Within-Group Differences in Sexual Orientation and Identity

ERIC Educational Resources Information Center

Worthington, Roger L.; Reynolds, Amy L.

2009-01-01

The purpose of this investigation was to examine within-group differences among self-identified sexual orientation and identity groups. To understand these within-group differences, 2 types of analysis were conducted. First, a sample of 2,732 participants completed the Sexual Orientation and Identity Scale. Cluster analyses were used to identify 3…

Joint genetic analysis of hippocampal size in mouse and human identifies a novel gene linked to neurodegenerative disease.

PubMed

Ashbrook, David G; Williams, Robert W; Lu, Lu; Stein, Jason L; Hibar, Derrek P; Nichols, Thomas E; Medland, Sarah E; Thompson, Paul M; Hager, Reinmar

2014-10-03

Variation in hippocampal volume has been linked to significant differences in memory, behavior, and cognition among individuals. To identify genetic variants underlying such differences and associated disease phenotypes, multinational consortia such as ENIGMA have used large magnetic resonance imaging (MRI) data sets in human GWAS studies. In addition, mapping studies in mouse model systems have identified genetic variants for brain structure variation with great power. A key challenge is to understand how genetically based differences in brain structure lead to the propensity to develop specific neurological disorders. We combine the largest human GWAS of brain structure with the largest mammalian model system, the BXD recombinant inbred mouse population, to identify novel genetic targets influencing brain structure variation that are linked to increased risk for neurological disorders. We first use a novel cross-species, comparative analysis using mouse and human genetic data to identify a candidate gene, MGST3, associated with adult hippocampus size in both systems. We then establish the coregulation and function of this gene in a comprehensive systems-analysis. We find that MGST3 is associated with hippocampus size and is linked to a group of neurodegenerative disorders, such as Alzheimer's.

Similarity of markers identified from cancer gene expression studies: observations from GEO.

PubMed

Shi, Xingjie; Shen, Shihao; Liu, Jin; Huang, Jian; Zhou, Yong; Ma, Shuangge

2014-09-01

Gene expression profiling has been extensively conducted in cancer research. The analysis of multiple independent cancer gene expression datasets may provide additional information and complement single-dataset analysis. In this study, we conduct multi-dataset analysis and are interested in evaluating the similarity of cancer-associated genes identified from different datasets. The first objective of this study is to briefly review some statistical methods that can be used for such evaluation. Both marginal analysis and joint analysis methods are reviewed. The second objective is to apply those methods to 26 Gene Expression Omnibus (GEO) datasets on five types of cancers. Our analysis suggests that for the same cancer, the marker identification results may vary significantly across datasets, and different datasets share few common genes. In addition, datasets on different cancers share few common genes. The shared genetic basis of datasets on the same or different cancers, which has been suggested in the literature, is not observed in the analysis of GEO data. © The Author 2013. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Analysis of Radiation Damage in Light Water Reactors: Comparison of Cluster Analysis Methods for the Analysis of Atom Probe Data.

PubMed

Hyde, Jonathan M; DaCosta, Gérald; Hatzoglou, Constantinos; Weekes, Hannah; Radiguet, Bertrand; Styman, Paul D; Vurpillot, Francois; Pareige, Cristelle; Etienne, Auriane; Bonny, Giovanni; Castin, Nicolas; Malerba, Lorenzo; Pareige, Philippe

2017-04-01

Irradiation of reactor pressure vessel (RPV) steels causes the formation of nanoscale microstructural features (termed radiation damage), which affect the mechanical properties of the vessel. A key tool for characterizing these nanoscale features is atom probe tomography (APT), due to its high spatial resolution and the ability to identify different chemical species in three dimensions. Microstructural observations using APT can underpin development of a mechanistic understanding of defect formation. However, with atom probe analyses there are currently multiple methods for analyzing the data. This can result in inconsistencies between results obtained from different researchers and unnecessary scatter when combining data from multiple sources. This makes interpretation of results more complex and calibration of radiation damage models challenging. In this work simulations of a range of different microstructures are used to directly compare different cluster analysis algorithms and identify their strengths and weaknesses.

Integrative multi-platform meta-analysis of gene expression profiles in pancreatic ductal adenocarcinoma patients for identifying novel diagnostic biomarkers.

PubMed

Irigoyen, Antonio; Jimenez-Luna, Cristina; Benavides, Manuel; Caba, Octavio; Gallego, Javier; Ortuño, Francisco Manuel; Guillen-Ponce, Carmen; Rojas, Ignacio; Aranda, Enrique; Torres, Carolina; Prados, Jose

2018-01-01

Applying differentially expressed genes (DEGs) to identify feasible biomarkers in diseases can be a hard task when working with heterogeneous datasets. Expression data are strongly influenced by technology, sample preparation processes, and/or labeling methods. The proliferation of different microarray platforms for measuring gene expression increases the need to develop models able to compare their results, especially when different technologies can lead to signal values that vary greatly. Integrative meta-analysis can significantly improve the reliability and robustness of DEG detection. The objective of this work was to develop an integrative approach for identifying potential cancer biomarkers by integrating gene expression data from two different platforms. Pancreatic ductal adenocarcinoma (PDAC), where there is an urgent need to find new biomarkers due its late diagnosis, is an ideal candidate for testing this technology. Expression data from two different datasets, namely Affymetrix and Illumina (18 and 36 PDAC patients, respectively), as well as from 18 healthy controls, was used for this study. A meta-analysis based on an empirical Bayesian methodology (ComBat) was then proposed to integrate these datasets. DEGs were finally identified from the integrated data by using the statistical programming language R. After our integrative meta-analysis, 5 genes were commonly identified within the individual analyses of the independent datasets. Also, 28 novel genes that were not reported by the individual analyses ('gained' genes) were also discovered. Several of these gained genes have been already related to other gastroenterological tumors. The proposed integrative meta-analysis has revealed novel DEGs that may play an important role in PDAC and could be potential biomarkers for diagnosing the disease.

Decoding and Reading Comprehension: A Meta-Analysis to Identify Which Reader and Assessment Characteristics Influence the Strength of the Relationship in English

ERIC Educational Resources Information Center

García, J. Ricardo; Cain, Kate

2014-01-01

The twofold purpose of this meta-analysis was to determine the relative importance of decoding skills to reading comprehension in reading development and to identify which reader characteristics and reading assessment characteristics contribute to differences in the decoding and reading comprehension correlation. A meta-analysis of 110 studies…

Forest and rangeland ecosystem condition indicators: identifying national areas of opportunity using data development analysis

Treesearch

John G. Hof; Curtis H. Flather; Tony J. Baltic; Rudy M. King

2004-01-01

This article reports the methodology and results of a data envelopment analysis (DEA) that attempts to identify areas in the country where there is maximum potential for improving the forest and rangeland condition, based on 12 indicator variables. This analysis differs from previous DEA studies in that the primary variables are measures of human activity and...

Plasma metabolomic study in Chinese patients with wet age-related macular degeneration.

PubMed

Luo, Dan; Deng, Tingting; Yuan, Wei; Deng, Hui; Jin, Ming

2017-09-06

Age-related macular degeneration (AMD) is a leading disease associated with blindness. It has a high incidence and complex pathogenesis. We aimed to study the metabolomic characteristics in Chinese patients with wet AMD by analyzing the morning plasma of 20 healthy controls and 20 wet AMD patients for metabolic differences. We used ultra-high-pressure liquid chromatography and quadrupole-time-of-flight mass spectrometry for this analysis. The relationship of these differences with AMD pathophysiology was also assessed. Remaining data were normalized using Pareto scaling, and then valid data were handled using multivariate data analysis with MetaboAnalysis software, including unsupervised principal component analysis and supervised partial least squares-discriminate analysis. The purpose of the present work was to identify significant metabolites for the analyses. Hierarchical clustering was conducted to identify metabolites that differed between the two groups. Significant metabolites were then identified using the established database, and features were mapped on the Kyoto Encyclopedia of Genes and Genomes. A total of 5443 ion peaks were detected, all of them attributable to the same 10 metabolites. These included some amino acids, isomaltose, hydrocortisone, and biliverdin. The heights of these peaks differed significantly between the two groups. The biosynthesis of amino acids pathways also differed profoundly between patients with wet AMD and controls. These findings suggested that metabolic profiles and and pathways differed between wet AMD and controls and may provide promising new targets for AMD-directed therapeutics and diagnostics.

The importance of source area mapping for rockfall hazard analysis

NASA Astrophysics Data System (ADS)

Valagussa, Andrea; Frattini, Paolo; Crosta, Giovanni B.

2013-04-01

A problem in the characterization of the area affected by rockfall is the correct source areas definition. Different positions or different size of the source areas along a cliff result in different possibilities of propagation and diverse interaction with passive countermeasures present in the area. Through the use of Hy-Stone (Crosta et al., 2004), a code able to perform 3D numerical modeling of rockfall processes, different types of source areas were tested on a case study slope along the western flank of the Mt. de La Saxe (Courmayeur, AO), developing between 1200 and 2055 m s.l.m. The first set of source areas consists of unstable rock masses identified on the basis of field survey and Terrestrial Laser Scanning (IMAGEO, 2011). A second set of source areas has been identified by using different thresholds of slope gradient. We tested slope thresholds between 50° and 75° at 5° intervals. The third source area dataset has been generating by performing a kinematic stability analysis. For this analysis, we mapped the join sets along the rocky cliff by means of the software COLTOP 3D (Jaboyedoff, 2004), and then we identified the portions of rocky cliff where planar/wedge and toppling failures are possible assuming an average friction angle of 35°. Through the outputs of the Hy-Stone models we extracted and analyzed the kinetic energy, height of fly and velocity of the blocks falling along the rocky cliff in order to compare the controls of different source areas. We observed strong variations of kinetic energy and fly height among the different models, especially when using unstable masses identified through Terrestrial Laser Scanning. This is mainly related to the size of the blocks identified as susceptible to failure. On the contrary, the slope gradient thresholds does not have a strong impact on rockfall propagation. This contribution highlights the importance of a careful and appropriate mapping of rockfall source area for rockfall hazard analysis and the design of passive countermeasures.

Comparative analysis of gene expression profiles of hip articular cartilage between non-traumatic necrosis and osteoarthritis.

PubMed

Wang, Wenyu; Liu, Yang; Hao, Jingcan; Zheng, Shuyu; Wen, Yan; Xiao, Xiao; He, Awen; Fan, Qianrui; Zhang, Feng; Liu, Ruiyu

2016-10-10

Hip cartilage destruction is consistently observed in the non-traumatic osteonecrosis of femoral head (NOFH) and accelerates its bone necrosis. The molecular mechanism underlying the cartilage damage of NOFH remains elusive. In this study, we conducted a systematically comparative study of gene expression profiles between NOFH and osteoarthritis (OA). Hip articular cartilage specimens were collected from 12 NOFH patients and 12 controls with traumatic femoral neck fracture for microarray (n=4) and quantitative real-time PCR validation experiments (n=8). Gene expression profiling of articular cartilage was performed using Agilent Human 4×44K Microarray chip. The accuracy of microarray experiment was further validated by qRT-PCR. Gene expression results of OA hip cartilage were derived from previously published study. Significance Analysis of Microarrays (SAM) software was applied for identifying differently expressed genes. Gene ontology (GO) and pathway enrichment analysis were conducted by Gene Set Enrichment Analysis software and DAVID tool, respectively. Totally, 27 differently expressed genes were identified for NOFH. Comparing the gene expression profiles of NOFH cartilage and OA cartilage detected 8 common differently expressed genes, including COL5A1, OGN, ANGPTL4, CRIP1, NFIL3, METRNL, ID2 and STEAP1. GO comparative analysis identified 10 common significant GO terms, mainly implicated in apoptosis and development process. Pathway comparative analysis observed that ECM-receptor interaction pathway and focal adhesion pathway were enriched in the differently expressed genes of both NOFH and hip OA. In conclusion, we identified a set of differently expressed genes, GO and pathways for NOFH articular destruction, some of which were also involved in the hip OA. Our study results may help to reveal the pathogenetic similarities and differences of cartilage damage of NOFH and hip OA. Copyright © 2016 Elsevier B.V. All rights reserved.

Development and Validation of 2D Difference Intensity Analysis for Chemical Library Screening by Protein-Detected NMR Spectroscopy.

PubMed

Egner, John M; Jensen, Davin R; Olp, Michael D; Kennedy, Nolan W; Volkman, Brian F; Peterson, Francis C; Smith, Brian C; Hill, R Blake

2018-03-02

An academic chemical screening approach was developed by using 2D protein-detected NMR, and a 352-chemical fragment library was screened against three different protein targets. The approach was optimized against two protein targets with known ligands: CXCL12 and BRD4. Principal component analysis reliably identified compounds that induced nonspecific NMR crosspeak broadening but did not unambiguously identify ligands with specific affinity (hits). For improved hit detection, a novel scoring metric-difference intensity analysis (DIA)-was devised that sums all positive and negative intensities from 2D difference spectra. Applying DIA quickly discriminated potential ligands from compounds inducing nonspecific NMR crosspeak broadening and other nonspecific effects. Subsequent NMR titrations validated chemotypes important for binding to CXCL12 and BRD4. A novel target, mitochondrial fission protein Fis1, was screened, and six hits were identified by using DIA. Screening these diverse protein targets identified quinones and catechols that induced nonspecific NMR crosspeak broadening, hampering NMR analyses, but are currently not computationally identified as pan-assay interference compounds. The results established a streamlined screening workflow that can easily be scaled and adapted as part of a larger screening pipeline to identify fragment hits and assess relative binding affinities in the range of 0.3-1.6 mm. DIA could prove useful in library screening and other applications in which NMR chemical shift perturbations are measured. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Bifactor Approach to Model Multifaceted Constructs in Statistical Mediation Analysis

ERIC Educational Resources Information Center

Gonzalez, Oscar; MacKinnon, David P.

2018-01-01

Statistical mediation analysis allows researchers to identify the most important mediating constructs in the causal process studied. Identifying specific mediators is especially relevant when the hypothesized mediating construct consists of multiple related facets. The general definition of the construct and its facets might relate differently to…

Exploratory Factor Analysis of Reading, Spelling, and Math Errors

ERIC Educational Resources Information Center

O'Brien, Rebecca; Pan, Xingyu; Courville, Troy; Bray, Melissa A.; Breaux, Kristina; Avitia, Maria; Choi, Dowon

2017-01-01

Norm-referenced error analysis is useful for understanding individual differences in students' academic skill development and for identifying areas of skill strength and weakness. The purpose of the present study was to identify underlying connections between error categories across five language and math subtests of the Kaufman Test of…

Sleep in patients with remitted bipolar disorders: a meta-analysis of actigraphy studies.

PubMed

Geoffroy, P A; Scott, J; Boudebesse, C; Lajnef, M; Henry, C; Leboyer, M; Bellivier, F; Etain, B

2015-02-01

Sleep dysregulation is highly prevalent in bipolar disorders (BDs), with previous actigraphic studies demonstrating sleep abnormalities during depressive, manic, and interepisode periods. We undertook a meta-analysis of published actigraphy studies to identify whether any abnormalities in the reported sleep profiles of remitted BD cases differ from controls. A systematic review identified independent studies that were eligible for inclusion in a random effects meta-analysis. Effect sizes for actigraphy parameters were expressed as standardized mean differences (SMD) with 95% confidence intervals (95% CI). Nine of 248 identified studies met eligibility criteria. Compared with controls (N=210), remitted BD cases (N=202) showed significant differences in SMD for sleep latency (0.51 [0.28-0.73]), sleep duration (0.57 [0.30-0.84]), wake after sleep onset (WASO) (0.28 [0.06-0.50]) and sleep efficiency (-0.38 [-0.70-0.07]). Moderate heterogeneity was identified for sleep duration (I2=44%) and sleep efficiency (I2=44%). Post hoc meta-regression analyses demonstrated that larger SMD for sleep duration were identified for studies with a greater age difference between BD cases and controls (β=0.22; P=0.03) and non-significantly lower levels of residual depressive symptoms in BD cases (β=-0.13; P=0.07). This meta-analysis of sleep in remitted bipolar disorder highlights disturbances in several sleep parameters. Future actigraphy studies should pay attention to age matching and levels of residual depressive symptoms. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Accounting for Scale Heterogeneity in Healthcare-Related Discrete Choice Experiments when Comparing Stated Preferences: A Systematic Review.

PubMed

Wright, Stuart J; Vass, Caroline M; Sim, Gene; Burton, Michael; Fiebig, Denzil G; Payne, Katherine

2018-02-28

Scale heterogeneity, or differences in the error variance of choices, may account for a significant amount of the observed variation in the results of discrete choice experiments (DCEs) when comparing preferences between different groups of respondents. The aim of this study was to identify if, and how, scale heterogeneity has been addressed in healthcare DCEs that compare the preferences of different groups. A systematic review identified all healthcare DCEs published between 1990 and February 2016. The full-text of each DCE was then screened to identify studies that compared preferences using data generated from multiple groups. Data were extracted and tabulated on year of publication, samples compared, tests for scale heterogeneity, and analytical methods to account for scale heterogeneity. Narrative analysis was used to describe if, and how, scale heterogeneity was accounted for when preferences were compared. A total of 626 healthcare DCEs were identified. Of these 199 (32%) aimed to compare the preferences of different groups specified at the design stage, while 79 (13%) compared the preferences of groups identified at the analysis stage. Of the 278 included papers, 49 (18%) discussed potential scale issues, 18 (7%) used a formal method of analysis to account for scale between groups, and 2 (1%) accounted for scale differences between preference groups at the analysis stage. Scale heterogeneity was present in 65% (n = 13) of studies that tested for it. Analytical methods to test for scale heterogeneity included coefficient plots (n = 5, 2%), heteroscedastic conditional logit models (n = 6, 2%), Swait and Louviere tests (n = 4, 1%), generalised multinomial logit models (n = 5, 2%), and scale-adjusted latent class analysis (n = 2, 1%). Scale heterogeneity is a prevalent issue in healthcare DCEs. Despite this, few published DCEs have discussed such issues, and fewer still have used formal methods to identify and account for the impact of scale heterogeneity. The use of formal methods to test for scale heterogeneity should be used, otherwise the results of DCEs potentially risk producing biased and potentially misleading conclusions regarding preferences for aspects of healthcare.

Metabolomic differentiation of maca (Lepidium meyenii) accessions cultivated under different conditions using NMR and chemometric analysis.

PubMed

Zhao, Jianping; Avula, Bharathi; Chan, Michael; Clément, Céline; Kreuzer, Michael; Khan, Ikhlas A

2012-01-01

To gain insights on the effects of color type, cultivation history, and growing site on the composition alterations of maca (Lepidium meyenii Walpers) hypocotyls, NMR profiling combined with chemometric analysis was applied to investigate the metabolite variability in different maca accessions. Maca hypocotyls with different colors (yellow, pink, violet, and lead-colored) cultivated at different geographic sites and different areas were examined for differences in metabolite expression. Differentiations of the maca accessions grown under the different cultivation conditions were determined by principle component analyses (PCAs) which were performed on the datasets derived from their ¹H NMR spectra. A total of 16 metabolites were identified by NMR analysis, and the changes in metabolite levels in relation to the color types and growing conditions of maca hypocotyls were evaluated using univariate statistical analysis. In addition, the changes of the correlation pattern among the metabolites identified in the maca accessions planted at the two different sites were examined. The results from both multivariate and univariate analysis indicated that the planting site was the major determining factor with regards to metabolite variations in maca hypocotyls, while the color of maca accession seems to be of minor importance in this respect. © Georg Thieme Verlag KG Stuttgart · New York.

Language Learner Motivational Types: A Cluster Analysis Study

ERIC Educational Resources Information Center

Papi, Mostafa; Teimouri, Yasser

2014-01-01

The study aimed to identify different second language (L2) learner motivational types drawing on the framework of the L2 motivational self system. A total of 1,278 secondary school students learning English in Iran completed a questionnaire survey. Cluster analysis yielded five different groups based on the strength of different variables within…

Characterization of Aroma-Active Components and Antioxidant Activity Analysis of E-jiao (Colla Corii Asini) from Different Geographical Origins.

PubMed

Zhang, Shan; Xu, Lu; Liu, Yang-Xi; Fu, Hai-Yan; Xiao, Zuo-Bing; She, Yuan-Bin

2018-04-01

E-jiao (Colla Corii Asini, CCA) has been widely used as a healthy food and Chinese medicine. Although authentic CCA is characterized by its typical sweet and neutral fragrance, its aroma components have been rarely investigated. This work investigated the aroma-active components and antioxidant activity of 19 CCAs from different geographical origins. CCA extracts obtained by simultaneous distillation and extraction were analyzed by gas chromatography-mass spectrometry (GC-MS), gas chromatography-olfactometry (GC-O) and sensory analysis. The antioxidant activity of CCAs was determined by ABTS and DPPH assays. A total of 65 volatile compounds were identified and quantified by GC-MS and 23 aroma-active compounds were identified by GC-O and aroma extract dilution analysis. The most powerful aroma-active compounds were identified based on the flavor dilution factor and their contents were compared among the 19 CCAs. Principal component analysis of the 23 aroma-active components showed 3 significant clusters. Canonical correlation analysis between antioxidant assays and the 23 aroma-active compounds indicates strong correlation (r = 0.9776, p = 0.0281). Analysis of aroma-active components shows potential for quality evaluation and discrimination of CCAs from different geographical origins.

Classroom Behaviour and Academic Achievement: How Classroom Behaviour Categories Relate to Gender and Academic Performance

ERIC Educational Resources Information Center

Borg, Elin

2015-01-01

Latent profile analysis was used to identify different categories of students having different "profiles" using self-reported classroom behaviour. Four categories of students with unique classroom behaviour profiles were identified among secondary school students in Oslo, Norway (n = 1570). Analyses examined how classroom behaviour…

Analysis of Pre-treatment Woody Vegetation and Environmental Data for the Missouri Ozark Forest Ecosystem Project

Treesearch

John M. Kabrick; David R. Larsen; Stephen R. Shifley

1997-01-01

We conducted a study to identify pre-treatment trends in woody species density, diameter, and basal area among MOFEP sites, blocks, and treatment areas; relate woody species differences among sites, blocks, and treatment areas to differences in environmental conditions; and identify potential treatment response differences based upon our fmdings. Sites 2 through 5 had...

Liver metabolomics analysis associated with feed efficiency on steers

USDA-ARS?s Scientific Manuscript database

The liver represents a metabolic crossroad regulating and modulating nutrients available from digestive tract absorption to the peripheral tissues. To identify potential differences in liver function that lead to differences in feed efficiency, liver metabolomic analysis was conducted using ultra-pe...

4C-ker: A Method to Reproducibly Identify Genome-Wide Interactions Captured by 4C-Seq Experiments.

PubMed

Raviram, Ramya; Rocha, Pedro P; Müller, Christian L; Miraldi, Emily R; Badri, Sana; Fu, Yi; Swanzey, Emily; Proudhon, Charlotte; Snetkova, Valentina; Bonneau, Richard; Skok, Jane A

2016-03-01

4C-Seq has proven to be a powerful technique to identify genome-wide interactions with a single locus of interest (or "bait") that can be important for gene regulation. However, analysis of 4C-Seq data is complicated by the many biases inherent to the technique. An important consideration when dealing with 4C-Seq data is the differences in resolution of signal across the genome that result from differences in 3D distance separation from the bait. This leads to the highest signal in the region immediately surrounding the bait and increasingly lower signals in far-cis and trans. Another important aspect of 4C-Seq experiments is the resolution, which is greatly influenced by the choice of restriction enzyme and the frequency at which it can cut the genome. Thus, it is important that a 4C-Seq analysis method is flexible enough to analyze data generated using different enzymes and to identify interactions across the entire genome. Current methods for 4C-Seq analysis only identify interactions in regions near the bait or in regions located in far-cis and trans, but no method comprehensively analyzes 4C signals of different length scales. In addition, some methods also fail in experiments where chromatin fragments are generated using frequent cutter restriction enzymes. Here, we describe 4C-ker, a Hidden-Markov Model based pipeline that identifies regions throughout the genome that interact with the 4C bait locus. In addition, we incorporate methods for the identification of differential interactions in multiple 4C-seq datasets collected from different genotypes or experimental conditions. Adaptive window sizes are used to correct for differences in signal coverage in near-bait regions, far-cis and trans chromosomes. Using several datasets, we demonstrate that 4C-ker outperforms all existing 4C-Seq pipelines in its ability to reproducibly identify interaction domains at all genomic ranges with different resolution enzymes.

4C-ker: A Method to Reproducibly Identify Genome-Wide Interactions Captured by 4C-Seq Experiments

PubMed Central

Raviram, Ramya; Rocha, Pedro P.; Müller, Christian L.; Miraldi, Emily R.; Badri, Sana; Fu, Yi; Swanzey, Emily; Proudhon, Charlotte; Snetkova, Valentina

2016-01-01

4C-Seq has proven to be a powerful technique to identify genome-wide interactions with a single locus of interest (or “bait”) that can be important for gene regulation. However, analysis of 4C-Seq data is complicated by the many biases inherent to the technique. An important consideration when dealing with 4C-Seq data is the differences in resolution of signal across the genome that result from differences in 3D distance separation from the bait. This leads to the highest signal in the region immediately surrounding the bait and increasingly lower signals in far-cis and trans. Another important aspect of 4C-Seq experiments is the resolution, which is greatly influenced by the choice of restriction enzyme and the frequency at which it can cut the genome. Thus, it is important that a 4C-Seq analysis method is flexible enough to analyze data generated using different enzymes and to identify interactions across the entire genome. Current methods for 4C-Seq analysis only identify interactions in regions near the bait or in regions located in far-cis and trans, but no method comprehensively analyzes 4C signals of different length scales. In addition, some methods also fail in experiments where chromatin fragments are generated using frequent cutter restriction enzymes. Here, we describe 4C-ker, a Hidden-Markov Model based pipeline that identifies regions throughout the genome that interact with the 4C bait locus. In addition, we incorporate methods for the identification of differential interactions in multiple 4C-seq datasets collected from different genotypes or experimental conditions. Adaptive window sizes are used to correct for differences in signal coverage in near-bait regions, far-cis and trans chromosomes. Using several datasets, we demonstrate that 4C-ker outperforms all existing 4C-Seq pipelines in its ability to reproducibly identify interaction domains at all genomic ranges with different resolution enzymes. PMID:26938081

Patterns of trust in sources of health information.

PubMed

Lawson, Rob; Forbes, Sarah; Williams, John

2011-01-21

To understand the different patterns of trust that exist regarding different sources of information about health issues. Data from a large national health lifestyles survey of New Zealanders was examined using a factor analysis of trust toward 24 health information sources (HIS). Differences in trust are compared across a range of demographic variables. Factor analysis identified six different groupings of health information. Variations in trust in sources for health information are identified by age, employment status, level of education, income, sex and ethnic group. Systematic variations exist in the trust that people report with respect to different sources of health information. Understanding these variations may assist policymakers and other agencies which are responsible for planning the dissemination of health information.

Managing Complexity in Evidence Analysis: A Worked Example in Pediatric Weight Management.

PubMed

Parrott, James Scott; Henry, Beverly; Thompson, Kyle L; Ziegler, Jane; Handu, Deepa

2018-05-02

Nutrition interventions are often complex and multicomponent. Typical approaches to meta-analyses that focus on individual causal relationships to provide guideline recommendations are not sufficient to capture this complexity. The objective of this study is to describe the method of meta-analysis used for the Pediatric Weight Management (PWM) Guidelines update and provide a worked example that can be applied in other areas of dietetics practice. The effects of PWM interventions were examined for body mass index (BMI), body mass index z-score (BMIZ), and waist circumference at four different time periods. For intervention-level effects, intervention types were identified empirically using multiple correspondence analysis paired with cluster analysis. Pooled effects of identified types were examined using random effects meta-analysis models. Differences in effects among types were examined using meta-regression. Context-level effects are examined using qualitative comparative analysis. Three distinct types (or families) of PWM interventions were identified: medical nutrition, behavioral, and missing components. Medical nutrition and behavioral types showed statistically significant improvements in BMIZ across all time points. Results were less consistent for BMI and waist circumference, although four distinct patterns of weight status change were identified. These varied by intervention type as well as outcome measure. Meta-regression indicated statistically significant differences between the medical nutrition and behavioral types vs the missing component type for both BMIZ and BMI, although the pattern varied by time period and intervention type. Qualitative comparative analysis identified distinct configurations of context characteristics at each time point that were consistent with positive outcomes among the intervention types. Although analysis of individual causal relationships is invaluable, this approach is inadequate to capture the complexity of dietetics practice. An alternative approach that integrates intervention-level with context-level meta-analyses may provide deeper understanding in the development of practice guidelines. Copyright © 2018 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

Comparative Phosphoproteomic Analysis of the Developing Seeds in Two Indica Rice ( Oryza sativa L.) Cultivars with Different Starch Quality.

PubMed

Pang, Yuehan; Zhou, Xin; Chen, Yaling; Bao, Jinsong

2018-03-21

Protein phosphorylation plays important roles in regulation of various molecular events such as plant growth and seed development. However, its involvement in starch biosynthesis is less understood. Here, a comparative phosphoproteomic analysis of two indica rice cultivars during grain development was performed. A total of 2079 and 2434 phosphopeptides from 1273 and 1442 phosphoproteins were identified, covering 2441 and 2808 phosphosites in indica rice 9311 and Guangluai4 (GLA4), respectively. Comparative analysis identified 303 differentially phosphorylated peptides, and 120 and 258 specifically phosphorylated peptides in 9311 and GLA4, respectively. Phosphopeptides in starch biosynthesis related enzymes such as AGPase, SSIIa, SSIIIa, BEI, BEIIb, PUL, and Pho1were identified. GLA4 and 9311 had different amylose content, pasting viscosities, and gelatinization temperature, suggesting subtle difference in starch biosynthesis and regulation between GLA4 and 9311. Our study will give added impetus to further understanding the regulatory mechanism of starch biosynthesis at the phosphorylation level.

Brazilian Road Traffic Fatalities: A Spatial and Environmental Analysis

PubMed Central

de Andrade, Luciano; Vissoci, João Ricardo Nickenig; Rodrigues, Clarissa Garcia; Finato, Karen; Carvalho, Elias; Pietrobon, Ricardo; de Souza, Eniuce Menezes; Nihei, Oscar Kenji; Lynch, Catherine; de Barros Carvalho, Maria Dalva

2014-01-01

Background Road traffic injuries (RTI) are a major public health epidemic killing thousands of people daily. Low and middle-income countries, such as Brazil, have the highest annual rates of road traffic fatalities. In order to improve road safety, this study mapped road traffic fatalities on a Brazilian highway to determine the main environmental factors affecting road traffic fatalities. Methods and Findings Four techniques were utilized to identify and analyze RTI hotspots. We used spatial analysis by points by applying kernel density estimator, and wavelet analysis to identify the main hot regions. Additionally, built environment analysis, and principal component analysis were conducted to verify patterns contributing to crash occurrence in the hotspots. Between 2007 and 2009, 379 crashes were notified, with 466 fatalities on BR277. Higher incidence of crashes occurred on sections of highway with double lanes (ratio 2∶1). The hotspot analysis demonstrated that both the eastern and western regions had higher incidences of crashes when compared to the central region. Through the built environment analysis, we have identified five different patterns, demonstrating that specific environmental characteristics are associated with different types of fatal crashes. Patterns 2 and 4 are constituted mainly by predominantly urban characteristics and have frequent fatal pedestrian crashes. Patterns 1, 3 and 5 display mainly rural characteristics and have higher prevalence of vehicular collisions. In the built environment analysis, the variables length of road in urban area, limited lighting, double lanes roadways, and less auxiliary lanes were associated with a higher incidence of fatal crashes. Conclusions By combining different techniques of analyses, we have identified numerous hotspots and environmental characteristics, which governmental or regulatory agencies could make use to plan strategies to reduce RTI and support life-saving policies. PMID:24498051

Urinary metabolomics analysis identifies key biomarkers of different stages of nonalcoholic fatty liver disease

PubMed Central

Dong, Shu; Zhan, Zong-Ying; Cao, Hong-Yan; Wu, Chao; Bian, Yan-Qin; Li, Jian-Yuan; Cheng, Gen-Hong; Liu, Ping; Sun, Ming-Yu

2017-01-01

AIM To identify a panel of biomarkers that can distinguish between non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH), and explore molecular mechanism involved in the process of developing NASH from NAFLD. METHODS Biomarkers may differ during stages of NAFLD. Urine and blood were obtained from non-diabetic subjects with NAFLD and steatosis, with normal liver function (n = 33), from patients with NASH, with abnormal liver function (n = 45), and from healthy age and sex-matched controls (n = 30). Samples were subjected to metabolomic analysis to identify potential non-invasive biomarkers. Differences in urinary metabolic profiles were analyzed using liquid chromatography tandem mass spectrometry with principal component analysis and partial least squares-discriminate analysis. RESULTS Compared with NAFLD patients, patients with NASH had abnormal liver function and high serum lipid concentrations. Urinary metabonomics found differences in 31 metabolites between these two groups, including differences in nucleic acids and amino acids. Pathway analysis based on overlapping metabolites showed that pathways of energy and amino acid metabolism, as well as the pentose phosphate pathway, were closely associated with pathological processes in NAFLD and NASH. CONCLUSION These findings suggested that a panel of biomarkers could distinguish between NAFLD and NASH, and could help to determine the molecular mechanism involved in the process of developing NASH from NAFLD. Urinary biomarkers may be diagnostic in these patients and could be used to assess responses to therapeutic interventions. PMID:28487615

Content analysis to detect high stress in oral interviews and text documents

NASA Technical Reports Server (NTRS)

Thirumalainambi, Rajkumar (Inventor); Jorgensen, Charles C. (Inventor)

2012-01-01

A system of interrogation to estimate whether a subject of interrogation is likely experiencing high stress, emotional volatility and/or internal conflict in the subject's responses to an interviewer's questions. The system applies one or more of four procedures, a first statistical analysis, a second statistical analysis, a third analysis and a heat map analysis, to identify one or more documents containing the subject's responses for which further examination is recommended. Words in the documents are characterized in terms of dimensions representing different classes of emotions and states of mind, in which the subject's responses that manifest high stress, emotional volatility and/or internal conflict are identified. A heat map visually displays the dimensions manifested by the subject's responses in different colors, textures, geometric shapes or other visually distinguishable indicia.

Identification of five chronic obstructive pulmonary disease subgroups with different prognoses in the ECLIPSE cohort using cluster analysis.

PubMed

Rennard, Stephen I; Locantore, Nicholas; Delafont, Bruno; Tal-Singer, Ruth; Silverman, Edwin K; Vestbo, Jørgen; Miller, Bruce E; Bakke, Per; Celli, Bartolomé; Calverley, Peter M A; Coxson, Harvey; Crim, Courtney; Edwards, Lisa D; Lomas, David A; MacNee, William; Wouters, Emiel F M; Yates, Julie C; Coca, Ignacio; Agustí, Alvar

2015-03-01

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease that likely includes clinically relevant subgroups. To identify subgroups of COPD in ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) subjects using cluster analysis and to assess clinically meaningful outcomes of the clusters during 3 years of longitudinal follow-up. Factor analysis was used to reduce 41 variables determined at recruitment in 2,164 patients with COPD to 13 main factors, and the variables with the highest loading were used for cluster analysis. Clusters were evaluated for their relationship with clinically meaningful outcomes during 3 years of follow-up. The relationships among clinical parameters were evaluated within clusters. Five subgroups were distinguished using cross-sectional clinical features. These groups differed regarding outcomes. Cluster A included patients with milder disease and had fewer deaths and hospitalizations. Cluster B had less systemic inflammation at baseline but had notable changes in health status and emphysema extent. Cluster C had many comorbidities, evidence of systemic inflammation, and the highest mortality. Cluster D had low FEV1, severe emphysema, and the highest exacerbation and COPD hospitalization rate. Cluster E was intermediate for most variables and may represent a mixed group that includes further clusters. The relationships among clinical variables within clusters differed from that in the entire COPD population. Cluster analysis using baseline data in ECLIPSE identified five COPD subgroups that differ in outcomes and inflammatory biomarkers and show different relationships between clinical parameters, suggesting the clusters represent clinically and biologically different subtypes of COPD.

Metabolomic biomarkers identify differences in milk produced by Holstein cows and other minor dairy animals.

PubMed

Yang, Yongxin; Zheng, Nan; Zhao, Xiaowei; Zhang, Yangdong; Han, Rongwei; Yang, Jinhui; Zhao, Shengguo; Li, Songli; Guo, Tongjun; Zang, Changjiang; Wang, Jiaqi

2016-03-16

Several milk metabolites are associated with breeds or species of dairy animals. A better understanding of milk metabolites from different dairy animals would advance their use in evaluating milk traits and detecting milk adulteration. The objective of this study was to characterize the milk metabolite profiles of Chinese Holstein, Jersey, yak, buffalo, goat, camel, and horse and identify any differences using non-targeted metabolomic approaches. Milk samples were tested using nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography-tandem mass spectrometry (LC-MS). Data were analyzed using a multivariate analysis of variance and differences in milk metabolites between Holstein and the other dairy animals were assessed using orthogonal partial least-squares discriminant analysis. Differential metabolites were identified and some metabolites, such as choline and succinic acid, were used to distinguish Holstein milk from that of the other studied animals. Metabolic pathway analysis of different metabolites revealed that glycerophospholipid metabolism as well as valine, leucine, and isoleucine biosynthesis were shared in the other ruminant animals (Jersey, buffalo, yak, and goat), and biosynthesis of unsaturated fatty acids was shared in the non-ruminant animals (camel and horse). These results can be useful for gaining a better understanding of the differences in milk synthesis between Holstein and the other dairy animals. Copyright © 2016. Published by Elsevier B.V.

DEIVA: a web application for interactive visual analysis of differential gene expression profiles.

PubMed

Harshbarger, Jayson; Kratz, Anton; Carninci, Piero

2017-01-07

Differential gene expression (DGE) analysis is a technique to identify statistically significant differences in RNA abundance for genes or arbitrary features between different biological states. The result of a DGE test is typically further analyzed using statistical software, spreadsheets or custom ad hoc algorithms. We identified a need for a web-based system to share DGE statistical test results, and locate and identify genes in DGE statistical test results with a very low barrier of entry. We have developed DEIVA, a free and open source, browser-based single page application (SPA) with a strong emphasis on being user friendly that enables locating and identifying single or multiple genes in an immediate, interactive, and intuitive manner. By design, DEIVA scales with very large numbers of users and datasets. Compared to existing software, DEIVA offers a unique combination of design decisions that enable inspection and analysis of DGE statistical test results with an emphasis on ease of use.

Rapid Discrimination for Traditional Complex Herbal Medicines from Different Parts, Collection Time, and Origins Using High-Performance Liquid Chromatography and Near-Infrared Spectral Fingerprints with Aid of Pattern Recognition Methods

PubMed Central

Fu, Haiyan; Fan, Yao; Zhang, Xu; Lan, Hanyue; Yang, Tianming; Shao, Mei; Li, Sihan

2015-01-01

As an effective method, the fingerprint technique, which emphasized the whole compositions of samples, has already been used in various fields, especially in identifying and assessing the quality of herbal medicines. High-performance liquid chromatography (HPLC) and near-infrared (NIR), with their unique characteristics of reliability, versatility, precision, and simple measurement, played an important role among all the fingerprint techniques. In this paper, a supervised pattern recognition method based on PLSDA algorithm by HPLC and NIR has been established to identify the information of Hibiscus mutabilis L. and Berberidis radix, two common kinds of herbal medicines. By comparing component analysis (PCA), linear discriminant analysis (LDA), and particularly partial least squares discriminant analysis (PLSDA) with different fingerprint preprocessing of NIR spectra variables, PLSDA model showed perfect functions on the analysis of samples as well as chromatograms. Most important, this pattern recognition method by HPLC and NIR can be used to identify different collection parts, collection time, and different origins or various species belonging to the same genera of herbal medicines which proved to be a promising approach for the identification of complex information of herbal medicines. PMID:26345990

Ethnic and Gender Differences in Identifying Gifted Students: A Multi-Cultural Analysis

ERIC Educational Resources Information Center

Sarouphim, Ketty M.; Maker, C. June

2010-01-01

The purpose of this study was to examine ethnic and gender differences in using DISCOVER, a performance-based assessment, for identifying gifted students. The sample consisted of 941 students from grades K-5 belonging to six ethnicities: White Americans, African-Americans, Hispanics, Native-Americans, South Pacific/Pacific Islanders, and Arabs.…

Wilderness on the internet: identifying wilderness information domains

Treesearch

Chuck Burgess

2000-01-01

Data collected from an online needs assessment revealed that Web site visitors with an interest in wilderness seek several different types of information. In order to gain further insight into the process of Web use for wilderness information, a follow-up analysis was conducted. This analysis was exploratory in nature, with the goal of identifying information domains...

Identifying Students' Expectancy-Value Beliefs: A Latent Class Analysis Approach to Analyzing Middle School Students' Science Self-Perceptions

ERIC Educational Resources Information Center

Phelan, Julia; Ing, Marsha; Nylund-Gibson, Karen; Brown, Richard S.

2017-01-01

This study extends current research by organizing information about students' expectancy-value achievement motivation, in a way that helps parents and teachers identify specific entry points to encourage and support students' science aspirations. This study uses latent class analysis to describe underlying differences in ability beliefs, task…

Analysis of copy number variations in Holstein cows identify potential mechanisms contributing to differences in residual feed intake

USDA-ARS?s Scientific Manuscript database

Genomic structural variation is an important and abundant source of genetic and phenotypic variation. In this study, we performed an initial analysis of CNVs using BovineHD SNP genotyping data from 147 Holstein cows identified as having high or low feed efficiency as estimated by residual feed intak...

Systematic analysis of microarray datasets to identify Parkinson's disease‑associated pathways and genes.

PubMed

Feng, Yinling; Wang, Xuefeng

2017-03-01

In order to investigate commonly disturbed genes and pathways in various brain regions of patients with Parkinson's disease (PD), microarray datasets from previous studies were collected and systematically analyzed. Different normalization methods were applied to microarray datasets from different platforms. A strategy combining gene co‑expression networks and clinical information was adopted, using weighted gene co‑expression network analysis (WGCNA) to screen for commonly disturbed genes in different brain regions of patients with PD. Functional enrichment analysis of commonly disturbed genes was performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Co‑pathway relationships were identified with Pearson's correlation coefficient tests and a hypergeometric distribution‑based test. Common genes in pathway pairs were selected out and regarded as risk genes. A total of 17 microarray datasets from 7 platforms were retained for further analysis. Five gene coexpression modules were identified, containing 9,745, 736, 233, 101 and 93 genes, respectively. One module was significantly correlated with PD samples and thus the 736 genes it contained were considered to be candidate PD‑associated genes. Functional enrichment analysis demonstrated that these genes were implicated in oxidative phosphorylation and PD. A total of 44 pathway pairs and 52 risk genes were revealed, and a risk gene pathway relationship network was constructed. Eight modules were identified and were revealed to be associated with PD, cancers and metabolism. A number of disturbed pathways and risk genes were unveiled in PD, and these findings may help advance understanding of PD pathogenesis.

Multivariate analysis for stormwater quality characteristics identification from different urban surface types in macau.

PubMed

Huang, J; Du, P; Ao, C; Ho, M; Lei, M; Zhao, D; Wang, Z

2007-12-01

Statistical analysis of stormwater runoff data enables general identification of runoff characteristics. Six catchments with different urban surface type including roofs, roadway, park, and residential/commercial in Macau were selected for sampling and study during the period from June 2005 to September 2006. Based on univariate statistical analysis of data sampled, major pollutants discharged from different urban surface type were identified. As for iron roof runoff, Zn is the most significant pollutant. The major pollutants from urban roadway runoff are TSS and COD. Stormwater runoff from commercial/residential and Park catchments show high level of COD, TN, and TP concentration. Principal component analysis was further done for identification of linkages between stormwater quality and urban surface types. Two potential pollution sources were identified for study catchments with different urban surface types. The first one is referred as nutrients losses, soil losses and organic pollutants discharges, the second is related to heavy metals losses. PCA was proved to be a viable tool to explain the type of pollution sources and its mechanism for different urban surface type catchments.

[Proteomic analysis of myocardial hypertrophy induced by left kidney artery coarctation in rats].

PubMed

Lv, Yuan-yuan; Sun, Biao; Ma, Ji-zheng

2009-05-01

To identify the expression of proteins in cardiomyocytes in rats with left kidney artery coarctation. 16 male SD rats were separated into 2 groups (n=8): 2 kidney 1 Clip group (2K1C) and sham operation group (SO). The postoperational 8th week, after examination by normal doppler and tissue doppler echocardiography, the extracted proteins from cardiomyocytes were isolated by two-dimensional gel electrophoresis with staining. The gel images were acquired by scanner and 2-DE analysis software. Different spots observed on two 2D gels were selected and identified by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS). Overall, 21 protein spots showed significant difference, and 14 out of which were identified. Kidney artery coactation-induced cardiac hypertrophy displays different expression of proteins in cardiomyocytes.

Spontaneous Swallowing Frequency [Has Potential to] Identify Dysphagia in Acute Stroke

PubMed Central

Carnaby, Giselle D; Sia, Isaac; Khanna, Anna; Waters, Michael

2014-01-01

Background and Purpose Spontaneous swallowing frequency has been described as an index of dysphagia in various health conditions. This study evaluated the potential of spontaneous swallow frequency analysis as a screening protocol for dysphagia in acute stroke. Methods In a cohort of 63 acute stroke cases swallow frequency rates (swallows per minute: SPM) were compared to stroke and swallow severity indices, age, time from stroke to assessment, and consciousness level. Mean differences in SPM were compared between patients with vs. without clinically significant dysphagia. ROC analysis was used to identify the optimal threshold in SPM which was compared to a validated clinical dysphagia examination for identification of dysphagia cases. Time series analysis was employed to identify the minimally adequate time period to complete spontaneous swallow frequency analysis. Results SPM correlated significantly with stroke and swallow severity indices but not with age, time from stroke onset, or consciousness level. Patients with dysphagia demonstrated significantly lower SPM rates. SPM differed by dysphagia severity. ROC analysis yielded a threshold of SPM ≤ 0.40 which identified dysphagia (per the criterion referent) with 0.96 sensitivity, 0.68 specificity, and 0.96 negative predictive value. Time series analysis indicated that a 5 to 10 minute sampling window was sufficient to calculate spontaneous swallow frequency to identify dysphagia cases in acute stroke. Conclusions Spontaneous swallowing frequency presents high potential to screen for dysphagia in acute stroke without the need for trained, available personnel. PMID:24149008

Spontaneous swallowing frequency has potential to identify dysphagia in acute stroke.

PubMed

Crary, Michael A; Carnaby, Giselle D; Sia, Isaac; Khanna, Anna; Waters, Michael F

2013-12-01

Spontaneous swallowing frequency has been described as an index of dysphagia in various health conditions. This study evaluated the potential of spontaneous swallow frequency analysis as a screening protocol for dysphagia in acute stroke. In a cohort of 63 acute stroke cases, swallow frequency rates (swallows per minute [SPM]) were compared with stroke and swallow severity indices, age, time from stroke to assessment, and consciousness level. Mean differences in SPM were compared between patients with versus without clinically significant dysphagia. Receiver operating characteristic curve analysis was used to identify the optimal threshold in SPM, which was compared with a validated clinical dysphagia examination for identification of dysphagia cases. Time series analysis was used to identify the minimally adequate time period to complete spontaneous swallow frequency analysis. SPM correlated significantly with stroke and swallow severity indices but not with age, time from stroke onset, or consciousness level. Patients with dysphagia demonstrated significantly lower SPM rates. SPM differed by dysphagia severity. Receiver operating characteristic curve analysis yielded a threshold of SPM≤0.40 that identified dysphagia (per the criterion referent) with 0.96 sensitivity, 0.68 specificity, and 0.96 negative predictive value. Time series analysis indicated that a 5- to 10-minute sampling window was sufficient to calculate spontaneous swallow frequency to identify dysphagia cases in acute stroke. Spontaneous swallowing frequency presents high potential to screen for dysphagia in acute stroke without the need for trained, available personnel.

Rumen fluid metabolomics analysis associated with feed efficiency on crossbred steers

USDA-ARS?s Scientific Manuscript database

The rumen plays a central role in the efficiency of digestion in ruminants. To identify potential differences in rumen function that lead to differences in feed efficiency, rumen metabolomic analysis by ultra-performance liquid chromatography/ time-of-flight mass spectrometry (MS) and multivariate/u...

Barriers and facilitators for implementing a new screening tool in an emergency department: A qualitative study applying the Theoretical Domains Framework.

PubMed

Kirk, Jeanette W; Sivertsen, Ditte M; Petersen, Janne; Nilsen, Per; Petersen, Helle V

2016-10-01

The aim was to identify the factors that were perceived as most important as facilitators or barriers to the introduction and intended use of a new tool in the emergency department among nurses and a geriatric team. A high incidence of functional decline after hospitalisation for acute medical illness has been shown in the oldest patients and those who are physically frail. In Denmark, more than 35% of older medical patients acutely admitted to the emergency department are readmitted within 90 days after discharge. A new screening tool for use in the emergency department aiming to identify patients at particularly high risk of functional decline and readmission was developed. Qualitative study based on semistructured interviews with nurses and a geriatric team in the emergency department and semistructured single interviews with their managers. The Theoretical Domains Framework guided data collection and analysis. Content analysis was performed whereby new themes and themes already existing within each domain were described. Six predominant domains were identified: (1) professional role and identity; (2) beliefs about consequences; (3) goals; (4) knowledge; (5) optimism and (6) environmental context and resources. The content analysis identified three themes, each containing two subthemes. The themes were professional role and identity, beliefs about consequences and preconditions for a successful implementation. Two different cultures were identified in the emergency department. These cultures applied to different professional roles and identity, different actions and sense making and identified how barriers and facilitators linked to the new screening tool were perceived. The results show that different cultures exist in the same local context and influence the perception of barriers and facilitators differently. These cultures must be identified and addressed when implementation is planned. © 2016 The Authors. Journal of Clinical Nursing Published by John Wiley & Sons Ltd.

Ultra-high-performance liquid chromatography/tandem high-resolution mass spectrometry analysis of sixteen red beverages containing carminic acid: identification of degradation products by using principal component analysis/discriminant analysis.

PubMed

Gosetti, Fabio; Chiuminatto, Ugo; Mazzucco, Eleonora; Mastroianni, Rita; Marengo, Emilio

2015-01-15

The study investigates the sunlight photodegradation process of carminic acid, a natural red colourant used in beverages. For this purpose, both carminic acid aqueous standard solutions and sixteen different commercial beverages, ten containing carminic acid and six containing E120 dye, were subjected to photoirradiation. The results show different patterns of degradation, not only between the standard solutions and the beverages, but also from beverage to beverage. Due to the different beverage recipes, unpredictable reactions take place between the dye and the other ingredients. To identify the dye degradation products in a very complex scenario, a methodology was used, based on the combined use of principal component analysis with discriminant analysis and ultra-high-performance liquid chromatography coupled with tandem high resolution mass spectrometry. The methodology is unaffected by beverage composition and allows the degradation products of carminic acid dye to be identified for each beverage. Copyright © 2014 Elsevier Ltd. All rights reserved.

Who's in and why? A typology of stakeholder analysis methods for natural resource management.

PubMed

Reed, Mark S; Graves, Anil; Dandy, Norman; Posthumus, Helena; Hubacek, Klaus; Morris, Joe; Prell, Christina; Quinn, Claire H; Stringer, Lindsay C

2009-04-01

Stakeholder analysis means many things to different people. Various methods and approaches have been developed in different fields for different purposes, leading to confusion over the concept and practice of stakeholder analysis. This paper asks how and why stakeholder analysis should be conducted for participatory natural resource management research. This is achieved by reviewing the development of stakeholder analysis in business management, development and natural resource management. The normative and instrumental theoretical basis for stakeholder analysis is discussed, and a stakeholder analysis typology is proposed. This consists of methods for: i) identifying stakeholders; ii) differentiating between and categorising stakeholders; and iii) investigating relationships between stakeholders. The range of methods that can be used to carry out each type of analysis is reviewed. These methods and approaches are then illustrated through a series of case studies funded through the Rural Economy and Land Use (RELU) programme. These case studies show the wide range of participatory and non-participatory methods that can be used, and discuss some of the challenges and limitations of existing methods for stakeholder analysis. The case studies also propose new tools and combinations of methods that can more effectively identify and categorise stakeholders and help understand their inter-relationships.

The impact of structural uncertainty on cost-effectiveness models for adjuvant endocrine breast cancer treatments: the need for disease-specific model standardization and improved guidance.

PubMed

Frederix, Gerardus W J; van Hasselt, Johan G C; Schellens, Jan H M; Hövels, Anke M; Raaijmakers, Jan A M; Huitema, Alwin D R; Severens, Johan L

2014-01-01

Structural uncertainty relates to differences in model structure and parameterization. For many published health economic analyses in oncology, substantial differences in model structure exist, leading to differences in analysis outcomes and potentially impacting decision-making processes. The objectives of this analysis were (1) to identify differences in model structure and parameterization for cost-effectiveness analyses (CEAs) comparing tamoxifen and anastrazole for adjuvant breast cancer (ABC) treatment; and (2) to quantify the impact of these differences on analysis outcome metrics. The analysis consisted of four steps: (1) review of the literature for identification of eligible CEAs; (2) definition and implementation of a base model structure, which included the core structural components for all identified CEAs; (3) definition and implementation of changes or additions in the base model structure or parameterization; and (4) quantification of the impact of changes in model structure or parameterizations on the analysis outcome metrics life-years gained (LYG), incremental costs (IC) and the incremental cost-effectiveness ratio (ICER). Eleven CEA analyses comparing anastrazole and tamoxifen as ABC treatment were identified. The base model consisted of the following health states: (1) on treatment; (2) off treatment; (3) local recurrence; (4) metastatic disease; (5) death due to breast cancer; and (6) death due to other causes. The base model estimates of anastrazole versus tamoxifen for the LYG, IC and ICER were 0.263 years, €3,647 and €13,868/LYG, respectively. In the published models that were evaluated, differences in model structure included the addition of different recurrence health states, and associated transition rates were identified. Differences in parameterization were related to the incidences of recurrence, local recurrence to metastatic disease, and metastatic disease to death. The separate impact of these model components on the LYG ranged from 0.207 to 0.356 years, while incremental costs ranged from €3,490 to €3,714 and ICERs ranged from €9,804/LYG to €17,966/LYG. When we re-analyzed the published CEAs in our framework by including their respective model properties, the LYG ranged from 0.207 to 0.383 years, IC ranged from €3,556 to €3,731 and ICERs ranged from €9,683/LYG to €17,570/LYG. Differences in model structure and parameterization lead to substantial differences in analysis outcome metrics. This analysis supports the need for more guidance regarding structural uncertainty and the use of standardized disease-specific models for health economic analyses of adjuvant endocrine breast cancer therapies. The developed approach in the current analysis could potentially serve as a template for further evaluations of structural uncertainty and development of disease-specific models.

Weighted gene co‑expression network analysis in identification of key genes and networks for ischemic‑reperfusion remodeling myocardium.

PubMed

Guo, Nan; Zhang, Nan; Yan, Liqiu; Lian, Zheng; Wang, Jiawang; Lv, Fengfeng; Wang, Yunfei; Cao, Xufen

2018-06-14

Acute myocardial infarction induces ventricular remodeling, which is implicated in dilated heart and heart failure. The pathogenical mechanism of myocardium remodeling remains to be elucidated. The aim of the present study was to identify key genes and networks for myocardium remodeling following ischemia‑reperfusion (IR). First, the mRNA expression data from the National Center for Biotechnology Information database were downloaded to identify differences in mRNA expression of the IR heart at days 2 and 7. Then, weighted gene co‑expression network analysis, hierarchical clustering, protein‑protein interaction (PPI) network, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were used to identify key genes and networks for the heart remodeling process following IR. A total of 3,321 differentially expressed genes were identified during the heart remodeling process. A total of 6 modules were identified through gene co‑expression network analysis. GO and KEGG analysis results suggested that each module represented a different biological function and was associated with different pathways. Finally, hub genes of each module were identified by PPI network construction. The present study revealed that heart remodeling following IR is a complicated process, involving extracellular matrix organization, neural development, apoptosis and energy metabolism. The dysregulated genes, including SRC proto‑oncogene, non‑receptor tyrosine kinase, discs large MAGUK scaffold protein 1, ATP citrate lyase, RAN, member RAS oncogene family, tumor protein p53, and polo like kinase 2, may be essential for heart remodeling following IR and may be used as potential targets for the inhibition of heart remodeling following acute myocardial infarction.

SU-F-T-246: Evaluation of Healthcare Failure Mode And Effect Analysis For Risk Assessment

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

Harry, T; University of California, San Diego, La Jolla, CA; Manger, R

Purpose: To evaluate the differences between the Veteran Affairs Healthcare Failure Modes and Effect Analysis (HFMEA) and the AAPM Task Group 100 Failure and Effect Analysis (FMEA) risk assessment techniques in the setting of a stereotactic radiosurgery (SRS) procedure were compared respectively. Understanding the differences in the techniques methodologies and outcomes will provide further insight into the applicability and utility of risk assessments exercises in radiation therapy. Methods: HFMEA risk assessment analysis was performed on a stereotactic radiosurgery procedure. A previous study from our institution completed a FMEA of our SRS procedure and the process map generated from this workmore » was used for the HFMEA. The process of performing the HFMEA scoring was analyzed, and the results from both analyses were compared. Results: The key differences between the two risk assessments are the scoring criteria for failure modes and identifying critical failure modes for potential hazards. The general consensus among the team performing the analyses was that scoring for the HFMEA was simpler and more intuitive then the FMEA. The FMEA identified 25 critical failure modes while the HFMEA identified 39. Seven of the FMEA critical failure modes were not identified by the HFMEA and 21 of the HFMEA critical failure modes were not identified by the FMEA. HFMEA as described by the Veteran Affairs provides guidelines on which failure modes to address first. Conclusion: HFMEA is a more efficient model for identifying gross risks in a process than FMEA. Clinics with minimal staff, time and resources can benefit from this type of risk assessment to eliminate or mitigate high risk hazards with nominal effort. FMEA can provide more in depth details but at the cost of elevated effort.« less

A precipitation regionalization and regime for Iran based on multivariate analysis

NASA Astrophysics Data System (ADS)

Raziei, Tayeb

2018-02-01

Monthly precipitation time series of 155 synoptic stations distributed over Iran, covering 1990-2014 time period, were used to identify areas with different precipitation time variability and regimes utilizing S-mode principal component analysis (PCA) and cluster analysis (CA) preceded by T-mode PCA, respectively. Taking into account the maximum loading values of the rotated components, the first approach revealed five sub-regions characterized by different precipitation time variability, while the second method delineated eight sub-regions featured with different precipitation regimes. The sub-regions identified by the two used methods, although partly overlapping, are different considering their areal extent and complement each other as they are useful for different purposes and applications. Northwestern Iran and the Caspian Sea area were found as the two most distinctive Iranian precipitation sub-regions considering both time variability and precipitation regime since they were well captured with relatively identical areas by the two used approaches. However, the areal extents of the other three sub-regions identified by the first approach were not coincident with the coverage of their counterpart sub-regions defined by the second approach. Results suggest that the precipitation sub-region identified by the two methods would not be necessarily the same, as the first method which accounts for the variance of the data grouped stations with similar temporal variability while the second one which considers a fixed climatology defined by the average over the period 1990-2014 clusters stations having a similar march of monthly precipitation.

Use of Parsimony Analysis to Identify Areas of Endemism of Chinese Birds: Implications for Conservation and Biogeography

PubMed Central

Huang, Xiao-Lei; Qiao, Ge-Xia; Lei, Fu-Min

2010-01-01

Parsimony analysis of endemicity (PAE) was used to identify areas of endemism (AOEs) for Chinese birds at the subregional level. Four AOEs were identified based on a distribution database of 105 endemic species and using 18 avifaunal subregions as the operating geographical units (OGUs). The four AOEs are the Qinghai-Zangnan Subregion, the Southwest Mountainous Subregion, the Hainan Subregion and the Taiwan Subregion. Cladistic analysis of subregions generally supports the division of China’s avifauna into Palaearctic and Oriental realms. Two PAE area trees were produced from two different distribution datasets (year 1976 and 2007). The 1976 topology has four distinct subregional branches; however, the 2007 topology has three distinct branches. Moreover, three Palaearctic subregions in the 1976 tree clustered together with the Oriental subregions in the 2007 tree. Such topological differences may reflect changes in the distribution of bird species through circa three decades. PMID:20559504

Protein Sectors: Statistical Coupling Analysis versus Conservation

PubMed Central

Teşileanu, Tiberiu; Colwell, Lucy J.; Leibler, Stanislas

2015-01-01

Statistical coupling analysis (SCA) is a method for analyzing multiple sequence alignments that was used to identify groups of coevolving residues termed “sectors”. The method applies spectral analysis to a matrix obtained by combining correlation information with sequence conservation. It has been asserted that the protein sectors identified by SCA are functionally significant, with different sectors controlling different biochemical properties of the protein. Here we reconsider the available experimental data and note that it involves almost exclusively proteins with a single sector. We show that in this case sequence conservation is the dominating factor in SCA, and can alone be used to make statistically equivalent functional predictions. Therefore, we suggest shifting the experimental focus to proteins for which SCA identifies several sectors. Correlations in protein alignments, which have been shown to be informative in a number of independent studies, would then be less dominated by sequence conservation. PMID:25723535

Visualizando el desarrollo de la nanomedicina en México.

PubMed

Robles-Belmont, Eduardo; Gortari-Rabiela, Rebeca de; Galarza-Barrios, Pilar; Siqueiros-García, Jesús Mario; Ruiz-León, Alejandro Arnulfo

2017-01-01

In this article we present a set of different visualizations of Mexico's nanomedicine scientific production data. Visualizations were developed using different methodologies for data analysis and visualization such as social network analysis, geography of science maps, and complex network communities analysis. Results are a multi-dimensional overview of the evolution of nanomedicine in Mexico. Moreover, visualizations allowed to identify trends and patterns of collaboration at the national and international level. Trends are also found in the knowledge structure of themes and disciplines. Finally, we identified the scientific communities in Mexico that are responsible for the new knowledge production in this emergent field of science. Copyright: © 2017 SecretarÍa de Salud

[Comparative Study of Patient Identifications for Conventional and Portable Chest Radiographs Utilizing ROC Analysis].

PubMed

Kawashima, Hiroki; Hayashi, Norio; Ohno, Naoki; Matsuura, Yukihiro; Sanada, Shigeru

2015-08-01

To evaluate the patient identification ability of radiographers, previous and current chest radiographs were assessed with observer study utilizing a receiver operating characteristics (ROCs) analysis. This study included portable and conventional chest radiographs from 43 same and 43 different patients. The dataset used in this study was divided into the three following groups: (1) a pair of portable radiographs, (2) a pair of conventional radiographs, and (3) a combination of each type of radiograph. Seven observers participated in this ROC study, which aimed to identify same or different patients, using these datasets. ROC analysis was conducted to calculate the average area under ROC curve obtained by each observer (AUCave), and a statistical test was performed using the multi-reader multi-case method. Comparable results were obtained with pairs of portable (AUCave: 0.949) and conventional radiographs (AUCave: 0.951). In a comparison between the same modality, there were no significant differences. In contrast, the ability to identify patients by comparing a portable and conventional radiograph (AUCave: 0.873) was lower than with the matching datasets (p=0.002 and p=0.004, respectively). In conclusion, the use of different imaging modalities reduces radiographers' ability to identify their patients.

Methods and Measures: Growth Mixture Modeling--A Method for Identifying Differences in Longitudinal Change among Unobserved Groups

ERIC Educational Resources Information Center

Ram, Nilam; Grimm, Kevin J.

2009-01-01

Growth mixture modeling (GMM) is a method for identifying multiple unobserved sub-populations, describing longitudinal change within each unobserved sub-population, and examining differences in change among unobserved sub-populations. We provide a practical primer that may be useful for researchers beginning to incorporate GMM analysis into their…

A comparative study of volatile components in Dianhong teas from fresh leaves of four tea cultivars by using chromatography-mass spectrometry, multivariate data analysis, and descriptive sensory analysis.

PubMed

Wang, Chao; Zhang, Chenxia; Kong, Yawen; Peng, Xiaopei; Li, Changwen; Liu, Shunhang; Du, Liping; Xiao, Dongguang; Xu, Yongquan

2017-10-01

Dianhong teas produced from fresh leaves of different tea cultivars (YK is Yunkang No. 10, XY is Xueya 100, CY is Changyebaihao, SS is Shishengmiao), were compared in terms of volatile compounds and descriptive sensory analysis. A total of 73 volatile compounds in 16 tea samples were tentatively identified. YK, XY, CY, and SS contained 55, 53, 49, and 51 volatile compounds, respectively. Partial least squares-discriminant analysis (PLS-DA) and hierarchical cluster analysis (HCA) were used to classify the samples, and 40 key components were selected based on variable importance in the projection. Moreover, 11 flavor attributes, namely, floral, fruity, grass/green, woody, sweet, roasty, caramel, mellow and thick, bitter, astringent, and sweet aftertaste were identified through descriptive sensory analysis (DSA). In generally, innate differences among the tea varieties significantly affected the intensities of most of the key sensory attributes of Dianhong teas possibly because of the different amounts of aroma-active and taste components in Dianhong teas. Copyright © 2017 Elsevier Ltd. All rights reserved.

Joint source based morphometry identifies linked gray and white matter group differences.

PubMed

Xu, Lai; Pearlson, Godfrey; Calhoun, Vince D

2009-02-01

We present a multivariate approach called joint source based morphometry (jSBM), to identify linked gray and white matter regions which differ between groups. In jSBM, joint independent component analysis (jICA) is used to decompose preprocessed gray and white matter images into joint sources and statistical analysis is used to determine the significant joint sources showing group differences and their relationship to other variables of interest (e.g. age or sex). The identified joint sources are groupings of linked gray and white matter regions with common covariation among subjects. In this study, we first provide a simulation to validate the jSBM approach. To illustrate our method on real data, jSBM is then applied to structural magnetic resonance imaging (sMRI) data obtained from 120 chronic schizophrenia patients and 120 healthy controls to identify group differences. JSBM identified four joint sources as significantly associated with schizophrenia. Linked gray-white matter regions identified in each of the joint sources included: 1) temporal--corpus callosum, 2) occipital/frontal--inferior fronto-occipital fasciculus, 3) frontal/parietal/occipital/temporal--superior longitudinal fasciculus and 4) parietal/frontal--thalamus. Age effects on all four joint sources were significant, but sex effects were significant only for the third joint source. Our findings demonstrate that jSBM can exploit the natural linkage between gray and white matter by incorporating them into a unified framework. This approach is applicable to a wide variety of problems to study linked gray and white matter group differences.

Evaluation of The Operational Benefits Versus Costs of An Automated Cargo Mover

DTIC Science & Technology

2016-12-01

logistics footprint and life-cycle cost are presented as part of this report. Analysis of modeling and simulation results identified statistically...life-cycle cost are presented as part of this report. Analysis of modeling and simulation results identified statistically significant differences...Error of Estimation. Source: Eskew and Lawler (1994). ...........................75 Figure 24. Load Results (100 Runs per Scenario

An Analysis Technique/Automated Tool for Comparing and Tracking Analysis Modes of Different Finite Element Models

NASA Technical Reports Server (NTRS)

Towner, Robert L.; Band, Jonathan L.

2012-01-01

An analysis technique was developed to compare and track mode shapes for different Finite Element Models. The technique may be applied to a variety of structural dynamics analyses, including model reduction validation (comparing unreduced and reduced models), mode tracking for various parametric analyses (e.g., launch vehicle model dispersion analysis to identify sensitivities to modal gain for Guidance, Navigation, and Control), comparing models of different mesh fidelity (e.g., a coarse model for a preliminary analysis compared to a higher-fidelity model for a detailed analysis) and mode tracking for a structure with properties that change over time (e.g., a launch vehicle from liftoff through end-of-burn, with propellant being expended during the flight). Mode shapes for different models are compared and tracked using several numerical indicators, including traditional Cross-Orthogonality and Modal Assurance Criteria approaches, as well as numerical indicators obtained by comparing modal strain energy and kinetic energy distributions. This analysis technique has been used to reliably identify correlated mode shapes for complex Finite Element Models that would otherwise be difficult to compare using traditional techniques. This improved approach also utilizes an adaptive mode tracking algorithm that allows for automated tracking when working with complex models and/or comparing a large group of models.

Sex-role ideology among self-identified psychotherapists.

PubMed

Harper, D W; Leichner, P P; McCrimmon, E

1985-10-01

Analysis of the sex-role ideology of 1,258 self-identified psychotherapists from nine occupations indicated that: the sample was representative; as a group, self-identified psychotherapists were moderately feminist; there were significant differences among occupations; and results were not due solely to the effects of age or sex distributions among occupations.

The response of numerical weather prediction analysis systems to FGGE 2b data

NASA Technical Reports Server (NTRS)

Hollingsworth, A.; Lorenc, A.; Tracton, S.; Arpe, K.; Cats, G.; Uppala, S.; Kallberg, P.

1985-01-01

An intercomparison of analyses of the main PGGE Level IIb data set is presented with three advanced analysis systems. The aims of the work are to estimate the extent and magnitude of the differences between the analyses, to identify the reasons for the differences, and finally to estimate the significance of the differences. Extratropical analyses only are considered. Objective evaluations of analysis quality, such as fit to observations, statistics of analysis differences, and mean fields are discussed. In addition, substantial emphasis is placed on subjective evaluation of a series of case studies that were selected to illustrate the importance of different aspects of the analysis procedures, such as quality control, data selection, resolution, dynamical balance, and the role of the assimilating forecast model. In some cases, the forecast models are used as selective amplifiers of analysis differences to assist in deciding which analysis was more nearly correct in the treatment of particular data.

Ratiometric analysis of in vivo retinal layer thicknesses in multiple sclerosis

NASA Astrophysics Data System (ADS)

Bhaduri, Basanta; Nolan, Ryan M.; Shelton, Ryan L.; Pilutti, Lara A.; Motl, Robert W.; Boppart, Stephen A.

2016-09-01

We performed ratiometric analysis of retinal optical coherence tomography images for the first time in multiple sclerosis (MS) patients. The ratiometric analysis identified differences in several retinal layer thickness ratios in the cohort of MS subjects without a history of optic neuritis (ON) compared to healthy control (HC) subjects, and there was no difference in standard retinal nerve fiber layer thickness (RNFLT). The difference in such ratios between HC subjects and those with mild MS-disability, without a difference in RNFLT, further suggests the possibility of using layer ratiometric analysis for detecting early retinal changes in MS. Ratiometric analysis may be useful and potentially more sensitive for detecting disease changes in MS.

Systemic Metabolomic Changes in Blood Samples of Lung Cancer Patients Identified by Gas Chromatography Time-of-Flight Mass Spectrometry

PubMed Central

Miyamoto, Suzanne; Taylor, Sandra L.; Barupal, Dinesh K.; Taguchi, Ayumu; Wohlgemuth, Gert; Wikoff, William R.; Yoneda, Ken Y.; Gandara, David R.; Hanash, Samir M.; Kim, Kyoungmi; Fiehn, Oliver

2015-01-01

Lung cancer is a leading cause of cancer deaths worldwide. Metabolic alterations in tumor cells coupled with systemic indicators of the host response to tumor development have the potential to yield blood profiles with clinical utility for diagnosis and monitoring of treatment. We report results from two separate studies using gas chromatography time-of-flight mass spectrometry (GC-TOF MS) to profile metabolites in human blood samples that significantly differ from non-small cell lung cancer (NSCLC) adenocarcinoma and other lung cancer cases. Metabolomic analysis of blood samples from the two studies yielded a total of 437 metabolites, of which 148 were identified as known compounds and 289 identified as unknown compounds. Differential analysis identified 15 known metabolites in one study and 18 in a second study that were statistically different (p-values <0.05). Levels of maltose, palmitic acid, glycerol, ethanolamine, glutamic acid, and lactic acid were increased in cancer samples while amino acids tryptophan, lysine and histidine decreased. Many of the metabolites were found to be significantly different in both studies, suggesting that metabolomics appears to be robust enough to find systemic changes from lung cancer, thus showing the potential of this type of analysis for lung cancer detection. PMID:25859693

Clinical Characteristics of Exacerbation-Prone Adult Asthmatics Identified by Cluster Analysis.

