 59 had biopsy proven cancer. Eye tracking data was collected and nearby fixations were clustered together. Suspicious areas on mammograms were independently identified based on thresholding an intensity saliency map followed by automatic segmentation and pruning steps. For each radiologist reported area, radiologist's fixation clusters in the area, as well as neighboring suspicious areas within 2.5° of the center of fixation, were found. A 45-dimensional feature vector containing gaze parameters of the corresponding cluster along with image-based characteristics was constructed. Gaze parameters included total number of fixations in the cluster, dwell time, time to hit the cluster for the first time, maximum number of consecutive fixations, and saccade magnitude of the first fixation in the cluster. Image-based features consisted of intensity, shape, and texture descriptors extracted from the region around the suspicious area, its surrounding tissue, and the entire breast. For each radiologist, a userspecific Support Vector Machine (SVM) model was built to classify the reported areas as TPs or FPs. Leave-one-out cross validation was utilized to avoid over-fitting. A feature selection step was embedded in the SVM training procedure by allowing radial basis function kernels to have 45 scaling factors. The proposed method was compared with the radiologists' performance using the jackknife alternative free-response receiver operating characteristic (JAFROC). The JAFROC figure of merit increased significantly for six radiologists.

Metric optimisation for analogue forecasting by simulated annealing

NASA Astrophysics Data System (ADS)

Bliefernicht, J.; Bárdossy, A.

2009-04-01

It is well known that weather patterns tend to recur from time to time. This property of the atmosphere is used by analogue forecasting techniques. They have a long history in weather forecasting and there are many applications predicting hydrological variables at the local scale for different lead times. The basic idea of the technique is to identify past weather situations which are similar (analogue) to the predicted one and to take the local conditions of the analogues as forecast. But the forecast performance of the analogue method depends on user-defined criteria like the choice of the distance function and the size of the predictor domain. In this study we propose a new methodology of optimising both criteria by minimising the forecast error with simulated annealing. The performance of the methodology is demonstrated for the probability forecast of daily areal precipitation. It is compared with a traditional analogue forecasting algorithm, which is used operational as an element of a hydrological forecasting system. The study is performed for several meso-scale catchments located in the Rhine basin in Germany. The methodology is validated by a jack-knife method in a perfect prognosis framework for a period of 48 years (1958-2005). The predictor variables are derived from the NCEP/NCAR reanalysis data set. The Brier skill score and the economic value are determined to evaluate the forecast skill and value of the technique. In this presentation we will present the concept of the optimisation algorithm and the outcome of the comparison. It will be also demonstrated how a decision maker should apply a probability forecast to maximise the economic benefit from it.

Prediction of long-term disability in multiple sclerosis.

PubMed

Schlaeger, R; D'Souza, M; Schindler, C; Grize, L; Dellas, S; Radue, E W; Kappos, L; Fuhr, P

2012-01-01

Little is known about the predictive value of neurophysiological measures for the long-term course of multiple sclerosis (MS). To prospectively investigate whether combined visual (VEP) and motor evoked potentials (MEP) allow prediction of disability over 14 years. A total of 30 patients with relapsing-remitting and secondary progressive MS were prospectively investigated with VEPs, MEPs and the Expanded Disability Status Scale (EDSS) at entry (T0) and after 6, 12 and 24 months, and with cranial MRI scans at entry (T2-weighted and gadolinium-enhanced T1-weighted images). EDSS was again assessed at year 14 (T4). The association between evoked potential (EP), magnetic resonance (MR) data and EDSS was measured using Spearman's rank correlation. Multivariable linear regression was performed to predict EDSS(T4) as a function of z-transformed EP-latencies(T0). The model was validated using a jack-knife procedure and the potential for improving it by inclusion of additional baseline variables was examined. EDSS values(T4) correlated with the sum of z-transformed EP-latencies(T0) (rho = 0.68, p < 0.0001), but not with MR-parameters(T0). EDSS(T4) as predicted by the formula EDSS(T4) = 4.194 + 0.088 * z-score P100(T0) + 0.071 * z-score CMCT(UE, T0) correlated with the observed values (rho = 0.69, p < 0.0001). Combined EPs allow prediction of long-term disability in small groups of patients with MS. This may have implications for the choice of monitoring methods in clinical trials and for daily practice decisions.

Plasma microRNA profile as a predictor of early virological response to interferon treatment in chronic hepatitis B patients.

PubMed

Zhang, Xiaonan; Chen, Cuncun; Wu, Min; Chen, Liang; Zhang, Jiming; Zhang, Xinxin; Zhang, Zhanqin; Wu, Jingdi; Wang, Jiefei; Chen, Xiaorong; Huang, Tao; Chen, Lixiang; Yuan, Zhenghong

2012-01-01

Interferon (IFN) and pegylated interferon (PEG-IFN) treatment of chronic hepatitis B leads to a sustained virological response in a limited proportion of patients and has considerable side effects. To find novel markers associated with prognosis of IFN therapy, we investigated whether a pretreatment plasma microRNA profile could be used to predict early virological response to IFN. We performed microRNA microarray analysis of plasma samples from 94 patients with chronic hepatitis B who received IFN therapy. The microRNA profiles from 13 liver biopsy samples were also measured. The OneR feature ranking and incremental feature selection method were used to rank and optimize the number of features in the model. Support vector machine prediction engine and jack-knife cross-validation were used to generate and evaluate the prediction model. The optimized model consisting of 11 microRNAs yielded a 74.2% overall accuracy in the training group and was independently confirmed in the test group (71.4% accuracy). Univariate and multivariate logistic regression analyses confirmed its independent association with early virological response (OR=7.35; P=2.12×10(-5)). Combining the microRNA profile with the alanine aminotransferase level improved the overall accuracy from 73.4% to 77.3%. Co-transfection of an HBV replicative construct with microRNA mimics revealed that let-7f, miR-939 and miR-638 were functionally associated with the HBV life cycle. The 11 microRNA signatures in plasma, together with basic clinical variables, might provide an accurate method to assist in medication decisions and improve the overall sustained response to IFN treatment.

iDNA-Prot: Identification of DNA Binding Proteins Using Random Forest with Grey Model

PubMed Central

Lin, Wei-Zhong; Fang, Jian-An; Xiao, Xuan; Chou, Kuo-Chen

2011-01-01

DNA-binding proteins play crucial roles in various cellular processes. Developing high throughput tools for rapidly and effectively identifying DNA-binding proteins is one of the major challenges in the field of genome annotation. Although many efforts have been made in this regard, further effort is needed to enhance the prediction power. By incorporating the features into the general form of pseudo amino acid composition that were extracted from protein sequences via the “grey model” and by adopting the random forest operation engine, we proposed a new predictor, called iDNA-Prot, for identifying uncharacterized proteins as DNA-binding proteins or non-DNA binding proteins based on their amino acid sequences information alone. The overall success rate by iDNA-Prot was 83.96% that was obtained via jackknife tests on a newly constructed stringent benchmark dataset in which none of the proteins included has pairwise sequence identity to any other in a same subset. In addition to achieving high success rate, the computational time for iDNA-Prot is remarkably shorter in comparison with the relevant existing predictors. Hence it is anticipated that iDNA-Prot may become a useful high throughput tool for large-scale analysis of DNA-binding proteins. As a user-friendly web-server, iDNA-Prot is freely accessible to the public at the web-site on http://icpr.jci.edu.cn/bioinfo/iDNA-Prot or http://www.jci-bioinfo.cn/iDNA-Prot. Moreover, for the convenience of the vast majority of experimental scientists, a step-by-step guide is provided on how to use the web-server to get the desired results. PMID:21935457

Evaluation of computer-aided diagnosis (CAD) software for the detection of lung nodules on multidetector row computed tomography (MDCT): JAFROC study for the improvement in radiologists' diagnostic accuracy.

PubMed

Hirose, Tomohiro; Nitta, Norihisa; Shiraishi, Junji; Nagatani, Yukihiro; Takahashi, Masashi; Murata, Kiyoshi

2008-12-01

The aim of this study was to evaluate the usefulness of computer-aided diagnosis (CAD) software for the detection of lung nodules on multidetector-row computed tomography (MDCT) in terms of improvement in radiologists' diagnostic accuracy in detecting lung nodules, using jackknife free-response receiver-operating characteristic (JAFROC) analysis. Twenty-one patients (6 without and 15 with lung nodules) were selected randomly from 120 consecutive thoracic computed tomographic examinations. The gold standard for the presence or absence of nodules in the observer study was determined by consensus of two radiologists. Six expert radiologists participated in a free-response receiver operating characteristic study for the detection of lung nodules on MDCT, in which cases were interpreted first without and then with the output of CAD software. Radiologists were asked to indicate the locations of lung nodule candidates on the monitor with their confidence ratings for the presence of lung nodules. The performance of the CAD software indicated that the sensitivity in detecting lung nodules was 71.4%, with 0.95 false-positive results per case. When radiologists used the CAD software, the average sensitivity improved from 39.5% to 81.0%, with an increase in the average number of false-positive results from 0.14 to 0.89 per case. The average figure-of-merit values for the six radiologists were 0.390 without and 0.845 with the output of the CAD software, and there was a statistically significant difference (P < .0001) using the JAFROC analysis. The CAD software for the detection of lung nodules on MDCT has the potential to assist radiologists by increasing their accuracy.

Quantitative measurement of a candidate serum biomarker peptide derived from α2-HS-glycoprotein, and a preliminary trial of multidimensional peptide analysis in females with pregnancy-induced hypertension.

PubMed

Hamamura, Kensuke; Yanagida, Mitsuaki; Ishikawa, Hitoshi; Banzai, Michio; Yoshitake, Hiroshi; Nonaka, Daisuke; Tanaka, Kenji; Sakuraba, Mayumi; Miyakuni, Yasuka; Takamori, Kenji; Nojima, Michio; Yoshida, Koyo; Fujiwara, Hiroshi; Takeda, Satoru; Araki, Yoshihiko

2018-03-01

Purpose We previously attempted to develop quantitative enzyme-linked immunosorbent assay (ELISA) systems for the PDA039/044/071 peptides, potential serum disease biomarkers (DBMs) of pregnancy-induced hypertension (PIH), primarily identified by a peptidomic approach (BLOTCHIP®-mass spectrometry (MS)). However, our methodology did not extend to PDA071 (cysteinyl α2-HS-glycoprotein 341-367 ), due to difficulty to produce a specific antibody against the peptide. The aim of the present study was to establish an alternative PDA071 quantitation system using liquid chromatography-multiple reaction monitoring (LC-MRM)/MS, to explore the potential utility of PDA071 as a DBM for PIH. Methods We tested heat/acid denaturation methods in efforts to purify serum PDA071 and developed an LC-MRM/MS method allowing for specific quantitation thereof. We measured serum PDA071 concentrations, and these results were validated including by three-dimensional (3D) plotting against PDA039 (kininogen-1 439-456 )/044 (kininogen-1 438-456 ) concentrations, followed by discriminant analysis. Results PDA071 was successfully extracted from serum using a heat denaturation method. Optimum conditions for quantitation via LC-MRM/MS were developed; the assayed serum PDA071 correlated well with the BLOTCHIP® assay values. Although the PDA071 alone did not significantly differ between patients and controls, 3D plotting of PDA039/044/071 peptide concentrations and construction of a Jackknife classification matrix were satisfactory in terms of PIH diagnostic precision. Conclusions Combination analysis using both PDA071 and PDA039/044 concentrations allowed PIH diagnostic accuracy to be attained, and our method will be valuable in future pathophysiological studies of hypertensive disorders of pregnancy.

Merging LIDAR digital terrain model with direct observed elevation points for urban flood numerical simulation

NASA Astrophysics Data System (ADS)

Arrighi, Chiara; Campo, Lorenzo

2017-04-01

In last years, the concern about the economical and lives loss due to urban floods has grown hand in hand with the numerical skills in simulating such events. The large amount of computational power needed in order to address the problem (simulating a flood in a complex terrain such as a medium-large city) is only one of the issues. Among them it is possible to consider the general lack of exhaustive observations during the event (exact extension, dynamic, water level reached in different parts of the involved area), needed for calibration and validation of the model, the need of considering the sewers effects, and the availability of a correct and precise description of the geometry of the problem. In large cities the topographic surveys are in general available with a number of points, but a complete hydraulic simulation needs a detailed description of the terrain on the whole computational domain. LIDAR surveys can achieve this goal, providing a comprehensive description of the terrain, although they often lack precision. In this work an optimal merging of these two sources of geometrical information, measured elevation points and LIDAR survey, is proposed, by taking into account the error variance of both. The procedure is applied to a flood-prone city over an area of 35 square km approximately starting with a DTM from LIDAR with a spatial resolution of 1 m, and 13000 measured points. The spatial pattern of the error (LIDAR vs points) is analysed, and the merging method is tested with a series of Jackknife procedures that take into account different densities of the available points. A discussion of the results is provided.

[Maximum entropy model versus remote sensing-based methods for extracting Oncomelania hupensis snail habitats].

PubMed

Cong-Cong, Xia; Cheng-Fang, Lu; Si, Li; Tie-Jun, Zhang; Sui-Heng, Lin; Yi, Hu; Ying, Liu; Zhi-Jie, Zhang

2016-12-02

To explore the technique of maximum entropy model for extracting Oncomelania hupensis snail habitats in Poyang Lake zone. The information of snail habitats and related environment factors collected in Poyang Lake zone were integrated to set up the maximum entropy based species model and generate snail habitats distribution map. Two Landsat 7 ETM+ remote sensing images of both wet and drought seasons in Poyang Lake zone were obtained, where the two indices of modified normalized difference water index (MNDWI) and normalized difference vegetation index (NDVI) were applied to extract snail habitats. The ROC curve, sensitivities and specificities were applied to assess their results. Furthermore, the importance of the variables for snail habitats was analyzed by using Jackknife approach. The evaluation results showed that the area under receiver operating characteristic curve (AUC) of testing data by the remote sensing-based method was only 0.56, and the sensitivity and specificity were 0.23 and 0.89 respectively. Nevertheless, those indices above-mentioned of maximum entropy model were 0.876, 0.89 and 0.74 respectively. The main concentration of snail habitats in Poyang Lake zone covered the northeast part of Yongxiu County, northwest of Yugan County, southwest of Poyang County and middle of Xinjian County, and the elevation was the most important environment variable affecting the distribution of snails, and the next was land surface temperature (LST). The maximum entropy model is more reliable and accurate than the remote sensing-based method for the sake of extracting snail habitats, which has certain guiding significance for the relevant departments to carry out measures to prevent and control high-risk snail habitats.

Comparative assessment of GIS-based methods and metrics for estimating long-term exposures to air pollution

NASA Astrophysics Data System (ADS)

Gulliver, John; de Hoogh, Kees; Fecht, Daniela; Vienneau, Danielle; Briggs, David

2011-12-01

The development of geographical information system techniques has opened up a wide array of methods for air pollution exposure assessment. The extent to which these provide reliable estimates of air pollution concentrations is nevertheless not clearly established. Nor is it clear which methods or metrics should be preferred in epidemiological studies. This paper compares the performance of ten different methods and metrics in terms of their ability to predict mean annual PM 10 concentrations across 52 monitoring sites in London, UK. Metrics analysed include indicators (distance to nearest road, traffic volume on nearest road, heavy duty vehicle (HDV) volume on nearest road, road density within 150 m, traffic volume within 150 m and HDV volume within 150 m) and four modelling approaches: based on the nearest monitoring site, kriging, dispersion modelling and land use regression (LUR). Measures were computed in a GIS, and resulting metrics calibrated and validated against monitoring data using a form of grouped jack-knife analysis. The results show that PM 10 concentrations across London show little spatial variation. As a consequence, most methods can predict the average without serious bias. Few of the approaches, however, show good correlations with monitored PM 10 concentrations, and most predict no better than a simple classification based on site type. Only land use regression reaches acceptable levels of correlation ( R2 = 0.47), though this can be improved by also including information on site type. This might therefore be taken as a recommended approach in many studies, though care is needed in developing meaningful land use regression models, and like any method they need to be validated against local data before their application as part of epidemiological studies.

Pressure injuries in elderly with acute myocardial infarction.

PubMed

Komici, Klara; Vitale, Dino F; Leosco, Dario; Mancini, Angela; Corbi, Graziamaria; Bencivenga, Leonardo; Mezzani, Alessandro; Trimarco, Bruno; Morisco, Carmine; Ferrara, Nicola; Rengo, Giuseppe

2017-01-01

To assess pressure injury (PI) incidence among patients hospitalized for acute myocardial infarction (AMI) in an intensive coronary care unit (ICCU) and to detect the impact of specific risk factors on the development of PI in this clinical setting. Prospective cohort study in ICCU setting. Patients admitted for AMI: patients mean age 67.5±11.5 years (n=165). Norton Scale, Mini Nutritional Assessment (MNA), demographic, clinical and biochemical data collected at the time of ICCU admission have been tested in a logistic model to assess the odds ratios (ORs) of PI risk development. The jackknifed area under the receiver operating characteristic curve (AUC) and the decision curve analysis have been employed to assess the additive predictive value of a factor. Twenty-seven (16.3%) patients developed PIs. An increased PI risk was associated with advanced age (OR =2.5 every 10-year increase; 95% CI =1.1-5.7), while probability of PI development was reduced in patients with higher left ventricular ejection fraction (LVEF) (OR =0.4 every 5% increase; 95% CI =0.24-0.66), MNA score (OR =0.65 every unit change; 95% CI =0.44-0.95) and Norton Scale score (OR =0.7 every unit change; 95% CI =0.57-0.88). The AUC and the decision curve analysis showed that LVEF inclusion improved the discrimination power and the clinical net benefit of the final model. Age, LVEF, Norton Scale and MNA scores have a strong and independent clinical value as predictors of in-hospital PI development in patients with AMI. This finding has the potential to improve the clinical management of patients admitted in ICCU.

A phantom-based JAFROC observer study of two CT reconstruction methods: the search for optimisation of lesion detection and effective dose

NASA Astrophysics Data System (ADS)

Thompson, John D.; Chakraborty, Dev P.; Szczepura, Katy; Vamvakas, Ioannis; Tootell, Andrew; Manning, David J.; Hogg, Peter

2015-03-01

Purpose: To investigate the dose saving potential of iterative reconstruction (IR) in a computed tomography (CT) examination of the thorax. Materials and Methods: An anthropomorphic chest phantom containing various configurations of simulated lesions (5, 8, 10 and 12mm; +100, -630 and -800 Hounsfield Units, HU) was imaged on a modern CT system over a tube current range (20, 40, 60 and 80mA). Images were reconstructed with (IR) and filtered back projection (FBP). An ATOM 701D (CIRS, Norfolk, VA) dosimetry phantom was used to measure organ dose. Effective dose was calculated. Eleven observers (15.11+/-8.75 years of experience) completed a free response study, localizing lesions in 544 single CT image slices. A modified jackknife alternative free-response receiver operating characteristic (JAFROC) analysis was completed to look for a significant effect of two factors: reconstruction method and tube current. Alpha was set at 0.05 to control the Type I error in this study. Results: For modified JAFROC analysis of reconstruction method there was no statistically significant difference in lesion detection performance between FBP and IR when figures-of-merit were averaged over tube current (F(1,10)=0.08, p = 0.789). For tube current analysis, significant differences were revealed between multiple pairs of tube current settings (F(3,10) = 16.96, p<0.001) when averaged over image reconstruction method. Conclusion: The free-response study suggests that lesion detection can be optimized at 40mA in this phantom model, a measured effective dose of 0.97mSv. In high-contrast regions the diagnostic value of IR, compared to FBP, is less clear.

[Prediction of the suitable distribution and responses to climate change of Elaeagnus mollis in Shanxi Province, China].

PubMed

Zhang, Yin Bo; Gao, Chen Hong; Qin, Hao

2018-04-01

Understanding the responses of the habitats of endangered species to climate change is of great significance for biodiversity conservation and the maintenance of the integrity of ecosystem function. In this study, the potential suitable distribution habitats of Elaeagnus mollis in Shanxi Province was simulated by the maximum entropy model, based on 73 occurrence field records and 35 environmental factors under the current climate condition. Moreover, with the Fifth Assessment Report of Intergovernmental Panel on Climate Change, the dynamics of distribution pattern was analyzed for E. mollis under different climate scenarios. The results showed that the area under the receiver operating characteristic curve (AUC) value was 0.987, indicating that the data fitted the model very well and that the prediction was highly reliable. Results from the Jackknife test showed that the main environmental variables affecting the E. mollis distribution were the precipitation seasonality, the range of annual temperature, annual mean temperature, isothermality, annual precipitation, and pH of topsoil, with the cumulative contribution reaching 94.8%. At present, the potential suitable habitats of E. mollis are mainly located in two regions, the southern of Lyuliang Mountain and Zhongtiao Mountain in Shanxi Province. Under different climate scenarios, the total suitable area of E. mollis would shrink in 2070s. In RCP 2.6 the suitable area would firstly increase and then decrease, while in RCP 4.5 and RCP 8.5 it would response sensitively and first decrease and then increase. Its spatial distribution in two suitable regions would show divergent responses to climate change. The distribution in southern Lyuliang Mountain would fluctuate slightly in latitudinal direction, while that in Zhongtiao Mountain would migrate along elevation.

Changes in the bee fauna of a German botanical garden between 1997 and 2017, attributable to climate warming, not other parameters.

PubMed

Hofmann, Michaela M; Fleischmann, Andreas; Renner, Susanne S

2018-03-14

Botanical gardens represent artificial, but stable environments. With this premise, we analyzed the Munich Botanical Garden's bee fauna in 1997/1999 and again in 2015/2017. The garden covers 20 ha, uses no bee-relevant insecticides, has a protected layout, and on three sides abuts protected areas. Outdoors, it cultivates some 10,871 species/subspecies, many suitable as pollen and nectar sources for bees. The first survey found 79 species, the second 106, or 55% of the 192 species recorded for Munich since 1990. A Jackknife estimate for the second survey suggests 115 expected species. Classifying bees according to their thermal preferences (warm habitats, cool habitats, broad preferences, or unknown) revealed that 15 warm-loving species were gained (newly found), two lost (no longer found), and 12 retained, but only one cool-loving species was gained, three lost, and none retained, which multinomial models show to be significant differences. Of the 62 retained species, 27 changed in abundance, with 18 less frequent and nine more frequent by 2017 than they had been in 1997/1999. Retention, gain, or loss were unconnected to pollen specialization and Red List status of bee species. Between 1997 and 2017, average temperatures in Munich have increased by 0.5 °C, and climate warming over the past century is the most plausible explanation for the directional increase in warm-loving and the decrease in cool-adapted species. These results highlight the potential of botanic gardens with their artificially diverse and near-pesticide-free floras as systems in which to investigate climate change per se as a possible factor in shifting insect diversity.

Characterizing informative sequence descriptors and predicting binding affinities of heterodimeric protein complexes.

PubMed

Srinivasulu, Yerukala Sathipati; Wang, Jyun-Rong; Hsu, Kai-Ti; Tsai, Ming-Ju; Charoenkwan, Phasit; Huang, Wen-Lin; Huang, Hui-Ling; Ho, Shinn-Ying

2015-01-01

Protein-protein interactions (PPIs) are involved in various biological processes, and underlying mechanism of the interactions plays a crucial role in therapeutics and protein engineering. Most machine learning approaches have been developed for predicting the binding affinity of protein-protein complexes based on structure and functional information. This work aims to predict the binding affinity of heterodimeric protein complexes from sequences only. This work proposes a support vector machine (SVM) based binding affinity classifier, called SVM-BAC, to classify heterodimeric protein complexes based on the prediction of their binding affinity. SVM-BAC identified 14 of 580 sequence descriptors (physicochemical, energetic and conformational properties of the 20 amino acids) to classify 216 heterodimeric protein complexes into low and high binding affinity. SVM-BAC yielded the training accuracy, sensitivity, specificity, AUC and test accuracy of 85.80%, 0.89, 0.83, 0.86 and 83.33%, respectively, better than existing machine learning algorithms. The 14 features and support vector regression were further used to estimate the binding affinities (Pkd) of 200 heterodimeric protein complexes. Prediction performance of a Jackknife test was the correlation coefficient of 0.34 and mean absolute error of 1.4. We further analyze three informative physicochemical properties according to their contribution to prediction performance. Results reveal that the following properties are effective in predicting the binding affinity of heterodimeric protein complexes: apparent partition energy based on buried molar fractions, relations between chemical structure and biological activity in principal component analysis IV, and normalized frequency of beta turn. The proposed sequence-based prediction method SVM-BAC uses an optimal feature selection method to identify 14 informative features to classify and predict binding affinity of heterodimeric protein complexes. The characterization

Modeling and mapping the current and future distribution of Pseudomonas syringae pv. actinidiae under climate change in China.

PubMed

Wang, Rulin; Li, Qing; He, Shisong; Liu, Yuan; Wang, Mingtian; Jiang, Gan

2018-01-01

Bacterial canker of kiwifruit caused by Pseudomonas syringae pv. actinidiae (Psa) is a major threat to the kiwifruit industry throughout the world and accounts for substantial economic losses in China. The aim of the present study was to test and explore the possibility of using MaxEnt (maximum entropy models) to predict and analyze the future large-scale distribution of Psa in China. Based on the current environmental factors, three future climate scenarios, which were suggested by the fifth IPCC report, and the current distribution sites of Psa, MaxEnt combined with ArcGIS was applied to predict the potential suitable areas and the changing trend of Psa in China. The jackknife test and correlation analysis were used to choose dominant climatic factors. The receiver operating characteristic curve (ROC) drawn by MaxEnt was used to evaluate the accuracy of the simulation. The results showed that under current climatic conditions, the area from latitude 25° to 36°N and from longitude 101° to 122°E is the primary potential suitable area of Psa in China. The highly suitable area (with suitability between 66 and 100) was mainly concentrated in Northeast Sichuan, South Shaanxi, most of Chongqing, West Hubei and Southwest Gansu and occupied 4.94% of land in China. Under different future emission scenarios, both the areas and the centers of the suitable areas all showed differences compared with the current situation. Four climatic variables, i.e., maximum April temperature (19%), mean temperature of the coldest quarter (14%), precipitation in May (11.5%) and minimum temperature in October (10.8%), had the largest impact on the distribution of Psa. The MaxEnt model is potentially useful for forecasting the future adaptive distribution of Psa under climate change, and it provides important guidance for comprehensive management.

Predicting protein subnuclear location with optimized evidence-theoretic K-nearest classifier and pseudo amino acid composition.

PubMed

Shen, Hong-Bin; Chou, Kuo-Chen

2005-11-25

The nucleus is the brain of eukaryotic cells that guides the life processes of the cell by issuing key instructions. For in-depth understanding of the biochemical process of the nucleus, the knowledge of localization of nuclear proteins is very important. With the avalanche of protein sequences generated in the post-genomic era, it is highly desired to develop an automated method for fast annotating the subnuclear locations for numerous newly found nuclear protein sequences so as to be able to timely utilize them for basic research and drug discovery. In view of this, a novel approach is developed for predicting the protein subnuclear location. It is featured by introducing a powerful classifier, the optimized evidence-theoretic K-nearest classifier, and using the pseudo amino acid composition [K.C. Chou, PROTEINS: Structure, Function, and Genetics, 43 (2001) 246], which can incorporate a considerable amount of sequence-order effects, to represent protein samples. As a demonstration, identifications were performed for 370 nuclear proteins among the following 9 subnuclear locations: (1) Cajal body, (2) chromatin, (3) heterochromatin, (4) nuclear diffuse, (5) nuclear pore, (6) nuclear speckle, (7) nucleolus, (8) PcG body, and (9) PML body. The overall success rates thus obtained by both the re-substitution test and jackknife cross-validation test are significantly higher than those by existing classifiers on the same working dataset. It is anticipated that the powerful approach may also become a useful high throughput vehicle to bridge the huge gap occurring in the post-genomic era between the number of gene sequences in databases and the number of gene products that have been functionally characterized. The OET-KNN classifier will be available at www.pami.sjtu.edu.cn/people/hbshen.

Phylogenetic studies favour the unification of Pennisetum, Cenchrus and Odontelytrum (Poaceae): a combined nuclear, plastid and morphological analysis, and nomenclatural combinations in Cenchrus.

PubMed

Chemisquy, M Amelia; Giussani, Liliana M; Scataglini, María A; Kellogg, Elizabeth A; Morrone, Osvaldo

2010-07-01

Twenty-five genera having sterile inflorescence branches were recognized as the bristle clade within the x = 9 Paniceae (Panicoideae). Within the bristle clade, taxonomic circumscription of Cenchrus (20-25 species), Pennisetum (80-140) and the monotypic Odontelytrum is still unclear. Several criteria have been applied to characterize Cenchrus and Pennisetum, but none of these has proved satisfactory as the diagnostic characters, such as fusion of bristles in the inflorescences, show continuous variation. A phylogenetic analysis based on morphological, plastid (trnL-F, ndhF) and nuclear (knotted) data is presented for a representative species sampling of the genera. All analyses were conducted under parsimony, using heuristic searches with TBR branch swapping. Branch support was assessed with parsimony jackknifing. Based on plastid and morphological data, Pennisetum, Cenchrus and Odontelytrum were supported as a monophyletic group: the PCO clade. Only one section of Pennisetum (Brevivalvula) was supported as monophyletic. The position of P. lanatum differed among data partitions, although the combined plastid and morphology and nuclear analyses showed this species to be a member of the PCO clade. The basic chromosome number x = 9 was found to be plesiomorphic, and x = 5, 7, 8, 10 and 17 were derived states. The nuclear phylogenetic analysis revealed a reticulate pattern of relationships among Pennisetum and Cenchrus, suggesting that there are at least three different genomes. Because apomixis can be transferred among species through hybridization, its history most likely reflects crossing relationships, rather than multiple independent appearances. Due to the consistency between the present results and different phylogenetic hypotheses (including morphological, developmental and multilocus approaches), and the high support found for the PCO clade, also including the type species of the three genera, we propose unification of Pennisetum, Cenchrus and Odontelytrum

Phylogenetic diversity and ecological pattern of ammonia-oxidizing archaea in the surface sediments of the western Pacific.

