Attentional bias to threat in the general population is contingent on target competition, not on attentional control settings.

PubMed

Wirth, Benedikt Emanuel; Wentura, Dirk

2018-04-01

Dot-probe studies usually find an attentional bias towards threatening stimuli only in anxious participants. Here, we investigated under what conditions such a bias occurs in unselected samples. According to contingent-capture theory, an irrelevant cue only captures attention if it matches an attentional control setting. Therefore, we first tested the hypothesis that an attentional control setting tuned to threat must be activated in (non-anxious) individuals. In Experiment 1, we used a dot-probe task with a manipulation of attentional control settings ('threat' - set vs. control set). Surprisingly, we found an (anxiety-independent) attentional bias to angry faces that was not moderated by attentional control settings. Since we presented two stimuli (i.e., a target and a distractor) on the target screen in Experiment 1 (a necessity to realise the test of contingent capture), but most dot-probe studies only employ a single target, we conducted Experiment 2 to test the hypothesis that attentional bias in the general population is contingent on target competition. Participants performed a dot-probe task, involving presentation of a stand-alone target or a target competing with a distractor. We found an (anxiety-independent) attentional bias towards angry faces in the latter but not the former condition. This suggests that attentional bias towards angry faces in unselected samples is not contingent on attentional control settings but on target competition.

Common genetic variants associated with cognitive performance identified using the proxy-phenotype method

PubMed Central

Rietveld, Cornelius A.; Esko, Tõnu; Davies, Gail; Pers, Tune H.; Turley, Patrick; Benyamin, Beben; Chabris, Christopher F.; Emilsson, Valur; Johnson, Andrew D.; Lee, James J.; de Leeuw, Christiaan; Marioni, Riccardo E.; Medland, Sarah E.; Miller, Michael B.; Rostapshova, Olga; van der Lee, Sven J.; Vinkhuyzen, Anna A. E.; Amin, Najaf; Conley, Dalton; Derringer, Jaime; van Duijn, Cornelia M.; Fehrmann, Rudolf; Franke, Lude; Glaeser, Edward L.; Hansell, Narelle K.; Hayward, Caroline; Iacono, William G.; Ibrahim-Verbaas, Carla; Jaddoe, Vincent; Karjalainen, Juha; Laibson, David; Lichtenstein, Paul; Liewald, David C.; Magnusson, Patrik K. E.; Martin, Nicholas G.; McGue, Matt; McMahon, George; Pedersen, Nancy L.; Pinker, Steven; Porteous, David J.; Posthuma, Danielle; Rivadeneira, Fernando; Smith, Blair H.; Starr, John M.; Tiemeier, Henning; Timpson, Nicholas J.; Trzaskowski, Maciej; Uitterlinden, André G.; Verhulst, Frank C.; Ward, Mary E.; Wright, Margaret J.; Davey Smith, George; Deary, Ian J.; Johannesson, Magnus; Plomin, Robert; Visscher, Peter M.; Benjamin, Daniel J.; Koellinger, Philipp D.

2014-01-01

We identify common genetic variants associated with cognitive performance using a two-stage approach, which we call the proxy-phenotype method. First, we conduct a genome-wide association study of educational attainment in a large sample (n = 106,736), which produces a set of 69 education-associated SNPs. Second, using independent samples (n = 24,189), we measure the association of these education-associated SNPs with cognitive performance. Three SNPs (rs1487441, rs7923609, and rs2721173) are significantly associated with cognitive performance after correction for multiple hypothesis testing. In an independent sample of older Americans (n = 8,652), we also show that a polygenic score derived from the education-associated SNPs is associated with memory and absence of dementia. Convergent evidence from a set of bioinformatics analyses implicates four specific genes (KNCMA1, NRXN1, POU2F3, and SCRT). All of these genes are associated with a particular neurotransmitter pathway involved in synaptic plasticity, the main cellular mechanism for learning and memory. PMID:25201988

Using Empirical Data to Set Cutoff Scores.

ERIC Educational Resources Information Center

Hills, John R.

Six experimental approaches to the problems of setting cutoff scores and choosing proper test length are briefly mentioned. Most of these methods share the premise that a test is a random sample of items, from a domain associated with a carefully specified objective. Each item is independent and is scored zero or one, with no provision for…

Lattice Independent Component Analysis for Mobile Robot Localization

NASA Astrophysics Data System (ADS)

Villaverde, Ivan; Fernandez-Gauna, Borja; Zulueta, Ekaitz

This paper introduces an approach to appearance based mobile robot localization using Lattice Independent Component Analysis (LICA). The Endmember Induction Heuristic Algorithm (EIHA) is used to select a set of Strong Lattice Independent (SLI) vectors, which can be assumed to be Affine Independent, and therefore candidates to be the endmembers of the data. Selected endmembers are used to compute the linear unmixing of the robot's acquired images. The resulting mixing coefficients are used as feature vectors for view recognition through classification. We show on a sample path experiment that our approach can recognise the localization of the robot and we compare the results with the Independent Component Analysis (ICA).

Analysis of near infrared spectra for age-grading of wild populations of Anopheles gambiae.

PubMed

Krajacich, Benjamin J; Meyers, Jacob I; Alout, Haoues; Dabiré, Roch K; Dowell, Floyd E; Foy, Brian D

2017-11-07

Understanding the age-structure of mosquito populations, especially malaria vectors such as Anopheles gambiae, is important for assessing the risk of infectious mosquitoes, and how vector control interventions may impact this risk. The use of near-infrared spectroscopy (NIRS) for age-grading has been demonstrated previously on laboratory and semi-field mosquitoes, but to date has not been utilized on wild-caught mosquitoes whose age is externally validated via parity status or parasite infection stage. In this study, we developed regression and classification models using NIRS on datasets of wild An. gambiae (s.l.) reared from larvae collected from the field in Burkina Faso, and two laboratory strains. We compared the accuracy of these models for predicting the ages of wild-caught mosquitoes that had been scored for their parity status as well as for positivity for Plasmodium sporozoites. Regression models utilizing variable selection increased predictive accuracy over the more common full-spectrum partial least squares (PLS) approach for cross-validation of the datasets, validation, and independent test sets. Models produced from datasets that included the greatest range of mosquito samples (i.e. different sampling locations and times) had the highest predictive accuracy on independent testing sets, though overall accuracy on these samples was low. For classification, we found that intramodel accuracy ranged between 73.5-97.0% for grouping of mosquitoes into "early" and "late" age classes, with the highest prediction accuracy found in laboratory colonized mosquitoes. However, this accuracy was decreased on test sets, with the highest classification of an independent set of wild-caught larvae reared to set ages being 69.6%. Variation in NIRS data, likely from dietary, genetic, and other factors limits the accuracy of this technique with wild-caught mosquitoes. Alternative algorithms may help improve prediction accuracy, but care should be taken to either maximize variety in models or minimize confounders.

A new framework of statistical inferences based on the valid joint sampling distribution of the observed counts in an incomplete contingency table.

PubMed

Tian, Guo-Liang; Li, Hui-Qiong

2017-08-01

Some existing confidence interval methods and hypothesis testing methods in the analysis of a contingency table with incomplete observations in both margins entirely depend on an underlying assumption that the sampling distribution of the observed counts is a product of independent multinomial/binomial distributions for complete and incomplete counts. However, it can be shown that this independency assumption is incorrect and can result in unreliable conclusions because of the under-estimation of the uncertainty. Therefore, the first objective of this paper is to derive the valid joint sampling distribution of the observed counts in a contingency table with incomplete observations in both margins. The second objective is to provide a new framework for analyzing incomplete contingency tables based on the derived joint sampling distribution of the observed counts by developing a Fisher scoring algorithm to calculate maximum likelihood estimates of parameters of interest, the bootstrap confidence interval methods, and the bootstrap testing hypothesis methods. We compare the differences between the valid sampling distribution and the sampling distribution under the independency assumption. Simulation studies showed that average/expected confidence-interval widths of parameters based on the sampling distribution under the independency assumption are shorter than those based on the new sampling distribution, yielding unrealistic results. A real data set is analyzed to illustrate the application of the new sampling distribution for incomplete contingency tables and the analysis results again confirm the conclusions obtained from the simulation studies.

Evaluation of artificial neural network algorithms for predicting METs and activity type from accelerometer data: validation on an independent sample.

PubMed

Freedson, Patty S; Lyden, Kate; Kozey-Keadle, Sarah; Staudenmayer, John

2011-12-01

Previous work from our laboratory provided a "proof of concept" for use of artificial neural networks (nnets) to estimate metabolic equivalents (METs) and identify activity type from accelerometer data (Staudenmayer J, Pober D, Crouter S, Bassett D, Freedson P, J Appl Physiol 107: 1330-1307, 2009). The purpose of this study was to develop new nnets based on a larger, more diverse, training data set and apply these nnet prediction models to an independent sample to evaluate the robustness and flexibility of this machine-learning modeling technique. The nnet training data set (University of Massachusetts) included 277 participants who each completed 11 activities. The independent validation sample (n = 65) (University of Tennessee) completed one of three activity routines. Criterion measures were 1) measured METs assessed using open-circuit indirect calorimetry; and 2) observed activity to identify activity type. The nnet input variables included five accelerometer count distribution features and the lag-1 autocorrelation. The bias and root mean square errors for the nnet MET trained on University of Massachusetts and applied to University of Tennessee were +0.32 and 1.90 METs, respectively. Seventy-seven percent of the activities were correctly classified as sedentary/light, moderate, or vigorous intensity. For activity type, household and locomotion activities were correctly classified by the nnet activity type 98.1 and 89.5% of the time, respectively, and sport was correctly classified 23.7% of the time. Use of this machine-learning technique operates reasonably well when applied to an independent sample. We propose the creation of an open-access activity dictionary, including accelerometer data from a broad array of activities, leading to further improvements in prediction accuracy for METs, activity intensity, and activity type.

How to test validity in orthodontic research: a mixed dentition analysis example.

PubMed

Donatelli, Richard E; Lee, Shin-Jae

2015-02-01

The data used to test the validity of a prediction method should be different from the data used to generate the prediction model. In this study, we explored whether an independent data set is mandatory for testing the validity of a new prediction method and how validity can be tested without independent new data. Several validation methods were compared in an example using the data from a mixed dentition analysis with a regression model. The validation errors of real mixed dentition analysis data and simulation data were analyzed for increasingly large data sets. The validation results of both the real and the simulation studies demonstrated that the leave-1-out cross-validation method had the smallest errors. The largest errors occurred in the traditional simple validation method. The differences between the validation methods diminished as the sample size increased. The leave-1-out cross-validation method seems to be an optimal validation method for improving the prediction accuracy in a data set with limited sample sizes. Copyright © 2015 American Association of Orthodontists. Published by Elsevier Inc. All rights reserved.

Is the technical performance of young soccer players influenced by hormonal status, sexual maturity, anthropometric profile, and physical performance?

PubMed

Moreira, Alexandre; Massa, Marcelo; Thiengo, Carlos R; Rodrigues Lopes, Rafael Alan; Lima, Marcelo R; Vaeyens, Roel; Barbosa, Wesley P; Aoki, Marcelo S

2017-12-01

The aim of this study was to examine the influence of hormonal status, anthropometric profile, sexual maturity level, and physical performance on the technical abilities of 40 young male soccer players during small-sided games (SSGs). Anthropometric profiling, saliva sampling, sexual maturity assessment (Tanner scale), and physical performance tests (Yo-Yo and vertical jumps) were conducted two weeks prior to the SSGs. Salivary testosterone was determined by the enzyme-linked immunosorbent assay method. Technical performance was determined by the frequency of actions during SSGs. Principal component analyses identified four technical actions of importance: total number of passes, effectiveness, goal attempts, and total tackles. A multivariate canonical correlation analysis was then employed to verify the prediction of a multiple dependent variables set (composed of four technical actions) from an independent set of variables, composed of testosterone concentration, stage of pubic hair and genitalia development, vertical jumps and Yo-Yo performance. A moderate-to-large relationship between the technical performance set and the independent set was observed. The canonical correlation was 0.75 with a canonical R 2 of 0.45. The highest structure coefficient in the technical performance set was observed for tackles (0.77), while testosterone presented the highest structure coefficient (0.75) for the variables of the independent set. The current data suggest that the selected independent set of variables might be useful in predicting SSG performance in young soccer players. Coaches should be aware that physical development plays a key role in technical performance to avoid decision-making mistakes during the selection of young players.

Effects of sample survey design on the accuracy of classification tree models in species distribution models

Treesearch

Thomas C. Edwards; D. Richard Cutler; Niklaus E. Zimmermann; Linda Geiser; Gretchen G. Moisen

2006-01-01

We evaluated the effects of probabilistic (hereafter DESIGN) and non-probabilistic (PURPOSIVE) sample surveys on resultant classification tree models for predicting the presence of four lichen species in the Pacific Northwest, USA. Models derived from both survey forms were assessed using an independent data set (EVALUATION). Measures of accuracy as gauged by...

Comparing the MMPI-2 Scale Scores of Parents Involved in Parental Competency and Child Custody Assessments

ERIC Educational Resources Information Center

Resendes, John; Lecci, Len

2012-01-01

MMPI-2 scores from a parent competency sample (N = 136 parents) are compared with a previously published data set of MMPI-2 scores for child custody litigants (N = 508 parents; Bathurst et al., 1997). Independent samples t tests yielded significant and in some cases substantial differences on the standard MMPI-2 clinical scales (especially Scales…

[Detection of the main quality indicators in red wine with infrared spectroscopy based on FastICA and neural network].

PubMed

Fang, Li-Min; Lin, Min

2009-08-01

For the rapid detection of the ethanol, pH and rest sugar in red wine, infrared (IR) spectra of 44 wine samples were analyzed. The algorithm of fast independent component analysis (FastICA) was used to decompose the data of IR spectra, and their independent components and the mixing matrix were obtained. Then, the ICA-NNR calibration model with three-level artificial neural network (ANN) structure was built by using back-propagation (BP) algorithm. The models were used to estimate the contents of ethanol, pH and rest sugar in red wine samples for both in calibration set and predicted set. Correlation coefficient (r) of prediction and root mean square error of prediction (RMSEP) were used as the evaluation indexes. The results indicate that the r and RMSEP for the prediction of ethanol content, pH and rest sugar content are 0.953, 0.983 and 0.994, and 0.161, 0.017 and 0.181, respectively. The maximum relative deviations between the ICA-NNR method predicted value and referenced value of the 22 samples in predicted set are less than 4%. The results of this paper provide a foundation for the application and further development of IR on-line red wine analyzer.

Diagnosing the predisposition for diabetes mellitus by means of mid-IR spectroscopy

NASA Astrophysics Data System (ADS)

Frueh, Johanna; Jacob, Stephan; Dolenko, Brion; Haering, Hans-Ullrich; Mischler, Reinhold; Quarder, Ortrud; Renn, Walter; Somorjai, Raymond L.; Staib, Arnulf; Werner, Gerhard H.; Petrich, Wolfgang H.

2002-03-01

The vicious circle of insulin resistance and hyperinsulinemia is considered to precede the manifestation of diabetes type-2 by decades and the corresponding cluster of risk factors is described as the 'insulin resistance syndrome' or 'metabolic syndrome'. Since the present diagnosis of insulin resistance is expensive, time consuming and cumbersome, there is a need for diagnostic alternatives. We conducted a clinical study on 129 healthy volunteers and 99 patients suffering from the metabolic syndrome. We applied mid-infrared spectroscopy to dried serum samples from these donors and evaluated the spectra by means of disease pattern recognition (DPR). Substantial differences were found between the spectra originating from healthy volunteers and those spectra originating from patients with the metabolic syndrome. A linear discriminant analysis was performed using approximately one half of the sample set for teaching the classification algorithm. Within this teaching set, a classification sensitivity and specificity of 84 percent and 81 percent respectively can be derived. Furthermore, the resulting discriminant function was applied to an independent validation of the remaining half of the samples. For the discrimination between 'healthy' and 'metabolic syndrome' a sensitivity and a specificity of 80 percent and 82 percent respectively is obtained upon validating the algorithm with the independent validation set.

Application of partial least squares near-infrared spectral classification in diabetic identification

NASA Astrophysics Data System (ADS)

Yan, Wen-juan; Yang, Ming; He, Guo-quan; Qin, Lin; Li, Gang

2014-11-01

In order to identify the diabetic patients by using tongue near-infrared (NIR) spectrum - a spectral classification model of the NIR reflectivity of the tongue tip is proposed, based on the partial least square (PLS) method. 39sample data of tongue tip's NIR spectra are harvested from healthy people and diabetic patients , respectively. After pretreatment of the reflectivity, the spectral data are set as the independent variable matrix, and information of classification as the dependent variables matrix, Samples were divided into two groups - i.e. 53 samples as calibration set and 25 as prediction set - then the PLS is used to build the classification model The constructed modelfrom the 53 samples has the correlation of 0.9614 and the root mean square error of cross-validation (RMSECV) of 0.1387.The predictions for the 25 samples have the correlation of 0.9146 and the RMSECV of 0.2122.The experimental result shows that the PLS method can achieve good classification on features of healthy people and diabetic patients.

Combinatorial Statistics on Trees and Networks

DTIC Science & Technology

2010-09-29

interaction graph is drawn from the Erdos- Renyi , G(n,p), where each edge is present independently with probability p. For this model we establish a double...special interest is the behavior of Gibbs sampling on the Erdos- Renyi random graph G{n, d/n), where each edge is chosen independently with...which have no counterparts in the coloring setting. Our proof presented here exploits in novel ways the local treelike structure of Erdos- Renyi

Valid statistical inference methods for a case-control study with missing data.

PubMed

Tian, Guo-Liang; Zhang, Chi; Jiang, Xuejun

2018-04-01

The main objective of this paper is to derive the valid sampling distribution of the observed counts in a case-control study with missing data under the assumption of missing at random by employing the conditional sampling method and the mechanism augmentation method. The proposed sampling distribution, called the case-control sampling distribution, can be used to calculate the standard errors of the maximum likelihood estimates of parameters via the Fisher information matrix and to generate independent samples for constructing small-sample bootstrap confidence intervals. Theoretical comparisons of the new case-control sampling distribution with two existing sampling distributions exhibit a large difference. Simulations are conducted to investigate the influence of the three different sampling distributions on statistical inferences. One finding is that the conclusion by the Wald test for testing independency under the two existing sampling distributions could be completely different (even contradictory) from the Wald test for testing the equality of the success probabilities in control/case groups under the proposed distribution. A real cervical cancer data set is used to illustrate the proposed statistical methods.

Utilizing Maximal Independent Sets as Dominating Sets in Scale-Free Networks

NASA Astrophysics Data System (ADS)

Derzsy, N.; Molnar, F., Jr.; Szymanski, B. K.; Korniss, G.

Dominating sets provide key solution to various critical problems in networked systems, such as detecting, monitoring, or controlling the behavior of nodes. Motivated by graph theory literature [Erdos, Israel J. Math. 4, 233 (1966)], we studied maximal independent sets (MIS) as dominating sets in scale-free networks. We investigated the scaling behavior of the size of MIS in artificial scale-free networks with respect to multiple topological properties (size, average degree, power-law exponent, assortativity), evaluated its resilience to network damage resulting from random failure or targeted attack [Molnar et al., Sci. Rep. 5, 8321 (2015)], and compared its efficiency to previously proposed dominating set selection strategies. We showed that, despite its small set size, MIS provides very high resilience against network damage. Using extensive numerical analysis on both synthetic and real-world (social, biological, technological) network samples, we demonstrate that our method effectively satisfies four essential requirements of dominating sets for their practical applicability on large-scale real-world systems: 1.) small set size, 2.) minimal network information required for their construction scheme, 3.) fast and easy computational implementation, and 4.) resiliency to network damage. Supported by DARPA, DTRA, and NSF.

Quarry identification of historical building materials by means of laser induced breakdown spectroscopy, X-ray fluorescence and chemometric analysis

NASA Astrophysics Data System (ADS)

Colao, F.; Fantoni, R.; Ortiz, P.; Vazquez, M. A.; Martin, J. M.; Ortiz, R.; Idris, N.

2010-08-01

To characterize historical building materials according to the geographic origin of the quarries from which they have been mined, the relative content of major and trace elements were determined by means of Laser Induced Breakdown Spectroscopy (LIBS) and X-ray Fluorescence (XRF) techniques. 48 different specimens were studied and the entire samples' set was divided in two different groups: the first, used as reference set, was composed by samples mined from eight different quarries located in Seville province; the second group was composed by specimens of unknown provenance collected in several historical buildings and churches in the city of Seville. Data reduction and analysis on laser induced breakdown spectroscopy and X-ray fluorescence measurements was performed using multivariate statistical approach, namely the Linear Discriminant Analysis (LDA), Principal Component Analysis (PCA) and Soft Independent Modeling of Class Analogy (SIMCA). A clear separation among reference sample materials mined from different quarries was observed in Principal Components (PC) score plots, then a supervised soft independent modeling of class analogy classification was trained and run, aiming to assess the provenance of unknown samples according to their elemental content. The obtained results were compared with the provenance assignments made on the basis of petrographical description. This work gives experimental evidence that laser induced breakdown spectroscopy measurements on a relatively small set of elements is a fast and effective method for the purpose of origin identification.

Multigenic Delineation of Lower Jaw Deformity in Triploid Atlantic Salmon (Salmo salar L.)

PubMed Central

Amoroso, Gianluca; Ventura, Tomer; Elizur, Abigail; Carter, Chris G.

2016-01-01

Lower jaw deformity (LJD) is a skeletal anomaly affecting farmed triploid Atlantic salmon (Salmo salar L.) which leads to considerable economic losses for industry and has animal welfare implications. The present study employed transcriptome analysis in parallel with real-time qPCR techniques to characterise for the first time the LJD condition in triploid Atlantic salmon juveniles using two independent sample sets: experimentally-sourced salmon (60 g) and commercially produced salmon (100 g). A total of eleven genes, some detected/identified through the transcriptome analysis (fbn2, gal and gphb5) and others previously determined to be related to skeletal physiology (alp, bmp4, col1a1, col2a1, fgf23, igf1, mmp13, ocn), were tested in the two independent sample sets. Gphb5, a recently discovered hormone, was significantly (P < 0.05) down-regulated in LJD affected fish in both sample sets, suggesting a possible hormonal involvement. In-situ hybridization detected gphb5 expression in oral epithelium, teeth and skin of the lower jaw. Col2a1 showed the same consistent significant (P < 0.05) down-regulation in LJD suggesting a possible cartilaginous impairment as a distinctive feature of the condition. Significant (P < 0.05) differential expression of other genes found in either one or the other sample set highlighted the possible effect of stage of development or condition progression on transcription and showed that anomalous bone development, likely driven by cartilage impairment, is more evident at larger fish sizes. The present study improved our understanding of LJD suggesting that a cartilage impairment likely underlies the condition and col2a1 may be a marker. In addition, the involvement of gphb5 urges further investigation of a hormonal role in LJD and skeletal physiology in general. PMID:27977809

Multigenic Delineation of Lower Jaw Deformity in Triploid Atlantic Salmon (Salmo salar L.).

PubMed

Amoroso, Gianluca; Ventura, Tomer; Cobcroft, Jennifer M; Adams, Mark B; Elizur, Abigail; Carter, Chris G

2016-01-01

Lower jaw deformity (LJD) is a skeletal anomaly affecting farmed triploid Atlantic salmon (Salmo salar L.) which leads to considerable economic losses for industry and has animal welfare implications. The present study employed transcriptome analysis in parallel with real-time qPCR techniques to characterise for the first time the LJD condition in triploid Atlantic salmon juveniles using two independent sample sets: experimentally-sourced salmon (60 g) and commercially produced salmon (100 g). A total of eleven genes, some detected/identified through the transcriptome analysis (fbn2, gal and gphb5) and others previously determined to be related to skeletal physiology (alp, bmp4, col1a1, col2a1, fgf23, igf1, mmp13, ocn), were tested in the two independent sample sets. Gphb5, a recently discovered hormone, was significantly (P < 0.05) down-regulated in LJD affected fish in both sample sets, suggesting a possible hormonal involvement. In-situ hybridization detected gphb5 expression in oral epithelium, teeth and skin of the lower jaw. Col2a1 showed the same consistent significant (P < 0.05) down-regulation in LJD suggesting a possible cartilaginous impairment as a distinctive feature of the condition. Significant (P < 0.05) differential expression of other genes found in either one or the other sample set highlighted the possible effect of stage of development or condition progression on transcription and showed that anomalous bone development, likely driven by cartilage impairment, is more evident at larger fish sizes. The present study improved our understanding of LJD suggesting that a cartilage impairment likely underlies the condition and col2a1 may be a marker. In addition, the involvement of gphb5 urges further investigation of a hormonal role in LJD and skeletal physiology in general.

TemperSAT: A new efficient fair-sampling random k-SAT solver

NASA Astrophysics Data System (ADS)

Fang, Chao; Zhu, Zheng; Katzgraber, Helmut G.

The set membership problem is of great importance to many applications and, in particular, database searches for target groups. Recently, an approach to speed up set membership searches based on the NP-hard constraint-satisfaction problem (random k-SAT) has been developed. However, the bottleneck of the approach lies in finding the solution to a large SAT formula efficiently and, in particular, a large number of independent solutions is needed to reduce the probability of false positives. Unfortunately, traditional random k-SAT solvers such as WalkSAT are biased when seeking solutions to the Boolean formulas. By porting parallel tempering Monte Carlo to the sampling of binary optimization problems, we introduce a new algorithm (TemperSAT) whose performance is comparable to current state-of-the-art SAT solvers for large k with the added benefit that theoretically it can find many independent solutions quickly. We illustrate our results by comparing to the currently fastest implementation of WalkSAT, WalkSATlm.

Biases in the OSSOS Detection of Large Semimajor Axis Trans-Neptunian Objects

NASA Astrophysics Data System (ADS)

Gladman, Brett; Shankman, Cory; OSSOS Collaboration

2017-10-01

The accumulating but small set of large semimajor axis trans-Neptunian objects (TNOs) shows an apparent clustering in the orientations of their orbits. This clustering must either be representative of the intrinsic distribution of these TNOs, or else have arisen as a result of observation biases and/or statistically expected variations for such a small set of detected objects. The clustered TNOs were detected across different and independent surveys, which has led to claims that the detections are therefore free of observational bias. This apparent clustering has led to the so-called “Planet 9” hypothesis that a super-Earth currently resides in the distant solar system and causes this clustering. The Outer Solar System Origins Survey (OSSOS) is a large program that ran on the Canada-France-Hawaii Telescope from 2013 to 2017, discovering more than 800 new TNOs. One of the primary design goals of OSSOS was the careful determination of observational biases that would manifest within the detected sample. We demonstrate the striking and non-intuitive biases that exist for the detection of TNOs with large semimajor axes. The eight large semimajor axis OSSOS detections are an independent data set, of comparable size to the conglomerate samples used in previous studies. We conclude that the orbital distribution of the OSSOS sample is consistent with being detected from a uniform underlying angular distribution.

OSSOS. VI. Striking Biases in the Detection of Large Semimajor Axis Trans-Neptunian Objects

NASA Astrophysics Data System (ADS)

Shankman, Cory; Kavelaars, J. J.; Bannister, Michele T.; Gladman, Brett J.; Lawler, Samantha M.; Chen, Ying-Tung; Jakubik, Marian; Kaib, Nathan; Alexandersen, Mike; Gwyn, Stephen D. J.; Petit, Jean-Marc; Volk, Kathryn

2017-08-01

The accumulating but small set of large semimajor axis trans-Neptunian objects (TNOs) shows an apparent clustering in the orientations of their orbits. This clustering must either be representative of the intrinsic distribution of these TNOs, or else have arisen as a result of observation biases and/or statistically expected variations for such a small set of detected objects. The clustered TNOs were detected across different and independent surveys, which has led to claims that the detections are therefore free of observational bias. This apparent clustering has led to the so-called “Planet 9” hypothesis that a super-Earth currently resides in the distant solar system and causes this clustering. The Outer Solar System Origins Survey (OSSOS) is a large program that ran on the Canada–France–Hawaii Telescope from 2013 to 2017, discovering more than 800 new TNOs. One of the primary design goals of OSSOS was the careful determination of observational biases that would manifest within the detected sample. We demonstrate the striking and non-intuitive biases that exist for the detection of TNOs with large semimajor axes. The eight large semimajor axis OSSOS detections are an independent data set, of comparable size to the conglomerate samples used in previous studies. We conclude that the orbital distribution of the OSSOS sample is consistent with being detected from a uniform underlying angular distribution.

Revealing strong bias in common measures of galaxy properties using new inclination-independent structures

NASA Astrophysics Data System (ADS)

Devour, Brian M.; Bell, Eric F.

2017-06-01

Accurate measurement of galaxy structures is a prerequisite for quantitative investigation of galaxy properties or evolution. Yet, the impact of galaxy inclination and dust on commonly used metrics of galaxy structure is poorly quantified. We use infrared data sets to select inclination-independent samples of disc and flattened elliptical galaxies. These samples show strong variation in Sérsic index, concentration and half-light radii with inclination. We develop novel inclination-independent galaxy structures by collapsing the light distribution in the near-infrared on to the major axis, yielding inclination-independent 'linear' measures of size and concentration. With these new metrics we select a sample of Milky Way analogue galaxies with similar stellar masses, star formation rates, sizes and concentrations. Optical luminosities, light distributions and spectral properties are all found to vary strongly with inclination: When inclining to edge-on, r-band luminosities dim by >1 magnitude, sizes decrease by a factor of 2, 'dust-corrected' estimates of star formation rate drop threefold, metallicities decrease by 0.1 dex and edge-on galaxies are half as likely to be classified as star forming. These systematic effects should be accounted for in analyses of galaxy properties.

Role of diversity in ICA and IVA: theory and applications

NASA Astrophysics Data System (ADS)

Adalı, Tülay

2016-05-01

Independent component analysis (ICA) has been the most popular approach for solving the blind source separation problem. Starting from a simple linear mixing model and the assumption of statistical independence, ICA can recover a set of linearly-mixed sources to within a scaling and permutation ambiguity. It has been successfully applied to numerous data analysis problems in areas as diverse as biomedicine, communications, finance, geo- physics, and remote sensing. ICA can be achieved using different types of diversity—statistical property—and, can be posed to simultaneously account for multiple types of diversity such as higher-order-statistics, sample dependence, non-circularity, and nonstationarity. A recent generalization of ICA, independent vector analysis (IVA), generalizes ICA to multiple data sets and adds the use of one more type of diversity, statistical dependence across the data sets, for jointly achieving independent decomposition of multiple data sets. With the addition of each new diversity type, identification of a broader class of signals become possible, and in the case of IVA, this includes sources that are independent and identically distributed Gaussians. We review the fundamentals and properties of ICA and IVA when multiple types of diversity are taken into account, and then ask the question whether diversity plays an important role in practical applications as well. Examples from various domains are presented to demonstrate that in many scenarios it might be worthwhile to jointly account for multiple statistical properties. This paper is submitted in conjunction with the talk delivered for the "Unsupervised Learning and ICA Pioneer Award" at the 2016 SPIE Conference on Sensing and Analysis Technologies for Biomedical and Cognitive Applications.

Reliable pre-eclampsia pathways based on multiple independent microarray data sets.

PubMed

Kawasaki, Kaoru; Kondoh, Eiji; Chigusa, Yoshitsugu; Ujita, Mari; Murakami, Ryusuke; Mogami, Haruta; Brown, J B; Okuno, Yasushi; Konishi, Ikuo

2015-02-01

Pre-eclampsia is a multifactorial disorder characterized by heterogeneous clinical manifestations. Gene expression profiling of preeclamptic placenta have provided different and even opposite results, partly due to data compromised by various experimental artefacts. Here we aimed to identify reliable pre-eclampsia-specific pathways using multiple independent microarray data sets. Gene expression data of control and preeclamptic placentas were obtained from Gene Expression Omnibus. Single-sample gene-set enrichment analysis was performed to generate gene-set activation scores of 9707 pathways obtained from the Molecular Signatures Database. Candidate pathways were identified by t-test-based screening using data sets, GSE10588, GSE14722 and GSE25906. Additionally, recursive feature elimination was applied to arrive at a further reduced set of pathways. To assess the validity of the pre-eclampsia pathways, a statistically-validated protocol was executed using five data sets including two independent other validation data sets, GSE30186, GSE44711. Quantitative real-time PCR was performed for genes in a panel of potential pre-eclampsia pathways using placentas of 20 women with normal or severe preeclamptic singleton pregnancies (n = 10, respectively). A panel of ten pathways were found to discriminate women with pre-eclampsia from controls with high accuracy. Among these were pathways not previously associated with pre-eclampsia, such as the GABA receptor pathway, as well as pathways that have already been linked to pre-eclampsia, such as the glutathione and CDKN1C pathways. mRNA expression of GABRA3 (GABA receptor pathway), GCLC and GCLM (glutathione metabolic pathway), and CDKN1C was significantly reduced in the preeclamptic placentas. In conclusion, ten accurate and reliable pre-eclampsia pathways were identified based on multiple independent microarray data sets. A pathway-based classification may be a worthwhile approach to elucidate the pathogenesis of pre-eclampsia. © The Author 2014. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Independent Research and Independent Exploratory Development Programs: FY92 Annual Report

DTIC Science & Technology

1993-04-01

transform- of an ERP provides a record of ERP energy at different times and scales. It does this by producing a set of filtered time series ai different...that the coefficients at any level are a series that measures energy within the bandwidth of that level as a function of time. For this reason it is...I to 25 Hz, and decimated to a final sampling rate of 50 Hz. The prestimulus baseline (200 ms) was adjusted to zero to remove any DC offset

A random sampling approach for robust estimation of tissue-to-plasma ratio from extremely sparse data.

PubMed

Chu, Hui-May; Ette, Ene I

2005-09-02

his study was performed to develop a new nonparametric approach for the estimation of robust tissue-to-plasma ratio from extremely sparsely sampled paired data (ie, one sample each from plasma and tissue per subject). Tissue-to-plasma ratio was estimated from paired/unpaired experimental data using independent time points approach, area under the curve (AUC) values calculated with the naïve data averaging approach, and AUC values calculated using sampling based approaches (eg, the pseudoprofile-based bootstrap [PpbB] approach and the random sampling approach [our proposed approach]). The random sampling approach involves the use of a 2-phase algorithm. The convergence of the sampling/resampling approaches was investigated, as well as the robustness of the estimates produced by different approaches. To evaluate the latter, new data sets were generated by introducing outlier(s) into the real data set. One to 2 concentration values were inflated by 10% to 40% from their original values to produce the outliers. Tissue-to-plasma ratios computed using the independent time points approach varied between 0 and 50 across time points. The ratio obtained from AUC values acquired using the naive data averaging approach was not associated with any measure of uncertainty or variability. Calculating the ratio without regard to pairing yielded poorer estimates. The random sampling and pseudoprofile-based bootstrap approaches yielded tissue-to-plasma ratios with uncertainty and variability. However, the random sampling approach, because of the 2-phase nature of its algorithm, yielded more robust estimates and required fewer replications. Therefore, a 2-phase random sampling approach is proposed for the robust estimation of tissue-to-plasma ratio from extremely sparsely sampled data.

Assessment of powder blend uniformity: Comparison of real-time NIR blend monitoring with stratified sampling in combination with HPLC and at-line NIR Chemical Imaging.

PubMed

Bakri, Barbara; Weimer, Marco; Hauck, Gerrit; Reich, Gabriele

2015-11-01

Scope of the study was (1) to develop a lean quantitative calibration for real-time near-infrared (NIR) blend monitoring, which meets the requirements in early development of pharmaceutical products and (2) to compare the prediction performance of this approach with the results obtained from stratified sampling using a sample thief in combination with off-line high pressure liquid chromatography (HPLC) and at-line near-infrared chemical imaging (NIRCI). Tablets were manufactured from powder blends and analyzed with NIRCI and HPLC to verify the real-time results. The model formulation contained 25% w/w naproxen as a cohesive active pharmaceutical ingredient (API), microcrystalline cellulose and croscarmellose sodium as cohesive excipients and free-flowing mannitol. Five in-line NIR calibration approaches, all using the spectra from the end of the blending process as reference for PLS modeling, were compared in terms of selectivity, precision, prediction accuracy and robustness. High selectivity could be achieved with a "reduced" approach i.e. API and time saving approach (35% reduction of API amount) based on six concentration levels of the API with three levels realized by three independent powder blends and the additional levels obtained by simply increasing the API concentration in these blends. Accuracy and robustness were further improved by combining this calibration set with a second independent data set comprising different excipient concentrations and reflecting different environmental conditions. The combined calibration model was used to monitor the blending process of independent batches. For this model formulation the target concentration of the API could be achieved within 3 min indicating a short blending time. The in-line NIR approach was verified by stratified sampling HPLC and NIRCI results. All three methods revealed comparable results regarding blend end point determination. Differences in both mean API concentration and RSD values could be attributed to differences in effective sample size and thief sampling errors. This conclusion was supported by HPLC and NIRCI analysis of tablets manufactured from powder blends after different blending times. In summary, the study clearly demonstrates the ability to develop efficient and robust quantitative calibrations for real-time NIR powder blend monitoring with a reduced set of powder blends while avoiding any bias caused by physical sampling. Copyright © 2015 Elsevier B.V. All rights reserved.

A place meaning scale for tropical marine settings.

PubMed

Wynveen, Christopher J; Kyle, Gerard T

2015-01-01

Over the past 20 years, most of the worldwide hectares set aside for environmental protection have been added to marine protected areas. Moreover, these areas are under tremendous pressure from negative anthropogenic impacts. Given this growth and pressure, there is a need to increase the understanding of the connection between people and marine environments in order to better manage the resource. One construct that researchers have used to understand human-environment connections is place meanings. Place meanings reflect the value and significance of a setting to individuals. Most investigations of place meanings have been confined to terrestrial settings. Moreover, most studies have had small sample sizes or have used place attachment scales as a proxy to gage the meanings individuals ascribe to a setting. Hence, it has become necessary to develop a place meaning scale for use with large samples and for use by those who are concerned about the management of marine environments. Therefore, the purpose of this investigation was to develop a scale to measure the importance people associate with the meanings they ascribe to tropical marine settings and empirically test the scale using two independent samples; that is, Great Barrier Reef Marine Park and the Florida Keys National Marine Sanctuary stakeholders.

A Place Meaning Scale for Tropical Marine Settings

NASA Astrophysics Data System (ADS)

Wynveen, Christopher J.; Kyle, Gerard T.

2015-01-01

Over the past 20 years, most of the worldwide hectares set aside for environmental protection have been added to marine protected areas. Moreover, these areas are under tremendous pressure from negative anthropogenic impacts. Given this growth and pressure, there is a need to increase the understanding of the connection between people and marine environments in order to better manage the resource. One construct that researchers have used to understand human-environment connections is place meanings. Place meanings reflect the value and significance of a setting to individuals. Most investigations of place meanings have been confined to terrestrial settings. Moreover, most studies have had small sample sizes or have used place attachment scales as a proxy to gage the meanings individuals ascribe to a setting. Hence, it has become necessary to develop a place meaning scale for use with large samples and for use by those who are concerned about the management of marine environments. Therefore, the purpose of this investigation was to develop a scale to measure the importance people associate with the meanings they ascribe to tropical marine settings and empirically test the scale using two independent samples; that is, Great Barrier Reef Marine Park and the Florida Keys National Marine Sanctuary stakeholders.

Improving Global Models of Remotely Sensed Ocean Chlorophyll Content Using Partial Least Squares and Geographically Weighted Regression

NASA Astrophysics Data System (ADS)

Gholizadeh, H.; Robeson, S. M.

2015-12-01

Empirical models have been widely used to estimate global chlorophyll content from remotely sensed data. Here, we focus on the standard NASA empirical models that use blue-green band ratios. These band ratio ocean color (OC) algorithms are in the form of fourth-order polynomials and the parameters of these polynomials (i.e. coefficients) are estimated from the NASA bio-Optical Marine Algorithm Data set (NOMAD). Most of the points in this data set have been sampled from tropical and temperate regions. However, polynomial coefficients obtained from this data set are used to estimate chlorophyll content in all ocean regions with different properties such as sea-surface temperature, salinity, and downwelling/upwelling patterns. Further, the polynomial terms in these models are highly correlated. In sum, the limitations of these empirical models are as follows: 1) the independent variables within the empirical models, in their current form, are correlated (multicollinear), and 2) current algorithms are global approaches and are based on the spatial stationarity assumption, so they are independent of location. Multicollinearity problem is resolved by using partial least squares (PLS). PLS, which transforms the data into a set of independent components, can be considered as a combined form of principal component regression (PCR) and multiple regression. Geographically weighted regression (GWR) is also used to investigate the validity of spatial stationarity assumption. GWR solves a regression model over each sample point by using the observations within its neighbourhood. PLS results show that the empirical method underestimates chlorophyll content in high latitudes, including the Southern Ocean region, when compared to PLS (see Figure 1). Cluster analysis of GWR coefficients also shows that the spatial stationarity assumption in empirical models is not likely a valid assumption.

A polymorphism in CCR1/CCR3 is associated with narcolepsy.

PubMed

Toyoda, Hiromi; Miyagawa, Taku; Koike, Asako; Kanbayashi, Takashi; Imanishi, Aya; Sagawa, Yohei; Kotorii, Nozomu; Kotorii, Tatayu; Hashizume, Yuji; Ogi, Kimihiro; Hiejima, Hiroshi; Kamei, Yuichi; Hida, Akiko; Miyamoto, Masayuki; Imai, Makoto; Fujimura, Yota; Tamura, Yoshiyuki; Ikegami, Azusa; Wada, Yamato; Moriya, Shunpei; Furuya, Hirokazu; Takeuchi, Masaki; Kirino, Yohei; Meguro, Akira; Remmers, Elaine F; Kawamura, Yoshiya; Otowa, Takeshi; Miyashita, Akinori; Kashiwase, Koichi; Khor, Seik-Soon; Yamasaki, Maria; Kuwano, Ryozo; Sasaki, Tsukasa; Ishigooka, Jun; Kuroda, Kenji; Kume, Kazuhiko; Chiba, Shigeru; Yamada, Naoto; Okawa, Masako; Hirata, Koichi; Mizuki, Nobuhisa; Uchimura, Naohisa; Shimizu, Tetsuo; Inoue, Yuichi; Honda, Yutaka; Mishima, Kazuo; Honda, Makoto; Tokunaga, Katsushi

2015-10-01

Etiology of narcolepsy-cataplexy involves multiple genetic and environmental factors. While the human leukocyte antigen (HLA)-DRB1*15:01-DQB1*06:02 haplotype is strongly associated with narcolepsy, it is not sufficient for disease development. To identify additional, non-HLA susceptibility genes, we conducted a genome-wide association study (GWAS) using Japanese samples. An initial sample set comprising 409 cases and 1562 controls was used for the GWAS of 525,196 single nucleotide polymorphisms (SNPs) located outside the HLA region. An independent sample set comprising 240 cases and 869 controls was then genotyped at 37 SNPs identified in the GWAS. We found that narcolepsy was associated with a SNP in the promoter region of chemokine (C-C motif) receptor 1 (CCR1) (rs3181077, P=1.6×10(-5), odds ratio [OR]=1.86). This rs3181077 association was replicated with the independent sample set (P=0.032, OR=1.36). We measured mRNA levels of candidate genes in peripheral blood samples of 38 cases and 37 controls. CCR1 and CCR3 mRNA levels were significantly lower in patients than in healthy controls, and CCR1 mRNA levels were associated with rs3181077 genotypes. In vitro chemotaxis assays were also performed to measure monocyte migration. We observed that monocytes from carriers of the rs3181077 risk allele had lower migration indices with a CCR1 ligand. CCR1 and CCR3 are newly discovered susceptibility genes for narcolepsy. These results highlight the potential role of CCR genes in narcolepsy and support the hypothesis that patients with narcolepsy have impaired immune function. Copyright © 2015 Elsevier Inc. All rights reserved.

Equilibrium Molecular Thermodynamics from Kirkwood Sampling

PubMed Central

2015-01-01

We present two methods for barrierless equilibrium sampling of molecular systems based on the recently proposed Kirkwood method (J. Chem. Phys.2009, 130, 134102). Kirkwood sampling employs low-order correlations among internal coordinates of a molecule for random (or non-Markovian) sampling of the high dimensional conformational space. This is a geometrical sampling method independent of the potential energy surface. The first method is a variant of biased Monte Carlo, where Kirkwood sampling is used for generating trial Monte Carlo moves. Using this method, equilibrium distributions corresponding to different temperatures and potential energy functions can be generated from a given set of low-order correlations. Since Kirkwood samples are generated independently, this method is ideally suited for massively parallel distributed computing. The second approach is a variant of reservoir replica exchange, where Kirkwood sampling is used to construct a reservoir of conformations, which exchanges conformations with the replicas performing equilibrium sampling corresponding to different thermodynamic states. Coupling with the Kirkwood reservoir enhances sampling by facilitating global jumps in the conformational space. The efficiency of both methods depends on the overlap of the Kirkwood distribution with the target equilibrium distribution. We present proof-of-concept results for a model nine-atom linear molecule and alanine dipeptide. PMID:25915525

Evaluation of a panel of 28 biomarkers for the non-invasive diagnosis of endometriosis.

PubMed

Vodolazkaia, A; El-Aalamat, Y; Popovic, D; Mihalyi, A; Bossuyt, X; Kyama, C M; Fassbender, A; Bokor, A; Schols, D; Huskens, D; Meuleman, C; Peeraer, K; Tomassetti, C; Gevaert, O; Waelkens, E; Kasran, A; De Moor, B; D'Hooghe, T M

2012-09-01

At present, the only way to conclusively diagnose endometriosis is laparoscopic inspection, preferably with histological confirmation. This contributes to the delay in the diagnosis of endometriosis which is 6-11 years. So far non-invasive diagnostic approaches such as ultrasound (US), MRI or blood tests do not have sufficient diagnostic power. Our aim was to develop and validate a non-invasive diagnostic test with a high sensitivity (80% or more) for symptomatic endometriosis patients, without US evidence of endometriosis, since this is the group most in need of a non-invasive test. A total of 28 inflammatory and non-inflammatory plasma biomarkers were measured in 353 EDTA plasma samples collected at surgery from 121 controls without endometriosis at laparoscopy and from 232 women with endometriosis (minimal-mild n = 148; moderate-severe n = 84), including 175 women without preoperative US evidence of endometriosis. Surgery was done during menstrual (n = 83), follicular (n = 135) and luteal (n = 135) phases of the menstrual cycle. For analysis, the data were randomly divided into an independent training (n = 235) and a test (n = 118) data set. Statistical analysis was done using univariate and multivariate (logistic regression and least squares support vector machines (LS-SVM) approaches in training- and test data set separately to validate our findings. In the training set, two models of four biomarkers (Model 1: annexin V, VEGF, CA-125 and glycodelin; Model 2: annexin V, VEGF, CA-125 and sICAM-1) analysed in plasma, obtained during the menstrual phase, could predict US-negative endometriosis with a high sensitivity (81-90%) and an acceptable specificity (68-81%). The same two models predicted US-negative endometriosis in the independent validation test set with a high sensitivity (82%) and an acceptable specificity (63-75%). In plasma samples obtained during menstruation, multivariate analysis of four biomarkers (annexin V, VEGF, CA-125 and sICAM-1/or glycodelin) enabled the diagnosis of endometriosis undetectable by US with a sensitivity of 81-90% and a specificity of 63-81% in independent training- and test data set. The next step is to apply these models for preoperative prediction of endometriosis in an independent set of patients with infertility and/or pain without US evidence of endometriosis, scheduled for laparoscopy.

[Studies on the brand traceability of milk powder based on NIR spectroscopy technology].

PubMed

Guan, Xiao; Gu, Fang-Qing; Liu, Jing; Yang, Yong-Jian

2013-10-01

Brand traceability of several different kinds of milk powder was studied by combining near infrared spectroscopy diffuse reflectance mode with soft independent modeling of class analogy (SIMCA) in the present paper. The near infrared spectrum of 138 samples, including 54 Guangming milk powder samples, 43 Netherlands samples, and 33 Nestle samples and 8 Yili samples, were collected. After pretreatment of full spectrum data variables in training set, principal component analysis was performed, and the contribution rate of the cumulative variance of the first three principal components was about 99.07%. Milk powder principal component regression model based on SIMCA was established, and used to classify the milk powder samples in prediction sets. The results showed that the recognition rate of Guangming milk powder, Netherlands milk powder and Nestle milk powder was 78%, 75% and 100%, the rejection rate was 100%, 87%, and 88%, respectively. Therefore, the near infrared spectroscopy combined with SIMCA model can classify milk powder with high accuracy, and is a promising identification method of milk powder variety.

A novel pooled-sample multiplex luminex assay for high-throughput measurement of relative telomere length.

PubMed

Jasmine, Farzana; Shinkle, Justin; Sabarinathan, Mekala; Ahsan, Habibul; Pierce, Brandon L; Kibriya, Muhammad G

2018-03-12

Relative telomere length (RTL) is a potential biomarker of aging and risk for chronic disease. Previously, we developed a probe-based RTL assay on Luminex platform, where probes for Telomere (T) and reference gene (R) for a given DNA sample were tested in a single well. Here, we describe a method of pooling multiple samples in one well to increase the throughput and cost-effectiveness. We used four different microbeads for the same T-probe and four different microbeads for the same R-probe. Each pair of probe sets were hybridized to DNA in separate plates and then pooled in a single plate for all the subsequent steps. We used DNA samples from 60 independent individuals and repeated in multiple batches to test the precision. The precision was good to excellent with Intraclass correlation coefficient (ICC) of 0.908 (95% CI 0.856-0.942). More than 67% of the variation in the RTL could be explained by sample-to-sample variation; less than 0.1% variation was due to batch-to-batch variation and 0.3% variation was explained by bead-to-bead variation. We increased the throughput of RTL Luminex assay from 60 to 240 samples per run. The new assay was validated against the original Luminex assay without pooling (r = 0.79, P = 1.44 × 10 -15 ). In an independent set of samples (n = 550), the new assay showed a negative correlation of RTL with age (r = -0.41), a result providing external validation for the method. We describe a novel high throughput pooled-sample multiplex Luminex assay for RTL with good to excellent precision suitable for large-scale studies. © 2018 Wiley Periodicals, Inc.

Signaling protein signature predicts clinical outcome of non-small-cell lung cancer.

PubMed

Jin, Bao-Feng; Yang, Fan; Ying, Xiao-Min; Gong, Lin; Hu, Shuo-Feng; Zhao, Qing; Liao, Yi-Da; Chen, Ke-Zhong; Li, Teng; Tai, Yan-Hong; Cao, Yuan; Li, Xiao; Huang, Yan; Zhan, Xiao-Yan; Qin, Xuan-He; Wu, Jin; Chen, Shuai; Guo, Sai-Sai; Zhang, Yu-Cheng; Chen, Jing; Shen, Dan-Hua; Sun, Kun-Kun; Chen, Lu; Li, Wei-Hua; Li, Ai-Ling; Wang, Na; Xia, Qing; Wang, Jun; Zhou, Tao

2018-03-06

Non-small-cell lung cancer (NSCLC) is characterized by abnormalities of numerous signaling proteins that play pivotal roles in cancer development and progression. Many of these proteins have been reported to be correlated with clinical outcomes of NSCLC. However, none of them could provide adequate accuracy of prognosis prediction in clinical application. A total of 384 resected NSCLC specimens from two hospitals in Beijing (BJ) and Chongqing (CQ) were collected. Using immunohistochemistry (IHC) staining on stored formalin-fixed paraffin-embedded (FFPE) surgical samples, we examined the expression levels of 75 critical proteins on BJ samples. Random forest algorithm (RFA) and support vector machines (SVM) computation were applied to identify protein signatures on 2/3 randomly assigned BJ samples. The identified signatures were tested on the remaining BJ samples, and were further validated with CQ independent cohort. A 6-protein signature for adenocarcinoma (ADC) and a 5-protein signature for squamous cell carcinoma (SCC) were identified from training sets and tested in testing sets. In independent validation with CQ cohort, patients can also be divided into high- and low-risk groups with significantly different median overall survivals by Kaplan-Meier analysis, both in ADC (31 months vs. 87 months, HR 2.81; P <  0.001) and SCC patients (27 months vs. not reached, HR 9.97; P <  0.001). Cox regression analysis showed that both signatures are independent prognostic indicators and outperformed TNM staging (ADC: adjusted HR 3.07 vs. 2.43, SCC: adjusted HR 7.84 vs. 2.24). Particularly, we found that only the ADC patients in high-risk group significantly benefited from adjuvant chemotherapy (P = 0.018). Both ADC and SCC protein signatures could effectively stratify the prognosis of NSCLC patients, and may support patient selection for adjuvant chemotherapy.

Breath-based biomarkers for tuberculosis

NASA Astrophysics Data System (ADS)

Kolk, Arend H. J.; van Berkel, Joep J. B. N.; Claassens, Mareli M.; Walters, Elisabeth; Kuijper, Sjoukje; Dallinga, Jan W.; van Schooten, Fredrik-Jan

2012-06-01

We investigated the potential of breath analysis by gas chromatography - mass spectrometry (GC-MS) to discriminate between samples collected prospectively from patients with suspected tuberculosis (TB). Samples were obtained in a TB endemic setting in South Africa where 28% of the culture proven TB patients had a Ziehl-Neelsen (ZN) negative sputum smear. A training set of breath samples from 50 sputum culture proven TB patients and 50 culture negative non-TB patients was analyzed by GC-MS. A classification model with 7 compounds resulted in a training set with a sensitivity of 72%, specificity of 86% and accuracy of 79% compared with culture. The classification model was validated with an independent set of breath samples from 21 TB and 50 non-TB patients. A sensitivity of 62%, specificity of 84% and accuracy of 77% was found. We conclude that the 7 volatile organic compounds (VOCs) that discriminate breath samples from TB and non-TB patients in our study population are probably host-response related VOCs and are not derived from the VOCs secreted by M. tuberculosis. It is concluded that at present GC-MS breath analysis is able to differentiate between TB and non-TB breath samples even among patients with a negative ZN sputum smear but a positive culture for M. tuberculosis. Further research is required to improve the sensitivity and specificity before this method can be used in routine laboratories.

Detection of Elevated Plasma Levels of EGF Receptor Prior to Breast Cancer Diagnosis among Hormone Therapy Users

PubMed Central

Pitteri, Sharon J.; Amon, Lynn M.; Buson, Tina Busald; Zhang, Yuzheng; Johnson, Melissa M.; Chin, Alice; Kennedy, Jacob; Wong, Chee-Hong; Zhang, Qing; Wang, Hong; Lampe, Paul D.; Prentice, Ross L.; McIntosh, Martin W.; Hanash, Samir M.; Li, Christopher I.

2010-01-01

Applying advanced proteomic technologies to prospectively collected specimens from large studies is one means of identifying preclinical changes in plasma proteins that are potentially relevant to the early detection of diseases like breast cancer. We conducted fourteen independent quantitative proteomics experiments comparing pooled plasma samples collected from 420 estrogen receptor positive (ER+) breast cancer patients ≤17 months prior to their diagnosis and matched controls. Based on the over 3.4 million tandem mass spectra collected in the discovery set, 503 proteins were quantified of which 57 differentiated cases from controls with a p-value<0.1. Seven of these proteins, for which quantitative ELISA assays were available, were assessed in an independent validation set. Of these candidates, epidermal growth factor receptor (EGFR) was validated as a predictor of breast cancer risk in an independent set of preclinical plasma samples for women overall [odds ratio (OR)=1.44, p-value=0.0008], and particularly for current users of estrogen plus progestin (E+P) menopausal hormone therapy (OR=2.49, p-value=0.0001). Among current E+P users EGFR's sensitivity for breast cancer risk was 31% with 90% specificity. While EGFR's sensitivity and specificity are insufficient for a clinically useful early detection biomarker, this study suggests that proteins that are elevated preclinically in women who go on to develop breast cancer can be discovered and validated using current proteomic technologies. Further studies are warranted to both examine the role of EGFR and to discover and validate other proteins that could potentially be used for breast cancer early detection. PMID:20959476

Nondestructive Detection and Quantification of Blueberry Bruising using Near-infrared (NIR) Hyperspectral Reflectance Imaging

NASA Astrophysics Data System (ADS)

Jiang, Yu; Li, Changying; Takeda, Fumiomi

2016-10-01

Currently, blueberry bruising is evaluated by either human visual/tactile inspection or firmness measurement instruments. These methods are destructive, time-consuming, and subjective. The goal of this paper was to develop a non-destructive approach for blueberry bruising detection and quantification. Experiments were conducted on 300 samples of southern highbush blueberry (Camellia, Rebel, and Star) and on 1500 samples of northern highbush blueberry (Bluecrop, Jersey, and Liberty) for hyperspectral imaging analysis, firmness measurement, and human evaluation. An algorithm was developed to automatically calculate a bruise ratio index (ratio of bruised to whole fruit area) for bruise quantification. The spectra of bruised and healthy tissues were statistically separated and the separation was independent of cultivars. Support vector machine (SVM) classification of the spectra from the regions of interest (ROIs) achieved over 94%, 92%, and 96% accuracy on the training set, independent testing set, and combined set, respectively. The statistical results showed that the bruise ratio index was equivalent to the measured firmness but better than the predicted firmness in regard to effectiveness of bruise quantification, and the bruise ratio index had a strong correlation with human assessment (R2 = 0.78 - 0.83). Therefore, the proposed approach and the bruise ratio index are effective to non-destructively detect and quantify blueberry bruising.

Nondestructive Detection and Quantification of Blueberry Bruising using Near-infrared (NIR) Hyperspectral Reflectance Imaging.

PubMed

Jiang, Yu; Li, Changying; Takeda, Fumiomi

2016-10-21

Currently, blueberry bruising is evaluated by either human visual/tactile inspection or firmness measurement instruments. These methods are destructive, time-consuming, and subjective. The goal of this paper was to develop a non-destructive approach for blueberry bruising detection and quantification. Experiments were conducted on 300 samples of southern highbush blueberry (Camellia, Rebel, and Star) and on 1500 samples of northern highbush blueberry (Bluecrop, Jersey, and Liberty) for hyperspectral imaging analysis, firmness measurement, and human evaluation. An algorithm was developed to automatically calculate a bruise ratio index (ratio of bruised to whole fruit area) for bruise quantification. The spectra of bruised and healthy tissues were statistically separated and the separation was independent of cultivars. Support vector machine (SVM) classification of the spectra from the regions of interest (ROIs) achieved over 94%, 92%, and 96% accuracy on the training set, independent testing set, and combined set, respectively. The statistical results showed that the bruise ratio index was equivalent to the measured firmness but better than the predicted firmness in regard to effectiveness of bruise quantification, and the bruise ratio index had a strong correlation with human assessment (R2 = 0.78 - 0.83). Therefore, the proposed approach and the bruise ratio index are effective to non-destructively detect and quantify blueberry bruising.

Perception Differential between Employers and Undergraduates on the Importance of Employability Skills

ERIC Educational Resources Information Center

Wye, Chung-Khain; Lim, Yet-Mee

2009-01-01

This paper attempts to investigate if the undergraduates' core competencies are able to meet with the requirements set by the employers and to analyse the effectiveness of personal qualities and employability skills development in private university in Malaysia. Questionnaires survey, mean score comparison, and independent sample t-test are used…

Who Stays? Who Leaves? An Examination of Sex Differences in Staying and Leaving.

ERIC Educational Resources Information Center

Poole, Millicent E.; Low, B. C.

The purpose of this study was to examine the major determinants of the "staying" and "leaving" process for samples of Melbourne (Australia) male and female adolescents. Sixty attitudinal statements were obtained from 796 adolescents and factor analysed. The subset of independent variables, together with a set of personality and…

HERO HELPS for Home Economics Related Occupation Coordinators. Volume I.

ERIC Educational Resources Information Center

Northern Arizona Univ., Flagstaff. Center for Vocational Education.

These 25 modules for independent study comprise the first volume of a two-volume set of HERO (Home Economics Related Occupations) HELPS for student use in competency-based professional development. A management system that includes a filing system, testing, record keeping, and scheduling is discussed. A sample contract and other class management…

Improved variance estimation of classification performance via reduction of bias caused by small sample size.

PubMed

Wickenberg-Bolin, Ulrika; Göransson, Hanna; Fryknäs, Mårten; Gustafsson, Mats G; Isaksson, Anders

2006-03-13

Supervised learning for classification of cancer employs a set of design examples to learn how to discriminate between tumors. In practice it is crucial to confirm that the classifier is robust with good generalization performance to new examples, or at least that it performs better than random guessing. A suggested alternative is to obtain a confidence interval of the error rate using repeated design and test sets selected from available examples. However, it is known that even in the ideal situation of repeated designs and tests with completely novel samples in each cycle, a small test set size leads to a large bias in the estimate of the true variance between design sets. Therefore different methods for small sample performance estimation such as a recently proposed procedure called Repeated Random Sampling (RSS) is also expected to result in heavily biased estimates, which in turn translates into biased confidence intervals. Here we explore such biases and develop a refined algorithm called Repeated Independent Design and Test (RIDT). Our simulations reveal that repeated designs and tests based on resampling in a fixed bag of samples yield a biased variance estimate. We also demonstrate that it is possible to obtain an improved variance estimate by means of a procedure that explicitly models how this bias depends on the number of samples used for testing. For the special case of repeated designs and tests using new samples for each design and test, we present an exact analytical expression for how the expected value of the bias decreases with the size of the test set. We show that via modeling and subsequent reduction of the small sample bias, it is possible to obtain an improved estimate of the variance of classifier performance between design sets. However, the uncertainty of the variance estimate is large in the simulations performed indicating that the method in its present form cannot be directly applied to small data sets.

Potential metabolomic biomarkers for reliable diagnosis of Behcet's disease using gas chromatography/ time-of-flight-mass spectrometry.

PubMed

Ahn, Joong Kyong; Kim, Jungyeon; Hwang, Jiwon; Song, Juhwan; Kim, Kyoung Heon; Cha, Hoon-Suk

2018-05-01

Although many diagnostic criteria of Behcet's disease (BD) have been developed and revised by experts, diagnosing BD is still complicated and challenging. No metabolomic studies on serum have been attempted to improve the diagnosis and to identify potential biomarkers of BD. The purposes of this study were to investigate distinctive metabolic changes in serum samples of BD patients and to identify metabolic candidate biomarkers for reliable diagnosis of BD using the metabolomics platform. Metabolomic profiling of 90 serum samples from 45 BD patients and 45 healthy controls (HCs) were performed via gas chromatography with time-of-flight mass spectrometry (GC/TOF-MS) with multivariate statistical analyses. A total of 104 metabolites were identified from samples. The serum metabolite profiles obtained from GC/TOF-MS analysis can distinguish BD patients from HC group in discovery set. The variation values of the partial least squared-discrimination analysis (PLS-DA) model are R 2 X of 0.246, R 2 Y of 0.913 and Q 2 of 0.852, respectively, indicating strong explanation and prediction capabilities of the model. A panel of five metabolic biomarkers, namely, decanoic acid, fructose, tagatose, linoleic acid and oleic acid were selected and adequately validated as putative biomarkers of BD (sensitivity 100%, specificity 97.1%, area under the curve 0.998) in the discovery set and independent set. The PLS_DA model showed clear discrimination of BD and HC groups by the five metabolic biomarkers in independent set. This is the first report on characteristic metabolic profiles and potential metabolite biomarkers in serum for reliable diagnosis of BD using GC/TOF-MS. Copyright © 2017. Published by Elsevier SAS.

On the existence, uniqueness, and asymptotic normality of a consistent solution of the likelihood equations for nonidentically distributed observations: Applications to missing data problems

NASA Technical Reports Server (NTRS)

Peters, C. (Principal Investigator)

1980-01-01

A general theorem is given which establishes the existence and uniqueness of a consistent solution of the likelihood equations given a sequence of independent random vectors whose distributions are not identical but have the same parameter set. In addition, it is shown that the consistent solution is a MLE and that it is asymptotically normal and efficient. Two applications are discussed: one in which independent observations of a normal random vector have missing components, and the other in which the parameters in a mixture from an exponential family are estimated using independent homogeneous sample blocks of different sizes.

Improving automatic peptide mass fingerprint protein identification by combining many peak sets.

PubMed

Rögnvaldsson, Thorsteinn; Häkkinen, Jari; Lindberg, Claes; Marko-Varga, György; Potthast, Frank; Samuelsson, Jim

2004-08-05

An automated peak picking strategy is presented where several peak sets with different signal-to-noise levels are combined to form a more reliable statement on the protein identity. The strategy is compared against both manual peak picking and industry standard automated peak picking on a set of mass spectra obtained after tryptic in gel digestion of 2D-gel samples from human fetal fibroblasts. The set of spectra contain samples ranging from strong to weak spectra, and the proposed multiple-scale method is shown to be much better on weak spectra than the industry standard method and a human operator, and equal in performance to these on strong and medium strong spectra. It is also demonstrated that peak sets selected by a human operator display a considerable variability and that it is impossible to speak of a single "true" peak set for a given spectrum. The described multiple-scale strategy both avoids time-consuming parameter tuning and exceeds the human operator in protein identification efficiency. The strategy therefore promises reliable automated user-independent protein identification using peptide mass fingerprints.

Questioning the utility of pooling samples in microarray experiments with cell lines.

PubMed

Lusa, L; Cappelletti, V; Gariboldi, M; Ferrario, C; De Cecco, L; Reid, J F; Toffanin, S; Gallus, G; McShane, L M; Daidone, M G; Pierotti, M A

2006-01-01

We describe a microarray experiment using the MCF-7 breast cancer cell line in two different experimental conditions for which the same number of independent pools as the number of individual samples was hybridized on Affymetrix GeneChips. Unexpectedly, when using individual samples, the number of probe sets found to be differentially expressed between treated and untreated cells was about three times greater than that found using pools. These findings indicate that pooling samples in microarray experiments where the biological variability is expected to be small might not be helpful and could even decrease one's ability to identify differentially expressed genes.

Insomnia Symptoms, Nightmares, and Suicidal Ideation in a College Student Sample

PubMed Central

Nadorff, Michael R.; Nazem, Sarra; Fiske, Amy

2011-01-01

Study Objectives: The purpose of this study was to investigate whether insomnia symptoms and nightmares are related to suicidal ideation independent of one another and independent of the symptoms of anxiety, depression, and posttraumatic stress disorder (PTSD). Design: The study consisted of questionnaires examining insomnia symptoms and nightmares, and symptoms of depression, anxiety, and PTSD. The questionnaires were administered online. Setting: University. Patients or Participants: 583 undergraduate students at a large, public university in southeastern United States. Interventions: N/A. Measurements and Results: Results indicated that both nightmares and insomnia symptoms were related to suicidal ideation, independent of one another. Nightmares, but not insomnia symptoms, were related to suicidal ideation after controlling for the symptoms of anxiety, depression, and PTSD. Conclusions: Nightmares may be more than a marker of PTSD and hence may be important in the identification of suicidal ideation. Citation: Nadorff MR; Nazem S; Fiske A. Insomnia symptoms, nightmares, and suicidal ideation in a college student sample. SLEEP 2011;34(1):93-98. PMID:21203379

Reaction time as an indicator of insufficient effort: Development and validation of an embedded performance validity parameter.

PubMed

Stevens, Andreas; Bahlo, Simone; Licha, Christina; Liske, Benjamin; Vossler-Thies, Elisabeth

2016-11-30

Subnormal performance in attention tasks may result from various sources including lack of effort. In this report, the derivation and validation of a performance validity parameter for reaction time is described, using a set of malingering-indices ("Slick-criteria"), and 3 independent samples of participants (total n =893). The Slick-criteria yield an estimate of the probability of malingering based on the presence of an external incentive, evidence from neuropsychological testing, from self-report and clinical data. In study (1) a validity parameter is derived using reaction time data of a sample, composed of inpatients with recent severe brain lesions not involved in litigation and of litigants with and without brain lesion. In study (2) the validity parameter is tested in an independent sample of litigants. In study (3) the parameter is applied to an independent sample comprising cooperative and non-cooperative testees. Logistic regression analysis led to a derived validity parameter based on median reaction time and standard deviation. It performed satisfactorily in studies (2) and (3) (study 2 sensitivity=0.94, specificity=1.00; study 3 sensitivity=0.79, specificity=0.87). The findings suggest that median reaction time and standard deviation may be used as indicators of negative response bias. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

An independent validation of a gene expression signature to differentiate malignant melanoma from benign melanocytic nevi.

PubMed

Clarke, Loren E; Flake, Darl D; Busam, Klaus; Cockerell, Clay; Helm, Klaus; McNiff, Jennifer; Reed, Jon; Tschen, Jaime; Kim, Jinah; Barnhill, Raymond; Elenitsas, Rosalie; Prieto, Victor G; Nelson, Jonathan; Kimbrell, Hillary; Kolquist, Kathryn A; Brown, Krystal L; Warf, M Bryan; Roa, Benjamin B; Wenstrup, Richard J

2017-02-15

Recently, a 23-gene signature was developed to produce a melanoma diagnostic score capable of differentiating malignant and benign melanocytic lesions. The primary objective of this study was to independently assess the ability of the gene signature to differentiate melanoma from benign nevi in clinically relevant lesions. A set of 1400 melanocytic lesions was selected from samples prospectively submitted for gene expression testing at a clinical laboratory. Each sample was tested and subjected to an independent histopathologic evaluation by 3 experienced dermatopathologists. A primary diagnosis (benign or malignant) was assigned to each sample, and diagnostic concordance among the 3 dermatopathologists was required for inclusion in analyses. The sensitivity and specificity of the score in differentiating benign and malignant melanocytic lesions were calculated to assess the association between the score and the pathologic diagnosis. The gene expression signature differentiated benign nevi from malignant melanoma with a sensitivity of 91.5% and a specificity of 92.5%. These results reflect the performance of the gene signature in a diverse array of samples encountered in routine clinical practice. Cancer 2017;123:617-628. © 2016 American Cancer Society. © 2016 Myriad Genetics, Inc. Cancer published by Wiley Periodicals, Inc. on behalf of American Cancer Society.

ASTM clustering for improving coal analysis by near-infrared spectroscopy.

PubMed

Andrés, J M; Bona, M T

2006-11-15

Multivariate analysis techniques have been applied to near-infrared (NIR) spectra coals to investigate the relationship between nine coal properties (moisture (%), ash (%), volatile matter (%), fixed carbon (%), heating value (kcal/kg), carbon (%), hydrogen (%), nitrogen (%) and sulphur (%)) and the corresponding predictor variables. In this work, a whole set of coal samples was grouped into six more homogeneous clusters following the ASTM reference method for classification prior to the application of calibration methods to each coal set. The results obtained showed a considerable improvement of the error determination compared with the calibration for the whole sample set. For some groups, the established calibrations approached the quality required by the ASTM/ISO norms for laboratory analysis. To predict property values for a new coal sample it is necessary the assignation of that sample to its respective group. Thus, the discrimination and classification ability of coal samples by Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS) in the NIR range was also studied by applying Soft Independent Modelling of Class Analogy (SIMCA) and Linear Discriminant Analysis (LDA) techniques. Modelling of the groups by SIMCA led to overlapping models that cannot discriminate for unique classification. On the other hand, the application of Linear Discriminant Analysis improved the classification of the samples but not enough to be satisfactory for every group considered.

Sample classification for improved performance of PLS models applied to the quality control of deep-frying oils of different botanic origins analyzed using ATR-FTIR spectroscopy.

PubMed

Kuligowski, Julia; Carrión, David; Quintás, Guillermo; Garrigues, Salvador; de la Guardia, Miguel

2011-01-01

The selection of an appropriate calibration set is a critical step in multivariate method development. In this work, the effect of using different calibration sets, based on a previous classification of unknown samples, on the partial least squares (PLS) regression model performance has been discussed. As an example, attenuated total reflection (ATR) mid-infrared spectra of deep-fried vegetable oil samples from three botanical origins (olive, sunflower, and corn oil), with increasing polymerized triacylglyceride (PTG) content induced by a deep-frying process were employed. The use of a one-class-classifier partial least squares-discriminant analysis (PLS-DA) and a rooted binary directed acyclic graph tree provided accurate oil classification. Oil samples fried without foodstuff could be classified correctly, independent of their PTG content. However, class separation of oil samples fried with foodstuff, was less evident. The combined use of double-cross model validation with permutation testing was used to validate the obtained PLS-DA classification models, confirming the results. To discuss the usefulness of the selection of an appropriate PLS calibration set, the PTG content was determined by calculating a PLS model based on the previously selected classes. In comparison to a PLS model calculated using a pooled calibration set containing samples from all classes, the root mean square error of prediction could be improved significantly using PLS models based on the selected calibration sets using PLS-DA, ranging between 1.06 and 2.91% (w/w).

40 CFR 80.613 - What defenses apply to persons deemed liable for a violation of a prohibited act under this subpart?

Code of Federal Regulations, 2011 CFR

2011-07-01

..., including sample collection, transportation, storage, and analysis. (4) Survey plan design requirements. The... contractual agreement between the branded refiner or importer and the person designed to prevent such action... conditions and limitations set forth in this paragraph (e): (1) Independent survey association. To comply...

40 CFR 80.613 - What defenses apply to persons deemed liable for a violation of a prohibited act under this subpart?

Code of Federal Regulations, 2010 CFR

2010-07-01

..., including sample collection, transportation, storage, and analysis. (4) Survey plan design requirements. The... contractual agreement between the branded refiner or importer and the person designed to prevent such action... subject to the conditions and limitations set forth in this paragraph (e): (1) Independent survey...

40 CFR 80.613 - What defenses apply to persons deemed liable for a violation of a prohibited act under this subpart?

Code of Federal Regulations, 2012 CFR

2012-07-01

..., including sample collection, transportation, storage, and analysis. (4) Survey plan design requirements. The... contractual agreement between the branded refiner or importer and the person designed to prevent such action... conditions and limitations set forth in this paragraph (e): (1) Independent survey association. To comply...

Assets and Life Satisfaction Patterns among Korean Older Adults: Latent Class Analysis

ERIC Educational Resources Information Center

Han, Chang-Keun; Hong, Song-Iee

2011-01-01

This study aims to examine the association of assets with life satisfaction patterns among Korean older adults aged 50 and above. This study used the first two panel data sets (2005 and 2007) from the Korean Retirement and Income Study, which collected information from a nationally representative sample. Key independent variables include financial…

Independent Predictors of Prognosis Based on Oral Cavity Squamous Cell Carcinoma Surgical Margins.

PubMed

Buchakjian, Marisa R; Ginader, Timothy; Tasche, Kendall K; Pagedar, Nitin A; Smith, Brian J; Sperry, Steven M

2018-05-01

Objective To conduct a multivariate analysis of a large cohort of oral cavity squamous cell carcinoma (OCSCC) cases for independent predictors of local recurrence (LR) and overall survival (OS), with emphasis on the relationship between (1) prognosis and (2) main specimen permanent margins and intraoperative tumor bed frozen margins. Study Design Retrospective cohort study. Setting Tertiary academic head and neck cancer program. Subjects and Methods This study included 426 patients treated with OCSCC resection between 2005 and 2014 at University of Iowa Hospitals and Clinics. Patients underwent excision of OCSCC with intraoperative tumor bed frozen margin sampling and main specimen permanent margin assessment. Multivariate analysis of the data set to predict LR and OS was performed. Results Independent predictors of LR included nodal involvement, histologic grade, and main specimen permanent margin status. Specifically, the presence of a positive margin (odds ratio, 6.21; 95% CI, 3.3-11.9) or <1-mm/carcinoma in situ margin (odds ratio, 2.41; 95% CI, 1.19-4.87) on the main specimen was an independent predictor of LR, whereas intraoperative tumor bed margins were not predictive of LR on multivariate analysis. Similarly, independent predictors of OS on multivariate analysis included nodal involvement, extracapsular extension, and a positive main specimen margin. Tumor bed margins did not independently predict OS. Conclusion The main specimen margin is a strong independent predictor of LR and OS on multivariate analysis. Intraoperative tumor bed frozen margins do not independently predict prognosis. We conclude that emphasis should be placed on evaluating the main specimen margins when estimating prognosis after OCSCC resection.

Remote sensing and urban public health

NASA Technical Reports Server (NTRS)

Rush, M.; Vernon, S.

1975-01-01

The applicability of remote sensing in the form of aerial photography to urban public health problems is examined. Environmental characteristics are analyzed to determine if health differences among areas could be predicted from the visual expression of remote sensing data. The analysis is carried out on a socioeconomic cross-sectional sample of census block groups. Six morbidity and mortality rates are the independent variables while environmental measures from aerial photographs and from the census constitute the two independent variable sets. It is found that environmental data collected by remote sensing are as good as census data in evaluating rates of health outcomes.

Multivariate analysis of standoff laser-induced breakdown spectroscopy spectra for classification of explosive-containing residues

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

De Lucia, Frank C. Jr.; Gottfried, Jennifer L.; Munson, Chase A.

2008-11-01

A technique being evaluated for standoff explosives detection is laser-induced breakdown spectroscopy (LIBS). LIBS is a real-time sensor technology that uses components that can be configured into a ruggedized standoff instrument. The U.S. Army Research Laboratory has been coupling standoff LIBS spectra with chemometrics for several years now in order to discriminate between explosives and nonexplosives. We have investigated the use of partial least squares discriminant analysis (PLS-DA) for explosives detection. We have extended our study of PLS-DA to more complex sample types, including binary mixtures, different types of explosives, and samples not included in the model. We demonstrate themore » importance of building the PLS-DA model by iteratively testing it against sample test sets. Independent test sets are used to test the robustness of the final model.« less

Norms governing urban African American adolescents’ sexual and substance-using behavior

PubMed Central

Dolcini, M. Margaret; Catania, Joseph A.; Harper, Gary W.; Watson, Susan E.; Ellen, Jonathan M.; Towner, Senna L.

2013-01-01

Using a probability-based neighborhood sample of urban African American youth and a sample of their close friends (N = 202), we conducted a one-year longitudinal study to examine key questions regarding sexual and drug using norms. The results provide validation of social norms governing sexual behavior, condom use, and substance use among friendship groups. These norms had strong to moderate homogeneity; and both normative strength and homogeneity were relatively stable over a one-year period independent of changes in group membership. The data further suggest that sex and substance using norms may operate as a normative set. Similar to studies of adults, we identified three distinct “norm-based” social strata in our sample. Together, our findings suggest that the norms investigated are valid targets for health promotion efforts, and such efforts may benefit from tailoring programs to the normative sets that make up the different social strata in a given adolescent community. PMID:23072891

Random and independent sampling of endogenous tryptic peptides from normal human EDTA plasma by liquid chromatography micro electrospray ionization and tandem mass spectrometry.

PubMed

Dufresne, Jaimie; Florentinus-Mefailoski, Angelique; Ajambo, Juliet; Ferwa, Ammara; Bowden, Peter; Marshall, John

2017-01-01

Normal human EDTA plasma samples were collected on ice, processed ice cold, and stored in a freezer at - 80 °C prior to experiments. Plasma test samples from the - 80 °C freezer were thawed on ice or intentionally warmed to room temperature. Protein content was measured by CBBR binding and the release of alcohol soluble amines by the Cd ninhydrin assay. Plasma peptides released over time were collected over C18 for random and independent sampling by liquid chromatography micro electrospray ionization and tandem mass spectrometry (LC-ESI-MS/MS) and correlated with X!TANDEM. Fully tryptic peptides by X!TANDEM returned a similar set of proteins, but was more computationally efficient, than "no enzyme" correlations. Plasma samples maintained on ice, or ice with a cocktail of protease inhibitors, showed lower background amounts of plasma peptides compared to samples incubated at room temperature. Regression analysis indicated that warming plasma to room temperature, versus ice cold, resulted in a ~ twofold increase in the frequency of peptide identification over hours-days of incubation at room temperature. The type I error rate of the protein identification from the X!TANDEM algorithm combined was estimated to be low compared to a null model of computer generated random MS/MS spectra. The peptides of human plasma were identified and quantified with low error rates by random and independent sampling that revealed 1000s of peptides from hundreds of human plasma proteins from endogenous tryptic peptides.

Evaluation of airborne asbestos exposure from routine handling of asbestos-containing wire gauze pads in the research laboratory.

PubMed

Garcia, Ediberto; Newfang, Daniel; Coyle, Jayme P; Blake, Charles L; Spencer, John W; Burrelli, Leonard G; Johnson, Giffe T; Harbison, Raymond D

2018-07-01

Three independently conducted asbestos exposure evaluations were conducted using wire gauze pads similar to standard practice in the laboratory setting. All testing occurred in a controlled atmosphere inside an enclosed chamber simulating a laboratory setting. Separate teams consisting of a laboratory technician, or technician and assistant simulated common tasks involving wire gauze pads, including heating and direct wire gauze manipulation. Area and personal air samples were collected and evaluated for asbestos consistent with the National Institute of Occupational Safety Health method 7400 and 7402, and the Asbestos Hazard Emergency Response Act (AHERA) method. Bulk gauze pad samples were analyzed by Polarized Light Microscopy and Transmission Electron Microscopy to determine asbestos content. Among air samples, chrysotile asbestos was the only fiber found in the first and third experiments, and tremolite asbestos for the second experiment. None of the air samples contained asbestos in concentrations above the current permissible regulatory levels promulgated by OSHA. These findings indicate that the level of asbestos exposure when working with wire gauze pads in the laboratory setting is much lower than levels associated with asbestosis or asbestos-related lung cancer and mesothelioma. Copyright © 2018. Published by Elsevier Inc.

Pharmacy patronage: identifying key factors in the decision making process using the determinant attribute approach.

PubMed

Franic, Duska M; Haddock, Sarah M; Tucker, Leslie Tootle; Wooten, Nathan

2008-01-01

To use the determinant attribute approach, a research method commonly used in marketing to identify the wants of various consumer groups, to evaluate consumer pharmacy choice when having a prescription order filled in different pharmacy settings. Cross sectional. Community independent, grocery store, community chain, and discount store pharmacies in Georgia between April 2005 and April 2006. Convenience sample of adult pharmacy consumers (n = 175). Survey measuring consumer preferences on 26 attributes encompassing general pharmacy site features (16 items), pharmacist characteristics (5 items), and pharmacy staff characteristics (5 items). 26 potential determinant attributes for pharmacy selection. 175 consumers were surveyed at community independent (n = 81), grocery store (n = 44), community chain (n = 27), or discount store (n = 23) pharmacy settings. The attributes of pharmacists and staff at all four pharmacy settings were shown to affect pharmacy patronage motives, although consumers frequenting non-community independent pharmacies were also motivated by secondary convenience factors, e.g., hours of operation, and prescription coverage. Most consumers do not perceive pharmacies as merely prescription-distribution centers that vary only by convenience. Prescriptions are not just another economic good. Pharmacy personnel influence pharmacy selection; therefore, optimal staff selection and training is likely the greatest asset and most important investment for ensuring pharmacy success.

Dynamic variable selection in SNP genotype autocalling from APEX microarray data.

PubMed

Podder, Mohua; Welch, William J; Zamar, Ruben H; Tebbutt, Scott J

2006-11-30

Single nucleotide polymorphisms (SNPs) are DNA sequence variations, occurring when a single nucleotide--adenine (A), thymine (T), cytosine (C) or guanine (G)--is altered. Arguably, SNPs account for more than 90% of human genetic variation. Our laboratory has developed a highly redundant SNP genotyping assay consisting of multiple probes with signals from multiple channels for a single SNP, based on arrayed primer extension (APEX). This mini-sequencing method is a powerful combination of a highly parallel microarray with distinctive Sanger-based dideoxy terminator sequencing chemistry. Using this microarray platform, our current genotype calling system (known as SNP Chart) is capable of calling single SNP genotypes by manual inspection of the APEX data, which is time-consuming and exposed to user subjectivity bias. Using a set of 32 Coriell DNA samples plus three negative PCR controls as a training data set, we have developed a fully-automated genotyping algorithm based on simple linear discriminant analysis (LDA) using dynamic variable selection. The algorithm combines separate analyses based on the multiple probe sets to give a final posterior probability for each candidate genotype. We have tested our algorithm on a completely independent data set of 270 DNA samples, with validated genotypes, from patients admitted to the intensive care unit (ICU) of St. Paul's Hospital (plus one negative PCR control sample). Our method achieves a concordance rate of 98.9% with a 99.6% call rate for a set of 96 SNPs. By adjusting the threshold value for the final posterior probability of the called genotype, the call rate reduces to 94.9% with a higher concordance rate of 99.6%. We also reversed the two independent data sets in their training and testing roles, achieving a concordance rate up to 99.8%. The strength of this APEX chemistry-based platform is its unique redundancy having multiple probes for a single SNP. Our model-based genotype calling algorithm captures the redundancy in the system considering all the underlying probe features of a particular SNP, automatically down-weighting any 'bad data' corresponding to image artifacts on the microarray slide or failure of a specific chemistry. In this regard, our method is able to automatically select the probes which work well and reduce the effect of other so-called bad performing probes in a sample-specific manner, for any number of SNPs.

Nondestructive Detection and Quantification of Blueberry Bruising using Near-infrared (NIR) Hyperspectral Reflectance Imaging

PubMed Central

Jiang, Yu; Li, Changying; Takeda, Fumiomi

2016-01-01

Currently, blueberry bruising is evaluated by either human visual/tactile inspection or firmness measurement instruments. These methods are destructive, time-consuming, and subjective. The goal of this paper was to develop a non-destructive approach for blueberry bruising detection and quantification. Experiments were conducted on 300 samples of southern highbush blueberry (Camellia, Rebel, and Star) and on 1500 samples of northern highbush blueberry (Bluecrop, Jersey, and Liberty) for hyperspectral imaging analysis, firmness measurement, and human evaluation. An algorithm was developed to automatically calculate a bruise ratio index (ratio of bruised to whole fruit area) for bruise quantification. The spectra of bruised and healthy tissues were statistically separated and the separation was independent of cultivars. Support vector machine (SVM) classification of the spectra from the regions of interest (ROIs) achieved over 94%, 92%, and 96% accuracy on the training set, independent testing set, and combined set, respectively. The statistical results showed that the bruise ratio index was equivalent to the measured firmness but better than the predicted firmness in regard to effectiveness of bruise quantification, and the bruise ratio index had a strong correlation with human assessment (R2 = 0.78 − 0.83). Therefore, the proposed approach and the bruise ratio index are effective to non-destructively detect and quantify blueberry bruising. PMID:27767050

Speeding up Coarse Point Cloud Registration by Threshold-Independent Baysac Match Selection

NASA Astrophysics Data System (ADS)

Kang, Z.; Lindenbergh, R.; Pu, S.

2016-06-01

This paper presents an algorithm for the automatic registration of terrestrial point clouds by match selection using an efficiently conditional sampling method -- threshold-independent BaySAC (BAYes SAmpling Consensus) and employs the error metric of average point-to-surface residual to reduce the random measurement error and then approach the real registration error. BaySAC and other basic sampling algorithms usually need to artificially determine a threshold by which inlier points are identified, which leads to a threshold-dependent verification process. Therefore, we applied the LMedS method to construct the cost function that is used to determine the optimum model to reduce the influence of human factors and improve the robustness of the model estimate. Point-to-point and point-to-surface error metrics are most commonly used. However, point-to-point error in general consists of at least two components, random measurement error and systematic error as a result of a remaining error in the found rigid body transformation. Thus we employ the measure of the average point-to-surface residual to evaluate the registration accuracy. The proposed approaches, together with a traditional RANSAC approach, are tested on four data sets acquired by three different scanners in terms of their computational efficiency and quality of the final registration. The registration results show the st.dev of the average point-to-surface residuals is reduced from 1.4 cm (plain RANSAC) to 0.5 cm (threshold-independent BaySAC). The results also show that, compared to the performance of RANSAC, our BaySAC strategies lead to less iterations and cheaper computational cost when the hypothesis set is contaminated with more outliers.

The meaning of "independence" for older people in different residential settings.