PubMed

Kim, Mi Ae; Shin, Seung Woo; Park, Jong Sook; Uh, Soo Taek; Chang, Hun Soo; Bae, Da Jeong; Cho, You Sook; Park, Hae Sim; Yoon, Ho Joo; Choi, Byoung Whui; Kim, Yong Hoon; Park, Choon Sik

2017-11-01

Asthma is a heterogeneous disease characterized by various types of airway inflammation and obstruction. Therefore, it is classified into several subphenotypes, such as early-onset atopic, obese non-eosinophilic, benign, and eosinophilic asthma, using cluster analysis. A number of asthmatics frequently experience exacerbation over a long-term follow-up period, but the exacerbation-prone subphenotype has rarely been evaluated by cluster analysis. This prompted us to identify clusters reflecting asthma exacerbation. A uniform cluster analysis method was applied to 259 adult asthmatics who were regularly followed-up for over 1 year using 12 variables, selected on the basis of their contribution to asthma phenotypes. After clustering, clinical profiles and exacerbation rates during follow-up were compared among the clusters. Four subphenotypes were identified: cluster 1 was comprised of patients with early-onset atopic asthma with preserved lung function, cluster 2 late-onset non-atopic asthma with impaired lung function, cluster 3 early-onset atopic asthma with severely impaired lung function, and cluster 4 late-onset non-atopic asthma with well-preserved lung function. The patients in clusters 2 and 3 were identified as exacerbation-prone asthmatics, showing a higher risk of asthma exacerbation. Two different phenotypes of exacerbation-prone asthma were identified among Korean asthmatics using cluster analysis; both were characterized by impaired lung function, but the age at asthma onset and atopic status were different between the two. Copyright © 2017 The Korean Academy of Asthma, Allergy and Clinical Immunology · The Korean Academy of Pediatric Allergy and Respiratory Disease

Acknowledging Different Needs: Developing a Taxonomy of Welfare Leavers.

ERIC Educational Resources Information Center

Julnes, George; Hayashi, Kentaro; Anderson, Steven

2001-01-01

Used cluster analysis of survey data for 506 respondents to create a taxonomy of welfare leavers in Illinois based on their self-reported well-being after leaving welfare. Used classification tree analysis to identify factors associated with different types of leavers. Findings highlight the existence of many marginally successful leavers who…

Archetypal analysis of diverse Pseudomonas aeruginosa transcriptomes reveals adaptation in cystic fibrosis airways

PubMed Central

2013-01-01

Background Analysis of global gene expression by DNA microarrays is widely used in experimental molecular biology. However, the complexity of such high-dimensional data sets makes it difficult to fully understand the underlying biological features present in the data. The aim of this study is to introduce a method for DNA microarray analysis that provides an intuitive interpretation of data through dimension reduction and pattern recognition. We present the first “Archetypal Analysis” of global gene expression. The analysis is based on microarray data from five integrated studies of Pseudomonas aeruginosa isolated from the airways of cystic fibrosis patients. Results Our analysis clustered samples into distinct groups with comprehensible characteristics since the archetypes representing the individual groups are closely related to samples present in the data set. Significant changes in gene expression between different groups identified adaptive changes of the bacteria residing in the cystic fibrosis lung. The analysis suggests a similar gene expression pattern between isolates with a high mutation rate (hypermutators) despite accumulation of different mutations for these isolates. This suggests positive selection in the cystic fibrosis lung environment, and changes in gene expression for these isolates are therefore most likely related to adaptation of the bacteria. Conclusions Archetypal analysis succeeded in identifying adaptive changes of P. aeruginosa. The combination of clustering and matrix factorization made it possible to reveal minor similarities among different groups of data, which other analytical methods failed to identify. We suggest that this analysis could be used to supplement current methods used to analyze DNA microarray data. PMID:24059747

Fourier Transform Infrared Spectroscopy (FTIR) and Multivariate Analysis for Identification of Different Vegetable Oils Used in Biodiesel Production

PubMed Central

Mueller, Daniela; Ferrão, Marco Flôres; Marder, Luciano; da Costa, Adilson Ben; de Cássia de Souza Schneider, Rosana

2013-01-01

The main objective of this study was to use infrared spectroscopy to identify vegetable oils used as raw material for biodiesel production and apply multivariate analysis to the data. Six different vegetable oil sources—canola, cotton, corn, palm, sunflower and soybeans—were used to produce biodiesel batches. The spectra were acquired by Fourier transform infrared spectroscopy using a universal attenuated total reflectance sensor (FTIR-UATR). For the multivariate analysis principal component analysis (PCA), hierarchical cluster analysis (HCA), interval principal component analysis (iPCA) and soft independent modeling of class analogy (SIMCA) were used. The results indicate that is possible to develop a methodology to identify vegetable oils used as raw material in the production of biodiesel by FTIR-UATR applying multivariate analysis. It was also observed that the iPCA found the best spectral range for separation of biodiesel batches using FTIR-UATR data, and with this result, the SIMCA method classified 100% of the soybean biodiesel samples. PMID:23539030

Sex differences in discriminative power of volleyball game-related statistics.

PubMed

João, Paulo Vicente; Leite, Nuno; Mesquita, Isabel; Sampaio, Jaime

2010-12-01

To identify sex differences in volleyball game-related statistics, the game-related statistics of several World Championships in 2007 (N=132) were analyzed using the software VIS from the International Volleyball Federation. Discriminant analysis was used to identify the game-related statistics which better discriminated performances by sex. Analysis yielded an emphasis on fault serves (SC = -.40), shot spikes (SC = .40), and reception digs (SC = .31). Specific robust numbers represent that considerable variability was evident in the game-related statistics profile, as men's volleyball games were better associated with terminal actions (errors of service), and women's volleyball games were characterized by continuous actions (in defense and attack). These differences may be related to the anthropometric and physiological differences between women and men and their influence on performance profiles.

Cross-cultural differences in psychiatric nurses' attitudes to inpatient aggression.

PubMed

Jansen, Gerard J; Middel, Berry; Dassen, Theo W N; Reijneveld, Menno S A

2006-04-01

Little is currently known about the attitudes of psychiatric nurses toward patient aggression, particularly from an international perspective. Attitudes toward patient aggression of psychiatric nurses from five European countries were investigated using a recently developed and tested attitude scale. Data were collected from a convenience sample of 1,769 student nurses and psychiatric nurses. Regression analysis was performed to identify personal and occupational characteristics of the respondents able to predict their attitude toward aggression. Analysis of variance was used to identify significant differences in attitudes between and among countries. Attitude was predicted by sex, contractual status (full vs. part time), and the type of ward on which subjects worked. With one exception (communicative attitude), attitudes differed across countries. More research on attitude formation is needed to determine which factors account for these differences.

Global analysis of glycoproteins identifies markers of endotoxin tolerant monocytes and GPR84 as a modulator of TNFα expression.

PubMed

Müller, Mario M; Lehmann, Roland; Klassert, Tilman E; Reifenstein, Stella; Conrad, Theresia; Moore, Christoph; Kuhn, Anna; Behnert, Andrea; Guthke, Reinhard; Driesch, Dominik; Slevogt, Hortense

2017-04-12

Exposure of human monocytes to lipopolysaccharide (LPS) induces a temporary insensitivity to subsequent LPS challenges, a cellular state called endotoxin tolerance. In this study, we investigated the LPS-induced global glycoprotein expression changes of tolerant human monocytes and THP-1 cells to identify markers and glycoprotein targets capable to modulate the immunosuppressive state. Using hydrazide chemistry and LC-MS/MS analysis, we analyzed glycoprotein expression changes during a 48 h LPS time course. The cellular snapshots at different time points identified 1491 glycoproteins expressed by monocytes and THP-1 cells. Label-free quantitative analysis revealed transient or long-lasting LPS-induced expression changes of secreted or membrane-anchored glycoproteins derived from intracellular membrane coated organelles or from the plasma membrane. Monocytes and THP-1 cells demonstrated marked differences in glycoproteins differentially expressed in the tolerant state. Among the shared differentially expressed glycoproteins G protein-coupled receptor 84 (GPR84) was identified as being capable of modulating pro-inflammatory TNFα mRNA expression in the tolerant cell state when activated with its ligand Decanoic acid.

Classification and identification of Rhodobryum roseum Limpr. and its adulterants based on fourier-transform infrared spectroscopy (FTIR) and chemometrics.

PubMed

Cao, Zhen; Wang, Zhenjie; Shang, Zhonglin; Zhao, Jiancheng

2017-01-01

Fourier-transform infrared spectroscopy (FTIR) with the attenuated total reflectance technique was used to identify Rhodobryum roseum from its four adulterants. The FTIR spectra of six samples in the range from 4000 cm-1 to 600 cm-1 were obtained. The second-derivative transformation test was used to identify the small and nearby absorption peaks. A cluster analysis was performed to classify the spectra in a dendrogram based on the spectral similarity. Principal component analysis (PCA) was used to classify the species of six moss samples. A cluster analysis with PCA was used to identify different genera. However, some species of the same genus exhibited highly similar chemical components and FTIR spectra. Fourier self-deconvolution and discrete wavelet transform (DWT) were used to enhance the differences among the species with similar chemical components and FTIR spectra. Three scales were selected as the feature-extracting space in the DWT domain. The results show that FTIR spectroscopy with chemometrics is suitable for identifying Rhodobryum roseum and its adulterants.

Independent Component Analysis of Resting-State Functional Magnetic Resonance Imaging in Pedophiles.

PubMed

Cantor, J M; Lafaille, S J; Hannah, J; Kucyi, A; Soh, D W; Girard, T A; Mikulis, D J

2016-10-01

Neuroimaging and other studies have changed the common view that pedophilia is a result of childhood sexual abuse and instead is a neurologic phenomenon with prenatal origins. Previous research has identified differences in the structural connectivity of the brain in pedophilia. To identify analogous differences in functional connectivity. Functional magnetic resonance images were recorded from three groups of participants while they were at rest: pedophilic men with a history of sexual offenses against children (n = 37) and two control groups: non-pedophilic men who committed non-sexual offenses (n = 28) and non-pedophilic men with no criminal history (n = 39). Functional magnetic resonance imaging data were subjected to independent component analysis to identify known functional networks of the brain, and groups were compared to identify differences in connectivity with those networks (or "components"). The pedophilic group demonstrated wide-ranging increases in functional connectivity with the default mode network compared with controls and regional differences (increases and decreases) with the frontoparietal network. Of these brain regions (total = 23), 20 have been identified by meta-analytic studies to respond to sexually relevant stimuli. Conversely, of the brain areas known to be those that respond to sexual stimuli, nearly all emerged in the present data as significantly different in pedophiles. This study confirms the presence of significant differences in the functional connectivity of the brain in pedophilia consistent with previously reported differences in structural connectivity. The connectivity differences detected here and elsewhere are opposite in direction from those associated with anti-sociality, arguing against anti-sociality and for pedophilia as the source of the neuroanatomic differences detected. Copyright © 2016 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

Mathematical methods to analysis of topology, functional variability and evolution of metabolic systems based on different decomposition concepts.

PubMed

Mrabet, Yassine; Semmar, Nabil

2010-05-01

Complexity of metabolic systems can be undertaken at different scales (metabolites, metabolic pathways, metabolic network map, biological population) and under different aspects (structural, functional, evolutive). To analyse such a complexity, metabolic systems need to be decomposed into different components according to different concepts. Four concepts are presented here consisting in considering metabolic systems as sets of metabolites, chemical reactions, metabolic pathways or successive processes. From a metabolomic dataset, such decompositions are performed using different mathematical methods including correlation, stiochiometric, ordination, classification, combinatorial and kinetic analyses. Correlation analysis detects and quantifies affinities/oppositions between metabolites. Stoichiometric analysis aims to identify the organisation of a metabolic network into different metabolic pathways on the hand, and to quantify/optimize the metabolic flux distribution through the different chemical reactions of the system. Ordination and classification analyses help to identify different metabolic trends and their associated metabolites in order to highlight chemical polymorphism representing different variability poles of the metabolic system. Then, metabolic processes/correlations responsible for such a polymorphism can be extracted in silico by combining metabolic profiles representative of different metabolic trends according to a weighting bootstrap approach. Finally evolution of metabolic processes in time can be analysed by different kinetic/dynamic modelling approaches.

Three perspectives on the mismatch between measures of material poverty.

PubMed

Hick, Rod

2015-03-01

The two most prominent measures of material poverty within contemporary European poverty analysis are low income and material deprivation. However, it is by now well-known that these measures identify substantially different people as being poor. In this research note, I seek to demonstrate that there are at least three ways to understand the mismatch between low income and material deprivation, relating to three different forms of identification: identifying poor households, identifying groups at risk of poverty and identifying trends in material poverty over time. Drawing on data from the British Household Panel Survey, I show that while low income and material deprivation identify very different households as being poor, and display distinct trends over time, in many cases they identify the same groups at being at risk of material poverty. © London School of Economics and Political Science 2014.

Ability of ICU Health-Care Professionals to Identify Patient-Ventilator Asynchrony Using Waveform Analysis.

PubMed

Ramirez, Ivan I; Arellano, Daniel H; Adasme, Rodrigo S; Landeros, Jose M; Salinas, Francisco A; Vargas, Alvaro G; Vasquez, Francisco J; Lobos, Ignacio A; Oyarzun, Magdalena L; Restrepo, Ruben D

2017-02-01

Waveform analysis by visual inspection can be a reliable, noninvasive, and useful tool for detecting patient-ventilator asynchrony. However, it is a skill that requires a properly trained professional. This observational study was conducted in 17 urban ICUs. Health-care professionals (HCPs) working in these ICUs were asked to recognize different types of asynchrony shown in 3 evaluation videos. The health-care professionals were categorized according to years of experience, prior training in mechanical ventilation, profession, and number of asynchronies identified correctly. A total of 366 HCPs were evaluated. Statistically significant differences were found when HCPs with and without prior training in mechanical ventilation (trained vs non-trained HCPs) were compared according to the number of asynchronies detected correctly (of the HCPs who identified 3 asynchronies, 63 [81%] trained vs 15 [19%] non-trained, P < .001; 2 asynchronies, 72 [65%] trained vs 39 [35%] non-trained, P = .034; 1 asynchrony, 55 [47%] trained vs 61 [53%] non-trained, P = .02; 0 asynchronies, 17 [28%] trained vs 44 [72%] non-trained, P < .001). HCPs who had prior training in mechanical ventilation also increased, nearly 4-fold, their odds of identifying ≥2 asynchronies correctly (odds ratio 3.67, 95% CI 1.93-6.96, P < .001). However, neither years of experience nor profession were associated with the ability of HCPs to identify asynchrony. HCPs who have specific training in mechanical ventilation increase their ability to identify asynchrony using waveform analysis. Neither experience nor profession proved to be a relevant factor to identify asynchrony correctly using waveform analysis. Copyright © 2017 by Daedalus Enterprises.

Identifying Effective Education Interventions in Sub-Saharan Africa: A Meta-Analysis of Rigorous Impact Evaluations

ERIC Educational Resources Information Center

Conn, Katharine

2014-01-01

The aim of this dissertation is to identify effective educational interventions in Sub-Saharan African with an impact on student learning. This is the first meta-analysis in the field of education conducted for Sub-Saharan Africa. This paper takes an in-depth look at twelve different types of education interventions or programs and attempts to not…

Interdisciplinary research and education in the Vienna Doctoral Programme on Water Resource Systems: a framework for evaluation

NASA Astrophysics Data System (ADS)

Bloeschl, G.; Carr, G.; Loucks, D. P.

2017-12-01

Greater understanding of how interdisciplinary research and education evolves is critical for identifying and implementing appropriate programme management strategies. We propose a program evaluation framework that is based on social learning processes (individual learning, interdisciplinary research practices, and interaction between researchers with different backgrounds); social capital outcomes (ability to interact, interpersonal connectivity, and shared understanding); and knowledge and human capital outcomes (new knowledge that integrates multiple research fields). The framework is tested on established case study doctoral program: the Vienna Doctoral Program on Water Resource Systems. Data are collected via mixed qualitative/quantitative methods that include semi-structured interviews, publication co-author analysis, analysis of research proposals, categorisation of the interdisciplinarity of publications and graduate analysis. Through the evaluation and analysis, several interesting findings about how interdisciplinary research evolves and can be supported are identified. Firstly, different aspects of individual learning seem to contribute to a researcher's ability to interact with researchers from other research fields and work collaboratively. These include learning new material from different research fields, learning how to learn new material and learning how to integrate different material. Secondly, shared interdisciplinary research practices can be identified that may be common to other programs and support interaction and shared understanding between different researchers. They include clarification and questioning, harnessing differences and setting defensible research boundaries. Thirdly, intensive interaction between researchers from different backgrounds support connectivity between the researchers, further enabling cross-disciplinary collaborative work. The case study data suggest that social learning processes and social capital outcomes precede new interdisciplinary research findings and are therefore a critical aspect to consider in interdisciplinary program management.

Exploring Game Performance in the National Basketball Association Using Player Tracking Data

PubMed Central

Calleja-González, Julio; Jiménez Sáiz, Sergio; Schelling i del Alcázar, Xavi; Balciunas, Mindaugas

2015-01-01

Recent player tracking technology provides new information about basketball game performance. The aim of this study was to (i) compare the game performances of all-star and non all-star basketball players from the National Basketball Association (NBA), and (ii) describe the different basketball game performance profiles based on the different game roles. Archival data were obtained from all 2013-2014 regular season games (n = 1230). The variables analyzed included the points per game, minutes played and the game actions recorded by the player tracking system. To accomplish the first aim, the performance per minute of play was analyzed using a descriptive discriminant analysis to identify which variables best predict the all-star and non all-star playing categories. The all-star players showed slower velocities in defense and performed better in elbow touches, defensive rebounds, close touches, close points and pull-up points, possibly due to optimized attention processes that are key for perceiving the required appropriate environmental information. The second aim was addressed using a k-means cluster analysis, with the aim of creating maximal different performance profile groupings. Afterwards, a descriptive discriminant analysis identified which variables best predict the different playing clusters. The results identified different playing profile of performers, particularly related to the game roles of scoring, passing, defensive and all-round game behavior. Coaching staffs may apply this information to different players, while accounting for individual differences and functional variability, to optimize practice planning and, consequently, the game performances of individuals and teams. PMID:26171606

Exploring Game Performance in the National Basketball Association Using Player Tracking Data.

PubMed

Sampaio, Jaime; McGarry, Tim; Calleja-González, Julio; Jiménez Sáiz, Sergio; Schelling I Del Alcázar, Xavi; Balciunas, Mindaugas

2015-01-01

Recent player tracking technology provides new information about basketball game performance. The aim of this study was to (i) compare the game performances of all-star and non all-star basketball players from the National Basketball Association (NBA), and (ii) describe the different basketball game performance profiles based on the different game roles. Archival data were obtained from all 2013-2014 regular season games (n = 1230). The variables analyzed included the points per game, minutes played and the game actions recorded by the player tracking system. To accomplish the first aim, the performance per minute of play was analyzed using a descriptive discriminant analysis to identify which variables best predict the all-star and non all-star playing categories. The all-star players showed slower velocities in defense and performed better in elbow touches, defensive rebounds, close touches, close points and pull-up points, possibly due to optimized attention processes that are key for perceiving the required appropriate environmental information. The second aim was addressed using a k-means cluster analysis, with the aim of creating maximal different performance profile groupings. Afterwards, a descriptive discriminant analysis identified which variables best predict the different playing clusters. The results identified different playing profile of performers, particularly related to the game roles of scoring, passing, defensive and all-round game behavior. Coaching staffs may apply this information to different players, while accounting for individual differences and functional variability, to optimize practice planning and, consequently, the game performances of individuals and teams.

Identification and Characteristics of microRNAs from Army Worm, Spodoptera frugiperda Cell Line Sf21

PubMed Central

Kakumani, Pavan Kumar; Chinnappan, Mahendran; Singh, Ashok K.; Malhotra, Pawan; Mukherjee, Sunil K.; Bhatnagar, Raj K.

2015-01-01

microRNAs play important regulatory role in all intrinsic cellular functions. Amongst lepidopteran insects, miRNAs from only Bombyx mori have been studied extensively with a little focus on Spodoptera sp. In the present study, we identified a total of 226 miRNAs from Spodoptera frugiperda cell line Sf21. Of the total, 116 miRNAs were well conserved within other insects, like B. mori, Drosophila melanogaster and Tribolium castenum while the remaining 110 miRNAs were identified as novel based on comparative analysis with the insect miRNA data set. Landscape distribution analysis based on Sf21 genome assembly revealed clustering of few novel miRNAs. A total of 5 miRNA clusters were identified and the largest one encodes 5 miRNA genes. In addition, 12 miRNAs were validated using northern blot analysis and putative functional role assignment for 6 Sf miRNAs was investigated by examining their relative abundance at different developmental stages of Spodoptera litura and body parts of 6th instar larvae. Further, we identified a total of 809 potential target genes with GO terms for selected miRNAs, involved in different metabolic and signalling pathways of the insect. The newly identified miRNAs greatly enrich the repertoire of insect miRNAs and analysis of expression profiles reveal their involvement at various steps of biochemical pathways of the army worm. PMID:25693181

Identification and characteristics of microRNAs from army worm, Spodoptera frugiperda cell line Sf21.

PubMed

Kakumani, Pavan Kumar; Chinnappan, Mahendran; Singh, Ashok K; Malhotra, Pawan; Mukherjee, Sunil K; Bhatnagar, Raj K

2015-01-01

microRNAs play important regulatory role in all intrinsic cellular functions. Amongst lepidopteran insects, miRNAs from only Bombyx mori have been studied extensively with a little focus on Spodoptera sp. In the present study, we identified a total of 226 miRNAs from Spodoptera frugiperda cell line Sf21. Of the total, 116 miRNAs were well conserved within other insects, like B. mori, Drosophila melanogaster and Tribolium castenum while the remaining 110 miRNAs were identified as novel based on comparative analysis with the insect miRNA data set. Landscape distribution analysis based on Sf21 genome assembly revealed clustering of few novel miRNAs. A total of 5 miRNA clusters were identified and the largest one encodes 5 miRNA genes. In addition, 12 miRNAs were validated using northern blot analysis and putative functional role assignment for 6 Sf miRNAs was investigated by examining their relative abundance at different developmental stages of Spodoptera litura and body parts of 6th instar larvae. Further, we identified a total of 809 potential target genes with GO terms for selected miRNAs, involved in different metabolic and signalling pathways of the insect. The newly identified miRNAs greatly enrich the repertoire of insect miRNAs and analysis of expression profiles reveal their involvement at various steps of biochemical pathways of the army worm.

Genetic relatedness of Brazilian Colletotrichum truncatum isolates assessed by vegetative compatibility groups and RAPD analysis.

PubMed

Sant'Anna, Juliane R; Miyamoto, Cláudia T; Rosada, Lúcia J; Franco, Claudinéia C S; Kaneshima, Edilson N; Castro-Prado, Marialba A A

2010-01-01

The genetic variation among nine soybean-originating isolates of Colletotrichum truncatum from different Brazilian states was studied. Nitrate non-utilizing (nit) mutants were obtained with potassium chlorate and used to characterize vegetative compatibility reactions, heterokaryosis and RAPD profile. Based on pairings of nit mutants from the different isolates, five vegetative complementation groups (VCG) were identified, and barriers to the formation of heterokaryons were observed among isolates derived from the same geographic area. No complementation was observed among any of the nit mutants recovered from the isolate A, which was designed heterokaryon-self-incompatible. Based on RAPD analysis, a polymorphism was detected among the wild isolate C and their nit1 and NitM mutants. RAPD amplification, with five different primers, also showed polymorphic profiles among Brazilian C. truncatum isolates. Dendrogram analysis resulted in a similarity degree ranging between 0.331 and 0.882 among isolates and identified three RAPD groups. Despite the lack of a correlation between the RAPD analysis and the vegetative compatibility grouping, results demonstrated the potential of VCG analysis to differentiate C. truncatum isolates genotypically similar when compared by RAPD.

Leishmania major: genetic heterogeneity of Iranian isolates by single-strand conformation polymorphism and sequence analysis of ribosomal DNA internal transcribed spacer.

PubMed

Tashakori, Mahnaz; Mahnaz, Tashakori; Kuhls, Katrin; Katrin, Kuhls; Al-Jawabreh, Amer; Amer, Al-Jawabreh; Mauricio, Isabel L; Isabel, Mauricio; Schönian, Gabriele; Gabriele, Schönian; Farajnia, Safar; Safar, Farajnia; Alimohammadian, Mohammad Hossein; Hossein, Alimohammadian Mohammad

2006-04-01

Protozoan parasites of Leishmania major are the causative agents of cutaneous leishmaniasis in different parts of Iran. We applied PCR-based methods to analyze L. major parasites isolated from patients with active lesions from different geographic areas in Iran in order to understand DNA polymorphisms within L. major species. Twenty-four isolates were identified as L. major by RFLP analysis of the ribosomal internal transcribed spacer 1 (ITS1) amplicons. These isolates were further studied by single-strand conformation polymorphism (SSCP) analysis and sequencing of ITS1 and ITS2. Data obtained from SSCP analysis of the ITS1 and ITS2 loci revealed three and four different patterns among all studied samples, respectively. Sequencing of ITS1 and ITS2 confirmed the results of SSCP analysis and showed the potential of the PCR-SSCP method for assessing genetic heterogeneity within L. major. Different patterns in ITS1 were due to substitution of one nucleotide, whereas in ITS2 the changes were defined by variation in the number of repeats in two polymorphic microsatellites. In total five genotypic groups LmA, LmB, LmC, LmD and LmE were identified among L. major isolates. The most frequent genotype, LmA, was detected in isolates collected from different endemic areas of cutaneous leishmaniasis in Iran. Genotypes LmC, LmD and LmE were found only in the new focus of CL in Damghan (Semnan province) and LmB was identified exclusively among isolates of Kashan focus (Isfahan province). The distribution of genetic polymorphisms suggests the existence of distinct endemic regions of L. major in Iran.

A Comparison of Athletic Movement Among Talent-Identified Juniors From Different Football Codes in Australia: Implications for Talent Development.

PubMed

Woods, Carl T; Keller, Brad S; McKeown, Ian; Robertson, Sam

2016-09-01

Woods, CT, Keller, BS, McKeown, I, and Robertson, S. A comparison of athletic movement among talent-identified juniors from different football codes in Australia: implications for talent development. J Strength Cond Res 30(9): 2440-2445, 2016-This study aimed to compare the athletic movement skill of talent-identified (TID) junior Australian Rules football (ARF) and soccer players. The athletic movement skill of 17 TID junior ARF players (17.5-18.3 years) was compared against 17 TID junior soccer players (17.9-18.7 years). Players in both groups were members of an elite junior talent development program within their respective football codes. All players performed an athletic movement assessment that included an overhead squat, double lunge, single-leg Romanian deadlift (both movements performed on right and left legs), a push-up, and a chin-up. Each movement was scored across 3 essential assessment criteria using a 3-point scale. The total score for each movement (maximum of 9) and the overall total score (maximum of 63) were used as the criterion variables for analysis. A multivariate analysis of variance tested the main effect of football code (2 levels) on the criterion variables, whereas a 1-way analysis of variance identified where differences occurred. A significant effect was noted, with the TID junior ARF players outscoring their soccer counterparts when performing the overhead squat and push-up. No other criterions significantly differed according to the main effect. Practitioners should be aware that specific sporting requirements may incur slight differences in athletic movement skill among TID juniors from different football codes. However, given the low athletic movement skill noted in both football codes, developmental coaches should address the underlying movement skill capabilities of juniors when prescribing physical training in both codes.

An efficient approach to identify different chemical markers between fibrous root and rhizome of Anemarrhena asphodeloides by ultra high-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry with multivariate statistical analysis.

PubMed

Wang, Fang-Xu; Yuan, Jian-Chao; Kang, Li-Ping; Pang, Xu; Yan, Ren-Yi; Zhao, Yang; Zhang, Jie; Sun, Xin-Guang; Ma, Bai-Ping

2016-09-10

An ultra high-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry approach coupled with multivariate statistical analysis was established and applied to rapidly distinguish the chemical differences between fibrous root and rhizome of Anemarrhena asphodeloides. The datasets of tR-m/z pairs, ion intensity and sample code were processed by principal component analysis and orthogonal partial least squares discriminant analysis. Chemical markers could be identified based on their exact mass data, fragmentation characteristics, and retention times. And the new compounds among chemical markers could be isolated rapidly guided by the ultra high-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry and their definitive structures would be further elucidated by NMR spectra. Using this approach, twenty-four markers were identified on line including nine new saponins and five new steroidal saponins of them were obtained in pure form. The study validated this proposed approach as a suitable method for identification of the chemical differences between various medicinal parts in order to expand medicinal parts and increase the utilization rate of resources. Copyright © 2016 Elsevier B.V. All rights reserved.

Textual Analysis of General Surgery Residency Personal Statements: Topics and Gender Differences.

PubMed

Ostapenko, Laura; Schonhardt-Bailey, Cheryl; Sublette, Jessica Walling; Smink, Douglas S; Osman, Nora Y

Applicants to US general surgery residency training programs submit standardized applications. Applicants use the personal statement to express their individual rationale for a career in surgery. Our research explores common topics and gender differences within the personal statements of general surgery applicants. We analyzed the electronic residency application service personal statements of 578 applicants (containing 3,82,405 words) from Liaison Committee on Medical Education-accredited medical schools to a single ACGME-accredited general surgery program using an automated textual analysis program to identify common topics and gender differences. Using a recursive algorithm, the program identified common words and clusters, grouping them into topic classes, which are internally validated. We identified and labeled 8 statistically significant topic classes through independent review: "my story," "the art of surgery," "clinical vignettes," "why I love surgery," "residency program characteristics," "working as a team," "academics and research," and "global health and policy." Although some classes were common to all applications, we also identified gender-specific differences. Notably, women were significantly more likely than men to be represented within the class of "working as a team." (p < 0.01) Furthermore, men were significantly more likely than women to be represented within the class of "clinical vignettes" (p < 0.01). Applying textual analysis to a national cohort, we identified common narrative topics in the personal statements of aspiring general surgeons, noting differences between the statements of men and women. Women were more likely to discuss surgery as a team endeavor while men were more likely to focus on the details of their surgical experiences. Our work mirrors what has been found in social psychology research on gender-based differences in how men and women communicate their career goals and aspirations in other competitive professional situations. Copyright © 2017 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Joint source based morphometry identifies linked gray and white matter group differences

PubMed Central

Xu, Lai; Pearlson, Godfrey; Calhoun, Vince D.

2009-01-01

We present a multivariate approach called joint source based morphometry (jSBM), to identify linked gray and white matter regions which differ between groups. In jSBM, joint independent component analysis (jICA) is used to decompose preprocessed gray and white matter images into joint sources and statistical analysis is used to determine the significant joint sources showing group differences and their relationship to other variables of interest (e.g. age or sex). The identified joint sources are groupings of linked gray and white matter regions with common covariation among subjects. In this study, we first provide a simulation to validate the jSBM approach. To illustrate our method on real data, jSBM is then applied to structural magnetic resonance imaging (sMRI) data obtained from 120 chronic schizophrenia patients and 120 healthy controls to identify group differences. JSBM identified four joint sources as significantly associated with schizophrenia. Linked gray–white matter regions identified in each of the joint sources included: 1) temporal — corpus callosum, 2) occipital/frontal — inferior fronto-occipital fasciculus, 3) frontal/parietal/occipital/temporal —superior longitudinal fasciculus and 4) parietal/frontal — thalamus. Age effects on all four joint sources were significant, but sex effects were significant only for the third joint source. Our findings demonstrate that jSBM can exploit the natural linkage between gray and white matter by incorporating them into a unified framework. This approach is applicable to a wide variety of problems to study linked gray and white matter group differences. PMID:18992825

Antimicrobial resistance determinant microarray for analysis of multi-drug resistant isolates

NASA Astrophysics Data System (ADS)

Taitt, Chris Rowe; Leski, Tomasz; Stenger, David; Vora, Gary J.; House, Brent; Nicklasson, Matilda; Pimentel, Guillermo; Zurawski, Daniel V.; Kirkup, Benjamin C.; Craft, David; Waterman, Paige E.; Lesho, Emil P.; Bangurae, Umaru; Ansumana, Rashid

2012-06-01

The prevalence of multidrug-resistant infections in personnel wounded in Iraq and Afghanistan has made it challenging for physicians to choose effective therapeutics in a timely fashion. To address the challenge of identifying the potential for drug resistance, we have developed the Antimicrobial Resistance Determinant Microarray (ARDM) to provide DNAbased analysis for over 250 resistance genes covering 12 classes of antibiotics. Over 70 drug-resistant bacteria from different geographic regions have been analyzed on ARDM, with significant differences in patterns of resistance identified: genes for resistance to sulfonamides, trimethoprim, chloramphenicol, rifampin, and macrolide-lincosamidesulfonamide drugs were more frequently identified in isolates from sources in Iraq/Afghanistan. Of particular concern was the presence of genes responsible for resistance to many of the last-resort antibiotics used to treat war traumaassociated infections.

Use of direct gradient analysis to uncover biological hypotheses in 16s survey data and beyond.

PubMed

Erb-Downward, John R; Sadighi Akha, Amir A; Wang, Juan; Shen, Ning; He, Bei; Martinez, Fernando J; Gyetko, Margaret R; Curtis, Jeffrey L; Huffnagle, Gary B

2012-01-01

This study investigated the use of direct gradient analysis of bacterial 16S pyrosequencing surveys to identify relevant bacterial community signals in the midst of a "noisy" background, and to facilitate hypothesis-testing both within and beyond the realm of ecological surveys. The results, utilizing 3 different real world data sets, demonstrate the utility of adding direct gradient analysis to any analysis that draws conclusions from indirect methods such as Principal Component Analysis (PCA) and Principal Coordinates Analysis (PCoA). Direct gradient analysis produces testable models, and can identify significant patterns in the midst of noisy data. Additionally, we demonstrate that direct gradient analysis can be used with other kinds of multivariate data sets, such as flow cytometric data, to identify differentially expressed populations. The results of this study demonstrate the utility of direct gradient analysis in microbial ecology and in other areas of research where large multivariate data sets are involved.

Understanding pea resistance mechanisms in response to Fusarium oxysporum through proteomic analysis.

PubMed

Castillejo, María Ángeles; Bani, Moustafa; Rubiales, Diego

2015-07-01

Fusarium oxysporum f. sp. pisi (Fop) is an important and destructive pathogen affecting pea crop (Pisum sativum) throughout the world. Control of this disease is achieved mainly by integration of different disease management procedures. However, the constant evolution of the pathogen drives the necessity to broaden the molecular basis of resistance to Fop. Our proteomic study was performed on pea with the aim of identifying proteins involved in different resistance mechanisms operating during F. oxysporum infection. For such purpose, we used a two-dimensional electrophoresis (2-DE) coupled to mass spectrometry (MALDI-TOF/TOF) analysis to study the root proteome of three pea genotypes showing different resistance response to Fop race 2. Multivariate statistical analysis identified 132 differential protein spots under the experimental conditions (genotypes/treatments). All of these protein spots were subjected to mass spectrometry analysis to deduce their possible functions. A total of 53 proteins were identified using a combination of peptide mass fingerprinting (PMF) and MSMS fragmentation. The following main functional categories were assigned to the identified proteins: carbohydrate and energy metabolism, nucleotides and aminoacid metabolism, signal transduction and cellular process, folding and degradation, redox and homeostasis, defense, biosynthetic process and transcription/translation. Results obtained in this work suggest that the most susceptible genotypes have increased levels of enzymes involved in the production of reducing power which could then be used as cofactor for enzymes of the redox reactions. This is in concordance with the fact that a ROS burst occurred in the same genotypes, as well as an increase of PR proteins. Conversely, in the resistant genotype proteins responsible to induce changes in the membrane and cell wall composition related to reinforcement were identified. Results are discussed in terms of the differential response to Fop. Copyright © 2015 Elsevier Ltd. All rights reserved.

Occurrence of different Canine distemper virus lineages in Italian dogs.

PubMed

Balboni, Andrea; De Lorenzo Dandola, Giorgia; Scagliarini, Alessandra; Prosperi, Santino; Battilani, Mara

2014-01-01

This study describes the sequence analysis of the H gene of 7 Canine distemper virus (CDV) strains identified in dogs in Italy between years 2002-2012. The phylogenetic analysis showed that the CDV strains belonged to 2 clusters: 6 viruses were identified as Arctic-like lineage and 1 as Europe 1 lineage. These data show a considerable prevalence of Arctic-like-CDVs in the analysed dogs. The dogs and the 3 viruses more recently identified showed 4 distinctive amino acid mutations compared to all other Arctic CDVs.

Qualitative and quantitative studies of chemical composition of sandarac resin by GC-MS.

PubMed

Kononenko, I; de Viguerie, L; Rochut, S; Walter, Ph

2017-01-01

The chemical composition of sandarac resin was investigated qualitatively and quantitatively by gas chromatography-mass spectrometry (GC-MS). Six compounds with labdane and pimarane skeletons were identified in the resin. The obtained mass spectra were interpreted and the mass spectrometric behaviour of these diterpenoids under EI conditions was described. Quantitative analysis by the method of internal standard revealed that identified diterpenoids represent only 10-30% of the analysed sample. The sandarac resin from different suppliers was analysed (from Kremer, Okhra, Color Rare, La Marchande de Couleurs, L'Atelier Montessori, Hevea). The analysis of different lumps of resins showed that the chemical composition differs from one lump to another, varying mainly in the relative distributions of the components.

Comparative analysis of student self-reflections on course projects

NASA Astrophysics Data System (ADS)

Pomales-García, Cristina; Cortés Barreto, Kenneth

2014-11-01

This study presents the skills, experiences, and values identified in project self-reflections of 161 undergraduate engineering students. Self-reflections from two different engineering design courses, which provide experiences in project-based learning (PBL), are analysed through the content analysis methodology. Results show that 'application', 'true life', 'satisfaction', and 'communication' are the common keywords shared in the reflections. Multiple hypothesis tests to identify differences between courses, project types, years, and gender suggest that there are no significant differences between experiences, skills, and values self-reported by students who completed either a case study or an industry project. Based on research findings, recommendations will be provided to enhance the engineering curriculum based on PBL experiences to support the development of relevant professional skills and experiences.

Is valve choice a significant determinant of paravalular leak post-transcatheter aortic valve implantation? A systematic review and meta-analysis.

PubMed

O'Sullivan, Katie E; Gough, Aideen; Segurado, Ricardo; Barry, Mitchel; Sugrue, Declan; Hurley, John

2014-05-01

Paravalvular regurgitation (PVR) following transcatheter aortic valve implantation (TAVI) is associated with poor survival. The two main valve delivery systems used to date differ significantly in both structure and deployment technique. The primary objective of this study was to perform a systematic review and meta-analysis of studies identifying PVR in patients post-TAVI using Medtronic CoreValve (MCV) and Edward Sapien (ES) valves in order to identify whether a significant difference exists between valve types. The secondary objective was to identify additional factors predisposing to PVR to provide an overview of the other associated considerations. A systematic review and meta-analysis of the current literature to identify PVR rate in patients with MCV and ES valves was performed. We also sought to examine other factors predisposing to PVR. A total of 5910 patients were identified from 9 studies. PVR rates for MCV and ES were analysed. MCV was associated with a higher PVR rate of 15.75% [95% confidence interval (CI) 12.48-19.32] compared with ES 3.93% [95% CI 1.05-8.38]. We separately reviewed predisposing factors associated with PVR. A formal comparison of the MCV and ES valve leakage rates by mixed-effects meta-regression with a fixed-effect moderator variable for valve type (MCV or ES) suggested a statistically significant difference in leakage rate between the two valve types (P = 0.0002). Unfavourable anatomical and pathological factors as well as valve choice have an impact on rates of PVR. Additionally, certain anatomical features dictate valve choice. A direct comparison of all the predisposing factors at this time is not possible and will require prospective multivariate analysis. There is, however, a significant difference in the PVR rates between valves based on the published observational data available to date. The ES valve associated with a lower incidence of PVR overall; therefore, we conclude that valve choice is indeed a significant determinant of PVR post-TAVI.

Comparative transcriptome analysis of different chemotypes elucidates withanolide biosynthesis pathway from medicinal plant Withania somnifera

PubMed Central

Gupta, Parul; Goel, Ridhi; Agarwal, Aditya Vikram; Asif, Mehar Hasan; Sangwan, Neelam Singh; Sangwan, Rajender Singh; Trivedi, Prabodh Kumar

2015-01-01

Withania somnifera is one of the most valuable medicinal plants synthesizing secondary metabolites known as withanolides. Despite pharmaceutical importance, limited information is available about the biosynthesis of withanolides. Chemo-profiling of leaf and root tissues of Withania suggest differences in the content and/or nature of withanolides in different chemotypes. To identify genes involved in chemotype and/or tissue-specific withanolide biosynthesis, we established transcriptomes of leaf and root tissues of distinct chemotypes. Genes encoding enzymes for intermediate steps of terpenoid backbone biosynthesis with their alternatively spliced forms and paralogous have been identified. Analysis suggests differential expression of large number genes among leaf and root tissues of different chemotypes. Study also identified differentially expressing transcripts encoding cytochrome P450s, glycosyltransferases, methyltransferases and transcription factors which might be involved in chemodiversity in Withania. Virus induced gene silencing of the sterol ∆7-reductase (WsDWF5) involved in the synthesis of 24-methylene cholesterol, withanolide backbone, suggests role of this enzyme in biosynthesis of withanolides. Information generated, in this study, provides a rich resource for functional analysis of withanolide-specific genes to elucidate chemotype- as well as tissue-specific withanolide biosynthesis. This genomic resource will also help in development of new tools for functional genomics and breeding in Withania. PMID:26688389

Methodological improvements in voxel-based analysis of diffusion tensor images: applications to study the impact of apolipoprotein E on white matter integrity.

PubMed

Newlander, Shawn M; Chu, Alan; Sinha, Usha S; Lu, Po H; Bartzokis, George

2014-02-01

To identify regional differences in apparent diffusion coefficient (ADC) and fractional anisotropy (FA) using customized preprocessing before voxel-based analysis (VBA) in 14 normal subjects with the specific genes that decrease (apolipoprotein [APO] E ε2) and that increase (APOE ε4) the risk of Alzheimer's disease. Diffusion tensor images (DTI) acquired at 1.5 Tesla were denoised with a total variation tensor regularization algorithm before affine and nonlinear registration to generate a common reference frame for the image volumes of all subjects. Anisotropic and isotropic smoothing with varying kernel sizes was applied to the aligned data before VBA to determine regional differences between cohorts segregated by allele status. VBA on the denoised tensor data identified regions of reduced FA in APOE ε4 compared with the APOE ε2 healthy older carriers. The most consistent results were obtained using the denoised tensor and anisotropic smoothing before statistical testing. In contrast, isotropic smoothing identified regional differences for small filter sizes alone, emphasizing that this method introduces bias in FA values for higher kernel sizes. Voxel-based DTI analysis can be performed on low signal to noise ratio images to detect subtle regional differences in cohorts using the proposed preprocessing techniques. Copyright © 2013 Wiley Periodicals, Inc.

Application of the Statistical ICA Technique in the DANCE Data Analysis

NASA Astrophysics Data System (ADS)

Baramsai, Bayarbadrakh; Jandel, M.; Bredeweg, T. A.; Rusev, G.; Walker, C. L.; Couture, A.; Mosby, S.; Ullmann, J. L.; Dance Collaboration

2015-10-01

The Detector for Advanced Neutron Capture Experiments (DANCE) at the Los Alamos Neutron Science Center is used to improve our understanding of the neutron capture reaction. DANCE is a highly efficient 4 π γ-ray detector array consisting of 160 BaF2 crystals which make it an ideal tool for neutron capture experiments. The (n, γ) reaction Q-value equals to the sum energy of all γ-rays emitted in the de-excitation cascades from the excited capture state to the ground state. The total γ-ray energy is used to identify reactions on different isotopes as well as the background. However, it's challenging to identify contribution in the Esum spectra from different isotopes with the similar Q-values. Recently we have tested the applicability of modern statistical methods such as Independent Component Analysis (ICA) to identify and separate different (n, γ) reaction yields on different isotopes that are present in the target material. ICA is a recently developed computational tool for separating multidimensional data into statistically independent additive subcomponents. In this conference talk, we present some results of the application of ICA algorithms and its modification for the DANCE experimental data analysis. This research is supported by the U. S. Department of Energy, Office of Science, Nuclear Physics under the Early Career Award No. LANL20135009.

Sex differences in gut microbiota in patients with major depressive disorder.

PubMed

Chen, Jian-Jun; Zheng, Peng; Liu, Yi-Yun; Zhong, Xiao-Gang; Wang, Hai-Yang; Guo, Yu-Jie; Xie, Peng

2018-01-01

Our previous studies found that disturbances in gut microbiota might have a causative role in the onset of major depressive disorder (MDD). The aim of this study was to investigate whether there were sex differences in gut microbiota in patients with MDD. First-episode drug-naïve MDD patients and healthy controls were included. 16S rRNA gene sequences extracted from the fecal samples of the included subjects were analyzed. Principal-coordinate analysis and partial least squares-discriminant analysis were used to assess whether there were sex-specific gut microbiota. A random forest algorithm was used to identify the differential operational taxonomic units. Linear discriminant-analysis effect size was further used to identify the dominant sex-specific phylotypes responsible for the differences between MDD patients and healthy controls. In total, 57 and 74 differential operational taxonomic units responsible for separating female and male MDD patients from their healthy counterparts were identified. Compared with their healthy counterparts, increased Actinobacteria and decreased Bacteroidetes levels were found in female and male MDD patients, respectively. The most differentially abundant bacterial taxa in female and male MDD patients belonged to phyla Actinobacteria and Bacteroidia, respectively. Meanwhile, female and male MDD patients had different dominant phylotypes. These results demonstrated that there were sex differences in gut microbiota in patients with MDD. The suitability of Actinobacteria and Bacteroidia as the sex-specific biomarkers for diagnosing MDD should be further explored.

Integrated corridor management analysis, modeling, and simulation for the I–15 corridor in San Diego, California—post-deployment analysis plan.

DOT National Transportation Integrated Search

2016-11-01

Post-Deployment Analysis, Modeling, and Simulation (AMS) activities focus on identifying impacts and benefits of the as-deployed Integrated Corridor Management (ICM) system. The as-deployed ICM strategies may differ from as-planned ...

Integrated corridor management : analysis, modeling, and simulation for the U.S.-15 corridor in Dallas, Texas—post-deployment analysis plan.

DOT National Transportation Integrated Search

2016-10-01

Post-Deployment Analysis, Modeling, and Simulation (AMS) activities focus on identifying impacts and benefits of the as-deployed Integrated Corridor Management (ICM) system. The as-deployed ICM strategies may differ from as-planned ...

A method comparison of photovoice and content analysis: research examining challenges and supports of family caregivers.

PubMed

Faucher, Mary Ann; Garner, Shelby L

2015-11-01

The purpose of this manuscript is to compare methods and thematic representations of the challenges and supports of family caregivers identified with photovoice methodology contrasted with content analysis, a more traditional qualitative approach. Results from a photovoice study utilizing a participatory action research framework was compared to an analysis of the audio-transcripts from that study utilizing content analysis methodology. Major similarities between the results are identified with some notable differences. Content analysis provides a more in-depth and abstract elucidation of the nature of the challenges and supports of the family caregiver. The comparison provides evidence to support the trustworthiness of photovoice methodology with limitations identified. The enhanced elaboration of theme and categories with content analysis may have some advantages relevant to the utilization of this knowledge by health care professionals. Copyright © 2015 Elsevier Inc. All rights reserved.

Principal component analysis and analysis of variance on the effects of Entellan New on the Raman spectra of fibers.

PubMed

Yu, Marcia M L; Sandercock, P Mark L

2012-01-01

During the forensic examination of textile fibers, fibers are usually mounted on glass slides for visual inspection and identification under the microscope. One method that has the capability to accurately identify single textile fibers without subsequent demounting is Raman microspectroscopy. The effect of the mountant Entellan New on the Raman spectra of fibers was investigated to determine if it is suitable for fiber analysis. Raman spectra of synthetic fibers mounted in three different ways were collected and subjected to multivariate analysis. Principal component analysis score plots revealed that while spectra from different fiber classes formed distinct groups, fibers of the same class formed a single group regardless of the mounting method. The spectra of bare fibers and those mounted in Entellan New were found to be statistically indistinguishable by analysis of variance calculations. These results demonstrate that fibers mounted in Entellan New may be identified directly by Raman microspectroscopy without further sample preparation. © 2011 American Academy of Forensic Sciences.

Characterization of volatile profile from ten different varieties of Chinese jujubes by HS-SPME/GC-MS coupled with E-nose.

PubMed

Chen, Qinqin; Song, Jianxin; Bi, Jinfeng; Meng, Xianjun; Wu, Xinye

2018-03-01

Volatile profile of ten different varieties of fresh jujubes was characterized by HS-SPME/GC-MS (headspace solid phase micro-extraction combined with gas chromatography-mass spectrometry) and E-nose (electronic nose). GC-MS results showed that a total of 51 aroma compounds were identified in jujubes, hexanoic acid, hexanal, (E)-2-hexenal, (Z)-2-heptenal, benzaldehyde and (E)-2-nonenal were the main aroma components with contributions that over 70%. Differentiation of jujube varieties was conducted by cluster analysis of GC-MS data and principal component analysis & linear discriminant analysis of E-nose data. Both results showed that jujubes could be mainly divided into two groups: group A (JZ, PDDZ, JSXZ and LWZZ) and group B (BZ, YZ, MZ, XZ and DZ). There were significant differences in contents of alcohols, acids and aromatic compounds between group A and B. GC-MS coupled with E-nose could be a fast and accurate method to identify the general flavor difference in different varieties of jujubes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Trace-Element Analysis by Use of PIXE Technique on Agricultural Products

NASA Astrophysics Data System (ADS)

Takagi, A.; Yokoyama, R.; Makisaka, K.; Kisamori, K.; Kuwada, Y.; Nishimura, D.; Matsumiya, R.; Fujita, Y.; Mihara, M.; Matsuta, K.; Fukuda, M.

2009-10-01

In order to examine whether a trace-element analysis by PIXE (Particle Induced X-ray Emission) gives a clue to identify production area of agricultural products, we carried out a study on soy beans as an example. In the present study, a proton beam at the energy of 2.3MeV was provided by Van de Graaff accelerator at Osaka University. We used a Ge detector with Be window to measure X-ray spectra. We prepared sample soy beans from China, Thailand, Taiwan, and 7 different areas in Japan. As a result of PIXE analysis, 5 elements, potassium, iron, zinc, arsenic and rubidium, have been identified. There are clear differences in relative amount of trace-elements between samples from different international regions. Chinese beans contain much more Rb than the others, while there are significant differences in Fe and Zn between beans of Thailand and Taiwan. There are relatively smaller differences among Japanese beans. This result shows that trace-elements bring us some practical information of the region where the product grown.

An application of statistics to comparative metagenomics

PubMed Central

Rodriguez-Brito, Beltran; Rohwer, Forest; Edwards, Robert A

2006-01-01

Background Metagenomics, sequence analyses of genomic DNA isolated directly from the environments, can be used to identify organisms and model community dynamics of a particular ecosystem. Metagenomics also has the potential to identify significantly different metabolic potential in different environments. Results Here we use a statistical method to compare curated subsystems, to predict the physiology, metabolism, and ecology from metagenomes. This approach can be used to identify those subsystems that are significantly different between metagenome sequences. Subsystems that were overrepresented in the Sargasso Sea and Acid Mine Drainage metagenome when compared to non-redundant databases were identified. Conclusion The methodology described herein applies statistics to the comparisons of metabolic potential in metagenomes. This analysis reveals those subsystems that are more, or less, represented in the different environments that are compared. These differences in metabolic potential lead to several testable hypotheses about physiology and metabolism of microbes from these ecosystems. PMID:16549025

An application of statistics to comparative metagenomics.

PubMed

Rodriguez-Brito, Beltran; Rohwer, Forest; Edwards, Robert A

2006-03-20

Metagenomics, sequence analyses of genomic DNA isolated directly from the environments, can be used to identify organisms and model community dynamics of a particular ecosystem. Metagenomics also has the potential to identify significantly different metabolic potential in different environments. Here we use a statistical method to compare curated subsystems, to predict the physiology, metabolism, and ecology from metagenomes. This approach can be used to identify those subsystems that are significantly different between metagenome sequences. Subsystems that were overrepresented in the Sargasso Sea and Acid Mine Drainage metagenome when compared to non-redundant databases were identified. The methodology described herein applies statistics to the comparisons of metabolic potential in metagenomes. This analysis reveals those subsystems that are more, or less, represented in the different environments that are compared. These differences in metabolic potential lead to several testable hypotheses about physiology and metabolism of microbes from these ecosystems.

Integrating genome-wide association studies and gene expression data highlights dysregulated multiple sclerosis risk pathways.

PubMed

Liu, Guiyou; Zhang, Fang; Jiang, Yongshuai; Hu, Yang; Gong, Zhongying; Liu, Shoufeng; Chen, Xiuju; Jiang, Qinghua; Hao, Junwei

2017-02-01

Much effort has been expended on identifying the genetic determinants of multiple sclerosis (MS). Existing large-scale genome-wide association study (GWAS) datasets provide strong support for using pathway and network-based analysis methods to investigate the mechanisms underlying MS. However, no shared genetic pathways have been identified to date. We hypothesize that shared genetic pathways may indeed exist in different MS-GWAS datasets. Here, we report results from a three-stage analysis of GWAS and expression datasets. In stage 1, we conducted multiple pathway analyses of two MS-GWAS datasets. In stage 2, we performed a candidate pathway analysis of the large-scale MS-GWAS dataset. In stage 3, we performed a pathway analysis using the dysregulated MS gene list from seven human MS case-control expression datasets. In stage 1, we identified 15 shared pathways. In stage 2, we successfully replicated 14 of these 15 significant pathways. In stage 3, we found that dysregulated MS genes were significantly enriched in 10 of 15 MS risk pathways identified in stages 1 and 2. We report shared genetic pathways in different MS-GWAS datasets and highlight some new MS risk pathways. Our findings provide new insights on the genetic determinants of MS.

Silicosis surveillance in New Jersey: targeting workplaces using occupational disease and exposure surveillance data.

PubMed

Valiante, D J; Richards, T B; Kinsley, K B

1992-01-01

To identify workplaces in New Jersey with potential for silica exposure, the New Jersey Department of Health compared four-digit Standard Industrial Classifications (SICs) identified by three different data sources: the National Occupational Exposure Survey (NOES), a new Jersey silicosis case registry, and regulatory agency compliance inspections in New Jersey. In total, the three data sources identified 204 SICs in New Jersey with potential for silica exposure. Forty-five percent of these SICs were identified by NOES only, 16% by registry cases only, 6% by compliance inspections only, and 33% by two or more sources. Since different surveillance sources implicate different SICs, this type of analysis is a useful first step in planning programs for prevention of silicosis.

Yeast species associated with orange juice: evaluation of different identification methods.

PubMed

Arias, Covadonga R; Burns, Jacqueline K; Friedrich, Lorrie M; Goodrich, Renee M; Parish, Mickey E

2002-04-01

Five different methods were used to identify yeast isolates from a variety of citrus juice sources. A total of 99 strains, including reference strains, were identified using a partial sequence of the 26S rRNA gene, restriction pattern analysis of the internal transcribed spacer region (5.8S-ITS), classical methodology, the RapID Yeast Plus system, and API 20C AUX. Twenty-three different species were identified representing 11 different genera. Distribution of the species was considerably different depending on the type of sample. Fourteen different species were identified from pasteurized single-strength orange juice that had been contaminated after pasteurization (PSOJ), while only six species were isolated from fresh-squeezed, unpasteurized orange juice (FSOJ). Among PSOJ isolates, Candida intermedia and Candida parapsilosis were the predominant species. Hanseniaspora occidentalis and Hanseniaspora uvarum represented up to 73% of total FSOJ isolates. Partial sequence of the 26S rRNA gene yielded the best results in terms of correct identification, followed by classical techniques and 5.8S-ITS analysis. The commercial identification kits RapID Yeast Plus system and API 20C AUX were able to correctly identify only 35 and 13% of the isolates, respectively. Six new 5.8S-ITS profiles were described, corresponding to Clavispora lusitaniae, Geotrichum citri-aurantii, H. occidentalis, H. vineae, Pichia fermentans, and Saccharomycopsis crataegensis. With the addition of these new profiles to the existing database, the use of 5.8S-ITS sequence became the best tool for rapid and accurate identification of yeast isolates from orange juice.

Evaluation of the impacts of traffic states on crash risks on freeways.

PubMed

Xu, Chengcheng; Liu, Pan; Wang, Wei; Li, Zhibin

2012-07-01

The primary objective of this study is to divide freeway traffic flow into different states, and to evaluate the safety performance associated with each state. Using traffic flow data and crash data collected from a northbound segment of the I-880 freeway in the state of California, United States, K-means clustering analysis was conducted to classify traffic flow into five different states. Conditional logistic regression models using case-controlled data were then developed to study the relationship between crash risks and traffic states. Traffic flow characteristics in each traffic state were compared to identify the underlying phenomena that made certain traffic states more hazardous than others. Crash risk models were also developed for different traffic states to identify how traffic flow characteristics such as speed and speed variance affected crash risks in different traffic states. The findings of this study demonstrate that the operations of freeway traffic can be divided into different states using traffic occupancy measured from nearby loop detector stations, and each traffic state can be assigned with a certain safety level. The impacts of traffic flow parameters on crash risks are different across different traffic flow states. A method based on discriminant analysis was further developed to identify traffic states given real-time freeway traffic flow data. Validation results showed that the method was of reasonably high accuracy for identifying freeway traffic states. Copyright © 2012 Elsevier Ltd. All rights reserved.

Integrative analysis for identification of shared markers from various functional cells/tissues for rheumatoid arthritis.

PubMed

Xia, Wei; Wu, Jian; Deng, Fei-Yan; Wu, Long-Fei; Zhang, Yong-Hong; Guo, Yu-Fan; Lei, Shu-Feng

2017-02-01

Rheumatoid arthritis (RA) is a systemic autoimmune disease. So far, it is unclear whether there exist common RA-related genes shared in different tissues/cells. In this study, we conducted an integrative analysis on multiple datasets to identify potential shared genes that are significant in multiple tissues/cells for RA. Seven microarray gene expression datasets representing various RA-related tissues/cells were downloaded from the Gene Expression Omnibus (GEO). Statistical analyses, testing both marginal and joint effects, were conducted to identify significant genes shared in various samples. Followed-up analyses were conducted on functional annotation clustering analysis, protein-protein interaction (PPI) analysis, gene-based association analysis, and ELISA validation analysis in in-house samples. We identified 18 shared significant genes, which were mainly involved in the immune response and chemokine signaling pathway. Among the 18 genes, eight genes (PPBP, PF4, HLA-F, S100A8, RNASEH2A, P2RY6, JAG2, and PCBP1) interact with known RA genes. Two genes (HLA-F and PCBP1) are significant in gene-based association analysis (P = 1.03E-31, P = 1.30E-2, respectively). Additionally, PCBP1 also showed differential protein expression levels in in-house case-control plasma samples (P = 2.60E-2). This study represented the first effort to identify shared RA markers from different functional cells or tissues. The results suggested that one of the shared genes, i.e., PCBP1, is a promising biomarker for RA.

Differences in expression of retinal pigment epithelium mRNA between normal canines

PubMed Central

2004-01-01

Abstract A reference database of differences in mRNA expression in normal healthy canine retinal pigment epithelium (RPE) has been established. This database identifies non-informative differences in mRNA expression that can be used in screening canine RPE for mutations associated with clinical effects on vision. Complementary DNA (cDNA) pools were prepared from mRNA harvested from RPE, amplified by PCR, and used in a subtractive hybridization protocol (representational differential analysis) to identify differences in RPE mRNA expression between canines. The effect of relatedness of the test canines on the frequency of occurrence of differences was evaluated by using 2 unrelated canines for comparison with 2 female sibling canines of blue heeler/bull terrier lineage. Differentially expressed cDNA species were cloned, sequenced, and identified by comparison to public database entries. The most frequently observed differentially expressed sequence from the unrelated canine comparison was cDNA with 21 base pairs (bp) identical to the human epithelial membrane protein 1 gene (present in 8 of 20 clones). Different clones from the same-sex sibling RPE contained repetitions of several short sequence motifs including the human epithelial membrane protein 1 (4 of 25 clones). Other prevalent differences between sibling RPE included sequences similar to a chicken genetic marker sequence motif (5 of 25), and 6 clones with homology to porcine major histocompatibility loci. In addition to identifying several repetitively occurring, noninformative, differentially expressed RPE mRNA species, the findings confirm that fewer differences occurred between siblings, highlighting the importance of using closely related subjects in representational difference analysis studies. PMID:15352545

Rapid identification of oral Actinomyces species cultivated from subgingival biofilm by MALDI-TOF-MS

PubMed Central

Stingu, Catalina S.; Borgmann, Toralf; Rodloff, Arne C.; Vielkind, Paul; Jentsch, Holger; Schellenberger, Wolfgang; Eschrich, Klaus

2015-01-01

Background Actinomyces are a common part of the residential flora of the human intestinal tract, genitourinary system and skin. Isolation and identification of Actinomyces by conventional methods is often difficult and time consuming. In recent years, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) has become a rapid and simple method to identify bacteria. Objective The present study evaluated a new in-house algorithm using MALDI-TOF-MS for rapid identification of different species of oral Actinomyces cultivated from subgingival biofilm. Design Eleven reference strains and 674 clinical strains were used in this study. All the strains were preliminarily identified using biochemical methods and then subjected to MALDI-TOF-MS analysis using both similarity-based analysis and classification methods (support vector machine [SVM]). The genotype of the reference strains and of 232 clinical strains was identified by sequence analysis of the 16S ribosomal RNA (rRNA). Results The sequence analysis of the 16S rRNA gene of all references strains confirmed their previous identification. The MALDI-TOF-MS spectra obtained from the reference strains and the other clinical strains undoubtedly identified as Actinomyces by 16S rRNA sequencing were used to create the mass spectra reference database. Already a visual inspection of the mass spectra of different species reveals both similarities and differences. However, the differences between them are not large enough to allow a reliable differentiation by similarity analysis. Therefore, classification methods were applied as an alternative approach for differentiation and identification of Actinomyces at the species level. A cross-validation of the reference database representing 14 Actinomyces species yielded correct results for all species which were represented by more than two strains in the database. Conclusions Our results suggest that a combination of MALDI-TOF-MS with powerful classification algorithms, such as SVMs, provide a useful tool for the differentiation and identification of oral Actinomyces. PMID:25597306

Study of the questionnaire of the Polytechnic University of Valencia (UPV) teaching staff, using students opinion survey. Statistical treatment

NASA Astrophysics Data System (ADS)

Martinez Gomez, Monica

Quality improvement of university institutions represents the most important challenge in the next years, and the potential tool to achieve it is based on the institutional evaluation in general, and specially the evaluation of the teaching performance. The opinion questionnaire from the students is the most generalised tool used to evaluate the teaching performance at Spanish universities. The general objective of this thesis is to develop a statistical methodology suitable to extract, analyse and interpret the information contained in the Questionnaire of Teaching Evaluation from Student Opinion (CEDA) of the UPV, aimed at optimising its practical use. The study is centred in the application of different multivariate techniques and has been structured in three parts: (1) Evaluation of the reliability, validity and dimensionality of the tool. The multivariate method used for this purpose is the Factorial Analysis. (2) Determination of the capacity of the questionnaire to identify different profiles of lecturers based on the quality perceived by students. This target is conducted with different multivariate classification techniques: hierarchical cluster analysis, non-hierarchical and two-stage analysis. Moreover, those items that best discriminate among the teaching typologies obtained are identified in the questionnaire. (3) Identification of the teaching typologies according to different descriptive characteristics referent to the subject and lecturer, with the use of decision trees. Once identified these typologies, a new discriminant analysis is conducted aimed at identifying those items that best characterise each typology. Finally, a study is carried out with the classification method SIMCA (Soft Independent Modelling of Class Analogy) in order to determine the discriminant loading of every item among the identified teaching typologies, allowing the identification of those that best distinguish the different classes obtained. With the combined use of the proposed techniques, it is expected to optimise the use of CEDA as a measuring tool and an indicator of the teaching quality at the university, that would allow the introduction of actions for the continuous improvement in the teaching processes of the UPV.

Characterisation of the macrophage transcriptome in glomerulonephritis-susceptible and -resistant rat strains

PubMed Central

Maratou, Klio; Behmoaras, Jacques; Fewings, Chris; Srivastava, Prashant; D’Souza, Zelpha; Smith, Jennifer; Game, Laurence; Cook, Terence; Aitman, Tim

2010-01-01

Crescentic glomerulonephritis (CRGN) is a major cause of rapidly progressive renal failure for which the underlying genetic basis is unknown. WKY rats show marked susceptibility to CRGN, while Lewis rats are resistant. Glomerular injury and crescent formation are macrophage-dependent and mainly explained by seven quantitative trait loci (Crgn1-7). Here, we used microarray analysis in basal and lipopolysaccharide (LPS)-stimulated macrophages to identify genes that reside on pathways predisposing WKY rats to CRGN. We detected 97 novel positional candidates for the uncharacterised Crgn3-7. We identified 10 additional secondary effector genes with profound differences in expression between the two strains (>5-fold change, <1% False Discovery Rate) for basal and LPS-stimulated macrophages. Moreover, we identified 8 genes with differentially expressed alternatively spliced isoforms, by using an in depth analysis at probe-level that allowed us to discard false positives due to polymorphisms between the two rat strains. Pathway analysis identified several common linked pathways, enriched for differentially expressed genes, which affect macrophage activation. In summary, our results identify distinct macrophage transcriptome profiles between two rat strains that differ in susceptibility to glomerulonephritis, provide novel positional candidates for Crgn3-7, and define groups of genes that play a significant role in differential regulation of macrophage activity. PMID:21179115

Identifying different transcribed proteins in the newly described Theraphosidae Pamphobeteus verdolaga.

PubMed

Estrada-Gómez, Sebastian; Vargas-Muñoz, Leidy Johana; Saldarriaga-Córdoba, Mónica; Cifuentes, Yeimy; Perafan, Carlos

2017-04-01

Theraphosidae spider venoms are well known for possess a complex mixture of protein and non-protein compounds in their venom. The objective of this study was to report and identify different proteins translated from the venom gland DNA information of the recently described Theraphosidae spider Pamphobeteus verdolaga. Using a venom gland transcriptomic analysis, we reported a set of the first complete sequences of seven different proteins of the recenlty described Theraphosidae spider P. verdolaga. Protein analysis indicates the presence of different proteins on the venom composition of this new spider, some of them uncommon in the Theraphosidae family. MS/MS analysis of P. verdolaga showed different fragments matching sphingomyelinases (sicaritoxin), barytoxins, hexatoxins, latroinsectotoxins, and linear (zadotoxins) peptides. Only four of the MS/MS fragments showed 100% sequence similarity with one of the transcribed proteins. Transcriptomic analysis showed the presence of different groups of proteins like phospholipases, hyaluronidases, inhibitory cysteine knots (ICK) peptides among others. The three database of protein domains used in this study (Pfam, SMART and CDD) showed congruency in the search of unique conserved protein domain for only four of the translated proteins. Those proteins matched with EF-hand proteins, cysteine rich secretory proteins, jingzhaotoxins, theraphotoxins and hexatoxins, from different Mygalomorphae spiders belonging to the families Theraphosidae, Barychelidae and Hexathelidae. None of the analyzed sequences showed a complete 100% similarity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Model-free fMRI group analysis using FENICA.

PubMed

Schöpf, V; Windischberger, C; Robinson, S; Kasess, C H; Fischmeister, F PhS; Lanzenberger, R; Albrecht, J; Kleemann, A M; Kopietz, R; Wiesmann, M; Moser, E

2011-03-01

Exploratory analysis of functional MRI data allows activation to be detected even if the time course differs from that which is expected. Independent Component Analysis (ICA) has emerged as a powerful approach, but current extensions to the analysis of group studies suffer from a number of drawbacks: they can be computationally demanding, results are dominated by technical and motion artefacts, and some methods require that time courses be the same for all subjects or that templates be defined to identify common components. We have developed a group ICA (gICA) method which is based on single-subject ICA decompositions and the assumption that the spatial distribution of signal changes in components which reflect activation is similar between subjects. This approach, which we have called Fully Exploratory Network Independent Component Analysis (FENICA), identifies group activation in two stages. ICA is performed on the single-subject level, then consistent components are identified via spatial correlation. Group activation maps are generated in a second-level GLM analysis. FENICA is applied to data from three studies employing a wide range of stimulus and presentation designs. These are an event-related motor task, a block-design cognition task and an event-related chemosensory experiment. In all cases, the group maps identified by FENICA as being the most consistent over subjects correspond to task activation. There is good agreement between FENICA results and regions identified in prior GLM-based studies. In the chemosensory task, additional regions are identified by FENICA and temporal concatenation ICA that we show is related to the stimulus, but exhibit a delayed response. FENICA is a fully exploratory method that allows activation to be identified without assumptions about temporal evolution, and isolates activation from other sources of signal fluctuation in fMRI. It has the advantage over other gICA methods that it is computationally undemanding, spotlights components relating to activation rather than artefacts, allows the use of familiar statistical thresholding through deployment of a higher level GLM analysis and can be applied to studies where the paradigm is different for all subjects. Copyright © 2010 Elsevier Inc. All rights reserved.

Integrating text mining, data mining, and network analysis for identifying genetic breast cancer trends.

PubMed

Jurca, Gabriela; Addam, Omar; Aksac, Alper; Gao, Shang; Özyer, Tansel; Demetrick, Douglas; Alhajj, Reda

2016-04-26

Breast cancer is a serious disease which affects many women and may lead to death. It has received considerable attention from the research community. Thus, biomedical researchers aim to find genetic biomarkers indicative of the disease. Novel biomarkers can be elucidated from the existing literature. However, the vast amount of scientific publications on breast cancer make this a daunting task. This paper presents a framework which investigates existing literature data for informative discoveries. It integrates text mining and social network analysis in order to identify new potential biomarkers for breast cancer. We utilized PubMed for the testing. We investigated gene-gene interactions, as well as novel interactions such as gene-year, gene-country, and abstract-country to find out how the discoveries varied over time and how overlapping/diverse are the discoveries and the interest of various research groups in different countries. Interesting trends have been identified and discussed, e.g., different genes are highlighted in relationship to different countries though the various genes were found to share functionality. Some text analysis based results have been validated against results from other tools that predict gene-gene relations and gene functions.

Copy Number Variants and Exome Sequencing Analysis in Six Pairs of Chinese Monozygotic Twins Discordant for Congenital Heart Disease.

PubMed

Xu, Yuejuan; Li, Tingting; Pu, Tian; Cao, Ruixue; Long, Fei; Chen, Sun; Sun, Kun; Xu, Rang

2017-12-01

Congenital heart disease (CHD) is one of the most common birth defects. More than 200 susceptibility loci have been identified for CHDs, yet a large part of the genetic risk factors remain unexplained. Monozygotic (MZ) twins are thought to be completely genetically identical; however, discordant phenotypes have been found in MZ twins. Recent studies have demonstrated genetic differences between MZ twins. We aimed to test whether copy number variants (CNVs) and/or genetic mutation differences play a role in the etiology of CHDs by using single nucleotide polymorphism (SNP) genotyping arrays and whole exome sequencing of twin pairs discordant for CHDs. Our goal was to identify mutations present only in the affected twins, which could identify novel candidates for CHD susceptibility loci. We present a comprehensive analysis for the CNVs and genetic mutation results of the selected individuals but detected no consistent differences within the twin pairs. Our study confirms that chromosomal structure or genetic mutation differences do not seem to play a role in the MZ twins discordant for CHD.

Identification of differences between finite element analysis and experimental vibration data

NASA Technical Reports Server (NTRS)

Lawrence, C.