PubMed

Cao, Huiluo; Hong, Yiguo; Li, Meng; Gu, Ji-Dong

2011-11-01

The phylogenetic diversity of ammonia-oxidizing archaea (AOA) was surveyed in the surface sediments from the northern part of the South China Sea (SCS). The distribution pattern of AOA in the western Pacific was discussed through comparing the SCS with other areas in the western Pacific including Changjiang Estuary and the adjacent East China Sea where high input of anthropogenic nitrogen was evident, the tropical West Pacific Continental Margins close to the Philippines, the deep-sea methane seep sediments in the Okhotsk Sea, the cold deep sea of Northeastern Japan Sea, and the hydrothermal field in the Southern Okinawa Trough. These various environments provide a wide spectrum of physical and chemical conditions for a better understanding of the distribution pattern and diversities of AOA in the western Pacific. Under these different conditions, the distinct community composition between shallow and deep-sea sediments was clearly delineated based on the UniFrac PCoA and Jackknife Environmental Cluster analyses. Phylogenetic analyses showed that a few ammonia-oxidizing archaeal subclades in the marine water column/sediment clade and endemic lineages were indicative phylotypes for some environments. Higher phylogenetic diversity was observed in the Philippines while lower diversity in the hydrothermal vent habitat. Water depth and possibly with other environmental factors could be the main driving forces to shape the phylogenetic diversity of AOA observed, not only in the SCS but also in the whole western Pacific. The multivariate regression tree analysis also supported this observation consistently. Moreover, the functions of current and other climate factors were also discussed in comparison of phylogenetic diversity. The information collectively provides important insights into the ecophysiological requirements of uncultured ammonia-oxidizing archaeal lineages in the western Pacific Ocean.

Detectability of BI-RADS category 3 or higher breast lesions and reading time on mammography: comparison between 5-MP and 8-MP LCD monitors.

PubMed

Yabuuchi, Hidetake; Kawanami, Satoshi; Kamitani, Takeshi; Matsumura, Tomomi; Yamasaki, Yuzo; Morishita, Junji; Honda, Hiroshi

2017-04-01

Background Five-megapixel (MP) displays are recommended as soft copy devices for digital mammogram. An 8-MP liquid crystal display (LCD) (two 4-MP displays within one display) might offer the advantage of being able to view biplane mammography more easily than the dual planes of 5-MP LCDs. Purpose To compare detectability of Breast Imaging Reporting and Data System (BI-RADS) category 3 or higher lesions and reading time on mammography between 5- MP and 8-MP LCDs. Material and Methods The mammograms of 240 breasts of 120 patients including 60 breasts with BI-RADS category 3 or higher lesions and 180 breasts with normal or category 2 lesions were enrolled. All bilateral mammograms were displayed on bifacial 5-MP LCDs or an 8-MP LCD (two 4-MP displays within one display). Six radiologists assessed 240 breasts on each display. The observations were analyzed using receiver operating characteristic (ROC) analysis. A jack-knife method was used for statistical analysis. We employed a paired t-test to determine whether any significant differences existed in the reading time between two different displays. A P value < 0.05 was considered significant. Results The mean areas under the ROC curve obtained using 5-MP and 8-MP LCDs were 0.925 and 0.915, respectively, and there was no significant difference ( P = 0.46). There was also no significant difference in the reading time between two types of displays (57.8 min. vs. 51.5 min, P = 0.39). Conclusion The detectability of BI-RADS category 3 or higher lesions and reading time using an 8-MP LCD were comparable to those using a 5-MP LCD.

Neurophysiological differences between patients clinically at high risk for schizophrenia and neurotypical controls--first steps in development of a biomarker.

PubMed

Duffy, Frank H; D'Angelo, Eugene; Rotenberg, Alexander; Gonzalez-Heydrich, Joseph

2015-11-02

Schizophrenia is a severe, disabling and prevalent mental disorder without cure and with a variable, incomplete pharmacotherapeutic response. Prior to onset in adolescence or young adulthood a prodromal period of abnormal symptoms lasting weeks to years has been identified and operationalized as clinically high risk (CHR) for schizophrenia. However, only a minority of subjects prospectively identified with CHR convert to schizophrenia, thereby limiting enthusiasm for early intervention(s). This study utilized objective resting electroencephalogram (EEG) quantification to determine whether CHR constitutes a cohesive entity and an evoked potential to assess CHR cortical auditory processing. This study constitutes an EEG-based quantitative neurophysiological comparison between two unmedicated subject groups: 35 neurotypical controls (CON) and 22 CHR patients. After artifact management, principal component analysis (PCA) identified EEG spectral and spectral coherence factors described by associated loading patterns. Discriminant function analysis (DFA) determined factors' discrimination success between subjects in the CON and CHR groups. Loading patterns on DFA-selected factors described CHR-specific spectral and coherence differences when compared to controls. The frequency modulated auditory evoked response (FMAER) explored functional CON-CHR differences within the superior temporal gyri. Variable reduction by PCA identified 40 coherence-based factors explaining 77.8% of the total variance and 40 spectral factors explaining 95.9% of the variance. DFA demonstrated significant CON-CHR group difference (P <0.00001) and successful jackknifed subject classification (CON, 85.7%; CHR, 86.4% correct). The population distribution plotted along the canonical discriminant variable was clearly bimodal. Coherence factors delineated loading patterns of altered connectivity primarily involving the bilateral posterior temporal electrodes. However, FMAER analysis showed no CON

"iSS-Hyb-mRMR": Identification of splicing sites using hybrid space of pseudo trinucleotide and pseudo tetranucleotide composition.

PubMed

Iqbal, Muhammad; Hayat, Maqsood

2016-05-01

Gene splicing is a vital source of protein diversity. Perfectly eradication of introns and joining exons is the prominent task in eukaryotic gene expression, as exons are usually interrupted by introns. Identification of splicing sites through experimental techniques is complicated and time-consuming task. With the avalanche of genome sequences generated in the post genomic age, it remains a complicated and challenging task to develop an automatic, robust and reliable computational method for fast and effective identification of splicing sites. In this study, a hybrid model "iSS-Hyb-mRMR" is proposed for quickly and accurately identification of splicing sites. Two sample representation methods namely; pseudo trinucleotide composition (PseTNC) and pseudo tetranucleotide composition (PseTetraNC) were used to extract numerical descriptors from DNA sequences. Hybrid model was developed by concatenating PseTNC and PseTetraNC. In order to select high discriminative features, minimum redundancy maximum relevance algorithm was applied on the hybrid feature space. The performance of these feature representation methods was tested using various classification algorithms including K-nearest neighbor, probabilistic neural network, general regression neural network, and fitting network. Jackknife test was used for evaluation of its performance on two benchmark datasets S1 and S2, respectively. The predictor, proposed in the current study achieved an accuracy of 93.26%, sensitivity of 88.77%, and specificity of 97.78% for S1, and the accuracy of 94.12%, sensitivity of 87.14%, and specificity of 98.64% for S2, respectively. It is observed, that the performance of proposed model is higher than the existing methods in the literature so for; and will be fruitful in the mechanism of RNA splicing, and other research academia. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

[Analytic methods for seed models with genotype x environment interactions].

PubMed

Zhu, J

1996-01-01

Genetic models with genotype effect (G) and genotype x environment interaction effect (GE) are proposed for analyzing generation means of seed quantitative traits in crops. The total genetic effect (G) is partitioned into seed direct genetic effect (G0), cytoplasm genetic of effect (C), and maternal plant genetic effect (Gm). Seed direct genetic effect (G0) can be further partitioned into direct additive (A) and direct dominance (D) genetic components. Maternal genetic effect (Gm) can also be partitioned into maternal additive (Am) and maternal dominance (Dm) genetic components. The total genotype x environment interaction effect (GE) can also be partitioned into direct genetic by environment interaction effect (G0E), cytoplasm genetic by environment interaction effect (CE), and maternal genetic by environment interaction effect (GmE). G0E can be partitioned into direct additive by environment interaction (AE) and direct dominance by environment interaction (DE) genetic components. GmE can also be partitioned into maternal additive by environment interaction (AmE) and maternal dominance by environment interaction (DmE) genetic components. Partitions of genetic components are listed for parent, F1, F2 and backcrosses. A set of parents, their reciprocal F1 and F2 seeds is applicable for efficient analysis of seed quantitative traits. MINQUE(0/1) method can be used for estimating variance and covariance components. Unbiased estimation for covariance components between two traits can also be obtained by the MINQUE(0/1) method. Random genetic effects in seed models are predictable by the Adjusted Unbiased Prediction (AUP) approach with MINQUE(0/1) method. The jackknife procedure is suggested for estimation of sampling variances of estimated variance and covariance components and of predicted genetic effects, which can be further used in a t-test for parameter. Unbiasedness and efficiency for estimating variance components and predicting genetic effects are tested by

Functional magnetic resonance imaging in a low-field intraoperative scanner.

PubMed

Schulder, Michael; Azmi, Hooman; Biswal, Bharat

2003-01-01

Functional magnetic resonance imaging (fMRI) has been used for preoperative planning and intraoperative surgical navigation. However, most experience to date has been with preoperative images acquired on high-field echoplanar MRI units. We explored the feasibility of acquiring fMRI of the motor cortex with a dedicated low-field intraoperative MRI (iMRI). Five healthy volunteers were scanned with the 0.12-tesla PoleStar N-10 iMRI (Odin Medical Technologies, Israel). A finger-tapping motor paradigm was performed with sequential scans, acquired alternately at rest and during activity. In addition, scans were obtained during breath holding alternating with normal breathing. The same paradigms were repeated using a 3-tesla MRI (Siemens Corp., Allandale, N.J., USA). Statistical analysis was performed offline using cross-correlation and cluster techniques. Data were resampled using the 'jackknife' process. The location, number of activated voxels and degrees of statistical significance between the two scanners were compared. With both the 0.12- and 3-tesla imagers, motor cortex activation was seen in all subjects to a significance of p < 0.02 or greater. No clustered pixels were seen outside the sensorimotor cortex. The resampled correlation coefficients were normally distributed, with a mean of 0.56 for both the 0.12- and 3-tesla scanners (standard deviations 0.11 and 0.08, respectively). The breath holding paradigm confirmed that the expected diffuse activation was seen on 0.12- and 3-tesla scans. Accurate fMRI with a low-field iMRI is feasible. Such data could be acquired immediately before or even during surgery. This would increase the utility of iMRI and allow for updated intraoperative functional imaging, free of the limitations of brain shift. Copyright 2003 S. Karger AG, Basel

Understanding Spatial and Temporal Variations of Arctic Circulation Using Oxygen Isotopes of Seawater

NASA Astrophysics Data System (ADS)

Yin, L.; Kopans-Johnson, C. R.; LeGrande, A. N.; Kelly, S.

2015-12-01

The isotopic ratio of 18O to 16O in seawater (2005ppm in ocean water is defined as 𝛿18Oseawater≡0 permil or 0‰) is a fundamental ocean tracer due to its distinct linear relationship with salinity(𝛿18O -S) from regional inland freshwater sources. As opposed to salinity alone, 𝛿18O distinguishes river runoff from sea-ice melt and traces ocean circulation pathways from coastal to open waters and surface to deep waters. Observations from the past 60 years of 𝛿18O seawater were compiled into a database by Schimdt et al. (1999), and subsequently used to calculate a 3-dimensional 1°x1° 𝛿18O global gridded dataset by LeGrande and Schmidt (2006). Although the Schmidt et al. (1999) Global Seawater Oxygen-18 Database (𝛿18Oobs) contains 25,514 measurements used to calculate the global gridded dataset, LeGrande and Schmidt (2006) point out that, "data coverage varies greatly from region to region," with seasonal variability creating biases in areas where sea ice is present. Python Pandas is used to automate the addition of 2,942 records to the Schmidt et al. (1999) Global Seawater Oxygen-18 Database (𝛿18Oobs), and examine the spatial and temporal distributions of 18O in the Arctic Ocean. 10 initial water masses are defined using spatial and temporal trends, clusters of observations, and Arctic surface circulation. Jackknife slope analysis of water mass 𝛿18O -S is used to determine anomalous data points and regional hydrology, resulting in 4 distinct Arctic water masses. These techniques are used to improve the gridded 𝛿18Oseawater dataset by distinguishing unique water masses, and accounting for seasonal variability of complex high latitude areas.

Critical determinants of the epilepsy treatment gap: a cross-national analysis in resource-limited settings

PubMed Central

Meyer, Ana-Claire L.; Dua, Tarun; Boscardin, John; Escarce, José J.; Saxena, Shekhar; Birbeck, Gretchen L.

2013-01-01

Purpose Epilepsy is one of the most common serious neurological disorders worldwide. Our objective was to determine which economic, healthcare, neurology and epilepsy specific resources were associated with untreated epilepsy in resource-constrained settings. Methods A systematic review of the literature identified community-based studies in resource-constrained settings that calculated the epilepsy treatment gap, the proportion with untreated epilepsy, from prevalent active epilepsy cases. Economic, healthcare, neurology and epilepsy specific resources were taken from existing datasets. Poisson regression models with jackknifed standard errors were used to create bivariate and multivariate models comparing the association between treatment status and economic and health resource indicators. Relative risks were reported. Key Findings Forty-seven studies of 8285 individuals from 24 countries met inclusion criteria. Bivariate analysis demonstrated that individuals residing in rural locations had significantly higher risks of untreated epilepsy [Relative Risk(RR)=1.63; 95% confidence interval(CI):1.26,2.11]. Significantly lower risks of untreated epilepsy were observed for higher physician density [RR=0.65, 95% CI:0.55,0.78], presence of a lay [RR=0.74, 95%CI:0.60,0.91] or professional association for epilepsy [RR=0.73, 95%CI:0.59,0.91], or post-graduate neurology training program [RR=0.67, 95%CI:0.55, 0.82]. In multivariate models, higher physician density maintained significant effects [RR=0.67; 95%CI:0.52,0.88]. Significance Even among resource-limited regions, people with epilepsy in countries with fewer economic, healthcare, neurology and epilepsy specific resources are more likely to have untreated epilepsy. Community-based epilepsy care programs have improved access to treatment but in order to decrease the epilepsy treatment gap, poverty and inequalities of healthcare, neurological and epilepsy resources must be dealt with at the local, national, and global

Technical efficiency of women's health prevention programs in Bucaramanga, Colombia: a four-stage analysis.

PubMed

Ruiz-Rodriguez, Myriam; Rodriguez-Villamizar, Laura A; Heredia-Pi, Ileana

2016-10-13

Primary Health Care (PHC) is an efficient strategy to improve health outcomes in populations. Nevertheless, studies of technical efficiency in health care have focused on hospitals, with very little on primary health care centers. The objective of the present study was to use the Data Envelopment Analysis to estimate the technical efficiency of three women's health promotion and disease prevention programs offered by primary care centers in Bucaramanga, Colombia. Efficiency was measured using a four-stage data envelopment analysis with a series of Tobit regressions to account for the effect of quality outcomes and context variables. Input/output information was collected from the institutions' records, chart reviews and personal interviews. Information about contextual variables was obtained from databases from the primary health program in the municipality. A jackknife analysis was used to assess the robustness of the results. The analysis was based on data from 21 public primary health care centers. The average efficiency scores, after adjusting for quality and context, were 92.4 %, 97.5 % and 86.2 % for the antenatal care (ANC), early detection of cervical cancer (EDCC) and family planning (FP) programs, respectively. On each program, 12 of the 21 (57.1 %) health centers were found to be technically efficient; having had the best-practice frontiers. Adjusting for context variables changed the scores and reference rankings of the three programs offered by the health centers. The performance of the women's health prevention programs offered by the centers was found to be heterogeneous. Adjusting for context and health care quality variables had a significant effect on the technical efficiency scores and ranking. The results can serve as a guide to strengthen management and organizational and planning processes related to local primary care services operating within a market-based model such as the one in Colombia.

The osmotic tolerance of boar spermatozoa and its usefulness as sperm quality parameter.

PubMed

Yeste, Marc; Briz, Mailo; Pinart, Elisabeth; Sancho, Sílvia; Bussalleu, Eva; Bonet, Sergi

2010-06-01

Predicting the fertility outcome of ejaculates is very important in the field of porcine reproduction. The aims of this study were to determine the effects of different osmotic treatments on boar spermatozoa and to correlate them with fertility and prolificacy, assessed as non-return rates within 60 days (NRR(60d)) of the first inseminations, and litter size (LS), respectively. Sperm samples (n=100) from one hundred healthy Piétrain boars were used to assess 48 treatments combining different osmolalities (ranged between 100 and 4000 mOsm kg(-1)), different compounds used to prepare anisotonic solutions, and two different modalities: return and non-return to isotonic conditions. Sperm quality was evaluated before and after applying the treatments on the basis of analyses of sperm viability, motility, morphology and percentages of acrosome-intact spermatozoa. Statistical analyses were performed using a one-way ANOVA and post hoc Tukey's test, linear regression analyses (Pearson correlation and multiple regression) and Jackknife cross-validation. Although three conventional parameters: sperm viability, sperm morphology and the percentages of acrosome-intact spermatozoa were significantly correlated with NRR(60d) and with LS, their respective osmotic tolerance parameters (defined for each parameter and treatment regarding with negative control) presented a higher Pearson coefficient with both fertility and prolificacy in three treatments (150 mOsm kg(-1) with non-return to isotonic conditions, 200 mOsm kg(-1) with return and 500 mOsm kg(-1) using sodium citrate and non-return to isotonic conditions). We conclude that osmotic resistance in sperm viability, sperm morphology and acrosome-intactness in the treatments mentioned above could be assessed along with classical parameters to better predict the fertilising ability of a given ejaculate. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Vibrational Markovian modelling of footprints after the interaction of antibiotics with the packaging region of HIV type 1.

PubMed

Díaz, Humberto González; de Armas, Ronal Ramos; Molina, Reinaldo

2003-11-01

The design of novel anti-HIV compounds has now become a crucial area for scientists working in numerous interrelated fields of science such as molecular biology, medicinal chemistry, mathematical biology, molecular modelling and bioinformatics. In this context, the development of simple but physically meaningful mathematical models to represent the interaction between anti-HIV drugs and their biological targets is of major interest. One such area currently under investigation involves the targets in the HIV-RNA-packaging region. In the work described here, we applied Markov chain theory in an attempt to describe the interaction between the antibiotic paromomycin and the packaging region of the RNA in Type-1 HIV. In this model, a nucleic acid squeezed graph is used. The vertices of the graph represent the nucleotides while the edges are the phosphodiester bonds. A stochastic (Markovian) matrix was subsequently defined on this graph, an operation that codifies the probabilities of interaction between specific nucleotides of HIV-RNA and the antibiotic. The strength of these local interactions can be calculated through an inelastic vibrational model. The successive power of this matrix codifies the probabilities with which the vibrations after drug-RNA interactions vanish along the polynucleotide main chain. The sums of self-return probabilities in the k-vicinity of each nucleotide represent physically meaningful descriptors. A linear discriminant function was developed and gave rise to excellent discrimination in 80.8% of interacting and footprinted nucleotides. The Jackknife method was employed to assess the stability and predictability of the model. On the other hand, a linear regression model predicted the local binding affinity constants between a specific nucleotide and the antibiotic (R(2)=0.91, Q(2)=0.86). These kinds of models could play an important role either in the discovery of new anti-HIV compounds or the study of their mode of action.

Markovian negentropies in bioinformatics. 1. A picture of footprints after the interaction of the HIV-1 Psi-RNA packaging region with drugs.

PubMed

Díaz, Humberto González; de Armas, Ronal Ramos; Molina, Reinaldo

2003-11-01

Many experts worldwide have highlighted the potential of RNA molecules as drug targets for the chemotherapeutic treatment of a range of diseases. In particular, the molecular pockets of RNA in the HIV-1 packaging region have been postulated as promising sites for antiviral action. The discovery of simpler methods to accurately represent drug-RNA interactions could therefore become an interesting and rapid way to generate models that are complementary to docking-based systems. The entropies of a vibrational Markov chain have been introduced here as physically meaningful descriptors for the local drug-nucleic acid complexes. A study of the interaction of the antibiotic Paromomycin with the packaging region of the RNA present in type-1 HIV has been carried out as an illustrative example of this approach. A linear discriminant function gave rise to excellent discrimination among 80.13% of interacting/non-interacting sites. More specifically, the model classified 36/45 nucleotides (80.0%) that interacted with paromomycin and, in addition, 85/106 (80.2%) footprinted (non-interacting) sites from the RNA viral sequence were recognized. The model showed a high Matthews' regression coefficient (C = 0.64). The Jackknife method was also used to assess the stability and predictability of the model by leaving out adenines, C, G, or U. Matthews' coefficients and overall accuracies for these approaches were between 0.55 and 0.68 and 75.8 and 82.7, respectively. On the other hand, a linear regression model predicted the local binding affinity constants between a specific nucleotide and the aforementioned antibiotic (R2 = 0.83,Q2 = 0.825). These kinds of models may play an important role either in the discovery of new anti-HIV compounds or in the elucidation of their mode of action. On request from the corresponding author (humbertogd@cbq.uclv.edu.cu or humbertogd@navegalia.com).

Making Mosquito Taxonomy Useful: A Stable Classification of Tribe Aedini that Balances Utility with Current Knowledge of Evolutionary Relationships.

PubMed

Wilkerson, Richard C; Linton, Yvonne-Marie; Fonseca, Dina M; Schultz, Ted R; Price, Dana C; Strickman, Daniel A

2015-01-01

The tribe Aedini (Family Culicidae) contains approximately one-quarter of the known species of mosquitoes, including vectors of deadly or debilitating disease agents. This tribe contains the genus Aedes, which is one of the three most familiar genera of mosquitoes. During the past decade, Aedini has been the focus of a series of extensive morphology-based phylogenetic studies published by Reinert, Harbach, and Kitching (RH&K). Those authors created 74 new, elevated or resurrected genera from what had been the single genus Aedes, almost tripling the number of genera in the entire family Culicidae. The proposed classification is based on subjective assessments of the "number and nature of the characters that support the branches" subtending particular monophyletic groups in the results of cladistic analyses of a large set of morphological characters of representative species. To gauge the stability of RH&K's generic groupings we reanalyzed their data with unweighted parsimony jackknife and maximum-parsimony analyses, with and without ordering 14 of the characters as in RH&K. We found that their phylogeny was largely weakly supported and their taxonomic rankings failed priority and other useful taxon-naming criteria. Consequently, we propose simplified aedine generic designations that 1) restore a classification system that is useful for the operational community; 2) enhance the ability of taxonomists to accurately place new species into genera; 3) maintain the progress toward a natural classification based on monophyletic groups of species; and 4) correct the current classification system that is subject to instability as new species are described and existing species more thoroughly defined. We do not challenge the phylogenetic hypotheses generated by the above-mentioned series of morphological studies. However, we reduce the ranks of the genera and subgenera of RH&K to subgenera or informal species groups, respectively, to preserve stability as new data become

Reliability of Different Mark-Recapture Methods for Population Size Estimation Tested against Reference Population Sizes Constructed from Field Data

PubMed Central

Grimm, Annegret; Gruber, Bernd; Henle, Klaus

2014-01-01

Reliable estimates of population size are fundamental in many ecological studies and biodiversity conservation. Selecting appropriate methods to estimate abundance is often very difficult, especially if data are scarce. Most studies concerning the reliability of different estimators used simulation data based on assumptions about capture variability that do not necessarily reflect conditions in natural populations. Here, we used data from an intensively studied closed population of the arboreal gecko Gehyra variegata to construct reference population sizes for assessing twelve different population size estimators in terms of bias, precision, accuracy, and their 95%-confidence intervals. Two of the reference populations reflect natural biological entities, whereas the other reference populations reflect artificial subsets of the population. Since individual heterogeneity was assumed, we tested modifications of the Lincoln-Petersen estimator, a set of models in programs MARK and CARE-2, and a truncated geometric distribution. Ranking of methods was similar across criteria. Models accounting for individual heterogeneity performed best in all assessment criteria. For populations from heterogeneous habitats without obvious covariates explaining individual heterogeneity, we recommend using the moment estimator or the interpolated jackknife estimator (both implemented in CAPTURE/MARK). If data for capture frequencies are substantial, we recommend the sample coverage or the estimating equation (both models implemented in CARE-2). Depending on the distribution of catchabilities, our proposed multiple Lincoln-Petersen and a truncated geometric distribution obtained comparably good results. The former usually resulted in a minimum population size and the latter can be recommended when there is a long tail of low capture probabilities. Models with covariates and mixture models performed poorly. Our approach identified suitable methods and extended options to evaluate the

Historical extension of operational NDVI products for livestock insurance in Kenya

NASA Astrophysics Data System (ADS)

Vrieling, Anton; Meroni, Michele; Shee, Apurba; Mude, Andrew G.; Woodard, Joshua; de Bie, C. A. J. M. (Kees); Rembold, Felix

2014-05-01

Droughts induce livestock losses that severely affect Kenyan pastoralists. Recent index insurance schemes have the potential of being a viable tool for insuring pastoralists against drought-related risk. Such schemes require as input a forage scarcity (or drought) index that can be reliably updated in near real-time, and that strongly relates to livestock mortality. Generally, a long record (>25 years) of the index is needed to correctly estimate mortality risk and calculate the related insurance premium. Data from current operational satellites used for large-scale vegetation monitoring span over a maximum of 15 years, a time period that is considered insufficient for accurate premium computation. This study examines how operational NDVI datasets compare to, and could be combined with the non-operational recently constructed 30-year GIMMS AVHRR record (1981-2011) to provide a near-real time drought index with a long term archive for the arid lands of Kenya. We compared six freely available, near-real time NDVI products: five from MODIS and one from SPOT-VEGETATION. Prior to comparison, all datasets were averaged in time for the two vegetative seasons in Kenya, and aggregated spatially at the administrative division level at which the insurance is offered. The feasibility of extending the resulting aggregated drought indices back in time was assessed using jackknifed R2 statistics (leave-one-year-out) for the overlapping period 2002-2011. We found that division-specific models were more effective than a global model for linking the division-level temporal variability of the index between NDVI products. Based on our results, good scope exists for historically extending the aggregated drought index, thus providing a longer operational record for insurance purposes. We showed that this extension may have large effects on the calculated insurance premium. Finally, we discuss several possible improvements to the drought index.

Making Mosquito Taxonomy Useful: A Stable Classification of Tribe Aedini that Balances Utility with Current Knowledge of Evolutionary Relationships

PubMed Central

Wilkerson, Richard C.; Linton, Yvonne-Marie; Fonseca, Dina M.; Schultz, Ted R.; Price, Dana C.; Strickman, Daniel A.

2015-01-01

The tribe Aedini (Family Culicidae) contains approximately one-quarter of the known species of mosquitoes, including vectors of deadly or debilitating disease agents. This tribe contains the genus Aedes, which is one of the three most familiar genera of mosquitoes. During the past decade, Aedini has been the focus of a series of extensive morphology-based phylogenetic studies published by Reinert, Harbach, and Kitching (RH&K). Those authors created 74 new, elevated or resurrected genera from what had been the single genus Aedes, almost tripling the number of genera in the entire family Culicidae. The proposed classification is based on subjective assessments of the “number and nature of the characters that support the branches” subtending particular monophyletic groups in the results of cladistic analyses of a large set of morphological characters of representative species. To gauge the stability of RH&K’s generic groupings we reanalyzed their data with unweighted parsimony jackknife and maximum-parsimony analyses, with and without ordering 14 of the characters as in RH&K. We found that their phylogeny was largely weakly supported and their taxonomic rankings failed priority and other useful taxon-naming criteria. Consequently, we propose simplified aedine generic designations that 1) restore a classification system that is useful for the operational community; 2) enhance the ability of taxonomists to accurately place new species into genera; 3) maintain the progress toward a natural classification based on monophyletic groups of species; and 4) correct the current classification system that is subject to instability as new species are described and existing species more thoroughly defined. We do not challenge the phylogenetic hypotheses generated by the above-mentioned series of morphological studies. However, we reduce the ranks of the genera and subgenera of RH&K to subgenera or informal species groups, respectively, to preserve stability as new data

Evaluation of a cosmic-ray neutron sensor network for improved land surface model prediction

NASA Astrophysics Data System (ADS)

Baatz, Roland; Hendricks Franssen, Harrie-Jan; Han, Xujun; Hoar, Tim; Reemt Bogena, Heye; Vereecken, Harry

2017-05-01

In situ soil moisture sensors provide highly accurate but very local soil moisture measurements, while remotely sensed soil moisture is strongly affected by vegetation and surface roughness. In contrast, cosmic-ray neutron sensors (CRNSs) allow highly accurate soil moisture estimation on the field scale which could be valuable to improve land surface model predictions. In this study, the potential of a network of CRNSs installed in the 2354 km2 Rur catchment (Germany) for estimating soil hydraulic parameters and improving soil moisture states was tested. Data measured by the CRNSs were assimilated with the local ensemble transform Kalman filter in the Community Land Model version 4.5. Data of four, eight and nine CRNSs were assimilated for the years 2011 and 2012 (with and without soil hydraulic parameter estimation), followed by a verification year 2013 without data assimilation. This was done using (i) a regional high-resolution soil map, (ii) the FAO soil map and (iii) an erroneous, biased soil map as input information for the simulations. For the regional soil map, soil moisture characterization was only improved in the assimilation period but not in the verification period. For the FAO soil map and the biased soil map, soil moisture predictions improved strongly to a root mean square error of 0.03 cm3 cm-3 for the assimilation period and 0.05 cm3 cm-3 for the evaluation period. Improvements were limited by the measurement error of CRNSs (0.03 cm3 cm-3). The positive results obtained with data assimilation of nine CRNSs were confirmed by the jackknife experiments with four and eight CRNSs used for assimilation. The results demonstrate that assimilated data of a CRNS network can improve the characterization of soil moisture content on the catchment scale by updating spatially distributed soil hydraulic parameters of a land surface model.