PubMed

Hillcoat-Nallétamby, Sarah

2014-05-01

Drawing on older people's understandings of "independence" and Collopy's work on autonomy, the article elaborates an interpretive framework of the concept in relation to 3 residential settings-the private dwelling-home, the extra-care, and the residential-care settings. Data include 91 qualitative interviews with frail, older people living in each setting, collected as part of a larger Welsh study. Thematic analysis techniques were employed to identify patterns in meanings of independence across settings and then interpreted using Collopy's conceptualizations of autonomy, as well as notions of space and interdependencies. Independence has multiple meanings for older people, but certain meanings are common to all settings: Accepting help at hand; doing things alone; having family, friends, and money as resources; and preserving physical and mental capacities. Concepts of delegated, executional, authentic, decisional, and consumer autonomy, as well as social interdependencies and spatial and social independence, do provide appropriate higher order interpretive constructs of these meanings across settings. A broader interpretive framework of "independence" should encompass concepts of relative independence, autonomy(ies), as well as spatial and social independence, and can provide more nuanced interpretations of structured dependency and institutionalization theories when applied to different residential settings.

The interpoint distance distribution as a descriptor of point patterns, with an application to spatial disease clustering.

PubMed

Bonetti, Marco; Pagano, Marcello

2005-03-15

The topic of this paper is the distribution of the distance between two points distributed independently in space. We illustrate the use of this interpoint distance distribution to describe the characteristics of a set of points within some fixed region. The properties of its sample version, and thus the inference about this function, are discussed both in the discrete and in the continuous setting. We illustrate its use in the detection of spatial clustering by application to a well-known leukaemia data set, and report on the results of a simulation experiment designed to study the power characteristics of the methods within that study region and in an artificial homogenous setting. Copyright (c) 2004 John Wiley & Sons, Ltd.

Educational Deficiencies Recognized by Independent Practice Dental Hygienists and their Suggestions for Change.

PubMed

Vannah, Courtney E; McComas, Martha; Taverna, Melanie; Hicks, Beatriz; Wright, Rebecca

2014-12-01

The purpose of this study was to determine the perceived level of preparedness Maine Independent Practice Dental Hygienists (IPDHs) received from their standard undergraduate dental hygiene education, and recognize areas necessary for further preparation in order to explore careers beyond the private practice dental model. A convenience sample of 6 IPDHs participated in a survey exploring their educational experience in public health and alternative practice settings. The survey also asked for their recommendations to advance dental hygiene education to meet the needs of those wishing to pursue alternative practice careers. This study found that participants felt underprepared by their dental hygiene education with deficits in exposure to public health, business skills necessary for independent practice, communication training and understanding of situations which require referral for treatment beyond the IPDH scope of practice. As the dental hygiene profession evolves, dental hygiene education must as well. The IPDH participants' recommendations for dental hygiene programs include increased exposure to alternative settings and underserved populations as well as elective courses for those students interested in alternative practice and business ownership. Copyright © 2014 The American Dental Hygienists’ Association.

Pearson's chi-square test and rank correlation inferences for clustered data.

PubMed

Shih, Joanna H; Fay, Michael P

2017-09-01

Pearson's chi-square test has been widely used in testing for association between two categorical responses. Spearman rank correlation and Kendall's tau are often used for measuring and testing association between two continuous or ordered categorical responses. However, the established statistical properties of these tests are only valid when each pair of responses are independent, where each sampling unit has only one pair of responses. When each sampling unit consists of a cluster of paired responses, the assumption of independent pairs is violated. In this article, we apply the within-cluster resampling technique to U-statistics to form new tests and rank-based correlation estimators for possibly tied clustered data. We develop large sample properties of the new proposed tests and estimators and evaluate their performance by simulations. The proposed methods are applied to a data set collected from a PET/CT imaging study for illustration. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Sampling errors in the estimation of empirical orthogonal functions. [for climatology studies

NASA Technical Reports Server (NTRS)

North, G. R.; Bell, T. L.; Cahalan, R. F.; Moeng, F. J.

1982-01-01

Empirical Orthogonal Functions (EOF's), eigenvectors of the spatial cross-covariance matrix of a meteorological field, are reviewed with special attention given to the necessary weighting factors for gridded data and the sampling errors incurred when too small a sample is available. The geographical shape of an EOF shows large intersample variability when its associated eigenvalue is 'close' to a neighboring one. A rule of thumb indicating when an EOF is likely to be subject to large sampling fluctuations is presented. An explicit example, based on the statistics of the 500 mb geopotential height field, displays large intersample variability in the EOF's for sample sizes of a few hundred independent realizations, a size seldom exceeded by meteorological data sets.

A rigorous test of the accuracy of USGS digital elevation models in forested areas of Oregon and Washington.

Treesearch

Ward W. Carson; Stephen E. Reutebuch

1997-01-01

A procedure for performing a rigorous test of elevational accuracy of DEMs using independent ground coordinate data digitized photogrammetrically from aerial photography is presented. The accuracy of a sample set of 23 DEMs covering National Forests in Oregon and Washington was evaluated. Accuracy varied considerably between eastern and western parts of Oregon and...

Associations between the social organization of communities and psychiatric disorders in rural Asia.

PubMed

Axinn, William G; Ghimire, Dirgha J; Williams, Nathalie E; Scott, Kate M

2015-10-01

We provide rare evidence of factors producing psychiatric variation in a general population sample from rural South Asia. The setting is particularly useful for demonstrating that variations in the social organization of communities, often difficult to observe in rich countries, are associated with important variations in mental health. Clinically validated survey measures are used to document variation in psychiatric disorders among 401 adults. This sample is chosen from a systematic sample of the general population of rural Nepal, in a community-level-controlled comparison design. Multilevel logistic regression is used to estimate multivariate models of the association between community-level nonfamily social organization and individual-level psychiatric disorders. Schools, markets, health services and social support groups each substantially reduce the odds of depression, post-traumatic stress disorder (PTSD), intermittent explosive disorder and anxiety disorders. Associations between schools, health services and social support groups and depression are statistically significant and independent of each other. The association between access to markets and PTSD is statistically significant and independent of other social organization and support groups. Community integration of some nonfamily social organizations promotes mental health in ways that may go unobserved in settings with many such organizations. More research on the mechanisms producing these associations is likely to reveal potential avenues for public policy and programs to improve mental health in the general population.

Associations between the Social Organization of Communities and Psychiatric Disorders in Rural Asia

PubMed Central

Axinn, William G.; Ghimire, Dirgha J.; Williams, Nathalie E.; Scott, Kate M.

2015-01-01

Purpose We provide rare evidence of factors producing psychiatric variation in a general population sample from rural South Asia. The setting is particularly useful for demonstrating that variations in the social organization of communities, often difficult to observe in rich countries, are associated with important variations in mental health. Methods Clinically validated survey measures are used to document variation in psychiatric disorders among 401 adults. This sample is chosen from a systematic sample of the general population of rural Nepal, in a community-level controlled comparison design. Multilevel logistic regression is used to estimate multivariate models of the association between community-level nonfamily social organization and individual-level psychiatric disorders. Results Schools, markets, health services and social support groups each substantially reduce the odds of depression, post-traumatic stress disorder (PTSD), intermittent explosive disorder (IED) and anxiety disorders. Associations between schools, health services and social support groups and depression are statistically significant and independent of each other. The association between access to markets and PTSD is statistically significant and independent of other social organization and support groups. Conclusions Community integration of some nonfamily social organizations promotes mental health in ways that may go unobserved in settings with many such organizations. More research on the mechanisms producing these associations is likely to reveal potential avenues for public policy and programs to improve mental health in the general population. PMID:25796491

Nonlinear Dynamics of Cantilever-Sample Interactions in Atomic Force Microscopy

NASA Technical Reports Server (NTRS)

Cantrell, John H.; Cantrell, Sean A.

2010-01-01

The interaction of the cantilever tip of an atomic force microscope (AFM) with the sample surface is obtained by treating the cantilever and sample as independent systems coupled by a nonlinear force acting between the cantilever tip and a volume element of the sample surface. The volume element is subjected to a restoring force from the remainder of the sample that provides dynamical equilibrium for the combined systems. The model accounts for the positions on the cantilever of the cantilever tip, laser probe, and excitation force (if any) via a basis set of set of orthogonal functions that may be generalized to account for arbitrary cantilever shapes. The basis set is extended to include nonlinear cantilever modes. The model leads to a pair of coupled nonlinear differential equations that are solved analytically using a matrix iteration procedure. The effects of oscillatory excitation forces applied either to the cantilever or to the sample surface (or to both) are obtained from the solution set and applied to the to the assessment of phase and amplitude signals generated by various acoustic-atomic force microscope (A-AFM) modalities. The influence of bistable cantilever modes of on AFM signal generation is discussed. The effects on the cantilever-sample surface dynamics of subsurface features embedded in the sample that are perturbed by surface-generated oscillatory excitation forces and carried to the cantilever via wave propagation are accounted by the Bolef-Miller propagating wave model. Expressions pertaining to signal generation and image contrast in A-AFM are obtained and applied to amplitude modulation (intermittent contact) atomic force microscopy and resonant difference-frequency atomic force ultrasonic microscopy (RDF-AFUM). The influence of phase accumulation in A-AFM on image contrast is discussed, as is the effect of hard contact and maximum nonlinearity regimes of A-AFM operation.

Exact sampling of graphs with prescribed degree correlations

NASA Astrophysics Data System (ADS)

Bassler, Kevin E.; Del Genio, Charo I.; Erdős, Péter L.; Miklós, István; Toroczkai, Zoltán

2015-08-01

Many real-world networks exhibit correlations between the node degrees. For instance, in social networks nodes tend to connect to nodes of similar degree and conversely, in biological and technological networks, high-degree nodes tend to be linked with low-degree nodes. Degree correlations also affect the dynamics of processes supported by a network structure, such as the spread of opinions or epidemics. The proper modelling of these systems, i.e., without uncontrolled biases, requires the sampling of networks with a specified set of constraints. We present a solution to the sampling problem when the constraints imposed are the degree correlations. In particular, we develop an exact method to construct and sample graphs with a specified joint-degree matrix, which is a matrix providing the number of edges between all the sets of nodes of a given degree, for all degrees, thus completely specifying all pairwise degree correlations, and additionally, the degree sequence itself. Our algorithm always produces independent samples without backtracking. The complexity of the graph construction algorithm is {O}({NM}) where N is the number of nodes and M is the number of edges.

Self-construal, affective valence of the encounter, and quality of social interactions: Within and cross-culture examination.

PubMed

Kafetsios, Konstantinos; Hess, Ursula; Nezlek, John B

2018-01-01

In two samples, one from Greece and another from Germany, we examined relationships between self-construal, emotional experience, and the quality of social interactions. In Greece, a more collectivistic culture, the negative affect people experienced in social interactions was more weakly related to the quality of social interactions for those higher in interdependent self-construal than it was for those lower in interdependent self-construal. In Germany, a more independent culture, a contrasting pattern was observed such that the positive affect people experienced in social interaction was more strongly related to the quality of social interactions for those higher in independent self-construal than it was for those lower in independent self-construal. These findings suggest that positive and negative affect in social encounters can have different effects for persons with independent and interdependent cultural orientations within different cultural settings.

Robust Covariate-Adjusted Log-Rank Statistics and Corresponding Sample Size Formula for Recurrent Events Data

PubMed Central

Song, Rui; Kosorok, Michael R.; Cai, Jianwen

2009-01-01

Summary Recurrent events data are frequently encountered in clinical trials. This article develops robust covariate-adjusted log-rank statistics applied to recurrent events data with arbitrary numbers of events under independent censoring and the corresponding sample size formula. The proposed log-rank tests are robust with respect to different data-generating processes and are adjusted for predictive covariates. It reduces to the Kong and Slud (1997, Biometrika 84, 847–862) setting in the case of a single event. The sample size formula is derived based on the asymptotic normality of the covariate-adjusted log-rank statistics under certain local alternatives and a working model for baseline covariates in the recurrent event data context. When the effect size is small and the baseline covariates do not contain significant information about event times, it reduces to the same form as that of Schoenfeld (1983, Biometrics 39, 499–503) for cases of a single event or independent event times within a subject. We carry out simulations to study the control of type I error and the comparison of powers between several methods in finite samples. The proposed sample size formula is illustrated using data from an rhDNase study. PMID:18162107

Refining Collective Coordinates and Improving Free Energy Representation in Variational Enhanced Sampling.

PubMed

Yang, Yi Isaac; Parrinello, Michele

2018-06-12

Collective variables are used often in many enhanced sampling methods, and their choice is a crucial factor in determining sampling efficiency. However, at times, searching for good collective variables can be challenging. In a recent paper, we combined time-lagged independent component analysis with well-tempered metadynamics in order to obtain improved collective variables from metadynamics runs that use lower quality collective variables [ McCarty, J.; Parrinello, M. J. Chem. Phys. 2017 , 147 , 204109 ]. In this work, we extend these ideas to variationally enhanced sampling. This leads to an efficient scheme that is able to make use of the many advantages of the variational scheme. We apply the method to alanine-3 in water. From an alanine-3 variationally enhanced sampling trajectory in which all the six dihedral angles are biased, we extract much better collective variables able to describe in exquisite detail the protein complex free energy surface in a low dimensional representation. The success of this investigation is helped by a more accurate way of calculating the correlation functions needed in the time-lagged independent component analysis and from the introduction of a new basis set to describe the dihedral angles arrangement.

Systematic versus random sampling in stereological studies.

PubMed

West, Mark J

2012-12-01

The sampling that takes place at all levels of an experimental design must be random if the estimate is to be unbiased in a statistical sense. There are two fundamental ways by which one can make a random sample of the sections and positions to be probed on the sections. Using a card-sampling analogy, one can pick any card at all out of a deck of cards. This is referred to as independent random sampling because the sampling of any one card is made without reference to the position of the other cards. The other approach to obtaining a random sample would be to pick a card within a set number of cards and others at equal intervals within the deck. Systematic sampling along one axis of many biological structures is more efficient than random sampling, because most biological structures are not randomly organized. This article discusses the merits of systematic versus random sampling in stereological studies.

Detection of K-ras gene mutation by liquid biopsy in patients with pancreatic cancer.

PubMed

Kinugasa, Hideaki; Nouso, Kazuhiro; Miyahara, Koji; Morimoto, Yuki; Dohi, Chihiro; Tsutsumi, Koichiro; Kato, Hironari; Matsubara, Takehiro; Okada, Hiroyuki; Yamamoto, Kazuhide

2015-07-01

Cell-free circulating tumor DNA (ctDNA) in serum has been considered to be a useful candidate for noninvasive cancer diagnosis. The current study was designed to estimate the clinical usefulness of genetic analysis for ctDNA by digital polymerase chain reaction in patients with pancreatic cancer. The authors compared K-ras mutations detected in endoscopic ultrasound-guided fine-needle aspiration biopsy tissue DNA and in ctDNA from 75 patients with pancreatic cancer. K-ras mutations in the serum of 66 independent, consecutive patients with pancreatic cancer were also analyzed and the authors compared the results with survival rates. The frequencies of the mutations in tissue samples at G12V, G12D, and G12R in codon 12 were 28 of 75 samples (37.3%), 22 of 75 samples (29.3%), and 6 of 75 samples (8.0%), respectively. Conversely, the rates of the mutations in ctDNA were 26 of 75 samples (34.6%), 29 of 75 samples (38.6%), and 4 of 75 samples (5.3%), respectively. Overall, the K-ras mutation rates in tissue and ctDNA were 74.7% and 62.6%, respectively, and the concordance rate between them was 58 of 75 samples (77.3%). Survival did not appear to differ by the presence of K-ras mutations in tissue DNA, but the survival of patients with K-ras mutations in ctDNA was significantly shorter than that of patients without mutations in both a development set (P = .006) and an independent validation set (P = .002). The difference was especially evident in cases with a G12V mutation. Analysis of ctDNA is a new useful procedure for detecting mutations in patients with pancreatic cancer. This noninvasive method may have great potential as a new strategy for the diagnosis of pancreatic cancer as well as for predicting survival. © 2015 American Cancer Society.

Challenges in projecting clustering results across gene expression-profiling datasets.

PubMed

Lusa, Lara; McShane, Lisa M; Reid, James F; De Cecco, Loris; Ambrogi, Federico; Biganzoli, Elia; Gariboldi, Manuela; Pierotti, Marco A

2007-11-21

Gene expression microarray studies for several types of cancer have been reported to identify previously unknown subtypes of tumors. For breast cancer, a molecular classification consisting of five subtypes based on gene expression microarray data has been proposed. These subtypes have been reported to exist across several breast cancer microarray studies, and they have demonstrated some association with clinical outcome. A classification rule based on the method of centroids has been proposed for identifying the subtypes in new collections of breast cancer samples; the method is based on the similarity of the new profiles to the mean expression profile of the previously identified subtypes. Previously identified centroids of five breast cancer subtypes were used to assign 99 breast cancer samples, including a subset of 65 estrogen receptor-positive (ER+) samples, to five breast cancer subtypes based on microarray data for the samples. The effect of mean centering the genes (i.e., transforming the expression of each gene so that its mean expression is equal to 0) on subtype assignment by method of centroids was assessed. Further studies of the effect of mean centering and of class prevalence in the test set on the accuracy of method of centroids classifications of ER status were carried out using training and test sets for which ER status had been independently determined by ligand-binding assay and for which the proportion of ER+ and ER- samples were systematically varied. When all 99 samples were considered, mean centering before application of the method of centroids appeared to be helpful for correctly assigning samples to subtypes, as evidenced by the expression of genes that had previously been used as markers to identify the subtypes. However, when only the 65 ER+ samples were considered for classification, many samples appeared to be misclassified, as evidenced by an unexpected distribution of ER+ samples among the resultant subtypes. When genes were mean centered before classification of samples for ER status, the accuracy of the ER subgroup assignments was highly dependent on the proportion of ER+ samples in the test set; this effect of subtype prevalence was not seen when gene expression data were not mean centered. Simple corrections such as mean centering of genes aimed at microarray platform or batch effect correction can have undesirable consequences because patient population effects can easily be confused with these assay-related effects. Careful thought should be given to the comparability of the patient populations before attempting to force data comparability for purposes of assigning subtypes to independent subjects.

Development of an objective gene expression panel as an alternative to self-reported symptom scores in human influenza challenge trials.

PubMed

Muller, Julius; Parizotto, Eneida; Antrobus, Richard; Francis, James; Bunce, Campbell; Stranks, Amanda; Nichols, Marshall; McClain, Micah; Hill, Adrian V S; Ramasamy, Adaikalavan; Gilbert, Sarah C

2017-06-08

Influenza challenge trials are important for vaccine efficacy testing. Currently, disease severity is determined by self-reported scores to a list of symptoms which can be highly subjective. A more objective measure would allow for improved data analysis. Twenty-one volunteers participated in an influenza challenge trial. We calculated the daily sum of scores (DSS) for a list of 16 influenza symptoms. Whole blood collected at baseline and 24, 48, 72 and 96 h post challenge was profiled on Illumina HT12v4 microarrays. Changes in gene expression most strongly correlated with DSS were selected to train a Random Forest model and tested on two independent test sets consisting of 41 individuals profiled on a different microarray platform and 33 volunteers assayed by qRT-PCR. 1456 probes are significantly associated with DSS at 1% false discovery rate. We selected 19 genes with the largest fold change to train a random forest model. We observed good concordance between predicted and actual scores in the first test set (r = 0.57; RMSE = -16.1%) with the greatest agreement achieved on samples collected approximately 72 h post challenge. Therefore, we assayed samples collected at baseline and 72 h post challenge in the second test set by qRT-PCR and observed good concordance (r = 0.81; RMSE = -36.1%). We developed a 19-gene qRT-PCR panel to predict DSS, validated on two independent datasets. A transcriptomics based panel could provide a more objective measure of symptom scoring in future influenza challenge studies. Trial registration Samples were obtained from a clinical trial with the ClinicalTrials.gov Identifier: NCT02014870, first registered on December 5, 2013.

Proteomic study of benign and malignant pleural effusion.

PubMed

Li, Hongqing; Tang, Zhonghao; Zhu, Huili; Ge, Haiyan; Cui, Shilei; Jiang, Weiping

2016-06-01

Lung adenocarcinoma can easily cause malignant pleural effusion which was difficult to discriminate from benign pleural effusion. Now there was no biomarker with high sensitivity and specificity for the malignant pleural effusion. This study used proteomics technology to acquire and analyze the protein profiles of the benign and malignant pleural effusion, to seek useful protein biomarkers with diagnostic value and to establish the diagnostic model. We chose the weak cationic-exchanger magnetic bead (WCX-MB) to purify peptides in the pleural effusion, used matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) to obtain peptide expression profiles from the benign and malignant pleural effusion samples, established and validated the diagnostic model through a genetic algorithm (GA) and finally identified the most promising protein biomarker. A GA diagnostic model was established with spectra of 3930.9 and 2942.8 m/z in the training set including 25 malignant pleural effusion and 26 benign pleural effusion samples, yielding both 100 % sensitivity and 100 % specificity. The accuracy of diagnostic prediction was validated in the independent testing set with 58 malignant pleural effusion and 34 benign pleural effusion samples. Blind evaluation was as follows: the sensitivity was 89.6 %, specificity 88.2 %, PPV 92.8 %, NPV 83.3 % and accuracy 89.1 % in the independent testing set. The most promising peptide biomarker was identified successfully: Isoform 1 of caspase recruitment domain-containing protein 9 (CARD9), with 3930.9 m/z, was decreased in the malignant pleural effusion. This model is suitable to discriminate benign and malignant pleural effusion and CARD9 can be used as a new peptide biomarker.

History of childhood trauma and disruptive behaviors in the medical setting.

PubMed

Sansone, Randy A; Farukhi, Shahzad; Wiederman, Michael W

2012-03-01

In this study, we examined relationships between five types of childhood trauma and 17 disruptive behaviors in the medical setting. Using a cross-sectional consecutive sample of 394 internal medicine outpatients, we surveyed participants about five types of childhood trauma (i.e. witnessing of violence, physical neglect, emotional abuse, physical abuse, and sexual abuse) and 17 disruptive behaviors in the medical setting (e.g., yelling, cursing, threatening medical personnel). Initial correlations indicated relationships between four of the five forms of childhood trauma and the number of different disruptive behaviors endorsed. However, using multiple regression analysis, only witnessing violence and physical abuse remained independent predictors of disruptive behaviors in the medical setting. Individuals with childhood histories of witnessing violence and/or physical abuse are at-risk for perpetrating various disruptive behaviors in the medical setting.

Rapid measurement of methyl cellulose precipitable tannins using ultraviolet spectroscopy with chemometrics: application to red wine and inter-laboratory calibration transfer.

PubMed

Dambergs, Robert G; Mercurio, Meagan D; Kassara, Stella; Cozzolino, Daniel; Smith, Paul A

2012-06-01

Information relating to tannin concentration in grapes and wine is not currently available simply and rapidly enough to inform decision-making by grape growers, winemakers, and wine researchers. Spectroscopy and chemometrics have been implemented for the analysis of critical grape and wine parameters and offer a possible solution for rapid tannin analysis. We report here the development and validation of an ultraviolet (UV) spectral calibration for the prediction of tannin concentration in red wines. Such spectral calibrations reduce the time and resource requirements involved in measuring tannins. A diverse calibration set (n = 204) was prepared with samples of Australian wines of five varieties (Cabernet Sauvignon, Shiraz, Merlot, Pinot Noir, and Durif), from regions spanning the wine grape growing areas of Australia, with varying climate and soils, and with vintages ranging from 1991 to 2007. The relationship between tannin measured by the methyl cellulose precipitation (MCP) reference method at 280 nm and tannin predicted with a multiple linear regression (MLR) calibration, using ultraviolet (UV) absorbance at 250, 270, 280, 290, and 315 nm, was strong (r(2)val = 0.92; SECV = 0.20 g/L). An independent validation set (n = 85) was predicted using the MLR algorithm developed with the calibration set and gave confidence in the ability to predict new samples, independent of the samples used to prepare the calibration (r(2)val = 0.94; SEP = 0.18 g/L). The MLR algorithm could also predict tannin in fermenting wines (r(2)val = 0.76; SEP = 0.18 g/L), but worked best from the second day of ferment on. This study also explored instrument-to-instrument transfer of a spectral calibration for MCP tannin. After slope and bias adjustments of the calibration, efficient calibration transfer to other laboratories was clearly demonstrated, with all instruments in the study effectively giving identical results on a transfer set.

Molecular analysis of HER2 signaling in human breast cancer by functional protein pathway activation mapping

PubMed Central

Wulfkuhle, Julia D.; Berg, Daniela; Wolff, Claudia; Langer, Rupert; Tran, Kai; Illi, Julie; Espina, Virginia; Pierobon, Mariaelena; Deng, Jianghong; DeMichele, Angela; Walch, Axel; Bronger, Holger; Becker, Ingrid; Waldhör, Christine; Höfler, Heinz; Esserman, Laura; Liotta, Lance A.; Becker, Karl-Friedrich; Petricoin, Emanuel F.

2017-01-01

Purpose Targeting of the HER2 protein in human breast cancer represents a major advance in oncology, but relies on measurements of total HER2 protein and not HER2 signaling network activation. We utilized reverse phase protein microarrays (RPMAs) to measure total and phosphorylated HER2 in the context of HER family signaling to understand correlations between phosphorylated and total levels of HER2 and downstream signaling activity. Experimental Design Three independent study sets, comprising a total of 415 individual patient samples from flash frozen core biopsy samples and FFPE surgical and core samples, were analyzed via RPMA. The phosphorylation and total levels of the HER receptor family proteins and downstream signaling molecules were measured in laser capture microdissected (LCM) enriched tumor epithelium from 127 frozen pre-treatment core biopsy samples and whole tissue lysates from 288 FFPE samples and these results were compared to FISH and IHC. Results RPMA measurements of total HER2 were highly concordant (> 90% all sets) with FISH and/or IHC data, as was phosphorylation of HER2 in the FISH/IHC+ population. Phosphorylation analysis of HER family signaling identified HER2 activation in some FISH/IHC- tumors and, identical to that seen with FISH/IHC+ tumors, the HER2 activation was concordant with EGFR and HER3 phosphorylation and downstream signaling endpoint activation. Conclusions Molecular profiling of HER2 signaling of a large cohort of human breast cancer specimens using a quantitative and sensitive functional pathway activation mapping technique reveals IHC-/FISH-/pHER2+ tumors with HER2 pathway activation independent of total HER2 levels and functional signaling through HER3 and EGFR. PMID:23045247

Effects of sample survey design on the accuracy of classification tree models in species distribution models

USGS Publications Warehouse

Edwards, T.C.; Cutler, D.R.; Zimmermann, N.E.; Geiser, L.; Moisen, Gretchen G.

2006-01-01

We evaluated the effects of probabilistic (hereafter DESIGN) and non-probabilistic (PURPOSIVE) sample surveys on resultant classification tree models for predicting the presence of four lichen species in the Pacific Northwest, USA. Models derived from both survey forms were assessed using an independent data set (EVALUATION). Measures of accuracy as gauged by resubstitution rates were similar for each lichen species irrespective of the underlying sample survey form. Cross-validation estimates of prediction accuracies were lower than resubstitution accuracies for all species and both design types, and in all cases were closer to the true prediction accuracies based on the EVALUATION data set. We argue that greater emphasis should be placed on calculating and reporting cross-validation accuracy rates rather than simple resubstitution accuracy rates. Evaluation of the DESIGN and PURPOSIVE tree models on the EVALUATION data set shows significantly lower prediction accuracy for the PURPOSIVE tree models relative to the DESIGN models, indicating that non-probabilistic sample surveys may generate models with limited predictive capability. These differences were consistent across all four lichen species, with 11 of the 12 possible species and sample survey type comparisons having significantly lower accuracy rates. Some differences in accuracy were as large as 50%. The classification tree structures also differed considerably both among and within the modelled species, depending on the sample survey form. Overlap in the predictor variables selected by the DESIGN and PURPOSIVE tree models ranged from only 20% to 38%, indicating the classification trees fit the two evaluated survey forms on different sets of predictor variables. The magnitude of these differences in predictor variables throws doubt on ecological interpretation derived from prediction models based on non-probabilistic sample surveys. ?? 2006 Elsevier B.V. All rights reserved.

Professional Learning Communities: An Analysis of Teacher Participation in a PLC and the Relationship with Student Academic Achievement

ERIC Educational Resources Information Center

Aylsworth, Anthony James

2012-01-01

This study sought to compare teacher participation in a Professional Learning Community with the performance of their students. Student achievement data from multiple subject-alike groups were compared in a pre-and post-PLC format, using an independent, two-sample t-test. Overall, 10 PLCs from one high school in a suburban, Iowa setting were…

Parental Perspectives during the Transition to Adulthood of Adolescents with a History of Specific Language Impairment (SLI)

ERIC Educational Resources Information Center

Conti-Ramsden, Gina; Botting, Nicola; Durkin, Kevin

2008-01-01

Purpose: This is the 2nd article of a companion set (the 1st article being on language and independence). It presents research examining parental perspectives on aspects of impairment in their offspring involving families rearing children with specific language impairment (SLI). Method: The same sample as that of the 1st study participated in this…

Do Programs for Runaway and Homeless Youth Work? A Qualitative Exploration From the Perspectives of Youth Clients in Diverse Settings.

PubMed

Gwadz, Marya; Freeman, Robert M; Kutnick, Alexandra H; Silverman, Elizabeth; Ritchie, Amanda S; Cleland, Charles M; Leonard, Noelle R; Srinagesh, Aradhana; Powlovich, Jamie; Bolas, James

2018-01-01

Runaway and homeless youth (RHY) comprise a large population of young people who reside outside the control and protection of parents and guardians and who experience numerous traumas and risk factors, but few buffering resources. Specialized settings have developed to serve RHY, but little is known about their effects. The present cross-sectional qualitative descriptive study, grounded in the positive youth development approach and the Youth Program Quality Assessment model, addressed this gap in the literature. From a larger sample of 29 RHY-specific settings across New York State, RHY ages 16-21 from 11 settings were purposively sampled for semi-structured in-depth interviews on their transitions into homelessness, experiences with settings, and unmet needs ( N  = 37 RHY). Data were analyzed with a theory-driven and inductive systematic content analysis approach. Half of participants (54%) were female; almost half (49%) identified as non-heterosexual; and 42% were African American/Black, 31% were Latino/Hispanic, and 28% were White/other. Results indicated that because RHY are a uniquely challenged population, distrustful of service settings and professional adults and skilled at surviving independently, the population-tailored approaches found in RHY-specific settings are vital to settings' abilities to effectively engage and serve RHY. We found the following four major themes regarding the positive effects of settings: (1) engaging with an RHY setting was emotionally challenging and frightening, and thus the experiences of safety and services tailored to RHY needs were critical; (2) instrumental support from staff was vital and most effective when received in a context of emotional support; (3) RHY were skilled at survival on the streets, but benefited from socialization into more traditional systems to foster future independent living; and (4) follow-through and aftercare were needed as RHY transitioned out of services. With respect to gaps in settings, RHY highlighted the following: (1) a desire for better management of tension between youths' needs for structure and wishes for autonomy and (2) lack of RHY input into program governance. This study advances our understanding of RHY, their service needs, and the ways settings meet these needs, as well as remaining gaps. It underscores the vital, life-changing, and even life-saving role these settings play for RHY.

Gossip-Based Dissemination

NASA Astrophysics Data System (ADS)

Friedman, Roy; Kermarrec, Anne-Marie; Miranda, Hugo; Rodrigues, Luís

Gossip-based networking has emerged as a viable approach to disseminate information reliably and efficiently in large-scale systems. Initially introduced for database replication [222], the applicability of the approach extends much further now. For example, it has been applied for data aggregation [415], peer sampling [416] and publish/subscribe systems [845]. Gossip-based protocols rely on a periodic peer-wise exchange of information in wired systems. By changing the way each peer is selected for the gossip communication, and which data are exchanged and processed [451], gossip systems can be used to perform different distributed tasks, such as, among others: overlay maintenance, distributed computation, and information dissemination (a collection of papers on gossip can be found in [451]). In a wired setting, the peer sampling service, allowing for a random or specific peer selection, is often provided as an independent service, able to operate independently from other gossip-based services [416].

L-statistics for Repeated Measurements Data With Application to Trimmed Means, Quantiles and Tolerance Intervals.

PubMed

Assaad, Houssein I; Choudhary, Pankaj K

2013-01-01

The L -statistics form an important class of estimators in nonparametric statistics. Its members include trimmed means and sample quantiles and functions thereof. This article is devoted to theory and applications of L -statistics for repeated measurements data, wherein the measurements on the same subject are dependent and the measurements from different subjects are independent. This article has three main goals: (a) Show that the L -statistics are asymptotically normal for repeated measurements data. (b) Present three statistical applications of this result, namely, location estimation using trimmed means, quantile estimation and construction of tolerance intervals. (c) Obtain a Bahadur representation for sample quantiles. These results are generalizations of similar results for independently and identically distributed data. The practical usefulness of these results is illustrated by analyzing a real data set involving measurement of systolic blood pressure. The properties of the proposed point and interval estimators are examined via simulation.

Estimating the Effective Sample Size of Tree Topologies from Bayesian Phylogenetic Analyses

PubMed Central

Lanfear, Robert; Hua, Xia; Warren, Dan L.

2016-01-01

Bayesian phylogenetic analyses estimate posterior distributions of phylogenetic tree topologies and other parameters using Markov chain Monte Carlo (MCMC) methods. Before making inferences from these distributions, it is important to assess their adequacy. To this end, the effective sample size (ESS) estimates how many truly independent samples of a given parameter the output of the MCMC represents. The ESS of a parameter is frequently much lower than the number of samples taken from the MCMC because sequential samples from the chain can be non-independent due to autocorrelation. Typically, phylogeneticists use a rule of thumb that the ESS of all parameters should be greater than 200. However, we have no method to calculate an ESS of tree topology samples, despite the fact that the tree topology is often the parameter of primary interest and is almost always central to the estimation of other parameters. That is, we lack a method to determine whether we have adequately sampled one of the most important parameters in our analyses. In this study, we address this problem by developing methods to estimate the ESS for tree topologies. We combine these methods with two new diagnostic plots for assessing posterior samples of tree topologies, and compare their performance on simulated and empirical data sets. Combined, the methods we present provide new ways to assess the mixing and convergence of phylogenetic tree topologies in Bayesian MCMC analyses. PMID:27435794

Rotation sets and phase-locking in an electronic three oscillator system

NASA Astrophysics Data System (ADS)

Ashwin, Peter; Guaschi, John; Phelps, J. M.

1993-07-01

The parameter space of an electronic three oscillator system is investigated and various codimension one and two bifurcations predicted by Baesens, Guckenheimer, Kim and MacKay are identified. Sampled time-series from the experimental systems are recorded and analysed for partial mode-locking or resonance (one or two independent rational relations between the average rates of change of the angles describing the system) using knowledge of where the invariant torus lies and the torus unfolding scheme of Ashwin and Swift. Examples of toroidal and annular chaos are investigated by finding bounds on the size and shape of the rotation set.

Millimeter- and submillimeter-wave characterization of various fabrics.

PubMed

Dunayevskiy, Ilya; Bortnik, Bartosz; Geary, Kevin; Lombardo, Russell; Jack, Michael; Fetterman, Harold

2007-08-20

Transmission measurements of 14 fabrics are presented in the millimeter-wave and submillimeter-wave electromagnetic regions from 130 GHz to 1.2 THz. Three independent sources and experimental set-ups were used to obtain accurate results over a wide spectral range. Reflectivity, a useful parameter for imaging applications, was also measured for a subset of samples in the submillimeter-wave regime along with polarization sensitivity of the transmitted beam and transmission through doubled layers. All of the measurements were performed in free space. Details of these experimental set-ups along with their respective challenges are presented.

Targeted Data Extraction of the MS/MS Spectra Generated by Data-independent Acquisition: A New Concept for Consistent and Accurate Proteome Analysis*

PubMed Central

Gillet, Ludovic C.; Navarro, Pedro; Tate, Stephen; Röst, Hannes; Selevsek, Nathalie; Reiter, Lukas; Bonner, Ron; Aebersold, Ruedi

2012-01-01

Most proteomic studies use liquid chromatography coupled to tandem mass spectrometry to identify and quantify the peptides generated by the proteolysis of a biological sample. However, with the current methods it remains challenging to rapidly, consistently, reproducibly, accurately, and sensitively detect and quantify large fractions of proteomes across multiple samples. Here we present a new strategy that systematically queries sample sets for the presence and quantity of essentially any protein of interest. It consists of using the information available in fragment ion spectral libraries to mine the complete fragment ion maps generated using a data-independent acquisition method. For this study, the data were acquired on a fast, high resolution quadrupole-quadrupole time-of-flight (TOF) instrument by repeatedly cycling through 32 consecutive 25-Da precursor isolation windows (swaths). This SWATH MS acquisition setup generates, in a single sample injection, time-resolved fragment ion spectra for all the analytes detectable within the 400–1200 m/z precursor range and the user-defined retention time window. We show that suitable combinations of fragment ions extracted from these data sets are sufficiently specific to confidently identify query peptides over a dynamic range of 4 orders of magnitude, even if the precursors of the queried peptides are not detectable in the survey scans. We also show that queried peptides are quantified with a consistency and accuracy comparable with that of selected reaction monitoring, the gold standard proteomic quantification method. Moreover, targeted data extraction enables ad libitum quantification refinement and dynamic extension of protein probing by iterative re-mining of the once-and-forever acquired data sets. This combination of unbiased, broad range precursor ion fragmentation and targeted data extraction alleviates most constraints of present proteomic methods and should be equally applicable to the comprehensive analysis of other classes of analytes, beyond proteomics. PMID:22261725

The estimation of tree posterior probabilities using conditional clade probability distributions.

PubMed

Larget, Bret

2013-07-01

In this article I introduce the idea of conditional independence of separated subtrees as a principle by which to estimate the posterior probability of trees using conditional clade probability distributions rather than simple sample relative frequencies. I describe an algorithm for these calculations and software which implements these ideas. I show that these alternative calculations are very similar to simple sample relative frequencies for high probability trees but are substantially more accurate for relatively low probability trees. The method allows the posterior probability of unsampled trees to be calculated when these trees contain only clades that are in other sampled trees. Furthermore, the method can be used to estimate the total probability of the set of sampled trees which provides a measure of the thoroughness of a posterior sample.

How important are autonomy and work setting to nurse practitioners' job satisfaction?

PubMed

Athey, Erin K; Leslie, Mayri Sagady; Briggs, Linda A; Park, Jeongyoung; Falk, Nancy L; Pericak, Arlene; El-Banna, Majeda M; Greene, Jessica

2016-06-01

Nurse practitioners (NPs) have reported aspects of their jobs that they are more and less satisfied with. However, few studies have examined the factors that predict overall job satisfaction. This study uses a large national sample to examine the extent to which autonomy and work setting predict job satisfaction. The 2012 National Sample Survey of Nurse Practitioners (n = 8311) was used to examine bivariate and multivariate relationships between work setting and three autonomy variables (independent billing practices, having one's NP skills fully utilized, and relationship with physician), and job satisfaction. NPs working in primary care reported the highest levels of autonomy across all three autonomy measures, while those working in hospital surgical settings reported the lowest levels. Autonomy, specifically feeling one's NP skills were fully utilized, was the factor most predictive of satisfaction. In multivariate analyses, those who strongly agreed their skills were being fully utilized had satisfaction scores almost one point higher than those who strongly disagreed. Work setting was only marginally related to job satisfaction. In order to attract and retain NPs in the future, healthcare organizations should ensure that NPs' skills are being fully utilized. ©2015 American Association of Nurse Practitioners.

Metabolomics biomarkers to predict acamprosate treatment response in alcohol-dependent subjects.

PubMed

Hinton, David J; Vázquez, Marely Santiago; Geske, Jennifer R; Hitschfeld, Mario J; Ho, Ada M C; Karpyak, Victor M; Biernacka, Joanna M; Choi, Doo-Sup

2017-05-31

Precision medicine for alcohol use disorder (AUD) allows optimal treatment of the right patient with the right drug at the right time. Here, we generated multivariable models incorporating clinical information and serum metabolite levels to predict acamprosate treatment response. The sample of 120 patients was randomly split into a training set (n = 80) and test set (n = 40) five independent times. Treatment response was defined as complete abstinence (no alcohol consumption during 3 months of acamprosate treatment) while nonresponse was defined as any alcohol consumption during this period. In each of the five training sets, we built a predictive model using a least absolute shrinkage and section operator (LASSO) penalized selection method and then evaluated the predictive performance of each model in the corresponding test set. The models predicted acamprosate treatment response with a mean sensitivity and specificity in the test sets of 0.83 and 0.31, respectively, suggesting our model performed well at predicting responders, but not non-responders (i.e. many non-responders were predicted to respond). Studies with larger sample sizes and additional biomarkers will expand the clinical utility of predictive algorithms for pharmaceutical response in AUD.

A new framework to enhance the interpretation of external validation studies of clinical prediction models.

PubMed

Debray, Thomas P A; Vergouwe, Yvonne; Koffijberg, Hendrik; Nieboer, Daan; Steyerberg, Ewout W; Moons, Karel G M

2015-03-01

It is widely acknowledged that the performance of diagnostic and prognostic prediction models should be assessed in external validation studies with independent data from "different but related" samples as compared with that of the development sample. We developed a framework of methodological steps and statistical methods for analyzing and enhancing the interpretation of results from external validation studies of prediction models. We propose to quantify the degree of relatedness between development and validation samples on a scale ranging from reproducibility to transportability by evaluating their corresponding case-mix differences. We subsequently assess the models' performance in the validation sample and interpret the performance in view of the case-mix differences. Finally, we may adjust the model to the validation setting. We illustrate this three-step framework with a prediction model for diagnosing deep venous thrombosis using three validation samples with varying case mix. While one external validation sample merely assessed the model's reproducibility, two other samples rather assessed model transportability. The performance in all validation samples was adequate, and the model did not require extensive updating to correct for miscalibration or poor fit to the validation settings. The proposed framework enhances the interpretation of findings at external validation of prediction models. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

[Application of simulated annealing method and neural network on optimizing soil sampling schemes based on road distribution].

PubMed

Han, Zong-wei; Huang, Wei; Luo, Yun; Zhang, Chun-di; Qi, Da-cheng

2015-03-01

Taking the soil organic matter in eastern Zhongxiang County, Hubei Province, as a research object, thirteen sample sets from different regions were arranged surrounding the road network, the spatial configuration of which was optimized by the simulated annealing approach. The topographic factors of these thirteen sample sets, including slope, plane curvature, profile curvature, topographic wetness index, stream power index and sediment transport index, were extracted by the terrain analysis. Based on the results of optimization, a multiple linear regression model with topographic factors as independent variables was built. At the same time, a multilayer perception model on the basis of neural network approach was implemented. The comparison between these two models was carried out then. The results revealed that the proposed approach was practicable in optimizing soil sampling scheme. The optimal configuration was capable of gaining soil-landscape knowledge exactly, and the accuracy of optimal configuration was better than that of original samples. This study designed a sampling configuration to study the soil attribute distribution by referring to the spatial layout of road network, historical samples, and digital elevation data, which provided an effective means as well as a theoretical basis for determining the sampling configuration and displaying spatial distribution of soil organic matter with low cost and high efficiency.

Identification of serum proteins discriminating colorectal cancer patients and healthy controls using surface-enhanced laser desorption ionisation-time of flight mass spectrometry.

PubMed

Engwegen, Judith Y M N; Helgason, Helgi H; Cats, Annemieke; Harris, Nathan; Bonfrer, Johannes M G; Schellens, Jan H M; Beijnen, Jos H

2006-03-14

To detect the new serum biomarkers for colorectal cancer (CRC) by serum protein profiling with surface-enhanced laser desorption ionisation--time of flight mass spectrometry (SELDI-TOF MS). Two independent serum sample sets were analysed separately with the ProteinChip technology (set A: 40 CRC+49 healthy controls; set B: 37 CRC+31 healthy controls), using chips with a weak cation exchange moiety and buffer pH 5. Discriminative power of differentially expressed proteins was assessed with a classification tree algorithm. Sensitivities and specificities of the generated classification trees were obtained by blindly applying data from set A to the generated trees from set B and vice versa. CRC serum protein profiles were also compared with those from breast, ovarian, prostate, and non-small cell lung cancer. Mass-to-charge ratios (m/z) 3.1x10(3), 3.3x10(3), 4.5x10(3), 6.6x10(3) and 28x10(3) were used as classifiers in the best-performing classification trees. Tree sensitivities and specificities were between 65% and 90%. Most of these discriminative m/z values were also different in the other tumour types investigated. M/z 3.3x10(3), main classifier in most trees, was a doubly charged form of the 6.6x10(3)-Da protein. The latter was identified as apolipoprotein C-I. M/z 3.1x10(3) was identified as an N-terminal fragment of albumin, and m/z 28x10(3) as apolipoprotein A-I. SELDI-TOF MS followed by classification tree pattern analysis is a suitable technique for finding new serum markers for CRC. Biomarkers can be identified and reproducibly detected in independent sample sets with high sensitivities and specificities. Although not specific for CRC, these biomarkers have a potential role in disease and treatment monitoring.

Modification of the Sandwich Estimator in Generalized Estimating Equations with Correlated Binary Outcomes in Rare Event and Small Sample Settings

PubMed Central

Rogers, Paul; Stoner, Julie

2016-01-01

Regression models for correlated binary outcomes are commonly fit using a Generalized Estimating Equations (GEE) methodology. GEE uses the Liang and Zeger sandwich estimator to produce unbiased standard error estimators for regression coefficients in large sample settings even when the covariance structure is misspecified. The sandwich estimator performs optimally in balanced designs when the number of participants is large, and there are few repeated measurements. The sandwich estimator is not without drawbacks; its asymptotic properties do not hold in small sample settings. In these situations, the sandwich estimator is biased downwards, underestimating the variances. In this project, a modified form for the sandwich estimator is proposed to correct this deficiency. The performance of this new sandwich estimator is compared to the traditional Liang and Zeger estimator as well as alternative forms proposed by Morel, Pan and Mancl and DeRouen. The performance of each estimator was assessed with 95% coverage probabilities for the regression coefficient estimators using simulated data under various combinations of sample sizes and outcome prevalence values with an Independence (IND), Autoregressive (AR) and Compound Symmetry (CS) correlation structure. This research is motivated by investigations involving rare-event outcomes in aviation data. PMID:26998504

Rapid detection of frozen-then-thawed minced beef using multispectral imaging and Fourier transform infrared spectroscopy.

PubMed

Ropodi, Athina I; Panagou, Efstathios Z; Nychas, George-John E

2018-01-01

In recent years, fraud detection has become a major priority for food authorities, as fraudulent practices can have various economic and safety consequences. This work explores ways of identifying frozen-then-thawed minced beef labeled as fresh in a rapid, large-scale and cost-effective way. For this reason, freshly-ground beef was purchased from seven separate shops at different times, divided in fifteen portions and placed in Petri dishes. Multi-spectral images and FTIR spectra of the first five were immediately acquired while the remaining were frozen (-20°C) and stored for 7 and 32days (5 samples for each time interval). Samples were thawed and subsequently subjected to similar data acquisition. In total, 105 multispectral images and FTIR spectra were collected which were further analyzed using partial least-squares discriminant analysis and support vector machines. Two meat batches (30 samples) were reserved for independent validation and the remaining five batches were divided in training and test set (75 samples). Results showed 100% overall correct classification for test and external validation MSI data, while FTIR data yielded 93.3 and 96.7% overall correct classification for FTIR test set and external validation set respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

Assessment of resampling methods for causality testing: A note on the US inflation behavior

PubMed Central

Kyrtsou, Catherine; Kugiumtzis, Dimitris; Diks, Cees

2017-01-01

Different resampling methods for the null hypothesis of no Granger causality are assessed in the setting of multivariate time series, taking into account that the driving-response coupling is conditioned on the other observed variables. As appropriate test statistic for this setting, the partial transfer entropy (PTE), an information and model-free measure, is used. Two resampling techniques, time-shifted surrogates and the stationary bootstrap, are combined with three independence settings (giving a total of six resampling methods), all approximating the null hypothesis of no Granger causality. In these three settings, the level of dependence is changed, while the conditioning variables remain intact. The empirical null distribution of the PTE, as the surrogate and bootstrapped time series become more independent, is examined along with the size and power of the respective tests. Additionally, we consider a seventh resampling method by contemporaneously resampling the driving and the response time series using the stationary bootstrap. Although this case does not comply with the no causality hypothesis, one can obtain an accurate sampling distribution for the mean of the test statistic since its value is zero under H0. Results indicate that as the resampling setting gets more independent, the test becomes more conservative. Finally, we conclude with a real application. More specifically, we investigate the causal links among the growth rates for the US CPI, money supply and crude oil. Based on the PTE and the seven resampling methods, we consistently find that changes in crude oil cause inflation conditioning on money supply in the post-1986 period. However this relationship cannot be explained on the basis of traditional cost-push mechanisms. PMID:28708870

Assessment of resampling methods for causality testing: A note on the US inflation behavior.

PubMed

Papana, Angeliki; Kyrtsou, Catherine; Kugiumtzis, Dimitris; Diks, Cees

2017-01-01

Different resampling methods for the null hypothesis of no Granger causality are assessed in the setting of multivariate time series, taking into account that the driving-response coupling is conditioned on the other observed variables. As appropriate test statistic for this setting, the partial transfer entropy (PTE), an information and model-free measure, is used. Two resampling techniques, time-shifted surrogates and the stationary bootstrap, are combined with three independence settings (giving a total of six resampling methods), all approximating the null hypothesis of no Granger causality. In these three settings, the level of dependence is changed, while the conditioning variables remain intact. The empirical null distribution of the PTE, as the surrogate and bootstrapped time series become more independent, is examined along with the size and power of the respective tests. Additionally, we consider a seventh resampling method by contemporaneously resampling the driving and the response time series using the stationary bootstrap. Although this case does not comply with the no causality hypothesis, one can obtain an accurate sampling distribution for the mean of the test statistic since its value is zero under H0. Results indicate that as the resampling setting gets more independent, the test becomes more conservative. Finally, we conclude with a real application. More specifically, we investigate the causal links among the growth rates for the US CPI, money supply and crude oil. Based on the PTE and the seven resampling methods, we consistently find that changes in crude oil cause inflation conditioning on money supply in the post-1986 period. However this relationship cannot be explained on the basis of traditional cost-push mechanisms.

Quantitative parameters of CT texture analysis as potential markersfor early prediction of spontaneous intracranial hemorrhage enlargement.

PubMed

Shen, Qijun; Shan, Yanna; Hu, Zhengyu; Chen, Wenhui; Yang, Bing; Han, Jing; Huang, Yanfang; Xu, Wen; Feng, Zhan

2018-04-30

To objectively quantify intracranial hematoma (ICH) enlargement by analysing the image texture of head CT scans and to provide objective and quantitative imaging parameters for predicting early hematoma enlargement. We retrospectively studied 108 ICH patients with baseline non-contrast computed tomography (NCCT) and 24-h follow-up CT available. Image data were assessed by a chief radiologist and a resident radiologist. Consistency analysis between observers was tested. The patients were divided into training set (75%) and validation set (25%) by stratified sampling. Patients in the training set were dichotomized according to 24-h hematoma expansion ≥ 33%. Using the Laplacian of Gaussian bandpass filter, we chose different anatomical spatial domains ranging from fine texture to coarse texture to obtain a series of derived parameters (mean grayscale intensity, variance, uniformity) in order to quantify and evaluate all data. The parameters were externally validated on validation set. Significant differences were found between the two groups of patients within variance at V 1.0 and in uniformity at U 1.0 , U 1.8 and U 2.5 . The intraclass correlation coefficients for the texture parameters were between 0.67 and 0.99. The area under the ROC curve between the two groups of ICH cases was between 0.77 and 0.92. The accuracy of validation set by CTTA was 0.59-0.85. NCCT texture analysis can objectively quantify the heterogeneity of ICH and independently predict early hematoma enlargement. • Heterogeneity is helpful in predicting ICH enlargement. • CTTA could play an important role in predicting early ICH enlargement. • After filtering, fine texture had the best diagnostic performance. • The histogram-based uniformity parameters can independently predict ICH enlargement. • CTTA is more objective, more comprehensive, more independently operable, than previous methods.

How can PPOs control prices without violating antitrust laws?

PubMed

Fried, J M

1984-03-01

Preferred provider organizations (PPOs) have caused concern because they raise the question whether providers can establish mechanisms to control the price of medical care without violating antitrust laws. The U.S. Supreme Court recently decided in Arizona v. Maricopa County Medical Society that the practices of a physicians' organization which set fee schedules by majority vote constituted price fixing because "independent competing entrepreneurs" made the agreements. The decision implies that PPOs must carefully structure collective efforts to set prices in order to avoid unlawful agreement among competitors. To avoid antitrust exposure, hospitals may independently determine prices and contract individually with providers, or they may act as brokers for individual physicians, establishing fees and claims-processing procedures and then contracting with physicians who agree to these requirements. Setting fees independently may be difficult, however, since hospitals need to know what payment physicians will accept. Thus some physician involvement is probably inevitable. No antitrust liability results, however, if individual physicians are sampled in an information-gathering process but do not collectively set fees. In addition, a PPO that is structured as a partnership or other joint arrangement involving true risk sharing should withstand antitrust challenge. In recent business review letters, the Department of Justice approved two different PPO structures: A Hospital Corporation of America subsidiary would contract (nonexclusively) with providers, hospitals, and third party payers to treat the third party payers' beneficiaries at discounted rates. The charges would be negotiated individually with each physician and hospital. A management consultant firm would act as an intermediary between providers and third party payers, negotiating patient discounts but not participating in fee setting. A PPO need not be structured in every respect like these programs. Individual situations vary, and with sound antitrust advice, PPOs can avoid legal pitfalls.

GAB2 as an Alzheimer Disease Susceptibility Gene

PubMed Central

Schjeide, Brit-Maren M.; Hooli, Basavaraj; Parkinson, Michele; Hogan, Meghan F.; DiVito, Jason; Mullin, Kristina; Blacker, Deborah; Tanzi, Rudolph E.; Bertram, Lars

2009-01-01

Background Genomewide association (GWA) studies have recently implicated 4 novel Alzheimer disease (AD) susceptibility loci (GAB2, GOLM1, and 2 uncharacterized loci to date on chromosomes 9p and 15q). To our knowledge, these findings have not been independently replicated. Objective To assess these GWA findings in 4 large data sets of families affected by AD. Design Follow-up of genetic association findings in previous studies. Setting Academic research. Participants More than 4000 DNA samples from almost 1300 families affected with AD. Main Outcome Measures Genetic association analysis testing of 4 GWA signals (rs7101429 [GAB2], rs7019241 [GOLM1], rs10519262 [chromosome 15q], and rs9886784 [chromosome 9p]) using family-based methods. Results In the combined analyses, only rs7101429 in GAB2 yielded significant evidence of association with the same allele as in the original GWA study (P = .002). The results are in agreement with recent meta-analyses of this and other GAB2 polymorphisms suggesting approximately a 30% decrease in risk for AD among carriers of the minor alleles. None of the other 3 tested loci showed consistent evidence for association with AD across the investigated data sets. Conclusions GAB2 contains genetic variants that may lead to a modest change in the risk for AD. Despite these promising results, more data from independent samples are needed to better evaluate the potential contribution of GAB2 to AD risk in the general population. PMID:19204163

Do Programs for Runaway and Homeless Youth Work? A Qualitative Exploration From the Perspectives of Youth Clients in Diverse Settings

PubMed Central

Gwadz, Marya; Freeman, Robert M.; Kutnick, Alexandra H.; Silverman, Elizabeth; Ritchie, Amanda S.; Cleland, Charles M.; Leonard, Noelle R.; Srinagesh, Aradhana; Powlovich, Jamie; Bolas, James

2018-01-01

Runaway and homeless youth (RHY) comprise a large population of young people who reside outside the control and protection of parents and guardians and who experience numerous traumas and risk factors, but few buffering resources. Specialized settings have developed to serve RHY, but little is known about their effects. The present cross-sectional qualitative descriptive study, grounded in the positive youth development approach and the Youth Program Quality Assessment model, addressed this gap in the literature. From a larger sample of 29 RHY-specific settings across New York State, RHY ages 16–21 from 11 settings were purposively sampled for semi-structured in-depth interviews on their transitions into homelessness, experiences with settings, and unmet needs (N = 37 RHY). Data were analyzed with a theory-driven and inductive systematic content analysis approach. Half of participants (54%) were female; almost half (49%) identified as non-heterosexual; and 42% were African American/Black, 31% were Latino/Hispanic, and 28% were White/other. Results indicated that because RHY are a uniquely challenged population, distrustful of service settings and professional adults and skilled at surviving independently, the population-tailored approaches found in RHY-specific settings are vital to settings’ abilities to effectively engage and serve RHY. We found the following four major themes regarding the positive effects of settings: (1) engaging with an RHY setting was emotionally challenging and frightening, and thus the experiences of safety and services tailored to RHY needs were critical; (2) instrumental support from staff was vital and most effective when received in a context of emotional support; (3) RHY were skilled at survival on the streets, but benefited from socialization into more traditional systems to foster future independent living; and (4) follow-through and aftercare were needed as RHY transitioned out of services. With respect to gaps in settings, RHY highlighted the following: (1) a desire for better management of tension between youths’ needs for structure and wishes for autonomy and (2) lack of RHY input into program governance. This study advances our understanding of RHY, their service needs, and the ways settings meet these needs, as well as remaining gaps. It underscores the vital, life-changing, and even life-saving role these settings play for RHY. PMID:29725587

Meta-analysis of gene expression profiles associated with histological classification and survival in 829 ovarian cancer samples.

PubMed

Fekete, Tibor; Rásó, Erzsébet; Pete, Imre; Tegze, Bálint; Liko, István; Munkácsy, Gyöngyi; Sipos, Norbert; Rigó, János; Györffy, Balázs

2012-07-01

Transcriptomic analysis of global gene expression in ovarian carcinoma can identify dysregulated genes capable to serve as molecular markers for histology subtypes and survival. The aim of our study was to validate previous candidate signatures in an independent setting and to identify single genes capable to serve as biomarkers for ovarian cancer progression. As several datasets are available in the GEO today, we were able to perform a true meta-analysis. First, 829 samples (11 datasets) were downloaded, and the predictive power of 16 previously published gene sets was assessed. Of these, eight were capable to discriminate histology subtypes, and none was capable to predict survival. To overcome the differences in previous studies, we used the 829 samples to identify new predictors. Then, we collected 64 ovarian cancer samples (median relapse-free survival 24.5 months) and performed TaqMan Real Time Polimerase Chain Reaction (RT-PCR) analysis for the best 40 genes associated with histology subtypes and survival. Over 90% of subtype-associated genes were confirmed. Overall survival was effectively predicted by hormone receptors (PGR and ESR2) and by TSPAN8. Relapse-free survival was predicted by MAPT and SNCG. In summary, we successfully validated several gene sets in a meta-analysis in large datasets of ovarian samples. Additionally, several individual genes identified were validated in a clinical cohort. Copyright © 2011 UICC.

Inference and quantification of peptidoforms in large sample cohorts by SWATH-MS

PubMed Central

Röst, Hannes L; Ludwig, Christina; Buil, Alfonso; Bensimon, Ariel; Soste, Martin; Spector, Tim D; Dermitzakis, Emmanouil T; Collins, Ben C; Malmström, Lars; Aebersold, Ruedi

2017-01-01

The consistent detection and quantification of protein post-translational modifications (PTMs) across sample cohorts is an essential prerequisite for the functional analysis of biological processes. Data-independent acquisition (DIA), a bottom-up mass spectrometry based proteomic strategy, exemplified by SWATH-MS, provides complete precursor and fragment ion information of a sample and thus, in principle, the information to identify peptidoforms, the modified variants of a peptide. However, due to the convoluted structure of DIA data sets the confident and systematic identification and quantification of peptidoforms has remained challenging. Here we present IPF (Inference of PeptidoForms), a fully automated algorithm that uses spectral libraries to query, validate and quantify peptidoforms in DIA data sets. The method was developed on data acquired by SWATH-MS and benchmarked using a synthetic phosphopeptide reference data set and phosphopeptide-enriched samples. The data indicate that IPF reduced false site-localization by more than 7-fold in comparison to previous approaches, while recovering 85.4% of the true signals. IPF was applied to detect and quantify peptidoforms carrying ten different types of PTMs in DIA data acquired from more than 200 samples of undepleted blood plasma of a human twin cohort. The data approportioned, for the first time, the contribution of heritable, environmental and longitudinal effects on the observed quantitative variability of specific modifications in blood plasma of a human population. PMID:28604659

Meta-analysis of pathway enrichment: combining independent and dependent omics data sets.

PubMed

Kaever, Alexander; Landesfeind, Manuel; Feussner, Kirstin; Morgenstern, Burkhard; Feussner, Ivo; Meinicke, Peter

2014-01-01

A major challenge in current systems biology is the combination and integrative analysis of large data sets obtained from different high-throughput omics platforms, such as mass spectrometry based Metabolomics and Proteomics or DNA microarray or RNA-seq-based Transcriptomics. Especially in the case of non-targeted Metabolomics experiments, where it is often impossible to unambiguously map ion features from mass spectrometry analysis to metabolites, the integration of more reliable omics technologies is highly desirable. A popular method for the knowledge-based interpretation of single data sets is the (Gene) Set Enrichment Analysis. In order to combine the results from different analyses, we introduce a methodical framework for the meta-analysis of p-values obtained from Pathway Enrichment Analysis (Set Enrichment Analysis based on pathways) of multiple dependent or independent data sets from different omics platforms. For dependent data sets, e.g. obtained from the same biological samples, the framework utilizes a covariance estimation procedure based on the nonsignificant pathways in single data set enrichment analysis. The framework is evaluated and applied in the joint analysis of Metabolomics mass spectrometry and Transcriptomics DNA microarray data in the context of plant wounding. In extensive studies of simulated data set dependence, the introduced correlation could be fully reconstructed by means of the covariance estimation based on pathway enrichment. By restricting the range of p-values of pathways considered in the estimation, the overestimation of correlation, which is introduced by the significant pathways, could be reduced. When applying the proposed methods to the real data sets, the meta-analysis was shown not only to be a powerful tool to investigate the correlation between different data sets and summarize the results of multiple analyses but also to distinguish experiment-specific key pathways.

Polarization Imaging Apparatus with Auto-Calibration

NASA Technical Reports Server (NTRS)

Zou, Yingyin Kevin (Inventor); Zhao, Hongzhi (Inventor); Chen, Qiushui (Inventor)

2013-01-01

A polarization imaging apparatus measures the Stokes image of a sample. The apparatus consists of an optical lens set, a first variable phase retarder (VPR) with its optical axis aligned 22.5 deg, a second variable phase retarder with its optical axis aligned 45 deg, a linear polarizer, a imaging sensor for sensing the intensity images of the sample, a controller and a computer. Two variable phase retarders were controlled independently by a computer through a controller unit which generates a sequential of voltages to control the phase retardations of the first and second variable phase retarders. A auto-calibration procedure was incorporated into the polarization imaging apparatus to correct the misalignment of first and second VPRs, as well as the half-wave voltage of the VPRs. A set of four intensity images, I(sub 0), I(sub 1), I(sub 2) and I(sub 3) of the sample were captured by imaging sensor when the phase retardations of VPRs were set at (0,0), (pi,0), (pi,pi) and (pi/2,pi), respectively. Then four Stokes components of a Stokes image, S(sub 0), S(sub 1), S(sub 2) and S(sub 3) were calculated using the four intensity images.

Polarization imaging apparatus with auto-calibration

DOEpatents

Zou, Yingyin Kevin; Zhao, Hongzhi; Chen, Qiushui

2013-08-20

A polarization imaging apparatus measures the Stokes image of a sample. The apparatus consists of an optical lens set, a first variable phase retarder (VPR) with its optical axis aligned 22.5.degree., a second variable phase retarder with its optical axis aligned 45.degree., a linear polarizer, a imaging sensor for sensing the intensity images of the sample, a controller and a computer. Two variable phase retarders were controlled independently by a computer through a controller unit which generates a sequential of voltages to control the phase retardations of the first and second variable phase retarders. A auto-calibration procedure was incorporated into the polarization imaging apparatus to correct the misalignment of first and second VPRs, as well as the half-wave voltage of the VPRs. A set of four intensity images, I.sub.0, I.sub.1, I.sub.2 and I.sub.3 of the sample were captured by imaging sensor when the phase retardations of VPRs were set at (0,0), (.pi.,0), (.pi.,.pi.) and (.pi./2,.pi.), respectively. Then four Stokes components of a Stokes image, S.sub.0, S.sub.1, S.sub.2 and S.sub.3 were calculated using the four intensity images.

Polarization imaging apparatus

NASA Technical Reports Server (NTRS)

Zou, Yingyin Kevin (Inventor); Chen, Qiushui (Inventor); Zhao, Hongzhi (Inventor)

2010-01-01

A polarization imaging apparatus measures the Stokes image of a sample. The apparatus consists of an optical lens set 11, a linear polarizer 14 with its optical axis 18, a first variable phase retarder 12 with its optical axis 16 aligned 22.5.degree. to axis 18, a second variable phase retarder 13 with its optical axis 17 aligned 45.degree. to axis 18, a imaging sensor 15 for sensing the intensity images of the sample, a controller 101 and a computer 102. Two variable phase retarders 12 and 13 were controlled independently by a computer 102 through a controller unit 101 which generates a sequential of voltages to control the phase retardations of VPRs 12 and 13. A set of four intensity images, I.sub.0, I.sub.1, I.sub.2 and I.sub.3 of the sample were captured by imaging sensor 15 when the phase retardations of VPRs 12 and 13 were set at (0,0), (.pi.,0), (.pi.,.pi.) and (.pi./2,.pi.), respectively Then four Stokes components of a Stokes image, S.sub.0, S.sub.1, S.sub.2 and S.sub.3 were calculated using the four intensity images.

Teaching calculus using module based on cooperative learning strategy

NASA Astrophysics Data System (ADS)

Arbin, Norazman; Ghani, Sazelli Abdul; Hamzah, Firdaus Mohamad

2014-06-01

The purpose of the research is to evaluate the effectiveness of a module which utilizes the cooperative learning for teaching Calculus for limit, derivative and integral. The sample consists of 50 semester 1 students from the Science Programme (AT 16) Sultan Idris Education University. A set of questions of related topics (pre and post) has been used as an instrument to collect data. The data is analyzed using inferential statistics involving the paired sample t-test and the independent t-test. The result shows that students have positive inclination towards the modulein terms of understanding.

Quadruple Axis Neutron Computed Tomography

NASA Astrophysics Data System (ADS)

Schillinger, Burkhard; Bausenwein, Dominik

Neutron computed tomography takes more time for a full tomography than X-rays or Synchrotron radiation, because the source intensity is limited. Most neutron imaging detectors have a square field of view, so if tomography of elongated, narrow samples, e.g. fuel rods, sword blades is recorded, much of the detector area is wasted. Using multiple rotation axes, several samples can be placed inside the field of view, and multiple tomographies can be recorded at the same time by later splitting the recorded images into separate tomography data sets. We describe a new multiple-axis setup using four independent miniaturized rotation tables.

A genome-wide association study of anorexia nervosa.

PubMed

Boraska, V; Franklin, C S; Floyd, J A B; Thornton, L M; Huckins, L M; Southam, L; Rayner, N W; Tachmazidou, I; Klump, K L; Treasure, J; Lewis, C M; Schmidt, U; Tozzi, F; Kiezebrink, K; Hebebrand, J; Gorwood, P; Adan, R A H; Kas, M J H; Favaro, A; Santonastaso, P; Fernández-Aranda, F; Gratacos, M; Rybakowski, F; Dmitrzak-Weglarz, M; Kaprio, J; Keski-Rahkonen, A; Raevuori, A; Van Furth, E F; Slof-Op 't Landt, M C T; Hudson, J I; Reichborn-Kjennerud, T; Knudsen, G P S; Monteleone, P; Kaplan, A S; Karwautz, A; Hakonarson, H; Berrettini, W H; Guo, Y; Li, D; Schork, N J; Komaki, G; Ando, T; Inoko, H; Esko, T; Fischer, K; Männik, K; Metspalu, A; Baker, J H; Cone, R D; Dackor, J; DeSocio, J E; Hilliard, C E; O'Toole, J K; Pantel, J; Szatkiewicz, J P; Taico, C; Zerwas, S; Trace, S E; Davis, O S P; Helder, S; Bühren, K; Burghardt, R; de Zwaan, M; Egberts, K; Ehrlich, S; Herpertz-Dahlmann, B; Herzog, W; Imgart, H; Scherag, A; Scherag, S; Zipfel, S; Boni, C; Ramoz, N; Versini, A; Brandys, M K; Danner, U N; de Kovel, C; Hendriks, J; Koeleman, B P C; Ophoff, R A; Strengman, E; van Elburg, A A; Bruson, A; Clementi, M; Degortes, D; Forzan, M; Tenconi, E; Docampo, E; Escaramís, G; Jiménez-Murcia, S; Lissowska, J; Rajewski, A; Szeszenia-Dabrowska, N; Slopien, A; Hauser, J; Karhunen, L; Meulenbelt, I; Slagboom, P E; Tortorella, A; Maj, M; Dedoussis, G; Dikeos, D; Gonidakis, F; Tziouvas, K; Tsitsika, A; Papezova, H; Slachtova, L; Martaskova, D; Kennedy, J L; Levitan, R D; Yilmaz, Z; Huemer, J; Koubek, D; Merl, E; Wagner, G; Lichtenstein, P; Breen, G; Cohen-Woods, S; Farmer, A; McGuffin, P; Cichon, S; Giegling, I; Herms, S; Rujescu, D; Schreiber, S; Wichmann, H-E; Dina, C; Sladek, R; Gambaro, G; Soranzo, N; Julia, A; Marsal, S; Rabionet, R; Gaborieau, V; Dick, D M; Palotie, A; Ripatti, S; Widén, E; Andreassen, O A; Espeseth, T; Lundervold, A; Reinvang, I; Steen, V M; Le Hellard, S; Mattingsdal, M; Ntalla, I; Bencko, V; Foretova, L; Janout, V; Navratilova, M; Gallinger, S; Pinto, D; Scherer, S W; Aschauer, H; Carlberg, L; Schosser, A; Alfredsson, L; Ding, B; Klareskog, L; Padyukov, L; Courtet, P; Guillaume, S; Jaussent, I; Finan, C; Kalsi, G; Roberts, M; Logan, D W; Peltonen, L; Ritchie, G R S; Barrett, J C; Estivill, X; Hinney, A; Sullivan, P F; Collier, D A; Zeggini, E; Bulik, C M

2014-10-01

Anorexia nervosa (AN) is a complex and heritable eating disorder characterized by dangerously low body weight. Neither candidate gene studies nor an initial genome-wide association study (GWAS) have yielded significant and replicated results. We performed a GWAS in 2907 cases with AN from 14 countries (15 sites) and 14 860 ancestrally matched controls as part of the Genetic Consortium for AN (GCAN) and the Wellcome Trust Case Control Consortium 3 (WTCCC3). Individual association analyses were conducted in each stratum and meta-analyzed across all 15 discovery data sets. Seventy-six (72 independent) single nucleotide polymorphisms were taken forward for in silico (two data sets) or de novo (13 data sets) replication genotyping in 2677 independent AN cases and 8629 European ancestry controls along with 458 AN cases and 421 controls from Japan. The final global meta-analysis across discovery and replication data sets comprised 5551 AN cases and 21 080 controls. AN subtype analyses (1606 AN restricting; 1445 AN binge-purge) were performed. No findings reached genome-wide significance. Two intronic variants were suggestively associated: rs9839776 (P=3.01 × 10(-7)) in SOX2OT and rs17030795 (P=5.84 × 10(-6)) in PPP3CA. Two additional signals were specific to Europeans: rs1523921 (P=5.76 × 10(-)(6)) between CUL3 and FAM124B and rs1886797 (P=8.05 × 10(-)(6)) near SPATA13. Comparing discovery with replication results, 76% of the effects were in the same direction, an observation highly unlikely to be due to chance (P=4 × 10(-6)), strongly suggesting that true findings exist but our sample, the largest yet reported, was underpowered for their detection. The accrual of large genotyped AN case-control samples should be an immediate priority for the field.

The Association of Multiple Interacting Genes with Specific Phenotypes in Rice Using Gene Coexpression Networks1[C][W][OA

PubMed Central

Ficklin, Stephen P.; Luo, Feng; Feltus, F. Alex

2010-01-01

Discovering gene sets underlying the expression of a given phenotype is of great importance, as many phenotypes are the result of complex gene-gene interactions. Gene coexpression networks, built using a set of microarray samples as input, can help elucidate tightly coexpressed gene sets (modules) that are mixed with genes of known and unknown function. Functional enrichment analysis of modules further subdivides the coexpressed gene set into cofunctional gene clusters that may coexist in the module with other functionally related gene clusters. In this study, 45 coexpressed gene modules and 76 cofunctional gene clusters were discovered for rice (Oryza sativa) using a global, knowledge-independent paradigm and the combination of two network construction methodologies. Some clusters were enriched for previously characterized mutant phenotypes, providing evidence for specific gene sets (and their annotated molecular functions) that underlie specific phenotypes. PMID:20668062

The association of multiple interacting genes with specific phenotypes in rice using gene coexpression networks.

PubMed

Ficklin, Stephen P; Luo, Feng; Feltus, F Alex

2010-09-01

Discovering gene sets underlying the expression of a given phenotype is of great importance, as many phenotypes are the result of complex gene-gene interactions. Gene coexpression networks, built using a set of microarray samples as input, can help elucidate tightly coexpressed gene sets (modules) that are mixed with genes of known and unknown function. Functional enrichment analysis of modules further subdivides the coexpressed gene set into cofunctional gene clusters that may coexist in the module with other functionally related gene clusters. In this study, 45 coexpressed gene modules and 76 cofunctional gene clusters were discovered for rice (Oryza sativa) using a global, knowledge-independent paradigm and the combination of two network construction methodologies. Some clusters were enriched for previously characterized mutant phenotypes, providing evidence for specific gene sets (and their annotated molecular functions) that underlie specific phenotypes.

FT-midIR determination of fatty acid profiles, including trans fatty acids, in bakery products after focused microwave-assisted Soxhlet extraction.

PubMed

Ruiz-Jiménez, J; Priego-Capote, F; Luque de Castro, M D

2006-08-01

A study of the feasibility of Fourier transform medium infrared spectroscopy (FT-midIR) for analytical determination of fatty acid profiles, including trans fatty acids, is presented. The training and validation sets-75% (102 samples) and 25% (36 samples) of the samples once the spectral outliers have been removed-to develop FT-midIR general equations, were built with samples from 140 commercial and home-made bakery products. The concentration of the analytes in the samples used for this study is within the typical range found in these kinds of products. Both sets were independent; thus, the validation set was only used for testing the equations. The criterion used for the selection of the validation set was samples with the highest number of neighbours and the most separation between them (H<0.6). Partial least squares regression and cross validation were used for multivariate calibration. The FT-midIR method does not require post-extraction manipulation and gives information about the fatty acid profile in two min. The 14:0, 16:0, 18:0, 18:1 and 18:2 fatty acids can be determined with excellent precision and other fatty acids with good precision according to the Shenk criteria, R (2)>/=0.90, SEP=1-1.5 SEL and R (2)=0.70-0.89, SEP=2-3 SEL, respectively. The results obtained with the proposed method were compared with those provided by the conventional method based on GC-MS. At 95% significance level, the differences between the values obtained for the different fatty acids were within the experimental error.

Testate amoeba transfer function performance along localised hydrological gradients.

PubMed

Tsyganov, Andrey N; Mityaeva, Olga A; Mazei, Yuri A; Payne, Richard J

2016-09-01

Testate amoeba transfer functions are widely used for reconstruction of palaeo-hydrological regime in peatlands. However, the limitations of this approach have become apparent with increasing attention to validation and assessing sources of uncertainty. This paper investigates effects of peatland type and sampling depth on the performance of a transfer function using an independent test-set from four Sphagnum-dominated sites in European Russia (Penza Region). We focus on transfer function performance along localised hydrological gradients, which is a useful analogue for predictive ability through time. The performance of the transfer function with the independent test-set was generally weaker than for the leave-one-out or bootstrap cross-validations. However, the transfer function was robust for the reconstruction of relative changes in water-table depth, provided the presence of good modern analogues and overlap in water-table depth ranges. When applied to subsurface samples, the performance of the transfer function was reduced due to selective decomposition, the presence of deep-dwelling taxa or vertical transfer of shells. Our results stress the importance of thorough testing of transfer functions, and highlight the role of taphonomic processes in determining results. Further studies of stratification, taxonomy and taphonomy of testate amoebae will be needed to improve the robustness of transfer function output. Copyright © 2015 Elsevier GmbH. All rights reserved.

Mental Health and Associated Sexual Health Behaviours in a Sample of Young People Attending a Music Festival in Melbourne, Victoria.

PubMed

Carrotte, Elise R; Vella, Alyce M; Hellard, Margaret E; Lim, Megan S C

2016-11-01

Poor mental health has previously been associated with risky sexual health behaviours among young people internationally and in clinical samples, but little is known about this relationship in non-clinical settings. We conducted a cross-sectional survey with a convenience sample of 1345 Australians aged 15-29. Multivariable logistic regression was used to identify sexual health behaviours independently associated with recent poor mental health including contraception use, STI testing, sexting and age at first sexual intercourse. Recent poor mental health was reported by 29.7 % of participants and independently associated with female gender (OR 1.8; 95 % CI 1.4-2.4), not identifying as heterosexual (OR 3.0; 95 % CI 2.1-4.4) and young age at first sexual intercourse among female participants (OR 1.4; 95 % CI 1.0-2.0). Results suggest mental health is largely driven by variables other than sexual health behaviours, although youth mental health services should consider inclusion of sexual health promotion within the scope of their services.

Psychopathological symptoms in two generations of the same family: a cross-cultural comparison.

PubMed

Essau, Cecilia A; Ishikawa, Shin-Ichi; Sasagawa, Satoko; Otsui, Kanako; Sato, Hiroshi; Okajima, Isa; Georgiou, George A; O'Callaghan, Jean; Bray, Diane

2013-12-01

The main aims of the present study were to compare the frequency and correlates of psychopathological symptoms in two generations of the same family in Japan and in England. The sample included 689 adolescents and one of their parents/guardians. All participants completed a set of questionnaires to measure psychopathological symptoms, self-construals, and perceived social support. In both parent and adolescent data, the Japanese sample reported significantly lower psychopathological symptoms than the English sample. The relationship between parental and adolescent psychopathology was significant in England, but not in Japan. In both countries, perceived social support and independent self-construal were generally associated with less psychopathological symptoms, and interdependent self-construal was associated with more symptoms. Additionally, in England, a significant interaction effect was found between social support and the self-construals. Participants with low independent and high interdependent self-construal had elevated levels of psychopathological symptoms when perceived social support was low. The present study illustrates the importance of culture in the transmission of psychopathological symptoms across different generations in the same family.

Mapping a multiplexed zoo of mRNA expression.

PubMed

Choi, Harry M T; Calvert, Colby R; Husain, Naeem; Huss, David; Barsi, Julius C; Deverman, Benjamin E; Hunter, Ryan C; Kato, Mihoko; Lee, S Melanie; Abelin, Anna C T; Rosenthal, Adam Z; Akbari, Omar S; Li, Yuwei; Hay, Bruce A; Sternberg, Paul W; Patterson, Paul H; Davidson, Eric H; Mazmanian, Sarkis K; Prober, David A; van de Rijn, Matt; Leadbetter, Jared R; Newman, Dianne K; Readhead, Carol; Bronner, Marianne E; Wold, Barbara; Lansford, Rusty; Sauka-Spengler, Tatjana; Fraser, Scott E; Pierce, Niles A

2016-10-01

In situ hybridization methods are used across the biological sciences to map mRNA expression within intact specimens. Multiplexed experiments, in which multiple target mRNAs are mapped in a single sample, are essential for studying regulatory interactions, but remain cumbersome in most model organisms. Programmable in situ amplifiers based on the mechanism of hybridization chain reaction (HCR) overcome this longstanding challenge by operating independently within a sample, enabling multiplexed experiments to be performed with an experimental timeline independent of the number of target mRNAs. To assist biologists working across a broad spectrum of organisms, we demonstrate multiplexed in situ HCR in diverse imaging settings: bacteria, whole-mount nematode larvae, whole-mount fruit fly embryos, whole-mount sea urchin embryos, whole-mount zebrafish larvae, whole-mount chicken embryos, whole-mount mouse embryos and formalin-fixed paraffin-embedded human tissue sections. In addition to straightforward multiplexing, in situ HCR enables deep sample penetration, high contrast and subcellular resolution, providing an incisive tool for the study of interlaced and overlapping expression patterns, with implications for research communities across the biological sciences. © 2016. Published by The Company of Biologists Ltd.

Mapping a multiplexed zoo of mRNA expression

PubMed Central

Choi, Harry M. T.; Calvert, Colby R.; Husain, Naeem; Huss, David; Barsi, Julius C.; Deverman, Benjamin E.; Hunter, Ryan C.; Kato, Mihoko; Lee, S. Melanie; Abelin, Anna C. T.; Rosenthal, Adam Z.; Akbari, Omar S.; Li, Yuwei; Hay, Bruce A.; Sternberg, Paul W.; Patterson, Paul H.; Davidson, Eric H.; Mazmanian, Sarkis K.; Prober, David A.; van de Rijn, Matt; Leadbetter, Jared R.; Newman, Dianne K.; Readhead, Carol; Bronner, Marianne E.; Wold, Barbara; Lansford, Rusty; Sauka-Spengler, Tatjana; Fraser, Scott E.

2016-01-01

In situ hybridization methods are used across the biological sciences to map mRNA expression within intact specimens. Multiplexed experiments, in which multiple target mRNAs are mapped in a single sample, are essential for studying regulatory interactions, but remain cumbersome in most model organisms. Programmable in situ amplifiers based on the mechanism of hybridization chain reaction (HCR) overcome this longstanding challenge by operating independently within a sample, enabling multiplexed experiments to be performed with an experimental timeline independent of the number of target mRNAs. To assist biologists working across a broad spectrum of organisms, we demonstrate multiplexed in situ HCR in diverse imaging settings: bacteria, whole-mount nematode larvae, whole-mount fruit fly embryos, whole-mount sea urchin embryos, whole-mount zebrafish larvae, whole-mount chicken embryos, whole-mount mouse embryos and formalin-fixed paraffin-embedded human tissue sections. In addition to straightforward multiplexing, in situ HCR enables deep sample penetration, high contrast and subcellular resolution, providing an incisive tool for the study of interlaced and overlapping expression patterns, with implications for research communities across the biological sciences. PMID:27702788

Evaluation of a Serum Lung Cancer Biomarker Panel.

PubMed

Mazzone, Peter J; Wang, Xiao-Feng; Han, Xiaozhen; Choi, Humberto; Seeley, Meredith; Scherer, Richard; Doseeva, Victoria

2018-01-01

A panel of 3 serum proteins and 1 autoantibody has been developed to assist with the detection of lung cancer. We aimed to validate the accuracy of the biomarker panel in an independent test set and explore the impact of adding a fourth serum protein to the panel, as well as the impact of combining molecular and clinical variables. The training set of serum samples was purchased from commercially available biorepositories. The testing set was from a biorepository at the Cleveland Clinic. All lung cancer and control subjects were >50 years old and had smoked a minimum of 20 pack-years. A panel of biomarkers including CEA (carcinoembryonic antigen), CYFRA21-1 (cytokeratin-19 fragment 21-1), CA125 (carbohydrate antigen 125), HGF (hepatocyte growth factor), and NY-ESO-1 (New York esophageal cancer-1 antibody) was measured using immunoassay techniques. The multiple of the median method, multivariate logistic regression, and random forest modeling was used to analyze the results. The training set consisted of 604 patient samples (268 with lung cancer and 336 controls) and the testing set of 400 patient samples (155 with lung cancer and 245 controls). With a threshold established from the training set, the sensitivity and specificity of both the 4- and 5-biomarker panels on the testing set was 49% and 96%, respectively. Models built on the testing set using only clinical variables had an area under the receiver operating characteristic curve of 0.68, using the biomarker panel 0.81 and by combining clinical and biomarker variables 0.86. This study validates the accuracy of a panel of proteins and an autoantibody in a population relevant to lung cancer detection and suggests a benefit to combining clinical features with the biomarker results.

Evaluation of a Serum Lung Cancer Biomarker Panel

PubMed Central

Mazzone, Peter J; Wang, Xiao-Feng; Han, Xiaozhen; Choi, Humberto; Seeley, Meredith; Scherer, Richard; Doseeva, Victoria

2018-01-01

Background: A panel of 3 serum proteins and 1 autoantibody has been developed to assist with the detection of lung cancer. We aimed to validate the accuracy of the biomarker panel in an independent test set and explore the impact of adding a fourth serum protein to the panel, as well as the impact of combining molecular and clinical variables. Methods: The training set of serum samples was purchased from commercially available biorepositories. The testing set was from a biorepository at the Cleveland Clinic. All lung cancer and control subjects were >50 years old and had smoked a minimum of 20 pack-years. A panel of biomarkers including CEA (carcinoembryonic antigen), CYFRA21-1 (cytokeratin-19 fragment 21-1), CA125 (carbohydrate antigen 125), HGF (hepatocyte growth factor), and NY-ESO-1 (New York esophageal cancer-1 antibody) was measured using immunoassay techniques. The multiple of the median method, multivariate logistic regression, and random forest modeling was used to analyze the results. Results: The training set consisted of 604 patient samples (268 with lung cancer and 336 controls) and the testing set of 400 patient samples (155 with lung cancer and 245 controls). With a threshold established from the training set, the sensitivity and specificity of both the 4- and 5-biomarker panels on the testing set was 49% and 96%, respectively. Models built on the testing set using only clinical variables had an area under the receiver operating characteristic curve of 0.68, using the biomarker panel 0.81 and by combining clinical and biomarker variables 0.86. Conclusions: This study validates the accuracy of a panel of proteins and an autoantibody in a population relevant to lung cancer detection and suggests a benefit to combining clinical features with the biomarker results. PMID:29371783

Nurse practitioner organizational climate in primary care settings: implications for professional practice.

PubMed

Poghosyan, Lusine; Nannini, Angela; Stone, Patricia W; Smaldone, Arlene

2013-01-01

The expansion of the nurse practitioner (NP) workforce in primary care is key to meeting the increased demand for care. Organizational climates in primary care settings affect NP professional practice and the quality of care. This study investigated organizational climate and its domains affecting NP professional practice in primary care settings. A qualitative descriptive design, with purposive sampling, was used to recruit 16 NPs practicing in primary care settings in Massachusetts. An interview guide was developed and pretested with two NPs and in 1 group interview with 7 NPs. Data collection took place in spring of 2011. Individual interviews lasted from 30-70 minutes, were audio recorded, and transcribed. Data were analyzed using Atlas.ti 6.0 software by 3 researchers. Content analysis was applied. Three previously identified themes, NP-physician relations, independent practice and autonomy, and professional visibility, as well as two new themes, organizational support and resources and NP-administration relations emerged from the analyses. NPs reported collegial relations with physicians, challenges in establishing independent practice, suboptimal relationships with administration, and lack of support. NP contributions to patient care were invisible. Favorable organizational climates should be promoted to support the expanding of NP workforce in primary care and to optimize recruitment and retention efforts. © 2013.

Using near infrared spectroscopy to classify soybean oil according to expiration date.