1986-01-01

An important problem that has emerged from combined analytical/experimental investigations is the task of identifying and quantifying the differences between results predicted by F.E. analysis and results obtained from experiment. The objective of this study is to extend and evaluate the procedure developed by Sidhu for correlation of linear F.E. and modal test data to include structures with viscous damping. The desirability of developing this procedure is that the differences are identified in terms of physical mass, damping, and stiffness parameters instead of in terms of frequencies and modes shapes. Since the differences are computed in terms of physical parameters, locations of modeling problems can be directly identified in the F.E. model. From simulated data it was determined that the accuracy of the computed differences increases as the number of experimentally measured modes included in the calculations is increased. When the number of experimental modes is at least equal to the number of translational degrees of freedom in the F.E. model both the location and magnitude of the differences can be computed very accurately. When the number of modes is less than this amount the location of the differences may be determined even though their magnitudes will be under estimated.

Criterion Predictability: Identifying Differences Between [r-squares

ERIC Educational Resources Information Center

Malgady, Robert G.

1976-01-01

An analysis of variance procedure for testing differences in r-squared, the coefficient of determination, across independent samples is proposed and briefly discussed. The principal advantage of the procedure is to minimize Type I error for follow-up tests of pairwise differences. (Author/JKS)

Quantitative Analysis of Repertoire Scale Immunoglobulin properties in Vaccine Induced B cell Responses

DTIC Science & Technology

Immunosequencing now readily generates 103105 sequences per sample ; however, statistical analysis of these repertoires is challenging because of the high genetic...diversity of BCRs and the elaborate clonal relationships among them. To date, most immunosequencing analyses have focused on reporting qualitative ...repertoire differences, (2) identifying how two repertoires differ, and (3) determining appropriate confidence intervals for assessing the size of the differences and their potential biological relevance.

Morphometric evaluation of the knee in Chinese population reveals sexual dimorphism and age-related differences.

PubMed

Li, Ke; Cavaignac, Etienne; Xu, Wei; Cheng, Qiang; Telmon, Nobert; Huang, Wei

2018-02-20

Morphologic data of the knee is very important in the design of total knee prostheses. Generally, the designs of the total knee prostheses are based on the knee anatomy of Caucasian population. Moreover, in forensic medicine, a person's age and sex might be estimated by the shape of their knees. The aim of this study is to utilize three-dimensional morphometric analysis of the knee in Chinese population to reveal sexual dimorphism and age-related differences. Sexually dimorphic differences and age-related differences of the distal femur were studied by using geometric morphometric analysis of ten osteometric landmarks on three-dimensional reconstructions of 259 knees in Chinese population. General Procrustes analysis, PCA, and other discriminant analysis such as Mahalanobis and Goodall's F test were conducted for the knee to identify sexually dimorphism and age-related differences of the knee. The shape of distal femur between the male and female is significantly different. A difference between males and females in distal femur shape was identified by PCA; PC1 and PC2 accounted for 61.63% of the variance measured. The correct sex was assigned in 84.9% of cases by CVA, and the cross-validation revealed a 81.1% rate of correct sex estimation. The osteometric analysis also showed significant differences between the three age-related subgroups (< 40, 40-60, > 60 years, p < 0.005). This study showed both sex-related difference and age-related difference in the distal femur in Chinese population by 3D geometric morphometric analysis. Our bone measurements and geometric morphometric analysis suggest that population characteristics should be taken into account and may provide references for design of total knee prostheses in a Chinese population. Moreover, this reliable, accurate method could be used to perform diachronic and interethnic comparisons.

Methodological flaws introduce strong bias into molecular analysis of microbial populations.

PubMed

Krakat, N; Anjum, R; Demirel, B; Schröder, P

2017-02-01

In this study, we report how different cell disruption methods, PCR primers and in silico analyses can seriously bias results from microbial population studies, with consequences for the credibility and reproducibility of the findings. Our results emphasize the pitfalls of commonly used experimental methods that can seriously weaken the interpretation of results. Four different cell lysis methods, three commonly used primer pairs and various computer-based analyses were applied to investigate the microbial diversity of a fermentation sample composed of chicken dung. The fault-prone, but still frequently used, amplified rRNA gene restriction analysis was chosen to identify common weaknesses. In contrast to other studies, we focused on the complete analytical process, from cell disruption to in silico analysis, and identified potential error rates. This identified a wide disagreement of results between applied experimental approaches leading to very different community structures depending on the chosen approach. The interpretation of microbial diversity data remains a challenge. In order to accurately investigate the taxonomic diversity and structure of prokaryotic communities, we suggest a multi-level approach combining DNA-based and DNA-independent techniques. The identified weaknesses of commonly used methods to study microbial diversity can be overcome by a multi-level approach, which produces more reliable data about the fate and behaviour of microbial communities of engineered habitats such as biogas plants, so that the best performance can be ensured. © 2016 The Society for Applied Microbiology.

Exploratory Cluster Analysis to Identify Patterns of Chronic Kidney Disease in the 500 Cities Project.

PubMed

Liu, Shelley H; Li, Yan; Liu, Bian

2018-05-17

Chronic kidney disease is a leading cause of death in the United States. We used cluster analysis to explore patterns of chronic kidney disease in 500 of the largest US cities. After adjusting for socio-demographic characteristics, we found that unhealthy behaviors, prevention measures, and health outcomes related to chronic kidney disease differ between cities in Utah and those in the rest of the United States. Cluster analysis can be useful for identifying geographic regions that may have important policy implications for preventing chronic kidney disease.

Detecting subtle hydrochemical anomalies with multivariate statistics: an example from homogeneous groundwaters in the Great Artesian Basin, Australia

NASA Astrophysics Data System (ADS)

O'Shea, Bethany; Jankowski, Jerzy

2006-12-01

The major ion composition of Great Artesian Basin groundwater in the lower Namoi River valley is relatively homogeneous in chemical composition. Traditional graphical techniques have been combined with multivariate statistical methods to determine whether subtle differences in the chemical composition of these waters can be delineated. Hierarchical cluster analysis and principal components analysis were successful in delineating minor variations within the groundwaters of the study area that were not visually identified in the graphical techniques applied. Hydrochemical interpretation allowed geochemical processes to be identified in each statistically defined water type and illustrated how these groundwaters differ from one another. Three main geochemical processes were identified in the groundwaters: ion exchange, precipitation, and mixing between waters from different sources. Both statistical methods delineated an anomalous sample suspected of being influenced by magmatic CO2 input. The use of statistical methods to complement traditional graphical techniques for waters appearing homogeneous is emphasized for all investigations of this type. Copyright

ACCEPTANCE OF FUNCTIONAL FOOD AMONG CHILEAN CONSUMERS: APPLE LEATHER.

PubMed

van Vliet, Maya; Adasme-Berrios, Cristian; Schnettler, Berta

2015-10-01

the aim of this study is to measure acceptance of a specific functional food: apple (fruit) leather, based on organoleptic characteristics and to identify consumer types and preferences for natural additives which increase the product's functionality and meet current nutritional needs. a sample of 800 consumers provided an evaluation of apple leather in terms of acceptance (liking). A sensorial panel was carried out using a 9-point hedonic scale. Cluster analysis was used to identify different acceptance-based consumer types. In addition, a conjoint analysis was carried out to determine preference for different additives. the cluster analysis resulted in four groups with significant differences in the average likings obtained from the sensory panel. Results indicate that the sweetness of the tested apple leather was evaluated best among all groups and, on average, color was rated as the worst attribute. However, overall likings differ significantly between groups. Results from the conjoint analysis indicate that, in general, consumers prefer natural additives included in the product which enhance functionality. although there is a "global acceptance" of the product, there are significant differences between groups. The results of the conjoint analysis indicate that, in general, consumers prefer the aggregation of natural additives which increase the product's functionality. Apple leather with natural additives, such as anticariogenics and antioxidants, can be considered a functional substitute of unhealthy snacks and/or sweets. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

Knowledge, attitudes towards and acceptability of genetic modification in Germany.

PubMed

Christoph, Inken B; Bruhn, Maike; Roosen, Jutta

2008-07-01

Genetic modification remains a controversial issue. The aim of this study is to analyse the attitudes towards genetic modification, the knowledge about it and its acceptability in different application areas among German consumers. Results are based on a survey from spring 2005. An exploratory factor analysis is conducted to identify the attitudes towards genetic modification. The identified factors are used in a cluster analysis that identified a cluster of supporters, of opponents and a group of indifferent consumers. Respondents' knowledge of genetics and biotechnology differs among the found clusters without revealing a clear relationship between knowledge and support of genetic modification. The acceptability of genetic modification varies by application area and cluster, and genetically modified non-food products are more widely accepted than food products. The perception of personal health risks has high explanatory power for attitudes and acceptability.

Identifying a system of predominant negative symptoms: Network analysis of three randomized clinical trials.

PubMed

Levine, Stephen Z; Leucht, Stefan

2016-12-01

Reasons for the recent mixed success of research into negative symptoms may be informed by conceptualizing negative symptoms as a system that is identifiable from network analysis. We aimed to identify: (I) negative symptom systems; (I) central negative symptoms within each system; and (III) differences between the systems, based on network analysis of negative symptoms for baseline, endpoint and change. Patients with chronic schizophrenia and predominant negative symptoms participated in three clinical trials that compared placebo and amisulpride to 60days (n=487). Networks analyses were computed from the Scale for the Assessment of Negative Symptoms (SANS) scores for baseline and endpoint for severity, and estimated change based on mixed models. Central symptoms to each network were identified. The networks were contrasted for connectivity with permutation tests. Network analysis showed that the baseline and endpoint symptom severity systems formed symptom groups of Affect, Poor responsiveness, Lack of interest, and Apathy-inattentiveness. The baseline and endpoint networks did not significantly differ in terms of connectivity, but both significantly (P<0.05) differed to the change network. In the change network the apathy-inattentiveness symptom group split into three other groups. The most central symptoms were Decreased Spontaneous Movements at baseline and endpoint, and Poverty of Speech for estimated change. Results provide preliminary evidence for: (I) a replicable negative symptom severity system; and (II) symptoms with high centrality (e.g., Decreased Spontaneous Movement), that may be future treatment targets following replication to ensure the curent results generalize to other samples. Copyright © 2016 Elsevier B.V. All rights reserved.

Metabolomic analysis of insulin resistance across different mouse strains and diets.

PubMed

Stöckli, Jacqueline; Fisher-Wellman, Kelsey H; Chaudhuri, Rima; Zeng, Xiao-Yi; Fazakerley, Daniel J; Meoli, Christopher C; Thomas, Kristen C; Hoffman, Nolan J; Mangiafico, Salvatore P; Xirouchaki, Chrysovalantou E; Yang, Chieh-Hsin; Ilkayeva, Olga; Wong, Kari; Cooney, Gregory J; Andrikopoulos, Sofianos; Muoio, Deborah M; James, David E

2017-11-24

Insulin resistance is a major risk factor for many diseases. However, its underlying mechanism remains unclear in part because it is triggered by a complex relationship between multiple factors, including genes and the environment. Here, we used metabolomics combined with computational methods to identify factors that classified insulin resistance across individual mice derived from three different mouse strains fed two different diets. Three inbred ILSXISS strains were fed high-fat or chow diets and subjected to metabolic phenotyping and metabolomics analysis of skeletal muscle. There was significant metabolic heterogeneity between strains, diets, and individual animals. Distinct metabolites were changed with insulin resistance, diet, and between strains. Computational analysis revealed 113 metabolites that were correlated with metabolic phenotypes. Using these 113 metabolites, combined with machine learning to segregate mice based on insulin sensitivity, we identified C22:1-CoA, C2-carnitine, and C16-ceramide as the best classifiers. Strikingly, when these three metabolites were combined into one signature, they classified mice based on insulin sensitivity more accurately than each metabolite on its own or other published metabolic signatures. Furthermore, C22:1-CoA was 2.3-fold higher in insulin-resistant mice and correlated significantly with insulin resistance. We have identified a metabolomic signature composed of three functionally unrelated metabolites that accurately predicts whole-body insulin sensitivity across three mouse strains. These data indicate the power of simultaneous analysis of individual, genetic, and environmental variance in mice for identifying novel factors that accurately predict metabolic phenotypes like whole-body insulin sensitivity. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Genetic diversity of influenza A(H1N1)2009 virus circulating during the season 2010-2011 in Spain.

PubMed

Ledesma, Juan; Pozo, Francisco; Reina, Gabriel; Blasco, Miriam; Rodríguez, Guadalupe; Montes, Milagrosa; López-Miragaya, Isabel; Salvador, Carmen; Reina, Jordi; Ortíz de Lejarazu, Raúl; Egido, Pilar; López Barba, José; Delgado, Concepción; Cuevas, María Teresa; Casas, Inmaculada

2012-01-01

Genetic diversity of influenza A(H1N1)2009 viruses has been reported since the pandemic virus emerged in April 2009. Different genetic clades have been identified and defined based on amino acid substitutions found in the haemagglutinin (HA) protein sequences. In Spain, circulating influenza viruses are monitored each season by the regional laboratories enrolled in the Spanish Influenza Surveillance System (SISS). The analysis of the HA gene sequence helps to detect the genetic diversity and viral evolution. To perform an analysis of the genetic diversity of influenza A(H1N1)2009 viruses circulating in Spain during the season 2010-2011 based on analysis of the HA sequence gene. Phylogenetic analysis based on the HA1 subunit of the haemagglutinin gene was carried out on 220 influenza A(H1N1)2009 viruses circulating during the season 2010-2011. Six different genetic groups were identified among circulating A(H1N1)2009 viruses, five of them were previously reported during season 2010-2011. A new group, characterized by E172K and K308E changes and a proline at position 83, was observed in 12.27% of the Spanish viruses. Co-circulation of six different genetic groups of influenza A(H1N1)2009 viruses was identified in Spain during the season 2010-2011. Nevertheless, at this stage, none of the groups identified to date have resulted in significant antigenic changes according to data collected by World Health Organization Collaborating Centres for influenza surveillance. Copyright © 2011 Elsevier B.V. All rights reserved.

Identifying models of HIV care and treatment service delivery in Tanzania, Uganda, and Zambia using cluster analysis and Delphi survey.

PubMed

Tsui, Sharon; Denison, Julie A; Kennedy, Caitlin E; Chang, Larry W; Koole, Olivier; Torpey, Kwasi; Van Praag, Eric; Farley, Jason; Ford, Nathan; Stuart, Leine; Wabwire-Mangen, Fred

2017-12-06

Organization of HIV care and treatment services, including clinic staffing and services, may shape clinical and financial outcomes, yet there has been little attempt to describe different models of HIV care in sub-Saharan Africa (SSA). Information about the relative benefits and drawbacks of different models could inform the scale-up of antiretroviral therapy (ART) and associated services in resource-limited settings (RLS), especially in light of expanded client populations with country adoption of WHO's test and treat recommendation. We characterized task-shifting/task-sharing practices in 19 diverse ART clinics in Tanzania, Uganda, and Zambia and used cluster analysis to identify unique models of service provision. We ran descriptive statistics to explore how the clusters varied by environmental factors and programmatic characteristics. Finally, we employed the Delphi Method to make systematic use of expert opinions to ensure that the cluster variables were meaningful in the context of actual task-shifting of ART services in SSA. The cluster analysis identified three task-shifting/task-sharing models. The main differences across models were the availability of medical doctors, the scope of clinical responsibility assigned to nurses, and the use of lay health care workers. Patterns of healthcare staffing in HIV service delivery were associated with different environmental factors (e.g., health facility levels, urban vs. rural settings) and programme characteristics (e.g., community ART distribution or integrated tuberculosis treatment on-site). Understanding the relative advantages and disadvantages of different models of care can help national programmes adapt to increased client load, select optimal adherence strategies within decentralized models of care, and identify differentiated models of care for clients to meet the growing needs of long-term ART patients who require more complicated treatment management.

Endophytic bacteria in plant tissue culture: differences between easy- and difficult-to-propagate Prunus avium genotypes.

PubMed

Quambusch, Mona; Pirttilä, Anna Maria; Tejesvi, Mysore V; Winkelmann, Traud; Bartsch, Melanie

2014-05-01

The endophytic bacterial communities of six Prunus avium L. genotypes differing in their growth patterns during in vitro propagation were identified by culture-dependent and culture-independent methods. Five morphologically distinct isolates from tissue culture material were identified by 16S rDNA sequence analysis. To detect and analyze the uncultivable fraction of endophytic bacteria, a clone library was established from the amplified 16S rDNA of total plant extract. Bacterial diversity within the clone libraries was analyzed by amplified ribosomal rDNA restriction analysis and by sequencing a clone for each identified operational taxonomic unit. The most abundant bacterial group was Mycobacterium sp., which was identified in the clone libraries of all analyzed Prunus genotypes. Other dominant bacterial genera identified in the easy-to-propagate genotypes were Rhodopseudomonas sp. and Microbacterium sp. Thus, the community structures in the easy- and difficult-to-propagate cherry genotypes differed significantly. The bacterial genera, which were previously reported to have plant growth-promoting effects, were detected only in genotypes with high propagation success, indicating a possible positive impact of these bacteria on in vitro propagation of P. avium, which was proven in an inoculation experiment. © The Author 2014. Published by Oxford University Press. All rights reserved.

Typology of emergent eating patterns in early childhood.

PubMed

Hittner, James B; Faith, Myles S

2011-12-01

The stability of eating patterns from infancy through childhood is largely unknown. This study identified subgroups of children based on emergent eating patterns from ages 1 to 3 years and examined differences between groups in demographic, anthropometric and temperamental variables. We conducted secondary analyses of 262 boys and 225 girls from the Colorado Adoption Project. Three eating styles (Reactivity to Food, Predictable Appetite, Distractibility at Mealtime) and five temperaments were assessed at ages 1 and 3 years. Weight and height (length) were assessed on children and mothers. Correlations examined the stability of eating patterns, cluster analysis identified subgroups of emergent eating styles, and analysis of variance identified variables differentiating the derived subgroups. Eating styles were moderately stable over time, although all increased on average. Four subgroups were identified: Diet Expanding and Preference Establishing Eaters (37%), Emerging Reactive Tendency Eaters (23%), Emerging Food-Indifferent and Non-Fussy Eaters (31%), and Emerging High-Reactive and Fussy Eaters (9%). The subgroups differed in year 1 Wt/L and Reaction to Food, and year 1-to-3 changes in Emotionality and Reaction to Food. Four emergent eating patterns were identified. How these subgroups of children differ in later weight and health trajectories warrants research. Copyright © 2011 Elsevier Ltd. All rights reserved.

The contribution of psychological factors to recovery after mild traumatic brain injury: is cluster analysis a useful approach?

PubMed

Snell, Deborah L; Surgenor, Lois J; Hay-Smith, E Jean C; Williman, Jonathan; Siegert, Richard J

2015-01-01

Outcomes after mild traumatic brain injury (MTBI) vary, with slow or incomplete recovery for a significant minority. This study examines whether groups of cases with shared psychological factors but with different injury outcomes could be identified using cluster analysis. This is a prospective observational study following 147 adults presenting to a hospital-based emergency department or concussion services in Christchurch, New Zealand. This study examined associations between baseline demographic, clinical, psychological variables (distress, injury beliefs and symptom burden) and outcome 6 months later. A two-step approach to cluster analysis was applied (Ward's method to identify clusters, K-means to refine results). Three meaningful clusters emerged (high-adapters, medium-adapters, low-adapters). Baseline cluster-group membership was significantly associated with outcomes over time. High-adapters appeared recovered by 6-weeks and medium-adapters revealed improvements by 6-months. The low-adapters continued to endorse many symptoms, negative recovery expectations and distress, being significantly at risk for poor outcome more than 6-months after injury (OR (good outcome) = 0.12; CI = 0.03-0.53; p < 0.01). Cluster analysis supported the notion that groups could be identified early post-injury based on psychological factors, with group membership associated with differing outcomes over time. Implications for clinical care providers regarding therapy targets and cases that may benefit from different intensities of intervention are discussed.

Metabolomic analysis based on 1H-nuclear magnetic resonance spectroscopy metabolic profiles in tuberculous, malignant and transudative pleural effusion

PubMed Central

Wang, Cheng; Peng, Jingjin; Kuang, Yanling; Zhang, Jiaqiang; Dai, Luming

2017-01-01

Pleural effusion is a common clinical manifestation with various causes. Current diagnostic and therapeutic methods have exhibited numerous limitations. By involving the analysis of dynamic changes in low molecular weight catabolites, metabolomics has been widely applied in various types of disease and have provided platforms to distinguish many novel biomarkers. However, to the best of our knowledge, there are few studies regarding the metabolic profiling for pleural effusion. In the current study, 58 pleural effusion samples were collected, among which 20 were malignant pleural effusions, 20 were tuberculous pleural effusions and 18 were transudative pleural effusions. The small molecule metabolite spectrums were obtained by adopting 1H nuclear magnetic resonance technology, and pattern-recognition multi-variable statistical analysis was used to screen out different metabolites. One-way analysis of variance, and Student-Newman-Keuls and the Kruskal-Wallis test were adopted for statistical analysis. Over 400 metabolites were identified in the untargeted metabolomic analysis and 26 metabolites were identified as significantly different among tuberculous, malignant and transudative pleural effusions. These metabolites were predominantly involved in the metabolic pathways of amino acids metabolism, glycometabolism and lipid metabolism. Statistical analysis revealed that eight metabolites contributed to the distinction between the three groups: Tuberculous, malignant and transudative pleural effusion. In the current study, the feasibility of identifying small molecule biochemical profiles in different types of pleural effusion were investigated reveal novel biological insights into the underlying mechanisms. The results provide specific insights into the biology of tubercular, malignant and transudative pleural effusion and may offer novel strategies for the diagnosis and therapy of associated diseases, including tuberculosis, advanced lung cancer and congestive heart failure. PMID:28627685

Proteomic and computational analysis of bronchoalveolar proteins during the course of the acute respiratory distress syndrome.

PubMed

Chang, Dong W; Hayashi, Shinichi; Gharib, Sina A; Vaisar, Tomas; King, S Trevor; Tsuchiya, Mitsuhiro; Ruzinski, John T; Park, David R; Matute-Bello, Gustavo; Wurfel, Mark M; Bumgarner, Roger; Heinecke, Jay W; Martin, Thomas R

2008-10-01

Acute lung injury causes complex changes in protein expression in the lungs. Whereas most prior studies focused on single proteins, newer methods allowing the simultaneous study of many proteins could lead to a better understanding of pathogenesis and new targets for treatment. The purpose of this study was to examine the changes in protein expression in the bronchoalveolar lavage fluid (BALF) of patients during the course of the acute respiratory distress syndrome (ARDS). Using two-dimensional difference gel electrophoresis (DIGE), the expression of proteins in the BALF from patients on Days 1 (n = 7), 3 (n = 8), and 7 (n = 5) of ARDS were compared with findings in normal volunteers (n = 9). The patterns of protein expression were analyzed using principal component analysis (PCA). Biological processes that were enriched in the BALF proteins of patients with ARDS were identified using Gene Ontology (GO) analysis. Protein networks that model the protein interactions in the BALF were generated using Ingenuity Pathway Analysis. An average of 991 protein spots were detected using DIGE. Of these, 80 protein spots, representing 37 unique proteins in all of the fluids, were identified using mass spectrometry. PCA confirmed important differences between the proteins in the ARDS and normal samples. GO analysis showed that these differences are due to the enrichment of proteins involved in inflammation, infection, and injury. The protein network analysis showed that the protein interactions in ARDS are complex and redundant, and revealed unexpected central components in the protein networks. Proteomics and protein network analysis reveals the complex nature of lung protein interactions in ARDS. The results provide new insights about protein networks in injured lungs, and identify novel mediators that are likely to be involved in the pathogenesis and progression of acute lung injury.

Systematic text condensation: a strategy for qualitative analysis.

PubMed

Malterud, Kirsti

2012-12-01

To present background, principles, and procedures for a strategy for qualitative analysis called systematic text condensation and discuss this approach compared with related strategies. Giorgi's psychological phenomenological analysis is the point of departure and inspiration for systematic text condensation. The basic elements of Giorgi's method and the elaboration of these in systematic text condensation are presented, followed by a detailed description of procedures for analysis according to systematic text condensation. Finally, similarities and differences compared with other frequently applied methods for qualitative analysis are identified, as the foundation of a discussion of strengths and limitations of systematic text condensation. Systematic text condensation is a descriptive and explorative method for thematic cross-case analysis of different types of qualitative data, such as interview studies, observational studies, and analysis of written texts. The method represents a pragmatic approach, although inspired by phenomenological ideas, and various theoretical frameworks can be applied. The procedure consists of the following steps: 1) total impression - from chaos to themes; 2) identifying and sorting meaning units - from themes to codes; 3) condensation - from code to meaning; 4) synthesizing - from condensation to descriptions and concepts. Similarities and differences comparing systematic text condensation with other frequently applied qualitative methods regarding thematic analysis, theoretical methodological framework, analysis procedures, and taxonomy are discussed. Systematic text condensation is a strategy for analysis developed from traditions shared by most of the methods for analysis of qualitative data. The method offers the novice researcher a process of intersubjectivity, reflexivity, and feasibility, while maintaining a responsible level of methodological rigour.

Dataset of the Botrytis cinerea phosphoproteome induced by different plant-based elicitors.

PubMed

Liñeiro, Eva; Chiva, Cristina; Cantoral, Jesús M; Sabido, Eduard; Fernández-Acero, Francisco Javier

2016-06-01

Phosphorylation is one of the main post-translational modification (PTM) involved in signaling network in the ascomycete Botrytis cinerea , one of the most relevant phytopathogenic fungus. The data presented in this article provided a differential mass spectrometry-based analysis of the phosphoproteome of B. cinerea under two different phenotypical conditions induced by the use of two different elicitors: glucose and deproteinized Tomate Cell Walls (TCW). A total 1138 and 733 phosphoproteins were identified for glucose and TCW culture conditions respectively. Raw data are deposited at the ProteomeXchange Consortium via the PRIDE partner repository with the data set identifier (PRIDE: http://www.ebi.ac.uk/pride/archive/projects/PXD003099). Further interpretation and discussion of these data are provided in our research article entitled "Phosphoproteome analysis of B.cinerea in response to different plant-based elicitors" (Liñeiro et al., 2016) [1].

Analysis of phenolic compounds in different parts of pomegranate (Punica granatum) fruit by HPLC-PDA-ESI/MS and evaluation of their antioxidant activity: application to different Italian varieties.

PubMed

Russo, Marina; Fanali, Chiara; Tripodo, Giusy; Dugo, Paola; Muleo, Rosario; Dugo, Laura; De Gara, Laura; Mondello, Luigi

2018-06-01

The analysis of pomegranate phenolic compounds belonging to different classes in different fruit parts was performed by high-performance liquid chromatography coupled with photodiode array and mass spectrometry detection. Two different separation methods were optimized for the analysis of anthocyanins and hydrolyzable tannins along with phenolic acids and flavonoids. Two C 18 columns, core-shell and fully porous particle stationary phases, were used. The parameters for separation of phenolic compounds were optimized considering chromatographic resolution and analysis time. Thirty-five phenolic compounds were found, and 28 of them were tentatively identified as belonging to four different phenolic compound classes; namely, anthocyanins, phenolic acids, hydrolyzable tannins, and flavonoids. Quantitative analysis was performed with a mixture of nine phenolic compounds belonging to phenolic compound classes representative of pomegranate. The method was then fully validated in terms of retention time precision, expressed as the relative standard deviation, limit of detection, limit of quantification, and linearity range. Phenolic compounds were analyzed directly in pomegranate juice, and after solvent extraction with a mixture of water and methanol with a small percentage of acid in peel and pulp samples. The accuracy of the extraction method was also assessed, and satisfactory values were obtained. Finally, the method was used to study identified analytes in pomegranate juice, peel, and pulp of six different Italian varieties and one international variety. Differences in phenolic compound profiles among the different pomegranate parts were observed. Pomegranate peel samples showed a high concentration of phenolic compounds, ellagitannins being the most abundant ones, with respect to pulp and juice samples for each variety. With the same samples, total phenols and antioxidant activity were evaluated through colorimetric assays, and the results were correlated among them.

Plasma metabonomics study of the patients with acute anterior uveitis based on ultra-performance liquid chromatography-mass spectrometry.

PubMed

Guo, Junguo; Yan, Tingqin; Bi, Hongsheng; Xie, Xiaofeng; Wang, Xingrong; Guo, Dadong; Jiang, Haiqiang

2014-06-01

The identification of the biomarkers of patients with acute anterior uveitis (AAU) may allow for a less invasive and more accurate diagnosis, as well as serving as a predictor in AAU progression and treatment response. The aim of this study was to identify the potential biomarkers and the metabolic pathways from plasma in patients with AAU. Both plasma metabolic biomarkers and metabolic pathways in the AAU patients versus healthy volunteers were investigated using ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) and a metabonomics approach. The principal component analysis (PCA) was used to separate AAU patients from healthy volunteers as well as to identify the different biomarkers between the two groups. Metabolic compounds were matched to the KEGG, METLIN, and HMDB databases, and metabolic pathways associated with AAU were identified. The PCA for UPLC-MS data shows that the metabolites in AAU patients were significantly different from those of healthy volunteers. Of the 4,396 total features detected by UPLC-MS, 102 features were significantly different between AAU patients and healthy volunteers according to the variable importance plot (VIP) values (greater than two) of partial least squares discriminate analysis (PLS-DA). Thirty-three metabolic compounds were identified and were considered as potential biomarkers. Meanwhile, ten metabolic pathways were found that were related to the AAU according to the identified biomarkers. These data suggest that metabolomics study can identify potential metabolites that differ between AAU patients and healthy volunteers. Based on the PCA, PLS-DA, several potential metabolic biomarkers and pathways in AAU patients were found and identified. In addition, the UPLC-MS technique combined with metabonomics could be a suitable systematic biology tool in research in clinical problems in ophthalmology, and can provide further insight into the pathophysiology of AAU.

Major differences in rates of occupational accidents between different nationalities of seafarers.

PubMed

Hansen, Henrik L; Laursen, Lise Hedgaard; Frydberg, Morten; Kristensen, Soeren

2008-01-01

Earlier studies and statistics have shown that merchant seafarers from the South East Asia had considerable lower accident rates when compared with seafarers from Western Europe. The purposes of the study were to investigate whether the earlier observations were sustained if further sources on occurrence of accidents were used and to identify specific causes of excess accident rates among certain nationalities. Occupational accidents aboard Danish merchant ships during one year were identified from four different sources. These included accidents reported to the maritime authorities, accidents reported to a mutual insurance company, files on medical costs reimbursed by the government and finally, accidents in which there has been contact to the radio medical service. Time at risk aboard was obtained from a register on all employment periods aboard merchant ships. A total of 943 accidents causing personal injury to a seafarer directly caused by work aboard were identified. Among these accidents, 499 had taken place aboard cargo ships in international trade. Only these were used in the detailed analysis. The accident rate for all identified accidents aboard cargo ships were 84 accidents per 1,000 years aboard. The crude incidence rate ratio (IRR) for East European seafarers was 0.88 and for South East Asians 0.38 using West European seafarers as reference. In a Poisson regression analysis, the IRR for South East Asians was 0.29 (0.22-0.38). In an analysis including only more serious accidents, IRR for South East Asians rose to 0.36 (0.26-0.48). This study indicates that seafarers from South East Asia, mainly the Philippines, may have a genuine lower risk of occupational accidents in comparison with seafarers from Western and Eastern Europe. Differences in approach to safety and risk taking between South East Asian and European seafarers should be identified and positives attitudes included in accident preventing programmes. Main messages Seafarers from South East Asia, mainly the Philippines, seem to have a genuine lower risk of occupational accidents in comparison with seafarers from Western and Eastern Europe. Differences in approach to safety and risk taking between South East Asian and European seafarers should be identified and positives attitudes included in accident preventing programmes.

[A study of Boletus bicolor from different areas using Fourier transform infrared spectrometry].

PubMed

Zhou, Zai-Jin; Liu, Gang; Ren, Xian-Pei

2010-04-01

It is hard to differentiate the same species of wild growing mushrooms from different areas by macromorphological features. In this paper, Fourier transform infrared (FTIR) spectroscopy combined with principal component analysis was used to identify 58 samples of boletus bicolor from five different areas. Based on the fingerprint infrared spectrum of boletus bicolor samples, principal component analysis was conducted on 58 boletus bicolor spectra in the range of 1 350-750 cm(-1) using the statistical software SPSS 13.0. According to the result, the accumulated contributing ratio of the first three principal components accounts for 88.87%. They included almost all the information of samples. The two-dimensional projection plot using first and second principal component is a satisfactory clustering effect for the classification and discrimination of boletus bicolor. All boletus bicolor samples were divided into five groups with a classification accuracy of 98.3%. The study demonstrated that wild growing boletus bicolor at species level from different areas can be identified by FTIR spectra combined with principal components analysis.

Identification and characterization of near-fatal asthma phenotypes by cluster analysis.

PubMed

Serrano-Pariente, J; Rodrigo, G; Fiz, J A; Crespo, A; Plaza, V

2015-09-01

Near-fatal asthma (NFA) is a heterogeneous clinical entity and several profiles of patients have been described according to different clinical, pathophysiological and histological features. However, there are no previous studies that identify in a unbiased way--using statistical methods such as clusters analysis--different phenotypes of NFA. Therefore, the aim of the present study was to identify and to characterize phenotypes of near fatal asthma using a cluster analysis. Over a period of 2 years, 33 Spanish hospitals enrolled 179 asthmatics admitted for an episode of NFA. A cluster analysis using two-steps algorithm was performed from data of 84 of these cases. The analysis defined three clusters of patients with NFA: cluster 1, the largest, including older patients with clinical and therapeutic criteria of severe asthma; cluster 2, with an high proportion of respiratory arrest (68%), impaired consciousness level (82%) and mechanical ventilation (93%); and cluster 3, which included younger patients, characterized by an insufficient anti-inflammatory treatment and frequent sensitization to Alternaria alternata and soybean. These results identify specific asthma phenotypes involved in NFA, confirming in part previous findings observed in studies with a clinical approach. The identification of patients with a specific NFA phenotype could suggest interventions to prevent future severe asthma exacerbations. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Rapid differentiation of Chinese hop varieties (Humulus lupulus) using volatile fingerprinting by HS-SPME-GC-MS combined with multivariate statistical analysis.

PubMed

Liu, Zechang; Wang, Liping; Liu, Yumei

2018-01-18

Hops impart flavor to beer, with the volatile components characterizing the various hop varieties and qualities. Fingerprinting, especially flavor fingerprinting, is often used to identify 'flavor products' because inconsistencies in the description of flavor may lead to an incorrect definition of beer quality. Compared to flavor fingerprinting, volatile fingerprinting is simpler and easier. We performed volatile fingerprinting using head space-solid phase micro-extraction gas chromatography-mass spectrometry combined with similarity analysis and principal component analysis (PCA) for evaluating and distinguishing between three major Chinese hops. Eighty-four volatiles were identified, which were classified into seven categories. Volatile fingerprinting based on similarity analysis did not yield any obvious result. By contrast, hop varieties and qualities were identified using volatile fingerprinting based on PCA. The potential variables explained the variance in the three hop varieties. In addition, the dendrogram and principal component score plot described the differences and classifications of hops. Volatile fingerprinting plus multivariate statistical analysis can rapidly differentiate between the different varieties and qualities of the three major Chinese hops. Furthermore, this method can be used as a reference in other fields. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

Electrochemical Characterization of Carbon Nanotubes for Fuel Cell MEA's

NASA Technical Reports Server (NTRS)

Panagaris, Jael; Loyselle, Patricia

2004-01-01

Single-walled and multi-walled carbon nanotubes from different sources have been evaluated before and after sonication to identify structural differences and evaluate electrochemical performance. Raman spectral analysis and cyclic voltammetry in situ with QCM were the principle means of evaluating the tubes. The raman data indicates that sonication in toluene modifies the structural properties of the nanotubes. Sonication also affects the electrochemical performance of single-walled nanotubes and the multi-walled tubes differently. The characterization of different types of carbon nanotubes leads up to identifying a potential candidate for incorporating carbon nanotubes for fuel cell MEA structures.

A Bayesian Network Based Global Sensitivity Analysis Method for Identifying Dominant Processes in a Multi-physics Model

NASA Astrophysics Data System (ADS)

Dai, H.; Chen, X.; Ye, M.; Song, X.; Zachara, J. M.

2016-12-01

Sensitivity analysis has been an important tool in groundwater modeling to identify the influential parameters. Among various sensitivity analysis methods, the variance-based global sensitivity analysis has gained popularity for its model independence characteristic and capability of providing accurate sensitivity measurements. However, the conventional variance-based method only considers uncertainty contribution of single model parameters. In this research, we extended the variance-based method to consider more uncertainty sources and developed a new framework to allow flexible combinations of different uncertainty components. We decompose the uncertainty sources into a hierarchical three-layer structure: scenario, model and parametric. Furthermore, each layer of uncertainty source is capable of containing multiple components. An uncertainty and sensitivity analysis framework was then constructed following this three-layer structure using Bayesian network. Different uncertainty components are represented as uncertain nodes in this network. Through the framework, variance-based sensitivity analysis can be implemented with great flexibility of using different grouping strategies for uncertainty components. The variance-based sensitivity analysis thus is improved to be able to investigate the importance of an extended range of uncertainty sources: scenario, model, and other different combinations of uncertainty components which can represent certain key model system processes (e.g., groundwater recharge process, flow reactive transport process). For test and demonstration purposes, the developed methodology was implemented into a test case of real-world groundwater reactive transport modeling with various uncertainty sources. The results demonstrate that the new sensitivity analysis method is able to estimate accurate importance measurements for any uncertainty sources which were formed by different combinations of uncertainty components. The new methodology can provide useful information for environmental management and decision-makers to formulate policies and strategies.

Drivers of wetland conversion: a global meta-analysis.

PubMed

van Asselen, Sanneke; Verburg, Peter H; Vermaat, Jan E; Janse, Jan H

2013-01-01

Meta-analysis of case studies has become an important tool for synthesizing case study findings in land change. Meta-analyses of deforestation, urbanization, desertification and change in shifting cultivation systems have been published. This present study adds to this literature, with an analysis of the proximate causes and underlying forces of wetland conversion at a global scale using two complementary approaches of systematic review. Firstly, a meta-analysis of 105 case-study papers describing wetland conversion was performed, showing that different combinations of multiple-factor proximate causes, and underlying forces, drive wetland conversion. Agricultural development has been the main proximate cause of wetland conversion, and economic growth and population density are the most frequently identified underlying forces. Secondly, to add a more quantitative component to the study, a logistic meta-regression analysis was performed to estimate the likelihood of wetland conversion worldwide, using globally-consistent biophysical and socioeconomic location factor maps. Significant factors explaining wetland conversion, in order of importance, are market influence, total wetland area (lower conversion probability), mean annual temperature and cropland or built-up area. The regression analyses results support the outcomes of the meta-analysis of the processes of conversion mentioned in the individual case studies. In other meta-analyses of land change, similar factors (e.g., agricultural development, population growth, market/economic factors) are also identified as important causes of various types of land change (e.g., deforestation, desertification). Meta-analysis helps to identify commonalities across the various local case studies and identify which variables may lead to individual cases to behave differently. The meta-regression provides maps indicating the likelihood of wetland conversion worldwide based on the location factors that have determined historic conversions.

Drivers of Wetland Conversion: a Global Meta-Analysis

PubMed Central

van Asselen, Sanneke; Verburg, Peter H.; Vermaat, Jan E.; Janse, Jan H.

2013-01-01

Meta-analysis of case studies has become an important tool for synthesizing case study findings in land change. Meta-analyses of deforestation, urbanization, desertification and change in shifting cultivation systems have been published. This present study adds to this literature, with an analysis of the proximate causes and underlying forces of wetland conversion at a global scale using two complementary approaches of systematic review. Firstly, a meta-analysis of 105 case-study papers describing wetland conversion was performed, showing that different combinations of multiple-factor proximate causes, and underlying forces, drive wetland conversion. Agricultural development has been the main proximate cause of wetland conversion, and economic growth and population density are the most frequently identified underlying forces. Secondly, to add a more quantitative component to the study, a logistic meta-regression analysis was performed to estimate the likelihood of wetland conversion worldwide, using globally-consistent biophysical and socioeconomic location factor maps. Significant factors explaining wetland conversion, in order of importance, are market influence, total wetland area (lower conversion probability), mean annual temperature and cropland or built-up area. The regression analyses results support the outcomes of the meta-analysis of the processes of conversion mentioned in the individual case studies. In other meta-analyses of land change, similar factors (e.g., agricultural development, population growth, market/economic factors) are also identified as important causes of various types of land change (e.g., deforestation, desertification). Meta-analysis helps to identify commonalities across the various local case studies and identify which variables may lead to individual cases to behave differently. The meta-regression provides maps indicating the likelihood of wetland conversion worldwide based on the location factors that have determined historic conversions. PMID:24282580

Similar but Different: Differences in Comprehension Diagnosis on the Neale Analysis of Reading Ability and the York Assessment of Reading for Comprehension

ERIC Educational Resources Information Center

Colenbrander, Danielle; Nickels, Lyndsey; Kohnen, Saskia

2017-01-01

Background: Identifying reading comprehension difficulties is challenging. There are many comprehension tests to choose from, and a child's diagnosis can be influenced by various factors such as a test's format and content and the choice of diagnostic criteria. We investigate these issues with reference to the Neale Analysis of Reading Ability…

Bioprospecting Chemical Diversity and Bioactivity in a Marine Derived Aspergillus terreus.

PubMed

Adpressa, Donovon A; Loesgen, Sandra

2016-02-01

A comparative metabolomic study of a marine derived fungus (Aspergillus terreus) grown under various culture conditions is presented. The fungus was grown in eleven different culture conditions using solid agar, broth cultures, or grain based media (OSMAC). Multivariate analysis of LC/MS data from the organic extracts revealed drastic differences in the metabolic profiles and guided our subsequent isolation efforts. The compound 7-desmethylcitreoviridin was isolated and identified, and is fully described for the first time. In addition, 16 known fungal metabolites were also isolated and identified. All compounds were elucidated by detailed spectroscopic analysis and tested for antibacterial activities against five human pathogens and tested for cytotoxicity. This study demonstrates that LC/MS based multivariate analysis provides a simple yet powerful tool to analyze the metabolome of a single fungal strain grown under various conditions. This approach allows environmentally-induced changes in metabolite expression to be rapidly visualized, and uses these differences to guide the discovery of new bioactive molecules. Copyright © 2016 Verlag Helvetica Chimica Acta AG, Zürich.

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

Andersen, Gary L.; Dubinsky, Eric A.

Herein are described 1058 different bacterial taxa that were unique to either human, grazing mammal, or bird fecal wastes. These identified taxa can serve as specific identifier taxa for these sources in environmental waters. Two field tests in marine waters demonstrate the capacity of phylogenetic microarray analysis to track multiple sources with one test.

[Identifying areas of epidemiological stratification in an onchocerciasis focus in Yanomami territory, Roraima, Brazil].

PubMed

Coelho, G E; Vieira, J B; Garcia-Zapata, M T; Schuertz, J C

1998-01-01

In this paper, aimed at suitable planning, analysis, and follow-up of treatment, control, and eradication in a human onchocerciasis program, were studied 27 geographic areas and examined 3,974 inhabitants. Four epidemiological areas with different prevalences were identified and stratified.

Net Venn - An integrated network analysis web platform for gene lists

USDA-ARS?s Scientific Manuscript database

Many lists containing biological identifiers such as gene lists have been generated in various genomics projects. Identifying the overlap among gene lists can enable us to understand the similarities and differences between the datasets. Here, we present an interactome network-based web application...

Classification and Validation of Behavioral Subtypes of Learning-Disabled Children.

ERIC Educational Resources Information Center

Speece, Deborah L.; And Others

1985-01-01

Using the Classroom Behavior Inventory, teachers rated the behaviors of 63 school-identified, learning-disabled first and second graders. Hierarchical cluster analysis techniques identified seven distinct behavioral subtypes. Internal validation techniques indicated that the subtypes were replicable and had profile patterns different from a sample…

Bovine Milk Comparative Proteome Analysis from Early, Mid, and Late Lactation in the Cattle Breed, Malnad Gidda (Bos indicus).

PubMed

Mol, Praseeda; Kannegundla, Uday; Dey, Gourav; Gopalakrishnan, Lathika; Dammalli, Manjunath; Kumar, Manish; Patil, Arun H; Basavaraju, Marappa; Rao, Akhila; Ramesha, Kerekoppa P; Prasad, Thottethodi Subrahmanya Keshava

2018-03-01

Bovine milk is important for both veterinary medicine and human nutrition. Understanding the bovine milk proteome at different stages of lactation has therefore broad significance for integrative biology and clinical medicine as well. Indeed, different lactation stages have marked influence on the milk yield, milk constituents, and nourishment of the neonates. We performed a comparative proteome analysis of the bovine milk obtained at different stages of lactation from the Indian indigenous cattle Malnad Gidda (Bos indicus), a widely available breed. The milk differential proteome during the lactation stages in B. indicus has not been investigated to date. Using high-resolution mass spectrometry-based quantitative proteomics of the bovine whey proteins at early, mid, and late lactation stages, we identified a total of 564 proteins, out of which 403 proteins were found to be differentially abundant at different lactation stages. As is expected of any body fluid proteome, 51% of the proteins identified in the milk were found to have signal peptides. Gene ontology analyses were carried out to categorize proteins altered across different lactation stages based on biological process and molecular function, which enabled us to correlate their significance in each lactation stage. We also investigated the potential pathways enriched in different lactation stages using bioinformatics pathway analysis tools. To the best of our knowledge, this study represents the first and largest inventory of milk proteins identified to date for an Indian cattle breed. We believe that the current study broadly informs both veterinary omics research and the emerging field of nutriproteomics during lactation stages.

Simultaneously Measured Interarm Blood Pressure Difference and Stroke: An Individual Participants Data Meta-Analysis.

PubMed

Tomiyama, Hirofumi; Ohkuma, Toshiaki; Ninomiya, Toshiharu; Mastumoto, Chisa; Kario, Kazuomi; Hoshide, Satoshi; Kita, Yoshikuni; Inoguchi, Toyoshi; Maeda, Yasutaka; Kohara, Katsuhiko; Tabara, Yasuharu; Nakamura, Motoyuki; Ohkubo, Takayoshi; Watada, Hirotaka; Munakata, Masanori; Ohishi, Mitsuru; Ito, Norihisa; Nakamura, Michinari; Shoji, Tetsuo; Vlachopoulos, Charalambos; Yamashina, Akira

2018-06-01

We conducted individual participant data meta-analysis to examine the validity of interarm blood pressure difference in simultaneous measurement as a marker to identify subjects with ankle-brachial pressure index <0.90 and to predict future cardiovascular events. We collected individual participant data on 13 317 Japanese subjects from 10 cohorts (general population-based cohorts, cohorts of patients with past history of cardiovascular events, and those with cardiovascular risk factors). Binary logistic regression analysis with adjustments identified interarm blood pressure difference >5 mm Hg as being associated with a significant odds ratio for the presence of ankle-brachial pressure index <0.90 (odds ratio, 2.19; 95% confidence interval, 1.60-3.03; P <0.01). Among 11 726 subjects without a past history of cardiovascular disease, 249 developed stroke during the average follow-up period of 7.4 years. Interarm blood pressure difference >15 mm Hg was associated with a significant Cox stratified adjusted hazard ratio for subsequent stroke (hazard ratio, 2.42; 95% confidence interval, 1.27-4.60; P <0.01). Therefore, interarm blood pressure differences, measured simultaneously in both arms, may be associated with vascular damage in the systemic arterial tree. These differences may be useful for identifying subjects with an ankle-brachial pressure index of <0.90 in the overall study population, and also a reliable predictor of future stroke in subjects without a past history of cardiovascular disease. These findings support the recommendation to measure blood pressure in both arms at the first visit. © 2018 American Heart Association, Inc.

Geographical classification of Epimedium based on HPLC fingerprint analysis combined with multi-ingredients quantitative analysis.

PubMed

Xu, Ning; Zhou, Guofu; Li, Xiaojuan; Lu, Heng; Meng, Fanyun; Zhai, Huaqiang

2017-05-01

A reliable and comprehensive method for identifying the origin and assessing the quality of Epimedium has been developed. The method is based on analysis of HPLC fingerprints, combined with similarity analysis, hierarchical cluster analysis (HCA), principal component analysis (PCA) and multi-ingredient quantitative analysis. Nineteen batches of Epimedium, collected from different areas in the western regions of China, were used to establish the fingerprints and 18 peaks were selected for the analysis. Similarity analysis, HCA and PCA all classified the 19 areas into three groups. Simultaneous quantification of the five major bioactive ingredients in the Epimedium samples was also carried out to confirm the consistency of the quality tests. These methods were successfully used to identify the geographical origin of the Epimedium samples and to evaluate their quality. Copyright © 2016 John Wiley & Sons, Ltd.

GC-MS analysis of headspace and liquid extracts for metabolomic differentiation of citrus Huanglongbing and zinc deficiency in leaves of 'Valencia' sweet orange from commercial groves.

PubMed

Cevallos-Cevallos, Juan Manuel; García-Torres, Rosalía; Etxeberria, Edgardo; Reyes-De-Corcuera, José Ignacio

2011-01-01

Citrus Huanglongbing (HLB) is considered the most destructive citrus disease worldwide. Symptoms-based detection of HLB is difficult due to similarities with zinc deficiency. To find metabolic differences between leaves from HLB-infected, zinc-deficient, and healthy 'Valencia' orange trees by using GC-MS based metabolomics. Analysis based on GC-MS methods for untargeted metabolite analysis of citrus leaves was developed and optimized. Sample extracts from healthy, zinc deficient, or HLB-infected sweet orange leaves were submitted to headspace solid phase micro-extraction (SPME) and derivatization treatments prior to GC-MS analysis. Principal components analysis achieved correct classification of all the derivatized liquid extracts. Analysis of variance revealed 6 possible biomarkers for HLB, of which 5 were identified as proline, β-elemene, (-)trans- caryophyllene, and α-humulene. Significant (P < 0.05) differences in oxo-butanedioic acid, arabitol, and neo-inositol were exclusively detected in samples from plants with zinc deficiency. Levels of isocaryophyllen, α-selinene, β-selinene, and fructose were significantly (P < 0.05) different in healthy leaves only. Results suggest the potential of using identified HLB biomarkers for rapid differentiation of HLB from zinc deficiency. Copyright © 2010 John Wiley & Sons, Ltd.

Modeling, Analyzing, and Mitigating Dissonance Between Alerting Systems

NASA Technical Reports Server (NTRS)

Song, Lixia; Kuchar, James K.

2003-01-01

Alerting systems are becoming pervasive in process operations, which may result in the potential for dissonance or conflict in information from different alerting systems that suggests different threat levels and/or actions to resolve hazards. Little is currently available to help in predicting or solving the dissonance problem. This thesis presents a methodology to model and analyze dissonance between alerting systems, providing both a theoretical foundation for understanding dissonance and a practical basis from which specific problems can be addressed. A state-space representation of multiple alerting system operation is generalized that can be tailored across a variety of applications. Based on the representation, two major causes of dissonance are identified: logic differences and sensor error. Additionally, several possible types of dissonance are identified. A mathematical analysis method is developed to identify the conditions for dissonance originating from logic differences. A probabilistic analysis methodology is developed to estimate the probability of dissonance originating from sensor error, and to compare the relative contribution to dissonance of sensor error against the contribution from logic differences. A hybrid model, which describes the dynamic behavior of the process with multiple alerting systems, is developed to identify dangerous dissonance space, from which the process can lead to disaster. Methodologies to avoid or mitigate dissonance are outlined. Two examples are used to demonstrate the application of the methodology. First, a conceptual In-Trail Spacing example is presented. The methodology is applied to identify the conditions for possible dissonance, to identify relative contribution of logic difference and sensor error, and to identify dangerous dissonance space. Several proposed mitigation methods are demonstrated in this example. In the second example, the methodology is applied to address the dissonance problem between two air traffic alert and avoidance systems: the existing Traffic Alert and Collision Avoidance System (TCAS) vs. the proposed Airborne Conflict Management system (ACM). Conditions on ACM resolution maneuvers are identified to avoid dynamic dissonance between TCAS and ACM. Also included in this report is an Appendix written by Lee Winder about recent and continuing work on alerting systems design. The application of Markov Decision Process (MDP) theory to complex alerting problems is discussed and illustrated with an abstract example system.

Integrative Analysis of Prognosis Data on Multiple Cancer Subtypes

PubMed Central

Liu, Jin; Huang, Jian; Zhang, Yawei; Lan, Qing; Rothman, Nathaniel; Zheng, Tongzhang; Ma, Shuangge

2014-01-01

Summary In cancer research, profiling studies have been extensively conducted, searching for genes/SNPs associated with prognosis. Cancer is diverse. Examining the similarity and difference in the genetic basis of multiple subtypes of the same cancer can lead to a better understanding of their connections and distinctions. Classic meta-analysis methods analyze each subtype separately and then compare analysis results across subtypes. Integrative analysis methods, in contrast, analyze the raw data on multiple subtypes simultaneously and can outperform meta-analysis methods. In this study, prognosis data on multiple subtypes of the same cancer are analyzed. An AFT (accelerated failure time) model is adopted to describe survival. The genetic basis of multiple subtypes is described using the heterogeneity model, which allows a gene/SNP to be associated with prognosis of some subtypes but not others. A compound penalization method is developed to identify genes that contain important SNPs associated with prognosis. The proposed method has an intuitive formulation and is realized using an iterative algorithm. Asymptotic properties are rigorously established. Simulation shows that the proposed method has satisfactory performance and outperforms a penalization-based meta-analysis method and a regularized thresholding method. An NHL (non-Hodgkin lymphoma) prognosis study with SNP measurements is analyzed. Genes associated with the three major subtypes, namely DLBCL, FL, and CLL/SLL, are identified. The proposed method identifies genes that are different from alternatives and have important implications and satisfactory prediction performance. PMID:24766212

Identification of Child Pedestrian Training Objectives: The Role of Task Analysis and Empirical Research.

ERIC Educational Resources Information Center

van der Molen, Hugo H.

1984-01-01

Describes a study designed to demonstrate that child pedestrian training objectives may be identified systematically through various task analysis methods, making use of different types of empirical information. Early approaches to analysis of pedestrian tasks are reviewed, and an outline of the Traffic Research Centre's pedestrian task analysis…

An Objective Comparison of Applied Behavior Analysis and Organizational Behavior Management Research

ERIC Educational Resources Information Center

Culig, Kathryn M.; Dickinson, Alyce M.; McGee, Heather M.; Austin, John

2005-01-01

This paper presents an objective review, analysis, and comparison of empirical studies targeting the behavior of adults published in Journal of Applied Behavior Analysis (JABA) and Journal of Organizational Behavior Management (JOBM) between 1997 and 2001. The purpose of the comparisons was to identify similarities and differences with respect to…

Partial Least Squares Based Gene Expression Analysis in EBV- Positive and EBV-Negative Posttransplant Lymphoproliferative Disorders.

PubMed

Wu, Sa; Zhang, Xin; Li, Zhi-Ming; Shi, Yan-Xia; Huang, Jia-Jia; Xia, Yi; Yang, Hang; Jiang, Wen-Qi

2013-01-01

Post-transplant lymphoproliferative disorder (PTLD) is a common complication of therapeutic immunosuppression after organ transplantation. Gene expression profile facilitates the identification of biological difference between Epstein-Barr virus (EBV) positive and negative PTLDs. Previous studies mainly implemented variance/regression analysis without considering unaccounted array specific factors. The aim of this study is to investigate the gene expression difference between EBV positive and negative PTLDs through partial least squares (PLS) based analysis. With a microarray data set from the Gene Expression Omnibus database, we performed PLS based analysis. We acquired 1188 differentially expressed genes. Pathway and Gene Ontology enrichment analysis identified significantly over-representation of dysregulated genes in immune response and cancer related biological processes. Network analysis identified three hub genes with degrees higher than 15, including CREBBP, ATXN1, and PML. Proteins encoded by CREBBP and PML have been reported to be interact with EBV before. Our findings shed light on expression distinction of EBV positive and negative PTLDs with the hope to offer theoretical support for future therapeutic study.

Routeing of power lines through least-cost path analysis and multicriteria evaluation to minimise environmental impacts

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

Bagli, Stefano, E-mail: stefano.bagli@gecosistema.i; Geneletti, Davide, E-mail: davide.geneletti@ing.unitn.i; Center for International Development, Harvard University, 79 JFK Street, Cambridge, MA 02138

2011-04-15

Least-cost path analysis (LCPA) allows designers to find the 'cheapest' way to connect two locations within a cost surface, which can be computed by combining multiple criteria, and therefore by accounting for different issues (environmental impact, economic investment, etc.). This procedure can be easily implemented with modern Geographic Information System (GIS) technologies, and consequently it has been widely employed to support planning and design of different types of linear infrastructures, ranging from roads to pipelines. This paper presents an approach based on the integration of multicriteria evaluation (MCE) and LCPA to identify the most suitable route for a 132 kVmore » power line. Criteria such as cost, visibility, population density, and ecosystem naturalness were used for the analysis. Firstly, spatial MCE and LCPA were combined to generate cost surfaces, and to identify alternative paths. Subsequently, MCE was used to compare the alternatives, and rank them according to their overall suitability. Finally, a sensitivity analysis allowed the stability of the results to be tested and the most critical factors of the evaluation to be detected. The study found that small changes in the location of the power line start and end points can result in significantly different paths, and consequently impact levels. This suggested that planners should always consider alternative potential locations of terminals in order to identify the best path. Furthermore, it was shown that the use of different weight scenarios may help making the model adaptable to varying environmental and social contexts. The approach was tested on a real-world case study in north-eastern Italy.« less

[Gender perspective can result in better research on sex differences and revascularization].

PubMed

Löfmark, U; Hammarström, A

2001-07-25

This article focuses on how sex differences in revascularization, PTCA and CABG, are discussed in medical research. We selected and analyzed 10 articles identified through Medline, for the purpose of studying such discussions. Three explanatory models were identified by qualitative analysis: biological, psychosocial and discriminatory. Although the articles focused on sex differences in revascularization, the discussions in the articles on this issue were sparse. We demonstrate how a gender perspective can generate new questions and theories and contribute to a better prognosis for women and men with heart disease.

A retrospective analysis of the role of proton pump inhibitors in colorectal cancer disease survival

PubMed Central

Graham, C.; Orr, C.; Bricks, C.S.; Hopman, W.M.; Hammad, N.; Ramjeesingh, R.

2016-01-01

Background Proton pump inhibitors (ppis) are a commonly used medication. A limited number of studies have identified a weak-to-moderate association between ppi use and colorectal cancer (crc) risk, but none to date have identified an effect of ppi use on crc survival. We therefore postulated that an association between ppi use and crc survival might potentially exist. Methods We performed a retrospective chart review of 1304 crc patients diagnosed from January 2005 to December 2011 and treated at the Cancer Centre of Southeastern Ontario. Kaplan–Meier analysis and Cox proportional hazards regression models were used to evaluate overall survival (os). Results We identified 117 patients (9.0%) who were taking ppis at the time of oncology consult. Those taking a ppi were also more often taking asa or statins (or both) and had a statistically significantly increased rate of cardiac disease. No identifiable difference in tumour characteristics was evident in the two groups, including tumour location, differentiation, lymph node status, and stage. Univariate analysis identified a statistically nonsignificant difference in survival, with those taking a ppi experiencing lesser 1-year (82.1% vs. 86.7%, p = 0.161), 2-year (70.1% vs. 76.8%, p = 0.111), and 5-year os (55.2% vs. 62.9%, p = 0.165). When controlling for patient demographics and tumour characteristics, multivariate Cox regression analysis identified a statistically significant effect of ppi in our patient population (hazard ratio: 1.343; 95% confidence interval: 1.011 to 1.785; p = 0.042). Conclusions Our results suggest a potential adverse effect of ppi use on os in crc patients. These results need further evaluation in prospective analyses. PMID:28050148

[MALDI-TOF and SELDI-TOF analysis: "tandem" techniques to identify potential biomarker in fibromyalgia].

PubMed

Giacomelli, C; Bazzichi, L; Giusti, L; Ciregia, F; Baldini, C; Da Valle, Y; De Feo, F; Sernissi, F; Rossi, A; Bombardieri, S; Lucacchini, A

2011-11-09

Fibromyalgia (FM) is characterized by the presence of chronic widespread pain throughout the musculoskeletal system and diffuse tenderness. Unfortunately, no laboratory tests have been appropriately validated for FM and correlated with the subsets and activity. The aim of this study was to apply a proteomic technique in saliva of FM patients: the Surface Enhance Laser Desorption/Ionization Time-of-Flight (SELDI-TOF). For this study, 57 FM patients and 35 HC patients were enrolled. The proteomic analysis of saliva was carried out using SELDI-TOF. The analysis was performed using different chip arrays with different characteristics of binding. The statistical analysis was performed using cluster analysis and the difference between two groups was underlined using Student’s t-test. Spectra analysis highlighted the presence of several peaks differently expressed in FM patients compared with controls. The preliminary results obtained by SELDI-TOF analysis were compared with those obtained in our previous study performed on whole saliva of FM patients by using electrophoresis. The m/z of two peaks, increased in FM patients, seem to overlap well with the molecular weight of calgranulin A and C and Rho GDP-dissociation inhibitor 2, which we had found up-regulated in our previous study. These preliminary results showed the possibility of identifying potential salivary biomarker through salivary proteomic analysis with MALDI-TOF and SELDI-TOF in FM patients. The peaks observed allow us to focus on some of the particular pathogenic aspects of FM, the oxidative stress which contradistinguishes this condition, the involvement of proteins related to the cytoskeletal arrangements, and central sensibilization.

Mapping remote and multidisciplinary learning barriers: lessons from challenge-based innovation at CERN

NASA Astrophysics Data System (ADS)

Jensen, Matilde Bisballe; Utriainen, Tuuli Maria; Steinert, Martin

2018-01-01

This paper presents the experienced difficulties of students participating in the multidisciplinary, remote collaborating engineering design course challenge-based innovation at CERN. This is with the aim to identify learning barriers and improve future learning experiences. We statistically analyse the rated differences between distinct design activities, educational background and remote vs. co-located collaboration. The analysis is based on a quantitative and qualitative questionnaire (N = 37). Our analysis found significant ranking differences between remote and co-located activities. This questions whether the remote factor might be a barrier for the originally intended learning goals. Further a correlation between analytical and converging design phases was identified. Hence, future facilitators are suggested to help students in the transition from one design phase to the next rather than only teaching methods in the individual design phases. Finally, we discuss how educators address the identified learning barriers when designing future courses including multidisciplinary or remote collaboration.

Signal analysis of the female singing voice: Features for perceptual singer identity

NASA Astrophysics Data System (ADS)

Mellody, Maureen

2001-07-01

Individual singing voices tend to be easy for a listener to identify, particularly when compared to the difficulty of identifying the performer of any other musical instrument. What cues does a listener use to identify a particular singing voice? This work seeks to identify a set of features with which one can synthesize notes with the vocal quality of a particular singer. Such analysis and synthesis influences computer music (in the creation of synthetic sounds with different timbre), vocal pedagogy (as a training tool to help singers understand properties of their own voice as well as different professional-quality voices), and vocal health (to identify improper behavior in vocal production). The problem of singer identification is approached in three phases: signal analysis, the development of low- order representations, and perceptual evaluation. To perform the signal analysis, a high-resolution time- frequency distribution is applied to vowel tokens from sopranos and mezzo-sopranos. From these results, low- order representations are created for each singer's notes, which are used to synthesize sounds with the timbral quality of that singer. Finally, these synthesized sounds, along with original recordings, are evaluated by trained listeners in a variety of perceptual experiments to determine the extent to which the vocal quality of the desired singer is captured. Results from the signal analysis show that amplitude and frequency estimates extracted from the time-frequency signal analysis can be used to re-create each signal with little degradation in quality and no loss of perceptual identity. Low-order representations derived from the signal analysis are used in clustering and classification, which successfully clusters signals with corresponding singer identity. Finally, perceptual results indicate that trained listeners are, surprisingly, only modestly successful at correctly identifying the singer of a recording, and find the task to be particularly difficult for certain voices and extremely easy for others. Listeners also indicate that the majority of sounds synthesized with the low-order representations sufficiently capture the desired vocal timbre. Again, the task is easy for certain voices and much more difficult when evaluating other singers, consistent with the results from the original recordings.

Achievement Goal Orientations and Subjective Well-Being: A Person-Centred Analysis

ERIC Educational Resources Information Center

Tuominen-Soini, Heta; Salmela-Aro, Katariina; Niemivirta, Markku

2008-01-01

This study examined whether students with different achievement goal orientation profiles differ in terms of subjective well-being (i.e., self-esteem, depressive symptoms, school-related burnout, and educational goal appraisals). Six groups of students with unique motivational profiles were identified. Observed differences in subjective well-being…

Comparative Economic Organization: The Analysis of Discrete Structural Alternatives.

ERIC Educational Resources Information Center

Williamson, Oliver E.

1991-01-01

Combines institutional economics with aspects of contract law and organization theory to identify and explicate the key differences distinguishing three generic forms of economic organization: market, hybrid, and hierarchy. These generic forms are distinguished by different coordinating and control mechanisms and by different abilities to adapt to…

Individual Differences in Consumer Buying Patterns: A Behavioral Economic Analysis

ERIC Educational Resources Information Center

Cavalcanti, Paulo R.; Oliveira-Castro, Jorge M.; Foxall, Gordon R.

2013-01-01

Although previous studies have identified several regularities in buying behavior, no integrated view of individual differences related to such patterns has been yet proposed. The present research examined individual differences in patterns of buying behavior of fast-moving consumer goods, using panel data with information concerning purchases of…

Integrated Analysis and Visualization of Group Differences in Structural and Functional Brain Connectivity: Applications in Typical Ageing and Schizophrenia.

PubMed

Langen, Carolyn D; White, Tonya; Ikram, M Arfan; Vernooij, Meike W; Niessen, Wiro J

2015-01-01

Structural and functional brain connectivity are increasingly used to identify and analyze group differences in studies of brain disease. This study presents methods to analyze uni- and bi-modal brain connectivity and evaluate their ability to identify differences. Novel visualizations of significantly different connections comparing multiple metrics are presented. On the global level, "bi-modal comparison plots" show the distribution of uni- and bi-modal group differences and the relationship between structure and function. Differences between brain lobes are visualized using "worm plots". Group differences in connections are examined with an existing visualization, the "connectogram". These visualizations were evaluated in two proof-of-concept studies: (1) middle-aged versus elderly subjects; and (2) patients with schizophrenia versus controls. Each included two measures derived from diffusion weighted images and two from functional magnetic resonance images. The structural measures were minimum cost path between two anatomical regions according to the "Statistical Analysis of Minimum cost path based Structural Connectivity" method and the average fractional anisotropy along the fiber. The functional measures were Pearson's correlation and partial correlation of mean regional time series. The relationship between structure and function was similar in both studies. Uni-modal group differences varied greatly between connectivity types. Group differences were identified in both studies globally, within brain lobes and between regions. In the aging study, minimum cost path was highly effective in identifying group differences on all levels; fractional anisotropy and mean correlation showed smaller differences on the brain lobe and regional levels. In the schizophrenia study, minimum cost path and fractional anisotropy showed differences on the global level and within brain lobes; mean correlation showed small differences on the lobe level. Only fractional anisotropy and mean correlation showed regional differences. The presented visualizations were helpful in comparing and evaluating connectivity measures on multiple levels in both studies.

Detection of Genetically Modified Sugarcane by Using Terahertz Spectroscopy and Chemometrics

NASA Astrophysics Data System (ADS)

Liu, J.; Xie, H.; Zha, B.; Ding, W.; Luo, J.; Hu, C.

2018-03-01

A methodology is proposed to identify genetically modified sugarcane from non-genetically modified sugarcane by using terahertz spectroscopy and chemometrics techniques, including linear discriminant analysis (LDA), support vector machine-discriminant analysis (SVM-DA), and partial least squares-discriminant analysis (PLS-DA). The classification rate of the above mentioned methods is compared, and different types of preprocessing are considered. According to the experimental results, the best option is PLS-DA, with an identification rate of 98%. The results indicated that THz spectroscopy and chemometrics techniques are a powerful tool to identify genetically modified and non-genetically modified sugarcane.

Meta-analytic framework for sparse K-means to identify disease subtypes in multiple transcriptomic studies

PubMed Central

Huo, Zhiguang; Ding, Ying; Liu, Silvia; Oesterreich, Steffi; Tseng, George

2016-01-01

Disease phenotyping by omics data has become a popular approach that potentially can lead to better personalized treatment. Identifying disease subtypes via unsupervised machine learning is the first step towards this goal. In this paper, we extend a sparse K-means method towards a meta-analytic framework to identify novel disease subtypes when expression profiles of multiple cohorts are available. The lasso regularization and meta-analysis identify a unique set of gene features for subtype characterization. An additional pattern matching reward function guarantees consistent subtype signatures across studies. The method was evaluated by simulations and leukemia and breast cancer data sets. The identified disease subtypes from meta-analysis were characterized with improved accuracy and stability compared to single study analysis. The breast cancer model was applied to an independent METABRIC dataset and generated improved survival difference between subtypes. These results provide a basis for diagnosis and development of targeted treatments for disease subgroups. PMID:27330233

Meta-analytic framework for sparse K-means to identify disease subtypes in multiple transcriptomic studies.

PubMed

Huo, Zhiguang; Ding, Ying; Liu, Silvia; Oesterreich, Steffi; Tseng, George

Disease phenotyping by omics data has become a popular approach that potentially can lead to better personalized treatment. Identifying disease subtypes via unsupervised machine learning is the first step towards this goal. In this paper, we extend a sparse K -means method towards a meta-analytic framework to identify novel disease subtypes when expression profiles of multiple cohorts are available. The lasso regularization and meta-analysis identify a unique set of gene features for subtype characterization. An additional pattern matching reward function guarantees consistent subtype signatures across studies. The method was evaluated by simulations and leukemia and breast cancer data sets. The identified disease subtypes from meta-analysis were characterized with improved accuracy and stability compared to single study analysis. The breast cancer model was applied to an independent METABRIC dataset and generated improved survival difference between subtypes. These results provide a basis for diagnosis and development of targeted treatments for disease subgroups.

Genetic architecture for susceptibility to gout in the KARE cohort study.

PubMed

Shin, Jimin; Kim, Younyoung; Kong, Minyoung; Lee, Chaeyoung

2012-06-01

This study aimed to identify functional associations of cis-regulatory regions with gout susceptibility using data resulted from a genome-wide association study (GWAS), and to show a genetic architecture for gout with interaction effects among genes within each of the identified functions. The GWAS was conducted with 8314 control subjects and 520 patients with gout in the Korea Association REsource cohort. However, genetic associations with any individual nucleotide variants were not discovered by Bonferroni multiple testing in the GWAS (P>1.42 × 10(-7)). Genomic regions enrichment analysis was employed to identify functional associations of cis-regulatory regions. This analysis revealed several biological processes associated with gout susceptibility, and they were quite different from those with serum uric acid level. Epistasis for susceptibility to gout was estimated using entropy decomposition with selected genes within each biological process identified by the genomic regions enrichment analysis. Some epistases among nucleotide sequence variants for gout susceptibility were found to be larger than their individual effects. This study provided the first evidence that genetic factors for gout susceptibility greatly differed from those for serum uric acid level, which may suggest that research endeavors for identifying genetic factors for gout susceptibility should not be heavily dependent on pathogenesis of uric acid. Interaction effects between genes should be examined to explain a large portion of phenotypic variability for gout susceptibility.

Identification of hydrologic indicators related to fish diversity and abundance: A data mining approach for fish community analysis

NASA Astrophysics Data System (ADS)

Yang, Yi-Chen E.; Cai, Ximing; Herricks, Edwin E.

2008-04-01

This paper develops a new approach to identify hydrologic indicators related to fish community and generate a quantitative function between an ecological target index and the identified hydrologic indicators. The approach is based on genetic programming (GP), a data mining method. Using the Shannon Index (a fish community diversity index) or the number of individuals (total abundance) of a fish community, as an ecological target, the GP identified the most ecologically relevant hydrologic indicators (ERHIs) from 32 indicators of hydrologic alteration, for the case study site, the upper Illinois River. Robustness analysis showed that different GP runs found a similar set of ERHIs; each of the identified ERHI from different GP runs had a consistent relationship with the target index. By comparing the GP results with those from principal component analysis and autecology matrix, the three approaches identified a small number (six) of common ERHIs. Particularly, the timing of low flow (Dmin) seems to be more relevant to the diversity of the fish community, while the magnitude of the low flow (Qb) is more relevant to the total fish abundance; large rising rates result in a significant improvement of fish diversity, which is counterintuitive and against previous findings. The quantitative function developed by GP was further used to construct an indicator impact matrix (IIM), which was demonstrated as a potentially useful tool for streamflow restoration design.