Mathematical Modeling of Intestinal Iron Absorption Using Genetic Programming

PubMed Central

Colins, Andrea; Gerdtzen, Ziomara P.; Nuñez, Marco T.; Salgado, J. Cristian

2017-01-01

Iron is a trace metal, key for the development of living organisms. Its absorption process is complex and highly regulated at the transcriptional, translational and systemic levels. Recently, the internalization of the DMT1 transporter has been proposed as an additional regulatory mechanism at the intestinal level, associated to the mucosal block phenomenon. The short-term effect of iron exposure in apical uptake and initial absorption rates was studied in Caco-2 cells at different apical iron concentrations, using both an experimental approach and a mathematical modeling framework. This is the first report of short-term studies for this system. A non-linear behavior in the apical uptake dynamics was observed, which does not follow the classic saturation dynamics of traditional biochemical models. We propose a method for developing mathematical models for complex systems, based on a genetic programming algorithm. The algorithm is aimed at obtaining models with a high predictive capacity, and considers an additional parameter fitting stage and an additional Jackknife stage for estimating the generalization error. We developed a model for the iron uptake system with a higher predictive capacity than classic biochemical models. This was observed both with the apical uptake dataset used for generating the model and with an independent initial rates dataset used to test the predictive capacity of the model. The model obtained is a function of time and the initial apical iron concentration, with a linear component that captures the global tendency of the system, and a non-linear component that can be associated to the movement of DMT1 transporters. The model presented in this paper allows the detailed analysis, interpretation of experimental data, and identification of key relevant components for this complex biological process. This general method holds great potential for application to the elucidation of biological mechanisms and their key components in other complex

Computer-aided detection of brain metastasis on 3D MR imaging: Observer performance study.

PubMed

Sunwoo, Leonard; Kim, Young Jae; Choi, Seung Hong; Kim, Kwang-Gi; Kang, Ji Hee; Kang, Yeonah; Bae, Yun Jung; Yoo, Roh-Eul; Kim, Jihang; Lee, Kyong Joon; Lee, Seung Hyun; Choi, Byung Se; Jung, Cheolkyu; Sohn, Chul-Ho; Kim, Jae Hyoung

2017-01-01

To assess the effect of computer-aided detection (CAD) of brain metastasis (BM) on radiologists' diagnostic performance in interpreting three-dimensional brain magnetic resonance (MR) imaging using follow-up imaging and consensus as the reference standard. The institutional review board approved this retrospective study. The study cohort consisted of 110 consecutive patients with BM and 30 patients without BM. The training data set included MR images of 80 patients with 450 BM nodules. The test set included MR images of 30 patients with 134 BM nodules and 30 patients without BM. We developed a CAD system for BM detection using template-matching and K-means clustering algorithms for candidate detection and an artificial neural network for false-positive reduction. Four reviewers (two neuroradiologists and two radiology residents) interpreted the test set images before and after the use of CAD in a sequential manner. The sensitivity, false positive (FP) per case, and reading time were analyzed. A jackknife free-response receiver operating characteristic (JAFROC) method was used to determine the improvement in the diagnostic accuracy. The sensitivity of CAD was 87.3% with an FP per case of 302.4. CAD significantly improved the diagnostic performance of the four reviewers with a figure-of-merit (FOM) of 0.874 (without CAD) vs. 0.898 (with CAD) according to JAFROC analysis (p < 0.01). Statistically significant improvement was noted only for less-experienced reviewers (FOM without vs. with CAD, 0.834 vs. 0.877, p < 0.01). The additional time required to review the CAD results was approximately 72 sec (40% of the total review time). CAD as a second reader helps radiologists improve their diagnostic performance in the detection of BM on MR imaging, particularly for less-experienced reviewers.

The pedicled internal pudendal artery perforator (PIPAP) flap for ischial pressure sore reconstruction: Technique and long-term outcome of a cohort study.

PubMed

Legemate, Catherine M; van der Kwaak, Monique; Gobets, David; Huikeshoven, Menno; van Zuijlen, Paul P M

2018-06-01

The ischial region is the site most affected by pressure sores and has the highest recurrence and complication rates compared to other affected sites. We developed a practical and safe pedicled flap for reconstruction of ischial pressure sores based on the rich available perforators from the internal pudendal artery and the surplus of skin at the infragluteal fold. A retrospective cohort study was conducted in all patients who underwent ischial pressure ulcer reconstruction using the PIPAP flap between March 2010 and March 2017. The skin flap was designed along the gluteal fold. The skin perforators of the pudendal artery were marked with a Doppler probe in the medial region of the gluteal fold. Surgery was performed in the jackknife position, and flaps were elevated in the suprafascial plane. Patients were assessed for minor (requiring no additional surgery) and major complications (requiring additional surgery). Twenty-seven patients (34 flaps) were identified. The median follow-up period was 38 months (IQR 37). Primary closure of the donor-site was achieved in all procedures, only one flap required muscle flap transposition in order to fill the dead space. The mean operating time was 60 ± 21 minutes. In six flaps (9%) wound healing problems were noted that did not require an additional operative procedure. Among the nine flaps (27%) that required a second procedure, 3 (9%) were necessary due to recurrent ulcers. The PIPAP flap is a safe and reliable alternative for ischial pressure sore reconstruction, certainly when compared to available techniques. Moreover, it has significant advantages over other techniques including minimal donor-site morbidity, preservation of posterior thigh skin, buttock-line integrity and reliable vascularity. Copyright © 2018 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

Climate change in our backyards: the reshuffling of North America's winter bird communities.

PubMed

Princé, Karine; Zuckerberg, Benjamin

2015-02-01

Much of the recent changes in North American climate have occurred during the winter months, and as result, overwintering birds represent important sentinels of anthropogenic climate change. While there is mounting evidence that bird populations are responding to a warming climate (e.g., poleward shifts) questions remain as to whether these species-specific responses are resulting in community-wide changes. Here, we test the hypothesis that a changing winter climate should favor the formation of winter bird communities dominated by warm-adapted species. To do this, we quantified changes in community composition using a functional index--the Community Temperature Index (CTI)--which measures the balance between low- and high-temperature dwelling species in a community. Using data from Project FeederWatch, an international citizen science program, we quantified spatiotemporal changes in winter bird communities (n = 38 bird species) across eastern North America and tested the influence of changes in winter minimum temperature over a 22-year period. We implemented a jackknife analysis to identify those species most influential in driving changes at the community level and the population dynamics (e.g., extinction or colonization) responsible for these community changes. Since 1990, we found that the winter bird community structure has changed with communities increasingly composed of warm-adapted species. This reshuffling of winter bird communities was strongest in southerly latitudes and driven primarily by local increases in abundance and regional patterns of colonization by southerly birds. CTI tracked patterns of changing winter temperature at different temporal scales ranging from 1 to 35 years. We conclude that a shifting winter climate has provided an opportunity for smaller, southerly distributed species to colonize new regions and promote the formation of unique winter bird assemblages throughout eastern North America. © 2014 John Wiley & Sons Ltd.

Adaptive Statistical Iterative Reconstruction-Applied Ultra-Low-Dose CT with Radiography-Comparable Radiation Dose: Usefulness for Lung Nodule Detection.

PubMed

Yoon, Hyun Jung; Chung, Myung Jin; Hwang, Hye Sun; Moon, Jung Won; Lee, Kyung Soo

2015-01-01

To assess the performance of adaptive statistical iterative reconstruction (ASIR)-applied ultra-low-dose CT (ULDCT) in detecting small lung nodules. Thirty patients underwent both ULDCT and standard dose CT (SCT). After determining the reference standard nodules, five observers, blinded to the reference standard reading results, independently evaluated SCT and both subsets of ASIR- and filtered back projection (FBP)-driven ULDCT images. Data assessed by observers were compared statistically. Converted effective doses in SCT and ULDCT were 2.81 ± 0.92 and 0.17 ± 0.02 mSv, respectively. A total of 114 lung nodules were detected on SCT as a standard reference. There was no statistically significant difference in sensitivity between ASIR-driven ULDCT and SCT for three out of the five observers (p = 0.678, 0.735, < 0.01, 0.038, and < 0.868 for observers 1, 2, 3, 4, and 5, respectively). The sensitivity of FBP-driven ULDCT was significantly lower than that of ASIR-driven ULDCT in three out of the five observers (p < 0.01 for three observers, and p = 0.064 and 0.146 for two observers). In jackknife alternative free-response receiver operating characteristic analysis, the mean values of figure-of-merit (FOM) for FBP, ASIR-driven ULDCT, and SCT were 0.682, 0.772, and 0.821, respectively, and there were no significant differences in FOM values between ASIR-driven ULDCT and SCT (p = 0.11), but the FOM value of FBP-driven ULDCT was significantly lower than that of ASIR-driven ULDCT and SCT (p = 0.01 and 0.00). Adaptive statistical iterative reconstruction-driven ULDCT delivering a radiation dose of only 0.17 mSv offers acceptable sensitivity in nodule detection compared with SCT and has better performance than FBP-driven ULDCT.

Adaptive Statistical Iterative Reconstruction-Applied Ultra-Low-Dose CT with Radiography-Comparable Radiation Dose: Usefulness for Lung Nodule Detection

PubMed Central

Yoon, Hyun Jung; Hwang, Hye Sun; Moon, Jung Won; Lee, Kyung Soo

2015-01-01

Objective To assess the performance of adaptive statistical iterative reconstruction (ASIR)-applied ultra-low-dose CT (ULDCT) in detecting small lung nodules. Materials and Methods Thirty patients underwent both ULDCT and standard dose CT (SCT). After determining the reference standard nodules, five observers, blinded to the reference standard reading results, independently evaluated SCT and both subsets of ASIR- and filtered back projection (FBP)-driven ULDCT images. Data assessed by observers were compared statistically. Results Converted effective doses in SCT and ULDCT were 2.81 ± 0.92 and 0.17 ± 0.02 mSv, respectively. A total of 114 lung nodules were detected on SCT as a standard reference. There was no statistically significant difference in sensitivity between ASIR-driven ULDCT and SCT for three out of the five observers (p = 0.678, 0.735, < 0.01, 0.038, and < 0.868 for observers 1, 2, 3, 4, and 5, respectively). The sensitivity of FBP-driven ULDCT was significantly lower than that of ASIR-driven ULDCT in three out of the five observers (p < 0.01 for three observers, and p = 0.064 and 0.146 for two observers). In jackknife alternative free-response receiver operating characteristic analysis, the mean values of figure-of-merit (FOM) for FBP, ASIR-driven ULDCT, and SCT were 0.682, 0.772, and 0.821, respectively, and there were no significant differences in FOM values between ASIR-driven ULDCT and SCT (p = 0.11), but the FOM value of FBP-driven ULDCT was significantly lower than that of ASIR-driven ULDCT and SCT (p = 0.01 and 0.00). Conclusion Adaptive statistical iterative reconstruction-driven ULDCT delivering a radiation dose of only 0.17 mSv offers acceptable sensitivity in nodule detection compared with SCT and has better performance than FBP-driven ULDCT. PMID:26357505

Prediction of subcellular localization of eukaryotic proteins using position-specific profiles and neural network with weighted inputs.

PubMed

Zou, Lingyun; Wang, Zhengzhi; Huang, Jiaomin

2007-12-01

Subcellular location is one of the key biological characteristics of proteins. Position-specific profiles (PSP) have been introduced as important characteristics of proteins in this article. In this study, to obtain position-specific profiles, the Position Specific Iterative-Basic Local Alignment Search Tool (PSI-BLAST) has been used to search for protein sequences in a database. Position-specific scoring matrices are extracted from the profiles as one class of characteristics. Four-part amino acid compositions and 1st-7th order dipeptide compositions have also been calculated as the other two classes of characteristics. Therefore, twelve characteristic vectors are extracted from each of the protein sequences. Next, the characteristic vectors are weighed by a simple weighing function and inputted into a BP neural network predictor named PSP-Weighted Neural Network (PSP-WNN). The Levenberg-Marquardt algorithm is employed to adjust the weight matrices and thresholds during the network training instead of the error back propagation algorithm. With a jackknife test on the RH2427 dataset, PSP-WNN has achieved a higher overall prediction accuracy of 88.4% rather than the prediction results by the general BP neural network, Markov model, and fuzzy k-nearest neighbors algorithm on this dataset. In addition, the prediction performance of PSP-WNN has been evaluated with a five-fold cross validation test on the PK7579 dataset and the prediction results have been consistently better than those of the previous method on the basis of several support vector machines, using compositions of both amino acids and amino acid pairs. These results indicate that PSP-WNN is a powerful tool for subcellular localization prediction. At the end of the article, influences on prediction accuracy using different weighting proportions among three characteristic vector categories have been discussed. An appropriate proportion is considered by increasing the prediction accuracy.

pLoc_bal-mGpos: Predict subcellular localization of Gram-positive bacterial proteins by quasi-balancing training dataset and PseAAC.

PubMed

Xiao, Xuan; Cheng, Xiang; Chen, Genqiang; Mao, Qi; Chou, Kuo-Chen

2018-05-26

Knowledge of protein subcellular localization is vitally important for both basic research and drug development. With the avalanche of protein sequences emerging in the post-genomic age, it is highly desired to develop computational tools for timely and effectively identifying their subcellular localization purely based on the sequence information alone. Recently, a predictor called "pLoc-mGpos" was developed for identifying the subcellular localization of Gram-positive bacterial proteins. Its performance is overwhelmingly better than that of the other predictors for the same purpose, particularly in dealing with multi-label systems in which some proteins, called "multiplex proteins", may simultaneously occur in two or more subcellular locations. Although it is indeed a very powerful predictor, more efforts are definitely needed to further improve it. This is because pLoc-mGpos was trained by an extremely skewed dataset in which some subset (subcellular location) was over 11 times the size of the other subsets. Accordingly, it cannot avoid the bias consequence caused by such an uneven training dataset. To alleviate such bias consequence, we have developed a new and bias-reducing predictor called pLoc_bal-mGpos by quasi-balancing the training dataset. Rigorous target jackknife tests on exactly the same experiment-confirmed dataset have indicated that the proposed new predictor is remarkably superior to pLoc-mGpos, the existing state-of-the-art predictor in identifying the subcellular localization of Gram-positive bacterial proteins. To maximize the convenience for most experimental scientists, a user-friendly web-server for the new predictor has been established at http://www.jci-bioinfo.cn/pLoc_bal-mGpos/, by which users can easily get their desired results without the need to go through the detailed mathematics. Copyright © 2018 Elsevier Inc. All rights reserved.

Classification and Analysis of Regulatory Pathways Using Graph Property, Biochemical and Physicochemical Property, and Functional Property

PubMed Central

Cai, Yu-Dong; Chou, Kuo-Chen

2011-01-01

Given a regulatory pathway system consisting of a set of proteins, can we predict which pathway class it belongs to? Such a problem is closely related to the biological function of the pathway in cells and hence is quite fundamental and essential in systems biology and proteomics. This is also an extremely difficult and challenging problem due to its complexity. To address this problem, a novel approach was developed that can be used to predict query pathways among the following six functional categories: (i) “Metabolism”, (ii) “Genetic Information Processing”, (iii) “Environmental Information Processing”, (iv) “Cellular Processes”, (v) “Organismal Systems”, and (vi) “Human Diseases”. The prediction method was established trough the following procedures: (i) according to the general form of pseudo amino acid composition (PseAAC), each of the pathways concerned is formulated as a 5570-D (dimensional) vector; (ii) each of components in the 5570-D vector was derived by a series of feature extractions from the pathway system according to its graphic property, biochemical and physicochemical property, as well as functional property; (iii) the minimum redundancy maximum relevance (mRMR) method was adopted to operate the prediction. A cross-validation by the jackknife test on a benchmark dataset consisting of 146 regulatory pathways indicated that an overall success rate of 78.8% was achieved by our method in identifying query pathways among the above six classes, indicating the outcome is quite promising and encouraging. To the best of our knowledge, the current study represents the first effort in attempting to identity the type of a pathway system or its biological function. It is anticipated that our report may stimulate a series of follow-up investigations in this new and challenging area. PMID:21980418

Predicting membrane protein types by fusing composite protein sequence features into pseudo amino acid composition.

PubMed

Hayat, Maqsood; Khan, Asifullah

2011-02-21

Membrane proteins are vital type of proteins that serve as channels, receptors, and energy transducers in a cell. Prediction of membrane protein types is an important research area in bioinformatics. Knowledge of membrane protein types provides some valuable information for predicting novel example of the membrane protein types. However, classification of membrane protein types can be both time consuming and susceptible to errors due to the inherent similarity of membrane protein types. In this paper, neural networks based membrane protein type prediction system is proposed. Composite protein sequence representation (CPSR) is used to extract the features of a protein sequence, which includes seven feature sets; amino acid composition, sequence length, 2 gram exchange group frequency, hydrophobic group, electronic group, sum of hydrophobicity, and R-group. Principal component analysis is then employed to reduce the dimensionality of the feature vector. The probabilistic neural network (PNN), generalized regression neural network, and support vector machine (SVM) are used as classifiers. A high success rate of 86.01% is obtained using SVM for the jackknife test. In case of independent dataset test, PNN yields the highest accuracy of 95.73%. These classifiers exhibit improved performance using other performance measures such as sensitivity, specificity, Mathew's correlation coefficient, and F-measure. The experimental results show that the prediction performance of the proposed scheme for classifying membrane protein types is the best reported, so far. This performance improvement may largely be credited to the learning capabilities of neural networks and the composite feature extraction strategy, which exploits seven different properties of protein sequences. The proposed Mem-Predictor can be accessed at http://111.68.99.218/Mem-Predictor. Copyright © 2010 Elsevier Ltd. All rights reserved.

iLoc-Animal: a multi-label learning classifier for predicting subcellular localization of animal proteins.

PubMed

Lin, Wei-Zhong; Fang, Jian-An; Xiao, Xuan; Chou, Kuo-Chen

2013-04-05

Predicting protein subcellular localization is a challenging problem, particularly when query proteins have multi-label features meaning that they may simultaneously exist at, or move between, two or more different subcellular location sites. Most of the existing methods can only be used to deal with the single-label proteins. Actually, multi-label proteins should not be ignored because they usually bear some special function worthy of in-depth studies. By introducing the "multi-label learning" approach, a new predictor, called iLoc-Animal, has been developed that can be used to deal with the systems containing both single- and multi-label animal (metazoan except human) proteins. Meanwhile, to measure the prediction quality of a multi-label system in a rigorous way, five indices were introduced; they are "Absolute-True", "Absolute-False" (or Hamming-Loss"), "Accuracy", "Precision", and "Recall". As a demonstration, the jackknife cross-validation was performed with iLoc-Animal on a benchmark dataset of animal proteins classified into the following 20 location sites: (1) acrosome, (2) cell membrane, (3) centriole, (4) centrosome, (5) cell cortex, (6) cytoplasm, (7) cytoskeleton, (8) endoplasmic reticulum, (9) endosome, (10) extracellular, (11) Golgi apparatus, (12) lysosome, (13) mitochondrion, (14) melanosome, (15) microsome, (16) nucleus, (17) peroxisome, (18) plasma membrane, (19) spindle, and (20) synapse, where many proteins belong to two or more locations. For such a complicated system, the outcomes achieved by iLoc-Animal for all the aforementioned five indices were quite encouraging, indicating that the predictor may become a useful tool in this area. It has not escaped our notice that the multi-label approach and the rigorous measurement metrics can also be used to investigate many other multi-label problems in molecular biology. As a user-friendly web-server, iLoc-Animal is freely accessible to the public at the web-site .

Association between structural and functional brain alterations in drug-free patients with schizophrenia: a multimodal meta-analysis.

PubMed

Gao, Xin; Zhang, Wenjing; Yao, Li; Xiao, Yuan; Liu, Lu; Liu, Jieke; Li, Siyi; Tao, Bo; Shah, Chandan; Gong, Qiyong; Sweeney, John A; Lui, Su

2018-03-01

Neuroimaging studies have shown both structural and functional abnormalities in patients with schizophrenia. Recently, studies have begun to explore the association between structural and functional grey matter abnormalities. By conducting a meta-analysis on morphometric and functional imaging studies of grey matter alterations in drug-free patients, the present study aims to examine the degree of overlap between brain regions with anatomic and functional changes in patients with schizophrenia. We performed a systematic search of PubMed, Embase, Web of Science and the Cochrane Library to identify relevant publications. A multimodal analysis was then conducted using Seed-based d Mapping software. Exploratory analyses included jackknife, subgroup and meta-regression analyses. We included 15 structural MRI studies comprising 486 drug-free patients and 485 healthy controls, and 16 functional MRI studies comprising 403 drug-free patients and 428 controls in our meta-analysis. Drug-free patients were examined to reduce pharmacological effects on the imaging data. Multimodal analysis showed considerable overlap between anatomic and functional changes, mainly in frontotemporal regions, bilateral medial posterior cingulate/paracingulate gyrus, bilateral insula, basal ganglia and left cerebellum. There were also brain regions showing only anatomic changes in the right superior frontal gyrus, left supramarginal gyrus, right lingual gyrus and functional alternations involving the right angular gyrus. The methodological aspects, patient characteristics and clinical variables of the included studies were heterogeneous, and we cannot exclude medication effects. The present study showed overlapping anatomic and functional brain abnormalities mainly in the default mode (DMN) and auditory networks (AN) in drug-free patients with schizophrenia. However, the pattern of changes differed in these networks. Decreased grey matter was associated with decreased activation within the DMN

Association between structural and functional brain alterations in drug-free patients with schizophrenia: a multimodal meta-analysis.

PubMed

Gao, Xin; Zhang, Wenjing; Yao, Li; Xiao, Yuan; Liu, Lu; Liu, Jieke; Li, Siyi; Tao, Bo; Shah, Chandan; Gong, Qiyong; Sweeney, John A; Lui, Su

2017-12-15

Neuroimaging studies have shown both structural and functional abnormalities in patients with schizophrenia. Recently, studies have begun to explore the association between structural and functional grey matter abnormalities. By conducting a meta-analysis on morphometric and functional imaging studies of grey matter alterations in drug-free patients, the present study aims to examine the degree of overlap between brain regions with anatomic and functional changes in patients with schizophrenia. We performed a systematic search of PubMed, Embase, Web of Science and the Cochrane Library to identify relevant publications. A multimodal analysis was then conducted using Seed-based d Mapping software. Exploratory analyses included jackknife, subgroup and meta-regression analyses. We included 15 structural MRI studies comprising 486 drug-free patients and 485 healthy controls, and 16 functional MRI studies comprising 403 drug-free patients and 428 controls in our meta-analysis. Drug-free patients were examined to reduce pharmacological effects on the imaging data. Multimodal analysis showed considerable overlap between anatomic and functional changes, mainly in frontotemporal regions, bilateral medial posterior cingulate/paracingulate gyrus, bilateral insula, basal ganglia and left cerebellum. There were also brain regions showing only anatomic changes in the right superior frontal gyrus, left supramarginal gyrus, right lingual gyrus and functional alternations involving the right angular gyrus. The methodological aspects, patient characteristics and clinical variables of the included studies were heterogeneous, and we cannot exclude medication effects. The present study showed overlapping anatomic and functional brain abnormalities mainly in the default mode (DMN) and auditory networks (AN) in drug-free patients with schizophrenia. However, the pattern of changes differed in these networks. Decreased grey matter was associated with decreased activation within the DMN

PRIMUS: Galaxy Clustering as a Function of Luminosity and Color at 0.2 < z < 1

NASA Astrophysics Data System (ADS)

Skibba, Ramin A.; Smith, M. Stephen M.; Coil, Alison L.; Moustakas, John; Aird, James; Blanton, Michael R.; Bray, Aaron D.; Cool, Richard J.; Eisenstein, Daniel J.; Mendez, Alexander J.; Wong, Kenneth C.; Zhu, Guangtun

2014-04-01

We present measurements of the luminosity and color-dependence of galaxy clustering at 0.2 < z < 1.0 in the Prism Multi-object Survey. We quantify the clustering with the redshift-space and projected two-point correlation functions, ξ(rp , π) and wp (rp ), using volume-limited samples constructed from a parent sample of over ~130, 000 galaxies with robust redshifts in seven independent fields covering 9 deg2 of sky. We quantify how the scale-dependent clustering amplitude increases with increasing luminosity and redder color, with relatively small errors over large volumes. We find that red galaxies have stronger small-scale (0.1 Mpc h -1 < rp < 1 Mpc h -1) clustering and steeper correlation functions compared to blue galaxies, as well as a strong color dependent clustering within the red sequence alone. We interpret our measured clustering trends in terms of galaxy bias and obtain values of b gal ≈ 0.9-2.5, quantifying how galaxies are biased tracers of dark matter depending on their luminosity and color. We also interpret the color dependence with mock catalogs, and find that the clustering of blue galaxies is nearly constant with color, while redder galaxies have stronger clustering in the one-halo term due to a higher satellite galaxy fraction. In addition, we measure the evolution of the clustering strength and bias, and we do not detect statistically significant departures from passive evolution. We argue that the luminosity- and color-environment (or halo mass) relations of galaxies have not significantly evolved since z ~ 1. Finally, using jackknife subsampling methods, we find that sampling fluctuations are important and that the COSMOS field is generally an outlier, due to having more overdense structures than other fields; we find that "cosmic variance" can be a significant source of uncertainty for high-redshift clustering measurements.

iHSP-PseRAAAC: Identifying the heat shock protein families using pseudo reduced amino acid alphabet composition.

PubMed

Feng, Peng-Mian; Chen, Wei; Lin, Hao; Chou, Kuo-Chen

2013-11-01

Heat shock proteins (HSPs) are a type of functionally related proteins present in all living organisms, both prokaryotes and eukaryotes. They play essential roles in protein-protein interactions such as folding and assisting in the establishment of proper protein conformation and prevention of unwanted protein aggregation. Their dysfunction may cause various life-threatening disorders, such as Parkinson's, Alzheimer's, and cardiovascular diseases. Based on their functions, HSPs are usually classified into six families: (i) HSP20 or sHSP, (ii) HSP40 or J-class proteins, (iii) HSP60 or GroEL/ES, (iv) HSP70, (v) HSP90, and (vi) HSP100. Although considerable progress has been achieved in discriminating HSPs from other proteins, it is still a big challenge to identify HSPs among their six different functional types according to their sequence information alone. With the avalanche of protein sequences generated in the post-genomic age, it is highly desirable to develop a high-throughput computational tool in this regard. To take up such a challenge, a predictor called iHSP-PseRAAAC has been developed by incorporating the reduced amino acid alphabet information into the general form of pseudo amino acid composition. One of the remarkable advantages of introducing the reduced amino acid alphabet is being able to avoid the notorious dimension disaster or overfitting problem in statistical prediction. It was observed that the overall success rate achieved by iHSP-PseRAAAC in identifying the functional types of HSPs among the aforementioned six types was more than 87%, which was derived by the jackknife test on a stringent benchmark dataset in which none of HSPs included has ≥40% pairwise sequence identity to any other in the same subset. It has not escaped our notice that the reduced amino acid alphabet approach can also be used to investigate other protein classification problems. As a user-friendly web server, iHSP-PseRAAAC is accessible to the public at http

Characterizing informative sequence descriptors and predicting binding affinities of heterodimeric protein complexes

PubMed Central

2015-01-01

Background Protein-protein interactions (PPIs) are involved in various biological processes, and underlying mechanism of the interactions plays a crucial role in therapeutics and protein engineering. Most machine learning approaches have been developed for predicting the binding affinity of protein-protein complexes based on structure and functional information. This work aims to predict the binding affinity of heterodimeric protein complexes from sequences only. Results This work proposes a support vector machine (SVM) based binding affinity classifier, called SVM-BAC, to classify heterodimeric protein complexes based on the prediction of their binding affinity. SVM-BAC identified 14 of 580 sequence descriptors (physicochemical, energetic and conformational properties of the 20 amino acids) to classify 216 heterodimeric protein complexes into low and high binding affinity. SVM-BAC yielded the training accuracy, sensitivity, specificity, AUC and test accuracy of 85.80%, 0.89, 0.83, 0.86 and 83.33%, respectively, better than existing machine learning algorithms. The 14 features and support vector regression were further used to estimate the binding affinities (Pkd) of 200 heterodimeric protein complexes. Prediction performance of a Jackknife test was the correlation coefficient of 0.34 and mean absolute error of 1.4. We further analyze three informative physicochemical properties according to their contribution to prediction performance. Results reveal that the following properties are effective in predicting the binding affinity of heterodimeric protein complexes: apparent partition energy based on buried molar fractions, relations between chemical structure and biological activity in principal component analysis IV, and normalized frequency of beta turn. Conclusions The proposed sequence-based prediction method SVM-BAC uses an optimal feature selection method to identify 14 informative features to classify and predict binding affinity of heterodimeric protein

Certain performance values arising from mammographic test set readings correlate well with clinical audit.

PubMed

Soh, BaoLin Pauline; Lee, Warwick Bruce; Mello-Thoms, Claudia; Tapia, Kriscia; Ryan, John; Hung, Wai Tak; Thompson, Graham; Heard, Rob; Brennan, Patrick

2015-08-01

Test sets have been increasingly utilised to augment clinical audit in breast screening programmes; however, their relationship has never been satisfactorily understood. This study examined the relationship between mammographic test set performance and clinical audit data. Clinical audit data over a 2-year period was generated for each of 20 radiologists. Sixty mammographic examinations, consisting of 40 normal and 20 cancer cases, formed the test set. Readers located any identifiable cancer, and levels of confidence were scored from 2 to 5, where a score of 3 and above is considered a recall rating. Jackknifing free response operating characteristic (JAFROC) figure-of-merit (FOM), location sensitivity and specificity were calculated for individual readers and then compared with clinical audit values using Spearman's rho. JAFROC FOM showed significant correlations to: recall rate at a first round of screening (r = 0.51; P = 0.02); rate of small invasive cancers per 10 000 reads (r = 0.5; P = 0.02); percentage of all cancers read that were not recalled (r = -0.51; P = 0.02); and sensitivity (r = 0.51; P = 0.02). Location sensitivity demonstrated significant correlations with: rate of small invasive cancers per 10 000 reads (r = 0.46; P = 0.04); rate of DCIS (ductal carcinoma in situ) per 10 000 reads (r = 0.44; P = 0.05); detection rate of all invasive cancers and DCIS per 10 000 reads (r = 0.54; P = 0.01); percentage of all cancers read that were not recalled (r = -0.57; P = 0.009); and sensitivity (r = 0.57; P = 0.009). No other significant relationships were noted. Performance indicators from test set demonstrate significant correlations with specific aspects of clinical performance, although caution needs to be exercised when generalising test set specificity to the clinical situation. © 2015 The Royal Australian and New Zealand College of Radiologists.