PubMed

da Costa, Gean Bezerra; Fernandes, David Douglas Sousa; Gomes, Adriano A; de Almeida, Valber Elias; Veras, Germano

2016-04-01

A rapid and non-destructive methodology is proposed for the screening of edible vegetable oils according to conservation state expiration date employing near infrared (NIR) spectroscopy and chemometric tools. A total of fifty samples of soybean vegetable oil, of different brands andlots, were used in this study; these included thirty expired and twenty non-expired samples. The oil oxidation was measured by peroxide index. NIR spectra were employed in raw form and preprocessed by offset baseline correction and Savitzky-Golay derivative procedure, followed by PCA exploratory analysis, which showed that NIR spectra would be suitable for the classification task of soybean oil samples. The classification models were based in SPA-LDA (Linear Discriminant Analysis coupled with Successive Projection Algorithm) and PLS-DA (Discriminant Analysis by Partial Least Squares). The set of samples (50) was partitioned into two groups of training (35 samples: 15 non-expired and 20 expired) and test samples (15 samples 5 non-expired and 10 expired) using sample-selection approaches: (i) Kennard-Stone, (ii) Duplex, and (iii) Random, in order to evaluate the robustness of the models. The obtained results for the independent test set (in terms of correct classification rate) were 96% and 98% for SPA-LDA and PLS-DA, respectively, indicating that the NIR spectra can be used as an alternative to evaluate the degree of oxidation of soybean oil samples. Copyright © 2015 Elsevier Ltd. All rights reserved.

Striking the Right Balance: Police Experience, Perceptions and Use of Independent Support Persons During Interviews Involving People with Intellectual Disability.

PubMed

Henshaw, Marie; Spivak, Benjamin; Thomas, Stuart D M

2018-03-01

Several jurisdictions mandate the presence of an independent support person during police interviews with vulnerable people. The current study investigated police officers' experiences and perceptions of these volunteers during interviews with people with intellectual disability(ies) (ID). The sample comprised 229 police officers who attended a mandatory firearms training course in Melbourne, Australia, in 2010. Participants commonly reported utilizing independent support persons and displayed a fair understanding of their role. Overall, volunteers were engaged more frequently than family/friends; police considered the volunteers to be more impartial during interviews, whereas family/friends provided a greater level of emotional support to interviewees. Independent support persons need to demonstrate two quite different types of support to people with intellectual disability(ies) during police interviews; these require quite different skill sets and suggest the need for more tailored training and support for these volunteers. Implications for future research and policy are discussed. © 2016 John Wiley & Sons Ltd.

Automated Validation of Results and Removal of Fragment Ion Interferences in Targeted Analysis of Data-independent Acquisition Mass Spectrometry (MS) using SWATHProphet*

PubMed Central

Keller, Andrew; Bader, Samuel L.; Shteynberg, David; Hood, Leroy; Moritz, Robert L.

2015-01-01

Proteomics by mass spectrometry technology is widely used for identifying and quantifying peptides and proteins. The breadth and sensitivity of peptide detection have been advanced by the advent of data-independent acquisition mass spectrometry. Analysis of such data, however, is challenging due to the complexity of fragment ion spectra that have contributions from multiple co-eluting precursor ions. We present SWATHProphet software that identifies and quantifies peptide fragment ion traces in data-independent acquisition data, provides accurate probabilities to ensure results are correct, and automatically detects and removes contributions to quantitation originating from interfering precursor ions. Integration in the widely used open source Trans-Proteomic Pipeline facilitates subsequent analyses such as combining results of multiple data sets together for improved discrimination using iProphet and inferring sample proteins using ProteinProphet. This novel development should greatly help make data-independent acquisition mass spectrometry accessible to large numbers of users. PMID:25713123

A Nasal Brush-based Classifier of Asthma Identified by Machine Learning Analysis of Nasal RNA Sequence Data.

PubMed

Pandey, Gaurav; Pandey, Om P; Rogers, Angela J; Ahsen, Mehmet E; Hoffman, Gabriel E; Raby, Benjamin A; Weiss, Scott T; Schadt, Eric E; Bunyavanich, Supinda

2018-06-11

Asthma is a common, under-diagnosed disease affecting all ages. We sought to identify a nasal brush-based classifier of mild/moderate asthma. 190 subjects with mild/moderate asthma and controls underwent nasal brushing and RNA sequencing of nasal samples. A machine learning-based pipeline identified an asthma classifier consisting of 90 genes interpreted via an L2-regularized logistic regression classification model. This classifier performed with strong predictive value and sensitivity across eight test sets, including (1) a test set of independent asthmatic and control subjects profiled by RNA sequencing (positive and negative predictive values of 1.00 and 0.96, respectively; AUC of 0.994), (2) two independent case-control cohorts of asthma profiled by microarray, and (3) five cohorts with other respiratory conditions (allergic rhinitis, upper respiratory infection, cystic fibrosis, smoking), where the classifier had a low to zero misclassification rate. Following validation in large, prospective cohorts, this classifier could be developed into a nasal biomarker of asthma.

Discrimination of whisky brands and counterfeit identification by UV-Vis spectroscopy and multivariate data analysis.

PubMed

Martins, Angélica Rocha; Talhavini, Márcio; Vieira, Maurício Leite; Zacca, Jorge Jardim; Braga, Jez Willian Batista

2017-08-15

The discrimination of whisky brands and counterfeit identification were performed by UV-Vis spectroscopy combined with partial least squares for discriminant analysis (PLS-DA). In the proposed method all spectra were obtained with no sample preparation. The discrimination models were built with the employment of seven whisky brands: Red Label, Black Label, White Horse, Chivas Regal (12years), Ballantine's Finest, Old Parr and Natu Nobilis. The method was validated with an independent test set of authentic samples belonging to the seven selected brands and another eleven brands not included in the training samples. Furthermore, seventy-three counterfeit samples were also used to validate the method. Results showed correct classification rates for genuine and false samples over 98.6% and 93.1%, respectively, indicating that the method can be helpful for the forensic analysis of whisky samples. Copyright © 2017 Elsevier Ltd. All rights reserved.

Goal commitment and the goal-setting process: conceptual clarification and empirical synthesis.

PubMed

Klein, H J; Wesson, M J; Hollenbeck, J R; Alge, B J

1999-12-01

Goals are central to current treatments of work motivation, and goal commitment is a critical construct in understanding the relationship between goals and task performance. Despite this importance, there is confusion about the role of goal commitment and only recently has this key construct received the empirical attention it warrants. This meta-analysis, based on 83 independent samples, updates the goal commitment literature by summarizing the accumulated evidence on the antecedents and consequences of goal commitment. Using this aggregate empirical evidence, the role of goal commitment in the goal-setting process is clarified and key areas for future research are identified.

[Determination of soluble solids content in Nanfeng Mandarin by Vis/NIR spectroscopy and UVE-ICA-LS-SVM].

PubMed

Sun, Tong; Xu, Wen-Li; Hu, Tian; Liu, Mu-Hua

2013-12-01

The objective of the present research was to assess soluble solids content (SSC) of Nanfeng mandarin by visible/near infrared (Vis/NIR) spectroscopy combined with new variable selection method, simplify prediction model and improve the performance of prediction model for SSC of Nanfeng mandarin. A total of 300 Nanfeng mandarin samples were used, the numbers of Nanfeng mandarin samples in calibration, validation and prediction sets were 150, 75 and 75, respectively. Vis/NIR spectra of Nanfeng mandarin samples were acquired by a QualitySpec spectrometer in the wavelength range of 350-1000 nm. Uninformative variables elimination (UVE) was used to eliminate wavelength variables that had few information of SSC, then independent component analysis (ICA) was used to extract independent components (ICs) from spectra that eliminated uninformative wavelength variables. At last, least squares support vector machine (LS-SVM) was used to develop calibration models for SSC of Nanfeng mandarin using extracted ICs, and 75 prediction samples that had not been used for model development were used to evaluate the performance of SSC model of Nanfeng mandarin. The results indicate t hat Vis/NIR spectroscopy combinedwith UVE-ICA-LS-SVM is suitable for assessing SSC o f Nanfeng mandarin, and t he precision o f prediction ishigh. UVE--ICA is an effective method to eliminate uninformative wavelength variables, extract important spectral information, simplify prediction model and improve the performance of prediction model. The SSC model developed by UVE-ICA-LS-SVM is superior to that developed by PLS, PCA-LS-SVM or ICA-LS-SVM, and the coefficient of determination and root mean square error in calibration, validation and prediction sets were 0.978, 0.230%, 0.965, 0.301% and 0.967, 0.292%, respectively.

Protein and glycomic plasma markers for early detection of adenoma and colon cancer.

PubMed

Rho, Jung-Hyun; Ladd, Jon J; Li, Christopher I; Potter, John D; Zhang, Yuzheng; Shelley, David; Shibata, David; Coppola, Domenico; Yamada, Hiroyuki; Toyoda, Hidenori; Tada, Toshifumi; Kumada, Takashi; Brenner, Dean E; Hanash, Samir M; Lampe, Paul D

2018-03-01

To discover and confirm blood-based colon cancer early-detection markers. We created a high-density antibody microarray to detect differences in protein levels in plasma from individuals diagnosed with colon cancer <3 years after blood was drawn (ie, prediagnostic) and cancer-free, matched controls. Potential markers were tested on plasma samples from people diagnosed with adenoma or cancer, compared with controls. Components of an optimal 5-marker panel were tested via immunoblotting using a third sample set, Luminex assay in a large fourth sample set and immunohistochemistry (IHC) on tissue microarrays. In the prediagnostic samples, we found 78 significantly (t-test) increased proteins, 32 of which were confirmed in the diagnostic samples. From these 32, optimal 4-marker panels of BAG family molecular chaperone regulator 4 (BAG4), interleukin-6 receptor subunit beta (IL6ST), von Willebrand factor (VWF) and CD44 or epidermal growth factor receptor (EGFR) were established. Each panel member and the panels also showed increases in the diagnostic adenoma and cancer samples in independent third and fourth sample sets via immunoblot and Luminex, respectively. IHC results showed increased levels of BAG4, IL6ST and CD44 in adenoma and cancer tissues. Inclusion of EGFR and CD44 sialyl Lewis-A and Lewis-X content increased the panel performance. The protein/glycoprotein panel was statistically significantly higher in colon cancer samples, characterised by a range of area under the curves from 0.90 (95% CI 0.82 to 0.98) to 0.86 (95% CI 0.83 to 0.88), for the larger second and fourth sets, respectively. A panel including BAG4, IL6ST, VWF, EGFR and CD44 protein/glycomics performed well for detection of early stages of colon cancer and should be further examined in larger studies. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Serum Autoantibodies in Chronic Prostate Inflammation in Prostate Cancer Patients.

PubMed

Schlick, Bettina; Massoner, Petra; Lueking, Angelika; Charoentong, Pornpimol; Blattner, Mirjam; Schaefer, Georg; Marquart, Klaus; Theek, Carmen; Amersdorfer, Peter; Zielinski, Dirk; Kirchner, Matthias; Trajanoski, Zlatko; Rubin, Mark A; Müllner, Stefan; Schulz-Knappe, Peter; Klocker, Helmut

2016-01-01

Chronic inflammation is frequently observed on histological analysis of malignant and non-malignant prostate specimens. It is a suspected supporting factor for prostate diseases and their progression and a main cause of false positive PSA tests in cancer screening. We hypothesized that inflammation induces autoantibodies, which may be useful biomarkers. We aimed to identify and validate prostate inflammation associated serum autoantibodies in prostate cancer patients and evaluate the expression of corresponding autoantigens. Radical prostatectomy specimens of prostate cancer patients (N = 70) were classified into high and low inflammation groups according to the amount of tissue infiltrating lymphocytes. The corresponding pre-surgery blood serum samples were scrutinized for autoantibodies using a low-density protein array. Selected autoantigens were identified in prostate tissue and their expression pattern analyzed by immunohistochemistry and qPCR. The identified autoantibody profile was cross-checked in an independent sample set (N = 63) using the Luminex-bead protein array technology. Protein array screening identified 165 autoantibodies differentially abundant in the serum of high compared to low inflammation patients. The expression pattern of three corresponding antigens were established in benign and cancer tissue by immunohistochemistry and qPCR: SPAST (Spastin), STX18 (Syntaxin 18) and SPOP (speckle-type POZ protein). Of these, SPAST was significantly increased in prostate tissue with high inflammation. All three autoantigens were differentially expressed in primary and/or castration resistant prostate tumors when analyzed in an inflammation-independent tissue microarray. Cross-validation of the inflammation autoantibody profile on an independent sample set using a Luminex-bead protein array, retrieved 51 of the significantly discriminating autoantibodies. Three autoantibodies were significantly upregulated in both screens, MUT, RAB11B and CSRP2 (p>0.05), two, SPOP and ZNF671, close to statistical significance (p = 0.051 and 0.076). We provide evidence of an inflammation-specific autoantibody profile and confirm the expression of corresponding autoantigens in prostate tissue. This supports evaluation of autoantibodies as non-invasive markers for prostate inflammation.

The performance of seven QPrediction risk scores in an independent external sample of patients from general practice: a validation study

PubMed Central

Hippisley-Cox, Julia; Coupland, Carol; Brindle, Peter

2014-01-01

Objectives To validate the performance of a set of risk prediction algorithms developed using the QResearch database, in an independent sample from general practices contributing to the Clinical Research Data Link (CPRD). Setting Prospective open cohort study using practices contributing to the CPRD database and practices contributing to the QResearch database. Participants The CPRD validation cohort consisted of 3.3 million patients, aged 25–99 years registered at 357 general practices between 1 Jan 1998 and 31 July 2012. The validation statistics for QResearch were obtained from the original published papers which used a one-third sample of practices separate to those used to derive the score. A cohort from QResearch was used to compare incidence rates and baseline characteristics and consisted of 6.8 million patients from 753 practices registered between 1 Jan 1998 and until 31 July 2013. Outcome measures Incident events relating to seven different risk prediction scores: QRISK2 (cardiovascular disease); QStroke (ischaemic stroke); QDiabetes (type 2 diabetes); QFracture (osteoporotic fracture and hip fracture); QKidney (moderate and severe kidney failure); QThrombosis (venous thromboembolism); QBleed (intracranial bleed and upper gastrointestinal haemorrhage). Measures of discrimination and calibration were calculated. Results Overall, the baseline characteristics of the CPRD and QResearch cohorts were similar though QResearch had higher recording levels for ethnicity and family history. The validation statistics for each of the risk prediction scores were very similar in the CPRD cohort compared with the published results from QResearch validation cohorts. For example, in women, the QDiabetes algorithm explained 50% of the variation within CPRD compared with 51% on QResearch and the receiver operator curve value was 0.85 on both databases. The scores were well calibrated in CPRD. Conclusions Each of the algorithms performed practically as well in the external independent CPRD validation cohorts as they had in the original published QResearch validation cohorts. PMID:25168040

Serum Autoantibodies in Chronic Prostate Inflammation in Prostate Cancer Patients

PubMed Central

Schlick, Bettina; Massoner, Petra; Lueking, Angelika; Charoentong, Pornpimol; Blattner, Mirjam; Schaefer, Georg; Marquart, Klaus; Theek, Carmen; Amersdorfer, Peter; Zielinski, Dirk; Kirchner, Matthias; Trajanoski, Zlatko; Rubin, Mark A.; Müllner, Stefan; Schulz-Knappe, Peter; Klocker, Helmut

2016-01-01

Background Chronic inflammation is frequently observed on histological analysis of malignant and non-malignant prostate specimens. It is a suspected supporting factor for prostate diseases and their progression and a main cause of false positive PSA tests in cancer screening. We hypothesized that inflammation induces autoantibodies, which may be useful biomarkers. We aimed to identify and validate prostate inflammation associated serum autoantibodies in prostate cancer patients and evaluate the expression of corresponding autoantigens. Methods Radical prostatectomy specimens of prostate cancer patients (N = 70) were classified into high and low inflammation groups according to the amount of tissue infiltrating lymphocytes. The corresponding pre-surgery blood serum samples were scrutinized for autoantibodies using a low-density protein array. Selected autoantigens were identified in prostate tissue and their expression pattern analyzed by immunohistochemistry and qPCR. The identified autoantibody profile was cross-checked in an independent sample set (N = 63) using the Luminex-bead protein array technology. Results Protein array screening identified 165 autoantibodies differentially abundant in the serum of high compared to low inflammation patients. The expression pattern of three corresponding antigens were established in benign and cancer tissue by immunohistochemistry and qPCR: SPAST (Spastin), STX18 (Syntaxin 18) and SPOP (speckle-type POZ protein). Of these, SPAST was significantly increased in prostate tissue with high inflammation. All three autoantigens were differentially expressed in primary and/or castration resistant prostate tumors when analyzed in an inflammation-independent tissue microarray. Cross-validation of the inflammation autoantibody profile on an independent sample set using a Luminex-bead protein array, retrieved 51 of the significantly discriminating autoantibodies. Three autoantibodies were significantly upregulated in both screens, MUT, RAB11B and CSRP2 (p>0.05), two, SPOP and ZNF671, close to statistical significance (p = 0.051 and 0.076). Conclusions We provide evidence of an inflammation-specific autoantibody profile and confirm the expression of corresponding autoantigens in prostate tissue. This supports evaluation of autoantibodies as non-invasive markers for prostate inflammation. PMID:26863016

Faulting of rocks in three-dimensional strain fields I. Failure of rocks in polyaxial, servo-control experiments

USGS Publications Warehouse

Reches, Z.; Dieterich, J.H.

1983-01-01

The dependence of the number of sets of faults and their orientation on the intermediate strain axis is investigated through polyaxial tests, reported here, and theoretical analysis, reported in an accompanying paper. In the experiments, cubic samples of Berea sandstone, Sierra-White and Westerly granites, and Candoro and Solnhofen limestones were loaded on their three pairs of faces by three independent, mutually perpendicular presses at room temperature. Two of the presses were servo-controlled and applied constant displacement rates throughout the experiment. Most samples display three or four sets of faults in orthorhombic symmetry. These faults form in several yielding events that follow a stage of elastic deformation. In many experiments, the maximum and the intermediate compressive stresses interchange orientations during the yielding events, where the corresponding strains are constant. The final stage of most experiments is characterized by slip along the faults. ?? 1983.

Faulting of rocks in three-dimensional strain fields I. Failure of rocks in polyaxial, servo-control experiments

NASA Astrophysics Data System (ADS)

Reches, Ze'ev; Dieterich, James H.

1983-05-01

The dependence of the number of sets of faults and their orientation on the intermediate strain axis is investigated through polyaxial tests, reported here, and theoretical analysis, reported in an accompanying paper. In the experiments, cubic samples of Berea sandstone, Sierra-White and Westerly granites, and Candoro and Solnhofen limestones were loaded on their three pairs of faces by three independent, mutually perpendicular presses at room temperature. Two of the presses were servo-controlled and applied constant displacement rates throughout the experiment. Most samples display three or four sets of faults in orthorhombic symmetry. These faults form in several yielding events that follow a stage of elastic deformation. In many experiments, the maximum and the intermediate compressive stresses interchange orientations during the yielding events, where the corresponding strains are constant. The final stage of most experiments is characterized by slip along the faults.

A Geographic Cline of Skull and Brain Morphology among Individuals of European Ancestry

PubMed Central

Bakken, Trygve E.; Dale, Anders M.; Schork, Nicholas J.

2011-01-01

Background Human skull and brain morphology are strongly influenced by genetic factors, and skull size and shape vary worldwide. However, the relationship between specific brain morphology and genetically-determined ancestry is largely unknown. Methods We used two independent data sets to characterize variation in skull and brain morphology among individuals of European ancestry. The first data set is a historical sample of 1,170 male skulls with 37 shape measurements drawn from 27 European populations. The second data set includes 626 North American individuals of European ancestry participating in the Alzheimer's Disease Neuroimaging Initiative (ADNI) with magnetic resonance imaging, height and weight, neurological diagnosis, and genome-wide single nucleotide polymorphism (SNP) data. Results We found that both skull and brain morphological variation exhibit a population-genetic fingerprint among individuals of European ancestry. This fingerprint shows a Northwest to Southeast gradient, is independent of body size, and involves frontotemporal cortical regions. Conclusion Our findings are consistent with prior evidence for gene flow in Europe due to historical population movements and indicate that genetic background should be considered in studies seeking to identify genes involved in human cortical development and neuropsychiatric disease. PMID:21849792

Identification and validation of biomarkers of IgV(H) mutation status in chronic lymphocytic leukemia using microfluidics quantitative real-time polymerase chain reaction technology.

PubMed

Abruzzo, Lynne V; Barron, Lynn L; Anderson, Keith; Newman, Rachel J; Wierda, William G; O'brien, Susan; Ferrajoli, Alessandra; Luthra, Madan; Talwalkar, Sameer; Luthra, Rajyalakshmi; Jones, Dan; Keating, Michael J; Coombes, Kevin R

2007-09-01

To develop a model incorporating relevant prognostic biomarkers for untreated chronic lymphocytic leukemia patients, we re-analyzed the raw data from four published gene expression profiling studies. We selected 88 candidate biomarkers linked to immunoglobulin heavy-chain variable region gene (IgV(H)) mutation status and produced a reliable and reproducible microfluidics quantitative real-time polymerase chain reaction array. We applied this array to a training set of 29 purified samples from previously untreated patients. In an unsupervised analysis, the samples clustered into two groups. Using a cutoff point of 2% homology to the germline IgV(H) sequence, one group contained all 14 IgV(H)-unmutated samples; the other contained all 15 mutated samples. We confirmed the differential expression of 37 of the candidate biomarkers using two-sample t-tests. Next, we constructed 16 different models to predict IgV(H) mutation status and evaluated their performance on an independent test set of 20 new samples. Nine models correctly classified 11 of 11 IgV(H)-mutated cases and eight of nine IgV(H)-unmutated cases, with some models using three to seven genes. Thus, we can classify cases with 95% accuracy based on the expression of as few as three genes.

Sample-independent approach to normalize two-dimensional data for orthogonality evaluation using whole separation space scaling.

PubMed

Jáčová, Jaroslava; Gardlo, Alžběta; Friedecký, David; Adam, Tomáš; Dimandja, Jean-Marie D

2017-08-18

Orthogonality is a key parameter that is used to evaluate the separation power of chromatography-based two-dimensional systems. It is necessary to scale the separation data before the assessment of the orthogonality. Current scaling approaches are sample-dependent, and the extent of the retention space that is converted into a normalized retention space is set according to the retention times of the first and last analytes contained in a unique sample to elute. The presence or absence of a highly retained analyte in a sample can thus significantly influence the amount of information (in terms of the total amount of separation space) contained in the normalized retention space considered for the calculation of the orthogonality. We propose a Whole Separation Space Scaling (WOSEL) approach that accounts for the whole separation space delineated by the analytical method, and not the sample. This approach enables an orthogonality-based evaluation of the efficiency of the analytical system that is independent of the sample selected. The WOSEL method was compared to two currently used orthogonality approaches through the evaluation of in silico-generated chromatograms and real separations of human biofluids and petroleum samples. WOSEL exhibits sample-to-sample stability values of 3.8% on real samples, compared to 7.0% and 10.1% for the two other methods, respectively. Using real analyses, we also demonstrate that some previously developed approaches can provide misleading conclusions on the overall orthogonality of a two-dimensional chromatographic system. Copyright © 2017 Elsevier B.V. All rights reserved.

An early-biomarker algorithm predicts lethal graft-versus-host disease and survival

PubMed Central

Hartwell, Matthew J.; Özbek, Umut; Holler, Ernst; Major-Monfried, Hannah; Reddy, Pavan; Aziz, Mina; Hogan, William J.; Ayuk, Francis; Efebera, Yvonne A.; Hexner, Elizabeth O.; Bunworasate, Udomsak; Qayed, Muna; Ordemann, Rainer; Wölfl, Matthias; Mielke, Stephan; Chen, Yi-Bin; Devine, Steven; Jagasia, Madan; Kitko, Carrie L.; Litzow, Mark R.; Kröger, Nicolaus; Locatelli, Franco; Morales, George; Nakamura, Ryotaro; Reshef, Ran; Rösler, Wolf; Weber, Daniela; Yanik, Gregory A.; Levine, John E.; Ferrara, James L.M.

2017-01-01

BACKGROUND. No laboratory test can predict the risk of nonrelapse mortality (NRM) or severe graft-versus-host disease (GVHD) after hematopoietic cellular transplantation (HCT) prior to the onset of GVHD symptoms. METHODS. Patient blood samples on day 7 after HCT were obtained from a multicenter set of 1,287 patients, and 620 samples were assigned to a training set. We measured the concentrations of 4 GVHD biomarkers (ST2, REG3α, TNFR1, and IL-2Rα) and used them to model 6-month NRM using rigorous cross-validation strategies to identify the best algorithm that defined 2 distinct risk groups. We then applied the final algorithm in an independent test set (n = 309) and validation set (n = 358). RESULTS. A 2-biomarker model using ST2 and REG3α concentrations identified patients with a cumulative incidence of 6-month NRM of 28% in the high-risk group and 7% in the low-risk group (P < 0.001). The algorithm performed equally well in the test set (33% vs. 7%, P < 0.001) and the multicenter validation set (26% vs. 10%, P < 0.001). Sixteen percent, 17%, and 20% of patients were at high risk in the training, test, and validation sets, respectively. GVHD-related mortality was greater in high-risk patients (18% vs. 4%, P < 0.001), as was severe gastrointestinal GVHD (17% vs. 8%, P < 0.001). The same algorithm can be successfully adapted to define 3 distinct risk groups at GVHD onset. CONCLUSION. A biomarker algorithm based on a blood sample taken 7 days after HCT can consistently identify a group of patients at high risk for lethal GVHD and NRM. FUNDING. The National Cancer Institute, American Cancer Society, and the Doris Duke Charitable Foundation. PMID:28194439

Validation of the Lung Subtyping Panel in Multiple Fresh-Frozen and Formalin-Fixed, Paraffin-Embedded Lung Tumor Gene Expression Data Sets.

PubMed

Faruki, Hawazin; Mayhew, Gregory M; Fan, Cheng; Wilkerson, Matthew D; Parker, Scott; Kam-Morgan, Lauren; Eisenberg, Marcia; Horten, Bruce; Hayes, D Neil; Perou, Charles M; Lai-Goldman, Myla

2016-06-01

Context .- A histologic classification of lung cancer subtypes is essential in guiding therapeutic management. Objective .- To complement morphology-based classification of lung tumors, a previously developed lung subtyping panel (LSP) of 57 genes was tested using multiple public fresh-frozen gene-expression data sets and a prospectively collected set of formalin-fixed, paraffin-embedded lung tumor samples. Design .- The LSP gene-expression signature was evaluated in multiple lung cancer gene-expression data sets totaling 2177 patients collected from 4 platforms: Illumina RNAseq (San Diego, California), Agilent (Santa Clara, California) and Affymetrix (Santa Clara) microarrays, and quantitative reverse transcription-polymerase chain reaction. Gene centroids were calculated for each of 3 genomic-defined subtypes: adenocarcinoma, squamous cell carcinoma, and neuroendocrine, the latter of which encompassed both small cell carcinoma and carcinoid. Classification by LSP into 3 subtypes was evaluated in both fresh-frozen and formalin-fixed, paraffin-embedded tumor samples, and agreement with the original morphology-based diagnosis was determined. Results .- The LSP-based classifications demonstrated overall agreement with the original clinical diagnosis ranging from 78% (251 of 322) to 91% (492 of 538 and 869 of 951) in the fresh-frozen public data sets and 84% (65 of 77) in the formalin-fixed, paraffin-embedded data set. The LSP performance was independent of tissue-preservation method and gene-expression platform. Secondary, blinded pathology review of formalin-fixed, paraffin-embedded samples demonstrated concordance of 82% (63 of 77) with the original morphology diagnosis. Conclusions .- The LSP gene-expression signature is a reproducible and objective method for classifying lung tumors and demonstrates good concordance with morphology-based classification across multiple data sets. The LSP panel can supplement morphologic assessment of lung cancers, particularly when classification by standard methods is challenging.

Power and instrument strength requirements for Mendelian randomization studies using multiple genetic variants.

PubMed

Pierce, Brandon L; Ahsan, Habibul; Vanderweele, Tyler J

2011-06-01

Mendelian Randomization (MR) studies assess the causality of an exposure-disease association using genetic determinants [i.e. instrumental variables (IVs)] of the exposure. Power and IV strength requirements for MR studies using multiple genetic variants have not been explored. We simulated cohort data sets consisting of a normally distributed disease trait, a normally distributed exposure, which affects this trait and a biallelic genetic variant that affects the exposure. We estimated power to detect an effect of exposure on disease for varying allele frequencies, effect sizes and samples sizes (using two-stage least squares regression on 10,000 data sets-Stage 1 is a regression of exposure on the variant. Stage 2 is a regression of disease on the fitted exposure). Similar analyses were conducted using multiple genetic variants (5, 10, 20) as independent or combined IVs. We assessed IV strength using the first-stage F statistic. Simulations of realistic scenarios indicate that MR studies will require large (n > 1000), often very large (n > 10,000), sample sizes. In many cases, so-called 'weak IV' problems arise when using multiple variants as independent IVs (even with as few as five), resulting in biased effect estimates. Combining genetic factors into fewer IVs results in modest power decreases, but alleviates weak IV problems. Ideal methods for combining genetic factors depend upon knowledge of the genetic architecture underlying the exposure. The feasibility of well-powered, unbiased MR studies will depend upon the amount of variance in the exposure that can be explained by known genetic factors and the 'strength' of the IV set derived from these genetic factors.

Communication: importance sampling including path correlation in semiclassical initial value representation calculations for time correlation functions.

PubMed

Pan, Feng; Tao, Guohua

2013-03-07

Full semiclassical (SC) initial value representation (IVR) for time correlation functions involves a double phase space average over a set of two phase points, each of which evolves along a classical path. Conventionally, the two initial phase points are sampled independently for all degrees of freedom (DOF) in the Monte Carlo procedure. Here, we present an efficient importance sampling scheme by including the path correlation between the two initial phase points for the bath DOF, which greatly improves the performance of the SC-IVR calculations for large molecular systems. Satisfactory convergence in the study of quantum coherence in vibrational relaxation has been achieved for a benchmark system-bath model with up to 21 DOF.

Development of a universal metabolome-standard method for long-term LC-MS metabolome profiling and its application for bladder cancer urine-metabolite-biomarker discovery.

PubMed

Peng, Jun; Chen, Yi-Ting; Chen, Chien-Lun; Li, Liang

2014-07-01

Large-scale metabolomics study requires a quantitative method to generate metabolome data over an extended period with high technical reproducibility. We report a universal metabolome-standard (UMS) method, in conjunction with chemical isotope labeling liquid chromatography-mass spectrometry (LC-MS), to provide long-term analytical reproducibility and facilitate metabolome comparison among different data sets. In this method, UMS of a specific type of sample labeled by an isotope reagent is prepared a priori. The UMS is spiked into any individual samples labeled by another form of the isotope reagent in a metabolomics study. The resultant mixture is analyzed by LC-MS to provide relative quantification of the individual sample metabolome to UMS. UMS is independent of a study undertaking as well as the time of analysis and useful for profiling the same type of samples in multiple studies. In this work, the UMS method was developed and applied for a urine metabolomics study of bladder cancer. UMS of human urine was prepared by (13)C2-dansyl labeling of a pooled sample from 20 healthy individuals. This method was first used to profile the discovery samples to generate a list of putative biomarkers potentially useful for bladder cancer detection and then used to analyze the verification samples about one year later. Within the discovery sample set, three-month technical reproducibility was examined using a quality control sample and found a mean CV of 13.9% and median CV of 9.4% for all the quantified metabolites. Statistical analysis of the urine metabolome data showed a clear separation between the bladder cancer group and the control group from the discovery samples, which was confirmed by the verification samples. Receiver operating characteristic (ROC) test showed that the area under the curve (AUC) was 0.956 in the discovery data set and 0.935 in the verification data set. These results demonstrated the utility of the UMS method for long-term metabolomics and discovering potential metabolite biomarkers for diagnosis of bladder cancer.

Chemometric brand differentiation of commercial spices using direct analysis in real time mass spectrometry.

PubMed

Pavlovich, Matthew J; Dunn, Emily E; Hall, Adam B

2016-05-15

Commercial spices represent an emerging class of fuels for improvised explosives. Being able to classify such spices not only by type but also by brand would represent an important step in developing methods to analytically investigate these explosive compositions. Therefore, a combined ambient mass spectrometric/chemometric approach was developed to quickly and accurately classify commercial spices by brand. Direct analysis in real time mass spectrometry (DART-MS) was used to generate mass spectra for samples of black pepper, cayenne pepper, and turmeric, along with four different brands of cinnamon, all dissolved in methanol. Unsupervised learning techniques showed that the cinnamon samples clustered according to brand. Then, we used supervised machine learning algorithms to build chemometric models with a known training set and classified the brands of an unknown testing set of cinnamon samples. Ten independent runs of five-fold cross-validation showed that the training set error for the best-performing models (i.e., the linear discriminant and neural network models) was lower than 2%. The false-positive percentages for these models were 3% or lower, and the false-negative percentages were lower than 10%. In particular, the linear discriminant model perfectly classified the testing set with 0% error. Repeated iterations of training and testing gave similar results, demonstrating the reproducibility of these models. Chemometric models were able to classify the DART mass spectra of commercial cinnamon samples according to brand, with high specificity and low classification error. This method could easily be generalized to other classes of spices, and it could be applied to authenticating questioned commercial samples of spices or to examining evidence from improvised explosives. Copyright © 2016 John Wiley & Sons, Ltd.

Parameter Optimization for Feature and Hit Generation in a General Unknown Screening Method-Proof of Concept Study Using a Design of Experiment Approach for a High Resolution Mass Spectrometry Procedure after Data Independent Acquisition.

PubMed

Elmiger, Marco P; Poetzsch, Michael; Steuer, Andrea E; Kraemer, Thomas

2018-03-06

High resolution mass spectrometry and modern data independent acquisition (DIA) methods enable the creation of general unknown screening (GUS) procedures. However, even when DIA is used, its potential is far from being exploited, because often, the untargeted acquisition is followed by a targeted search. Applying an actual GUS (including untargeted screening) produces an immense amount of data that must be dealt with. An optimization of the parameters regulating the feature detection and hit generation algorithms of the data processing software could significantly reduce the amount of unnecessary data and thereby the workload. Design of experiment (DoE) approaches allow a simultaneous optimization of multiple parameters. In a first step, parameters are evaluated (crucial or noncrucial). Second, crucial parameters are optimized. The aim in this study was to reduce the number of hits, without missing analytes. The obtained parameter settings from the optimization were compared to the standard settings by analyzing a test set of blood samples spiked with 22 relevant analytes as well as 62 authentic forensic cases. The optimization lead to a marked reduction of workload (12.3 to 1.1% and 3.8 to 1.1% hits for the test set and the authentic cases, respectively) while simultaneously increasing the identification rate (68.2 to 86.4% and 68.8 to 88.1%, respectively). This proof of concept study emphasizes the great potential of DoE approaches to master the data overload resulting from modern data independent acquisition methods used for general unknown screening procedures by optimizing software parameters.

The limitations of simple gene set enrichment analysis assuming gene independence.

PubMed

Tamayo, Pablo; Steinhardt, George; Liberzon, Arthur; Mesirov, Jill P

2016-02-01

Since its first publication in 2003, the Gene Set Enrichment Analysis method, based on the Kolmogorov-Smirnov statistic, has been heavily used, modified, and also questioned. Recently a simplified approach using a one-sample t-test score to assess enrichment and ignoring gene-gene correlations was proposed by Irizarry et al. 2009 as a serious contender. The argument criticizes Gene Set Enrichment Analysis's nonparametric nature and its use of an empirical null distribution as unnecessary and hard to compute. We refute these claims by careful consideration of the assumptions of the simplified method and its results, including a comparison with Gene Set Enrichment Analysis's on a large benchmark set of 50 datasets. Our results provide strong empirical evidence that gene-gene correlations cannot be ignored due to the significant variance inflation they produced on the enrichment scores and should be taken into account when estimating gene set enrichment significance. In addition, we discuss the challenges that the complex correlation structure and multi-modality of gene sets pose more generally for gene set enrichment methods. © The Author(s) 2012.

Angular dispersion of oblique phonon modes in BiFeO3 from micro-Raman scattering

NASA Astrophysics Data System (ADS)

Hlinka, J.; Pokorny, J.; Karimi, S.; Reaney, I. M.

2011-01-01

The angular dispersion of oblique phonon modes in a multiferroic BiFeO3 has been obtained from a micro-Raman spectroscopic investigation of a coarse grain ceramic sample. Continuity of the measured angular dispersion curves allows conclusive identification of all pure zone-center polar modes. The method employed here to reconstruct the anisotropic crystal property from a large set of independent local measurements on a macroscopically isotropic ceramic sample profits from the considerable dispersion of the oblique modes in ferroelectric perovskites and it can be in principle conveniently applied to any other optically uniaxial ferroelectric material.

A comparison of the social competence of children with moderate intellectual disability in inclusive versus segregated school settings.

PubMed

Hardiman, Sharon; Guerin, Suzanne; Fitzsimons, Elaine

2009-01-01

This is the first study to compare the social competence of children with moderate intellectual disability in inclusive versus segregated school settings in the Republic of Ireland. A convenience sample was recruited through two large ID services. The sample comprised 45 children across two groups: Group 1 (n=20; inclusive school) and Group 2 (n=25; segregated school). Parents and teachers completed the Strengths and Difficulties Questionnaire and the Adaptive Behaviour Scale-School: 2nd edition. A series of 2 x 2 ANOVAs were carried out on social competence scores using educational placement type (inclusive vs segregated school) and proxy rater (parent vs teacher) as the independent variables. Key findings indicated that children in inclusive schools did not differ significantly from children in segregated schools on the majority of proxy ratings of social competence. This supports the belief that children with intellectual disabilities can function well in different educational settings. Present findings highlight the importance of utilising the functional model of ID when selecting and designing school placements for children with moderate ID.

Detection of addition of barley to coffee using near infrared spectroscopy and chemometric techniques.

PubMed

Ebrahimi-Najafabadi, Heshmatollah; Leardi, Riccardo; Oliveri, Paolo; Casolino, Maria Chiara; Jalali-Heravi, Mehdi; Lanteri, Silvia

2012-09-15

The current study presents an application of near infrared spectroscopy for identification and quantification of the fraudulent addition of barley in roasted and ground coffee samples. Nine different types of coffee including pure Arabica, Robusta and mixtures of them at different roasting degrees were blended with four types of barley. The blending degrees were between 2 and 20 wt% of barley. D-optimal design was applied to select 100 and 30 experiments to be used as calibration and test set, respectively. Partial least squares regression (PLS) was employed to build the models aimed at predicting the amounts of barley in coffee samples. In order to obtain simplified models, taking into account only informative regions of the spectral profiles, a genetic algorithm (GA) was applied. A completely independent external set was also used to test the model performances. The models showed excellent predictive ability with root mean square errors (RMSE) for the test and external set equal to 1.4% w/w and 0.8% w/w, respectively. Copyright © 2012 Elsevier B.V. All rights reserved.

Nuclear Forensic Inferences Using Iterative Multidimensional Statistics

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

Robel, M; Kristo, M J; Heller, M A

2009-06-09

Nuclear forensics involves the analysis of interdicted nuclear material for specific material characteristics (referred to as 'signatures') that imply specific geographical locations, production processes, culprit intentions, etc. Predictive signatures rely on expert knowledge of physics, chemistry, and engineering to develop inferences from these material characteristics. Comparative signatures, on the other hand, rely on comparison of the material characteristics of the interdicted sample (the 'questioned sample' in FBI parlance) with those of a set of known samples. In the ideal case, the set of known samples would be a comprehensive nuclear forensics database, a database which does not currently exist. Inmore » fact, our ability to analyze interdicted samples and produce an extensive list of precise materials characteristics far exceeds our ability to interpret the results. Therefore, as we seek to develop the extensive databases necessary for nuclear forensics, we must also develop the methods necessary to produce the necessary inferences from comparison of our analytical results with these large, multidimensional sets of data. In the work reported here, we used a large, multidimensional dataset of results from quality control analyses of uranium ore concentrate (UOC, sometimes called 'yellowcake'). We have found that traditional multidimensional techniques, such as principal components analysis (PCA), are especially useful for understanding such datasets and drawing relevant conclusions. In particular, we have developed an iterative partial least squares-discriminant analysis (PLS-DA) procedure that has proven especially adept at identifying the production location of unknown UOC samples. By removing classes which fell far outside the initial decision boundary, and then rebuilding the PLS-DA model, we have consistently produced better and more definitive attributions than with a single pass classification approach. Performance of the iterative PLS-DA method compared favorably to that of classification and regression tree (CART) and k nearest neighbor (KNN) algorithms, with the best combination of accuracy and robustness, as tested by classifying samples measured independently in our laboratories against the vendor QC based reference set.« less

Plasma Nervonic Acid Is a Potential Biomarker for Major Depressive Disorder: A Pilot Study.

PubMed

Kageyama, Yuki; Kasahara, Takaoki; Nakamura, Takemichi; Hattori, Kotaro; Deguchi, Yasuhiko; Tani, Munehide; Kuroda, Kenji; Yoshida, Sumiko; Goto, Yu-Ichi; Inoue, Koki; Kato, Tadafumi

2018-03-01

Diagnostic biomarkers of major depressive disorder, bipolar disorder, and schizophrenia are urgently needed, because none are currently available. We performed a comprehensive metabolome analysis of plasma samples from drug-free patients with major depressive disorder (n=9), bipolar disorder (n=6), schizophrenia (n=17), and matched healthy controls (n=19) (cohort 1) using liquid chromatography time-of-flight mass spectrometry. A significant effect of diagnosis was found for 2 metabolites: nervonic acid and cortisone, with nervonic acid being the most significantly altered. The reproducibility of the results and effects of psychotropic medication on nervonic acid were verified in cohort 2, an independent sample set of medicated patients [major depressive disorder (n=45), bipolar disorder (n=71), schizophrenia (n=115)], and controls (n=90) using gas chromatography time-of-flight mass spectrometry. The increased levels of nervonic acid in patients with major depressive disorder compared with controls and patients with bipolar disorder in cohort 1 were replicated in the independent sample set (cohort 2). In cohort 2, plasma nervonic acid levels were also increased in the patients with major depressive disorder compared with the patients with schizophrenia. In cohort 2, nervonic acid levels were increased in the depressive state in patients with major depressive disorder compared with the levels in the remission state in patients with major depressive disorder and the depressive state in patients with bipolar disorder. These results suggested that plasma nervonic acid is a good candidate biomarker for the depressive state of major depressive disorder. © The Author 2017. Published by Oxford University Press on behalf of CINP.

Utility of metabolic profiling of serum in the diagnosis of pregnancy complications.

PubMed

Powell, Katie L; Carrozzi, Anthony; Stephens, Alexandre S; Tasevski, Vitomir; Morris, Jonathan M; Ashton, Anthony W; Dona, Anthony C

2018-06-01

Currently there are no clinical screening tests available to identify pregnancies at risk of developing preeclampsia (PET) and/or intrauterine growth restriction (IUGR), both of which are associated with abnormal placentation. Metabolic profiling is now a stable analytical platform used in many laboratories and has successfully been used to identify biomarkers associated with various pathological states. We used nuclear magnetic resonance spectroscopy (NMR) to metabolically profile serum samples collected from 143 pregnant women at 26-41 weeks gestation with pregnancy outcomes of PET, IUGR, PET IUGR or small for gestational age (SGA) that were age-matched to normal pre/term pregnancies. Spectral analysis found no difference in the measured metabolites from normal term, pre-term and SGA samples, and of 25 identified metabolites, only glutamate was marginally different between groups. Of the identified metabolites, 3-methylhistidine, creatinine, acetyl groups and acetate, were determined to be independent predictors of PET and produced area under the curves (AUC) = 0.938 and 0.936 for the discovery and validation sets. Only 3-hydroxybutyrate was determined to be an independent predictor of IUGR, however the model had low predictive power (AUC = 0.623 and 0.581 for the discovery and validation sets). A sub-panel of metabolites had strong predictive power for identifying PET samples in a validation dataset, however prediction of IUGR was more difficult using the identified metabolites. NMR based metabolomics can identify metabolites strongly associated with disease and has the potential to be useful in developing early clinical screening tests for at risk pregnancies. Copyright © 2018 Elsevier Ltd. All rights reserved.

Customized Consensus Spectral Library Building for Untargeted Quantitative Metabolomics Analysis with Data Independent Acquisition Mass Spectrometry and MetaboDIA Workflow.

PubMed

Chen, Gengbo; Walmsley, Scott; Cheung, Gemmy C M; Chen, Liyan; Cheng, Ching-Yu; Beuerman, Roger W; Wong, Tien Yin; Zhou, Lei; Choi, Hyungwon

2017-05-02

Data independent acquisition-mass spectrometry (DIA-MS) coupled with liquid chromatography is a promising approach for rapid, automatic sampling of MS/MS data in untargeted metabolomics. However, wide isolation windows in DIA-MS generate MS/MS spectra containing a mixed population of fragment ions together with their precursor ions. This precursor-fragment ion map in a comprehensive MS/MS spectral library is crucial for relative quantification of fragment ions uniquely representative of each precursor ion. However, existing reference libraries are not sufficient for this purpose since the fragmentation patterns of small molecules can vary in different instrument setups. Here we developed a bioinformatics workflow called MetaboDIA to build customized MS/MS spectral libraries using a user's own data dependent acquisition (DDA) data and to perform MS/MS-based quantification with DIA data, thus complementing conventional MS1-based quantification. MetaboDIA also allows users to build a spectral library directly from DIA data in studies of a large sample size. Using a marine algae data set, we show that quantification of fragment ions extracted with a customized MS/MS library can provide as reliable quantitative data as the direct quantification of precursor ions based on MS1 data. To test its applicability in complex samples, we applied MetaboDIA to a clinical serum metabolomics data set, where we built a DDA-based spectral library containing consensus spectra for 1829 compounds. We performed fragment ion quantification using DIA data using this library, yielding sensitive differential expression analysis.

The Estimation of Tree Posterior Probabilities Using Conditional Clade Probability Distributions

PubMed Central

Larget, Bret

2013-01-01

In this article I introduce the idea of conditional independence of separated subtrees as a principle by which to estimate the posterior probability of trees using conditional clade probability distributions rather than simple sample relative frequencies. I describe an algorithm for these calculations and software which implements these ideas. I show that these alternative calculations are very similar to simple sample relative frequencies for high probability trees but are substantially more accurate for relatively low probability trees. The method allows the posterior probability of unsampled trees to be calculated when these trees contain only clades that are in other sampled trees. Furthermore, the method can be used to estimate the total probability of the set of sampled trees which provides a measure of the thoroughness of a posterior sample. [Bayesian phylogenetics; conditional clade distributions; improved accuracy; posterior probabilities of trees.] PMID:23479066

Circum-Arctic petroleum systems identified using decision-tree chemometrics

USGS Publications Warehouse

Peters, K.E.; Ramos, L.S.; Zumberge, J.E.; Valin, Z.C.; Scotese, C.R.; Gautier, D.L.

2007-01-01

Source- and age-related biomarker and isotopic data were measured for more than 1000 crude oil samples from wells and seeps collected above approximately 55??N latitude. A unique, multitiered chemometric (multivariate statistical) decision tree was created that allowed automated classification of 31 genetically distinct circumArctic oil families based on a training set of 622 oil samples. The method, which we call decision-tree chemometrics, uses principal components analysis and multiple tiers of K-nearest neighbor and SIMCA (soft independent modeling of class analogy) models to classify and assign confidence limits for newly acquired oil samples and source rock extracts. Geochemical data for each oil sample were also used to infer the age, lithology, organic matter input, depositional environment, and identity of its source rock. These results demonstrate the value of large petroleum databases where all samples were analyzed using the same procedures and instrumentation. Copyright ?? 2007. The American Association of Petroleum Geologists. All rights reserved.

Principal component analysis for designed experiments.

PubMed

Konishi, Tomokazu

2015-01-01

Principal component analysis is used to summarize matrix data, such as found in transcriptome, proteome or metabolome and medical examinations, into fewer dimensions by fitting the matrix to orthogonal axes. Although this methodology is frequently used in multivariate analyses, it has disadvantages when applied to experimental data. First, the identified principal components have poor generality; since the size and directions of the components are dependent on the particular data set, the components are valid only within the data set. Second, the method is sensitive to experimental noise and bias between sample groups. It cannot reflect the experimental design that is planned to manage the noise and bias; rather, it estimates the same weight and independence to all the samples in the matrix. Third, the resulting components are often difficult to interpret. To address these issues, several options were introduced to the methodology. First, the principal axes were identified using training data sets and shared across experiments. These training data reflect the design of experiments, and their preparation allows noise to be reduced and group bias to be removed. Second, the center of the rotation was determined in accordance with the experimental design. Third, the resulting components were scaled to unify their size unit. The effects of these options were observed in microarray experiments, and showed an improvement in the separation of groups and robustness to noise. The range of scaled scores was unaffected by the number of items. Additionally, unknown samples were appropriately classified using pre-arranged axes. Furthermore, these axes well reflected the characteristics of groups in the experiments. As was observed, the scaling of the components and sharing of axes enabled comparisons of the components beyond experiments. The use of training data reduced the effects of noise and bias in the data, facilitating the physical interpretation of the principal axes. Together, these introduced options result in improved generality and objectivity of the analytical results. The methodology has thus become more like a set of multiple regression analyses that find independent models that specify each of the axes.

Pitfalls in statistical landslide susceptibility modelling

NASA Astrophysics Data System (ADS)

Schröder, Boris; Vorpahl, Peter; Märker, Michael; Elsenbeer, Helmut

2010-05-01

The use of statistical methods is a well-established approach to predict landslide occurrence probabilities and to assess landslide susceptibility. This is achieved by applying statistical methods relating historical landslide inventories to topographic indices as predictor variables. In our contribution, we compare several new and powerful methods developed in machine learning and well-established in landscape ecology and macroecology for predicting the distribution of shallow landslides in tropical mountain rainforests in southern Ecuador (among others: boosted regression trees, multivariate adaptive regression splines, maximum entropy). Although these methods are powerful, we think it is necessary to follow a basic set of guidelines to avoid some pitfalls regarding data sampling, predictor selection, and model quality assessment, especially if a comparison of different models is contemplated. We therefore suggest to apply a novel toolbox to evaluate approaches to the statistical modelling of landslide susceptibility. Additionally, we propose some methods to open the "black box" as an inherent part of machine learning methods in order to achieve further explanatory insights into preparatory factors that control landslides. Sampling of training data should be guided by hypotheses regarding processes that lead to slope failure taking into account their respective spatial scales. This approach leads to the selection of a set of candidate predictor variables considered on adequate spatial scales. This set should be checked for multicollinearity in order to facilitate model response curve interpretation. Model quality assesses how well a model is able to reproduce independent observations of its response variable. This includes criteria to evaluate different aspects of model performance, i.e. model discrimination, model calibration, and model refinement. In order to assess a possible violation of the assumption of independency in the training samples or a possible lack of explanatory information in the chosen set of predictor variables, the model residuals need to be checked for spatial auto¬correlation. Therefore, we calculate spline correlograms. In addition to this, we investigate partial dependency plots and bivariate interactions plots considering possible interactions between predictors to improve model interpretation. Aiming at presenting this toolbox for model quality assessment, we investigate the influence of strategies in the construction of training datasets for statistical models on model quality.

Novel glioblastoma markers with diagnostic and prognostic value identified through transcriptome analysis.

PubMed

Reddy, Sreekanth P; Britto, Ramona; Vinnakota, Katyayni; Aparna, Hebbar; Sreepathi, Hari Kishore; Thota, Balaram; Kumari, Arpana; Shilpa, B M; Vrinda, M; Umesh, Srikantha; Samuel, Cini; Shetty, Mitesh; Tandon, Ashwani; Pandey, Paritosh; Hegde, Sridevi; Hegde, A S; Balasubramaniam, Anandh; Chandramouli, B A; Santosh, Vani; Kondaiah, Paturu; Somasundaram, Kumaravel; Rao, M R Satyanarayana

2008-05-15

Current methods of classification of astrocytoma based on histopathologic methods are often subjective and less accurate. Although patients with glioblastoma have grave prognosis, significant variability in patient outcome is observed. Therefore, the aim of this study was to identify glioblastoma diagnostic and prognostic markers through microarray analysis. We carried out transcriptome analysis of 25 diffusely infiltrating astrocytoma samples [WHO grade II--diffuse astrocytoma, grade III--anaplastic astrocytoma, and grade IV--glioblastoma (GBM)] using cDNA microarrays containing 18,981 genes. Several of the markers identified were also validated by real-time reverse transcription quantitative PCR and immunohistochemical analysis on an independent set of tumor samples (n = 100). Survival analysis was carried out for two markers on another independent set of retrospective cases (n = 51). We identified several differentially regulated grade-specific genes. Independent validation by real-time reverse transcription quantitative PCR analysis found growth arrest and DNA-damage-inducible alpha (GADD45alpha) and follistatin-like 1 (FSTL1) to be up-regulated in most GBMs (both primary and secondary), whereas superoxide dismutase 2 and adipocyte enhancer binding protein 1 were up-regulated in the majority of primary GBM. Further, identification of the grade-specific expression of GADD45alpha and FSTL1 by immunohistochemical staining reinforced our findings. Analysis of retrospective GBM cases with known survival data revealed that cytoplasmic overexpression of GADD45alpha conferred better survival while the coexpression of FSTL1 with p53 was associated with poor survival. Our study reveals that GADD45alpha and FSTLI are GBM-specific whereas superoxide dismutase 2 and adipocyte enhancer binding protein 1 are primary GBM-specific diagnostic markers. Whereas GADD45alpha overexpression confers a favorable prognosis, FSTL1 overexpression is a hallmark of poor prognosis in GBM patients.

The Social Interaction Anxiety Scale (SIAS) and the Social Phobia Scale (SPS): a comparison of two short-form versions.

PubMed

Fergus, Thomas A; Valentiner, David P; Kim, Hyun-Soo; McGrath, Patrick B

2014-12-01

The widespread use of Mattick and Clarke's (1998) Social Interaction Anxiety Scale (SIAS) and Social Phobia Scale (SPS) led 2 independent groups of researchers to develop short forms of these measures (Fergus, Valentiner, McGrath, Gier-Lonsway, & Kim, 2012; Peters, Sunderland, Andrews, Rapee, & Mattick, 2012). This 3-part study examined the psychometric properties of Fergus et al.'s and Peters et al.'s short forms of the SIAS and SPS using an American nonclinical adolescent sample in Study 1 (N = 98), American patient sample with an anxiety disorder in Study 2 (N = 117), and both a South Korean college student sample (N = 341) and an American college student sample (N = 550) in Study 3. Scores on both sets of short forms evidenced adequate internal consistency, interitem correlations, and measurement invariance. Scores on Fergus et al.'s short forms, particularly their SIAS short form, tended to capture more unique variance in scores of criterion measures than did scores on Peters et al.'s short forms. Implications for the use of these 2 sets of short forms are discussed. (c) 2014 APA, all rights reserved.

Fine PM measurements: personal and indoor air monitoring.

PubMed

Jantunen, M; Hänninen, O; Koistinen, K; Hashim, J H

2002-12-01

This review compiles personal and indoor microenvironment particulate matter (PM) monitoring needs from recently set research objectives, most importantly the NRC published "Research Priorities for Airborne Particulate Matter (1998)". Techniques and equipment used to monitor PM personal exposures and microenvironment concentrations and the constituents of the sampled PM during the last 20 years are then reviewed. Development objectives are set and discussed for personal and microenvironment PM samplers and monitors, for filter materials, and analytical laboratory techniques for equipment calibration, filter weighing and laboratory climate control. The progress is leading towards smaller sample flows, lighter, silent, independent (battery powered) monitors with data logging capacity to store microenvironment or activity relevant sensor data, advanced flow controls and continuous recording of the concentration. The best filters are non-hygroscopic, chemically pure and inert, and physically robust against mechanical wear. Semiautomatic and primary standard equivalent positive displacement flow meters are replacing the less accurate methods in flow calibration, and also personal sampling flow rates should become mass flow controlled (with or without volumetric compensation for pressure and temperature changes). In the weighing laboratory the alternatives are climatic control (set temperature and relative humidity), and mechanically simpler thermostatic heating, air conditioning and dehumidification systems combined with numerical control of temperature, humidity and pressure effects on flow calibration and filter weighing.

BloodSpot: a database of gene expression profiles and transcriptional programs for healthy and malignant haematopoiesis

PubMed Central

Bagger, Frederik Otzen; Sasivarevic, Damir; Sohi, Sina Hadi; Laursen, Linea Gøricke; Pundhir, Sachin; Sønderby, Casper Kaae; Winther, Ole; Rapin, Nicolas; Porse, Bo T.

2016-01-01

Research on human and murine haematopoiesis has resulted in a vast number of gene-expression data sets that can potentially answer questions regarding normal and aberrant blood formation. To researchers and clinicians with limited bioinformatics experience, these data have remained available, yet largely inaccessible. Current databases provide information about gene-expression but fail to answer key questions regarding co-regulation, genetic programs or effect on patient survival. To address these shortcomings, we present BloodSpot (www.bloodspot.eu), which includes and greatly extends our previously released database HemaExplorer, a database of gene expression profiles from FACS sorted healthy and malignant haematopoietic cells. A revised interactive interface simultaneously provides a plot of gene expression along with a Kaplan–Meier analysis and a hierarchical tree depicting the relationship between different cell types in the database. The database now includes 23 high-quality curated data sets relevant to normal and malignant blood formation and, in addition, we have assembled and built a unique integrated data set, BloodPool. Bloodpool contains more than 2000 samples assembled from six independent studies on acute myeloid leukemia. Furthermore, we have devised a robust sample integration procedure that allows for sensitive comparison of user-supplied patient samples in a well-defined haematopoietic cellular space. PMID:26507857

The upper critical field of filamentary Nb3Sn conductors

NASA Astrophysics Data System (ADS)

Godeke, A.; Jewell, M. C.; Fischer, C. M.; Squitieri, A. A.; Lee, P. J.; Larbalestier, D. C.

2005-05-01

We have examined the upper critical field of a large and representative set of present multifilamentary Nb3Sn wires and one bulk sample over a temperature range from 1.4 K up to the zero-field critical temperature. Since all present wires use a solid-state diffusion reaction to form the A15 layers, inhomogeneities with respect to Sn content are inevitable, in contrast to some previously studied homogeneous samples. Our study emphasizes the effects that these inevitable inhomogeneities have on the field-temperature phase boundary. The property inhomogeneities are extracted from field-dependent resistive transitions which we find broaden with increasing inhomogeneity. The upper 90%-99% of the transitions clearly separates alloyed and binary wires but a pure, Cu-free binary bulk sample also exhibits a zero-temperature critical field that is comparable to the ternary wires. The highest μ0Hc2 detected in the ternary wires are remarkably constant: The highest zero-temperature upper critical fields and zero-field critical temperatures fall within 29.5±0.3 and 17.8±0.3K, respectively, independent of the wire layout. The complete field-temperature phase boundary can be described very well with the relatively simple Maki-DeGennes model using a two-parameter fit, independent of composition, strain state, sample layout, or applied critical state criterion.

The Fungal Frontier: A Comparative Analysis of Methods Used in the Study of the Human Gut Mycobiome.

PubMed

Huseyin, Chloe E; Rubio, Raul Cabrera; O'Sullivan, Orla; Cotter, Paul D; Scanlan, Pauline D

2017-01-01

The human gut is host to a diverse range of fungal species, collectively referred to as the gut "mycobiome". The gut mycobiome is emerging as an area of considerable research interest due to the potential roles of these fungi in human health and disease. However, there is no consensus as to what the best or most suitable methodologies available are with respect to characterizing the human gut mycobiome. The aim of this study is to provide a comparative analysis of several previously published mycobiome-specific culture-dependent and -independent methodologies, including choice of culture media, incubation conditions (aerobic versus anaerobic), DNA extraction method, primer set and freezing of fecal samples to assess their relative merits and suitability for gut mycobiome analysis. There was no significant effect of media type or aeration on culture-dependent results. However, freezing was found to have a significant effect on fungal viability, with significantly lower fungal numbers recovered from frozen samples. DNA extraction method had a significant effect on DNA yield and quality. However, freezing and extraction method did not have any impact on either α or β diversity. There was also considerable variation in the ability of different fungal-specific primer sets to generate PCR products for subsequent sequence analysis. Through this investigation two DNA extraction methods and one primer set was identified which facilitated the analysis of the mycobiome for all samples in this study. Ultimately, a diverse range of fungal species were recovered using both approaches, with Candida and Saccharomyces identified as the most common fungal species recovered using culture-dependent and culture-independent methods, respectively. As has been apparent from ecological surveys of the bacterial fraction of the gut microbiota, the use of different methodologies can also impact on our understanding of gut mycobiome composition and therefore requires careful consideration. Future research into the gut mycobiome needs to adopt a common strategy to minimize potentially confounding effects of methodological choice and to facilitate comparative analysis of datasets.

The pre-synaptic vesicle protein synaptotagmin is a novel biomarker for Alzheimer's disease.

PubMed

Öhrfelt, Annika; Brinkmalm, Ann; Dumurgier, Julien; Brinkmalm, Gunnar; Hansson, Oskar; Zetterberg, Henrik; Bouaziz-Amar, Elodie; Hugon, Jacques; Paquet, Claire; Blennow, Kaj

2016-10-03

Synaptic degeneration is a central pathogenic event in Alzheimer's disease that occurs early during the course of disease and correlates with cognitive symptoms. The pre-synaptic vesicle protein synaptotagmin-1 appears to be essential for the maintenance of an intact synaptic transmission and cognitive function. Synaptotagmin-1 in cerebrospinal fluid is a candidate Alzheimer biomarker for synaptic dysfunction that also may correlate with cognitive decline. In this study, a novel mass spectrometry-based assay for measurement of cerebrospinal fluid synaptotagmin-1 was developed, and was evaluated in two independent sample sets of patients and controls. Sample set I included cerebrospinal fluid samples from patients with dementia due to Alzheimer's disease (N = 17, age 52-86 years), patients with mild cognitive impairment due to Alzheimer's disease (N = 5, age 62-88 years), and controls (N = 17, age 41-82 years). Sample set II included cerebrospinal fluid samples from patients with dementia due to Alzheimer's disease (N = 24, age 52-84 years), patients with mild cognitive impairment due to Alzheimer's disease (N = 18, age 58-83 years), and controls (N = 36, age 43-80 years). The reproducibility of the novel method showed coefficients of variation of the measured synaptotagmin-1 peptide 215-223 (VPYSELGGK) and peptide 238-245 (HDIIGEFK) of 14 % or below. In both investigated sample sets, the CSF levels of synaptotagmin-1 were significantly increased in patients with dementia due to Alzheimer's disease (P ≤ 0.0001) and in patients with mild cognitive impairment due to Alzheimer's disease (P < 0.001). In addition, in sample set I the synaptotagmin-1 level was significantly higher in patients with mild cognitive impairment due to Alzheimer's disease compared with patients with dementia due to Alzheimer's disease (P ≤ 0.05). Cerebrospinal fluid synaptotagmin-1 is a promising biomarker to monitor synaptic dysfunction and degeneration in Alzheimer's disease that may be useful for clinical diagnosis, to monitor effect on synaptic integrity by novel drug candidates, and to explore pathophysiology directly in patients with Alzheimer's disease.

Culture-Independent Study of the Late-Stage of a Bloom of the Toxic Dinoflagellate Ostreopsis cf. ovata: Preliminary Findings Suggest Genetic Differences at the Sub-Species Level and Allow ITS2 Structure Characterization.

PubMed

Ramos, Vitor; Salvi, Daniele; Machado, João Paulo; Vale, Micaela; Azevedo, Joana; Vasconcelos, Vitor

2015-06-30

Available genomic data for the toxic, bloom-forming, benthic Ostreopsis spp. are traditionally obtained from isolates rather than from individuals originally present in environmental samples. Samples from the final phase of the first reported Ostreopsis bloom in European North Atlantic waters (Algarve, south coast of Portugal) were studied and characterized, using a culture-independent approach. In the first instance, a microscopy-based analysis revealed the intricate complexity of the samples. Then, we evaluated the adequacy of commonly used molecular tools (i.e., primers and nuclear ribosomal markers) for the study of Ostreopsis diversity in natural samples. A PCR-based methodology previously developed to identify/detect common Ostreopsis species was tested, including one new combination of existing PCR primers. Two sets of environmental rRNA sequences were obtained, one of them (1052 bp) with the newly tested primer set. These latter sequences encompass both the ITS1-5.8S-ITS2 region and the D1/D2 domain of the LSU rRNA gene, leading us to an accurate identification of ITS2. In turn, this allowed us to predict and show for the first time the ITS2 secondary structure of Ostreopsis. With 92 bp in length and a two-helix structure, the ITS2 of this genus revealed to be unique among the dinoflagellates. Both the PCR approach as the phylogenetic analyses allowed to place the Ostreopsis cells observed in the samples within the O. cf. ovata phylospecies' complex, discarding the presence of O. cf. siamensis. The (phylo)genetic results point out a certain level of nucleotide sequence divergence, but were inconclusive in relation to a possible geographic origin of the O. cf. ovata population from the Algarve's bloom.

Vitamin D deficiency and pregnancy rates in women undergoing single embryo, blastocyst stage, transfer (SET) for IVF/ICSI.

PubMed

Polyzos, Nikolaos P; Anckaert, Ellen; Guzman, Luis; Schiettecatte, Johan; Van Landuyt, Lisbet; Camus, Michel; Smitz, Johan; Tournaye, Herman

2014-09-01

What is the influence of vitamin D deficiency on pregnancy rates among women undergoing IVF/ICSI and Day 5 (blastocyst stage) single embryo transfer (SET)? Vitamin D deficiency results in significantly lower pregnancy rates in women undergoing single blastocyst transfer. Preliminary experiments have identified the presence of vitamin D receptors in the female reproductive system. However, results regarding the effect of vitamin D deficiency on clinical outcomes are conflicting. None of the previous studies adopted a SET strategy. Serum vitamin D concentration was measured retrospectively in patients who underwent SET on Day 5. Overall 368 consecutive infertile women treated within a period of 15 months were included in the study. All patients underwent ovarian stimulation for IVF/ICSI and Day 5 SET. Serum samples were obtained 7 days prior to embryo transfer and stored frozen at -20°C. Samples were collectively analyzed for their 25-OH vitamin D content. Vitamin D deficiency was defined as serum 25-OH vitamin D levels <20 ng/ml in accordance with the Institute of Medicine and the Endocrine Society clinical practice guidelines. Clinical pregnancy rates were significantly lower in women with vitamin D deficiency compared with those with higher vitamin D values (41 versus 54%, P = 0.015).Logistic regression analysis was performed to identify whether vitamin D deficiency is independently associated with clinical pregnancy rates after controlling for 16 potential confounding factors. According to our results vitamin D deficiency was independently associated with lower clinical pregnancy rates, odds ratios [ORs (95% confidence interval (CI) 0.61 (0.39-0.95)] for vitamin D deficiency (deficient versus non-deficient women), P = 0.030. Finally, even when restricting our analysis to women undergoing elective SET (274 patients), vitamin D deficiency was again independently associated with pregnancy rates [OR (95% CI) 0.56 (0.33-0.93), P = 0.024]. Our results refer only to patients undergoing Day 5 SET. Although vitamin D deficiency appears to compromise pregnancy rates in this population, no guidance can be provided regarding a potential relationship between vitamin D deficiency and ovarian reserve or response to ovarian stimulation. Vitamin D deficiency impairs pregnancy rates in women undergoing single blastocyst transfer. Future prospective confirmatory studies are needed to validate our results and examine the exact underlying mechanism by which vitamin D levels may impair pregnancy rates in infertile women undergoing IVF/ICSI. None declared. © The Author 2014. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Panels of tumor-derived RNA markers in peripheral blood of patients with non-small cell lung cancer: their dependence on age, gender and clinical stages.

PubMed

Chian, Chih-Feng; Hwang, Yi-Ting; Terng, Harn-Jing; Lee, Shih-Chun; Chao, Tsui-Yi; Chang, Hung; Ho, Ching-Liang; Wu, Yi-Ying; Perng, Wann-Cherng

2016-08-02

Peripheral blood mononuclear cell (PBMC)-derived gene signatures were investigated for their potential use in the early detection of non-small cell lung cancer (NSCLC). In our study, 187 patients with NSCLC and 310 age- and gender-matched controls, and an independent set containing 29 patients for validation were included. Eight significant NSCLC-associated genes were identified, including DUSP6, EIF2S3, GRB2, MDM2, NF1, POLDIP2, RNF4, and WEE1. The logistic model containing these significant markers was able to distinguish subjects with NSCLC from controls with an excellent performance, 80.7% sensitivity, 90.6% specificity, and an area under the receiver operating characteristic curve (AUC) of 0.924. Repeated random sub-sampling for 100 times was used to validate the performance of classification training models with an average AUC of 0.92. Additional cross-validation using the independent set resulted in the sensitivity 75.86%. Furthermore, six age/gender-dependent genes: CPEB4, EIF2S3, GRB2, MCM4, RNF4, and STAT2 were identified using age and gender stratification approach. STAT2 and WEE1 were explored as stage-dependent using stage-stratified subpopulation. We conclude that these logistic models using different signatures for total and stratified samples are potential complementary tools for assessing the risk of NSCLC.

GAB2 as an Alzheimer disease susceptibility gene: follow-up of genomewide association results.

PubMed

Schjeide, Brit-Maren M; Hooli, Basavaraj; Parkinson, Michele; Hogan, Meghan F; DiVito, Jason; Mullin, Kristina; Blacker, Deborah; Tanzi, Rudolph E; Bertram, Lars

2009-02-01

Genomewide association (GWA) studies have recently implicated 4 novel Alzheimer disease (AD) susceptibility loci (GAB2, GOLM1, and 2 uncharacterized loci to date on chromosomes 9p and 15q). To our knowledge, these findings have not been independently replicated. To assess these GWA findings in 4 large data sets of families affected by AD. Follow-up of genetic association findings in previous studies. Academic research. More than 4000 DNA samples from almost 1300 families affected with AD. Genetic association analysis testing of 4 GWA signals (rs7101429 [GAB2], rs7019241 [GOLM1], rs10519262 [chromosome 15q], and rs9886784 [chromosome 9p]) using family-based methods. In the combined analyses, only rs7101429 in GAB2 yielded significant evidence of association with the same allele as in the original GWA study (P =.002). The results are in agreement with recent meta-analyses of this and other GAB2 polymorphisms suggesting approximately a 30% decrease in risk for AD among carriers of the minor alleles. None of the other 3 tested loci showed consistent evidence for association with AD across the investigated data sets. GAB2 contains genetic variants that may lead to a modest change in the risk for AD. Despite these promising results, more data from independent samples are needed to better evaluate the potential contribution of GAB2 to AD risk in the general population.

An omnibus permutation test on ensembles of two-locus analyses can detect pure epistasis and genetic heterogeneity in genome-wide association studies.

PubMed

Setsirichok, Damrongrit; Tienboon, Phuwadej; Jaroonruang, Nattapong; Kittichaijaroen, Somkit; Wongseree, Waranyu; Piroonratana, Theera; Usavanarong, Touchpong; Limwongse, Chanin; Aporntewan, Chatchawit; Phadoongsidhi, Marong; Chaiyaratana, Nachol

2013-01-01

This article presents the ability of an omnibus permutation test on ensembles of two-locus analyses (2LOmb) to detect pure epistasis in the presence of genetic heterogeneity. The performance of 2LOmb is evaluated in various simulation scenarios covering two independent causes of complex disease where each cause is governed by a purely epistatic interaction. Different scenarios are set up by varying the number of available single nucleotide polymorphisms (SNPs) in data, number of causative SNPs and ratio of case samples from two affected groups. The simulation results indicate that 2LOmb outperforms multifactor dimensionality reduction (MDR) and random forest (RF) techniques in terms of a low number of output SNPs and a high number of correctly-identified causative SNPs. Moreover, 2LOmb is capable of identifying the number of independent interactions in tractable computational time and can be used in genome-wide association studies. 2LOmb is subsequently applied to a type 1 diabetes mellitus (T1D) data set, which is collected from a UK population by the Wellcome Trust Case Control Consortium (WTCCC). After screening for SNPs that locate within or near genes and exhibit no marginal single-locus effects, the T1D data set is reduced to 95,991 SNPs from 12,146 genes. The 2LOmb search in the reduced T1D data set reveals that 12 SNPs, which can be divided into two independent sets, are associated with the disease. The first SNP set consists of three SNPs from MUC21 (mucin 21, cell surface associated), three SNPs from MUC22 (mucin 22), two SNPs from PSORS1C1 (psoriasis susceptibility 1 candidate 1) and one SNP from TCF19 (transcription factor 19). A four-locus interaction between these four genes is also detected. The second SNP set consists of three SNPs from ATAD1 (ATPase family, AAA domain containing 1). Overall, the findings indicate the detection of pure epistasis in the presence of genetic heterogeneity and provide an alternative explanation for the aetiology of T1D in the UK population.

Boomerang: A method for recursive reclassification.

PubMed

Devlin, Sean M; Ostrovnaya, Irina; Gönen, Mithat

2016-09-01

While there are many validated prognostic classifiers used in practice, often their accuracy is modest and heterogeneity in clinical outcomes exists in one or more risk subgroups. Newly available markers, such as genomic mutations, may be used to improve the accuracy of an existing classifier by reclassifying patients from a heterogenous group into a higher or lower risk category. The statistical tools typically applied to develop the initial classifiers are not easily adapted toward this reclassification goal. In this article, we develop a new method designed to refine an existing prognostic classifier by incorporating new markers. The two-stage algorithm called Boomerang first searches for modifications of the existing classifier that increase the overall predictive accuracy and then merges to a prespecified number of risk groups. Resampling techniques are proposed to assess the improvement in predictive accuracy when an independent validation data set is not available. The performance of the algorithm is assessed under various simulation scenarios where the marker frequency, degree of censoring, and total sample size are varied. The results suggest that the method selects few false positive markers and is able to improve the predictive accuracy of the classifier in many settings. Lastly, the method is illustrated on an acute myeloid leukemia data set where a new refined classifier incorporates four new mutations into the existing three category classifier and is validated on an independent data set. © 2016, The International Biometric Society.

Investigation of Metabolomic Blood Biomarkers for Detection of Adenocarcinoma Lung Cancer

PubMed Central

Fahrmann, Johannes F.; Kim, Kyoungmi; DeFelice, Brian C.; Taylor, Sandra L.; Gandara, David R.; Yoneda, Ken Y.; Cooke, David T.; Fiehn, Oliver; Kelly, Karen; Miyamoto, Suzanne

2015-01-01

Background Untargeted metabolomics was utilized in case control studies of adenocarcinoma (ADC) lung cancer in order to develop and test metabolite classifiers in serum and plasma as potential biomarkers for diagnosing lung cancer. Methods Serum and plasma were collected and used in two independent case-control studies (ADC1 and ADC2). Controls were frequency matched for gender, age and smoking history. There were 52 ADC cases and 31 controls in ADC1 and 43 ADC cases and 43 controls in ADC2. Metabolomics was conducted using gas chromatography time-of-flight mass spectrometry. Differential analysis was performed on ADC1 and the top candidates (FDR < 0.05) for serum and plasma used to develop individual and multiplex-classifiers that were then tested on an independent set of serum and plasma samples (ADC2). Results Aspartate provided the best accuracy (81.4%) for an individual metabolite classifier in serum whereas pyrophosphate had the best accuracy (77.9%) in plasma when independently tested. Multiplex classifiers of either 2 or 4 serum metabolites had an accuracy of 72.7% when independently tested. For plasma, a multi-metabolite classifier consisting of 8 metabolites gave an accuracy of 77.3% when independently tested. Comparison of overall diagnostic performance between the two blood matrices yielded similar performances. However, serum is most ideal given higher sensitivity for low abundant metabolites. Conclusion This study shows the potential of metabolite-based diagnostic tests for detection of lung adenocarcinoma. Further validation in a larger pool of samples is warranted. Impact These biomarkers could improve early detection and diagnosis of lung cancer. PMID:26282632

Independence of the uniformity principle from Church's thesis in intuitionistic set theory

NASA Astrophysics Data System (ADS)

Khakhanyan, V. Kh

2013-12-01

We prove the independence of the strong uniformity principle from Church's thesis with choice in intuitionistic set theory with the axiom of extensionality extended by Markov's principle and the double complement for sets.

Resonant Acoustic Determination of Complex Elastic Moduli

NASA Technical Reports Server (NTRS)

Brown, David A.; Garrett, Steven L.

1991-01-01

A simple, inexpensive, yet accurate method for measuring the dynamic complex modulus of elasticity is described. Using a 'free-free' bar selectively excited in three independent vibrational modes, the shear modulus is obtained by measuring the frequency of the torsional resonant mode and the Young's modulus is determined from measurement of either the longitudinal or flexural mode. The damping properties are obtained by measuring the quality factor (Q) for each mode. The Q is inversely proportional to the loss tangent. The viscoelastic behavior of the sample can be obtained by tracking a particular resonant mode (and thus a particular modulus) using a phase locked loop (PLL) and by changing the temperature of the sample. The change in the damping properties is obtained by measuring the in-phase amplitude of the PLL which is proportional to the Q of the material. The real and imaginary parts or the complex modulus can be obtained continuously as a function of parameters such as temperature, pressure, or humidity. For homogeneous and isotropic samples only two independent moduli are needed in order to characterize the complete set of elastic constants, thus, values can be obtained for the dynamic Poisson's ratio, bulk modulus, Lame constants, etc.

Early Cone Setting in Picea abies acrocona Is Associated with Increased Transcriptional Activity of a MADS Box Transcription Factor1[W][OA

PubMed Central

Uddenberg, Daniel; Reimegård, Johan; Clapham, David; Almqvist, Curt; von Arnold, Sara; Emanuelsson, Olof; Sundström, Jens F.

2013-01-01

Conifers normally go through a long juvenile period, for Norway spruce (Picea abies) around 20 to 25 years, before developing male and female cones. We have grown plants from inbred crosses of a naturally occurring spruce mutant (acrocona). One-fourth of the segregating acrocona plants initiate cones already in their second growth cycle, suggesting control by a single locus. The early cone-setting properties of the acrocona mutant were utilized to identify candidate genes involved in vegetative-to-reproductive phase change in Norway spruce. Poly(A+) RNA samples from apical and basal shoots of cone-setting and non-cone-setting plants were subjected to high-throughput sequencing (RNA-seq). We assembled and investigated 33,383 expressed putative protein-coding acrocona transcripts. Eight transcripts were differentially expressed between selected sample pairs. One of these (Acr42124_1) was significantly up-regulated in apical shoot samples from cone-setting acrocona plants, and the encoded protein belongs to the MADS box gene family of transcription factors. Using quantitative real-time polymerase chain reaction with independently derived plant material, we confirmed that the MADS box gene is up-regulated in both needles and buds of cone-inducing shoots when reproductive identity is determined. Our results constitute important steps for the development of a rapid cycling model system that can be used to study gene function in conifers. In addition, our data suggest the involvement of a MADS box transcription factor in the vegetative-to-reproductive phase change in Norway spruce. PMID:23221834

A comparison between families obtained from different proper elements

NASA Technical Reports Server (NTRS)

Zappala, Vincenzo; Cellino, Alberto; Farinella, Paolo

1992-01-01

Using the hierarchical method of family identification developed by Zappala et al., the results coming from the data set of proper elements computed by Williams (about 2100 numbered + about 1200 PLS 2 asteroids) and by Milani and Knezevic (5.7 version, about 4200 asteroids) are compared. Apart from some expected discrepancies due to the different data sets and/or low accuracy of proper elements computed in peculiar dynamical zones, a good agreement was found in several cases. It follows that these high reliability families represent a sample which can be considered independent on the methods used for their proper elements computation. Therefore, they should be considered as the best candidates for detailed physical studies.

Quality geriatric care as perceived by nurses in long-term and acute care settings.

PubMed

Barba, Beth Ellen; Hu, Jie; Efird, Jimmy

2012-03-01

This study focused on differences in nurses' satisfaction with the quality of care of older people and with organisational characteristics and work environment in acute care and long-term care settings. Numerous studies have explored links between nurses' satisfaction with care and work environments on the one hand and a variety of physical, behavioural and psychological reactions of nurses on the other. One key to keeping nurses in the workplace is a better understanding of nurses' satisfaction with the quality of care they provide. Descriptive design. The self-selected sample included 298 registered nurses and licensed practical nurses who provide care to minority, underserved and disadvantaged older populations in 89 long-term care and <100 bed hospitals in 38 rural counties and eight metropolitan areas in a Southern state. All completed the Agency Geriatric Nursing Care survey, which consisted of a 13-item scale measuring nurses' satisfaction with the quality of geriatric care in their practice settings and an 11-item scale examining obstacles to providing quality geriatric care. Demographic variables were compared with chi-square. Independent t-tests were used to examine differences between nurses in long-term care and acute care settings. Significant differences were found in level of satisfaction and perceived obstacles to providing quality care to older adults between participants from acute and long-term care. Participants in long-term care had greater satisfaction with the quality of geriatric care than those in acute facilities. Nurses in long-term care were more satisfied that care was evidence-based; specialised to individual needs of older adults; promoted autonomy and independence of elders; and was continuous across settings. Participants in acute facilities perceived more obstacles to providing quality geriatric care than nurses in long-term care facilities. Modification of hospital geriatric practice environments and leadership commitment to evidence-based practice guidelines that promote autonomy and independence of patients and staff could improve acute care nurses' perceptions of quality of geriatric care. © 2011 Blackwell Publishing Ltd.

Prison Health Care Governance: Guaranteeing Clinical Independence

PubMed Central

Pont, Jörg; Enggist, Stefan; Stöver, Heino; Williams, Brie; Greifinger, Robert

2018-01-01

Clinical independence is an essential component of good health care and health care professionalism, particularly in correctional settings (jails, prisons, and other places of detention), where the relationship between patients and caregivers is not based on free choice and where the punitive correctional setting can challenge optimal medical care. Independence for the delivery of health care services is defined by international standards as a critical element for quality health care in correctional settings, yet many correctional facilities do not meet these standards because of a lack of awareness, persisting legal regulations, contradictory terms of employment for health professionals, or current health care governance structures. We present recommendations for the implementation of independent health care in correctional settings. PMID:29470125

The Context Dependency of the Self-Report Version of the Strength and Difficulties Questionnaire (SDQ): A Cross-Sectional Study between Two Administration Settings

PubMed Central

Hoofs, H.; Jansen, N. W. H.; Mohren, D. C. L.; Jansen, M. W. J.; Kant, I. J.

2015-01-01

Background The Strength and Difficulties Questionnaire (SDQ) is a screening instrument for psychosocial problems in children and adolescents, which is applied in “individual” and “collective” settings. Assessment in the individual setting is confidential for clinical applications, such as preventive child healthcare, while assessment in the collective setting is anonymous and applied in (epidemiological) research. Due to administration differences between the settings it remains unclear whether results and conclusions actually can be used interchangeably. This study therefore aims to investigate whether the SDQ is invariant across settings. Methods Two independent samples were retrieved (mean age = 14.07 years), one from an individual setting (N = 6,594) and one from a collective setting (N = 4,613). The SDQ was administered in the second year of secondary school in both settings. Samples come from the same socio-geographic population in the Netherlands. Results Confirmatory factor analysis showed that the SDQ was measurement invariant/equivalent across settings and gender. On average, children in the individual setting scored lower on total difficulties (mean difference = 2.05) and the psychosocial problems subscales compared to those in the collective setting. This was also reflected in the cut-off points for caseness, defined by the 90th percentiles, which were lower in the individual setting. Using cut-off points from the collective in the individual setting therefore resulted in a small number of cases, 2 to 3%, while ∼10% is expected. Conclusion The SDQ has the same connotation across the individual and collective setting. The observed structural differences regarding the mean scores, however, undermine the validity of the cross-use of absolute SDQ-scores between these settings. Applying cut-off scores from the collective setting in the individual setting could, therefore, result in invalid conclusions and potential misuse of the instrument. To correctly apply cut-off scores these should be retrieved from the applied setting. PMID:25886464

Further evidence for cosmological evolution of the fine structure constant.

PubMed

Webb, J K; Murphy, M T; Flambaum, V V; Dzuba, V A; Barrow, J D; Churchill, C W; Prochaska, J X; Wolfe, A M

2001-08-27

We describe the results of a search for time variability of the fine structure constant alpha using absorption systems in the spectra of distant quasars. Three large optical data sets and two 21 cm and mm absorption systems provide four independent samples, spanning approximately 23% to 87% of the age of the universe. Each sample yields a smaller alpha in the past and the optical sample shows a 4 sigma deviation: Delta alpha/alpha = -0.72+/-0.18 x 10(-5) over the redshift range 0.5

Comparison of Feature Selection Techniques in Machine Learning for Anatomical Brain MRI in Dementia.

PubMed

Tohka, Jussi; Moradi, Elaheh; Huttunen, Heikki

2016-07-01

We present a comparative split-half resampling analysis of various data driven feature selection and classification methods for the whole brain voxel-based classification analysis of anatomical magnetic resonance images. We compared support vector machines (SVMs), with or without filter based feature selection, several embedded feature selection methods and stability selection. While comparisons of the accuracy of various classification methods have been reported previously, the variability of the out-of-training sample classification accuracy and the set of selected features due to independent training and test sets have not been previously addressed in a brain imaging context. We studied two classification problems: 1) Alzheimer's disease (AD) vs. normal control (NC) and 2) mild cognitive impairment (MCI) vs. NC classification. In AD vs. NC classification, the variability in the test accuracy due to the subject sample did not vary between different methods and exceeded the variability due to different classifiers. In MCI vs. NC classification, particularly with a large training set, embedded feature selection methods outperformed SVM-based ones with the difference in the test accuracy exceeding the test accuracy variability due to the subject sample. The filter and embedded methods produced divergent feature patterns for MCI vs. NC classification that suggests the utility of the embedded feature selection for this problem when linked with the good generalization performance. The stability of the feature sets was strongly correlated with the number of features selected, weakly correlated with the stability of classification accuracy, and uncorrelated with the average classification accuracy.

Expression signature as a biomarker for prenatal diagnosis of trisomy 21.

PubMed

Volk, Marija; Maver, Aleš; Lovrečić, Luca; Juvan, Peter; Peterlin, Borut

2013-01-01

A universal biomarker panel with the potential to predict high-risk pregnancies or adverse pregnancy outcome does not exist. Transcriptome analysis is a powerful tool to capture differentially expressed genes (DEG), which can be used as biomarker-diagnostic-predictive tool for various conditions in prenatal setting. In search of biomarker set for predicting high-risk pregnancies, we performed global expression profiling to find DEG in Ts21. Subsequently, we performed targeted validation and diagnostic performance evaluation on a larger group of case and control samples. Initially, transcriptomic profiles of 10 cultivated amniocyte samples with Ts21 and 9 with normal euploid constitution were determined using expression microarrays. Datasets from Ts21 transcriptomic studies from GEO repository were incorporated. DEG were discovered using linear regression modelling and validated using RT-PCR quantification on an independent sample of 16 cases with Ts21 and 32 controls. The classification performance of Ts21 status based on expression profiling was performed using supervised machine learning algorithm and evaluated using a leave-one-out cross validation approach. Global gene expression profiling has revealed significant expression changes between normal and Ts21 samples, which in combination with data from previously performed Ts21 transcriptomic studies, were used to generate a multi-gene biomarker for Ts21, comprising of 9 gene expression profiles. In addition to biomarker's high performance in discriminating samples from global expression profiling, we were also able to show its discriminatory performance on a larger sample set 2, validated using RT-PCR experiment (AUC=0.97), while its performance on data from previously published studies reached discriminatory AUC values of 1.00. Our results show that transcriptomic changes might potentially be used to discriminate trisomy of chromosome 21 in the prenatal setting. As expressional alterations reflect both, causal and reactive cellular mechanisms, transcriptomic changes may thus have future potential in the diagnosis of a wide array of heterogeneous diseases that result from genetic disturbances.