Genome-Wide Locations of Potential Epimutations Associated with Environmentally Induced Epigenetic Transgenerational Inheritance of Disease Using a Sequential Machine Learning Prediction Approach.

PubMed

Haque, M Muksitul; Holder, Lawrence B; Skinner, Michael K

2015-01-01

Environmentally induced epigenetic transgenerational inheritance of disease and phenotypic variation involves germline transmitted epimutations. The primary epimutations identified involve altered differential DNA methylation regions (DMRs). Different environmental toxicants have been shown to promote exposure (i.e., toxicant) specific signatures of germline epimutations. Analysis of genomic features associated with these epimutations identified low-density CpG regions (<3 CpG / 100bp) termed CpG deserts and a number of unique DNA sequence motifs. The rat genome was annotated for these and additional relevant features. The objective of the current study was to use a machine learning computational approach to predict all potential epimutations in the genome. A number of previously identified sperm epimutations were used as training sets. A novel machine learning approach using a sequential combination of Active Learning and Imbalance Class Learner analysis was developed. The transgenerational sperm epimutation analysis identified approximately 50K individual sites with a 1 kb mean size and 3,233 regions that had a minimum of three adjacent sites with a mean size of 3.5 kb. A select number of the most relevant genomic features were identified with the low density CpG deserts being a critical genomic feature of the features selected. A similar independent analysis with transgenerational somatic cell epimutation training sets identified a smaller number of 1,503 regions of genome-wide predicted sites and differences in genomic feature contributions. The predicted genome-wide germline (sperm) epimutations were found to be distinct from the predicted somatic cell epimutations. Validation of the genome-wide germline predicted sites used two recently identified transgenerational sperm epimutation signature sets from the pesticides dichlorodiphenyltrichloroethane (DDT) and methoxychlor (MXC) exposure lineage F3 generation. Analysis of this positive validation data set showed a 100% prediction accuracy for all the DDT-MXC sperm epimutations. Observations further elucidate the genomic features associated with transgenerational germline epimutations and identify a genome-wide set of potential epimutations that can be used to facilitate identification of epigenetic diagnostics for ancestral environmental exposures and disease susceptibility.

A meta-analysis to evaluate the cellular processes regulated by the interactome of endogenous and over-expressed estrogen receptor alpha.

PubMed

Simões, Joana; Amado, Francisco M; Vitorino, Rui; Helguero, Luisa A

2015-01-01

The nature of the proteins complexes that regulate ERα subcellular localization and activity is still an open question in breast cancer biology. Identification of such complexes will help understand development of endocrine resistance in ER+ breast cancer. Mass spectrometry (MS) has allowed comprehensive analysis of the ERα interactome. We have compared six published works analyzing the ERα interactome of MCF-7 and HeLa cells in order to identify a shared or different pathway-related fingerprint. Overall, 806 ERα interacting proteins were identified. The cellular processes were differentially represented according to the ERα purification methodology, indicating that the methodologies used are complementary. While in MCF-7 cells, the interactome of endogenous and over-expressed ERα essentially represents the same biological processes and cellular components, the proteins identified were not over-lapping; thus, suggesting that the biological response may differ as the regulatory/participating proteins in these complexes are different. Interestingly, biological processes uniquely associated to ERα over-expressed in HeLa cell line included L-serine biosynthetic process, cellular amino acid biosynthetic process and cell redox homeostasis. In summary, all the approaches analyzed in this meta-analysis are valid and complementary; in particular, for those cases where the processes occur at low frequency with normal ERα levels, and can be identified when the receptor is over-expressed. However special effort should be put into validating these findings in cells expressing physiological ERα levels.

Matrix assisted laser desorption ionization mass spectrometry imaging identifies markers of ageing and osteoarthritic cartilage

PubMed Central

2014-01-01

Introduction Cartilage protein distribution and the changes that occur in cartilage ageing and disease are essential in understanding the process of cartilage ageing and age related diseases such as osteoarthritis. The aim of this study was to investigate the peptide profiles in ageing and osteoarthritic (OA) cartilage sections using matrix assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI). Methods The distribution of proteins in young, old and OA equine cartilage was compared following tryptic digestion of cartilage slices and MALDI-MSI undertaken with a MALDI SYNAPT™ HDMS system. Protein identification was undertaken using database searches following multivariate analysis. Peptide intensity differences between young, ageing and OA cartilage were imaged with Biomap software. Analysis of aggrecanase specific cleavage patterns of a crude cartilage proteoglycan extract were used to validate some of the differences in peptide intensity identified. Immunohistochemistry studies validated the differences in protein abundance. Results Young, old and OA equine cartilage was discriminated based on their peptide signature using discriminant analysis. Proteins including aggrecan core protein, fibromodulin, and cartilage oligomeric matrix protein were identified and localised. Fibronectin peptides displayed a stronger intensity in OA cartilage. Age-specific protein markers for collectin-43 and cartilage oligomeric matrix protein were identified. In addition potential fibromodulin and biglycan peptides targeted for degradation in OA were detected. Conclusions MALDI-MSI provided a novel platform to study cartilage ageing and disease enabling age and disease specific peptides in cartilage to be elucidated and spatially resolved. PMID:24886698

Layer-by-Layer Proteomic Analysis of Mytilus galloprovincialis Shell

PubMed Central

Wang, Xin-xing; Bao, Lin-fei; Fan, Mei-hua; Li, Xiao-min; Wu, Chang-wen; Xia, Shu-wei

2015-01-01

Bivalve shell is a biomineralized tissue with various layers/microstructures and excellent mechanical properties. Shell matrix proteins (SMPs) pervade and envelop the mineral crystals and play essential roles in biomineralization. Despite that Mytilus is an economically important bivalve, only few proteomic studies have been performed for the shell, and current knowledge of the SMP set responsible for different shell layers of Mytilus remains largely patchy. In this study, we observed that Mytilus galloprovincialis shell contained three layers, including nacre, fibrous prism, and myostracum that is involved in shell-muscle attachment. A parallel proteomic analysis was performed for these three layers. By combining LC-MS/MS analysis with Mytilus EST database interrogations, a whole set of 113 proteins was identified, and the distribution of these proteins in different shell layers followed a mosaic pattern. For each layer, about a half of identified proteins are unique and the others are shared by two or all of three layers. This is the first description of the protein set exclusive to nacre, myostracum, and fibrous prism in Mytilus shell. Moreover, most of identified proteins in the present study are novel SMPs, which greatly extended biomineralization-related protein data of Mytilus. These results are useful, on one hand, for understanding the roles of SMPs in the deposition of different shell layers. On the other hand, the identified protein set of myostracum provides candidates for further exploring the mechanism of adductor muscle-shell attachment. PMID:26218932

Identifying Psychopathy Subtypes on the Basis of Personality Structure

ERIC Educational Resources Information Center

Hicks, Brian M.; Markon, Kristian E.; Patrick, Christopher J.; Krueger, Robert F.; Newman, Joseph P.

2004-01-01

The authors used model-based cluster analysis to identify subtypes of criminal psychopaths on the basis of differences in personality structure. Participants included 96 male prisoners diagnosed as psychopathic, using the Psychopathy Checklist Revised (PCL-R; R. D. Hare, 1991). Personality was assessed using the brief form of the Multidimensional…

Managing the Risks Associated with End-User Computing.

ERIC Educational Resources Information Center

Alavi, Maryam; Weiss, Ira R.

1986-01-01

Identifies organizational risks of end-user computing (EUC) associated with different stages of the end-user applications life cycle (analysis, design, implementation). Generic controls are identified that address each of the risks enumerated in a manner that allows EUC management to select those most appropriate to their EUC environment. (5…

Rapid Communication: MiR-92a as a housekeeping gene for analysis of bovine mastitis-related microRNA in milk.

PubMed

Lai, Y C; Fujikawa, T; Ando, T; Kitahara, G; Koiwa, M; Kubota, C; Miura, N

2017-06-01

Our aim was to identify a suitable microRNA housekeeping gene for real-time PCR analysis of bovine mastitis-related microRNA in milk. We identified , , and as housekeeping gene candidates on the basis of previous Solexa sequencing results. Threshold cycle (CT) values for , , and did not differ between milk from control cows and milk from mastitis-affected cows. NormFinder software identified as the most stable single housekeeping gene. We evaluated the suitability of the housekeeping gene candidates by using them to assess expression levels of the inflammation-related gene . Regardless of the housekeeping gene candidates used for normalization, relative expression levels of were significantly higher in mastitis-affected samples than in control samples. However, of all the housekeeping genes and gene combinations investigated, normalization with alone generated the difference in relative expression between mastitis-affected and control samples with the highest significance. These results suggest that is suitable for use as a housekeeping gene for analysis of bovine mastitis-related microRNA in milk.

Proteomics analysis identified peroxiredoxin 2 involved in early-phase left ventricular impairment in hamsters with cardiomyopathy.

PubMed

Kuzuya, Kentaro; Ichihara, Sahoko; Suzuki, Yuka; Inoue, Chisa; Ichihara, Gaku; Kurimoto, Syota; Oikawa, Shinji

2018-01-01

Given the hypothesis that inflammation plays a critical role in the progression of cardiovascular diseases, the aim of the present study was to identify new diagnostic and prognostic biomarkers of myocardial proteins involved in early-phase cardiac impairment, using proteomics analysis. Using the two-dimensional fluorescence difference gel electrophoresis (2D-DIGE) combined with MALDI-TOF/TOF tandem mass spectrometry, we compared differences in the expression of proteins in the whole left ventricles between control hamsters, dilated cardiomyopathic hamsters (TO-2), and hypertrophy cardiomyopathic hamsters (Bio14.6) at 6 weeks of age (n = 6, each group). Proteomic analysis identified 10 protein spots with significant alterations, with 7 up-regulated and 3 down-regulated proteins in the left ventricles of both TO-2 and Bio 14.6 hamsters, compared with control hamsters. Of the total alterations, peroxiredoxin 2 (PRDX2) showed significant upregulation in the left ventricles of TO-2 and Bio 14.6 hamsters. Our data suggest that PRDX2, a redox regulating molecule, is involved in early-phase left ventricular impairment in hamsters with cardiomyopathy.

Different type 2 diabetes risk assessments predict dissimilar numbers at ‘high risk’: a retrospective analysis of diabetes risk-assessment tools

PubMed Central

Gray, Benjamin J; Bracken, Richard M; Turner, Daniel; Morgan, Kerry; Thomas, Michael; Williams, Sally P; Williams, Meurig; Rice, Sam; Stephens, Jeffrey W

2015-01-01

Background Use of a validated risk-assessment tool to identify individuals at high risk of developing type 2 diabetes is currently recommended. It is under-reported, however, whether a different risk tool alters the predicted risk of an individual. Aim This study explored any differences between commonly used validated risk-assessment tools for type 2 diabetes. Design and setting Cross-sectional analysis of individuals who participated in a workplace-based risk assessment in Carmarthenshire, South Wales. Method Retrospective analysis of 676 individuals (389 females and 287 males) who participated in a workplace-based diabetes risk-assessment initiative. Ten-year risk of type 2 diabetes was predicted using the validated QDiabetes®, Leicester Risk Assessment (LRA), FINDRISC, and Cambridge Risk Score (CRS) algorithms. Results Differences between the risk-assessment tools were apparent following retrospective analysis of individuals. CRS categorised the highest proportion (13.6%) of individuals at ‘high risk’ followed by FINDRISC (6.6%), QDiabetes (6.1%), and, finally, the LRA was the most conservative risk tool (3.1%). Following further analysis by sex, over one-quarter of males were categorised at high risk using CRS (25.4%), whereas a greater percentage of females were categorised as high risk using FINDRISC (7.8%). Conclusion The adoption of a different valid risk-assessment tool can alter the predicted risk of an individual and caution should be used to identify those individuals who really are at high risk of type 2 diabetes. PMID:26541180

Different type 2 diabetes risk assessments predict dissimilar numbers at 'high risk': a retrospective analysis of diabetes risk-assessment tools.

PubMed

Gray, Benjamin J; Bracken, Richard M; Turner, Daniel; Morgan, Kerry; Thomas, Michael; Williams, Sally P; Williams, Meurig; Rice, Sam; Stephens, Jeffrey W

2015-12-01

Use of a validated risk-assessment tool to identify individuals at high risk of developing type 2 diabetes is currently recommended. It is under-reported, however, whether a different risk tool alters the predicted risk of an individual. This study explored any differences between commonly used validated risk-assessment tools for type 2 diabetes. Cross-sectional analysis of individuals who participated in a workplace-based risk assessment in Carmarthenshire, South Wales. Retrospective analysis of 676 individuals (389 females and 287 males) who participated in a workplace-based diabetes risk-assessment initiative. Ten-year risk of type 2 diabetes was predicted using the validated QDiabetes(®), Leicester Risk Assessment (LRA), FINDRISC, and Cambridge Risk Score (CRS) algorithms. Differences between the risk-assessment tools were apparent following retrospective analysis of individuals. CRS categorised the highest proportion (13.6%) of individuals at 'high risk' followed by FINDRISC (6.6%), QDiabetes (6.1%), and, finally, the LRA was the most conservative risk tool (3.1%). Following further analysis by sex, over one-quarter of males were categorised at high risk using CRS (25.4%), whereas a greater percentage of females were categorised as high risk using FINDRISC (7.8%). The adoption of a different valid risk-assessment tool can alter the predicted risk of an individual and caution should be used to identify those individuals who really are at high risk of type 2 diabetes. © British Journal of General Practice 2015.

Proteomic Analysis of Lyme Disease: Global Protein Comparison of Three Strains of Borrelia burgdorferi

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

Jacobs, Jon M.; Yang, Xiaohua; Luft, Benjamin J.

2005-04-01

The Borrelia burgdorferi spirochete is the causative agent of Lyme disease, the most common tick-borne disease in the United States. It has been studied extensively to help understand its pathogenicity of infection and how it can persist in different mammalian hosts. We report the proteomic analysis of the archetype B. burgdorferi B31 strain and two other strains (ND40, and JD-1) having different Borrelia pathotypes using strong cation exchange fractionation of proteolytic peptides followed by high-resolution, reversed phase capillary liquid chromatography coupled with ion trap tandem mass spectrometric (LC-MS/MS) analysis. Protein identification was facilitated by the availability of the complete B31more » genome sequence. A total of 665 Borrelia proteins were identified representing ~38 % coverage of the theoretical B31 proteome. A significant overlap was observed between the identified proteins in direct comparisons between any two strains (>72%), but distinct differences were observed among identified hypothetical and outer membrane proteins of the three strains. Such a concurrent proteomic overview of three Borrelia strains based upon only the B31 genome sequence is shown to provide significant insights into the presence or absence of specific proteins and a broad overall comparison among strains.« less

Diversity of lactic acid bacteria in suan-tsai and fu-tsai, traditional fermented mustard products of Taiwan.

PubMed

Chao, Shiou-Huei; Wu, Ruei-Jie; Watanabe, Koichi; Tsai, Ying-Chieh

2009-11-15

Fu-tsai and suan-tsai are spontaneously fermented mustard products traditionally prepared by the Hakka tribe of Taiwan. We chose 5 different processing stages of these products for analysis of the microbial community of lactic acid bacteria (LAB) by 16S rRNA gene sequencing. From 500 LAB isolates we identified 119 representative strains belonging to 5 genera and 18 species, including Enterococcus (1 species), Lactobacillus (11 species), Leuconostoc (3 species), Pediococcus (1 species), and Weissella (2 species). The LAB composition of mustard fermented for 3 days, known as the Mu sample, was the most diverse, with 11 different LAB species being isolated. We used sequence analysis of the 16S rRNA gene to identify the LAB strains and analysis of the dnaA, pheS, and rpoA genes to identify 13 LAB strains for which identification by 16S rRNA gene sequences was not possible. These 13 strains were found to belong to 5 validated known species: Lactobacillus farciminis, Leuconostoc mesenteroides, Leuconostoc pseudomesenteroides, Weissella cibaria, and Weissella paramesenteroides, and 5 possibly novel Lactobacillus species. These results revealed that there is a high level of diversity in LAB at the different stages of fermentation in the production of suan-tsai and fu-tsai.

Global Sensitivity Analysis for Identifying Important Parameters of Nitrogen Nitrification and Denitrification under Model and Scenario Uncertainties

NASA Astrophysics Data System (ADS)

Ye, M.; Chen, Z.; Shi, L.; Zhu, Y.; Yang, J.

2017-12-01

Nitrogen reactive transport modeling is subject to uncertainty in model parameters, structures, and scenarios. While global sensitivity analysis is a vital tool for identifying the parameters important to nitrogen reactive transport, conventional global sensitivity analysis only considers parametric uncertainty. This may result in inaccurate selection of important parameters, because parameter importance may vary under different models and modeling scenarios. By using a recently developed variance-based global sensitivity analysis method, this paper identifies important parameters with simultaneous consideration of parametric uncertainty, model uncertainty, and scenario uncertainty. In a numerical example of nitrogen reactive transport modeling, a combination of three scenarios of soil temperature and two scenarios of soil moisture leads to a total of six scenarios. Four alternative models are used to evaluate reduction functions used for calculating actual rates of nitrification and denitrification. The model uncertainty is tangled with scenario uncertainty, as the reduction functions depend on soil temperature and moisture content. The results of sensitivity analysis show that parameter importance varies substantially between different models and modeling scenarios, which may lead to inaccurate selection of important parameters if model and scenario uncertainties are not considered. This problem is avoided by using the new method of sensitivity analysis in the context of model averaging and scenario averaging. The new method of sensitivity analysis can be applied to other problems of contaminant transport modeling when model uncertainty and/or scenario uncertainty are present.

Identification of antimutagenic properties of anthocyanins and other polyphenols from rose (Rosa centifolia) petals and tea.

PubMed

Kumar, Sanjeev; Gautam, Satyendra; Sharma, Arun

2013-06-01

Petals from different rose (Rosa centifolia) cultivars ("passion," "pink noblesse," and "sphinx") were assessed for antimutagenicity using Escherichia coli RNA polymerase B (rpoB)-based Rif (S) →Rif (R) (rifampicin sensitive to resistant) forward mutation assay against ethyl methanesulfonate (EMS)-induced mutagenesis. The aqueous extracts of rose petals from different cultivars exhibited a wide variation in their antimutagenicity. Among these, cv. "passion" was found to display maximum antimutagenicity. Upon further fractionation, the anthocyanin extract of cv. "passion" displayed significantly higher antimutagenicity than its phenolic extract. During thin-layer chromatography (TLC) analysis, the anthocyanin extract got resolved into 3 spots: yellow (Rf : 0.14), blue (Rf : 0.30), and pink (Rf : 0.49). Among these spots, the blue one displayed significantly higher antimutagenicity than the other 2. Upon high-performance liquid chromatography analysis, this blue spot further got resolved into 2 peaks (Rt : 2.7 and 3.8 min). The 2nd peak (Rt : 3.8 min) displaying high antimutagenicity was identified by ESI-IT-MS/MS analysis as peonidin 3-glucoside, whereas less antimutagenic peak 1 (Rt : 2.7) was identified as cyanidin 3, 5-diglucoside. The other TLC bands were also characterized by ESI-IT-MS/MS analysis. The least antimutagenic pink band (Rf : 0.49) was identified as malvidin 3-acetylglucoside-4-vinylcatechol, whereas non-antimutagenic yellow band (Rf : 0.14) was identified as luteolinidin anthocyanin derivative. Interestingly, the anthocyanin extracted from rose tea of cv. "passion" exhibited a similar antimutagenicity as that of the raw rose petal indicating the thermal stability of the contributing bioactive(s). The findings thus indicated the health protective property of differently colored rose cultivars and the nature of their active bioingredients. © 2013 Institute of Food Technologists®

Identifying inaccuracy of MS Project using system analysis

NASA Astrophysics Data System (ADS)

Fachrurrazi; Husin, Saiful; Malahayati, Nurul; Irzaidi

2018-05-01

The problem encountered in project owner’s financial accounting report is the difference in total project costs of MS Project to the Indonesian Standard (Standard Indonesia Standard / Cost Estimating Standard Book of Indonesia). It is one of the MS Project problems concerning to its cost accuracy, so cost data cannot be used in an integrated way for all project components. This study focuses on finding the causes of inaccuracy of the MS Projects. The aim of this study, which is operationally, are: (i) identifying cost analysis procedures for both current methods (SNI) and MS Project; (ii) identifying cost bias in each element of the cost analysis procedure; and (iii) analysing the cost differences (cost bias) in each element to identify what the cause of inaccuracies in MS Project toward SNI is. The method in this study is comparing for both the system analysis of MS Project and SNI. The results are: (i) MS Project system in Work of Resources element has limitation for two decimal digits only, have led to its inaccuracy. Where the Work of Resources (referred to as effort) in MS Project represents multiplication between the Quantities of Activities and Requirements of resources in SNI; (ii) MS Project and SNI have differences in the costing methods (the cost estimation methods), in which the SNI uses the Quantity-Based Costing (QBC), meanwhile MS Project uses the Time-Based Costing (TBC). Based on this research, we recommend to the contractors who use SNI should make an adjustment for Work of Resources in MS Project (with correction index) so that it can be used in an integrated way to the project owner’s financial accounting system. Further research will conduct for improvement the MS Project as an integrated tool toward all part of the project participant.

Comparative Characterization of Crofelemer Samples Using Data Mining and Machine Learning Approaches With Analytical Stability Data Sets.

PubMed

Nariya, Maulik K; Kim, Jae Hyun; Xiong, Jian; Kleindl, Peter A; Hewarathna, Asha; Fisher, Adam C; Joshi, Sangeeta B; Schöneich, Christian; Forrest, M Laird; Middaugh, C Russell; Volkin, David B; Deeds, Eric J

2017-11-01

There is growing interest in generating physicochemical and biological analytical data sets to compare complex mixture drugs, for example, products from different manufacturers. In this work, we compare various crofelemer samples prepared from a single lot by filtration with varying molecular weight cutoffs combined with incubation for different times at different temperatures. The 2 preceding articles describe experimental data sets generated from analytical characterization of fractionated and degraded crofelemer samples. In this work, we use data mining techniques such as principal component analysis and mutual information scores to help visualize the data and determine discriminatory regions within these large data sets. The mutual information score identifies chemical signatures that differentiate crofelemer samples. These signatures, in many cases, would likely be missed by traditional data analysis tools. We also found that supervised learning classifiers robustly discriminate samples with around 99% classification accuracy, indicating that mathematical models of these physicochemical data sets are capable of identifying even subtle differences in crofelemer samples. Data mining and machine learning techniques can thus identify fingerprint-type attributes of complex mixture drugs that may be used for comparative characterization of products. Copyright © 2017 American Pharmacists Association®. All rights reserved.

Spatiotemporal analysis of single-trial EEG of emotional pictures based on independent component analysis and source location

NASA Astrophysics Data System (ADS)

Liu, Jiangang; Tian, Jie

2007-03-01

The present study combined the Independent Component Analysis (ICA) and low-resolution brain electromagnetic tomography (LORETA) algorithms to identify the spatial distribution and time course of single-trial EEG record differences between neural responses to emotional stimuli vs. the neutral. Single-trial multichannel (129-sensor) EEG records were collected from 21 healthy, right-handed subjects viewing the emotion emotional (pleasant/unpleasant) and neutral pictures selected from International Affective Picture System (IAPS). For each subject, the single-trial EEG records of each emotional pictures were concatenated with the neutral, and a three-step analysis was applied to each of them in the same way. First, the ICA was performed to decompose each concatenated single-trial EEG records into temporally independent and spatially fixed components, namely independent components (ICs). The IC associated with artifacts were isolated. Second, the clustering analysis classified, across subjects, the temporally and spatially similar ICs into the same clusters, in which nonparametric permutation test for Global Field Power (GFP) of IC projection scalp maps identified significantly different temporal segments of each emotional condition vs. neutral. Third, the brain regions accounted for those significant segments were localized spatially with LORETA analysis. In each cluster, a voxel-by-voxel randomization test identified significantly different brain regions between each emotional condition vs. the neutral. Compared to the neutral, both emotional pictures elicited activation in the visual, temporal, ventromedial and dorsomedial prefrontal cortex and anterior cingulated gyrus. In addition, the pleasant pictures activated the left middle prefrontal cortex and the posterior precuneus, while the unpleasant pictures activated the right orbitofrontal cortex, posterior cingulated gyrus and somatosensory region. Our results were well consistent with other functional imaging studies, while revealed temporal dynamics of emotional processing of specific brain structure with high temporal resolution.

Conceptual Analysis and Implications of Students' Individual Differences to Curriculum Implementation in Technical Education

ERIC Educational Resources Information Center

Akpan, Godwin A.; Essien, Emmanuel O.; Okure, Okure S.

2013-01-01

Individual differences refer to the unique ways each human being differs from another human being as expressed in behaviour or perceived in the physical appearance. Three factors of individual differences identified to be closely related to learning/acquisition of skills and performance of tasks. These are personality dimensions, self-efficacy and…

A new concept to study the effect of climate change on different flood types

NASA Astrophysics Data System (ADS)

Nissen, Katrin; Nied, Manuela; Pardowitz, Tobias; Ulbrich, Uwe; Merz, Bruno

2014-05-01

Flooding is triggered by the interaction of various processes. Especially important are the hydrological conditions prior to the event (e.g. soil saturation, snow cover) and the meteorological conditions during flood development (e.g. rainfall, temperature). Depending on these (pre-) conditions different flood types may develop such as long-rain floods, short-rain floods, flash floods, snowmelt floods and rain-on-snow floods. A new concept taking these factors into account is introduced and applied to flooding in the Elbe River basin. During the period September 1957 to August 2002, 82 flood events are identified and classified according to their flood type. The hydrological and meteorological conditions at each day during the analysis period are detemined. In case of the hydrological conditions, a soil moisture pattern classification is carried out. Soil moisture is simulated with a rainfall-runoff model driven by atmospheric observations. Days of similar soil moisture patterns are identified by a principle component analysis and a subsequent cluster analysis on the leading principal components. The meteorological conditions are identified by applying a cluster analysis to the geopotential height, temperature and humidity fields of the ERA40 reanalysis data set using the SANDRA cluster algorithm. We are able to identify specific pattern combinations of hydrological pre-conditions and meteorological conditions which favour different flood types. Based on these results it is possible to analyse the effect of climate change on different flood types. As an example we show first results obtained using an ensemble of climate scenario simulations of ECHAM5 MPIOM model, taking only the changes in the meteorological conditions into account. According to the simulations, the frequency of the meteorological patterns favouring long-rain, short-rain and flash floods will not change significantly under future climate conditions. A significant increase is, however, predicted for the amount of precipitation associated with many of the relevant meteorological patterns. The increase varies between 12 and 67% depending on the weather pattern.

[Analysis of software for identifying spectral line of laser-induced breakdown spectroscopy based on LabVIEW].

PubMed

Hu, Zhi-yu; Zhang, Lei; Ma, Wei-guang; Yan, Xiao-juan; Li, Zhi-xin; Zhang, Yong-zhi; Wang, Le; Dong, Lei; Yin, Wang-bao; Jia, Suo-tang

2012-03-01

Self-designed identifying software for LIBS spectral line was introduced. Being integrated with LabVIEW, the soft ware can smooth spectral lines and pick peaks. The second difference and threshold methods were employed. Characteristic spectrum of several elements matches the NIST database, and realizes automatic spectral line identification and qualitative analysis of the basic composition of sample. This software can analyze spectrum handily and rapidly. It will be a useful tool for LIBS.

Scheffersomyces stipitis: a comparative systems biology study with the Crabtree positive yeast Saccharomyces cerevisiae

PubMed Central

2012-01-01

Background Scheffersomyces stipitis is a Crabtree negative yeast, commonly known for its capacity to ferment pentose sugars. Differently from Crabtree positive yeasts such as Saccharomyces cerevisiae, the onset of fermentation in S. stipitis is not dependent on the sugar concentration, but is regulated by a decrease in oxygen levels. Even though S. stipitis has been extensively studied due to its potential application in pentoses fermentation, a limited amount of information is available about its metabolism during aerobic growth on glucose. Here, we provide a systems biology based comparison between the two yeasts, uncovering the metabolism of S. stipitis during aerobic growth on glucose under batch and chemostat cultivations. Results Starting from the analysis of physiological data, we confirmed through 13C-based flux analysis the fully respiratory metabolism of S. stipitis when growing both under glucose limited or glucose excess conditions. The patterns observed showed similarity to the fully respiratory metabolism observed for S. cerevisiae under chemostat cultivations however, intracellular metabolome analysis uncovered the presence of several differences in metabolite patterns. To describe gene expression levels under the two conditions, we performed RNA sequencing and the results were used to quantify transcript abundances of genes from the central carbon metabolism and compared with those obtained with S. cerevisiae. Interestingly, genes involved in central pathways showed different patterns of expression, suggesting different regulatory networks between the two yeasts. Efforts were focused on identifying shared and unique families of transcription factors between the two yeasts through in silico transcription factors analysis, suggesting a different regulation of glycolytic and glucoenogenic pathways. Conclusions The work presented addresses the impact of high-throughput methods in describing and comparing the physiology of Crabtree positive and Crabtree negative yeasts. Based on physiological data and flux analysis we identified the presence of one metabolic condition for S. stipitis under aerobic batch and chemostat cultivations, which shows similarities to the oxidative metabolism observed for S. cerevisiae under chemostat cultivations. Through metabolome analysis and genome-wide transcriptomic analysis several differences were identified. Interestingly, in silico analysis of transciption factors was useful to address a different regulation of mRNAs of genes involved in the central carbon metabolism. To our knowledge, this is the first time that the metabolism of S. stiptis is investigated in details and is compared to S. cerevisiae. Our study provides useful results and allows for the possibility to incorporate these data into recently developed genome-scaled metabolic, thus contributing to improve future industrial applications of S. stipitis as cell factory. PMID:23043429

Stress at work: development of the Stress Perception Questionnaire of Rome (SPQR), an ad hoc questionnaire for multidimensional assessment of work related stress.

PubMed

Cinti, M E; Cannavò, M; Fioravanti, M

2017-01-01

Stress is an emotional condition, mostly experienced as negative, initially identified and defined by Selye in the mid-thirties of the last Century. Since the first definition, stress concerns the adaptation pro- cess mostly related to environmental changes. An application of stress focuses on the evaluation of its interference on work conditions, and the scientific evidence on work related stress is very ample and rich. We are proposing a new ad hoc questionnaire for the multidimensional assessment of work related stress, called Stress Perception Question- naire of Rome (SPQR) composed of 50 items. The development of this questionnaire is based on a multi-step process: a) Identification of all the relevant topics to work related stress and areas in the scientific evidence and their transformation on specific contents of 60 tentative items; b) Exploratory factor analysis aimed to identify the best items (50) which could guarantee the maximum convergence on single scales (8), and the minimum redundancy between scales; c) Validation of the 8 scales' structure by a confirmatory factor analysis (fully achieved); d) Factor analysis for a second level factor resulting in a single factor identified as the questionnaire total score (Stress Score); d) Reliability analysis of the questionnaire total score and the single scale scores (at optimum level); e) Validation by external criteria of work related stress identified in the presence of personal violence episodes experienced by a group of health workers with different professional profiles and from two different hospitals in Rome. Our results show that the SPQR is a useful and sensitive tool for assessing the presence of emotional stress related problems identifiable in a work environment. The advantage of this questionnaire is that it allows for a multidimensional description of the different components of this problematic area besides its ability to quantify the overall stress level of those who have been administered the SPQR.

Text analysis methods, text analysis apparatuses, and articles of manufacture

DOEpatents

Whitney, Paul D; Willse, Alan R; Lopresti, Charles A; White, Amanda M

2014-10-28

Text analysis methods, text analysis apparatuses, and articles of manufacture are described according to some aspects. In one aspect, a text analysis method includes accessing information indicative of data content of a collection of text comprising a plurality of different topics, using a computing device, analyzing the information indicative of the data content, and using results of the analysis, identifying a presence of a new topic in the collection of text.

[Preliminary study on effective components of Tripterygium wilfordii for liver toxicity based on spectrum-effect correlation analysis].

PubMed

Zhao, Xiao-Mei; Pu, Shi-Biao; Zhao, Qing-Guo; Gong, Man; Wang, Jia-Bo; Ma, Zhi-Jie; Xiao, Xiao-He; Zhao, Kui-Jun

2016-08-01

In this paper, the spectrum-effect correlation analysis method was used to explore the main effective components of Tripterygium wilfordii for liver toxicity, and provide reference for promoting the quality control of T. wilfordii. Chinese medicine T.wilfordii was taken as the study object, and LC-Q-TOF-MS was used to characterize the chemical components in T. wilfordii samples from different areas, and their main components were initially identified after referring to the literature. With the normal human hepatocytes (LO2 cell line)as the carrier, acetaminophen as positive medicine, and cell inhibition rate as testing index, the simple correlation analysis and multivariate linear correlation analysis methods were used to screen the main components of T. wilfordii for liver toxicity. As a result, 10 kinds of main components were identified, and the spectrum-effect correlation analysis showed that triptolide may be the toxic component, which was consistent with previous results of traditional literature. Meanwhile it was found that tripterine and demethylzeylasteral may greatly contribute to liver toxicity in multivariate linear correlation analysis. T. wilfordii samples of different varieties or different origins showed large difference in quality, and the T. wilfordii from southwest China showed lower liver toxicity, while those from Hunan and Anhui province showed higher liver toxicity. This study will provide data support for further rational use of T. wilfordii and research on its liver toxicity ingredients. Copyright© by the Chinese Pharmaceutical Association.

Apparent Fibre Density: a novel measure for the analysis of diffusion-weighted magnetic resonance images.

PubMed

Raffelt, David; Tournier, J-Donald; Rose, Stephen; Ridgway, Gerard R; Henderson, Robert; Crozier, Stuart; Salvado, Olivier; Connelly, Alan

2012-02-15

This article proposes a new measure called Apparent Fibre Density (AFD) for the analysis of high angular resolution diffusion-weighted images using higher-order information provided by fibre orientation distributions (FODs) computed using spherical deconvolution. AFD has the potential to provide specific information regarding differences between populations by identifying not only the location, but also the orientations along which differences exist. In this work, analytical and numerical Monte-Carlo simulations are used to support the use of the FOD amplitude as a quantitative measure (i.e. AFD) for population and longitudinal analysis. To perform robust voxel-based analysis of AFD, we present and evaluate a novel method to modulate the FOD to account for changes in fibre bundle cross-sectional area that occur during spatial normalisation. We then describe a novel approach for statistical analysis of AFD that uses cluster-based inference of differences extended throughout space and orientation. Finally, we demonstrate the capability of the proposed method by performing voxel-based AFD comparisons between a group of Motor Neurone Disease patients and healthy control subjects. A significant decrease in AFD was detected along voxels and orientations corresponding to both the corticospinal tract and corpus callosal fibres that connect the primary motor cortices. In addition to corroborating previous findings in MND, this study demonstrates the clear advantage of using this type of analysis by identifying differences along single fibre bundles in regions containing multiple fibre populations. Copyright © 2011 Elsevier Inc. All rights reserved.

Widespread Signals of Convergent Adaptation to High Altitude in Asia and America

PubMed Central

Foll, Matthieu; Gaggiotti, Oscar E.; Daub, Josephine T.; Vatsiou, Alexandra; Excoffier, Laurent

2014-01-01

Living at high altitude is one of the most difficult challenges that humans had to cope with during their evolution. Whereas several genomic studies have revealed some of the genetic bases of adaptations in Tibetan, Andean, and Ethiopian populations, relatively little evidence of convergent evolution to altitude in different continents has accumulated. This lack of evidence can be due to truly different evolutionary responses, but it can also be due to the low power of former studies that have mainly focused on populations from a single geographical region or performed separate analyses on multiple pairs of populations to avoid problems linked to shared histories between some populations. We introduce here a hierarchical Bayesian method to detect local adaptation that can deal with complex demographic histories. Our method can identify selection occurring at different scales, as well as convergent adaptation in different regions. We apply our approach to the analysis of a large SNP data set from low- and high-altitude human populations from America and Asia. The simultaneous analysis of these two geographic areas allows us to identify several candidate genome regions for altitudinal selection, and we show that convergent evolution among continents has been quite common. In addition to identifying several genes and biological processes involved in high-altitude adaptation, we identify two specific biological pathways that could have evolved in both continents to counter toxic effects induced by hypoxia. PMID:25262650

Metric Selection for Evaluation of Human Supervisory Control Systems

DTIC Science & Technology

2009-12-01

finding a significant effect when there is none becomes more likely. The inflation of type I error due to multiple dependent variables can be handled...with multivariate analysis techniques, such as Multivariate Analysis of Variance (MANOVA) (Johnson & Wichern, 2002). However, it should be noted that...the few significant differences among many insignificant ones. The best way to avoid failure to identify significant differences is to design an

Combining Different Tools for EEG Analysis to Study the Distributed Character of Language Processing

PubMed Central

da Rocha, Armando Freitas; Foz, Flávia Benevides; Pereira, Alfredo

2015-01-01

Recent studies on language processing indicate that language cognition is better understood if assumed to be supported by a distributed intelligent processing system enrolling neurons located all over the cortex, in contrast to reductionism that proposes to localize cognitive functions to specific cortical structures. Here, brain activity was recorded using electroencephalogram while volunteers were listening or reading small texts and had to select pictures that translate meaning of these texts. Several techniques for EEG analysis were used to show this distributed character of neuronal enrollment associated with the comprehension of oral and written descriptive texts. Low Resolution Tomography identified the many different sets (s i) of neurons activated in several distinct cortical areas by text understanding. Linear correlation was used to calculate the information H(e i) provided by each electrode of the 10/20 system about the identified s i. H(e i) Principal Component Analysis (PCA) was used to study the temporal and spatial activation of these sources s i. This analysis evidenced 4 different patterns of H(e i) covariation that are generated by neurons located at different cortical locations. These results clearly show that the distributed character of language processing is clearly evidenced by combining available EEG technologies. PMID:26713089

Combining Different Tools for EEG Analysis to Study the Distributed Character of Language Processing.

PubMed

Rocha, Armando Freitas da; Foz, Flávia Benevides; Pereira, Alfredo

2015-01-01

Recent studies on language processing indicate that language cognition is better understood if assumed to be supported by a distributed intelligent processing system enrolling neurons located all over the cortex, in contrast to reductionism that proposes to localize cognitive functions to specific cortical structures. Here, brain activity was recorded using electroencephalogram while volunteers were listening or reading small texts and had to select pictures that translate meaning of these texts. Several techniques for EEG analysis were used to show this distributed character of neuronal enrollment associated with the comprehension of oral and written descriptive texts. Low Resolution Tomography identified the many different sets (s i ) of neurons activated in several distinct cortical areas by text understanding. Linear correlation was used to calculate the information H(e i ) provided by each electrode of the 10/20 system about the identified s i . H(e i ) Principal Component Analysis (PCA) was used to study the temporal and spatial activation of these sources s i . This analysis evidenced 4 different patterns of H(e i ) covariation that are generated by neurons located at different cortical locations. These results clearly show that the distributed character of language processing is clearly evidenced by combining available EEG technologies.

Moral distress and burnout syndrome: are there relationships between these phenomena in nursing workers?

PubMed

Dalmolin, Graziele de Lima; Lunardi, Valéria Lerch; Lunardi, Guilherme Lerch; Barlem, Edison Luiz Devos; Silveira, Rosemary Silva da

2014-01-01

to identify relationships between moral distress and Burnout in the professional performance from the perceptions of the experiences of nursing workers. this is a survey type study with 375 nursing workers working in three different hospitals of southern Rio Grande do Sul, with the application of adaptations of the Moral Distress Scale and the Maslach Burnout Inventory, validated and standardized for use in Brazil. Data validation occurred through factor analysis and Cronbach's alpha. For the data analysis bivariate analysis using Pearson's correlation and multivariate analysis using multiple regression were performed. the existence of a weak correlation between moral distress and Burnout was verified. A possible positive correlation between Burnout and therapeutic obstinacy, and a negative correlation between professional fulfillment and moral distress were identified. the need was identified for further studies that include mediating and moderating variables that may explain more clearly the models studied.

Moral distress and Burnout syndrome: are there relationships between these phenomena in nursing workers?1

PubMed Central

Dalmolin, Graziele de Lima; Lunardi, Valéria Lerch; Lunardi, Guilherme Lerch; Barlem, Edison Luiz Devos; da Silveira, Rosemary Silva

2014-01-01

Objective to identify relationships between moral distress and Burnout in the professional performance from the perceptions of the experiences of nursing workers. Methods this is a survey type study with 375 nursing workers working in three different hospitals of southern Rio Grande do Sul, with the application of adaptations of the Moral Distress Scale and the Maslach Burnout Inventory, validated and standardized for use in Brazil. Data validation occurred through factor analysis and Cronbach's alpha. For the data analysis bivariate analysis using Pearson's correlation and multivariate analysis using multiple regression were performed. Results the existence of a weak correlation between moral distress and Burnout was verified. A possible positive correlation between Burnout and therapeutic obstinacy, and a negative correlation between professional fulfillment and moral distress were identified. Conclusion the need was identified for further studies that include mediating and moderating variables that may explain more clearly the models studied. PMID:24553701

A qualitative study describing nursing home nurses sensemaking to detect medication order discrepancies.

PubMed

Vogelsmeier, Amy; Anderson, Ruth A; Anbari, Allison; Ganong, Lawrence; Farag, Amany; Niemeyer, MaryAnn

2017-08-04

Medication reconciliation is a safety practice to identify medication order discrepancies when patients' transitions between settings. In nursing homes, registered nurses (RNs) and licensed practical nurses (LPNs), each group with different education preparation and scope of practice responsibilities, perform medication reconciliation. However, little is known about how they differ in practice when making sense of medication orders to detect discrepancies. Therefore, the purpose of this study was to describe differences in RN and LPN sensemaking when detecting discrepancies. We used a qualitative methodology in a study of 13 RNs and 13 LPNs working in 12 Midwestern United States nursing homes. We used both conventional content analysis and directed content analysis methods to analyze semi-structured interviews. Four resident transfer vignettes embedded with medication order discrepancies guided the interviews. Participants were asked to describe their roles with medication reconciliation and their rationale for identifying medication order discrepancies within the vignettes as well as to share their experiences of performing medication reconciliation. The analysis approach was guided by Weick's Sensemaking theory. RNs provided explicit stories of identifying medication order discrepancies as well as examples of clinical reasoning to assure medication order appropriateness whereas LPNs described comparing medication lists. RNs and LPNs both acknowledged competing demands, but when performing medication reconciliation, RNs were more concerned about accuracy and safety, whereas LPNs were more concerned about time. Nursing home nurses, particularly RNs, are in an important position to identify discrepancies that could cause resident harm. Both RNs and LPNs are valuable assets to nursing home care and keeping residents safe, yet RNs offer a unique contribution to complex processes such as medication reconciliation. Nursing home leaders must acknowledge the differences in RN and LPN contributions and make certain nurses in the most qualified role are assigned to ensure residents remain safe.

Identification of evolutionarily conserved Momordica charantia microRNAs using computational approach and its utility in phylogeny analysis.

PubMed

Thirugnanasambantham, Krishnaraj; Saravanan, Subramanian; Karikalan, Kulandaivelu; Bharanidharan, Rajaraman; Lalitha, Perumal; Ilango, S; HairulIslam, Villianur Ibrahim

2015-10-01

Momordica charantia (bitter gourd, bitter melon) is a monoecious Cucurbitaceae with anti-oxidant, anti-microbial, anti-viral and anti-diabetic potential. Molecular studies on this economically valuable plant are very essential to understand its phylogeny and evolution. MicroRNAs (miRNAs) are conserved, small, non-coding RNA with ability to regulate gene expression by bind the 3' UTR region of target mRNA and are evolved at different rates in different plant species. In this study we have utilized homology based computational approach and identified 27 mature miRNAs for the first time from this bio-medically important plant. The phylogenetic tree developed from binary data derived from the data on presence/absence of the identified miRNAs were noticed to be uncertain and biased. Most of the identified miRNAs were highly conserved among the plant species and sequence based phylogeny analysis of miRNAs resolved the above difficulties in phylogeny approach using miRNA. Predicted gene targets of the identified miRNAs revealed their importance in regulation of plant developmental process. Reported miRNAs held sequence conservation in mature miRNAs and the detailed phylogeny analysis of pre-miRNA sequences revealed genus specific segregation of clusters. Copyright © 2015 Elsevier Ltd. All rights reserved.

Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer.

PubMed

Phelan, Catherine M; Kuchenbaecker, Karoline B; Tyrer, Jonathan P; Kar, Siddhartha P; Lawrenson, Kate; Winham, Stacey J; Dennis, Joe; Pirie, Ailith; Riggan, Marjorie J; Chornokur, Ganna; Earp, Madalene A; Lyra, Paulo C; Lee, Janet M; Coetzee, Simon; Beesley, Jonathan; McGuffog, Lesley; Soucy, Penny; Dicks, Ed; Lee, Andrew; Barrowdale, Daniel; Lecarpentier, Julie; Leslie, Goska; Aalfs, Cora M; Aben, Katja K H; Adams, Marcia; Adlard, Julian; Andrulis, Irene L; Anton-Culver, Hoda; Antonenkova, Natalia; Aravantinos, Gerasimos; Arnold, Norbert; Arun, Banu K; Arver, Brita; Azzollini, Jacopo; Balmaña, Judith; Banerjee, Susana N; Barjhoux, Laure; Barkardottir, Rosa B; Bean, Yukie; Beckmann, Matthias W; Beeghly-Fadiel, Alicia; Benitez, Javier; Bermisheva, Marina; Bernardini, Marcus Q; Birrer, Michael J; Bjorge, Line; Black, Amanda; Blankstein, Kenneth; Blok, Marinus J; Bodelon, Clara; Bogdanova, Natalia; Bojesen, Anders; Bonanni, Bernardo; Borg, Åke; Bradbury, Angela R; Brenton, James D; Brewer, Carole; Brinton, Louise; Broberg, Per; Brooks-Wilson, Angela; Bruinsma, Fiona; Brunet, Joan; Buecher, Bruno; Butzow, Ralf; Buys, Saundra S; Caldes, Trinidad; Caligo, Maria A; Campbell, Ian; Cannioto, Rikki; Carney, Michael E; Cescon, Terence; Chan, Salina B; Chang-Claude, Jenny; Chanock, Stephen; Chen, Xiao Qing; Chiew, Yoke-Eng; Chiquette, Jocelyne; Chung, Wendy K; Claes, Kathleen B M; Conner, Thomas; Cook, Linda S; Cook, Jackie; Cramer, Daniel W; Cunningham, Julie M; D'Aloisio, Aimee A; Daly, Mary B; Damiola, Francesca; Damirovna, Sakaeva Dina; Dansonka-Mieszkowska, Agnieszka; Dao, Fanny; Davidson, Rosemarie; DeFazio, Anna; Delnatte, Capucine; Doheny, Kimberly F; Diez, Orland; Ding, Yuan Chun; Doherty, Jennifer Anne; Domchek, Susan M; Dorfling, Cecilia M; Dörk, Thilo; Dossus, Laure; Duran, Mercedes; Dürst, Matthias; Dworniczak, Bernd; Eccles, Diana; Edwards, Todd; Eeles, Ros; Eilber, Ursula; Ejlertsen, Bent; Ekici, Arif B; Ellis, Steve; Elvira, Mingajeva; Eng, Kevin H; Engel, Christoph; Evans, D Gareth; Fasching, Peter A; Ferguson, Sarah; Ferrer, Sandra Fert; Flanagan, James M; Fogarty, Zachary C; Fortner, Renée T; Fostira, Florentia; Foulkes, William D; Fountzilas, George; Fridley, Brooke L; Friebel, Tara M; Friedman, Eitan; Frost, Debra; Ganz, Patricia A; Garber, Judy; García, María J; Garcia-Barberan, Vanesa; Gehrig, Andrea; Gentry-Maharaj, Aleksandra; Gerdes, Anne-Marie; Giles, Graham G; Glasspool, Rosalind; Glendon, Gord; Godwin, Andrew K; Goldgar, David E; Goranova, Teodora; Gore, Martin; Greene, Mark H; Gronwald, Jacek; Gruber, Stephen; Hahnen, Eric; Haiman, Christopher A; Håkansson, Niclas; Hamann, Ute; Hansen, Thomas V O; Harrington, Patricia A; Harris, Holly R; Hauke, Jan; Hein, Alexander; Henderson, Alex; Hildebrandt, Michelle A T; Hillemanns, Peter; Hodgson, Shirley; Høgdall, Claus K; Høgdall, Estrid; Hogervorst, Frans B L; Holland, Helene; Hooning, Maartje J; Hosking, Karen; Huang, Ruea-Yea; Hulick, Peter J; Hung, Jillian; Hunter, David J; Huntsman, David G; Huzarski, Tomasz; Imyanitov, Evgeny N; Isaacs, Claudine; Iversen, Edwin S; Izatt, Louise; Izquierdo, Angel; Jakubowska, Anna; James, Paul; Janavicius, Ramunas; Jernetz, Mats; Jensen, Allan; Jensen, Uffe Birk; John, Esther M; Johnatty, Sharon; Jones, Michael E; Kannisto, Päivi; Karlan, Beth Y; Karnezis, Anthony; Kast, Karin; Kennedy, Catherine J; Khusnutdinova, Elza; Kiemeney, Lambertus A; Kiiski, Johanna I; Kim, Sung-Won; Kjaer, Susanne K; Köbel, Martin; Kopperud, Reidun K; Kruse, Torben A; Kupryjanczyk, Jolanta; Kwong, Ava; Laitman, Yael; Lambrechts, Diether; Larrañaga, Nerea; Larson, Melissa C; Lazaro, Conxi; Le, Nhu D; Le Marchand, Loic; Lee, Jong Won; Lele, Shashikant B; Leminen, Arto; Leroux, Dominique; Lester, Jenny; Lesueur, Fabienne; Levine, Douglas A; Liang, Dong; Liebrich, Clemens; Lilyquist, Jenna; Lipworth, Loren; Lissowska, Jolanta; Lu, Karen H; Lubinński, Jan; Luccarini, Craig; Lundvall, Lene; Mai, Phuong L; Mendoza-Fandiño, Gustavo; Manoukian, Siranoush; Massuger, Leon F A G; May, Taymaa; Mazoyer, Sylvie; McAlpine, Jessica N; McGuire, Valerie; McLaughlin, John R; McNeish, Iain; Meijers-Heijboer, Hanne; Meindl, Alfons; Menon, Usha; Mensenkamp, Arjen R; Merritt, Melissa A; Milne, Roger L; Mitchell, Gillian; Modugno, Francesmary; Moes-Sosnowska, Joanna; Moffitt, Melissa; Montagna, Marco; Moysich, Kirsten B; Mulligan, Anna Marie; Musinsky, Jacob; Nathanson, Katherine L; Nedergaard, Lotte; Ness, Roberta B; Neuhausen, Susan L; Nevanlinna, Heli; Niederacher, Dieter; Nussbaum, Robert L; Odunsi, Kunle; Olah, Edith; Olopade, Olufunmilayo I; Olsson, Håkan; Olswold, Curtis; O'Malley, David M; Ong, Kai-Ren; Onland-Moret, N Charlotte; Orr, Nicholas; Orsulic, Sandra; Osorio, Ana; Palli, Domenico; Papi, Laura; Park-Simon, Tjoung-Won; Paul, James; Pearce, Celeste L; Pedersen, Inge Søkilde; Peeters, Petra H M; Peissel, Bernard; Peixoto, Ana; Pejovic, Tanja; Pelttari, Liisa M; Permuth, Jennifer B; Peterlongo, Paolo; Pezzani, Lidia; Pfeiler, Georg; Phillips, Kelly-Anne; Piedmonte, Marion; Pike, Malcolm C; Piskorz, Anna M; Poblete, Samantha R; Pocza, Timea; Poole, Elizabeth M; Poppe, Bruce; Porteous, Mary E; Prieur, Fabienne; Prokofyeva, Darya; Pugh, Elizabeth; Pujana, Miquel Angel; Pujol, Pascal; Radice, Paolo; Rantala, Johanna; Rappaport-Fuerhauser, Christine; Rennert, Gad; Rhiem, Kerstin; Rice, Patricia; Richardson, Andrea; Robson, Mark; Rodriguez, Gustavo C; Rodríguez-Antona, Cristina; Romm, Jane; Rookus, Matti A; Rossing, Mary Anne; Rothstein, Joseph H; Rudolph, Anja; Runnebaum, Ingo B; Salvesen, Helga B; Sandler, Dale P; Schoemaker, Minouk J; Senter, Leigha; Setiawan, V Wendy; Severi, Gianluca; Sharma, Priyanka; Shelford, Tameka; Siddiqui, Nadeem; Side, Lucy E; Sieh, Weiva; Singer, Christian F; Sobol, Hagay; Song, Honglin; Southey, Melissa C; Spurdle, Amanda B; Stadler, Zsofia; Steinemann, Doris; Stoppa-Lyonnet, Dominique; Sucheston-Campbell, Lara E; Sukiennicki, Grzegorz; Sutphen, Rebecca; Sutter, Christian; Swerdlow, Anthony J; Szabo, Csilla I; Szafron, Lukasz; Tan, Yen Y; Taylor, Jack A; Tea, Muy-Kheng; Teixeira, Manuel R; Teo, Soo-Hwang; Terry, Kathryn L; Thompson, Pamela J; Thomsen, Liv Cecilie Vestrheim; Thull, Darcy L; Tihomirova, Laima; Tinker, Anna V; Tischkowitz, Marc; Tognazzo, Silvia; Toland, Amanda Ewart; Tone, Alicia; Trabert, Britton; Travis, Ruth C; Trichopoulou, Antonia; Tung, Nadine; Tworoger, Shelley S; van Altena, Anne M; Van Den Berg, David; van der Hout, Annemarie H; van der Luijt, Rob B; Van Heetvelde, Mattias; Van Nieuwenhuysen, Els; van Rensburg, Elizabeth J; Vanderstichele, Adriaan; Varon-Mateeva, Raymonda; Vega, Ana; Edwards, Digna Velez; Vergote, Ignace; Vierkant, Robert A; Vijai, Joseph; Vratimos, Athanassios; Walker, Lisa; Walsh, Christine; Wand, Dorothea; Wang-Gohrke, Shan; Wappenschmidt, Barbara; Webb, Penelope M; Weinberg, Clarice R; Weitzel, Jeffrey N; Wentzensen, Nicolas; Whittemore, Alice S; Wijnen, Juul T; Wilkens, Lynne R; Wolk, Alicja; Woo, Michelle; Wu, Xifeng; Wu, Anna H; Yang, Hannah; Yannoukakos, Drakoulis; Ziogas, Argyrios; Zorn, Kristin K; Narod, Steven A; Easton, Douglas F; Amos, Christopher I; Schildkraut, Joellen M; Ramus, Susan J; Ottini, Laura; Goodman, Marc T; Park, Sue K; Kelemen, Linda E; Risch, Harvey A; Thomassen, Mads; Offit, Kenneth; Simard, Jacques; Schmutzler, Rita Katharina; Hazelett, Dennis; Monteiro, Alvaro N; Couch, Fergus J; Berchuck, Andrew; Chenevix-Trench, Georgia; Goode, Ellen L; Sellers, Thomas A; Gayther, Simon A; Antoniou, Antonis C; Pharoah, Paul D P

2017-05-01

To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC.

Using Refined Regression Analysis To Assess The Ecological Services Of Restored Wetlands

EPA Science Inventory

A hierarchical approach to regression analysis of wetland water treatment was conducted to determine which factors are the most appropriate for characterizing wetlands of differing structure and function. We used this approach in an effort to identify the types and characteristi...

Use of stable isotope analysis in determining aquatic food webs

EPA Science Inventory

Stable isotope analysis is a useful tool for describing resource-consumer dynamics in ecosystems. In general, organisms of a given trophic level or functional feeding group will have a stable isotope ratio identifiable different than their prey because of preferential use of one ...

Angel or Devil? Dentists and Dental Students Conceptions of Pediatric Dental Patients through Metaphor Analysis.

PubMed

Buldur, B

The aim of this qualitative study was to identify the conceptions of dentists and dental students (DSs) about pediatric dental patients (PDPs) using metaphor analysis. The study group (N = 259) consisted of dentists and DSs. Participants completed the sentence "A pediatric dental patient is like ... because …..." in order to reveal the metaphors they use about the concept of PDPs. The data were analyzed using the mixed-methods: qualitative (metaphor analysis) and quantitative (chi-square) data analysis techniques. The dentists and DSs produced 259 metaphors. These metaphors were gathered under six different conceptual categories that define a PDP as unpredictable, dangerous, uncontrollable, requiring care and sensitivity, valuable, and orientable. The most important factors leading to these conceptions were the uncooperativeness of some PDPs and the effectiveness of behavior management. The results of this study indicate that there was no significant difference among DSs, general dentists and specialist dentists with respect to six conceptual categories that identify the conceptions about PDPs.

Analysis of human nails by laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Hosseinimakarem, Zahra; Tavassoli, Seyed Hassan

2011-05-01

Laser-induced breakdown spectroscopy (LIBS) is applied to analyze human fingernails using nanosecond laser pulses. Measurements on 45 nail samples are carried out and 14 key species are identified. The elements detected with the present system are: Al, C, Ca, Fe, H, K, Mg, N, Na, O, Si, Sr, Ti as well as CN molecule. Sixty three emission lines have been identified in the spectrum that are dominated by calcium lines. A discriminant function analysis is used to discriminate among different genders and age groups. This analysis demonstrates efficient discrimination among these groups. The mean concentration of each element is compared between different groups. Correlation between concentrations of elements in fingernails is calculated. A strong correlation is found between sodium and potassium while calcium and magnesium levels are inversely correlated. A case report on high levels of sodium and potassium in patients with hyperthyroidism is presented. It is shown that LIBS could be a promising technique for the analysis of nails and therefore identification of health problems.

Image analysis technique as a tool to identify morphological changes in Trametes versicolor pellets according to exopolysaccharide or laccase production.

PubMed

Tavares, Ana P M; Silva, Rui P; Amaral, António L; Ferreira, Eugénio C; Xavier, Ana M R B

2014-02-01

Image analysis technique was applied to identify morphological changes of pellets from white-rot fungus Trametes versicolor on agitated submerged cultures during the production of exopolysaccharide (EPS) or ligninolytic enzymes. Batch tests with four different experimental conditions were carried out. Two different culture media were used, namely yeast medium or Trametes defined medium and the addition of lignolytic inducers as xylidine or pulp and paper industrial effluent were evaluated. Laccase activity, EPS production, and final biomass contents were determined for batch assays and the pellets morphology was assessed by image analysis techniques. The obtained data allowed establishing the choice of the metabolic pathways according to the experimental conditions, either for laccase enzymatic production in the Trametes defined medium, or for EPS production in the rich Yeast Medium experiments. Furthermore, the image processing and analysis methodology allowed for a better comprehension of the physiological phenomena with respect to the corresponding pellets morphological stages.

The Cuban scorpion Rhopalurus junceus (Scorpiones, Buthidae): component variations in venom samples collected in different geographical areas

PubMed Central

2013-01-01

Backgound The venom of the Cuban scorpion Rhopalurus junceus is poorly study from the point of view of their components at molecular level and the functions associated. The purpose of this article was to conduct a proteomic analysis of venom components from scorpions collected in different geographical areas of the country. Results Venom from the blue scorpion, as it is called, was collected separately from specimens of five distinct Cuban towns (Moa, La Poa, Limonar, El Chote and Farallones) of the Nipe-Sagua-Baracoa mountain massif and fractionated by high performance liquid chromatography (HPLC); the molecular masses of each fraction were ascertained by mass spectrometry analysis. At least 153 different molecular mass components were identified among the five samples analyzed. Molecular masses varied from 466 to 19755 Da. Scorpion HPLC profiles differed among these different geographical locations and the predominant molecular masses of their components. The most evident differences are in the relative concentration of the venom components. The most abundant components presented molecular weights around 4 kDa, known to be K+-channel specific peptides, and 7 kDa, known to be Na+-channel specific peptides, but with small molecular weight differences. Approximately 30 peptides found in venom samples from the different geographical areas are identical, supporting the idea that they all probably belong to the same species, with some interpopulational variations. Differences were also found in the presence of phospholipase, found in venoms from the Poa area (molecular weights on the order of 14 to 19 kDa). The only ubiquitous enzyme identified in the venoms from all five localities studied (hyaluronidase) presented the same 45 kD molecular mass, identified by gel electrophoresis analysis. Conclusions The venom of these scorpions from different geographical areas seem to be similar, and are rich in peptides that have of the same molecular masses of the peptides purified from other scorpions that affect ion-channel functions. PMID:23849540

Geographic atrophy phenotype identification by cluster analysis.

PubMed

Monés, Jordi; Biarnés, Marc

2018-03-01

To identify ocular phenotypes in patients with geographic atrophy secondary to age-related macular degeneration (GA) using a data-driven cluster analysis. This was a retrospective analysis of data from a prospective, natural history study of patients with GA who were followed for ≥6 months. Cluster analysis was used to identify subgroups within the population based on the presence of several phenotypic features: soft drusen, reticular pseudodrusen (RPD), primary foveal atrophy, increased fundus autofluorescence (FAF), greyish FAF appearance and subfoveal choroidal thickness (SFCT). A comparison of features between the subgroups was conducted, and a qualitative description of the new phenotypes was proposed. The atrophy growth rate between phenotypes was then compared. Data were analysed from 77 eyes of 77 patients with GA. Cluster analysis identified three groups: phenotype 1 was characterised by high soft drusen load, foveal atrophy and slow growth; phenotype 3 showed high RPD load, extrafoveal and greyish FAF appearance and thin SFCT; the characteristics of phenotype 2 were midway between phenotypes 1 and 3. Phenotypes differed in all measured features (p≤0.013), with decreases in the presence of soft drusen, foveal atrophy and SFCT seen from phenotypes 1 to 3 and corresponding increases in high RPD load, high FAF and greyish FAF appearance. Atrophy growth rate differed between phenotypes 1, 2 and 3 (0.63, 1.91 and 1.73 mm 2 /year, respectively, p=0.0005). Cluster analysis identified three distinct phenotypes in GA. One of them showed a particularly slow growth pattern. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Toward Enhancing Automated Credibility Assessment: A Model for Question Type Classification and Tools for Linguistic Analysis

ERIC Educational Resources Information Center

Moffitt, Kevin Christopher

2011-01-01

The three objectives of this dissertation were to develop a question type model for predicting linguistic features of responses to interview questions, create a tool for linguistic analysis of documents, and use lexical bundle analysis to identify linguistic differences between fraudulent and non-fraudulent financial reports. First, The Moffitt…

Healthcare waste management: an interpretive structural modeling approach.

PubMed

Thakur, Vikas; Anbanandam, Ramesh

2016-06-13

Purpose - The World Health Organization identified infectious healthcare waste as a threat to the environment and human health. India's current medical waste management system has limitations, which lead to ineffective and inefficient waste handling practices. Hence, the purpose of this paper is to: first, identify the important barriers that hinder India's healthcare waste management (HCWM) systems; second, classify operational, tactical and strategical issues to discuss the managerial implications at different management levels; and third, define all barriers into four quadrants depending upon their driving and dependence power. Design/methodology/approach - India's HCWM system barriers were identified through the literature, field surveys and brainstorming sessions. Interrelationships among all the barriers were analyzed using interpretive structural modeling (ISM). Fuzzy-Matrice d'Impacts Croisés Multiplication Appliquée á un Classement (MICMAC) analysis was used to classify HCWM barriers into four groups. Findings - In total, 25 HCWM system barriers were identified and placed in 12 different ISM model hierarchy levels. Fuzzy-MICMAC analysis placed eight barriers in the second quadrant, five in third and 12 in fourth quadrant to define their relative ISM model importance. Research limitations/implications - The study's main limitation is that all the barriers were identified through a field survey and barnstorming sessions conducted only in Uttarakhand, Northern State, India. The problems in implementing HCWM practices may differ with the region, hence, the current study needs to be replicated in different Indian states to define the waste disposal strategies for hospitals. Practical implications - The model will help hospital managers and Pollution Control Boards, to plan their resources accordingly and make policies, targeting key performance areas. Originality/value - The study is the first attempt to identify India's HCWM system barriers and prioritize them.

Suicide in the oldest old: an observational study and cluster analysis.

PubMed

Sinyor, Mark; Tan, Lynnette Pei Lin; Schaffer, Ayal; Gallagher, Damien; Shulman, Kenneth

2016-01-01

The older population are at a high risk for suicide. This study sought to learn more about the characteristics of suicide in the oldest-old and to use a cluster analysis to determine if oldest-old suicide victims assort into clinically meaningful subgroups. Data were collected from a coroner's chart review of suicide victims in Toronto from 1998 to 2011. We compared two age groups (65-79 year olds, n = 335, and 80+ year olds, n = 191) and then conducted a hierarchical agglomerative cluster analysis using Ward's method to identify distinct clusters in the 80+ group. The younger and older age groups differed according to marital status, living circumstances and pattern of stressors. The cluster analysis identified three distinct clusters in the 80+ group. Cluster 1 was the largest (n = 124) and included people who were either married or widowed who had significantly more depression and somewhat more medical health stressors. In contrast, cluster 2 (n = 50) comprised people who were almost all single and living alone with significantly less identified depression and slightly fewer medical health stressors. All members of cluster 3 (n = 17) lived in a retirement residence or nursing home, and this group had the highest rates of depression, dementia, other mental illness and past suicide attempts. This is the first study to use the cluster analysis technique to identify meaningful subgroups among suicide victims in the oldest-old. The results reveal different patterns of suicide in the older population that may be relevant for clinical care. Copyright © 2015 John Wiley & Sons, Ltd.

Paths to tobacco abstinence: A repeated-measures latent class analysis.

PubMed

McCarthy, Danielle E; Ebssa, Lemma; Witkiewitz, Katie; Shiffman, Saul

2015-08-01

Knowledge of smoking change processes may be enhanced by identifying pathways to stable abstinence. We sought to identify latent classes of smokers based on their day-to-day smoking status in the first weeks of a cessation attempt. We examined treatment effects on class membership and compared classes on baseline individual differences and 6-month abstinence rates. In this secondary analysis of a double-blind randomized placebo-controlled clinical trial (N = 1,433) of 5 smoking cessation pharmacotherapies (nicotine patch, nicotine lozenge, bupropion SR, patch and lozenge, or bupropion SR and lozenge), we conducted repeated-measures latent class analysis of daily smoking status (any smoking vs. none) for the first 27 days of a quit attempt. Treatment and covariate relations with latent class membership were examined. Distal outcome analysis compared confirmed 6-month abstinence rates among the latent classes. A 5-class solution was selected. Three-quarters of smokers were in stable smoking or abstinent classes, but 25% were in classes with unstable abstinence probabilities over time. Active treatment (compared to placebo), and particularly the patch and lozenge combination, promoted early quitting. Latent classes differed in 6-month abstinence rates and on several baseline variables, including nicotine dependence, quitting history, self-efficacy, sleep disturbance, and minority status. Repeated-measures latent class analysis identified latent classes of smoking change patterns affected by treatment, related to known risk factors, and predictive of distal outcomes. Tracking behavior early in a change attempt may identify prognostic patterns of change and facilitate adaptive treatment planning. (c) 2015 APA, all rights reserved).

On the performance of tests for the detection of signatures of selection: a case study with the Spanish autochthonous beef cattle populations.

PubMed

González-Rodríguez, Aldemar; Munilla, Sebastián; Mouresan, Elena F; Cañas-Álvarez, Jhon J; Díaz, Clara; Piedrafita, Jesús; Altarriba, Juan; Baro, Jesús Á; Molina, Antonio; Varona, Luis

2016-10-28

Procedures for the detection of signatures of selection can be classified according to the source of information they use to reject the null hypothesis of absence of selection. Three main groups of tests can be identified that are based on: (1) the analysis of the site frequency spectrum, (2) the study of the extension of the linkage disequilibrium across the length of the haplotypes that surround the polymorphism, and (3) the differentiation among populations. The aim of this study was to compare the performance of a subset of these procedures by using a dataset on seven Spanish autochthonous beef cattle populations. Analysis of the correlations between the logarithms of the statistics that were obtained by 11 tests for detecting signatures of selection at each single nucleotide polymorphism confirmed that they can be clustered into the three main groups mentioned above. A factor analysis summarized the results of the 11 tests into three canonical axes that were each associated with one of the three groups. Moreover, the signatures of selection identified with the first and second groups of tests were shared across populations, whereas those with the third group were more breed-specific. Nevertheless, an enrichment analysis identified the metabolic pathways that were associated with each group; they coincided with canonical axes and were related to immune response, muscle development, protein biosynthesis, skin and pigmentation, glucose metabolism, fat metabolism, embryogenesis and morphology, heart and uterine metabolism, regulation of the hypothalamic-pituitary-thyroid axis, hormonal, cellular cycle, cell signaling and extracellular receptors. We show that the results of the procedures used to identify signals of selection differed substantially between the three groups of tests. However, they can be classified using a factor analysis. Moreover, each canonical factor that coincided with a group of tests identified different signals of selection, which could be attributed to processes of selection that occurred at different evolutionary times. Nevertheless, the metabolic pathways that were associated with each group of tests were similar, which suggests that the selection events that occurred during the evolutionary history of the populations probably affected the same group of traits.

Typing of the rabies virus in Chile, 2002-2008.

PubMed

Yung, V; Favi, M; Fernandez, J

2012-12-01

In Chile, dog rabies has been controlled and insectivorous bats have been identified as the main rabies reservoir. This study aimed to determine the rabies virus (RABV) variants circulating in the country between 2002 and 2008. A total of 612 RABV isolates were tested using a panel with eight monoclonal antibodies against the viral nucleoprotein (N-mAbs) for antigenic typing, and a product of 320-bp of the nucleoprotein gene was sequenced from 99 isolates. Typing of the isolates revealed six different antigenic variants but phylogenetic analysis identified four clusters associated with four different bat species. Tadarida brasiliensis bats were confirmed as the main reservoir. This methodology identified several independent rabies enzootics maintained by different species of insectivorous bats in Chile.

Species identification of corynebacteria by cellular fatty acid analysis.

PubMed

Van den Velde, Sandra; Lagrou, Katrien; Desmet, Koen; Wauters, Georges; Verhaegen, Jan

2006-02-01

We evaluated the usefulness of cellular fatty acid analysis for the identification of corynebacteria. Therefore, 219 well-characterized strains belonging to 21 Corynebacterium species were analyzed with the Sherlock System of MIDI (Newark, DE). Most Corynebacterium species have a qualitative different fatty acid profile. Corynebacterium coyleae (subgroup 1), Corynebacterium riegelii, Corynebacterium simulans, and Corynebacterium imitans differ only quantitatively. Corynebacterium afermentans afermentans and C. coyleae (subgroup 2) have both a similar qualitative and quantitative profile. The commercially available database (CLIN 40, MIDI) identified only one third of the 219 strains correctly at the species level. We created a new database with these 219 strains. This new database was tested with 34 clinical isolates and could identify 29 strains correctly. Strains that remained unidentified were 2 Corynebacterium aurimucosum (not included in our database), 1 C. afermentans afermentans, and 2 Corynebacterium pseudodiphtheriticum. Cellular fatty acid analysis with a self-created database can be used for the identification and differentiation of corynebacteria.