Modelling Spatial Patterns and Drivers of Wildfires in Honduras Using Remote Sensing and Geographic Information Systems

NASA Astrophysics Data System (ADS)

Valdez Vasquez, M. C.; Chen, C. F.; Chiang, S. H.

2016-12-01

Forests in Honduras are one of the most important resources as they provide a wide range of environmental, economic, and social benefits. However, they are endangered as a result of the relentless occurrence of wildfires during the dry season. Despite the knowledge acquired by the population concerning the effects of wildfires, the frequency is increasing, a pattern attributable to the numerous ignition sources linked to human activity. The purpose of this study is to integrate the wildfire occurrences throughout the 2010-2015 period with a series of anthropogenic and non-anthropogenic variables using the random forest algorithm (RF). We use a series of variables that represent the anthropogenic activity, the flammability of vegetation, climatic conditions, and topography. To represent the anthropogenic activity, we included the continuous distances to rivers, roads, and settlements. To characterize the vegetation flammability, we used the normalized difference vegetation index (NDVI) and the normalized multi-band drought index (NMDI) acquired from MODIS surface reflectance data. Additionally, we included the topographical variables elevation, slope, and solar radiation derived from the ASTER global digital elevation model (GDEM V2). To represent the climatic conditions, we employed the land surface temperature (LST) product from the MODIS sensor and the WorldClim precipitation data. We analyzed the explanatory variables through native RF variable importance analysis and jackknife test, and the results revealed that the dry fuel conditions and low precipitation combined with the proximity to non-paved roads were the major drivers of wildfires. Furthermore, we predicted the areas with highest wildfire susceptibility, which are located mainly in the central and eastern regions of the country, within coniferous and mixed forests. Results acquired were validated using the area under the receiver operating characteristic (ROC) curve and the point biserial correlation

Lesion detection performance: comparative analysis of low-dose CT data of the chest on two hybrid imaging systems.

PubMed

Jessop, Maryam; Thompson, John D; Coward, Joanne; Sanderud, Audun; Jorge, José; de Groot, Martijn; Lança, Luís; Hogg, Peter

2015-03-01

Incidental findings on low-dose CT images obtained during hybrid imaging are an increasing phenomenon as CT technology advances. Understanding the diagnostic value of incidental findings along with the technical limitations is important when reporting image results and recommending follow-up, which may result in an additional radiation dose from further diagnostic imaging and an increase in patient anxiety. This study assessed lesions incidentally detected on CT images acquired for attenuation correction on two SPECT/CT systems. An anthropomorphic chest phantom containing simulated lesions of varying size and density was imaged on an Infinia Hawkeye 4 and a Symbia T6 using the low-dose CT settings applied for attenuation correction acquisitions in myocardial perfusion imaging. Twenty-two interpreters assessed 46 images from each SPECT/CT system (15 normal images and 31 abnormal images; 41 lesions). Data were evaluated using a jackknife alternative free-response receiver-operating-characteristic analysis (JAFROC). JAFROC analysis showed a significant difference (P < 0.0001) in lesion detection, with the figures of merit being 0.599 (95% confidence interval, 0.568, 0.631) and 0.810 (95% confidence interval, 0.781, 0.839) for the Infinia Hawkeye 4 and Symbia T6, respectively. Lesion detection on the Infinia Hawkeye 4 was generally limited to larger, higher-density lesions. The Symbia T6 allowed improved detection rates for midsized lesions and some lower-density lesions. However, interpreters struggled to detect small (5 mm) lesions on both image sets, irrespective of density. Lesion detection is more reliable on low-dose CT images from the Symbia T6 than from the Infinia Hawkeye 4. This phantom-based study gives an indication of potential lesion detection in the clinical context as shown by two commonly used SPECT/CT systems, which may assist the clinician in determining whether further diagnostic imaging is justified. © 2015 by the Society of Nuclear Medicine and

PRIMUS: Galaxy clustering as a function of luminosity and color at 0.2 < z < 1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Skibba, Ramin A.; Smith, M. Stephen M.; Coil, Alison L.

2014-04-01

We present measurements of the luminosity and color-dependence of galaxy clustering at 0.2 < z < 1.0 in the Prism Multi-object Survey. We quantify the clustering with the redshift-space and projected two-point correlation functions, ξ(r{sub p} , π) and w{sub p} (r{sub p} ), using volume-limited samples constructed from a parent sample of over ∼130, 000 galaxies with robust redshifts in seven independent fields covering 9 deg{sup 2} of sky. We quantify how the scale-dependent clustering amplitude increases with increasing luminosity and redder color, with relatively small errors over large volumes. We find that red galaxies have stronger small-scale (0.1more » Mpc h {sup –1} < r{sub p} < 1 Mpc h {sup –1}) clustering and steeper correlation functions compared to blue galaxies, as well as a strong color dependent clustering within the red sequence alone. We interpret our measured clustering trends in terms of galaxy bias and obtain values of b {sub gal} ≈ 0.9-2.5, quantifying how galaxies are biased tracers of dark matter depending on their luminosity and color. We also interpret the color dependence with mock catalogs, and find that the clustering of blue galaxies is nearly constant with color, while redder galaxies have stronger clustering in the one-halo term due to a higher satellite galaxy fraction. In addition, we measure the evolution of the clustering strength and bias, and we do not detect statistically significant departures from passive evolution. We argue that the luminosity- and color-environment (or halo mass) relations of galaxies have not significantly evolved since z ∼ 1. Finally, using jackknife subsampling methods, we find that sampling fluctuations are important and that the COSMOS field is generally an outlier, due to having more overdense structures than other fields; we find that 'cosmic variance' can be a significant source of uncertainty for high-redshift clustering measurements.« less

Spatial Distribution of Sand Fly Vectors and Eco-Epidemiology of Cutaneous Leishmaniasis Transmission in Colombia.

PubMed

Ferro, Cristina; López, Marla; Fuya, Patricia; Lugo, Ligia; Cordovez, Juan Manuel; González, Camila

2015-01-01

Leishmania is transmitted by Phlebotominae insects that maintain the enzootic cycle by circulating between sylvatic and domestic mammals; humans enter the cycles as accidental hosts due to the vector's search for blood source. In Colombia, leishmaniasis is an endemic disease and 95% of all cases are cutaneous (CL), these cases have been reported in several regions of the country where the intervention of sylvatic areas by the introduction of agriculture seem to have an impact on the rearrangement of new transmission cycles. Our study aimed to update vector species distribution in the country and to analyze the relationship between vectors' distribution, climate, land use and CL prevalence. A database with geographic information was assembled, and ecological niche modeling was performed to explore the potential distribution of each of the 21 species of medical importance in Colombia, using thirteen bioclimatic variables, three topographic and three principal components derived from NDVI. Binary models for each species were obtained and related to both land use coverage, and a CL prevalence map with available epidemiological data. Finally, maps of species potential distribution were summed to define potential species richness in the country. In total, 673 single records were obtained with Lutzomyia gomezi, Lutzomyia longipalpis, Psychodopygus panamensis, Psathyromyia shannoni and Pintomyia evansi the species with the highest number of records. Eighteen species had significant models, considering the area under the curve and the jackknife results: L. gomezi and P. panamensis had the widest potential distribution. All sand fly species except for Nyssomyia antunesi are mainly distributed in regions with rates of prevalence between 0.33 to 101.35 cases per 100,000 inhabitants and 76% of collection data points fall into transformed ecosystems. Distribution ranges of sand flies with medical importance in Colombia correspond predominantly to disturbed areas, where the

Housefly Population Density Correlates with Shigellosis among Children in Mirzapur, Bangladesh: A Time Series Analysis

PubMed Central

Farag, Tamer H.; Faruque, Abu S.; Wu, Yukun; Das, Sumon K.; Hossain, Anowar; Ahmed, Shahnawaz; Ahmed, Dilruba; Nasrin, Dilruba; Kotloff, Karen L.; Panchilangam, Sandra; Nataro, James P.; Cohen, Dani; Blackwelder, William C.; Levine, Myron M.

2013-01-01

Background Shigella infections are a public health problem in developing and transitional countries because of high transmissibility, severity of clinical disease, widespread antibiotic resistance and lack of a licensed vaccine. Whereas Shigellae are known to be transmitted primarily by direct fecal-oral contact and less commonly by contaminated food and water, the role of the housefly Musca domestica as a mechanical vector of transmission is less appreciated. We sought to assess the contribution of houseflies to Shigella-associated moderate-to-severe diarrhea (MSD) among children less than five years old in Mirzapur, Bangladesh, a site where shigellosis is hyperendemic, and to model the potential impact of a housefly control intervention. Methods Stool samples from 843 children presenting to Kumudini Hospital during 2009–2010 with new episodes of MSD (diarrhea accompanied by dehydration, dysentery or hospitalization) were analyzed. Housefly density was measured twice weekly in six randomly selected sentinel households. Poisson time series regression was performed and autoregression-adjusted attributable fractions (AFs) were calculated using the Bruzzi method, with standard errors via jackknife procedure. Findings Dramatic springtime peaks in housefly density in 2009 and 2010 were followed one to two months later by peaks of Shigella-associated MSD among toddlers and pre-school children. Poisson time series regression showed that housefly density was associated with Shigella cases at three lags (six weeks) (Incidence Rate Ratio = 1.39 [95% CI: 1.23 to 1.58] for each log increase in fly count), an association that was not confounded by ambient air temperature. Autocorrelation-adjusted AF calculations showed that a housefly control intervention could have prevented approximately 37% of the Shigella cases over the study period. Interpretation Houseflies may play an important role in the seasonal transmission of Shigella in some developing country ecologies

Housefly population density correlates with shigellosis among children in Mirzapur, Bangladesh: a time series analysis.

PubMed

Farag, Tamer H; Faruque, Abu S; Wu, Yukun; Das, Sumon K; Hossain, Anowar; Ahmed, Shahnawaz; Ahmed, Dilruba; Nasrin, Dilruba; Kotloff, Karen L; Panchilangam, Sandra; Nataro, James P; Cohen, Dani; Blackwelder, William C; Levine, Myron M

2013-01-01

Shigella infections are a public health problem in developing and transitional countries because of high transmissibility, severity of clinical disease, widespread antibiotic resistance and lack of a licensed vaccine. Whereas Shigellae are known to be transmitted primarily by direct fecal-oral contact and less commonly by contaminated food and water, the role of the housefly Musca domestica as a mechanical vector of transmission is less appreciated. We sought to assess the contribution of houseflies to Shigella-associated moderate-to-severe diarrhea (MSD) among children less than five years old in Mirzapur, Bangladesh, a site where shigellosis is hyperendemic, and to model the potential impact of a housefly control intervention. Stool samples from 843 children presenting to Kumudini Hospital during 2009-2010 with new episodes of MSD (diarrhea accompanied by dehydration, dysentery or hospitalization) were analyzed. Housefly density was measured twice weekly in six randomly selected sentinel households. Poisson time series regression was performed and autoregression-adjusted attributable fractions (AFs) were calculated using the Bruzzi method, with standard errors via jackknife procedure. Dramatic springtime peaks in housefly density in 2009 and 2010 were followed one to two months later by peaks of Shigella-associated MSD among toddlers and pre-school children. Poisson time series regression showed that housefly density was associated with Shigella cases at three lags (six weeks) (Incidence Rate Ratio = 1.39 [95% CI: 1.23 to 1.58] for each log increase in fly count), an association that was not confounded by ambient air temperature. Autocorrelation-adjusted AF calculations showed that a housefly control intervention could have prevented approximately 37% of the Shigella cases over the study period. Houseflies may play an important role in the seasonal transmission of Shigella in some developing country ecologies. Interventions to control houseflies should be

Use of large-scale atmospheric energetics for understanding the dynamics of contrasting Indian summer monsoon rainfall in different years

NASA Astrophysics Data System (ADS)

Dutta, Somenath; Narkhedkar, Sanjay G.; Mukhopadhyay, Parthasarathi; Yadav, Mamta; Sunitha Devi

2018-06-01

An attempt has been made to understand the dynamics of contrasting Indian summer monsoon rainfall (ISMR) in different years during 1979-2017, from large-scale atmospheric energetics aspects. Daily values of eddy and zonal available potential energy (APE), their generation, eddy and zonal kinetic energy (KE), conversions of zonal KE and eddy APE to eddy KE, and conversions of zonal APE to zonal KE and eddy APE were computed over the region bounded by 65°E-95°E and 5°N-35°N during the period 1 May to 30 September for 39 years (1979-2017), using daily ECMWF reanalyzed atmospheric data at 0.125° × 0.125° resolution (3 components of wind and temperature). ISMR was classified into three categories, viz., deficient and below normal, normal and above normal and excess. The daily anomaly of these energetics parameters in each of these years was computed using jackknife method and then the composite of the daily anomalies of these parameters constructed for the years with the above-mentioned three categories of ISMR. The following salient features emerge from this study: Analysis of composite anomaly shows that in case of excess and above normal (below normal and deficient) ISMR, C(A Z , K Z) was less (more) than normal. In case of excess and above normal (below normal and deficient) ISMR, C(A E , K E) was more (less) than normal. Broadly, C(A Z , A E) was more than normal in the years with deficient and below normal ISMR, whereas it was less than normal for years with excess and above normal ISMR. Broadly, G(A Z) was below normal for the years with above normal and excess ISMR, whereas it was above normal for the years with below normal and deficient ISMR. Total kinetic energy and total conversion to eddy kinetic energy was above normal for the years with above normal and excess ISMR.

Benthic macrofauna habitat associations in Willapa Bay, Washington, USA

NASA Astrophysics Data System (ADS)

Ferraro, Steven P.; Cole, Faith A.

2007-02-01

Estuary-wide benthic macrofauna-habitat associations in Willapa Bay, Washington, United States, were determined for 4 habitats (eelgrass [ Zostera marina], Atlantic cordgrass [ Spartina alterniflora], mud shrimp [ Upogebia pugettensis], ghost shrimp [ Neotrypaea californiensis]) in 1996 and 7 habitats (eelgrass, Atlantic cordgrass, mud shrimp, ghost shrimp, oyster [ Crassostrea gigas], bare mud/sand, subtidal) in 1998. Most benthic macrofaunal species inhabited multiple habitats; however, 2 dominants, a fanworm, Manayunkia aestuarina, in Spartina, and a sand dollar, Dendraster excentricus, in subtidal, were rare or absent in all other habitats. Benthic macrofaunal Bray-Curtis similarity varied among all habitats except eelgrass and oyster. There were significant differences among habitats within- and between-years on several of the following ecological indicators: mean number of species ( S), abundance ( A), biomass ( B), abundance of deposit (AD), suspension (AS), and facultative (AF) feeders, Swartz's index (SI), Brillouin's index ( H), and jackknife estimates of habitat species richness (HSR). In the 4 habitats sampled in both years, A was about 2.5× greater in 1996 (a La Niña year) than 1998 (a strong El Niño year) yet relative values of S, A, B, AD, AS, SI, and H among the habitats were not significantly different, indicating strong benthic macrofauna-habitat associations despite considerable climatic and environmental variability. In general, the rank order of habitats on indicators associated with high diversity and productivity (high S, A, B, SI, H, HSR) was eelgrass = oyster ≥ Atlantic cordgrass ≥ mud shrimp ≥ bare mud/sand ≥ ghost shrimp = subtidal. Vegetation, burrowing shrimp, and oyster density and sediment %silt + clay and %total organic carbon were generally poor, temporally inconsistent predictors of ecological indicator variability within habitats. The benthic macrofauna-habitat associations in this study can be used to help identify

Ngram time series model to predict activity type and energy cost from wrist, hip and ankle accelerometers: implications of age

PubMed Central

Strath, Scott J; Kate, Rohit J; Keenan, Kevin G; Welch, Whitney A; Swartz, Ann M

2016-01-01

To develop and test time series single site and multi-site placement models, we used wrist, hip and ankle processed accelerometer data to estimate energy cost and type of physical activity in adults. Ninety-nine subjects in three age groups (18–39, 40–64, 65 + years) performed 11 activities while wearing three triaxial accelereometers: one each on the non-dominant wrist, hip, and ankle. During each activity net oxygen cost (METs) was assessed. The time series of accelerometer signals were represented in terms of uniformly discretized values called bins. Support Vector Machine was used for activity classification with bins and every pair of bins used as features. Bagged decision tree regression was used for net metabolic cost prediction. To evaluate model performance we employed the jackknife leave-one-out cross validation method. Single accelerometer and multi-accelerometer site model estimates across and within age group revealed similar accuracy, with a bias range of −0.03 to 0.01 METs, bias percent of −0.8 to 0.3%, and a rMSE range of 0.81–1.04 METs. Multi-site accelerometer location models improved activity type classification over single site location models from a low of 69.3% to a maximum of 92.8% accuracy. For each accelerometer site location model, or combined site location model, percent accuracy classification decreased as a function of age group, or when young age groups models were generalized to older age groups. Specific age group models on average performed better than when all age groups were combined. A time series computation show promising results for predicting energy cost and activity type. Differences in prediction across age group, a lack of generalizability across age groups, and that age group specific models perform better than when all ages are combined needs to be considered as analytic calibration procedures to detect energy cost and type are further developed. PMID:26449155

Diagnostic Performance of Gadoxetic Acid-enhanced Liver MR Imaging versus Multidetector CT in the Detection of Dysplastic Nodules and Early Hepatocellular Carcinoma.

PubMed

Kim, Bo Ram; Lee, Jeong Min; Lee, Dong Ho; Yoon, Jeong Hee; Hur, Bo Yun; Suh, Kyung Suk; Yi, Nam-Joon; Lee, Kyung Boon; Han, Joon Koo

2017-10-01

Purpose To compare the diagnostic performance of gadoxetic acid-enhanced liver magnetic resonance (MR) imaging with that of contrast material-enhanced multidetector computed tomography (CT) in the detection of borderline hepatocellular nodules in patients with liver cirrhosis and to determine the Liver Imaging Reporting and Data System (LI-RADS) categories of these detected nodules. Materials and Methods The institutional review board approved this retrospective study and waived the informed consent requirement. Sixty-eight patients with pathologically proven dysplastic nodules (DNs) (low-grade DNs, n = 20; high-grade DNs, n = 17), early hepatocellular carcinomas (HCCs) (n = 42), or progressed HCCs (n = 33) underwent gadoxetic acid-enhanced MR imaging and multidetector CT. An additional 57 patients without any DNs or HCCs in the explanted livers were included as control subjects. Three radiologists independently graded the presence of liver nodules on a five-point confidence scale and assigned LI-RADS categories by using imaging findings. Jackknife alternative free-response receiver operating characteristics (JAFROC) software was used to compare the diagnostic accuracy of each modality in lesion detection. Results Reader-averaged figures of merit estimated with JAFROC software to detect hepatocellular nodules were 0.774 for multidetector CT and 0.842 for MR imaging (P = .002). Readers had significantly higher detection sensitivity for early HCCs with MR imaging than with multidetector CT (78.6% vs 52.4% [P = .001], 71.4% vs 50.0% [P = .011], and 73.8% vs 50.0% [P = .001], respectively). A high proportion of overall detected early HCCs at multidetector CT (59.4%) and MR imaging (72.3%) were categorized as LI-RADS category 4. Most early HCCs (76.2%) and high-grade DNs (82.4%) demonstrated hypointensity on hepatobiliary phase images. In total, 30 more LI-RADS category 4 early HCCs were identified with MR imaging than with multidetector CT across all readers

Revised and annotated checklist of aquatic and semi-aquatic Heteroptera of Hungary with comments on biodiversity patterns

PubMed Central

Boda, Pál; Bozóki, Tamás; Vásárhelyi, Tamás; Bakonyi, Gábor; Várbíró, Gábor

2015-01-01

Abstract A basic knowledge of regional faunas is necessary to follow the changes in macroinvertebrate communities caused by environmental influences and climatic trends in the future. We collected all the available data on water bugs in Hungary using an inventory method, a UTM grid based database was built, and Jackknife richness estimates and species accumulation curves were calculated. Fauna compositions were compared among Central-European states. As a result, an updated and annotated checklist for Hungary is provided, containing 58 species in 21 genera and 12 families. A total 66.8% of the total UTM 10 × 10 km squares in Hungary possess faunistic data for water bugs. The species number in grid cells numbered from 0 to 42, and their diversity patterns showed heterogeneity. The estimated species number of 58 is equal to the actual number of species known from the country. The asymptotic shape of the accumulative species curve predicts that additional sampling efforts will not increase the number of species currently known from Hungary. These results suggest that the number of species in the country was estimated correctly and that the species accumulation curve levels off at an asymptotic value. Thus a considerable increase in species richness is not expected in the future. Even with the species composition changing the chance of species turn-over does exist. Overall, 36.7% of the European water bug species were found in Hungary. The differences in faunal composition between Hungary and its surrounding countries were caused by the rare or unique species, whereas 33 species are common in the faunas of the eight countries. Species richness does show a correlation with latitude, and similar species compositions were observed in the countries along the same latitude. The species list and the UTM-based database are now up-to-date for Hungary, and it will provide a basis for future studies of distributional and biodiversity patterns, biogeography, relative abundance

Virus-PLoc: a fusion classifier for predicting the subcellular localization of viral proteins within host and virus-infected cells.

PubMed

Shen, Hong-Bin; Chou, Kuo-Chen

2007-02-15

Viruses can reproduce their progenies only within a host cell, and their actions depend both on its destructive tendencies toward a specific host cell and on environmental conditions. Therefore, knowledge of the subcellular localization of viral proteins in a host cell or virus-infected cell is very useful for in-depth studying of their functions and mechanisms as well as designing antiviral drugs. An analysis on the Swiss-Prot database (version 50.0, released on May 30, 2006) indicates that only 23.5% of viral protein entries are annotated for their subcellular locations in this regard. As for the gene ontology database, the corresponding percentage is 23.8%. Such a gap calls for the development of high throughput tools for timely annotating the localization of viral proteins within host and virus-infected cells. In this article, a predictor called "Virus-PLoc" has been developed that is featured by fusing many basic classifiers with each engineered according to the K-nearest neighbor rule. The overall jackknife success rate obtained by Virus-PLoc in identifying the subcellular compartments of viral proteins was 80% for a benchmark dataset in which none of proteins has more than 25% sequence identity to any other in a same location site. Virus-PLoc will be freely available as a web-server at http://202.120.37.186/bioinf/virus for the public usage. Furthermore, Virus-PLoc has been used to provide large-scale predictions of all viral protein entries in Swiss-Prot database that do not have subcellular location annotations or are annotated as being uncertain. The results thus obtained have been deposited in a downloadable file prepared with Microsoft Excel and named "Tab_Virus-PLoc.xls." This file is available at the same website and will be updated twice a year to include the new entries of viral proteins and reflect the continuous development of Virus-PLoc. 2006 Wiley Periodicals, Inc.

Interpretation Time Using a Concurrent-Read Computer-Aided Detection System for Automated Breast Ultrasound in Breast Cancer Screening of Women With Dense Breast Tissue.

PubMed

Jiang, Yulei; Inciardi, Marc F; Edwards, Alexandra V; Papaioannou, John

2018-05-24

The purpose of this study was to compare diagnostic accuracy and interpretation time of screening automated breast ultrasound (ABUS) for women with dense breast tissue without and with use of a recently U.S. Food and Drug Administration-approved computer-aided detection (CAD) system for concurrent read. In a retrospective observer performance study, 18 radiologists interpreted a cancer-enriched set (i.e., cancer prevalence higher than in the original screening cohort) of 185 screening ABUS studies (52 with and 133 without breast cancer). These studies were from a large cohort of ABUS screened patients interpreted as BI-RADS density C or D. Each reader interpreted each case twice in a counterbalanced study, once without the CAD system and once with it, separated by 4 weeks. For each case, each reader identified abnormal findings and reported BI-RADS assessment category and level of suspicion for breast cancer. Interpretation time was recorded. Level of suspicion data were compared to evaluate diagnostic accuracy by means of the Dorfman-Berbaum-Metz method of jackknife with ANOVA ROC analysis. Interpretation times were compared by ANOVA. The ROC AUC was 0.848 with the CAD system, compared with 0.828 without it, for a difference of 0.020 (95% CI, -0.011 to 0.051) and was statistically noninferior to the AUC without the CAD system with respect to a margin of -0.05 (p = 0.000086). The mean interpretation time was 3 minutes 33 seconds per case without the CAD system and 2 minutes 24 seconds with it, for a difference of 1 minute 9 seconds saved (95% CI, 44-93 seconds; p = 0.000014), or a reduction in interpretation time to 67% of the time without the CAD system. Use of the concurrent-read CAD system for interpretation of screening ABUS studies of women with dense breast tissue who do not have symptoms is expected to make interpretation significantly faster and produce noninferior diagnostic accuracy compared with interpretation without the CAD system.

Monitoring hydrofrac-induced seismicity by surface arrays - the DHM-Project Basel case study

NASA Astrophysics Data System (ADS)

Blascheck, P.; Häge, M.; Joswig, M.

2012-04-01

The method "nanoseismic monitoring" was applied during the hydraulic stimulation at the Deep-Heat-Mining-Project (DHM-Project) Basel. Two small arrays in a distance of 2.1 km and 4.8 km to the borehole recorded continuously for two days. During this time more than 2500 seismic events were detected. The method of the surface monitoring of induced seismicity was compared to the reference which the hydrofrac monitoring presented. The latter was conducted by a network of borehole seismometers by Geothermal Explorers Limited. Array processing provides a outlier resistant, graphical jack-knifing localization method which resulted in a average deviation towards the reference of 850 m. Additionally, by applying the relative localization master-event method, the NNW-SSE strike direction of the reference was confirmed. It was shown that, in order to successfully estimate the magnitude of completeness as well as the b-value at the event rate and detection sensibility present, 3 h segments of data are sufficient. This is supported by two segment out of over 13 h of evaluated data. These segments were chosen so that they represent a time during the high seismic noise during normal working hours in daytime as well as the minimum anthropogenic noise at night. The low signal-to-noise ratio was compensated by the application of a sonogram event detection as well as a coincidence analysis within each array. Sonograms allow by autoadaptive, non-linear filtering to enhance signals whose amplitudes are just above noise level. For these events the magnitude was determined by the master-event method, allowing to compute the magnitude of completeness by the entire-magnitude-range method provided by the ZMAP toolbox. Additionally, the b-values were determined and compared to the reference values. An introduction to the method of "nanoseismic monitoring" will be given as well as the comparison to reference data in the Basel case study.

Historical shoreline mapping (II): Application of the Digital Shoreline Mapping and Analysis Systems (DSMS/DSAS) to shoreline change mapping in Puerto Rico

USGS Publications Warehouse

Thieler, E. Robert; Danforth, William W.

1994-01-01

A new, state-of-the-art method for mapping historical shorelines from maps and aerial photographs, the Digital Shoreline Mapping System (DSMS), has been developed. The DSMS is a freely available, public domain software package that meets the cartographic and photogrammetric requirements of precise coastal mapping, and provides a means to quantify and analyze different sources of error in the mapping process. The DSMS is also capable of resolving imperfections in aerial photography that commonly are assumed to be nonexistent. The DSMS utilizes commonly available computer hardware and software, and permits the entire shoreline mapping process to be executed rapidly by a single person in a small lab. The DSMS generates output shoreline position data that are compatible with a variety of Geographic Information Systems (GIS). A second suite of programs, the Digital Shoreline Analysis System (DSAS) has been developed to calculate shoreline rates-of-change from a series of shoreline data residing in a GIS. Four rate-of-change statistics are calculated simultaneously (end-point rate, average of rates, linear regression and jackknife) at a user-specified interval along the shoreline using a measurement baseline approach. An example of DSMS and DSAS application using historical maps and air photos of Punta Uvero, Puerto Rico provides a basis for assessing the errors associated with the source materials as well as the accuracy of computed shoreline positions and erosion rates. The maps and photos used here represent a common situation in shoreline mapping: marginal-quality source materials. The maps and photos are near the usable upper limit of scale and accuracy, yet the shoreline positions are still accurate ±9.25 m when all sources of error are considered. This level of accuracy yields a resolution of ±0.51 m/yr for shoreline rates-of-change in this example, and is sufficient to identify the short-term trend (36 years) of shoreline change in the study area.

iGPCR-Drug: A Web Server for Predicting Interaction between GPCRs and Drugs in Cellular Networking

PubMed Central

Xiao, Xuan; Min, Jian-Liang; Wang, Pu; Chou, Kuo-Chen

2013-01-01

Involved in many diseases such as cancer, diabetes, neurodegenerative, inflammatory and respiratory disorders, G-protein-coupled receptors (GPCRs) are among the most frequent targets of therapeutic drugs. It is time-consuming and expensive to determine whether a drug and a GPCR are to interact with each other in a cellular network purely by means of experimental techniques. Although some computational methods were developed in this regard based on the knowledge of the 3D (dimensional) structure of protein, unfortunately their usage is quite limited because the 3D structures for most GPCRs are still unknown. To overcome the situation, a sequence-based classifier, called “iGPCR-drug”, was developed to predict the interactions between GPCRs and drugs in cellular networking. In the predictor, the drug compound is formulated by a 2D (dimensional) fingerprint via a 256D vector, GPCR by the PseAAC (pseudo amino acid composition) generated with the grey model theory, and the prediction engine is operated by the fuzzy K-nearest neighbour algorithm. Moreover, a user-friendly web-server for iGPCR-drug was established at http://www.jci-bioinfo.cn/iGPCR-Drug/. For the convenience of most experimental scientists, a step-by-step guide is provided on how to use the web-server to get the desired results without the need to follow the complicated math equations presented in this paper just for its integrity. The overall success rate achieved by iGPCR-drug via the jackknife test was 85.5%, which is remarkably higher than the rate by the existing peer method developed in 2010 although no web server was ever established for it. It is anticipated that iGPCR-Drug may become a useful high throughput tool for both basic research and drug development, and that the approach presented here can also be extended to study other drug – target interaction networks. PMID:24015221

Phylogenetic studies favour the unification of Pennisetum, Cenchrus and Odontelytrum (Poaceae): a combined nuclear, plastid and morphological analysis, and nomenclatural combinations in Cenchrus

PubMed Central

Chemisquy, M. Amelia; Giussani, Liliana M.; Scataglini, María A.; Kellogg, Elizabeth A.; Morrone, Osvaldo

2010-01-01

Backgrounds and Aims Twenty-five genera having sterile inflorescence branches were recognized as the bristle clade within the x = 9 Paniceae (Panicoideae). Within the bristle clade, taxonomic circumscription of Cenchrus (20–25 species), Pennisetum (80–140) and the monotypic Odontelytrum is still unclear. Several criteria have been applied to characterize Cenchrus and Pennisetum, but none of these has proved satisfactory as the diagnostic characters, such as fusion of bristles in the inflorescences, show continuous variation. Methods A phylogenetic analysis based on morphological, plastid (trnL-F, ndhF) and nuclear (knotted) data is presented for a representative species sampling of the genera. All analyses were conducted under parsimony, using heuristic searches with TBR branch swapping. Branch support was assessed with parsimony jackknifing. Key Results Based on plastid and morphological data, Pennisetum, Cenchrus and Odontelytrum were supported as a monophyletic group: the PCO clade. Only one section of Pennisetum (Brevivalvula) was supported as monophyletic. The position of P. lanatum differed among data partitions, although the combined plastid and morphology and nuclear analyses showed this species to be a member of the PCO clade. The basic chromosome number x = 9 was found to be plesiomorphic, and x = 5, 7, 8, 10 and 17 were derived states. The nuclear phylogenetic analysis revealed a reticulate pattern of relationships among Pennisetum and Cenchrus, suggesting that there are at least three different genomes. Because apomixis can be transferred among species through hybridization, its history most likely reflects crossing relationships, rather than multiple independent appearances. Conclusions Due to the consistency between the present results and different phylogenetic hypotheses (including morphological, developmental and multilocus approaches), and the high support found for the PCO clade, also including the type species of the three genera, we propose

Validation of a single-stage fixed-rate step test for the prediction of maximal oxygen uptake in healthy adults.