SET protein accumulates in HNSCC and contributes to cell survival: antioxidant defense, Akt phosphorylation and AVOs acidification.

PubMed

Leopoldino, Andréia M; Squarize, Cristiane H; Garcia, Cristiana B; Almeida, Luciana O; Pestana, Cezar R; Sobral, Lays M; Uyemura, Sérgio A; Tajara, Eloiza H; Silvio Gutkind, J; Curti, Carlos

2012-11-01

Determination of the SET protein levels in head and neck squamous cell carcinoma (HNSCC) tissue samples and the SET role in cell survival and response to oxidative stress in HNSCC cell lineages. SET protein was analyzed in 372 HNSCC tissue samples by immunohistochemistry using tissue microarray and HNSCC cell lineages. Oxidative stress was induced with the pro-oxidant tert-butylhydroperoxide (50 and 250μM) in the HNSCC HN13 cell lineage either with (siSET) or without (siNC) SET knockdown. Cell viability was evaluated by trypan blue exclusion and annexin V/propidium iodide assays. It was assessed caspase-3 and -9, PARP-1, DNA fragmentation, NM23-H1, SET, Akt and phosphorylated Akt (p-Akt) status. Acidic vesicular organelles (AVOs) were assessed by the acridine orange assay. Glutathione levels and transcripts of antioxidant genes were assayed by fluorometry and real time PCR, respectively. SET levels were up-regulated in 97% tumor tissue samples and in HNSCC cell lineages. SiSET in HN13 cells (i) promoted cell death but did not induced caspases, PARP-1 cleavage or DNA fragmentation, and (ii) decreased resistance to death induced by oxidative stress, indicating SET involvement through caspase-independent mechanism. The red fluorescence induced by siSET in HN13 cells in the acridine orange assay suggests SET-dependent prevention of AVOs acidification. NM23-H1 protein was restricted to the cytoplasm of siSET/siNC HN13 cells under oxidative stress, in association with decrease of cleaved SET levels. In the presence of oxidative stress, siNC HN13 cells showed lower GSH antioxidant defense (GSH/GSSG ratio) but higher expression of the antioxidant genes PRDX6, SOD2 and TXN compared to siSET HN13 cells. Still under oxidative stress, p-Akt levels were increased in siNC HN13 cells but not in siSET HN13, indicating its involvement in HN13 cell survival. Similar results for the main SET effects were observed in HN12 and CAL 27 cell lineages, except that HN13 cells were more resistant to death. SET is potential (i) marker for HNSCC associated with cancer cell resistance and (ii) new target in cancer therapy. Copyright © 2012 Elsevier Ltd. All rights reserved.

Prediction of physical-chemical properties of crude oils by 1H NMR analysis of neat samples and chemometrics.

PubMed

Masili, Alice; Puligheddu, Sonia; Sassu, Lorenzo; Scano, Paola; Lai, Adolfo

2012-11-01

In this work, we report the feasibility study to predict the properties of neat crude oil samples from 300-MHz NMR spectral data and partial least squares (PLS) regression models. The study was carried out on 64 crude oil samples obtained from 28 different extraction fields and aims at developing a rapid and reliable method for characterizing the crude oil in a fast and cost-effective way. The main properties generally employed for evaluating crudes' quality and behavior during refining were measured and used for calibration and testing of the PLS models. Among these, the UOP characterization factor K (K(UOP)) used to classify crude oils in terms of composition, density (D), total acidity number (TAN), sulfur content (S), and true boiling point (TBP) distillation yields were investigated. Test set validation with an independent set of data was used to evaluate model performance on the basis of standard error of prediction (SEP) statistics. Model performances are particularly good for K(UOP) factor, TAN, and TPB distillation yields, whose standard error of calibration and SEP values match the analytical method precision, while the results obtained for D and S are less accurate but still useful for predictions. Furthermore, a strategy that reduces spectral data preprocessing and sample preparation procedures has been adopted. The models developed with such an ample crude oil set demonstrate that this methodology can be applied with success to modern refining process requirements. Copyright © 2012 John Wiley & Sons, Ltd.

Flight program language requirements. Volume 3: Appendices

NASA Technical Reports Server (NTRS)

1972-01-01

Government-sponsored study and development efforts were directed toward design and implementation of high level programming languages suitable for future aerospace applications. The study centered around an evaluation of the four most pertinent existing aerospace languages. Evaluation criteria were established, and selected kernels from the current Saturn 5 and Skylab flight programs were used as benchmark problems for sample coding. An independent review of the language specifications incorporated anticipated future programming requirements into the evaluation. A set of language requirements was synthesized from these activities.

Neighbourhood Socioeconomic Status and Biological “Wear & Tear” in a Nationally Representative Sample of US Adults

PubMed Central

Bird, Chloe E; Seeman, Teresa; Escarce, José J; Basurto-Dávila, Ricardo; Finch, Brian K; Dubowitz, Tamara; Heron, Melonie; Hale, Lauren; Merkin, Sharon Stein; Weden, Margaret; Lurie, Nicole; Alcoa, Paul O’Neill

2012-01-01

Objective To assess whether neighbourhood socioeconomic status (NSES) is independently associated with disparities in biological “wear and tear”—measured by allostatic load (AL)—in a nationally representative sample of U.S. adults. Design Cross-sectional study. Setting Population-based U.S. survey, the Third National Health and Nutrition Examination Survey (NHANES III), merged with U.S. Census data describing respondents’ neighbourhoods. Participants 13,184 adults from 83 counties and 1,805 census tracts who completed NHANES III interviews and medical examinations and whose residential addresses could be reliably geocoded to census tracts. Main Outcome Measures A summary measure of biological risk, incorporating nine biomarkers that together represent AL across metabolic, cardiovascular, and inflammatory subindices. Results Being male, older, having lower income, less education, being Mexican-American, and being both Black and female were all independently associated with worse AL. After adjusting for these characteristics, living in a lower SES neighbourhood was associated with worse AL (coeff. = −0.46; CI −0.079, −0.012). The relationship between NSES and AL did not vary significantly by gender or race/ethnicity. Conclusions Living in a lower SES neighbourhood in the United States is associated with significantly greater biological wear and tear as measured by AL, and this relationship is independent of individual SES characteristics. Our findings demonstrate that where one lives is independently associated with AL, thereby suggesting that policies that improve NSES may also yield health returns. PMID:19759056

Physically motivated correlation formalism in hyperspectral imaging

NASA Astrophysics Data System (ADS)

Roy, Ankita; Rafert, J. Bruce

2004-05-01

Most remote sensing data-sets contain a limiting number of independent spatial and spectral measurements, beyond which no effective increase in information is achieved. This paper presents a Physically Motivated Correlation Formalism (PMCF) ,which places both Spatial and Spectral data on an equivalent mathematical footing in the context of a specific Kernel, such that, optimal combinations of independent data can be selected from the entire Hypercube via the method of "Correlation Moments". We present an experimental and computational analysis of Hyperspectral data sets using the Michigan Tech VFTHSI [Visible Fourier Transform Hyperspectral Imager] based on a Sagnac Interferometer, adjusted to obtain high SNR levels. The captured Signal Interferograms of different targets - aerial snaps of Houghton and lab-based data (white light , He-Ne laser , discharge tube sources) with the provision of customized scan of targets with the same exposures are processed using inverse imaging transformations and filtering techniques to obtain the Spectral profiles and generate Hypercubes to compute Spectral/Spatial/Cross Moments. PMCF answers the question of how optimally the entire hypercube should be sampled and finds how many spatial-spectral pixels are required for a particular target recognition.

Rapid antibiotic-resistance predictions from genome sequence data for Staphylococcus aureus and Mycobacterium tuberculosis

PubMed Central

Bradley, Phelim; Gordon, N. Claire; Walker, Timothy M.; Dunn, Laura; Heys, Simon; Huang, Bill; Earle, Sarah; Pankhurst, Louise J.; Anson, Luke; de Cesare, Mariateresa; Piazza, Paolo; Votintseva, Antonina A.; Golubchik, Tanya; Wilson, Daniel J.; Wyllie, David H.; Diel, Roland; Niemann, Stefan; Feuerriegel, Silke; Kohl, Thomas A.; Ismail, Nazir; Omar, Shaheed V.; Smith, E. Grace; Buck, David; McVean, Gil; Walker, A. Sarah; Peto, Tim E. A.; Crook, Derrick W.; Iqbal, Zamin

2015-01-01

The rise of antibiotic-resistant bacteria has led to an urgent need for rapid detection of drug resistance in clinical samples, and improvements in global surveillance. Here we show how de Bruijn graph representation of bacterial diversity can be used to identify species and resistance profiles of clinical isolates. We implement this method for Staphylococcus aureus and Mycobacterium tuberculosis in a software package (‘Mykrobe predictor') that takes raw sequence data as input, and generates a clinician-friendly report within 3 minutes on a laptop. For S. aureus, the error rates of our method are comparable to gold-standard phenotypic methods, with sensitivity/specificity of 99.1%/99.6% across 12 antibiotics (using an independent validation set, n=470). For M. tuberculosis, our method predicts resistance with sensitivity/specificity of 82.6%/98.5% (independent validation set, n=1,609); sensitivity is lower here, probably because of limited understanding of the underlying genetic mechanisms. We give evidence that minor alleles improve detection of extremely drug-resistant strains, and demonstrate feasibility of the use of emerging single-molecule nanopore sequencing techniques for these purposes. PMID:26686880

Jet Stream Analysis and Forecast Errors Using GADS Aircraft Observations in the DAO, ECMWF, and NCEP Models

NASA Technical Reports Server (NTRS)

Cardinali, Carla; Rukhovets, Leonid; Tenenbaum, Joel

2003-01-01

We have utilized an extensive set of independent British Airways flight data recording wind vector and temperature observations (the Global Aircraft Data Set [GADS] archive) in three ways: (a) as an independent check of operational analyses; (b) as an analysis observing system experiment (OSE) as if the GADS observations were available in real time; and (c) as the corresponding forecast simulation experiment applicable to future operational forecasts. Using a 31 day sample (0000 UTC 20 December 2000 through 0000 UTC 20 January 2000) from Winter 2000, we conclude that over the data-dense continental U. S. analyzed jet streaks are too weak by -2% to -5%. Over nearby data-sparse regions of Canada, analyzed jet streaks are too weak by -5% to -9%. The second range provides a limit on the accuracy of current jet streak analyses over the portions of the -85% of the earth's surface that are poorly covered by non-satellite observations. The -5% to -9% range is relevant for the pre-third generation satellite (AIRS, IASI, GIFTS) era.

Predictive models for radial sap flux variation in coniferous, diffuse-porous and ring-porous temperate trees.

PubMed

Berdanier, Aaron B; Miniat, Chelcy F; Clark, James S

2016-08-01

Accurately scaling sap flux observations to tree or stand levels requires accounting for variation in sap flux between wood types and by depth into the tree. However, existing models for radial variation in axial sap flux are rarely used because they are difficult to implement, there is uncertainty about their predictive ability and calibration measurements are often unavailable. Here we compare different models with a diverse sap flux data set to test the hypotheses that radial profiles differ by wood type and tree size. We show that radial variation in sap flux is dependent on wood type but independent of tree size for a range of temperate trees. The best-fitting model predicted out-of-sample sap flux observations and independent estimates of sapwood area with small errors, suggesting robustness in the new settings. We develop a method for predicting whole-tree water use with this model and include computer code for simple implementation in other studies. Published by Oxford University Press 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

A concept of a MIABIS based register of biosample collections at the Medical University of Innsbruck.

PubMed

Hofer, Philipp; Fiegl, Heidi; Angerer, Justina; Mueller-Holzner, Elisabeth; Chamson, Martina; Klocker, Helmut; Steiner, Eberhardt; Hauffe, Helga; Zschocke, Johannes; Goebel, Georg

2014-01-01

The knowledge about the quality of samples and associated clinical data in biospecimen collections is a premise of clinical research. An electronic biosample register aims to facilitate the discovery of information about biosample collections in a hospital. Moreover, it might improve scientific collaboration and research quality through a shared access to harmonized sample collection description data. The aim of this paper is to present a concept of a web-based biosample register of the existing biosample collections at the Medical University of Innsbruck. A uniform description model is built based on an analysis of the sample collection data of independent sample management systems from two departments within the hospital. An extended set of attributes of the minimum dataset used by the Swedish sample collection register (MIABIS) has been applied to all biosample collections as a common description model. The results of the analysis and the data model are presented together with a first concept of a sample collection search register.

A 6-gene signature identifies four molecular subgroups of neuroblastoma

PubMed Central

2011-01-01

Background There are currently three postulated genomic subtypes of the childhood tumour neuroblastoma (NB); Type 1, Type 2A, and Type 2B. The most aggressive forms of NB are characterized by amplification of the oncogene MYCN (MNA) and low expression of the favourable marker NTRK1. Recently, mutations or high expression of the familial predisposition gene Anaplastic Lymphoma Kinase (ALK) was associated to unfavourable biology of sporadic NB. Also, various other genes have been linked to NB pathogenesis. Results The present study explores subgroup discrimination by gene expression profiling using three published microarray studies on NB (47 samples). Four distinct clusters were identified by Principal Components Analysis (PCA) in two separate data sets, which could be verified by an unsupervised hierarchical clustering in a third independent data set (101 NB samples) using a set of 74 discriminative genes. The expression signature of six NB-associated genes ALK, BIRC5, CCND1, MYCN, NTRK1, and PHOX2B, significantly discriminated the four clusters (p < 0.05, one-way ANOVA test). PCA clusters p1, p2, and p3 were found to correspond well to the postulated subtypes 1, 2A, and 2B, respectively. Remarkably, a fourth novel cluster was detected in all three independent data sets. This cluster comprised mainly 11q-deleted MNA-negative tumours with low expression of ALK, BIRC5, and PHOX2B, and was significantly associated with higher tumour stage, poor outcome and poor survival compared to the Type 1-corresponding favourable group (INSS stage 4 and/or dead of disease, p < 0.05, Fisher's exact test). Conclusions Based on expression profiling we have identified four molecular subgroups of neuroblastoma, which can be distinguished by a 6-gene signature. The fourth subgroup has not been described elsewhere, and efforts are currently made to further investigate this group's specific characteristics. PMID:21492432

Verifying the operational set-up of a radionuclide air-monitoring station.

PubMed

Werzi, R; Padoani, F

2007-05-01

A worldwide radionuclide network of 80 stations, part of the International Monitoring System, was designed to monitor compliance with the Comprehensive Nuclear-Test-Ban Treaty. After installation, the stations are certified to comply with the minimum requirements laid down by the Preparatory Commission of the Comprehensive Nuclear-Test-Ban Treaty Organization. Among the several certification tests carried out at each station, the verification of the radionuclide activity concentrations is a crucial one and is based on an independent testing of the airflow rate measurement system and of the gamma detector system, as well as on the assessment of the samples collected during parallel sampling and measured at radionuclide laboratories.

Association of High Myopia with Crystallin Beta A4 (CRYBA4) Gene Polymorphisms in the Linkage-Identified MYP6 Locus

PubMed Central

Ho, Daniel W. H.; Yap, Maurice K. H.; Ng, Po Wah; Fung, Wai Yan; Yip, Shea Ping

2012-01-01

Background Myopia is the most common ocular disorder worldwide and imposes tremendous burden on the society. It is a complex disease. The MYP6 locus at 22 q12 is of particular interest because many studies have detected linkage signals at this interval. The MYP6 locus is likely to contain susceptibility gene(s) for myopia, but none has yet been identified. Methodology/Principal Findings Two independent subject groups of southern Chinese in Hong Kong participated in the study an initial study using a discovery sample set of 342 cases and 342 controls, and a follow-up study using a replication sample set of 316 cases and 313 controls. Cases with high myopia were defined by spherical equivalent ≤ -8 dioptres and emmetropic controls by spherical equivalent within ±1.00 dioptre for both eyes. Manual candidate gene selection from the MYP6 locus was supported by objective in silico prioritization. DNA samples of discovery sample set were genotyped for 178 tagging single nucleotide polymorphisms (SNPs) from 26 genes. For replication, 25 SNPs (tagging or located at predicted transcription factor or microRNA binding sites) from 4 genes were subsequently examined using the replication sample set. Fisher P value was calculated for all SNPs and overall association results were summarized by meta-analysis. Based on initial and replication studies, rs2009066 located in the crystallin beta A4 (CRYBA4) gene was identified to be the most significantly associated with high myopia (initial study: P = 0.02; replication study: P = 1.88e-4; meta-analysis: P = 1.54e-5) among all the SNPs tested. The association result survived correction for multiple comparisons. Under the allelic genetic model for the combined sample set, the odds ratio of the minor allele G was 1.41 (95% confidence intervals, 1.21-1.64). Conclusions/Significance A novel susceptibility gene (CRYBA4) was discovered for high myopia. Our study also signified the potential importance of appropriate gene prioritization in candidate selection. PMID:22792142

Psychometric evaluation of the Revised Professional Practice Environment (RPPE) scale.

PubMed

Erickson, Jeanette Ives; Duffy, Mary E; Ditomassi, Marianne; Jones, Dorothy

2009-05-01

The purpose was to examine the psychometric properties of the Revised Professional Practice Environment (RPPE) scale. Despite renewed focus on studying health professionals' practice environments, there are still few reliable and valid instruments available to assist nurse administrators in decision making. A psychometric evaluation using a random-sample cross-validation procedure (calibration sample [CS], n = 775; validation sample [VS], n = 775) was undertaken. Cronbach alpha internal consistency reliability of the total score (r = 0.93 [CS] and 0.92 [VS]), resulting subscale scores (r range: 0.80-0.87 [CS], 0.81-0.88 [VS]), and principal components analyses with Varimax rotation and Kaiser normalization (8 components, 59.2% variance [CS], 59.7% [VS]) produced almost identical results in both samples. The multidimensional RPPE is a psychometrically sound measure of 8 components of the professional practice environment in the acute care setting and sufficiently reliable and valid for use as independent subscales in healthcare research.

Genetic Predisposition to Ischemic Stroke

PubMed Central

Kamatani, Yoichiro; Takahashi, Atsushi; Hata, Jun; Furukawa, Ryohei; Shiwa, Yuh; Yamaji, Taiki; Hara, Megumi; Tanno, Kozo; Ohmomo, Hideki; Ono, Kanako; Takashima, Naoyuki; Matsuda, Koichi; Wakai, Kenji; Sawada, Norie; Iwasaki, Motoki; Yamagishi, Kazumasa; Ago, Tetsuro; Ninomiya, Toshiharu; Fukushima, Akimune; Hozawa, Atsushi; Minegishi, Naoko; Satoh, Mamoru; Endo, Ryujin; Sasaki, Makoto; Sakata, Kiyomi; Kobayashi, Seiichiro; Ogasawara, Kuniaki; Nakamura, Motoyuki; Hitomi, Jiro; Kita, Yoshikuni; Tanaka, Keitaro; Iso, Hiroyasu; Kitazono, Takanari; Kubo, Michiaki; Tanaka, Hideo; Tsugane, Shoichiro; Kiyohara, Yutaka; Yamamoto, Masayuki; Sobue, Kenji; Shimizu, Atsushi

2017-01-01

Background and Purpose— The prediction of genetic predispositions to ischemic stroke (IS) may allow the identification of individuals at elevated risk and thereby prevent IS in clinical practice. Previously developed weighted multilocus genetic risk scores showed limited predictive ability for IS. Here, we investigated the predictive ability of a newer method, polygenic risk score (polyGRS), based on the idea that a few strong signals, as well as several weaker signals, can be collectively informative to determine IS risk. Methods— We genotyped 13 214 Japanese individuals with IS and 26 470 controls (derivation samples) and generated both multilocus genetic risk scores and polyGRS, using the same derivation data set. The predictive abilities of each scoring system were then assessed using 2 independent sets of Japanese samples (KyushuU and JPJM data sets). Results— In both validation data sets, polyGRS was shown to be significantly associated with IS, but weighted multilocus genetic risk scores was not. Comparing the highest with the lowest polyGRS quintile, the odds ratios for IS were 1.75 (95% confidence interval, 1.33–2.31) and 1.99 (95% confidence interval, 1.19–3.33) in the KyushuU and JPJM samples, respectively. Using the KyushuU samples, the addition of polyGRS to a nongenetic risk model resulted in a significant improvement of the predictive ability (net reclassification improvement=0.151; P<0.001). Conclusions— The polyGRS was shown to be superior to weighted multilocus genetic risk scores as an IS prediction model. Thus, together with the nongenetic risk factors, polyGRS will provide valuable information for individual risk assessment and management of modifiable risk factors. PMID:28034966

Evaluation of Elecsys Syphilis Assay for Routine and Blood Screening and Detection of Early Infection

PubMed Central

Kremastinou, J.; Polymerou, V.; Lavranos, D.; Aranda Arrufat, A.; Harwood, J.; Martínez Lorenzo, M. J.; Ng, K. P.; Queiros, L.; Vereb, I.

2016-01-01

Treponema pallidum infections can have severe complications if not diagnosed and treated at an early stage. Screening and diagnosis of syphilis require assays with high specificity and sensitivity. The Elecsys Syphilis assay is an automated treponemal immunoassay for the detection of antibodies against T. pallidum. The performance of this assay was investigated previously in a multicenter study. The current study expands on that evaluation in a variety of diagnostic settings and patient populations, at seven independent laboratories. The samples included routine diagnostic samples, blood donation samples, samples from patients with confirmed HIV infections, samples from living organ or bone marrow donors, and banked samples, including samples previously confirmed as syphilis positive. This study also investigated the seroconversion sensitivity of the assay. With a total of 1,965 syphilis-negative routine diagnostic samples and 5,792 syphilis-negative samples collected from blood donations, the Elecsys Syphilis assay had specificity values of 99.85% and 99.86%, respectively. With 333 samples previously identified as syphilis positive, the sensitivity was 100% regardless of disease stage. The assay also showed 100% sensitivity and specificity with samples from 69 patients coinfected with HIV. The Elecsys Syphilis assay detected infection in the same bleed or earlier, compared with comparator assays, in a set of sequential samples from a patient with primary syphilis. In archived serial blood samples collected from 14 patients with direct diagnoses of primary syphilis, the Elecsys Syphilis assay detected T. pallidum antibodies for 3 patients for whom antibodies were not detected with the Architect Syphilis TP assay, indicating a trend for earlier detection of infection, which may have the potential to shorten the time between infection and reactive screening test results. PMID:27358468

AN INDEPENDENT MEASUREMENT OF THE INCIDENCE OF Mg II ABSORBERS ALONG GAMMA-RAY BURST SIGHT LINES: THE END OF THE MYSTERY?

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

Cucchiara, A.; Prochaska, J. X.; Zhu, G.

2013-08-20

In 2006, Prochter et al. reported a statistically significant enhancement of very strong Mg II absorption systems intervening the sight lines to gamma-ray bursts (GRBs) relative to the incidence of such absorption along quasar sight lines. This counterintuitive result has inspired a diverse set of astrophysical explanations (e.g., dust, gravitational lensing) but none of these has obviously resolved the puzzle. Using the largest set of GRB afterglow spectra available, we reexamine the purported enhancement. In an independent sample of GRB spectra with a survey path three times larger than Prochter et al., we measure the incidence per unit redshift ofmore » {>=}1 A rest-frame equivalent width Mg II absorbers at z Almost-Equal-To 1 to be l(z) = 0.18 {+-} 0.06. This is fully consistent with current estimates for the incidence of such absorbers along quasar sight lines. Therefore, we do not confirm the original enhancement and suggest those results suffered from a statistical fluke. Signatures of the original result do remain in our full sample (l(z) shows an Almost-Equal-To 1.5 enhancement over l(z){sub QSO}), but the statistical significance now lies at Almost-Equal-To 90% c.l. Restricting our analysis to the subset of high-resolution spectra of GRB afterglows (which overlaps substantially with Prochter et al.), we still reproduce a statistically significant enhancement of Mg II absorption. The reason for this excess, if real, is still unclear since there is no connection between the rapid afterglow follow-up process with echelle (or echellette) spectrographs and the detectability of strong Mg II doublets. Only a larger sample of such high-resolution data will shed some light on this matter.« less

Excavating past population structures by surname-based sampling: the genetic legacy of the Vikings in northwest England

PubMed Central

Bowden, Georgina R.; Balaresque, Patricia; King, Turi E.; Hansen, Ziff; Lee, Andrew C.; Pergl-Wilson, Giles; Hurley, Emma; Roberts, Stephen J.; Waite, Patrick; Jesch, Judith; Jones, Abigail L.; Thomas, Mark G.; Harding, Stephen E.; Jobling, Mark A.

2009-01-01

The genetic structures of past human populations are obscured by recent migrations and expansions, and can been observed only indirectly by inference from modern samples. However, the unique link between a heritable cultural marker, the patrilineal surname, and a genetic marker, the Y chromosome, provides a means to target sets of modern individuals that might resemble populations at the time of surname establishment. As a test case, we studied samples from the Wirral peninsula and West Lancashire, in northwest England. Place names and archaeology show clear evidence of a past Viking presence, but heavy immigration and population growth since the Industrial Revolution are likely to have weakened the genetic signal of a thousand-year-old Scandinavian contribution. Samples ascertained on the basis of two generations of residence were compared with independent samples based on known ancestry in the region, plus the possession of a surname known from historical records to have been present there in medieval times. The Y-chromosomal haplotypes of these two sets of samples are significantly different, and in admixture analyses the surname-ascertained samples show markedly greater Scandinavian ancestry proportions, supporting the idea that northwest England was once heavily populated by Scandinavian settlers. The method of historical surname-based ascertainment promises to allow investigation of the influence of migration and drift over the last few centuries in changing the population structure of Britain, and will have general utility in other regions where surnames are patrilineal and suitable historical records survive. PMID:18032405

Disequilibrium and human capital in pharmacy labor markets: evidence from four states.

PubMed

Cline, Richard R

2003-01-01

To estimate the association between pharmacists' stocks of human capital (work experience and education), practice setting, demographics, and wage rates in the overall labor market and to estimate the association between these same variables and wage rates within six distinct pharmacy employment sectors. Wage estimation is used as a proxy measure of demand for pharmacists' services. Descriptive survey analysis. Illinois, Minnesota, Ohio, and Wisconsin. Licensed pharmacists working 30 or more hours per week. Analysis of data collected with cross-sectional mail surveys conducted in four states. Hourly wage rates for all pharmacists working 30 or more hours per week and hourly wage rates for pharmacists employed in large chain, independent, mass-merchandiser, hospital, health maintenance organization (HMO), and other settings. A total of 2,235 responses were received, for an adjusted response rate of 53.1%. Application of exclusion criteria left 1,450 responses from full-time pharmacists to analyze. Results from estimations of wages in the pooled sample and for pharmacists in the hospital setting suggest that advanced training and years of experience are associated positively with higher hourly wages. Years of experience were also associated positively with higher wages in independent and other settings, while neither advanced education nor experience was related to wages in large chain, mass-merchandiser, or HMO settings. Overall, the market for full-time pharmacists' labor is competitive, and employers pay wage premiums to those with larger stocks of human capital, especially advanced education and more years of pharmacy practice experience. The evidence supports the hypothesis that demand is exceeding supply in select employment sectors.

Extending the utility of the Depression Anxiety Stress scale by examining its psychometric properties in Chinese settings.

PubMed

Chan, Raymond C K; Xu, Ting; Huang, Jia; Wang, Yi; Zhao, Qing; Shum, David H K; O'Gorman, John; Potangaroa, Regan

2012-12-30

The Depression Anxiety Stress scale (DASS) is a widely used instrument for assessing mental health status, but the construct validity of the Chinese version of the test has not been demonstrated. The current study recruited three independent samples of Chinese participants to examine its reliability, factor structure, and utility in differentiating groups expected to show high and low scores on the scales. The first sample comprised 605 undergraduate student volunteers from Beijing, the second sample comprised 138 residents from the Sichuan Province who had experienced the 2008 earthquake there, and the third sample comprised 86 Beijing residents. Cronbach's alpha values in excess of 0.80 were found for all samples and all scales. Confirmatory factor analysis with the student sample supported a three-factor latent structure for the DASS (depression, anxiety, and stress). Substantially higher scores on all scales were found for the Sichuan earthquake sample compared with the Beijing resident's sample. Implications of these findings for the assessment of mental status using the DASS in China are discussed. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

BloodSpot: a database of gene expression profiles and transcriptional programs for healthy and malignant haematopoiesis.

PubMed

Bagger, Frederik Otzen; Sasivarevic, Damir; Sohi, Sina Hadi; Laursen, Linea Gøricke; Pundhir, Sachin; Sønderby, Casper Kaae; Winther, Ole; Rapin, Nicolas; Porse, Bo T

2016-01-04

Research on human and murine haematopoiesis has resulted in a vast number of gene-expression data sets that can potentially answer questions regarding normal and aberrant blood formation. To researchers and clinicians with limited bioinformatics experience, these data have remained available, yet largely inaccessible. Current databases provide information about gene-expression but fail to answer key questions regarding co-regulation, genetic programs or effect on patient survival. To address these shortcomings, we present BloodSpot (www.bloodspot.eu), which includes and greatly extends our previously released database HemaExplorer, a database of gene expression profiles from FACS sorted healthy and malignant haematopoietic cells. A revised interactive interface simultaneously provides a plot of gene expression along with a Kaplan-Meier analysis and a hierarchical tree depicting the relationship between different cell types in the database. The database now includes 23 high-quality curated data sets relevant to normal and malignant blood formation and, in addition, we have assembled and built a unique integrated data set, BloodPool. Bloodpool contains more than 2000 samples assembled from six independent studies on acute myeloid leukemia. Furthermore, we have devised a robust sample integration procedure that allows for sensitive comparison of user-supplied patient samples in a well-defined haematopoietic cellular space. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

The evolution of phylogeographic data sets.

PubMed

Garrick, Ryan C; Bonatelli, Isabel A S; Hyseni, Chaz; Morales, Ariadna; Pelletier, Tara A; Perez, Manolo F; Rice, Edwin; Satler, Jordan D; Symula, Rebecca E; Thomé, Maria Tereza C; Carstens, Bryan C

2015-03-01

Empirical phylogeographic studies have progressively sampled greater numbers of loci over time, in part motivated by theoretical papers showing that estimates of key demographic parameters improve as the number of loci increases. Recently, next-generation sequencing has been applied to questions about organismal history, with the promise of revolutionizing the field. However, no systematic assessment of how phylogeographic data sets have changed over time with respect to overall size and information content has been performed. Here, we quantify the changing nature of these genetic data sets over the past 20 years, focusing on papers published in Molecular Ecology. We found that the number of independent loci, the total number of alleles sampled and the total number of single nucleotide polymorphisms (SNPs) per data set has improved over time, with particularly dramatic increases within the past 5 years. Interestingly, uniparentally inherited organellar markers (e.g. animal mitochondrial and plant chloroplast DNA) continue to represent an important component of phylogeographic data. Single-species studies (cf. comparative studies) that focus on vertebrates (particularly fish and to some extent, birds) represent the gold standard of phylogeographic data collection. Based on the current trajectory seen in our survey data, forecast modelling indicates that the median number of SNPs per data set for studies published by the end of the year 2016 may approach ~20,000. This survey provides baseline information for understanding the evolution of phylogeographic data sets and underscores the fact that development of analytical methods for handling very large genetic data sets will be critical for facilitating growth of the field. © 2015 John Wiley & Sons Ltd.

Macrodissection prior to closed system RT-qPCR is not necessary for estrogen receptor and HER2 concordance with IHC/FISH in breast cancer.

PubMed

Gupta, Swati; Mani, Navin R; Carvajal-Hausdorf, Daniel E; Bossuyt, Veerle; Ho, Kenneth; Weidler, Jodi; Wong, Wendy; Rhees, Brian; Bates, Michael; Rimm, David L

2018-06-01

An on-demand, closed RT-qPCR, the GeneXpert (GX) system, has the potential to provide biomarker information in low-resourced settings and elsewhere. We used this system with a research use only version of the Breast Cancer STRAT4 cartridge that measures the mRNA expression levels of ERBB2, ESR1, PGR, and MKi67. Here we evaluated the impact of non-macrodissected (non m-d) versus macrodissected (m-d) samples using STRAT4 on formalin-fixed, paraffin-embedded (FFPE) core needle biopsies. Two cohorts were assessed: (1) 60 FFPE infiltrating ductal carcinoma (IDCA) cases and (2) 20 FFPE IDCA cases with ductal carcinoma in situ (DCIS) with a range of HER2 expression as determined by clinical immunohistochemistry and fluorescence in situ hybridization (IHC/FISH). We observed about half of the core needle biopsy area as invasive tumor in both IDCA (mean = 51.5%) and IDCA with DCIS (mean = 53.5%) cohorts, but also found the mRNA levels were independent of tumor area. We found excellent agreement of the mRNA transcript level between the paired samples, m-d versus non m-d, for ERBB2, ESR1, PGR, and MKi67 for both the IDCA and IDCA with DCIS cohorts. No significant difference (P > 0.99) was observed when we compared the mRNA transcript level between the paired samples m-d versus non m-d. In addition, we noted a significant concordance (P < 0.001) between RT-qPCR and IHC/FISH for HER2-positivity, ER-positivity, and PR-positivity, independent of specimen dissection. These data suggest that mRNA expression for ERBB2, ESR, and PGR is sufficiently low in surrounding tissue cells such that macrodissection is not required for assessment of key breast cancer mRNA markers and is independent of the amount of input tumor. This approach may be valuable in settings lacking pathology expertise or using specimen types, such as fine-needle aspirates, where it may be challenging to separate non-tumor from tumor tissue.

[Development of the soft independent modelling of class analogies model to discrimination Vibrio parahemolyticus by Smartongue].

PubMed

Huang, Jianfeng; Zhao, Guangying; Dou, Wenchao

2011-04-01

To explore a new rapid detection method for detecting of Food pathogens. We used the Smartongue, to determine the composition informations of the liquid culture samples and combined with soft independent modelling of class analogies (SIMCA) to analyze their respective species, then set up a Smartongue -SIMCA model to discriminate the V. parahaemolyticus. The Smartongue has 6 working electrodes and three frequency segments, we can built 18 discrimination models in one detection. After comparing all the 18 discrimination models, the optimal working electrodes and frequency segments were selected out, they were: palladium electrode in 1 Hz frequency segment, tungsten electrode in 100 Hz and silver electrode in 100 Hz. Then 10 species of pathogenic Vibrio were discriminated by the 3 models. The V. damsela, V. metschnikovii, V. alginalyticus, V. cincinnatiensis, V. metschnikovii and V. cholerae O serogroup samples could be discriminated by the SIMCA model of V. parahaemolyticus with palladium electrode 1 Hz frequency segment; V. mimicus and V. vulnincus samples could be discriminated by the SIMCA model of V. parahaemolyticus with tungsten electrode 100 Hz frequency segment; V. carcariae and V. cholerae non-O serogroup samples could be discriminated with the SIMCA model of V. parahaemolyticus in silver electrode 100 Hz frequency segment. The accurate discrimination of ten species of Vibrio samples is 100%. The Smartongue combined with SIMCA can discriminate V. parahaemolyticus with other pathogenic Vibrio effectively. It has a promising future as a new rapid detection method for V. parahaemolyticus.

A simple linear model for estimating ozone AOT40 at forest sites from raw passive sampling data.

PubMed

Ferretti, Marco; Cristofolini, Fabiana; Cristofori, Antonella; Gerosa, Giacomo; Gottardini, Elena

2012-08-01

A rapid, empirical method is described for estimating weekly AOT40 from ozone concentrations measured with passive samplers at forest sites. The method is based on linear regression and was developed after three years of measurements in Trentino (northern Italy). It was tested against an independent set of data from passive sampler sites across Italy. It provides good weekly estimates compared with those measured by conventional monitors (0.85 ≤R(2)≤ 0.970; 97 ≤ RMSE ≤ 302). Estimates obtained using passive sampling at forest sites are comparable to those obtained by another estimation method based on modelling hourly concentrations (R(2) = 0.94; 131 ≤ RMSE ≤ 351). Regression coefficients of passive sampling are similar to those obtained with conventional monitors at forest sites. Testing against an independent dataset generated by passive sampling provided similar results (0.86 ≤R(2)≤ 0.99; 65 ≤ RMSE ≤ 478). Errors tend to accumulate when weekly AOT40 estimates are summed to obtain the total AOT40 over the May-July period, and the median deviation between the two estimation methods based on passive sampling is 11%. The method proposed does not require any assumptions, complex calculation or modelling technique, and can be useful when other estimation methods are not feasible, either in principle or in practice. However, the method is not useful when estimates of hourly concentrations are of interest.

The influence of tobacco countermarketing ads on college students' knowledge, attitudes, and beliefs.

PubMed

Murphy-Hoefer, Rebecca; Hyland, Andrew; Rivard, Cheryl

2010-01-01

To determine which antitobacco messages were perceived effective in changing college students' knowledge, attitudes, and beliefs about tobacco use. College students (n = 1,020) were surveyed before and after viewing 4 30-second antitobacco advertisements in 1 of 3 theme categories-social norms, health consequences, or tobacco industry manipulation. An independent samples t test was used to test for differences in the mean responses to the knowledge, attitude, and belief questions at posttest by smoking status and gender. Health consequences ads significantly increased overall knowledge and negative attitudes and beliefs. Findings from this study may help health educators who work in college settings and other young adult settings to include media messages as part of a comprehensive tobacco control program.

Transforming reflectance spectra into Munsell color space by using prime colors.

PubMed

Romney, A Kimball; Fulton, James T

2006-10-17

Independent researchers have proved mathematically that, given a set of color-matching functions, there exists a unique set of three monochromatic spectral lights that optimizes luminous efficiency and color gamut. These lights are called prime colors. We present a method for transforming reflectance spectra into Munsell color space by using hypothetical absorbance curves based on Gaussian approximations of the prime colors and a simplified version of opponent process theory. The derived color appearance system is represented as a 3D color system that is qualitatively similar to a conceptual representation of the Munsell color system. We illustrate the application of the model and compare it with existing models by using reflectance spectra obtained from 1,269 Munsell color samples.

Detecting concerted demographic response across community assemblages using hierarchical approximate Bayesian computation.

PubMed

Chan, Yvonne L; Schanzenbach, David; Hickerson, Michael J

2014-09-01

Methods that integrate population-level sampling from multiple taxa into a single community-level analysis are an essential addition to the comparative phylogeographic toolkit. Detecting how species within communities have demographically tracked each other in space and time is important for understanding the effects of future climate and landscape changes and the resulting acceleration of extinctions, biological invasions, and potential surges in adaptive evolution. Here, we present a statistical framework for such an analysis based on hierarchical approximate Bayesian computation (hABC) with the goal of detecting concerted demographic histories across an ecological assemblage. Our method combines population genetic data sets from multiple taxa into a single analysis to estimate: 1) the proportion of a community sample that demographically expanded in a temporally clustered pulse and 2) when the pulse occurred. To validate the accuracy and utility of this new approach, we use simulation cross-validation experiments and subsequently analyze an empirical data set of 32 avian populations from Australia that are hypothesized to have expanded from smaller refugia populations in the late Pleistocene. The method can accommodate data set heterogeneity such as variability in effective population size, mutation rates, and sample sizes across species and exploits the statistical strength from the simultaneous analysis of multiple species. This hABC framework used in a multitaxa demographic context can increase our understanding of the impact of historical climate change by determining what proportion of the community responded in concert or independently and can be used with a wide variety of comparative phylogeographic data sets as biota-wide DNA barcoding data sets accumulate. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Estimating the efficacy of Alcoholics Anonymous without self-selection bias: an instrumental variables re-analysis of randomized clinical trials.

PubMed

Humphreys, Keith; Blodgett, Janet C; Wagner, Todd H

2014-11-01

Observational studies of Alcoholics Anonymous' (AA) effectiveness are vulnerable to self-selection bias because individuals choose whether or not to attend AA. The present study, therefore, employed an innovative statistical technique to derive a selection bias-free estimate of AA's impact. Six data sets from 5 National Institutes of Health-funded randomized trials (1 with 2 independent parallel arms) of AA facilitation interventions were analyzed using instrumental variables models. Alcohol-dependent individuals in one of the data sets (n = 774) were analyzed separately from the rest of sample (n = 1,582 individuals pooled from 5 data sets) because of heterogeneity in sample parameters. Randomization itself was used as the instrumental variable. Randomization was a good instrument in both samples, effectively predicting increased AA attendance that could not be attributed to self-selection. In 5 of the 6 data sets, which were pooled for analysis, increased AA attendance that was attributable to randomization (i.e., free of self-selection bias) was effective at increasing days of abstinence at 3-month (B = 0.38, p = 0.001) and 15-month (B = 0.42, p = 0.04) follow-up. However, in the remaining data set, in which preexisting AA attendance was much higher, further increases in AA involvement caused by the randomly assigned facilitation intervention did not affect drinking outcome. For most individuals seeking help for alcohol problems, increasing AA attendance leads to short- and long-term decreases in alcohol consumption that cannot be attributed to self-selection. However, for populations with high preexisting AA involvement, further increases in AA attendance may have little impact. Copyright © 2014 by the Research Society on Alcoholism.

Partial least squares density modeling (PLS-DM) - a new class-modeling strategy applied to the authentication of olives in brine by near-infrared spectroscopy.

PubMed

Oliveri, Paolo; López, M Isabel; Casolino, M Chiara; Ruisánchez, Itziar; Callao, M Pilar; Medini, Luca; Lanteri, Silvia

2014-12-03

A new class-modeling method, referred to as partial least squares density modeling (PLS-DM), is presented. The method is based on partial least squares (PLS), using a distance-based sample density measurement as the response variable. Potential function probability density is subsequently calculated on PLS scores and used, jointly with residual Q statistics, to develop efficient class models. The influence of adjustable model parameters on the resulting performances has been critically studied by means of cross-validation and application of the Pareto optimality criterion. The method has been applied to verify the authenticity of olives in brine from cultivar Taggiasca, based on near-infrared (NIR) spectra recorded on homogenized solid samples. Two independent test sets were used for model validation. The final optimal model was characterized by high efficiency and equilibrate balance between sensitivity and specificity values, if compared with those obtained by application of well-established class-modeling methods, such as soft independent modeling of class analogy (SIMCA) and unequal dispersed classes (UNEQ). Copyright © 2014 Elsevier B.V. All rights reserved.

Dimension independence in exterior algebra.

PubMed Central

Hawrylycz, M

1995-01-01

The identities between homogeneous expressions in rank 1 vectors and rank n - 1 covectors in a Grassmann-Cayley algebra of rank n, in which one set occurs multilinearly, are shown to represent a set of dimension-independent identities. The theorem yields an infinite set of nontrivial geometric identities from a given identity. PMID:11607520

Deletion of the GluA1 AMPA receptor subunit impairs recency-dependent object recognition memory

PubMed Central

Sanderson, David J.; Hindley, Emma; Smeaton, Emily; Denny, Nick; Taylor, Amy; Barkus, Chris; Sprengel, Rolf; Seeburg, Peter H.; Bannerman, David M.

2011-01-01

Deletion of the GluA1 AMPA receptor subunit impairs short-term spatial recognition memory. It has been suggested that short-term recognition depends upon memory caused by the recent presentation of a stimulus that is independent of contextual–retrieval processes. The aim of the present set of experiments was to test whether the role of GluA1 extends to nonspatial recognition memory. Wild-type and GluA1 knockout mice were tested on the standard object recognition task and a context-independent recognition task that required recency-dependent memory. In a first set of experiments it was found that GluA1 deletion failed to impair performance on either of the object recognition or recency-dependent tasks. However, GluA1 knockout mice displayed increased levels of exploration of the objects in both the sample and test phases compared to controls. In contrast, when the time that GluA1 knockout mice spent exploring the objects was yoked to control mice during the sample phase, it was found that GluA1 deletion now impaired performance on both the object recognition and the recency-dependent tasks. GluA1 deletion failed to impair performance on a context-dependent recognition task regardless of whether object exposure in knockout mice was yoked to controls or not. These results demonstrate that GluA1 is necessary for nonspatial as well as spatial recognition memory and plays an important role in recency-dependent memory processes. PMID:21378100

Identifying Risk Factors for Drug Use in an Iranian Treatment Sample: A Prediction Approach Using Decision Trees.

PubMed

Amirabadizadeh, Alireza; Nezami, Hossein; Vaughn, Michael G; Nakhaee, Samaneh; Mehrpour, Omid

2018-05-12

Substance abuse exacts considerable social and health care burdens throughout the world. The aim of this study was to create a prediction model to better identify risk factors for drug use. A prospective cross-sectional study was conducted in South Khorasan Province, Iran. Of the total of 678 eligible subjects, 70% (n: 474) were randomly selected to provide a training set for constructing decision tree and multiple logistic regression (MLR) models. The remaining 30% (n: 204) were employed in a holdout sample to test the performance of the decision tree and MLR models. Predictive performance of different models was analyzed by the receiver operating characteristic (ROC) curve using the testing set. Independent variables were selected from demographic characteristics and history of drug use. For the decision tree model, the sensitivity and specificity for identifying people at risk for drug abuse were 66% and 75%, respectively, while the MLR model was somewhat less effective at 60% and 73%. Key independent variables in the analyses included first substance experience, age at first drug use, age, place of residence, history of cigarette use, and occupational and marital status. While study findings are exploratory and lack generalizability they do suggest that the decision tree model holds promise as an effective classification approach for identifying risk factors for drug use. Convergent with prior research in Western contexts is that age of drug use initiation was a critical factor predicting a substance use disorder.

A CpG island methylator phenotype in acute myeloid leukemia independent of IDH mutations and associated with a favorable outcome.

PubMed

Kelly, A D; Kroeger, H; Yamazaki, J; Taby, R; Neumann, F; Yu, S; Lee, J T; Patel, B; Li, Y; He, R; Liang, S; Lu, Y; Cesaroni, M; Pierce, S A; Kornblau, S M; Bueso-Ramos, C E; Ravandi, F; Kantarjian, H M; Jelinek, J; Issa, J-Pj

2017-10-01

Genetic changes are infrequent in acute myeloid leukemia (AML) compared with other malignancies and often involve epigenetic regulators, suggesting that an altered epigenome may underlie AML biology and outcomes. In 96 AML cases including 65 pilot samples selected for cured/not-cured, we found higher CpG island (CGI) promoter methylation in cured patients. Expanded genome-wide digital restriction enzyme analysis of methylation data revealed a CGI methylator phenotype independent of IDH1/2 mutations we term AML-CGI methylator phenotype (CIMP) (A-CIMP + ). A-CIMP was associated with longer overall survival (OS) in this data set (median OS, years: A-CIMP + =not reached, CIMP - =1.17; P=0.08). For validation we used 194 samples from The Cancer Genome Atlas interrogated with Illumina 450k methylation arrays where we confirmed longer OS in A-CIMP (median OS, years: A-CIMP + =2.34, A-CIMP - =1.00; P=0.01). Hypermethylation in A-CIMP + favored CGIs (OR: CGI/non-CGI=5.21), and while A-CIMP + was enriched in CEBPA (P=0.002) and WT1 mutations (P=0.02), 70% of cases lacked either mutation. Hypermethylated genes in A-CIMP + function in pluripotency maintenance, and a gene expression signature of A-CIMP was associated with outcomes in multiple data sets. We conclude that CIMP in AML cannot be explained solely by gene mutations (for example, IDH1/2, TET2), and that curability in A-CIMP + AML should be validated prospectively.

Effects of sampling strategy, detection probability, and independence of counts on the use of point counts

USGS Publications Warehouse

Pendleton, G.W.; Ralph, C. John; Sauer, John R.; Droege, Sam

1995-01-01

Many factors affect the use of point counts for monitoring bird populations, including sampling strategies, variation in detection rates, and independence of sample points. The most commonly used sampling plans are stratified sampling, cluster sampling, and systematic sampling. Each of these might be most useful for different objectives or field situations. Variation in detection probabilities and lack of independence among sample points can bias estimates and measures of precision. All of these factors should be con-sidered when using point count methods.

Are polychlorinated biphenyl residues adequately describe by aroclor mixture equivalents. Isomer-specific principal components analysis of such residues in fish and turtles

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

Schwartz, T.R.; Stalling, D.L.; Rice, C.L.

1987-01-01

Polychlorinated biphenyl (PCB) residues from fish and turtles were analyzed with SIMCA (Soft Independent Modeling of Class Analogy), a principal components analysis technique. A series of technical Aroclors were also analyzed to provide a reference data set for pattern recognition. Environmental PCB residues are often expressed in terms of relative Aroclor composition. In this work, we assessed the similarity of Aroclors to class models derived for fish and turtles to ascertain if the PCB residues in the samples could be described by an Aroclor or Aroclor mixture. Using PCA, we found that these samples could not be described by anmore » Aroclor or Aroclor mixture and that it would be inappropriate to report these samples as such. 18 references, 3 figures, 3 tables.« less

Implicit leadership theories in applied settings: factor structure, generalizability, and stability over time.

PubMed

Epitropaki, Olga; Martin, Robin

2004-04-01

The present empirical investigation had a 3-fold purpose: (a) to cross-validate L. R. Offermann, J. K. Kennedy, and P. W. Wirtz's (1994) scale of Implicit Leadership Theories (ILTs) in several organizational settings and to further provide a shorter scale of ILTs in organizations; (b) to assess the generalizability of ILTs across different employee groups, and (c) to evaluate ILTs' change over time. Two independent samples were used for the scale validation (N1 = 500 and N2 = 439). A 6-factor structure (Sensitivity, Intelligence, Dedication, Dynamism, Tyranny, and Masculinity) was found to most accurately represent ELTs in organizational settings. Regarding the generalizability of ILTs, although the 6-factor structure was consistent across different employee groups, there was only partial support for total factorial invariance. Finally, evaluation of gamma, beta, and alpha change provided support for ILTs' stability over time.

Generation and performance of special quasirandom structures for studying the elastic properties of random alloys: Application to Al-Ti

NASA Astrophysics Data System (ADS)

von Pezold, Johann; Dick, Alexey; Friák, Martin; Neugebauer, Jörg

2010-03-01

The performance of special-quasirandom structures (SQSs) for the description of elastic properties of random alloys was evaluated. A set of system-independent 32-atom-fcc SQS spanning the entire concentration range was generated and used to determine C11 , C12 , and C44 of binary random substitutional AlTi alloys. The elastic properties of these alloys could be described using the set of SQS with an accuracy comparable to the accuracy achievable by statistical sampling of the configurational space of 3×3×3 (108 atom, C44 ) and 4×4×4 (256 atom, C11 and C12 ) fcc supercells, irrespective of the impurity concentration. The smaller system size makes the proposed SQS ideal candidates for the ab initio determination of the elastic constants of random substitutional alloys. The set of optimized SQS is provided.

Using regression methods to estimate stream phosphorus loads at the Illinois River, Arkansas

USGS Publications Warehouse

Haggard, B.E.; Soerens, T.S.; Green, W.R.; Richards, R.P.

2003-01-01

The development of total maximum daily loads (TMDLs) requires evaluating existing constituent loads in streams. Accurate estimates of constituent loads are needed to calibrate watershed and reservoir models for TMDL development. The best approach to estimate constituent loads is high frequency sampling, particularly during storm events, and mass integration of constituents passing a point in a stream. Most often, resources are limited and discrete water quality samples are collected on fixed intervals and sometimes supplemented with directed sampling during storm events. When resources are limited, mass integration is not an accurate means to determine constituent loads and other load estimation techniques such as regression models are used. The objective of this work was to determine a minimum number of water-quality samples needed to provide constituent concentration data adequate to estimate constituent loads at a large stream. Twenty sets of water quality samples with and without supplemental storm samples were randomly selected at various fixed intervals from a database at the Illinois River, northwest Arkansas. The random sets were used to estimate total phosphorus (TP) loads using regression models. The regression-based annual TP loads were compared to the integrated annual TP load estimated using all the data. At a minimum, monthly sampling plus supplemental storm samples (six samples per year) was needed to produce a root mean square error of less than 15%. Water quality samples should be collected at least semi-monthly (every 15 days) in studies less than two years if seasonal time factors are to be used in the regression models. Annual TP loads estimated from independently collected discrete water quality samples further demonstrated the utility of using regression models to estimate annual TP loads in this stream system.

Make the most of your samples: Bayes factor estimators for high-dimensional models of sequence evolution.

PubMed

Baele, Guy; Lemey, Philippe; Vansteelandt, Stijn

2013-03-06

Accurate model comparison requires extensive computation times, especially for parameter-rich models of sequence evolution. In the Bayesian framework, model selection is typically performed through the evaluation of a Bayes factor, the ratio of two marginal likelihoods (one for each model). Recently introduced techniques to estimate (log) marginal likelihoods, such as path sampling and stepping-stone sampling, offer increased accuracy over the traditional harmonic mean estimator at an increased computational cost. Most often, each model's marginal likelihood will be estimated individually, which leads the resulting Bayes factor to suffer from errors associated with each of these independent estimation processes. We here assess the original 'model-switch' path sampling approach for direct Bayes factor estimation in phylogenetics, as well as an extension that uses more samples, to construct a direct path between two competing models, thereby eliminating the need to calculate each model's marginal likelihood independently. Further, we provide a competing Bayes factor estimator using an adaptation of the recently introduced stepping-stone sampling algorithm and set out to determine appropriate settings for accurately calculating such Bayes factors, with context-dependent evolutionary models as an example. While we show that modest efforts are required to roughly identify the increase in model fit, only drastically increased computation times ensure the accuracy needed to detect more subtle details of the evolutionary process. We show that our adaptation of stepping-stone sampling for direct Bayes factor calculation outperforms the original path sampling approach as well as an extension that exploits more samples. Our proposed approach for Bayes factor estimation also has preferable statistical properties over the use of individual marginal likelihood estimates for both models under comparison. Assuming a sigmoid function to determine the path between two competing models, we provide evidence that a single well-chosen sigmoid shape value requires less computational efforts in order to approximate the true value of the (log) Bayes factor compared to the original approach. We show that the (log) Bayes factors calculated using path sampling and stepping-stone sampling differ drastically from those estimated using either of the harmonic mean estimators, supporting earlier claims that the latter systematically overestimate the performance of high-dimensional models, which we show can lead to erroneous conclusions. Based on our results, we argue that highly accurate estimation of differences in model fit for high-dimensional models requires much more computational effort than suggested in recent studies on marginal likelihood estimation.

Make the most of your samples: Bayes factor estimators for high-dimensional models of sequence evolution

PubMed Central

2013-01-01

Background Accurate model comparison requires extensive computation times, especially for parameter-rich models of sequence evolution. In the Bayesian framework, model selection is typically performed through the evaluation of a Bayes factor, the ratio of two marginal likelihoods (one for each model). Recently introduced techniques to estimate (log) marginal likelihoods, such as path sampling and stepping-stone sampling, offer increased accuracy over the traditional harmonic mean estimator at an increased computational cost. Most often, each model’s marginal likelihood will be estimated individually, which leads the resulting Bayes factor to suffer from errors associated with each of these independent estimation processes. Results We here assess the original ‘model-switch’ path sampling approach for direct Bayes factor estimation in phylogenetics, as well as an extension that uses more samples, to construct a direct path between two competing models, thereby eliminating the need to calculate each model’s marginal likelihood independently. Further, we provide a competing Bayes factor estimator using an adaptation of the recently introduced stepping-stone sampling algorithm and set out to determine appropriate settings for accurately calculating such Bayes factors, with context-dependent evolutionary models as an example. While we show that modest efforts are required to roughly identify the increase in model fit, only drastically increased computation times ensure the accuracy needed to detect more subtle details of the evolutionary process. Conclusions We show that our adaptation of stepping-stone sampling for direct Bayes factor calculation outperforms the original path sampling approach as well as an extension that exploits more samples. Our proposed approach for Bayes factor estimation also has preferable statistical properties over the use of individual marginal likelihood estimates for both models under comparison. Assuming a sigmoid function to determine the path between two competing models, we provide evidence that a single well-chosen sigmoid shape value requires less computational efforts in order to approximate the true value of the (log) Bayes factor compared to the original approach. We show that the (log) Bayes factors calculated using path sampling and stepping-stone sampling differ drastically from those estimated using either of the harmonic mean estimators, supporting earlier claims that the latter systematically overestimate the performance of high-dimensional models, which we show can lead to erroneous conclusions. Based on our results, we argue that highly accurate estimation of differences in model fit for high-dimensional models requires much more computational effort than suggested in recent studies on marginal likelihood estimation. PMID:23497171

Independent component analysis decomposition of hospital emergency department throughput measures

NASA Astrophysics Data System (ADS)

He, Qiang; Chu, Henry

2016-05-01

We present a method adapted from medical sensor data analysis, viz. independent component analysis of electroencephalography data, to health system analysis. Timely and effective care in a hospital emergency department is measured by throughput measures such as median times patients spent before they were admitted as an inpatient, before they were sent home, before they were seen by a healthcare professional. We consider a set of five such measures collected at 3,086 hospitals distributed across the U.S. One model of the performance of an emergency department is that these correlated throughput measures are linear combinations of some underlying sources. The independent component analysis decomposition of the data set can thus be viewed as transforming a set of performance measures collected at a site to a collection of outputs of spatial filters applied to the whole multi-measure data. We compare the independent component sources with the output of the conventional principal component analysis to show that the independent components are more suitable for understanding the data sets through visualizations.

Non-coding cancer driver candidates identified with a sample- and position-specific model of the somatic mutation rate

PubMed Central

Juul, Malene; Bertl, Johanna; Guo, Qianyun; Nielsen, Morten Muhlig; Świtnicki, Michał; Hornshøj, Henrik; Madsen, Tobias; Hobolth, Asger; Pedersen, Jakob Skou

2017-01-01

Non-coding mutations may drive cancer development. Statistical detection of non-coding driver regions is challenged by a varying mutation rate and uncertainty of functional impact. Here, we develop a statistically founded non-coding driver-detection method, ncdDetect, which includes sample-specific mutational signatures, long-range mutation rate variation, and position-specific impact measures. Using ncdDetect, we screened non-coding regulatory regions of protein-coding genes across a pan-cancer set of whole-genomes (n = 505), which top-ranked known drivers and identified new candidates. For individual candidates, presence of non-coding mutations associates with altered expression or decreased patient survival across an independent pan-cancer sample set (n = 5454). This includes an antigen-presenting gene (CD1A), where 5’UTR mutations correlate significantly with decreased survival in melanoma. Additionally, mutations in a base-excision-repair gene (SMUG1) correlate with a C-to-T mutational-signature. Overall, we find that a rich model of mutational heterogeneity facilitates non-coding driver identification and integrative analysis points to candidates of potential clinical relevance. DOI: http://dx.doi.org/10.7554/eLife.21778.001 PMID:28362259

Classification and quantitation of milk powder by near-infrared spectroscopy and mutual information-based variable selection and partial least squares

NASA Astrophysics Data System (ADS)

Chen, Hui; Tan, Chao; Lin, Zan; Wu, Tong

2018-01-01

Milk is among the most popular nutrient source worldwide, which is of great interest due to its beneficial medicinal properties. The feasibility of the classification of milk powder samples with respect to their brands and the determination of protein concentration is investigated by NIR spectroscopy along with chemometrics. Two datasets were prepared for experiment. One contains 179 samples of four brands for classification and the other contains 30 samples for quantitative analysis. Principal component analysis (PCA) was used for exploratory analysis. Based on an effective model-independent variable selection method, i.e., minimal-redundancy maximal-relevance (MRMR), only 18 variables were selected to construct a partial least-square discriminant analysis (PLS-DA) model. On the test set, the PLS-DA model based on the selected variable set was compared with the full-spectrum PLS-DA model, both of which achieved 100% accuracy. In quantitative analysis, the partial least-square regression (PLSR) model constructed by the selected subset of 260 variables outperforms significantly the full-spectrum model. It seems that the combination of NIR spectroscopy, MRMR and PLS-DA or PLSR is a powerful tool for classifying different brands of milk and determining the protein content.

A systematic examination of a random sampling strategy for source apportionment calculations.

PubMed

Andersson, August

2011-12-15

Estimating the relative contributions from multiple potential sources of a specific component in a mixed environmental matrix is a general challenge in diverse fields such as atmospheric, environmental and earth sciences. Perhaps the most common strategy for tackling such problems is by setting up a system of linear equations for the fractional influence of different sources. Even though an algebraic solution of this approach is possible for the common situation with N+1 sources and N source markers, such methodology introduces a bias, since it is implicitly assumed that the calculated fractions and the corresponding uncertainties are independent of the variability of the source distributions. Here, a random sampling (RS) strategy for accounting for such statistical bias is examined by investigating rationally designed synthetic data sets. This random sampling methodology is found to be robust and accurate with respect to reproducibility and predictability. This method is also compared to a numerical integration solution for a two-source situation where source variability also is included. A general observation from this examination is that the variability of the source profiles not only affects the calculated precision but also the mean/median source contributions. Copyright © 2011 Elsevier B.V. All rights reserved.

The acoustic effect of cryogenically treating trumpets

NASA Astrophysics Data System (ADS)

Jones, Jesse; Rogers, Chris

2003-10-01

The acoustic effect of cryogenically treating trumpets is investigated. Ten Vincent Bach Stradivarious B♭ trumpets are studied, half of which have been cryogenically treated. The trumpets were played by six players of varying proficiency, with sound samples being recorded directly to disk at a sampling rate of 44.1 kHz. Both the steady-state and initial transient portions of the audio samples are analyzed. When comparing the average power spectra of the treated trumpets to the untreated set, no repeatable, statistically independent differences are observed in the data. Differences observed in player-to-player and trumpet-to-trumpet comparisons overshadow any differences that may have been brought on due to the cryogenic treatment. Qualitatively, players established no clear preference between the treated and untreated trumpets regarding tone and playability, and could not differentiate between the two sets of instruments. All data was collected in a double blind fashion. The treatment itself is a three step process, involving an 8 hour linear cool down period, a 10 hour period of sustained exposure to -195°C (-300°F), and a 20-25 hour period of warming back to room temperature. [Work was completed with the support of Steinway & Sons Pianos and Selmer Musical Instruments.

Developing a complex independent component analysis technique to extract non-stationary patterns from geophysical time-series

NASA Astrophysics Data System (ADS)

Forootan, Ehsan; Kusche, Jürgen

2016-04-01

Geodetic/geophysical observations, such as the time series of global terrestrial water storage change or sea level and temperature change, represent samples of physical processes and therefore contain information about complex physical interactionswith many inherent time scales. Extracting relevant information from these samples, for example quantifying the seasonality of a physical process or its variability due to large-scale ocean-atmosphere interactions, is not possible by rendering simple time series approaches. In the last decades, decomposition techniques have found increasing interest for extracting patterns from geophysical observations. Traditionally, principal component analysis (PCA) and more recently independent component analysis (ICA) are common techniques to extract statistical orthogonal (uncorrelated) and independent modes that represent the maximum variance of observations, respectively. PCA and ICA can be classified as stationary signal decomposition techniques since they are based on decomposing the auto-covariance matrix or diagonalizing higher (than two)-order statistical tensors from centered time series. However, the stationary assumption is obviously not justifiable for many geophysical and climate variables even after removing cyclic components e.g., the seasonal cycles. In this paper, we present a new decomposition method, the complex independent component analysis (CICA, Forootan, PhD-2014), which can be applied to extract to non-stationary (changing in space and time) patterns from geophysical time series. Here, CICA is derived as an extension of real-valued ICA (Forootan and Kusche, JoG-2012), where we (i) define a new complex data set using a Hilbert transformation. The complex time series contain the observed values in their real part, and the temporal rate of variability in their imaginary part. (ii) An ICA algorithm based on diagonalization of fourth-order cumulants is then applied to decompose the new complex data set in (i). (iii) Dominant non-stationary patterns are recognized as independent complex patterns that can be used to represent the space and time amplitude and phase propagations. We present the results of CICA on simulated and real cases e.g., for quantifying the impact of large-scale ocean-atmosphere interaction on global mass changes. Forootan (PhD-2014) Statistical signal decomposition techniques for analyzing time-variable satellite gravimetry data, PhD Thesis, University of Bonn, http://hss.ulb.uni-bonn.de/2014/3766/3766.htm Forootan and Kusche (JoG-2012) Separation of global time-variable gravity signals into maximally independent components, Journal of Geodesy 86 (7), 477-497, doi: 10.1007/s00190-011-0532-5

Multiple foci of spatial attention in multimodal working memory.

PubMed

Katus, Tobias; Eimer, Martin

2016-11-15

The maintenance of sensory information in working memory (WM) is mediated by the attentional activation of stimulus representations that are stored in perceptual brain regions. Using event-related potentials (ERPs), we measured tactile and visual contralateral delay activity (tCDA/CDA components) in a bimodal WM task to concurrently track the attention-based maintenance of information stored in anatomically segregated (somatosensory and visual) brain areas. Participants received tactile and visual sample stimuli on both sides, and in different blocks, memorized these samples on the same side or on opposite sides. After a retention delay, memory was unpredictably tested for touch or vision. In the same side blocks, tCDA and CDA components simultaneously emerged over the same hemisphere, contralateral to the memorized tactile/visual sample set. In opposite side blocks, these two components emerged over different hemispheres, but had the same sizes and onset latencies as in the same side condition. Our results reveal distinct foci of tactile and visual spatial attention that were concurrently maintained on task-relevant stimulus representations in WM. The independence of spatially-specific biasing mechanisms for tactile and visual WM content suggests that multimodal information is stored in distributed perceptual brain areas that are activated through modality-specific processes that can operate simultaneously and largely independently of each other. Copyright © 2016 Elsevier Inc. All rights reserved.

Authentication of Organically and Conventionally Grown Basils by Gas Chromatography/Mass Spectrometry Chemical Profiles

PubMed Central

Wang, Zhengfang; Chen, Pei; Yu, Liangli; Harrington, Peter de B.

2013-01-01

Basil plants cultivated by organic and conventional farming practices were accurately classified by pattern recognition of gas chromatography/mass spectrometry (GC/MS) data. A novel extraction procedure was devised to extract characteristic compounds from ground basil powders. Two in-house fuzzy classifiers, i.e., the fuzzy rule-building expert system (FuRES) and the fuzzy optimal associative memory (FOAM) for the first time, were used to build classification models. Two crisp classifiers, i.e., soft independent modeling by class analogy (SIMCA) and the partial least-squares discriminant analysis (PLS-DA), were used as control methods. Prior to data processing, baseline correction and retention time alignment were performed. Classifiers were built with the two-way data sets, the total ion chromatogram representation of data sets, and the total mass spectrum representation of data sets, separately. Bootstrapped Latin partition (BLP) was used as an unbiased evaluation of the classifiers. By using two-way data sets, average classification rates with FuRES, FOAM, SIMCA, and PLS-DA were 100 ± 0%, 94.4 ± 0.4%, 93.3 ± 0.4%, and 100 ± 0%, respectively, for 100 independent evaluations. The established classifiers were used to classify a new validation set collected 2.5 months later with no parametric changes except that the training set and validation set were individually mean-centered. For the new two-way validation set, classification rates with FuRES, FOAM, SIMCA, and PLS-DA were 100%, 83%, 97%, and 100%, respectively. Thereby, the GC/MS analysis was demonstrated as a viable approach for organic basil authentication. It is the first time that a FOAM has been applied to classification. A novel baseline correction method was used also for the first time. The FuRES and the FOAM are demonstrated as powerful tools for modeling and classifying GC/MS data of complex samples and the data pretreatments are demonstrated to be useful to improve the performance of classifiers. PMID:23398171

Comparing the MMPI-2 scale scores of parents involved in parental competency and child custody assessments.

PubMed

Resendes, John; Lecci, Len

2012-12-01

MMPI-2 scores from a parent competency sample (N = 136 parents) are compared with a previously published data set of MMPI-2 scores for child custody litigants (N = 508 parents; Bathurst et al., 1997). Independent samples t tests yielded significant and in some cases substantial differences on the standard MMPI-2 clinical scales (especially Scales 4, 8, 2, and 0), with the competency sample obtaining higher clinical scores as well as higher scores on F, FB, VRIN, TRIN, and L, but lower scores on K, relative to the custody sample. Despite the higher scores in the competency sample, MMPI-2 mean scores did not exceed the clinical cutoff (T > 65). Moreover, the present competency sample essentially replicates the MMPI-2 scores of a previously published competency sample, suggesting that the present findings are representative of that population. The present findings suggest that separate reference groups be used when conducting child custody vs. parental competency evaluations, as these appear to be distinct populations despite there being similarities in the testing circumstances.

Genetic utility of broadly defined bipolar schizoaffective disorder as a diagnostic concept

PubMed Central

Hamshere, M. L.; Green, E. K.; Jones, I. R.; Jones, L.; Moskvina, V.; Kirov, G.; Grozeva, D.; Nikolov, I.; Vukcevic, D.; Caesar, S.; Gordon-Smith, K.; Fraser, C.; Russell, E.; Breen, G.; St Clair, D.; Collier, D. A.; Young, A. H.; Ferrier, I. N.; Farmer, A.; McGuffin, P.; Holmans, P. A.; Owen, M. J.; O’Donovan, M. C.; Craddock, N.

2009-01-01

Background Psychiatric phenotypes are currently defined according to sets of descriptive criteria. Although many of these phenotypes are heritable, it would be useful to know whether any of the various diagnostic categories in current use identify cases that are particularly helpful for biological–genetic research. Aims To use genome-wide genetic association data to explore the relative genetic utility of seven different descriptive operational diagnostic categories relevant to bipolar illness within a large UK case–control bipolar disorder sample. Method We analysed our previously published Wellcome Trust Case Control Consortium (WTCCC) bipolar disorder genome-wide association data-set, comprising 1868 individuals with bipolar disorder and 2938 controls genotyped for 276 122 single nucleotide polymorphisms (SNPs) that met stringent criteria for genotype quality. For each SNP we performed a test of association (bipolar disorder group v. control group) and used the number of associated independent SNPs statistically significant at P<0.00001 as a metric for the overall genetic signal in the sample. We next compared this metric with that obtained using each of seven diagnostic subsets of the group with bipolar disorder: Research Diagnostic Criteria (RDC): bipolar I disorder; manic disorder; bipolar II disorder; schizoaffective disorder, bipolar type; DSM–IV: bipolar I disorder; bipolar II disorder; schizoaffective disorder, bipolar type. Results The RDC schizoaffective disorder, bipolar type (v. controls) stood out from the other diagnostic subsets as having a significant excess of independent association signals (P<0.003) compared with that expected in samples of the same size selected randomly from the total bipolar disorder group data-set. The strongest association in this subset of participants with bipolar disorder was at rs4818065 (P = 2.42×10–7). Biological systems implicated included gamma amniobutyric acid (GABA)A receptors. Genes having at least one associated polymorphism at P<10–4 included B3GALTS, A2BP1, GABRB1, AUTS2, BSN, PTPRG, GIRK2 and CDH12. Conclusions Our findings show that individuals with broadly defined bipolar schizoaffective features have either a particularly strong genetic contribution or that, as a group, are genetically more homogeneous than the other phenotypes tested. The results point to the importance of using diagnostic approaches that recognise this group of individuals. Our approach can be applied to similar data-sets for other psychiatric and non-psychiatric phenotypes. PMID:19567891

Distributed Adaptive Control: Beyond Single-Instant, Discrete Variables

NASA Technical Reports Server (NTRS)

Wolpert, David H.; Bieniawski, Stefan

2005-01-01

In extensive form noncooperative game theory, at each instant t, each agent i sets its state x, independently of the other agents, by sampling an associated distribution, q(sub i)(x(sub i)). The coupling between the agents arises in the joint evolution of those distributions. Distributed control problems can be cast the same way. In those problems the system designer sets aspects of the joint evolution of the distributions to try to optimize the goal for the overall system. Now information theory tells us what the separate q(sub i) of the agents are most likely to be if the system were to have a particular expected value of the objective function G(x(sub 1),x(sub 2), ...). So one can view the job of the system designer as speeding an iterative process. Each step of that process starts with a specified value of E(G), and the convergence of the q(sub i) to the most likely set of distributions consistent with that value. After this the target value for E(sub q)(G) is lowered, and then the process repeats. Previous work has elaborated many schemes for implementing this process when the underlying variables x(sub i) all have a finite number of possible values and G does not extend to multiple instants in time. That work also is based on a fixed mapping from agents to control devices, so that the the statistical independence of the agents' moves means independence of the device states. This paper also extends that work to relax all of these restrictions. This extends the applicability of that work to include continuous spaces and Reinforcement Learning. This paper also elaborates how some of that earlier work can be viewed as a first-principles justification of evolution-based search algorithms.

Robustness of NMR-based metabolomics to generate comparable data sets for olive oil cultivar classification. An inter-laboratory study on Apulian olive oils.

PubMed

Piccinonna, Sara; Ragone, Rosa; Stocchero, Matteo; Del Coco, Laura; De Pascali, Sandra Angelica; Schena, Francesco Paolo; Fanizzi, Francesco Paolo

2016-05-15

Nuclear Magnetic Resonance (NMR) spectroscopy is emerging as a powerful technique in olive oil fingerprinting, but its analytical robustness has to be proved. Here, we report a comparative study between two laboratories on olive oil (1)H NMR fingerprinting, aiming to demonstrate the robustness of NMR-based metabolomics in generating comparable data sets for cultivar classification. Sample preparation and data acquisition were performed independently in two laboratories, equipped with different resolution spectrometers (400 and 500 MHz), using two identical sets of mono-varietal olive oils. Partial Least Squares (PLS)-based techniques were applied to compare the data sets produced by the two laboratories. Despite differences in spectrum baseline, and in intensity and shape of peaks, the amount of shared information was significant (almost 70%) and related to cultivar (same metabolites discriminated between cultivars). In conclusion, regardless of the variability due to operator and machine, the data sets from the two participating units were comparable for the purpose of classification. Copyright © 2015 Elsevier Ltd. All rights reserved.

An Optimized Set of Fluorescence In Situ Hybridization Probes for Detection of Pancreatobiliary Tract Cancer in Cytology Brush Samples.

PubMed

Barr Fritcher, Emily G; Voss, Jesse S; Brankley, Shannon M; Campion, Michael B; Jenkins, Sarah M; Keeney, Matthew E; Henry, Michael R; Kerr, Sarah M; Chaiteerakij, Roongruedee; Pestova, Ekaterina V; Clayton, Amy C; Zhang, Jun; Roberts, Lewis R; Gores, Gregory J; Halling, Kevin C; Kipp, Benjamin R

2015-12-01

Pancreatobiliary cancer is detected by fluorescence in situ hybridization (FISH) of pancreatobiliary brush samples with UroVysion probes, originally designed to detect bladder cancer. We designed a set of new probes to detect pancreatobiliary cancer and compared its performance with that of UroVysion and routine cytology analysis. We tested a set of FISH probes on tumor tissues (cholangiocarcinoma or pancreatic carcinoma) and non-tumor tissues from 29 patients. We identified 4 probes that had high specificity for tumor vs non-tumor tissues; we called this set of probes pancreatobiliary FISH. We performed a retrospective analysis of brush samples from 272 patients who underwent endoscopic retrograde cholangiopancreatography for evaluation of malignancy at the Mayo Clinic; results were available from routine cytology and FISH with UroVysion probes. Archived residual specimens were retrieved and used to evaluate the pancreatobiliary FISH probes. Cutoff values for FISH with the pancreatobiliary probes were determined using 89 samples and validated in the remaining 183 samples. Clinical and pathologic evidence of malignancy in the pancreatobiliary tract within 2 years of brush sample collection was used as the standard; samples from patients without malignancies were used as negative controls. The validation cohort included 85 patients with malignancies (46.4%) and 114 patients with primary sclerosing cholangitis (62.3%). Samples containing cells above the cutoff for polysomy (copy number gain of ≥2 probes) were classified as positive in FISH with the UroVysion and pancreatobiliary probes. Multivariable logistic regression was used to estimate associations between clinical and pathology findings and results from FISH. The combination of FISH probes 1q21, 7p12, 8q24, and 9p21 identified cancer cells with 93% sensitivity and 100% specificity in pancreatobiliary tissue samples and were therefore included in the pancreatobiliary probe set. In the validation cohort of brush samples, pancreatobiliary FISH identified samples from patients with malignancy with a significantly higher level of sensitivity (64.7%) than the UroVysion probes (45.9%) (P < .001) or routine cytology analysis (18.8%) (P < .001), but similar specificity (92.9%, 90.8%, and 100.0% respectively). Factors significantly associated with detection of carcinoma, in adjusted analyses, included detection of polysomy by pancreatobiliary FISH (P < .001), a mass by cross-sectional imaging (P < .001), cancer cells by routine cytology (overall P = .003), as well as absence of primary sclerosing cholangitis (P = .011). We identified a set of FISH probes that detects cancer cells in pancreatobiliary brush samples from patients with and without primary sclerosing cholangitis with higher levels of sensitivity than UroVysion probes. Cytologic brushing test results and clinical features were independently associated with detection of cancer and might be used to identify patients with pancreatobiliary cancers. Copyright © 2015 AGA Institute. Published by Elsevier Inc. All rights reserved.

Bladder cancer biomarker discovery using global metabolomic profiling of urine.

PubMed

Wittmann, Bryan M; Stirdivant, Steven M; Mitchell, Matthew W; Wulff, Jacob E; McDunn, Jonathan E; Li, Zhen; Dennis-Barrie, Aphrihl; Neri, Bruce P; Milburn, Michael V; Lotan, Yair; Wolfert, Robert L

2014-01-01

Bladder cancer (BCa) is a common malignancy worldwide and has a high probability of recurrence after initial diagnosis and treatment. As a result, recurrent surveillance, primarily involving repeated cystoscopies, is a critical component of post diagnosis patient management. Since cystoscopy is invasive, expensive and a possible deterrent to patient compliance with regular follow-up screening, new non-invasive technologies to aid in the detection of recurrent and/or primary bladder cancer are strongly needed. In this study, mass spectrometry based metabolomics was employed to identify biochemical signatures in human urine that differentiate bladder cancer from non-cancer controls. Over 1000 distinct compounds were measured including 587 named compounds of known chemical identity. Initial biomarker identification was conducted using a 332 subject sample set of retrospective urine samples (cohort 1), which included 66 BCa positive samples. A set of 25 candidate biomarkers was selected based on statistical significance, fold difference and metabolic pathway coverage. The 25 candidate biomarkers were tested against an independent urine sample set (cohort 2) using random forest analysis, with palmitoyl sphingomyelin, lactate, adenosine and succinate providing the strongest predictive power for differentiating cohort 2 cancer from non-cancer urines. Cohort 2 metabolite profiling revealed additional metabolites, including arachidonate, that were higher in cohort 2 cancer vs. non-cancer controls, but were below quantitation limits in the cohort 1 profiling. Metabolites related to lipid metabolism may be especially interesting biomarkers. The results suggest that urine metabolites may provide a much needed non-invasive adjunct diagnostic to cystoscopy for detection of bladder cancer and recurrent disease management.

In-situ generation of carrier gases for scientific analyses on Mars

NASA Technical Reports Server (NTRS)

Finn, J. E.; Sridhar, K. R.

1997-01-01

The search for useful raw materials on planetary surfaces will involve various scientific analyses of soil and rock samples. The devices performing these measurements often require inert carrier gases for moving analytes and purging instrumentation. At present, the carrier or sweep gas must be carried from Earth in a compressed gas cylinder, and so the supply of this depletable resource sets a hard limit on the (flexible) life span of the experiment. If a suitable carrier gas could be produced in-situ, then the scientific return of exploration missions could be extended and enhanced greatly. Many more samples could be analyzed, long-ranging rovers could have independent gas supplies, and designs could have added flexibility with respect to gas consumption.

Sampling flies or sampling flaws? Experimental design and inference strength in forensic entomology.

PubMed

Michaud, J-P; Schoenly, Kenneth G; Moreau, G

2012-01-01

Forensic entomology is an inferential science because postmortem interval estimates are based on the extrapolation of results obtained in field or laboratory settings. Although enormous gains in scientific understanding and methodological practice have been made in forensic entomology over the last few decades, a majority of the field studies we reviewed do not meet the standards for inference, which are 1) adequate replication, 2) independence of experimental units, and 3) experimental conditions that capture a representative range of natural variability. Using a mock case-study approach, we identify design flaws in field and lab experiments and suggest methodological solutions for increasing inference strength that can inform future casework. Suggestions for improving data reporting in future field studies are also proposed.

tICA-Metadynamics: Accelerating Metadynamics by Using Kinetically Selected Collective Variables.

PubMed

M Sultan, Mohammad; Pande, Vijay S

2017-06-13

Metadynamics is a powerful enhanced molecular dynamics sampling method that accelerates simulations by adding history-dependent multidimensional Gaussians along selective collective variables (CVs). In practice, choosing a small number of slow CVs remains challenging due to the inherent high dimensionality of biophysical systems. Here we show that time-structure based independent component analysis (tICA), a recent advance in Markov state model literature, can be used to identify a set of variationally optimal slow coordinates for use as CVs for Metadynamics. We show that linear and nonlinear tICA-Metadynamics can complement existing MD studies by explicitly sampling the system's slowest modes and can even drive transitions along the slowest modes even when no such transitions are observed in unbiased simulations.

Type of gambling as an independent risk factor for suicidal events in pathological gamblers.

PubMed

Bischof, Anja; Meyer, Christian; Bischof, Gallus; John, Ulrich; Wurst, Friedrich Martin; Thon, Natasha; Lucht, Michael; Grabe, Hans-Joergen; Rumpf, Hans-Juergen

2016-03-01

Individuals with pathological gambling have an increased risk for suicidal events. Additionally, the prevalence of comorbid psychiatric disorders is high among pathological gamblers. This study analyzes whether the type of gambling is associated with suicidal events in pathological gamblers independently from comorbidity. Participants were recruited in 4 different ways: via random telephone sample from the general population, via individual invitation for study participation in gambling locations, through various media and the distribution of a leaflet in various settings, and via inpatient treatment facilities for pathological gambling. The final sample included 442 participants with a lifetime diagnosis of pathological gambling. A standardized clinical interview was conducted. High financial losses were associated with suicidal events (odds ratio [OR] = 1.94, 95% 95% confidence interval [CI], [1.11, 3.37]), as were mood disorders (OR = 7.70, 95% CI, [4.44, 13.37]) and female gender (OR = 2.52, 95% CI, [1.20, 5.28]). Gambling on electronic gambling machines in gambling halls or bars was associated with increased odds of suicidal events (OR = 2.94, 95% CI, [1.38, 6.24]). Other types of gambling, such as casino games or betting on sports, or the number of DSM-IV criteria for pathological gambling were not associated independently with suicidal events. Our findings suggest that gambling on electronic gambling machines in gambling halls or bars is associated with suicidal events in pathological gamblers independently of comorbidity. This result shows that the type of gambling needs to be considered as a relevant factor in gambling research. (c) 2016 APA, all rights reserved).

The (non-)replicability of regulatory resource depletion: A field report employing non-invasive brain stimulation

PubMed Central

Martijn, Carolien; Alberts, Hugo J. E. M.; Thomson, Alix C.; David, Bastian; Kessler, Daniel

2017-01-01

Cognitive effort and self-control are exhausting. Although evidence is ambiguous, behavioural studies have repeatedly suggested that control-demanding tasks seem to deplete a limited cache of self-regulatory resources leading to performance degradations and fatigue. While resource depletion has indirectly been associated with a decline in right prefrontal cortex capacity, its precise neural underpinnings have not yet been revealed. This study consisted of two independent experiments, which set out to investigate the causal role of the right dorsolateral prefrontal cortex (DLPFC) in a classic dual phase depletion paradigm employing non-invasive brain stimulation. In Experiment 1 we demonstrated a general depletion effect, which was significantly eliminated by anodal transcranial Direct Current Stimulation to the right DLPFC. In Experiment 2, however, we failed to replicate the basic psychological depletion effect within a second independent sample. The dissimilar results are discussed in the context of the current ‘replication crisis’ and suggestions for future studies are offered. While our current results do not allow us to firmly argue for or against the existence of resource depletion, we outline why it is crucial to further clarify which specific external and internal circumstances lead to limited replicability of the described effect. We showcase and discuss the current inter-lab replication problem based on two independent samples tested within one research group (intra-lab). PMID:28362843

True lemurs…true species - species delimitation using multiple data sources in the brown lemur complex

PubMed Central

2013-01-01

Background Species are the fundamental units in evolutionary biology. However, defining them as evolutionary independent lineages requires integration of several independent sources of information in order to develop robust hypotheses for taxonomic classification. Here, we exemplarily propose an integrative framework for species delimitation in the “brown lemur complex” (BLC) of Madagascar, which consists of seven allopatric populations of the genus Eulemur (Primates: Lemuridae), which were sampled extensively across northern, eastern and western Madagascar to collect fecal samples for DNA extraction as well as recordings of vocalizations. Our data base was extended by including museum specimens with reliable identification and locality information for skull shape and pelage color analysis. Results Between-group analyses of principal components revealed significant heterogeneity in skull shape, pelage color variation and loud calls across all seven populations. Furthermore, post-hoc statistical tests between pairs of populations revealed considerable discordance among different data sets for different dyads. Despite a high degree of incomplete lineage sorting among nuclear loci, significant exclusive ancestry was found for all populations, except for E. cinereiceps, based on one mitochondrial and three nuclear genetic loci. Conclusions Using several independent lines of evidence, our results confirm the species status of the members of the BLC under the general lineage concept of species. More generally, the present analyses demonstrate the importance and value of integrating different kinds of data in delimiting recently evolved radiations. PMID:24159931

Decay of random correlation functions for unimodal maps

NASA Astrophysics Data System (ADS)

Baladi, Viviane; Benedicks, Michael; Maume-Deschamps, Véronique

2000-10-01

Since the pioneering results of Jakobson and subsequent work by Benedicks-Carleson and others, it is known that quadratic maps tfa( χ) = a - χ2 admit a unique absolutely continuous invariant measure for a positive measure set of parameters a. For topologically mixing tfa, Young and Keller-Nowicki independently proved exponential decay of correlation functions for this a.c.i.m. and smooth observables. We consider random compositions of small perturbations tf + ωt, with tf = tfa or another unimodal map satisfying certain nonuniform hyperbolicity axioms, and ωt chosen independently and identically in [-ɛ, ɛ]. Baladi-Viana showed exponential mixing of the associated Markov chain, i.e., averaging over all random itineraries. We obtain stretched exponential bounds for the random correlation functions of Lipschitz observables for the sample measure μωof almost every itinerary.

Collision rates and impact velocities in the Main Asteroid Belt

NASA Technical Reports Server (NTRS)

Farinella, Paolo; Davis, Donald R.

1992-01-01

Wetherill's (1967) algorithm is presently used to compute the mutual collision probabilities and impact velocities of a set of 682 asteroids with large-than-50-km radius representative of a bias-free sample of asteroid orbits. While collision probabilities are nearly independent of eccentricities, a significant decrease is associated with larger inclinations. Collisional velocities grow steeply with orbital eccentricity and inclination, but with curiously small variation across the asteroid belt. Family asteroids are noted to undergo collisions with other family members 2-3 times more often than with nonmembers.

Inflammatory macrophage-associated 3-gene signature predicts subclinical allograft injury and graft survival.

PubMed

Azad, Tej D; Donato, Michele; Heylen, Line; Liu, Andrew B; Shen-Orr, Shai S; Sweeney, Timothy E; Maltzman, Jonathan Scott; Naesens, Maarten; Khatri, Purvesh

2018-01-25

Late allograft failure is characterized by cumulative subclinical insults manifesting over many years. Although immunomodulatory therapies targeting host T cells have improved short-term survival rates, rates of chronic allograft loss remain high. We hypothesized that other immune cell types may drive subclinical injury, ultimately leading to graft failure. We collected whole-genome transcriptome profiles from 15 independent cohorts composed of 1,697 biopsy samples to assess the association of an inflammatory macrophage polarization-specific gene signature with subclinical injury. We applied penalized regression to a subset of the data sets and identified a 3-gene inflammatory macrophage-derived signature. We validated discriminatory power of the 3-gene signature in 3 independent renal transplant data sets with mean AUC of 0.91. In a longitudinal cohort, the 3-gene signature strongly correlated with extent of injury and accurately predicted progression of subclinical injury 18 months before clinical manifestation. The 3-gene signature also stratified patients at high risk of graft failure as soon as 15 days after biopsy. We found that the 3-gene signature also distinguished acute rejection (AR) accurately in 3 heart transplant data sets but not in lung transplant. Overall, we identified a parsimonious signature capable of diagnosing AR, recognizing subclinical injury, and risk-stratifying renal transplant patients. Our results strongly suggest that inflammatory macrophages may be a viable therapeutic target to improve long-term outcomes for organ transplantation patients.