Transcriptomic analysis of Arabidopsis developing stems: a close-up on cell wall genes

PubMed Central

Minic, Zoran; Jamet, Elisabeth; San-Clemente, Hélène; Pelletier, Sandra; Renou, Jean-Pierre; Rihouey, Christophe; Okinyo, Denis PO; Proux, Caroline; Lerouge, Patrice; Jouanin, Lise

2009-01-01

Background Different strategies (genetics, biochemistry, and proteomics) can be used to study proteins involved in cell biogenesis. The availability of the complete sequences of several plant genomes allowed the development of transcriptomic studies. Although the expression patterns of some Arabidopsis thaliana genes involved in cell wall biogenesis were identified at different physiological stages, detailed microarray analysis of plant cell wall genes has not been performed on any plant tissues. Using transcriptomic and bioinformatic tools, we studied the regulation of cell wall genes in Arabidopsis stems, i.e. genes encoding proteins involved in cell wall biogenesis and genes encoding secreted proteins. Results Transcriptomic analyses of stems were performed at three different developmental stages, i.e., young stems, intermediate stage, and mature stems. Many genes involved in the synthesis of cell wall components such as polysaccharides and monolignols were identified. A total of 345 genes encoding predicted secreted proteins with moderate or high level of transcripts were analyzed in details. The encoded proteins were distributed into 8 classes, based on the presence of predicted functional domains. Proteins acting on carbohydrates and proteins of unknown function constituted the two most abundant classes. Other proteins were proteases, oxido-reductases, proteins with interacting domains, proteins involved in signalling, and structural proteins. Particularly high levels of expression were established for genes encoding pectin methylesterases, germin-like proteins, arabinogalactan proteins, fasciclin-like arabinogalactan proteins, and structural proteins. Finally, the results of this transcriptomic analyses were compared with those obtained through a cell wall proteomic analysis from the same material. Only a small proportion of genes identified by previous proteomic analyses were identified by transcriptomics. Conversely, only a few proteins encoded by genes having moderate or high level of transcripts were identified by proteomics. Conclusion Analysis of the genes predicted to encode cell wall proteins revealed that about 345 genes had moderate or high levels of transcripts. Among them, we identified many new genes possibly involved in cell wall biogenesis. The discrepancies observed between results of this transcriptomic study and a previous proteomic study on the same material revealed post-transcriptional mechanisms of regulation of expression of genes encoding cell wall proteins. PMID:19149885

[Process management in the hospital pharmacy for the improvement of the patient safety].

PubMed

Govindarajan, R; Perelló-Juncá, A; Parès-Marimòn, R M; Serrais-Benavente, J; Ferrandez-Martí, D; Sala-Robinat, R; Camacho-Calvente, A; Campabanal-Prats, C; Solà-Anderiu, I; Sanchez-Caparrós, S; Gonzalez-Estrada, J; Martinez-Olalla, P; Colomer-Palomo, J; Perez-Mañosas, R; Rodríguez-Gallego, D

2013-01-01

To define a process management model for a hospital pharmacy in order to measure, analyse and make continuous improvements in patient safety and healthcare quality. In order to implement process management, Igualada Hospital was divided into different processes, one of which was the Hospital Pharmacy. A multidisciplinary management team was given responsibility for each process. For each sub-process one person was identified to be responsible, and a working group was formed under his/her leadership. With the help of each working group, a risk analysis using failure modes and effects analysis (FMEA) was performed, and the corresponding improvement actions were implemented. Sub-process indicators were also identified, and different process management mechanisms were introduced. The first risk analysis with FMEA produced more than thirty preventive actions to improve patient safety. Later, the weekly analysis of errors, as well as the monthly analysis of key process indicators, permitted us to monitor process results and, as each sub-process manager participated in these meetings, also to assume accountability and responsibility, thus consolidating the culture of excellence. The introduction of different process management mechanisms, with the participation of people responsible for each sub-process, introduces a participative management tool for the continuous improvement of patient safety and healthcare quality. Copyright © 2012 SECA. Published by Elsevier Espana. All rights reserved.

Influence of the Strain History on TWIP Steel Deformation Mechanisms in the Deep-Drawing Process

NASA Astrophysics Data System (ADS)

Lapovok, R.; Timokhina, I.; Mester, A.-K.; Weiss, M.; Shekhter, A.

2018-03-01

A study of preferable deformation modes on strain path and strain level in a TWIP steel sheet was performed. Different strain paths were obtained by stretch forming of specimens with various shapes and tensile tests. TEM analysis was performed on samples cut from various locations in the deformed specimens, which had different strain paths and strain levels and the preferable deformation modes were identified. Stresses caused by various strain paths were considered and an analytical analysis performed to identify the preferable deformation modes for the case of single crystal. For a single crystal, in assumption of the absence of lattice rotation, the strain path and the level of accumulated equivalent strain define the preferable deformation mode. For a polycrystalline material, such analytical analysis is not possible due to the large number of grains and, therefore, numerical simulation was employed. For the polycrystalline material, the role of strain path diminishes due to the presence of a large number of grains with random orientations and the effect of accumulated strain becomes dominant. However, at small strains the strain path still defines the level of twinning activity. TEM analysis experimentally confirmed that various deformation modes lead to different deformation strengthening mechanisms.

Using sperm morphometry and multivariate analysis to differentiate species of gray Mazama

PubMed Central

Duarte, José Maurício Barbanti

2016-01-01

There is genetic evidence that the two species of Brazilian gray Mazama, Mazama gouazoubira and Mazama nemorivaga, belong to different genera. This study identified significant differences that separated them into distinct groups, based on characteristics of the spermatozoa and ejaculate of both species. The characteristics that most clearly differentiated between the species were ejaculate colour, white for M. gouazoubira and reddish for M. nemorivaga, and sperm head dimensions. Multivariate analysis of sperm head dimension and format data accurately discriminated three groups for species with total percentage of misclassified of 0.71. The individual analysis, by animal, and the multivariate analysis have also discriminated correctly all five animals (total percentage of misclassified of 13.95%), and the canonical plot has shown three different clusters: Cluster 1, including individuals of M. nemorivaga; Cluster 2, including two individuals of M. gouazoubira; and Cluster 3, including a single individual of M. gouazoubira. The results obtained in this work corroborate the hypothesis of the formation of new genera and species for gray Mazama. Moreover, the easily applied method described herein can be used as an auxiliary tool to identify sibling species of other taxonomic groups. PMID:28018612

Influence of the Strain History on TWIP Steel Deformation Mechanisms in the Deep-Drawing Process

NASA Astrophysics Data System (ADS)

Lapovok, R.; Timokhina, I.; Mester, A.-K.; Weiss, M.; Shekhter, A.

2018-06-01

A study of preferable deformation modes on strain path and strain level in a TWIP steel sheet was performed. Different strain paths were obtained by stretch forming of specimens with various shapes and tensile tests. TEM analysis was performed on samples cut from various locations in the deformed specimens, which had different strain paths and strain levels and the preferable deformation modes were identified. Stresses caused by various strain paths were considered and an analytical analysis performed to identify the preferable deformation modes for the case of single crystal. For a single crystal, in assumption of the absence of lattice rotation, the strain path and the level of accumulated equivalent strain define the preferable deformation mode. For a polycrystalline material, such analytical analysis is not possible due to the large number of grains and, therefore, numerical simulation was employed. For the polycrystalline material, the role of strain path diminishes due to the presence of a large number of grains with random orientations and the effect of accumulated strain becomes dominant. However, at small strains the strain path still defines the level of twinning activity. TEM analysis experimentally confirmed that various deformation modes lead to different deformation strengthening mechanisms.

Holder and Topic Based Analysis of Emotions on Blog Texts: A Case Study for Bengali

NASA Astrophysics Data System (ADS)

Das, Dipankar; Bandyopadhyay, Sivaji

The paper presents an extended approach of analyzing emotions of the blog users on different topics. The rule based techniques to identify emotion holders and topics with respect to their corresponding emotional expressions helps to develop the baseline system. On the other hand, the Support Vector Machine (SVM) based supervised framework identifies the holders, topics and emotional expressions from the blog sentences by outperforming the baseline system. The existence of many to many relations between the holders and the topics with respect to Ekman's six different emotion classes has been examined using two way evaluation techniques, one is with respect to holder and other is from the perspective of topic. The results of the system were found satisfactory in comparison with the agreement of the subjective annotation. The error analysis shows that the topic of a blog at document level is not always conveyed at the sentence level. Moreover, the difficulty in identifying topic from a blog document is due to the problem of identifying some features like bigrams, Named Entities and sentiment. Thus, we employed a semantic clustering approach along with these features to identify the similarity between document level topic and sentential topic as well as to improve the results of identifying the document level topic.

Whole genome population genetics analysis of Sudanese goats identifies regions harboring genes associated with major traits.

PubMed

Rahmatalla, Siham A; Arends, Danny; Reissmann, Monika; Said Ahmed, Ammar; Wimmers, Klaus; Reyer, Henry; Brockmann, Gudrun A

2017-10-23

Sudan is endowed with a variety of indigenous goat breeds which are used for meat and milk production and which are well adapted to the local environment. The aim of the present study was to determine the genetic diversity and relationship within and between the four main Sudanese breeds of Nubian, Desert, Taggar and Nilotic goats. Using the 50 K SNP chip, 24 animals of each breed were genotyped. More than 96% of high quality SNPs were polymorphic with an average minor allele frequency of 0.3. In all breeds, no significant difference between observed (0.4) and expected (0.4) heterozygosity was found and the inbreeding coefficients (F IS ) did not differ from zero. F st coefficients for the genetic distance between breeds also did not significantly deviate from zero. In addition, the analysis of molecular variance revealed that 93% of the total variance in the examined population can be explained by differences among individuals, while only 7% result from differences between the breeds. These findings provide evidence for high genetic diversity and little inbreeding within breeds on one hand, and low diversity between breeds on the other hand. Further examinations using Nei's genetic distance and STRUCTURE analysis clustered Taggar goats distinct from the other breeds. In a principal component (PC) analysis, PC1 could separate Taggar, Nilotic and a mix of Nubian and Desert goats into three groups. The SNPs that contributed strongly to PC1 showed high F st values in Taggar goat versus the other goat breeds. PCA allowed us to identify target genomic regions which contain genes known to influence growth, development, bone formation and the immune system. The information on the genetic variability and diversity in this study confirmed that Taggar goat is genetically different from the other goat breeds in Sudan. The SNPs identified by the first principal components show high F st values in Taggar goat and allowed to identify candidate genes which can be used in the development of breed selection programs to improve local breeds and find genetic factors contributing to the adaptation to harsh environments.

Genome-wide analysis of coordinated transcript abundance during seed development in different Brassica rapa morphotypes.

PubMed

Basnet, Ram Kumar; Moreno-Pachon, Natalia; Lin, Ke; Bucher, Johan; Visser, Richard G F; Maliepaard, Chris; Bonnema, Guusje

2013-12-01

Brassica seeds are important as basic units of plant growth and sources of vegetable oil. Seed development is regulated by many dynamic metabolic processes controlled by complex networks of spatially and temporally expressed genes. We conducted a global microarray gene co-expression analysis by measuring transcript abundance of developing seeds from two diverse B. rapa morphotypes: a pak choi (leafy-type) and a yellow sarson (oil-type), and two of their doubled haploid (DH) progenies, (1) to study the timing of metabolic processes in developing seeds, (2) to explore the major transcriptional differences in developing seeds of the two morphotypes, and (3) to identify the optimum stage for a genetical genomics study in B. rapa seed. Seed developmental stages were similar in developing seeds of pak choi and yellow sarson of B. rapa; however, the colour of embryo and seed coat differed among these two morphotypes. In this study, most transcriptional changes occurred between 25 and 35 DAP, which shows that the timing of seed developmental processes in B. rapa is at later developmental stages than in the related species B. napus. Using a Weighted Gene Co-expression Network Analysis (WGCNA), we identified 47 "gene modules", of which 27 showed a significant association with temporal and/or genotypic variation. An additional hierarchical cluster analysis identified broad spectra of gene expression patterns during seed development. The predominant variation in gene expression was according to developmental stages rather than morphotype differences. Since lipids are the major storage compounds of Brassica seeds, we investigated in more detail the regulation of lipid metabolism. Four co-regulated gene clusters were identified with 17 putative cis-regulatory elements predicted in their 1000 bp upstream region, either specific or common to different lipid metabolic pathways. This is the first study of genome-wide profiling of transcript abundance during seed development in B. rapa. The identification of key physiological events, major expression patterns, and putative cis-regulatory elements provides useful information to construct gene regulatory networks in B. rapa developing seeds and provides a starting point for a genetical genomics study of seed quality traits.

Coats' disease and congenital retinoschisis in a single eye: a case report and DNA analysis.

PubMed

Berinstein, D M; Hiraoka, M; Trese, M T; Shastry, B S

2001-01-01

The clinical features of Coats' disease and congenital retinoschisis (RS) are distinctly different. Therefore, finding changes consistent with Coats' disease and congenital RS in a single eye is an unusual occurrence. The following report describes two cases with a Coats' telangiectatic lesion in one region of the retina separated by normal retina and the presence of central and peripheral congenital RS. Molecular genetic analysis of the Norrie disease and RS genes failed to identify disease-causing or polymorphic mutations in either of the genes, suggesting that the above condition is clinically and genetically a different disorder. Further studies are needed to identify the genes responsible for the above disorder and associated ocular manifestations. Copyright 2001 S. Karger AG, Basel.

Proteomic analysis of human dental cementum and alveolar bone

PubMed Central

Salmon, Cristiane R.; Tomazela, Daniela M.; Ruiz, Karina Gonzales Silvério; Foster, Brian L.; Leme, Adriana Franco Paes; Sallum, Enilson Antonio; Somerman, Martha J.; Nociti, Francisco H.

2013-01-01

Dental cementum (DC) is a bone-like tissue covering the tooth root and responsible for attaching the tooth to the alveolar bone (AB) via the periodontal ligament (PDL). Studies have unsuccessfully tried to identify factors specific to DC versus AB, in an effort to better understand DC development and regeneration. The present study aimed to use matched human DC and AB samples (n=7) to generate their proteomes for comparative analysis. Bone samples were harvested from tooth extraction sites, whereas DC samples were obtained from the apical root portion of extracted third molars. Samples were denatured, followed by protein extraction reduction, alkylation and digestion for analysis by nanoAcquity HPLC system and LTQ-FT Ultra. Data analysis demonstrated that a total of 318 proteins were identified in AB and DC. In addition to shared proteins between these tissues, 105 and 83 proteins exclusive to AB or DC were identified, respectively. This is the first report analyzing the proteomic composition of human DC matrix and identifying putative unique and enriched proteins in comparison to alveolar bone. These findings may provide novel insights into developmental differences between DC and AB, and identify candidate biomarkers that may lead to more efficient and predictable therapies for periodontal regeneration. PMID:24007660

Novel Computational Protocols for Functionally Classifying and Characterising Serine Beta-Lactamases

PubMed Central

Das, Sayoni; Dawson, Natalie L.; Dobrijevic, Dragana; Orengo, Christine

2016-01-01

Beta-lactamases represent the main bacterial mechanism of resistance to beta-lactam antibiotics and are a significant challenge to modern medicine. We have developed an automated classification and analysis protocol that exploits structure- and sequence-based approaches and which allows us to propose a grouping of serine beta-lactamases that more consistently captures and rationalizes the existing three classification schemes: Classes, (A, C and D, which vary in their implementation of the mechanism of action); Types (that largely reflect evolutionary distance measured by sequence similarity); and Variant groups (which largely correspond with the Bush-Jacoby clinical groups). Our analysis platform exploits a suite of in-house and public tools to identify Functional Determinants (FDs), i.e. residue sites, responsible for conferring different phenotypes between different classes, different types and different variants. We focused on Class A beta-lactamases, the most highly populated and clinically relevant class, to identify FDs implicated in the distinct phenotypes associated with different Class A Types and Variants. We show that our FunFHMMer method can separate the known beta-lactamase classes and identify those positions likely to be responsible for the different implementations of the mechanism of action in these enzymes. Two novel algorithms, ASSP and SSPA, allow detection of FD sites likely to contribute to the broadening of the substrate profiles. Using our approaches, we recognise 151 Class A types in UniProt. Finally, we used our beta-lactamase FunFams and ASSP profiles to detect 4 novel Class A types in microbiome samples. Our platforms have been validated by literature studies, in silico analysis and some targeted experimental verification. Although developed for the serine beta-lactamases they could be used to classify and analyse any diverse protein superfamily where sub-families have diverged over both long and short evolutionary timescales. PMID:27332861

Metabolomic Analyses of Leishmania Reveal Multiple Species Differences and Large Differences in Amino Acid Metabolism

PubMed Central

Wang, Lijie; Zhang, Tong; Watson, David G.; Silva, Ana Marta; Coombs, Graham H.

2015-01-01

Comparative genomic analyses of Leishmania species have revealed relatively minor heterogeneity amongst recognised housekeeping genes and yet the species cause distinct infections and pathogenesis in their mammalian hosts. To gain greater information on the biochemical variation between species, and insights into possible metabolic mechanisms underpinning visceral and cutaneous leishmaniasis, we have undertaken in this study a comparative analysis of the metabolomes of promastigotes of L. donovani, L. major and L. mexicana. The analysis revealed 64 metabolites with confirmed identity differing 3-fold or more between the cell extracts of species, with 161 putatively identified metabolites differing similarly. Analysis of the media from cultures revealed an at least 3-fold difference in use or excretion of 43 metabolites of confirmed identity and 87 putatively identified metabolites that differed to a similar extent. Strikingly large differences were detected in their extent of amino acid use and metabolism, especially for tryptophan, aspartate, arginine and proline. Major pathways of tryptophan and arginine catabolism were shown to be to indole-3-lactate and arginic acid, respectively, which were excreted. The data presented provide clear evidence on the value of global metabolomic analyses in detecting species-specific metabolic features, thus application of this technology should be a major contributor to gaining greater understanding of how pathogens are adapted to infecting their hosts. PMID:26368322

Bioinformatics Analysis Reveals Distinct Molecular Characteristics of Hepatitis B-Related Hepatocellular Carcinomas from Very Early to Advanced Barcelona Clinic Liver Cancer Stages.

PubMed

Kong, Fan-Yun; Wei, Xiao; Zhou, Kai; Hu, Wei; Kou, Yan-Bo; You, Hong-Juan; Liu, Xiao-Mei; Zheng, Kui-Yang; Tang, Ren-Xian

2016-01-01

Hepatocellular carcinoma (HCC)is the fifth most common malignancy associated with high mortality. One of the risk factors for HCC is chronic hepatitis B virus (HBV) infection. The treatment strategy for the disease is dependent on the stage of HCC, and the Barcelona clinic liver cancer (BCLC) staging system is used in most HCC cases. However, the molecular characteristics of HBV-related HCC in different BCLC stages are still unknown. Using GSE14520 microarray data from HBV-related HCC cases with BCLC stages from 0 (very early stage) to C (advanced stage) in the gene expression omnibus (GEO) database, differentially expressed genes (DEGs), including common DEGs and unique DEGs in different BCLC stages, were identified. These DEGs were located on different chromosomes. The molecular functions and biology pathways of DEGs were identified by gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and the interactome networks of DEGs were constructed using the NetVenn online tool. The results revealed that both common DEGs and stage-specific DEGs were associated with various molecular functions and were involved in special biological pathways. In addition, several hub genes were found in the interactome networks of DEGs. The identified DEGs and hub genes promote our understanding of the molecular mechanisms underlying the development of HBV-related HCC through the different BCLC stages, and might be used as staging biomarkers or molecular targets for the treatment of HCC with HBV infection.

Meta-analysis to refine map position and reduce confidence intervals for delayed canopy wilting QTLs in soybean

USDA-ARS?s Scientific Manuscript database

Slow canopy wilting in soybean has been identified as a potentially beneficial trait for ameliorating drought effects on yield. Previous research identified QTLs for slow wilting from two different bi-parental populations and this information was combined with data from three other populations to id...

The Management of Resistance to Change and Polarity in Educational Organisations.

ERIC Educational Resources Information Center

Theron, A. M. C.; Westhuizen, Philip C. van der

Research has shown that organizations differ on the basis of their willingness to change and the strategies they use to manage change. For this paper, data were gathered through a review of the literature and through nonstandard interviews with persons in two identified organizations who handle grievance procedures. The analysis identifies the…

Which Industries Are Sensitive to Business Cycles?

ERIC Educational Resources Information Center

Berman, Jay; Pfleeger, Janet

1997-01-01

An analysis of the 1994-2005 Bureau of Labor Statistics employment projections can be used to identify industries that are projected to move differently with business cycles in the future than with those of the past, and can be used to identify the industries and occupations that are most prone to business cycle swings. (Author)

The Effect of Recommendation Systems on Internet-Based Learning for Different Learners: A Data Mining Analysis

ERIC Educational Resources Information Center

Liu, Chen-Chung; Chang, Chia-Jung; Tseng, Jui-Min

2013-01-01

A general challenge facing Internet-based learners is how to identify information objects which are helpful in expanding their understanding of important information in a domain. Recommendation systems may assist learners in identifying potentially helpful information objects. However, the recent literature mainly focuses on the technical…

Proteomic analysis of early-stage embryos: implications for egg quality in hapuku (Polyprion oxygeneios).

PubMed

Kohn, Yair Y; Symonds, Jane E; Kleffmann, Torsten; Nakagawa, Shinichi; Lagisz, Malgorzata; Lokman, P Mark

2015-12-01

In order to develop biomarkers that may help predict the egg quality of captive hapuku (Polyprion oxygeneios) and provide potential avenues for its manipulation, the present study (1) sequenced the proteome of early-stage embryos using isobaric tag for relative and absolute quantification analysis, and (2) aimed to establish the predictive value of the abundance of identified proteins with regard to egg quality through regression analysis. Egg quality was determined for eight different egg batches by blastomere symmetry scores. In total, 121 proteins were identified and assigned to one of nine major groups according to their function/pathway. A mixed-effects model analysis revealed a decrease in relative protein abundance that correlated with (decreasing) egg quality in one major group (heat-shock proteins). No differences were found in the other protein groups. Linear regression analysis, performed for each identified protein separately, revealed seven proteins that showed a significant decrease in relative abundance with reduced blastomere symmetry: two correlates that have been named in other studies (vitellogenin, heat-shock protein-70) and a further five new candidate proteins (78 kDa glucose-regulated protein, elongation factor-2, GTP-binding nuclear protein Ran, iduronate 2-sulfatase and 6-phosphogluconate dehydrogenase). Notwithstanding issues associated with multiple statistical testing, we conclude that these proteins, and especially iduronate 2-sulfatase and the generic heat-shock protein group, could serve as biomarkers of egg quality in hapuku.

Sexual dimorphic floral development in dioecious plants revealed by transcriptome, phytohormone, and DNA methylation analysis in Populus tomentosa.

PubMed

Song, Yuepeng; Ma, Kaifeng; Ci, Dong; Chen, Qingqing; Tian, Jiaxing; Zhang, Deqiang

2013-12-01

Dioecious plants have evolved sex-specific floral development mechanisms. However, the precise gene expression patterns in dioecious plant flower development remain unclear. Here, we used andromonoecious poplar, an exceptional model system, to eliminate the confounding effects of genetic background of dioecious plants. Comparative transcriptome and physiological analysis allowed us to characterize sex-specific development of female and male flowers. Transcriptome analysis identified genes significantly differentially expressed between the sexes, including genes related to floral development, phytohormone synthesis and metabolism, and DNA methylation. Correlation analysis revealed a significant correlation between phytohormone signaling and gene expression, identifying specific phytohormone-responsive genes and their cis-regulatory elements. Two genes related to DNA methylation, METHYLTRANSFERASE1 (MET1) and DECREASED DNA METHYLATION 1 (DDM1), which are located in the sex determination region of Chromosome XIX, have differential expression between female and male flowers. A time-course analysis revealed that MET1 and DDM1 expression may produce different DNA methylation levels in female and male flowers. Understanding the interactions of phytohormone signaling, DNA methylation and target gene expression should lead to a better understanding of sexual differences in floral development. Thus, this study identifies a set of candidate genes for further studies of poplar sexual dimorphism and relates sex-specific floral development to physiological and epigenetic changes.

Surprisal analysis of genome-wide transcript profiling identifies differentially expressed genes and pathways associated with four growth conditions in the microalga Chlamydomonas.

PubMed

Bogaert, Kenny A; Manoharan-Basil, Sheeba S; Perez, Emilie; Levine, Raphael D; Remacle, Francoise; Remacle, Claire

2018-01-01

The usual cultivation mode of the green microalga Chlamydomonas is liquid medium and light. However, the microalga can also be grown on agar plates and in darkness. Our aim is to analyze and compare gene expression of cells cultivated in these different conditions. For that purpose, RNA-seq data are obtained from Chlamydomonas samples of two different labs grown in four environmental conditions (agar@light, agar@dark, liquid@light, liquid@dark). The RNA seq data are analyzed by surprisal analysis, which allows the simultaneous meta-analysis of all the samples. First we identify a balance state, which defines a state where the expression levels are similar in all the samples irrespectively of their growth conditions, or lab origin. In addition our analysis identifies additional constraints needed to quantify the deviation with respect to the balance state. The first constraint differentiates the agar samples versus the liquid ones; the second constraint the dark samples versus the light ones. The two constraints are almost of equal importance. Pathways involved in stress responses are found in the agar phenotype while the liquid phenotype comprises ATP and NADH production pathways. Remodeling of membrane is suggested in the dark phenotype while photosynthetic pathways characterize the light phenotype. The same trends are also present when performing purely statistical analysis such as K-means clustering and differentially expressed genes.

Cell Painting, a high-content image-based assay for morphological profiling using multiplexed fluorescent dyes

PubMed Central

Bray, Mark-Anthony; Singh, Shantanu; Han, Han; Davis, Chadwick T.; Borgeson, Blake; Hartland, Cathy; Kost-Alimova, Maria; Gustafsdottir, Sigrun M.; Gibson, Christopher C.; Carpenter, Anne E.

2016-01-01

In morphological profiling, quantitative data are extracted from microscopy images of cells to identify biologically relevant similarities and differences among samples based on these profiles. This protocol describes the design and execution of experiments using Cell Painting, a morphological profiling assay multiplexing six fluorescent dyes imaged in five channels, to reveal eight broadly relevant cellular components or organelles. Cells are plated in multi-well plates, perturbed with the treatments to be tested, stained, fixed, and imaged on a high-throughput microscope. Then, automated image analysis software identifies individual cells and measures ~1,500 morphological features (various measures of size, shape, texture, intensity, etc.) to produce a rich profile suitable for detecting subtle phenotypes. Profiles of cell populations treated with different experimental perturbations can be compared to suit many goals, such as identifying the phenotypic impact of chemical or genetic perturbations, grouping compounds and/or genes into functional pathways, and identifying signatures of disease. Cell culture and image acquisition takes two weeks; feature extraction and data analysis take an additional 1-2 weeks. PMID:27560178

A simple algorithm for the identification of clinical COPD phenotypes.

PubMed

Burgel, Pierre-Régis; Paillasseur, Jean-Louis; Janssens, Wim; Piquet, Jacques; Ter Riet, Gerben; Garcia-Aymerich, Judith; Cosio, Borja; Bakke, Per; Puhan, Milo A; Langhammer, Arnulf; Alfageme, Inmaculada; Almagro, Pere; Ancochea, Julio; Celli, Bartolome R; Casanova, Ciro; de-Torres, Juan P; Decramer, Marc; Echazarreta, Andrés; Esteban, Cristobal; Gomez Punter, Rosa Mar; Han, MeiLan K; Johannessen, Ane; Kaiser, Bernhard; Lamprecht, Bernd; Lange, Peter; Leivseth, Linda; Marin, Jose M; Martin, Francis; Martinez-Camblor, Pablo; Miravitlles, Marc; Oga, Toru; Sofia Ramírez, Ana; Sin, Don D; Sobradillo, Patricia; Soler-Cataluña, Juan J; Turner, Alice M; Verdu Rivera, Francisco Javier; Soriano, Joan B; Roche, Nicolas

2017-11-01

This study aimed to identify simple rules for allocating chronic obstructive pulmonary disease (COPD) patients to clinical phenotypes identified by cluster analyses.Data from 2409 COPD patients of French/Belgian COPD cohorts were analysed using cluster analysis resulting in the identification of subgroups, for which clinical relevance was determined by comparing 3-year all-cause mortality. Classification and regression trees (CARTs) were used to develop an algorithm for allocating patients to these subgroups. This algorithm was tested in 3651 patients from the COPD Cohorts Collaborative International Assessment (3CIA) initiative.Cluster analysis identified five subgroups of COPD patients with different clinical characteristics (especially regarding severity of respiratory disease and the presence of cardiovascular comorbidities and diabetes). The CART-based algorithm indicated that the variables relevant for patient grouping differed markedly between patients with isolated respiratory disease (FEV 1 , dyspnoea grade) and those with multi-morbidity (dyspnoea grade, age, FEV 1 and body mass index). Application of this algorithm to the 3CIA cohorts confirmed that it identified subgroups of patients with different clinical characteristics, mortality rates (median, from 4% to 27%) and age at death (median, from 68 to 76 years).A simple algorithm, integrating respiratory characteristics and comorbidities, allowed the identification of clinically relevant COPD phenotypes. Copyright ©ERS 2017.

Using Markov Chain Analyses in Counselor Education Research

ERIC Educational Resources Information Center

Duys, David K.; Headrick, Todd C.

2004-01-01

This study examined the efficacy of an infrequently used statistical analysis in counselor education research. A Markov chain analysis was used to examine hypothesized differences between students' use of counseling skills in an introductory course. Thirty graduate students participated in the study. Independent raters identified the microskills…

[Analysis of researchers' implication in a research-intervention in the Stork Network: a tool for institutional analysis].

PubMed

Fortuna, Cinira Magali; Mesquita, Luana Pinho de; Matumoto, Silvia; Monceau, Gilles

2016-09-19

This qualitative study is based on institutional analysis as the methodological theoretical reference with the objective of analyzing researchers' implication during a research-intervention and the interferences caused by this analysis. The study involved researchers from courses in medicine, nursing, and dentistry at two universities and workers from a Regional Health Department in follow-up on the implementation of the Stork Network in São Paulo State, Brazil. The researchers worked together in the intervention and in analysis workshops, supported by an external institutional analysis. Two institutions stood out in the analysis: the research, established mainly with characteristics of neutrality, and management, with Taylorist characteristics. Differences between researchers and difficulties in identifying actions proper to network management and research were some of the interferences that were identified. The study concludes that implication analysis is a powerful tool for such studies.

Adélie Penguin Population Diet Monitoring by Analysis of Food DNA in Scats

PubMed Central

Jarman, Simon N.; McInnes, Julie C.; Faux, Cassandra; Polanowski, Andrea M.; Marthick, James; Deagle, Bruce E.; Southwell, Colin; Emmerson, Louise

2013-01-01

The Adélie penguin is the most important animal currently used for ecosystem monitoring in the Southern Ocean. The diet of this species is generally studied by visual analysis of stomach contents; or ratios of isotopes of carbon and nitrogen incorporated into the penguin from its food. There are significant limitations to the information that can be gained from these methods. We evaluated population diet assessment by analysis of food DNA in scats as an alternative method for ecosystem monitoring with Adélie penguins as an indicator species. Scats were collected at four locations, three phases of the breeding cycle, and in four different years. A novel molecular diet assay and bioinformatics pipeline based on nuclear small subunit ribosomal RNA gene (SSU rDNA) sequencing was used to identify prey DNA in 389 scats. Analysis of the twelve population sample sets identified spatial and temporal dietary change in Adélie penguin population diet. Prey diversity was found to be greater than previously thought. Krill, fish, copepods and amphipods were the most important food groups, in general agreement with other Adélie penguin dietary studies based on hard part or stable isotope analysis. However, our DNA analysis estimated that a substantial portion of the diet was gelatinous groups such as jellyfish and comb jellies. A range of other prey not previously identified in the diet of this species were also discovered. The diverse prey identified by this DNA-based scat analysis confirms that the generalist feeding of Adélie penguins makes them a useful indicator species for prey community composition in the coastal zone of the Southern Ocean. Scat collection is a simple and non-invasive field sampling method that allows DNA-based estimation of prey community differences at many temporal and spatial scales and provides significant advantages over alternative diet analysis approaches. PMID:24358158

Adélie penguin population diet monitoring by analysis of food DNA in scats.

PubMed

Jarman, Simon N; McInnes, Julie C; Faux, Cassandra; Polanowski, Andrea M; Marthick, James; Deagle, Bruce E; Southwell, Colin; Emmerson, Louise

2013-01-01

The Adélie penguin is the most important animal currently used for ecosystem monitoring in the Southern Ocean. The diet of this species is generally studied by visual analysis of stomach contents; or ratios of isotopes of carbon and nitrogen incorporated into the penguin from its food. There are significant limitations to the information that can be gained from these methods. We evaluated population diet assessment by analysis of food DNA in scats as an alternative method for ecosystem monitoring with Adélie penguins as an indicator species. Scats were collected at four locations, three phases of the breeding cycle, and in four different years. A novel molecular diet assay and bioinformatics pipeline based on nuclear small subunit ribosomal RNA gene (SSU rDNA) sequencing was used to identify prey DNA in 389 scats. Analysis of the twelve population sample sets identified spatial and temporal dietary change in Adélie penguin population diet. Prey diversity was found to be greater than previously thought. Krill, fish, copepods and amphipods were the most important food groups, in general agreement with other Adélie penguin dietary studies based on hard part or stable isotope analysis. However, our DNA analysis estimated that a substantial portion of the diet was gelatinous groups such as jellyfish and comb jellies. A range of other prey not previously identified in the diet of this species were also discovered. The diverse prey identified by this DNA-based scat analysis confirms that the generalist feeding of Adélie penguins makes them a useful indicator species for prey community composition in the coastal zone of the Southern Ocean. Scat collection is a simple and non-invasive field sampling method that allows DNA-based estimation of prey community differences at many temporal and spatial scales and provides significant advantages over alternative diet analysis approaches.

Making Sense of Sensemaking: Requirements of a Cognitive Analysis to Support C2 Decision Support System Design

DTIC Science & Technology

2006-06-01

heart of a distinction within the CSE community with respect to the differences between Cognitive Task Analysis (CTA) and Cognitive Work Analysis...Wesley. Pirolli, P. and Card, S. (2005). The sensemaking process and leverage points for analyst technology as identified through cognitive task analysis . In...D. D., and Elm, W. C. (2000). Cognitive task analysis as bootstrapping multiple converging techniques. In Schraagen, Chipman, and Shalin (Eds

Identifying 1st instar larvae for three forensically important blowfly species using "fingerprint" cuticular hydrocarbon analysis.

PubMed

Moore, Hannah E; Adam, Craig D; Drijfhout, Falko P

2014-07-01

Calliphoridae are known to be the most forensically important insects when it comes to establishing the minimum post mortem interval (PMImin) in criminal investigations. The first step in calculating the PMImin is to identify the larvae present to species level. Accurate identification which is conventionally carried out by morphological analysis is crucial because different insects have different life stage timings. Rapid identification in the immature larvae stages would drastically cut time in criminal investigations as it would eliminate the need to rear larvae to adult flies to determine the species. Cuticular hydrocarbon analysis on 1st instar larvae has been applied to three forensically important blowflies; Lucilia sericata, Calliphora vicina and Calliphora vomitoria, using gas chromatography-mass spectrometry (GC-MS) and principal component analysis (PCA). The results show that each species holds a distinct "fingerprint" hydrocarbon profile, allowing for accurate identification to be established in 1-day old larvae, when it can be challenging to apply morphological criteria. Consequently, this GC-MS based technique could accelerate and strengthen the identification process, not only for forensically important species, but also for other entomological samples which are hard to identify using morphological features. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Rumours about wildlife pest introductions: European rabbits in Spain.

PubMed

Delibes-Mateos, Miguel

2017-03-01

Rumours associated with wildlife are frequent, although they have received little attention in the scientific literature. Studying rumours is important because of their relevance not only in a broad theoretical sense but also in environmental management. The goal of this study is to explore the complexity of the relationships between humans and wildlife through a thematic analysis of rumours associated with allegedly introduced European rabbits (Oryctolagus cuniculus) that cause crop damage in Spain. For this purpose, potential rumours were identified using the Google search engine. Data analysis consisted of reading and re-reading Web-based texts to identify main themes, ideas and topics with the assistance of NVivo 10 software. The analysis identified three main themes: (1) the reviewed websites referred to allegedly introduced rabbits which differed from native rabbits; (2) differences were based on alleged observations of unnatural behaviour, physiology or physical appearance of introduced rabbits; (3) rumours were frequently used in the context of the rabbit management conflict; e.g. farmers accused hunters of releasing harmful rabbits. This study suggests that the analysis of wildlife-release rumours sheds light on the position of parties involved in conflicts associated with the (alleged) introduction of wildlife species. It stresses the importance of rumours in conservation and environmental management, and opens the door to future research.

Resting-state low-frequency fluctuations reflect individual differences in spoken language learning.

PubMed

Deng, Zhizhou; Chandrasekaran, Bharath; Wang, Suiping; Wong, Patrick C M

2016-03-01

A major challenge in language learning studies is to identify objective, pre-training predictors of success. Variation in the low-frequency fluctuations (LFFs) of spontaneous brain activity measured by resting-state functional magnetic resonance imaging (RS-fMRI) has been found to reflect individual differences in cognitive measures. In the present study, we aimed to investigate the extent to which initial spontaneous brain activity is related to individual differences in spoken language learning. We acquired RS-fMRI data and subsequently trained participants on a sound-to-word learning paradigm in which they learned to use foreign pitch patterns (from Mandarin Chinese) to signal word meaning. We performed amplitude of spontaneous low-frequency fluctuation (ALFF) analysis, graph theory-based analysis, and independent component analysis (ICA) to identify functional components of the LFFs in the resting-state. First, we examined the ALFF as a regional measure and showed that regional ALFFs in the left superior temporal gyrus were positively correlated with learning performance, whereas ALFFs in the default mode network (DMN) regions were negatively correlated with learning performance. Furthermore, the graph theory-based analysis indicated that the degree and local efficiency of the left superior temporal gyrus were positively correlated with learning performance. Finally, the default mode network and several task-positive resting-state networks (RSNs) were identified via the ICA. The "competition" (i.e., negative correlation) between the DMN and the dorsal attention network was negatively correlated with learning performance. Our results demonstrate that a) spontaneous brain activity can predict future language learning outcome without prior hypotheses (e.g., selection of regions of interest--ROIs) and b) both regional dynamics and network-level interactions in the resting brain can account for individual differences in future spoken language learning success. Copyright © 2015 Elsevier Ltd. All rights reserved.

Resting-state low-frequency fluctuations reflect individual differences in spoken language learning

PubMed Central

Deng, Zhizhou; Chandrasekaran, Bharath; Wang, Suiping; Wong, Patrick C.M.

2016-01-01

A major challenge in language learning studies is to identify objective, pre-training predictors of success. Variation in the low-frequency fluctuations (LFFs) of spontaneous brain activity measured by resting-state functional magnetic resonance imaging (RS-fMRI) has been found to reflect individual differences in cognitive measures. In the present study, we aimed to investigate the extent to which initial spontaneous brain activity is related to individual differences in spoken language learning. We acquired RS-fMRI data and subsequently trained participants on a sound-to-word learning paradigm in which they learned to use foreign pitch patterns (from Mandarin Chinese) to signal word meaning. We performed amplitude of spontaneous low-frequency fluctuation (ALFF) analysis, graph theory-based analysis, and independent component analysis (ICA) to identify functional components of the LFFs in the resting-state. First, we examined the ALFF as a regional measure and showed that regional ALFFs in the left superior temporal gyrus were positively correlated with learning performance, whereas ALFFs in the default mode network (DMN) regions were negatively correlated with learning performance. Furthermore, the graph theory-based analysis indicated that the degree and local efficiency of the left superior temporal gyrus were positively correlated with learning performance. Finally, the default mode network and several task-positive resting-state networks (RSNs) were identified via the ICA. The “competition” (i.e., negative correlation) between the DMN and the dorsal attention network was negatively correlated with learning performance. Our results demonstrate that a) spontaneous brain activity can predict future language learning outcome without prior hypotheses (e.g., selection of regions of interest – ROIs) and b) both regional dynamics and network-level interactions in the resting brain can account for individual differences in future spoken language learning success. PMID:26866283

Large-scale transcriptome analysis reveals arabidopsis metabolic pathways are frequently influenced by different pathogens.

PubMed

Jiang, Zhenhong; He, Fei; Zhang, Ziding

2017-07-01

Through large-scale transcriptional data analyses, we highlighted the importance of plant metabolism in plant immunity and identified 26 metabolic pathways that were frequently influenced by the infection of 14 different pathogens. Reprogramming of plant metabolism is a common phenomenon in plant defense responses. Currently, a large number of transcriptional profiles of infected tissues in Arabidopsis (Arabidopsis thaliana) have been deposited in public databases, which provides a great opportunity to understand the expression patterns of metabolic pathways during plant defense responses at the systems level. Here, we performed a large-scale transcriptome analysis based on 135 previously published expression samples, including 14 different pathogens, to explore the expression pattern of Arabidopsis metabolic pathways. Overall, metabolic genes are significantly changed in expression during plant defense responses. Upregulated metabolic genes are enriched on defense responses, and downregulated genes are enriched on photosynthesis, fatty acid and lipid metabolic processes. Gene set enrichment analysis (GSEA) identifies 26 frequently differentially expressed metabolic pathways (FreDE_Paths) that are differentially expressed in more than 60% of infected samples. These pathways are involved in the generation of energy, fatty acid and lipid metabolism as well as secondary metabolite biosynthesis. Clustering analysis based on the expression levels of these 26 metabolic pathways clearly distinguishes infected and control samples, further suggesting the importance of these metabolic pathways in plant defense responses. By comparing with FreDE_Paths from abiotic stresses, we find that the expression patterns of 26 FreDE_Paths from biotic stresses are more consistent across different infected samples. By investigating the expression correlation between transcriptional factors (TFs) and FreDE_Paths, we identify several notable relationships. Collectively, the current study will deepen our understanding of plant metabolism in plant immunity and provide new insights into disease-resistant crop improvement.

Global-local methodologies and their application to nonlinear analysis

NASA Technical Reports Server (NTRS)

Noor, Ahmed K.

1989-01-01

An assessment is made of the potential of different global-local analysis strategies for predicting the nonlinear and postbuckling responses of structures. Two postbuckling problems of composite panels are used as benchmarks and the application of different global-local methodologies to these benchmarks is outlined. The key elements of each of the global-local strategies are discussed and future research areas needed to realize the full potential of global-local methodologies are identified.

Characteristic fingerprinting based on macamides for discrimination of maca (Lepidium meyenii) by LC/MS/MS and multivariate statistical analysis.

PubMed

Pan, Yu; Zhang, Ji; Li, Hong; Wang, Yuan-Zhong; Li, Wan-Yi

2016-10-01

Macamides with a benzylalkylamide nucleus are characteristic and major bioactive compounds in the functional food maca (Lepidium meyenii Walp). The aim of this study was to explore variations in macamide content among maca from China and Peru. Twenty-seven batches of maca hypocotyls with different phenotypes, sampled from different geographical origins, were extracted and profiled by liquid chromatography with ultraviolet detection/tandem mass spectrometry (LC-UV/MS/MS). Twelve macamides were identified by MS operated in multiple scanning modes. Similarity analysis showed that maca samples differed significantly in their macamide fingerprinting. Partial least squares discriminant analysis (PLS-DA) was used to differentiate samples according to their geographical origin and to identify the most relevant variables in the classification model. The prediction accuracy for raw maca was 91% and five macamides were selected and considered as chemical markers for sample classification. When combined with a PLS-DA model, characteristic fingerprinting based on macamides could be recommended for labelling for the authentication of maca from different geographical origins. The results provided potential evidence for the relationships between environmental or other factors and distribution of macamides. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Quality evaluation of Shenmaidihuang Pills based on the chromatographic fingerprints and simultaneous determination of seven bioactive constituents.

PubMed

Liu, Sifei; Zhang, Guangrui; Qiu, Ying; Wang, Xiaobo; Guo, Lihan; Zhao, Yanxin; Tong, Meng; Wei, Lan; Sun, Lixin

2016-12-01

In this study, we aimed to establish a comprehensive and practical quality evaluation system for Shenmaidihuang pills. A simple and reliable high-performance liquid chromatography coupled with photodiode array detection method was developed both for fingerprint analysis and quantitative determination. In fingerprint analysis, relative retention time and relative peak area were used to identify the common peaks in 18 samples for investigation. Twenty one peaks were selected as the common peaks to evaluate the similarities of 18 Shenmaidihuang pills samples with different manufacture dates. Furthermore, similarity analysis was applied to evaluate the similarity of samples. Hierarchical cluster analysis and principal component analysis were also performed to evaluate the variation of Shenmaidihuang pills. In quantitative analysis, linear regressions, injection precisions, recovery, repeatability and sample stability were all tested and good results were obtained to simultaneously determine the seven identified compounds, namely, 5-hydroxymethylfurfural, morroniside, loganin, paeonol, paeoniflorin, psoralen, isopsoralen in Shenmaidihuang pills. The contents of some analytes in different batches of samples indicated significant difference, especially for 5-hydroxymethylfurfural. So, it was concluded that the chromatographic fingerprint method obtained by high-performance liquid chromatography coupled with photodiode array detection associated with multiple compounds determination is a powerful and meaningful tool to comprehensively conduct the quality control of Shenmaidihuang pills. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Topical tranexamic acid in total knee replacement: a systematic review and meta-analysis.

PubMed

Panteli, Michalis; Papakostidis, Costas; Dahabreh, Ziad; Giannoudis, Peter V

2013-10-01

To examine the safety and efficacy of topical use of tranexamic acid (TA) in total knee arthroplasty (TKA). An electronic literature search of PubMed Medline; Ovid Medline; Embase; and the Cochrane Library was performed, identifying studies published in any language from 1966 to February 2013. The studies enrolled adults undergoing a primary TKA, where topical TA was used. Inverse variance statistical method and either a fixed or random effect model, depending on the absence or presence of statistical heterogeneity were used; subgroup analysis was performed when possible. We identified a total of seven eligible reports for analysis. Our meta-analysis indicated that when compared with the control group, topical application of TA limited significantly postoperative drain output (mean difference: -268.36ml), total blood loss (mean difference=-220.08ml), Hb drop (mean difference=-0.94g/dL) and lowered the risk of transfusion requirements (risk ratio=0.47, 95CI=0.26-0.84), without increased risk of thromboembolic events. Sub-group analysis indicated that a higher dose of topical TA (>2g) significantly reduced transfusion requirements. Although the present meta-analysis proved a statistically significant reduction of postoperative blood loss and transfusion requirements with topical use of TA in TKA, the clinical importance of the respective estimates of effect size should be interpreted with caution. I, II. Copyright © 2013 Elsevier B.V. All rights reserved.

Foveal analysis and peripheral selection during active visual sampling

PubMed Central

Ludwig, Casimir J. H.; Davies, J. Rhys; Eckstein, Miguel P.

2014-01-01

Human vision is an active process in which information is sampled during brief periods of stable fixation in between gaze shifts. Foveal analysis serves to identify the currently fixated object and has to be coordinated with a peripheral selection process of the next fixation location. Models of visual search and scene perception typically focus on the latter, without considering foveal processing requirements. We developed a dual-task noise classification technique that enables identification of the information uptake for foveal analysis and peripheral selection within a single fixation. Human observers had to use foveal vision to extract visual feature information (orientation) from different locations for a psychophysical comparison. The selection of to-be-fixated locations was guided by a different feature (luminance contrast). We inserted noise in both visual features and identified the uptake of information by looking at correlations between the noise at different points in time and behavior. Our data show that foveal analysis and peripheral selection proceeded completely in parallel. Peripheral processing stopped some time before the onset of an eye movement, but foveal analysis continued during this period. Variations in the difficulty of foveal processing did not influence the uptake of peripheral information and the efficacy of peripheral selection, suggesting that foveal analysis and peripheral selection operated independently. These results provide important theoretical constraints on how to model target selection in conjunction with foveal object identification: in parallel and independently. PMID:24385588

Meta-analysis of randomized controlled trials comparing outcomes for stapled hemorrhoidopexy versus LigaSure hemorrhoidectomy for symptomatic hemorrhoids in adults.

PubMed

Lee, Ko-Chao; Chen, Hong-Hwa; Chung, Kuan-Chih; Hu, Wan-Hsiang; Chang, Chia-Lo; Lin, Shung-Eing; Tsai, Kai-Lung; Lu, Chien-Chang

2013-01-01

This purpose of the meta-analysis was to compare treatment outcomes for adult patients with symptomatic hemorrhoids treated by stapled hemorrhoidopexy or LigaSure hemorrhoidectomy. A search of public medical databases was made to identify randomized controlled trials (RCTs) comparing stapled hemorrhoidopexy (SH) with LigaSure hemorrhoidectomy (LH) for the treatment of adult patients with symptomatic grade 3 and grade 4 hemorrhoids. Postoperative pain as measured using a visual analog scale was the primary outcome, and rate of recurrent prolapse and postoperative bleeding were secondary outcome measures. Four RCTs were identified that met the inclusion criteria. Data for the pooled outcomes were analyzed using odds ratio (OR) analysis. None of the studies in the analysis indicated a significant difference between SH and LH for the outcomes VAS pain score, recurrence rate, or postoperative bleeding. Pooled analysis revealed a significant OR in favor of the SH method for recurrent prolapse (OR = 5.529, P = 0.016) for up to 2 years after surgery. No significant differences between the two methods were identified for VAS pain scores (OR = -1.060, P = 0.149) or postoperative bleeding OR = 1.188, P = 0.871). Pooled analysis of RCT results comparing SH to LH for symptomatic hemorrhoids revealed a significantly greater incidence of recurrent prolapse for SH. The two techniques were associated with similar levels of postoperative pain and postoperative bleeding. Copyright © 2013 Surgical Associates Ltd. Published by Elsevier Ltd. All rights reserved.

Identification of Medicinal Mugua Origin by Near Infrared Spectroscopy Combined with Partial Least-squares Discriminant Analysis.

PubMed

Han, Bangxing; Peng, Huasheng; Yan, Hui

2016-01-01

Mugua is a common Chinese herbal medicine. There are three main medicinal origin places in China, Xuancheng City Anhui Province, Qijiang District Chongqing City, Yichang City, Hubei Province, and suitable for food origin places Linyi City Shandong Province. To construct a qualitative analytical method to identify the origin of medicinal Mugua by near infrared spectroscopy (NIRS). Partial least squares discriminant analysis (PLSDA) model was established after the Mugua derived from five different origins were preprocessed by the original spectrum. Moreover, the hierarchical cluster analysis was performed. The result showed that PLSDA model was established. According to the relationship of the origins-related important score and wavenumber, and K-mean cluster analysis, the Muguas derived from different origins were effectively identified. NIRS technology can quickly and accurately identify the origin of Mugua, provide a new method and technology for the identification of Chinese medicinal materials. After preprocessed by D1+autoscale, more peaks were increased in the preprocessed Mugua in the near infrared spectrumFive latent variable scores could reflect the information related to the origin place of MuguaOrigins of Mugua were well-distinguished according to K. mean value clustering analysis. Abbreviations used: TCM: Traditional Chinese Medicine, NIRS: Near infrared spectroscopy, SG: Savitzky-Golay smoothness, D1: First derivative, D2: Second derivative, SNV: Standard normal variable transformation, MSC: Multiplicative scatter correction, PLSDA: Partial least squares discriminant analysis, LV: Latent variable, VIP scores: Important score.

A systems biology strategy to identify molecular mechanisms of action and protein indicators of traumatic brain injury.

PubMed

Yu, Chenggang; Boutté, Angela; Yu, Xueping; Dutta, Bhaskar; Feala, Jacob D; Schmid, Kara; Dave, Jitendra; Tawa, Gregory J; Wallqvist, Anders; Reifman, Jaques

2015-02-01

The multifactorial nature of traumatic brain injury (TBI), especially the complex secondary tissue injury involving intertwined networks of molecular pathways that mediate cellular behavior, has confounded attempts to elucidate the pathology underlying the progression of TBI. Here, systems biology strategies are exploited to identify novel molecular mechanisms and protein indicators of brain injury. To this end, we performed a meta-analysis of four distinct high-throughput gene expression studies involving different animal models of TBI. By using canonical pathways and a large human protein-interaction network as a scaffold, we separately overlaid the gene expression data from each study to identify molecular signatures that were conserved across the different studies. At 24 hr after injury, the significantly activated molecular signatures were nonspecific to TBI, whereas the significantly suppressed molecular signatures were specific to the nervous system. In particular, we identified a suppressed subnetwork consisting of 58 highly interacting, coregulated proteins associated with synaptic function. We selected three proteins from this subnetwork, postsynaptic density protein 95, nitric oxide synthase 1, and disrupted in schizophrenia 1, and hypothesized that their abundance would be significantly reduced after TBI. In a penetrating ballistic-like brain injury rat model of severe TBI, Western blot analysis confirmed our hypothesis. In addition, our analysis recovered 12 previously identified protein biomarkers of TBI. The results suggest that systems biology may provide an efficient, high-yield approach to generate testable hypotheses that can be experimentally validated to identify novel mechanisms of action and molecular indicators of TBI. © 2014 The Authors. Journal of Neuroscience Research Published by Wiley Periodicals, Inc.

High-Resolution Melting (HRM) of Hypervariable Mitochondrial DNA Regions for Forensic Science.

PubMed

Dos Santos Rocha, Alípio; de Amorim, Isis Salviano Soares; Simão, Tatiana de Almeida; da Fonseca, Adenilson de Souza; Garrido, Rodrigo Grazinoli; Mencalha, Andre Luiz

2018-03-01

Forensic strategies commonly are proceeding by analysis of short tandem repeats (STRs); however, new additional strategies have been proposed for forensic science. Thus, this article standardized the high-resolution melting (HRM) of DNA for forensic analyzes. For HRM, mitochondrial DNA (mtDNA) from eight individuals were extracted from mucosa swabs by DNAzol reagent, samples were amplified by PCR and submitted to HRM analysis to identify differences in hypervariable (HV) regions I and II. To confirm HRM, all PCR products were DNA sequencing. The data suggest that is possible discriminate DNA from different samples by HRM curves. Also, uncommon dual-dissociation was identified in a single PCR product, increasing HRM analyzes by evaluation of melting peaks. Thus, HRM is accurate and useful to screening small differences in HVI and HVII regions from mtDNA and increase the efficiency of laboratory routines based on forensic genetics. © 2017 American Academy of Forensic Sciences.

Comparative Performance Analysis of Different Fingerprint Biometric Scanners for Patient Matching.

PubMed

Kasiiti, Noah; Wawira, Judy; Purkayastha, Saptarshi; Were, Martin C

2017-01-01

Unique patient identification within health services is an operational challenge in healthcare settings. Use of key identifiers, such as patient names, hospital identification numbers, national ID, and birth date are often inadequate for ensuring unique patient identification. In addition approximate string comparator algorithms, such as distance-based algorithms, have proven suboptimal for improving patient matching, especially in low-resource settings. Biometric approaches may improve unique patient identification. However, before implementing the technology in a given setting, such as health care, the right scanners should be rigorously tested to identify an optimal package for the implementation. This study aimed to investigate the effects of factors such as resolution, template size, and scan capture area on the matching performance of different fingerprint scanners for use within health care settings. Performance analysis of eight different scanners was tested using the demo application distributed as part of the Neurotech Verifinger SDK 6.0.

P300: Waves Identification with and without Subtraction of Traces

PubMed Central

Romero, Ana Carla Leite; Reis, Ana Cláudia Mirândola Barbosa; Oliveira, Anna Caroline Silva de; Oliveira Simões, Humberto de; Oliveira Junqueira, Cinthia Amorim de; Frizzo, Ana Cláudia Figueiredo

2017-01-01

Introduction  The P300 test requires well-defined and unique criteria, in addition to training for the examiners, for a uniform analysis of studies and to avoid variations and errors in the interpretation of measurement results. Objectives  The objective of this study is to verify whether there are differences in P300 with and without subtraction of traces of standard and nonstandard stimuli. Method  We conducted this study in collaboration with two research electrophysiology laboratories. From Laboratory 1, we selected 40 tests of subjects between 7–44 years, from Laboratory 2, we selected 83 tests of subjects between 18–44 years. We first performed the identification with the nonstandard stimuli; then, we subtracted the nonstandard stimuli from the standard stimuli. The examiners identified the waves, performing a descriptive and comparative analysis of traces with and without subtraction. Results  After a comparative analysis of the traces with and without subtraction, there was no significant difference when compared with analysis of traces in both laboratories, within the conditions, of right ears ( p  = 0.13 and 0.28 for differences between latency and amplitude measurements) and left ears ( p  = 0.15 and 0.09 for differences between latency and amplitude measurements) from Laboratory 1. As for Laboratory 2, when investigating both ears, results did not identify significant differences ( p  = 0.098 and 0.28 for differences between latency and amplitude measurements). Conclusion  There was no difference verified in traces with and without subtraction. We suggest the identification of this potential performed through nonstandard stimuli. PMID:29018497

Metabolite analysis of endophytic fungi from cultivars of Zingiber officinale Rosc. identifies myriad of bioactive compounds including tyrosol.

PubMed

Anisha, C; Radhakrishnan, E K

2017-06-01

Endophytic fungi associated with rhizomes of four cultivars of Zingiber officinale were identified by molecular and morphological methods and evaluated for their activity against soft rot pathogen Pythium myriotylum and clinical pathogens. The volatile bioactive metabolites produced by these isolates were identified by GC-MS analysis of the fungal crude extracts. Understanding of the metabolites produced by endophytes is also important in the context of raw consumption of ginger as medicine and spice. A total of fifteen isolates were identified from the four varieties studied. The various genera identified were Acremonium sp., Gliocladiopsis sp., Fusarium sp., Colletotrichum sp., Aspergillus sp., Phlebia sp., Earliella sp., and Pseudolagarobasidium sp. The endophytic community was unique to each variety, which could be due to the varying host genotype. Fungi from phylum Basidiomycota were identified for the first time from ginger. Seven isolates showed activity against Pythium, while only two showed antibacterial activity. The bioactive metabolites identified in the fungal crude extracts include tyrosol, benzene acetic acid, ergone, dehydromevalonic lactone, N-aminopyrrolidine, and many bioactive fatty acids and their derivatives which included linoleic acid, oleic acid, myristic acid, n-hexadecanoic acid, palmitic acid methyl ester, and methyl linoleate. The presence of these varying bioactive endophytic fungi may be one of the reasons for the differences in the performance of the different ginger varieties.

Individual Differences, Intelligence, and Behavior Analysis

PubMed Central

Williams, Ben; Myerson, Joel; Hale, Sandra

2008-01-01

Despite its avowed goal of understanding individual behavior, the field of behavior analysis has largely ignored the determinants of consistent differences in level of performance among individuals. The present article discusses major findings in the study of individual differences in intelligence from the conceptual framework of a functional analysis of behavior. In addition to general intelligence, we discuss three other major aspects of behavior in which individuals differ: speed of processing, working memory, and the learning of three-term contingencies. Despite recent progress in our understanding of the relations among these aspects of behavior, numerous issues remain unresolved. Researchers need to determine which learning tasks predict individual differences in intelligence and which do not, and then identify the specific characteristics of these tasks that make such prediction possible. PMID:18831127

Predominant yeasts in Chinese traditional sourdough and their influence on aroma formation in Chinese steamed bread.

PubMed

Liu, Tongjie; Li, Yang; Sadiq, Faizan A; Yang, Huanyi; Gu, Jingsi; Yuan, Lei; Lee, Yuan Kun; He, Guoqing

2018-03-01

A total of 105 yeast isolates was obtained from 15 sourdough samples collected from different regions in China and subjected to random amplified polymorphic DNA (RAPD) analysis. Six species were identified including Pichia membranifaciens, which has not previously been reported in Chinese sourdoughs. Different species of yeast were used in single-culture fermentation to make Chinese steamed bread (CSB). The volatiles of the CSB were captured by solid-phase microextraction method, separated and identified by gas chromatography-mass spectrometry. In total, 41 volatile compounds were found in all the steamed breads. All CSBs showed a similar volatile profile; however, significant differences in the quantity of some volatile compounds were seen among the CSB fermented by different yeast species. A partial least squares discriminant analysis showed that the CSBs could be separated by their characteristic volatile profiles. The study suggested that the aromatic properties of CSB are determined by the yeast used. Copyright © 2017 Elsevier Ltd. All rights reserved.

Matrix Effects and Interferences of Different Citrus Fruit Coextractives in Pesticide Residue Analysis Using Ultrahigh-Performance Liquid Chromatography-High-Resolution Mass Spectrometry.

PubMed

Besil, Natalia; Cesio, Verónica; Heinzen, Horacio; Fernandez-Alba, Amadeo R

2017-06-14

The matrix effects of ethyl acetate extracts from seven different citrus fruits on the determination of 80 pesticide residues using liquid chromatography coupled to high-resolution time-of-flight mass spectrometry (UHPLC-(ESI)-HR-TOF) at 4 GHz resolution mode were studied. Only 20% of the evaluated pesticides showed noticeable matrix effects (ME) due to coelution with natural products between t R = 3 and 11 min. Principal component analysis (PCA) of the detected coextractives grouped the mandarins and the orange varieties, but separated lemon, oranges, and mandarins from each other. Matrix effects were different among species but similar between varieties, forcing the determination of pesticide residues through matrix-matched calibration curves with the same fruit. Twenty-three natural products (synephrine, naringin, poncirin, glycosides of hesperitin, limonin, nomilin, and a few fatty acids, among others) were identified in the analyzed extracts. Twelve of the identified compounds coeluted with 28 of the pesticides under study, causing different matrix effects.

Systemic bioinformatics analysis of skeletal muscle gene expression profiles of sepsis

PubMed Central

Yang, Fang; Wang, Yumei

2018-01-01

Sepsis is a type of systemic inflammatory response syndrome with high morbidity and mortality. Skeletal muscle dysfunction is one of the major complications of sepsis that may also influence the outcome of sepsis. The aim of the present study was to explore and identify potential mechanisms and therapeutic targets of sepsis. Systemic bioinformatics analysis of skeletal muscle gene expression profiles from the Gene Expression Omnibus was performed. Differentially expressed genes (DEGs) in samples from patients with sepsis and control samples were screened out using the limma package. Differential co-expression and coregulation (DCE and DCR, respectively) analysis was performed based on the Differential Co-expression Analysis package to identify differences in gene co-expression and coregulation patterns between the control and sepsis groups. Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways of DEGs were identified using the Database for Annotation, Visualization and Integrated Discovery, and inflammatory, cancer and skeletal muscle development-associated biological processes and pathways were identified. DCE and DCR analysis revealed several potential therapeutic targets for sepsis, including genes and transcription factors. The results of the present study may provide a basis for the development of novel therapeutic targets and treatment methods for sepsis. PMID:29805480

Identifiability of PBPK Models with Applications to ...

EPA Pesticide Factsheets

Any statistical model should be identifiable in order for estimates and tests using it to be meaningful. We consider statistical analysis of physiologically-based pharmacokinetic (PBPK) models in which parameters cannot be estimated precisely from available data, and discuss different types of identifiability that occur in PBPK models and give reasons why they occur. We particularly focus on how the mathematical structure of a PBPK model and lack of appropriate data can lead to statistical models in which it is impossible to estimate at least some parameters precisely. Methods are reviewed which can determine whether a purely linear PBPK model is globally identifiable. We propose a theorem which determines when identifiability at a set of finite and specific values of the mathematical PBPK model (global discrete identifiability) implies identifiability of the statistical model. However, we are unable to establish conditions that imply global discrete identifiability, and conclude that the only safe approach to analysis of PBPK models involves Bayesian analysis with truncated priors. Finally, computational issues regarding posterior simulations of PBPK models are discussed. The methodology is very general and can be applied to numerous PBPK models which can be expressed as linear time-invariant systems. A real data set of a PBPK model for exposure to dimethyl arsinic acid (DMA(V)) is presented to illustrate the proposed methodology. We consider statistical analy

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

PubMed

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

2015-11-02

Schizophrenia is a severe, disabling and prevalent mental disorder without cure and with a variable, incomplete pharmacotherapeutic response. Prior to onset in adolescence or young adulthood a prodromal period of abnormal symptoms lasting weeks to years has been identified and operationalized as clinically high risk (CHR) for schizophrenia. However, only a minority of subjects prospectively identified with CHR convert to schizophrenia, thereby limiting enthusiasm for early intervention(s). This study utilized objective resting electroencephalogram (EEG) quantification to determine whether CHR constitutes a cohesive entity and an evoked potential to assess CHR cortical auditory processing. This study constitutes an EEG-based quantitative neurophysiological comparison between two unmedicated subject groups: 35 neurotypical controls (CON) and 22 CHR patients. After artifact management, principal component analysis (PCA) identified EEG spectral and spectral coherence factors described by associated loading patterns. Discriminant function analysis (DFA) determined factors' discrimination success between subjects in the CON and CHR groups. Loading patterns on DFA-selected factors described CHR-specific spectral and coherence differences when compared to controls. The frequency modulated auditory evoked response (FMAER) explored functional CON-CHR differences within the superior temporal gyri. Variable reduction by PCA identified 40 coherence-based factors explaining 77.8% of the total variance and 40 spectral factors explaining 95.9% of the variance. DFA demonstrated significant CON-CHR group difference (P <0.00001) and successful jackknifed subject classification (CON, 85.7%; CHR, 86.4% correct). The population distribution plotted along the canonical discriminant variable was clearly bimodal. Coherence factors delineated loading patterns of altered connectivity primarily involving the bilateral posterior temporal electrodes. However, FMAER analysis showed no CON-CHR group differences. CHR subjects form a cohesive group, significantly separable from CON subjects by EEG-derived indices. Symptoms of CHR may relate to altered connectivity with the posterior temporal regions but not to primary auditory processing abnormalities within these regions.

Comparative Study on Synergetic Degradation of a Reactive Dye Using Different Types of Fly Ash in Combined Adsorption and Photocatalysis

NASA Astrophysics Data System (ADS)

Giri Babu, P. V. S.; Swaminathan, G.

2016-09-01

A comprehensive study was carried out on four different fly ashes used as a catalyst for the degradation of Acid Red 1 using ultraviolet rays. These fly ashes are collected from different thermal power stations located at various places in India and having different chemical compositions. Three fly ashes are from lignite-based thermal power plants, and one is from the coal-based power plant. One fly ash is classified as Class F, two fly ashes are classified as Class C and remaining one is not conforming to ASTM C618 classification. X-Ray Fluorescence analysis was used to identify the chemical composition of fly ashes and SiO2, Al2O3, CaO, Fe2O3 and TiO2 were found to be the major elements present in different proportions. Various analysis were carried out on all the fly ashes like Scanning Electron Microscopy to identify the microphysical properties, Energy Dispersive X-Ray spectroscopy to quantify the elements present in the catalyst and X-Ray Diffraction to identify the catalyst phase analysis. The radical generated during the reaction was identified by Electron paramagnetic resonance spectroscopy. The parameters such as initial pH of the dye solution, catalyst dosage and initial dye concentration which influence the dye degradation efficiency were studied and optimised. In 60 min duration, the dye degradation efficiency at optimum parametric values of pH 2.5, initial dye concentration of 10 mg/L and catalyst dosage of 1.0 g/L using various fly ashes, i.e., Salam Power Plant, Barmer Lignite Power Plant, Kutch Lignite Power Plant and Neyveli Lignite Thermal Power plant (NLTP) were found to be 40, 60, 67 and 95 % respectively. The contribution of adsorption alone was 18 % at the above mentioned optimum parametric values. Among the above four fly ash NLTP fly ashes proved to be most efficient.

Nonlinear truncation error analysis of finite difference schemes for the Euler equations

NASA Technical Reports Server (NTRS)

Klopfer, G. H.; Mcrae, D. S.

1983-01-01

It is pointed out that, in general, dissipative finite difference integration schemes have been found to be quite robust when applied to the Euler equations of gas dynamics. The present investigation considers a modified equation analysis of both implicit and explicit finite difference techniques as applied to the Euler equations. The analysis is used to identify those error terms which contribute most to the observed solution errors. A technique for analytically removing the dominant error terms is demonstrated, resulting in a greatly improved solution for the explicit Lax-Wendroff schemes. It is shown that the nonlinear truncation errors are quite large and distributed quite differently for each of the three conservation equations as applied to a one-dimensional shock tube problem.

Identifying management competencies for health care executives: review of a series of Delphi studies.

PubMed

Hudak, R P; Brooke, P P; Finstuen, K

2000-01-01

This analysis reviews a selected body of research that identifies the essential areas of management expertise required of future health care executives. To ensure consistency, six studies are analyzed, utilizing the Delphi technique, to query a broad spectrum of experts in different fields and sites of health care management. The analysis identifies a number of management competencies, i.e., managerial capabilities, which current and aspiring health care executives, in various settings and with differing educational backgrounds, should possess to enhance the probability of their success in current and future positions of responsibility. In addition, this review identifies the skills (technical expertise), knowledge (facts and principles) and abilities (physical, mental or legal power) required to support achievement of these competencies. Leadership and resource management, including cost and finance dimensions, are the highest-rated requisite management competencies. The dominant skills, knowledge and abilities (SKAs) are related to interpersonal skills. The lowest-rated SKAs are related to job-specific, technical skills. Recommendations include the review of this research by formal and continuing education programs to determine the content of their courses and areas for future research. Similarly, current health care executives should assess this research to assist in identifying competency gaps. Lastly, this analysis recommends that the Delphi technique, as a valid and replicable methodology, be applied toward the study of non-executive health care managers, e.g., students, clinicians, mid-level managers and integrated systems administrators, to determine their requisite management competencies and SKAs.

Age determination by teeth examination: a comparison between different morphologic and quantitative analyses.

PubMed

Amariti, M L; Restori, M; De Ferrari, F; Paganelli, C; Faglia, R; Legnani, G

1999-06-01

Age determination by teeth examination is one of the main means of determining personal identification. Current studies have suggested different techniques for determining the age of a subject by means of the analysis of microscopic and macroscopic structural modifications of the tooth with ageing. The histological approach is useful among the various methodologies utilized for this purpose. It is still unclear as to what is the best technique, as almost all the authors suggest the use of the approach they themselves have tested. In the present study, age determination by means of microscopic techniques has been based on the quantitative analysis of three parameters, all well recognized in specialized literature: 1. dentinal tubules density/sclerosis 2. tooth translucency 3. analysis of the cementum thickness. After a description of the three methodologies (with automatic image processing of the dentinal sclerosis utilizing an appropriate computer program developed by the authors) the results obtained on cases using the three different approaches are presented, and the merits and failings of each technique are identified with the intention of identifying the one offering the least degree of error in age determination.

A Method for Populating the Knowledge Base of AFIT’s Domain-Oriented Application Composition System

DTIC Science & Technology

1993-12-01

Analysis ( FODA ). The approach identifies prominent features (similarities) and distinctive features (differences) of software systems within an... analysis approaches we have summarized, the re- searchers described FODA in sufficient detail to use on large domain analysis projects (ones with...Software Technology Center, July 1991. 18. Kang, Kyo C. and others. Feature-Oriented Domain Analysis ( FODA ) Feasibility Study. Technical Report, Software

Spaceborne power systems preference analyses. Volume 1: Summary

NASA Technical Reports Server (NTRS)

Smith, J. H.; Feinberg, A.; Miles, R. F., Jr.

1985-01-01

Sixteen alternative spaceborne nuclear power system concepts were ranked using multiattribute decision analysis to identify promising concepts for further technology development. Four groups interviewed were: safety, systems definition and design, technology assessment, and mission analysis. The ranking results were consistent from group and for different utility function models for individuals.

Students' Self-Identified Long-Term Leadership Development Goals: An Analysis by Gender and Race

ERIC Educational Resources Information Center

Rosch, David M.; Boyd, Barry L.; Duran, Kristina M.

2014-01-01

Leadership development goal statements of 92 undergraduate students enrolled in a multi-year self-directed leadership development program were analyzed using content and thematic analyses to investigate patterns of similarities and differences across gender and race. This qualitative analysis utilized a theoretical framework that approached…

The Concerns about Counseling Racial Minority Clients Scale

ERIC Educational Resources Information Center

Wei, Meifen; Chao, Ruth Chu-Lien; Tsai, Pei-Chun; Botello-Zamarron, Raquel

2012-01-01

The purpose of this study was to develop and validate the Concerns about Counseling Racial Minority Clients (CCRMC) scale among counselor trainees. Sample 1 was used for an exploratory factor analysis and confirmatory factor analysis. Four factors were identified, Managing Cultural Differences ([alpha] = 0.82), Offending or Hurting Clients…

A Statewide Analysis of RNs' Intention To Leave Their Position.

ERIC Educational Resources Information Center

Rambur, Betty; Palumbo, Mary Val; McIntosh, Barbara; Mongeon, Joan

2003-01-01

Secondary analysis of registered nurse work force data from Vermont (n=4,418, 85% response) identified predictors of intention to leave current position. Differences in intention vary by educational attainment, hours worked, gender, practice role, and practice activity. Improving retention will require increased attention to compensation,…

A Latent Class Analysis of Dyadic Perfectionism in a College Sample

ERIC Educational Resources Information Center

Lopez, Frederick G.; Fons-Scheyd, Alia; Bush-King, Imelda; McDermott, Ryon C.