PubMed

Hansen, Dominique; Jacobs, Nele; Thijs, Herbert; Dendale, Paul; Claes, Neree

2016-09-01

Healthcare professionals with limited access to ergospirometry remain in need of valid and simple submaximal exercise tests to predict maximal oxygen uptake (VO2max ). Despite previous validation studies concerning fixed-rate step tests, accurate equations for the estimation of VO2max remain to be formulated from a large sample of healthy adults between age 18-75 years (n > 100). The aim of this study was to develop a valid equation to estimate VO2max from a fixed-rate step test in a larger sample of healthy adults. A maximal ergospirometry test, with assessment of cardiopulmonary parameters and VO2max , and a 5-min fixed-rate single-stage step test were executed in 112 healthy adults (age 18-75 years). During the step test and subsequent recovery, heart rate was monitored continuously. By linear regression analysis, an equation to predict VO2max from the step test was formulated. This equation was assessed for level of agreement by displaying Bland-Altman plots and calculation of intraclass correlations with measured VO2max . Validity further was assessed by employing a Jackknife procedure. The linear regression analysis generated the following equation to predict VO2max (l min(-1) ) from the step test: 0·054(BMI)+0·612(gender)+3·359(body height in m)+0·019(fitness index)-0·012(HRmax)-0·011(age)-3·475. This equation explained 78% of the variance in measured VO2max (F = 66·15, P<0·001). The level of agreement and intraclass correlation was high (ICC = 0·94, P<0·001) between measured and predicted VO2max . From this study, a valid fixed-rate single-stage step test equation has been developed to estimate VO2max in healthy adults. This tool could be employed by healthcare professionals with limited access to ergospirometry. © 2015 Scandinavian Society of Clinical Physiology and Nuclear Medicine. Published by John Wiley & Sons Ltd.

Nonexercise Equations to Estimate Fitness in White European and South Asian Men.

PubMed

O'Donovan, Gary; Bakrania, Kishan; Ghouri, Nazim; Yates, Thomas; Gray, Laura J; Hamer, Mark; Stamatakis, Emmanuel; Khunti, Kamlesh; Davies, Melanie; Sattar, Naveed; Gill, Jason M R

2016-05-01

Cardiorespiratory fitness is a strong, independent predictor of health, whether it is measured in an exercise test or estimated in an equation. The purpose of this study was to develop and validate equations to estimate fitness in middle-age white European and South Asian men. Multiple linear regression models (n = 168, including 83 white European and 85 South Asian men) were created using variables that are thought to be important in predicting fitness (V˙O2max, mL·kg⁻¹·min⁻¹): age (yr), body mass index (kg·m⁻²), resting HR (bpm); smoking status (0, never smoked; 1, ex or current smoker), physical activity expressed as quintiles (0, quintile 1; 1, quintile 2; 2, quintile 3; 3, quintile 4; 4, quintile 5), categories of moderate- to-vigorous intensity physical activity (MVPA) (0, <75 min·wk⁻¹; 1, 75-150 min·wk⁻¹; 2, >150-225 min·wk⁻¹; 3, >225-300 min·wk⁻¹; 4, >300 min·wk⁻¹), or minutes of MVPA (min·wk⁻¹); and, ethnicity (0, South Asian; 1, white). The leave-one-out cross-validation procedure was used to assess the generalizability, and the bootstrap and jackknife resampling techniques were used to estimate the variance and bias of the models. Around 70% of the variance in fitness was explained in models with an ethnicity variable, such as: V˙O2max = 77.409 - (age × 0.374) - (body mass index × 0.906) - (ex or current smoker × 1.976) + (physical activity quintile coefficient) - (resting HR × 0.066) + (white ethnicity × 8.032), where physical activity quintile 1 is 0, 2 is 1.127, 3 is 1.869, 4 is 3.793, and 5 is 3.029. Only around 50% of the variance was explained in models without an ethnicity variable. All models with an ethnicity variable were generalizable and had low variance and bias. These data demonstrate the importance of incorporating ethnicity in nonexercise equations to estimate cardiorespiratory fitness in multiethnic populations.

Lg Attenuation and Site Response in the SiChuan basin and the Bayan Har block before the 2008 Ms8.0 Wenchuan Earthquake

NASA Astrophysics Data System (ADS)

Zhu, X.

2017-12-01

On 12 May, 2008, the Sichuan province in China suffered the catastrophic Wenchuan earthquake (MS 8). Prior to the event, a large number of small to moderate earthquakes occurred in the area were recorded at stations of SiChuan Seismic Network (SCSN). The wave data were collected during the years 2006-2008, The Fourier amplitude spectra of Lg wave are used to determine attenuation and site responses. We analyze over 3300 seismograms for Lg-wave propagation from 291 local and regional earthquakes recorded at distances from 100 to 700 km, the earthquakes varied in ML2.0 and 5.7.A joint inversion method estimating attenuation and site responses from seismic spectral ratios is implemented in the study; modeling errors are determined using a delete-j jackknife resampling technique.Variations of the Lg attenuation in a chronological order are studied. The event occurred on the Longmen Shan Fault (LSF), the LSF constitutes boundary betweeb Bayan Har block and eastern. The data are divided into two subgroups based on the seismic ray paths which contained entirely within the SiChuan basin or the Bayan Har block. The waveforms were processed in a frequency range of 1-7 Hz with an interval of 0.2 Hz. On the vertical component, Lg Attenuation in the Bayan Har block are fit by a frequency-dependent function Q(f)=250.2±13.7f0.52±0.03,the SiChuan basin is characterized by function Q(f)=193±23f0.0.81±0.05. The obtained attenuation curves indicate that the spectral amplitudes decay faster in the SiChuan basin than in the Bayan Har block. Site responses from the 48 stations are estimated, the site responses vary among these stations by more than a factor of 10 within the frequency range of interest.The results from the regrouping of data in chronological order show that when the Whenchuan earthquake is approaching, the changes in attenuation occur significantly, but the changes in site responses do not occur.

Predictive performance of rainfall thresholds for shallow landslide triggering in Switzerland from daily gridded precipitation data

NASA Astrophysics Data System (ADS)

Leonarduzzi, E.; Molnar, P.; McArdell, B. W.

2017-12-01

In Switzerland floods are responsible for most of the damage caused by rainfall-triggered natural hazards (89%), followed by landslides (6%, almost 600 M USD) as reported in Hilker et al. (2009) for the period 1972-2007. A high-resolution gridded daily precipitation dataset is combined with a landslide inventory containing over 2000 events in the period 1972-2012 to analyze rainfall thresholds that lead to landsliding in Switzerland. First triggering rainfall and landslides are co-located obtaining the distributions of triggering and non-triggering rainfall event properties at the scale of the precipitation data (2*2 km2) and considering 1 day as the interarrival time to separate events. Then rainfall thresholds are obtained by maximizing true positives (accurate predictions) while minimizing false negatives (false alarms), using the True Skill Statistic. The best predictive performance is obtained by the intensity-duration ID threshold curve, followed by peak daily intensity (Imax) and mean event intensity (Imean). Event duration by itself has very low predictive power. In addition to country-wide thresholds, local ones are also defined by regionalization based on surface erodibility and local long-term climate (mean daily precipitation). Different Imax thresholds are determined for each of the regions separately. It is found that wetter local climate and lower erodibility lead to significantly higher rainfall thresholds required to trigger landslides. However, the improvement in model performance due to regionalization is marginal and much lower than what can be achieved by having a high quality landslide database. In order to validate the performance of the Imax rainfall threshold model, reference cases will be presented in which the landslide locations and timing are randomized and the landslide sample size is reduced. Jack-knife and cross-validation experiments demonstrate that the model is robust. The results highlight the potential of using rainfall I

Measurements of the pairwise kinematic Sunyaev-Zel'dovich effect with the Atacama Cosmology Telescope and future surveys

NASA Astrophysics Data System (ADS)

Vavagiakis, Eve Marie; De Bernardis, Francesco; Aiola, Simone; Battaglia, Nicholas; Niemack, Michael D.; ACTPol Collaboration

2017-06-01

We have made improved measurements of the kinematic Sunyaev-Zel’dovich (kSZ) effect using data from the Atacama Cosmology Telescope (ACT) and the Baryon Oscillation Spectroscopic Survey (BOSS). We used a map of the Cosmic Microwave Background (CMB) from two seasons of observations each by ACT and the Atacama Cosmology Telescope Polarimeter (ACTPol) receiver. We evaluated the mean pairwise baryon momentum associated with the positions of 50,000 bright galaxies in the BOSS DR11 Large Scale Structure catalog via 600 square degrees of overlapping sky area. The measurement of the kSZ signal arising from the large-scale motions of clusters was made by fitting data to an analytical model. The free parameter of the fit determined the optical depth to microwave photon scattering for the cluster sample. We estimated the covariance matrix of the mean pairwise momentum as a function of galaxy separation using CMB simulations, jackknife evaluation, and bootstrap estimates. The most conservative simulation-based uncertainties gave signal-to-noise estimates between 3.6 and 4.1 for various luminosity cuts. Additionally, we explored a novel approach to estimating cluster optical depths from the average thermal Sunyaev-Zel’dovich (tSZ) signal at the BOSS DR11 catalog positions. Our results were broadly consistent with those obtained from the kSZ signal. In the future, the tSZ signal may provide a valuable probe of cluster optical depths, enabling the extraction of velocities from the kSZ sourced mean pairwise momenta. New CMB maps from three seasons of ACTPol observations with multi-frequency coverage overlap with nearly four times as many DR11 sources and promise to improve statistics and systematics for SZ measurements. With these and other upcoming data, the pairwise kSZ signal is poised to become a powerful new cosmological tool, able to probe large physical scales to inform neutrino physics and test models of modified gravity and dark energy.

Life history dependent morphometric variation in stream-dwelling Atlantic salmon

USGS Publications Warehouse

Letcher, B.H.

2003-01-01

The time course of morphometric variation among life histories for stream-dwelling Atlantic salmon (Salmo salar L.) parr (age-0+ to age-2+) was analyzed. Possible life histories were combinations of parr maturity status in the autumn (mature or immature) and age at outmigration (smolt at age-2+ or later age). Actual life histories expressed with enough fish for analysis in the 1997 cohort were immature/age-2+ smolt, mature/age-2 +smolt, and mature/age-2+ non-smolt. Tagged fish were assigned to one of the three life histories and digital pictures from the field were analyzed using landmark-based geometric morphometrics. Results indicated that successful grouping of fish according to life history varied with fish age, but that fish could be grouped before the actual expression of the life histories. By March (age-1+), fish were successfully grouped using a descriptive discriminant function and successful assignment ranged from 84 to 97% for the remainder of stream residence. A jackknife of the discriminant function revealed an average life history prediction success of 67% from age-1+ summer to smolting. Low sample numbers for one of the life histories may have limited prediction success. A MANOVA on the shape descriptors (relative warps) also indicated significant differences in shape among life histories from age-1+ summer through to smolting. Across all samples, shape varied significantly with size. Within samples, shape did not vary significantly with size for samples from December (age-0+) to May (age-1+). During the age-1+ summer however, shape varied significantly with size, but the relationship between shape and size was not different among life histories. In the autumn (age-1+) and winter (age-2+), life history differences explained a significant portion of the change in shape with size. Life history dependent morphometric variation may be useful to indicate the timing of early expressions of life history variation and as a tool to explore temporal and

Landslide triggering-thickness susceptibility, a simple proxy for landslide hazard? A test in the Mili catchment (North-Eastern Sicily, Italy)

NASA Astrophysics Data System (ADS)

Lombardo, Luigi; Fubelli, Giandomenico; Amato, Gabriele; Bonasera, Mauro; Mai, Martin

2016-04-01

This study implements a landslide triggering-thickness susceptibility approach in order to investigate the landslide scenario in the catchment of Mili, this being located in the north-easternmost sector of Sicily (Italy). From a detailed geomorphological campaign, thicknesses of mobilised materials at the triggering zone of each mass movement were collected and subsequently used as a dependent variable to be analysed in the framework of spatial predictive models. The adopted modelling methodology consisted of a presence-only learning algorithm which differently from classic presence-absence methods does not rely on stable conditions in order to derive functional relationships between dependent and independent variables. The dependent was pre-processed by reclassifying the crown thickness spectrum into a binary condition expressing thick (values equal or greater than 1m) and thin (values less than 1m) landslide crown classes. The explanatory variables were selected to express triggering-thickness dependency at different scales, these being in close proximity to the triggering point through primary and secondary attributes from a 2m-cell side Lidar HRDEM, at a medium scale through vegetation indexes from multispectral satellite images (ASTER) and a coarser scale through a geological, land use and tectonic maps. The choice of a presence-only approach allowed to effectively discriminate between the two types of landslide thicknesses at the triggering zone, producing excellent prediction skills associated with relatively low variances across a set of 50 randomly generated replicates. In addition, the role of each predictor was assessed for the two considered classes as relevant differences arose in terms of their contribution to the final models. In this regard, predictor importance, Jack-knife tests and response curves were used to assess the reliability of the models together with their geomorphological reasonability. This work attempts to capitalize on fieldwork data

Food selection among Atlantic Coast seaducks in relation to historic food habits

USGS Publications Warehouse

Perry, M.C.; Osenton, P.C.; Wells-Berlin, A. M.; Kidwell, D.M.

2005-01-01

Food selection among Atlantic Coast seaducks during 1999-2005 was determined from hunter-killed ducks and compared to data from historic food habits file (1885-1985) for major migrational and wintering areas in the Atlantic Flyway. Food selection was determined by analyses of the gullet (esophagus and proventriculus) and gizzard of 860 ducks and summarized by aggregate percent for each species. When sample size was adequate comparisons were made among age and sex groupings and also among local sites in major habitat areas. Common eiders in Maine and the Canadian Maritimes fed predominantly (53%) on the blue mussel (Mytilus edulis). Scoters in Massachusetts, Maine, and the Canadian Maritimes fed predominantly on the blue mussel (46%), Atlantic jackknife clam (Ensis directus; 19%), and Atlantic surf clam (Spisula solidissima; 15%), whereas scoters in the Chesapeake Bay fed predominantly on hooked mussel (Ischadium recurvum; 42%), the stout razor clam (Tagelus plebeius; 22%), and dwarf surf clam (Mulinia lateralis; 15%). The amethyst gem clam (Gemma gemma) was the predominant food (45%) of long-tailed ducks in Chesapeake Bay. Buffleheads and common goldeneyes fed on a mixed diet of mollusks and soft bodied invertebrates (amphipods, isopods and polychaetes). No major differences were noticed between the sexes in regard to food selection in any of the wintering areas. Comparisons to historic food habits in all areas failed to detect major differences. However, several invertebrate species recorded in historic samples were not found in current samples and two invasive species (Atlantic Rangia, Rangia cuneata and green crab, Carcinas maenas) were recorded in modem samples, but not in historic samples. Benthic sampling in areas where seaducks were collected showed a close correlation between consumption and availability. Each seaduck species appears to fill a unique niche in regard to feeding ecology, although there is much overlap of prey species selected. Understanding

The Application of Censored Regression Models in Low Streamflow Analyses

NASA Astrophysics Data System (ADS)

Kroll, C.; Luz, J.

2003-12-01

Estimation of low streamflow statistics at gauged and ungauged river sites is often a daunting task. This process is further confounded by the presence of intermittent streamflows, where streamflow is sometimes reported as zero, within a region. Streamflows recorded as zero may be zero, or may be less than the measurement detection limit. Such data is often referred to as censored data. Numerous methods have been developed to characterize intermittent streamflow series. Logit regression has been proposed to develop regional models of the probability annual lowflows series (such as 7-day lowflows) are zero. In addition, Tobit regression, a method of regression that allows for censored dependent variables, has been proposed for lowflow regional regression models in regions where the lowflow statistic of interest estimated as zero at some sites in the region. While these methods have been proposed, their use in practice has been limited. Here a delete-one jackknife simulation is presented to examine the performance of Logit and Tobit models of 7-day annual minimum flows in 6 USGS water resource regions in the United States. For the Logit model, an assessment is made of whether sites are correctly classified as having at least 10% of 7-day annual lowflows equal to zero. In such a situation, the 7-day, 10-year lowflow (Q710), a commonly employed low streamflow statistic, would be reported as zero. For the Tobit model, a comparison is made between results from the Tobit model, and from performing either ordinary least squares (OLS) or principal component regression (PCR) after the zero sites are dropped from the analysis. Initial results for the Logit model indicate this method to have a high probability of correctly classifying sites into groups with Q710s as zero and non-zero. Initial results also indicate the Tobit model produces better results than PCR and OLS when more than 5% of the sites in the region have Q710 values calculated as zero.

Spatial Distribution of Sand Fly Vectors and Eco-Epidemiology of Cutaneous Leishmaniasis Transmission in Colombia

PubMed Central

Ferro, Cristina; López, Marla; Fuya, Patricia; Lugo, Ligia; Cordovez, Juan Manuel; González, Camila

2015-01-01

Background Leishmania is transmitted by Phlebotominae insects that maintain the enzootic cycle by circulating between sylvatic and domestic mammals; humans enter the cycles as accidental hosts due to the vector’s search for blood source. In Colombia, leishmaniasis is an endemic disease and 95% of all cases are cutaneous (CL), these cases have been reported in several regions of the country where the intervention of sylvatic areas by the introduction of agriculture seem to have an impact on the rearrangement of new transmission cycles. Our study aimed to update vector species distribution in the country and to analyze the relationship between vectors’ distribution, climate, land use and CL prevalence. Methods A database with geographic information was assembled, and ecological niche modeling was performed to explore the potential distribution of each of the 21 species of medical importance in Colombia, using thirteen bioclimatic variables, three topographic and three principal components derived from NDVI. Binary models for each species were obtained and related to both land use coverage, and a CL prevalence map with available epidemiological data. Finally, maps of species potential distribution were summed to define potential species richness in the country. Results In total, 673 single records were obtained with Lutzomyia gomezi, Lutzomyia longipalpis, Psychodopygus panamensis, Psathyromyia shannoni and Pintomyia evansi the species with the highest number of records. Eighteen species had significant models, considering the area under the curve and the jackknife results: L. gomezi and P. panamensis had the widest potential distribution. All sand fly species except for Nyssomyia antunesi are mainly distributed in regions with rates of prevalence between 0.33 to 101.35 cases per 100,000 inhabitants and 76% of collection data points fall into transformed ecosystems. Discussion Distribution ranges of sand flies with medical importance in Colombia correspond

Spectroscopic determination of leaf traits using infrared spectra

NASA Astrophysics Data System (ADS)

Buitrago, Maria F.; Groen, Thomas A.; Hecker, Christoph A.; Skidmore, Andrew K.

2018-07-01

Leaf traits characterise and differentiate single species but can also be used for monitoring vegetation structure and function. Conventional methods to measure leaf traits, especially at the molecular level (e.g. water, lignin and cellulose content), are expensive and time-consuming. Spectroscopic methods to estimate leaf traits can provide an alternative approach. In this study, we investigated high spectral resolution (6612 bands) emissivity measurements from the short to the long wave infrared (1.4-16.0 μm) of leaves from 19 different plant species ranging from herbaceous to woody, and from temperate to tropical types. At the same time, we measured 14 leaf traits to characterise a leaf, including chemical (e.g., leaf water content, nitrogen, cellulose) and physical features (e.g., leaf area and leaf thickness). We fitted partial least squares regression (PLSR) models across the SWIR, MWIR and LWIR for each leaf trait. Then, reduced models (PLSRred) were derived by iteratively reducing the number of bands in the model (using a modified Jackknife resampling method with a Martens and Martens uncertainty test) down to a few bands (4-10 bands) that contribute the most to the variation of the trait. Most leaf traits could be determined from infrared data with a moderate accuracy (65 < Rcv2 < 77% for observed versus predicted plots) based on PLSRred models, while the accuracy using the whole infrared range (6612 bands) presented higher accuracies, 74 < Rcv2 < 90%. Using the full SWIR range (1.4-2.5 μm) shows similarly high accuracies compared to the whole infrared. Leaf thickness, leaf water content, cellulose, lignin and stomata density are the traits that could be estimated most accurately from infrared data (with Rcv2 above 0.80 for the full range models). Leaf thickness, cellulose and lignin were predicted with reasonable accuracy from a combination of single infrared bands. Nevertheless, for all leaf traits, a combination of a few bands yields moderate to

Standard-, Reduced-, and No-Dose Thin-Section Radiologic Examinations: Comparison of Capability for Nodule Detection and Nodule Type Assessment in Patients Suspected of Having Pulmonary Nodules.

PubMed

Ohno, Yoshiharu; Koyama, Hisanobu; Yoshikawa, Takeshi; Kishida, Yuji; Seki, Shinichiro; Takenaka, Daisuke; Yui, Masao; Miyazaki, Mitsue; Sugimura, Kazuro

2017-08-01

Purpose To compare the capability of pulmonary thin-section magnetic resonance (MR) imaging with ultrashort echo time (UTE) with that of standard- and reduced-dose thin-section computed tomography (CT) in nodule detection and evaluation of nodule type. Materials and Methods The institutional review board approved this study, and written informed consent was obtained from each patient. Standard- and reduced-dose chest CT (60 and 250 mA) and MR imaging with UTE were used to examine 52 patients; 29 were men (mean age, 66.4 years ± 7.3 [standard deviation]; age range, 48-79 years) and 23 were women (mean age, 64.8 years ± 10.1; age range, 42-83 years). Probability of nodule presence was assessed for all methods with a five-point visual scoring system. All nodules were then classified as missed, ground-glass, part-solid, or solid nodules. To compare nodule detection capability of the three methods, consensus for performances was rated by using jackknife free-response receiver operating characteristic analysis, and κ analysis was used to compare intermethod agreement for nodule type classification. Results There was no significant difference (F = 0.70, P = .59) in figure of merit between methods (standard-dose CT, 0.86; reduced-dose CT, 0.84; MR imaging with UTE, 0.86). There was no significant difference in sensitivity between methods (standard-dose CT vs reduced-dose CT, P = .50; standard-dose CT vs MR imaging with UTE, P = .50; reduced-dose CT vs MR imaging with UTE, P >.99). Intermethod agreement was excellent (standard-dose CT vs reduced-dose CT, κ = 0.98, P < .001; standard-dose CT vs MR imaging with UTE, κ = 0.98, P < .001; reduced-dose CT vs MR imaging with UTE, κ = 0.99, P < .001). Conclusion Pulmonary thin-section MR imaging with UTE was useful in nodule detection and evaluation of nodule type, and it is considered at least as efficacious as standard- or reduced-dose thin-section CT. © RSNA, 2017 Online supplemental material is available for this article.

Association between structural and functional brain alterations in drug-free patients with schizophrenia: a multimodal meta-analysis

PubMed

Gao, Xin; Zhang, Wenjing; Yao, Li; Xiao, Yuan; Liu, Lu; Liu, Jieke; Li, Siyi; Tao, Bo; Shah, Chandan; Gong, Qiyong; Sweeney, John; Lui, Su

2017-12-05

Neuroimaging studies have shown both structural and functional abnormalities in patients with schizophrenia. Recently, studies have begun to explore the association between structural and functional grey matter abnormalities. By conducting a meta­-analysis on morphometric and functional imaging studies of grey matter alterations in drug-free patients, the present study aims to examine the degree of overlap between brain regions with anatomic and functional changes in patients with schizophrenia. We performed a systematic search of PubMed, Embase, Web of Science and the Cochrane Library to identify relevant publications. A multimodal analysis was then conducted using Seed-based d Mapping software. Exploratory analyses included jackknife, subgroup and meta-regression analyses. We included 15 structural MRI studies comprising 486 drug-free patients and 485 healthy controls, and 16 functional MRI studies comprising 403 drug-free patients and 428 controls in our meta-analysis. Drug-free patients were examined to reduce pharmacological effects on the imaging data. Multimodal analysis showed considerable overlap between anatomic and functional changes, mainly in frontotemporal regions, bilateral medial posterior cingulate/paracingulate gyrus, bilateral insula, basal ganglia and left cerebellum. There were also brain regions showing only anatomic changes in the right superior frontal gyrus, left supramarginal gyrus, right lingual gyrus and functional alternations involving the right angular ­gyrus. The methodological aspects, patient characteristics and clinical variables of the included studies were heterogeneous, and we cannot exclude medication effects. The present study showed overlapping anatomic and functional brain abnormalities mainly in the default mode (DMN) and auditory networks (AN) in drug-free patients with schizophrenia. However, the pattern of changes differed in these networks. Decreased grey matter was associated with decreased activation within the DMN

School-age effects of the newborn individualized developmental care and assessment program for preterm infants with intrauterine growth restriction: preliminary findings.

PubMed

McAnulty, Gloria; Duffy, Frank H; Kosta, Sandra; Weisenfeld, Neil I; Warfield, Simon K; Butler, Samantha C; Alidoost, Moona; Bernstein, Jane Holmes; Robertson, Richard; Zurakowski, David; Als, Heidelise

2013-02-19

The experience in the newborn intensive care nursery results in premature infants' neurobehavioral and neurophysiological dysfunction and poorer brain structure. Preterms with severe intrauterine growth restriction are doubly jeopardized given their compromised brains. The Newborn Individualized Developmental Care and Assessment Program improved outcome at early school-age for preterms with appropriate intrauterine growth. It also showed effectiveness to nine months for preterms with intrauterine growth restriction. The current study tested effectiveness into school-age for preterms with intrauterine growth restriction regarding executive function (EF), electrophysiology (EEG) and neurostructure (MRI). Twenty-three 9-year-old former growth-restricted preterms, randomized at birth to standard care (14 controls) or to the Newborn Individualized Developmental Care and Assessment Program (9 experimentals) were assessed with standardized measures of cognition, achievement, executive function, electroencephalography, and magnetic resonance imaging. The participating children were comparable to those lost to follow-up, and the controls to the experimentals, in terms of newborn background health and demographics. All outcome measures were corrected for mother's intelligence. Analysis techniques included two-group analysis of variance and stepwise discriminate analysis for the outcome measures, Wilks' lambda and jackknifed classification to ascertain two-group classification success per and across domains; canonical correlation analysis to explore relationships among neuropsychological, electrophysiological and neurostructural domains at school-age, and from the newborn period to school-age. Controls and experimentals were comparable in age at testing, anthropometric and health parameters, and in cognitive and achievement scores. Experimentals scored better in executive function, spectral coherence, and cerebellar volumes. Furthermore, executive function, spectral coherence

Preliminary clinical evaluation of a noninvasive device for the measurement of coagulability in the elderly.

PubMed

Lerman, Yaffa; Werber, Moshe M; Fine, Ilya; Kemelman, Polina

2011-01-01

The feasibility of the noninvasive assessment of blood 'coagulability' (the tendency to coagulate) has been tested by using a novel device, the Thrombo-Monitor. It monitors, by using the principles of near infra-red (NIR) dynamic light scattering, the tendency of blood to create clots. The Thrombo-Monitor observes the very initial changes of blood viscosity, which occurs due to the temporarily induced stasis of capillary blood of the finger. One hundred and fifteen patients aged >65 years (matched by age and sex) participated in the study. Patients were initially divided into four groups based on the patient's medical therapy. The study groups were: warfarin, enoxaparin, aspirin and/or clopidogrel, and a control group. The medications were given according to the patient's comorbidities (eg, atrial fibrillation [AF], status post pulmonary embolism [S/p PE], status post cerebrovascular accident [S/p CVA]). The Thrombo-Monitor Index (TMI) is a noninvasive index, derived on the basis of laboratory test results of international normalized ratio (INR) and prothrombin time (PT) values. For the group of patients who were treated only with warfarin, TMI was adjusted by using the jackknife statistical approach to create maximum correlation and linearity with INR and PT values that ranged from 1.1 to 5.0. For all warfarin patients (N = 35) the TMI was found to have a good correlation with INR and PT values (R(2) = 0.64, P < 0.00001); mean TMI = 1.86 (SD = 0.91); mean INR and PT = 2.3 (SD = 0.91). The calibration curve thus generated was used to calculate the TMI for all other groups: aspirin group, mean TMI = 1.3 (SD = 0.14, N = 23), corresponding approximately to INR and PT values of 1.036; enoxaparin group (N = 24), mean TMI = 1.34 (SD = 0.304), corresponding to mean INR and PT values of 1.07 (SD = 0.3); control group, INR and PT ≥ 1 (N = 32), mean TMI = 1.24 (SD = 0.32). R(2) of all control and warfarin patients (N = 67) was 0.55 (P < 0.00001). In summary, the newly

High accuracy prediction of beta-turns and their types using propensities and multiple alignments.