Handling of uncertainty due to interference fringe in FT-NIR transmittance spectroscopy - Performance comparison of interference elimination techniques using glucose-water system

NASA Astrophysics Data System (ADS)

Beganović, Anel; Beć, Krzysztof B.; Henn, Raphael; Huck, Christian W.

2018-05-01

The applicability of two elimination techniques for interferences occurring in measurements with cells of short pathlength using Fourier transform near-infrared (FT-NIR) spectroscopy was evaluated. Due to the growing interest in the field of vibrational spectroscopy in aqueous biological fluids (e.g. glucose in blood), aqueous solutions of D-(+)-glucose were prepared and split into a calibration set and an independent validation set. All samples were measured with two FT-NIR spectrometers at various spectral resolutions. Moving average smoothing (MAS) and fast Fourier transform filter (FFT filter) were applied to the interference affected FT-NIR spectra in order to eliminate the interference pattern. After data pre-treatment, partial least squares regression (PLSR) models using different NIR regions were constructed using untreated (interference affected) spectra and spectra treated with MAS and FFT filter. The prediction of the independent validation set revealed information about the performance of the utilized interference elimination techniques, as well as the different NIR regions. The results showed that the combination band of water at approx. 5200 cm-1 is of great importance since its performance was superior to the one of the so-called first overtone of water at approx. 6800 cm-1. Furthermore, this work demonstrated that MAS and FFT filter are fast and easy-to-use techniques for the elimination of interference fringes in FT-NIR transmittance spectroscopy.

The Fungal Frontier: A Comparative Analysis of Methods Used in the Study of the Human Gut Mycobiome

PubMed Central

Huseyin, Chloe E.; Rubio, Raul Cabrera; O’Sullivan, Orla; Cotter, Paul D.; Scanlan, Pauline D.

2017-01-01

The human gut is host to a diverse range of fungal species, collectively referred to as the gut “mycobiome”. The gut mycobiome is emerging as an area of considerable research interest due to the potential roles of these fungi in human health and disease. However, there is no consensus as to what the best or most suitable methodologies available are with respect to characterizing the human gut mycobiome. The aim of this study is to provide a comparative analysis of several previously published mycobiome-specific culture-dependent and -independent methodologies, including choice of culture media, incubation conditions (aerobic versus anaerobic), DNA extraction method, primer set and freezing of fecal samples to assess their relative merits and suitability for gut mycobiome analysis. There was no significant effect of media type or aeration on culture-dependent results. However, freezing was found to have a significant effect on fungal viability, with significantly lower fungal numbers recovered from frozen samples. DNA extraction method had a significant effect on DNA yield and quality. However, freezing and extraction method did not have any impact on either α or β diversity. There was also considerable variation in the ability of different fungal-specific primer sets to generate PCR products for subsequent sequence analysis. Through this investigation two DNA extraction methods and one primer set was identified which facilitated the analysis of the mycobiome for all samples in this study. Ultimately, a diverse range of fungal species were recovered using both approaches, with Candida and Saccharomyces identified as the most common fungal species recovered using culture-dependent and culture-independent methods, respectively. As has been apparent from ecological surveys of the bacterial fraction of the gut microbiota, the use of different methodologies can also impact on our understanding of gut mycobiome composition and therefore requires careful consideration. Future research into the gut mycobiome needs to adopt a common strategy to minimize potentially confounding effects of methodological choice and to facilitate comparative analysis of datasets. PMID:28824566

Exploration of attenuated total reflectance mid-infrared spectroscopy and multivariate calibration to measure immunoglobulin G in human sera.

PubMed

Hou, Siyuan; Riley, Christopher B; Mitchell, Cynthia A; Shaw, R Anthony; Bryanton, Janet; Bigsby, Kathryn; McClure, J Trenton

2015-09-01

Immunoglobulin G (IgG) is crucial for the protection of the host from invasive pathogens. Due to its importance for human health, tools that enable the monitoring of IgG levels are highly desired. Consequently there is a need for methods to determine the IgG concentration that are simple, rapid, and inexpensive. This work explored the potential of attenuated total reflectance (ATR) infrared spectroscopy as a method to determine IgG concentrations in human serum samples. Venous blood samples were collected from adults and children, and from the umbilical cord of newborns. The serum was harvested and tested using ATR infrared spectroscopy. Partial least squares (PLS) regression provided the basis to develop the new analytical methods. Three PLS calibrations were determined: one for the combined set of the venous and umbilical cord serum samples, the second for only the umbilical cord samples, and the third for only the venous samples. The number of PLS factors was chosen by critical evaluation of Monte Carlo-based cross validation results. The predictive performance for each PLS calibration was evaluated using the Pearson correlation coefficient, scatter plot and Bland-Altman plot, and percent deviations for independent prediction sets. The repeatability was evaluated by standard deviation and relative standard deviation. The results showed that ATR infrared spectroscopy is potentially a simple, quick, and inexpensive method to measure IgG concentrations in human serum samples. The results also showed that it is possible to build a united calibration curve for the umbilical cord and the venous samples. Copyright © 2015 Elsevier B.V. All rights reserved.

Research on Abnormal Detection Based on Improved Combination of K - means and SVDD

NASA Astrophysics Data System (ADS)

Hao, Xiaohong; Zhang, Xiaofeng

2018-01-01

In order to improve the efficiency of network intrusion detection and reduce the false alarm rate, this paper proposes an anomaly detection algorithm based on improved K-means and SVDD. The algorithm first uses the improved K-means algorithm to cluster the training samples of each class, so that each class is independent and compact in class; Then, according to the training samples, the SVDD algorithm is used to construct the minimum superspheres. The subordinate relationship of the samples is determined by calculating the distance of the minimum superspheres constructed by SVDD. If the test sample is less than the center of the hypersphere, the test sample belongs to this class, otherwise it does not belong to this class, after several comparisons, the final test of the effective detection of the test sample.In this paper, we use KDD CUP99 data set to simulate the proposed anomaly detection algorithm. The results show that the algorithm has high detection rate and low false alarm rate, which is an effective network security protection method.

Analysis of Setting Efficacy in Young Male and Female Volleyball Players.

PubMed

González-Silva, Jara; Domínguez, Alberto Moreno; Fernández-Echeverría, Carmen; Rabaz, Fernando Claver; Arroyo, M Perla Moreno

2016-12-01

The main objective of this study was to analyse the variables that predicted setting efficacy in complex I (KI) in volleyball, in formative categories and depending on gender. The study sample was comprised of 5842 game actions carried out by the 16 male category and the 18 female category teams that participated in the Under-16 Spanish Championship. The dependent variable was setting efficacy. The independent variables were grouped into: serve variables (a serve zone, the type of serve, striking technique, an in-game role of the server and serve direction), reception variables (a reception zone, a receiver player and reception efficacy) and setting variables (a setter's position, a setting zone, the type of a set, setting technique, a set's area and tempo of a set). Multinomial logistic regression showed that the best predictive variables of setting efficacy, both in female and male categories, were reception efficacy, setting technique and tempo of a set. In the male category, the jump serve was the greatest predictor of setting efficacy, while in the female category, it was the set's area. Therefore, in the male category, it was not only the preceding action that affected setting efficacy, but also the serve. On the contrary, in the female category, only variables of the action itself and of the previous action, reception, affected setting efficacy. The results obtained in the present study should be taken into account in the training process of both male and female volleyball players in formative stages.

Factors associated with personal protection equipment use and hand hygiene among hemodialysis staff.

PubMed

Shimokura, Gayle; Weber, David J; Miller, William C; Wurtzel, Heather; Alter, Miriam J

2006-04-01

Because exposure to blood by health care workers is frequent during hemodialysis, gloves are required for all contact with patients and their equipment, followed by hand hygiene. In this study, we investigated factors associated with performing these practices as recommended. Staff members from a sample of 45 US hemodialysis facilities were surveyed using an anonymous self-administered questionnaire. Factors independently associated with reporting increased compliance with recommended hand hygiene and glove use practices during patient care were identified with multivariate modeling. Of 605 eligible staff members, 420 (69%) responded: registered nurses, 41%; dialysis technicians, 51%; and licensed practical nurses, 8%. Only 35% reported that dialysis patients were at risk for bloodborne virus infections, and only 36% reported always following recommended hand hygiene and glove use practices. Independent factors associated with more frequent compliance were being a technician (versus a registered nurse) and reporting always doing what was needed to protect themselves from infection. Compliance with recommended hand hygiene and glove use practices by hemodialysis staff was low. The rationale for infection control practices specific to the hemodialysis setting was poorly understood by all staff. Infection control training should be tailored to this setting and should address misconceptions.

Some considerations on the use of ecological models to predict species' geographic distributions

USGS Publications Warehouse

Peterjohn, B.G.

2001-01-01

Peterson (2001) used Genetic Algorithm for Rule-set Prediction (GARP) models to predict distribution patterns from Breeding Bird Survey (BBS) data. Evaluations of these models should consider inherent limitations of BBS data: (1) BBS methods may not sample species and habitats equally; (2) using BBS data for both model development and testing may overlook poor fit of some models; and (3) BBS data may not provide the desired spatial resolution or capture temporal changes in species distributions. The predictive value of GARP models requires additional study, especially comparisons with distribution patterns from independent data sets. When employed at appropriate temporal and geographic scales, GARP models show considerable promise for conservation biology applications but provide limited inferences concerning processes responsible for the observed patterns.

Carbon nuclear magnetic resonance spectroscopic fingerprinting of commercial gasoline: pattern-recognition analyses for screening quality control purposes.

PubMed

Flumignan, Danilo Luiz; Boralle, Nivaldo; Oliveira, José Eduardo de

2010-06-30

In this work, the combination of carbon nuclear magnetic resonance ((13)C NMR) fingerprinting with pattern-recognition analyses provides an original and alternative approach to screening commercial gasoline quality. Soft Independent Modelling of Class Analogy (SIMCA) was performed on spectroscopic fingerprints to classify representative commercial gasoline samples, which were selected by Hierarchical Cluster Analyses (HCA) over several months in retails services of gas stations, into previously quality-defined classes. Following optimized (13)C NMR-SIMCA algorithm, sensitivity values were obtained in the training set (99.0%), with leave-one-out cross-validation, and external prediction set (92.0%). Governmental laboratories could employ this method as a rapid screening analysis to discourage adulteration practices. Copyright 2010 Elsevier B.V. All rights reserved.

Analyzing ROC curves using the effective set-size model

NASA Astrophysics Data System (ADS)

Samuelson, Frank W.; Abbey, Craig K.; He, Xin

2018-03-01

The Effective Set-Size model has been used to describe uncertainty in various signal detection experiments. The model regards images as if they were an effective number (M*) of searchable locations, where the observer treats each location as a location-known-exactly detection task with signals having average detectability d'. The model assumes a rational observer behaves as if he searches an effective number of independent locations and follows signal detection theory at each location. Thus the location-known-exactly detectability (d') and the effective number of independent locations M* fully characterize search performance. In this model the image rating in a single-response task is assumed to be the maximum response that the observer would assign to these many locations. The model has been used by a number of other researchers, and is well corroborated. We examine this model as a way of differentiating imaging tasks that radiologists perform. Tasks involving more searching or location uncertainty may have higher estimated M* values. In this work we applied the Effective Set-Size model to a number of medical imaging data sets. The data sets include radiologists reading screening and diagnostic mammography with and without computer-aided diagnosis (CAD), and breast tomosynthesis. We developed an algorithm to fit the model parameters using two-sample maximum-likelihood ordinal regression, similar to the classic bi-normal model. The resulting model ROC curves are rational and fit the observed data well. We find that the distributions of M* and d' differ significantly among these data sets, and differ between pairs of imaging systems within studies. For example, on average tomosynthesis increased readers' d' values, while CAD reduced the M* parameters. We demonstrate that the model parameters M* and d' are correlated. We conclude that the Effective Set-Size model may be a useful way of differentiating location uncertainty from the diagnostic uncertainty in medical imaging tasks.

Molecular differential diagnosis of follicular thyroid carcinoma and adenoma based on gene expression profiling by using formalin-fixed paraffin-embedded tissues

PubMed Central

2013-01-01

Background Differential diagnosis between malignant follicular thyroid cancer (FTC) and benign follicular thyroid adenoma (FTA) is a great challenge for even an experienced pathologist and requires special effort. Molecular markers may potentially support a differential diagnosis between FTC and FTA in postoperative specimens. The purpose of this study was to derive molecular support for differential post-operative diagnosis, in the form of a simple multigene mRNA-based classifier that would differentiate between FTC and FTA tissue samples. Methods A molecular classifier was created based on a combined analysis of two microarray datasets (using 66 thyroid samples). The performance of the classifier was assessed using an independent dataset comprising 71 formalin-fixed paraffin-embedded (FFPE) samples (31 FTC and 40 FTA), which were analysed by quantitative real-time PCR (qPCR). In addition, three other microarray datasets (62 samples) were used to confirm the utility of the classifier. Results Five of 8 genes selected from training datasets (ELMO1, EMCN, ITIH5, KCNAB1, SLCO2A1) were amplified by qPCR in FFPE material from an independent sample set. Three other genes did not amplify in FFPE material, probably due to low abundance. All 5 analysed genes were downregulated in FTC compared to FTA. The sensitivity and specificity of the 5-gene classifier tested on the FFPE dataset were 71% and 72%, respectively. Conclusions The proposed approach could support histopathological examination: 5-gene classifier may aid in molecular discrimination between FTC and FTA in FFPE material. PMID:24099521

Micro X-ray Fluorescence Study of Late Pre-Hispanic Ceramics from the Western Slopes of the South Central Andes Region in the Arica y Parinacota Region, Chile: A New Methodological Approach

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

Flewett, S.; Saintenoy, T.; Sepulveda, M.

Archeological ceramic paste material typically consists of a mix of a clay matrix and various millimeter and sub-millimeter sized mineral inclusions. Micro X-ray Fluorescence (μXRF) is a standard compositional classification tool, and in this work we propose and demonstrate an improved fluorescence map processing protocol where the mineral inclusions are automatically separated from the clay matrix to allow independent statistical analysis of the two parts. Application of this protocol allowed us to improve enhance the differentiation discrimination between different ceramic shards compared with the standard procedure of comparing working with only the spatially averaged elemental concentrations. Using the new protocol,more » we performed an initial compositional classification of a set of 83 ceramic shards from the western slopes of the south central Andean region in the Arica y Parinacota region of present-day far northern Chile. Comparing the classifications obtained using the new versus the old (average concentrations only) protocols, we found that some samples were erroneously classified with the old protocol. From an archaeological perspective, a very broad and heterogeneous sample set was used in this study due to the fact that this was the first such study to be performed on ceramics from this region. This allowed a general overview to be obtained, however further work on more specific sample sets will be necessary to extract concrete archaeological conclusions.« less

Goal setting as a strategy for dietary and physical activity behavior change: a review of the literature.

PubMed

Shilts, Mical Kay; Horowitz, Marcel; Townsend, Marilyn S

2004-01-01

Estimate effectiveness of goal setting for nutrition and physical activity behavior change, review the effect of goal-setting characteristics on behavior change, and investigate effectiveness of interventions containing goal setting. For this review, a literature search was conducted for the period January 1977 through December 2003 that included a Current Contents, Biosis Previews, Medline, PubMed, PsycINFO, and ERIC search of databases and a reference list search. Key words were goal, goal setting, nutrition, diet, dietary, physical activity, exercise, behavior change, interventions, and fitness. The search identified 144 studies, of which 28 met inclusion criteria for being published in a peer reviewed journal and using goal setting in an intervention to modify dietary or physical activity behaviors. Excluded from this review were those studies that (1) evaluated goal setting cross-sectionally without an intervention; (2) used goal setting for behavioral disorders, to improve academic achievement, or in sports performance; (3) were reviews. The articles were categorized by target audience and secondarily by research focus. Data extracted included outcome measure, research rating, purpose, sample, sample description, assignment, findings, and goal-setting support. Thirteen of the 23 adult studies used a goal-setting effectiveness study design and eight produced positive results supporting goal setting. No adolescent or child studies used this design. The results were inconclusive for the studies investigating goal-setting characteristics (n = 7). Four adult and four child intervention evaluation studies showed positive outcomes. No studies reported power calculations, and only 32% of the studies were rated as fully supporting goal setting. Goal setting has shown some promise in promoting dietary and physical activity behavior change among adults, but methodological issues still need to be resolved. The literature with adolescents and children is limited, and the authors are not aware of any published studies with this audience investigating the independent effect of goal setting on dietary or physical activity behavior. Although, goal setting is widely used with children and adolescents in nutrition interventions, its effectiveness has yet to be reported.

Toxigenic Clostridium difficile colonization among hospitalised adults; risk factors and impact on survival.

PubMed

Behar, Laura; Chadwick, David; Dunne, Angela; Jones, Christopher I; Proctor, Claire; Rajkumar, Chakravarthi; Sharratt, Paula; Stanley, Philip; Whiley, Angela; Wilks, Mark; Llewelyn, Martin J

2017-07-01

To establish risk factors for Clostridium difficile colonization among hospitalized patients in England. Patients admitted to elderly medicine wards at three acute hospitals in England were recruited to a prospective observational study. Participants were asked to provide a stool sample as soon as possible after enrolment and then weekly during their hospital stay. Samples were cultured for C. difficile before ribotyping and toxin detection by PCR. A multivariable logistic regression model of risk factors for C. difficile colonization was fitted from univariable risk factors significant at the p < 0.05 level. 410/727 participants submitted ≥1 stool sample and 40 (9.8%) carried toxigenic C. difficile in the first sample taken. Ribotype 106 was identified three times and seven other ribotypes twice. No ribotype 027 strains were identified. Independent predictors of colonization were previous C. difficile infection (OR 4.53 (95% C.I. 1.33-15.48) and malnutrition (MUST score ≥2) (OR 3.29 (95% C.I. 1.47-7.35)). Although C. difficile colonised patients experienced higher 90-day mortality, colonization was not an independent risk for death. In a non-epidemic setting patients who have previously had CDI and have a MUST score of ≥2 are at increased risk of C. difficile colonization and could be targeted for active surveillance to prevent C. difficile transmission. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

The Brief Illness Perceptions Questionnaire identifies 3 classes of people seeking rehabilitation for mechanical neck pain.

PubMed

Walton, David M; Lefebvre, Andy; Reynolds, Darcy

2015-06-01

Illness representations pertain to the ways in which an individual constructs and understands the experience of a health condition. The Brief Illness Perceptions Questionnaire (BIPQ) comprises 9 items intended to capture the key components of the Illness Representations Model. The purpose of this paper was to explore the utility of the BIPQ for evaluating and classifying uncomplicated mechanical neck pain in the rehabilitation setting. A convenience sample of 198 subjects presenting to physiotherapy for neck pain problems were used in this study. In the first step, 183 subjects completed the BIPQ and a series of related cognitive measures. Latent class analysis (LCA) was used to explore the number of identifiable classes amongst the sample based on BIPQ response patterns. A regression equation was created to facilitate classification. In the second step, an independent sample of 15 subjects were classified using the equation established in step 1, and they were followed over a 3 month period. The LCA revealed 3 classes of subjects with optimal fit statistics: mildly affected, moderately affected, and severely affected. Inter-group comparisons of the secondary cognitive measures supported these labels. Classification accuracy of a regression equation was high (94.5%). Applying the equation to the independent longitudinal sample revealed that it functioned equally well and that the classes may have prognostic value. The BIPQ may be a useful clinical tool for classification of neck pain. Copyright © 2014 Elsevier Ltd. All rights reserved.

Systematic review of interventions addressing social isolation and depression in aged care clients.

PubMed

Franck, Linél; Molyneux, Natalie; Parkinson, Lynne

2016-06-01

A systematic review was undertaken of studies reporting interventions for reducing social isolation and depression in older people receiving aged care services (community or residential). Gray literature and relevant electronic databases were systematically searched for studies published in English between January 2009 and December 2013. Two reviewers independently screened studies for selection using predetermined inclusion and exclusion criteria and independently completed methodological quality review at study level. Studies of poor methodological quality were excluded. Data were extracted at study level by one reviewer and independently checked by a second reviewer, using a standardized form. The results across studies were qualitatively synthesized with outcomes described and summarized at last follow-up. Although the original objective was to review rural studies, no intervention studies based in rural areas met criteria for inclusion in the review, and only urban studies could be reviewed. Of 403 articles, six articles representing five studies with moderate-to-low risk of bias were included for review. All study participants were older adults ranging in age from 77 to 86 years. All studies had small sample sizes, ranging from 26 to 113 participants. Three of the five included intervention studies successfully reduced social isolation; one also successfully reduced depression. Only one intervention, group-based reminiscence therapy, was reported as successful in reducing both social isolation and depression in older people within an urban aged care setting. More research is needed to explore transferability of interventions across different aged care settings and into rural areas.

ICT services for active ageing and independent living: identification and assessment.

PubMed

Christophorou, Christophoros; Kleanthous, Styliani; Georgiadis, Dimosthenis; Cereghetti, Donato M; Andreou, Panayiotis; Wings, Cindy; Christodoulou, Eleni; Samaras, George

2016-09-01

Based on the demographic changes and the rapid increase of older population in Europe, major challenges are expected to rise, both in the economy as well as the society, whether the dominant care model for supporting elderly in living independently at home continues to rely on informal and formal caregivers' assistance. To respond to the above challenges, assistive technologies are called to develop Information and Communication Technology (ICT) services for supporting seniors to remain active and independent, for as long as possible, in their chosen home environment. The work described in this Letter is based on the Miraculous-Life project and it emphasises the identification and assessment of a set of services that an ICT system for Ageing Well should support, in an actual end-users setting. The outcome of this work may inform fellow researchers and other projects in the area of Ageing Well in: (i) understanding which ICT services can be the most valuable for end-users' Quality of Life, (ii) prioritising the development of related ICT services and (iii) facilitating better recourse allocation in order to reduce any risks associated to implementation failures of these services within their respective projects. A final trial phase is planned, aiming to validate the Miraculous Life prototype longitudinally in a naturalistic environment with a larger sample size. During this trial, it will be investigated if perceived usefulness, satisfaction and motivation could be predicted by sociodemographic variables and personality.

Prognostic significance of microsatellite instability‑associated pathways and genes in gastric cancer.

PubMed

Hang, Xiaosheng; Li, Dapeng; Wang, Jianping; Wang, Ge

2018-07-01

The aim of the present study was to reveal the potential molecular mechanisms of microsatellite instability (MSI) on the prognosis of gastric cancer (GC). The investigation was performed based on an RNAseq expression profiling dataset downloaded from The Cancer Genome Atlas, including 64 high‑level MSI (MSI‑H) GC samples, 44 low‑level MSI (MSI‑L) GC samples and 187 stable microsatellite (MSI‑S) GC samples. Differentially expressed genes (DEGs) were identified between the MSI‑H, MSI‑L and MSI‑S samples. Pathway enrichment analysis was performed for the identified DEGs and the pathway deviation scores of the significant enrichment pathways were calculated. A Multi‑Layer Perceptron (MLP) classifier, based on the different pathways associated with the MSI statuses was constructed for predicting the outcome of patients with GC, which was validated in another independent dataset. A total of 190 DEGs were selected between the MSI‑H, MSI‑L and MSI‑S samples. The MLP classifier was established based on the deviation scores of 10 significant pathways, among which antigen processing and presentation, and inflammatory bowel disease pathways were significantly enriched with HLA‑DRB5, HLA‑DMA, HLA‑DQA1 and HLA‑DRA; the measles, toxoplasmosis and herpes simplex infection pathways were significantly enriched with Janus kinase 2 (JAK2), caspase‑8 (CASP8) and Fas. The classifier performed well on an independent validation set with 100 GC samples. Taken together, the results indicated that MSI status may affect GC prognosis, partly through the antigen processing and presentation, inflammatory bowel disease, measles, toxoplasmosis and herpes simplex infection pathways. HLA‑DRB5, HLA‑DMA, HLA‑DQA1, HLA‑DRA, JAK2, CASP8 and Fas may be predictive factors for prognosis in GC.

Nappy pad urine samples for investigation and treatment of UTI in young children: the ‘DUTY’ prospective diagnostic cohort study

PubMed Central

Butler, Christopher C; Sterne, Jonathan AC; Lawton, Michael; O’Brien, Kathryn; Wootton, Mandy; Hood, Kerenza; Hollingworth, William; Little, Paul; Delaney, Brendan C; van der Voort, Judith; Dudley, Jan; Birnie, Kate; Pickles, Timothy; Waldron, Cherry-Ann; Downing, Harriet; Thomas-Jones, Emma; Lisles, Catherine; Rumsby, Kate; Durbaba, Stevo; Whiting, Penny; Harman, Kim; Howe, Robin; MacGowan, Alasdair; Fletcher, Margaret; Hay, Alastair D

2016-01-01

Background The added diagnostic utility of nappy pad urine samples and the proportion that are contaminated is unknown. Aim To develop a clinical prediction rule for the diagnosis of urinary tract infection (UTI) based on sampling using the nappy pad method. Design and setting Acutely unwell children <5 years presenting to 233 UK primary care sites. Method Logistic regression to identify independent associations of symptoms, signs, and urine dipstick test results with UTI; diagnostic utility quantified as area under the receiver operator curves (AUROC). Nappy pad rule characteristics, AUROC, and contamination, compared with findings from clean-catch samples. Results Nappy pad samples were obtained from 3205 children (82% aged <2 years; 48% female), culture results were available for 2277 (71.0%) and 30 (1.3%) had a UTI on culture. Female sex, smelly urine, darker urine, and the absence of nappy rash were independently associated with a UTI, with an internally-validated, coefficient model AUROC of 0.81 (0.87 for clean-catch), which increased to 0.87 (0.90 for clean-catch) with the addition of dipstick results. GPs’ ‘working diagnosis’ had an AUROC 0.63 (95% confidence intervals [CI] = 0.53 to 0.72). A total of 12.2% of nappy pad and 1.8% of clean-catch samples were ‘frankly contaminated’ (risk ratio 6.66; 95% CI = 4.95 to 8.96; P<0.001). Conclusion Nappy pad urine culture results, with features that can be reported by parents and dipstick tests, can be clinically useful, but are less accurate and more often contaminated compared with clean-catch urine culture. PMID:27364678

Identification and characterization of unrecognized viruses in stool samples of non-polio acute flaccid paralysis children by simplified VIDISCA.

PubMed

Shaukat, Shahzad; Angez, Mehar; Alam, Muhammad Masroor; Jebbink, Maarten F; Deijs, Martin; Canuti, Marta; Sharif, Salmaan; de Vries, Michel; Khurshid, Adnan; Mahmood, Tariq; van der Hoek, Lia; Zaidi, Syed Sohail Zahoor

2014-08-12

The use of sequence independent methods combined with next generation sequencing for identification purposes in clinical samples appears promising and exciting results have been achieved to understand unexplained infections. One sequence independent method, Virus Discovery based on cDNA Amplified Fragment Length Polymorphism (VIDISCA) is capable of identifying viruses that would have remained unidentified in standard diagnostics or cell cultures. VIDISCA is normally combined with next generation sequencing, however, we set up a simplified VIDISCA which can be used in case next generation sequencing is not possible. Stool samples of 10 patients with unexplained acute flaccid paralysis showing cytopathic effect in rhabdomyosarcoma cells and/or mouse cells were used to test the efficiency of this method. To further characterize the viruses, VIDISCA-positive samples were amplified and sequenced with gene specific primers. Simplified VIDISCA detected seven viruses (70%) and the proportion of eukaryotic viral sequences from each sample ranged from 8.3 to 45.8%. Human enterovirus EV-B97, EV-B100, echovirus-9 and echovirus-21, human parechovirus type-3, human astrovirus probably a type-3/5 recombinant, and tetnovirus-1 were identified. Phylogenetic analysis based on the VP1 region demonstrated that the human enteroviruses are more divergent isolates circulating in the community. Our data support that a simplified VIDISCA protocol can efficiently identify unrecognized viruses grown in cell culture with low cost, limited time without need of advanced technical expertise. Also complex data interpretation is avoided thus the method can be used as a powerful diagnostic tool in limited resources. Redesigning the routine diagnostics might lead to additional detection of previously undiagnosed viruses in clinical samples of patients.

Affected States Soft Independent Modeling by Class Analogy from the Relation Between Independent Variables, Number of Independent Variables and Sample Size

PubMed Central

Kanık, Emine Arzu; Temel, Gülhan Orekici; Erdoğan, Semra; Kaya, İrem Ersöz

2013-01-01

Objective: The aim of study is to introduce method of Soft Independent Modeling of Class Analogy (SIMCA), and to express whether the method is affected from the number of independent variables, the relationship between variables and sample size. Study Design: Simulation study. Material and Methods: SIMCA model is performed in two stages. In order to determine whether the method is influenced by the number of independent variables, the relationship between variables and sample size, simulations were done. Conditions in which sample sizes in both groups are equal, and where there are 30, 100 and 1000 samples; where the number of variables is 2, 3, 5, 10, 50 and 100; moreover where the relationship between variables are quite high, in medium level and quite low were mentioned. Results: Average classification accuracy of simulation results which were carried out 1000 times for each possible condition of trial plan were given as tables. Conclusion: It is seen that diagnostic accuracy results increase as the number of independent variables increase. SIMCA method is a method in which the relationship between variables are quite high, the number of independent variables are many in number and where there are outlier values in the data that can be used in conditions having outlier values. PMID:25207065

Affected States soft independent modeling by class analogy from the relation between independent variables, number of independent variables and sample size.

PubMed

Kanık, Emine Arzu; Temel, Gülhan Orekici; Erdoğan, Semra; Kaya, Irem Ersöz

2013-03-01

The aim of study is to introduce method of Soft Independent Modeling of Class Analogy (SIMCA), and to express whether the method is affected from the number of independent variables, the relationship between variables and sample size. Simulation study. SIMCA model is performed in two stages. In order to determine whether the method is influenced by the number of independent variables, the relationship between variables and sample size, simulations were done. Conditions in which sample sizes in both groups are equal, and where there are 30, 100 and 1000 samples; where the number of variables is 2, 3, 5, 10, 50 and 100; moreover where the relationship between variables are quite high, in medium level and quite low were mentioned. Average classification accuracy of simulation results which were carried out 1000 times for each possible condition of trial plan were given as tables. It is seen that diagnostic accuracy results increase as the number of independent variables increase. SIMCA method is a method in which the relationship between variables are quite high, the number of independent variables are many in number and where there are outlier values in the data that can be used in conditions having outlier values.

Oxygen-isotopic Compositions of Low-FeO relicts in High-FeO Host Chondrules in Acfer 094, a Type 3.0 Carbonaceous Chondrite Closely Related to CM

NASA Technical Reports Server (NTRS)

Rubin, Alan E.; Kunihiro, Tak; Wasson, John T.

2006-01-01

With one exception, the low-FeO relict olivine grains within high-FeO porphyritic chondrules in the type 3.0 Acfer 094 carbonaceous chondrite have DELTA O-17 ( = delta O-17 - 0.52 X delta O-18) values that are substantially more negative than those of the high-FeO olivine host materials. These results are similar to observations made earlier on chondrules in C03.0 chondrites and are consistent with two independent models: (1) Nebular solids evolved from low-FeO, low-DELTA O-17 compositions towards high-FeO, more positive DELTA O-17 compositions; and (2) the range of compositions resulted from the mixing of two independently formed components. The two models predict different trajectories on a DELTA O-17 vs. log Fe/Mg (olivine) diagram, but our sample set has too few values at intermediate Fe/Mg ratios to yield a definitive answer. Published data showing that Acfer 094 has higher volatile contents than CO chondrites suggest a closer link to CM chondrites. This is consistent with the high modal matrix abundance in Acfer 094 (49 vol.%). Acfer 094 may be an unaltered CM chondrite or an exceptionally matrix-rich CO chondrite. Chondrules in Acfer 094 and in CO and CM carbonaceous chondrites appear to sample the same population. Textural differences between Acfer 094 and CM chondrites are largely attributable to the high degree of hydrothermal alteration that the CM chondrites experienced in an asteroidal setting.

Gene signature of the post-Chernobyl papillary thyroid cancer.

PubMed

Handkiewicz-Junak, Daria; Swierniak, Michal; Rusinek, Dagmara; Oczko-Wojciechowska, Małgorzata; Dom, Genevieve; Maenhaut, Carine; Unger, Kristian; Detours, Vincent; Bogdanova, Tetiana; Thomas, Geraldine; Likhtarov, Ilya; Jaksik, Roman; Kowalska, Malgorzata; Chmielik, Ewa; Jarzab, Michal; Swierniak, Andrzej; Jarzab, Barbara

2016-07-01

Following the nuclear accidents in Chernobyl and later in Fukushima, the nuclear community has been faced with important issues concerning how to search for and diagnose biological consequences of low-dose internal radiation contamination. Although after the Chernobyl accident an increase in childhood papillary thyroid cancer (PTC) was observed, it is still not clear whether the molecular biology of PTCs associated with low-dose radiation exposure differs from that of sporadic PTC. We investigated tissue samples from 65 children/young adults with PTC using DNA microarray (Affymetrix, Human Genome U133 2.0 Plus) with the aim of identifying molecular differences between radiation-induced (exposed to Chernobyl radiation, ECR) and sporadic PTC. All participants were resident in the same region so that confounding factors related to genetics or environment were minimized. There were small but significant differences in the gene expression profiles between ECR and non-ECR PTC (global test, p < 0.01), with 300 differently expressed probe sets (p < 0.001) corresponding to 239 genes. Multifactorial analysis of variance showed that besides radiation exposure history, the BRAF mutation exhibited independent effects on the PTC expression profile; the histological subset and patient age at diagnosis had negligible effects. Ten genes (PPME1, HDAC11, SOCS7, CIC, THRA, ERBB2, PPP1R9A, HDGF, RAD51AP1, and CDK1) from the 19 investigated with quantitative RT-PCR were confirmed as being associated with radiation exposure in an independent, validation set of samples. Significant, but subtle, differences in gene expression in the post-Chernobyl PTC are associated with previous low-dose radiation exposure.

Elevated expression of CXC chemokines in pediatric osteosarcoma patients.

PubMed

Li, Yiting; Flores, Ricardo; Yu, Alexander; Okcu, M Fatih; Murray, Jeffrey; Chintagumpala, Murali; Hicks, John; Lau, Ching C; Man, Tsz-Kwong

2011-01-01

Osteosarcoma is the most common malignant bone tumor in children. Despite the advent of chemotherapy, the survival of osteosarcoma patients has not been significantly improved recently. Chemokines are a group of signaling molecules that have been implicated in tumorigenesis and metastasis. The authors used an antibody microarray to identify chemokines that were elevated in the plasma samples of osteosarcoma patients. The results were validated using enzyme-linked immunosorbent assays on an independent set of samples. The tumor expressions of 3 chemokines were examined in 2 sets of osteosarcoma tissue arrays. The authors also evaluated the proliferative effect of the chemokines in 4 osteosarcoma cell lines. The authors found that the plasma levels of CXCL4, CXCL6, and CXCL12 in the osteosarcoma patients were significantly higher than those in the controls, and the results were validated by an independent osteosarcoma cohort (P < .05). However, CXCL4 (100%) and CXCL6 (91%) were frequently expressed in osteosarcoma, whereas CXCL12 was only expressed in 4%. Survival analysis further showed that higher circulating levels of CXCL4 and CXCL6, but not CXCL12, were associated with a poorer outcome of osteosarcoma patients. Addition of exogenous chemokines significantly promoted the growth of different osteosarcoma cells (P < .05). The results demonstrate that CXCL4 and CXCL6 are frequently expressed in osteosarcoma, and that the plasma levels of these 2 chemokines are associated with patient outcomes. Further study of these circulating chemokines may provide a promising approach for prognostication of osteosarcoma. Targeting these chemokines or their receptors may also lead to a novel therapeutic invention. © 2010 American Cancer Society.

Gaussian process based independent analysis for temporal source separation in fMRI.

PubMed

Hald, Ditte Høvenhoff; Henao, Ricardo; Winther, Ole

2017-05-15

Functional Magnetic Resonance Imaging (fMRI) gives us a unique insight into the processes of the brain, and opens up for analyzing the functional activation patterns of the underlying sources. Task-inferred supervised learning with restrictive assumptions in the regression set-up, restricts the exploratory nature of the analysis. Fully unsupervised independent component analysis (ICA) algorithms, on the other hand, can struggle to detect clear classifiable components on single-subject data. We attribute this shortcoming to inadequate modeling of the fMRI source signals by failing to incorporate its temporal nature. fMRI source signals, biological stimuli and non-stimuli-related artifacts are all smooth over a time-scale compatible with the sampling time (TR). We therefore propose Gaussian process ICA (GPICA), which facilitates temporal dependency by the use of Gaussian process source priors. On two fMRI data sets with different sampling frequency, we show that the GPICA-inferred temporal components and associated spatial maps allow for a more definite interpretation than standard temporal ICA methods. The temporal structures of the sources are controlled by the covariance of the Gaussian process, specified by a kernel function with an interpretable and controllable temporal length scale parameter. We propose a hierarchical model specification, considering both instantaneous and convolutive mixing, and we infer source spatial maps, temporal patterns and temporal length scale parameters by Markov Chain Monte Carlo. A companion implementation made as a plug-in for SPM can be downloaded from https://github.com/dittehald/GPICA. Copyright © 2017 Elsevier Inc. All rights reserved.

The stroke impairment assessment set: its internal consistency and predictive validity.

PubMed

Tsuji, T; Liu, M; Sonoda, S; Domen, K; Chino, N

2000-07-01

To study the scale quality and predictive validity of the Stroke Impairment Assessment Set (SIAS) developed for stroke outcome research. Rasch analysis of the SIAS; stepwise multiple regression analysis to predict discharge functional independence measure (FIM) raw scores from demographic data, the SIAS scores, and the admission FIM scores; cross-validation of the prediction rule. Tertiary rehabilitation center in Japan. One hundred ninety stroke inpatients for the study of the scale quality and the predictive validity; a second sample of 116 stroke inpatients for the cross-validation study. Mean square fit statistics to study the degree of fit to the unidimensional model; logits to express item difficulties; discharge FIM scores for the study of predictive validity. The degree of misfit was acceptable except for the shoulder range of motion (ROM), pain, visuospatial function, and speech items; and the SIAS items could be arranged on a common unidimensional scale. The difficulty patterns were identical at admission and at discharge except for the deep tendon reflexes, ROM, and pain items. They were also similar for the right- and left-sided brain lesion groups except for the speech and visuospatial items. For the prediction of the discharge FIM scores, the independent variables selected were age, the SIAS total scores, and the admission FIM scores; and the adjusted R2 was .64 (p < .0001). Stability of the predictive equation was confirmed in the cross-validation sample (R2 = .68, p < .001). The unidimensionality of the SIAS was confirmed, and the SIAS total scores proved useful for stroke outcome prediction.

Multi-Source Learning for Joint Analysis of Incomplete Multi-Modality Neuroimaging Data

PubMed Central

Yuan, Lei; Wang, Yalin; Thompson, Paul M.; Narayan, Vaibhav A.; Ye, Jieping

2013-01-01

Incomplete data present serious problems when integrating largescale brain imaging data sets from different imaging modalities. In the Alzheimer’s Disease Neuroimaging Initiative (ADNI), for example, over half of the subjects lack cerebrospinal fluid (CSF) measurements; an independent half of the subjects do not have fluorodeoxyglucose positron emission tomography (FDG-PET) scans; many lack proteomics measurements. Traditionally, subjects with missing measures are discarded, resulting in a severe loss of available information. We address this problem by proposing two novel learning methods where all the samples (with at least one available data source) can be used. In the first method, we divide our samples according to the availability of data sources, and we learn shared sets of features with state-of-the-art sparse learning methods. Our second method learns a base classifier for each data source independently, based on which we represent each source using a single column of prediction scores; we then estimate the missing prediction scores, which, combined with the existing prediction scores, are used to build a multi-source fusion model. To illustrate the proposed approaches, we classify patients from the ADNI study into groups with Alzheimer’s disease (AD), mild cognitive impairment (MCI) and normal controls, based on the multi-modality data. At baseline, ADNI’s 780 participants (172 AD, 397 MCI, 211 Normal), have at least one of four data types: magnetic resonance imaging (MRI), FDG-PET, CSF and proteomics. These data are used to test our algorithms. Comprehensive experiments show that our proposed methods yield stable and promising results. PMID:24014189

Iterative Strain-Gage Balance Calibration Data Analysis for Extended Independent Variable Sets

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert Manfred

2011-01-01

A new method was developed that makes it possible to use an extended set of independent calibration variables for an iterative analysis of wind tunnel strain gage balance calibration data. The new method permits the application of the iterative analysis method whenever the total number of balance loads and other independent calibration variables is greater than the total number of measured strain gage outputs. Iteration equations used by the iterative analysis method have the limitation that the number of independent and dependent variables must match. The new method circumvents this limitation. It simply adds a missing dependent variable to the original data set by using an additional independent variable also as an additional dependent variable. Then, the desired solution of the regression analysis problem can be obtained that fits each gage output as a function of both the original and additional independent calibration variables. The final regression coefficients can be converted to data reduction matrix coefficients because the missing dependent variables were added to the data set without changing the regression analysis result for each gage output. Therefore, the new method still supports the application of the two load iteration equation choices that the iterative method traditionally uses for the prediction of balance loads during a wind tunnel test. An example is discussed in the paper that illustrates the application of the new method to a realistic simulation of temperature dependent calibration data set of a six component balance.

A functional polymorphism of the TNF-{alpha} gene that is associated with type 2 DM

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

Susa, Shinji; Daimon, Makoto; Sakabe, Jun-Ichi

2008-05-09

To examine the association of the tumor necrosis factor-{alpha} (TNF-{alpha}) gene region with type 2 diabetes (DM), 11 single-nucleotide polymorphisms (SNPs) of the region were analyzed. The initial study using a sample set (148 cases vs. 227 controls) showed a significant association of the SNP IVS1G + 123A of the TNF-{alpha} gene with DM (p = 0.0056). Multiple logistic regression analysis using an enlarged sample set (225 vs. 716) revealed the significant association of the SNP with DM independently of any clinical traits examined (OR: 1.49, p = 0.014). The functional relevance of the SNP were examined by the electrophoreticmore » mobility shift assays using nuclear extracts from the U937 and NIH3T3 cells and luciferase assays in these cells with Simian virus 40 promoter- and TNF-{alpha} promoter-reporter gene constructs. The functional analyses showed that YY1 transcription factor bound allele-specifically to the SNP region and, the IVS1 + 123A allele had an increase in luciferase expression compared with the G allele.« less

Charge and magnetic ordering in the electron-doped magnetoresistive materials CaMnO3-δ (δ=0.06,0.11)

NASA Astrophysics Data System (ADS)

Wiebe, C. R.; Greedan, J. E.; Gardner, J. S.; Zeng, Z.; Greenblatt, M.

2001-08-01

The magnetoresistive ``electron''-doped materials CaMnO3-δ (δ=0.06,0.11) have been investigated using powder neutron diffraction. The two materials are n-type semiconductors which exhibit antiferromagnetic ordering at TN~125 K, but they have different magnetic structures. The CaMnO2.94 sample orders in a simple G-type antiferromagnetic structure, which is also observed in CaMnO3. The CaMnO2.89 sample, on the other hand, exhibits two magnetic features: the G-type reflections as noted above, and a set of reflections that can be indexed on a k=(0,0,14) ordering wave vector. A model for the magnetic structure is proposed which involves Mn3+/Mn4+ charge ordering concomitant with the magnetic ordering. The presence of a set of weak, temperature independent structural reflections which can also be indexed on a k=(0,0,14) supercell suggests an oxygen vacancy ordering which may play a role in the charge ordering.

Cross-Study Homogeneity of Psoriasis Gene Expression in Skin across a Large Expression Range

PubMed Central

Kerkof, Keith; Timour, Martin; Russell, Christopher B.

2013-01-01

Background In psoriasis, only limited overlap between sets of genes identified as differentially expressed (psoriatic lesional vs. psoriatic non-lesional) was found using statistical and fold-change cut-offs. To provide a framework for utilizing prior psoriasis data sets we sought to understand the consistency of those sets. Methodology/Principal Findings Microarray expression profiling and qRT-PCR were used to characterize gene expression in PP and PN skin from psoriasis patients. cDNA (three new data sets) and cRNA hybridization (four existing data sets) data were compared using a common analysis pipeline. Agreement between data sets was assessed using varying qualitative and quantitative cut-offs to generate a DEG list in a source data set and then using other data sets to validate the list. Concordance increased from 67% across all probe sets to over 99% across more than 10,000 probe sets when statistical filters were employed. The fold-change behavior of individual genes tended to be consistent across the multiple data sets. We found that genes with <2-fold change values were quantitatively reproducible between pairs of data-sets. In a subset of transcripts with a role in inflammation changes detected by microarray were confirmed by qRT-PCR with high concordance. For transcripts with both PN and PP levels within the microarray dynamic range, microarray and qRT-PCR were quantitatively reproducible, including minimal fold-changes in IL13, TNFSF11, and TNFRSF11B and genes with >10-fold changes in either direction such as CHRM3, IL12B and IFNG. Conclusions/Significance Gene expression changes in psoriatic lesions were consistent across different studies, despite differences in patient selection, sample handling, and microarray platforms but between-study comparisons showed stronger agreement within than between platforms. We could use cut-offs as low as log10(ratio) = 0.1 (fold-change = 1.26), generating larger gene lists that validate on independent data sets. The reproducibility of PP signatures across data sets suggests that different sample sets can be productively compared. PMID:23308107

Performance of amplicon-based next generation DNA sequencing for diagnostic gene mutation profiling in oncopathology.

PubMed

Sie, Daoud; Snijders, Peter J F; Meijer, Gerrit A; Doeleman, Marije W; van Moorsel, Marinda I H; van Essen, Hendrik F; Eijk, Paul P; Grünberg, Katrien; van Grieken, Nicole C T; Thunnissen, Erik; Verheul, Henk M; Smit, Egbert F; Ylstra, Bauke; Heideman, Daniëlle A M

2014-10-01

Next generation DNA sequencing (NGS) holds promise for diagnostic applications, yet implementation in routine molecular pathology practice requires performance evaluation on DNA derived from routine formalin-fixed paraffin-embedded (FFPE) tissue specimens. The current study presents a comprehensive analysis of TruSeq Amplicon Cancer Panel-based NGS using a MiSeq Personal sequencer (TSACP-MiSeq-NGS) for somatic mutation profiling. TSACP-MiSeq-NGS (testing 212 hotspot mutation amplicons of 48 genes) and a data analysis pipeline were evaluated in a retrospective learning/test set approach (n = 58/n = 45 FFPE-tumor DNA samples) against 'gold standard' high-resolution-melting (HRM)-sequencing for the genes KRAS, EGFR, BRAF and PIK3CA. Next, the performance of the validated test algorithm was assessed in an independent, prospective cohort of FFPE-tumor DNA samples (n = 75). In the learning set, a number of minimum parameter settings was defined to decide whether a FFPE-DNA sample is qualified for TSACP-MiSeq-NGS and for calling mutations. The resulting test algorithm revealed 82% (37/45) compliance to the quality criteria and 95% (35/37) concordant assay findings for KRAS, EGFR, BRAF and PIK3CA with HRM-sequencing (kappa = 0.92; 95% CI = 0.81-1.03) in the test set. Subsequent application of the validated test algorithm to the prospective cohort yielded a success rate of 84% (63/75), and a high concordance with HRM-sequencing (95% (60/63); kappa = 0.92; 95% CI = 0.84-1.01). TSACP-MiSeq-NGS detected 77 mutations in 29 additional genes. TSACP-MiSeq-NGS is suitable for diagnostic gene mutation profiling in oncopathology.

Impact of antibiotic administration on blood culture positivity at the beginning of sepsis: a prospective clinical cohort study.

PubMed

Scheer, Christian S; Fuchs, Christian; Gründling, Matthias; Vollmer, Marcus; Bast, Juliane; Bohnert, Jürgen A; Zimmermann, Kathrin; Hahnenkamp, Klaus; Rehberg, Sebastian; Kuhn, Sven-Olaf

2018-06-04

Sepsis guidelines recommend obtaining blood cultures before starting anti-infective therapy in patients with sepsis. However, little is known how antibiotic treatment prior to sampling affects bacterial growth. The aim of this study was to compare the results of blood cultures drawn prior to and under antibiotic therapy. Prospective clinical cohort study of septic patients. Adult ICU patients with 2 or 3 blood culture (BC) sets at the beginning of sepsis between 2010 and 2017 were included. Patients with blood culture samplings obtained prior to antibiotic therapy were compared to patients with samplings under antibiotic therapy. Blood culture positivity, defined as microbiological pathogen finding, was compared between the groups. Logistic regression was performed to adjust the impact of different factors with respect to blood culture positivity. In total, 559 patients with 1364 blood culture sets at the beginning of sepsis were analyzed. BC positivity was 50.6% (78/154) among septic patients who did not receive antibiotics and only 27.7% (112/405) in those who were already under antibiotics (P<0.001). Logistic regression revealed antibiotic therapy as an independent factor for less pathogen identification (Odds ratio 0.4; 95%CI 0.3-0.6). Gram-positive pathogens (28.3%(111/392) vs. 11.9%(116/972);P<0.001) and also gram-negative pathogens (16.3%(64/392) vs. 9.3%(90/972);P<0.001) were more frequent in BC sets drawn prior to antibiotic therapy compared to sets under antibiotics. Obtaining blood cultures under antibiotic therapy is associated with a significant loss of pathogen detection. This strongly emphasizes the current recommendation to obtain blood cultures prior to antibiotic administration in patients with sepsis. Copyright © 2018. Published by Elsevier Ltd.

Effects of Sampling Strategy, Detection Probability, and Independence of Counts on the Use of Point Counts

Treesearch

Grey W. Pendleton

1995-01-01

Many factors affect the use of point counts for monitoring bird populations, including sampling strategies, variation in detection rates, and independence of sample points. The most commonly used sampling plans are stratified sampling, cluster sampling, and systematic sampling. Each of these might be most useful for different objectives or field situations. Variation...

Linking species richness curves from non-contiguous sampling to contiguous-nested SAR: An empirical study

NASA Astrophysics Data System (ADS)

Lazarina, Maria; Kallimanis, Athanasios S.; Pantis, John D.; Sgardelis, Stefanos P.

2014-11-01

The species-area relationship (SAR) is one of the few generalizations in ecology. However, many different relationships are denoted as SARs. Here, we empirically evaluated the differences between SARs derived from nested-contiguous and non-contiguous sampling designs, using plants, birds and butterflies datasets from Great Britain, Greece, Massachusetts, New York and San Diego. The shape of SAR depends on the sampling scheme, but there is little empirical documentation on the magnitude of the deviation between different types of SARs and the factors affecting it. We implemented a strictly nested sampling design to construct nested-contiguous SAR (SACR), and systematic nested but non-contiguous, and random designs to construct non-contiguous species richness curves (SASRs for systematic and SACs for random designs) per dataset. The SACR lay below any SASR and most of the SACs. The deviation between them was related to the exponent f of the power law relationship between sampled area and extent. The lower the exponent f, the higher was the deviation between the curves. We linked SACR to SASR and SAC through the concept of "effective" area (Ae), i.e. the nested-contiguous area containing equal number of species with the accumulated sampled area (AS) of a non-contiguous sampling. The relationship between effective and sampled area was modeled as log(Ae) = klog(AS). A Generalized Linear Model was used to estimate the values of k from sampling design and dataset properties. The parameter k increased with the average distance between samples and with beta diversity, while k decreased with f. For both systematic and random sampling, the model performed well in predicting effective area in both the training set and in the test set which was totally independent from the training one. Through effective area, we can link different types of species richness curves based on sampling design properties, sampling effort, spatial scale and beta diversity patterns.

Origins of mass-dependent and mass-independent Ca isotope variations in meteoritic components and meteorites

NASA Astrophysics Data System (ADS)

Bermingham, K. R.; Gussone, N.; Mezger, K.; Krause, J.

2018-04-01

The Ca isotope composition of meteorites and their components may vary due to mass-dependent and/or -independent isotope effects. In order to evaluate the origin of these effects, five amoeboid olivine aggregates (AOAs), three calcium aluminum inclusions (CAIs), five chondrules (C), a dark inclusion from Allende (CV3), two dark fragments from North West Africa 753 (NWA 753; R3.9), and a whole rock sample of Orgueil (CI1) were analyzed. This is the first coupled mass-dependent and -independent Ca isotope dataset to include AOAs, a dark inclusion, and dark fragments. Where sample masses permit, Ca isotope data are reported with corresponding petrographic analyses and rare earth element (REE) relative abundance patterns. The CAIs and AOAs are enriched in light Ca isotopes (δ44/40Ca -5.32 to +0.72, where δ44/40Ca is reported relative to SRM 915a). Samples CAI 5 and AOA 1 have anomalous Group II REE patterns. These REE and δ44/40Ca data suggest that the CAI 5 and AOA 1 compositions were set via kinetic isotope fractionation during condensation and evaporation. The remaining samples show mass-dependent Ca isotope variations which cluster between δ44/40Ca +0.53 and +1.59, some of which are coupled with unfractionated REE abundance patterns. These meteoritic components likely formed through the coaccretion of the evaporative residue and condensate following Group II CAI formation or their chemical and isotopic signatures were decoupled (e.g., via nebular or parent-body alteration). The whole rock sample of Orgueil has a δ44/40Ca +0.67 ± 0.18 which is in agreement with most published data. Parent-body alteration, terrestrial alteration, and variable sampling of Ca-rich meteoritic components can have an effect on δ44/40Ca compositions in whole rock meteorites. Samples AOA 1, CAI 5, C 2, and C 4 display mass-independent 48/44Ca anomalies (ε48/44Ca +6 to +12) which are resolved from the standard composition. Other samples measured for these effects (AOA 5, CAI 1, CAI 2, C 3, D 1, D 2, D 3) possess the same 48/44Ca isotope composition as the standard within analytical uncertainty. These data indicate a heterogeneous distribution of 48Ca in the early solar nebula during formation of CAIs, AOAs, and chondrules. In a ε48/44Ca vs. δ44/40Ca plot, no strong correlation is evident which suggests that the thermal processing event which caused a heterogeneous distribution of ε48/44Ca in the solar nebula is unlikely to be directly related to the thermal processing event that caused coupled REE and Ca mass-dependent isotopic fractionation in meteoritic components.

Application of transmission infrared spectroscopy and partial least squares regression to predict immunoglobulin G concentration in dairy and beef cow colostrum.

PubMed

Elsohaby, Ibrahim; Windeyer, M Claire; Haines, Deborah M; Homerosky, Elizabeth R; Pearson, Jennifer M; McClure, J Trenton; Keefe, Greg P

2018-03-06

The objective of this study was to explore the potential of transmission infrared (TIR) spectroscopy in combination with partial least squares regression (PLSR) for quantification of dairy and beef cow colostral immunoglobulin G (IgG) concentration and assessment of colostrum quality. A total of 430 colostrum samples were collected from dairy (n = 235) and beef (n = 195) cows and tested by a radial immunodiffusion (RID) assay and TIR spectroscopy. Colostral IgG concentrations obtained by the RID assay were linked to the preprocessed spectra and divided into combined and prediction data sets. Three PLSR calibration models were built: one for the dairy cow colostrum only, the second for beef cow colostrum only, and the third for the merged dairy and beef cow colostrum. The predictive performance of each model was evaluated separately using the independent prediction data set. The Pearson correlation coefficients between IgG concentrations as determined by the TIR-based assay and the RID assay were 0.84 for dairy cow colostrum, 0.88 for beef cow colostrum, and 0.92 for the merged set of dairy and beef cow colostrum. The average of the differences between colostral IgG concentrations obtained by the RID- and TIR-based assays were -3.5, 2.7, and 1.4 g/L for dairy, beef, and merged colostrum samples, respectively. Further, the average relative error of the colostral IgG predicted by the TIR spectroscopy from the RID assay was 5% for dairy cow, 1.2% for beef cow, and 0.8% for the merged data set. The average intra-assay CV% of the IgG concentration predicted by the TIR-based method were 3.2%, 2.5%, and 6.9% for dairy cow, beef cow, and merged data set, respectively.The utility of TIR method for assessment of colostrum quality was evaluated using the entire data set and showed that TIR spectroscopy accurately identified the quality status of 91% of dairy cow colostrum, 95% of beef cow colostrum, and 89% and 93% of the merged dairy and beef cow colostrum samples, respectively. The results showed that TIR spectroscopy demonstrates potential as a simple, rapid, and cost-efficient method for use as an estimate of IgG concentration in dairy and beef cow colostrum samples and assessment of colostrum quality. The results also showed that merging the dairy and beef cow colostrum sample data sets improved the predictive ability of the TIR spectroscopy.

Predictors of personal recovery for persons with psychiatric disabilities: An examination of the Unity Model of Recovery.

PubMed

Song, Li-Yu

2017-04-01

This study examined a comprehensive set of potential correlates of recovery based on the Unity Model of Recovery. Thirty-two community psychiatric rehabilitation centers in Taiwan agreed to participate in this study. A sample of 592 participants were administered the questionnaires. Five groups of independent variables were included in the model: socio-demographic variables, illness variables, resilience, informal support, and formal support. The results of regression analysis provided support for the validity of the Unity Model of Recovery. The independent variables explained 53.5% of the variance in recovery for the full sample, and 55.5% for the subsample of the consumers who have been ever employed. The significance of the three cornerstones (resilience, family support, and symptoms) for recovery was confirmed. Other critical support variables, including the extent of rehabilitation service use, professional relationship, and professional support were also found to be significant factors. Among all the significant correlates, resilience, family support, and extent of rehabilitation service use ranked in the top three. The findings could shed light on paths to recovery. Implications for psychiatric services were discussed and suggested. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Estimating maize production in Kenya using NDVI: Some statistical considerations

USGS Publications Warehouse

Lewis, J.E.; Rowland, James; Nadeau , A.

1998-01-01

A regression model approach using a normalized difference vegetation index (NDVI) has the potential for estimating crop production in East Africa. However, before production estimation can become a reality, the underlying model assumptions and statistical nature of the sample data (NDVI and crop production) must be examined rigorously. Annual maize production statistics from 1982-90 for 36 agricultural districts within Kenya were used as the dependent variable; median area NDVI (independent variable) values from each agricultural district and year were extracted from the annual maximum NDVI data set. The input data and the statistical association of NDVI with maize production for Kenya were tested systematically for the following items: (1) homogeneity of the data when pooling the sample, (2) gross data errors and influence points, (3) serial (time) correlation, (4) spatial autocorrelation and (5) stability of the regression coefficients. The results of using a simple regression model with NDVI as the only independent variable are encouraging (r 0.75, p 0.05) and illustrate that NDVI can be a responsive indicator of maize production, especially in areas of high NDVI spatial variability, which coincide with areas of production variability in Kenya.

Prevalence of falls in elderly women

PubMed Central

Vitor, Priscila Regina Rorato; de Oliveira, Ana Carolina Kovaleski; Kohler, Renan; Winter, Gabriele Regiane; Rodacki, Cintia; Krause, Maressa Priscila

2015-01-01

OBJECTIVE: To verify prevalence of falls and fear of falling, and to compare functional fitness among elderly women fallers and non-fallers. METHODS: Seventy-eight elderly women participated in this study. Cases of falls and the fear of falling were self-reported by the elderly women, while the functional fitness was measured by a set of functional tests. Mean and standard deviation were used to describe the sample. Independent t-test was used to compare functional fitness between groups. RESULTS: The prevalence of falls in this sample was 32.4%. Among women fallers, 40% self-reported a high fear of falling. CONCLUSION: It is recommended that functional and resistance exercises are included in the preventive strategies for reducing risk factors for falls and its determinants in elderly women. Level of Evidence II, Prognostic-Prospective Study. PMID:26207095

Indications of a spatial variation of the fine structure constant.

PubMed

Webb, J K; King, J A; Murphy, M T; Flambaum, V V; Carswell, R F; Bainbridge, M B

2011-11-04

We previously reported Keck telescope observations suggesting a smaller value of the fine structure constant α at high redshift. New Very Large Telescope (VLT) data, probing a different direction in the Universe, shows an inverse evolution; α increases at high redshift. Although the pattern could be due to as yet undetected systematic effects, with the systematics as presently understood the combined data set fits a spatial dipole, significant at the 4.2 σ level, in the direction right ascension 17.5 ± 0.9 h, declination -58 ± 9 deg. The independent VLT and Keck samples give consistent dipole directions and amplitudes, as do high and low redshift samples. A search for systematics, using observations duplicated at both telescopes, reveals none so far which emulate this result.

Ultrahigh-Dimensional Multiclass Linear Discriminant Analysis by Pairwise Sure Independence Screening

PubMed Central

Pan, Rui; Wang, Hansheng; Li, Runze

2016-01-01

This paper is concerned with the problem of feature screening for multi-class linear discriminant analysis under ultrahigh dimensional setting. We allow the number of classes to be relatively large. As a result, the total number of relevant features is larger than usual. This makes the related classification problem much more challenging than the conventional one, where the number of classes is small (very often two). To solve the problem, we propose a novel pairwise sure independence screening method for linear discriminant analysis with an ultrahigh dimensional predictor. The proposed procedure is directly applicable to the situation with many classes. We further prove that the proposed method is screening consistent. Simulation studies are conducted to assess the finite sample performance of the new procedure. We also demonstrate the proposed methodology via an empirical analysis of a real life example on handwritten Chinese character recognition. PMID:28127109

Hyperspectral imaging for detection of non-O157 Shiga-toxin producing Escherichia coli (STEC) serogroups on spread plates of mixed cultures

NASA Astrophysics Data System (ADS)

Yoon, Seung Chul; Windham, William R.; Ladely, Scott; Heitschmidt, Gerald W.; Lawrence, Kurt C.; Park, Bosoon; Narang, Neelam; Cray, William C.

2012-05-01

We investigated the feasibility of visible and near-infrared (VNIR) hyperspectral imaging for rapid presumptive-positive screening of six representative non-O157 Shiga-toxin producing Escherichia coli (STEC) serogroups (O26, O45, O103, O111, O121, and O145) on spread plates of mixed cultures. Although the traditional culture method is still the "gold standard" for presumptive-positive pathogen screening, it is time-consuming, labor-intensive, not effective in testing large amount of food samples, and cannot completely prevent unwanted background microflora from growing together with target microorganisms on agar media. A previous study was performed using the data obtained from pure cultures individually inoculated on spot and/or spread plates in order to develop multivariate classification models differentiating each colony of the six non-O157 STEC serogroups and to optimize the models in terms of parameters. This study dealt with the validation of the trained and optimized models with a test set of new independent samples obtained from colonies on spread plates of mixed cultures. A new validation protocol appropriate to a hyperspectral imaging study for mixed cultures was developed. One imaging experiment with colonies obtained from two serial dilutions was performed. A total of six agar plates were prepared, where O45, O111 and O121 serogroups were inoculated into all six plates and each of O45, O103 and O145 serogroups was added into the mixture of the three common bacterial cultures. The number of colonies grown after 24-h incubation was 331 and the number of pixels associated with the grown colonies was 16,379. The best model found from this validation study was based on pre-processing with standard normal variate and detrending (SNVD), first derivative, spectral smoothing, and k-nearest neighbor classification (kNN, k=3) of scores in the principal component subspace spanned by 6 principal components. The independent testing results showed 95% overall detection accuracy at pixel level and 97% at colony level. The developed model was proven to be still valid even for the independent samples although the size of a test set was small and only one experiment was performed. This study was an important first step in validating and updating multivariate classification models for rapid screening of ground beef samples contaminated by non-O157 STEC pathogens using hyperspectral imaging.

Principal Component Noise Filtering for NAST-I Radiometric Calibration

NASA Technical Reports Server (NTRS)

Tian, Jialin; Smith, William L., Sr.

2011-01-01

The National Polar-orbiting Operational Environmental Satellite System (NPOESS) Airborne Sounder Testbed- Interferometer (NAST-I) instrument is a high-resolution scanning interferometer that measures emitted thermal radiation between 3.3 and 18 microns. The NAST-I radiometric calibration is achieved using internal blackbody calibration references at ambient and hot temperatures. In this paper, we introduce a refined calibration technique that utilizes a principal component (PC) noise filter to compensate for instrument distortions and artifacts, therefore, further improve the absolute radiometric calibration accuracy. To test the procedure and estimate the PC filter noise performance, we form dependent and independent test samples using odd and even sets of blackbody spectra. To determine the optimal number of eigenvectors, the PC filter algorithm is applied to both dependent and independent blackbody spectra with a varying number of eigenvectors. The optimal number of PCs is selected so that the total root-mean-square (RMS) error is minimized. To estimate the filter noise performance, we examine four different scenarios: apply PC filtering to both dependent and independent datasets, apply PC filtering to dependent calibration data only, apply PC filtering to independent data only, and no PC filters. The independent blackbody radiances are predicted for each case and comparisons are made. The results show significant reduction in noise in the final calibrated radiances with the implementation of the PC filtering algorithm.

Multivariate analyses of peripheral blood leukocyte transcripts distinguish Alzheimer's, Parkinson's, control, and those at risk for developing Alzheimer's.

PubMed

Delvaux, Elaine; Mastroeni, Diego; Nolz, Jennifer; Chow, Nienwen; Sabbagh, Marwan; Caselli, Richard J; Reiman, Eric M; Marshall, Frederick J; Coleman, Paul D

2017-10-01

The need for a reliable, simple, and inexpensive blood test for Alzheimer's disease (AD) suitable for use in a primary care setting is widely recognized. This has led to a large number of publications describing blood tests for AD, which have, for the most part, not been replicable. We have chosen to examine transcripts expressed by the cellular, leukocyte compartment of blood. We have used hypothesis-based cDNA arrays and quantitative PCR to quantify the expression of selected sets of genes followed by multivariate analyses in multiple independent samples. Rather than a single study with no replicates, we chose an experimental design in which there were multiple replicates using different platforms and different sample populations. We have divided 177 blood samples and 27 brain samples into multiple replicates to demonstrate the ability to distinguish early clinical AD (Clinical Dementia Rating scale 0.5), Parkinson's disease (PD), and cognitively unimpaired APOE4 homozygotes, as well as to determine persons at risk for future cognitive impairment with significant accuracy. We assess our methods in a training/test set and also show that the variables we use distinguish AD, PD, and control brain. Importantly, we describe the variability of the weights assigned to individual transcripts in multivariate analyses in repeated studies and suggest that the variability we describe may be the cause of inability to repeat many earlier studies. Our data constitute a proof of principle that multivariate analysis of the transcriptome related to cell stress and inflammation of peripheral blood leukocytes has significant potential as a minimally invasive and inexpensive diagnostic tool for diagnosis and early detection of risk for AD. Copyright © 2017 Elsevier Inc. All rights reserved.

Quantitative analysis of in vivo mucosal bacterial biofilms.

PubMed

Singhal, Deepti; Boase, Sam; Field, John; Jardeleza, Camille; Foreman, Andrew; Wormald, Peter-John

2012-01-01

Quantitative assays of mucosal biofilms on ex vivo samples are challenging using the currently applied specialized microscopic techniques to identify them. The COMSTAT2 computer program has been applied to in vitro biofilm models for quantifying biofilm structures seen on confocal scanning laser microscopy (CSLM). The aim of this study was to quantify Staphylococcus aureus (S. aureus) biofilms seen via CSLM on ex situ samples of sinonasal mucosa, using the COMSTAT2 program. S. aureus biofilms were grown in frontal sinuses of 4 merino sheep as per a previously standardized sheep sinusitis model for biofilms. Two sinonasal mucosal samples, 10 mm × 10 mm in size, from each of the 2 sinuses of the 4 sheep were analyzed for biofilm presence with Baclight stain and CSLM. Two random image stacks of mucosa with S. aureus biofilm were recorded from each sample, and analyzed using COMSTAT2 software that translates image stacks into a simplified 3-dimensional matrix of biofilm mass by eliminating surrounding host tissue. Three independent observers analyzed images using COMSTAT2 and 3 repeated rounds of analyses were done to calculate biofilm biomass. The COMSTAT2 application uses an observer-dependent threshold setting to translate CSLM biofilm images into a simplified 3-dimensional output for quantitative analysis. Intraclass correlation coefficient (ICC) between thresholds set by the 3 observers for each image stacks was 0.59 (p = 0.0003). Threshold values set at different points of time by a single observer also showed significant correlation as seen by ICC of 0.80 (p < 0.001). COMSTAT2 can be applied to quantify and study the complex 3-dimensional biofilm structures that are recorded via CSLM on mucosal tissue like the sinonasal mucosa. Copyright © 2011 American Rhinologic Society-American Academy of Otolaryngic Allergy, LLC.

Differential effects of common variants in SCN2A on general cognitive ability, brain physiology, and messenger RNA expression in schizophrenia cases and control individuals.

PubMed

Dickinson, Dwight; Straub, Richard E; Trampush, Joey W; Gao, Yuan; Feng, Ningping; Xie, Bin; Shin, Joo Heon; Lim, Hun Ki; Ursini, Gianluca; Bigos, Kristin L; Kolachana, Bhaskar; Hashimoto, Ryota; Takeda, Masatoshi; Baum, Graham L; Rujescu, Dan; Callicott, Joseph H; Hyde, Thomas M; Berman, Karen F; Kleinman, Joel E; Weinberger, Daniel R

2014-06-01

One approach to understanding the genetic complexity of schizophrenia is to study associated behavioral and biological phenotypes that may be more directly linked to genetic variation. To identify single-nucleotide polymorphisms associated with general cognitive ability (g) in people with schizophrenia and control individuals. Genomewide association study, followed by analyses in unaffected siblings and independent schizophrenia samples, functional magnetic resonance imaging studies of brain physiology in vivo, and RNA sequencing in postmortem brain samples. The discovery cohort and unaffected siblings were participants in the National Institute of Mental Health Clinical Brain Disorders Branch schizophrenia genetics studies. Additional schizophrenia cohorts were from psychiatric treatment settings in the United States, Japan, and Germany. The discovery cohort comprised 339 with schizophrenia and 363 community control participants. Follow-up analyses studied 147 unaffected siblings of the schizophrenia cases and independent schizophrenia samples including a total of an additional 668 participants. Imaging analyses included 87 schizophrenia cases and 397 control individuals. Brain tissue samples were available for 64 cases and 61 control individuals. We studied genomewide association with g, by group, in the discovery cohort. We used selected genotypes to test specific associations in unaffected siblings and independent schizophrenia samples. Imaging analyses focused on activation in the prefrontal cortex during working memory. Brain tissue studies yielded messenger RNA expression levels for RefSeq transcripts. The schizophrenia discovery cohort showed genomewide-significant association of g with polymorphisms in sodium channel gene SCN2A, accounting for 10.4% of g variance (rs10174400, P = 9.27 × 10(-10)). Control individuals showed a trend for g/genotype association with reversed allelic directionality. The genotype-by-group interaction was also genomewide significant (P = 1.75 × 10(-9)). Siblings showed a genotype association with g parallel to the schizophrenia group and the same interaction pattern. Parallel, but weaker, associations with cognition were found in independent schizophrenia samples. Imaging analyses showed a similar pattern of genotype associations by group and genotype-by-group interaction. Sequencing of RNA in brain revealed reduced expression in 2 of 3 SCN2A alternative transcripts in the patient group, with genotype-by-group interaction, that again paralleled the cognition effects. The findings implicate SCN2A and sodium channel biology in cognitive impairment in schizophrenia cases and unaffected relatives and may facilitate development of cognition-enhancing treatments.

The Brunnsviken Brief Quality of Life Scale (BBQ): Development and Psychometric Evaluation.

PubMed

Lindner, Philip; Frykheden, Ola; Forsström, David; Andersson, Erik; Ljótsson, Brjánn; Hedman, Erik; Andersson, Gerhard; Carlbring, Per

2016-04-01

Measurements of subjective quality of life (QoL) are an important complement to symptom ratings in clinical research and practice. Despite there being several established QoL self-rating scales, we identified a need for a freely accessible, easy-to-use inventory, validated for use with both clinical and non-clinical samples, based on the overall life satisfaction conceptualization of QoL. The Brunnsviken Brief Quality of life scale (BBQ) was designed to meet these requirements. Items were selected by performing a factor analysis on a large data-set of QoL ratings collected previously. Six life areas (Leisure time, View on life, Creativity, Learning, Friends and Friendship, and View of self) were identified as important for overall QoL and were included in the BBQ. A psychometric evaluation was performed using two independent samples: healthy undergraduate students (n = 163), and a sample seeking treatment for social anxiety disorder (n = 568). Results suggested a unifactorial structure, with good concurrent and convergent validity, high internal and test-retest reliability, and accurate classification ability. We conclude that the BBQ is a valid and reliable measure of subjective QoL for use in clinical and research settings. The BBQ is presently available in 31 languages and can be freely downloaded from www.bbqscale.com .

Bio-Benchmarking of Electronic Nose Sensors

PubMed Central

Berna, Amalia Z.; Anderson, Alisha R.; Trowell, Stephen C.

2009-01-01

Background Electronic noses, E-Noses, are instruments designed to reproduce the performance of animal noses or antennae but generally they cannot match the discriminating power of the biological original and have, therefore, been of limited utility. The manner in which odorant space is sampled is a critical factor in the performance of all noses but so far it has been described in detail only for the fly antenna. Methodology Here we describe how a set of metal oxide (MOx) E-Nose sensors, which is the most commonly used type, samples odorant space and compare it with what is known about fly odorant receptors (ORs). Principal Findings Compared with a fly's odorant receptors, MOx sensors from an electronic nose are on average more narrowly tuned but much more highly correlated with each other. A set of insect ORs can therefore sample broader regions of odorant space independently and redundantly than an equivalent number of MOx sensors. The comparison also highlights some important questions about the molecular nature of fly ORs. Conclusions The comparative approach generates practical learnings that may be taken up by solid-state physicists or engineers in designing new solid-state electronic nose sensors. It also potentially deepens our understanding of the performance of the biological system. PMID:19641604

Label-Free LC-MS/MS Proteomic Analysis of Cerebrospinal Fluid Identifies Protein/Pathway Alterations and Candidate Biomarkers for Amyotrophic Lateral Sclerosis.

PubMed

Collins, Mahlon A; An, Jiyan; Hood, Brian L; Conrads, Thomas P; Bowser, Robert P

2015-11-06

Analysis of the cerebrospinal fluid (CSF) proteome has proven valuable to the study of neurodegenerative disorders. To identify new protein/pathway alterations and candidate biomarkers for amyotrophic lateral sclerosis (ALS), we performed comparative proteomic profiling of CSF from sporadic ALS (sALS), healthy control (HC), and other neurological disease (OND) subjects using label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS). A total of 1712 CSF proteins were detected and relatively quantified by spectral counting. Levels of several proteins with diverse biological functions were significantly altered in sALS samples. Enrichment analysis was used to link these alterations to biological pathways, which were predominantly related to inflammation, neuronal activity, and extracellular matrix regulation. We then used our CSF proteomic profiles to create a support vector machines classifier capable of discriminating training set ALS from non-ALS (HC and OND) samples. Four classifier proteins, WD repeat-containing protein 63, amyloid-like protein 1, SPARC-like protein 1, and cell adhesion molecule 3, were identified by feature selection and externally validated. The resultant classifier distinguished ALS from non-ALS samples with 83% sensitivity and 100% specificity in an independent test set. Collectively, our results illustrate the utility of CSF proteomic profiling for identifying ALS protein/pathway alterations and candidate disease biomarkers.

Chimeric 16S rRNA sequence formation and detection in Sanger and 454-pyrosequenced PCR amplicons

PubMed Central

Haas, Brian J.; Gevers, Dirk; Earl, Ashlee M.; Feldgarden, Mike; Ward, Doyle V.; Giannoukos, Georgia; Ciulla, Dawn; Tabbaa, Diana; Highlander, Sarah K.; Sodergren, Erica; Methé, Barbara; DeSantis, Todd Z.; Petrosino, Joseph F.; Knight, Rob; Birren, Bruce W.

2011-01-01

Bacterial diversity among environmental samples is commonly assessed with PCR-amplified 16S rRNA gene (16S) sequences. Perceived diversity, however, can be influenced by sample preparation, primer selection, and formation of chimeric 16S amplification products. Chimeras are hybrid products between multiple parent sequences that can be falsely interpreted as novel organisms, thus inflating apparent diversity. We developed a new chimera detection tool called Chimera Slayer (CS). CS detects chimeras with greater sensitivity than previous methods, performs well on short sequences such as those produced by the 454 Life Sciences (Roche) Genome Sequencer, and can scale to large data sets. By benchmarking CS performance against sequences derived from a controlled DNA mixture of known organisms and a simulated chimera set, we provide insights into the factors that affect chimera formation such as sequence abundance, the extent of similarity between 16S genes, and PCR conditions. Chimeras were found to reproducibly form among independent amplifications and contributed to false perceptions of sample diversity and the false identification of novel taxa, with less-abundant species exhibiting chimera rates exceeding 70%. Shotgun metagenomic sequences of our mock community appear to be devoid of 16S chimeras, supporting a role for shotgun metagenomics in validating novel organisms discovered in targeted sequence surveys. PMID:21212162

Stability of BDNF in Human Samples Stored Up to 6 Months and Correlations of Serum and EDTA-Plasma Concentrations.

PubMed

Polyakova, Maryna; Schlögl, Haiko; Sacher, Julia; Schmidt-Kassow, Maren; Kaiser, Jochen; Stumvoll, Michael; Kratzsch, Jürgen; Schroeter, Matthias L

2017-06-03

Brain-derived neurotrophic factor (BDNF), an important neural growth factor, has gained growing interest in neuroscience, but many influencing physiological and analytical aspects still remain unclear. In this study we assessed the impact of storage time at room temperature, repeated freeze/thaw cycles, and storage at -80 °C up to 6 months on serum and ethylenediaminetetraacetic acid (EDTA)-plasma BDNF. Furthermore, we assessed correlations of serum and plasma BDNF concentrations in two independent sets of samples. Coefficients of variations (CVs) for serum BDNF concentrations were significantly lower than CVs of plasma concentrations ( n = 245, p = 0.006). Mean serum and plasma concentrations at all analyzed time points remained within the acceptable change limit of the inter-assay precision as declared by the manufacturer. Serum and plasma BDNF concentrations correlated positively in both sets of samples and at all analyzed time points of the stability assessment ( r = 0.455 to r s = 0.596; p < 0.004). In summary, when considering the acceptable change limit, BDNF was stable in serum and in EDTA-plasma up to 6 months. Due to a higher reliability, we suggest favoring serum over EDTA-plasma for future experiments assessing peripheral BDNF concentrations.

Late Pleistocene/Holocene craniofacial morphology in Mesoamerican Paleoindians: implications for the peopling of the New World.

PubMed

González-José, Rolando; Neves, Walter; Lahr, Marta Mirazón; González, Silvia; Pucciarelli, Héctor; Hernández Martínez, Miquel; Correal, Gonzalo

2005-12-01

Several studies on craniofacial morphology showed that most Paleoindians, who were the first settlers of the New World, clearly differ from modern Amerindians and East Asians, their supposed descendants and sister group, respectively. Here we present new evidence supporting this view from the Late Pleistocene/Early Holocene horizon from Mexico, as well as from the most complete set of dated Paleoindian remains. We analyzed the phenotypic resemblance of early Mexicans with other South Paleoamerican and modern human series. Two independent approaches to the data were used. In the first case, individual specimens were tested for morphological similarity with a set of modern reference samples. In the second analysis, Mexican specimens were treated as a sample in order to compute minimum genetic distances. Results from both approaches tend to associate early Mexican skulls with Paleoindians from Brazil, an Archaic sample from Colombia, and several circum-Pacific populations. These results give support to a model in which morphologically generalized groups of non-Northeast Asian descent (the so-called Paleoamericans) entered the continent first, and then dispersed from North to South America through Central America. The large geographic dispersal of Paleoamericans, and their presence in Mexico in the Early Holocene, raise new issues about the continent's settlement scenario. 2005 Wiley-Liss, Inc.

A blood-based proteomic classifier for the molecular characterization of pulmonary nodules.

PubMed

Li, Xiao-jun; Hayward, Clive; Fong, Pui-Yee; Dominguez, Michel; Hunsucker, Stephen W; Lee, Lik Wee; McLean, Matthew; Law, Scott; Butler, Heather; Schirm, Michael; Gingras, Olivier; Lamontagne, Julie; Allard, Rene; Chelsky, Daniel; Price, Nathan D; Lam, Stephen; Massion, Pierre P; Pass, Harvey; Rom, William N; Vachani, Anil; Fang, Kenneth C; Hood, Leroy; Kearney, Paul

2013-10-16

Each year, millions of pulmonary nodules are discovered by computed tomography and subsequently biopsied. Because most of these nodules are benign, many patients undergo unnecessary and costly invasive procedures. We present a 13-protein blood-based classifier that differentiates malignant and benign nodules with high confidence, thereby providing a diagnostic tool to avoid invasive biopsy on benign nodules. Using a systems biology strategy, we identified 371 protein candidates and developed a multiple reaction monitoring (MRM) assay for each. The MRM assays were applied in a three-site discovery study (n = 143) on plasma samples from patients with benign and stage IA lung cancer matched for nodule size, age, gender, and clinical site, producing a 13-protein classifier. The classifier was validated on an independent set of plasma samples (n = 104), exhibiting a negative predictive value (NPV) of 90%. Validation performance on samples from a nondiscovery clinical site showed an NPV of 94%, indicating the general effectiveness of the classifier. A pathway analysis demonstrated that the classifier proteins are likely modulated by a few transcription regulators (NF2L2, AHR, MYC, and FOS) that are associated with lung cancer, lung inflammation, and oxidative stress networks. The classifier score was independent of patient nodule size, smoking history, and age, which are risk factors used for clinical management of pulmonary nodules. Thus, this molecular test provides a potential complementary tool to help physicians in lung cancer diagnosis.

Analysis of biofluids in aqueous environment based on mid-infrared spectroscopy.

PubMed

Fabian, Heinz; Lasch, Peter; Naumann, Dieter

2005-01-01

In this study we describe a semiautomatic Fourier transform infrared spectroscopic methodology for the analysis of liquid serum samples, which combines simple sample introduction with high sample throughput. The applicability of this new infrared technology to the analysis of liquid serum samples from a cohort of cattle naturally infected with bovine spongiform encephalopathy and from controls was explored in comparison to the conventional approach based on transmission infrared spectroscopy of dried serum films. Artifical neural network analysis of the infrared data was performed to differentiate between bovine spongiform encephalopathy-negative controls and animals in the late stage of the disease. After training of artifical neural network classifiers, infrared spectra of sera from an independent external validation data set were analyzed. In this way, sensitivities between 90 and 96% and specificities between 84 and 92% were achieved, respectively, depending upon the strategy of data collection and data analysis. Based on these results, the advantages and limitations of the liquid sample technique and the dried film approach for routine analysis of biofluids are discussed. 2005 Society of Photo-Optical Instrumentation Engineers.

On evaluating compliance with air pollution levels not to be exceeded more than once per year

NASA Technical Reports Server (NTRS)

Neustadter, H. E.; Sidik, S. M.

1974-01-01

The adequacy is considered of currently practiced monitoring and data reduction techniques for assessing compliance with 24-hour Air Quality Standards (AQS) not to be exceeded more than once per year. The present situation for suspended particulates is discussed. The following conclusions are reached: (1) For typical less than daily sampling (i.e., 60 to 120 24-hour samples per year) the deviation from independence of the data set should not be substantial. (2) The interchange of exponentiation and expectation operations in the EPA data reduction model, underestimates the second highest level by about 4 to 8 percent for typical sigma values. (3) Estimates of the second highest pollution level have associated with them a large statistical variability arising from the finite size of the sample. The 0.95 confidence interval ranges from + or - 40 percent for 120 samples per year to + or - 84 percent for 30 samples per year. (4) The design value suggested by EPA for abatement and/or control planning purposes typically gives a margin of safety of 60 to 120 percent.

Validation and Application of a PCR Primer Set to Quantify Fungal Communities in the Soil Environment by Real-Time Quantitative PCR

PubMed Central

Chemidlin Prévost-Bouré, Nicolas; Christen, Richard; Dequiedt, Samuel; Mougel, Christophe; Lelièvre, Mélanie; Jolivet, Claudy; Shahbazkia, Hamid Reza; Guillou, Laure; Arrouays, Dominique; Ranjard, Lionel

2011-01-01

Fungi constitute an important group in soil biological diversity and functioning. However, characterization and knowledge of fungal communities is hampered because few primer sets are available to quantify fungal abundance by real-time quantitative PCR (real-time Q-PCR). The aim in this study was to quantify fungal abundance in soils by incorporating, into a real-time Q-PCR using the SYBRGreen® method, a primer set already used to study the genetic structure of soil fungal communities. To satisfy the real-time Q-PCR requirements to enhance the accuracy and reproducibility of the detection technique, this study focused on the 18S rRNA gene conserved regions. These regions are little affected by length polymorphism and may provide sufficiently small targets, a crucial criterion for enhancing accuracy and reproducibility of the detection technique. An in silico analysis of 33 primer sets targeting the 18S rRNA gene was performed to select the primer set with the best potential for real-time Q-PCR: short amplicon length; good fungal specificity and coverage. The best consensus between specificity, coverage and amplicon length among the 33 sets tested was the primer set FR1 / FF390. This in silico analysis of the specificity of FR1 / FF390 also provided additional information to the previously published analysis on this primer set. The specificity of the primer set FR1 / FF390 for Fungi was validated in vitro by cloning - sequencing the amplicons obtained from a real time Q-PCR assay performed on five independent soil samples. This assay was also used to evaluate the sensitivity and reproducibility of the method. Finally, fungal abundance in samples from 24 soils with contrasting physico-chemical and environmental characteristics was examined and ranked to determine the importance of soil texture, organic carbon content, C∶N ratio and land use in determining fungal abundance in soils. PMID:21931659

Ensemble coding of face identity is present but weaker in congenital prosopagnosia.

PubMed

Robson, Matthew K; Palermo, Romina; Jeffery, Linda; Neumann, Markus F

2018-03-01

Individuals with congenital prosopagnosia (CP) are impaired at identifying individual faces but do not appear to show impairments in extracting the average identity from a group of faces (known as ensemble coding). However, possible deficits in ensemble coding in a previous study (CPs n = 4) may have been masked because CPs relied on pictorial (image) cues rather than identity cues. Here we asked whether a larger sample of CPs (n = 11) would show intact ensemble coding of identity when availability of image cues was minimised. Participants viewed a "set" of four faces and then judged whether a subsequent individual test face, either an exemplar or a "set average", was in the preceding set. Ensemble coding occurred when matching (vs. mismatching) averages were mistakenly endorsed as set members. We assessed both image- and identity-based ensemble coding, by varying whether test faces were either the same or different images of the identities in the set. CPs showed significant ensemble coding in both tasks, indicating that their performance was independent of image cues. As a group, CPs' ensemble coding was weaker than controls in both tasks, consistent with evidence that perceptual processing of face identity is disrupted in CP. This effect was driven by CPs (n= 3) who, in addition to having impaired face memory, also performed particularly poorly on a measure of face perception (CFPT). Future research, using larger samples, should examine whether deficits in ensemble coding may be restricted to CPs who also have substantial face perception deficits. Copyright © 2018 Elsevier Ltd. All rights reserved.