2011-01-01

A latent class analysis of dyadic perfectionism scores within a college sample (N = 369) identified four classes of participants. Controlling for gender and current dating status, class membership was associated with significant differences on several measures of relationship attitudes. Gender and class membership also significantly interacted in…

Analysis of a Suspected Drug Sample

ERIC Educational Resources Information Center

Schurter, Eric J.; Zook-Gerdau, Lois Anne; Szalay, Paul

2011-01-01

This general chemistry laboratory uses differences in solubility to separate a mixture of caffeine and aspirin while introducing the instrumental analysis methods of GCMS and FTIR. The drug mixture is separated by partitioning aspirin and caffeine between dichloromethane and aqueous base. TLC and reference standards are used to identify aspirin…

Differences in X-chromosome transcriptional activity and cholesterol metabolism between placentae from swine breeds from Asian and Western origins.

PubMed

Bischoff, Steve R; Tsai, Shengdar Q; Hardison, Nicholas E; Motsinger-Reif, Alison A; Freking, Bradley A; Nonneman, Dan J; Rohrer, Gary A; Piedrahita, Jorge A

2013-01-01

To gain insight into differences in placental physiology between two swine breeds noted for their dissimilar reproductive performance, that is, the Chinese Meishan and white composite (WC), we examined gene expression profiles of placental tissues collected at 25, 45, 65, 85, and 105 days of gestation by microarrays. Using a linear mixed model, a total of 1,595 differentially expressed genes were identified between the two pig breeds using a false-discovery rate q-value ≤0.05. Among these genes, we identified breed-specific isoforms of XIST, a long non-coding RNA responsible X-chromosome dosage compensation in females. Additionally, we explored the interaction of placental gene expression and chromosomal location by DIGMAP and identified three Sus scrofa X chromosomal bands (Xq13, Xq21, Xp11) that represent transcriptionally active clusters that differ between Meishan and WC during placental development. Also, pathway analysis identified fundamental breed differences in placental cholesterol trafficking and its synthesis. Direct measurement of cholesterol confirmed that the cholesterol content was significantly higher in the Meishan versus WC placentae. Taken together, this work identifies key metabolic pathways that differ in the placentae of two swine breeds noted for differences in reproductive prolificacy.

Origin Discrimination of Osmanthus fragrans var. thunbergii Flowers using GC-MS and UPLC-PDA Combined with Multivariable Analysis Methods.

PubMed

Zhou, Fei; Zhao, Yajing; Peng, Jiyu; Jiang, Yirong; Li, Maiquan; Jiang, Yuan; Lu, Baiyi

2017-07-01

Osmanthus fragrans flowers are used as folk medicine and additives for teas, beverages and foods. The metabolites of O. fragrans flowers from different geographical origins were inconsistent in some extent. Chromatography and mass spectrometry combined with multivariable analysis methods provides an approach for discriminating the origin of O. fragrans flowers. To discriminate the Osmanthus fragrans var. thunbergii flowers from different origins with the identified metabolites. GC-MS and UPLC-PDA were conducted to analyse the metabolites in O. fragrans var. thunbergii flowers (in total 150 samples). Principal component analysis (PCA), soft independent modelling of class analogy analysis (SIMCA) and random forest (RF) analysis were applied to group the GC-MS and UPLC-PDA data. GC-MS identified 32 compounds common to all samples while UPLC-PDA/QTOF-MS identified 16 common compounds. PCA of the UPLC-PDA data generated a better clustering than PCA of the GC-MS data. Ten metabolites (six from GC-MS and four from UPLC-PDA) were selected as effective compounds for discrimination by PCA loadings. SIMCA and RF analysis were used to build classification models, and the RF model, based on the four effective compounds (caffeic acid derivative, acteoside, ligustroside and compound 15), yielded better results with the classification rate of 100% in the calibration set and 97.8% in the prediction set. GC-MS and UPLC-PDA combined with multivariable analysis methods can discriminate the origin of Osmanthus fragrans var. thunbergii flowers. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Statistical Test of Expression Pattern (STEPath): a new strategy to integrate gene expression data with genomic information in individual and meta-analysis studies.

PubMed

Martini, Paolo; Risso, Davide; Sales, Gabriele; Romualdi, Chiara; Lanfranchi, Gerolamo; Cagnin, Stefano

2011-04-11

In the last decades, microarray technology has spread, leading to a dramatic increase of publicly available datasets. The first statistical tools developed were focused on the identification of significant differentially expressed genes. Later, researchers moved toward the systematic integration of gene expression profiles with additional biological information, such as chromosomal location, ontological annotations or sequence features. The analysis of gene expression linked to physical location of genes on chromosomes allows the identification of transcriptionally imbalanced regions, while, Gene Set Analysis focuses on the detection of coordinated changes in transcriptional levels among sets of biologically related genes. In this field, meta-analysis offers the possibility to compare different studies, addressing the same biological question to fully exploit public gene expression datasets. We describe STEPath, a method that starts from gene expression profiles and integrates the analysis of imbalanced region as an a priori step before performing gene set analysis. The application of STEPath in individual studies produced gene set scores weighted by chromosomal activation. As a final step, we propose a way to compare these scores across different studies (meta-analysis) on related biological issues. One complication with meta-analysis is batch effects, which occur because molecular measurements are affected by laboratory conditions, reagent lots and personnel differences. Major problems occur when batch effects are correlated with an outcome of interest and lead to incorrect conclusions. We evaluated the power of combining chromosome mapping and gene set enrichment analysis, performing the analysis on a dataset of leukaemia (example of individual study) and on a dataset of skeletal muscle diseases (meta-analysis approach). In leukaemia, we identified the Hox gene set, a gene set closely related to the pathology that other algorithms of gene set analysis do not identify, while the meta-analysis approach on muscular disease discriminates between related pathologies and correlates similar ones from different studies. STEPath is a new method that integrates gene expression profiles, genomic co-expressed regions and the information about the biological function of genes. The usage of the STEPath-computed gene set scores overcomes batch effects in the meta-analysis approaches allowing the direct comparison of different pathologies and different studies on a gene set activation level.

A regulation probability model-based meta-analysis of multiple transcriptomics data sets for cancer biomarker identification.

PubMed

Xie, Xin-Ping; Xie, Yu-Feng; Wang, Hong-Qiang

2017-08-23

Large-scale accumulation of omics data poses a pressing challenge of integrative analysis of multiple data sets in bioinformatics. An open question of such integrative analysis is how to pinpoint consistent but subtle gene activity patterns across studies. Study heterogeneity needs to be addressed carefully for this goal. This paper proposes a regulation probability model-based meta-analysis, jGRP, for identifying differentially expressed genes (DEGs). The method integrates multiple transcriptomics data sets in a gene regulatory space instead of in a gene expression space, which makes it easy to capture and manage data heterogeneity across studies from different laboratories or platforms. Specifically, we transform gene expression profiles into a united gene regulation profile across studies by mathematically defining two gene regulation events between two conditions and estimating their occurring probabilities in a sample. Finally, a novel differential expression statistic is established based on the gene regulation profiles, realizing accurate and flexible identification of DEGs in gene regulation space. We evaluated the proposed method on simulation data and real-world cancer datasets and showed the effectiveness and efficiency of jGRP in identifying DEGs identification in the context of meta-analysis. Data heterogeneity largely influences the performance of meta-analysis of DEGs identification. Existing different meta-analysis methods were revealed to exhibit very different degrees of sensitivity to study heterogeneity. The proposed method, jGRP, can be a standalone tool due to its united framework and controllable way to deal with study heterogeneity.

Ole e 13 is the unique food allergen in olive: Structure-functional, substrates docking, and molecular allergenicity comparative analysis.

PubMed

Jimenez-Lopez, J C; Robles-Bolivar, P; Lopez-Valverde, F J; Lima-Cabello, E; Kotchoni, S O; Alché, J D

2016-05-01

Thaumatin-like proteins (TLPs) are enzymes with important functions in pathogens defense and in the response to biotic and abiotic stresses. Last identified olive allergen (Ole e 13) is a TLP, which may also importantly contribute to food allergy and cross-allergenicity to pollen allergen proteins. The goals of this study are the characterization of the structural-functionality of Ole e 13 with a focus in its catalytic mechanism, and its molecular allergenicity by extensive analysis using different molecular computer-aided approaches covering a) functional-regulatory motifs, b) comparative study of linear sequence, 2-D and 3D structural homology modeling, c) molecular docking with two different β-D-glucans, d) conservational and evolutionary analysis, e) catalytic mechanism modeling, and f) IgE-binding, B- and T-cell epitopes identification and comparison to other allergenic TLPs. Sequence comparison, structure-based features, and phylogenetic analysis identified Ole e 13 as a thaumatin-like protein. 3D structural characterization revealed a conserved overall folding among plants TLPs, with mayor differences in the acidic (catalytic) cleft. Molecular docking analysis using two β-(1,3)-glucans allowed to identify fundamental residues involved in the endo-1,3-β-glucanase activity, and defining E84 as one of the conserved residues of the TLPs responsible of the nucleophilic attack to initiate the enzymatic reaction and D107 as proton donor, thus proposing a catalytic mechanism for Ole e 13. Identification of IgE-binding, B- and T-cell epitopes may help designing strategies to improve diagnosis and immunotherapy to food allergy and cross-allergenic pollen TLPs. Copyright © 2016 Elsevier Inc. All rights reserved.

Genotyping of Chromobacterium violaceum isolates by recA PCR-RFLP analysis.

PubMed

Scholz, Holger Christian; Witte, Angela; Tomaso, Herbert; Al Dahouk, Sascha; Neubauer, Heinrich

2005-03-15

Intraspecies variation of Chromobacterium violaceum was examined by comparative sequence - and by restriction fragment length polymorphism analysis of the recombinase A gene (recA-PCR-RFLP). Primers deduced from the known recA gene sequence of the type strain C. violaceum ATCC 12472(T) allowed the specific amplification of a 1040bp recA fragment from each of the 13 C. violaceum strains investigated, whereas other closely related organisms tested negative. HindII-PstI-recA RFLP analysis generated from 13 representative C. violaceum strains enabled us to identify at least three different genospecies. In conclusion, analysis of the recA gene provides a rapid and robust nucleotide sequence-based approach to specifically identify and classify C. violaceum on genospecies level.

Identification of atmospheric organic sources using the carbon hollow tube-gas chromatography method and factor analysis

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

Cobb, G.P.; Braman, R.S.; Gilbert, R.A.

Atmospheric organics were sampled and analyzed by using the carbon hollow tube-gas chromatography method. Chromatograms from spice mixtures, cigarettes, and ambient air were analyzed. Principal factor analysis of row order chromatographic data produces factors which are eigenchromatograms of the components in the samples. Component sources are identified from the eigenchromatograms in all experiments and the individual eigenchromatogram corresponding to a particular source is determined in most cases. Organic sources in ambient air and in cigaretts are identified with 87% certainty. Analysis of clove cigarettes allows the determination of the relative amount of clove in different cigarettes. A new nondestructive qualitymore » control method using the hollow tube-gas chromatography analysis is discussed.« less

Spatial and Temporal Dust Source Variability in Northern China Identified Using Advanced Remote Sensing Analysis

NASA Technical Reports Server (NTRS)

Taramelli, A.; Pasqui, M.; Barbour, J.; Kirschbaum, D.; Bottai, L.; Busillo, C.; Calastrini, F.; Guarnieri, F.; Small, C.

2013-01-01

The aim of this research is to provide a detailed characterization of spatial patterns and temporal trends in the regional and local dust source areas within the desert of the Alashan Prefecture (Inner Mongolia, China). This problem was approached through multi-scale remote sensing analysis of vegetation changes. The primary requirements for this regional analysis are high spatial and spectral resolution data, accurate spectral calibration and good temporal resolution with a suitable temporal baseline. Landsat analysis and field validation along with the low spatial resolution classifications from MODIS and AVHRR are combined to provide a reliable characterization of the different potential dust-producing sources. The representation of intra-annual and inter-annual Normalized Difference Vegetation Index (NDVI) trend to assess land cover discrimination for mapping potential dust source using MODIS and AVHRR at larger scale is enhanced by Landsat Spectral Mixing Analysis (SMA). The combined methodology is to determine the extent to which Landsat can distinguish important soils types in order to better understand how soil reflectance behaves at seasonal and inter-annual timescales. As a final result mapping soil surface properties using SMA is representative of responses of different land and soil cover previously identified by NDVI trend. The results could be used in dust emission models even if they are not reflecting aggregate formation, soil stability or particle coatings showing to be critical for accurately represent dust source over different regional and local emitting areas.

A Novel Feature-Map Based ICA Model for Identifying the Individual, Intra/Inter-Group Brain Networks across Multiple fMRI Datasets.

PubMed

Wang, Nizhuan; Chang, Chunqi; Zeng, Weiming; Shi, Yuhu; Yan, Hongjie

2017-01-01

Independent component analysis (ICA) has been widely used in functional magnetic resonance imaging (fMRI) data analysis to evaluate functional connectivity of the brain; however, there are still some limitations on ICA simultaneously handling neuroimaging datasets with diverse acquisition parameters, e.g., different repetition time, different scanner, etc. Therefore, it is difficult for the traditional ICA framework to effectively handle ever-increasingly big neuroimaging datasets. In this research, a novel feature-map based ICA framework (FMICA) was proposed to address the aforementioned deficiencies, which aimed at exploring brain functional networks (BFNs) at different scales, e.g., the first level (individual subject level), second level (intragroup level of subjects within a certain dataset) and third level (intergroup level of subjects across different datasets), based only on the feature maps extracted from the fMRI datasets. The FMICA was presented as a hierarchical framework, which effectively made ICA and constrained ICA as a whole to identify the BFNs from the feature maps. The simulated and real experimental results demonstrated that FMICA had the excellent ability to identify the intergroup BFNs and to characterize subject-specific and group-specific difference of BFNs from the independent component feature maps, which sharply reduced the size of fMRI datasets. Compared with traditional ICAs, FMICA as a more generalized framework could efficiently and simultaneously identify the variant BFNs at the subject-specific, intragroup, intragroup-specific and intergroup levels, implying that FMICA was able to handle big neuroimaging datasets in neuroscience research.

Research priorities by professional background - A detailed analysis of the James Lind Alliance Priority Setting Partnership.

PubMed

Arulkumaran, Nishkantha; Reay, Hannah; Brett, Stephen J

2016-05-01

The Intensive Care Foundation, in partnership with the James Lind Alliance, has supported a national project to identify and prioritise unanswered questions about adult intensive care that are important to people who have been critically ill, their families, and the health professionals who care for them. We conducted a secondary analysis to explore differences in priorities determined by different respondent groups in order to identify different groups' perceptions of gaps in knowledge. There were two surveys conducted as part of the original project. Survey 1 comprised a single open question to identify important research topics; survey 2 aimed to prioritise these topics using a 10-point Likert scale. In survey 1, despite clear differences in suggestions amongst the respondent groups, themes of comfort/communication and post-ICU rehabilitation were the within the top 2 suggestions across all groups. Patients and relatives suggested research topics to which they could easily relate, whereas there was a greater breadth of suggestions from clinicians. In survey 2, the number of research priorities that received a mode score of 10 varied from 1 to 36. Patients scored 36 out of the 37 topics with a mode score of 10. All other groups scored topics with more discrimination, with the number of topics with a mode score of 10 ranging from 1 to 20. Differences in the proportions of the representative groups are therefore unlikely to have translated to an impartial conclusion. Clinicians, patients, and family members have jointly identified the research priorities for UK ICM practice.

Real-space analysis of radiation-induced specific changes with independent component analysis

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

Borek, Dominika; Bromberg, Raquel; Hattne, Johan

A method of analysis is presented that allows for the separation of specific radiation-induced changes into distinct components in real space. The method relies on independent component analysis (ICA) and can be effectively applied to electron density maps and other types of maps, provided that they can be represented as sets of numbers on a grid. Here, for glucose isomerase crystals, ICA was used in a proof-of-concept analysis to separate temperature-dependent and temperature-independent components of specific radiation-induced changes for data sets acquired from multiple crystals across multiple temperatures. ICA identified two components, with the temperature-independent component being responsible for themore » majority of specific radiation-induced changes at temperatures below 130 K. The patterns of specific temperature-independent radiation-induced changes suggest a contribution from the tunnelling of electron holes as a possible explanation. In the second case, where a group of 22 data sets was collected on a single thaumatin crystal, ICA was used in another type of analysis to separate specific radiation-induced effects happening on different exposure-level scales. Here, ICA identified two components of specific radiation-induced changes that likely result from radiation-induced chemical reactions progressing with different rates at different locations in the structure. In addition, ICA unexpectedly identified the radiation-damage state corresponding to reduced disulfide bridges rather than the zero-dose extrapolated state as the highest contrast structure. The application of ICA to the analysis of specific radiation-induced changes in real space and the data pre-processing for ICA that relies on singular value decomposition, which was used previously in data space to validate a two-component physical model of X-ray radiation-induced changes, are discussed in detail. This work lays a foundation for a better understanding of protein-specific radiation chemistries and provides a framework for analysing effects of specific radiation damage in crystallographic and cryo-EM experiments.« less

NAEP Trends: Main NAEP vs. Long-Term Trend

ERIC Educational Resources Information Center

Beaton, Albert E.; Chromy, James R.

2010-01-01

The objectives of this research are to (a) compare the trend lines after some adjustments for level and scale only and determine if and how they differ; (b) describe the methodology of each assessment and identify similarities and differences; and (c) attempt to explain any observed differences based on comparable subsets or on special analysis.…

A Comparative Study of the Effects of Cultural Differences on the Adoption of Mobile Learning

ERIC Educational Resources Information Center

Arpaci, Ibrahim

2015-01-01

The objective of this paper is to understand the impact of cultural differences on mobile learning adoption through identifying key adoption characteristics in Canada and Turkey, which have markedly different cultural backgrounds. A multi-group analysis was employed to test the hypothesised relationships based on the data collected by means of…

Influence of aging on the neural correlates of autobiographical, episodic, and semantic memory retrieval.

PubMed

St-Laurent, Marie; Abdi, Hervé; Burianová, Hana; Grady, Cheryl L

2011-12-01

We used fMRI to assess the neural correlates of autobiographical, semantic, and episodic memory retrieval in healthy young and older adults. Participants were tested with an event-related paradigm in which retrieval demand was the only factor varying between trials. A spatio-temporal partial least square analysis was conducted to identify the main patterns of activity characterizing the groups across conditions. We identified brain regions activated by all three memory conditions relative to a control condition. This pattern was expressed equally in both age groups and replicated previous findings obtained in a separate group of younger adults. We also identified regions whose activity differentiated among the different memory conditions. These patterns of differentiation were expressed less strongly in the older adults than in the young adults, a finding that was further confirmed by a barycentric discriminant analysis. This analysis showed an age-related dedifferentiation in autobiographical and episodic memory tasks but not in the semantic memory task or the control condition. These findings suggest that the activation of a common memory retrieval network is maintained with age, whereas the specific aspects of brain activity that differ with memory content are more vulnerable and less selectively engaged in older adults. Our results provide a potential neural mechanism for the well-known age differences in episodic/autobiographical memory, and preserved semantic memory, observed when older adults are compared with younger adults.

Comparative Transcriptome Profiling of Rice Near-Isogenic Line Carrying Xa23 under Infection of Xanthomonas oryzae pv. oryzae.

PubMed

Tariq, Rezwan; Wang, Chunlian; Qin, Tengfei; Xu, Feifei; Tang, Yongchao; Gao, Ying; Ji, Zhiyuan; Zhao, Kaijun

2018-03-02

Bacterial blight, caused by Xanthomonas oryzae pv. oryzae ( Xoo ), is an overwhelming disease in rice-growing regions worldwide. Our previous studies revealed that the executor R gene Xa23 confers broad-spectrum disease resistance to all naturally occurring biotypes of Xoo . In this study, comparative transcriptomic profiling of two near-isogenic lines (NILs), CBB23 (harboring Xa23 ) and JG30 (without Xa23 ), before and after infection of the Xoo strain, PXO99 A , was done by RNA sequencing, to identify genes associated with the resistance. After high throughput sequencing, 1645 differentially expressed genes (DEGs) were identified between CBB23 and JG30 at different time points. Gene Ontlogy (GO) analysis categorized the DEGs into biological process, molecular function, and cellular component. KEGG analysis categorized the DEGs into different pathways, and phenylpropanoid biosynthesis was the most prominent pathway, followed by biosynthesis of plant hormones, flavonoid biosynthesis, and glycolysis/gluconeogenesis. Further analysis led to the identification of differentially expressed transcription factors (TFs) and different kinase responsive genes in CBB23, than that in JG30. Besides TFs and kinase responsive genes, DEGs related to ethylene, jasmonic acid, and secondary metabolites were also identified in both genotypes after PXO99 A infection. The data of DEGs are a precious resource for further clarifying the network of Xa23 -mediated resistance.

Comparative Transcriptome Profiling of Rice Near-Isogenic Line Carrying Xa23 under Infection of Xanthomonas oryzae pv. oryzae

PubMed Central

Tariq, Rezwan; Wang, Chunlian; Qin, Tengfei; Xu, Feifei; Tang, Yongchao; Gao, Ying; Ji, Zhiyuan; Zhao, Kaijun

2018-01-01

Bacterial blight, caused by Xanthomonas oryzae pv. oryzae (Xoo), is an overwhelming disease in rice-growing regions worldwide. Our previous studies revealed that the executor R gene Xa23 confers broad-spectrum disease resistance to all naturally occurring biotypes of Xoo. In this study, comparative transcriptomic profiling of two near-isogenic lines (NILs), CBB23 (harboring Xa23) and JG30 (without Xa23), before and after infection of the Xoo strain, PXO99A, was done by RNA sequencing, to identify genes associated with the resistance. After high throughput sequencing, 1645 differentially expressed genes (DEGs) were identified between CBB23 and JG30 at different time points. Gene Ontlogy (GO) analysis categorized the DEGs into biological process, molecular function, and cellular component. KEGG analysis categorized the DEGs into different pathways, and phenylpropanoid biosynthesis was the most prominent pathway, followed by biosynthesis of plant hormones, flavonoid biosynthesis, and glycolysis/gluconeogenesis. Further analysis led to the identification of differentially expressed transcription factors (TFs) and different kinase responsive genes in CBB23, than that in JG30. Besides TFs and kinase responsive genes, DEGs related to ethylene, jasmonic acid, and secondary metabolites were also identified in both genotypes after PXO99A infection. The data of DEGs are a precious resource for further clarifying the network of Xa23-mediated resistance. PMID:29498672

De novo comparative transcriptome analysis of genes involved in fruit morphology of pumpkin cultivars with extreme size difference and development of EST-SSR markers.

PubMed

Xanthopoulou, Aliki; Ganopoulos, Ioannis; Psomopoulos, Fotis; Manioudaki, Maria; Moysiadis, Theodoros; Kapazoglou, Aliki; Osathanunkul, Maslin; Michailidou, Sofia; Kalivas, Apostolos; Tsaftaris, Athanasios; Nianiou-Obeidat, Irini; Madesis, Panagiotis

2017-07-30

The genetic basis of fruit size and shape was investigated for the first time in Cucurbita species and genetic loci associated with fruit morphology have been identified. Although extensive genomic resources are available at present for tomato (Solanum lycopersicum), cucumber (Cucumis sativus), melon (Cucumis melo) and watermelon (Citrullus lanatus), genomic databases for Cucurbita species are limited. Recently, our group reported the generation of pumpkin (Cucurbita pepo) transcriptome databases from two contrasting cultivars with extreme fruit sizes. In the current study we used these databases to perform comparative transcriptome analysis in order to identify genes with potential roles in fruit morphology and fruit size. Differential Gene Expression (DGE) analysis between cv. 'Munchkin' (small-fruit) and cv. 'Big Moose' (large-fruit) revealed a variety of candidate genes associated with fruit morphology with significant differences in gene expression between the two cultivars. In addition, we have set the framework for generating EST-SSR markers, which discriminate different C. pepo cultivars and show transferability to related Cucurbitaceae species. The results of the present study will contribute to both further understanding the molecular mechanisms regulating fruit morphology and furthermore identifying the factors that determine fruit size. Moreover, they may lead to the development of molecular marker tools for selecting genotypes with desired morphological traits. Copyright © 2017. Published by Elsevier B.V.

Seizure semiology identifies patients with bilateral temporal lobe epilepsy.

PubMed

Loesch, Anna Mira; Feddersen, Berend; Tezer, F Irsel; Hartl, Elisabeth; Rémi, Jan; Vollmar, Christian; Noachtar, Soheyl

2015-01-01

Laterality in temporal lobe epilepsy is usually defined by EEG and imaging results. We investigated whether the analysis of seizure semiology including lateralizing seizure phenomena identifies bilateral independent temporal lobe seizure onset. We investigated the seizure semiology in 17 patients in whom invasive EEG-video-monitoring documented bilateral temporal seizure onset. The results were compared to 20 left and 20 right consecutive temporal lobe epilepsy (TLE) patients who were seizure free after anterior temporal lobe resection. The seizure semiology was analyzed using the semiological seizure classification with particular emphasis on the sequence of seizure phenomena over time and lateralizing seizure phenomena. Statistical analysis included chi-square test or Fisher's exact test. Bitemporal lobe epilepsy patients had more frequently different seizure semiology (100% vs. 40%; p<0.001) and significantly more often lateralizing seizure phenomena pointing to bilateral seizure onset compared to patients with unilateral TLE (67% vs. 11%; p<0.001). The sensitivity of identical vs. different seizure semiology for the identification of bilateral TLE was high (100%) with a specificity of 60%. Lateralizing seizure phenomena had a low sensitivity (59%) but a high specificity (89%). The combination of lateralizing seizure phenomena and different seizure semiology showed a high specificity (94%) but a low sensitivity (59%). The analysis of seizure semiology including lateralizing seizure phenomena adds important clinical information to identify patients with bilateral TLE. Copyright © 2014 Elsevier B.V. All rights reserved.

Multivariate classification of small order watersheds in the Quabbin Reservoir Basin, Massachusetts

USGS Publications Warehouse

Lent, R.M.; Waldron, M.C.; Rader, J.C.

1998-01-01

A multivariate approach was used to analyze hydrologic, geologic, geographic, and water-chemistry data from small order watersheds in the Quabbin Reservoir Basin in central Massachusetts. Eighty three small order watersheds were delineated and landscape attributes defining hydrologic, geologic, and geographic features of the watersheds were compiled from geographic information system data layers. Principal components analysis was used to evaluate 11 chemical constituents collected bi-weekly for 1 year at 15 surface-water stations in order to subdivide the basin into subbasins comprised of watersheds with similar water quality characteristics. Three principal components accounted for about 90 percent of the variance in water chemistry data. The principal components were defined as a biogeochemical variable related to wetland density, an acid-neutralization variable, and a road-salt variable related to density of primary roads. Three subbasins were identified. Analysis of variance and multiple comparisons of means were used to identify significant differences in stream water chemistry and landscape attributes among subbasins. All stream water constituents were significantly different among subbasins. Multiple regression techniques were used to relate stream water chemistry to landscape attributes. Important differences in landscape attributes were related to wetlands, slope, and soil type.A multivariate approach was used to analyze hydrologic, geologic, geographic, and water-chemistry data from small order watersheds in the Quabbin Reservoir Basin in central Massachusetts. Eighty three small order watersheds were delineated and landscape attributes defining hydrologic, geologic, and geographic features of the watersheds were compiled from geographic information system data layers. Principal components analysis was used to evaluate 11 chemical constituents collected bi-weekly for 1 year at 15 surface-water stations in order to subdivide the basin into subbasins comprised of watersheds with similar water quality characteristics. Three principal components accounted for about 90 percent of the variance in water chemistry data. The principal components were defined as a biogeochemical variable related to wetland density, an acid-neutralization variable, and a road-salt variable related to density of primary roads. Three subbasins were identified. Analysis of variance and multiple comparisons of means were used to identify significant differences in stream water chemistry and landscape attributes among subbasins. All stream water constituents were significantly different among subbasins. Multiple regression techniques were used to relate stream water chemistry to landscape attributes. Important differences in landscape attributes were related to wetlands, slope, and soil type.

Phylogenetic analysis of IDD gene family and characterization of its expression in response to flower induction in Malus.

PubMed

Fan, Sheng; Zhang, Dong; Xing, Libo; Qi, Siyan; Du, Lisha; Wu, Haiqin; Shao, Hongxia; Li, Youmei; Ma, Juanjuan; Han, Mingyu

2017-08-01

Although INDETERMINATE DOMAIN (IDD) genes encoding specific plant transcription factors have important roles in plant growth and development, little is known about apple IDD (MdIDD) genes and their potential functions in the flower induction. In this study, we identified 20 putative IDD genes in apple and named them according to their chromosomal locations. All identified MdIDD genes shared a conserved IDD domain. A phylogenetic analysis separated MdIDDs and other plant IDD genes into four groups. Bioinformatic analysis of chemical characteristics, gene structure, and prediction of protein-protein interactions demonstrated the functional and structural diversity of MdIDD genes. To further uncover their potential functions, we performed analysis of tandem, synteny, and gene duplications, which indicated several paired homologs of IDD genes between apple and Arabidopsis. Additionally, genome duplications also promoted the expansion and evolution of the MdIDD genes. Quantitative real-time PCR revealed that all the MdIDD genes showed distinct expression levels in five different tissues (stems, leaves, buds, flowers, and fruits). Furthermore, the expression levels of candidate MdIDD genes were also investigated in response to various circumstances, including GA treatment (decreased the flowering rate), sugar treatment (increased the flowering rate), alternate-bearing conditions, and two varieties with different-flowering intensities. Parts of them were affected by exogenous treatments and showed different expression patterns. Additionally, changes in response to alternate-bearing and different-flowering varieties of apple trees indicated that they were also responsive to flower induction. Taken together, our comprehensive analysis provided valuable information for further analysis of IDD genes aiming at flower induction.

Substantial equivalence analysis in fruits from three Theobroma species through chemical composition and protein profiling.

PubMed

Pérez-Mora, Walter; Jorrin-Novo, Jesús V; Melgarejo, Luz Marina

2018-02-01

Substantial equivalence studies were performed in three Theobroma spp., cacao, bicolor and grandiflorum through chemical composition analysis and protein profiling of fruit (pulp juice and seeds). Principal component analysis of sugar, organic acid, and phenol content in pulp juice revealed equivalence among the three species, with differences in some of the compounds that may result in different organoleptic properties. Proteins were extracted from seeds and pulp juice, resolved by two dimensional electrophoresis and major spots subjected to mass spectrometry analysis and identification. The protein profile, as revealed by principal component analysis, was variable among the three species in both seed and pulp, with qualitative and quantitative differences in some of protein species. The functional grouping of the identified proteins correlated with the biological role of each organ. Some of the identified proteins are of interest, being minimally discussed, including vicilin, a protease inhibitor, and a flavonol synthase/flavanone 3-hydroxylase. Theobroma grandiflorum and Theobroma bicolor are endemic Amazonian plants that are poorly traded at the local level. As close relatives of Theobroma cacao, they may provide a good alternative for human consumption and industrial purposes. In this regard, we performed equivalence studies by conducting a comparative biochemical and proteomics analysis of the fruit, pulp juice and seeds of these three species. The results indicated equivalent chemical compositions and variable protein profiles with some differences in the content of the specific compounds or protein species that may result in variable organoleptic properties between the species and can be exploited for traceability purposes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Expression analysis of a heat-inducible, Myo-inositol-1-phosphate synthase (MIPS) gene from wheat and the alternatively spliced variants of rice and Arabidopsis.

PubMed

Khurana, Neetika; Chauhan, Harsh; Khurana, Paramjit

2012-01-01

Molecular dissection and a deeper analysis of the heat stress response mechanism in wheat have been poorly understood so far. This study delves into the molecular basis of action of TaMIPS, a heat stress-inducible enzyme that was identified through PCR-select subtraction technology, which is named here as TaMIPS2. MIPS (L-Myo-inositol-phosphate synthase) is important for the normal growth and development in plants. Expression profiling showed that TaMIPS2 is expressed during different developing seed stages upon heat stress. Also, the transcript levels increase in unfertilized ovaries and significant amounts are present during the recovery period providing evidence that MIPS is crucial for its role in heat stress recovery and flower development. Alternatively spliced forms from rice and Arabidopsis were also identified and their expression analysis revealed that apart from heat stress, some of the spliced variants were also inducible by drought, NaCl, Cold, ABA, BR, SA and mannitol. In silico promoter analysis revealed various cis-elements that could contribute for the differential regulation of MIPS in different plant systems. Phylogenetic analysis indicated that MIPS are highly conserved among monocots and dicots and TaMIPS2 grouped specifically with monocots. Comparative analyses was undertaken by different experimental approaches, i.e., semi-quantitative RT-PCR, quantitative RT-PCR, Genevestigator as a reference expression tool and motif analysis to predict the possible function of TaMIPS2 in regulating the different aspects of plant development under abiotic stress in wheat.

Chemical Engineering Students: A Distinct Group among Engineers

ERIC Educational Resources Information Center

Godwin, Allison; Potvin, Geoff

2013-01-01

This paper explores differences between chemical engineering students and students of other engineering disciplines, as identified by their intended college major. The data used in this analysis was taken from the nationally representative Sustainability and Gender in Engineering (SaGE) survey. Chemical engineering students differ significantly…

Comparative analysis of targeted metabolomics: dominance-based rough set approach versus orthogonal partial least square-discriminant analysis.

PubMed

Blasco, H; Błaszczyński, J; Billaut, J C; Nadal-Desbarats, L; Pradat, P F; Devos, D; Moreau, C; Andres, C R; Emond, P; Corcia, P; Słowiński, R

2015-02-01

Metabolomics is an emerging field that includes ascertaining a metabolic profile from a combination of small molecules, and which has health applications. Metabolomic methods are currently applied to discover diagnostic biomarkers and to identify pathophysiological pathways involved in pathology. However, metabolomic data are complex and are usually analyzed by statistical methods. Although the methods have been widely described, most have not been either standardized or validated. Data analysis is the foundation of a robust methodology, so new mathematical methods need to be developed to assess and complement current methods. We therefore applied, for the first time, the dominance-based rough set approach (DRSA) to metabolomics data; we also assessed the complementarity of this method with standard statistical methods. Some attributes were transformed in a way allowing us to discover global and local monotonic relationships between condition and decision attributes. We used previously published metabolomics data (18 variables) for amyotrophic lateral sclerosis (ALS) and non-ALS patients. Principal Component Analysis (PCA) and Orthogonal Partial Least Square-Discriminant Analysis (OPLS-DA) allowed satisfactory discrimination (72.7%) between ALS and non-ALS patients. Some discriminant metabolites were identified: acetate, acetone, pyruvate and glutamine. The concentrations of acetate and pyruvate were also identified by univariate analysis as significantly different between ALS and non-ALS patients. DRSA correctly classified 68.7% of the cases and established rules involving some of the metabolites highlighted by OPLS-DA (acetate and acetone). Some rules identified potential biomarkers not revealed by OPLS-DA (beta-hydroxybutyrate). We also found a large number of common discriminating metabolites after Bayesian confirmation measures, particularly acetate, pyruvate, acetone and ascorbate, consistent with the pathophysiological pathways involved in ALS. DRSA provides a complementary method for improving the predictive performance of the multivariate data analysis usually used in metabolomics. This method could help in the identification of metabolites involved in disease pathogenesis. Interestingly, these different strategies mostly identified the same metabolites as being discriminant. The selection of strong decision rules with high value of Bayesian confirmation provides useful information about relevant condition-decision relationships not otherwise revealed in metabolomics data. Copyright © 2014 Elsevier Inc. All rights reserved.

Statistical physics approach to quantifying differences in myelinated nerve fibers

PubMed Central

Comin, César H.; Santos, João R.; Corradini, Dario; Morrison, Will; Curme, Chester; Rosene, Douglas L.; Gabrielli, Andrea; da F. Costa, Luciano; Stanley, H. Eugene

2014-01-01

We present a new method to quantify differences in myelinated nerve fibers. These differences range from morphologic characteristics of individual fibers to differences in macroscopic properties of collections of fibers. Our method uses statistical physics tools to improve on traditional measures, such as fiber size and packing density. As a case study, we analyze cross–sectional electron micrographs from the fornix of young and old rhesus monkeys using a semi-automatic detection algorithm to identify and characterize myelinated axons. We then apply a feature selection approach to identify the features that best distinguish between the young and old age groups, achieving a maximum accuracy of 94% when assigning samples to their age groups. This analysis shows that the best discrimination is obtained using the combination of two features: the fraction of occupied axon area and the effective local density. The latter is a modified calculation of axon density, which reflects how closely axons are packed. Our feature analysis approach can be applied to characterize differences that result from biological processes such as aging, damage from trauma or disease or developmental differences, as well as differences between anatomical regions such as the fornix and the cingulum bundle or corpus callosum. PMID:24676146

Statistical physics approach to quantifying differences in myelinated nerve fibers

NASA Astrophysics Data System (ADS)

Comin, César H.; Santos, João R.; Corradini, Dario; Morrison, Will; Curme, Chester; Rosene, Douglas L.; Gabrielli, Andrea; da F. Costa, Luciano; Stanley, H. Eugene

2014-03-01

We present a new method to quantify differences in myelinated nerve fibers. These differences range from morphologic characteristics of individual fibers to differences in macroscopic properties of collections of fibers. Our method uses statistical physics tools to improve on traditional measures, such as fiber size and packing density. As a case study, we analyze cross-sectional electron micrographs from the fornix of young and old rhesus monkeys using a semi-automatic detection algorithm to identify and characterize myelinated axons. We then apply a feature selection approach to identify the features that best distinguish between the young and old age groups, achieving a maximum accuracy of 94% when assigning samples to their age groups. This analysis shows that the best discrimination is obtained using the combination of two features: the fraction of occupied axon area and the effective local density. The latter is a modified calculation of axon density, which reflects how closely axons are packed. Our feature analysis approach can be applied to characterize differences that result from biological processes such as aging, damage from trauma or disease or developmental differences, as well as differences between anatomical regions such as the fornix and the cingulum bundle or corpus callosum.

Onset dynamics of action potentials in rat neocortical neurons and identified snail neurons: quantification of the difference.

PubMed

Volgushev, Maxim; Malyshev, Aleksey; Balaban, Pavel; Chistiakova, Marina; Volgushev, Stanislav; Wolf, Fred

2008-04-09

The generation of action potentials (APs) is a key process in the operation of nerve cells and the communication between neurons. Action potentials in mammalian central neurons are characterized by an exceptionally fast onset dynamics, which differs from the typically slow and gradual onset dynamics seen in identified snail neurons. Here we describe a novel method of analysis which provides a quantitative measure of the onset dynamics of action potentials. This method captures the difference between the fast, step-like onset of APs in rat neocortical neurons and the gradual, exponential-like AP onset in identified snail neurons. The quantitative measure of the AP onset dynamics, provided by the method, allows us to perform quantitative analyses of factors influencing the dynamics.

Onset Dynamics of Action Potentials in Rat Neocortical Neurons and Identified Snail Neurons: Quantification of the Difference

PubMed Central

Volgushev, Maxim; Malyshev, Aleksey; Balaban, Pavel; Chistiakova, Marina; Volgushev, Stanislav; Wolf, Fred

2008-01-01

The generation of action potentials (APs) is a key process in the operation of nerve cells and the communication between neurons. Action potentials in mammalian central neurons are characterized by an exceptionally fast onset dynamics, which differs from the typically slow and gradual onset dynamics seen in identified snail neurons. Here we describe a novel method of analysis which provides a quantitative measure of the onset dynamics of action potentials. This method captures the difference between the fast, step-like onset of APs in rat neocortical neurons and the gradual, exponential-like AP onset in identified snail neurons. The quantitative measure of the AP onset dynamics, provided by the method, allows us to perform quantitative analyses of factors influencing the dynamics. PMID:18398478

Proteomic analysis of mare follicular fluid during late follicle development

PubMed Central

2011-01-01

Background Follicular fluid accumulates into the antrum of follicle from the early stage of follicle development. Studies on its components may contribute to a better understanding of the mechanisms underlying follicular development and oocyte quality. With this objective, we performed a proteomic analysis of mare follicular fluid. First, we hypothesized that proteins in follicular fluid may differ from those in the serum, and also may change during follicle development. Second, we used four different approaches of Immunodepletion and one enrichment method, in order to overcome the masking effect of high-abundance proteins present in the follicular fluid, and to identify those present in lower abundance. Finally, we compared our results with previous studies performed in mono-ovulant (human) and poly-ovulant (porcine and canine) species in an attempt to identify common and/or species-specific proteins. Methods Follicular fluid samples were collected from ovaries at three different stages of follicle development (early dominant, late dominant and preovulatory). Blood samples were also collected at each time. The proteomic analysis was carried out on crude, depleted and enriched follicular fluid by 2D-PAGE, 1D-PAGE and mass spectrometry. Results Total of 459 protein spots were visualized by 2D-PAGE of crude mare follicular fluid, with no difference among the three physiological stages. Thirty proteins were observed as differentially expressed between serum and follicular fluid. Enrichment method was found to be the most powerful method for detection and identification of low-abundance proteins from follicular fluid. Actually, we were able to identify 18 proteins in the crude follicular fluid, and as many as 113 in the enriched follicular fluid. Inhibins and a few other proteins involved in reproduction could only be identified after enrichment of follicular fluid, demonstrating the power of the method used. The comparison of proteins found in mare follicular fluid with proteins previously identified in human, porcine and canine follicular fluids, led to the identification of 12 common proteins and of several species-specific proteins. Conclusions This study provides the first description of mare follicular fluid proteome during the late follicle development stages. We identified several proteins from crude, depleted and enriched follicular fluid. Our results demonstrate that the enrichment method, combined with 2D-PAGE and mass spectrometry, can be successfully used to visualize and further identify the low-abundance proteins in the follicular fluid. PMID:21923925

Proteomic analysis of mare follicular fluid during late follicle development.

PubMed

Fahiminiya, Somayyeh; Labas, Valérie; Roche, Stéphane; Dacheux, Jean-Louis; Gérard, Nadine

2011-09-17

Follicular fluid accumulates into the antrum of follicle from the early stage of follicle development. Studies on its components may contribute to a better understanding of the mechanisms underlying follicular development and oocyte quality. With this objective, we performed a proteomic analysis of mare follicular fluid. First, we hypothesized that proteins in follicular fluid may differ from those in the serum, and also may change during follicle development. Second, we used four different approaches of Immunodepletion and one enrichment method, in order to overcome the masking effect of high-abundance proteins present in the follicular fluid, and to identify those present in lower abundance. Finally, we compared our results with previous studies performed in mono-ovulant (human) and poly-ovulant (porcine and canine) species in an attempt to identify common and/or species-specific proteins. Follicular fluid samples were collected from ovaries at three different stages of follicle development (early dominant, late dominant and preovulatory). Blood samples were also collected at each time. The proteomic analysis was carried out on crude, depleted and enriched follicular fluid by 2D-PAGE, 1D-PAGE and mass spectrometry. Total of 459 protein spots were visualized by 2D-PAGE of crude mare follicular fluid, with no difference among the three physiological stages. Thirty proteins were observed as differentially expressed between serum and follicular fluid. Enrichment method was found to be the most powerful method for detection and identification of low-abundance proteins from follicular fluid. Actually, we were able to identify 18 proteins in the crude follicular fluid, and as many as 113 in the enriched follicular fluid. Inhibins and a few other proteins involved in reproduction could only be identified after enrichment of follicular fluid, demonstrating the power of the method used. The comparison of proteins found in mare follicular fluid with proteins previously identified in human, porcine and canine follicular fluids, led to the identification of 12 common proteins and of several species-specific proteins. This study provides the first description of mare follicular fluid proteome during the late follicle development stages. We identified several proteins from crude, depleted and enriched follicular fluid. Our results demonstrate that the enrichment method, combined with 2D-PAGE and mass spectrometry, can be successfully used to visualize and further identify the low-abundance proteins in the follicular fluid.

Hotspots in research on the measurement of medical students' clinical competence from 2012-2016 based on co-word analysis.

PubMed

Chang, Xing; Zhou, Xin; Luo, Linzhi; Yang, Chengjia; Pan, Hui; Zhang, Shuyang

2017-09-12

This study aimed to identify hotspots in research on clinical competence measurements from 2012 to 2016. The authors retrieved literature published between 2012 and 2016 from PubMed using selected medical subject headings (MeSH) terms. They used BibExcel software to generate high-frequency MeSH terms and identified hotspots by co-word analysis and cluster analysis. The authors searched 588 related articles and identified 31 high-frequency MeSH terms. In addition, they obtained 6 groups of high-frequency MeSH terms that reflected the domain hotspots. This study identified 6 hotspots of domain research, including studies on influencing factors and perception evaluation, improving and developing measurement tools, feedback measurement, measurement approaches based on computer simulation, the measurement of specific students in different learning phases, and the measurement of students' communication ability. All of these research topics could provide useful information for educators and researchers to continually conduct in-depth studies.

A framework to spatially cluster air pollution monitoring sites in US based on the PM2.5 composition

PubMed Central

Austin, Elena; Coull, Brent A.; Zanobetti, Antonella; Koutrakis, Petros

2013-01-01

Background Heterogeneity in the response to PM2.5 is hypothesized to be related to differences in particle composition across monitoring sites which reflect differences in source types as well as climatic and topographic conditions impacting different geographic locations. Identifying spatial patterns in particle composition is a multivariate problem that requires novel methodologies. Objectives Use cluster analysis methods to identify spatial patterns in PM2.5 composition. Verify that the resulting clusters are distinct and informative. Methods 109 monitoring sites with 75% reported speciation data during the period 2003–2008 were selected. These sites were categorized based on their average PM2.5 composition over the study period using k-means cluster analysis. The obtained clusters were validated and characterized based on their physico-chemical characteristics, geographic locations, emissions profiles, population density and proximity to major emission sources. Results Overall 31 clusters were identified. These include 21 clusters with 2 or more sites which were further grouped into 4 main types using hierarchical clustering. The resulting groupings are chemically meaningful and represent broad differences in emissions. The remaining clusters, encompassing single sites, were characterized based on their particle composition and geographic location. Conclusions The framework presented here provides a novel tool which can be used to identify and further classify sites based on their PM2.5 composition. The solution presented is fairly robust and yielded groupings that were meaningful in the context of air-pollution research. PMID:23850585

Progression Rate Associated Peripheral Blood Biomarkers of Parkinson's Disease.

PubMed

Fan, Yanxia; Xiao, Shuping

2018-06-23

Parkinson disease (PD) is one of the most frequent neurodegenerative disorders. The aim of this study was to identify blood biomarkers capable to discriminate PD patients with different progression rates. Differentially expressed genes (DEGs) were acquired by comparing the expression profiles of PD patients with rapid and slow progression rates, using an expression dataset from Gene Expression Omnibus (GEO) under accession code of GSE80599. Altered biological processes and pathways were revealed by functional annotation. Potential biomarkers of PD were identified by protein-protein interaction (PPI) network analysis. Critical transcription factors (TFs) and miRNAs regulating DEGs were predicted by TF analysis and miRNA analysis. A total of 225 DEGs were identified between PD patients with rapid and slow progression profiles. These genes were significantly enriched in biological processes and pathways related to fatty acid metabolism. Among these DEGs, ZFAND4, SRMS, UBL4B, PVALB, DIRAS1, PDP2, LRCH1, and MYL4 were potential progression rate associated biomarkers of PD. Additionally, these DEGs may be regulated by miRNAs of the miR-30 family and TFs STAT1 and GRHL3. Our results may contribute to our understanding of the molecular mechanisms underlying different PD progression profiles.

Radiogenomics: a systems biology approach to understanding genetic risk factors for radiotherapy toxicity ?

PubMed Central

Herskind, Carsten; Talbot, Christopher J.; Kerns, Sarah L.; Veldwijk, Marlon R.; Rosenstein, Barry S.; West, Catharine M. L.

2016-01-01

Adverse reactions in normal tissue after radiotherapy (RT) limit the dose that can be given to tumour cells. Since 80% of individual variation in clinical response is estimated to be caused by patient-related factors, identifying these factors might allow prediction of patients with increased risk of developing severe reactions. While inactivation of cell renewal is considered a major cause of toxicity in early-reacting normal tissues, complex interactions involving multiple cell types, cytokines, and hypoxia seem important for late reactions. Here, we review ‘omics’ approaches such as screening of genetic polymorphisms or gene expression analysis, and assess the potential of epigenetic factors, posttranslational modification, signal transduction, and metabolism. Furthermore, functional assays have suggested possible associations with clinical risk of adverse reaction. Pathway analysis incorporating different ‘omics’ approaches may be more efficient in identifying critical pathways than pathway analysis based on single ‘omics’ data sets. Integrating these pathways with functional assays may be powerful in identifying multiple subgroups of RT patients characterized by different mechanisms. Thus ‘omics’ and functional approaches may synergize if they are integrated into radiogenomics ‘systems biology’ to facilitate the goal of individualised radiotherapy. PMID:26944314

Geometric morphometric analysis reveals age-related differences in the distal femur of Europeans.

PubMed

Cavaignac, Etienne; Savall, Frederic; Chantalat, Elodie; Faruch, Marie; Reina, Nicolas; Chiron, Philippe; Telmon, Norbert

2017-12-01

Few studies have looked into age-related variations in femur shape. We hypothesized that three-dimensional (3D) geometric morphometric analysis of the distal femur would reveal age-related differences. The purpose of this study was to show that differences in distal femur shape related to age could be identified, visualized, and quantified using three-dimensional (3D) geometric morphometric analysis. Geometric morphometric analysis was carried out on CT scans of the distal femur of 256 subjects living in the south of France. Ten landmarks were defined on 3D reconstructions of the distal femur. Both traditional metric and geometric morphometric analyses were carried out on these bone reconstructions. These analyses were used to identify trends in bone shape in various age-based subgroups (<40, 40-60, >60). Only the average bone shape of the < 40-year subgroup was statistically different from that of the other two groups. When the population was divided into two subgroups using 40 years of age as a threshold, the subject's age was correctly assigned 80% of the time. Age-related differences are present in this bone segment. This reliable, accurate method could be used for virtual autopsy and to perform diachronic and interethnic comparisons. Moreover, this study provides updated morphometric data for a modern population in the south of France. Manufacturers of knee replacement implants will have to adapt their prosthesis models as the population evolves over time.

Effect of varying postmortem deboning time and sampling position on visible and near infrared spectra of broiler breast filets

USDA-ARS?s Scientific Manuscript database

Visible-Near Infrared spectroscopy (Vis-NIR) was used to characterize broiler breast filets with varied deboning times and identify how the side and position of the sampling affects the chemometric analysis and prediction capabilities. This study served to identify what differences, if any, exist wh...

Competencies Required by Special Librarians: An Analysis by Educational Levels

ERIC Educational Resources Information Center

Peyvand Robati, Alireza; Singh, Diljit

2013-01-01

This paper presents the results of a study conducted with the aim of identifying competencies needed by special librarians in Iran at three different levels of library and information science education. A list of competencies was initially identified from the literature and 21 semi-structured interviews with managers of special libraries in Iran.…

An Examination of High School Graduates Who Identify Teachers as Influential in Their Choice of College

ERIC Educational Resources Information Center

Mozie-Ross, Yvette D.

2011-01-01

This exploratory study contributes to what is known about the college choice process by providing a quantitative comparative analysis to determine how high school graduates who identify teachers as influential in their choice of college differ from graduates who do not. Specifically, this study answers the following research question: How do…

Substance Use and Abuse Trajectories across Adolescence: A Latent Trajectory Analysis of a Community-Recruited Sample of Girls

ERIC Educational Resources Information Center

Marti, C. Nathan; Stice, Eric; Springer, David W.

2010-01-01

We used data from a school-based study of 496 adolescent girls to identify qualitatively distinct substance use and substance abuse developmental trajectory groups and tested whether the problematic groups differed from the non-problematic groups on baseline and outcome validation variables. Results identified four substance use groups (late…

A Review of Practical Reasoning in Child and Youth Research

ERIC Educational Resources Information Center

Ljungdalh, Anders Kruse

2016-01-01

The purpose of the review is to investigate various relations between the concepts of competence and participation found within child and youth research with the aim of identifying differences in practical reasoning of the various kinds of child research. The search identified 260 articles, and an in-depth analysis of 39 articles was conducted,…

The SAT Gender Gap: Identifying the Causes.

ERIC Educational Resources Information Center

Rosser, Phyllis

Questions on the Scholastic Aptitude Test (SAT) with the largest score differences between women and men of all racial and ethnic groups were identified. Patterns of difficulty that would explain the SAT's continuing underprediction of female first-year college performance were studied. An item analysis of one form of the June 1986 SAT for 1,112…

Training Needs Analysis. A Resource for Identifying Training Needs, Selecting Training Strategies, and Developing Training Plans.

ERIC Educational Resources Information Center

Bartram, Sharon; Gibson, Brenda

Designed as a practical tool for trainers, this manual contains 22 instruments and documents for gathering and processing information about training and development issues within an organization. Part one of the two-part manual examines the process of identifying and analyzing training needs. It reviews the different types of information the…

Identification of Major Histocompatibility Complex-Regulated Body Odorants by Statistical Analysis of a Comparative Gas Chromatography/Mass Spectrometry Experiment

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

Willse, Alan R.; Belcher, Ann; Preti, George

2005-04-15

Gas chromatography (GC), combined with mass spectrometry (MS) detection, is a powerful analytical technique that can be used to separate, quantify, and identify volatile compounds in complex mixtures. This paper examines the application of GC-MS in a comparative experiment to identify volatiles that differ in concentration between two groups. A complex mixture might comprise several hundred or even thousands of volatile compounds. Because their number and location in a chromatogram generally are unknown, and because components overlap in populous chromatograms, the statistical problems offer significant challenges beyond traditional two-group screening procedures. We describe a statistical procedure to compare two-dimensional GC-MSmore » profiles between groups, which entails (1) signal processing: baseline correction and peak detection in single ion chromatograms; (2) aligning chromatograms in time; (3) normalizing differences in overall signal intensities; and (4) detecting chromatographic regions that differ between groups. Compared to existing approaches, the proposed method is robust to errors made at earlier stages of analysis, such as missed peaks or slightly misaligned chromatograms. To illustrate the method, we identify differences in GC-MS chromatograms of ether-extracted urine collected from two nearly identical inbred groups of mice, to investigate the relationship between odor and genetics of the major histocompatibility complex.« less

Identification and Characterization of Unique Subgroups of Chronic Pain Individuals with Dispositional Personality Traits.

PubMed

Mehta, S; Rice, D; McIntyre, A; Getty, H; Speechley, M; Sequeira, K; Shapiro, A P; Morley-Forster, P; Teasell, R W

2016-01-01

Objective. The current study attempted to identify and characterize distinct CP subgroups based on their level of dispositional personality traits. The secondary objective was to compare the difference among the subgroups in mood, coping, and disability. Methods. Individuals with chronic pain were assessed for demographic, psychosocial, and personality measures. A two-step cluster analysis was conducted in order to identify distinct subgroups of patients based on their level of personality traits. Differences in clinical outcomes were compared using the multivariate analysis of variance based on cluster membership. Results. In 229 participants, three clusters were formed. No significant difference was seen among the clusters on patient demographic factors including age, sex, relationship status, duration of pain, and pain intensity. Those with high levels of dispositional personality traits had greater levels of mood impairment compared to the other two groups (p < 0.05). Significant difference in disability was seen between the subgroups. Conclusions. The study identified a high risk group of CP individuals whose level of personality traits significantly correlated with impaired mood and coping. Use of pharmacological treatment alone may not be successful in improving clinical outcomes among these individuals. Instead, a more comprehensive treatment involving psychological treatments may be important in managing the personality traits that interfere with recovery.

Identifying Patient Attitudinal Clusters Associated with Asthma Control: The European REALISE Survey.

PubMed

van der Molen, Thys; Fletcher, Monica; Price, David

Asthma is a highly heterogeneous disease that can be classified into different clinical phenotypes, and treatment may be tailored accordingly. However, factors beyond purely clinical traits, such as patient attitudes and behaviors, can also have a marked impact on treatment outcomes. The objective of this study was to further analyze data from the REcognise Asthma and LInk to Symptoms and Experience (REALISE) Europe survey, to identify distinct patient groups sharing common attitudes toward asthma and its management. Factor analysis of respondent data (N = 7,930) from the REALISE Europe survey consolidated the 34 attitudinal variables provided by the study population into a set of 8 summary factors. Cluster analyses were used to identify patient clusters that showed similar attitudes and behaviors toward each of the 8 summary factors. Five distinct patient clusters were identified and named according to the key characteristics comprising that cluster: "Confident and self-managing," "Confident and accepting of their asthma," "Confident but dependent on others," "Concerned but confident in their health care professional (HCP)," and "Not confident in themselves or their HCP." Clusters showed clear variability in attributes such as degree of confidence in managing their asthma, use of reliever and preventer medication, and level of asthma control. The 5 patient clusters identified in this analysis displayed distinctly different personal attitudes that would require different approaches in the consultation room certainly for asthma but probably also for other chronic diseases. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Influence of sociodemographic characteristics on different dimensions of household food insecurity in Montevideo, Uruguay.

PubMed

Rossi, Máximo; Ferre, Zuleika; Curutchet, María Rosa; Giménez, Ana; Ares, Gastón

2017-03-01

To determine the factor structure of the Latin American & Caribbean Household Food Security Scale (ELCSA) and to study the influence of sociodemographic characteristics on each of the identified dimensions in Montevideo, Uruguay. Cross-sectional survey with a representative sample of urban households. Household food insecurity was measured using the ELCSA. The percentage of respondents who gave affirmative responses for each of the items of the ELCSA was determined. Exploratory factor analysis was carried out to determine the ELCSA's factor structure. A probit model was used to determine the impact of some individual and household sociodemographic characteristics on the identified dimensions of food insecurity. Metropolitan area centred on Montevideo, the capital city of Uruguay, April-September 2014. Adults aged between 18 and 93 years (n 742). The percentage of affirmative responses to the items of the ELCSA ranged from 4·4 to 31·7 %. Two factors were identified in the exploratory factor analysis performed on data from households without children under 18 years old, whereas three factors were identified for households with children. The identified factors were associated with different severity levels of food insecurity. Likelihood of experiencing different levels of food insecurity was affected by individual characteristics of the respondent as well as characteristics of the household. The influence of sociodemographic variables varied among the ELCSA dimensions. Household income had the largest influence on all dimensions, which indicates a strong relationship between income and food insecurity.

Global-local methodologies and their application to nonlinear analysis. [for structural postbuckling study

NASA Technical Reports Server (NTRS)

Noor, Ahmed K.

1986-01-01

An assessment is made of the potential of different global-local analysis strategies for predicting the nonlinear and postbuckling responses of structures. Two postbuckling problems of composite panels are used as benchmarks and the application of different global-local methodologies to these benchmarks is outlined. The key elements of each of the global-local strategies are discussed and future research areas needed to realize the full potential of global-local methodologies are identified.

Genomic characterization of two new enterovirus types, EV-A114 and EV-A121.

PubMed

Deshpande, Jagadish M; Sharma, Deepa K; Saxena, Vinay K; Shetty, Sushmitha A; Qureshi, Tarique Husain I H; Nalavade, Uma P

2016-12-01

Enteroviruses cause a variety of illnesses of the gastrointestinal tract, central nervous system and cardiovascular system. Phylogenetic analysis of VP1 sequences has identified 106 different human enteroviruses classified into four enterovirus species within the genus Enterovirus of the family Picornaviridae. It is likely that not all enterovirus types have been discovered. Between September 2013 and October 2014, stool samples of 6274 apparently healthy children of up to 5 years of age residing in Gorakhpur district, Uttar Pradesh, India were screened for enteroviruses. Virus isolates obtained in RD and Hep-2c cells were identified by complete VP1 sequencing. Enteroviruses were isolated from 3042 samples. A total of 87 different enterovirus types were identified. Two isolates with 71 and 74 % nucleotide sequence similarity to all other known enteroviruses were recognized as novel types. In this paper we report identification and complete genome sequence analysis of these two isolates classified as EV-A114 and EV-A121.

Proteome analysis of bell pepper (Capsicum annuum L.) chromoplasts.

PubMed

Siddique, Muhammad Asim; Grossmann, Jonas; Gruissem, Wilhelm; Baginsky, Sacha

2006-12-01

We report a comprehensive proteome analysis of chromoplasts from bell pepper (Capsicum annuum L.). The combination of a novel strategy for database-independent detection of proteins from tandem mass spectrometry (MS/MS) data with standard database searches allowed us to identify 151 proteins with a high level of confidence. These include several well-known plastid proteins but also novel proteins that were not previously reported from other plastid proteome studies. The majority of the identified proteins are active in plastid carbohydrate and amino acid metabolism. Among the most abundant individual proteins are capsanthin/capsorubin synthase and fibrillin, which are involved in the synthesis and storage of carotenoids that accumulate to high levels in chromoplasts. The relative abundances of the identified chromoplast proteins differ remarkably compared with their abundances in other plastid types, suggesting a chromoplast-specific metabolic network. Our results provide an overview of the major metabolic pathways active in chromoplasts and extend existing knowledge about prevalent metabolic activities of different plastid types.

Domain Hierarchy and closed Loops (DHcL): a server for exploring hierarchy of protein domain structure

PubMed Central

Koczyk, Grzegorz; Berezovsky, Igor N.

2008-01-01

Domain hierarchy and closed loops (DHcL) (http://sitron.bccs.uib.no/dhcl/) is a web server that delineates energy hierarchy of protein domain structure and detects domains at different levels of this hierarchy. The server also identifies closed loops and van der Waals locks, which constitute a structural basis for the protein domain hierarchy. The DHcL can be a useful tool for an express analysis of protein structures and their alternative domain decompositions. The user submits a PDB identifier(s) or uploads a 3D protein structure in a PDB format. The results of the analysis are the location of domains at different levels of hierarchy, closed loops, van der Waals locks and their interactive visualization. The server maintains a regularly updated database of domains, closed loop and van der Waals locks for all X-ray structures in PDB. DHcL server is available at: http://sitron.bccs.uib.no/dhcl. PMID:18502776

Everyday ethical problems in dementia care: a teleological model.

PubMed

Bolmsjö, Ingrid Agren; Edberg, Anna-Karin; Sandman, Lars

2006-07-01

In this article, a teleological model for analysis of everyday ethical situations in dementia care is used to analyse and clarify perennial ethical problems in nursing home care for persons with dementia. This is done with the aim of describing how such a model could be useful in a concrete care context. The model was developed by Sandman and is based on four aspects: the goal; ethical side-constraints to what can be done to realize such a goal; structural constraints; and nurses' ethical competency. The model contains the following main steps: identifying and describing the normative situation; identifying and describing the different possible alternatives; assessing and evaluating the different alternatives; and deciding on, implementing and evaluating the chosen alternative. Three ethically difficult situations from dementia care were used for the application of the model. The model proved useful for the analysis of nurses' everyday ethical dilemmas and will be further explored to evaluate how well it can serve as a tool to identify and handle problems that arise in nursing care.

Sleep duration and sleep quality in people with and without intellectual disability: A meta-analysis.

PubMed

Surtees, Andrew D R; Oliver, Chris; Jones, Chris A; Evans, David L; Richards, Caroline

2017-11-28

This study provides the first meta-analysis of the purported differences in sleep time and sleep quality between people with and without intellectual disabilities. Twenty-one papers were identified that compared sleep time and/or sleep quality in people with and without intellectual disabilities. The meta-analysis of sleep time revealed that people with an intellectual disability slept for 18 min less, on average, than people without an intellectual disability. This significant difference was limited to those studies that tested groups of people with an identified genetic syndrome or developmental disorder. The analysis of sleep quality also concluded that people with intellectual disabilities experienced poorer sleep: In 93% of comparisons between groups, sleep was found to be of poorer quality in the group of people with intellectual disabilities. There were no differences found between studies that measured sleep objectively and those that used diary or questionnaire measures. Notably, most samples were drawn from populations of people with specified genetic syndromes or developmental disorders, rather than intellectual disability of heterogeneous origin. Similarly, most studies investigated sleep in children, although there was no evidence that the differences between the groups reduced during adulthood. Most studies used highly-regarded objective measures of sleep, such as polysomnography or actigraphy, although methodological flaws were evident in the identification of samples and the measurement of intellectual disability. Copyright © 2017 Elsevier Ltd. All rights reserved.

Influence of common genetic variation on lung cancer risk: meta-analysis of 14 900 cases and 29 485 controls

PubMed Central

Timofeeva, Maria N.; Hung, Rayjean J.; Rafnar, Thorunn; Christiani, David C.; Field, John K.; Bickeböller, Heike; Risch, Angela; McKay, James D.; Wang, Yufei; Dai, Juncheng; Gaborieau, Valerie; McLaughlin, John; Brenner, Darren; Narod, Steven A.; Caporaso, Neil E.; Albanes, Demetrius; Thun, Michael; Eisen, Timothy; Wichmann, H.-Erich; Rosenberger, Albert; Han, Younghun; Chen, Wei; Zhu, Dakai; Spitz, Margaret; Wu, Xifeng; Pande, Mala; Zhao, Yang; Zaridze, David; Szeszenia-Dabrowska, Neonilia; Lissowska, Jolanta; Rudnai, Peter; Fabianova, Eleonora; Mates, Dana; Bencko, Vladimir; Foretova, Lenka; Janout, Vladimir; Krokan, Hans E.; Gabrielsen, Maiken Elvestad; Skorpen, Frank; Vatten, Lars; Njølstad, Inger; Chen, Chu; Goodman, Gary; Lathrop, Mark; Benhamou, Simone; Vooder, Tõnu; Välk, Kristjan; Nelis, Mari; Metspalu, Andres; Raji, Olaide; Chen, Ying; Gosney, John; Liloglou, Triantafillos; Muley, Thomas; Dienemann, Hendrik; Thorleifsson, Gudmar; Shen, Hongbing; Stefansson, Kari; Brennan, Paul; Amos, Christopher I.; Houlston, Richard; Landi, Maria Teresa

2012-01-01

Recent genome-wide association studies (GWASs) have identified common genetic variants at 5p15.33, 6p21–6p22 and 15q25.1 associated with lung cancer risk. Several other genetic regions including variants of CHEK2 (22q12), TP53BP1 (15q15) and RAD52 (12p13) have been demonstrated to influence lung cancer risk in candidate- or pathway-based analyses. To identify novel risk variants for lung cancer, we performed a meta-analysis of 16 GWASs, totaling 14 900 cases and 29 485 controls of European descent. Our data provided increased support for previously identified risk loci at 5p15 (P = 7.2 × 10−16), 6p21 (P = 2.3 × 10−14) and 15q25 (P = 2.2 × 10−63). Furthermore, we demonstrated histology-specific effects for 5p15, 6p21 and 12p13 loci but not for the 15q25 region. Subgroup analysis also identified a novel disease locus for squamous cell carcinoma at 9p21 (CDKN2A/p16INK4A/p14ARF/CDKN2B/p15INK4B/ANRIL; rs1333040, P = 3.0 × 10−7) which was replicated in a series of 5415 Han Chinese (P = 0.03; combined analysis, P = 2.3 × 10−8). This large analysis provides additional evidence for the role of inherited genetic susceptibility to lung cancer and insight into biological differences in the development of the different histological types of lung cancer. PMID:22899653

Genetic and phenotypic diversity of 2,4-dichlorophenoxyacetic acid (2,4-D)-degrading bacteria isolated from 2,4-D-treated field soils.

PubMed Central

Ka, J O; Holben, W E; Tiedje, J M

1994-01-01

Forty-seven numerically dominant 2,4-dichlorophenoxyacetic acid (2,4-D)-degrading bacteria were isolated at different times from 1989 through 1992 from eight agricultural plots (3.6 by 9.1 m) which were either not treated with 2,4-D or treated with 2,4-D at three different concentrations. Isolates were obtained from the most dilute positive most-probable-number tubes inoculated with soil samples from the different plots on seven sampling dates over the 3-year period. The isolates were compared by using fatty acid methyl ester (FAME) profiles, chromosomal patterns obtained by PCR amplification of repetitive extragenic palindromic (REP) sequences, and hybridization patterns obtained with probes for the tfd genes of plasmid pJP4 and a probe (Spa probe) that detects a distinctly different 2,4-D-degrading isolate, Sphingomonas paucimobilis (formerly Pseudomonas paucimobilis). A total of 57% of the isolates were identified to the species level by the FAME analysis, and these isolates were strains of Sphingomonas, Pseudomonas, or Alcaligenes species. Hybridization analysis revealed four groups. Group I strains, which exhibited sequence homology with tfdA, -B, -C, and -D genes, were rather diverse, as determined by both the FAME analysis and the REP-PCR analysis. Group II, which exhibited homology only with the tfdA gene, was a small group and was probably a subset of group I. All group I and II strains had plasmids. Hybridization analysis revealed that the tfd genes were located on plasmids in 75% of these strains and on the chromosome or a large plasmid in the other 25% of the strains. One strain exhibited tfdA and -B hybridization associated with a plasmid band, while tfdC and -D hybridized with the chromosomal band area. The group III strains exhibited no detectable homology to tfd genes but hybridized to the Spa probe. The members of this group were tightly clustered as determined by both the FAME analysis and the REP-PCR analysis, were distinctly different from group I strains as determined by the FAME analysis, and had very few plasmids; this group contained more of the 47 isolates than any other group. The group III strains were identified as S. paucimobilis. The group IV strains, which hybridized to neither the tft prove nor the Spa probe, were as diverse as the group I strains as determined by the FAME and REP-PCR analyses. Most of group IV strains could not be identified by the FAME analysis.(ABSTRACT TRUNCATED AT 250 WORDS) Images PMID:8017907

Determination of the pure silicon monocarbide content of silicon carbide and products based on silicon carbide

NASA Technical Reports Server (NTRS)

Prost, L.; Pauillac, A.

1978-01-01

Experience has shown that different methods of analysis of SiC products give different results. Methods identified as AFNOR, FEPA, and manufacturer P, currently used to detect SiC, free C, free Si, free Fe, and SiO2 are reviewed. The AFNOR method gives lower SiC content, attributed to destruction of SiC by grinding. Two products sent to independent labs for analysis by the AFNOR and FEPA methods showed somewhat different results, especially for SiC, SiO2, and Al2O3 content, whereas an X-ray analysis showed a SiC content approximately 10 points lower than by chemical methods.

The effectiveness of pressure garment therapy for the prevention of abnormal scarring after burn injury: a meta-analysis.

PubMed

Anzarut, Alexander; Olson, Jarret; Singh, Prabhjyot; Rowe, Brian H; Tredget, Edward E

2009-01-01

This study had three objectives. First, to conduct a systematic review to identify the available evidence for the use of pressure garment therapy (PGT); second, to assess the quality of the available evidence; and third, to conduct a meta-analysis to quantify the effectiveness of PGT for the prevention of abnormal scarring after burn injury. Standard care for the prevention of abnormal scarring after burn injury includes pressure garment therapy (PGT); however, it is associated with potential patient morbidity and high costs. We hypothesise that an assessment of the available evidence supporting the use of pressure garment therapy will aid in directing clinical care and future research. Randomised control trials were identified from CINHAL, EMBASE, MEDLINE, CENTRAL, the 'grey literature' and hand searching of the Proceedings of the American Burn Association. Primary authors and pressure garment manufacturers were contacted to identify eligible trials. Bibliographies from included studies and reviews were searched. Study results were pooled to yield weighted mean differences or standardised mean difference and reported using 95% confidence intervals. The review incorporated six unique trials involving 316 patients. Original data from one unpublished trial were included. Overall, studies were considered to be of high methodological quality. The meta-analysis was unable to demonstrate a difference between global assessments of PGT-treated scars and control scars [weighted mean differences (WMD): -0.46; 95% confidence interval (CI): -1.07 to 0.16]. The meta-analysis for scar height showed a small, but statistically significant, decrease in height for the PGT-treated group standardised mean differences (SMD): -0.31; 95% CI: -0.63, 0.00. Results of meta-analyses of secondary outcome measures of scar vascularity, pliability and colour failed to demonstrate a difference between groups. PGT does not appear to alter global scar scores. It does appear to improve scar height, although this difference is small and of questionable clinical importance. The beneficial effects of PGT remain unproven, while the potential morbidity and cost are not insignificant. Given current evidence, additional research is required to examine the effectiveness, risks and costs of PGT.