PubMed

Fuchs, Patrick F J; Alix, Alain J P

2005-06-01

We have developed a method that predicts both the presence and the type of beta-turns, using a straightforward approach based on propensities and multiple alignments. The propensities were calculated classically, but the way to use them for prediction was completely new: starting from a tetrapeptide sequence on which one wants to evaluate the presence of a beta-turn, the propensity for a given residue is modified by taking into account all the residues present in the multiple alignment at this position. The evaluation of a score is then done by weighting these propensities by the use of Position-specific score matrices generated by PSI-BLAST. The introduction of secondary structure information predicted by PSIPRED or SSPRO2 as well as taking into account the flanking residues around the tetrapeptide improved the accuracy greatly. This latter evaluated on a database of 426 reference proteins (previously used on other studies) by a sevenfold crossvalidation gave very good results with a Matthews Correlation Coefficient (MCC) of 0.42 and an overall prediction accuracy of 74.8%; this places our method among the best ones. A jackknife test was also done, which gave results within the same range. This shows that it is possible to reach neural networks accuracy with considerably less computional cost and complexity. Furthermore, propensities remain excellent descriptors of amino acid tendencies to belong to beta-turns, which can be useful for peptide or protein engineering and design. For beta-turn type prediction, we reached the best accuracy ever published in terms of MCC (except for the irregular type IV) in the range of 0.25-0.30 for types I, II, and I' and 0.13-0.15 for types VIII, II', and IV. To our knowledge, our method is the only one available on the Web that predicts types I' and II'. The accuracy evaluated on two larger databases of 547 and 823 proteins was not improved significantly. All of this was implemented into a Web server called COUDES (French acronym

Estimation of parameters of dose volume models and their confidence limits

NASA Astrophysics Data System (ADS)

van Luijk, P.; Delvigne, T. C.; Schilstra, C.; Schippers, J. M.

2003-07-01

Predictions of the normal-tissue complication probability (NTCP) for the ranking of treatment plans are based on fits of dose-volume models to clinical and/or experimental data. In the literature several different fit methods are used. In this work frequently used methods and techniques to fit NTCP models to dose response data for establishing dose-volume effects, are discussed. The techniques are tested for their usability with dose-volume data and NTCP models. Different methods to estimate the confidence intervals of the model parameters are part of this study. From a critical-volume (CV) model with biologically realistic parameters a primary dataset was generated, serving as the reference for this study and describable by the NTCP model. The CV model was fitted to this dataset. From the resulting parameters and the CV model, 1000 secondary datasets were generated by Monte Carlo simulation. All secondary datasets were fitted to obtain 1000 parameter sets of the CV model. Thus the 'real' spread in fit results due to statistical spreading in the data is obtained and has been compared with estimates of the confidence intervals obtained by different methods applied to the primary dataset. The confidence limits of the parameters of one dataset were estimated using the methods, employing the covariance matrix, the jackknife method and directly from the likelihood landscape. These results were compared with the spread of the parameters, obtained from the secondary parameter sets. For the estimation of confidence intervals on NTCP predictions, three methods were tested. Firstly, propagation of errors using the covariance matrix was used. Secondly, the meaning of the width of a bundle of curves that resulted from parameters that were within the one standard deviation region in the likelihood space was investigated. Thirdly, many parameter sets and their likelihood were used to create a likelihood-weighted probability distribution of the NTCP. It is concluded that for the

Evaluation of clinical image processing algorithms used in digital mammography.

PubMed

Zanca, Federica; Jacobs, Jurgen; Van Ongeval, Chantal; Claus, Filip; Celis, Valerie; Geniets, Catherine; Provost, Veerle; Pauwels, Herman; Marchal, Guy; Bosmans, Hilde

2009-03-01

Screening is the only proven approach to reduce the mortality of breast cancer, but significant numbers of breast cancers remain undetected even when all quality assurance guidelines are implemented. With the increasing adoption of digital mammography systems, image processing may be a key factor in the imaging chain. Although to our knowledge statistically significant effects of manufacturer-recommended image processings have not been previously demonstrated, the subjective experience of our radiologists, that the apparent image quality can vary considerably between different algorithms, motivated this study. This article addresses the impact of five such algorithms on the detection of clusters of microcalcifications. A database of unprocessed (raw) images of 200 normal digital mammograms, acquired with the Siemens Novation DR, was collected retrospectively. Realistic simulated microcalcification clusters were inserted in half of the unprocessed images. All unprocessed images were subsequently processed with five manufacturer-recommended image processing algorithms (Agfa Musica 1, IMS Raffaello Mammo 1.2, Sectra Mamea AB Sigmoid, Siemens OPVIEW v2, and Siemens OPVIEW v1). Four breast imaging radiologists were asked to locate and score the clusters in each image on a five point rating scale. The free-response data were analyzed by the jackknife free-response receiver operating characteristic (JAFROC) method and, for comparison, also with the receiver operating characteristic (ROC) method. JAFROC analysis revealed highly significant differences between the image processings (F = 8.51, p < 0.0001), suggesting that image processing strongly impacts the detectability of clusters. Siemens OPVIEW2 and Siemens OPVIEW1 yielded the highest and lowest performances, respectively. ROC analysis of the data also revealed significant differences between the processing but at lower significance (F = 3.47, p = 0.0305) than JAFROC. Both statistical analysis methods revealed that the

Subspace Dimensionality: A Tool for Automated QC in Seismic Array Processing

NASA Astrophysics Data System (ADS)

Rowe, C. A.; Stead, R. J.; Begnaud, M. L.

2013-12-01

identifying bad array elements through a jackknifing process to isolate the anomalous channels, so that an automated analysis system might discard them prior to FK analysis and beamforming on events of interest.

One year survival of ART and conventional restorations in patients with disability

PubMed Central

2014-01-01

Background Providing restorative treatment for persons with disability may be challenging and has been related to the patient’s ability to cope with the anxiety engendered by treatment and to cooperate fully with the demands of the clinical situation. The aim of the present study was to assess the survival rate of ART restorations compared to conventional restorations in people with disability referred for special care dentistry. Methods Three treatment protocols were distinguished: ART (hand instruments/high-viscosity glass-ionomer); conventional restorative treatment (rotary instrumentation/resin composite) in the clinic (CRT/clinic) and under general anaesthesia (CRT/GA). Patients were referred for restorative care to a special care centre and treated by one of two specialists. Patients and/or their caregivers were provided with written and verbal information regarding the proposed techniques, and selected the type of treatment they were to receive. Treatment was provided as selected but if this option proved clinically unfeasible one of the alternative techniques was subsequently proposed. Evaluation of restoration survival was performed by two independent trained and calibrated examiners using established ART restoration assessment codes at 6 months and 12 months. The Proportional Hazard model with frailty corrections was applied to calculate survival estimates over a one year period. Results 66 patients (13.6 ± 7.8 years) with 16 different medical disorders participated. CRT/clinic proved feasible for 5 patients (7.5%), the ART approach for 47 patients (71.2%), and 14 patients received CRT/GA (21.2%). In all, 298 dentine carious lesions were restored in primary and permanent teeth, 182 (ART), 21 (CRT/clinic) and 95 (CRT/GA). The 1-year survival rates and jackknife standard error of ART and CRT restorations were 97.8 ± 1.0% and 90.5 ± 3.2%, respectively (p = 0.01). Conclusions These short-term results indicate that ART appears to be an

EEG spectral coherence data distinguish chronic fatigue syndrome patients from healthy controls and depressed patients--a case control study.

PubMed

Duffy, Frank H; McAnulty, Gloria B; McCreary, Michelle C; Cuchural, George J; Komaroff, Anthony L

2011-07-01

Previous studies suggest central nervous system involvement in chronic fatigue syndrome (CFS), yet there are no established diagnostic criteria. CFS may be difficult to differentiate from clinical depression. The study's objective was to determine if spectral coherence, a computational derivative of spectral analysis of the electroencephalogram (EEG), could distinguish patients with CFS from healthy control subjects and not erroneously classify depressed patients as having CFS. This is a study, conducted in an academic medical center electroencephalography laboratory, of 632 subjects: 390 healthy normal controls, 70 patients with carefully defined CFS, 24 with major depression, and 148 with general fatigue. Aside from fatigue, all patients were medically healthy by history and examination. EEGs were obtained and spectral coherences calculated after extensive artifact removal. Principal Components Analysis identified coherence factors and corresponding factor loading patterns. Discriminant analysis determined whether spectral coherence factors could reliably discriminate CFS patients from healthy control subjects without misclassifying depression as CFS. Analysis of EEG coherence data from a large sample (n = 632) of patients and healthy controls identified 40 factors explaining 55.6% total variance. Factors showed highly significant group differentiation (p < .0004) identifying 89.5% of unmedicated female CFS patients and 92.4% of healthy female controls. Recursive jackknifing showed predictions were stable. A conservative 10-factor discriminant function model was subsequently applied, and also showed highly significant group discrimination (p < .001), accurately classifying 88.9% unmedicated males with CFS, and 82.4% unmedicated male healthy controls. No patient with depression was classified as having CFS. The model was less accurate (73.9%) in identifying CFS patients taking psychoactive medications. Factors involving the temporal lobes were of primary

The relative roles of types of extracurricular activity on smoking and drinking initiation among tweens.

PubMed

Adachi-Mejia, Anna M; Gibson Chambers, Jennifer J; Li, Zhigang; Sargent, James D

2014-01-01

Youth involvement in extracurricular activities may help prevent smoking and drinking initiation. However, the relative roles of types of extracurricular activity on these risks are unclear. Therefore, we examined the association between substance use and participation in team sports with a coach, other sports without a coach, music, school clubs, and other clubs in a nationally representative sample of U.S. tweens. We conducted telephone surveys with 6522 U.S. students (ages 10 to 14 years) in 2003. We asked participants if they had ever tried smoking or drinking, and we asked them about their participation in extracurricular activities. We used sample weighting to produce response estimates that were representative of the population of adolescents aged 10 to 14 years at the time of data collection. Logistic regression models that adjusted for appropriate sampling weights using jackknife variance estimation tested associations with trying smoking and drinking, controlling for sociodemographics, child and parent characteristics, friend/sibling/parent substance use, and media use. A little over half of the students reported participating in team sports with a coach (55.5%) and without a coach (55.4%) a few times per week or more. Most had minimal to no participation in school clubs (74.2%); however, most reported being involved in other clubs (85.8%). A little less than half participated in music, choir, dance, and/or band lessons. Over half of participants involved in religious activity did those activities a few times per week or more. In the multiple regression analysis, team sport participation with a coach was the only extracurricular activity associated with lower risk of trying smoking (adjusted odds ratio 0.68, 95% confidence interval 0.49, 0.96) compared to none or minimal participation. Participating in other clubs was the only extracurricular activity associated with lower risk of trying drinking (adjusted odds ratio 0.56, 95% confidence interval 0.32, 0

RNA-Seq Meta-analysis identifies genes in skeletal muscle associated with gain and intake across a multi-season study of crossbred beef steers.

PubMed

Keel, Brittney N; Zarek, Christina M; Keele, John W; Kuehn, Larry A; Snelling, Warren M; Oliver, William T; Freetly, Harvey C; Lindholm-Perry, Amanda K

2018-06-04

Feed intake and body weight gain are economically important inputs and outputs of beef production systems. The purpose of this study was to discover differentially expressed genes that will be robust for feed intake and gain across a large segment of the cattle industry. Transcriptomic studies often suffer from issues with reproducibility and cross-validation. One way to improve reproducibility is by integrating multiple datasets via meta-analysis. RNA sequencing (RNA-Seq) was performed on longissimus dorsi muscle from 80 steers (5 cohorts, each with 16 animals) selected from the outside fringe of a bivariate gain and feed intake distribution to understand the genes and pathways involved in feed efficiency. In each cohort, 16 steers were selected from one of four gain and feed intake phenotypes (n = 4 per phenotype) in a 2 × 2 factorial arrangement with gain and feed intake as main effect variables. Each cohort was analyzed as a single experiment using a generalized linear model and results from the 5 cohort analyses were combined in a meta-analysis to identify differentially expressed genes (DEG) across the cohorts. A total of 51 genes were differentially expressed for the main effect of gain, 109 genes for the intake main effect, and 11 genes for the gain x intake interaction (P corrected  < 0.05). A jackknife sensitivity analysis showed that, in general, the meta-analysis produced robust DEGs for the two main effects and their interaction. Pathways identified from over-represented genes included mitochondrial energy production and oxidative stress pathways for the main effect of gain due to DEG including GPD1, NDUFA6, UQCRQ, ACTC1, and MGST3. For intake, metabolic pathways including amino acid biosynthesis and degradation were identified, and for the interaction analysis the pathways identified included GADD45, pyridoxal 5'phosphate salvage, and caveolar mediated endocytosis signaling. Variation among DEG identified by cohort suggests that

iNR-PhysChem: A Sequence-Based Predictor for Identifying Nuclear Receptors and Their Subfamilies via Physical-Chemical Property Matrix

PubMed Central

Xiao, Xuan; Wang, Pu; Chou, Kuo-Chen

2012-01-01

Nuclear receptors (NRs) form a family of ligand-activated transcription factors that regulate a wide variety of biological processes, such as homeostasis, reproduction, development, and metabolism. Human genome contains 48 genes encoding NRs. These receptors have become one of the most important targets for therapeutic drug development. According to their different action mechanisms or functions, NRs have been classified into seven subfamilies. With the avalanche of protein sequences generated in the postgenomic age, we are facing the following challenging problems. Given an uncharacterized protein sequence, how can we identify whether it is a nuclear receptor? If it is, what subfamily it belongs to? To address these problems, we developed a predictor called iNR-PhysChem in which the protein samples were expressed by a novel mode of pseudo amino acid composition (PseAAC) whose components were derived from a physical-chemical matrix via a series of auto-covariance and cross-covariance transformations. It was observed that the overall success rate achieved by iNR-PhysChem was over 98% in identifying NRs or non-NRs, and over 92% in identifying NRs among the following seven subfamilies: NR1thyroid hormone like, NR2HNF4-like, NR3estrogen like, NR4nerve growth factor IB-like, NR5fushi tarazu-F1 like, NR6germ cell nuclear factor like, and NR0knirps like. These rates were derived by the jackknife tests on a stringent benchmark dataset in which none of protein sequences included has pairwise sequence identity to any other in a same subset. As a user-friendly web-server, iNR-PhysChem is freely accessible to the public at either http://www.jci-bioinfo.cn/iNR-PhysChem or http://icpr.jci.edu.cn/bioinfo/iNR-PhysChem. Also a step-by-step guide is provided on how to use the web-server to get the desired results without the need to follow the complicated mathematics involved in developing the predictor. It is anticipated that iNR-PhysChem may become a useful high throughput tool

Waveform complexity caused by near trench structure and its impact on earthquake source study: application to the 2015 Illapel earthquake sequence

NASA Astrophysics Data System (ADS)

Qian, Y.; Wei, S.; Wu, W.; Ni, S.

2017-12-01

Among various types of 3D heterogeneity in the Earth, trench might be the most complex systems, which includes rapidly varying bathymetry and usually thick sediment below water layer. These structure complexities can cause substantial waveform complexities on seismograms, but their corresponding impact on the earthquake source studies has not yet been well understood. Here we explore those effects via studies of two moderate aftershocks (one near the coast while the other close to the Peru-Chile trench axis) in the 2015 Illapel earthquake sequence. The horizontal locations and depths of these two events are poorly constrained and the reported results of various agencies display substantial variations. Thus, we first relocated the epicenters using the P-wave first arrivals and determined other parameters by waveform fitting. In a jackknifing way, we found that the trench event has large differences between regional and teleseismic solutions, in particular for depth, while the coastal event shows consistent results. The teleseismic P/Pdiff waves between these two events also display distinctly different features. More specifically, the trench event has more complex P/Pdiff waves and stronger coda waves, in terms of amplitude and duration (longer than 100s). The coda waves are coherent across stations at different distances and azimuths, indicating a more likely origin of scattering waves due to 3D heterogeneity near trench. To quantitatively model those 3D effects, we adopted a hybrid waveform simulation approach that computes the 3D wavefield in the source region by the Spectral Element Method (SEM) and then propagates the wavefield to teleseismic and shadow zone distances through the Direct Solution Method (DSM). We incorporated the GEBCO bathymetry and water layer into the SEM simulations and assumed the IASP91 1D model for DSM computation. Comparing with the poor 1D synthetics fitting to the data, we do obtain dramatic improvement in 3D waveform fittings across a

Effect of Quantitative Nuclear Image Features on Recurrence of Ductal Carcinoma In Situ (DCIS) of the Breast

PubMed Central

Axelrod, David E.; Miller, Naomi A.; Lickley, H. Lavina; Qian, Jin; Christens-Barry, William A.; Yuan, Yan; Fu, Yuejiao; Chapman, Judith-Anne W.

2008-01-01

Background Nuclear grade has been associated with breast DCIS recurrence and progression to invasive carcinoma; however, our previous study of a cohort of patients with breast DCIS did not find such an association with outcome. Fifty percent of patients had heterogeneous DCIS with more than one nuclear grade. The aim of the current study was to investigate the effect of quantitative nuclear features assessed with digital image analysis on ipsilateral DCIS recurrence. Methods Hematoxylin and eosin stained slides for a cohort of 80 patients with primary breast DCIS were reviewed and two fields with representative grade (or grades) were identified by a Pathologist and simultaneously used for acquisition of digital images for each field. Van Nuys worst nuclear grade was assigned, as was predominant grade, and heterogeneous grading when present. Patients were grouped by heterogeneity of their nuclear grade: Group A: nuclear grade 1 only, nuclear grades 1 and 2, or nuclear grade 2 only (32 patients), Group B: nuclear grades 1, 2 and 3, or nuclear grades 2 and 3 (31 patients), Group 3: nuclear grade 3 only (17 patients). Nuclear fine structure was assessed by software which captured thirty-nine nuclear feature values describing nuclear morphometry, densitometry, and texture. Step-wise forward Cox regressions were performed with previous clinical and pathologic factors, and the new image analysis features. Results Duplicate measurements were similar for 89.7% to 97.4% of assessed image features. The rate of correct classification of nuclear grading with digital image analysis features was similar in the two fields, and pooled assessment across both fields. In the pooled assessment, a discriminant function with one nuclear morphometric and one texture feature was significantly (p = 0.001) associated with nuclear grading, and provided correct jackknifed classification of a patient’s nuclear grade for Group A (78.1%), Group B (48.4%), and Group C (70.6%). The factors

A Designed Experiments Approach to Optimizing MALDI-TOF MS Spectrum Processing Parameters Enhances Detection of Antibiotic Resistance in Campylobacter jejuni

PubMed Central

Penny, Christian; Grothendick, Beau; Zhang, Lin; Borror, Connie M.; Barbano, Duane; Cornelius, Angela J.; Gilpin, Brent J.; Fagerquist, Clifton K.; Zaragoza, William J.; Jay-Russell, Michele T.; Lastovica, Albert J.; Ragimbeau, Catherine; Cauchie, Henry-Michel; Sandrin, Todd R.

2016-01-01

MALDI-TOF MS has been utilized as a reliable and rapid tool for microbial fingerprinting at the genus and species levels. Recently, there has been keen interest in using MALDI-TOF MS beyond the genus and species levels to rapidly identify antibiotic resistant strains of bacteria. The purpose of this study was to enhance strain level resolution for Campylobacter jejuni through the optimization of spectrum processing parameters using a series of designed experiments. A collection of 172 strains of C. jejuni were collected from Luxembourg, New Zealand, North America, and South Africa, consisting of four groups of antibiotic resistant isolates. The groups included: (1) 65 strains resistant to cefoperazone (2) 26 resistant to cefoperazone and beta-lactams (3) 5 strains resistant to cefoperazone, beta-lactams, and tetracycline, and (4) 76 strains resistant to cefoperazone, teicoplanin, amphotericin, B and cephalothin. Initially, a model set of 16 strains (three biological replicates and three technical replicates per isolate, yielding a total of 144 spectra) of C. jejuni was subjected to each designed experiment to enhance detection of antibiotic resistance. The most optimal parameters were applied to the larger collection of 172 isolates (two biological replicates and three technical replicates per isolate, yielding a total of 1,031 spectra). We observed an increase in antibiotic resistance detection whenever either a curve based similarity coefficient (Pearson or ranked Pearson) was applied rather than a peak based (Dice) and/or the optimized preprocessing parameters were applied. Increases in antimicrobial resistance detection were scored using the jackknife maximum similarity technique following cluster analysis. From the first four groups of antibiotic resistant isolates, the optimized preprocessing parameters increased detection respective to the aforementioned groups by: (1) 5% (2) 9% (3) 10%, and (4) 2%. An additional second categorization was created from the

Growing season temperatures in Europe and climate forcings over the past 1400 years.

PubMed

Guiot, Joel; Corona, Christophe

2010-04-01

The lack of instrumental data before the mid-19th-century limits our understanding of present warming trends. In the absence of direct measurements, we used proxies that are natural or historical archives recording past climatic changes. A gridded reconstruction of spring-summer temperature was produced for Europe based on tree-rings, documentaries, pollen assemblages and ice cores. The majority of proxy series have an annual resolution. For a better inference of long-term climate variation, they were completed by low-resolution data (decadal or more), mostly on pollen and ice-core data. An original spectral analog method was devised to deal with this heterogeneous dataset, and to preserve long-term variations and the variability of temperature series. So we can replace the recent climate changes in a broader context of the past 1400 years. This preservation is possible because the method is not based on a calibration (regression) but on similarities between assemblages of proxies. The reconstruction of the April-September temperatures was validated with a Jack-knife technique. It was also compared to other spatially gridded temperature reconstructions, literature data, and glacier advance and retreat curves. We also attempted to relate the spatial distribution of European temperature anomalies to known solar and volcanic forcings. We found that our results were accurate back to 750. Cold periods prior to the 20(th) century can be explained partly by low solar activity and/or high volcanic activity. The Medieval Warm Period (MWP) could be correlated to higher solar activity. During the 20(th) century, however only anthropogenic forcing can explain the exceptionally high temperature rise. Warm periods of the Middle Age were spatially more heterogeneous than last decades, and then locally it could have been warmer. However, at the continental scale, the last decades were clearly warmer than any period of the last 1400 years. The heterogeneity of MWP versus the

SU-D-207B-07: Development of a CT-Radiomics Based Early Response Prediction Model During Delivery of Chemoradiation Therapy for Pancreatic Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klawikowski, S; Christian, J; Schott, D

Purpose: Pilot study developing a CT-texture based model for early assessment of treatment response during the delivery of chemoradiation therapy (CRT) for pancreatic cancer. Methods: Daily CT data acquired for 24 pancreatic head cancer patients using CT-on-rails, during the routine CT-guided CRT delivery with a radiation dose of 50.4 Gy in 28 fractions, were analyzed. The pancreas head was contoured on each daily CT. Texture analysis was performed within the pancreas head contour using a research tool (IBEX). Over 1300 texture metrics including: grey level co-occurrence, run-length, histogram, neighborhood intensity difference, and geometrical shape features were calculated for each dailymore » CT. Metric-trend information was established by finding the best fit of either a linear, quadratic, or exponential function for each metric value verses accumulated dose. Thus all the daily CT texture information was consolidated into a best-fit trend type for a given patient and texture metric. Linear correlation was performed between the patient histological response vector (good, medium, poor) and all combinations of 23 patient subgroups (statistical jackknife) determining which metrics were most correlated to response and repeatedly reliable across most patients. Control correlations against CT scanner, reconstruction kernel, and gated/nongated CT images were also calculated. Euclidean distance measure was used to group/sort patient vectors based on the data of these trend-response metrics. Results: We found four specific trend-metrics (Gray Level Coocurence Matrix311-1InverseDiffMomentNorm, Gray Level Coocurence Matrix311-1InverseDiffNorm, Gray Level Coocurence Matrix311-1 Homogeneity2, and Intensity Direct Local StdMean) that were highly correlated with patient response and repeatedly reliable. Our four trend-metric model successfully ordered our pilot response dataset (p=0.00070). We found no significant correlation to our control parameters: gating (p=0

Computer-aided detection of breast masses: Four-view strategy for screening mammography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wei Jun; Chan Heangping; Zhou Chuan

2011-04-15

Purpose: To improve the performance of a computer-aided detection (CAD) system for mass detection by using four-view information in screening mammography. Methods: The authors developed a four-view CAD system that emulates radiologists' reading by using the craniocaudal and mediolateral oblique views of the ipsilateral breast to reduce false positives (FPs) and the corresponding views of the contralateral breast to detect asymmetry. The CAD system consists of four major components: (1) Initial detection of breast masses on individual views, (2) information fusion of the ipsilateral views of the breast (referred to as two-view analysis), (3) information fusion of the corresponding viewsmore » of the contralateral breast (referred to as bilateral analysis), and (4) fusion of the four-view information with a decision tree. The authors collected two data sets for training and testing of the CAD system: A mass set containing 389 patients with 389 biopsy-proven masses and a normal set containing 200 normal subjects. All cases had four-view mammograms. The true locations of the masses on the mammograms were identified by an experienced MQSA radiologist. The authors randomly divided the mass set into two independent sets for cross validation training and testing. The overall test performance was assessed by averaging the free response receiver operating characteristic (FROC) curves of the two test subsets. The FP rates during the FROC analysis were estimated by using the normal set only. The jackknife free-response ROC (JAFROC) method was used to estimate the statistical significance of the difference between the test FROC curves obtained with the single-view and the four-view CAD systems. Results: Using the single-view CAD system, the breast-based test sensitivities were 58% and 77% at the FP rates of 0.5 and 1.0 per image, respectively. With the four-view CAD system, the breast-based test sensitivities were improved to 76% and 87% at the corresponding FP rates

The relative roles of types of extracurricular activity on smoking and drinking initiation among tweens

PubMed Central

Adachi-Mejia, Anna M.; Gibson Chambers, Jennifer J.; Li, Zhigang; Sargent, James D.

2014-01-01

Objective Youth involvement in extracurricular activities may help prevent smoking and drinking initiation. However, the relative roles of types of extracurricular activity on these risks are unclear. Therefore, we examined the association between substance use and participation in team sports with a coach, other sports without a coach, music, school clubs, and other clubs in a nationally representative sample of US tweens. Methods We conducted telephone surveys with 6,522 U.S. students (ages 10-14) in 2003. We asked participants if they had ever tried smoking or drinking and about their participation in extracurricular activities. We used sample weighting to produce response estimates that were representative of the population of adolescents aged 10-14 years at the time of data collection. Logistic regression models that adjusted for appropriate sampling weights using Jackknife variance estimation tested associations with trying smoking and drinking, controlling for sociodemographics, child and parent characteristics, friend/sibling/parent substance use, and media use. Results A little over half of the students reported participating in team sports with a coach (55.5%) and without a coach (55.4%) a few times per week or more. Most had minimal to no participation in school clubs (74.2%), however most reported being involved in other clubs (85.8%). A little less than half participated in music, choir, dance, and/or band lessons. Over half of participants involved in religious activity did those activities a few times per week or more. In the multiple regression analysis, team sport participation with a coach was the only extracurricular activity associated with lower risk of trying smoking (adjusted OR = 0.68, 95% C.I. 0.49, 0.96) compared to none or minimal participation. Participating in other clubs was the only extracurricular activity associated with lower risk of trying drinking (adjusted OR = 0.56, 95% C.I. 0.32, 0.99) compared to none or minimal participation

Temporal Subtraction of Serial CT Images with Large Deformation Diffeomorphic Metric Mapping in the Identification of Bone Metastases.