Effect of Sling Exercise Training on Balance in Patients with Stroke: A Meta-Analysis

PubMed Central

Peng, Qiyuan; Chen, Jingjie; Zou, Yucong; Liu, Gang

2016-01-01

Objective This study aims to evaluate the effect of sling exercise training (SET) on balance in patients with stroke. Methods PubMed, Cochrane Library, Ovid LWW, CBM, CNKI, WanFang, and VIP databases were searched for randomized controlled trials of the effect of SET on balance in patients with stroke. The study design and participants were subjected to metrological analysis. Berg balance Scale (BBS), Barthel index score (BI), and Fugl-Meyer Assessment (FMA) were used as independent parameters for evaluating balance function, activities of daily living(ADL) and motor function after stroke respectively, and were subjected to meta-analysis by RevMan5.3 software. Results Nine studies with 460 participants were analyzed. Results of meta-analysis showed that the SET treatment combined with conventional rehabilitation was superior to conventional rehabilitation treatments, with increased degrees of BBS (WMD = 3.81, 95% CI [0.15, 7.48], P = 0.04), BI (WMD = 12.98, 95% CI [8.39, 17.56], P < 0.00001), and FMA (SMD = 0.76, 95% CI [0.41, 1.11], P < 0.0001). Conclusion Based on limited evidence from 9 trials, the SET treatment combined with conventional rehabilitation was superior to conventional rehabilitation treatments, with increased degrees of BBS, BI and FMA, So the SET treatment can improvement of balance function after stroke, but the interpretation of our findings is required to be made with caution due to limitations in included trials such as small sample sizes and the risk of bias. Therefore, more multi-center and large-sampled randomized controlled trials are needed to confirm its clinical applications. PMID:27727288

Differential expression patterns of housekeeping genes increase diagnostic and prognostic value in lung cancer

PubMed Central

Chang, Yu-Chun; Ding, Yan; Dong, Lingsheng; Zhu, Lang-Jing; Jensen, Roderick V.

2018-01-01

Background Using DNA microarrays, we previously identified 451 genes expressed in 19 different human tissues. Although ubiquitously expressed, the variable expression patterns of these “housekeeping genes” (HKGs) could separate one normal human tissue type from another. Current focus on identifying “specific disease markers” is problematic as single gene expression in a given sample represents the specific cellular states of the sample at the time of collection. In this study, we examine the diagnostic and prognostic potential of the variable expressions of HKGs in lung cancers. Methods Microarray and RNA-seq data for normal lungs, lung adenocarcinomas (AD), squamous cell carcinomas of the lung (SQCLC), and small cell carcinomas of the lung (SCLC) were collected from online databases. Using 374 of 451 HKGs, differentially expressed genes between pairs of sample types were determined via two-sided, homoscedastic t-test. Principal component analysis and hierarchical clustering classified normal lung and lung cancers subtypes according to relative gene expression variations. We used uni- and multi-variate cox-regressions to identify significant predictors of overall survival in AD patients. Classifying genes were selected using a set of training samples and then validated using an independent test set. Gene Ontology was examined by PANTHER. Results This study showed that the differential expression patterns of 242, 245, and 99 HKGs were able to distinguish normal lung from AD, SCLC, and SQCLC, respectively. From these, 70 HKGs were common across the three lung cancer subtypes. These HKGs have low expression variation compared to current lung cancer markers (e.g., EGFR, KRAS) and were involved in the most common biological processes (e.g., metabolism, stress response). In addition, the expression pattern of 106 HKGs alone was a significant classifier of AD versus SQCLC. We further highlighted that a panel of 13 HKGs was an independent predictor of overall survival and cumulative risk in AD patients. Discussion Here we report HKG expression patterns may be an effective tool for evaluation of lung cancer states. For example, the differential expression pattern of 70 HKGs alone can separate normal lung tissue from various lung cancers while a panel of 106 HKGs was a capable class predictor of subtypes of non-small cell carcinomas. We also reported that HKGs have significantly lower variance compared to traditional cancer markers across samples, highlighting the robustness of a panel of genes over any one specific biomarker. Using RNA-seq data, we showed that the expression pattern of 13 HKGs is a significant, independent predictor of overall survival for AD patients. This reinforces the predictive power of a HKG panel across different gene expression measurement platforms. Thus, we propose the expression patterns of HKGs alone may be sufficient for the diagnosis and prognosis of individuals with lung cancer. PMID:29761043

STBase: one million species trees for comparative biology.

PubMed

McMahon, Michelle M; Deepak, Akshay; Fernández-Baca, David; Boss, Darren; Sanderson, Michael J

2015-01-01

Comprehensively sampled phylogenetic trees provide the most compelling foundations for strong inferences in comparative evolutionary biology. Mismatches are common, however, between the taxa for which comparative data are available and the taxa sampled by published phylogenetic analyses. Moreover, many published phylogenies are gene trees, which cannot always be adapted immediately for species level comparisons because of discordance, gene duplication, and other confounding biological processes. A new database, STBase, lets comparative biologists quickly retrieve species level phylogenetic hypotheses in response to a query list of species names. The database consists of 1 million single- and multi-locus data sets, each with a confidence set of 1000 putative species trees, computed from GenBank sequence data for 413,000 eukaryotic taxa. Two bodies of theoretical work are leveraged to aid in the assembly of multi-locus concatenated data sets for species tree construction. First, multiply labeled gene trees are pruned to conflict-free singly-labeled species-level trees that can be combined between loci. Second, impacts of missing data in multi-locus data sets are ameliorated by assembling only decisive data sets. Data sets overlapping with the user's query are ranked using a scheme that depends on user-provided weights for tree quality and for taxonomic overlap of the tree with the query. Retrieval times are independent of the size of the database, typically a few seconds. Tree quality is assessed by a real-time evaluation of bootstrap support on just the overlapping subtree. Associated sequence alignments, tree files and metadata can be downloaded for subsequent analysis. STBase provides a tool for comparative biologists interested in exploiting the most relevant sequence data available for the taxa of interest. It may also serve as a prototype for future species tree oriented databases and as a resource for assembly of larger species phylogenies from precomputed trees.

A MAD-Bayes Algorithm for State-Space Inference and Clustering with Application to Querying Large Collections of ChIP-Seq Data Sets.

PubMed

Zuo, Chandler; Chen, Kailei; Keleş, Sündüz

2017-06-01

Current analytic approaches for querying large collections of chromatin immunoprecipitation followed by sequencing (ChIP-seq) data from multiple cell types rely on individual analysis of each data set (i.e., peak calling) independently. This approach discards the fact that functional elements are frequently shared among related cell types and leads to overestimation of the extent of divergence between different ChIP-seq samples. Methods geared toward multisample investigations have limited applicability in settings that aim to integrate 100s to 1000s of ChIP-seq data sets for query loci (e.g., thousands of genomic loci with a specific binding site). Recently, Zuo et al. developed a hierarchical framework for state-space matrix inference and clustering, named MBASIC, to enable joint analysis of user-specified loci across multiple ChIP-seq data sets. Although this versatile framework estimates both the underlying state-space (e.g., bound vs. unbound) and also groups loci with similar patterns together, its Expectation-Maximization-based estimation structure hinders its applicability with large number of loci and samples. We address this limitation by developing MAP-based asymptotic derivations from Bayes (MAD-Bayes) framework for MBASIC. This results in a K-means-like optimization algorithm that converges rapidly and hence enables exploring multiple initialization schemes and flexibility in tuning. Comparison with MBASIC indicates that this speed comes at a relatively insignificant loss in estimation accuracy. Although MAD-Bayes MBASIC is specifically designed for the analysis of user-specified loci, it is able to capture overall patterns of histone marks from multiple ChIP-seq data sets similar to those identified by genome-wide segmentation methods such as ChromHMM and Spectacle.

Short-term effects of goal-setting focusing on the life goal concept on subjective well-being and treatment engagement in subacute inpatients: a quasi-randomized controlled trial

PubMed Central

Ogawa, Tatsuya; Omon, Kyohei; Yuda, Tomohisa; Ishigaki, Tomoya; Imai, Ryota; Ohmatsu, Satoko; Morioka, Shu

2016-01-01

Objective: To investigate the short-term effects of the life goal concept on subjective well-being and treatment engagement, and to determine the sample size required for a larger trial. Design: A quasi-randomized controlled trial that was not blinded. Setting: A subacute rehabilitation ward. Subjects: A total of 66 patients were randomized to a goal-setting intervention group with the life goal concept (Life Goal), a standard rehabilitation group with no goal-setting intervention (Control 1), or a goal-setting intervention group without the life goal concept (Control 2). Interventions: The goal-setting intervention in the Life Goal and Control 2 was Goal Attainment Scaling. The Life Goal patients were assessed in terms of their life goals, and the hierarchy of goals was explained. The intervention duration was four weeks. Main measures: Patients were assessed pre- and post-intervention. The outcome measures were the Hospital Anxiety and Depression Scale, 12-item General Health Questionnaire, Pittsburgh Rehabilitation Participation Scale, and Functional Independence Measure. Results: Of the 296 potential participants, 66 were enrolled; Life Goal (n = 22), Control 1 (n = 22) and Control 2 (n = 22). Anxiety was significantly lower in the Life Goal (4.1 ±3.0) than in Control 1 (6.7 ±3.4), but treatment engagement was significantly higher in the Life Goal (5.3 ±0.4) compared with both the Control 1 (4.8 ±0.6) and Control 2 (4.9 ±0.5). Conclusions: The life goal concept had a short-term effect on treatment engagement. A sample of 31 patients per group would be required for a fully powered clinical trial. PMID:27496700

Establishment of performance standards and a cut-score for the Canadian Forces firefighter physical fitness maintenance evaluation (FF PFME).

PubMed

Todd Rogers, W; Docherty, David; Petersen, Stewart

2014-01-01

The bookmark method for setting cut-scores was used to re-set the cut-score for the Canadian Forces Firefighter Physical Fitness Maintenance Evaluation (FF PFME). The time required to complete 10 tasks that together simulate a first-response firefighting emergency was accepted as a measure of work capacity. A panel of 25 Canadian Forces firefighter supervisors set cut-scores in three rounds. Each round involved independent evaluation of nine video work samples, where the times systematically increased from 400 seconds to 560 seconds. Results for Round 1 were discussed before moving to Round 2 and results for Round 2 were discussed before moving to Round 3. Accounting for the variability among panel members at the end of Round 3, a cut-score of 481 seconds (mean Round 3 plus 2 SEM) was recommended. Firefighters who complete the FF PFME in 481 seconds or less have the physical capacity to complete first-response firefighting work.

Systematic computation with functional gene-sets among leukemic and hematopoietic stem cells reveals a favorable prognostic signature for acute myeloid leukemia.

PubMed

Yang, Xinan Holly; Li, Meiyi; Wang, Bin; Zhu, Wanqi; Desgardin, Aurelie; Onel, Kenan; de Jong, Jill; Chen, Jianjun; Chen, Luonan; Cunningham, John M

2015-03-24

Genes that regulate stem cell function are suspected to exert adverse effects on prognosis in malignancy. However, diverse cancer stem cell signatures are difficult for physicians to interpret and apply clinically. To connect the transcriptome and stem cell biology, with potential clinical applications, we propose a novel computational "gene-to-function, snapshot-to-dynamics, and biology-to-clinic" framework to uncover core functional gene-sets signatures. This framework incorporates three function-centric gene-set analysis strategies: a meta-analysis of both microarray and RNA-seq data, novel dynamic network mechanism (DNM) identification, and a personalized prognostic indicator analysis. This work uses complex disease acute myeloid leukemia (AML) as a research platform. We introduced an adjustable "soft threshold" to a functional gene-set algorithm and found that two different analysis methods identified distinct gene-set signatures from the same samples. We identified a 30-gene cluster that characterizes leukemic stem cell (LSC)-depleted cells and a 25-gene cluster that characterizes LSC-enriched cells in parallel; both mark favorable-prognosis in AML. Genes within each signature significantly share common biological processes and/or molecular functions (empirical p = 6e-5 and 0.03 respectively). The 25-gene signature reflects the abnormal development of stem cells in AML, such as AURKA over-expression. We subsequently determined that the clinical relevance of both signatures is independent of known clinical risk classifications in 214 patients with cytogenetically normal AML. We successfully validated the prognosis of both signatures in two independent cohorts of 91 and 242 patients respectively (log-rank p < 0.0015 and 0.05; empirical p < 0.015 and 0.08). The proposed algorithms and computational framework will harness systems biology research because they efficiently translate gene-sets (rather than single genes) into biological discoveries about AML and other complex diseases.

Point Analysis in Java applied to histological images of the perforant pathway: a user's account.

PubMed

Scorcioni, Ruggero; Wright, Susan N; Patrick Card, J; Ascoli, Giorgio A; Barrionuevo, Germán

2008-01-01

The freeware Java tool Point Analysis in Java (PAJ), created to perform 3D point analysis, was tested in an independent laboratory setting. The input data consisted of images of the hippocampal perforant pathway from serial immunocytochemical localizations of the rat brain in multiple views at different resolutions. The low magnification set (x2 objective) comprised the entire perforant pathway, while the high magnification set (x100 objective) allowed the identification of individual fibers. A preliminary stereological study revealed a striking linear relationship between the fiber count at high magnification and the optical density at low magnification. PAJ enabled fast analysis for down-sampled data sets and a friendly interface with automated plot drawings. Noted strengths included the multi-platform support as well as the free availability of the source code, conducive to a broad user base and maximum flexibility for ad hoc requirements. PAJ has great potential to extend its usability by (a) improving its graphical user interface, (b) increasing its input size limit, (c) improving response time for large data sets, and (d) potentially being integrated with other Java graphical tools such as ImageJ.

Optimized velocity distributions for direct dark matter detection

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

Ibarra, Alejandro; Rappelt, Andreas, E-mail: ibarra@tum.de, E-mail: andreas.rappelt@tum.de

We present a method to calculate, without making assumptions about the local dark matter velocity distribution, the maximal and minimal number of signal events in a direct detection experiment given a set of constraints from other direct detection experiments and/or neutrino telescopes. The method also allows to determine the velocity distribution that optimizes the signal rates. We illustrate our method with three concrete applications: i) to derive a halo-independent upper limit on the cross section from a set of null results, ii) to confront in a halo-independent way a detection claim to a set of null results and iii) tomore » assess, in a halo-independent manner, the prospects for detection in a future experiment given a set of current null results.« less

Independent components analysis to increase efficiency of discriminant analysis methods (FDA and LDA): Application to NMR fingerprinting of wine.

PubMed

Monakhova, Yulia B; Godelmann, Rolf; Kuballa, Thomas; Mushtakova, Svetlana P; Rutledge, Douglas N

2015-08-15

Discriminant analysis (DA) methods, such as linear discriminant analysis (LDA) or factorial discriminant analysis (FDA), are well-known chemometric approaches for solving classification problems in chemistry. In most applications, principle components analysis (PCA) is used as the first step to generate orthogonal eigenvectors and the corresponding sample scores are utilized to generate discriminant features for the discrimination. Independent components analysis (ICA) based on the minimization of mutual information can be used as an alternative to PCA as a preprocessing tool for LDA and FDA classification. To illustrate the performance of this ICA/DA methodology, four representative nuclear magnetic resonance (NMR) data sets of wine samples were used. The classification was performed regarding grape variety, year of vintage and geographical origin. The average increase for ICA/DA in comparison with PCA/DA in the percentage of correct classification varied between 6±1% and 8±2%. The maximum increase in classification efficiency of 11±2% was observed for discrimination of the year of vintage (ICA/FDA) and geographical origin (ICA/LDA). The procedure to determine the number of extracted features (PCs, ICs) for the optimum DA models was discussed. The use of independent components (ICs) instead of principle components (PCs) resulted in improved classification performance of DA methods. The ICA/LDA method is preferable to ICA/FDA for recognition tasks based on NMR spectroscopic measurements. Copyright © 2015 Elsevier B.V. All rights reserved.

New Teff and [Fe/H] spectroscopic calibration for FGK dwarfs and GK giants

NASA Astrophysics Data System (ADS)

Teixeira, G. D. C.; Sousa, S. G.; Tsantaki, M.; Monteiro, M. J. P. F. G.; Santos, N. C.; Israelian, G.

2016-10-01

Context. The ever-growing number of large spectroscopic survey programs has increased the importance of fast and reliable methods with which to determine precise stellar parameters. Some of these methods are highly dependent on correct spectroscopic calibrations. Aims: The goal of this work is to obtain a new spectroscopic calibration for a fast estimate of Teff and [Fe/H] for a wide range of stellar spectral types. Methods: We used spectra from a joint sample of 708 stars, compiled from 451 FGK dwarfs and 257 GK-giant stars. We used homogeneously determined spectroscopic stellar parameters to derive temperature calibrations using a set of selected EW line-ratios, and [Fe/H] calibrations using a set of selected Fe I lines. Results: We have derived 322 EW line-ratios and 100 Fe I lines that can be used to compute Teff and [Fe/H], respectively. We show that these calibrations are effective for FGK dwarfs and GK-giant stars in the following ranges: 4500 K

Measuring the effect of inter-study variability on estimating prediction error.

PubMed

Ma, Shuyi; Sung, Jaeyun; Magis, Andrew T; Wang, Yuliang; Geman, Donald; Price, Nathan D

2014-01-01

The biomarker discovery field is replete with molecular signatures that have not translated into the clinic despite ostensibly promising performance in predicting disease phenotypes. One widely cited reason is lack of classification consistency, largely due to failure to maintain performance from study to study. This failure is widely attributed to variability in data collected for the same phenotype among disparate studies, due to technical factors unrelated to phenotypes (e.g., laboratory settings resulting in "batch-effects") and non-phenotype-associated biological variation in the underlying populations. These sources of variability persist in new data collection technologies. Here we quantify the impact of these combined "study-effects" on a disease signature's predictive performance by comparing two types of validation methods: ordinary randomized cross-validation (RCV), which extracts random subsets of samples for testing, and inter-study validation (ISV), which excludes an entire study for testing. Whereas RCV hardwires an assumption of training and testing on identically distributed data, this key property is lost in ISV, yielding systematic decreases in performance estimates relative to RCV. Measuring the RCV-ISV difference as a function of number of studies quantifies influence of study-effects on performance. As a case study, we gathered publicly available gene expression data from 1,470 microarray samples of 6 lung phenotypes from 26 independent experimental studies and 769 RNA-seq samples of 2 lung phenotypes from 4 independent studies. We find that the RCV-ISV performance discrepancy is greater in phenotypes with few studies, and that the ISV performance converges toward RCV performance as data from additional studies are incorporated into classification. We show that by examining how fast ISV performance approaches RCV as the number of studies is increased, one can estimate when "sufficient" diversity has been achieved for learning a molecular signature likely to translate without significant loss of accuracy to new clinical settings.

Dream-Enacting Behaviors in a Normal Population

PubMed Central

Nielsen, Tore; Svob, Connie; Kuiken, Don

2009-01-01

Study Objectives: Determine the prevalence and gender distributions of behaviors enacted during dreaming (“dream-enacting [DE] behaviors”) in a normal population; the independence of such behaviors from other parasomnias; and the influence of different question wordings, socially desirable responding and personality on prevalence. Design: 3-group questionnaire study Setting: University classrooms Participants: Three undergraduate samples (Ns = 443, 201, 496; mean ages = 19.9 ± 3.2 y; 20.1 ± 3.4 y; 19.1 ± 1.6 y) Interventions: N/A Measurements and Results: Subjects completed questionnaires about DE behaviors and Social Desirability. Study 1 employed a nonspecific question about the behaviors, Study 2 employed the same question with examples, and Study 3 employed 7 questions describing specific behavior subtypes (speaking, crying, smiling/laughing, fear, anger, movement, sexual arousal). Somnambulism, somniloquy, nightmares, dream recall, alexithymia, and absorption were also assessed. Factor analyses were conducted to determine relationships among DE behaviors and their independence from other parasomnias. Prevalence increased with increasing question specificity (35.9%, 76.7%, and 98.2% for the 3 samples). No gender difference obtained for the nonspecific question, but robust differences occurred for more specific questions. Females reported more speaking, crying, fear and smiling/laughing than did males; males reported more sexual arousal. When controlling other parasomnias and dream recall frequency, these differences persisted. Factor solutions revealed that DE behaviors were independent of other parasomnias and of dream recall frequency, except for an association between dream-talking and somniloquy. Sexual arousal was related only to age. Behaviors were independent of alexithymia but moderately related to absorption. Conclusions: Dream-enacting behaviors are prevalent in healthy subjects and sensitive to question wording but not social desirability. Subtypes are related, differ with gender and occur independently of other parasomnias. Citation: Nielsen T; Svob C; Kuiken D. Dream-enacting behaviors in a normal population. SLEEP 2009;32(12):1629-1636. PMID:20041599

Malthus in the Bedroom: Birth Spacing as Birth Control in Pre-Transition England.

PubMed

Cinnirella, Francesco; Klemp, Marc; Weisdorf, Jacob

2017-04-01

We use duration models on a well-known historical data set of more than 15,000 families and 60,000 births in England for the period 1540-1850 to show that the sampled families adjusted the timing of their births in accordance with the economic conditions as well as their stock of dependent children. The effects were larger among the lower socioeconomic ranks. Our findings on the existence of parity-dependent as well as parity-independent birth spacing in England are consistent with the growing evidence that marital birth control was present in pre-transitional populations.

A practical approach for writer-dependent symbol recognition using a writer-independent symbol recognizer.

PubMed

LaViola, Joseph J; Zeleznik, Robert C

2007-11-01

We present a practical technique for using a writer-independent recognition engine to improve the accuracy and speed while reducing the training requirements of a writer-dependent symbol recognizer. Our writer-dependent recognizer uses a set of binary classifiers based on the AdaBoost learning algorithm, one for each possible pairwise symbol comparison. Each classifier consists of a set of weak learners, one of which is based on a writer-independent handwriting recognizer. During online recognition, we also use the n-best list of the writer-independent recognizer to prune the set of possible symbols and thus reduce the number of required binary classifications. In this paper, we describe the geometric and statistical features used in our recognizer and our all-pairs classification algorithm. We also present the results of experiments that quantify the effect incorporating a writer-independent recognition engine into a writer-dependent recognizer has on accuracy, speed, and user training time.

Why a simulation system doesn`t match the plant

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

Sowell, R.

1998-03-01

Process simulations, or mathematical models, are widely used by plant engineers and planners to obtain a better understanding of a particular process. These simulations are used to answer questions such as how can feed rate be increased, how can yields be improved, how can energy consumption be decreased, or how should the available independent variables be set to maximize profit? Although current process simulations are greatly improved over those of the `70s and `80s, there are many reasons why a process simulation doesn`t match the plant. Understanding these reasons can assist in using simulations to maximum advantage. The reasons simulationsmore » do not match the plant may be placed in three main categories: simulation effects or inherent error, sampling and analysis effects of measurement error, and misapplication effects or set-up error.« less

User's manual for two dimensional FDTD version TEA and TMA codes for scattering from frequency-independent dielectic materials

NASA Technical Reports Server (NTRS)

Beggs, John H.; Luebbers, Raymond J.; Kunz, Karl S.

1991-01-01

The Penn State Finite Difference Time Domain Electromagnetic Scattering Code Versions TEA and TMA are two dimensional numerical electromagnetic scattering codes based upon the Finite Difference Time Domain Technique (FDTD) first proposed by Yee in 1966. The supplied version of the codes are two versions of our current two dimensional FDTD code set. This manual provides a description of the codes and corresponding results for the default scattering problem. The manual is organized into eleven sections: introduction, Version TEA and TMA code capabilities, a brief description of the default scattering geometry, a brief description of each subroutine, a description of the include files (TEACOM.FOR TMACOM.FOR), a section briefly discussing scattering width computations, a section discussing the scattering results, a sample problem set section, a new problem checklist, references and figure titles.

The Feasibility of Utilizing a Comic for Education in the Emergency Department Setting.

PubMed

Hanson, Aaron; Drendel, Amy L; Ashwal, Gary; Thomas, Alex

2017-05-01

The objective of this study was to determine the feasibility of a comic education module in the Emergency Department setting. A convenience sample of 50 injured children and their caregivers were enrolled. The comic was found to be likeable, easy to read, and provided important information to both children and their caregivers. Total time to read the comic was three minutes (SD 1.4, range 1.4-7.1). Most children (60%) read the comic independently, including all children over age 14 years. At 72-hour phone follow-up, 86% of caregivers had accurate recall of all three comic teaching points. This innovative comic educational module is feasible for use for children ages 4-18 years in the Emergency Department. Though this comic was intended to educate children, caregivers recalled all three teaching points 72 hours after discharge.

Electromagnetic beam diffraction by a finite lamellar structure: an aperiodic coupled-wave method.

PubMed

Guizal, Brahim; Barchiesi, Dominique; Felbacq, Didier

2003-12-01

We have developed a new formulation of the coupled-wave method (CWM) to handle aperiodic lamellar structures, and it will be referred to as the aperiodic coupled-wave method (ACWM). The space is still divided into three regions, but the fields are written by use of their Fourier integrals instead of the Fourier series. In the modulated region the relative permittivity is represented by its Fourier transform, and then a set of integro-differential equations is derived. Discretizing the last system leads to a set of ordinary differential equations that is reduced to an eigenvalue problem, as is usually done in the CWM. To assess the method, we compare our results with three independent formalisms: the Rayleigh perturbation method for small samples, the volume integral method, and the finite-element method.

Fine mapping on chromosome 13q32-34 and brain expression analysis implicates MYO16 in schizophrenia.

PubMed

Rodriguez-Murillo, Laura; Xu, Bin; Roos, J Louw; Abecasis, Gonçalo R; Gogos, Joseph A; Karayiorgou, Maria

2014-03-01

We previously reported linkage of schizophrenia and schizoaffective disorder to 13q32-34 in the European descent Afrikaner population from South Africa. The nature of genetic variation underlying linkage peaks in psychiatric disorders remains largely unknown and both rare and common variants may be contributing. Here, we examine the contribution of common variants located under the 13q32-34 linkage region. We used densely spaced SNPs to fine map the linkage peak region using both a discovery sample of 415 families and a meta-analysis incorporating two additional replication family samples. In a second phase of the study, we use one family-based data set with 237 families and independent case-control data sets for fine mapping of the common variant association signal using HapMap SNPs. We report a significant association with a genetic variant (rs9583277) within the gene encoding for the myosin heavy-chain Myr 8 (MYO16), which has been implicated in neuronal phosphoinositide 3-kinase signaling. Follow-up analysis of HapMap variation within MYO16 in a second set of Afrikaner families and additional case-control data sets of European descent highlighted a region across introns 2-6 as the most likely region to harbor common MYO16 risk variants. Expression analysis revealed a significant increase in the level of MYO16 expression in the brains of schizophrenia patients. Our results suggest that common variation within MYO16 may contribute to the genetic liability to schizophrenia.

A goal attainment pain management program for older adults with arthritis.

PubMed

Davis, Gail C; White, Terri L

2008-12-01

The purpose of this study was to test a pain management intervention that integrates goal setting with older adults (age > or =65) living independently in residential settings. This preliminary testing of the Goal Attainment Pain Management Program (GAPMAP) included a sample of 17 adults (mean age 79.29 years) with self-reported pain related to arthritis. Specific study aims were to: 1) explore the use of individual goal setting; 2) determine participants' levels of goal attainment; 3) determine whether changes occurred in the pain management methods used and found to be helpful by GAPMAP participants; and 4) determine whether changes occurred in selected pain-related variables (i.e., experience of living with persistent pain, the expected outcomes of pain management, pain management barriers, and global ratings of perceived pain intensity and success of pain management). Because of the small sample size, both parametric (t test) and nonparametric (Wilcoxon signed rank test) analyses were used to examine differences from pretest to posttest. Results showed that older individuals could successfully participate in setting and attaining individual goals. Thirteen of the 17 participants (76%) met their goals at the expected level or above. Two management methods (exercise and using a heated pool, tub, or shower) were used significantly more often after the intervention, and two methods (exercise and distraction) were identified as significantly more helpful. Two pain-related variables (experience of living with persistent pain and expected outcomes of pain management) revealed significant change, and all of those tested showed overall improvement.

Reliability analysis of a sensitive and independent stabilometry parameter set

PubMed Central

Nagymáté, Gergely; Orlovits, Zsanett

2018-01-01

Recent studies have suggested reduced independent and sensitive parameter sets for stabilometry measurements based on correlation and variance analyses. However, the reliability of these recommended parameter sets has not been studied in the literature or not in every stance type used in stabilometry assessments, for example, single leg stances. The goal of this study is to evaluate the test-retest reliability of different time-based and frequency-based parameters that are calculated from the center of pressure (CoP) during bipedal and single leg stance for 30- and 60-second measurement intervals. Thirty healthy subjects performed repeated standing trials in a bipedal stance with eyes open and eyes closed conditions and in a single leg stance with eyes open for 60 seconds. A force distribution measuring plate was used to record the CoP. The reliability of the CoP parameters was characterized by using the intraclass correlation coefficient (ICC), standard error of measurement (SEM), minimal detectable change (MDC), coefficient of variation (CV) and CV compliance rate (CVCR). Based on the ICC, SEM and MDC results, many parameters yielded fair to good reliability values, while the CoP path length yielded the highest reliability (smallest ICC > 0.67 (0.54–0.79), largest SEM% = 19.2%). Usually, frequency type parameters and extreme value parameters yielded poor reliability values. There were differences in the reliability of the maximum CoP velocity (better with 30 seconds) and mean power frequency (better with 60 seconds) parameters between the different sampling intervals. PMID:29664938

Reliability analysis of a sensitive and independent stabilometry parameter set.

PubMed

Nagymáté, Gergely; Orlovits, Zsanett; Kiss, Rita M

2018-01-01

Recent studies have suggested reduced independent and sensitive parameter sets for stabilometry measurements based on correlation and variance analyses. However, the reliability of these recommended parameter sets has not been studied in the literature or not in every stance type used in stabilometry assessments, for example, single leg stances. The goal of this study is to evaluate the test-retest reliability of different time-based and frequency-based parameters that are calculated from the center of pressure (CoP) during bipedal and single leg stance for 30- and 60-second measurement intervals. Thirty healthy subjects performed repeated standing trials in a bipedal stance with eyes open and eyes closed conditions and in a single leg stance with eyes open for 60 seconds. A force distribution measuring plate was used to record the CoP. The reliability of the CoP parameters was characterized by using the intraclass correlation coefficient (ICC), standard error of measurement (SEM), minimal detectable change (MDC), coefficient of variation (CV) and CV compliance rate (CVCR). Based on the ICC, SEM and MDC results, many parameters yielded fair to good reliability values, while the CoP path length yielded the highest reliability (smallest ICC > 0.67 (0.54-0.79), largest SEM% = 19.2%). Usually, frequency type parameters and extreme value parameters yielded poor reliability values. There were differences in the reliability of the maximum CoP velocity (better with 30 seconds) and mean power frequency (better with 60 seconds) parameters between the different sampling intervals.

Fixed-Precision Sequential Sampling Plans for Estimating Alfalfa Caterpillar, Colias lesbia, Egg Density in Alfalfa, Medicago sativa, Fields in Córdoba, Argentina

PubMed Central

Serra, Gerardo V.; Porta, Norma C. La; Avalos, Susana; Mazzuferi, Vilma

2013-01-01

The alfalfa caterpillar, Colias lesbia (Fabricius) (Lepidoptera: Pieridae), is a major pest of alfalfa, Medicago sativa L. (Fabales: Fabaceae), crops in Argentina. Its management is based mainly on chemical control of larvae whenever the larvae exceed the action threshold. To develop and validate fixed-precision sequential sampling plans, an intensive sampling programme for C. lesbia eggs was carried out in two alfalfa plots located in the Province of Córdoba, Argentina, from 1999 to 2002. Using Resampling for Validation of Sampling Plans software, 12 additional independent data sets were used to validate the sequential sampling plan with precision levels of 0.10 and 0.25 (SE/mean), respectively. For a range of mean densities of 0.10 to 8.35 eggs/sample, an average sample size of only 27 and 26 sample units was required to achieve a desired precision level of 0.25 for the sampling plans of Green and Kuno, respectively. As the precision level was increased to 0.10, average sample size increased to 161 and 157 sample units for the sampling plans of Green and Kuno, respectively. We recommend using Green's sequential sampling plan because it is less sensitive to changes in egg density. These sampling plans are a valuable tool for researchers to study population dynamics and to evaluate integrated pest management strategies. PMID:23909840

Environmental Influences on Independent Collaborative Play

ERIC Educational Resources Information Center

Mawson, Brent

2010-01-01

Data from two qualitative research projects indicated a relationship between the type of early childhood setting and children's independent collaborative play. The first research project involved 22 three and four-year-old children in a daylong setting and 47 children four-year-old children in a sessional kindergarten. The second project involved…

Attitudes of Florida pharmacists toward implementing a state prescription drug monitoring program for controlled substances.

PubMed

Fass, Jennifer A; Hardigan, Patrick C

2011-01-01

As of May 23, 2011, 35 states had an operational prescription drug monitoring program (PDMP), and 13 additional states, including Florida in 2009, had passed legislation to implement a PDMP. PDMPs, electronic databases that collect and track designated data on controlled substances and other commonly abused medications, are intended to serve as a tool for health care practitioners when prescribing and dispensing controlled substances to reduce drug abuse and diversion. In an analysis of 1,268 drug-caused deaths from January through June 2010 in Florida, the top 3 prescription drugs included the controlled substances oxycodone (56%), alprazolam (35%), and methadone (26%), all of which would be subject to reporting in Florida's PDMP when implemented. Because pharmacists are the health care professionals most affected by PDMP reporting requirements, evaluating their attitudes about PDMP implementation is important. To assess Florida pharmacists' attitudes toward implementing a PDMP in the state. This was a cross-sectional study conducted in Florida between February 2010 and June 2010 prior to the implementation of the proposed PDMP. A random sample of 5,000 of approximately 26,000 pharmacists licensed in Florida was invited to participate in a voluntary and anonymous 10-question self-administered mail survey of which 4 survey items assessed pharmacists' attitudes towards implementing a PDMP in the state. Of the 5,000 pharmacists contacted by mail, 911 (18.2%) completed the survey, of whom 836 responded to the items assessing opinions about PDMPs and provided practice site information. A majority of pharmacists across all practice settings agreed or strongly agreed with the statements that a PDMP "should be implemented in Florida" (chain 84.0%, hospital 74.2%, independent 77.9%, and other 71.1%) and that a PDMP would decrease "the incidence of doctor shopping" if implemented (chain 80.8%, hospital 67.2%, independent 71.7%, and other 63.3%). A majority of pharmacists across all practice settings disagreed or strongly disagreed with the statements that they would be "discouraged to dispense controlled substances" by the PDMP (chain 61.4%, hospital 50.0%, independent 60.2%, and other 63.8%) and that PDMP implementation would be "an invasion of patients' privacy" (chain 80.3%, hospital 67.7%, independent 67.3%, and other 69.3%). In a small-sample survey, a majority of Florida pharmacists across all practice settings were in favor of implementing a PDMP in Florida. This is the first study to examine Florida pharmacists' attitudes toward PDMP implementation, and the results should prompt future analyses of relevant outcomes, such as drug abuse, drug-related mortality, and doctor shopping.

Legal Protections in Public Accommodations Settings: A Critical Public Health Issue for Transgender and Gender-Nonconforming People

PubMed Central

Reisner, Sari L; Hughto, Jaclyn M White; Dunham, Emilia E; Heflin, Katherine J; Begenyi, Jesse Blue Glass; Coffey-Esquivel, Julia; Cahill, Sean

2015-01-01

Context Gender minority people who are transgender or gender nonconforming experience widespread discrimination and health inequities. Since 2012, Massachusetts law has provided protections against discrimination on the basis of gender identity in employment, housing, credit, public education, and hate crimes. The law does not, however, protect against discrimination in public accommodations (eg, hospitals, health centers, transportation, nursing homes, supermarkets, retail establishments). For this article, we examined the frequency and health correlates of public accommodations discrimination among gender minority adults in Massachusetts, with attention to discrimination in health care settings. Methods In 2013, we recruited a community-based sample (n = 452) both online and in person. The respondents completed a 1-time, electronic survey assessing demographics, health, health care utilization, and discrimination in public accommodations venues in the past 12 months. Using adjusted multivariable logistic regression models, we examined whether experiencing public accommodations discrimination in health care was independently associated with adverse self-reported health, adjusting for discrimination in other public accommodations settings. Findings Overall, 65% of respondents reported public accommodations discrimination in the past 12 months. The 5 most prevalent discrimination settings were transportation (36%), retail (28%), restaurants (26%), public gatherings (25%), and health care (24%). Public accommodations discrimination in the past 12 months in health care settings was independently associated with a 31% to 81% increased risk of adverse emotional and physical symptoms and a 2-fold to 3-fold increased risk of postponement of needed care when sick or injured and of preventive or routine health care, adjusting for discrimination in other public accommodations settings (which also conferred an additional 20% to 77% risk per discrimination setting endorsed). Conclusions Discrimination in public accommodations is common and is associated with adverse health outcomes among transgender and gender-nonconforming adults in Massachusetts. Discrimination in health care settings creates a unique health risk for gender minority people. The passage and enforcement of transgender rights laws that include protections against discrimination in public accommodations—inclusive of health care—are a public health policy approach critically needed to address transgender health inequities. PMID:26219197

Development of a direct observation Measure of Environmental Qualities of Activity Settings.

PubMed

King, Gillian; Rigby, Patty; Batorowicz, Beata; McMain-Klein, Margot; Petrenchik, Theresa; Thompson, Laura; Gibson, Michelle

2014-08-01

The aim of this study was to develop an observer-rated measure of aesthetic, physical, social, and opportunity-related qualities of leisure activity settings for young people (with or without disabilities). Eighty questionnaires were completed by sets of raters who independently rated 22 community/home activity settings. The scales of the 32-item Measure of Environmental Qualities of Activity Settings (MEQAS; Opportunities for Social Activities, Opportunities for Physical Activities, Pleasant Physical Environment, Opportunities for Choice, Opportunities for Personal Growth, and Opportunities to Interact with Adults) were determined using principal components analyses. Test-retest reliability was determined for eight activity settings, rated twice (4-6wk interval) by a trained rater. The factor structure accounted for 80% of the variance. The Kaiser-Meyer-Olkin Measure of Sampling Adequacy was 0.73. Cronbach's alphas for the scales ranged from 0.76 to 0.96, and interrater reliabilities (ICCs) ranged from 0.60 to 0.93. Test-retest reliabilities ranged from 0.70 to 0.90. Results suggest that the MEQAS has a sound factor structure and preliminary evidence of internal consistency, interrater, and test-retest reliability. The MEQAS is the first observer-completed measure of environmental qualities of activity settings. The MEQAS allows researchers to assess comprehensively qualities and affordances of activity settings, and can be used to design and assess environmental qualities of programs for young people. © 2014 Mac Keith Press.

A Jungle in There: Bacteria in Belly Buttons are Highly Diverse, but Predictable

PubMed Central

Hulcr, Jiri; Latimer, Andrew M.; Henley, Jessica B.; Rountree, Nina R.; Fierer, Noah; Lucky, Andrea; Lowman, Margaret D.; Dunn, Robert R.

2012-01-01

The belly button is one of the habitats closest to us, and yet it remains relatively unexplored. We analyzed bacteria and arachaea from the belly buttons of humans from two different populations sampled within a nation-wide citizen science project. We examined bacterial and archaeal phylotypes present and their diversity using multiplex pyrosequencing of 16S rDNA libraries. We then tested the oligarchy hypothesis borrowed from tropical macroecology, namely that the frequency of phylotypes in one sample of humans predicts its frequency in another independent sample. We also tested the predictions that frequent phylotypes (the oligarchs) tend to be common when present, and tend to be more phylogenetically clustered than rare phylotypes. Once rarefied to four hundred reads per sample, bacterial communities from belly buttons proved to be at least as diverse as communities known from other skin studies (on average 67 bacterial phylotypes per belly button). However, the belly button communities were strongly dominated by a few taxa: only 6 phylotypes occurred on >80% humans. While these frequent bacterial phylotypes (the archaea were all rare) are a tiny part of the total diversity of bacteria in human navels (<0.3% of phylotypes), they constitute a major portion of individual reads (∼1/3), and are predictable among independent samples of humans, in terms of both the occurrence and evolutionary relatedness (more closely related than randomly drawn equal sets of phylotypes). Thus, the hypothesis that “oligarchs” dominate diverse assemblages appears to be supported by human-associated bacteria. Although it remains difficult to predict which species of bacteria might be found on a particular human, predicting which species are most frequent (or rare) seems more straightforward, at least for those species living in belly buttons. PMID:23144827

Mutation patterns in small cell and non-small cell lung cancer patients suggest a different level of heterogeneity between primary and metastatic tumors.

PubMed

Saber, Ali; Hiltermann, T Jeroen N; Kok, Klaas; Terpstra, M Martijn; de Lange, Kim; Timens, Wim; Groen, Harry J M; van den Berg, Anke

2017-02-01

Several studies have shown heterogeneity in lung cancer, with parallel existence of multiple subclones characterized by their own specific mutational landscape. The extent to which minor clones become dominant in distinct metastasis is not clear. The aim of our study was to gain insight in the evolution pattern of lung cancer by investigating genomic heterogeneity between primary tumor and its distant metastases. Whole exome sequencing (WES) was performed on 24 tumor and five normal samples of two small cell lung carcinoma (SCLC) and three non-SCLC (NSCLC) patients. Validation of somatic variants in these 24 and screening of 33 additional samples was done by single primer enrichment technology. For each of the three NSCLC patients, about half of the mutations were shared between all tumor samples, whereas for SCLC patients, this percentage was around 95. Independent validation of the non-ubiquitous mutations confirmed the WES data for the vast majority of the variants. Phylogenetic trees indicated more distance between the tumor samples of the NSCLC patients as compared to the SCLC patients. Analysis of 30 independent DNA samples of 16 biopsies used for WES revealed a low degree of intra-tumor heterogeneity of the selected sets of mutations. In the primary tumors of all five patients, variable percentages (19-67%) of the seemingly metastases-specific mutations were present albeit at low read frequencies. Patients with advanced NSCLC have a high percentage of non-ubiquitous mutations indicative of branched evolution. In contrast, the low degree of heterogeneity in SCLC suggests a parallel and linear model of evolution. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Factors influencing pharmacists’ adoption of prescribing: qualitative application of the diffusion of innovations theory

PubMed Central

2013-01-01

Background In 2007, Alberta became the first Canadian jurisdiction to grant pharmacists a wide range of prescribing privileges. Our objective was to understand what factors influence pharmacists’ adoption of prescribing using a model for the Diffusion of Innovations in healthcare services. Methods Pharmacists participated in semi-structured telephone interviews to discuss their prescribing practices and explore the facilitators and barriers to implementation. Pharmacists working in community, hospital, PCN, or other settings were selected using a mix of random and purposive sampling. Two investigators independently analyzed each transcript using an Interpretive Description approach to identify themes. Analyses were informed by a model explaining the Diffusion of Innovations in health service organizations. Results Thirty-eight participants were interviewed. Prescribing behaviours varied from non-adoption through to product, disease, and patient focused use of prescribing. Pharmacists’ adoption of prescribing was dependent on the innovation itself, adopter, system readiness, and communication and influence. Adopting pharmacists viewed prescribing as a legitimization of previous practice and advantageous to instrumental daily tasks. The complexity of knowledge required for prescribing increased respectively in product, disease and patient focused prescribing scenarios. Individual adopters had higher levels of self-efficacy toward prescribing skills. At a system level, pharmacists who were in practice settings that were patient focused were more likely to adopt advanced prescribing practices, over those in product-focused settings. All pharmacists stated that physician relationships impacted their prescribing behaviours and individual pharmacists’ decisions to apply for independent prescribing privileges. Conclusions Diffusion of Innovations theory was helpful in understanding the multifaceted nature of pharmacists’ adoption of prescribing. The characteristics of the prescribing model itself which legitimized prior practices, the model of practice in a pharmacy setting, and relationships with physicians were prominent influences on pharmacists’ prescribing behaviours. PMID:24034176

Head-to-Head Comparison and Evaluation of 92 Plasma Protein Biomarkers for Early Detection of Colorectal Cancer in a True Screening Setting.

PubMed

Chen, Hongda; Zucknick, Manuela; Werner, Simone; Knebel, Phillip; Brenner, Hermann

2015-07-15

Novel noninvasive blood-based screening tests are strongly desirable for early detection of colorectal cancer. We aimed to conduct a head-to-head comparison of the diagnostic performance of 92 plasma-based tumor-associated protein biomarkers for early detection of colorectal cancer in a true screening setting. Among all available 35 carriers of colorectal cancer and a representative sample of 54 men and women free of colorectal neoplasms recruited in a cohort of screening colonoscopy participants in 2005-2012 (N = 5,516), the plasma levels of 92 protein biomarkers were measured. ROC analyses were conducted to evaluate the diagnostic performance. A multimarker algorithm was developed through the Lasso logistic regression model and validated in an independent validation set. The .632+ bootstrap method was used to adjust for the potential overestimation of diagnostic performance. Seventeen protein markers were identified to show statistically significant differences in plasma levels between colorectal cancer cases and controls. The adjusted area under the ROC curves (AUC) of these 17 individual markers ranged from 0.55 to 0.70. An eight-marker classifier was constructed that increased the adjusted AUC to 0.77 [95% confidence interval (CI), 0.59-0.91]. When validating this algorithm in an independent validation set, the AUC was 0.76 (95% CI, 0.65-0.85), and sensitivities at cutoff levels yielding 80% and 90% specificities were 65% (95% CI, 41-80%) and 44% (95% CI, 24-72%), respectively. The identified profile of protein biomarkers could contribute to the development of a powerful multimarker blood-based test for early detection of colorectal cancer. ©2015 American Association for Cancer Research.

Dynamic least-squares kernel density modeling of Fokker-Planck equations with application to neural population.

PubMed

Shotorban, Babak

2010-04-01

The dynamic least-squares kernel density (LSQKD) model [C. Pantano and B. Shotorban, Phys. Rev. E 76, 066705 (2007)] is used to solve the Fokker-Planck equations. In this model the probability density function (PDF) is approximated by a linear combination of basis functions with unknown parameters whose governing equations are determined by a global least-squares approximation of the PDF in the phase space. In this work basis functions are set to be Gaussian for which the mean, variance, and covariances are governed by a set of partial differential equations (PDEs) or ordinary differential equations (ODEs) depending on what phase-space variables are approximated by Gaussian functions. Three sample problems of univariate double-well potential, bivariate bistable neurodynamical system [G. Deco and D. Martí, Phys. Rev. E 75, 031913 (2007)], and bivariate Brownian particles in a nonuniform gas are studied. The LSQKD is verified for these problems as its results are compared against the results of the method of characteristics in nondiffusive cases and the stochastic particle method in diffusive cases. For the double-well potential problem it is observed that for low to moderate diffusivity the dynamic LSQKD well predicts the stationary PDF for which there is an exact solution. A similar observation is made for the bistable neurodynamical system. In both these problems least-squares approximation is made on all phase-space variables resulting in a set of ODEs with time as the independent variable for the Gaussian function parameters. In the problem of Brownian particles in a nonuniform gas, this approximation is made only for the particle velocity variable leading to a set of PDEs with time and particle position as independent variables. Solving these PDEs, a very good performance by LSQKD is observed for a wide range of diffusivities.

Factors influencing pharmacists' adoption of prescribing: qualitative application of the diffusion of innovations theory.

PubMed

Makowsky, Mark J; Guirguis, Lisa M; Hughes, Christine A; Sadowski, Cheryl A; Yuksel, Nese

2013-09-14

In 2007, Alberta became the first Canadian jurisdiction to grant pharmacists a wide range of prescribing privileges. Our objective was to understand what factors influence pharmacists' adoption of prescribing using a model for the Diffusion of Innovations in healthcare services. Pharmacists participated in semi-structured telephone interviews to discuss their prescribing practices and explore the facilitators and barriers to implementation. Pharmacists working in community, hospital, PCN, or other settings were selected using a mix of random and purposive sampling. Two investigators independently analyzed each transcript using an Interpretive Description approach to identify themes. Analyses were informed by a model explaining the Diffusion of Innovations in health service organizations. Thirty-eight participants were interviewed. Prescribing behaviours varied from non-adoption through to product, disease, and patient focused use of prescribing. Pharmacists' adoption of prescribing was dependent on the innovation itself, adopter, system readiness, and communication and influence. Adopting pharmacists viewed prescribing as a legitimization of previous practice and advantageous to instrumental daily tasks. The complexity of knowledge required for prescribing increased respectively in product, disease and patient focused prescribing scenarios. Individual adopters had higher levels of self-efficacy toward prescribing skills. At a system level, pharmacists who were in practice settings that were patient focused were more likely to adopt advanced prescribing practices, over those in product-focused settings. All pharmacists stated that physician relationships impacted their prescribing behaviours and individual pharmacists' decisions to apply for independent prescribing privileges. Diffusion of Innovations theory was helpful in understanding the multifaceted nature of pharmacists' adoption of prescribing. The characteristics of the prescribing model itself which legitimized prior practices, the model of practice in a pharmacy setting, and relationships with physicians were prominent influences on pharmacists' prescribing behaviours.

Stromal mast cells in invasive breast cancer are a marker of favourable prognosis: a study of 4,444 cases.

PubMed

Rajput, Ashish B; Turbin, Dmitry A; Cheang, Maggie Cu; Voduc, David K; Leung, Sam; Gelmon, Karen A; Gilks, C Blake; Huntsman, David G

2008-01-01

We have previously demonstrated in a pilot study of 348 invasive breast cancers that mast cell (MC) infiltrates within primary breast cancers are associated with a good prognosis. Our aim was to verify this finding in a larger cohort of invasive breast cancer patients and examine the relationship between the presence of MCs and other clinical and pathological features. Clinically annotated tissue microarrays (TMAs) containing 4,444 cases were constructed and stained with c-Kit (CD-117) using standard immunoperoxidase techniques to identify and quantify MCs. For statistical analysis, we applied a split-sample validation technique. Breast cancer specific survival was analyzed by Kaplan-Meier [KM] method and log rank test was used to compare survival curves. Survival analysis by KM method showed that the presence of stromal MCs was a favourable prognostic factor in the training set (P = 0.001), and the validation set group (P = 0.006). X-tile plot generated to define the optimal number of MCs showed that the presence of any number of stromal MCs predicted good prognosis. Multivariate analysis showed that the MC effect in the training set (Hazard ratio [HR] = 0.804, 95% Confidence interval [CI], 0.653-0.991, P = 0.041) and validation set analysis (HR = 0.846, 95% CI, 0.683-1.049, P = 0.128) was independent of age, tumor grade, tumor size, lymph node, ER and Her2 status. This study concludes that stromal MC infiltration in invasive breast cancer is an independent good prognostic marker and reiterates the critical role of local inflammatory responses in breast cancer progression.

Stromal mast cells in invasive breast cancer are a marker of favourable prognosis: a study of 4,444 cases

PubMed Central

Rajput, Ashish B.; Turbin, Dmitry A.; Cheang, Maggie CU; Voduc, David K.; Leung, Sam; Gelmon, Karen A.; Gilks, C. Blake

2007-01-01

Purpose We have previously demonstrated in a pilot study of 348 invasive breast cancers that mast cell (MC) infiltrates within primary breast cancers are associated with a good prognosis. Our aim was to verify this finding in a larger cohort of invasive breast cancer patients and examine the relationship between the presence of MCs and other clinical and pathological features. Experimental design Clinically annotated tissue microarrays (TMAs) containing 4,444 cases were constructed and stained with c-Kit (CD-117) using standard immunoperoxidase techniques to identify and quantify MCs. For statistical analysis, we applied a split-sample validation technique. Breast cancer specific survival was analyzed by Kaplan–Meier [KM] method and log rank test was used to compare survival curves. Results Survival analysis by KM method showed that the presence of stromal MCs was a favourable prognostic factor in the training set (P = 0.001), and the validation set group (P = 0.006). X-tile plot generated to define the optimal number of MCs showed that the presence of any number of stromal MCs predicted good prognosis. Multivariate analysis showed that the MC effect in the training set (Hazard ratio [HR] = 0.804, 95% Confidence interval [CI], 0.653–0.991, P = 0.041) and validation set analysis (HR = 0.846, 95% CI, 0.683–1.049, P = 0.128) was independent of age, tumor grade, tumor size, lymph node, ER and Her2 status. Conclusions This study concludes that stromal MC infiltration in invasive breast cancer is an independent good prognostic marker and reiterates the critical role of local inflammatory responses in breast cancer progression. PMID:17431762

Copy number variation signature to predict human ancestry

PubMed Central

2012-01-01

Background Copy number variations (CNVs) are genomic structural variants that are found in healthy populations and have been observed to be associated with disease susceptibility. Existing methods for CNV detection are often performed on a sample-by-sample basis, which is not ideal for large datasets where common CNVs must be estimated by comparing the frequency of CNVs in the individual samples. Here we describe a simple and novel approach to locate genome-wide CNVs common to a specific population, using human ancestry as the phenotype. Results We utilized our previously published Genome Alteration Detection Analysis (GADA) algorithm to identify common ancestry CNVs (caCNVs) and built a caCNV model to predict population structure. We identified a 73 caCNV signature using a training set of 225 healthy individuals from European, Asian, and African ancestry. The signature was validated on an independent test set of 300 individuals with similar ancestral background. The error rate in predicting ancestry in this test set was 2% using the 73 caCNV signature. Among the caCNVs identified, several were previously confirmed experimentally to vary by ancestry. Our signature also contains a caCNV region with a single microRNA (MIR270), which represents the first reported variation of microRNA by ancestry. Conclusions We developed a new methodology to identify common CNVs and demonstrated its performance by building a caCNV signature to predict human ancestry with high accuracy. The utility of our approach could be extended to large case–control studies to identify CNV signatures for other phenotypes such as disease susceptibility and drug response. PMID:23270563

Ultrasonic characterization of granites obtained from industrial quarries of Extremadura (Spain).

PubMed

del Río, L M; López, F; Esteban, F J; Tejado, J J; Mota, M; González, I; San Emeterio, J L; Ramos, A

2006-12-22

The industry of ornamental rocks, such as granites, represents one of the most important industrial activities in the region of Extremadura, SW Spain. A detailed knowledge of the intrinsic properties of this natural stone and its environmental evolution is a required goal in order to fully characterize its quality. In this work, two independent NDT acoustic techniques have been used to measure the acoustic velocity of longitudinal waves in different prismatic granitic-samples of industrial quarries. A low-frequency transceiver set-up, based on a high-voltage BPV Steinkamp instrument and two 50 kHz probes, has been used to measure pulse travel times by ultrasonic through-transmission testing. In complementary fashion, an Erudite MK3 test equipment with an electromagnetic vibrator and two piezoelectric sensors has also been employed to measure ultrasonic velocity by means of a resonance-based method, using the same types of granite varieties. In addition, a comprehensive set of physical/mechanical properties have also been analyzed, according to Spanish regulations in force, by means of alternative methods including destructive techniques such as strength, porosity, absorption, etc. A large number of samples, representing the most important varieties of granites from quarries of Extremadura, have been analyzed using the above-mentioned procedures. Some results obtained by destructive techniques have been correlated with those found using ultrasonic techniques. Our experimental setting allowed a complementary characterization of granite samples and a thorough validation of the different techniques employed, thus providing the industry of ornamental rocks with a non-destructive tool that will facilitate a more detailed insight on the properties of the rocks under study.

The effects of sampling bias and model complexity on the predictive performance of MaxEnt species distribution models.

PubMed

Syfert, Mindy M; Smith, Matthew J; Coomes, David A

2013-01-01

Species distribution models (SDMs) trained on presence-only data are frequently used in ecological research and conservation planning. However, users of SDM software are faced with a variety of options, and it is not always obvious how selecting one option over another will affect model performance. Working with MaxEnt software and with tree fern presence data from New Zealand, we assessed whether (a) choosing to correct for geographical sampling bias and (b) using complex environmental response curves have strong effects on goodness of fit. SDMs were trained on tree fern data, obtained from an online biodiversity data portal, with two sources that differed in size and geographical sampling bias: a small, widely-distributed set of herbarium specimens and a large, spatially clustered set of ecological survey records. We attempted to correct for geographical sampling bias by incorporating sampling bias grids in the SDMs, created from all georeferenced vascular plants in the datasets, and explored model complexity issues by fitting a wide variety of environmental response curves (known as "feature types" in MaxEnt). In each case, goodness of fit was assessed by comparing predicted range maps with tree fern presences and absences using an independent national dataset to validate the SDMs. We found that correcting for geographical sampling bias led to major improvements in goodness of fit, but did not entirely resolve the problem: predictions made with clustered ecological data were inferior to those made with the herbarium dataset, even after sampling bias correction. We also found that the choice of feature type had negligible effects on predictive performance, indicating that simple feature types may be sufficient once sampling bias is accounted for. Our study emphasizes the importance of reducing geographical sampling bias, where possible, in datasets used to train SDMs, and the effectiveness and essentialness of sampling bias correction within MaxEnt.

Model-independent constraints on possible modifications of Newtonian gravity

NASA Technical Reports Server (NTRS)

Talmadge, C.; Berthias, J.-P.; Hellings, R. W.; Standish, E. M.

1988-01-01

New model-independent constraints on possible modifications of Newtonian gravity over solar-system distance scales are presented, and their implications discussed. The constraints arise from the analysis of various planetary astrometric data sets. The results of the model-independent analysis are then applied to set limits on a variation in the l/r-squared behavior of gravity, on possible Yukawa-type interactions with ranges of the order of planetary distance scales, and on a deviation from Newtonian gravity of the type discussed by Milgrom (1983).

An integrated approach for identifying wrongly labelled samples when performing classification in microarray data.

PubMed

Leung, Yuk Yee; Chang, Chun Qi; Hung, Yeung Sam

2012-01-01

Using hybrid approach for gene selection and classification is common as results obtained are generally better than performing the two tasks independently. Yet, for some microarray datasets, both classification accuracy and stability of gene sets obtained still have rooms for improvement. This may be due to the presence of samples with wrong class labels (i.e. outliers). Outlier detection algorithms proposed so far are either not suitable for microarray data, or only solve the outlier detection problem on their own. We tackle the outlier detection problem based on a previously proposed Multiple-Filter-Multiple-Wrapper (MFMW) model, which was demonstrated to yield promising results when compared to other hybrid approaches (Leung and Hung, 2010). To incorporate outlier detection and overcome limitations of the existing MFMW model, three new features are introduced in our proposed MFMW-outlier approach: 1) an unbiased external Leave-One-Out Cross-Validation framework is developed to replace internal cross-validation in the previous MFMW model; 2) wrongly labeled samples are identified within the MFMW-outlier model; and 3) a stable set of genes is selected using an L1-norm SVM that removes any redundant genes present. Six binary-class microarray datasets were tested. Comparing with outlier detection studies on the same datasets, MFMW-outlier could detect all the outliers found in the original paper (for which the data was provided for analysis), and the genes selected after outlier removal were proven to have biological relevance. We also compared MFMW-outlier with PRAPIV (Zhang et al., 2006) based on same synthetic datasets. MFMW-outlier gave better average precision and recall values on three different settings. Lastly, artificially flipped microarray datasets were created by removing our detected outliers and flipping some of the remaining samples' labels. Almost all the 'wrong' (artificially flipped) samples were detected, suggesting that MFMW-outlier was sufficiently powerful to detect outliers in high-dimensional microarray datasets.

Raman spectroscopic detection and identification of Burkholderia mallei and Burkholderia pseudomallei in feedstuff.

PubMed

Stöckel, Stephan; Meisel, Susann; Elschner, Mandy; Melzer, Falk; Rösch, Petra; Popp, Jürgen

2015-01-01

Burkholderia mallei (the etiologic agent of glanders in equines and rarely humans) and Burkholderia pseudomallei, causing melioidosis in humans and animals, are designated category B biothreat agents. The intrinsically high resistance of both agents to many antibiotics, their potential use as bioweapons, and their low infectious dose, necessitate the need for rapid and accurate detection methods. Current methods to identify these organisms may require up to 1 week, as they rely on phenotypic characteristics and an extensive set of biochemical reactions. In this study, Raman microspectroscopy, a cultivation-independent typing technique for single bacterial cells with the potential for being a rapid point-of-care analysis system, is evaluated to identify and differentiate B. mallei and B. pseudomallei within hours. Here, not only broth-cultured microbes but also bacteria isolated out of pelleted animal feedstuff were taken into account. A database of Raman spectra allowed a calculation of classification functions, which were trained to differentiate Raman spectra of not only both pathogens but also of five further Burkholderia spp. and four species of the closely related genus Pseudomonas. The developed two-stage classification system comprising two support vector machine (SVM) classifiers was then challenged by a test set of 11 samples to simulate the case of a real-world-scenario, when "unknown samples" are to be identified. In the end, all test set samples were identified correctly, even if the contained bacterial strains were not incorporated in the database before or were isolated out of animal feedstuff. Specifically, the five test samples bearing B. mallei and B. pseudomallei were correctly identified on species level with accuracies between 93.9 and 98.7%. The sample analysis itself requires no biomass enrichment step prior to the analysis and can be performed under biosafety level 1 (BSL 1) conditions after inactivating the bacteria with formaldehyde.

A nonparametric method to generate synthetic populations to adjust for complex sampling design features.

PubMed

Dong, Qi; Elliott, Michael R; Raghunathan, Trivellore E

2014-06-01

Outside of the survey sampling literature, samples are often assumed to be generated by a simple random sampling process that produces independent and identically distributed (IID) samples. Many statistical methods are developed largely in this IID world. Application of these methods to data from complex sample surveys without making allowance for the survey design features can lead to erroneous inferences. Hence, much time and effort have been devoted to develop the statistical methods to analyze complex survey data and account for the sample design. This issue is particularly important when generating synthetic populations using finite population Bayesian inference, as is often done in missing data or disclosure risk settings, or when combining data from multiple surveys. By extending previous work in finite population Bayesian bootstrap literature, we propose a method to generate synthetic populations from a posterior predictive distribution in a fashion inverts the complex sampling design features and generates simple random samples from a superpopulation point of view, making adjustment on the complex data so that they can be analyzed as simple random samples. We consider a simulation study with a stratified, clustered unequal-probability of selection sample design, and use the proposed nonparametric method to generate synthetic populations for the 2006 National Health Interview Survey (NHIS), and the Medical Expenditure Panel Survey (MEPS), which are stratified, clustered unequal-probability of selection sample designs.

A nonparametric method to generate synthetic populations to adjust for complex sampling design features

PubMed Central

Dong, Qi; Elliott, Michael R.; Raghunathan, Trivellore E.

2017-01-01

Outside of the survey sampling literature, samples are often assumed to be generated by a simple random sampling process that produces independent and identically distributed (IID) samples. Many statistical methods are developed largely in this IID world. Application of these methods to data from complex sample surveys without making allowance for the survey design features can lead to erroneous inferences. Hence, much time and effort have been devoted to develop the statistical methods to analyze complex survey data and account for the sample design. This issue is particularly important when generating synthetic populations using finite population Bayesian inference, as is often done in missing data or disclosure risk settings, or when combining data from multiple surveys. By extending previous work in finite population Bayesian bootstrap literature, we propose a method to generate synthetic populations from a posterior predictive distribution in a fashion inverts the complex sampling design features and generates simple random samples from a superpopulation point of view, making adjustment on the complex data so that they can be analyzed as simple random samples. We consider a simulation study with a stratified, clustered unequal-probability of selection sample design, and use the proposed nonparametric method to generate synthetic populations for the 2006 National Health Interview Survey (NHIS), and the Medical Expenditure Panel Survey (MEPS), which are stratified, clustered unequal-probability of selection sample designs. PMID:29200608

Integrative topological analysis of mass spectrometry data reveals molecular features with clinical relevance in esophageal squamous cell carcinoma

PubMed Central

Gao, She-Gan; Liu, Rui-Min; Zhao, Yun-Gang; Wang, Pei; Ward, Douglas G.; Wang, Guang-Chao; Guo, Xiang-Qian; Gu, Juan; Niu, Wan-Bin; Zhang, Tian; Martin, Ashley; Guo, Zhi-Peng; Feng, Xiao-Shan; Qi, Yi-Jun; Ma, Yuan-Fang

2016-01-01

Combining MS-based proteomic data with network and topological features of such network would identify more clinically relevant molecules and meaningfully expand the repertoire of proteins derived from MS analysis. The integrative topological indexes representing 95.96% information of seven individual topological measures of node proteins were calculated within a protein-protein interaction (PPI) network, built using 244 differentially expressed proteins (DEPs) identified by iTRAQ 2D-LC-MS/MS. Compared with DEPs, differentially expressed genes (DEGs) and comprehensive features (CFs), structurally dominant nodes (SDNs) based on integrative topological index distribution produced comparable classification performance in three different clinical settings using five independent gene expression data sets. The signature molecules of SDN-based classifier for distinction of early from late clinical TNM stages were enriched in biological traits of protein synthesis, intracellular localization and ribosome biogenesis, which suggests that ribosome biogenesis represents a promising therapeutic target for treating ESCC. In addition, ITGB1 expression selected exclusively by integrative topological measures correlated with clinical stages and prognosis, which was further validated with two independent cohorts of ESCC samples. Thus the integrative topological analysis of PPI networks proposed in this study provides an alternative approach to identify potential biomarkers and therapeutic targets from MS/MS data with functional insights in ESCC. PMID:26898710

Statistical variation in progressive scrambling

NASA Astrophysics Data System (ADS)

Clark, Robert D.; Fox, Peter C.

2004-07-01

The two methods most often used to evaluate the robustness and predictivity of partial least squares (PLS) models are cross-validation and response randomization. Both methods may be overly optimistic for data sets that contain redundant observations, however. The kinds of perturbation analysis widely used for evaluating model stability in the context of ordinary least squares regression are only applicable when the descriptors are independent of each other and errors are independent and normally distributed; neither assumption holds for QSAR in general and for PLS in particular. Progressive scrambling is a novel, non-parametric approach to perturbing models in the response space in a way that does not disturb the underlying covariance structure of the data. Here, we introduce adjustments for two of the characteristic values produced by a progressive scrambling analysis - the deprecated predictivity (Q_s^{ast^2}) and standard error of prediction (SDEP s * ) - that correct for the effect of introduced perturbation. We also explore the statistical behavior of the adjusted values (Q_0^{ast^2} and SDEP 0 * ) and the sensitivity to perturbation (d q 2/d r yy ' 2). It is shown that the three statistics are all robust for stable PLS models, in terms of the stochastic component of their determination and of their variation due to sampling effects involved in training set selection.

Development, evaluation and comparison of two independent sampling and analytical methods for ortho-phthalaldehyde vapors and condensation aerosols in air† ‡

PubMed Central

2015-01-01

Two independent sampling and analytical methods for ortho-phthalaldehyde (OPA) in air have been developed, evaluated and compared (1) a reagent-coated solid sorbent HPLC-UV method and (2) an impinger-fluorescence method. In the first method, air sampling is conducted at 1.0 L min−1 with a sampler containing 350 mg of silica gel coated with 1 mg of acidified 2,4-dinitrophenylhydrazine (DNPH). After sampling, excess DNPH in ethyl acetate is added to the sampler prior to storage for 68 hours. The OPA-DNPH derivative is eluted with 4.0 mL of dimethyl sulfoxide (DMSO) for measurement by HPLC with a UV detector set at 3S5 nm. The estimated detection limit is 0.016 µg per sample or 0.067 µg m−3 (0.012 ppb) for a 240 L air sample. Recoveries of vapor spikes at levels of 1.2 to 6.2 µg were 96 to 101%. Recoveries of spikes as mixtures of vapor and condensation aerosols were 97 to 100%. In the second method, air sampling is conducted at 1.0 L mm−1 with a midget impinger containing 10 mL of DMSO solution containing N-acetyl-l-cysteine and ethylenediamine. The fluorescence reading is taken 80 min after the completion of air sampling. Since the time of taking the fluorescence reading is critical, the reading is taken with a portable fluorometer. The estimated detection limit is 0.024 µg per sample or 0.1 µg m−3 (0.018 ppb) for a 240 L air sample. Recoveries of OPA vapor spikes at levels of 1.4 to 5.0 µg per sample were 97 to 105%. Recoveries of spikes as mixtures of vapors and condensation aerosols were 95 to 99%. The collection efficiency for a mixture of vapor and condensation aerosol was 99.4%. The two methods were compared side-by-side in a generation system constructed for producing controlled atmospheres of OPA vapor in air. Average air concentrations of OPA vapor found by both methods agreed within ±10%. PMID:26346658

Mining the human urine proteome for monitoring renal transplant injury

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

Sigdel, Tara K.; Gao, Yuqian; He, Jintang

The human urinary proteome reflects systemic and inherent renal injury perturbations and can be analyzed to harness specific biomarkers for different kidney transplant injury states. 396 unique urine samples were collected contemporaneously with an allograft biopsy from 396 unique kidney transplant recipients. Centralized, blinded histology on the graft was used to classify matched urine samples into categories of acute rejection (AR), chronic allograft nephropathy (CAN), BK virus nephritis (BKVN), and stable graft (STA). Liquid chromatography–mass spectrometry (LC-MS) based proteomics using iTRAQ based discovery (n=108) and global label-free LC-MS analyses of individual samples (n=137) for quantitative proteome assessment were used inmore » the discovery step. Selected reaction monitoring (SRM) was applied to identify and validate minimal urine protein/peptide biomarkers to accurately segregate organ injury causation and pathology on unique urine samples (n=151). A total of 958 proteins were initially quantified by iTRAQ, 87% of which were also identified among 1574 urine proteins detected in LC-MS validation. 103 urine proteins were significantly (p<0.05) perturbed in injury and enriched for humoral immunity, complement activation, and lymphocyte trafficking. A set of 131 peptides corresponding to 78 proteins were assessed by SRM for their significance in an independent sample cohort. A minimal set of 35 peptides mapping to 33 proteins, were modeled to segregate different injury groups (AUC =93% for AR, 99% for CAN, 83% for BKVN). Urinary proteome discovery and targeted validation identified urine protein fingerprints for non-invasive differentiation of kidney transplant injuries, thus opening the door for personalized immune risk assessment and therapy.« less

Improving estimates of genetic maps: a meta-analysis-based approach.

PubMed

Stewart, William C L

2007-07-01

Inaccurate genetic (or linkage) maps can reduce the power to detect linkage, increase type I error, and distort haplotype and relationship inference. To improve the accuracy of existing maps, I propose a meta-analysis-based method that combines independent map estimates into a single estimate of the linkage map. The method uses the variance of each independent map estimate to combine them efficiently, whether the map estimates use the same set of markers or not. As compared with a joint analysis of the pooled genotype data, the proposed method is attractive for three reasons: (1) it has comparable efficiency to the maximum likelihood map estimate when the pooled data are homogeneous; (2) relative to existing map estimation methods, it can have increased efficiency when the pooled data are heterogeneous; and (3) it avoids the practical difficulties of pooling human subjects data. On the basis of simulated data modeled after two real data sets, the proposed method can reduce the sampling variation of linkage maps commonly used in whole-genome linkage scans. Furthermore, when the independent map estimates are also maximum likelihood estimates, the proposed method performs as well as or better than when they are estimated by the program CRIMAP. Since variance estimates of maps may not always be available, I demonstrate the feasibility of three different variance estimators. Overall, the method should prove useful to investigators who need map positions for markers not contained in publicly available maps, and to those who wish to minimize the negative effects of inaccurate maps. Copyright 2007 Wiley-Liss, Inc.

Determination of the optimal number of components in independent components analysis.

PubMed

Kassouf, Amine; Jouan-Rimbaud Bouveresse, Delphine; Rutledge, Douglas N

2018-03-01

Independent components analysis (ICA) may be considered as one of the most established blind source separation techniques for the treatment of complex data sets in analytical chemistry. Like other similar methods, the determination of the optimal number of latent variables, in this case, independent components (ICs), is a crucial step before any modeling. Therefore, validation methods are required in order to decide about the optimal number of ICs to be used in the computation of the final model. In this paper, three new validation methods are formally presented. The first one, called Random_ICA, is a generalization of the ICA_by_blocks method. Its specificity resides in the random way of splitting the initial data matrix into two blocks, and then repeating this procedure several times, giving a broader perspective for the selection of the optimal number of ICs. The second method, called KMO_ICA_Residuals is based on the computation of the Kaiser-Meyer-Olkin (KMO) index of the transposed residual matrices obtained after progressive extraction of ICs. The third method, called ICA_corr_y, helps to select the optimal number of ICs by computing the correlations between calculated proportions and known physico-chemical information about samples, generally concentrations, or between a source signal known to be present in the mixture and the signals extracted by ICA. These three methods were tested using varied simulated and experimental data sets and compared, when necessary, to ICA_by_blocks. Results were relevant and in line with expected ones, proving the reliability of the three proposed methods. Copyright © 2017 Elsevier B.V. All rights reserved.

Report: Independent Ground Water Sampling Generally Confirms EPA’s Data at Wheeler Pit Superfund Site in Wisconsin

EPA Pesticide Factsheets

Report #10-P-0218, September 8, 2010. With minimal exceptions, our independent sampling results at the Wheeler Pit Superfund Site were consistent with the sampling results that EPA Region 5 has obtained historically.

How Many Separable Sources? Model Selection In Independent Components Analysis

PubMed Central

Woods, Roger P.; Hansen, Lars Kai; Strother, Stephen

2015-01-01

Unlike mixtures consisting solely of non-Gaussian sources, mixtures including two or more Gaussian components cannot be separated using standard independent components analysis methods that are based on higher order statistics and independent observations. The mixed Independent Components Analysis/Principal Components Analysis (mixed ICA/PCA) model described here accommodates one or more Gaussian components in the independent components analysis model and uses principal components analysis to characterize contributions from this inseparable Gaussian subspace. Information theory can then be used to select from among potential model categories with differing numbers of Gaussian components. Based on simulation studies, the assumptions and approximations underlying the Akaike Information Criterion do not hold in this setting, even with a very large number of observations. Cross-validation is a suitable, though computationally intensive alternative for model selection. Application of the algorithm is illustrated using Fisher's iris data set and Howells' craniometric data set. Mixed ICA/PCA is of potential interest in any field of scientific investigation where the authenticity of blindly separated non-Gaussian sources might otherwise be questionable. Failure of the Akaike Information Criterion in model selection also has relevance in traditional independent components analysis where all sources are assumed non-Gaussian. PMID:25811988

Confirmatory factor analysis applied to the Force Concept Inventory

NASA Astrophysics Data System (ADS)

Eaton, Philip; Willoughby, Shannon D.

2018-06-01

In 1995, Huffman and Heller used exploratory factor analysis to draw into question the factors of the Force Concept Inventory (FCI). Since then several papers have been published examining the factors of the FCI on larger sets of student responses and understandable factors were extracted as a result. However, none of these proposed factor models have been verified to not be unique to their original sample through the use of independent sets of data. This paper seeks to confirm the factor models proposed by Scott et al. in 2012, and Hestenes et al. in 1992, as well as another expert model proposed within this study through the use of confirmatory factor analysis (CFA) and a sample of 20 822 postinstruction student responses to the FCI. Upon application of CFA using the full sample, all three models were found to fit the data with acceptable global fit statistics. However, when CFA was performed using these models on smaller sample sizes the models proposed by Scott et al. and Eaton and Willoughby were found to be far more stable than the model proposed by Hestenes et al. The goodness of fit of these models to the data suggests that the FCI can be scored on factors that are not unique to a single class. These scores could then be used to comment on how instruction methods effect the performance of students along a single factor and more in-depth analyses of curriculum changes may be possible as a result.

Timing and Rate of Deglaciation of the MIS 2 Cordilleran Ice Sheet in Yukon Territory

NASA Astrophysics Data System (ADS)

Ward, B. C.; Bond, J. D.; Gosse, J. C.; Turner, D. G.

2015-12-01

The northern Cordilleran ice sheet (CIS) consisted of a series of quasi-independent ice lobes that coalesced during the last glacial maximum (LGM) to form a continuous carapace of precipitation limited ice over southern Yukon. Variations in effective precipitation to different source areas of these ice lobes have been used to explain disparities in glacier extents in marine oxygen isotope stages (MIS) 4 and 6. Deglaciation of the northern margin of the CIS and its rate of recession from the LGM are poorly understood. We use cosmogenic nuclide exposure dating (10Be and 36Cl) on groups of 3-4 glacial erratics to reconstruct the timing and rate of deglaciation. Our sampling concentrated on the St. Elias, Cassiar and Selwyn lobes, as well an independent glacier from the Ogilvie Mountains. Boulders sampled up-ice from terminal moraines show that the initiation of deglaciation varied regionally. 36Cl ages from the Ogilvie Mountains indicate that deglaciation initiated by 24.8 ka. Further south in the Selwyn Lobe, two sites separated by ~150 km returned ages of 15.2 and 16.1 ka. To the south-west, three boulders from the Cassiar Lobe are 13.6 ka. Rates of deglaciation are best constrained for the Cassiar Lobe with two transects along different flow lines. Multiple valley bottom samples in the mid-deglaciation setting at Whitehorse yielded ages of 12.0 ka, while one boulder from the adjacent ridge top 600 m above is 13.5 ka. In the accumulation zone, ice-free conditions occurred by 10.8 ka. The other transect has higher elevation samples in a mid-deglaciation setting in the Pelly Mountains that indicate deglaciation occurred by 13.0 ka. Samples taken from high elevation and valley bottom sites close to accumulation zones of the Cassiar Lobe yielded ages of 13.6 and 11.0 ka, respectively. These results provide a chronology for the style of deglaciation interpreted from regional mapping throughout Yukon: gradual initial retreat and thinning marked by moraines, followed by rapid downwasting and regional stagnation. Thinning of the ice to expose uplands in the Cassiar lobe was coincident with margin retreat. The increase in rates of deglaciation after 12 ka fits well with mapped evidence of regional stagnation. These ages correspond to evidence in the north Pacific of rapid warming immediately after the Younger Dryas in the pre-Boreal.

The aggregate site frequency spectrum for comparative population genomic inference.

PubMed

Xue, Alexander T; Hickerson, Michael J

2015-12-01

Understanding how assemblages of species responded to past climate change is a central goal of comparative phylogeography and comparative population genomics, an endeavour that has increasing potential to integrate with community ecology. New sequencing technology now provides the potential to perform complex demographic inference at unprecedented resolution across assemblages of nonmodel species. To this end, we introduce the aggregate site frequency spectrum (aSFS), an expansion of the site frequency spectrum to use single nucleotide polymorphism (SNP) data sets collected from multiple, co-distributed species for assemblage-level demographic inference. We describe how the aSFS is constructed over an arbitrary number of independent population samples and then demonstrate how the aSFS can differentiate various multispecies demographic histories under a wide range of sampling configurations while allowing effective population sizes and expansion magnitudes to vary independently. We subsequently couple the aSFS with a hierarchical approximate Bayesian computation (hABC) framework to estimate degree of temporal synchronicity in expansion times across taxa, including an empirical demonstration with a data set consisting of five populations of the threespine stickleback (Gasterosteus aculeatus). Corroborating what is generally understood about the recent postglacial origins of these populations, the joint aSFS/hABC analysis strongly suggests that the stickleback data are most consistent with synchronous expansion after the Last Glacial Maximum (posterior probability = 0.99). The aSFS will have general application for multilevel statistical frameworks to test models involving assemblages and/or communities, and as large-scale SNP data from nonmodel species become routine, the aSFS expands the potential for powerful next-generation comparative population genomic inference. © 2015 The Authors. Molecular Ecology Published by John Wiley & Sons Ltd.

Genome-wide association study of therapeutic opioid dosing identifies a novel locus upstream of OPRM1

PubMed Central

Smith, Andrew H.; Jensen, Kevin P.; Li, Jin; Nunez, Yaira; Farrer, Lindsay A.; Hakonarson, Hakon; Cook-Sather, Scott D.; Kranzler, Henry R.; Gelernter, Joel

2017-01-01

Opioids are very effective analgesics, but they are also highly addictive. Methadone is used to treat opioid dependence (OD), acting as a selective agonist at the μ-opioid receptor encoded by the gene OPRM1. Determining the optimal methadone maintenance dose is time-consuming; currently, no biomarkers are available to guide treatment. In methadone-treated OD subjects drawn from a case and control sample, we conducted a genome-wide association study (GWAS) of usual daily methadone dose. In African-American (AA) OD subjects (n = 383), we identified a genome-wide significant association between therapeutic methadone dose (mean = 68.0 mg, standard deviation (SD) = 30.1 mg) and rs73568641 (P = 2.8 × 10−8), the nearest gene (306 kilobases) being OPRM1. Each minor (C) allele corresponded to an additional ~20 mg/day of oral methadone, an effect specific to AAs. In European-Americans (EAs) (n = 1,027), no genome-wide significant associations with methadone dose (mean = 77.8 mg, SD = 33.9 mg) were observed. In an independent set of opioid-naïve AA children being treated for surgical pain, rs73568641-C was associated with a higher required dose of morphine (n = 241, P = 3.9 × 10−2). Similarly, independent genomic loci previously shown to associate with higher opioid analgesic dose were associated with higher methadone dose in the OD sample (AA and EA: n = 1,410, genetic score P = 1.3 × 10−3). The present results in AAs indicate that genetic variants influencing opioid sensitivity across different clinical settings could contribute to precision pharmacotherapy for pain and addiction. PMID:28115739

Assessment of the Uniqueness of Wind Tunnel Strain-Gage Balance Load Predictions

NASA Technical Reports Server (NTRS)

Ulbrich, N.

2016-01-01

A new test was developed to assess the uniqueness of wind tunnel strain-gage balance load predictions that are obtained from regression models of calibration data. The test helps balance users to gain confidence in load predictions of non-traditional balance designs. It also makes it possible to better evaluate load predictions of traditional balances that are not used as originally intended. The test works for both the Iterative and Non-Iterative Methods that are used in the aerospace testing community for the prediction of balance loads. It is based on the hypothesis that the total number of independently applied balance load components must always match the total number of independently measured bridge outputs or bridge output combinations. This hypothesis is supported by a control volume analysis of the inputs and outputs of a strain-gage balance. It is concluded from the control volume analysis that the loads and bridge outputs of a balance calibration data set must separately be tested for linear independence because it cannot always be guaranteed that a linearly independent load component set will result in linearly independent bridge output measurements. Simple linear math models for the loads and bridge outputs in combination with the variance inflation factor are used to test for linear independence. A highly unique and reversible mapping between the applied load component set and the measured bridge output set is guaranteed to exist if the maximum variance inflation factor of both sets is less than the literature recommended threshold of five. Data from the calibration of a six{component force balance is used to illustrate the application of the new test to real-world data.

Identification and functional validation of HPV-mediated hypermethylation in head and neck squamous cell carcinoma

PubMed Central

2013-01-01

Background Human papillomavirus-positive (HPV+) head and neck squamous cell carcinoma (HNSCC) represents a distinct clinical and epidemiological condition compared with HPV-negative (HPV-) HNSCC. To test the possible involvement of epigenetic modulation by HPV in HNSCC, we conducted a genome-wide DNA-methylation analysis. Methods Using laser-capture microdissection of 42 formalin-fixed paraffin wax-embedded (FFPE) HNSCCs, we generated DNA-methylation profiles of 18 HPV+ and 14 HPV- samples, using Infinium 450 k BeadArray technology. Methylation data were validated in two sets of independent HPV+/HPV- HNSCC samples (fresh-frozen samples and cell lines) using two independent methods (Infinium 450 k and whole-genome methylated DNA immunoprecipitation sequencing (MeDIP-seq)). For the functional analysis, an HPV- HNSCC cell line was transduced with lentiviral constructs containing the two HPV oncogenes (E6 and E7), and effects on methylation were assayed using the Infinium 450 k technology. Results and discussion Unsupervised clustering over the methylation variable positions (MVPs) with greatest variation showed that samples segregated in accordance with HPV status, but also that HPV+ tumors are heterogeneous. MVPs were significantly enriched at transcriptional start sites, leading to the identification of a candidate CpG island methylator phenotype in a sub-group of the HPV+ tumors. Supervised analysis identified a strong preponderance (87%) of MVPs towards hypermethylation in HPV+ HNSCC. Meta-analysis of our HNSCC and publicly available methylation data in cervical and lung cancers confirmed the observed DNA-methylation signature to be HPV-specific and tissue-independent. Grouping of MVPs into functionally more significant differentially methylated regions identified 43 hypermethylated promoter DMRs, including for three cadherins of the Polycomb group target genes. Integration with independent expression data showed strong negative correlation, especially for the cadherin gene-family members. Combinatorial ectopic expression of the two HPV oncogenes (E6 and E7) in an HPV- HNSCC cell line partially phenocopied the hypermethylation signature seen in HPV+ HNSCC tumors, and established E6 as the main viral effector gene. Conclusions Our data establish that archival FFPE tissue is very suitable for this type of methylome analysis, and suggest that HPV modulates the HNSCC epigenome through hypermethylation of Polycomb repressive complex 2 target genes such as cadherins, which are implicated in tumor progression and metastasis. PMID:23419152

How soil organic matter composition controls hexachlorobenzene-soil-interactions: adsorption isotherms and quantum chemical modeling.

PubMed

Ahmed, Ashour A; Kühn, Oliver; Aziz, Saadullah G; Hilal, Rifaat H; Leinweber, Peter

2014-04-01

Hazardous persistent organic pollutants (POPs) interact in soil with the soil organic matter (SOM) but this interaction is insufficiently understood at the molecular level. We investigated the adsorption of hexachlorobenzene (HCB) on soil samples with systematically modified SOM. These samples included the original soil, the soil modified by adding a hot water extract (HWE) fraction (soil+3 HWE and soil+6 HWE), and the pyrolyzed soil. The SOM contents increased in the order pyrolyzed soil

Application of artificial neural networks to chemostratigraphy

NASA Astrophysics Data System (ADS)

Malmgren, BjöRn A.; Nordlund, Ulf

1996-08-01

Artificial neural networks, a branch of artificial intelligence, are computer systems formed by a number of simple, highly interconnected processing units that have the ability to learn a set of target vectors from a set of associated input signals. Neural networks learn by self-adjusting a set of parameters, using some pertinent algorithm to minimize the error between the desired output and network output. We explore the potential of this approach in solving a problem involving classification of geochemical data. The data, taken from the literature, are derived from four late Quaternary zones of volcanic ash of basaltic and rhyolithic origin from the Norwegian Sea. These ash layers span the oxygen isotope zones 1, 5, 7, and 11, respectively (last 420,000 years). The data consist of nine geochemical variables (oxides) determined in each of 183 samples. We employed a three-layer back propagation neural network to assess its efficiency to optimally differentiate samples from the four ash zones on the basis of their geochemical composition. For comparison, three statistical pattern recognition techniques, linear discriminant analysis, the k-nearest neighbor (k-NN) technique, and SIMCA (soft independent modeling of class analogy), were applied to the same data. All of these showed considerably higher error rates than the artificial neural network, indicating that the back propagation network was indeed more powerful in correctly classifying the ash particles to the appropriate zone on the basis of their geochemical composition.

Mark-recapture using tetracycline and genetics reveal record-high bear density

USGS Publications Warehouse

Peacock, E.; Titus, K.; Garshelis, D.L.; Peacock, M.M.; Kuc, M.

2011-01-01

We used tetracycline biomarking, augmented with genetic methods to estimate the size of an American black bear (Ursus americanus) population on an island in Southeast Alaska. We marked 132 and 189 bears that consumed remote, tetracycline-laced baits in 2 different years, respectively, and observed 39 marks in 692 bone samples subsequently collected from hunters. We genetically analyzed hair samples from bait sites to determine the sex of marked bears, facilitating derivation of sex-specific population estimates. We obtained harvest samples from beyond the study area to correct for emigration. We estimated a density of 155 independent bears/100 km2, which is equivalent to the highest recorded for this species. This high density appears to be maintained by abundant, accessible natural food. Our population estimate (approx. 1,000 bears) could be used as a baseline and to set hunting quotas. The refined biomarking method for abundance estimation is a useful alternative where physical captures or DNA-based estimates are precluded by cost or logistics. Copyright ?? 2011 The Wildlife Society.