[Study of the clinical phenotype of symptomatic chronic airways disease by hierarchical cluster analysis and two-step cluster analyses].

PubMed

Ning, P; Guo, Y F; Sun, T Y; Zhang, H S; Chai, D; Li, X M

2016-09-01

To study the distinct clinical phenotype of chronic airway diseases by hierarchical cluster analysis and two-step cluster analysis. A population sample of adult patients in Donghuamen community, Dongcheng district and Qinghe community, Haidian district, Beijing from April 2012 to January 2015, who had wheeze within the last 12 months, underwent detailed investigation, including a clinical questionnaire, pulmonary function tests, total serum IgE levels, blood eosinophil level and a peak flow diary. Nine variables were chosen as evaluating parameters, including pre-salbutamol forced expired volume in one second(FEV1)/forced vital capacity(FVC) ratio, pre-salbutamol FEV1, percentage of post-salbutamol change in FEV1, residual capacity, diffusing capacity of the lung for carbon monoxide/alveolar volume adjusted for haemoglobin level, peak expiratory flow(PEF) variability, serum IgE level, cumulative tobacco cigarette consumption (pack-years) and respiratory symptoms (cough and expectoration). Subjects' different clinical phenotype by hierarchical cluster analysis and two-step cluster analysis was identified. (1) Four clusters were identified by hierarchical cluster analysis. Cluster 1 was chronic bronchitis in smokers with normal pulmonary function. Cluster 2 was chronic bronchitis or mild chronic obstructive pulmonary disease (COPD) patients with mild airflow limitation. Cluster 3 included COPD patients with heavy smoking, poor quality of life and severe airflow limitation. Cluster 4 recognized atopic patients with mild airflow limitation, elevated serum IgE and clinical features of asthma. Significant differences were revealed regarding pre-salbutamol FEV1/FVC%, pre-salbutamol FEV1% pred, post-salbutamol change in FEV1%, maximal mid-expiratory flow curve(MMEF)% pred, carbon monoxide diffusing capacity per liter of alveolar(DLCO)/(VA)% pred, residual volume(RV)% pred, total serum IgE level, smoking history (pack-years), St.George's respiratory questionnaire(SGRQ) score, acute exacerbation in the past one year, PEF variability and allergic dermatitis (P<0.05). (2) Four clusters were also identified by two-step cluster analysis as followings, cluster 1, COPD patients with moderate to severe airflow limitation; cluster 2, asthma and COPD patients with heavy smoking, airflow limitation and increased airways reversibility; cluster 3, patients having less smoking and normal pulmonary function with wheezing but no chronic cough; cluster 4, chronic bronchitis patients with normal pulmonary function and chronic cough. Significant differences were revealed regarding gender distribution, respiratory symptoms, pre-salbutamol FEV1/FVC%, pre-salbutamol FEV1% pred, post-salbutamol change in FEV1%, MMEF% pred, DLCO/VA% pred, RV% pred, PEF variability, total serum IgE level, cumulative tobacco cigarette consumption (pack-years), and SGRQ score (P<0.05). By different cluster analyses, distinct clinical phenotypes of chronic airway diseases are identified. Thus, individualized treatments may guide doctors to provide based on different phenotypes.

Brucella proteomes--a review.

PubMed

DelVecchio, Vito G; Wagner, Mary Ann; Eschenbrenner, Michel; Horn, Troy A; Kraycer, Jo Ann; Estock, Frank; Elzer, Phil; Mujer, Cesar V

2002-12-20

The proteomes of selected Brucella spp. have been extensively analyzed by utilizing current proteomic technology involving 2-DE and MALDI-MS. In Brucella melitensis, more than 500 proteins were identified. The rapid and large-scale identification of proteins in this organism was accomplished by using the annotated B. melitensis genome which is now available in the GenBank. Coupled with new and powerful tools for data analysis, differentially expressed proteins were identified and categorized into several classes. A global overview of protein expression patterns emerged, thereby facilitating the simultaneous analysis of different metabolic pathways in B. melitensis. Such a global characterization would not have been possible by using time consuming and traditional biochemical approaches. The era of post-genomic technology offers new and exciting opportunities to understand the complete biology of different Brucella species.

Melissopalynological Characterization of North Algerian Honeys.

PubMed

Nair, Samira; Meddah, Boumedienne; Aoues, Abdelkader

2013-03-07

A pollen analysis of Algerian honey was conducted on a total of 10 honey samples. The samples were prepared using the methodology described by Louveaux et al ., that was then further adapted by Ohe et al . The samples were subsequently observed using light microscopy. A total of 36 pollen taxa were discovered and could be identified in the analyzed honey samples. Seventy percent of the studied samples belonged to the group ofmonofloral honeys represented by Eucalyptus globulus , Thymus vulgaris , Citrus sp. and Lavandula angustifolia . Multifloral honeys comprised 30% of the honey samples, with pollen grains of Lavandula stoechas (28.49%) standing out as the most prevalent. Based on cluster analysis, two different groups of honey were observed according to different pollen types found in the samples. The identified pollen spectrum of honey confirmed their botanical origin.

Analysis of evolutionary conservation patterns and their influence on identifying protein functional sites.

PubMed

Fang, Chun; Noguchi, Tamotsu; Yamana, Hayato

2014-10-01

Evolutionary conservation information included in position-specific scoring matrix (PSSM) has been widely adopted by sequence-based methods for identifying protein functional sites, because all functional sites, whether in ordered or disordered proteins, are found to be conserved at some extent. However, different functional sites have different conservation patterns, some of them are linear contextual, some of them are mingled with highly variable residues, and some others seem to be conserved independently. Every value in PSSMs is calculated independently of each other, without carrying the contextual information of residues in the sequence. Therefore, adopting the direct output of PSSM for prediction fails to consider the relationship between conservation patterns of residues and the distribution of conservation scores in PSSMs. In order to demonstrate the importance of combining PSSMs with the specific conservation patterns of functional sites for prediction, three different PSSM-based methods for identifying three kinds of functional sites have been analyzed. Results suggest that, different PSSM-based methods differ in their capability to identify different patterns of functional sites, and better combining PSSMs with the specific conservation patterns of residues would largely facilitate the prediction.

Genome-Wide Identification and Expression Analysis of the WRKY Gene Family in Cassava

PubMed Central

Wei, Yunxie; Shi, Haitao; Xia, Zhiqiang; Tie, Weiwei; Ding, Zehong; Yan, Yan; Wang, Wenquan; Hu, Wei; Li, Kaimian

2016-01-01

The WRKY family, a large family of transcription factors (TFs) found in higher plants, plays central roles in many aspects of physiological processes and adaption to environment. However, little information is available regarding the WRKY family in cassava (Manihot esculenta). In the present study, 85 WRKY genes were identified from the cassava genome and classified into three groups according to conserved WRKY domains and zinc-finger structure. Conserved motif analysis showed that all of the identified MeWRKYs had the conserved WRKY domain. Gene structure analysis suggested that the number of introns in MeWRKY genes varied from 1 to 5, with the majority of MeWRKY genes containing three exons. Expression profiles of MeWRKY genes in different tissues and in response to drought stress were analyzed using the RNA-seq technique. The results showed that 72 MeWRKY genes had differential expression in their transcript abundance and 78 MeWRKY genes were differentially expressed in response to drought stresses in different accessions, indicating their contribution to plant developmental processes and drought stress resistance in cassava. Finally, the expression of 9 WRKY genes was analyzed by qRT-PCR under osmotic, salt, ABA, H2O2, and cold treatments, indicating that MeWRKYs may be involved in different signaling pathways. Taken together, this systematic analysis identifies some tissue-specific and abiotic stress-responsive candidate MeWRKY genes for further functional assays in planta, and provides a solid foundation for understanding of abiotic stress responses and signal transduction mediated by WRKYs in cassava. PMID:26904033

Genome-Wide Identification and Expression Analysis of the WRKY Gene Family in Cassava.

PubMed

Wei, Yunxie; Shi, Haitao; Xia, Zhiqiang; Tie, Weiwei; Ding, Zehong; Yan, Yan; Wang, Wenquan; Hu, Wei; Li, Kaimian

2016-01-01

The WRKY family, a large family of transcription factors (TFs) found in higher plants, plays central roles in many aspects of physiological processes and adaption to environment. However, little information is available regarding the WRKY family in cassava (Manihot esculenta). In the present study, 85 WRKY genes were identified from the cassava genome and classified into three groups according to conserved WRKY domains and zinc-finger structure. Conserved motif analysis showed that all of the identified MeWRKYs had the conserved WRKY domain. Gene structure analysis suggested that the number of introns in MeWRKY genes varied from 1 to 5, with the majority of MeWRKY genes containing three exons. Expression profiles of MeWRKY genes in different tissues and in response to drought stress were analyzed using the RNA-seq technique. The results showed that 72 MeWRKY genes had differential expression in their transcript abundance and 78 MeWRKY genes were differentially expressed in response to drought stresses in different accessions, indicating their contribution to plant developmental processes and drought stress resistance in cassava. Finally, the expression of 9 WRKY genes was analyzed by qRT-PCR under osmotic, salt, ABA, H2O2, and cold treatments, indicating that MeWRKYs may be involved in different signaling pathways. Taken together, this systematic analysis identifies some tissue-specific and abiotic stress-responsive candidate MeWRKY genes for further functional assays in planta, and provides a solid foundation for understanding of abiotic stress responses and signal transduction mediated by WRKYs in cassava.

CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks.

PubMed

Li, Min; Li, Dongyan; Tang, Yu; Wu, Fangxiang; Wang, Jianxin

2017-08-31

Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results is crucial to display the structure of biological networks. Here we present CytoCluster, a cytoscape plugin integrating six clustering algorithms, HC-PIN (Hierarchical Clustering algorithm in Protein Interaction Networks), OH-PIN (identifying Overlapping and Hierarchical modules in Protein Interaction Networks), IPCA (Identifying Protein Complex Algorithm), ClusterONE (Clustering with Overlapping Neighborhood Expansion), DCU (Detecting Complexes based on Uncertain graph model), IPC-MCE (Identifying Protein Complexes based on Maximal Complex Extension), and BinGO (the Biological networks Gene Ontology) function. Users can select different clustering algorithms according to their requirements. The main function of these six clustering algorithms is to detect protein complexes or functional modules. In addition, BinGO is used to determine which Gene Ontology (GO) categories are statistically overrepresented in a set of genes or a subgraph of a biological network. CytoCluster can be easily expanded, so that more clustering algorithms and functions can be added to this plugin. Since it was created in July 2013, CytoCluster has been downloaded more than 9700 times in the Cytoscape App store and has already been applied to the analysis of different biological networks. CytoCluster is available from http://apps.cytoscape.org/apps/cytocluster.

CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks

PubMed Central

Li, Min; Li, Dongyan; Tang, Yu; Wang, Jianxin

2017-01-01

Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results is crucial to display the structure of biological networks. Here we present CytoCluster, a cytoscape plugin integrating six clustering algorithms, HC-PIN (Hierarchical Clustering algorithm in Protein Interaction Networks), OH-PIN (identifying Overlapping and Hierarchical modules in Protein Interaction Networks), IPCA (Identifying Protein Complex Algorithm), ClusterONE (Clustering with Overlapping Neighborhood Expansion), DCU (Detecting Complexes based on Uncertain graph model), IPC-MCE (Identifying Protein Complexes based on Maximal Complex Extension), and BinGO (the Biological networks Gene Ontology) function. Users can select different clustering algorithms according to their requirements. The main function of these six clustering algorithms is to detect protein complexes or functional modules. In addition, BinGO is used to determine which Gene Ontology (GO) categories are statistically overrepresented in a set of genes or a subgraph of a biological network. CytoCluster can be easily expanded, so that more clustering algorithms and functions can be added to this plugin. Since it was created in July 2013, CytoCluster has been downloaded more than 9700 times in the Cytoscape App store and has already been applied to the analysis of different biological networks. CytoCluster is available from http://apps.cytoscape.org/apps/cytocluster. PMID:28858211

Optimization study for metabolomics analysis of human sweat by liquid chromatography-tandem mass spectrometry in high resolution mode.

PubMed

Calderón-Santiago, M; Priego-Capote, F; Jurado-Gámez, B; Luque de Castro, M D

2014-03-14

Sweat has recently gained popularity as a potential tool for diagnostics and biomarker monitoring as it is a non-invasive biofluid the composition of which could be modified by certain pathologies, as is the case with cystic fibrosis, which increases chloride levels in sweat. The aim of the present study was to develop an analytical method for analysis of human sweat by liquid chromatography-mass spectrometry (LC-Q-TOF MS/MS) in high resolution mode. Thus, different sample preparation strategies and different chromatographic modes (HILIC and C18 reverse modes) were compared to check their effect on the profile of sweat metabolites. Forty-one compounds were identified by the MS/MS information obtained with a mass tolerance window below 4 ppm. Amino acids, dicarboxylic acids and other interesting metabolites such as inosine, choline, uric acid and tyramine were identified. Among the tested protocols, direct analysis after dilution was a suited option to obtain a representative snapshot of sweat metabolome. In addition, sample clean up by C18 SpinColumn SPE cartridges improved the sensitivity of most identified compounds and reduced the number of interferents. As most of the identified metabolites are involved in key biochemical pathways, this study opens new possibilities to the use of sweat as a source of metabolite biomarkers of specific disorders. Copyright © 2014 Elsevier B.V. All rights reserved.

Proposed shade guide for human facial skin and lip: a pilot study.

PubMed

Wee, Alvin G; Beatty, Mark W; Gozalo-Diaz, David J; Kim-Pusateri, Seungyee; Marx, David B

2013-08-01

Currently, no commercially available facial shade guide exists in the United States for the fabrication of facial prostheses. The purpose of this study was to measure facial skin and lip color in a human population sample stratified by age, gender, and race. Clustering analysis was used to determine optimal color coordinates for a proposed facial shade guide. Participants (n=119) were recruited from 4 racial/ethnic groups, 5 age groups, and both genders. Reflectance measurements of participants' noses and lower lips were made by using a spectroradiometer and xenon arc lamp with a 45/0 optical configuration. Repeated measures ANOVA (α=.05), to identify skin and lip color differences, resulting from race, age, gender, and location, and a hierarchical clustering analysis, to identify clusters of skin colors) were used. Significant contributors to L*a*b* facial color were race and facial location (P<.01). b* affected all factors (P<.05). Age affected only b* (P<.001), while gender affected only L* (P<.05) and b* (P<.05). Analyses identified 5 clusters of skin color. The study showed that skin color caused by age and gender primarily occurred within the yellow-blue axis. A significant lightness difference between gender groups was also found. Clustering analysis identified 5 distinct skin shade tabs. Copyright © 2013 The Editorial Council of the Journal of Prosthetic Dentistry. Published by Mosby, Inc. All rights reserved.

Integration of multispectral satellite and hyperspectral field data for aquatic macrophyte studies

NASA Astrophysics Data System (ADS)

John, C. M.; Kavya, N.

2014-11-01

Aquatic macrophytes (AM) can serve as useful indicators of water pollution along the littoral zones. The spectral signatures of various AM were investigated to determine whether species could be discriminated by remote sensing. In this study the spectral readings of different AM communities identified were done using the ASD Fieldspec® Hand Held spectro-radiometer in the wavelength range of 325-1075 nm. The collected specific reflectance spectra were applied to space borne multi-spectral remote sensing data from Worldview-2, acquired on 26th March 2011. The dimensionality reduction of the spectro-radiometric data was done using the technique principal components analysis (PCA). Out of the different PCA axes generated, 93.472 % variance of the spectra was explained by the first axis. The spectral derivative analysis was done to identify the wavelength where the greatest difference in reflectance is shown. The identified wavelengths are 510, 690, 720, 756, 806, 885, 907 and 923 nm. The output of PCA and derivative analysis were applied to Worldview-2 satellite data for spectral subsetting. The unsupervised classification was used to effectively classify the AM species using the different spectral subsets. The accuracy assessment of the results of the unsupervised classification and their comparison were done. The overall accuracy of the result of unsupervised classification using the band combinations Red-Edge, Green, Coastal blue & Red-edge, Yellow, Blue is 100%. The band combinations NIR-1, Green, Coastal blue & NIR-1, Yellow, Blue yielded an accuracy of 82.35 %. The existing vegetation indices and new hyper-spectral indices for the different type of AM communities were computed. Overall, results of this study suggest that high spectral and spatial resolution images provide useful information for natural resource managers especially with regard to the location identification and distribution mapping of macrophyte species and their communities.

Comparative Proteome Profiling during Cardiac Hypertrophy and Myocardial Infarction Reveals Altered Glucose Oxidation by Differential Activation of Pyruvate Dehydrogenase E1 Component Subunit β.

PubMed

Mitra, Arkadeep; Basak, Trayambak; Ahmad, Shadab; Datta, Kaberi; Datta, Ritwik; Sengupta, Shantanu; Sarkar, Sagartirtha

2015-06-05

Cardiac hypertrophy and myocardial infarction (MI) are two etiologically different disease forms with varied pathological characteristics. However, the precise molecular mechanisms and specific causal proteins associated with these diseases are obscure to date. In this study, a comparative cardiac proteome profiling was performed in Wistar rat models for diseased and control (sham) groups using two-dimensional difference gel electrophoresis followed by matrix-assisted laser desorption/ionization tandem time-of-flight mass spectrometry. Proteins were identified using Protein Pilot™ software (version 4.0) and were subjected to stringent statistical analysis. Alteration of key proteins was validated by Western blot analysis. The differentially expressed protein sets identified in this study were associated with different functional groups, involving various metabolic pathways, stress responses, cytoskeletal organization, apoptotic signaling and other miscellaneous functions. It was further deciphered that altered energy metabolism during hypertrophy in comparison to MI may be predominantly attributed to induced glucose oxidation level, via reduced phosphorylation of pyruvate dehydrogenase E1 component subunit β (PDHE1-B) protein during hypertrophy. This study reports for the first time the global changes in rat cardiac proteome during two etiologically different cardiac diseases and identifies key signaling regulators modulating ontogeny of these two diseases culminating in heart failure. This study also pointed toward differential activation of PDHE1-B that accounts for upregulation of glucose oxidation during hypertrophy. Downstream analysis of altered proteome and the associated modulators would enhance our present knowledge regarding altered pathophysiology of these two etiologically different cardiac disease forms. Copyright © 2014 Elsevier Ltd. All rights reserved.

Business Process Modelling is an Essential Part of a Requirements Analysis. Contribution of EFMI Primary Care Working Group.

PubMed

de Lusignan, S; Krause, P; Michalakidis, G; Vicente, M Tristan; Thompson, S; McGilchrist, M; Sullivan, F; van Royen, P; Agreus, L; Desombre, T; Taweel, A; Delaney, B

2012-01-01

To perform a requirements analysis of the barriers to conducting research linking of primary care, genetic and cancer data. We extended our initial data-centric approach to include socio-cultural and business requirements. We created reference models of core data requirements common to most studies using unified modelling language (UML), dataflow diagrams (DFD) and business process modelling notation (BPMN). We conducted a stakeholder analysis and constructed DFD and UML diagrams for use cases based on simulated research studies. We used research output as a sensitivity analysis. Differences between the reference model and use cases identified study specific data requirements. The stakeholder analysis identified: tensions, changes in specification, some indifference from data providers and enthusiastic informaticians urging inclusion of socio-cultural context. We identified requirements to collect information at three levels: micro- data items, which need to be semantically interoperable, meso- the medical record and data extraction, and macro- the health system and socio-cultural issues. BPMN clarified complex business requirements among data providers and vendors; and additional geographical requirements for patients to be represented in both linked datasets. High quality research output was the norm for most repositories. Reference models provide high-level schemata of the core data requirements. However, business requirements' modelling identifies stakeholder issues and identifies what needs to be addressed to enable participation.

Individual Difference Relations in Psychometric and Experimental Cognitive Tasks. Final Report. No. 163.

ERIC Educational Resources Information Center

Carroll, John B.

Fifty-five recent studies of individual differences (IDs) in elementary cognitive tasks (ECTs) are reviewed. Twenty-five data sets are examined, analyzed, or reanalyzed by factor analysis. The following promising dimensions are identified: basic perceptual processes, reaction and movement times, mental comparison and recognition tasks, retrieval…

The Effects of Phonetic Similarity and List Length on Children's Sound Categorization Performance.

ERIC Educational Resources Information Center

Snowling, Margaret J.; And Others

1994-01-01

Examined the phonological analysis and verbal working memory components of the sound categorization task and their relationships to reading skill differences. Children were tested on sound categorization by having them identify odd words in sequences. Sound categorization performance was sensitive to individual differences in speech perception…

Individual and Class Norms Differentially Predict Proactive and Reactive Aggression: A Functional Analysis

ERIC Educational Resources Information Center

Frey, Karin S.; Higheagle Strong, Zoe; Onyewuenyi, Adaurennaya C.

2017-01-01

Theory and research using a social-information processing framework indicate that reward-focused (proactive) aggression has different social consequences than defense-focused (reactive) aggression. Students use norms that identify expected and socially approved behaviors as guides to their own actions. Differences in social-cognitive processing…

Coping with Relationship Stressors: A Decade Review

ERIC Educational Resources Information Center

Seiffge-Krenke, Inge

2011-01-01

This review identifies key issues in research on adolescent coping with stress with parents, friends, and romantic partners during the past decade. An analysis of 78 studies revealed findings on relationship stressors and the potential links between the use of different coping styles for different relationship types. Research has confirmed…

Reconsidering Consultants' Strategic Use of the Business Case for Diversity

ERIC Educational Resources Information Center

Mease, Jennifer J.

2012-01-01

The business case for diversity--the practice of connecting human differences to an organization's bottom line--has been critiqued for its compromised treatment of human difference. Through a grounded in action discursive analysis of 19 interviews with diversity consultants, this research identifies three occupational demands that prompted…

Classroom Discussions: Possibilities and Limitations for Democratic Classroom Practices

ERIC Educational Resources Information Center

Aasebø, Turid Skarre

2017-01-01

Are students offered possibilities to experience democratic practice in classrooms? Using an analysis of empirical data from classroom discussions in lower secondary school, this article identifies and explores two different types of classroom discussions which give students different positions: a conversation in which students are positioned as…

The Roles and Practices of Specialists in Teamed Institutional Leadership

ERIC Educational Resources Information Center

Dexter, Sara; Louis, Karen Seashore; Anderson, Ronald E.

2009-01-01

This article explores the role of leadership, experts, and expertise and the functioning of teams in nine schools that modeled an exemplary integration of technology to support schoolwide instructional improvement. Through cross-case analysis, we identified three different staffing patterns and two different support patterns in how the technology…

A Contrastive Rhetoric Analysis of English and Hindi Editorials

ERIC Educational Resources Information Center

Bolgün, M. Ali; Mangla, Asham

2017-01-01

This study explores and identifies a number of key qualitative and quantitative differences in textual discourse styles in English and Hindi editorials found in the "New York Times" ("NYT) and "Navbharat", respectively. These differences could be the source of strenuous processing of such editorials by learners of Hindi.…

Diversity and bioprospection of fungal community present in oligotrophic soil of continental Antarctica

USDA-ARS?s Scientific Manuscript database

The diversity of fungal communities from different substrates in Antarctica were studied and their capability to produce bioactive compounds. A one hundred and one fungal isolates were identified by molecular analysis in 35 different fungal taxa from 20 genera. Pseudogymnoascus sp. 3, Pseudogymnoasc...

How Can Visual Analytics Assist Investigative Analysis? Design Implications from an Evaluation.

PubMed

Youn-Ah Kang; Görg, Carsten; Stasko, John

2011-05-01

Despite the growing number of systems providing visual analytic support for investigative analysis, few empirical studies of the potential benefits of such systems have been conducted, particularly controlled, comparative evaluations. Determining how such systems foster insight and sensemaking is important for their continued growth and study, however. Furthermore, studies that identify how people use such systems and why they benefit (or not) can help inform the design of new systems in this area. We conducted an evaluation of the visual analytics system Jigsaw employed in a small investigative sensemaking exercise, and compared its use to three other more traditional methods of analysis. Sixteen participants performed a simulated intelligence analysis task under one of the four conditions. Experimental results suggest that Jigsaw assisted participants to analyze the data and identify an embedded threat. We describe different analysis strategies used by study participants and how computational support (or the lack thereof) influenced the strategies. We then illustrate several characteristics of the sensemaking process identified in the study and provide design implications for investigative analysis tools based thereon. We conclude with recommendations on metrics and techniques for evaluating visual analytics systems for investigative analysis.

A strategy for evaluating pathway analysis methods.

PubMed

Yu, Chenggang; Woo, Hyung Jun; Yu, Xueping; Oyama, Tatsuya; Wallqvist, Anders; Reifman, Jaques

2017-10-13

Researchers have previously developed a multitude of methods designed to identify biological pathways associated with specific clinical or experimental conditions of interest, with the aim of facilitating biological interpretation of high-throughput data. Before practically applying such pathway analysis (PA) methods, we must first evaluate their performance and reliability, using datasets where the pathways perturbed by the conditions of interest have been well characterized in advance. However, such 'ground truths' (or gold standards) are often unavailable. Furthermore, previous evaluation strategies that have focused on defining 'true answers' are unable to systematically and objectively assess PA methods under a wide range of conditions. In this work, we propose a novel strategy for evaluating PA methods independently of any gold standard, either established or assumed. The strategy involves the use of two mutually complementary metrics, recall and discrimination. Recall measures the consistency of the perturbed pathways identified by applying a particular analysis method to an original large dataset and those identified by the same method to a sub-dataset of the original dataset. In contrast, discrimination measures specificity-the degree to which the perturbed pathways identified by a particular method to a dataset from one experiment differ from those identifying by the same method to a dataset from a different experiment. We used these metrics and 24 datasets to evaluate six widely used PA methods. The results highlighted the common challenge in reliably identifying significant pathways from small datasets. Importantly, we confirmed the effectiveness of our proposed dual-metric strategy by showing that previous comparative studies corroborate the performance evaluations of the six methods obtained by our strategy. Unlike any previously proposed strategy for evaluating the performance of PA methods, our dual-metric strategy does not rely on any ground truth, either established or assumed, of the pathways perturbed by a specific clinical or experimental condition. As such, our strategy allows researchers to systematically and objectively evaluate pathway analysis methods by employing any number of datasets for a variety of conditions.

The Effect of Using Discourse Analysis Method on Improving Cognitive and Affective Skills in Language and Literature Teaching

ERIC Educational Resources Information Center

Kapanadze, Dilek Ünveren

2018-01-01

The aim of this study is to identify the effect of using discourse analysis method on the skills of reading comprehension, textual analysis, creating discourse and use of language. In this study, the authentic test model with pre-test and post-test control group was used in order to determine the difference of academic achievement between…

Tracking the When, Where, and With Whom of Alcohol Use

PubMed Central

Freisthler, Bridget; Lipperman-Kreda, Sharon; Bersamin, Melina; Gruenewald, Paul J.

2014-01-01

Prevention researchers have found that drinking in different contexts is related to different alcohol problems. Where and with whom people drink affects the types of alcohol-related problems they experience. Consequently, identifying those contexts that result in the greatest number of problems provides a novel opportunity to target new prevention efforts aimed at those contexts. However, identifying these contexts poses methodological challenges to prevention research. To overcome these challenges, researchers need tools that allow them to gather detailed information about when and where people choose to drink and how contextual factors influence drinking risks. New data collection and analysis techniques, such as activity-space analysis, which examines movement through different contexts, and ecological momentary assessment, which captures microlevel contextual changes as individuals move through their days, can advance the field of alcohol studies by providing detailed information on the use of drinking contexts, particularly when combined. Data acquired through these methods allow researchers to better identify those contexts where and conditions under which drinking and problems related to drinking occur. Use of these methods will allow prevention practitioners to target prevention efforts to those contexts that place most drinkers at risk and tailor prevention efforts to each context for specific outcomes. PMID:26258998

Functional connectivity decreases in autism in emotion, self, and face circuits identified by Knowledge-based Enrichment Analysis.

PubMed

Cheng, Wei; Rolls, Edmund T; Zhang, Jie; Sheng, Wenbo; Ma, Liang; Wan, Lin; Luo, Qiang; Feng, Jianfeng

2017-03-01

A powerful new method is described called Knowledge based functional connectivity Enrichment Analysis (KEA) for interpreting resting state functional connectivity, using circuits that are functionally identified using search terms with the Neurosynth database. The method derives its power by focusing on neural circuits, sets of brain regions that share a common biological function, instead of trying to interpret single functional connectivity links. This provides a novel way of investigating how task- or function-related networks have resting state functional connectivity differences in different psychiatric states, provides a new way to bridge the gap between task and resting-state functional networks, and potentially helps to identify brain networks that might be treated. The method was applied to interpreting functional connectivity differences in autism. Functional connectivity decreases at the network circuit level in 394 patients with autism compared with 473 controls were found in networks involving the orbitofrontal cortex, anterior cingulate cortex, middle temporal gyrus cortex, and the precuneus, in networks that are implicated in the sense of self, face processing, and theory of mind. The decreases were correlated with symptom severity. Copyright © 2017. Published by Elsevier Inc.

Identification and functional characterization of effectors in expressed sequence tags from various life cycle stages of the potato cyst nematode Globodera pallida.

PubMed

Jones, John T; Kumar, Amar; Pylypenko, Liliya A; Thirugnanasambandam, Amarnath; Castelli, Lydia; Chapman, Sean; Cock, Peter J A; Grenier, Eric; Lilley, Catherine J; Phillips, Mark S; Blok, Vivian C

2009-11-01

In this article, we describe the analysis of over 9000 expressed sequence tags (ESTs) from cDNA libraries obtained from various life cycle stages of Globodera pallida. We have identified over 50 G. pallida effectors from this dataset using bioinformatics analysis, by screening clones in order to identify secreted proteins up-regulated after the onset of parasitism and using in situ hybridization to confirm the expression in pharyngeal gland cells. A substantial gene family encoding G. pallida SPRYSEC proteins has been identified. The expression of these genes is restricted to the dorsal pharyngeal gland cell. Different members of the SPRYSEC family of proteins from G. pallida show different subcellular localization patterns in plants, with some localized to the cytoplasm and others to the nucleus and nucleolus. Differences in subcellular localization may reflect diverse functional roles for each individual protein or, more likely, variety in the compartmentalization of plant proteins targeted by the nematode. Our data are therefore consistent with the suggestion that the SPRYSEC proteins suppress host defences, as suggested previously, and that they achieve this through interaction with a range of host targets.

High-Resolution Melt Analysis for Rapid Comparison of Bacterial Community Compositions

PubMed Central

Hjelmsø, Mathis Hjort; Hansen, Lars Hestbjerg; Bælum, Jacob; Feld, Louise; Holben, William E.

2014-01-01

In the study of bacterial community composition, 16S rRNA gene amplicon sequencing is today among the preferred methods of analysis. The cost of nucleotide sequence analysis, including requisite computational and bioinformatic steps, however, takes up a large part of many research budgets. High-resolution melt (HRM) analysis is the study of the melt behavior of specific PCR products. Here we describe a novel high-throughput approach in which we used HRM analysis targeting the 16S rRNA gene to rapidly screen multiple complex samples for differences in bacterial community composition. We hypothesized that HRM analysis of amplified 16S rRNA genes from a soil ecosystem could be used as a screening tool to identify changes in bacterial community structure. This hypothesis was tested using a soil microcosm setup exposed to a total of six treatments representing different combinations of pesticide and fertilization treatments. The HRM analysis identified a shift in the bacterial community composition in two of the treatments, both including the soil fumigant Basamid GR. These results were confirmed with both denaturing gradient gel electrophoresis (DGGE) analysis and 454-based 16S rRNA gene amplicon sequencing. HRM analysis was shown to be a fast, high-throughput technique that can serve as an effective alternative to gel-based screening methods to monitor microbial community composition. PMID:24610853

Sociocultural Meanings of Nanotechnology: Research Methodologies

NASA Astrophysics Data System (ADS)

Bainbridge, William Sims

2004-06-01

This article identifies six social-science research methodologies that will be useful for charting the sociocultural meaning of nanotechnology: web-based questionnaires, vignette experiments, analysis of web linkages, recommender systems, quantitative content analysis, and qualitative textual analysis. Data from a range of sources are used to illustrate how the methods can delineate the intellectual content and institutional structure of the emerging nanotechnology culture. Such methods will make it possible in future to test hypotheses such as that there are two competing definitions of nanotechnology - the technical-scientific and the science-fiction - that are influencing public perceptions by different routes and in different directions.

The different conformations and crystal structures of dihydroergocristine

NASA Astrophysics Data System (ADS)

Mönch, B.; Kraus, W.; Köppen, R.; Emmerling, F.

2016-02-01

The identification of different forms of dihydroergocristine (DHEC) was carried out by crystallization from different organic solvents. DHEC was identified as potential template for molecularly imprinted polymers (MIPs) for the epimeric specific analysis of ergot alkaloids (EAs) in food. DHEC was crystallized from different solvents in order to mimic the typical MIP synthesis conditions. Four new solvatomorphs of DHEC were obtained. All solvatomorphs contain a water molecule in the crystal structure, whereas three compounds contain an additional solvent molecule. Based on the conformation of DHEC a comparison with typical EA molecules was possible. The analysis showed that DHEC is a suitable template for MIPs for EAs.

Exploring biomedical ontology mappings with graph theory methods.

PubMed

Kocbek, Simon; Kim, Jin-Dong

2017-01-01

In the era of semantic web, life science ontologies play an important role in tasks such as annotating biological objects, linking relevant data pieces, and verifying data consistency. Understanding ontology structures and overlapping ontologies is essential for tasks such as ontology reuse and development. We present an exploratory study where we examine structure and look for patterns in BioPortal, a comprehensive publicly available repository of live science ontologies. We report an analysis of biomedical ontology mapping data over time. We apply graph theory methods such as Modularity Analysis and Betweenness Centrality to analyse data gathered at five different time points. We identify communities, i.e., sets of overlapping ontologies, and define similar and closest communities. We demonstrate evolution of identified communities over time and identify core ontologies of the closest communities. We use BioPortal project and category data to measure community coherence. We also validate identified communities with their mutual mentions in scientific literature. With comparing mapping data gathered at five different time points, we identified similar and closest communities of overlapping ontologies, and demonstrated evolution of communities over time. Results showed that anatomy and health ontologies tend to form more isolated communities compared to other categories. We also showed that communities contain all or the majority of ontologies being used in narrower projects. In addition, we identified major changes in mapping data after migration to BioPortal Version 4.

Efficacy and Safety of Oral Beclomethasone Dipropionate in Ulcerative Colitis: A Systematic Review and Meta-Analysis.

PubMed

Manguso, Francesco; Bennato, Raffaele; Lombardi, Giovanni; Riccio, Elisabetta; Costantino, Giuseppe; Fries, Walter

2016-01-01

We performed a systematic review and meta-analysis of all the available evidence comparing efficacy and safety of oral prolonged released beclomethasone dipropionate (BDP) to active oral controls in patients with mild-to-moderate ulcerative colitis (UC). A subgroup-analysis compared the effectiveness of BDP and 5-ASA. Literature research was performed in different databases, as well as manual search to identify abstracts from international meetings with data not included in extensive publications. Experts in the field and companies involved in BDP development and manufacture were contacted to identify unpublished studies used for registration purposes. Dichotomous data were pooled to obtain odds ratio meta-analysis. Five randomized controlled trials that compared oral BDP 5mg/day vs. all oral active controls in treating UC were identified as eligible. Efficacy and safety have been addressed after 4-week treatment period. One study evaluated efficacy and safety of BDP vs. prednisone and 4 of BDP vs. 5-ASA. Treatment with oral BDP 5 mg/day induces a significant better clinical response compared to oral 5-ASA (OR 1.86, 95% CI = 1.23-2.82, P = 0.003). The effect is detectable even when the comparison to prednisone is added (OR 1.41, 95% CI = 1.03-1.93, P = 0.03). Data on remission indicate that the potential clinical efficacy of BDP may be better than 5-ASA (OR 1.55, 95% CI = 1.00-2.40, P = 0.05). This difference is lost when the comparison with prednisone is added (OR 1.30, 95% CI = 0.76-2.23, P = 0.34). The safety analysis showed no differences between BDP and 5-ASA (OR 0.55, 95% CI = 0.24-1.27, P = 0.16). The lack of difference is maintained even when the study with prednisone is added (OR 0.67, 95% CI = 0.44-1.01, P = 0.06). However, the trend of difference is clear and indicates a more favourable safety profile of BDP compared to 5-ASA and PD. Oral prolonged release BDP showed a superior efficacy vs. oral 5-ASA in inducing clinical improvement of mild-to-moderate UC with a similar safety profile.

How Methodologic Differences Affect Results of Economic Analyses: A Systematic Review of Interferon Gamma Release Assays for the Diagnosis of LTBI

PubMed Central

Oxlade, Olivia; Pinto, Marcia; Trajman, Anete; Menzies, Dick

2013-01-01

Introduction Cost effectiveness analyses (CEA) can provide useful information on how to invest limited funds, however they are less useful if different analysis of the same intervention provide unclear or contradictory results. The objective of our study was to conduct a systematic review of methodologic aspects of CEA that evaluate Interferon Gamma Release Assays (IGRA) for the detection of Latent Tuberculosis Infection (LTBI), in order to understand how differences affect study results. Methods A systematic review of studies was conducted with particular focus on study quality and the variability in inputs used in models used to assess cost-effectiveness. A common decision analysis model of the IGRA versus Tuberculin Skin Test (TST) screening strategy was developed and used to quantify the impact on predicted results of observed differences of model inputs taken from the studies identified. Results Thirteen studies were ultimately included in the review. Several specific methodologic issues were identified across studies, including how study inputs were selected, inconsistencies in the costing approach, the utility of the QALY (Quality Adjusted Life Year) as the effectiveness outcome, and how authors choose to present and interpret study results. When the IGRA versus TST test strategies were compared using our common decision analysis model predicted effectiveness largely overlapped. Implications Many methodologic issues that contribute to inconsistent results and reduced study quality were identified in studies that assessed the cost-effectiveness of the IGRA test. More specific and relevant guidelines are needed in order to help authors standardize modelling approaches, inputs, assumptions and how results are presented and interpreted. PMID:23505412

Comparative genomic analysis of Acinetobacter strains isolated from murine colonic crypts.

PubMed

Saffarian, Azadeh; Touchon, Marie; Mulet, Céline; Tournebize, Régis; Passet, Virginie; Brisse, Sylvain; Rocha, Eduardo P C; Sansonetti, Philippe J; Pédron, Thierry

2017-07-11

A restricted set of aerobic bacteria dominated by the Acinetobacter genus was identified in murine intestinal colonic crypts. The vicinity of such bacteria with intestinal stem cells could indicate that they protect the crypt against cytotoxic and genotoxic signals. Genome analyses of these bacteria were performed to better appreciate their biodegradative capacities. Two taxonomically different clusters of Acinetobacter were isolated from murine proximal colonic crypts, one was identified as A. modestus and the other as A. radioresistens. Their identification was performed through biochemical parameters and housekeeping gene sequencing. After selection of one strain of each cluster (A. modestus CM11G and A. radioresistens CM38.2), comparative genomic analysis was performed on whole-genome sequencing data. The antibiotic resistance pattern of these two strains is different, in line with the many genes involved in resistance to heavy metals identified in both genomes. Moreover whereas the operon benABCDE involved in benzoate metabolism is encoded by the two genomes, the operon antABC encoding the anthranilate dioxygenase, and the phenol hydroxylase gene cluster are absent in the A. modestus genomic sequence, indicating that the two strains have different capacities to metabolize xenobiotics. A common feature of the two strains is the presence of a type IV pili system, and the presence of genes encoding proteins pertaining to secretion systems such as Type I and Type II secretion systems. Our comparative genomic analysis revealed that different Acinetobacter isolated from the same biological niche, even if they share a large majority of genes, possess unique features that could play a specific role in the protection of the intestinal crypt.

Consumer-orientated development of hybrid beef burger and sausage analogues.

PubMed

Neville, Michelle; Tarrega, Amparo; Hewson, Louise; Foster, Tim

2017-07-01

Hybrid meat analogues, whereby a proportion of meat has been partially replaced by more sustainable protein sources, have been proposed to provide a means for more sustainable diets in the future. Consumer testing was conducted to determine consumer acceptability of different formulations of Hybrid beef burgers and pork sausages in comparison with both meat and meat-free commercial products. Acceptability data were generated using the 9-point hedonic scale. Check-all-that-apply (CATA) questioning was used to determine the sensory attributes perceived in each product as well as information on the attributes of consumers' ideal products. It was identified that Hybrid products were generally well liked among consumers and no significant differences in consumer acceptability (p > .05) were identified between Hybrid and full meat products, whereas meat-free products were found to be less accepted. However, Hybrid sausages received higher acceptability scores (6.00-6.51) than Hybrid burgers (5.84-5.92) suggesting that format may have a large impact on consumer acceptability of Hybrid products. Correspondence Analysis (CA) indicated that Hybrid products were grouped with meat products in their sensory attributes. Penalty analysis found that a "meaty flavor" was the largest factor driving consumer acceptability in both burgers and sausages. Cluster analysis of consumer acceptability data identified key differences in overall acceptability between different consumer groups (consumers who only eat meat products and consumers who eat both meat and meat-free products). The Hybrid concept was found to bridge the acceptability gap between meat and meat-free products; however, further product reformulation is required to optimize consumer acceptability.

A Method for Accurate Group Difference Detection by Constraining the Mixing Coefficients in an ICA Framework

PubMed Central

Sui, Jing; Adali, Tülay; Pearlson, Godfrey D.; Clark, Vincent P.; Calhoun, Vince D.

2009-01-01

Independent component analysis (ICA) is a promising method that is increasingly used to analyze brain imaging data such as functional magnetic resonance imaging (fMRI), structural MRI, and electroencephalography and has also proved useful for group comparison, e.g., differentiating healthy controls from patients. An advantage of ICA is its ability to identify components that are mixed in an unknown manner. However, ICA is not necessarily robust and optimal in identifying between-group effects, especially in highly noisy situations. Here, we propose a modified ICA framework for multi-group data analysis that incorporates prior information regarding group membership as a constraint into the mixing coefficients. Our approach, called coefficient-constrained ICA (CC-ICA), prioritizes identification of components that show a significant group difference. The performance of CC-ICA via synthetic and hybrid data simulations is evaluated under different hypothesis testing assumptions and signal to noise ratios (SNRs). Group analysis is also conducted on real multitask fMRI data. Results show that CC-ICA improves the estimation accuracy of the independent components greatly, especially those that have different patterns for different groups (e.g., patients vs. controls); In addition, it enhances the data extraction sensitivity to group differences by ranking components with P value or J-divergence more consistently with the ground truth. The proposed algorithm performs quite well for both group-difference detection and multitask fMRI data fusion, which may prove especially important for the identification of relevant disease biomarkers. PMID:19172631

Meta-analysis of the association between short-term exposure to ambient ozone and respiratory hospital admissions

NASA Astrophysics Data System (ADS)

Ji, Meng; Cohan, Daniel S.; Bell, Michelle L.

2011-04-01

Ozone is associated with health impacts including respiratory outcomes; however, results differ across studies. Meta-analysis is an increasingly important approach to synthesizing evidence across studies. We conducted meta-analysis of short-term ozone exposure and respiratory hospitalizations to evaluate variation across studies and explore some of the challenges in meta-analysis. We identified 136 estimates from 96 studies and investigated how estimates differed by age, ozone metric, season, lag, region, disease category, and hospitalization type. Overall results indicate associations between ozone and various kinds of respiratory hospitalizations; however, study characteristics affected risk estimates. Estimates were similar, but higher, for the elderly compared to all ages and for previous day exposure compared to same day exposure. Comparison across studies was hindered by variation in definitions of disease categories, as some (e.g., asthma) were identified through >= 3 different sets of ICD codes. Although not all analyses exhibited evidence of publication bias, adjustment for publication bias generally lowered overall estimates. Emergency hospitalizations for total respiratory disease increased by 4.47% (95% interval: 2.48, 6.50%) per 10 ppb 24 h ozone among the elderly without adjustment for publication bias and 2.97% (1.05, 4.94%) with adjustment. Comparison of multi-city study results and meta-analysis based on single-city studies further suggested publication bias.

The Synthesis of Silicon Carbide in Rhombohedral Form with Different Chemicals

NASA Astrophysics Data System (ADS)

KARİPER, İ. AFŞIN

2017-06-01

This study describes the attempt at producing silicon carbide using a simpler and less costly method. Within the study, XRD, EDX, and FTIR analyses were performed to determine the structural properties of the product, and SEM analyses were used to identify its surface properties. The characteristics such as porosity and surface area were determined through BET analysis. The starting reagents were compared with the product using FTIR analysis, whereas the product was compared with a sample of SiC procured from a supplier who manufactures high-purity products through BET analysis. In EDX analysis, approximately 72 pct Si and 28 pct C were identified. The vibrational peaks of the synthesized product (characteristics Si-C bonds) were observed at around 1076 cm-1 (FTIR analysis). At the same time, the outcomes were compared with major publications in the literature.

Using Structural Equation Models with Latent Variables to Study Student Growth and Development.

ERIC Educational Resources Information Center

Pike, Gary R.

1991-01-01

Analysis of data on freshman-to-senior developmental gains in 722 University of Tennessee-Knoxville students provides evidence of the advantages of structural equation modeling with latent variables and suggests that the group differences identified by traditional analysis of variance and covariance techniques may be an artifact of measurement…

Public and Private School Costs. A Local Analysis, 1994.

ERIC Educational Resources Information Center

Public Policy Forum, Inc., Milwaukee, WI.

This document presents findings of a study that identified key factors of cost-per-pupil differences between public and private school spending among selected Milwaukee area public and private schools. The analysis was limited to cost factors only, specifically, to per-pupil spending. Methodology included a review of the school budgets of 7 public…

Cognitive Task Analysis of Prioritization in Air Traffic Control.

ERIC Educational Resources Information Center

Redding, Richard E.; And Others

A cognitive task analysis was performed to analyze the key cognitive components of the en route air traffic controllers' jobs. The goals were to ascertain expert mental models and decision-making strategies and to identify important differences in controller knowledge, skills, and mental models as a function of expertise. Four groups of…

An Integrative Framework for the Analysis of Multiple and Multimodal Representations for Meaning-Making in Science Education

ERIC Educational Resources Information Center

Tang, Kok-Sing; Delgado, Cesar; Moje, Elizabeth Birr

2014-01-01

This paper presents an integrative framework for analyzing science meaning-making with representations. It integrates the research on multiple representations and multimodal representations by identifying and leveraging the differences in their units of analysis in two dimensions: timescale and compositional grain size. Timescale considers the…

IRB Process Improvements: A Machine Learning Analysis.

PubMed

Shoenbill, Kimberly; Song, Yiqiang; Cobb, Nichelle L; Drezner, Marc K; Mendonca, Eneida A

2017-06-01

Clinical research involving humans is critically important, but it is a lengthy and expensive process. Most studies require institutional review board (IRB) approval. Our objective is to identify predictors of delays or accelerations in the IRB review process and apply this knowledge to inform process change in an effort to improve IRB efficiency, transparency, consistency and communication. We analyzed timelines of protocol submissions to determine protocol or IRB characteristics associated with different processing times. Our evaluation included single variable analysis to identify significant predictors of IRB processing time and machine learning methods to predict processing times through the IRB review system. Based on initial identified predictors, changes to IRB workflow and staffing procedures were instituted and we repeated our analysis. Our analysis identified several predictors of delays in the IRB review process including type of IRB review to be conducted, whether a protocol falls under Veteran's Administration purview and specific staff in charge of a protocol's review. We have identified several predictors of delays in IRB protocol review processing times using statistical and machine learning methods. Application of this knowledge to process improvement efforts in two IRBs has led to increased efficiency in protocol review. The workflow and system enhancements that are being made support our four-part goal of improving IRB efficiency, consistency, transparency, and communication.

Breed differences in dogs sensitivity to human points: a meta-analysis.

PubMed

Dorey, Nicole R; Udell, Monique A R; Wynne, Clive D L

2009-07-01

The last decade has seen a substantial increase in research on the behavioral and cognitive abilities of pet dogs, Canis familiaris. The most commonly used experimental paradigm is the object-choice task in which a dog is given a choice of two containers and guided to the reinforced object by human pointing gestures. We review here studies of this type and attempt a meta-analysis of the available data. In the meta-analysis breeds of dogs were grouped into the eight categories of the American Kennel Club, and into four clusters identified by Parker and Ostrander [Parker, H.G., Ostrander, E.A., 2005. Canine genomics and genetics: running with the pack. PLoS Genet. 1, 507-513] on the basis of a genetic analysis. No differences in performance between breeds categorized in either fashion were identified. Rather, all dog breeds appear to be similarly and highly successful in following human points to locate desired food. We suggest this result could be due to the paucity of data available in published studies, and the restricted range of breeds tested.

Noise modeling and analysis of an IMU-based attitude sensor: improvement of performance by filtering and sensor fusion

NASA Astrophysics Data System (ADS)

K., Nirmal; A. G., Sreejith; Mathew, Joice; Sarpotdar, Mayuresh; Suresh, Ambily; Prakash, Ajin; Safonova, Margarita; Murthy, Jayant

2016-07-01

We describe the characterization and removal of noises present in the Inertial Measurement Unit (IMU) MPU- 6050, which was initially used in an attitude sensor, and later used in the development of a pointing system for small balloon-borne astronomical payloads. We found that the performance of the IMU degraded with time because of the accumulation of different errors. Using Allan variance analysis method, we identified the different components of noise present in the IMU, and verified the results by the power spectral density analysis (PSD). We tried to remove the high-frequency noise using smooth filters such as moving average filter and then Savitzky Golay (SG) filter. Even though we managed to filter some high-frequency noise, these filters performance wasn't satisfactory for our application. We found the distribution of the random noise present in IMU using probability density analysis and identified that the noise in our IMU was white Gaussian in nature. Hence, we used a Kalman filter to remove the noise and which gave us good performance real time.

Phenotypes Determined by Cluster Analysis in Moderate to Severe Bronchial Asthma.

PubMed

Youroukova, Vania M; Dimitrova, Denitsa G; Valerieva, Anna D; Lesichkova, Spaska S; Velikova, Tsvetelina V; Ivanova-Todorova, Ekaterina I; Tumangelova-Yuzeir, Kalina D

2017-06-01

Bronchial asthma is a heterogeneous disease that includes various subtypes. They may share similar clinical characteristics, but probably have different pathological mechanisms. To identify phenotypes using cluster analysis in moderate to severe bronchial asthma and to compare differences in clinical, physiological, immunological and inflammatory data between the clusters. Forty adult patients with moderate to severe bronchial asthma out of exacerbation were included. All underwent clinical assessment, anthropometric measurements, skin prick testing, standard spirometry and measurement fraction of exhaled nitric oxide. Blood eosinophilic count, serum total IgE and periostin levels were determined. Two-step cluster approach, hierarchical clustering method and k-mean analysis were used for identification of the clusters. We have identified four clusters. Cluster 1 (n=14) - late-onset, non-atopic asthma with impaired lung function, Cluster 2 (n=13) - late-onset, atopic asthma, Cluster 3 (n=6) - late-onset, aspirin sensitivity, eosinophilic asthma, and Cluster 4 (n=7) - early-onset, atopic asthma. Our study is the first in Bulgaria in which cluster analysis is applied to asthmatic patients. We identified four clusters. The variables with greatest force for differentiation in our study were: age of asthma onset, duration of diseases, atopy, smoking, blood eosinophils, nonsteroidal anti-inflammatory drugs hypersensitivity, baseline FEV1/FVC and symptoms severity. Our results support the concept of heterogeneity of bronchial asthma and demonstrate that cluster analysis can be an useful tool for phenotyping of disease and personalized approach to the treatment of patients.

The Adjustment Disorder--New Module 20 as a Screening Instrument: Cluster Analysis and Cut-off Values.

PubMed

Lorenz, L; Bachem, R C; Maercker, A

2016-10-01

Adjustment disorder (AjD) is a transient mental health condition emerging after stressful life events. Its diagnostic criteria have recently been under revision which led to the development of the Adjustment Disorder--New Module 20 (ADNM-20) as a self-report assessment. To identify a threshold value for people at high risk for AjD. As part of a randomized controlled trial evaluating a self-help manual for burglary victims, the baseline data of all participants (n=80) were analyzed. Besides the ADNM-20, participants answered self-report questionnaires regarding the external variables post-traumatic stress disorder symptomatology, depression, anxiety, and stress levels. We used cluster analysis and ROC analysis to identify the most appropriate cut-off value. The cluster analysis identified three different subgroups. They differed in their level of AjD symptomatology from low to high symptom severity. The same pattern of impairment was found for the external variables. The ROC analysis testing the ADNM-20 sum scoreagainst the theory-based diagnostic algorithm, revealed an optimal cut-off score at 47.5 to distinguish between people at high risk for AjD and people at low risk. The ADNM-20 distinguishes between people with low, moderate, and high symptomatology. The recommendation for a cut-off score at 47.5 facilitates the use of the ADNM-20 in research and practice.

Event-related fMRI studies of false memory: An Activation Likelihood Estimation meta-analysis.

PubMed

Kurkela, Kyle A; Dennis, Nancy A

2016-01-29

Over the last two decades, a wealth of research in the domain of episodic memory has focused on understanding the neural correlates mediating false memories, or memories for events that never happened. While several recent qualitative reviews have attempted to synthesize this literature, methodological differences amongst the empirical studies and a focus on only a sub-set of the findings has limited broader conclusions regarding the neural mechanisms underlying false memories. The current study performed a voxel-wise quantitative meta-analysis using activation likelihood estimation to investigate commonalities within the functional magnetic resonance imaging (fMRI) literature studying false memory. The results were broken down by memory phase (encoding, retrieval), as well as sub-analyses looking at differences in baseline (hit, correct rejection), memoranda (verbal, semantic), and experimental paradigm (e.g., semantic relatedness and perceptual relatedness) within retrieval. Concordance maps identified significant overlap across studies for each analysis. Several regions were identified in the general false retrieval analysis as well as multiple sub-analyses, indicating their ubiquitous, yet critical role in false retrieval (medial superior frontal gyrus, left precentral gyrus, left inferior parietal cortex). Additionally, several regions showed baseline- and paradigm-specific effects (hit/perceptual relatedness: inferior and middle occipital gyrus; CRs: bilateral inferior parietal cortex, precuneus, left caudate). With respect to encoding, analyses showed common activity in the left middle temporal gyrus and anterior cingulate cortex. No analysis identified a common cluster of activation in the medial temporal lobe. Copyright © 2015 Elsevier Ltd. All rights reserved.

Serum Biochemical Phenotypes in the Domestic Dog

PubMed Central

Chang, Yu-Mei; Hadox, Erin; Szladovits, Balazs; Garden, Oliver A.

2016-01-01

The serum or plasma biochemical profile is essential in the diagnosis and monitoring of systemic disease in veterinary medicine, but current reference intervals typically take no account of breed-specific differences. Breed-specific hematological phenotypes have been documented in the domestic dog, but little has been published on serum biochemical phenotypes in this species. Serum biochemical profiles of dogs in which all measurements fell within the existing reference intervals were retrieved from a large veterinary database. Serum biochemical profiles from 3045 dogs were retrieved, of which 1495 had an accompanying normal glucose concentration. Sixty pure breeds plus a mixed breed control group were represented by at least 10 individuals. All analytes, except for sodium, chloride and glucose, showed variation with age. Total protein, globulin, potassium, chloride, creatinine, cholesterol, total bilirubin, ALT, CK, amylase, and lipase varied between sexes. Neutering status significantly impacted all analytes except albumin, sodium, calcium, urea, and glucose. Principal component analysis of serum biochemical data revealed 36 pure breeds with distinctive phenotypes. Furthermore, comparative analysis identified 23 breeds with significant differences from the mixed breed group in all biochemical analytes except urea and glucose. Eighteen breeds were identified by both principal component and comparative analysis. Tentative reference intervals were generated for breeds with a distinctive phenotype identified by comparative analysis and represented by at least 120 individuals. This is the first large-scale analysis of breed-specific serum biochemical phenotypes in the domestic dog and highlights potential genetic components of biochemical traits in this species. PMID:26919479

Quantitative Analysis of Localized Sources Identified by Focal Impulse and Rotor Modulation Mapping in Atrial Fibrillation

PubMed Central

Benharash, Peyman; Buch, Eric; Frank, Paul; Share, Michael; Tung, Roderick; Shivkumar, Kalyanam; Mandapati, Ravi

2015-01-01

Background New approaches to ablation of atrial fibrillation (AF) include focal impulse and rotor modulation (FIRM) mapping, and initial results reported with this technique have been favorable. We sought to independently evaluate the approach by analyzing quantitative characteristics of atrial electrograms used to identify rotors and describe acute procedural outcomes of FIRM-guided ablation. Methods and Results All FIRM-guided ablation procedures (n=24; 50% paroxysmal) at University of California, Los Angeles Medical Center were included for analysis. During AF, unipolar atrial electrograms collected from a 64-pole basket catheter were used to construct phase maps and identify putative AF sources. These sites were targeted for ablation, in conjunction with pulmonary vein isolation in most patients (n=19; 79%). All patients had rotors identified (mean, 2.3±0.9 per patient; 72% in left atrium). Prespecified acute procedural end point was achieved in 12 of 24 (50%) patients: AF termination (n=1), organization (n=3), or >10% slowing of AF cycle length (n=8). Basket electrodes were within 1 cm of 54% of left atrial surface area, and a mean of 31 electrodes per patient showed interpretable atrial electrograms. Offline analysis revealed no differences between rotor and distant sites in dominant frequency or Shannon entropy. Electroanatomic mapping showed no rotational activation at FIRM-identified rotor sites in 23 of 24 patients (96%). Conclusions FIRM-identified rotor sites did not exhibit quantitative atrial electrogram characteristics expected from rotors and did not differ quantitatively from surrounding tissue. Catheter ablation at these sites, in conjunction with pulmonary vein isolation, resulted in AF termination or organization in a minority of patients (4/24; 17%). Further validation of this approach is necessary. PMID:25873718

Morphological identification and COI barcodes of adult flies help determine species identities of chironomid larvae (Diptera, Chironomidae).

PubMed

Failla, A J; Vasquez, A A; Hudson, P; Fujimoto, M; Ram, J L

2016-02-01

Establishing reliable methods for the identification of benthic chironomid communities is important due to their significant contribution to biomass, ecology and the aquatic food web. Immature larval specimens are more difficult to identify to species level by traditional morphological methods than their fully developed adult counterparts, and few keys are available to identify the larval species. In order to develop molecular criteria to identify species of chironomid larvae, larval and adult chironomids from Western Lake Erie were subjected to both molecular and morphological taxonomic analysis. Mitochondrial cytochrome c oxidase I (COI) barcode sequences of 33 adults that were identified to species level by morphological methods were grouped with COI sequences of 189 larvae in a neighbor-joining taxon-ID tree. Most of these larvae could be identified only to genus level by morphological taxonomy (only 22 of the 189 sequenced larvae could be identified to species level). The taxon-ID tree of larval sequences had 45 operational taxonomic units (OTUs, defined as clusters with >97% identity or individual sequences differing from nearest neighbors by >3%; supported by analysis of all larval pairwise differences), of which seven could be identified to species or 'species group' level by larval morphology. Reference sequences from the GenBank and BOLD databases assigned six larval OTUs with presumptive species level identifications and confirmed one previously assigned species level identification. Sequences from morphologically identified adults in the present study grouped with and further classified the identity of 13 larval OTUs. The use of morphological identification and subsequent DNA barcoding of adult chironomids proved to be beneficial in revealing possible species level identifications of larval specimens. Sequence data from this study also contribute to currently inadequate public databases relevant to the Great Lakes region, while the neighbor-joining analysis reported here describes the application and confirmation of a useful tool that can accelerate identification and bioassessment of chironomid communities.

Morphological identification and COI barcodes of adult flies help determine species identities of chironomid larvae (Diptera, Chironomidae)

USGS Publications Warehouse

Failla, Andrew Joseph; Vasquez, Adrian Amelio; Hudson, Patrick L.; Fujimoto, Masanori; Ram, Jeffrey L.

2016-01-01

Establishing reliable methods for the identification of benthic chironomid communities is important due to their significant contribution to biomass, ecology and the aquatic food web. Immature larval specimens are more difficult to identify to species level by traditional morphological methods than their fully developed adult counterparts, and few keys are available to identify the larval species. In order to develop molecular criteria to identify species of chironomid larvae, larval and adult chironomids from Western Lake Erie were subjected to both molecular and morphological taxonomic analysis. Mitochondrial cytochrome c oxidase I (COI) barcode sequences of 33 adults that were identified to species level by morphological methods were grouped with COI sequences of 189 larvae in a neighbor-joining taxon-ID tree. Most of these larvae could be identified only to genus level by morphological taxonomy (only 22 of the 189 sequenced larvae could be identified to species level). The taxon-ID tree of larval sequences had 45 operational taxonomic units (OTUs, defined as clusters with >97% identity or individual sequences differing from nearest neighbors by >3%; supported by analysis of all larval pairwise differences), of which seven could be identified to species or ‘species group’ level by larval morphology. Reference sequences from the GenBank and BOLD databases assigned six larval OTUs with presumptive species level identifications and confirmed one previously assigned species level identification. Sequences from morphologically identified adults in the present study grouped with and further classified the identity of 13 larval OTUs. The use of morphological identification and subsequent DNA barcoding of adult chironomids proved to be beneficial in revealing possible species level identifications of larval specimens. Sequence data from this study also contribute to currently inadequate public databases relevant to the Great Lakes region, while the neighbor-joining analysis reported here describes the application and confirmation of a useful tool that can accelerate identification and bioassesment of chironomid communities.

Predictors of self-rated health in patients with chronic nonmalignant pain.

PubMed

Siedlecki, Sandra L

2006-09-01

Self-rated health (SRH) is an important outcome measure that has been found to accurately predict mortality, morbidity, function, and psychologic well-being. Chronic nonmalignant pain presents with a pattern that includes low levels of power and high levels of pain, depression, and disability. Differences in SRH may be related to variations within this pattern. The purpose of this analysis was to identify determinants of SRH and test their ability to predict SRH in patients with chronic nonmalignant pain. SRH was measured by response to a single three-option age-comparative question. The Power as Knowing Participation in Change Tool, McGill Pain Questionnaire Short Form, Center for Epidemiological Studies Depression Scale, and Pain Disability Index were used to measure independent variables. Multivariate analysis of variance revealed significant differences (p = .001) between SRH categories on the combined dependent variable. Analysis of variance conducted as a follow-up identified significant differences for power (p < .001) and depression (p = .003), but not for pain or pain-related disability; and discriminant analysis found that power and depression correctly classified patients with 75% accuracy. Findings suggest pain interventions designed to improve mood and provide opportunities for knowing participation may have a greater impact on overall health than those that target only pain and disability.

Validation of reference genes for quantitative real-time PCR during leaf and flower development in Petunia hybrida

PubMed Central

2010-01-01

Background Identification of genes with invariant levels of gene expression is a prerequisite for validating transcriptomic changes accompanying development. Ideally expression of these genes should be independent of the morphogenetic process or environmental condition tested as well as the methods used for RNA purification and analysis. Results In an effort to identify endogenous genes meeting these criteria nine reference genes (RG) were tested in two Petunia lines (Mitchell and V30). Growth conditions differed in Mitchell and V30, and different methods were used for RNA isolation and analysis. Four different software tools were employed to analyze the data. We merged the four outputs by means of a non-weighted unsupervised rank aggregation method. The genes identified as optimal for transcriptomic analysis of Mitchell and V30 were EF1α in Mitchell and CYP in V30, whereas the least suitable gene was GAPDH in both lines. Conclusions The least adequate gene turned out to be GAPDH indicating that it should be rejected as reference gene in Petunia. The absence of correspondence of the best-suited genes suggests that assessing reference gene stability is needed when performing normalization of data from transcriptomic analysis of flower and leaf development. PMID:20056000

The Detection of Patients at Risk of Gastrointestinal Toxicity during Pelvic Radiotherapy by Electronic Nose and FAIMS: A Pilot Study

PubMed Central

Covington, James A.; Wedlake, Linda; Andreyev, Jervoise; Ouaret, Nathalie; Thomas, Matthew G.; Nwokolo, Chuka U.; Bardhan, Karna D.; Arasaradnam, Ramesh P.

2012-01-01

It is well known that the electronic nose can be used to identify differences between human health and disease for a range of disorders. We present a pilot study to investigate if the electronic nose and a newer technology, FAIMS (Field Asymmetric Ion Mobility Spectrometry), can be used to identify and help inform the treatment pathway for patients receiving pelvic radiotherapy, which frequently causes gastrointestinal side-effects, severe in some. From a larger group, 23 radiotherapy patients were selected where half had the highest levels of toxicity and the others the lowest. Stool samples were obtained before and four weeks after radiotherapy and the volatiles and gases emitted analysed by both methods; these chemicals are products of fermentation caused by gut microflora. Principal component analysis of the electronic nose data and wavelet transform followed by Fisher discriminant analysis of FAIMS data indicated that it was possible to separate patients after treatment by their toxicity levels. More interestingly, differences were also identified in their pre-treatment samples. We believe these patterns arise from differences in gut microflora where some combinations of bacteria result to give this olfactory signature. In the future our approach may result in a technique that will help identify patients at “high risk” even before radiation treatment is started. PMID:23201982

Proteomic analysis of rutin-induced secreted proteins from Aspergillus flavus.

PubMed

Medina, Martha L; Kiernan, Urban A; Francisco, Wilson A

2004-03-01

Few studies have been conducted to identify the extracellular proteins and enzymes secreted by filamentous fungi, particularly with respect to dispensable metabolic pathways. Proteomic analysis has proven to be the most powerful method for identification of proteins in complex mixtures and is suitable for the study of the alteration of protein expression under different environmental conditions. The filamentous fungus Aspergillus flavus can degrade the flavonoid rutin as the only source of carbon via an extracellular enzyme system. In this study, a proteomic analysis was used to differentiate and identify the extracellular rutin-induced and non-induced proteins secreted by A. flavus. The secreted proteins were analyzed by two-dimensional electrophoresis and MALDI-TOF mass spectrometry. While 15 rutin-induced proteins and 7 non-induced proteins were identified, more than 90 protein spots remain unidentified, indicating that these proteins are either novel proteins or proteins that have not yet been sequenced.

Genome-wide meta-analysis identifies novel gender specific loci associated with thyroid antibodies level in Croatians.

PubMed

Matana, Antonela; Popović, Marijana; Boutin, Thibaud; Torlak, Vesela; Brdar, Dubravka; Gunjača, Ivana; Kolčić, Ivana; Boraska Perica, Vesna; Punda, Ante; Polašek, Ozren; Hayward, Caroline; Barbalić, Maja; Zemunik, Tatijana

2018-04-18

Autoimmune thyroid diseases (AITD) are multifactorial endocrine diseases most frequently accompanied by Tg and TPO autoantibodies. Both antibodies have a higher prevalence in females and act under a strong genetic influence. To identify novel variants underlying thyroid antibody levels, we performed GWAS meta-analysis on the plasma levels of TgAb and TPOAb in three Croatian cohorts, as well as gender specific GWAS and a bivariate analysis. No significant association was detected with the level of TgAb and TPOAb in the meta-analysis of GWAS or bivariate results for all individuals. The bivariate analysis in females only revealed a genome-wide significant association for the locus near GRIN3A (rs4457391, P = 7.76 × 10 -9 ). The same locus had borderline association with TPOAb levels in females (rs1935377, P = 8.58 × 10 -8 ). In conclusion, we identified a novel gender specific locus associated with TgAb and TPOAb levels. Our findings provide a novel insight into genetic and gender differences associated with thyroid antibodies. Copyright © 2018 Elsevier Inc. All rights reserved.

Examining inter-family differences in intra-family (parent-adolescent) dynamics using grid-sequence analysis.

PubMed

Brinberg, Miriam; Fosco, Gregory M; Ram, Nilam

2017-12-01

Family systems theorists have forwarded a set of theoretical principles meant to guide family scientists and practitioners in their conceptualization of patterns of family interaction-intra-family dynamics-that, over time, give rise to family and individual dysfunction and/or adaptation. In this article, we present an analytic approach that merges state space grid methods adapted from the dynamic systems literature with sequence analysis methods adapted from molecular biology into a "grid-sequence" method for studying inter-family differences in intra-family dynamics. Using dyadic data from 86 parent-adolescent dyads who provided up to 21 daily reports about connectedness, we illustrate how grid-sequence analysis can be used to identify a typology of intrafamily dynamics and to inform theory about how specific types of intrafamily dynamics contribute to adolescent behavior problems and family members' mental health. Methodologically, grid-sequence analysis extends the toolbox of techniques for analysis of family experience sampling and daily diary data. Substantively, we identify patterns of family level microdynamics that may serve as new markers of risk/protective factors and potential points for intervention in families. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Quantitative descriptive analysis and principal component analysis for sensory characterization of Indian milk product cham-cham.

PubMed

Puri, Ritika; Khamrui, Kaushik; Khetra, Yogesh; Malhotra, Ravinder; Devraja, H C

2016-02-01

Promising development and expansion in the market of cham-cham, a traditional Indian dairy product is expected in the coming future with the organized production of this milk product by some large dairies. The objective of this study was to document the extent of variation in sensory properties of market samples of cham-cham collected from four different locations known for their excellence in cham-cham production and to find out the attributes that govern much of variation in sensory scores of this product using quantitative descriptive analysis (QDA) and principal component analysis (PCA). QDA revealed significant (p < 0.05) difference in sensory attributes of cham-cham among the market samples. PCA identified four significant principal components that accounted for 72.4 % of the variation in the sensory data. Factor scores of each of the four principal components which primarily correspond to sweetness/shape/dryness of interior, surface appearance/surface dryness, rancid and firmness attributes specify the location of each market sample along each of the axes in 3-D graphs. These findings demonstrate the utility of quantitative descriptive analysis for identifying and measuring attributes of cham-cham that contribute most to its sensory acceptability.

Preliminary analysis of the potential of LANDSAT imagery to study desertification. [Xique-Xique, Brazil

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Lombardo, M. A.; Decarvalho, V. C.

1980-01-01

The use of LANDSAT imagery to define and delimit areas under process of desertification was investigated. Imagery for two different years (1973 and 1978) and two different seasons (dry and rainy seasons in 1976), were used to identify terrain morphology and vegetation cover. The analysis of LANDSAT interpretation, combined with geological and soil information obtained from published literature, allowed the identification of eleven ecological units which were classified corresponding to the degree of the Xique Xique region of Rio Sao Francisco.

Clinical phenotypes and survival of pre-capillary pulmonary hypertension in systemic sclerosis.

PubMed

Launay, David; Montani, David; Hassoun, Paul M; Cottin, Vincent; Le Pavec, Jérôme; Clerson, Pierre; Sitbon, Olivier; Jaïs, Xavier; Savale, Laurent; Weatherald, Jason; Sobanski, Vincent; Mathai, Stephen C; Shafiq, Majid; Cordier, Jean-François; Hachulla, Eric; Simonneau, Gérald; Humbert, Marc

2018-01-01

Pre-capillary pulmonary hypertension (PH) in systemic sclerosis (SSc) is a heterogeneous condition with an overall bad prognosis. The objective of this study was to identify and characterize homogeneous phenotypes by a cluster analysis in SSc patients with PH. Patients were identified from two prospective cohorts from the US and France. Clinical, pulmonary function, high-resolution chest tomography, hemodynamic and survival data were extracted. We performed cluster analysis using the k-means method and compared survival between clusters using Cox regression analysis. Cluster analysis of 200 patients identified four homogenous phenotypes. Cluster C1 included patients with mild to moderate risk pulmonary arterial hypertension (PAH) with limited or no interstitial lung disease (ILD) and low DLCO with a 3-year survival of 81.5% (95% CI: 71.4-88.2). C2 had pre-capillary PH due to extensive ILD and worse 3-year survival compared to C1 (adjusted hazard ratio [HR] 3.14; 95% CI 1.66-5.94; p = 0.0004). C3 had severe PAH and a trend towards worse survival (HR 2.53; 95% CI 0.99-6.49; p = 0.052). Cluster C4 and C1 were similar with no difference in survival (HR 0.65; 95% CI 0.19-2.27, p = 0.507) but with a higher DLCO in C4. PH in SSc can be characterized into distinct clusters that differ in prognosis.