PubMed

Sakamoto, Ryo; Yakami, Masahiro; Fujimoto, Koji; Nakagomi, Keita; Kubo, Takeshi; Emoto, Yutaka; Akasaka, Thai; Aoyama, Gakuto; Yamamoto, Hiroyuki; Miller, Michael I; Mori, Susumu; Togashi, Kaori

2017-11-01

Purpose To determine the improvement of radiologist efficiency and performance in the detection of bone metastases at serial follow-up computed tomography (CT) by using a temporal subtraction (TS) technique based on an advanced nonrigid image registration algorithm. Materials and Methods This retrospective study was approved by the institutional review board, and informed consent was waived. CT image pairs (previous and current scans of the torso) in 60 patients with cancer (primary lesion location: prostate, n = 14; breast, n = 16; lung, n = 20; liver, n = 10) were included. These consisted of 30 positive cases with a total of 65 bone metastases depicted only on current images and confirmed by two radiologists who had access to additional imaging examinations and clinical courses and 30 matched negative control cases (no bone metastases). Previous CT images were semiautomatically registered to current CT images by the algorithm, and TS images were created. Seven radiologists independently interpreted CT image pairs to identify newly developed bone metastases without and with TS images with an interval of at least 30 days. Jackknife free-response receiver operating characteristics (JAFROC) analysis was conducted to assess observer performance. Reading time was recorded, and usefulness was evaluated with subjective scores of 1-5, with 5 being extremely useful and 1 being useless. Significance of these values was tested with the Wilcoxon signed-rank test. Results The subtraction images depicted various types of bone metastases (osteolytic, n = 28; osteoblastic, n = 26; mixed osteolytic and blastic, n = 11) as temporal changes. The average reading time was significantly reduced (384.3 vs 286.8 seconds; Wilcoxon signed rank test, P = .028). The average figure-of-merit value increased from 0.758 to 0.835; however, this difference was not significant (JAFROC analysis, P = .092). The subjective usefulness survey response showed a median score of 5 for use of the technique

School-age effects of the newborn individualized developmental care and assessment program for preterm infants with intrauterine growth restriction: preliminary findings

PubMed Central

2013-01-01

Background The experience in the newborn intensive care nursery results in premature infants’ neurobehavioral and neurophysiological dysfunction and poorer brain structure. Preterms with severe intrauterine growth restriction are doubly jeopardized given their compromised brains. The Newborn Individualized Developmental Care and Assessment Program improved outcome at early school-age for preterms with appropriate intrauterine growth. It also showed effectiveness to nine months for preterms with intrauterine growth restriction. The current study tested effectiveness into school-age for preterms with intrauterine growth restriction regarding executive function (EF), electrophysiology (EEG) and neurostructure (MRI). Methods Twenty-three 9-year-old former growth-restricted preterms, randomized at birth to standard care (14 controls) or to the Newborn Individualized Developmental Care and Assessment Program (9 experimentals) were assessed with standardized measures of cognition, achievement, executive function, electroencephalography, and magnetic resonance imaging. The participating children were comparable to those lost to follow-up, and the controls to the experimentals, in terms of newborn background health and demographics. All outcome measures were corrected for mother’s intelligence. Analysis techniques included two-group analysis of variance and stepwise discriminate analysis for the outcome measures, Wilks’ lambda and jackknifed classification to ascertain two-group classification success per and across domains; canonical correlation analysis to explore relationships among neuropsychological, electrophysiological and neurostructural domains at school-age, and from the newborn period to school-age. Results Controls and experimentals were comparable in age at testing, anthropometric and health parameters, and in cognitive and achievement scores. Experimentals scored better in executive function, spectral coherence, and cerebellar volumes. Furthermore

Frequency-dependent Lg Q within the continental United States

USGS Publications Warehouse

Erickson, D.; McNamara, D.E.; Benz, H.M.

2004-01-01

Frequency-dependent crustal attenuation (1/Q) is determined for seven distinct physiographic/tectonic regions of the continental United States using high-quality Lg waveforms recorded on broadband stations in the frequency band 0.5 to 16 Hz. Lg attenuation is determined from time-domain amplitude measurements in one-octave frequency bands centered on the frequencies 0.75, 1.0, 3.0, 6.0, and 12.0 Hz. Modeling errors are determined using a delete-j jackknife resampling technique. The frequency-dependent quality factor is modeled in the form of Q = Q0 fη. Regions were initially selected based on tectonic provinces but were eventually limited and adjusted to maximize ray path coverage in each area. Earthquake data was recorded on several different networks and constrained to events occurring within the crust (<40 km depth) and at least mb 3.5 in size. A singular value decomposition inversion technique was applied to the data to simultaneously solve for source and receiver terms along with Q for each region at specific frequencies. The lowest crustal Q was observed in northern and southern California where Q is described by the functions Q = 152(±37)f0.72(±0.16) and Q = 105(±26)f0.67(±0.16), respectively. The Basin and Range Province, Pacific Northwest, and Rocky Mountain states also display lower Q and a strong frequency dependence characterized by the functions Q = 200(±40)f0.68(±0.12), Q = 152(±49)f0.76(±0.18), and Q = 166(±37)f0.61(±0.14), respectively. In contrast, in the central and northeast United States Q functions are Q = 640(±225)f0.344(±0.22) and Q = 650(±143)f0.36(±0.14), respectively, show a high crustal Q and a weaker frequency dependence. These results improve upon previous Lg modeling by subdividing the United States into smaller, distinct tectonic regions and using significantly more data that provide improved constraints on frequency-dependent attenuation and errors. A detailed attenuation map of the continental United States can

Computer-aided detection of clustered microcalcifications in multiscale bilateral filtering regularized reconstructed digital breast tomosynthesis volume

DOE Office of Scientific and Technical Information (OSTI.GOV)

Samala, Ravi K., E-mail: rsamala@umich.edu; Chan, Heang-Ping; Lu, Yao

Purpose: Develop a computer-aided detection (CADe) system for clustered microcalcifications in digital breast tomosynthesis (DBT) volume enhanced with multiscale bilateral filtering (MSBF) regularization. Methods: With Institutional Review Board approval and written informed consent, two-view DBT of 154 breasts, of which 116 had biopsy-proven microcalcification (MC) clusters and 38 were free of MCs, was imaged with a General Electric GEN2 prototype DBT system. The DBT volumes were reconstructed with MSBF-regularized simultaneous algebraic reconstruction technique (SART) that was designed to enhance MCs and reduce background noise while preserving the quality of other tissue structures. The contrast-to-noise ratio (CNR) of MCs was furthermore » improved with enhancement-modulated calcification response (EMCR) preprocessing, which combined multiscale Hessian response to enhance MCs by shape and bandpass filtering to remove the low-frequency structured background. MC candidates were then located in the EMCR volume using iterative thresholding and segmented by adaptive region growing. Two sets of potential MC objects, cluster centroid objects and MC seed objects, were generated and the CNR of each object was calculated. The number of candidates in each set was controlled based on the breast volume. Dynamic clustering around the centroid objects grouped the MC candidates to form clusters. Adaptive criteria were designed to reduce false positive (FP) clusters based on the size, CNR values and the number of MCs in the cluster, cluster shape, and cluster based maximum intensity projection. Free-response receiver operating characteristic (FROC) and jackknife alternative FROC (JAFROC) analyses were used to assess the performance and compare with that of a previous study. Results: Unpaired two-tailedt-test showed a significant increase (p < 0.0001) in the ratio of CNRs for MCs with and without MSBF regularization compared to similar ratios for FPs. For view-based detection

A stable pattern of EEG spectral coherence distinguishes children with autism from neuro-typical controls - a large case control study

PubMed Central

2012-01-01

Background The autism rate has recently increased to 1 in 100 children. Genetic studies demonstrate poorly understood complexity. Environmental factors apparently also play a role. Magnetic resonance imaging (MRI) studies demonstrate increased brain sizes and altered connectivity. Electroencephalogram (EEG) coherence studies confirm connectivity changes. However, genetic-, MRI- and/or EEG-based diagnostic tests are not yet available. The varied study results likely reflect methodological and population differences, small samples and, for EEG, lack of attention to group-specific artifact. Methods Of the 1,304 subjects who participated in this study, with ages ranging from 1 to 18 years old and assessed with comparable EEG studies, 463 children were diagnosed with autism spectrum disorder (ASD); 571 children were neuro-typical controls (C). After artifact management, principal components analysis (PCA) identified EEG spectral coherence factors with corresponding loading patterns. The 2- to 12-year-old subsample consisted of 430 ASD- and 554 C-group subjects (n = 984). Discriminant function analysis (DFA) determined the spectral coherence factors' discrimination success for the two groups. Loading patterns on the DFA-selected coherence factors described ASD-specific coherence differences when compared to controls. Results Total sample PCA of coherence data identified 40 factors which explained 50.8% of the total population variance. For the 2- to 12-year-olds, the 40 factors showed highly significant group differences (P < 0.0001). Ten randomly generated split half replications demonstrated high-average classification success (C, 88.5%; ASD, 86.0%). Still higher success was obtained in the more restricted age sub-samples using the jackknifing technique: 2- to 4-year-olds (C, 90.6%; ASD, 98.1%); 4- to 6-year-olds (C, 90.9%; ASD 99.1%); and 6- to 12-year-olds (C, 98.7%; ASD, 93.9%). Coherence loadings demonstrated reduced short-distance and reduced, as well as increased

Computed tomographic (CT) neuroradiological evaluation of intra-axial and extra-axial lesions: a receiver operating characteristic (ROC) study of film and 1K workstation

NASA Astrophysics Data System (ADS)

El-Saden, Suzie; Hademenos, George J.; Zhu, Wei; Sayre, James W.; Glenn, Brad; Steidler, Jim; Kode, L.; King, Brian; Quinones, Diana; Valentino, Daniel J.; Bentsen, John R.

1995-04-01

Digital display workstations are now commonly used for cross-sectional image viewing; however, few receiver operating characteristic (ROC) studies have been performed to evaluate the diagnostic efficiency of hard copy versus a workstation display for neuroradiology applications. We have performed an ROC study of film and 1K workstation based on the diagnostic performance of neuroradiology fellows to detect subtle intra- axial (high density (HD) and low density (LD)) and extra-axial (fluid, blood) lesions presented on computed tomographic (CT) images. An ROC analysis of the interpretation of approximately 200 CT images (1/2 normals and 1/2 abnormals) was performed by five experienced observers. The total number of abnormal images were equally divided among the three represented types of lesions (HD, LD, and extra-axial lesions). The images comprising the extra-axial lesion group were further subdivided into the following three distinct types: subdural hemorrhage, subarachnoid hemorrhage, and epidural hemorrhage. A fraction of the abnormal images were represented by more than one type of lesion, e.g., one abnormal image could contain both a HD and LD lesion. The digitized CT images were separated into four groups and read on the standard light box and a 1K workstation monitor equipped with simple image processing functions. Confidence ratings were scaled on a range from 0 (least confident) to 4 (most confident). Reader order sequences were randomized for each reader and for each modality. Each observer read from a total of eight different groups with a four-week intermission following the fourth group. The randomly assigned image number, lesion type and approximate location, incidental findings and comments, and confidence ratings were reported in individual worksheets for each image. ROC curves that were generated and analyzed for the various subgroups are presented in addition to the overall generalized jackknifed estimates of the grouped data. Also, 95% confidence

A stable pattern of EEG spectral coherence distinguishes children with autism from neuro-typical controls - a large case control study.

PubMed

Duffy, Frank H; Als, Heidelise

2012-06-26

The autism rate has recently increased to 1 in 100 children. Genetic studies demonstrate poorly understood complexity. Environmental factors apparently also play a role. Magnetic resonance imaging (MRI) studies demonstrate increased brain sizes and altered connectivity. Electroencephalogram (EEG) coherence studies confirm connectivity changes. However, genetic-, MRI- and/or EEG-based diagnostic tests are not yet available. The varied study results likely reflect methodological and population differences, small samples and, for EEG, lack of attention to group-specific artifact. Of the 1,304 subjects who participated in this study, with ages ranging from 1 to 18 years old and assessed with comparable EEG studies, 463 children were diagnosed with autism spectrum disorder (ASD); 571 children were neuro-typical controls (C). After artifact management, principal components analysis (PCA) identified EEG spectral coherence factors with corresponding loading patterns. The 2- to 12-year-old subsample consisted of 430 ASD- and 554 C-group subjects (n = 984). Discriminant function analysis (DFA) determined the spectral coherence factors' discrimination success for the two groups. Loading patterns on the DFA-selected coherence factors described ASD-specific coherence differences when compared to controls. Total sample PCA of coherence data identified 40 factors which explained 50.8% of the total population variance. For the 2- to 12-year-olds, the 40 factors showed highly significant group differences (P < 0.0001). Ten randomly generated split half replications demonstrated high-average classification success (C, 88.5%; ASD, 86.0%). Still higher success was obtained in the more restricted age sub-samples using the jackknifing technique: 2- to 4-year-olds (C, 90.6%; ASD, 98.1%); 4- to 6-year-olds (C, 90.9%; ASD 99.1%); and 6- to 12-year-olds (C, 98.7%; ASD, 93.9%). Coherence loadings demonstrated reduced short-distance and reduced, as well as increased, long-distance coherences

Uncertainty in Pedotransfer Functions from Soil Survey Data

NASA Astrophysics Data System (ADS)

Pachepsky, Y. A.; Rawls, W. J.

2002-05-01

Pedotransfer functions (PTFs) are empirical relationships between hard-to-get soil parameters, i.e. hydraulic properties, and more easily obtainable basic soil properties, such as texture. Use of PTFs in large-scale projects and pilot studies relies on data of soil survey that provides soil basic data as a categorical information. Unlike numerical variables, categorical data cannot be directly used in statistical regressions or neural networks to develop PTFs. Objectives of this work were (a) to find and test techniques to develop PTFs for soil water retention and saturated hydraulic conductivity with soil categorical data as inputs, (b) to evaluate sources of uncertainty in results of such PTFs and to research opportunities of mitigating the uncertainty. We used a subset of about 12,000 samples from the US National Soil characterization database to estimate water retention, and the data set for circa 1000 hydraulic conductivity measurements done in the US. Regression trees and polynomial neural networks based on dummy coding were the techniques tried for the PTF development. The jackknife validation was used to prevent the over-parameterization. Both techniques were equally efficient in developing PTFs, but regression trees gave much more transparent results. Textural class was the leading predictor with RMSE values of about 6.5 and 4.1 vol.% for water retention at -33 and -1500 kPa, respectively. The RMSE values decreased 10% when the laboratory textural analysis was used to establish the textural class. Textural class in the field was determined correctly only in 41% of all cases. To mitigate this source of error, we added slopes, position on the slope classes, and land surface shape classes to the list of PTF inputs. Regression trees generated topotextural groups that encompassed several textural classes. Using topographic variables and soil horizon appeared to be the way to make up for errors made in field determination of texture. Adding field descriptors of

Observer Performance in the Detection and Classification of Malignant Hepatic Nodules and Masses with CT Image-Space Denoising and Iterative Reconstruction

PubMed Central

Yu, Lifeng; Li, Zhoubo; Manduca, Armando; Blezek, Daniel J.; Hough, David M.; Venkatesh, Sudhakar K.; Brickner, Gregory C.; Cernigliaro, Joseph C.; Hara, Amy K.; Fidler, Jeff L.; Lake, David S.; Shiung, Maria; Lewis, David; Leng, Shuai; Augustine, Kurt E.; Carter, Rickey E.; Holmes, David R.; McCollough, Cynthia H.

2015-01-01

Purpose To determine if lower-dose computed tomographic (CT) scans obtained with adaptive image-based noise reduction (adaptive nonlocal means [ANLM]) or iterative reconstruction (sinogram-affirmed iterative reconstruction [SAFIRE]) result in reduced observer performance in the detection of malignant hepatic nodules and masses compared with routine-dose scans obtained with filtered back projection (FBP). Materials and Methods This study was approved by the institutional review board and was compliant with HIPAA. Informed consent was obtained from patients for the retrospective use of medical records for research purposes. CT projection data from 33 abdominal and 27 liver or pancreas CT examinations were collected (median volume CT dose index, 13.8 and 24.0 mGy, respectively). Hepatic malignancy was defined by progression or regression or with histopathologic findings. Lower-dose data were created by using a validated noise insertion method (10.4 mGy for abdominal CT and 14.6 mGy for liver or pancreas CT) and images reconstructed with FBP, ANLM, and SAFIRE. Four readers evaluated routine-dose FBP images and all lower-dose images, circumscribing liver lesions and selecting diagnosis. The jackknife free-response receiver operating characteristic figure of merit (FOM) was calculated on a per–malignant nodule or per-mass basis. Noninferiority was defined by the lower limit of the 95% confidence interval (CI) of the difference between lower-dose and routine-dose FOMs being less than −0.10. Results Twenty-nine patients had 62 malignant hepatic nodules and masses. Estimated FOM differences between lower-dose FBP and lower-dose ANLM versus routine-dose FBP were noninferior (difference: −0.041 [95% CI: −0.090, 0.009] and −0.003 [95% CI: −0.052, 0.047], respectively). In patients with dedicated liver scans, lower-dose ANLM images were noninferior (difference: +0.015 [95% CI: −0.077, 0.106]), whereas lower-dose FBP images were not (difference −0.049 [95% CI: �

Parameter regionalisation methods for a semi-distributed rainfall-runoff model: application to a Northern Apennine region

NASA Astrophysics Data System (ADS)

Neri, Mattia; Toth, Elena

2017-04-01

the "parameters averaging" approach) or for averaging the simulated streamflow (in the "output averaging" approach): in particular, weights are estimated as a function of the similarity/distance of the ungauged basin/zone to the donors, on the basis of a set of geo-morphological catchment descriptors. The predictive accuracy of the different regionalisation methods is finally assessed by jack-knife cross-validation against the observed daily runoff for all the study catchments.

A border versus non-border comparison of food environment, poverty, and ethnic composition in Texas urban settings.

PubMed

Salinas, Jennifer J; Sexton, Ken

2015-01-01

The goal was to examine the relationship between the food environment and selected socioeconomic variables and ethnic/racial makeup in the eight largest urban settings in Texas so as to gain a better understanding of the relationships among Hispanic composition, poverty, and urban foodscapes, comparing border to non-border urban environments. Census-tract level data on (a) socioeconomic factors, like percentage below the poverty line and number of households on foodstamps, and (b) ethnic variables, like percent of Mexican origin and percent foreign born, were obtained from the U.S. Census. Data at the census-tract level on the total number of healthy (e.g., supermarkets) and less-healthy (e.g., fast food outlets) food retailers were acquired from the CDC's modified retail food environment index (mRFEI). Variation among urban settings in terms of the relationship between mRFEI scores and socioeconomic and ethnic context was tested using a mixed-effect model, and linear regression was used to identify significant factors for each urban location. A jackknife variance estimate was used to account for clustering and autocorrelation of adjacent census tracts. Average census-tract mRFEI scores exhibited comparatively small variation across Texas urban settings, while socioeconomic and ethnic factors varied significantly. The only covariates significantly associated with mRFEI score were percent foreign born and percent Mexican origin. Compared to the highest-population county (Harris, which incorporates most of Houston), the only counties that had significantly different mRFEI scores were Bexar, which is analogous to San Antonio (2.12 lower), El Paso (2.79 higher), and Neuces, which encompasses Corpus Christi (2.90 less). Significant interaction effects between mRFEI and percent foreign born (El Paso, Tarrant - Fort Worth, Travis - Austin), percent Mexican origin (Hidalgo - McAllen, El Paso, Tarrant, Travis), and percent living below the poverty line (El Paso) were

Long-term changes and spatio-temporal variability of the growing season temperature in Europe during the last Millennium

NASA Astrophysics Data System (ADS)

Guiot, Joel; Corona, Christophe

2010-05-01

A gridded reconstruction of April to September temperature was produced for Europe based on tree-rings, documentaries, pollen and ice cores. The majority of the proxy series have an annual resolution. For a better inference of long-term climate variations, they were completed by number of low resolution data (decadal or more), mostly on pollen and ice-core data. An original spectral analogue method was devised to deal with this heterogeneous dataset, and especially to preserve the long-term variations and the variability of the temperature series. It is the condition is to make pertinent the comparison of the recent climate changes to a broader context of 1400 years. The reconstruction of the April-September temperature was validated with a Jack-knife technique, and it was also compared with other spatially gridded temperature reconstructions, literature data, and glacier advance and retreat curves. We also attempted to relate the spatial distribution of European temperature anomalies to known solar and volcanic forcings. We found that (1) our results are sound back to A.D. 750; (2) conditions during the last decade have exceeded all those known during the last millennium; (3) before the 20th century, cold periods can partly be explained by low solar activity and/or high volcanic activity and that Medieval Warm Period (MWP) is consistent with a high solar activity; (4) during the 20th century, however only anthropogenic forcing can explain the exceptionally high temperature rise; (5) based on an analysis of the distribution of extreme temperatures, the maximum event of the Medieval Period (1.1°C higher than the 1960-1990 reference period) had a return period of more than 1000 years, but this recently fell to less than 26 years; (6) all decades before AD 1350 were warm on average but relatively heterogeneous, while the last decade was homogeneously warmer. These results support the fact that we are facing an unprecedented changing climate in Europe unlike any known

Digital Mapping of Soil Salinity and Crop Yield across a Coastal Agricultural Landscape Using Repeated Electromagnetic Induction (EMI) Surveys

PubMed Central

Yao, Rongjiang; Yang, Jingsong; Wu, Danhua; Xie, Wenping; Gao, Peng; Jin, Wenhui

2016-01-01

Reliable and real-time information on soil and crop properties is important for the development of management practices in accordance with the requirements of a specific soil and crop within individual field units. This is particularly the case in salt-affected agricultural landscape where managing the spatial variability of soil salinity is essential to minimize salinization and maximize crop output. The primary objectives were to use linear mixed-effects model for soil salinity and crop yield calibration with horizontal and vertical electromagnetic induction (EMI) measurements as ancillary data, to characterize the spatial distribution of soil salinity and crop yield and to verify the accuracy of spatial estimation. Horizontal and vertical EMI (type EM38) measurements at 252 locations were made during each survey, and root zone soil samples and crop samples at 64 sampling sites were collected. This work was periodically conducted on eight dates from June 2012 to May 2013 in a coastal salt-affected mud farmland. Multiple linear regression (MLR) and restricted maximum likelihood (REML) were applied to calibrate root zone soil salinity (ECe) and crop annual output (CAO) using ancillary data, and spatial distribution of soil ECe and CAO was generated using digital soil mapping (DSM) and the precision of spatial estimation was examined using the collected meteorological and groundwater data. Results indicated that a reduced model with EMh as a predictor was satisfactory for root zone ECe calibration, whereas a full model with both EMh and EMv as predictors met the requirement of CAO calibration. The obtained distribution maps of ECe showed consistency with those of EMI measurements at the corresponding time, and the spatial distribution of CAO generated from ancillary data showed agreement with that derived from raw crop data. Statistics of jackknifing procedure confirmed that the spatial estimation of ECe and CAO exhibited reliability and high accuracy. A general

Anisotropy of the galaxy cluster X-ray luminosity-temperature relation

NASA Astrophysics Data System (ADS)

Migkas, Konstantinos; Reiprich, Thomas H.

2018-03-01

We introduce a new test to study the cosmological principle with galaxy clusters. Galaxy clusters exhibit a tight correlation between the luminosity and temperature of the X-ray-emitting intracluster medium. While the luminosity measurement depends on cosmological parameters through the luminosity distance, the temperature determination is cosmology-independent. We exploit this property to test the isotropy of the luminosity distance over the full extragalactic sky, through the normalization a of the LX-T scaling relation and the cosmological parameters Ωm and H0. To this end, we use two almost independent galaxy cluster samples: the ASCA Cluster Catalog (ACC) and the XMM Cluster Survey (XCS-DR1). Interestingly enough, these two samples appear to have the same pattern for a with respect to the Galactic longitude. More specifically, we identify one sky region within l (-15°, 90°) (Group A) that shares very different best-fit values for the normalization of the LX-T relation for both ACC and XCS-DR1 samples. We use the Bootstrap and Jackknife methods to assess the statistical significance of these results. We find the deviation of Group A, compared to the rest of the sky in terms of a, to be 2.7σ for ACC and 3.1σ for XCS-DR1. This tension is not significantly relieved after excluding possible outliers and is not attributed to different redshift (z), temperature (T), or distributions of observable uncertainties. Moreover, a redshift conversion to the cosmic microwave background (CMB) frame does not have an important impact on our results. Using also the HIFLUGCS sample, we show that a possible excess of cool-core clusters in this region, is not able to explain the obtained deviations. Furthermore, we tested for a dependence of the results on supercluster environment, where the fraction of disturbed clusters might be enhanced, possibly affecting the LX-T relation. We indeed find a trend in the XCS-DR1 sample for supercluster members to be underluminous compared to

Establishing macroecological trait datasets: digitalization, extrapolation, and validation of diet preferences in terrestrial mammals worldwide

PubMed Central

Kissling, Wilm Daniel; Dalby, Lars; Fløjgaard, Camilla; Lenoir, Jonathan; Sandel, Brody; Sandom, Christopher; Trøjelsgaard, Kristian; Svenning, Jens-Christian

2014-01-01

Ecological trait data are essential for understanding the broad-scale distribution of biodiversity and its response to global change. For animals, diet represents a fundamental aspect of species’ evolutionary adaptations, ecological and functional roles, and trophic interactions. However, the importance of diet for macroevolutionary and macroecological dynamics remains little explored, partly because of the lack of comprehensive trait datasets. We compiled and evaluated a comprehensive global dataset of diet preferences of mammals (“MammalDIET”). Diet information was digitized from two global and cladewide data sources and errors of data entry by multiple data recorders were assessed. We then developed a hierarchical extrapolation procedure to fill-in diet information for species with missing information. Missing data were extrapolated with information from other taxonomic levels (genus, other species within the same genus, or family) and this extrapolation was subsequently validated both internally (with a jack-knife approach applied to the compiled species-level diet data) and externally (using independent species-level diet information from a comprehensive continentwide data source). Finally, we grouped mammal species into trophic levels and dietary guilds, and their species richness as well as their proportion of total richness were mapped at a global scale for those diet categories with good validation results. The success rate of correctly digitizing data was 94%, indicating that the consistency in data entry among multiple recorders was high. Data sources provided species-level diet information for a total of 2033 species (38% of all 5364 terrestrial mammal species, based on the IUCN taxonomy). For the remaining 3331 species, diet information was mostly extrapolated from genus-level diet information (48% of all terrestrial mammal species), and only rarely from other species within the same genus (6%) or from family level (8%). Internal and external

Stock assessment of fishery target species in Lake Koka, Ethiopia.

PubMed

Tesfaye, Gashaw; Wolff, Matthias

2015-09-01

Effective management is essential for small-scale fisheries to continue providing food and livelihoods for households, particularly in developing countries where other options are often limited. Studies on the population dynamics and stock assessment on fishery target species are thus imperative to sustain their fisheries and the benefits for the society. In Lake Koka (Ethiopia), very little is known about the vital population parameters and exploitation status of the fishery target species: tilapia Oreochromis niloticus, common carp Cyprinus carpio and catfish Clarias gariepinus. Our study, therefore, aimed at determining the vital population parameters and assessing the status of these target species in Lake Koka using length frequency data collected quarterly from commercial catches from 2007-2012. A total of 20,097 fish specimens (distributed as 7,933 tilapia, 6,025 catfish and 6,139 common carp) were measured for the analysis. Von Bertalarffy growth parameters and their confidence intervals were determined from modal progression analysis using ELEFAN I and applying the jackknife technique. Mortality parameters were determined from length-converted catch curves and empirical models. The exploitation status of these target species were then assessed by computing exploitation rates (E) from mortality parameters as well as from size indicators i.e., assessing the size distribution of fish catches relative to the size at maturity (Lm), the size that provides maximum cohort biomass (Lopt) and the abundance of mega-spawners. The mean value of growth parameters L∞, K and the growth performance index ø' were 44.5 cm, 0.41/year and 2.90 for O. niloticus, 74.1 cm, 0.28/year and 3.19 for C. carpio and 121.9 cm, 0.16/year and 3.36 for C. gariepinus, respectively. The 95 % confidence intervals of the estimates were also computed. Total mortality (Z) estimates were 1.47, 0.83 and 0.72/year for O. niloticus, C. carpio and C. gariepinus, respectively. Our study suggest that

Effect of reconstruction methods and x-ray tube current–time product on nodule detection in an anthropomorphic thorax phantom: A crossed-modality JAFROC observer study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thompson, J. D., E-mail: j.d.thompson@salford.ac.uk; Chakraborty, D. P.; Szczepura, K.

Purpose: To evaluate nodule detection in an anthropomorphic chest phantom in computed tomography (CT) images reconstructed with adaptive iterative dose reduction 3D (AIDR{sup 3D}) and filtered back projection (FBP) over a range of tube current–time product (mAs). Methods: Two phantoms were used in this study: (i) an anthropomorphic chest phantom was loaded with spherical simulated nodules of 5, 8, 10, and 12 mm in diameter and +100, −630, and −800 Hounsfield units electron density; this would generate CT images for the observer study; (ii) a whole-body dosimetry verification phantom was used to ultimately estimate effective dose and risk according tomore » the model of the BEIR VII committee. Both phantoms were scanned over a mAs range (10, 20, 30, and 40), while all other acquisition parameters remained constant. Images were reconstructed with both AIDR{sup 3D} and FBP. For the observer study, 34 normal cases (no nodules) and 34 abnormal cases (containing 1–3 nodules, mean 1.35 ± 0.54) were chosen. Eleven observers evaluated images from all mAs and reconstruction methods under the free-response paradigm. A crossed-modality jackknife alternative free-response operating characteristic (JAFROC) analysis method was developed for data analysis, averaging data over the two factors influencing nodule detection in this study: mAs and image reconstruction (AIDR{sup 3D} or FBP). A Bonferroni correction was applied and the threshold for declaring significance was set at 0.025 to maintain the overall probability of Type I error at α = 0.05. Contrast-to-noise (CNR) was also measured for all nodules and evaluated by a linear least squares analysis. Results: For random-reader fixed-case crossed-modality JAFROC analysis, there was no significant difference in nodule detection between AIDR{sup 3D} and FBP when data were averaged over mAs [F(1, 10) = 0.08, p = 0.789]. However, when data were averaged over reconstruction methods, a significant difference was seen between

A regional high-resolution carbon flux inversion of North America for 2004

NASA Astrophysics Data System (ADS)

Schuh, A. E.; Denning, A. S.; Corbin, K. D.; Baker, I. T.; Uliasz, M.; Parazoo, N.; Andrews, A. E.; Worthy, D. E. J.

2010-05-01

. We perform the inversion with two independently derived boundary inflow conditions and calculate jackknife-based statistics to test the robustness of the model results. We then compare final results to estimates obtained from the CarbonTracker inversion system and at the Southern Great Plains flux site. Results are promising, showing the ability to correct carbon fluxes from the biosphere models over annual and seasonal time scales, as well as over the different GPP and ER components. Additionally, the correlation of an estimated sink of carbon in the South Central United States with regional anomalously high precipitation in an area of managed agricultural and forest lands provides interesting hypotheses for future work.