Pilot climate data system user's guide

NASA Technical Reports Server (NTRS)

Reph, M. G.; Treinish, L. A.; Bloch, L.

1984-01-01

Instructions for using the Pilot Climate Data System (PCDS), an interactive, scientific data management system for locating, obtaining, manipulating, and displaying climate-research data are presented. The PCDS currently provides this supoort for approximately twenty data sets. Figures that illustrate the terminal displays which a user sees when he/she runs the PCDS and some examples of the output from this system are included. The capabilities which are described in detail allow a user to perform the following: (1) obtain comprehensive descriptions of a number of climate parameter data sets and the associated sensor measurements from which they were derived; (2) obtain detailed information about the temporal coverage and data volume of data sets which are readily accessible via the PCDS; (3) extract portions of a data set using criteria such as time range and geographic location, and output the data to tape, user terminal, system printer, or online disk files in a special data-set-independent format; (4) access and manipulate the data in these data-set-independent files, performing such functions as combining the data, subsetting the data, and averaging the data; and (5) create various graphical representations of the data stored in the data-set-independent files.

Evaluation of the Illumigene Malaria LAMP: A Robust Molecular Diagnostic Tool for Malaria Parasites

PubMed Central

Lucchi, Naomi W.; Gaye, Marie; Diallo, Mammadou Alpha; Goldman, Ira F.; Ljolje, Dragan; Deme, Awa Bineta; Badiane, Aida; Ndiaye, Yaye Die; Barnwell, John W.; Udhayakumar, Venkatachalam; Ndiaye, Daouda

2016-01-01

Isothermal nucleic acid amplification assays such as the loop mediated isothermal amplification (LAMP), are well suited for field use as they do not require thermal cyclers to amplify the DNA. To further facilitate the use of LAMP assays in remote settings, simpler sample preparation methods and lyophilized reagents are required. The performance of a commercial malaria LAMP assay (Illumigene Malaria LAMP) was evaluated using two sample preparation workflows (simple filtration prep (SFP)) and gravity-driven filtration prep (GFP)) and pre-dispensed lyophilized reagents. Laboratory and clinical samples were tested in a field laboratory in Senegal and the results independently confirmed in a reference laboratory in the U.S.A. The Illumigene Malaria LAMP assay was easily implemented in the clinical laboratory and gave similar results to a real-time PCR reference test with limits of detection of ≤2.0 parasites/μl depending on the sample preparation method used. This assay reliably detected Plasmodium sp. parasites in a simple low-tech format, providing a much needed alternative to the more complex molecular tests for malaria diagnosis. PMID:27827432

Methods of analysis by the U.S. Geological Survey National Water Quality Laboratory; extraction of nitroaromatic compounds from water by polystyrene divinylbenzene cartridge and determination by high-performance liquid chromatography

USGS Publications Warehouse

Lindley, C.E.; Burkhardt, M.R.; DeRusseau, S.N.

1994-01-01

Organic explosives are determined in samples of ground water and surface water with emphasis on identifying and quantifying trinitrotoluene (TNT) metabolites. Water samples are filtered to remove suspended particulate material and passed through a polystyrene divinylbenzene-packed cartridge by a vacuum-extraction system. The target analytes subsequently are eluted with acetonitrile. A high-performance liquid chromatograph (HPLC) equipped with a photodiode-array detector is used for sample analysis. Analytes are separated on an octadecylsilane column using a methanol, water, and acetonitrile gradient elution. The compounds 2,4- and 2,6-dinitrotoluene are separated through an independent, isocratic elution. Method detection limits, on the basis of a 1-liter sample size, range from 0.11 to 0.32 microgram per liter. Recoveries averaged from 71 to 101 percent for 13 analytes in one set of HPLC-grade water fortified at about 1 microgram per liter. The method is limited to use by analysts experienced in handling explosive materials. (USGS)

A study of performance assessment task organization in high school optics

NASA Astrophysics Data System (ADS)

Zawicki, Joseph Leo

2002-01-01

This investigation was undertaken to validate three performance assessment tasks in high school physics. The tasks that were studied were developed around three organizational models of performance assessments: integrated, independent and surrogate. The integrated model required students to answer questions, make observations and demonstrate skills related to the index of refraction of a particular material. All of the questions and activities the students completed were related to a sample of a particular plastic sample that was the focus of this task. The independent model is analogous to the station model that is currently used on three New York State assessments: the Grade 4 - Elementary Science Program Evaluation Test, the Intermediate Level Science (ILS) Test, and the Physical Setting: Earth Science Regents Exam. Students took measurements related to the index of refraction of a plastic sample that was the focus of the initial portion of this task; the remaining questions on the assessment were generally related to the concept of the index of refraction but did not refer back to the initial sample. The final task organization followed the surrogate model. In this model, students reviewed data that was collected and analyzed by other (fictitious) students. The students completing this task were asked to review the work presented on this assessment for errors; they evaluated the conclusions and statements presented on the assessment. Students were also asked to determine if the student work was acceptable or if this investigation should be repeated. Approximately 300 students from urban, suburban and rural districts across Western New York State participated in the study. The tasks were administered during the spring semester of the 2000--2001 school year. The participating schools had at least covered the topic of refraction, both in classroom lectures and in laboratory activities. Each student completed only one form of the task---either the integrated, the independent or the surrogate form. A set of ten questions, compiled from past New York State Regents Examinations in Physics, was used as an additional measurement of student conceptual understanding. This question set was identified as the "Optics Baseline Test" (OBT). Additionally, classroom teachers ranked the academic performance of each of the students in their classroom on the outcomes of the physics course; these rankings were compared with student scores on the performance assessment tasks. The process skills incorporated within the individual questions on each task were reviewed by a panel of expert teachers. Student scores on the tasks themselves were examined using a principal component analysis. This analysis provided support for the process skill subtests organized around the general process skills of planning, performing, and reasoning. Scoring guides and inter-rater reliabilities were established for each task. The reliabilities for tasks, subtests and questions were fairly high, indicting adequate task reliability. Correlations between student performance on the individual tasks and the OBT were not significant. Teacher ranking of student achievement in individual classrooms also failed to correlate significantly with student performance on tasks. The lack of correlation could be attributed to several factors, including (among others) a wide range of student opportunities to learn from the seven schools in the sample. As has been reported in the performance assessment literature, there were no significant differences between the performance of male and female students. (Abstract shortened by UMI.)

Independent highly sensitive characterization of asparagine deamidation and aspartic acid isomerization by sheathless CZE-ESI-MS/MS.

PubMed

Gahoual, Rabah; Beck, Alain; François, Yannis-Nicolas; Leize-Wagner, Emmanuelle

2016-02-01

Amino acids residues are commonly submitted to various physicochemical modifications occurring at physiological pH and temperature. Post-translational modifications (PTMs) require comprehensive characterization because of their major influence on protein structure and involvement in numerous in vivo process or signaling. Mass spectrometry (MS) has gradually become an analytical tool of choice to characterize PTMs; however, some modifications are still challenging because of sample faint modification levels or difficulty to separate an intact peptide from modified counterparts before their transfer to the ionization source. Here, we report the implementation of capillary zone electrophoresis coupled to electrospray ionization tandem mass spectrometry (CZE-ESI-MS/MS) by the intermediate of a sheathless interfacing for independent and highly sensitive characterization of asparagine deamidation (deaN) and aspartic acid isomerization (isoD). CZE selectivity regarding deaN and isoD was studied extensively using different sets of synthetic peptides based on actual tryptic peptides. Results demonstrated CZE ability to separate the unmodified peptide from modified homologous exhibiting deaN, isoD or both independently with a resolution systematically superior to 1.29. Developed CZE-ESI-MS/MS method was applied for the characterization of monoclonal antibodies and complex protein mixture. Conserved CZE selectivity could be demonstrated even for complex samples, and foremost results obtained showed that CZE selectivity is similar regardless of the composition of the peptide. Separation of modified peptides prior to the MS analysis allowed to characterize and estimate modification levels of the sample independently for deaN and isoD even for peptides affected by both modifications and, as a consequence, enables to distinguish the formation of l-aspartic acid or d-aspartic acid generated from deaN. Separation based on peptide modification allowed, as supported by the ESI efficiency provided by CZE-ESI-MS/MS properties, and enabled to characterize and estimate studied PTMs with an unprecedented sensitivity and proved the relevance of implementing an electrophoretic driven separation for MS-based peptide analysis. Copyright © 2016 John Wiley & Sons, Ltd.

Search for narrow resonances in dilepton mass spectra in proton-proton collisions at √{ s} = 13 TeV and combination with 8 TeV data

NASA Astrophysics Data System (ADS)

Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Brondolin, E.; Dragicevic, M.; Erö, J.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hartl, C.; Hörmann, N.; Hrubec, J.; Jeitler, M.; König, A.; Krätschmer, I.; Liko, D.; Matsushita, T.; Mikulec, I.; Rabady, D.; Rad, N.; Rahbaran, B.; Rohringer, H.; Schieck, J.; Strauss, J.; Treberer-Treberspurg, W.; Waltenberger, W.; Wulz, C.-E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Alderweireldt, S.; De Wolf, E. A.; Janssen, X.; Lauwers, J.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Abu Zeid, S.; Blekman, F.; D'Hondt, J.; Daci, N.; De Bruyn, I.; Deroover, K.; Heracleous, N.; Lowette, S.; Moortgat, S.; Moreels, L.; Olbrechts, A.; Python, Q.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Parijs, I.; Brun, H.; Caillol, C.; Clerbaux, B.; De Lentdecker, G.; Delannoy, H.; Fasanella, G.; Favart, L.; Goldouzian, R.; Grebenyuk, A.; Karapostoli, G.; Lenzi, T.; Léonard, A.; Luetic, J.; Maerschalk, T.; Marinov, A.; Randle-conde, A.; Seva, T.; Vander Velde, C.; Vanlaer, P.; Yonamine, R.; Zenoni, F.; Zhang, F.; Cimmino, A.; Cornelis, T.; Dobur, D.; Fagot, A.; Garcia, G.; Gul, M.; Poyraz, D.; Salva, S.; Schöfbeck, R.; Sharma, A.; Tytgat, M.; Van Driessche, W.; Yazgan, E.; Zaganidis, N.; Bakhshiansohi, H.; Beluffi, C.; Bondu, O.; Brochet, S.; Bruno, G.; Caudron, A.; De Visscher, S.; Delaere, C.; Delcourt, M.; Francois, B.; Giammanco, A.; Jafari, A.; Jez, P.; Komm, M.; Lemaitre, V.; Magitteri, A.; Mertens, A.; Musich, M.; Nuttens, C.; Piotrzkowski, K.; Quertenmont, L.; Selvaggi, M.; Vidal Marono, M.; Wertz, S.; Beliy, N.; Aldá Júnior, W. L.; Alves, F. L.; Alves, G. A.; Brito, L.; Hensel, C.; Moraes, A.; Pol, M. E.; Rebello Teles, P.; Belchior Batista Das Chagas, E.; Carvalho, W.; Chinellato, J.; Custódio, A.; Da Costa, E. M.; Da Silveira, G. G.; De Jesus Damiao, D.; De Oliveira Martins, C.; Fonseca De Souza, S.; Huertas Guativa, L. M.; Malbouisson, H.; Matos Figueiredo, D.; Mora Herrera, C.; Mundim, L.; Nogima, H.; Prado Da Silva, W. L.; Santoro, A.; Sznajder, A.; Tonelli Manganote, E. J.; Vilela Pereira, A.; Ahuja, S.; Bernardes, C. A.; Dogra, S.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Moon, C. S.; Novaes, S. F.; Padula, Sandra S.; Romero Abad, D.; Ruiz Vargas, J. C.; Aleksandrov, A.; Hadjiiska, R.; Iaydjiev, P.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Vutova, M.; Dimitrov, A.; Glushkov, I.; Litov, L.; Pavlov, B.; Petkov, P.; Fang, W.; Ahmad, M.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Chen, Y.; Cheng, T.; Jiang, C. H.; Leggat, D.; Liu, Z.; Romeo, F.; Shaheen, S. M.; Spiezia, A.; Tao, J.; Wang, C.; Wang, Z.; Zhang, H.; Zhao, J.; Ban, Y.; Chen, G.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Xu, Z.; Avila, C.; Cabrera, A.; Chaparro Sierra, L. F.; Florez, C.; Gomez, J. P.; González Hernández, C. F.; Ruiz Alvarez, J. D.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Puljak, I.; Ribeiro Cipriano, P. M.; Sculac, T.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Ferencek, D.; Kadija, K.; Micanovic, S.; Sudic, L.; Susa, T.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Rykaczewski, H.; Finger, M.; Finger, M.; Carrera Jarrin, E.; Ellithi Kamel, A.; Mahmoud, M. A.; Radi, A.; Calpas, B.; Kadastik, M.; Murumaa, M.; Perrini, L.; Raidal, M.; Tiko, A.; Veelken, C.; Eerola, P.; Pekkanen, J.; Voutilainen, M.; Härkönen, J.; Karimäki, V.; Kinnunen, R.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Tuominiemi, J.; Tuovinen, E.; Wendland, L.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Favaro, C.; Ferri, F.; Ganjour, S.; Ghosh, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Kucher, I.; Locci, E.; Machet, M.; Malcles, J.; Rander, J.; Rosowsky, A.; Titov, M.; Zghiche, A.; Abdulsalam, A.; Antropov, I.; Baffioni, S.; Beaudette, F.; Busson, P.; Cadamuro, L.; Chapon, E.; Charlot, C.; Davignon, O.; Granier de Cassagnac, R.; Jo, M.; Lisniak, S.; Miné, P.; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Pigard, P.; Regnard, S.; Salerno, R.; Sirois, Y.; Strebler, T.; Yilmaz, Y.; Zabi, A.; Agram, J.-L.; Andrea, J.; Aubin, A.; Bloch, D.; Brom, J.-M.; Buttignol, M.; Chabert, E. C.; Chanon, N.; Collard, C.; Conte, E.; Coubez, X.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Le Bihan, A.-C.; Skovpen, K.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Bernet, C.; Boudoul, G.; Bouvier, E.; Carrillo Montoya, C. A.; Chierici, R.; Contardo, D.; Courbon, B.; Depasse, P.; El Mamouni, H.; Fan, J.; Fay, J.; Gascon, S.; Gouzevitch, M.; Grenier, G.; Ille, B.; Lagarde, F.; Laktineh, I. B.; Lethuillier, M.; Mirabito, L.; Pequegnot, A. L.; Perries, S.; Popov, A.; Sabes, D.; Sordini, V.; Vander Donckt, M.; Verdier, P.; Viret, S.; Toriashvili, T.; Rurua, L.; Autermann, C.; Beranek, S.; Feld, L.; Heister, A.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Ostapchuk, A.; Preuten, M.; Raupach, F.; Schael, S.; Schomakers, C.; Schulte, J. F.; Schulz, J.; Verlage, T.; Weber, H.; Zhukov, V.; Brodski, M.; Dietz-Laursonn, E.; Duchardt, D.; Endres, M.; Erdmann, M.; Erdweg, S.; Esch, T.; Fischer, R.; Güth, A.; Hamer, M.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Knutzen, S.; Merschmeyer, M.; Meyer, A.; Millet, P.; Mukherjee, S.; Olschewski, M.; Padeken, K.; Pook, T.; Radziej, M.; Reithler, H.; Rieger, M.; Scheuch, F.; Sonnenschein, L.; Teyssier, D.; Thüer, S.; Cherepanov, V.; Flügge, G.; Haj Ahmad, W.; Hoehle, F.; Kargoll, B.; Kress, T.; Künsken, A.; Lingemann, J.; Müller, T.; Nehrkorn, A.; Nowack, A.; Nugent, I. M.; Pistone, C.; Pooth, O.; Stahl, A.; Aldaya Martin, M.; Asawatangtrakuldee, C.; Beernaert, K.; Behnke, O.; Behrens, U.; Bin Anuar, A. A.; Borras, K.; Campbell, A.; Connor, P.; Contreras-Campana, C.; Costanza, F.; Diez Pardos, C.; Dolinska, G.; Eckerlin, G.; Eckstein, D.; Eren, E.; Gallo, E.; Garay Garcia, J.; Geiser, A.; Gizhko, A.; Grados Luyando, J. M.; Gunnellini, P.; Harb, A.; Hauk, J.; Hempel, M.; Jung, H.; Kalogeropoulos, A.; Karacheban, O.; Kasemann, M.; Keaveney, J.; Kleinwort, C.; Korol, I.; Krücker, D.; Lange, W.; Lelek, A.; Leonard, J.; Lipka, K.; Lobanov, A.; Lohmann, W.; Mankel, R.; Melzer-Pellmann, I.-A.; Meyer, A. B.; Mittag, G.; Mnich, J.; Mussgiller, A.; Ntomari, E.; Pitzl, D.; Placakyte, R.; Raspereza, A.; Roland, B.; Sahin, M. Ö.; Saxena, P.; Schoerner-Sadenius, T.; Seitz, C.; Spannagel, S.; Stefaniuk, N.; Van Onsem, G. P.; Walsh, R.; Wissing, C.; Blobel, V.; Centis Vignali, M.; Draeger, A. R.; Dreyer, T.; Garutti, E.; Gonzalez, D.; Haller, J.; Hoffmann, M.; Junkes, A.; Klanner, R.; Kogler, R.; Kovalchuk, N.; Lapsien, T.; Lenz, T.; Marchesini, I.; Marconi, D.; Meyer, M.; Niedziela, M.; Nowatschin, D.; Pantaleo, F.; Peiffer, T.; Perieanu, A.; Poehlsen, J.; Sander, C.; Scharf, C.; Schleper, P.; Schmidt, A.; Schumann, S.; Schwandt, J.; Stadie, H.; Steinbrück, G.; Stober, F. M.; Stöver, M.; Tholen, H.; Troendle, D.; Usai, E.; Vanelderen, L.; Vanhoefer, A.; Vormwald, B.; Barth, C.; Baus, C.; Berger, J.; Butz, E.; Chwalek, T.; Colombo, F.; De Boer, W.; Dierlamm, A.; Fink, S.; Friese, R.; Giffels, M.; Gilbert, A.; Goldenzweig, P.; Haitz, D.; Hartmann, F.; Heindl, S. M.; Husemann, U.; Katkov, I.; Lobelle Pardo, P.; Maier, B.; Mildner, H.; Mozer, M. U.; Müller, Th.; Plagge, M.; Quast, G.; Rabbertz, K.; Röcker, S.; Roscher, F.; Schröder, M.; Shvetsov, I.; Sieber, G.; Simonis, H. J.; Ulrich, R.; Wagner-Kuhr, J.; Wayand, S.; Weber, M.; Weiler, T.; Williamson, S.; Wöhrmann, C.; Wolf, R.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Giakoumopoulou, V. A.; Kyriakis, A.; Loukas, D.; Topsis-Giotis, I.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Tziaferi, E.; Evangelou, I.; Flouris, G.; Foudas, C.; Kokkas, P.; Loukas, N.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Filipovic, N.; Bencze, G.; Hajdu, C.; Hidas, P.; Horvath, D.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Zsigmond, A. J.; Beni, N.; Czellar, S.; Karancsi, J.; Makovec, A.; Molnar, J.; Szillasi, Z.; Bartók, M.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Bahinipati, S.; Choudhury, S.; Mal, P.; Mandal, K.; Nayak, A.; Sahoo, D. K.; Sahoo, N.; Swain, S. K.; Bansal, S.; Beri, S. B.; Bhatnagar, V.; Chawla, R.; Bhawandeep, U.; Kalsi, A. K.; Kaur, A.; Kaur, M.; Kumar, R.; Mehta, A.; Mittal, M.; Singh, J. B.; Walia, G.; Kumar, Ashok; Bhardwaj, A.; Choudhary, B. C.; Garg, R. B.; Keshri, S.; Malhotra, S.; Naimuddin, M.; Nishu, N.; Ranjan, K.; Sharma, R.; Sharma, V.; Bhattacharya, R.; Bhattacharya, S.; Chatterjee, K.; Dey, S.; Dutt, S.; Dutta, S.; Ghosh, S.; Majumdar, N.; Modak, A.; Mondal, K.; Mukhopadhyay, S.; Nandan, S.; Purohit, A.; Roy, A.; Roy, D.; Roy Chowdhury, S.; Sarkar, S.; Sharan, M.; Thakur, S.; Behera, P. K.; Chudasama, R.; Dutta, D.; Jha, V.; Kumar, V.; Mohanty, A. K.; Netrakanti, P. K.; Pant, L. M.; Shukla, P.; Topkar, A.; Aziz, T.; Dugad, S.; Kole, G.; Mahakud, B.; Mitra, S.; Mohanty, G. B.; Parida, B.; Sur, N.; Sutar, B.; Banerjee, S.; Bhowmik, S.; Dewanjee, R. K.; Ganguly, S.; Guchait, M.; Jain, Sa.; Kumar, S.; Maity, M.; Majumder, G.; Mazumdar, K.; Sarkar, T.; Wickramage, N.; Chauhan, S.; Dube, S.; Hegde, V.; Kapoor, A.; Kothekar, K.; Rane, A.; Sharma, S.; Behnamian, H.; Chenarani, S.; Eskandari Tadavani, E.; Etesami, S. M.; Fahim, A.; Khakzad, M.; Mohammadi Najafabadi, M.; Naseri, M.; Paktinat Mehdiabadi, S.; Rezaei Hosseinabadi, F.; Safarzadeh, B.; Zeinali, M.; Felcini, M.; Grunewald, M.; Abbrescia, M.; Calabria, C.; Caputo, C.; Colaleo, A.; Creanza, D.; Cristella, L.; De Filippis, N.; De Palma, M.; Fiore, L.; Iaselli, G.; Maggi, G.; Maggi, M.; Miniello, G.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Ranieri, A.; Selvaggi, G.; Silvestris, L.; Venditti, R.; Verwilligen, P.; Abbiendi, G.; Battilana, C.; Bonacorsi, D.; Braibant-Giacomelli, S.; Brigliadori, L.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Chhibra, S. S.; Codispoti, G.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Marcellini, S.; Masetti, G.; Montanari, A.; Navarria, F. L.; Perrotta, A.; Rossi, A. M.; Rovelli, T.; Siroli, G. P.; Tosi, N.; Albergo, S.; Chiorboli, M.; Costa, S.; Di Mattia, A.; Giordano, F.; Potenza, R.; Tricomi, A.; Tuve, C.; Barbagli, G.; Ciulli, V.; Civinini, C.; D'Alessandro, R.; Focardi, E.; Gori, V.; Lenzi, P.; Meschini, M.; Paoletti, S.; Sguazzoni, G.; Viliani, L.; Benussi, L.; Bianco, S.; Fabbri, F.; Piccolo, D.; Primavera, F.; Calvelli, V.; Ferro, F.; Lo Vetere, M.; Monge, M. R.; Robutti, E.; Tosi, S.; Brianza, L.; Dinardo, M. E.; Fiorendi, S.; Gennai, S.; Ghezzi, A.; Govoni, P.; Malberti, M.; Malvezzi, S.; Manzoni, R. A.; Marzocchi, B.; Menasce, D.; Moroni, L.; Paganoni, M.; Pedrini, D.; Pigazzini, S.; Ragazzi, S.; Tabarelli de Fatis, T.; Buontempo, S.; Cavallo, N.; De Nardo, G.; Di Guida, S.; Esposito, M.; Fabozzi, F.; Iorio, A. O. M.; Lanza, G.; Lista, L.; Meola, S.; Paolucci, P.; Sciacca, C.; Thyssen, F.; Azzi, P.; Bacchetta, N.; Benato, L.; Bisello, D.; Boletti, A.; Carlin, R.; Carvalho Antunes De Oliveira, A.; Checchia, P.; Dall'Osso, M.; De Castro Manzano, P.; Dorigo, T.; Dosselli, U.; Gasparini, F.; Gasparini, U.; Gozzelino, A.; Lacaprara, S.; Margoni, M.; Meneguzzo, A. T.; Pazzini, J.; Pozzobon, N.; Ronchese, P.; Simonetto, F.; Torassa, E.; Zanetti, M.; Zotto, P.; Zucchetta, A.; Zumerle, G.; Braghieri, A.; Magnani, A.; Montagna, P.; Ratti, S. P.; Re, V.; Riccardi, C.; Salvini, P.; Vai, I.; Vitulo, P.; Alunni Solestizi, L.; Bilei, G. M.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Leonardi, R.; Mantovani, G.; Menichelli, M.; Saha, A.; Santocchia, A.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Bernardini, J.; Boccali, T.; Castaldi, R.; Ciocci, M. A.; Dell'Orso, R.; Donato, S.; Fedi, G.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Lomtadze, T.; Martini, L.; Messineo, A.; Palla, F.; Rizzi, A.; Savoy-Navarro, A.; Spagnolo, P.; Tenchini, R.; Tonelli, G.; Venturi, A.; Verdini, P. G.; Barone, L.; Cavallari, F.; Cipriani, M.; D'imperio, G.; Del Re, D.; Diemoz, M.; Gelli, S.; Longo, E.; Margaroli, F.; Meridiani, P.; Organtini, G.; Paramatti, R.; Preiato, F.; Rahatlou, S.; Rovelli, C.; Santanastasio, F.; Amapane, N.; Arcidiacono, R.; Argiro, S.; Arneodo, M.; Bartosik, N.; Bellan, R.; Biino, C.; Cartiglia, N.; Costa, M.; Cotto, G.; Covarelli, R.; Degano, A.; Demaria, N.; Finco, L.; Kiani, B.; Mariotti, C.; Maselli, S.; Migliore, E.; Monaco, V.; Monteil, E.; Obertino, M. M.; Pacher, L.; Pastrone, N.; Pelliccioni, M.; Pinna Angioni, G. L.; Ravera, F.; Romero, A.; Rotondo, F.; Ruspa, M.; Sacchi, R.; Sola, V.; Solano, A.; Staiano, A.; Traczyk, P.; Belforte, S.; Casarsa, M.; Cossutti, F.; Della Ricca, G.; La Licata, C.; Schizzi, A.; Zanetti, A.; Kim, D. H.; Kim, G. N.; Kim, M. S.; Lee, S.; Lee, S. W.; Oh, Y. 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F.; Mucia, N.; Odell, N.; Pollack, B.; Schmitt, M. H.; Sung, K.; Trovato, M.; Velasco, M.; Dev, N.; Hildreth, M.; Hurtado Anampa, K.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Marinelli, N.; Meng, F.; Mueller, C.; Musienko, Y.; Planer, M.; Reinsvold, A.; Ruchti, R.; Smith, G.; Taroni, S.; Wayne, M.; Wolf, M.; Woodard, A.; Alimena, J.; Antonelli, L.; Brinson, J.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Francis, B.; Hart, A.; Hill, C.; Hughes, R.; Ji, W.; Liu, B.; Luo, W.; Puigh, D.; Winer, B. L.; Wulsin, H. W.; Cooperstein, S.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Lange, D.; Luo, J.; Marlow, D.; Medvedeva, T.; Mei, K.; Mooney, M.; Olsen, J.; Palmer, C.; Piroué, P.; Stickland, D.; Tully, C.; Zuranski, A.; Malik, S.; Barker, A.; Barnes, V. E.; Folgueras, S.; Gutay, L.; Jha, M. K.; Jones, M.; Jung, A. W.; Jung, K.; Miller, D. H.; Neumeister, N.; Shi, X.; Sun, J.; Svyatkovskiy, A.; Wang, F.; Xie, W.; Xu, L.; Parashar, N.; Stupak, J.; Adair, A.; Akgun, B.; Chen, Z.; Ecklund, K. M.; Geurts, F. J. M.; Guilbaud, M.; Li, W.; Michlin, B.; Northup, M.; Padley, B. P.; Redjimi, R.; Roberts, J.; Rorie, J.; Tu, Z.; Zabel, J.; Betchart, B.; Bodek, A.; de Barbaro, P.; Demina, R.; Duh, Y. t.; Ferbel, T.; Galanti, M.; Garcia-Bellido, A.; Han, J.; Hindrichs, O.; Khukhunaishvili, A.; Lo, K. H.; Tan, P.; Verzetti, M.; Agapitos, A.; Chou, J. P.; Contreras-Campana, E.; Gershtein, Y.; Gómez Espinosa, T. A.; Halkiadakis, E.; Heindl, M.; Hidas, D.; Hughes, E.; Kaplan, S.; Kunnawalkam Elayavalli, R.; Kyriacou, S.; Lath, A.; Nash, K.; Saka, H.; Salur, S.; Schnetzer, S.; Sheffield, D.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Foerster, M.; Heideman, J.; Riley, G.; Rose, K.; Spanier, S.; Thapa, K.; Bouhali, O.; Celik, A.; Dalchenko, M.; De Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Gilmore, J.; Huang, T.; Juska, E.; Kamon, T.; Mueller, R.; Pakhotin, Y.; Patel, R.; Perloff, A.; Perniè, L.; Rathjens, D.; Rose, A.; Safonov, A.; Tatarinov, A.; Ulmer, K. A.; Akchurin, N.; Cowden, C.; Damgov, J.; De Guio, F.; Dragoiu, C.; Dudero, P. R.; Faulkner, J.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Libeiro, T.; Peltola, T.; Undleeb, S.; Volobouev, I.; Wang, Z.; Delannoy, A. G.; Greene, S.; Gurrola, A.; Janjam, R.; Johns, W.; Maguire, C.; Melo, A.; Ni, H.; Sheldon, P.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Barria, P.; Cox, B.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Li, H.; Neu, C.; Sinthuprasith, T.; Sun, X.; Wang, Y.; Wolfe, E.; Xia, F.; Clarke, C.; Harr, R.; Karchin, P. E.; Lamichhane, P.; Sturdy, J.; Belknap, D. A.; Dasu, S.; Dodd, L.; Duric, S.; Gomber, B.; Grothe, M.; Herndon, M.; Hervé, A.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Ojalvo, I.; Perry, T.; Polese, G.; Ruggles, T.; Savin, A.; Smith, N.; Smith, W. H.; Taylor, D.; Woods, N.; CMS Collaboration

2017-05-01

A search for narrow resonances in dielectron and dimuon invariant mass spectra has been performed using data obtained from proton-proton collisions at √{ s} = 13 TeV collected with the CMS detector. The integrated luminosity for the dielectron sample is 2.7 fb-1 and for the dimuon sample 2.9 fb-1. The sensitivity of the search is increased by combining these data with a previously analyzed set of data obtained at √{ s} = 8 TeV and corresponding to a luminosity of 20 fb-1. No evidence for non-standard-model physics is found, either in the 13 TeV data set alone, or in the combined data set. Upper limits on the product of production cross section and branching fraction have also been calculated in a model-independent manner to enable interpretation in models predicting a narrow dielectron or dimuon resonance structure. Limits are set on the masses of hypothetical particles that could appear in new-physics scenarios. For the ZSSM‧ particle, which arises in the sequential standard model, and for the superstring inspired Zψ‧ particle, 95% confidence level lower mass limits for the combined data sets and combined channels are found to be 3.37 and 2.82 TeV, respectively. The corresponding limits for the lightest Kaluza-Klein graviton arising in the Randall-Sundrum model of extra dimensions with coupling parameters 0.01 and 0.10 are 1.46 and 3.11 TeV, respectively. These results significantly exceed the limits based on the 8 TeV LHC data.

Search for narrow resonances in dilepton mass spectra in proton-proton collisions at $$\\sqrt{s}$$ = 13 TeV and combination with 8 TeV data

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

Khachatryan, Vardan

A search for narrow resonances in dielectron and dimuon invariant mass spectra has been performed using data obtained from proton-proton collisions atmore » $$ \\sqrt{s} = $$ 13 TeV collected with the CMS detector. The integrated luminosity for the dielectron sample is 2.7 fb$$^{-1}$$ and for the dimuon sample 2.9 fb$$^{-1}$$. The sensitivity of the search is increased by combining these data with a previously analysed set of data obtained at $$ \\sqrt{s} = $$ 8 TeV and corresponding to a luminosity of 20 fb$$^{-1}$$. No evidence for non-standard-model physics is found, either in the 13 TeV data set alone, or in the combined data set. Upper limits on the product of production cross section and branching fraction have also been calculated in a model-independent manner to enable interpretation in models predicting a narrow dielectron or dimuon resonance structure. Limits are set on the masses of hypothetical particles that could appear in new-physics scenarios. For the $$\\mathrm{Z}'_{\\text{SSM}}$$ particle, which arises in the sequential standard model, and for the superstring inspired $$\\mathrm{Z}'_{\\psi}$$ particle, 95% confidence level lower mass limits for the combined data sets and combined channels are found to be 3.37 and 2.82 TeV, respectively. The corresponding limits for Kaluza-Klein gravitons arising in the Randall-Sundrum model of extra dimensions with coupling parameters 0.01 and 0.10 are 1.46 and 3.11 TeV, respectively. Lastly, these results significantly extend previous limits.« less

Search for narrow resonances in dilepton mass spectra in proton-proton collisions at $$\\sqrt{s}$$ = 13 TeV and combination with 8 TeV data

DOE PAGES

Khachatryan, Vardan

2017-02-14

A search for narrow resonances in dielectron and dimuon invariant mass spectra has been performed using data obtained from proton-proton collisions atmore » $$ \\sqrt{s} = $$ 13 TeV collected with the CMS detector. The integrated luminosity for the dielectron sample is 2.7 fb$$^{-1}$$ and for the dimuon sample 2.9 fb$$^{-1}$$. The sensitivity of the search is increased by combining these data with a previously analysed set of data obtained at $$ \\sqrt{s} = $$ 8 TeV and corresponding to a luminosity of 20 fb$$^{-1}$$. No evidence for non-standard-model physics is found, either in the 13 TeV data set alone, or in the combined data set. Upper limits on the product of production cross section and branching fraction have also been calculated in a model-independent manner to enable interpretation in models predicting a narrow dielectron or dimuon resonance structure. Limits are set on the masses of hypothetical particles that could appear in new-physics scenarios. For the $$\\mathrm{Z}'_{\\text{SSM}}$$ particle, which arises in the sequential standard model, and for the superstring inspired $$\\mathrm{Z}'_{\\psi}$$ particle, 95% confidence level lower mass limits for the combined data sets and combined channels are found to be 3.37 and 2.82 TeV, respectively. The corresponding limits for Kaluza-Klein gravitons arising in the Randall-Sundrum model of extra dimensions with coupling parameters 0.01 and 0.10 are 1.46 and 3.11 TeV, respectively. Lastly, these results significantly extend previous limits.« less

Independent test assessment using the extreme value distribution theory.

PubMed

Almeida, Marcio; Blondell, Lucy; Peralta, Juan M; Kent, Jack W; Jun, Goo; Teslovich, Tanya M; Fuchsberger, Christian; Wood, Andrew R; Manning, Alisa K; Frayling, Timothy M; Cingolani, Pablo E; Sladek, Robert; Dyer, Thomas D; Abecasis, Goncalo; Duggirala, Ravindranath; Blangero, John

2016-01-01

The new generation of whole genome sequencing platforms offers great possibilities and challenges for dissecting the genetic basis of complex traits. With a very high number of sequence variants, a naïve multiple hypothesis threshold correction hinders the identification of reliable associations by the overreduction of statistical power. In this report, we examine 2 alternative approaches to improve the statistical power of a whole genome association study to detect reliable genetic associations. The approaches were tested using the Genetic Analysis Workshop 19 (GAW19) whole genome sequencing data. The first tested method estimates the real number of effective independent tests actually being performed in whole genome association project by the use of an extreme value distribution and a set of phenotype simulations. Given the familiar nature of the GAW19 data and the finite number of pedigree founders in the sample, the number of correlations between genotypes is greater than in a set of unrelated samples. Using our procedure, we estimate that the effective number represents only 15 % of the total number of independent tests performed. However, even using this corrected significance threshold, no genome-wide significant association could be detected for systolic and diastolic blood pressure traits. The second approach implements a biological relevance-driven hypothesis tested by exploiting prior computational predictions on the effect of nonsynonymous genetic variants detected in a whole genome sequencing association study. This guided testing approach was able to identify 2 promising single-nucleotide polymorphisms (SNPs), 1 for each trait, targeting biologically relevant genes that could help shed light on the genesis of the human hypertension. The first gene, PFH14 , associated with systolic blood pressure, interacts directly with genes involved in calcium-channel formation and the second gene, MAP4 , encodes a microtubule-associated protein and had already been detected by previous genome-wide association study experiments conducted in an Asian population. Our results highlight the necessity of the development of alternative approached to improve the efficiency on the detection of reasonable candidate associations in whole genome sequencing studies.

Multinomial Logistic Regression & Bootstrapping for Bayesian Estimation of Vertical Facies Prediction in Heterogeneous Sandstone Reservoirs

NASA Astrophysics Data System (ADS)

Al-Mudhafar, W. J.

2013-12-01

Precisely prediction of rock facies leads to adequate reservoir characterization by improving the porosity-permeability relationships to estimate the properties in non-cored intervals. It also helps to accurately identify the spatial facies distribution to perform an accurate reservoir model for optimal future reservoir performance. In this paper, the facies estimation has been done through Multinomial logistic regression (MLR) with respect to the well logs and core data in a well in upper sandstone formation of South Rumaila oil field. The entire independent variables are gamma rays, formation density, water saturation, shale volume, log porosity, core porosity, and core permeability. Firstly, Robust Sequential Imputation Algorithm has been considered to impute the missing data. This algorithm starts from a complete subset of the dataset and estimates sequentially the missing values in an incomplete observation by minimizing the determinant of the covariance of the augmented data matrix. Then, the observation is added to the complete data matrix and the algorithm continues with the next observation with missing values. The MLR has been chosen to estimate the maximum likelihood and minimize the standard error for the nonlinear relationships between facies & core and log data. The MLR is used to predict the probabilities of the different possible facies given each independent variable by constructing a linear predictor function having a set of weights that are linearly combined with the independent variables by using a dot product. Beta distribution of facies has been considered as prior knowledge and the resulted predicted probability (posterior) has been estimated from MLR based on Baye's theorem that represents the relationship between predicted probability (posterior) with the conditional probability and the prior knowledge. To assess the statistical accuracy of the model, the bootstrap should be carried out to estimate extra-sample prediction error by randomly drawing datasets with replacement from the training data. Each sample has the same size of the original training set and it can be conducted N times to produce N bootstrap datasets to re-fit the model accordingly to decrease the squared difference between the estimated and observed categorical variables (facies) leading to decrease the degree of uncertainty.

Performance Evaluation of an Improved GC-MS Method to Quantify Methylmercury in Fish.

PubMed

Watanabe, Takahiro; Kikuchi, Hiroyuki; Matsuda, Rieko; Hayashi, Tomoko; Akaki, Koichi; Teshima, Reiko

2015-01-01

Here, we set out to improve our previously developed methylmercury analytical method, involving phenyl derivatization and gas chromatography-mass spectrometry (GC-MS). In the improved method, phenylation of methylmercury with sodium tetraphenylborate was carried out in a toluene/water two-phase system, instead of in water alone. The modification enabled derivatization at optimum pH, and the formation of by-products was dramatically reduced. In addition, adsorption of methyl phenyl mercury in the GC system was suppressed by co-injection of PEG200, enabling continuous analysis without loss of sensitivity. The performance of the improved analytical method was independently evaluated by three analysts using certified reference materials and methylmercury-spiked fresh fish samples. The present analytical method was validated as suitable for determination of compliance with the provisional regulation value for methylmercury in fish, set in the Food Sanitation haw.

College Women's Feminist Identity: A Multidimensional Analysis with Implications for Coping with Sexism.

PubMed

Leaper, Campbell; Arias, Diana M

2011-04-01

This study examined components of women's feminist identity and possible relations to their reported coping responses to sexism. A sample of 169 undergraduate women (M = 19.4 y, SD = 1.2) from diverse ethnic backgrounds completed surveys assessing their experiences and gender-related views. The first set of analyses revealed that women's social gender identity, exposure to feminism, and gender-egalitarian attitudes independently contributed to feminist identification; moreover, non-stereotyping of feminists further predicted feminist self-identification. A second set of analyses tested the relative contribution of feminist identity components to women's cognitive appraisals of coping responses to sexual harassment. Seeking social support was predicted by self-identification as a feminist (for White European American women only). Confronting was predicted by social gender identity, non-stereotyping of feminists, and public identification as a feminist. Findings highlight possible components of women's feminist identity and their possible impact on coping responses to sexism.

Detection of periodicity based on independence tests - III. Phase distance correlation periodogram

NASA Astrophysics Data System (ADS)

Zucker, Shay

2018-02-01

I present the Phase Distance Correlation (PDC) periodogram - a new periodicity metric, based on the Distance Correlation concept of Gábor Székely. For each trial period, PDC calculates the distance correlation between the data samples and their phases. PDC requires adaptation of the Székely's distance correlation to circular variables (phases). The resulting periodicity metric is best suited to sparse data sets, and it performs better than other methods for sawtooth-like periodicities. These include Cepheid and RR-Lyrae light curves, as well as radial velocity curves of eccentric spectroscopic binaries. The performance of the PDC periodogram in other contexts is almost as good as that of the Generalized Lomb-Scargle periodogram. The concept of phase distance correlation can be adapted also to astrometric data, and it has the potential to be suitable also for large evenly spaced data sets, after some algorithmic perfection.

Validation of national land-cover characteristics data for regional water-quality assessment

USGS Publications Warehouse

Zelt, Ronald B.; Brown, Jesslyn F.; Kelley, M.S.

1995-01-01

Land-cover information is used routinely to support the interpretation of water-quality data. The Prototype 1990 Conterminous US Land Cover Characteristics Data Set, developed primarily from Advanced Very High Resolution Radiometer (AVHRR) data, was made available to the US Geological Survey's National Water-Quality Assessment (NAWQA) Program. The study described in this paper explored the utility of the 1990 national data set for developing quantitative estimates of the areal extent of principal land-cover types within large areal units. Land-cover data were collected in 1993 at 210 sites in the Central Nebraska Basins, one of the NAWQA study units. Median percentage-corn estimates for each sampling stratum wre used to produce areally weighted estimates of the percentage-corn cover for hydrologic units. Comparison of those areal estimates with an independent source of 1992 land-cover data showed good agreement. -Authors

Disordered eating, socio-cultural media influencers, body image, and psychological factors among a racially/ethnically diverse population of college women

PubMed Central

Quick, Virginia M.; Byrd-Bredbenner, Carol

2013-01-01

This study examined disordered eating, socio-cultural media influencers, body image, and psychological factors among a large, racially/ethnically diverse sample of college women (n=1445; 58% White, 21% Asian, 11% Hispanic, 11% Black) who completed an online survey. Black women were significantly more satisfied with their weight and shape and had lower eating concerns, disinhibited eating, and emotional eating than all other racial/ethnic groups. Black women tended to have significantly higher levels of self-esteem, were less likely to compare their body to those of people in the media, felt less pressured to attain the physical appearance standard set by the media, and had less awareness of the societal appearance norms set by the media than other racial groups. Findings suggest that Black college women, independent of weight status, may be protected from disordered eating, negative body image, and societal media pressures. PMID:24411747

Disordered eating, socio-cultural media influencers, body image, and psychological factors among a racially/ethnically diverse population of college women.

PubMed

Quick, Virginia M; Byrd-Bredbenner, Carol

2014-01-01

This study examined disordered eating, socio-cultural media influencers, body image, and psychological factors among a large, racially/ethnically diverse sample of college women (n=1445; 58% White, 21% Asian, 11% Hispanic, 11% Black) who completed an online survey. Black women were significantly more satisfied with their weight and shape and had lower eating concerns, disinhibited eating, and emotional eating than all other racial/ethnic groups. Black women tended to have significantly higher levels of self-esteem, were less likely to compare their body to those of people in the media, felt less pressured to attain the physical appearance standard set by the media, and had less awareness of the societal appearance norms set by the media than other racial groups. Findings suggest that Black college women, independent of weight status, may be protected from disordered eating, negative body image, and societal media pressures. © 2013.

Search for microscopic black holes in pp collisions at $$ \\sqrt{s}=8 $$ TeV

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

Chatrchyan, S.; Khachatryan, V.; Sirunyan, A. M.

2013-07-01

A search for microscopic black holes and string balls is presented, based on a data sample of pp collisions at sqrt(s) = 8 TeV recorded by the CMS experiment at the Large Hadron Collider and corresponding to an integrated luminosity of 12 inverse femtobarns. No excess of events with energetic multiparticle final states, typical of black hole production or of similar new physics processes, is observed. Given the agreement of the observations with the expected standard model background, which is dominated by QCD multijet production, 95% confidence limits are set on the production of semiclassical or quantum black holes, ormore » of string balls, corresponding to the exclusions of masses below 4.3 to 6.2 TeV, depending on model assumptions. In addition, model-independent limits are set on new physics processes resulting in energetic multiparticle final states.« less

A Voltammetric Electronic Tongue for the Resolution of Ternary Nitrophenol Mixtures

PubMed Central

González-Calabuig, Andreu; Cetó, Xavier

2018-01-01

This work reports the applicability of a voltammetric sensor array able to quantify the content of 2,4-dinitrophenol, 4-nitrophenol, and picric acid in artificial samples using the electronic tongue (ET) principles. The ET is based on cyclic voltammetry signals, obtained from an array of metal disk electrodes and a graphite epoxy composite electrode, compressed using discrete wavelet transform with chemometric tools such as artificial neural networks (ANNs). ANNs were employed to build the quantitative prediction model. In this manner, a set of standards based on a full factorial design, ranging from 0 to 300 mg·L−1, was prepared to build the model; afterward, the model was validated with a completely independent set of standards. The model successfully predicted the concentration of the three considered phenols with a normalized root mean square error of 0.030 and 0.076 for the training and test subsets, respectively, and r ≥ 0.948. PMID:29342848

A New Electromagnetic Instrument for Thickness Gauging of Conductive Materials

NASA Technical Reports Server (NTRS)

Fulton, J. P.; Wincheski, B.; Nath, S.; Reilly, J.; Namkung, M.

1994-01-01

Eddy current techniques are widely used to measure the thickness of electrically conducting materials. The approach, however, requires an extensive set of calibration standards and can be quite time consuming to set up and perform. Recently, an electromagnetic sensor was developed which eliminates the need for impedance measurements. The ability to monitor the magnitude of a voltage output independent of the phase enables the use of extremely simple instrumentation. Using this new sensor a portable hand-held instrument was developed. The device makes single point measurements of the thickness of nonferromagnetic conductive materials. The technique utilized by this instrument requires calibration with two samples of known thicknesses that are representative of the upper and lower thickness values to be measured. The accuracy of the instrument depends upon the calibration range, with a larger range giving a larger error. The measured thicknesses are typically within 2-3% of the calibration range (the difference between the thin and thick sample) of their actual values. In this paper the design, operational and performance characteristics of the instrument along with a detailed description of the thickness gauging algorithm used in the device are presented.

Deep Hashing for Scalable Image Search.

PubMed

Lu, Jiwen; Liong, Venice Erin; Zhou, Jie

2017-05-01

In this paper, we propose a new deep hashing (DH) approach to learn compact binary codes for scalable image search. Unlike most existing binary codes learning methods, which usually seek a single linear projection to map each sample into a binary feature vector, we develop a deep neural network to seek multiple hierarchical non-linear transformations to learn these binary codes, so that the non-linear relationship of samples can be well exploited. Our model is learned under three constraints at the top layer of the developed deep network: 1) the loss between the compact real-valued code and the learned binary vector is minimized, 2) the binary codes distribute evenly on each bit, and 3) different bits are as independent as possible. To further improve the discriminative power of the learned binary codes, we extend DH into supervised DH (SDH) and multi-label SDH by including a discriminative term into the objective function of DH, which simultaneously maximizes the inter-class variations and minimizes the intra-class variations of the learned binary codes with the single-label and multi-label settings, respectively. Extensive experimental results on eight widely used image search data sets show that our proposed methods achieve very competitive results with the state-of-the-arts.

Estimating biodiversity of fungi in activated sludge communities using culture-independent methods.

PubMed

Evans, Tegan N; Seviour, Robert J

2012-05-01

Fungal diversity of communities in several activated sludge plants treating different influent wastes was determined by comparative sequence analyses of their 18S rRNA genes. Methods for DNA extraction and choice of primers for PCR amplification were both optimised using denaturing gradient gel electrophoresis profile patterns. Phylogenetic analysis revealed that the levels of fungal biodiversity in some communities, like those treating paper pulp wastes, were low, and most of the fungi detected in all communities examined were novel uncultured representatives of the major fungal subdivisions, in particular, the newly described clade Cryptomycota. The fungal populations in activated sludge revealed by these culture-independent methods were markedly different to those based on culture-dependent data. Members of the genera Penicillium, Cladosporium, Aspergillus and Mucor, which have been commonly identified in mixed liquor, were not identified in any of these plant communities. Non-fungal eukaryotic 18S rRNA genes were also amplified with the primer sets used. This is the first report where culture-independent methods have been applied to flocculated activated sludge biomass samples to estimate fungal community composition and, as expected, the data obtained gave a markedly different view of their population biodiversity compared to that based on culture-dependent methods.

Detecting macroecological patterns in bacterial communities across independent studies of global soils.

PubMed

Ramirez, Kelly S; Knight, Christopher G; de Hollander, Mattias; Brearley, Francis Q; Constantinides, Bede; Cotton, Anne; Creer, Si; Crowther, Thomas W; Davison, John; Delgado-Baquerizo, Manuel; Dorrepaal, Ellen; Elliott, David R; Fox, Graeme; Griffiths, Robert I; Hale, Chris; Hartman, Kyle; Houlden, Ashley; Jones, David L; Krab, Eveline J; Maestre, Fernando T; McGuire, Krista L; Monteux, Sylvain; Orr, Caroline H; van der Putten, Wim H; Roberts, Ian S; Robinson, David A; Rocca, Jennifer D; Rowntree, Jennifer; Schlaeppi, Klaus; Shepherd, Matthew; Singh, Brajesh K; Straathof, Angela L; Bhatnagar, Jennifer M; Thion, Cécile; van der Heijden, Marcel G A; de Vries, Franciska T

2018-02-01

The emergence of high-throughput DNA sequencing methods provides unprecedented opportunities to further unravel bacterial biodiversity and its worldwide role from human health to ecosystem functioning. However, despite the abundance of sequencing studies, combining data from multiple individual studies to address macroecological questions of bacterial diversity remains methodically challenging and plagued with biases. Here, using a machine-learning approach that accounts for differences among studies and complex interactions among taxa, we merge 30 independent bacterial data sets comprising 1,998 soil samples from 21 countries. Whereas previous meta-analysis efforts have focused on bacterial diversity measures or abundances of major taxa, we show that disparate amplicon sequence data can be combined at the taxonomy-based level to assess bacterial community structure. We find that rarer taxa are more important for structuring soil communities than abundant taxa, and that these rarer taxa are better predictors of community structure than environmental factors, which are often confounded across studies. We conclude that combining data from independent studies can be used to explore bacterial community dynamics, identify potential 'indicator' taxa with an important role in structuring communities, and propose hypotheses on the factors that shape bacterial biogeography that have been overlooked in the past.

46 CFR 129.315 - Power sources for OSVs of 100 or more gross tons.

Code of Federal Regulations, 2010 CFR

2010-10-01

... VESSELS ELECTRICAL INSTALLATIONS Power Sources and Distribution Systems § 129.315 Power sources for OSVs... one set must be independent of the main propulsion plant. A generator not independent of the main propulsion plant must comply with § 111.10-4(d) of this chapter. With any one generating set stopped, the...

Autonomous water sampling for long-term monitoring of trace metals in remote environments.

PubMed

Kim, Hyojin; Bishop, James K B; Wood, Todd J; Fung, Inez Y

2012-10-16

A remotely controlled autonomous method for long-term high-frequency sampling of environmental waters in remote locations is described. The method which preserves sample integrity of dissolved trace metals and major ions for month-long periods employs a gravitational filtration system (GFS) that separates dissolved and particulate phases as samples are collected. The key elements of GFS are (1) a modified "air-outlet" filter holder to maximize filtration rate and thus minimize filtration artifacts; and (2) the direct delivery of filtrate to dedicated bottle sets for specific analytes. Depth and screen filter types were evaluated with depth filters showing best performance. GFS performance is validated using ground, stream, and estuary waters. Over 30 days of storage, samples with GFS treatment had average recoveries of 95 ± 19% and 105 ± 7% of Fe and Mn, respectively; without GFS treatment, average recoveries were only 16% and 18%. Dissolved major cations K, Mg, and Na were stable independent of collection methodology, whereas Ca in some groundwater samples decreased up to 42% without GFS due to CaCO(3) precipitation. In-field performance of GFS equipped autosamplers is demonstrated using ground and streamwater samples collected at the Angelo Coast Range Reserve, California from October 3 to November 4 2011.

[Genetic aspects of species structure of the compost worm Eisenia foetida (Sav.) (Oligochaeta, Lumbricidae)].

PubMed

Bolotetskiĭ, N M; Kodolova, O P

2002-01-01

Distribution of frequencies alleles of polymorphous loci of peroxidase (Pox), leucineaminopeptidase (Lap), phosphoglucomutase (Pgm) and octanoldehydrogenase (Odh) were studied by electrophoresis in polyacrylamide gel in 22 local samples of Esenia foetida in Russia (European part), Ukraine, Kazakhstan and Kirghizia. The samples form two spatial groups--"northern" and "southern", distinguished by set of alleles in every studied locus. The "northern" groups is formed by local populations of European Russia from Murmansk region on the north to Smolensk region on the south, and also by cultivated population of selection line "red California hybrid". The "southern" group is formed by local populations on the territory of Russia from middle Volga to the North Caucasus, Ukraine, Kazakhstan, Kirghizia, cultivated populations from Kirghizia and Portugal. High degree of genetic difference between samples and independence of alleles frequencies distribution from geographical location and habitat allows to consider almost all studied groups as separate populations. Statistical processing of Nei genetic distances (Nei, 1972) revealed reliable differences between averages of within- and intergroup distances. Besides, discrete differences between intervals of significance of genetic distances were revealed. The results indicate that on the studied territory E. foetida has hierarchical two level structure. The first level is formed by local populations differed by frequency of the same alleles. The second level is formed by local populations, united into spatial groups, that are qualitatively distinguished by the set of alleles in the same loci.

SDSS-II SUPERNOVA SURVEY: AN ANALYSIS OF THE LARGEST SAMPLE OF TYPE IA SUPERNOVAE AND CORRELATIONS WITH HOST-GALAXY SPECTRAL PROPERTIES

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

Wolf, Rachel C.; Gupta, Ravi R.; Sako, Masao

2016-04-20

Using the largest single-survey sample of Type Ia supernovae (SNe Ia) to date, we study the relationship between properties of SNe Ia and those of their host galaxies, focusing primarily on correlations with Hubble residuals (HRs). Our sample consists of 345 photometrically classified or spectroscopically confirmed SNe Ia discovered as part of the SDSS-II Supernova Survey (SDSS-SNS). This analysis utilizes host-galaxy spectroscopy obtained during the SDSS-I/II spectroscopic survey and from an ancillary program on the SDSS-III Baryon Oscillation Spectroscopic Survey that obtained spectra for nearly all host galaxies of SDSS-II SN candidates. In addition, we use photometric host-galaxy properties frommore » the SDSS-SNS data release such as host stellar mass and star formation rate. We confirm the well-known relation between HR and host-galaxy mass and find a 3.6 σ significance of a nonzero linear slope. We also recover correlations between HR and host-galaxy gas-phase metallicity and specific star formation rate as they are reported in the literature. With our large data set, we examine correlations between HR and multiple host-galaxy properties simultaneously and find no evidence of a significant correlation. We also independently analyze our spectroscopically confirmed and photometrically classified SNe Ia and comment on the significance of similar combined data sets for future surveys.« less

Diagnostic performance enhancement of pancreatic cancer using proteomic multimarker panel

PubMed Central

Namkung, Junghyun; Yi, Sung Gon; Kim, Hyunsoo; Yu, Jiyoung; Kim, Yongkang; Kwon, Min-Seok; Kwon, Wooil; Oh, Do-Youn; Kim, Sun-Whe; Jeong, Seung-Yong; Han, Wonshik; Lee, Kyu Eun; Heo, Jin Seok; Park, Joon Oh; Park, Joo Kyung; Kim, Song Cheol; Kang, Chang Moo; Lee, Woo Jin; Lee, Seungyeoun; Han, Sangjo; Park, Taesung; Jang, Jin-Young; Kim, Youngsoo

2017-01-01

Due to its high mortality rate and asymptomatic nature, early detection rates of pancreatic ductal adenocarcinoma (PDAC) remain poor. We measured 1000 biomarker candidates in 134 clinical plasma samples by multiple reaction monitoring-mass spectrometry (MRM-MS). Differentially abundant proteins were assembled into a multimarker panel from a training set (n=684) and validated in independent set (n=318) from five centers. The level of panel proteins was also confirmed by immunoassays. The panel including leucine-rich alpha-2 glycoprotein (LRG1), transthyretin (TTR), and CA19-9 had a sensitivity of 82.5% and a specificity of 92.1%. The triple-marker panel exceeded the diagnostic performance of CA19-9 by more than 10% (AUCCA19-9 = 0.826, AUCpanel= 0.931, P < 0.01) in all PDAC samples and by more than 30% (AUCCA19-9 = 0.520, AUCpanel = 0.830, P < 0.001) in patients with normal range of CA19-9 (<37U/mL). Further, it differentiated PDAC from benign pancreatic disease (AUCCA19-9 = 0.812, AUCpanel = 0.892, P < 0.01) and other cancers (AUCCA19-9 = 0.796, AUCpanel = 0.899, P < 0.001). Overall, the multimarker panel that we have developed and validated in large-scale samples by MRM-MS and immunoassay has clinical applicability in the early detection of PDAC. PMID:29190982

Comparison of Bolton analysis and Little’s irregularity index on laser scanned three-dimensional digital study models with conventional study models

NASA Astrophysics Data System (ADS)

Kurnia, H.; Noerhadi, N. A. I.

2017-08-01

Three-dimensional digital study models were introduced following advances in digital technology. This study was carried out to assess the reliability of digital study models scanned by a laser scanning device newly assembled. The aim of this study was to compare the digital study models and conventional models. Twelve sets of dental impressions were taken from patients with mild-to-moderate crowding. The impressions were taken twice, one with alginate and the other with polyvinylsiloxane. The alginate impressions were made into conventional models, and the polyvinylsiloxane impressions were scanned to produce digital models. The mesiodistal tooth width and Little’s irregularity index (LII) were measured manually with digital calipers on the conventional models and digitally on the digital study models. Bolton analysis was performed on each study models. Each method was carried out twice to check for intra-observer variability. The reproducibility (comparison of the methods) was assessed using independent-sample t-tests. The mesiodistal tooth width between conventional and digital models did not significantly differ (p > 0.05). Independent-sample t-tests did not identify statistically significant differences for Bolton analysis and LII (p = 0.603 for Bolton and p = 0894 for LII). The measurements of the digital study models are as accurate as those of the conventional models.

A Serum Protein Profile Predictive of the Resistance to Neoadjuvant Chemotherapy in Advanced Breast Cancers*

PubMed Central

Hyung, Seok-Won; Lee, Min Young; Yu, Jong-Han; Shin, Byunghee; Jung, Hee-Jung; Park, Jong-Moon; Han, Wonshik; Lee, Kyung-Min; Moon, Hyeong-Gon; Zhang, Hui; Aebersold, Ruedi; Hwang, Daehee; Lee, Sang-Won; Yu, Myeong-Hee; Noh, Dong-Young

2011-01-01

Prediction of the responses to neoadjuvant chemotherapy (NACT) can improve the treatment of patients with advanced breast cancer. Genes and proteins predictive of chemoresistance have been extensively studied in breast cancer tissues. However, noninvasive serum biomarkers capable of such prediction have been rarely exploited. Here, we performed profiling of N-glycosylated proteins in serum from fifteen advanced breast cancer patients (ten patients sensitive to and five patients resistant to NACT) to discover serum biomarkers of chemoresistance using a label-free liquid chromatography-tandem MS method. By performing a series of statistical analyses of the proteomic data, we selected thirteen biomarker candidates and tested their differential serum levels by Western blotting in 13 independent samples (eight patients sensitive to and five patients resistant to NACT). Among the candidates, we then selected the final set of six potential serum biomarkers (AHSG, APOB, C3, C9, CP, and ORM1) whose differential expression was confirmed in the independent samples. Finally, we demonstrated that a multivariate classification model using the six proteins could predict responses to NACT and further predict relapse-free survival of patients. In summary, global N-glycoproteome profile in serum revealed a protein pattern predictive of the responses to NACT, which can be further validated in large clinical studies. PMID:21799047

Food- and health-related correlates of self-reported body mass index among low-income mothers of young children

PubMed Central

McCurdy, Karen; Kisler, Tiffani; Gorman, Kathleen S.; Metallinos-Katsaras, Elizabeth

2015-01-01

Objective Examine how income-related challenges around food and health are associated with variation in self-reported maternal body weight among low-income mothers. Design Cross-sectional, correlational design. Convenience sample recruited from 7 daycare centers and a Supplemental Nutrition Assistance Program outreach project. Maternal self-report data collected between October 2009 and May 2011. Setting Two Northeastern cities. Participants Sample of 166 mothers; 67% overweight or obese, 55% Hispanic, 42% reporting household food insecurity (HFI). Main Outcome Measures Maternal self-reported height and weight to calculate Body Mass Index (BMI). Independent variables: food program participation, supermarket use, 8-item food shopping practices scale, HFI, maternal depressive symptoms, self-rated health (SRH). Analysis Hierarchical multiple regression analysis tested relationships between maternal BMI with the independent variables of interest, adjusting for demographic confounds. Results Shopping practices to stretch food dollars (P = .04), using community food assistance programs (P < .05), and HFI (P < .04) correlated with heavier maternal BMIs; higher SRH corresponded to lower BMIs (P =.004). Conclusions and Implications Some strategies low-income mothers use to manage food resources are associated with heavier BMIs. Nutrition educators, public health practitioners, and researchers need to collaboratively address the associations between these strategies, food insecurity, poor health, and unhealthy weight. PMID:25794991

Targeted plasma proteomics identifies a novel, robust association between cornulin and Swedish moist snuff.

PubMed

Sundkvist, Anneli; Myte, Robin; Bodén, Stina; Enroth, Stefan; Gyllensten, Ulf; Harlid, Sophia; van Guelpen, Bethany

2018-02-02

Lifestyle behaviors are believed to influence the body's inflammatory state. Chronic low-grade inflammation contributes to the development of major non-communicable diseases such as diabetes, cardiovascular disease and cancer. Inflammation may thus be an important link between lifestyle and disease. We evaluated self-reported physical activity, tobacco use and alcohol consumption in relation to plasma levels of 160 validated inflammatory and cancer biomarkers. The study included 138 participants from a population-based cohort, all with repeated sampling of plasma and data ten years apart, allowing consideration of both intra- and inter-individual variation. Of 17 relationships identified, the strongest was an independent, positive association between cornulin (CRNN) and Swedish moist snuff (snus) use. We replicated the finding in a second cohort of 501 individuals, in which a dose-response relationship was also observed. Snus explained approximately one fifth of the variance in CRNN levels in both sample sets (18% and 23%). In conclusion, we identified a novel, independent, dose-dependent association between CRNN and snus use. Further study is warranted, to evaluate the performance of CRNN as a potential snus biomarker. The putative importance of lifestyle behaviors on a wide range of protein biomarkers illustrates the need for more personalized biomarker cut-offs.

Small-mammal density estimation: A field comparison of grid-based vs. web-based density estimators

USGS Publications Warehouse

Parmenter, R.R.; Yates, Terry L.; Anderson, D.R.; Burnham, K.P.; Dunnum, J.L.; Franklin, A.B.; Friggens, M.T.; Lubow, B.C.; Miller, M.; Olson, G.S.; Parmenter, Cheryl A.; Pollard, J.; Rexstad, E.; Shenk, T.M.; Stanley, T.R.; White, Gary C.

2003-01-01

Statistical models for estimating absolute densities of field populations of animals have been widely used over the last century in both scientific studies and wildlife management programs. To date, two general classes of density estimation models have been developed: models that use data sets from capture–recapture or removal sampling techniques (often derived from trapping grids) from which separate estimates of population size (NÌ‚) and effective sampling area (AÌ‚) are used to calculate density (DÌ‚ = NÌ‚/AÌ‚); and models applicable to sampling regimes using distance-sampling theory (typically transect lines or trapping webs) to estimate detection functions and densities directly from the distance data. However, few studies have evaluated these respective models for accuracy, precision, and bias on known field populations, and no studies have been conducted that compare the two approaches under controlled field conditions. In this study, we evaluated both classes of density estimators on known densities of enclosed rodent populations. Test data sets (n = 11) were developed using nine rodent species from capture–recapture live-trapping on both trapping grids and trapping webs in four replicate 4.2-ha enclosures on the Sevilleta National Wildlife Refuge in central New Mexico, USA. Additional “saturation” trapping efforts resulted in an enumeration of the rodent populations in each enclosure, allowing the computation of true densities. Density estimates (DÌ‚) were calculated using program CAPTURE for the grid data sets and program DISTANCE for the web data sets, and these results were compared to the known true densities (D) to evaluate each model's relative mean square error, accuracy, precision, and bias. In addition, we evaluated a variety of approaches to each data set's analysis by having a group of independent expert analysts calculate their best density estimates without a priori knowledge of the true densities; this “blind” test allowed us to evaluate the influence of expertise and experience in calculating density estimates in comparison to simply using default values in programs CAPTURE and DISTANCE. While the rodent sample sizes were considerably smaller than the recommended minimum for good model results, we found that several models performed well empirically, including the web-based uniform and half-normal models in program DISTANCE, and the grid-based models Mb and Mbh in program CAPTURE (with AÌ‚ adjusted by species-specific full mean maximum distance moved (MMDM) values). These models produced accurate DÌ‚ values (with 95% confidence intervals that included the true D values) and exhibited acceptable bias but poor precision. However, in linear regression analyses comparing each model's DÌ‚ values to the true D values over the range of observed test densities, only the web-based uniform model exhibited a regression slope near 1.0; all other models showed substantial slope deviations, indicating biased estimates at higher or lower density values. In addition, the grid-based DÌ‚ analyses using full MMDM values for WÌ‚ area adjustments required a number of theoretical assumptions of uncertain validity, and we therefore viewed their empirical successes with caution. Finally, density estimates from the independent analysts were highly variable, but estimates from web-based approaches had smaller mean square errors and better achieved confidence-interval coverage of D than did grid-based approaches. Our results support the contention that web-based approaches for density estimation of small-mammal populations are both theoretically and empirically superior to grid-based approaches, even when sample size is far less than often recommended. In view of the increasing need for standardized environmental measures for comparisons among ecosystems and through time, analytical models based on distance sampling appear to offer accurate density estimation approaches for research studies involving small-mammal abundances.

The rural community care gerontologic nurse entrepreneur: role development strategies.

PubMed

Caffrey, Rosalie A

2005-10-01

Rural elderly individuals are an underserved population with limited access to health care. There is an increasing need for independent community care nurses to provide assistance to home-based elderly individuals with chronic illnesses to prevent unnecessary medical and placement decisions and, thus, allow them to maintain independence and quality of life. This article describes the rural setting and why community care nurses are needed, and explores strategies for implementing the role of the independent nurse entrepreneur in caring for community-based elderly individuals in rural settings.

Use of a fishery-independent trawl survey to evaluate distribution patterns of subadult sharks in Georgia

USGS Publications Warehouse

Belcher, C.N.; Jennings, Cecil A.

2009-01-01

We investigated the utility of a fishery-independent trawl survey for assessing a potential multispecies shark nursery in Georgia's nearshore and inshore waters. A total of 234 subadult sharks from six species were captured during 85 of 216 trawls. Catch rates and size distributions for subadult sharks and the ratio of neonates to juveniles were consistent among areas. The highest concentrations of subadult sharks occurred in creeks and sounds. Species composition varied among areas. The Atlantic sharpnose shark Rhizoprionodon terraenovae was the most abundant species in sound and nearshore stations, whereas the bonnethead Sphyrna tiburo was the most abundant species in creeks. The aggregate of other species occurred with higher frequency in the sounds and nearshore. Sampling characteristics of the trawl survey were compared with those from a fishery-independent longline survey of subadult sharks to assess the similarity of the two gears. A total of 193 subadult sharks from seven species were captured during 57 of 96 longline sets, whereas 52 subadults from four species were captured during 20 of 48 trawls. Selectivity and efficiency differed between the two gears. The trawl had lower catch rates, caught smaller sharks, and encountered a different suite of species than the longline. General seasonal trends in relative abundance also differed between the two gears; the longline showed an increasing trend in abundance, whereas the trawl showed a stable trend. Although trawls were not found to be efficient for sampling subadult sharks from most species, they can be a useful source of supplemental data.

The effectiveness of family-based treatment for full and partial adolescent anorexia nervosa in an independent private practice setting: Clinical outcomes.

PubMed

Goldstein, Mandy; Murray, Stuart B; Griffiths, Scott; Rayner, Kathryn; Podkowka, Jessica; Bateman, Joel E; Wallis, Andrew; Thornton, Christopher E

2016-11-01

Anorexia nervosa (AN) is a severe psychiatric illness with little evidence supporting treatment in adults. Among adolescents with AN, family-based treatment (FBT) is considered first-line outpatient approach, with a growing evidence base. However, research on FBT has stemmed from specialist services in research/public health settings. This study investigated the effectiveness of FBT in a case series of adolescent AN treated in a private practice setting. Thirty-four adolescents with full or partial AN, diagnosed according to DSM-IV criteria, participated, and were assessed at pretreatment and post-treatment. Assessments included change in % expected body weight, mood, and eating pathology. Significant weight gain was observed from pretreatment to post-treatment. 45.9% of the sample demonstrated full weight restoration and a further 43.2% achieved partial weight-based remission. Missing data precluded an examination of change in mood and ED psychopathology. Effective dissemination across different service types is important to the wider availability of evidence-based treatments. These weight restoration data lend preliminary support to the implementation of FBT in real world treatment settings. © 2016 Wiley Periodicals, Inc. (Int J Eat Disord 2016; 49:1023-1026). © 2016 Wiley Periodicals, Inc.

"Theory Becoming Alive": The Learning Transition Process of Newly Graduated Nurses in Canada.

PubMed

Nour, Violet; Williams, Anne M

2018-01-01

Background Newly graduated nurses often encounter a gap between theory and practice in clinical settings. Although this has been the focus of considerable research, little is known about the learning transition process. Purpose The purpose of this study was to explore the experiences of newly graduated nurses in acute healthcare settings within Canada. This study was conducted to gain a greater understanding of the experiences and challenges faced by graduates. Methods Grounded theory method was utilized with a sample of 14 registered nurses who were employed in acute-care settings. Data were collected using in-depth interviews. Constant comparative analysis was used to analyze data. Results Findings revealed a core category, "Theory Becoming Alive," and four supporting categories: Entry into Practice, Immersion, Committing, and Evolving. Theory Becoming Alive described the process of new graduate nurses' clinical learning experiences as well as the challenges that they encountered in clinical settings after graduating. Conclusions This research provides a greater understanding of learning process of new graduate nurses in Canada. It highlights the importance of providing supportive environments to assist new graduate nurses to develop confidence as independent registered nurses in clinical areas. Future research directions as well as supportive educational strategies are described.

A pilot cluster randomized controlled trial of structured goal-setting following stroke.

PubMed

Taylor, William J; Brown, Melanie; William, Levack; McPherson, Kathryn M; Reed, Kirk; Dean, Sarah G; Weatherall, Mark

2012-04-01

To determine the feasibility, the cluster design effect and the variance and minimal clinical importance difference in the primary outcome in a pilot study of a structured approach to goal-setting. A cluster randomized controlled trial. Inpatient rehabilitation facilities. People who were admitted to inpatient rehabilitation following stroke who had sufficient cognition to engage in structured goal-setting and complete the primary outcome measure. Structured goal elicitation using the Canadian Occupational Performance Measure. Quality of life at 12 weeks using the Schedule for Individualised Quality of Life (SEIQOL-DW), Functional Independence Measure, Short Form 36 and Patient Perception of Rehabilitation (measuring satisfaction with rehabilitation). Assessors were blinded to the intervention. Four rehabilitation services and 41 patients were randomized. We found high values of the intraclass correlation for the outcome measures (ranging from 0.03 to 0.40) and high variance of the SEIQOL-DW (SD 19.6) in relation to the minimally importance difference of 2.1, leading to impractically large sample size requirements for a cluster randomized design. A cluster randomized design is not a practical means of avoiding contamination effects in studies of inpatient rehabilitation goal-setting. Other techniques for coping with contamination effects are necessary.

An automatic flow system for NIR screening analysis of liquefied petroleum gas with respect to propane content.

PubMed

Dantas, Hebertty V; Barbosa, Mayara F; Nascimento, Elaine C L; Moreira, Pablo N T; Galvão, Roberto K H; Araújo, Mário C U

2013-03-15

This paper proposes a NIR spectrometric method for screening analysis of liquefied petroleum gas (LPG) samples. The proposed method is aimed at discriminating samples with low and high propane content, which can be useful for the adjustment of burn settings in industrial applications. A gas flow system was developed to introduce the LPG sample into a NIR flow cell at constant pressure. In addition, a gas chromatographer was employed to determine the propane content of the sample for reference purposes. The results of a principal component analysis, as well as a classification study using SIMCA (soft independent modeling of class analogies), revealed that the samples can be successfully discriminated with respect to propane content by using the NIR spectrum in the range 8100-8800 cm(-1). In addition, by using SPA-LDA (linear discriminant analysis with variables selected by the successive projections algorithm), it was found that perfect discrimination can also be achieved by using only two wavenumbers (8215 and 8324 cm(-1)). This finding may be of value for the design of a dedicated, low-cost instrument for routine analyses. Copyright © 2012 Elsevier B.V. All rights reserved.

Estimation of the rain signal in the presence of large surface clutter

NASA Technical Reports Server (NTRS)

Ahamad, Atiq; Moore, Richard K.

1994-01-01

The principal limitation for the use of a spaceborne imaging SAR as a rain radar is the surface-clutter problem. Signals may be estimated in the presence of noise by averaging large numbers of independent samples. This method was applied to obtain an estimate of the rain echo by averaging a set of N(sub c) samples of the clutter in a separate measurement and subtracting the clutter estimate from the combined estimate. The number of samples required for successful estimation (within 10-20%) for off-vertical angles of incidence appears to be prohibitively large. However, by appropriately degrading the resolution in both range and azimuth, the required number of samples can be obtained. For vertical incidence, the number of samples required for successful estimation is reasonable. In estimating the clutter it was assumed that the surface echo is the same outside the rain volume as it is within the rain volume. This may be true for the forest echo, but for convective storms over the ocean the surface echo outside the rain volume is very different from that within. It is suggested that the experiment be performed with vertical incidence over forest to overcome this limitation.

Submillisecond X-ray photon correlation spectroscopy from a pixel array detector with fast dual gating and no readout dead-time

DOE PAGES

Zhang, Qingteng; Dufresne, Eric M.; Grybos, Pawel; ...

2016-04-19

Small-angle scattering X-ray photon correlation spectroscopy (XPCS) studies were performed using a novel photon-counting pixel array detector with dual counters for each pixel. Each counter can be read out independently from the other to ensure there is no readout dead-time between the neighboring frames. A maximum frame rate of 11.8 kHz was achieved. Results on test samples show good agreement with simple diffusion. Lastly, the potential of extending the time resolution of XPCS beyond the limit set by the detector frame rate using dual counters is also discussed.

Submillisecond X-ray photon correlation spectroscopy from a pixel array detector with fast dual gating and no readout dead-time

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

Zhang, Qingteng; Dufresne, Eric M.; Grybos, Pawel

Small-angle scattering X-ray photon correlation spectroscopy (XPCS) studies were performed using a novel photon-counting pixel array detector with dual counters for each pixel. Each counter can be read out independently from the other to ensure there is no readout dead-time between the neighboring frames. A maximum frame rate of 11.8 kHz was achieved. Results on test samples show good agreement with simple diffusion. Lastly, the potential of extending the time resolution of XPCS beyond the limit set by the detector frame rate using dual counters is also discussed.

Nano-metrology and terrain modelling - convergent practice in surface characterisation

USGS Publications Warehouse

Pike, R.J.

2000-01-01

The quantification of magnetic-tape and disk topography has a macro-scale counterpart in the Earth sciences - terrain modelling, the numerical representation of relief and pattern of the ground surface. The two practices arose independently and continue to function separately. This methodological paper introduces terrain modelling, discusses its similarities to and differences from industrial surface metrology, and raises the possibility of a unified discipline of quantitative surface characterisation. A brief discussion of an Earth-science problem, subdividing a heterogeneous terrain surface from a set of sample measurements, exemplifies a multivariate statistical procedure that may transfer to tribological applications of 3-D metrological height data.

Submillisecond X-ray photon correlation spectroscopy from a pixel array detector with fast dual gating and no readout dead-time.

PubMed

Zhang, Qingteng; Dufresne, Eric M; Grybos, Pawel; Kmon, Piotr; Maj, Piotr; Narayanan, Suresh; Deptuch, Grzegorz W; Szczygiel, Robert; Sandy, Alec

2016-05-01

Small-angle scattering X-ray photon correlation spectroscopy (XPCS) studies were performed using a novel photon-counting pixel array detector with dual counters for each pixel. Each counter can be read out independently from the other to ensure there is no readout dead-time between the neighboring frames. A maximum frame rate of 11.8 kHz was achieved. Results on test samples show good agreement with simple diffusion. The potential of extending the time resolution of XPCS beyond the limit set by the detector frame rate using dual counters is also discussed.

Availability and capacity of substance abuse programs in correctional settings: A classification and regression tree analysis.

PubMed

Taxman, Faye S; Kitsantas, Panagiota

2009-08-01

OBJECTIVE TO BE ADDRESSED: The purpose of this study was to investigate the structural and organizational factors that contribute to the availability and increased capacity for substance abuse treatment programs in correctional settings. We used classification and regression tree statistical procedures to identify how multi-level data can explain the variability in availability and capacity of substance abuse treatment programs in jails and probation/parole offices. The data for this study combined the National Criminal Justice Treatment Practices (NCJTP) Survey and the 2000 Census. The NCJTP survey was a nationally representative sample of correctional administrators for jails and probation/parole agencies. The sample size included 295 substance abuse treatment programs that were classified according to the intensity of their services: high, medium, and low. The independent variables included jurisdictional-level structural variables, attributes of the correctional administrators, and program and service delivery characteristics of the correctional agency. The two most important variables in predicting the availability of all three types of services were stronger working relationships with other organizations and the adoption of a standardized substance abuse screening tool by correctional agencies. For high and medium intensive programs, the capacity increased when an organizational learning strategy was used by administrators and the organization used a substance abuse screening tool. Implications on advancing treatment practices in correctional settings are discussed, including further work to test theories on how to better understand access to intensive treatment services. This study presents the first phase of understanding capacity-related issues regarding treatment programs offered in correctional settings.

A method and knowledge base for automated inference of patient problems from structured data in an electronic medical record.

PubMed

Wright, Adam; Pang, Justine; Feblowitz, Joshua C; Maloney, Francine L; Wilcox, Allison R; Ramelson, Harley Z; Schneider, Louise I; Bates, David W

2011-01-01

Accurate knowledge of a patient's medical problems is critical for clinical decision making, quality measurement, research, billing and clinical decision support. Common structured sources of problem information include the patient problem list and billing data; however, these sources are often inaccurate or incomplete. To develop and validate methods of automatically inferring patient problems from clinical and billing data, and to provide a knowledge base for inferring problems. We identified 17 target conditions and designed and validated a set of rules for identifying patient problems based on medications, laboratory results, billing codes, and vital signs. A panel of physicians provided input on a preliminary set of rules. Based on this input, we tested candidate rules on a sample of 100,000 patient records to assess their performance compared to gold standard manual chart review. The physician panel selected a final rule for each condition, which was validated on an independent sample of 100,000 records to assess its accuracy. Seventeen rules were developed for inferring patient problems. Analysis using a validation set of 100,000 randomly selected patients showed high sensitivity (range: 62.8-100.0%) and positive predictive value (range: 79.8-99.6%) for most rules. Overall, the inference rules performed better than using either the problem list or billing data alone. We developed and validated a set of rules for inferring patient problems. These rules have a variety of applications, including clinical decision support, care improvement, augmentation of the problem list, and identification of patients for research cohorts.

Fine Mapping on Chromosome 13q32–34 and Brain Expression Analysis Implicates MYO16 in Schizophrenia

PubMed Central

Rodriguez-Murillo, Laura; Xu, Bin; Roos, J Louw; Abecasis, Gonçalo R; Gogos, Joseph A; Karayiorgou, Maria

2014-01-01

We previously reported linkage of schizophrenia and schizoaffective disorder to 13q32–34 in the European descent Afrikaner population from South Africa. The nature of genetic variation underlying linkage peaks in psychiatric disorders remains largely unknown and both rare and common variants may be contributing. Here, we examine the contribution of common variants located under the 13q32–34 linkage region. We used densely spaced SNPs to fine map the linkage peak region using both a discovery sample of 415 families and a meta-analysis incorporating two additional replication family samples. In a second phase of the study, we use one family-based data set with 237 families and independent case–control data sets for fine mapping of the common variant association signal using HapMap SNPs. We report a significant association with a genetic variant (rs9583277) within the gene encoding for the myosin heavy-chain Myr 8 (MYO16), which has been implicated in neuronal phosphoinositide 3-kinase signaling. Follow-up analysis of HapMap variation within MYO16 in a second set of Afrikaner families and additional case–control data sets of European descent highlighted a region across introns 2–6 as the most likely region to harbor common MYO16 risk variants. Expression analysis revealed a significant increase in the level of MYO16 expression in the brains of schizophrenia patients. Our results suggest that common variation within MYO16 may contribute to the genetic liability to schizophrenia. PMID:24141571

C-reactive protein as a marker of melanoma progression.

PubMed

Fang, Shenying; Wang, Yuling; Sui, Dawen; Liu, Huey; Ross, Merrick I; Gershenwald, Jeffrey E; Cormier, Janice N; Royal, Richard E; Lucci, Anthony; Schacherer, Christopher W; Gardner, Julie M; Reveille, John D; Bassett, Roland L; Wang, Li-E; Wei, Qingyi; Amos, Christopher I; Lee, Jeffrey E

2015-04-20

To investigate the association between blood levels of C-reactive protein (CRP) in patients with melanoma and overall survival (OS), melanoma-specific survival (MSS), and disease-free survival. Two independent sets of plasma samples from a total of 1,144 patients with melanoma (587 initial and 557 confirmatory) were available for CRP determination. Kaplan-Meier method and Cox regression were used to evaluate the relationship between CRP and clinical outcome. Among 115 patients who underwent sequential blood draws, we evaluated the relationship between change in disease status and change in CRP using nonparametric tests. Elevated CRP level was associated with poorer OS and MSS in the initial, confirmatory, and combined data sets (combined data set: OS hazard ratio, 1.44 per unit increase of logarithmic CRP; 95% CI, 1.30 to 1.59; P < .001; MSS hazard ratio, 1.51 per unit increase of logarithmic CRP; 95% CI, 1.36 to 1.68; P < .001). These findings persisted after multivariable adjustment. As compared with CRP < 10 mg/L, CRP ≥ 10 mg/L conferred poorer OS in patients with any-stage, stage I/II, or stage III/IV disease and poorer disease-free survival in those with stage I/II disease. In patients who underwent sequential evaluation of CRP, an association was identified between an increase in CRP and melanoma disease progression. CRP is an independent prognostic marker in patients with melanoma. CRP measurement should be considered for incorporation into prospective studies of outcome in patients with melanoma and clinical trials of systemic therapies for those with melanoma. © 2015 by American Society of Clinical Oncology.

C-Reactive Protein As a Marker of Melanoma Progression

PubMed Central

Fang, Shenying; Wang, Yuling; Sui, Dawen; Liu, Huey; Ross, Merrick I.; Gershenwald, Jeffrey E.; Cormier, Janice N.; Royal, Richard E.; Lucci, Anthony; Schacherer, Christopher W.; Gardner, Julie M.; Reveille, John D.; Bassett, Roland L.; Wang, Li-E; Wei, Qingyi; Amos, Christopher I.; Lee, Jeffrey E.

2015-01-01

Purpose To investigate the association between blood levels of C-reactive protein (CRP) in patients with melanoma and overall survival (OS), melanoma-specific survival (MSS), and disease-free survival. Patients and Methods Two independent sets of plasma samples from a total of 1,144 patients with melanoma (587 initial and 557 confirmatory) were available for CRP determination. Kaplan-Meier method and Cox regression were used to evaluate the relationship between CRP and clinical outcome. Among 115 patients who underwent sequential blood draws, we evaluated the relationship between change in disease status and change in CRP using nonparametric tests. Results Elevated CRP level was associated with poorer OS and MSS in the initial, confirmatory, and combined data sets (combined data set: OS hazard ratio, 1.44 per unit increase of logarithmic CRP; 95% CI, 1.30 to 1.59; P < .001; MSS hazard ratio, 1.51 per unit increase of logarithmic CRP; 95% CI, 1.36 to 1.68; P < .001). These findings persisted after multivariable adjustment. As compared with CRP < 10 mg/L, CRP ≥ 10 mg/L conferred poorer OS in patients with any-stage, stage I/II, or stage III/IV disease and poorer disease-free survival in those with stage I/II disease. In patients who underwent sequential evaluation of CRP, an association was identified between an increase in CRP and melanoma disease progression. Conclusion CRP is an independent prognostic marker in patients with melanoma. CRP measurement should be considered for incorporation into prospective studies of outcome in patients with melanoma and clinical trials of systemic therapies for those with melanoma. PMID:25779565

Sample reproducibility of genetic association using different multimarker TDTs in genome-wide association studies: characterization and a new approach.

PubMed

Abad-Grau, Mara M; Medina-Medina, Nuria; Montes-Soldado, Rosana; Matesanz, Fuencisla; Bafna, Vineet

2012-01-01

Multimarker Transmission/Disequilibrium Tests (TDTs) are very robust association tests to population admixture and structure which may be used to identify susceptibility loci in genome-wide association studies. Multimarker TDTs using several markers may increase power by capturing high-degree associations. However, there is also a risk of spurious associations and power reduction due to the increase in degrees of freedom. In this study we show that associations found by tests built on simple null hypotheses are highly reproducible in a second independent data set regardless the number of markers. As a test exhibiting this feature to its maximum, we introduce the multimarker 2-Groups TDT (mTDT(2G)), a test which under the hypothesis of no linkage, asymptotically follows a χ2 distribution with 1 degree of freedom regardless the number of markers. The statistic requires the division of parental haplotypes into two groups: disease susceptibility and disease protective haplotype groups. We assessed the test behavior by performing an extensive simulation study as well as a real-data study using several data sets of two complex diseases. We show that mTDT(2G) test is highly efficient and it achieves the highest power among all the tests used, even when the null hypothesis is tested in a second independent data set. Therefore, mTDT(2G) turns out to be a very promising multimarker TDT to perform genome-wide searches for disease susceptibility loci that may be used as a preprocessing step in the construction of more accurate genetic models to predict individual susceptibility to complex diseases.