Presence-only approach to assess landslide triggering-thickness susceptibility. A test for the Mili catchment (North-Eastern Sicily, Italy)

NASA Astrophysics Data System (ADS)

Lombardo, Luigi; Fubelli, Giandomenico; Amato, Gabriele; Bonasera, Mauro; Hochschild, Volker; Rotigliano, Edoardo

2015-04-01

thicknesses. In addition, the role of each predictor within the whole modelling procedure was assessed by applying Jackknife tests. These analyses focussed on evaluating the variation of AUC values across replicates comparing single variable models with models based on the full set of predictors iteratively deprived of one covariate. As a result, relevant differences among main contributors between the two considered classes were also quantitatively derived and geomorphologically interpreted. This work can be considered as an example for creating specific landslide susceptibility maps to be used in master planning in order to establish proportional countermeasures to different activation mechanisms. Keywords: statistical analysis, shallow landslide, landslide susceptibility, triggering factors, presence-only approach

Computer-aided mass detection in mammography: False positive reduction via gray-scale invariant ranklet texture features

DOE Office of Scientific and Technical Information (OSTI.GOV)

Masotti, Matteo; Lanconelli, Nico; Campanini, Renato

marks when compared to the previous one. Specifically, at 60%, 65%, and 70% per-mammogram sensitivity, the new CAD system achieves 0.50, 0.68, and 0.92 FP marks per mammogram, whereas at 70%, 75%, and 80% per-case sensitivity it achieves 0.37, 0.48, and 0.71 FP marks per mammogram, respectively. Conversely, at the same sensitivities, the previous CAD system reached 0.71, 0.87, and 1.15 FP marks per mammogram, and 0.57, 0.73, and 0.92 FPs per mammogram. Also, statistical significance of the difference between the two per-mammogram and per-case FROC curves is demonstrated by the p-value<0.001 returned by jackknife FROC analysis performed on the two CAD systems.« less

Clinical Model for NASH and Advanced Fibrosis in Adult Patients With Diabetes and NAFLD: Guidelines for Referral in NAFLD

PubMed Central

Bazick, Jessica; Donithan, Michele; Neuschwander-Tetri, Brent A.; Kleiner, David; Brunt, Elizabeth M.; Wilson, Laura; Doo, Ed; Lavine, Joel; Tonascia, James

2015-01-01

OBJECTIVE Approximately 18 million people in the U.S. have coexisting type 2 diabetes and nonalcoholic fatty liver disease (NAFLD). It is not known who among these patients has nonalcoholic steatohepatitis (NASH) with advanced fibrosis. Therefore, we aimed to determine factors that are associated with both NASH and advanced fibrosis in patients with diabetes and NAFLD in order to identify who should be prioritized for referral to a hepatologist for further diagnostic evaluation and treatment. RESEARCH DESIGN AND METHODS This study was derived from the NASH Clinical Research Network studies and included 1,249 patients with biopsy-proven NAFLD (including a model development cohort of 346 patients and an independent validation cohort of 100 patients with type 2 diabetes as defined by the American Diabetes Association criteria). Outcome measures were presence of NASH or advanced fibrosis (stage 3 or 4) using cross-validated, by jackknife method, multivariable-adjusted area under the receiver operating characteristic curve (AUROC) and 95% CI. RESULTS The mean ± SD age and BMI of patients with diabetes and NAFLD was 52.5 ± 10.3 years and 35.8 ± 6.8 kg/m2, respectively. The prevalence of NASH and advanced fibrosis was 69.2% and 41.0%, respectively. The model for NASH included white race, BMI, waist, alanine aminotransferase (ALT), Aspartate aminotransferase (AST), albumin, HbA1c, HOMA of insulin resistance, and ferritin with an AUROC of 0.80 (95% CI 0.75–0.84, P = 0.007). The specificity, sensitivity, negative predictive values (NPVs), and positive predictive values (PPVs) were 90.0%, 56.8%, 47.7%, and 93.2%, respectively, and the model correctly classified 67% of patients as having NASH. The model for predicting advanced fibrosis included age, Hispanic ethnicity, BMI, waist-to-hip ratio, hypertension, ALT-to-AST ratio, alkaline phosphatase, isolated abnormal alkaline phosphatase, bilirubin (total and direct), globulin, albumin, serum insulin, hematocrit

Digital Mapping of Soil Salinity and Crop Yield across a Coastal Agricultural Landscape Using Repeated Electromagnetic Induction (EMI) Surveys.

PubMed

Yao, Rongjiang; Yang, Jingsong; Wu, Danhua; Xie, Wenping; Gao, Peng; Jin, Wenhui

2016-01-01

Reliable and real-time information on soil and crop properties is important for the development of management practices in accordance with the requirements of a specific soil and crop within individual field units. This is particularly the case in salt-affected agricultural landscape where managing the spatial variability of soil salinity is essential to minimize salinization and maximize crop output. The primary objectives were to use linear mixed-effects model for soil salinity and crop yield calibration with horizontal and vertical electromagnetic induction (EMI) measurements as ancillary data, to characterize the spatial distribution of soil salinity and crop yield and to verify the accuracy of spatial estimation. Horizontal and vertical EMI (type EM38) measurements at 252 locations were made during each survey, and root zone soil samples and crop samples at 64 sampling sites were collected. This work was periodically conducted on eight dates from June 2012 to May 2013 in a coastal salt-affected mud farmland. Multiple linear regression (MLR) and restricted maximum likelihood (REML) were applied to calibrate root zone soil salinity (ECe) and crop annual output (CAO) using ancillary data, and spatial distribution of soil ECe and CAO was generated using digital soil mapping (DSM) and the precision of spatial estimation was examined using the collected meteorological and groundwater data. Results indicated that a reduced model with EMh as a predictor was satisfactory for root zone ECe calibration, whereas a full model with both EMh and EMv as predictors met the requirement of CAO calibration. The obtained distribution maps of ECe showed consistency with those of EMI measurements at the corresponding time, and the spatial distribution of CAO generated from ancillary data showed agreement with that derived from raw crop data. Statistics of jackknifing procedure confirmed that the spatial estimation of ECe and CAO exhibited reliability and high accuracy. A general

Spine and spinal cord injury in motor vehicle crashes: a function of change in velocity and energy dissipation on impact with respect to the direction of crash.

PubMed

Smith, Joyce A; Siegel, John H; Siddiqi, Shabana Q

2005-07-01

To examine the effect of change in velocity (DeltaV) and energy dissipation (IE) on impact, above and below the test levels for Federal MVC Safety Standards, on the incidence of spine fractures (SF), spinal cord injury (SCI)), SF mortality and the associated injury patterns in Frontal (F) and Lateral (L) MVCs. Comparison of 214 patients with SF or SCI with 938 patients who did not have SF or SCI. 1152 MVC adult drivers or front-seat passengers (701 F & 451 L) evaluated at 10 Level I CIREN study Trauma Centers together with vehicle and crash scene engineering reconstruction. Patient seat belt (SB) and/or airbag (AB) use correlated with clinical, or autopsy findings. The relationship between DeltaV and IE rose exponentially as DeltaV increased. Of the 1152 patients, all with AIS> or =3 injuries, there were 214 patients with spine fractures of AIS > or =2. In FMVCs there were more SF patients with Cervical SF than in LMVCs (68F versus 64 L) and more Thoracic (35F versus 21L) and Lumbar (39F versus 16L) SF. However, the incidence of spinal cord injury was greatest in the Cervical SF (33%), compared with the Thoracic SF (18%), or Lumbar SF (2%). Most important, in FMVCs 49% of SF, 47% of SCI and 71% of the SF deaths (p < 0.05) occurred at > mean of 47.4 kph. In contrast, in LMVCs 51% of SF, 52% of SCI and 67% of the SF deaths occurred at DeltaV > mean of 35.3 kph. However, 80% of all deaths in SCI occurred in Cervical SF cases, in these 74% also had a brain injury. In contrast, the deaths in Thoracic SF were due to combinations of brain (45%), thorax (95%) or associated pelvic fracture injuries (50%). Airbag (AB), or Seat belt (SB) restraints appeared to protect FMVC SF patients from SCI at lower DeltaV, but 84% of Cervical SCI patients at DeltaV > 47 kph had AB protection and in a few cases the AB appeared responsible for the SCI. In contrast, 82% of Lumbar SF patients had SB, but in FMVCs where jackknifing due to backloading occurred, improper SB positioning may have

Program package for multicanonical simulations of U(1) lattice gauge theory-Second version

NASA Astrophysics Data System (ADS)

Bazavov, Alexei; Berg, Bernd A.

2013-03-01

A new version STMCMUCA_V1_1 of our program package is available. It eliminates compatibility problems of our Fortran 77 code, originally developed for the g77 compiler, with Fortran 90 and 95 compilers. New version program summaryProgram title: STMC_U1MUCA_v1_1 Catalogue identifier: AEET_v1_1 Licensing provisions: Standard CPC license, http://cpc.cs.qub.ac.uk/licence/licence.html Programming language: Fortran 77 compatible with Fortran 90 and 95 Computers: Any capable of compiling and executing Fortran code Operating systems: Any capable of compiling and executing Fortran code RAM: 10 MB and up depending on lattice size used No. of lines in distributed program, including test data, etc.: 15059 No. of bytes in distributed program, including test data, etc.: 215733 Keywords: Markov chain Monte Carlo, multicanonical, Wang-Landau recursion, Fortran, lattice gauge theory, U(1) gauge group, phase transitions of continuous systems Classification: 11.5 Catalogue identifier of previous version: AEET_v1_0 Journal Reference of previous version: Computer Physics Communications 180 (2009) 2339-2347 Does the new version supersede the previous version?: Yes Nature of problem: Efficient Markov chain Monte Carlo simulation of U(1) lattice gauge theory (or other continuous systems) close to its phase transition. Measurements and analysis of the action per plaquette, the specific heat, Polyakov loops and their structure factors. Solution method: Multicanonical simulations with an initial Wang-Landau recursion to determine suitable weight factors. Reweighting to physical values using logarithmic coding and calculating jackknife error bars. Reasons for the new version: The previous version was developed for the g77 compiler Fortran 77 version. Compiler errors were encountered with Fortran 90 and Fortran 95 compilers (specified below). Summary of revisions: epsilon=one/10**10 is replaced by epsilon/10.0D10 in the parameter statements of the subroutines u1_bmha.f, u1_mucabmha.f, u1wl

Clinical Model for NASH and Advanced Fibrosis in Adult Patients With Diabetes and NAFLD: Guidelines for Referral in NAFLD.

PubMed

Bazick, Jessica; Donithan, Michele; Neuschwander-Tetri, Brent A; Kleiner, David; Brunt, Elizabeth M; Wilson, Laura; Doo, Ed; Lavine, Joel; Tonascia, James; Loomba, Rohit

2015-07-01

Approximately 18 million people in the U.S. have coexisting type 2 diabetes and nonalcoholic fatty liver disease (NAFLD). It is not known who among these patients has nonalcoholic steatohepatitis (NASH) with advanced fibrosis. Therefore, we aimed to determine factors that are associated with both NASH and advanced fibrosis in patients with diabetes and NAFLD in order to identify who should be prioritized for referral to a hepatologist for further diagnostic evaluation and treatment. This study was derived from the NASH Clinical Research Network studies and included 1,249 patients with biopsy-proven NAFLD (including a model development cohort of 346 patients and an independent validation cohort of 100 patients with type 2 diabetes as defined by the American Diabetes Association criteria). Outcome measures were presence of NASH or advanced fibrosis (stage 3 or 4) using cross-validated, by jackknife method, multivariable-adjusted area under the receiver operating characteristic curve (AUROC) and 95% CI. The mean ± SD age and BMI of patients with diabetes and NAFLD was 52.5 ± 10.3 years and 35.8 ± 6.8 kg/m(2), respectively. The prevalence of NASH and advanced fibrosis was 69.2% and 41.0%, respectively. The model for NASH included white race, BMI, waist, alanine aminotransferase (ALT), Aspartate aminotransferase (AST), albumin, HbA1c, HOMA of insulin resistance, and ferritin with an AUROC of 0.80 (95% CI 0.75-0.84, P = 0.007). The specificity, sensitivity, negative predictive values (NPVs), and positive predictive values (PPVs) were 90.0%, 56.8%, 47.7%, and 93.2%, respectively, and the model correctly classified 67% of patients as having NASH. The model for predicting advanced fibrosis included age, Hispanic ethnicity, BMI, waist-to-hip ratio, hypertension, ALT-to-AST ratio, alkaline phosphatase, isolated abnormal alkaline phosphatase, bilirubin (total and direct), globulin, albumin, serum insulin, hematocrit, international normalized ratio, and platelet count with

SIFlore, a dataset of geographical distribution of vascular plants covering five centuries of knowledge in France: Results of a collaborative project coordinated by the Federation of the National Botanical Conservatories.

PubMed

Just, Anaïs; Gourvil, Johan; Millet, Jérôme; Boullet, Vincent; Milon, Thomas; Mandon, Isabelle; Dutrève, Bruno

2015-01-01

the National Inventory of Natural Heritage (http://www.inpn.fr) and the Global Biodiversity Information Facility (http://www.gbif.fr). SIFlore is regularly updated with additional data records. It is also planned to expand the scope of the dataset to include information about taxon biology, phenology, ecology, chorology, frequency, conservation status and seed banks. A map showing an estimation of the dataset completeness (based on Jackknife 1 estimator) is presented and included as a numerical appendix. SIFlore aims to make the data of the flora of France available at the national level for conservation, policy management and scientific research. Such a dataset will provide enough information to allow for macro-ecological reviews of species distribution patterns and, coupled with climatic or topographic datasets, the identification of determinants of these patterns. This dataset can be considered as the primary indicator of the current state of knowledge of flora distribution across France. At a policy level, and in the context of global warming, this should promote the adoption of new measures aiming to improve and intensify flora conservation and surveys.

SIFlore, a dataset of geographical distribution of vascular plants covering five centuries of knowledge in France: Results of a collaborative project coordinated by the Federation of the National Botanical Conservatories

PubMed Central

Just, Anaïs; Gourvil, Johan; Millet, Jérôme; Boullet, Vincent; Milon, Thomas; Mandon, Isabelle; Dutrève, Bruno

2015-01-01

the websites of the National Inventory of Natural Heritage (http://www.inpn.fr) and the Global Biodiversity Information Facility (http://www.gbif.fr). SIFlore is regularly updated with additional data records. It is also planned to expand the scope of the dataset to include information about taxon biology, phenology, ecology, chorology, frequency, conservation status and seed banks. A map showing an estimation of the dataset completeness (based on Jackknife 1 estimator) is presented and included as a numerical appendix. Purpose: SIFlore aims to make the data of the flora of France available at the national level for conservation, policy management and scientific research. Such a dataset will provide enough information to allow for macro-ecological reviews of species distribution patterns and, coupled with climatic or topographic datasets, the identification of determinants of these patterns. This dataset can be considered as the primary indicator of the current state of knowledge of flora distribution across France. At a policy level, and in the context of global warming, this should promote the adoption of new measures aiming to improve and intensify flora conservation and surveys. PMID:26491386

Generation of synthetic flood hydrographs by hydrological donors (SHYDONHY method)

NASA Astrophysics Data System (ADS)

Paquet, Emmanuel

2017-04-01

for extreme flood estimation, generate a suitable synthetic hydrograph, also by combining selected hydrographs of the sub-set. The reliability of the method is assessed by performing a jackknife validation on the whole dataset of stations, in particular by reconstructing the hydrograph of the biggest flood of each station and comparing it to the actual one. Some applications are presented, e.g. the coupling of SHYDONHY with the SCHADEX method (Paquet et al., 2003) for the stochastic simulation of extreme reservoir level in dams. References: Lang, M., Ouarda, T. B. M. J., & Bobée, B. (1999). Towards operational guidelines for over-threshold modeling. Journal of hydrology, 225(3), 103-117. Paquet, E., Garavaglia, F., Garçon, R., & Gailhard, J. (2013). The SCHADEX method: A semi-continuous rainfall-runoff simulation for extreme flood estimation. Journal of Hydrology, 495, 23-37. Yue, S., Ouarda, T. B., Bobée, B., Legendre, P., & Bruneau, P. (2002). Approach for describing statistical properties of flood hydrograph. Journal of hydrologic engineering, 7(2), 147-153.

Implementing the national AIGA flash flood warning system in France

NASA Astrophysics Data System (ADS)

Organde, Didier; Javelle, Pierre; Demargne, Julie; Arnaud, Patrick; Caseri, Angelica; Fine, Jean-Alain; de Saint Aubin, Céline

2015-04-01

The French national hydro-meteorological and flood forecasting centre (SCHAPI) aims to implement a national flash flood warning system to improve flood alerts for small-to-medium (up to 1000 km2) ungauged basins. This system is based on the AIGA method, co-developed by IRSTEA these last 10 years. The method, initially set up for the Mediterranean area, is based on a simple event-based hourly hydrologic distributed model run every 15 minutes (Javelle et al. 2014). The hydrologic model ingests operational radar-gauge rainfall grids from Météo-France at a 1-km² resolution to produce discharges for successive outlets along the river network. Discharges are then compared to regionalized flood quantiles of given return periods and warnings (expressed as the range of the return period estimated in real-time) are provided on a river network map. The main interest of the method is to provide forecasters and emergency services with a synthetic view in real time of the ongoing flood situation, information that is especially critical in ungauged flood prone areas. In its enhanced national version, the hourly event-based distributed model is coupled to a continuous daily rainfall-runoff model which provides baseflow and a soil moisture index (for each 1-km² pixel) at the beginning of the hourly simulation. The rainfall-runoff models were calibrated on a selection of 700 French hydrometric stations with Météo-France radar-gauge reanalysis dataset for the 2002-2006 period. To estimate model parameters for ungauged basins, the 2 hydrologic models were regionalised by testing both regressions (using different catchment attributes, such as catchment area, soil type, and climate characteristic) and spatial proximity techniques (transposing parameters from neighbouring donor catchments), as well as different homogeneous hydrological areas. The most valuable regionalisation method was determined for each model through jack-knife cross-validation. The system performance was then

Assessment of NHTSA’s Report “Relationships Between Fatality Risk, Mass, and Footprint in Model Year 2003-2010 Passenger Cars and LTVs”

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wenzel, Tom

NHTSA recently completed a logistic regression analysis updating its 2003, 2010, and 2012 studies of the relationship between vehicle mass and US fatality risk per vehicle mile traveled (VMT; Kahane 2010, Kahane 2012, Puckett 2016). The new study updates the 2012 analysis using FARS data from 2005 to 2011 for model year 2003 to 2010. Using the updated databases, NHTSA estimates that reducing vehicle mass by 100 pounds while holding footprint fixed would increase fatality risk per VMT by 1.49% for lighter-than-average cars and by 0.50% for heavierthan- average cars, but reduce risk by 0.10% for lighter-than-average light-duty trucks, bymore » 0.71% for heavier-than-average light-duty trucks, and by 0.99% for CUVs/minivans. Using a jack knife method to estimate the statistical uncertainty of these point estimates, NHTSA finds that none of these estimates are statistically significant at the 95% confidence level; however, the 1.49% increase in risk associated with mass reduction in lighter-than-average cars, and the 0.71% and 0.99% decreases in risk associated with mass reduction in heavier-than-average light trucks and CUVs/minivans, are statistically significant at the 90% confidence interval. The effect of mass reduction on risk that NHTSA estimated in 2016 is more beneficial than in its 2012 study, particularly for light trucks and CUVs/minivans. The 2016 NHTSA analysis estimates that reducing vehicle footprint by one square foot while holding mass constant would increase fatality risk per VMT by 0.28% in cars, by 0.38% in light trucks, and by 1.18% in CUVs and minivans.This report replicates the 2016 NHTSA analysis, and reproduces their main results. This report uses the confidence intervals output by the logistic regression models, which are smaller than the intervals NHTSA estimated using a jack-knife technique that accounts for the sampling error in the FARS fatality and state crash data. In addition to reproducing the NHTSA results, this report also

First high resolution P wave velocity structure beneath Tenerife Island, (Canary Islands, Spain)

NASA Astrophysics Data System (ADS)

Garcia-Yeguas, Araceli; Ivan, Koulakov; Ibañez Jesus, M.; Valenti, Sallarès.

2010-05-01

and accuracy tests were carried out to quantify the reliability of the final velocity models. Checkerboard tests show that the well-resolved are located up to 6-8 km depth. Also we carried out synthetic tests in which we successfully reproduce single anomalies observed in the velocity models. Especially we have study carefully the low velocity anomalies found in the NW and SE, which have been recovered successfully. The jack-knife technique have been used and our results are stable if we remove the 50% of the data for different stations, but if we reject all the data for some stations, the velocity models can change. These tests assure the uniqueness of the first 3D velocity model that characterizes the internal structure of the Tenerife Island. As main conclusions of our work we can remark: a) This is the first 3-D velocity image of the area; b) we have observed low velocity anomalies near to surface that could be associated to the presence of magma, water reservoirs and volcanic landslides; c) high velocity anomalies could be related to ancient volcanic episodes or basement structures; d) our results could help to resolve many questions relate to the evolution of the volcanic system, as the presence or not of big landslides, calderic explosions or others; e) this image is a very important tool to improve the knowledge of the volcanic hazard, and therefore volcanic risk. We would like to highlight the importance of take into account the risk of eruption in other areas besides Pico Teide-Las Cañadas system.

Impact of compressed breast thickness and dose on lesion detectability in digital mammography: FROC study with simulated lesions in real mammograms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Salvagnini, Elena, E-mail: elena.salvagnini@gmail.

Purpose: The aim of this work was twofold: (1) to examine whether, with standard automatic exposure control (AEC) settings that maintain pixel values in the detector constant, lesion detectability in clinical images decreases as a function of breast thickness and (2) to verify whether a new AEC setup can increase lesion detectability at larger breast thicknesses. Methods: Screening patient images, acquired on two identical digital mammography systems, were collected over a period of 2 yr. Mammograms were acquired under standard AEC conditions (part 1) and subsequently with a new AEC setup (part 2), programmed to use the standard AEC settingsmore » for compressed breast thicknesses ≤49 mm, while a relative dose increase was applied above this thickness. The images were divided into four thickness groups: T1 ≤ 29 mm, T2 = 30–49 mm, T3 = 50–69 mm, and T4 ≥ 70 mm, with each thickness group containing 130 randomly selected craniocaudal lesion-free images. Two measures of density were obtained for every image: a BI-RADS score and a map of volumetric breast density created with a software application (VolparaDensity, Matakina, NZ). This information was used to select subsets of four images, containing one image from each thickness group, matched to a (global) BI-RADS score and containing a region with the same (local) VOLPARA volumetric density value. One selected lesion (a microcalcification cluster or a mass) was simulated into each of the four images. This process was repeated so that, for a given thickness group, half the images contained a single lesion and half were lesion-free. The lesion templates created and inserted in groups T3 and T4 for the first part of the study were then inserted into the images of thickness groups T3 and T4 acquired with higher dose settings. Finally, all images were visualized using the ViewDEX software and scored by four radiologists performing a free search study. A statistical jackknife-alternative free-response receiver

Optimized multiple quantum MAS lineshape simulations in solid state NMR

NASA Astrophysics Data System (ADS)

Brouwer, William J.; Davis, Michael C.; Mueller, Karl T.

2009-10-01

/Linux Operating system: UNIX/Linux Has the code been vectorised or parallelized?: Yes RAM: Example: (1597 powder angles) × (200 Samples) × (81 F2 frequency pts) × (31 F1 frequency points) = 3.5M, SMP AMD opteron Classification: 2.3 External routines: OCTAVE ( http://www.gnu.org/software/octave/), GNU Scientific Library ( http://www.gnu.org/software/gsl/), OPENMP ( http://openmp.org/wp/) Nature of problem: The optimal simulation and modeling of multiple quantum magic angle spinning NMR spectra, for general systems, especially those with mild to significant disorder. The approach outlined and implemented in C and OCTAVE also produces model parameter error estimates. Solution method: A model for each distinct chemical site is first proposed, for the individual contribution of crystallite orientations to the spectrum. This model is averaged over all powder angles [1], as well as the (stochastic) parameters; isotropic chemical shift and quadrupole coupling constant. The latter is accomplished via sampling from a bi-variate Gaussian distribution, using the Box-Muller algorithm to transform Sobol (quasi) random numbers [2]. A simulated annealing optimization is performed, and finally the non-linear jackknife [3] is applied in developing model parameter error estimates. Additional comments: The distribution contains a script, mqmasOpt.m, which runs in the OCTAVE language workspace. Running time: Example: (1597 powder angles) × (200 Samples) × (81 F2 frequency pts) × (31 F1 frequency points) = 58.35 seconds, SMP AMD opteron. References:S.K. Zaremba, Annali di Matematica Pura ed Applicata 73 (1966) 293. H. Niederreiter, Random Number Generation and Quasi-Monte Carlo Methods, SIAM, 1992. T. Fox, D. Hinkley, K. Larntz, Technometrics 22 (1980) 29.

Assessment of NHTSA’s Report “Relationships Between Fatality Risk, Mass, and Footprint in Model Year 2004-2011 Passenger Cars and LTVs” (LBNL Phase 1)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wenzel, Tom P.

mass reduction while maintaining footprint on societal U.S. fatality risk is small, and not statistically significant at the 95% or 90% confidence level for all vehicle types based on the jack-knife method NHTSA used. This report also finds that the estimated effects of other control variables, such as vehicle type, specific safety technologies, and crash conditions such as whether the crash occurred at night, in a rural county, or on a high-speed road, on risk are much larger, in some cases two orders of magnitude larger, than the estimated effect of mass or footprint reduction on risk. Finally, this report shows that after accounting for the many vehicle, driver, and crash variables NHTSA used in its regression analyses, there remains a wide variation in risk by vehicle make and model, and this variation is unrelated to vehicle mass. Although the purpose of the NHTSA and LBNL reports is to estimate the effect of vehicle mass reduction on societal risk, this is not exactly what the regression models are estimating. Rather, they are estimating the recent historical relationship between mass and risk, after accounting for most measurable differences between vehicles, drivers, and crash times and locations. In essence, the regression models are comparing the risk of a 2600-lb Dodge Neon with that of a 2500-lb Honda Civic, after attempting to account for all other differences between the two vehicles. The models are not estimating the effect of literally removing 100 pounds from the Neon, leaving everything else unchanged. In addition, the analyses are based on the relationship of vehicle mass and footprint on risk for recent vehicle designs (model year 2004 to 2011). These relationships may or may not continue into the future as manufacturers utilize new vehicle designs and incorporate new technologies, such as more extensive use of strong lightweight materials and specific safety technologies. Therefore, throughout this report we use the phrase “the estimated effect

Robot-assisted posterior retroperitoneoscopic adrenalectomy using single-port access: technical feasibility and preliminary results.

PubMed

Park, Jae Hyun; Kim, Soo Young; Lee, Cho-Rok; Park, Seulkee; Jeong, Jun Soo; Kang, Sang-Wook; Jeong, Jong Ju; Nam, Kee-Hyun; Chung, Woong Youn; Park, Cheong Soo

2013-08-01

Posterior retroperitoneoscopic adrenalectomy (PRA) has several benefits compared with transperitoneal adrenalectomy in that it is safe and has a short learning curve. In addition, it provides direct short access to the target organ, prevents irritation to the intraperitoneal space, and does not require retraction of adjacent organs.1 (-) 3 We have performed several cases of robot-assisted PRA using single-port access for small adrenal tumors. This multimedia article introduces the detailed methods and preliminary results of this procedure. Five patients underwent single-port robot-assisted PRA between March 2010 and June 2011 at our institution. During the procedure, patients were placed in a prone jackknife position with their hip joints bent at a right angle (Fig. 1). A 3 cm transverse skin incision was made just below the lowest tip of the 12th rib (Fig. 2), and the Glove port (Nelis, Kyung-gi, Korea) was placed through the skin incision while maintaining pneumoretroperitoneum (Fig. 3). CO2 was then insufflated to a pressure of 18 mm Hg to create an adequate working space. A 10 mm robotic camera with a 30-degree up view was placed at the center of the incision through the most cephalic portion of the Glove port. A Maryland dissector or Prograsp forceps (Intuitive Surgical, Inc., Sunnyvale, CA) was placed on the medial side of the incision, and Harmonic curved shears (Intuitive Surgical) were placed on the lateral side of the incision (Fig. 4). Using the Maryland dissector and the harmonic curved shears, the Gerota fascia is opened, perinephric fat is dissected, and the kidney upper pole is mobilized to expose the adrenal gland (Fig. 5). Gland dissection starts with lower margin detachment from the upper kidney pole in a lateral to medial direction (Fig. 6). After dissecting the adrenal gland from surrounding adipose tissue and medial isolation of the adrenal central vein, the vessel is ligated with a 5 mm hemolock clip (Fig. 7). Patient

The Muenster Red Sky Survey: Large-scale structures in the universe

NASA Astrophysics Data System (ADS)

Ungruhe, R.; Seitter, W. C.; Duerbeck, H. W.

2003-01-01

%, the corrections are above 0.2 mag.The iteration procedure for the indirect adjustment of single platesmay cause a magnitude gradient in north-south or east-west direction. Investigations of the magnitude differences between photographic and CCD magnitudes versus right ascension and declination show no significant gradients.In order to generate a complete catalogue of galaxies and stars, all double or multiple objects that occur in overlap regions have to be excluded. After the merging of all single plates (including half of the overlap regions), both catalogues contain 5.5 million galaxies and 20.2 million stars. The completeness of the catalogues was investigated from the comparison of counts of stars and galaxies with simulations. The limit of completenessis at magnitude18.3 for galaxies, and at 18.8 for stars. In the case of galaxies, a clear deficit is seen for galaxies down to magitude 16 in comparison with the simulation. Neither by taking into account galaxy evolution, nor by changes in the cosmological parameters, an adjustment of the simulation to the catalogue counts was possible. These results and those of others support the assumption that we are dealing with a real galaxy deficit. The determined slope of 0.66 of the galaxy counts is, within the limits of accuracy, in agreement with the measured values of other authors. No comparable star counts are available. The N-point angular correlation function were determined from various sub-catalogues consisting of 9, 25, 63, 121 and 152 fields as well asfor limiting magnitudes from magnitudes 15.0 to 19.0. The computation of chance distributions was carried out for galaxy counts in cells with side borders from 25''to 28.4''. Averaged correlation functions and their coefficients were determined by means of factorial moments. The delete-d jackknife procedure was applied for the error estimate, with 200 replications per subcatalogue. The 2-point angular correlation function shows a linear trend in logarithmic plots