Sample Reproducibility of Genetic Association Using Different Multimarker TDTs in Genome-Wide Association Studies: Characterization and a New Approach

PubMed Central

Abad-Grau, Mara M.; Medina-Medina, Nuria; Montes-Soldado, Rosana; Matesanz, Fuencisla; Bafna, Vineet

2012-01-01

Multimarker Transmission/Disequilibrium Tests (TDTs) are very robust association tests to population admixture and structure which may be used to identify susceptibility loci in genome-wide association studies. Multimarker TDTs using several markers may increase power by capturing high-degree associations. However, there is also a risk of spurious associations and power reduction due to the increase in degrees of freedom. In this study we show that associations found by tests built on simple null hypotheses are highly reproducible in a second independent data set regardless the number of markers. As a test exhibiting this feature to its maximum, we introduce the multimarker -Groups TDT ( ), a test which under the hypothesis of no linkage, asymptotically follows a distribution with degree of freedom regardless the number of markers. The statistic requires the division of parental haplotypes into two groups: disease susceptibility and disease protective haplotype groups. We assessed the test behavior by performing an extensive simulation study as well as a real-data study using several data sets of two complex diseases. We show that test is highly efficient and it achieves the highest power among all the tests used, even when the null hypothesis is tested in a second independent data set. Therefore, turns out to be a very promising multimarker TDT to perform genome-wide searches for disease susceptibility loci that may be used as a preprocessing step in the construction of more accurate genetic models to predict individual susceptibility to complex diseases. PMID:22363405

Perianth organization and intra-specific floral variability.

PubMed

Herrera, J; Arista, M; Ortiz, P L

2008-11-01

Floral symmetry and fusion of perianth parts are factors that contribute to fine-tune the match between flowers and their animal pollination vectors. In the present study, we investigated whether the possession of a sympetalous (fused) corolla and bilateral symmetry of flowers translate into decreased intra-specific variability as a result of natural stabilizing selection exerted by pollinators. Average size of the corolla and intra-specific variability were determined in two sets of southern Spanish entomophilous plant species. In the first set, taxa were paired by family to control for the effect of phylogeny (phylogenetically independent contrasts), whereas in the second set species were selected at random. Flower size data from a previous study (with different species) were also used to test the hypothesis that petal fusion contributes to decrease intra-specific variability. In the phylogenetically independent contrasts, floral symmetry was a significant correlate of intra-specific variation, with bilaterally symmetrical flowers showing more constancy than radially symmetrical flowers (i.e. unsophisticated from a functional perspective). As regards petal fusion, species with fused petals were on average more constant than choripetalous species, but the difference was not statistically significant. The reanalysis of data from a previous study yielded largely similar results, with a distinct effect of symmetry on variability, but no effect of petal fusion. The randomly-chosen species sample, on the other hand, failed to reveal any significant effect of either symmetry or petal fusion on intra-specific variation. The problem of low-statistical power in this kind of analysis, and the difficulty of testing an evolutionary hypothesis that involves phenotypic traits with a high degree of morphological correlation is discussed.

Accuracy of microRNAs as markers for the detection of neck lymph node metastases in patients with head and neck squamous cell carcinoma.

PubMed

de Carvalho, Ana Carolina; Scapulatempo-Neto, Cristovam; Maia, Danielle Calheiros Campelo; Evangelista, Adriane Feijó; Morini, Mariana Andozia; Carvalho, André Lopes; Vettore, André Luiz

2015-05-09

The presence of metastatic disease in cervical lymph nodes of head and neck squamous cell carcinoma (HNSCC) patients is a very important determinant in therapy choice and prognosis, with great impact in overall survival. Frequently, routine lymph node staging cannot detect occult metastases and the post-surgical histologic evaluation of resected lymph nodes is not sensitive in detecting small metastatic deposits. Molecular markers based on tissue-specific microRNA expression are alternative accurate diagnostic markers. Herein, we evaluated the feasibility of using the expression of microRNAs to detect metastatic cells in formalin-fixed paraffin-embedded (FFPE) lymph nodes and in fine-needle aspiration (FNA) biopsies of HNSCC patients. An initial screening compared the expression of 667 microRNAs in a discovery set comprised by metastatic and non-metastatic lymph nodes from HNSCC patients. The most differentially expressed microRNAs were validated by qRT-PCR in two independent cohorts: i) 48 FFPE lymph node samples, and ii) 113 FNA lymph node biopsies. The accuracy of the markers in identifying metastatic samples was assessed through the analysis of sensitivity, specificity, accuracy, negative predictive value, positive predictive value, and area under the curve values. Seven microRNAs highly expressed in metastatic lymph nodes from the discovery set were validated in FFPE lymph node samples. MiR-203 and miR-205 identified all metastatic samples, regardless of the size of the metastatic deposit. Additionally, these markers also showed high accuracy when FNA samples were examined. The high accuracy of miR-203 and miR-205 warrant these microRNAs as diagnostic markers of neck metastases in HNSCC. These can be evaluated in entire lymph nodes and in FNA biopsies collected at different time-points such as pre-treatment samples, intraoperative sentinel node biopsy, and during patient follow-up. These markers can be useful in a clinical setting in the management of HNSCC patients from initial disease staging and therapy planning to patient surveillance.

Spectral gene set enrichment (SGSE).

PubMed

Frost, H Robert; Li, Zhigang; Moore, Jason H

2015-03-03

Gene set testing is typically performed in a supervised context to quantify the association between groups of genes and a clinical phenotype. In many cases, however, a gene set-based interpretation of genomic data is desired in the absence of a phenotype variable. Although methods exist for unsupervised gene set testing, they predominantly compute enrichment relative to clusters of the genomic variables with performance strongly dependent on the clustering algorithm and number of clusters. We propose a novel method, spectral gene set enrichment (SGSE), for unsupervised competitive testing of the association between gene sets and empirical data sources. SGSE first computes the statistical association between gene sets and principal components (PCs) using our principal component gene set enrichment (PCGSE) method. The overall statistical association between each gene set and the spectral structure of the data is then computed by combining the PC-level p-values using the weighted Z-method with weights set to the PC variance scaled by Tracy-Widom test p-values. Using simulated data, we show that the SGSE algorithm can accurately recover spectral features from noisy data. To illustrate the utility of our method on real data, we demonstrate the superior performance of the SGSE method relative to standard cluster-based techniques for testing the association between MSigDB gene sets and the variance structure of microarray gene expression data. Unsupervised gene set testing can provide important information about the biological signal held in high-dimensional genomic data sets. Because it uses the association between gene sets and samples PCs to generate a measure of unsupervised enrichment, the SGSE method is independent of cluster or network creation algorithms and, most importantly, is able to utilize the statistical significance of PC eigenvalues to ignore elements of the data most likely to represent noise.

Molecular cancer classification using a meta-sample-based regularized robust coding method.

PubMed

Wang, Shu-Lin; Sun, Liuchao; Fang, Jianwen

2014-01-01

Previous studies have demonstrated that machine learning based molecular cancer classification using gene expression profiling (GEP) data is promising for the clinic diagnosis and treatment of cancer. Novel classification methods with high efficiency and prediction accuracy are still needed to deal with high dimensionality and small sample size of typical GEP data. Recently the sparse representation (SR) method has been successfully applied to the cancer classification. Nevertheless, its efficiency needs to be improved when analyzing large-scale GEP data. In this paper we present the meta-sample-based regularized robust coding classification (MRRCC), a novel effective cancer classification technique that combines the idea of meta-sample-based cluster method with regularized robust coding (RRC) method. It assumes that the coding residual and the coding coefficient are respectively independent and identically distributed. Similar to meta-sample-based SR classification (MSRC), MRRCC extracts a set of meta-samples from the training samples, and then encodes a testing sample as the sparse linear combination of these meta-samples. The representation fidelity is measured by the l2-norm or l1-norm of the coding residual. Extensive experiments on publicly available GEP datasets demonstrate that the proposed method is more efficient while its prediction accuracy is equivalent to existing MSRC-based methods and better than other state-of-the-art dimension reduction based methods.

Joint use of over- and under-sampling techniques and cross-validation for the development and assessment of prediction models.

PubMed

Blagus, Rok; Lusa, Lara

2015-11-04

Prediction models are used in clinical research to develop rules that can be used to accurately predict the outcome of the patients based on some of their characteristics. They represent a valuable tool in the decision making process of clinicians and health policy makers, as they enable them to estimate the probability that patients have or will develop a disease, will respond to a treatment, or that their disease will recur. The interest devoted to prediction models in the biomedical community has been growing in the last few years. Often the data used to develop the prediction models are class-imbalanced as only few patients experience the event (and therefore belong to minority class). Prediction models developed using class-imbalanced data tend to achieve sub-optimal predictive accuracy in the minority class. This problem can be diminished by using sampling techniques aimed at balancing the class distribution. These techniques include under- and oversampling, where a fraction of the majority class samples are retained in the analysis or new samples from the minority class are generated. The correct assessment of how the prediction model is likely to perform on independent data is of crucial importance; in the absence of an independent data set, cross-validation is normally used. While the importance of correct cross-validation is well documented in the biomedical literature, the challenges posed by the joint use of sampling techniques and cross-validation have not been addressed. We show that care must be taken to ensure that cross-validation is performed correctly on sampled data, and that the risk of overestimating the predictive accuracy is greater when oversampling techniques are used. Examples based on the re-analysis of real datasets and simulation studies are provided. We identify some results from the biomedical literature where the incorrect cross-validation was performed, where we expect that the performance of oversampling techniques was heavily overestimated.

Evaluating the power to detect temporal trends in fishery-independent time surveys: A case study based on gill nets set in the Ohio waters of Lake Erie for walleyes

USGS Publications Warehouse

Wagner, Tyler; Vandergoot, Christopher S.; Tyson, Jeff

2011-01-01

Fishery-independent (FI) surveys provide critical information used for the sustainable management and conservation of fish populations. Because fisheries management often requires the effects of management actions to be evaluated and detected within a relatively short time frame, it is important that research be directed toward FI survey evaluation, especially with respect to the ability to detect temporal trends. Using annual FI gill-net survey data for Lake Erie walleyes Sander vitreus collected from 1978 to 2006 as a case study, our goals were to (1) highlight the usefulness of hierarchical models for estimating spatial and temporal sources of variation in catch per effort (CPE); (2) demonstrate how the resulting variance estimates can be used to examine the statistical power to detect temporal trends in CPE in relation to sample size, duration of sampling, and decisions regarding what data are most appropriate for analysis; and (3) discuss recommendations for evaluating FI surveys and analyzing the resulting data to support fisheries management. This case study illustrated that the statistical power to detect temporal trends was low over relatively short sampling periods (e.g., 5–10 years) unless the annual decline in CPE reached 10–20%. For example, if 50 sites were sampled each year, a 10% annual decline in CPE would not be detected with more than 0.80 power until 15 years of sampling, and a 5% annual decline would not be detected with more than 0.8 power for approximately 22 years. Because the evaluation of FI surveys is essential for ensuring that trends in fish populations can be detected over management-relevant time periods, we suggest using a meta-analysis–type approach across systems to quantify sources of spatial and temporal variation. This approach can be used to evaluate and identify sampling designs that increase the ability of managers to make inferences about trends in fish stocks.

Evaluating the power to detect temporal trends in fishery independent surveys: A case study based on Gillnets Set in the Ohio waters of Lake Erie for walleye

USGS Publications Warehouse

Wagner, Tyler; Vandergoot, Christopher S.; Tyson, Jeff

2009-01-01

Fishery-independent (FI) surveys provide critical information used for the sustainable management and conservation of fish populations. Because fisheries management often requires the effects of management actions to be evaluated and detected within a relatively short time frame, it is important that research be directed toward FI survey evaluation, especially with respect to the ability to detect temporal trends. Using annual FI gill-net survey data for Lake Erie walleyes Sander vitreus collected from 1978 to 2006 as a case study, our goals were to (1) highlight the usefulness of hierarchical models for estimating spatial and temporal sources of variation in catch per effort (CPE); (2) demonstrate how the resulting variance estimates can be used to examine the statistical power to detect temporal trends in CPE in relation to sample size, duration of sampling, and decisions regarding what data are most appropriate for analysis; and (3) discuss recommendations for evaluating FI surveys and analyzing the resulting data to support fisheries management. This case study illustrated that the statistical power to detect temporal trends was low over relatively short sampling periods (e.g., 5–10 years) unless the annual decline in CPE reached 10–20%. For example, if 50 sites were sampled each year, a 10% annual decline in CPE would not be detected with more than 0.80 power until 15 years of sampling, and a 5% annual decline would not be detected with more than 0.8 power for approximately 22 years. Because the evaluation of FI surveys is essential for ensuring that trends in fish populations can be detected over management-relevant time periods, we suggest using a meta-analysis–type approach across systems to quantify sources of spatial and temporal variation. This approach can be used to evaluate and identify sampling designs that increase the ability of managers to make inferences about trends in fish stocks.

Naturally-Emerging Technology-Based Leadership Roles in Three Independent Schools: A Social Network-Based Case Study Using Fuzzy Set Qualitative Comparative Analysis

ERIC Educational Resources Information Center

Velastegui, Pamela J.

2013-01-01

This hypothesis-generating case study investigates the naturally emerging roles of technology brokers and technology leaders in three independent schools in New York involving 92 school educators. A multiple and mixed method design utilizing Social Network Analysis (SNA) and fuzzy set Qualitative Comparative Analysis (FSQCA) involved gathering…

Classification of JET Neutron and Gamma Emissivity Profiles

NASA Astrophysics Data System (ADS)

Craciunescu, T.; Murari, A.; Kiptily, V.; Vega, J.; Contributors, JET

2016-05-01

In thermonuclear plasmas, emission tomography uses integrated measurements along lines of sight (LOS) to determine the two-dimensional (2-D) spatial distribution of the volume emission intensity. Due to the availability of only a limited number views and to the coarse sampling of the LOS, the tomographic inversion is a limited data set problem. Several techniques have been developed for tomographic reconstruction of the 2-D gamma and neutron emissivity on JET. In specific experimental conditions the availability of LOSs is restricted to a single view. In this case an explicit reconstruction of the emissivity profile is no longer possible. However, machine learning classification methods can be used in order to derive the type of the distribution. In the present approach the classification is developed using the theory of belief functions which provide the support to fuse the results of independent clustering and supervised classification. The method allows to represent the uncertainty of the results provided by different independent techniques, to combine them and to manage possible conflicts.

Interaction of reward seeking and self-regulation in the prediction of risk taking: A cross-national test of the dual systems model.

PubMed

Duell, Natasha; Steinberg, Laurence; Chein, Jason; Al-Hassan, Suha M; Bacchini, Dario; Lei, Chang; Chaudhary, Nandita; Di Giunta, Laura; Dodge, Kenneth A; Fanti, Kostas A; Lansford, Jennifer E; Malone, Patrick S; Oburu, Paul; Pastorelli, Concetta; Skinner, Ann T; Sorbring, Emma; Tapanya, Sombat; Uribe Tirado, Liliana Maria; Alampay, Liane Peña

2016-10-01

In the present analysis, we test the dual systems model of adolescent risk taking in a cross-national sample of over 5,200 individuals aged 10 through 30 (M = 17.05 years, SD = 5.91) from 11 countries. We examine whether reward seeking and self-regulation make independent, additive, or interactive contributions to risk taking, and ask whether these relations differ as a function of age and culture. To compare across cultures, we conduct 2 sets of analyses: 1 comparing individuals from Asian and Western countries, and 1 comparing individuals from low- and high-GDP countries. Results indicate that reward seeking and self-regulation have largely independent associations with risk taking and that the influences of each variable on risk taking are not unique to adolescence, but that their link to risk taking varies across cultures. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Use of Sequence-independent, single-primer amplification (SISPA) with NGS platform for detection of RNA viruses in clinical samples

USDA-ARS?s Scientific Manuscript database

Current technologies for next generation sequencing (NGS) have revolutionized metagenomics analysis of clinical samples. One advantage of the NGS platform is the possibility to sequence the genetic material in samples without any prior knowledge of the sequence contained within. Sequence-Independent...

A nonvoxel-based dose convolution/superposition algorithm optimized for scalable GPU architectures.

PubMed

Neylon, J; Sheng, K; Yu, V; Chen, Q; Low, D A; Kupelian, P; Santhanam, A

2014-10-01

Real-time adaptive planning and treatment has been infeasible due in part to its high computational complexity. There have been many recent efforts to utilize graphics processing units (GPUs) to accelerate the computational performance and dose accuracy in radiation therapy. Data structure and memory access patterns are the key GPU factors that determine the computational performance and accuracy. In this paper, the authors present a nonvoxel-based (NVB) approach to maximize computational and memory access efficiency and throughput on the GPU. The proposed algorithm employs a ray-tracing mechanism to restructure the 3D data sets computed from the CT anatomy into a nonvoxel-based framework. In a process that takes only a few milliseconds of computing time, the algorithm restructured the data sets by ray-tracing through precalculated CT volumes to realign the coordinate system along the convolution direction, as defined by zenithal and azimuthal angles. During the ray-tracing step, the data were resampled according to radial sampling and parallel ray-spacing parameters making the algorithm independent of the original CT resolution. The nonvoxel-based algorithm presented in this paper also demonstrated a trade-off in computational performance and dose accuracy for different coordinate system configurations. In order to find the best balance between the computed speedup and the accuracy, the authors employed an exhaustive parameter search on all sampling parameters that defined the coordinate system configuration: zenithal, azimuthal, and radial sampling of the convolution algorithm, as well as the parallel ray spacing during ray tracing. The angular sampling parameters were varied between 4 and 48 discrete angles, while both radial sampling and parallel ray spacing were varied from 0.5 to 10 mm. The gamma distribution analysis method (γ) was used to compare the dose distributions using 2% and 2 mm dose difference and distance-to-agreement criteria, respectively. Accuracy was investigated using three distinct phantoms with varied geometries and heterogeneities and on a series of 14 segmented lung CT data sets. Performance gains were calculated using three 256 mm cube homogenous water phantoms, with isotropic voxel dimensions of 1, 2, and 4 mm. The nonvoxel-based GPU algorithm was independent of the data size and provided significant computational gains over the CPU algorithm for large CT data sizes. The parameter search analysis also showed that the ray combination of 8 zenithal and 8 azimuthal angles along with 1 mm radial sampling and 2 mm parallel ray spacing maintained dose accuracy with greater than 99% of voxels passing the γ test. Combining the acceleration obtained from GPU parallelization with the sampling optimization, the authors achieved a total performance improvement factor of >175 000 when compared to our voxel-based ground truth CPU benchmark and a factor of 20 compared with a voxel-based GPU dose convolution method. The nonvoxel-based convolution method yielded substantial performance improvements over a generic GPU implementation, while maintaining accuracy as compared to a CPU computed ground truth dose distribution. Such an algorithm can be a key contribution toward developing tools for adaptive radiation therapy systems.

A nonvoxel-based dose convolution/superposition algorithm optimized for scalable GPU architectures

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

Neylon, J., E-mail: jneylon@mednet.ucla.edu; Sheng, K.; Yu, V.

Purpose: Real-time adaptive planning and treatment has been infeasible due in part to its high computational complexity. There have been many recent efforts to utilize graphics processing units (GPUs) to accelerate the computational performance and dose accuracy in radiation therapy. Data structure and memory access patterns are the key GPU factors that determine the computational performance and accuracy. In this paper, the authors present a nonvoxel-based (NVB) approach to maximize computational and memory access efficiency and throughput on the GPU. Methods: The proposed algorithm employs a ray-tracing mechanism to restructure the 3D data sets computed from the CT anatomy intomore » a nonvoxel-based framework. In a process that takes only a few milliseconds of computing time, the algorithm restructured the data sets by ray-tracing through precalculated CT volumes to realign the coordinate system along the convolution direction, as defined by zenithal and azimuthal angles. During the ray-tracing step, the data were resampled according to radial sampling and parallel ray-spacing parameters making the algorithm independent of the original CT resolution. The nonvoxel-based algorithm presented in this paper also demonstrated a trade-off in computational performance and dose accuracy for different coordinate system configurations. In order to find the best balance between the computed speedup and the accuracy, the authors employed an exhaustive parameter search on all sampling parameters that defined the coordinate system configuration: zenithal, azimuthal, and radial sampling of the convolution algorithm, as well as the parallel ray spacing during ray tracing. The angular sampling parameters were varied between 4 and 48 discrete angles, while both radial sampling and parallel ray spacing were varied from 0.5 to 10 mm. The gamma distribution analysis method (γ) was used to compare the dose distributions using 2% and 2 mm dose difference and distance-to-agreement criteria, respectively. Accuracy was investigated using three distinct phantoms with varied geometries and heterogeneities and on a series of 14 segmented lung CT data sets. Performance gains were calculated using three 256 mm cube homogenous water phantoms, with isotropic voxel dimensions of 1, 2, and 4 mm. Results: The nonvoxel-based GPU algorithm was independent of the data size and provided significant computational gains over the CPU algorithm for large CT data sizes. The parameter search analysis also showed that the ray combination of 8 zenithal and 8 azimuthal angles along with 1 mm radial sampling and 2 mm parallel ray spacing maintained dose accuracy with greater than 99% of voxels passing the γ test. Combining the acceleration obtained from GPU parallelization with the sampling optimization, the authors achieved a total performance improvement factor of >175 000 when compared to our voxel-based ground truth CPU benchmark and a factor of 20 compared with a voxel-based GPU dose convolution method. Conclusions: The nonvoxel-based convolution method yielded substantial performance improvements over a generic GPU implementation, while maintaining accuracy as compared to a CPU computed ground truth dose distribution. Such an algorithm can be a key contribution toward developing tools for adaptive radiation therapy systems.« less

Robust model selection and the statistical classification of languages

NASA Astrophysics Data System (ADS)

García, J. E.; González-López, V. A.; Viola, M. L. L.

2012-10-01

In this paper we address the problem of model selection for the set of finite memory stochastic processes with finite alphabet, when the data is contaminated. We consider m independent samples, with more than half of them being realizations of the same stochastic process with law Q, which is the one we want to retrieve. We devise a model selection procedure such that for a sample size large enough, the selected process is the one with law Q. Our model selection strategy is based on estimating relative entropies to select a subset of samples that are realizations of the same law. Although the procedure is valid for any family of finite order Markov models, we will focus on the family of variable length Markov chain models, which include the fixed order Markov chain model family. We define the asymptotic breakdown point (ABDP) for a model selection procedure, and we show the ABDP for our procedure. This means that if the proportion of contaminated samples is smaller than the ABDP, then, as the sample size grows our procedure selects a model for the process with law Q. We also use our procedure in a setting where we have one sample conformed by the concatenation of sub-samples of two or more stochastic processes, with most of the subsamples having law Q. We conducted a simulation study. In the application section we address the question of the statistical classification of languages according to their rhythmic features using speech samples. This is an important open problem in phonology. A persistent difficulty on this problem is that the speech samples correspond to several sentences produced by diverse speakers, corresponding to a mixture of distributions. The usual procedure to deal with this problem has been to choose a subset of the original sample which seems to best represent each language. The selection is made by listening to the samples. In our application we use the full dataset without any preselection of samples. We apply our robust methodology estimating a model which represent the main law for each language. Our findings agree with the linguistic conjecture, related to the rhythm of the languages included on our dataset.

Stable Chimeras and Independently Synchronizable Clusters

NASA Astrophysics Data System (ADS)

Cho, Young Sul; Nishikawa, Takashi; Motter, Adilson E.

2017-08-01

Cluster synchronization is a phenomenon in which a network self-organizes into a pattern of synchronized sets. It has been shown that diverse patterns of stable cluster synchronization can be captured by symmetries of the network. Here, we establish a theoretical basis to divide an arbitrary pattern of symmetry clusters into independently synchronizable cluster sets, in which the synchronization stability of the individual clusters in each set is decoupled from that in all the other sets. Using this framework, we suggest a new approach to find permanently stable chimera states by capturing two or more symmetry clusters—at least one stable and one unstable—that compose the entire fully symmetric network.

Microarray-based gene expression profiling in patients with cryopyrin-associated periodic syndromes defines a disease-related signature and IL-1-responsive transcripts.

PubMed

Balow, James E; Ryan, John G; Chae, Jae Jin; Booty, Matthew G; Bulua, Ariel; Stone, Deborah; Sun, Hong-Wei; Greene, James; Barham, Beverly; Goldbach-Mansky, Raphaela; Kastner, Daniel L; Aksentijevich, Ivona

2013-06-01

To analyse gene expression patterns and to define a specific gene expression signature in patients with the severe end of the spectrum of cryopyrin-associated periodic syndromes (CAPS). The molecular consequences of interleukin 1 inhibition were examined by comparing gene expression patterns in 16 CAPS patients before and after treatment with anakinra. We collected peripheral blood mononuclear cells from 22 CAPS patients with active disease and from 14 healthy children. Transcripts that passed stringent filtering criteria (p values≤false discovery rate 1%) were considered as differentially expressed genes (DEG). A set of DEG was validated by quantitative reverse transcription PCR and functional studies with primary cells from CAPS patients and healthy controls. We used 17 CAPS and 66 non-CAPS patient samples to create a set of gene expression models that differentiates CAPS patients from controls and from patients with other autoinflammatory conditions. Many DEG include transcripts related to the regulation of innate and adaptive immune responses, oxidative stress, cell death, cell adhesion and motility. A set of gene expression-based models comprising the CAPS-specific gene expression signature correctly classified all 17 samples from an independent dataset. This classifier also correctly identified 15 of 16 post-anakinra CAPS samples despite the fact that these CAPS patients were in clinical remission. We identified a gene expression signature that clearly distinguished CAPS patients from controls. A number of DEG were in common with other systemic inflammatory diseases such as systemic onset juvenile idiopathic arthritis. The CAPS-specific gene expression classifiers also suggest incomplete suppression of inflammation at low doses of anakinra.

Microarray-based gene expression profiling in patients with cryopyrin-associated periodic syndromes defines a disease-related signature and IL-1-responsive transcripts

PubMed Central

Balow, James E; Ryan, John G; Chae, Jae Jin; Booty, Matthew G; Bulua, Ariel; Stone, Deborah; Sun, Hong-Wei; Greene, James; Barham, Beverly; Goldbach-Mansky, Raphaela; Kastner, Daniel L; Aksentijevich, Ivona

2014-01-01

Objective To analyse gene expression patterns and to define a specific gene expression signature in patients with the severe end of the spectrum of cryopyrin-associated periodic syndromes (CAPS). The molecular consequences of interleukin 1 inhibition were examined by comparing gene expression patterns in 16 CAPS patients before and after treatment with anakinra. Methods We collected peripheral blood mononuclear cells from 22 CAPS patients with active disease and from 14 healthy children. Transcripts that passed stringent filtering criteria (p values ≤ false discovery rate 1%) were considered as differentially expressed genes (DEG). A set of DEG was validated by quantitative reverse transcription PCR and functional studies with primary cells from CAPS patients and healthy controls. We used 17 CAPS and 66 non-CAPS patient samples to create a set of gene expression models that differentiates CAPS patients from controls and from patients with other autoinflammatory conditions. Results Many DEG include transcripts related to the regulation of innate and adaptive immune responses, oxidative stress, cell death, cell adhesion and motility. A set of gene expression-based models comprising the CAPS-specific gene expression signature correctly classified all 17 samples from an independent dataset. This classifier also correctly identified 15 of 16 postanakinra CAPS samples despite the fact that these CAPS patients were in clinical remission. Conclusions We identified a gene expression signature that clearly distinguished CAPS patients from controls. A number of DEG were in common with other systemic inflammatory diseases such as systemic onset juvenile idiopathic arthritis. The CAPS-specific gene expression classifiers also suggest incomplete suppression of inflammation at low doses of anakinra. PMID:23223423

Characterizing the phytoplankton soup: pump and plumbing effects on the particle assemblage in underway optical seawater systems.

PubMed

Cetinić, Ivona; Poulton, Nicole; Slade, Wayne H

2016-09-05

Many optical and biogeochemical data sets, crucial for algorithm development and satellite data validation, are collected using underway seawater systems over the course of research cruises. Phytoplankton and particle size distribution (PSD) in the ocean is a key measurement, required in oceanographic research and ocean optics. Using a data set collected in the North Atlantic, spanning different oceanic water types, we outline the differences observed in concurrent samples collected from two different flow-through systems: a permanently plumbed science seawater supply with an impeller pump, and an independent system with shorter, clean tubing runs and a diaphragm pump. We observed an average of 40% decrease in phytoplankton counts, and significant changes to the PSD in 10-45 µm range, when comparing impeller and diaphragm pump systems. Change in PSD seems to be more dependent on the type of the phytoplankton, than the size, with photosynthetic ciliates displaying the largest decreases in cell counts (78%). Comparison of chlorophyll concentrations across the two systems demonstrated lower sensitivity to sampling system type. Observed changes in several measured biogeochemical parameters (associated with phytoplankton size distribution) using the two sampling systems, should be used as a guide towards building best practices when it comes to the deployment of flow-through systems in the field for examining optics and biogeochemistry. Using optical models, we evaluated potential impact of the observed change in measured phytoplankton size spectra onto scattering measurements, resulting in significant differences between modeled optical properties across systems (~40%). Researchers should be aware of the methods used with previously collected data sets, and take into consideration the potentially significant and highly variable ecosystem-dependent biases in designing field studies in the future.

Computational approach for deriving cancer progression roadmaps from static sample data

PubMed Central

Yao, Jin; Yang, Le; Chen, Runpu; Nowak, Norma J.

2017-01-01

Abstract As with any biological process, cancer development is inherently dynamic. While major efforts continue to catalog the genomic events associated with human cancer, it remains difficult to interpret and extrapolate the accumulating data to provide insights into the dynamic aspects of the disease. Here, we present a computational strategy that enables the construction of a cancer progression model using static tumor sample data. The developed approach overcame many technical limitations of existing methods. Application of the approach to breast cancer data revealed a linear, branching model with two distinct trajectories for malignant progression. The validity of the constructed model was demonstrated in 27 independent breast cancer data sets, and through visualization of the data in the context of disease progression we were able to identify a number of potentially key molecular events in the advance of breast cancer to malignancy. PMID:28108658

Abstracting ICU Nursing Care Quality Data From the Electronic Health Record.

PubMed

Seaman, Jennifer B; Evans, Anna C; Sciulli, Andrea M; Barnato, Amber E; Sereika, Susan M; Happ, Mary Beth

2017-09-01

The electronic health record is a potentially rich source of data for clinical research in the intensive care unit setting. We describe the iterative, multi-step process used to develop and test a data abstraction tool, used for collection of nursing care quality indicators from the electronic health record, for a pragmatic trial. We computed Cohen's kappa coefficient (κ) to assess interrater agreement or reliability of data abstracted using preliminary and finalized tools. In assessing the reliability of study data ( n = 1,440 cases) using the finalized tool, 108 randomly selected cases (10% of first half sample; 5% of last half sample) were independently abstracted by a second rater. We demonstrated mean κ values ranging from 0.61 to 0.99 for all indicators. Nursing care quality data can be accurately and reliably abstracted from the electronic health records of intensive care unit patients using a well-developed data collection tool and detailed training.

Qualitative fusion technique based on information poor system and its application to factor analysis for vibration of rolling bearings

NASA Astrophysics Data System (ADS)

Xia, Xintao; Wang, Zhongyu

2008-10-01

For some methods of stability analysis of a system using statistics, it is difficult to resolve the problems of unknown probability distribution and small sample. Therefore, a novel method is proposed in this paper to resolve these problems. This method is independent of probability distribution, and is useful for small sample systems. After rearrangement of the original data series, the order difference and two polynomial membership functions are introduced to estimate the true value, the lower bound and the supper bound of the system using fuzzy-set theory. Then empirical distribution function is investigated to ensure confidence level above 95%, and the degree of similarity is presented to evaluate stability of the system. Cases of computer simulation investigate stable systems with various probability distribution, unstable systems with linear systematic errors and periodic systematic errors and some mixed systems. The method of analysis for systematic stability is approved.

A k-Vector Approach to Sampling, Interpolation, and Approximation

NASA Astrophysics Data System (ADS)

Mortari, Daniele; Rogers, Jonathan

2013-12-01

The k-vector search technique is a method designed to perform extremely fast range searching of large databases at computational cost independent of the size of the database. k-vector search algorithms have historically found application in satellite star-tracker navigation systems which index very large star catalogues repeatedly in the process of attitude estimation. Recently, the k-vector search algorithm has been applied to numerous other problem areas including non-uniform random variate sampling, interpolation of 1-D or 2-D tables, nonlinear function inversion, and solution of systems of nonlinear equations. This paper presents algorithms in which the k-vector search technique is used to solve each of these problems in a computationally-efficient manner. In instances where these tasks must be performed repeatedly on a static (or nearly-static) data set, the proposed k-vector-based algorithms offer an extremely fast solution technique that outperforms standard methods.

On the origin of nonlinear elasticity in disparate rocks

DOE PAGES

Riviere, Jacques Vincent; Shokouhi, Parisa; Guyer, Robert A.; ...

2015-03-31

Dynamic acousto-elastic (DAE) studies are performed on a set of 6 rock samples (four sandstones, one soapstone, and one granite). From these studies, at 20 strain levels 10 -7 < ϵ < 10 -5, four measures characterizing the nonlinear elastic response of each sample are found. Additionally, each sample is tested with nonlinear resonant ultrasonic spectroscopy (NRUS) and a fth measure of nonlinear elastic response is found. The ve measures of the nonlinear elastic response of the samples (approximately 3 x 6 x 20 x 5 numbers as each measurement is repeated 3 times) are subjected to careful analysis usingmore » model independent statistical methods, principal component analysis and fuzzy clustering. This analysis reveals di erences among the samples and di erences among the nonlinear measures. Four of the nonlinear measures are sensing much the same physical mechanism in the samples. The fth is seeing something di erent. This is the case for all samples. Although the same physical mechanisms (two) are operating in all samples there are distinctive features in the way the physical mechanisms present themselves from sample to sample. This suggests classi cation of the samples into two groups. The numbers in this study and the classi cation of the measures/samples constitute an empirical characterization of rock nonlinear elastic properties that can serve as a valuable testing ground for physically based theories that relate rock nonlinear elastic properties to microscopic elastic features.« less

Sparse feature selection for classification and prediction of metastasis in endometrial cancer.

PubMed

Ahsen, Mehmet Eren; Boren, Todd P; Singh, Nitin K; Misganaw, Burook; Mutch, David G; Moore, Kathleen N; Backes, Floor J; McCourt, Carolyn K; Lea, Jayanthi S; Miller, David S; White, Michael A; Vidyasagar, Mathukumalli

2017-03-27

Metastasis via pelvic and/or para-aortic lymph nodes is a major risk factor for endometrial cancer. Lymph-node resection ameliorates risk but is associated with significant co-morbidities. Incidence in patients with stage I disease is 4-22% but no mechanism exists to accurately predict it. Therefore, national guidelines for primary staging surgery include pelvic and para-aortic lymph node dissection for all patients whose tumor exceeds 2cm in diameter. We sought to identify a robust molecular signature that can accurately classify risk of lymph node metastasis in endometrial cancer patients. 86 tumors matched for age and race, and evenly distributed between lymph node-positive and lymph node-negative cases, were selected as a training cohort. Genomic micro-RNA expression was profiled for each sample to serve as the predictive feature matrix. An independent set of 28 tumor samples was collected and similarly characterized to serve as a test cohort. A feature selection algorithm was designed for applications where the number of samples is far smaller than the number of measured features per sample. A predictive miRNA expression signature was developed using this algorithm, which was then used to predict the metastatic status of the independent test cohort. A weighted classifier, using 18 micro-RNAs, achieved 100% accuracy on the training cohort. When applied to the testing cohort, the classifier correctly predicted 90% of node-positive cases, and 80% of node-negative cases (FDR = 6.25%). Results indicate that the evaluation of the quantitative sparse-feature classifier proposed here in clinical trials may lead to significant improvement in the prediction of lymphatic metastases in endometrial cancer patients.

Precision Scaling Relations for Disk Galaxies in the Local Universe

NASA Astrophysics Data System (ADS)

Lapi, A.; Salucci, P.; Danese, L.

2018-05-01

We build templates of rotation curves as a function of the I-band luminosity via the mass modeling (by the sum of a thin exponential disk and a cored halo profile) of suitably normalized, stacked data from wide samples of local spiral galaxies. We then exploit such templates to determine fundamental stellar and halo properties for a sample of about 550 local disk-dominated galaxies with high-quality measurements of the optical radius R opt and of the corresponding rotation velocity V opt. Specifically, we determine the stellar M ⋆ and halo M H masses, the halo size R H and velocity scale V H, and the specific angular momenta of the stellar j ⋆ and dark matter j H components. We derive global scaling relationships involving such stellar and halo properties both for the individual galaxies in our sample and for their mean within bins; the latter are found to be in pleasing agreement with previous determinations by independent methods (e.g., abundance matching techniques, weak-lensing observations, and individual rotation curve modeling). Remarkably, the size of our sample and the robustness of our statistical approach allow us to attain an unprecedented level of precision over an extended range of mass and velocity scales, with 1σ dispersion around the mean relationships of less than 0.1 dex. We thus set new standard local relationships that must be reproduced by detailed physical models, which offer a basis for improving the subgrid recipes in numerical simulations, that provide a benchmark to gauge independent observations and check for systematics, and that constitute a basic step toward the future exploitation of the spiral galaxy population as a cosmological probe.

Monitoring microbiological changes in drinking water systems using a fast and reproducible flow cytometric method.

PubMed

Prest, E I; Hammes, F; Kötzsch, S; van Loosdrecht, M C M; Vrouwenvelder, J S

2013-12-01

Flow cytometry (FCM) is a rapid, cultivation-independent tool to assess and evaluate bacteriological quality and biological stability of water. Here we demonstrate that a stringent, reproducible staining protocol combined with fixed FCM operational and gating settings is essential for reliable quantification of bacteria and detection of changes in aquatic bacterial communities. Triplicate measurements of diverse water samples with this protocol typically showed relative standard deviation values and 95% confidence interval values below 2.5% on all the main FCM parameters. We propose a straightforward and instrument-independent method for the characterization of water samples based on the combination of bacterial cell concentration and fluorescence distribution. Analysis of the fluorescence distribution (or so-called fluorescence fingerprint) was accomplished firstly through a direct comparison of the raw FCM data and subsequently simplified by quantifying the percentage of large and brightly fluorescent high nucleic acid (HNA) content bacteria in each sample. Our approach enables fast differentiation of dissimilar bacterial communities (less than 15 min from sampling to final result), and allows accurate detection of even small changes in aquatic environments (detection above 3% change). Demonstrative studies on (a) indigenous bacterial growth in water, (b) contamination of drinking water with wastewater, (c) household drinking water stagnation and (d) mixing of two drinking water types, univocally showed that this FCM approach enables detection and quantification of relevant bacterial water quality changes with high sensitivity. This approach has the potential to be used as a new tool for application in the drinking water field, e.g. for rapid screening of the microbial water quality and stability during water treatment and distribution in networks and premise plumbing. Copyright © 2013 Elsevier Ltd. All rights reserved.

Gene identification for risk of relapse in stage I lung adenocarcinoma patients: a combined methodology of gene expression profiling and computational gene network analysis.

PubMed

Ludovini, Vienna; Bianconi, Fortunato; Siggillino, Annamaria; Piobbico, Danilo; Vannucci, Jacopo; Metro, Giulio; Chiari, Rita; Bellezza, Guido; Puma, Francesco; Della Fazia, Maria Agnese; Servillo, Giuseppe; Crinò, Lucio

2016-05-24

Risk assessment and treatment choice remains a challenge in early non-small-cell lung cancer (NSCLC). The aim of this study was to identify novel genes involved in the risk of early relapse (ER) compared to no relapse (NR) in resected lung adenocarcinoma (AD) patients using a combination of high throughput technology and computational analysis. We identified 18 patients (n.13 NR and n.5 ER) with stage I AD. Frozen samples of patients in ER, NR and corresponding normal lung (NL) were subjected to Microarray technology and quantitative-PCR (Q-PCR). A gene network computational analysis was performed to select predictive genes. An independent set of 79 ADs stage I samples was used to validate selected genes by Q-PCR.From microarray analysis we selected 50 genes, using the fold change ratio of ER versus NR. They were validated both in pool and individually in patient samples (ER and NR) by Q-PCR. Fourteen increased and 25 decreased genes showed a concordance between two methods. They were used to perform a computational gene network analysis that identified 4 increased (HOXA10, CLCA2, AKR1B10, FABP3) and 6 decreased (SCGB1A1, PGC, TFF1, PSCA, SPRR1B and PRSS1) genes. Moreover, in an independent dataset of ADs samples, we showed that both high FABP3 expression and low SCGB1A1 expression was associated with a worse disease-free survival (DFS).Our results indicate that it is possible to define, through gene expression and computational analysis, a characteristic gene profiling of patients with an increased risk of relapse that may become a tool for patient selection for adjuvant therapy.

Accounting for imperfect detection of groups and individuals when estimating abundance.

PubMed

Clement, Matthew J; Converse, Sarah J; Royle, J Andrew

2017-09-01

If animals are independently detected during surveys, many methods exist for estimating animal abundance despite detection probabilities <1. Common estimators include double-observer models, distance sampling models and combined double-observer and distance sampling models (known as mark-recapture-distance-sampling models; MRDS). When animals reside in groups, however, the assumption of independent detection is violated. In this case, the standard approach is to account for imperfect detection of groups, while assuming that individuals within groups are detected perfectly. However, this assumption is often unsupported. We introduce an abundance estimator for grouped animals when detection of groups is imperfect and group size may be under-counted, but not over-counted. The estimator combines an MRDS model with an N-mixture model to account for imperfect detection of individuals. The new MRDS-Nmix model requires the same data as an MRDS model (independent detection histories, an estimate of distance to transect, and an estimate of group size), plus a second estimate of group size provided by the second observer. We extend the model to situations in which detection of individuals within groups declines with distance. We simulated 12 data sets and used Bayesian methods to compare the performance of the new MRDS-Nmix model to an MRDS model. Abundance estimates generated by the MRDS-Nmix model exhibited minimal bias and nominal coverage levels. In contrast, MRDS abundance estimates were biased low and exhibited poor coverage. Many species of conservation interest reside in groups and could benefit from an estimator that better accounts for imperfect detection. Furthermore, the ability to relax the assumption of perfect detection of individuals within detected groups may allow surveyors to re-allocate resources toward detection of new groups instead of extensive surveys of known groups. We believe the proposed estimator is feasible because the only additional field data required are a second estimate of group size.

Accounting for imperfect detection of groups and individuals when estimating abundance

USGS Publications Warehouse

Clement, Matthew J.; Converse, Sarah J.; Royle, J. Andrew

2017-01-01

If animals are independently detected during surveys, many methods exist for estimating animal abundance despite detection probabilities <1. Common estimators include double-observer models, distance sampling models and combined double-observer and distance sampling models (known as mark-recapture-distance-sampling models; MRDS). When animals reside in groups, however, the assumption of independent detection is violated. In this case, the standard approach is to account for imperfect detection of groups, while assuming that individuals within groups are detected perfectly. However, this assumption is often unsupported. We introduce an abundance estimator for grouped animals when detection of groups is imperfect and group size may be under-counted, but not over-counted. The estimator combines an MRDS model with an N-mixture model to account for imperfect detection of individuals. The new MRDS-Nmix model requires the same data as an MRDS model (independent detection histories, an estimate of distance to transect, and an estimate of group size), plus a second estimate of group size provided by the second observer. We extend the model to situations in which detection of individuals within groups declines with distance. We simulated 12 data sets and used Bayesian methods to compare the performance of the new MRDS-Nmix model to an MRDS model. Abundance estimates generated by the MRDS-Nmix model exhibited minimal bias and nominal coverage levels. In contrast, MRDS abundance estimates were biased low and exhibited poor coverage. Many species of conservation interest reside in groups and could benefit from an estimator that better accounts for imperfect detection. Furthermore, the ability to relax the assumption of perfect detection of individuals within detected groups may allow surveyors to re-allocate resources toward detection of new groups instead of extensive surveys of known groups. We believe the proposed estimator is feasible because the only additional field data required are a second estimate of group size.

Effect of blood sampling schedule and method of calculating the area under the curve on validity and precision of glycaemic index values.

PubMed

Wolever, Thomas M S

2004-02-01

To evaluate the suitability for glycaemic index (GI) calculations of using blood sampling schedules and methods of calculating area under the curve (AUC) different from those recommended, the GI values of five foods were determined by recommended methods (capillary blood glucose measured seven times over 2.0 h) in forty-seven normal subjects and different calculations performed on the same data set. The AUC was calculated in four ways: incremental AUC (iAUC; recommended method), iAUC above the minimum blood glucose value (AUCmin), net AUC (netAUC) and iAUC including area only before the glycaemic response curve cuts the baseline (AUCcut). In addition, iAUC was calculated using four different sets of less than seven blood samples. GI values were derived using each AUC calculation. The mean GI values of the foods varied significantly according to the method of calculating GI. The standard deviation of GI values calculating using iAUC (20.4), was lower than six of the seven other methods, and significantly less (P<0.05) than that using netAUC (24.0). To be a valid index of food glycaemic response independent of subject characteristics, GI values in subjects should not be related to their AUC after oral glucose. However, calculating GI using AUCmin or less than seven blood samples resulted in significant (P<0.05) relationships between GI and mean AUC. It is concluded that, in subjects without diabetes, the recommended blood sampling schedule and method of AUC calculation yields more valid and/or more precise GI values than the seven other methods tested here. The only method whose results agreed reasonably well with the recommended method (ie. within +/-5 %) was AUCcut.

Analysis of Serum Total and Free PSA Using Immunoaffinity Depletion Coupled to SRM: Correlation with Clinical Immunoassay Tests

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

Liu, Tao; Hossain, Mahmud; Schepmoes, Athena A.

2012-08-03

Sandwich immunoassay is the standard technique used in clinical labs for quantifying protein biomarkers for disease detection, monitoring and therapeutic intervention. Albeit highly sensitive, the development of a specific immunoassay is rather time-consuming and associated with extremely high cost due to the requirement for paired immunoaffinity reagents of high specificity. Recently, mass spectrometry-based methods, specifically selected reaction monitoring mass spectrometry (SRM-MS), have been increasingly applied to measure low abundance biomarker candidates in tissue and biofluids, owing to high sensitivity and specificity, simplicity of assay configuration, and great multiplexing capability. In this study, we report for the first time the developmentmore » of immunoaffinity depletion-based workflows and SRM-MS assays that enable sensitive and accurate quantification of total and free prostate-specific antigen (PSA) in serum without the requirement for specific PSA antibodies. With stable isotope dilution and external calibration, low ng/mL level detection of both total and free PSA was consistently achieved in both PSA-spiked female serum samples and actual patient serum samples. Moreover, comparison of the results obtained when SRM PSA assays and conventional immunoassays were applied to the same samples showed very good correlation (R2 values ranging from 0.90 to 0.99) in several independent clinical serum sample sets, including a set of 33 samples assayed in a blinded test. These results demonstrate that the workflows and SRM assays developed here provide an attractive alternative for reliably measuring total and free PSA in human blood. Furthermore, simultaneous measurement of free and total PSA and many other biomarkers can be performed in a single analysis using high-resolution liquid chromatographic separation coupled with SRM-MS.« less

[Discrimination of donkey meat by NIR and chemometrics].

PubMed

Niu, Xiao-Ying; Shao, Li-Min; Dong, Fang; Zhao, Zhi-Lei; Zhu, Yan

2014-10-01

Donkey meat samples (n = 167) from different parts of donkey body (neck, costalia, rump, and tendon), beef (n = 47), pork (n = 51) and mutton (n = 32) samples were used to establish near-infrared reflectance spectroscopy (NIR) classification models in the spectra range of 4,000~12,500 cm(-1). The accuracies of classification models constructed by Mahalanobis distances analysis, soft independent modeling of class analogy (SIMCA) and least squares-support vector machine (LS-SVM), respectively combined with pretreatment of Savitzky-Golay smooth (5, 15 and 25 points) and derivative (first and second), multiplicative scatter correction and standard normal variate, were compared. The optimal models for intact samples were obtained by Mahalanobis distances analysis with the first 11 principal components (PCs) from original spectra as inputs and by LS-SVM with the first 6 PCs as inputs, and correctly classified 100% of calibration set and 98. 96% of prediction set. For minced samples of 7 mm diameter the optimal result was attained by LS-SVM with the first 5 PCs from original spectra as inputs, which gained an accuracy of 100% for calibration and 97.53% for prediction. For minced diameter of 5 mm SIMCA model with the first 8 PCs from original spectra as inputs correctly classified 100% of calibration and prediction. And for minced diameter of 3 mm Mahalanobis distances analysis and SIMCA models both achieved 100% accuracy for calibration and prediction respectively with the first 7 and 9 PCs from original spectra as inputs. And in these models, donkey meat samples were all correctly classified with 100% either in calibration or prediction. The results show that it is feasible that NIR with chemometrics methods is used to discriminate donkey meat from the else meat.

Quantification of trace metals in infant formula premixes using laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Cama-Moncunill, Raquel; Casado-Gavalda, Maria P.; Cama-Moncunill, Xavier; Markiewicz-Keszycka, Maria; Dixit, Yash; Cullen, Patrick J.; Sullivan, Carl

2017-09-01

Infant formula is a human milk substitute generally based upon fortified cow milk components. In order to mimic the composition of breast milk, trace elements such as copper, iron and zinc are usually added in a single operation using a premix. The correct addition of premixes must be verified to ensure that the target levels in infant formulae are achieved. In this study, a laser-induced breakdown spectroscopy (LIBS) system was assessed as a fast validation tool for trace element premixes. LIBS is a promising emission spectroscopic technique for elemental analysis, which offers real-time analyses, little to no sample preparation and ease of use. LIBS was employed for copper and iron determinations of premix samples ranging approximately from 0 to 120 mg/kg Cu/1640 mg/kg Fe. LIBS spectra are affected by several parameters, hindering subsequent quantitative analyses. This work aimed at testing three matrix-matched calibration approaches (simple-linear regression, multi-linear regression and partial least squares regression (PLS)) as means for precision and accuracy enhancement of LIBS quantitative analysis. All calibration models were first developed using a training set and then validated with an independent test set. PLS yielded the best results. For instance, the PLS model for copper provided a coefficient of determination (R2) of 0.995 and a root mean square error of prediction (RMSEP) of 14 mg/kg. Furthermore, LIBS was employed to penetrate through the samples by repetitively measuring the same spot. Consequently, LIBS spectra can be obtained as a function of sample layers. This information was used to explore whether measuring deeper into the sample could reduce possible surface-contaminant effects and provide better quantifications.

Daily Alcohol Use as an Independent Risk Factor for HIV Seroconversion Among People Who Inject Drugs

PubMed Central

Young, Samantha; Wood, Evan; Dong, Huiru; Kerr, Thomas; Hayashi, Kanna

2015-01-01

Aims To estimate the relationship between daily alcohol use and HIV seroconversion among people who inject drugs (PWID) in a Canadian setting. Design and Setting Data from an open prospective cohort study of PWID in Vancouver, Canada, recruited via snowball sampling and street outreach between May 1996 and November 2013. An interviewer-administered questionnaire including standardized behavioural assessment, and HIV antibody testing were conducted semiannually. Baseline HIV-seronegative participants completing ≥1 follow-up visits were eligible for the present analysis. Participants 1683 eligible participants, including 564 (33.5%) women, were followed for a median of 79.8 (interquartile range [IQR]: 33.3 – 119.1) months. Measurements The primary endpoint was time to HIV seroconversion, with the date of HIV seroconversion estimated as the midpoint between the last negative and the first positive antibody test results. The primary explanatory variable was self-reported daily alcohol use in the previous 6 months assessed semiannually. Other covariates considered included demographic, behavioural, social/structural, and environmental risk factors for HIV infection among PWID (e.g. daily cocaine injection, methadone use, etc.). Findings Of 1683 PWID, there were 176 HIV seroconversions during follow-up with an incidence density of 1.5 (95% confidence interval [CI]: 1.3 – 1.7) cases per 100 person-years. At baseline, 339 (20.1%) consumed alcohol at least daily in the previous six months. In multivariable extended Cox regression analyses, daily alcohol use remained independently associated with HIV seroconversion (Adjusted Hazard Ratio: 1.48; 95% CI: 1.00–2.17). Conclusions Daily alcohol use appears to be an independent risk factor for HIV seroconversion among our cohort of PWID. PMID:26639363

Prediction of Response to Sorafenib in Hepatocellular Carcinoma: A Putative Marker Panel by Multiple Reaction Monitoring-Mass Spectrometry (MRM-MS).

PubMed

Kim, Hyunsoo; Yu, Su Jong; Yeo, Injun; Cho, Young Youn; Lee, Dong Hyeon; Cho, Yuri; Cho, Eun Ju; Lee, Jeong-Hoon; Kim, Yoon Jun; Lee, Sungyoung; Jun, Jongsoo; Park, Taesung; Yoon, Jung-Hwan; Kim, Youngsoo

2017-07-01

Sorafenib is the only standard treatment for unresectable hepatocellular carcinoma (HCC), but it provides modest survival benefits over placebo, necessitating predictive biomarkers of the response to sorafenib. Serum samples were obtained from 115 consecutive patients with HCC before sorafenib treatment and analyzed by multiple reaction monitoring-mass spectrometry (MRM-MS) and ELISA to quantify candidate biomarkers. We verified a triple-marker panel to be predictive of the response to sorafenib by MRM-MS, comprising CD5 antigen-like (CD5L), immunoglobulin J (IGJ), and galectin-3-binding protein (LGALS3BP), in HCC patients. This panel was a significant predictor (AUROC > 0.950) of the response to sorafenib treatment, having the best cut-off value (0.4) by multivariate analysis. In the training set, patients who exceeded this cut-off value had significantly better overall survival (median, 21.4 months) than those with lower values (median, 8.6 months; p = 0.001). Further, a value that was lower than this cutoff was an independent predictor of poor overall survival [hazard ratio (HR), 2.728; 95% confidence interval (CI), 1.312-5.672; p = 0.007] and remained an independent predictive factor of rapid progression (HR, 2.631; 95% CI, 1.448-4.780; p = 0.002). When applied to the independent validation set, levels of the cut-off value for triple-marker panel maintained their prognostic value for poor clinical outcomes. On the contrast, the triple-marker panel was not a prognostic factor for patients who were treated with transarterial chemoembolization (TACE). The discriminatory signature of a triple-marker panel provides new insights into targeted proteomic biomarkers for individualized sorafenib therapy. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

A novel multi-tissue RNA diagnostic of healthy ageing relates to cognitive health status.

PubMed

Sood, Sanjana; Gallagher, Iain J; Lunnon, Katie; Rullman, Eric; Keohane, Aoife; Crossland, Hannah; Phillips, Bethan E; Cederholm, Tommy; Jensen, Thomas; van Loon, Luc J C; Lannfelt, Lars; Kraus, William E; Atherton, Philip J; Howard, Robert; Gustafsson, Thomas; Hodges, Angela; Timmons, James A

2015-09-07

Diagnostics of the human ageing process may help predict future healthcare needs or guide preventative measures for tackling diseases of older age. We take a transcriptomics approach to build the first reproducible multi-tissue RNA expression signature by gene-chip profiling tissue from sedentary normal subjects who reached 65 years of age in good health. One hundred and fifty probe-sets form an accurate classifier of young versus older muscle tissue and this healthy ageing RNA classifier performed consistently in independent cohorts of human muscle, skin and brain tissue (n = 594, AUC = 0.83-0.96) and thus represents a biomarker for biological age. Using the Uppsala Longitudinal Study of Adult Men birth-cohort (n = 108) we demonstrate that the RNA classifier is insensitive to confounding lifestyle biomarkers, while greater gene score at age 70 years is independently associated with better renal function at age 82 years and longevity. The gene score is 'up-regulated' in healthy human hippocampus with age, and when applied to blood RNA profiles from two large independent age-matched dementia case-control data sets (n = 717) the healthy controls have significantly greater gene scores than those with cognitive impairment. Alone, or when combined with our previously described prototype Alzheimer disease (AD) RNA 'disease signature', the healthy ageing RNA classifier is diagnostic for AD. We identify a novel and statistically robust multi-tissue RNA signature of human healthy ageing that can act as a diagnostic of future health, using only a peripheral blood sample. This RNA signature has great potential to assist research aimed at finding treatments for and/or management of AD and other ageing-related conditions.

The association between attachment and mental health symptoms among school-going adolescents in northern Uganda: the moderating role of war-related trauma.

PubMed

Okello, James; Nakimuli-Mpungu, Etheldreda; Musisi, Seggane; Broekaert, Eric; Derluyn, Ilse

2014-01-01

The association between attachment and mental health symptoms in adolescents in a post-conflict low resource setting has not been documented. We investigated the relationship between parent and peer attachment and posttraumatic stress, depression and anxiety symptoms in a sample of 551 adolescents aged 13-21 years old. Attachment quality was assessed using the Inventory of Parent and Peer Attachment (IPPA). Post-traumatic stress, depression and anxiety symptoms were assessed using the Impact of Events Scale Revised (IESR) and Hopkins Symptom Checklist for Adolescents (HSCL-37A) respectively. Gender differences in attachment relationships were determined using independent t-tests. Multivariate logistic regression was used to assess whether attachment relationships were independently associated with posttraumatic stress, depression and anxiety symptoms. Hierarchical linear regression analyses were conducted to explore the moderating role of war-related trauma. Our analyses revealed gender differences in attachment to parents, with males reporting stronger attachment than females. Parental attachment was protective against depression and anxiety symptoms but not posttraumatic stress symptoms after adjusting for potential confounders. Alienation by parents was independently associated with an increase in these mental health symptoms while peer attachment was not associated with any of these symptoms. However, in situations of severe trauma, our analyses showed that peer attachment was significantly protective against post-traumatic stress symptoms. Secure parental attachment is associated with better psychosocial adjustment in adolescents affected by war. Further, adolescents with secure peer attachment relationships in situations of severe war trauma may be less likely to develop posttraumatic stress symptoms. Interventions to enhance peer support in this post conflict setting would benefit this vulnerable population.

Computer-based test-bed for clinical assessment of hand/wrist feed-forward neuroprosthetic controllers using artificial neural networks.

PubMed

Luján, J L; Crago, P E

2004-11-01

Neuroprosthestic systems can be used to restore hand grasp and wrist control in individuals with C5/C6 spinal cord injury. A computer-based system was developed for the implementation, tuning and clinical assessment of neuroprosthetic controllers, using off-the-shelf hardware and software. The computer system turned a Pentium III PC running Windows NT into a non-dedicated, real-time system for the control of neuroprostheses. Software execution (written using the high-level programming languages LabVIEW and MATLAB) was divided into two phases: training and real-time control. During the training phase, the computer system collected input/output data by stimulating the muscles and measuring the muscle outputs in real-time, analysed the recorded data, generated a set of training data and trained an artificial neural network (ANN)-based controller. During real-time control, the computer system stimulated the muscles using stimulus pulsewidths predicted by the ANN controller in response to a sampled input from an external command source, to provide independent control of hand grasp and wrist posture. System timing was stable, reliable and capable of providing muscle stimulation at frequencies up to 24Hz. To demonstrate the application of the test-bed, an ANN-based controller was implemented with three inputs and two independent channels of stimulation. The ANN controller's ability to control hand grasp and wrist angle independently was assessed by quantitative comparison of the outputs of the stimulated muscles with a set of desired grasp or wrist postures determined by the command signal. Controller performance results were mixed, but the platform provided the tools to implement and assess future controller designs.

The Association between Attachment and Mental Health Symptoms among School-Going Adolescents in Northern Uganda: The Moderating Role of War-Related Trauma

PubMed Central

Okello, James; Nakimuli-Mpungu, Etheldreda; Musisi, Seggane; Broekaert, Eric; Derluyn, Ilse

2014-01-01

Background The association between attachment and mental health symptoms in adolescents in a post-conflict low resource setting has not been documented. Methods We investigated the relationship between parent and peer attachment and posttraumatic stress, depression and anxiety symptoms in a sample of 551 adolescents aged 13–21 years old. Attachment quality was assessed using the Inventory of Parent and Peer Attachment (IPPA). Post-traumatic stress, depression and anxiety symptoms were assessed using the Impact of Events Scale Revised (IESR) and Hopkins Symptom Checklist for Adolescents (HSCL-37A) respectively. Gender differences in attachment relationships were determined using independent t-tests. Multivariate logistic regression was used to assess whether attachment relationships were independently associated with posttraumatic stress, depression and anxiety symptoms. Hierarchical linear regression analyses were conducted to explore the moderating role of war-related trauma. Results Our analyses revealed gender differences in attachment to parents, with males reporting stronger attachment than females. Parental attachment was protective against depression and anxiety symptoms but not posttraumatic stress symptoms after adjusting for potential confounders. Alienation by parents was independently associated with an increase in these mental health symptoms while peer attachment was not associated with any of these symptoms. However, in situations of severe trauma, our analyses showed that peer attachment was significantly protective against post-traumatic stress symptoms. Conclusions Secure parental attachment is associated with better psychosocial adjustment in adolescents affected by war. Further, adolescents with secure peer attachment relationships in situations of severe war trauma may be less likely to develop posttraumatic stress symptoms. Interventions to enhance peer support in this post conflict setting would benefit this vulnerable population. PMID:24614005

The Identification of Novel Potential Injury Mechanisms and Candidate Biomarkers in Renal Allograft Rejection by Quantitative Proteomics*

PubMed Central

Sigdel, Tara K.; Salomonis, Nathan; Nicora, Carrie D.; Ryu, Soyoung; He, Jintang; Dinh, Van; Orton, Daniel J.; Moore, Ronald J.; Hsieh, Szu-Chuan; Dai, Hong; Thien-Vu, Minh; Xiao, Wenzhong; Smith, Richard D.; Qian, Wei-Jun; Camp, David G.; Sarwal, Minnie M.

2014-01-01

Early transplant dysfunction and failure because of immunological and nonimmunological factors still presents a significant clinical problem for transplant recipients. A critical unmet need is the noninvasive detection and prediction of immune injury such that acute injury can be reversed by proactive immunosuppression titration. In this study, we used iTRAQ -based proteomic discovery and targeted ELISA validation to discover and validate candidate urine protein biomarkers from 262 renal allograft recipients with biopsy-confirmed allograft injury. Urine samples were randomly split into a training set of 108 patients and an independent validation set of 154 patients, which comprised the clinical biopsy-confirmed phenotypes of acute rejection (AR) (n = 74), stable graft (STA) (n = 74), chronic allograft injury (CAI) (n = 58), BK virus nephritis (BKVN) (n = 38), nephrotic syndrome (NS) (n = 8), and healthy, normal control (HC) (n = 10). A total of 389 proteins were measured that displayed differential abundances across urine specimens of the injury types (p < 0.05) with a significant finding that SUMO2 (small ubiquitin-related modifier 2) was identified as a “hub” protein for graft injury irrespective of causation. Sixty-nine urine proteins had differences in abundance (p < 0.01) in AR compared with stable graft, of which 12 proteins were up-regulated in AR with a mean fold increase of 2.8. Nine urine proteins were highly specific for AR because of their significant differences (p < 0.01; fold increase >1.5) from all other transplant categories (HLA class II protein HLA-DRB1, KRT14, HIST1H4B, FGG, ACTB, FGB, FGA, KRT7, DPP4). Increased levels of three of these proteins, fibrinogen beta (FGB; p = 0.04), fibrinogen gamma (FGG; p = 0.03), and HLA DRB1 (p = 0.003) were validated by ELISA in AR using an independent sample set. The fibrinogen proteins further segregated AR from BK virus nephritis (FGB p = 0.03, FGG p = 0.02), a finding that supports the utility of monitoring these urinary proteins for the specific and sensitive noninvasive diagnosis of acute renal allograft rejection. PMID:24335474

The uniform data system for medical rehabilitation: report of patients with traumatic spinal cord injury discharged from rehabilitation programs in 2002-2010.

PubMed

Granger, Carl V; Karmarkar, Amol M; Graham, James E; Deutsch, Anne; Niewczyk, Paulette; Divita, Margaret A; Ottenbacher, Kenneth J

2012-04-01

This study aimed to provide benchmarking information from a large national sample of patients receiving inpatient rehabilitation after a traumatic spinal cord injury. This was an analysis of secondary data from 891 inpatient medical rehabilitation facilities in the United States that contributed traumatic spinal cord injury data to the Uniform Data System for Medical Rehabilitation from January 2002 to December 2010. Variables analyzed included demographic information (age, sex, marital status, race/ethnicity, prehospital living setting, discharge setting), hospitalization information (length of stay, program interruptions, payer, onset date, rehabilitation impairment group, International Classification of Diseases 9 codes for admitting diagnosis, co-morbidities), and functional status (Functional Independence Measure [FIM] instrument ratings at admission and discharge, FIM efficiency, FIM gain). The final sample included 47,153 patients with traumatic spinal cord injury. Overall, the mean length of stay was 26.2 ± 23.2 days: yearly means ranged from 29.7 ± 25.4 in 2002 to 22.9 ± 18.9 in 2009. FIM total admission and discharge ratings also declined during the 8-yr study period; admission decreased from 60.5 ± 17.4 to 55.9 ± 16.3; discharge decreased from 86.1 ± 23.8 to 82.4 ± 23.4. Rehabilitation efficiency (FIM gain per day) remained relatively stable over time (1.6 ± 1.7 points per day). The percentage of all patients discharged to the community ranged from 75.8% to 71.5% per year. Wheelchair users stayed in rehabilitation longer than did persons who could walk (34.6 ± 217.4 vs. 17.4 ± 14.1 days) and also experienced less functional improvement (21.6 ± 15.8 vs. 29.6 ± 16.3 FIM points). National data from persons with traumatic spinal cord injury in 2002-2010 indicate that lengths of stay declined, but efficiency in functional independence was stable to slightly increased. More than 70% of patients were consistently discharged to community settings after inpatient rehabilitation.

Emotional and tangible social support in a German population-based sample: Development and validation of the Brief Social Support Scale (BS6).

PubMed

Beutel, Manfred E; Brähler, Elmar; Wiltink, Jörg; Michal, Matthias; Klein, Eva M; Jünger, Claus; Wild, Philipp S; Münzel, Thomas; Blettner, Maria; Lackner, Karl; Nickels, Stefan; Tibubos, Ana N

2017-01-01

Aim of the study was the development and validation of the psychometric properties of a six-item bi-factorial instrument for the assessment of social support (emotional and tangible support) with a population-based sample. A cross-sectional data set of N = 15,010 participants enrolled in the Gutenberg Health Study (GHS) in 2007-2012 was divided in two sub-samples. The GHS is a population-based, prospective, observational single-center cohort study in the Rhein-Main-Region in western Mid-Germany. The first sub-sample was used for scale development by performing an exploratory factor analysis. In order to test construct validity, confirmatory factor analyses were run to compare the extracted bi-factorial model with the one-factor solution. Reliability of the scales was indicated by calculating internal consistency. External validity was tested by investigating demographic characteristics health behavior, and distress using analysis of variance, Spearman and Pearson correlation analysis, and logistic regression analysis. Based on an exploratory factor analysis, a set of six items was extracted representing two independent factors. The two-factor structure of the Brief Social Support Scale (BS6) was confirmed by the results of the confirmatory factor analyses. Fit indices of the bi-factorial model were good and better compared to the one-factor solution. External validity was demonstrated for the BS6. The BS6 is a reliable and valid short scale that can be applied in social surveys due to its brevity to assess emotional and practical dimensions of social support.

A chronic fatigue syndrome – related proteome in human cerebrospinal fluid

PubMed Central

Baraniuk, James N; Casado, Begona; Maibach, Hilda; Clauw, Daniel J; Pannell, Lewis K; Hess S, Sonja

2005-01-01

Background Chronic Fatigue Syndrome (CFS), Persian Gulf War Illness (PGI), and fibromyalgia are overlapping symptom complexes without objective markers or known pathophysiology. Neurological dysfunction is common. We assessed cerebrospinal fluid to find proteins that were differentially expressed in this CFS-spectrum of illnesses compared to control subjects. Methods Cerebrospinal fluid specimens from 10 CFS, 10 PGI, and 10 control subjects (50 μl/subject) were pooled into one sample per group (cohort 1). Cohort 2 of 12 control and 9 CFS subjects had their fluids (200 μl/subject) assessed individually. After trypsin digestion, peptides were analyzed by capillary chromatography, quadrupole-time-of-flight mass spectrometry, peptide sequencing, bioinformatic protein identification, and statistical analysis. Results Pooled CFS and PGI samples shared 20 proteins that were not detectable in the pooled control sample (cohort 1 CFS-related proteome). Multilogistic regression analysis (GLM) of cohort 2 detected 10 proteins that were shared by CFS individuals and the cohort 1 CFS-related proteome, but were not detected in control samples. Detection of ≥1 of a select set of 5 CFS-related proteins predicted CFS status with 80% concordance (logistic model). The proteins were α-1-macroglobulin, amyloid precursor-like protein 1, keratin 16, orosomucoid 2 and pigment epithelium-derived factor. Overall, 62 of 115 proteins were newly described. Conclusion This pilot study detected an identical set of central nervous system, innate immune and amyloidogenic proteins in cerebrospinal fluids from two independent cohorts of subjects with overlapping CFS, PGI and fibromyalgia. Although syndrome names and definitions were different, the proteome and presumed pathological mechanism(s) may be shared. PMID:16321154

Comparison of gene expression microarray data with count-based RNA measurements informs microarray interpretation.

PubMed

Richard, Arianne C; Lyons, Paul A; Peters, James E; Biasci, Daniele; Flint, Shaun M; Lee, James C; McKinney, Eoin F; Siegel, Richard M; Smith, Kenneth G C

2014-08-04

Although numerous investigations have compared gene expression microarray platforms, preprocessing methods and batch correction algorithms using constructed spike-in or dilution datasets, there remains a paucity of studies examining the properties of microarray data using diverse biological samples. Most microarray experiments seek to identify subtle differences between samples with variable background noise, a scenario poorly represented by constructed datasets. Thus, microarray users lack important information regarding the complexities introduced in real-world experimental settings. The recent development of a multiplexed, digital technology for nucleic acid measurement enables counting of individual RNA molecules without amplification and, for the first time, permits such a study. Using a set of human leukocyte subset RNA samples, we compared previously acquired microarray expression values with RNA molecule counts determined by the nCounter Analysis System (NanoString Technologies) in selected genes. We found that gene measurements across samples correlated well between the two platforms, particularly for high-variance genes, while genes deemed unexpressed by the nCounter generally had both low expression and low variance on the microarray. Confirming previous findings from spike-in and dilution datasets, this "gold-standard" comparison demonstrated signal compression that varied dramatically by expression level and, to a lesser extent, by dataset. Most importantly, examination of three different cell types revealed that noise levels differed across tissues. Microarray measurements generally correlate with relative RNA molecule counts within optimal ranges but suffer from expression-dependent accuracy bias and precision that varies across datasets. We urge microarray users to consider expression-level effects in signal interpretation and to evaluate noise properties in each dataset independently.

Blood Gene Expression Predicts Bronchiolitis Obliterans Syndrome

PubMed Central

Danger, Richard; Royer, Pierre-Joseph; Reboulleau, Damien; Durand, Eugénie; Loy, Jennifer; Tissot, Adrien; Lacoste, Philippe; Roux, Antoine; Reynaud-Gaubert, Martine; Gomez, Carine; Kessler, Romain; Mussot, Sacha; Dromer, Claire; Brugière, Olivier; Mornex, Jean-François; Guillemain, Romain; Dahan, Marcel; Knoop, Christiane; Botturi, Karine; Foureau, Aurore; Pison, Christophe; Koutsokera, Angela; Nicod, Laurent P.; Brouard, Sophie; Magnan, Antoine; Jougon, J.

2018-01-01

Bronchiolitis obliterans syndrome (BOS), the main manifestation of chronic lung allograft dysfunction, leads to poor long-term survival after lung transplantation. Identifying predictors of BOS is essential to prevent the progression of dysfunction before irreversible damage occurs. By using a large set of 107 samples from lung recipients, we performed microarray gene expression profiling of whole blood to identify early biomarkers of BOS, including samples from 49 patients with stable function for at least 3 years, 32 samples collected at least 6 months before BOS diagnosis (prediction group), and 26 samples at or after BOS diagnosis (diagnosis group). An independent set from 25 lung recipients was used for validation by quantitative PCR (13 stables, 11 in the prediction group, and 8 in the diagnosis group). We identified 50 transcripts differentially expressed between stable and BOS recipients. Three genes, namely POU class 2 associating factor 1 (POU2AF1), T-cell leukemia/lymphoma protein 1A (TCL1A), and B cell lymphocyte kinase, were validated as predictive biomarkers of BOS more than 6 months before diagnosis, with areas under the curve of 0.83, 0.77, and 0.78 respectively. These genes allow stratification based on BOS risk (log-rank test p < 0.01) and are not associated with time posttransplantation. This is the first published large-scale gene expression analysis of blood after lung transplantation. The three-gene blood signature could provide clinicians with new tools to improve follow-up and adapt treatment of patients likely to develop BOS. PMID:29375549

Approach for determining the contributions of phytoplankton, colored organic material, and nonalgal particles to the total spectral absorption in marine waters.

PubMed

Lin, Junfang; Cao, Wenxi; Wang, Guifeng; Hu, Shuibo

2013-06-20

Using a data set of 1333 samples, we assess the spectral absorption relationships of different wave bands for phytoplankton (ph) and particles. We find that a nonlinear model (second-order quadratic equations) delivers good performance in describing their spectral characteristics. Based on these spectral relationships, we develop a method for partitioning the total absorption coefficient into the contributions attributable to phytoplankton [a(ph)(λ)], colored dissolved organic material [CDOM; a(CDOM)(λ)], and nonalgal particles [NAP; a(NAP)(λ)]. This method is validated using a data set that contains 550 simultaneous measurements of phytoplankton, CDOM, and NAP from the NASA bio-Optical Marine Algorithm Dataset. We find that our method is highly efficient and robust, with significant accuracy: the relative root-mean-square errors (RMSEs) are 25.96%, 38.30%, and 19.96% for a(ph)(443), a(CDOM)(443), and the CDOM exponential slope, respectively. The performance is still satisfactory when the method is applied to water samples from the northern South China Sea as a regional case. The computed and measured absorption coefficients (167 samples) agree well with the RMSEs, i.e., 18.50%, 32.82%, and 10.21% for a(ph)(443), a(CDOM)(443), and the CDOM exponential slope, respectively. Finally, the partitioning method is applied directly to an independent data set (1160 samples) derived from the Bermuda Bio-Optics Project that contains relatively low absorption values, and we also obtain good inversion accuracy [RMSEs of 32.37%, 32.57%, and 11.52% for a(ph)(443), a(CDOM)(443), and the CDOM exponential slope, respectively]. Our results indicate that this partitioning method delivers satisfactory performance for the retrieval of a(ph), a(CDOM), and a(NAP). Therefore, this may be a useful tool for extracting absorption coefficients from in situ measurements or remotely sensed ocean-color data.

Batch Effect Confounding Leads to Strong Bias in Performance Estimates Obtained by Cross-Validation

PubMed Central

Delorenzi, Mauro

2014-01-01

Background With the large amount of biological data that is currently publicly available, many investigators combine multiple data sets to increase the sample size and potentially also the power of their analyses. However, technical differences (“batch effects”) as well as differences in sample composition between the data sets may significantly affect the ability to draw generalizable conclusions from such studies. Focus The current study focuses on the construction of classifiers, and the use of cross-validation to estimate their performance. In particular, we investigate the impact of batch effects and differences in sample composition between batches on the accuracy of the classification performance estimate obtained via cross-validation. The focus on estimation bias is a main difference compared to previous studies, which have mostly focused on the predictive performance and how it relates to the presence of batch effects. Data We work on simulated data sets. To have realistic intensity distributions, we use real gene expression data as the basis for our simulation. Random samples from this expression matrix are selected and assigned to group 1 (e.g., ‘control’) or group 2 (e.g., ‘treated’). We introduce batch effects and select some features to be differentially expressed between the two groups. We consider several scenarios for our study, most importantly different levels of confounding between groups and batch effects. Methods We focus on well-known classifiers: logistic regression, Support Vector Machines (SVM), k-nearest neighbors (kNN) and Random Forests (RF). Feature selection is performed with the Wilcoxon test or the lasso. Parameter tuning and feature selection, as well as the estimation of the prediction performance of each classifier, is performed within a nested cross-validation scheme. The estimated classification performance is then compared to what is obtained when applying the classifier to independent data. PMID:24967636

Mobile suitcase laboratory for rapid detection of Leishmania donovani using recombinase polymerase amplification assay.

PubMed

Mondal, Dinesh; Ghosh, Prakash; Khan, Md Anik Ashfaq; Hossain, Faria; Böhlken-Fascher, Susanne; Matlashewski, Greg; Kroeger, Axel; Olliaro, Piero; Abd El Wahed, Ahmed

2016-05-13

Leishmania donovani (LD) is a protozoan parasite transmitted to humans from sand flies, which causes Visceral Leishmaniasis (VL). Currently, the diagnosis is based on presence of the anti-LD antibodies and clinical symptoms. Molecular diagnosis would require real-time PCR, which is not easy to implement at field settings. In this study, we report on the development and testing of a recombinase polymerase amplification (RPA) assay for the detection of LD. A genomic DNA sample was applied to determine the assay analytical sensitivity. The cross-reactivity of the assay was tested by DNA of Leishmania spp. and of pathogens considered for differential diagnosis. The clinical performance of the assay was evaluated on LD positive and negative samples. All results were compared with real-time PCR. To allow the use of the assay at field settings, a mobile suitcase laboratory (56 × 45.5 × 26.5 cm) was developed and operated at the local hospital in Mymensingh, Bangladesh. The LD RPA assay detected equivalent to one LD genomic DNA. The assay was performed at constant temperature (42 °C) in 15 min. The RPA assay also detected other Leishmania species (L. major, L. aethiopica and L. infantum), but did not identify nucleic acid of other pathogens. Forty-eight samples from VL, asymptomatic and post-kala-azar dermal leishmaniasis subjects were detected positive and 48 LD-negative samples were negative by both LD RPA and real-time PCR assays, which indicates 100 % agreement. The suitcase laboratory was successfully operated at the local hospital by using a solar-powered battery. DNA extraction was performed by a novel magnetic bead based method (SpeedXtract), in which a simple fast lysis protocol was applied. Moreover, All reagents were cold-chain independent. The mobile suitcase laboratory using RPA is ideal for rapid sensitive and specific detection of LD especially at low resource settings and could contribute to VL control and elimination programmes.

Mapping of explosive contamination using GC/chemiluminescence and ion mobility spectrometry techniques

NASA Astrophysics Data System (ADS)

Miller, Carla J.; Glenn, D. F.; Hartenstein, Steven D.; Hallowell, Susan F.

1998-12-01

Recent efforts at the Idaho National Engineering and Environmental Laboratory (INEEL) have included mapping explosive contamination resulting from manufacturing and carrying improvised explosive devices (IEDs). Two types of trace detection equipment were used to determine levels of contamination from designated sampling areas. A total of twenty IEDs were constructed: ten using TNT and ten using C-4. Two test scenarios were used. The first scenario tracked the activities of a manufacturer who straps the device onto an independent courier. The courier then performed a series of activities to simulate waiting in an airport. The second scenario tracked the activities of a manufacturer who also served as the courier. A sample set for each test consisted of thirty samples from various locations on each IED manufacturer, thirty from each IED courier, twenty-five from the manufacturing area, and twenty-five from the courier area. Pre-samples and post-samples were collected for analysis with each detection technique. Samples analyzed by gc/chemiluminescence were taken by swiping a teflon- coated sampling swipe across the surface of the sampling area to pick up any explosive particles. Samples analyzed by ion mobility spectrometry (IMS) were taken from the clothing of the manufacturer and courier by vacuuming the surface and collecting particulates on a fiberglass filter. Samples for IMS analysis from the manufacturing and courier rooms were taken by wiping a cotton sampling swipe across the surface area. Currently, building IEDs and monitoring the explosive contamination is being directed toward detection with portal monitors.

STBase: One Million Species Trees for Comparative Biology

PubMed Central

McMahon, Michelle M.; Deepak, Akshay; Fernández-Baca, David; Boss, Darren; Sanderson, Michael J.

2015-01-01

Comprehensively sampled phylogenetic trees provide the most compelling foundations for strong inferences in comparative evolutionary biology. Mismatches are common, however, between the taxa for which comparative data are available and the taxa sampled by published phylogenetic analyses. Moreover, many published phylogenies are gene trees, which cannot always be adapted immediately for species level comparisons because of discordance, gene duplication, and other confounding biological processes. A new database, STBase, lets comparative biologists quickly retrieve species level phylogenetic hypotheses in response to a query list of species names. The database consists of 1 million single- and multi-locus data sets, each with a confidence set of 1000 putative species trees, computed from GenBank sequence data for 413,000 eukaryotic taxa. Two bodies of theoretical work are leveraged to aid in the assembly of multi-locus concatenated data sets for species tree construction. First, multiply labeled gene trees are pruned to conflict-free singly-labeled species-level trees that can be combined between loci. Second, impacts of missing data in multi-locus data sets are ameliorated by assembling only decisive data sets. Data sets overlapping with the user’s query are ranked using a scheme that depends on user-provided weights for tree quality and for taxonomic overlap of the tree with the query. Retrieval times are independent of the size of the database, typically a few seconds. Tree quality is assessed by a real-time evaluation of bootstrap support on just the overlapping subtree. Associated sequence alignments, tree files and metadata can be downloaded for subsequent analysis. STBase provides a tool for comparative biologists interested in exploiting the most relevant sequence data available for the taxa of interest. It may also serve as a prototype for future species tree oriented databases and as a resource for assembly of larger species phylogenies from precomputed trees. PMID:25679219

Hydrological, water-quality, and ecological data for streams in Independence, Missouri, June 2005 through September 2013

USGS Publications Warehouse

Niesen, Shelley L.; Christensen, Eric D.

2015-01-01

Water-quality, hydrological, and ecological data collected from June 2005 through September 2013 from the Little Blue River and smaller streams within the City of Independence, Missouri, are presented in this report. These data were collected as a part of an ongoing cooperative study between the U.S. Geological Survey and the City of Independence Water Pollution Control Department to characterize the water quality and ecological condition of Independence streams. The quantities, sources of selected constituents, and processes affecting water quality and aquatic life were evaluated to determine the resulting ecological condition of streams within Independence. Data collected for this study fulfill the municipal separate sewer system permit requirements for the City of Independence and can be used to provide a baseline with which city managers can determine the effectiveness of current (2014) and future best management practices within Independence. Continuous streamflow and water-quality data, collected during base flow and stormflow, included physical and chemical properties, inorganic constituents, common organic micro-constituents, pesticides in streambed sediment and surface water, fecal indicator bacteria and microbial source tracking data, and suspended sediment. Dissolved oxygen, pH, specific conductance, water temperature, and turbidity data were measured continuously at seven sites within Independence. Base-flow and stormflow samples were collected at eight gaged and two ungaged sites. Fecal sources samples were collected for reference for microbial source tracking, and sewage influent samples were collected as additional source samples. Dry-weather screening was done on 11 basins within Independence to identify potential contaminant sources to the streams. Benthic macroinvertebrate community surveys and habitat assessments were done on 10 stream sites and 2 comparison sites outside the city. Sampling and laboratory procedures and quality-assurance and quality-control methods used in data collection for this study are described in this report.

Estimating the gravitational-wave content of initial-data sets for numerical relativity using the Beetle--Burko scalar

NASA Astrophysics Data System (ADS)

Burko, Lior M.

2006-04-01

The Beetle--Burko radiation scalar is a gauge independent, tetrad independent, and background independent quantity that depends only on the radiative degrees of freedom where the notion of radiation is incontrovertible, and can be computed from spatial data as is typical in numerical relativity simulations even for strongly dynamical spacetimes. We show that the Beetle--Burko radiation scalar can be used for estimating the graviational-wave content of initial-data sets in numerical relativity, and can thus be useful for the construction of physically meaningful ones, and the identification of ``junk'' data on the intial value surface. We apply this method for the case of a momentarily stationary black hole binary, and demonstrate how the Beetle-- Burko scalar distinguishes between Misner and Brill--Lindquist initial data. The method, however, is robust, and is applicable to generic initial data sets. In addition to initial data sets, the Beetle--Burko radiation scalar is equally applicable also for evolution data.

Quantitative transmission Raman spectroscopy of pharmaceutical tablets and capsules.

PubMed

Johansson, Jonas; Sparén, Anders; Svensson, Olof; Folestad, Staffan; Claybourn, Mike

2007-11-01

Quantitative analysis of pharmaceutical formulations using the new approach of transmission Raman spectroscopy has been investigated. For comparison, measurements were also made in conventional backscatter mode. The experimental setup consisted of a Raman probe-based spectrometer with 785 nm excitation for measurements in backscatter mode. In transmission mode the same system was used to detect the Raman scattered light, while an external diode laser of the same type was used as excitation source. Quantitative partial least squares models were developed for both measurement modes. The results for tablets show that the prediction error for an independent test set was lower for the transmission measurements with a relative root mean square error of about 2.2% as compared with 2.9% for the backscatter mode. Furthermore, the models were simpler in the transmission case, for which only a single partial least squares (PLS) component was required to explain the variation. The main reason for the improvement using the transmission mode is a more representative sampling of the tablets compared with the backscatter mode. Capsules containing mixtures of pharmaceutical powders were also assessed by transmission only. The quantitative results for the capsules' contents were good, with a prediction error of 3.6% w/w for an independent test set. The advantage of transmission Raman over backscatter Raman spectroscopy has been demonstrated for quantitative analysis of pharmaceutical formulations, and the prospects for reliable, lean calibrations for pharmaceutical analysis is discussed.

Boomerang: A Method for Recursive Reclassification

PubMed Central

Devlin, Sean M.; Ostrovnaya, Irina; Gönen, Mithat

2016-01-01

Summary While there are many validated prognostic classifiers used in practice, often their accuracy is modest and heterogeneity in clinical outcomes exists in one or more risk subgroups. Newly available markers, such as genomic mutations, may be used to improve the accuracy of an existing classifier by reclassifying patients from a heterogenous group into a higher or lower risk category. The statistical tools typically applied to develop the initial classifiers are not easily adapted towards this reclassification goal. In this paper, we develop a new method designed to refine an existing prognostic classifier by incorporating new markers. The two-stage algorithm called Boomerang first searches for modifications of the existing classifier that increase the overall predictive accuracy and then merges to a pre-specified number of risk groups. Resampling techniques are proposed to assess the improvement in predictive accuracy when an independent validation data set is not available. The performance of the algorithm is assessed under various simulation scenarios where the marker frequency, degree of censoring, and total sample size are varied. The results suggest that the method selects few false positive markers and is able to improve the predictive accuracy of the classifier in many settings. Lastly, the method is illustrated on an acute myeloid leukemia dataset where a new refined classifier incorporates four new mutations into the existing three category classifier and is validated on an independent dataset. PMID:26754051

Vision and Voyages: Lessons Learned from the Planetary Decadal Survey

NASA Astrophysics Data System (ADS)

Squyres, S. W.

2015-12-01

The most recent planetary decadal survey, entitled Vision and Voyages for Planetary Science in the Decade 2013-2022, provided a detailed set of priorities for solar system exploration. Those priorities drew on broad input from the U.S. and international planetary science community. Using white papers, town hall meetings, and open meetings of the decadal committees, community views were solicited and a consensus began to emerge. The final report summarized that consensus. Like many past decadal reports, the centerpiece of Vision and Voyages was a set of priorities for future space flight projects. Two things distinguished this report from some previous decadals. First, conservative and independent cost estimates were obtained for all of the projects that were considered. These independent cost estimates, rather than estimates generated by project advocates, were used to judge each project's expected science return per dollar. Second, rather than simply accepting NASA's ten-year projection of expected funding for planetary exploration, decision rules were provided to guide program adjustments if actual funding did not follow projections. To date, NASA has closely followed decadal recommendations. In particular, the two highest priority "flagship" missions, a Mars rover to collect samples for return to Earth and a mission to investigate a possible ocean on Europa, are both underway. The talk will describe the planetary decadal process in detail, and provide a more comprehensive assessment of NASA's response to it.