Cost-effectiveness of training rural providers to identify and treat patients at risk for fragility fractures.

PubMed

Nelson, S D; Nelson, R E; Cannon, G W; Lawrence, P; Battistone, M J; Grotzke, M; Rosenblum, Y; LaFleur, J

2014-12-01

This is a cost-effectiveness analysis of training rural providers to identify and treat osteoporosis. Results showed a slight cost savings, increase in life years, increase in treatment rates, and decrease in fracture incidence. However, the results were sensitive to small differences in effectiveness, being cost-effective in 70 % of simulations during probabilistic sensitivity analysis. We evaluated the cost-effectiveness of training rural providers to identify and treat veterans at risk for fragility fractures relative to referring these patients to an urban medical center for specialist care. The model evaluated the impact of training on patient life years, quality-adjusted life years (QALYs), treatment rates, fracture incidence, and costs from the perspective of the Department of Veterans Affairs. We constructed a Markov microsimulation model to compare costs and outcomes of a hypothetical cohort of veterans seen by rural providers. Parameter estimates were derived from previously published studies, and we conducted one-way and probabilistic sensitivity analyses on the parameter inputs. Base-case analysis showed that training resulted in no additional costs and an extra 0.083 life years (0.054 QALYs). Our model projected that as a result of training, more patients with osteoporosis would receive treatment (81.3 vs. 12.2 %), and all patients would have a lower incidence of fractures per 1,000 patient years (hip, 1.628 vs. 1.913; clinical vertebral, 0.566 vs. 1.037) when seen by a trained provider compared to an untrained provider. Results remained consistent in one-way sensitivity analysis and in probabilistic sensitivity analyses, training rural providers was cost-effective (less than $50,000/QALY) in 70 % of the simulations. Training rural providers to identify and treat veterans at risk for fragility fractures has a potential to be cost-effective, but the results are sensitive to small differences in effectiveness. It appears that provider education alone is not enough to make a significant difference in fragility fracture rates among veterans.

Understanding Health Care Social Media Use From Different Stakeholder Perspectives: A Content Analysis of an Online Health Community

PubMed Central

Wu, Yang; Liu, Jingfang; Li, Jia; Zhang, Pengzhu

2017-01-01

Background Health care social media used for health information exchange and emotional communication involves different types of users, including patients, caregivers, and health professionals. However, it is difficult to identify different stakeholders because user identification data are lacking due to privacy protection and proprietary interests. Therefore, identifying the concerns of different stakeholders and how they use health care social media when confronted with huge amounts of health-related messages posted by users is a critical problem. Objective We aimed to develop a new content analysis method using text mining techniques applied in health care social media to (1) identify different health care stakeholders, (2) determine hot topics of concern, and (3) measure sentiment expression by different stakeholders. Methods We collected 138,161 messages posted by 39,606 members in lung cancer, diabetes, and breast cancer forums in the online community MedHelp.org over 10 years (January 2007 to October 2016) as experimental data. We used text mining techniques to process text data to identify different stakeholders and determine health-related hot topics, and then analyzed sentiment expression. Results We identified 3 significantly different stakeholder groups using expectation maximization clustering (3 performance metrics: Rand=0.802, Jaccard=0.393, Fowlkes-Mallows=0.537; P<.001), in which patients (24,429/39,606, 61.68%) and caregivers (12,232/39,606, 30.88%) represented the majority of the population, in contrast to specialists (2945/39,606, 7.43%). We identified 5 significantly different health-related topics: symptom, examination, drug, procedure, and complication (Rand=0.783, Jaccard=0.369, Fowlkes-Mallows=0.495; P<.001). Patients were concerned most about symptom topics related to lung cancer (536/1657, 32.34%), drug topics related to diabetes (1883/5904, 31.89%), and examination topics related to breast cancer (8728/23,934, 36.47%). By comparison, caregivers were more concerned about drug topics related to lung cancer (300/2721, 11.03% vs 109/1657, 6.58%), procedure topics related to breast cancer (3952/13,954, 28.32% vs 5822/23,934, 24.33%), and complication topics (4449/25,701, 17.31% vs 4070/31,495, 12.92%). In addition, patients (9040/36,081, 25.05%) were more likely than caregivers (2659/18,470, 14.39%) and specialists (17,943/83,610, 21.46%) to express their emotions. However, patients’ sentiment intensity score (2.46) was lower than those of caregivers (4.66) and specialists (5.14). In particular, for caregivers, negative sentiment scores were higher than positive scores (2.56 vs 2.18), with the opposite among specialists (2.62 vs 2.46). Overall, the proportion of negative messages was greater than that of positive messages related to symptom, complication, and examination. The pattern was opposite for drug and procedure topics. A trend analysis showed that patients and caregivers gradually changed their emotional state in a positive direction. Conclusions The hot topics of interest and sentiment expression differed significantly among different stakeholders in different disease forums. These findings could help improve social media services to facilitate diverse stakeholder engagement for health information sharing and social interaction more effectively. PMID:28389418

Global Trends in Language Learning in the 21st Century

ERIC Educational Resources Information Center

Eaton, Sarah Elaine

2010-01-01

Today's language classroom is vastly different from that of the mid- to late 20th century. The study is a meta-analysis of recent research which provided the means to identify current and emerging trends in the field. Informed by this research, some identified trends that are shaping the 21st century language classroom are outdated practices such…

A Comparative Needs Analysis of Supportive Services for Non-Handicapped and Handicapped Persons Seeking Post-Secondary Education from the Community College System.

ERIC Educational Resources Information Center

Graham, Gary L.; And Others

This study was concerned with identifying the specific information needs and personal needs of handicapped students and comparing the selected needs with needs of general students. The study hypothesis was that there is no significant difference between identified needs of handicapped students and those of general students. The significance…

"The Purpose of This Study Is to": Connecting Lexical Bundles and Moves in Research Article Introductions

ERIC Educational Resources Information Center

Cortes, Viviana

2013-01-01

This article presents a group of lexical bundles identified in a corpus of research article introductions as the first step in the analysis of these expressions in the different sections of the research article. A one-million word corpus of research article introductions from various disciplines was compiled and the lexical bundles identified in…

Segmenting the Stream of Consciousness: The Psychological Correlates of Temporal Structures in the Time Series Data of a Continuous Performance Task

ERIC Educational Resources Information Center

Smallwood, Jonathan; McSpadden, Merrill; Luus, Bryan; Schooler, Joanthan

2008-01-01

Using principal component analysis, we examined whether structural properties in the time series of response time would identify different mental states during a continuous performance task. We examined whether it was possible to identify regular patterns which were present in blocks classified as lacking controlled processing, either…

Combined Analysis of the Fruit Metabolome and Transcriptome Reveals Candidate Genes Involved in Flavonoid Biosynthesis in Actinidia arguta.

PubMed

Li, Yukuo; Fang, Jinbao; Qi, Xiujuan; Lin, Miaomiao; Zhong, Yunpeng; Sun, Leiming; Cui, Wen

2018-05-15

To assess the interrelation between the change of metabolites and the change of fruit color, we performed a combined metabolome and transcriptome analysis of the flesh in two different Actinidia arguta cultivars: "HB" ("Hongbaoshixing") and "YF" ("Yongfengyihao") at two different fruit developmental stages: 70d (days after full bloom) and 100d (days after full bloom). Metabolite and transcript profiling was obtained by ultra-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometer and high-throughput RNA sequencing, respectively. The identification and quantification results of metabolites showed that a total of 28,837 metabolites had been obtained, of which 13,715 were annotated. In comparison of HB100 vs. HB70, 41 metabolites were identified as being flavonoids, 7 of which, with significant difference, were identified as bracteatin, luteolin, dihydromyricetin, cyanidin, pelargonidin, delphinidin and (-)-epigallocatechin. Association analysis between metabolome and transcriptome revealed that there were two metabolic pathways presenting significant differences during fruit development, one of which was flavonoid biosynthesis, in which 14 structural genes were selected to conduct expression analysis, as well as 5 transcription factor genes obtained by transcriptome analysis. RT-qPCR results and cluster analysis revealed that AaF3H , AaLDOX , AaUFGT , AaMYB , AabHLH , and AaHB2 showed the best possibility of being candidate genes. A regulatory network of flavonoid biosynthesis was established to illustrate differentially expressed candidate genes involved in accumulation of metabolites with significant differences, inducing red coloring during fruit development. Such a regulatory network linking genes and flavonoids revealed a system involved in the pigmentation of all-red-fleshed and all-green-fleshed A. arguta , suggesting this conjunct analysis approach is not only useful in understanding the relationship between genotype and phenotype, but is also a powerful tool for providing more valuable information for breeding.

Open Reading Frame Phylogenetic Analysis on the Cloud

PubMed Central

2013-01-01

Phylogenetic analysis has become essential in researching the evolutionary relationships between viruses. These relationships are depicted on phylogenetic trees, in which viruses are grouped based on sequence similarity. Viral evolutionary relationships are identified from open reading frames rather than from complete sequences. Recently, cloud computing has become popular for developing internet-based bioinformatics tools. Biocloud is an efficient, scalable, and robust bioinformatics computing service. In this paper, we propose a cloud-based open reading frame phylogenetic analysis service. The proposed service integrates the Hadoop framework, virtualization technology, and phylogenetic analysis methods to provide a high-availability, large-scale bioservice. In a case study, we analyze the phylogenetic relationships among Norovirus. Evolutionary relationships are elucidated by aligning different open reading frame sequences. The proposed platform correctly identifies the evolutionary relationships between members of Norovirus. PMID:23671843

Synthesis, structural, thermal and Hirshfeld surface analysis of novel [1,2,4]triazolo[3,4-b][1,3,4] thiadiazine carrying 1,4-benzothiazine-3-one moiety

NASA Astrophysics Data System (ADS)

Shruthi, C.; Ravindrachary, V.; Guruswamy, B.; Lokanath, N. K.; Kumara, Karthik; Goveas, Janet

2018-05-01

Needle shaped single crystal of the title compound was grown by slow evaporation solution growth technique using ethanol as solvent. The grown single crystal was characterized using FT-IR, Single crystal XRD and Thermal analysis. The FT-IR spectrum confirms the molecular structure and identifies the different functional groups present in the compound. Single crystal XRD study reveals that the crystallized compound belongs to the monoclinic crystal system with P21/c space group and the corresponding cell parameters were identified. The thermal stability of the material was determined using both TGA and DTA analysis. The intermolecular interaction of each individual atom in the crystal lattice was estimated using Hirshfeld surface and finger print analysis.

Diversity analysis of lactic acid bacteria in takju, Korean rice wine.

PubMed

Jin, Jianbo; Kim, So-Young; Jin, Qing; Eom, Hyun-Ju; Han, Nam Soo

2008-10-01

To investigate the lactic acid bacterial population in Korean traditional rice wines, biotyping was performed using cell morphology and whole-cell protein pattern analysis by SDSPAGE, and then the isolates were identified by 16S rRNA sequencing analysis. Based on the morphological characteristics, 103 LAB isolates were detected in wine samples, characterized by whole-cell protein pattern analysis, and they were then divided into 18 patterns. By gene sequencing of 16S rRNA, the isolates were identified as Lactobacillus paracasei, Lb. arizonensis, Lb. plantarum, Lb. harbinensis, Lb. parabuchneri, Lb. brevis, and Lb. hilgardii when listed by their frequency of occurrence. It was found that the difference in bacterial diversity between rice and grape wines depends on the raw materials, especially the composition of starch and glucose.

Large Modal Survey Testing Using the Ibrahim Time Domain Identification Technique

NASA Technical Reports Server (NTRS)

Ibrahim, S. R.; Pappa, R. S.

1985-01-01

The ability of the ITD identification algorithm in identifying a complete set of structural modal parameters using a large number of free-response time histories simultaneously in one analysis, assuming a math model with a high number of degrees-of-freedom, has been studied. Identification results using simulated free responses of a uniform rectangular plate, with 225 measurement stations, and experimental responses from a ground vibration test of the Long Duration Exposure Facility (LDEF) Space Shuttle payload, with 142 measurement stations, are presented. As many as 300 degrees-of-freedom were allowed in analyzing these data. In general, the use of a significantly oversized math model in the identification process was found to maintain or increase identification accuracy and to identify modes of low response level that are not identified with smaller math model sizes. The concept of a Mode Shape Correlation Constant is introduced for use when more than one identification analysis of the same structure are conducted. This constant quantifies the degree of correlation between any two sets of complex mode shapes identified using different excitation conditions, different user-selectable algorithm constants, or overlapping sets of measurements.

Large modal survey testing using the Ibrahim time domain /ITD/ identification technique

NASA Technical Reports Server (NTRS)

Ibrahim, S. R.; Pappa, R. S.

1981-01-01

The ability of the ITD identification algorithm in identifying a complete set of structural modal parameters using a large number of free-response time histories simultaneously in one analysis, assuming a math model with a high number of degrees-of-freedom, has been studied. Identification results using simulated free responses of a uniform rectangular plate, with 225 measurement stations, and experimental responses from a ground vibration test of the Long Duration Exposure Facility (LDEF) Space Shuttle payload, with 142 measurement stations, are presented. As many as 300 degrees-of-freedom were allowed in analyzing these data. In general, the use of a significantly oversized math model in the identification process was found to maintain or increase identification accuracy and to identify modes of low response level that are not identified with smaller math model sizes. The concept of a Mode Shape Correlation Constant is introduced for use when more than one identification analysis of the same structure are conducted. This constant quantifies the degree of correlation between any two sets of complex mode shapes identified using different excitation conditions, different user-selectable algorithm constants, or overlapping sets of measurements.

A Comparative Analysis of Industrial Escherichia coli K–12 and B Strains in High-Glucose Batch Cultivations on Process-, Transcriptome- and Proteome Level

PubMed Central

Marisch, Karoline; Bayer, Karl; Scharl, Theresa; Mairhofer, Juergen; Krempl, Peter M.; Hummel, Karin; Razzazi-Fazeli, Ebrahim; Striedner, Gerald

2013-01-01

Escherichia coli K–12 and B strains are among the most frequently used bacterial hosts for production of recombinant proteins on an industrial scale. To improve existing processes and to accelerate bioprocess development, we performed a detailed host analysis. We investigated the different behaviors of the E. coli production strains BL21, RV308, and HMS174 in response to high-glucose concentrations. Tightly controlled cultivations were conducted under defined environmental conditions for the in-depth analysis of physiological behavior. In addition to acquisition of standard process parameters, we also used DNA microarray analysis and differential gel electrophoresis (EttanTM DIGE). Batch cultivations showed different yields of the distinct strains for cell dry mass and growth rate, which were highest for BL21. In addition, production of acetate, triggered by excess glucose supply, was much higher for the K–12 strains compared to the B strain. Analysis of transcriptome data showed significant alteration in 347 of 3882 genes common among all three hosts. These differentially expressed genes included, for example, those involved in transport, iron acquisition, and motility. The investigation of proteome patterns additionally revealed a high number of differentially expressed proteins among the investigated hosts. The subsequently selected 38 spots included proteins involved in transport and motility. The results of this comprehensive analysis delivered a full genomic picture of the three investigated strains. Differentially expressed groups for targeted host modification were identified like glucose transport or iron acquisition, enabling potential optimization of strains to improve yield and process quality. Dissimilar growth profiles of the strains confirm different genotypes. Furthermore, distinct transcriptome patterns support differential regulation at the genome level. The identified proteins showed high agreement with the transcriptome data and suggest similar regulation within a host at both levels for the identified groups. Such host attributes need to be considered in future process design and operation. PMID:23950949

A comparative analysis of industrial Escherichia coli K-12 and B strains in high-glucose batch cultivations on process-, transcriptome- and proteome level.

PubMed

Marisch, Karoline; Bayer, Karl; Scharl, Theresa; Mairhofer, Juergen; Krempl, Peter M; Hummel, Karin; Razzazi-Fazeli, Ebrahim; Striedner, Gerald

2013-01-01

Escherichia coli K-12 and B strains are among the most frequently used bacterial hosts for production of recombinant proteins on an industrial scale. To improve existing processes and to accelerate bioprocess development, we performed a detailed host analysis. We investigated the different behaviors of the E. coli production strains BL21, RV308, and HMS174 in response to high-glucose concentrations. Tightly controlled cultivations were conducted under defined environmental conditions for the in-depth analysis of physiological behavior. In addition to acquisition of standard process parameters, we also used DNA microarray analysis and differential gel electrophoresis (Ettan(TM) DIGE). Batch cultivations showed different yields of the distinct strains for cell dry mass and growth rate, which were highest for BL21. In addition, production of acetate, triggered by excess glucose supply, was much higher for the K-12 strains compared to the B strain. Analysis of transcriptome data showed significant alteration in 347 of 3882 genes common among all three hosts. These differentially expressed genes included, for example, those involved in transport, iron acquisition, and motility. The investigation of proteome patterns additionally revealed a high number of differentially expressed proteins among the investigated hosts. The subsequently selected 38 spots included proteins involved in transport and motility. The results of this comprehensive analysis delivered a full genomic picture of the three investigated strains. Differentially expressed groups for targeted host modification were identified like glucose transport or iron acquisition, enabling potential optimization of strains to improve yield and process quality. Dissimilar growth profiles of the strains confirm different genotypes. Furthermore, distinct transcriptome patterns support differential regulation at the genome level. The identified proteins showed high agreement with the transcriptome data and suggest similar regulation within a host at both levels for the identified groups. Such host attributes need to be considered in future process design and operation.

[Analysis of different forms Linderae Radix based on HPLC and NIRS fingerprints].

PubMed

Du, Wei-Feng; Yue, Xian-Ke; Wu, Yao; Ge, Wei-Hong; Lu, Tu-Lin; Wang, Zhi-Min

2016-10-01

Three different forms of Linderae Radix were evaluated by HPLC combined with NIRS fingerprint. The Linderae Radix was divided into three forms, including spindle root, straight root and old root. The HPLC fingerprints were developed, and then cluster analysis was performed using the SPSS software. The near-infrared spectra of Linderae Radix was collected, and then established the discriminant analysis model. The similarity values of the spindle root and straight root all were above 0.990, while the similarity value of the old root was less than 0.850. Two forms of Linderae Radix were obviously divided into three parts by the NIRS model and Cluster analysis. The results of HPLC and FT-NIR analysis showed the quality of Linderae Radix old root was different from the spindle root and straight root. The combined use of the two methods could identify different forms of Linderae Radix quickly and accurately. Copyright© by the Chinese Pharmaceutical Association.

Microstructure and tuber properties of potato varieties with different genetic profiles.

PubMed

Romano, Annalisa; Masi, Paolo; Aversano, Riccardo; Carucci, Francesca; Palomba, Sara; Carputo, Domenico

2018-01-15

The objectives of this research were to study tuber starch characteristics and chemical - thermal properties of 21 potato varieties, and to determine their genetic diversity through SSR markers. Starch granular size varied among samples, with a wide diameter distribution (5-85μm), while granule shapes were similar. Differential Scanning Calorimeter analysis showed that the transition temperatures (69°C-74°C) and enthalpies of gelatinization (0.9J/g-3.8J/g) of tubers were also variety dependent. SSR analysis allowed the detection of 157 alleles across all varieties, with an average value of 6.8 alleles per locus. Variety-specific alleles were also identified. SSR-based cluster analysis revealed that varieties with interesting quality attributes were distributed among all clusters and sub-clusters, suggesting that the genetic basis of traits analyzed may differ among our varieties. The information obtained in this study may be useful to identify and develop varieties with slowly digestible starch. Copyright © 2017 Elsevier Ltd. All rights reserved.

Metabolomics-based optimal koji fermentation for tyrosinase inhibition supplemented with Astragalus radix.

PubMed

Kim, Ah Jin; Choi, Jung Nam; Kim, Jiyoung; Yeo, Soo Hwan; Choi, Ji Ho; Lee, Choong Hwan

2012-01-01

The present study was focused on improving the quality of rice koji by fermentation with a selected Aspergillus oryzae strain and a plant Astragalus radix. A. oryzae KCCM 60345 was used as main inoculant and the Astragalus radix was added as supplement in rice koji preparation. LC-MS based metabolite analysis and tyrosinase inhibitory activities were studied for different time periods. A. oryzae KCCM 60345 fermented rice koji supplemented with Astragalus showed higher tyrosinase inhibition activity at 4 d of fermentation and metabolite analysis with PCA and PLS-DA indicated differences in kojic acid, calycosin-7-O-β-D-glucoside, ononin, calycosin, and formononetin as compared with other forms of rice koji fermentation. By correlation analysis between metabolites and tyrosinase inhibitory activity, calycosin and kojic acid were identified as major tyrosinase inhibitors. Based on these results, we concluded that A. oryzae KCCM 60345 supplemented with Astragalus radix is useful for whitening effects, and we identified optimal conditions for rice koji preparation.

Comparing sugar components of cereal and pseudocereal flour by GC-MS analysis.

PubMed

Ačanski, Marijana M; Vujić, Djura N

2014-02-15

Gas chromatography with mass spectrometry was used for carrying out a qualitative analysis of the ethanol soluble flour extract of different types of cereals bread wheat and spelt and pseudocereals (amaranth and buckwheat). TMSI (trimethylsilylimidazole) was used as a reagent for the derivatisation of carbohydrates into trimethylsilyl ethers. All samples were first defatted with hexane. (In our earlier investigations, hexane extracts were used for the analysis of fatty acid of lipid components.) Many components of pentoses, hexoses and disaccharides were identified using 73 and 217 Da mass and the Wiley Online Library search. The aim of this paper is not to identify and find new components, but to compare sugar components of tested samples of flour of cereals bread wheat and spelt and pseudocereals (amarnath and buckwheat). Results were analysed using descriptive statistics (dendrograms and PCA). The results show that this method can be used for making a distinction among different types of flour. Copyright © 2013 Elsevier Ltd. All rights reserved.

Dissecting the Genetic Basis for Seed Coat Mucilage Heteroxylan Biosynthesis in Plantago ovata Using Gamma Irradiation and Infrared Spectroscopy

PubMed Central

Tucker, Matthew R.; Ma, Chao; Phan, Jana; Neumann, Kylie; Shirley, Neil J.; Hahn, Michael G.; Cozzolino, Daniel; Burton, Rachel A.

2017-01-01

Seeds from the myxospermous species Plantago ovata release a polysaccharide-rich mucilage upon contact with water. This seed coat derived mucilage is composed predominantly of heteroxylan (HX) and is utilized as a gluten-free dietary fiber supplement to promote human colorectal health. In this study, a gamma-irradiated P. ovata population was generated and screened using histological stains and Fourier Transform Mid Infrared (FTMIR) spectroscopy to identify putative mutants showing defects in seed coat mucilage HX composition and/or structure. FTMIR analysis of dry seed revealed variation in regions of the IR spectra previously linked to xylan structure in Secale cereale (rye). Subsequent absorbance ratio and PCA multivariate analysis identified 22 putative mutant families with differences in the HX IR fingerprint region. Many of these showed distinct changes in the amount and subtle changes in structure of HX after mucilage extrusion, while 20% of the putative HX mutants identified by FTMIR showed no difference in staining patterns of extruded mucilage compared to wild-type. Transcriptional screening analysis of two putative reduced xylan in mucilage (rxm) mutants, rxm1 and rxm3, revealed that changes in HX levels in rxm1 correlate with reduced transcription of known and novel genes associated with xylan synthesis, possibly indicative of specific co-regulatory units within the xylan biosynthetic pathway. These results confirm that FTMIR is a suitable method for identifying putative mutants with altered mucilage HX composition in P. ovata, and therefore forms a resource to identify novel genes involved in xylan biosynthesis. PMID:28377777

Spatial interpolation methods and geostatistics for mapping groundwater contamination in a coastal area.

PubMed

Elumalai, Vetrimurugan; Brindha, K; Sithole, Bongani; Lakshmanan, Elango

2017-04-01

Mapping groundwater contaminants and identifying the sources are the initial steps in pollution control and mitigation. Due to the availability of different mapping methods and the large number of emerging pollutants, these methods need to be used together in decision making. The present study aims to map the contaminated areas in Richards Bay, South Africa and compare the results of ordinary kriging (OK) and inverse distance weighted (IDW) interpolation techniques. Statistical methods were also used for identifying contamination sources. Na-Cl groundwater type was dominant followed by Ca-Mg-Cl. Data analysis indicate that silicate weathering, ion exchange and fresh water-seawater mixing are the major geochemical processes controlling the presence of major ions in groundwater. Factor analysis also helped to confirm the results. Overlay analysis by OK and IDW gave different results. Areas where groundwater was unsuitable as a drinking source were 419 and 116 km 2 for OK and IDW, respectively. Such diverse results make decision making difficult, if only one method was to be used. Three highly contaminated zones within the study area were more accurately identified by OK. If large areas are identified as being contaminated such as by IDW in this study, the mitigation measures will be expensive. If these areas were underestimated, then even though management measures are taken, it will not be effective for a longer time. Use of multiple techniques like this study will help to avoid taking harsh decisions. Overall, the groundwater quality in this area was poor, and it is essential to identify alternate drinking water source or treat the groundwater before ingestion.

A latent class analysis of friendship network types and their predictors in the second half of life.

PubMed

Miche, Martina; Huxhold, Oliver; Stevens, Nan L

2013-07-01

Friendships contribute uniquely to well-being in (late) adulthood. However, studies on friendship often ignore interindividual differences in friendship patterns. The aim of this study was to investigate such differences including their predictors. The study builds on Matthews's qualitative model of friendship styles. Matthews distinguished 3 approaches to friendship differing by number of friends, duration of friendships, and emotional closeness. We used latent class analysis to identify friendship network types in a sample of middle-aged and older adults aged 40-85 years (N = 1,876). Data came from the German Aging Survey (DEAS). Our analysis revealed 4 distinct friendship network types that were in high congruence with Matthews's typology. We identified these as a discerning style, which focuses on few close relationships, an independent style, which refrains from close engagements, and 2 acquisitive styles that both acquire new friends across their whole life course but differ regarding the emotional closeness of their friendships. Socioeconomic status, gender, health, and network-disturbing and network-sustaining variables predicted affiliations with network types. We argue that future studies should consider a holistic view of friendships in order to better understand the association between friendships and well-being in the second half of life.

Cadmium, lead, and mercury levels in feathers of small passerine birds: noninvasive sampling strategy.

PubMed

Bianchi, Nicola; Ancora, Stefania; di Fazio, Noemi; Leonzio, Claudio

2008-10-01

Bird feathers have been widely used as a nondestructive biological material for monitoring heavy metals. Sources of metals taken up by feathers include diet (metals are incorporated during feather formation), preening, and direct contact with metals in water, air, dust, and plants. In the literature, data regarding the origin of trace elements in feathers are not univocal. Only in the vast literature concerning mercury (as methyl mercury) has endogenous origin been determined. In the present study, we investigate cadmium, lead, and mercury levels in feathers of prey of Falco eleonorae in relation to the ecological characteristics (molt, habitat, and contamination by soil) of the different species. Cluster analysis identified two main groups of species. Differences and correlations within and between groups identified by cluster analysis were then checked by nonparametric statistical analysis. The results showed that mercury levels had a pattern significantly different from those of cadmium and lead, which in turn showed a significant positive correlation, suggesting different origins. Nests of F. eleonorae proved to be a good source for feathers of small trans-Saharan passerines collected by a noninvasive method. They provided abundant feathers of the various species in a relatively small area--in this case, the falcon colony on the Isle of San Pietro, Sardinia, Italy.

Methylation-sensitive amplified polymorphism analysis of Verticillium wilt-stressed cotton (Gossypium).

PubMed

Wang, W; Zhang, M; Chen, H D; Cai, X X; Xu, M L; Lei, K Y; Niu, J H; Deng, L; Liu, J; Ge, Z J; Yu, S X; Wang, B H

2016-10-06

In this study, a methylation-sensitive amplification polymorphism analysis system was used to analyze DNA methylation level in three cotton accessions. Two disease-sensitive near-isogenic lines, PD94042 and IL41, and one disease-resistant Gossypium mustelinum accession were exposed to Verticillium wilt, to investigate molecular disease resistance mechanisms in cotton. We observed multiple different DNA methylation types across the three accessions following Verticillium wilt exposure. These included hypomethylation, hypermethylation, and other patterns. In general, the global DNA methylation level was significantly increased in the disease-resistant accession G. mustelinum following disease exposure. In contrast, there was no significant difference in the disease-sensitive accession PD94042, and a significant decrease was observed in IL41. Our results suggest that disease-resistant cotton might employ a mechanism to increase methylation level in response to disease stress. The differing methylation patterns, together with the increase in global DNA methylation level, might play important roles in tolerance to Verticillium wilt in cotton. Through cloning and analysis of differently methylated DNA sequences, we were also able to identify several genes that may contribute to disease resistance in cotton. Our results revealed the effect of DNA methylation on cotton disease resistance, and also identified genes that played important roles, which may shed light on the future cotton disease-resistant molecular breeding.

The mechanisms of action underlying the efficacy of psychological nightmare treatments: A systematic review and thematic analysis of discussed hypotheses.

PubMed

Rousseau, Andréanne; Belleville, Geneviève

2018-06-01

Studies of psychotherapeutic treatments for nightmares have yielded support for their effectiveness. However, no consensus exists to explain how they work. This study combines a systematic review with a qualitative thematic analysis to identify and categorize the existing proposed mechanisms of action (MAs) of nightmare treatments. The systematic review allowed for a great number of scholarly publications on supported psychological treatments for nightmares to be identified. Characteristics of the study and citations regarding potential MAs were extracted using a standardized coding grid. Then, thematic analysis allowed citations to be grouped under six different categories of possible MAs according to their similarities and differences. Results reveal that an increased sense of mastery was the most often cited hypothesis to explain the efficacy of nightmare psychotherapies. Other mechanisms included emotional processing leading to modification of the fear structure, modification of beliefs, restoration of sleep functions, decreased arousal, and prevention of avoidance. An illustration of the different variables involved in the treatment of nightmares is proposed. Different avenues for operationalization of these MAs are put forth to enable future research on nightmare treatments to measure and link them to efficacy measures, and test the implications of the illustration. Copyright © 2017 Elsevier Ltd. All rights reserved.

Characterising infant inter-breath interval patterns during active and quiet sleep using recurrence plot analysis.

PubMed

Terrill, Philip I; Wilson, Stephen J; Suresh, Sadasivam; Cooper, David M

2009-01-01

Breathing patterns are characteristically different between active and quiet sleep states in infants. It has been previously identified that breathing dynamics are governed by a non-linear controller which implies the need for a nonlinear analytical tool. Further, it has been shown that quantified nonlinear variables are different between adult sleep states. This study aims to determine whether a nonlinear analytical tool known as recurrence plot analysis can characterize breath intervals of active and quiet sleep states in infants. Overnight polysomnograms were obtained from 32 healthy infants. The 6 longest periods each of active and quiet sleep were identified and a software routine extracted inter-breath interval data for recurrence plot analysis. Determinism (DET), laminarity (LAM) and radius (RAD) values were calculated for an embedding dimension of 4, 6, 8 and 16, and fixed recurrence of 0.5, 1, 2, 3.5 and 5%. Recurrence plots exhibited characteristically different patterns for active and quiet sleep. Active sleep periods typically had higher values of RAD, DET and LAM than for quiet sleep, and this trend was invariant to a specific choice of embedding dimension or fixed recurrence. These differences may provide a basis for automated sleep state classification, and the quantitative investigation of pathological breathing patterns.

Principal component analysis of three-dimensional face shape: Identifying shape features that change with age.

PubMed

Kurosumi, M; Mizukoshi, K

2018-05-01

The types of shape feature that constitutes a face have not been comprehensively established, and most previous studies of age-related changes in facial shape have focused on individual characteristics, such as wrinkle, sagging skin, etc. In this study, we quantitatively measured differences in face shape between individuals and investigated how shape features changed with age. We analyzed three-dimensionally the faces of 280 Japanese women aged 20-69 years and used principal component analysis to establish the shape features that characterized individual differences. We also evaluated the relationships between each feature and age, clarifying the shape features characteristic of different age groups. Changes in facial shape in middle age were a decreased volume of the upper face and increased volume of the whole cheeks and around the chin. Changes in older people were an increased volume of the lower cheeks and around the chin, sagging skin, and jaw distortion. Principal component analysis was effective for identifying facial shape features that represent individual and age-related differences. This method allowed straightforward measurements, such as the increase or decrease in cheeks caused by soft tissue changes or skeletal-based changes to the forehead or jaw, simply by acquiring three-dimensional facial images. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Comparative proteomic analysis of male and female venoms from the Cuban scorpion Rhopalurus junceus.

PubMed

Rodríguez-Ravelo, Rodolfo; Batista, Cesar V F; Coronas, Fredy I V; Zamudio, Fernando Z; Hernández-Orihuela, Lorena; Espinosa-López, Georgina; Ruiz-Urquiola, Ariel; Possani, Lourival D

2015-12-01

A complete mass spectrometry analysis of venom components from male and female scorpions of the species Rhophalurus junceus of Cuba is reported. In the order of 200 individual molecular masses were identified in both venoms, from which 63 are identical in male and females genders. It means that a significant difference of venom components exists between individuals of different sexes, but the most abundant components are present in both sexes. The relative abundance of identical components is different among the genders. Three well defined groups of different peptides were separated and identified. The first group corresponds to peptides with molecular masses of 1000-2000 Da; the second to peptides with 3500-4500 Da molecular weight, and the third with 6500-8000 Da molecular weights. A total of 86 peptides rich in disulfide bridges were found in the venoms, 27 with three disulfide bridges and 59 with four disulfide bridges. LC-MS/MS analysis allowed the identification and amino acid sequence determination of 31 novel peptides in male venom. Two new putative K(+)-channel peptides were sequences by Edman degradation. They contain 37 amino acid residues, packed by three disulfide bridges and were assigned the systematic numbers: α-KTx 1.18 and α-KTx 2.15. Copyright © 2015 Elsevier Ltd. All rights reserved.

Primary anastomosis or ostomy in necrotizing enterocolitis?

PubMed

Haricharan, Ramanathapura N; Gallimore, Jade Palazzola; Nasr, Ahmed

2017-11-01

In neonates requiring operation for necrotizing enterocolitis (NEC), the complications due to enterostomy (ES) and the need for another operation to restore continuity have prompted several surgeons to employ primary anastomosis (PA) after resection as the operative strategy of choice. Our objective was to compare primary anastomosis to stoma formation in this population using systematic review and meta-analysis. Publications describing both interventions were identified by searching multiple databases. Appropriate studies that reported outcomes after PA and ES for NEC were included for analysis that was performed using the MedCalc3000 software. Results are reported as odds ratios (OR, 95% CI). No randomized trials were identified. Twelve studies were included for the final analysis. Neonates who underwent PA were associated with significantly less risk of mortality when compared to those who underwent ES (OR 0.34, 95% CI 0.17-0.68, p 0.002), possibly due to differences in severity of NEC. Although the types of complications in these groups were different, there was no significant difference in risk of complication (OR 0.86, 0.55-1.33, p 0.50). In neonates undergoing an operation for severe NEC, there is no significant difference in the risk of complications between primary anastomosis and enterostomy. A definitive suggestion cannot be made regarding the choice of one operative strategy over another.

Gender differences in food preferences of school-aged children and adolescents.

PubMed

Caine-Bish, Natalie L; Scheule, Barbara

2009-11-01

Schools have the opportunity, through the National School Lunch Program and Local School Wellness Policies, to have a significant impact on healthy eating behaviors. An understanding of children's and adolescents' food preferences in relation to gender and age will facilitate the successful creation of both healthy and financially viable school menus. The purpose of this study was to identify food preferences with respect to gender of school-age children and adolescents in an Ohio school district. A survey was administered to 1818 3rd- to 12th-grade students in 1 rural northeast Ohio school district. Students filled out an anonymous questionnaire about their preferences for 80 different foods using a 5-point rating scale. The student data were grouped according to school level attended: elementary (3rd-6th), middle (7th-8th), and high school (9th-12th). An exploratory factor analysis identified entrée and side dish factors. Cronbach's alpha was used to measure each factor's internal reliability. Differences in mean scores by gender and grade for each of the entrée and side dish factors by gender and grade were identified using analysis of variance (ANOVA). Boys preferred the meat, fish, and poultry foods over girls; girls preferred fruits and vegetables over boys (p < .05). Furthermore, gender differences in preferences were also demonstrated with respect to school level. Food preferences differed between genders and these gender differences varied among elementary, middle, and high school students. Gender differences should be considered when providing food choices to boys and girls at all ages.

Pattern of distant extrahepatic metastases in primary liver cancer: a SEER based study.

PubMed

Wu, Wenrui; He, Xingkang; Andayani, Dewi; Yang, Liya; Ye, Jianzhong; Li, Yating; Chen, Yanfei; Li, Lanjuan

2017-01-01

Background and Aims : Primary liver cancer remains still the common cause of cancer-related deaths globally and the prognosis for patients with extrahepatic metastasis is poor. The aim of our study was to assess extrahepatic metastatic pattern of different histological subtypes and evaluate prognostic effects of extrahepatic metastasis in patients with advanced disease. Methods: Based on the Surveillance, Epidemiology and End Results (SEER) database, eligible patients diagnosed with primary liver cancer was identified between 2010 to 2012. We adopted Chi-square test to compared metastasis distribution among different histological types. We compared survival difference of patients with different extrahepatic metastasises by Kaplan-Meier analysis. Cox proportional hazard models were performed to identify other prognostic factors of overall survival. Results: We finally identified 8677 patients who were diagnosed with primary liver cancer from 2010 to 2012 and 1775 patients were in distant metastasis stages. Intrahepatic cholangiocarcinoma was more invasive and had a higher percentage of metastasis compared with hepatocellular carcinoma. Lung was the most common metastasis and brain was the least common site for both hepatocellular carcinoma and intrahepatic cholangiocarcinoma. Extrahepatic metastasis could consider as an independent prognostic factor for patients with liver cancer. Patients with brain metastasis had the worst prognosis, compared with other metastasis in overall survival (OS) and cancer-specific survival (CSS) analysis. Conclusions: Different histological subtypes of liver cancer had different metastasis patterns. There were profound differences in risk of mortality among distant extrahepatic metastatic sites. Results from our studies would provide some information for follow-up strategies and future studies.

A Computational Framework for Identifiability and Ill-Conditioning Analysis of Lithium-Ion Battery Models

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

López C, Diana C.; Wozny, Günter; Flores-Tlacuahuac, Antonio

2016-03-23

The lack of informative experimental data and the complexity of first-principles battery models make the recovery of kinetic, transport, and thermodynamic parameters complicated. We present a computational framework that combines sensitivity, singular value, and Monte Carlo analysis to explore how different sources of experimental data affect parameter structural ill conditioning and identifiability. Our study is conducted on a modified version of the Doyle-Fuller-Newman model. We demonstrate that the use of voltage discharge curves only enables the identification of a small parameter subset, regardless of the number of experiments considered. Furthermore, we show that the inclusion of a single electrolyte concentrationmore » measurement significantly aids identifiability and mitigates ill-conditioning.« less

Origin-based polyphenolic fingerprinting of Theobroma cacao in unfermented and fermented beans.

PubMed

D'Souza, Roy N; Grimbs, Sergio; Behrends, Britta; Bernaert, Herwig; Ullrich, Matthias S; Kuhnert, Nikolai

2017-09-01

A comprehensive analysis of cocoa polyphenols from unfermented and fermented cocoa beans from a wide range of geographic origins was carried out to catalogue systematic differences based on their origin as well as fermentation status. This study identifies previously unknown compounds with the goal to ascertain, which of these are responsible for the largest differences between bean types. UHPLC coupled with ultra-high resolution time-of-flight mass spectrometry was employed to identify and relatively quantify various oligomeric proanthocyanidins and their glycosides amongst several other unreported compounds. A series of biomarkers allowing a clear distinction between unfermented and fermented cocoa beans and for beans of different origins were identified. The large sample set employed allowed comparison of statistically significant variations of key cocoa constituents. Copyright © 2017 Elsevier Ltd. All rights reserved.

Positional differences in the wound transcriptome of skin and oral mucosa

PubMed Central

2010-01-01

Background When compared to skin, oral mucosal wounds heal rapidly and with reduced scar formation. Recent studies suggest that intrinsic differences in inflammation, growth factor production, levels of stem cells, and cellular proliferation capacity may underlie the exceptional healing that occurs in oral mucosa. The current study was designed to compare the transcriptomes of oral mucosal and skin wounds in order to identify critical differences in the healing response at these two sites using an unbiased approach. Results Using microarray analysis, we explored the differences in gene expression in skin and oral mucosal wound healing in a murine model of paired equivalent sized wounds. Samples were examined from days 0 to 10 and spanned all stages of the wound healing process. Using unwounded matched tissue as a control, filtering identified 1,479 probe sets in skin wounds yet only 502 probe sets in mucosal wounds that were significantly differentially expressed over time. Clusters of genes that showed similar patterns of expression were also identified in each wound type. Analysis of functionally related gene expression demonstrated dramatically different reactions to injury between skin and mucosal wounds. To explore whether site-specific differences might be derived from intrinsic differences in cellular responses at each site, we compared the response of isolated epithelial cells from skin and oral mucosa to a defined in vitro stimulus. When cytokine levels were measured, epithelial cells from skin produced significantly higher amounts of proinflammatory cytokines than cells from oral mucosa. Conclusions The results provide the first detailed molecular profile of the site-specific differences in the genetic response to injury in mucosa and skin, and suggest the divergent reactions to injury may derive from intrinsic differences in the cellular responses at each site. PMID:20704739

Positional differences in the wound transcriptome of skin and oral mucosa.

PubMed

Chen, Lin; Arbieva, Zarema H; Guo, Shujuan; Marucha, Phillip T; Mustoe, Thomas A; DiPietro, Luisa A

2010-08-12

When compared to skin, oral mucosal wounds heal rapidly and with reduced scar formation. Recent studies suggest that intrinsic differences in inflammation, growth factor production, levels of stem cells, and cellular proliferation capacity may underlie the exceptional healing that occurs in oral mucosa. The current study was designed to compare the transcriptomes of oral mucosal and skin wounds in order to identify critical differences in the healing response at these two sites using an unbiased approach. Using microarray analysis, we explored the differences in gene expression in skin and oral mucosal wound healing in a murine model of paired equivalent sized wounds. Samples were examined from days 0 to 10 and spanned all stages of the wound healing process. Using unwounded matched tissue as a control, filtering identified 1,479 probe sets in skin wounds yet only 502 probe sets in mucosal wounds that were significantly differentially expressed over time. Clusters of genes that showed similar patterns of expression were also identified in each wound type. Analysis of functionally related gene expression demonstrated dramatically different reactions to injury between skin and mucosal wounds. To explore whether site-specific differences might be derived from intrinsic differences in cellular responses at each site, we compared the response of isolated epithelial cells from skin and oral mucosa to a defined in vitro stimulus. When cytokine levels were measured, epithelial cells from skin produced significantly higher amounts of proinflammatory cytokines than cells from oral mucosa. The results provide the first detailed molecular profile of the site-specific differences in the genetic response to injury in mucosa and skin, and suggest the divergent reactions to injury may derive from intrinsic differences in the cellular responses at each site.

Comparative proteomic analysis between the domesticated silkworm (Bombyx mori) reared on fresh mulberry leaves and on artificial diet.

PubMed

Zhou, Zhong-Hua; Yang, Hui-Juan; Chen, Ming; Lou, Cheng-Fu; Zhang, Yao-Zhou; Chen, Ke-Ping; Wang, Yong; Yu, Mei-Lan; Yu, Fang; Li, Jian-Ying; Zhong, Bo-Xiong

2008-12-01

To gain an insight into the effects of different diets on growth and development of the domesticated silkworm at protein level, we employed comparative proteomic approach to investigate the proteomic differences of midgut, hemolymph, fat body and posterior silk gland of the silkworms reared on fresh mulberry leaves and on artificial diet. Seventy-six differentially expressed proteins were identified by MALDI TOF/TOF MS, and among them, 41 proteins were up-regulated, and 35 proteins were downregulated. Database searches, combined with GO analysis and KEGG pathway analysis revealed that some hemolymph proteins such as Nuecin, Gloverin-like proteins, PGRP, P50 and beta/-N-acetylglucosamidase were related to innate immunity of the silkworm, and some proteins identified in silkworm midgut including Myosin 1 light chain, Tropomyosin 1, Profilin, Serpin-2 and GSH-Px were involved in digestion and nutrition absorption. Moreover, two up-regulated enzymes in fat body of larvae reared on artificial diet were identified as V-ATPase subunit B and Arginine kinase which participate in energy metabolism. Furthermore, 6 down-regulated proteins identified in posterior silk gland of silkworm larvae reared on artificial diet including Ribosomal protein SA, EF-2, EF-1gamma, AspAT, ERp57 and PHB were related to silk synthesis. Our results suggested that the different diets could alter the expression of proteins related to immune system, digestion and absorption of nutrient, energy metabolism and silk synthesis poor nutrition and absorption of nutrition in silkworm. The results also confirmed that the poor nutrient absorption, weakened innate immunity, decreased energy metabolism and reduced silk synthesis are the main reasons for low cocoons yield, inferior filament quality, low survival rate of young larvae and insufficient resistance against specific pathogens in the silkworms fed on artificial diet.

Neural correlates of social exclusion across ages: A coordinate-based meta-analysis of functional MRI studies.

PubMed

Vijayakumar, Nandita; Cheng, Theresa W; Pfeifer, Jennifer H

2017-06-01

Given the recent surge in functional neuroimaging studies on social exclusion, the current study employed activation likelihood estimation (ALE) based meta-analyses to identify brain regions that have consistently been implicated across different experimental paradigms used to investigate exclusion. We also examined the neural correlates underlying Cyberball, the most commonly used paradigm to study exclusion, as well as differences in exclusion-related activation between developing (7-18 years of age, from pre-adolescence up to late adolescence) and emerging adult (broadly defined as undergraduates, including late adolescence and young adulthood) samples. Results revealed involvement of the bilateral medial prefrontal and posterior cingulate cortices, right precuneus and left ventrolateral prefrontal cortex across the different paradigms used to examine social exclusion; similar activation patterns were identified when restricting the analysis to Cyberball studies. Investigations into age-related effects revealed that ventrolateral prefrontal activations identified in the full sample were driven by (i.e. present in) developmental samples, while medial prefrontal activations were driven by emerging adult samples. In addition, the right ventral striatum was implicated in exclusion, but only in developmental samples. Subtraction analysis revealed significantly greater activation likelihood in striatal and ventrolateral prefrontal clusters in the developmental samples as compared to emerging adults, though the opposite contrast failed to identify any significant regions. Findings integrate the knowledge accrued from functional neuroimaging studies on social exclusion to date, highlighting involvement of lateral prefrontal regions implicated in regulation and midline structures involved in social cognitive and self-evaluative processes across experimental paradigms and ages, as well as limbic structures in developing samples specifically. Copyright © 2017 Elsevier Inc. All rights reserved.

Different fecal microbiotas and volatile organic compounds in treated and untreated children with celiac disease.

PubMed

Di Cagno, Raffaella; Rizzello, Carlo G; Gagliardi, Francesca; Ricciuti, Patrizia; Ndagijimana, Maurice; Francavilla, Ruggiero; Guerzoni, M Elisabetta; Crecchio, Carmine; Gobbetti, Marco; De Angelis, Maria

2009-06-01

This study aimed at investigating the fecal microbiotas of children with celiac disease (CD) before (U-CD) and after (T-CD) they were fed a gluten-free diet and of healthy children (HC). Brothers or sisters of T-CD were enrolled as HC. Each group consisted of seven children. PCR-denaturing gradient gel electrophoresis (DGGE) analysis with V3 universal primers revealed a unique profile for each fecal sample. PCR-DGGE analysis with group- or genus-specific 16S rRNA gene primers showed that the Lactobacillus community of U-CD changed significantly, while the diversity of the Lactobacillus community of T-CD was quite comparable to that of HC. Compared to HC, the ratio of cultivable lactic acid bacteria and Bifidobacterium to Bacteroides and enterobacteria was lower in T-CD and even lower in U-CD. The percentages of strains identified as lactobacilli differed as follows: HC (ca. 38%) > T-CD (ca. 17%) > U-CD (ca. 10%). Lactobacillus brevis, Lactobacillus rossiae, and Lactobacillus pentosus were identified only in fecal samples from T-CD and HC. Lactobacillus fermentum, Lactobacillus delbrueckii subsp. bulgaricus, and Lactobacillus gasseri were identified only in several fecal samples from HC. Compared to HC, the composition of Bifidobacterium species of T-CD varied, and it varied even more for U-CD. Forty-seven volatile organic compounds (VOCs) belonging to different chemical classes were identified using gas-chromatography mass spectrometry-solid-phase microextraction analysis. The median concentrations varied markedly for HC, T-CD, and U-CD. Overall, the r(2) values for VOC data for brothers and sisters were equal to or lower than those for unrelated HC and T-CD. This study shows the effect of CD pathology on the fecal microbiotas of children.

Worldwide Lineages of Clinical Pneumococci in a Japanese Teaching Hospital Identified by DiversiLab System.

PubMed

Kashiwaya, Kiyoshi; Saga, Tomoo; Ishii, Yoshikazu; Sakata, Ryuji; Iwata, Morihiro; Yoshizawa, Sadako; Chang, Bin; Ohnishi, Makoto; Tateda, Kazuhiro

2016-06-01

Pneumococcal Molecular Epidemiology Network (PMEN) clones are representatives of worldwide-spreading pathogens. DiversiLab system, a repetitive PCR system, has been proposed as a less labor-and time-intensive genotyping platform alternative to conventional methods. However, the utility and analysis parameters of DiversiLab for identifying worldwide lineages was not established. To evaluate and optimize the performance of DiversiLab for identifying worldwide pneumococcal lineages, we examined 245 consecutive isolates of clinical Streptococcus pneumoniae from all age-group patients at a teaching hospital in Japan. The capsular swelling reaction of all isolates yielded 24 different serotypes. Intensive visual observation (VO) of DiversiLab band pattern difference divided all isolates into 73 clusters. Multilocus sequence typing (MLST) of representative 73 isolates from each VO cluster yielded 51 different STs. Among them, PMEN-related lineages accounted for 63% (46/73). Although the serotype of PMEN-related isolates was identical to that of the original PMEN clone in 70% (32/46), CC156-related PMEN lineages, namely Greece(6B)-22 and Colombia(23F)-26, harbored various capsular types discordant to the original PMEN clones. Regarding automated analysis, genotyping by extended Jaccard (XJ) with a 75% similarity index cutoff (SIC) showed the highest correlation with serotyping (adjusted Rand's coefficient, 0.528). Elevating the SIC for XJ to 85% increased the discriminatory power sufficient for distinguishing two major PMEN-related isolates of Taiwan(19F)-14 and Netherlands(3)-31. These results demonstrated a potential utility of DiversiLab for identifying worldwide lineage of pneumococcus. An optimized parameters of automated analysis should be useful especially for comparison for reference strains by "identification" function of DiversiLab. Copyright © 2016 Japanese Society of Chemotherapy and The Japanese Association for Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

E-Nose and GC-MS Reveal a Difference in the Volatile Profiles of White- and Red-Fleshed Peach Fruit

PubMed Central

Xin, Rui; Liu, Xiaohong; Wei, Chunyan; Yang, Chong; Liu, Hongru; Cao, Xiangmei; Wu, Di; Chen, Kunsong

2018-01-01

First purchases of fruit are mainly dependent on aspects of appearance such as color. However, repeat buys of fruit are determined by internal quality traits such as flavor-related volatiles. Differences in volatile profiles in white- and red-fleshed peach fruit are not well understood. In the present study, peach cultivars with white- and red-fleshed fruit were subjected to sensory analysis using electronic nose (e-nose) to evaluate overview volatile profiles. Approximately 97.3% of the total variation in peach color-volatiles was explained by the first principle component 1 (PC1) and PC2. After analyzing sensory differences between peach fruit samples, 50 volatile compounds were characterized based on GC-MS. Multivariate analysis such as partial least squares discriminant analysis (PLS-DA) was applied to identify volatile compounds that contribute to difference in white- and red-fleshed peach fruit cultivars. A total of 18 volatiles that could separate peach fruit cultivars with different colors in flesh during ripening were identified based on variable importance in projection (VIP) score. Fruity note latone γ-hexalactone had higher contents in red-fleshed cultivars, while grassy note C6 compounds such as hexanal, 2-hexenal, (E)-2-hexenal, 1-hexanol, and (Z)-2-hexen-1-ol showed great accumulation in white-fleshed peach fruit. PMID:29498705

GC-MS-based metabolite profiling of Cosmos caudatus leaves possessing alpha-glucosidase inhibitory activity.

PubMed

Javadi, Neda; Abas, Faridah; Abd Hamid, Azizah; Simoh, Sanimah; Shaari, Khozirah; Ismail, Intan Safinar; Mediani, Ahmed; Khatib, Alfi

2014-06-01

Cosmos caudatus, which is known as "Ulam Raja," is an herbal plant used in Malaysia to enhance vitality. This study focused on the evaluation of the α-glucosidase inhibitory activity of different ethanolic extracts of C. caudatus. Six series of samples extracted with water, 20%, 40%, 60%, 80%, and 100% ethanol (EtOH) were employed. Gas chromatography-mass spectrometry (GC-MS) and orthogonal partial least-squares (OPLS) analysis was used to correlate bioactivity of different extracts to different metabolite profiles of C. caudatus. The obtained OPLS scores indicated a distinct and remarkable separation into 6 clusters, which were indicative of the 6 different ethanol concentrations. GC-MS can be integrated with multivariate data analysis to identify compounds that inhibit α-glucosidase activity. In addition, catechin, α-linolenic acid, α-D-glucopyranoside, and vitamin E compounds were identified and indicate the potential α-glucosidase inhibitory activity of this herb. GC-MS and multivariate data analysis was applied to discriminate Cosmos caudatus samples extracted with water and different ratio of ethanol. Orthogonal partial least-squares (OPLS) model developed was used to determine the major metabolites contributed to α-glucosidase inhibitory activity. This approach also has the ability to predict the bioactivity of a new set of extracts based on a developed validated regression model that is important for quality control of the herb preparation. © 2014 Institute of Food Technologists®

Application of Factor Analysis on the Financial Ratios of Indian Cement Industry and Validation of the Results by Cluster Analysis

NASA Astrophysics Data System (ADS)

De, Anupam; Bandyopadhyay, Gautam; Chakraborty, B. N.

2010-10-01

Financial ratio analysis is an important and commonly used tool in analyzing financial health of a firm. Quite a large number of financial ratios, which can be categorized in different groups, are used for this analysis. However, to reduce number of ratios to be used for financial analysis and regrouping them into different groups on basis of empirical evidence, Factor Analysis technique is being used successfully by different researches during the last three decades. In this study Factor Analysis has been applied over audited financial data of Indian cement companies for a period of 10 years. The sample companies are listed on the Stock Exchange India (BSE and NSE). Factor Analysis, conducted over 44 variables (financial ratios) grouped in 7 categories, resulted in 11 underlying categories (factors). Each factor is named in an appropriate manner considering the factor loads and constituent variables (ratios). Representative ratios are identified for each such factor. To validate the results of Factor Analysis and to reach final conclusion regarding the representative ratios, Cluster Analysis had been performed.

Parallel RNAi screens across different cell lines identify generic and cell type-specific regulators of actin organization and cell morphology.

PubMed

Liu, Tao; Sims, David; Baum, Buzz

2009-01-01

In recent years RNAi screening has proven a powerful tool for dissecting gene functions in animal cells in culture. However, to date, most RNAi screens have been performed in a single cell line, and results then extrapolated across cell types and systems. Here, to dissect generic and cell type-specific mechanisms underlying cell morphology, we have performed identical kinome RNAi screens in six different Drosophila cell lines, derived from two distinct tissues of origin. This analysis identified a core set of kinases required for normal cell morphology in all lines tested, together with a number of kinases with cell type-specific functions. Most significantly, the screen identified a role for minibrain (mnb/DYRK1A), a kinase associated with Down's syndrome, in the regulation of actin-based protrusions in CNS-derived cell lines. This cell type-specific requirement was not due to the peculiarities in the morphology of CNS-derived cells and could not be attributed to differences in mnb expression. Instead, it likely reflects differences in gene expression that constitute the cell type-specific functional context in which mnb/DYRK1A acts. Using parallel RNAi screens and gene expression analyses across cell types we have identified generic and cell type-specific regulators of cell morphology, which include mnb/DYRK1A in the regulation of protrusion morphology in CNS-derived cell lines. This analysis reveals the importance of using different cell types to gain a thorough understanding of gene function across the genome and, in the case of kinases, the difficulties of using the differential gene expression to predict function.

A detailed comparison of analysis processes for MCC-IMS data in disease classification—Automated methods can replace manual peak annotations

PubMed Central

Horsch, Salome; Kopczynski, Dominik; Kuthe, Elias; Baumbach, Jörg Ingo; Rahmann, Sven

2017-01-01

Motivation Disease classification from molecular measurements typically requires an analysis pipeline from raw noisy measurements to final classification results. Multi capillary column—ion mobility spectrometry (MCC-IMS) is a promising technology for the detection of volatile organic compounds in the air of exhaled breath. From raw measurements, the peak regions representing the compounds have to be identified, quantified, and clustered across different experiments. Currently, several steps of this analysis process require manual intervention of human experts. Our goal is to identify a fully automatic pipeline that yields competitive disease classification results compared to an established but subjective and tedious semi-manual process. Method We combine a large number of modern methods for peak detection, peak clustering, and multivariate classification into analysis pipelines for raw MCC-IMS data. We evaluate all combinations on three different real datasets in an unbiased cross-validation setting. We determine which specific algorithmic combinations lead to high AUC values in disease classifications across the different medical application scenarios. Results The best fully automated analysis process achieves even better classification results than the established manual process. The best algorithms for the three analysis steps are (i) SGLTR (Savitzky-Golay Laplace-operator filter thresholding regions) and LM (Local Maxima) for automated peak identification, (ii) EM clustering (Expectation Maximization) and DBSCAN (Density-Based Spatial Clustering of Applications with Noise) for the clustering step and (iii) RF (Random Forest) for multivariate classification. Thus, automated methods can replace the manual steps in the analysis process to enable an unbiased high throughput use of the technology. PMID:28910313

Clonal Analysis of the Microbiota of Severe Early Childhood Caries

PubMed Central

Kanasi, E.; Dewhirst, F.E.; Chalmers, N.I.; Kent, R.; Moore, A.; Hughes, C.V.; Pradhan, N.; Loo, C.Y.; Tanner, A.C.R.

2010-01-01

Background/Aims Severe early childhood caries is a microbial infection that severely compromises the dentition of young children. The aim of this study was to characterize the microbiota of severe early childhood caries. Methods Dental plaque samples from 2- to 6-year-old children were analyzed using 16S rRNA gene cloning and sequencing, and by specific PCR amplification for Streptococcus mutans and Bifidobacteriaceae species. Results Children with severe caries (n = 39) had more dental plaque and gingival inflammation than caries-free children (n = 41). Analysis of phylotypes from operational taxonomic unit analysis of 16S rRNA clonal metalibraries from severe caries and caries-free children indicated that while libraries differed significantly (p < 0.0001), there was increased diversity than detected in this clonal analysis. Using the Human Oral Microbiome Database, 139 different taxa were identified. Within the limits of this study, caries-associated taxa included Granulicatella elegans (p < 0.01) and Veillonella sp. HOT-780 (p < 0.01). The species associated with caries-free children included Capnocytophaga gingivalis (p < 0.01), Abiotrophia defectiva (p < 0.01), Lachnospiraceae sp. HOT-100 (p < 0.05), Streptococcus sanguinis (p < 0.05) and Streptococcus cristatus (p < 0.05). By specific PCR, S. mutans (p < 0.005) and Bifidobacteriaceae spp. (p < 0.0001) were significantly associated with severe caries. Conclusion Clonal analysis of 80 children identified a diverse microbiota that differed between severe caries and caries-free children, but the association of S. mutans with caries was from specific PCR analysis, not from clonal analysis, of samples. PMID:20861633

GOEAST: a web-based software toolkit for Gene Ontology enrichment analysis.

PubMed

Zheng, Qi; Wang, Xiu-Jie

2008-07-01

Gene Ontology (GO) analysis has become a commonly used approach for functional studies of large-scale genomic or transcriptomic data. Although there have been a lot of software with GO-related analysis functions, new tools are still needed to meet the requirements for data generated by newly developed technologies or for advanced analysis purpose. Here, we present a Gene Ontology Enrichment Analysis Software Toolkit (GOEAST), an easy-to-use web-based toolkit that identifies statistically overrepresented GO terms within given gene sets. Compared with available GO analysis tools, GOEAST has the following improved features: (i) GOEAST displays enriched GO terms in graphical format according to their relationships in the hierarchical tree of each GO category (biological process, molecular function and cellular component), therefore, provides better understanding of the correlations among enriched GO terms; (ii) GOEAST supports analysis for data from various sources (probe or probe set IDs of Affymetrix, Illumina, Agilent or customized microarrays, as well as different gene identifiers) and multiple species (about 60 prokaryote and eukaryote species); (iii) One unique feature of GOEAST is to allow cross comparison of the GO enrichment status of multiple experiments to identify functional correlations among them. GOEAST also provides rigorous statistical tests to enhance the reliability of analysis results. GOEAST is freely accessible at http://omicslab.genetics.ac.cn/GOEAST/

Histogram analysis parameters identify multiple associations between DWI and DCE MRI in head and neck squamous cell carcinoma.

PubMed

Meyer, Hans Jonas; Leifels, Leonard; Schob, Stefan; Garnov, Nikita; Surov, Alexey

2018-01-01

Nowadays, multiparametric investigations of head and neck squamous cell carcinoma (HNSCC) are established. These approaches can better characterize tumor biology and behavior. Diffusion weighted imaging (DWI) can by means of apparent diffusion coefficient (ADC) quantitatively characterize different tissue compartments. Dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) reflects perfusion and vascularization of tissues. Recently, a novel approach of data acquisition, namely histogram analysis of different images is a novel diagnostic approach, which can provide more information of tissue heterogeneity. The purpose of this study was to analyze possible associations between DWI, and DCE parameters derived from histogram analysis in patients with HNSCC. Overall, 34 patients, 9 women and 25 men, mean age, 56.7±10.2years, with different HNSCC were involved in the study. DWI was obtained by using of an axial echo planar imaging sequence with b-values of 0 and 800s/mm 2 . Dynamic T1w DCE sequence after intravenous application of contrast medium was performed for estimation of the following perfusion parameters: volume transfer constant (K trans ), volume of the extravascular extracellular leakage space (Ve), and diffusion of contrast medium from the extravascular extracellular leakage space back to the plasma (Kep). Both ADC and perfusion parameters maps were processed offline in DICOM format with custom-made Matlab-based application. Thereafter, polygonal ROIs were manually drawn on the transferred maps on each slice. For every parameter, mean, maximal, minimal, and median values, as well percentiles 10th, 25th, 75th, 90th, kurtosis, skewness, and entropy were estimated. Сorrelation analysis identified multiple statistically significant correlations between the investigated parameters. Ve related parameters correlated well with different ADC values. Especially, percentiles 10 and 75, mode, and median values showed stronger correlations in comparison to other parameters. Thereby, the calculated correlation coefficients ranged from 0.62 to 0.69. Furthermore, K trans related parameters showed multiple slightly to moderate significant correlations with different ADC values. Strongest correlations were identified between ADC P75 and K trans min (p=0.58, P=0.0007), and ADC P75 and K trans P10 (p=0.56, P=0.001). Only four K ep related parameters correlated statistically significant with ADC fractions. Strongest correlation was found between K ep max and ADC mode (p=-0.47, P=0.008). Multiple statistically significant correlations between, DWI and DCE MRI parameters derived from histogram analysis were identified in HNSCC. Copyright © 2017 Elsevier Inc. All rights reserved.

OVCAR-3 Spheroid-Derived Cells Display Distinct Metabolic Profiles

PubMed Central

Vermeersch, Kathleen A.; Wang, Lijuan; Mezencev, Roman; McDonald, John F.; Styczynski, Mark P.

2015-01-01

Introduction Recently, multicellular spheroids were isolated from a well-established epithelial ovarian cancer cell line, OVCAR-3, and were propagated in vitro. These spheroid-derived cells displayed numerous hallmarks of cancer stem cells, which are chemo- and radioresistant cells thought to be a significant cause of cancer recurrence and resultant mortality. Gene set enrichment analysis of expression data from the OVCAR-3 cells and the spheroid-derived putative cancer stem cells identified several metabolic pathways enriched in differentially expressed genes. Before this, there had been little previous knowledge or investigation of systems-scale metabolic differences between cancer cells and cancer stem cells, and no knowledge of such differences in ovarian cancer stem cells. Methods To determine if there were substantial metabolic changes corresponding with these transcriptional differences, we used two-dimensional gas chromatography coupled to mass spectrometry to measure the metabolite profiles of the two cell lines. Results These two cell lines exhibited significant metabolic differences in both intracellular and extracellular metabolite measurements. Principal components analysis, an unsupervised dimensional reduction technique, showed complete separation between the two cell types based on their metabolite profiles. Pathway analysis of intracellular metabolomics data revealed close overlap with metabolic pathways identified from gene expression data, with four out of six pathways found enriched in gene-level analysis also enriched in metabolite-level analysis. Some of those pathways contained multiple metabolites that were individually statistically significantly different between the two cell lines, with one of the most broadly and consistently different pathways, arginine and proline metabolism, suggesting an interesting hypothesis about cancerous and stem-like metabolic phenotypes in this pair of cell lines. Conclusions Overall, we demonstrate for the first time that metabolism in an ovarian cancer stem cell line is distinct from that of more differentiated isogenic cancer cells, supporting the potential importance of metabolism in the differences between cancer cells and cancer stem cells. PMID:25688563

Balancing precision and risk: should multiple detection methods be analyzed separately in N-mixture models?

USGS Publications Warehouse

Graves, Tabitha A.; Royle, J. Andrew; Kendall, Katherine C.; Beier, Paul; Stetz, Jeffrey B.; Macleod, Amy C.

2012-01-01

Using multiple detection methods can increase the number, kind, and distribution of individuals sampled, which may increase accuracy and precision and reduce cost of population abundance estimates. However, when variables influencing abundance are of interest, if individuals detected via different methods are influenced by the landscape differently, separate analysis of multiple detection methods may be more appropriate. We evaluated the effects of combining two detection methods on the identification of variables important to local abundance using detections of grizzly bears with hair traps (systematic) and bear rubs (opportunistic). We used hierarchical abundance models (N-mixture models) with separate model components for each detection method. If both methods sample the same population, the use of either data set alone should (1) lead to the selection of the same variables as important and (2) provide similar estimates of relative local abundance. We hypothesized that the inclusion of 2 detection methods versus either method alone should (3) yield more support for variables identified in single method analyses (i.e. fewer variables and models with greater weight), and (4) improve precision of covariate estimates for variables selected in both separate and combined analyses because sample size is larger. As expected, joint analysis of both methods increased precision as well as certainty in variable and model selection. However, the single-method analyses identified different variables and the resulting predicted abundances had different spatial distributions. We recommend comparing single-method and jointly modeled results to identify the presence of individual heterogeneity between detection methods in N-mixture models, along with consideration of detection probabilities, correlations among variables, and tolerance to risk of failing to identify variables important to a subset of the population. The benefits of increased precision should be weighed against those risks. The analysis framework presented here will be useful for other species exhibiting heterogeneity by detection method.

Comparative secretome analysis of rat stomach under different nutritional status.

PubMed

Senin, Lucia L; Roca-Rivada, Arturo; Castelao, Cecilia; Alonso, Jana; Folgueira, Cintia; Casanueva, Felipe F; Pardo, Maria; Seoane, Luisa M

2015-02-26

Obesity is a major public health threat for many industrialised countries. Bariatric surgery is the most effective treatment against obesity, suggesting that gut derived signals are crucial for energy balance regulation. Several descriptive studies have proven the presence of gastric endogenous systems that modulate energy homeostasis; however, these systems and the interactions between them are still not well known. In the present study, we show for the first time the comparative 2-DE gastric secretome analysis under different nutritional status. We have identified 38 differently secreted proteins by comparing stomach secretomes from tissue explant cultures of rats under feeding, fasting and re-feeding conditions. Among the proteins identified, glyceraldehyde-3-phosphate dehydrogenase was found to be more abundant in gastric secretome and plasma after re-feeding, and downregulated in obesity. Additionally, two calponin-1 species were decreased in feeding state, and other were modulated by nutritional and metabolic conditions. These and other secreted proteins identified in this work may be considered as potential gastrokines implicated in food intake regulation. The present work has an important impact in the field of obesity, especially in the regulation of body weight maintenance by the stomach. Nowadays, the most effective treatment in the fight against obesity is bariatric surgery, which suggests that stomach derived signals might be crucial for the regulation of the energy homeostasis. However, until now, the knowledge about the gastrokines and its mechanism of action has been poorly elucidated. In the present work, we had updated a previously validated explant secretion model for proteomic studies; this analysis allowed us, for the first time, to study the gastric secretome without interferences from other organs. We had identified 38 differently secreted proteins comparing ex vivo cultured stomachs from rats under feeding, fasting and re-feeding regimes. The results in the present article provide novel targets to study the role of the stomach in body weight and appetite regulation, and suggest new potential therapeutic targets for treating obesity. Copyright © 2015 Elsevier B.V. All rights reserved.

Nuclear proliferomics: A new field of study to identify signatures of nuclear materials as demonstrated on alpha-UO3.

PubMed

Schwerdt, Ian J; Brenkmann, Alexandria; Martinson, Sean; Albrecht, Brent D; Heffernan, Sean; Klosterman, Michael R; Kirkham, Trenton; Tasdizen, Tolga; McDonald Iv, Luther W

2018-08-15

The use of a limited set of signatures in nuclear forensics and nuclear safeguards may reduce the discriminating power for identifying unknown nuclear materials, or for verifying processing at existing facilities. Nuclear proliferomics is a proposed new field of study that advocates for the acquisition of large databases of nuclear material properties from a variety of analytical techniques. As demonstrated on a common uranium trioxide polymorph, α-UO 3 , in this paper, nuclear proliferomics increases the ability to improve confidence in identifying the processing history of nuclear materials. Specifically, α-UO 3 was investigated from the calcination of unwashed uranyl peroxide at 350, 400, 450, 500, and 550 °C in air. Scanning electron microscopy (SEM) images were acquired of the surface morphology, and distinct qualitative differences are presented between unwashed and washed uranyl peroxide, as well as the calcination products from the unwashed uranyl peroxide at the investigated temperatures. Differential scanning calorimetry (DSC), UV-Vis spectrophotometry, powder X-ray diffraction (p-XRD), and thermogravimetric analysis-mass spectrometry (TGA-MS) were used to understand the source of these morphological differences as a function of calcination temperature. Additionally, the SEM images were manually segmented using Morphological Analysis for MAterials (MAMA) software to identify quantifiable differences in morphology for three different surface features present on the unwashed uranyl peroxide calcination products. No single quantifiable signature was sufficient to discern all calcination temperatures with a high degree of confidence; therefore, advanced statistical analysis was performed to allow the combination of a number of quantitative signatures, with their associated uncertainties, to allow for complete discernment by calcination history. Furthermore, machine learning was applied to the acquired SEM images to demonstrate automated discernment with at least 89% accuracy. Copyright © 2018 Elsevier B.V. All rights reserved.

Photogrammetric Analysis of Attractiveness in Indian Faces

PubMed Central

Duggal, Shveta; Kapoor, DN; Verma, Santosh; Sagar, Mahesh; Lee, Yung-Seop; Moon, Hyoungjin

2016-01-01

Background The objective of this study was to assess the attractive facial features of the Indian population. We tried to evaluate subjective ratings of facial attractiveness and identify which facial aesthetic subunits were important for facial attractiveness. Methods A cross-sectional study was conducted of 150 samples (referred to as candidates). Frontal photographs were analyzed. An orthodontist, a prosthodontist, an oral surgeon, a dentist, an artist, a photographer and two laymen (estimators) subjectively evaluated candidates' faces using visual analog scale (VAS) scores. As an objective method for facial analysis, we used balanced angular proportional analysis (BAPA). Using SAS 10.1 (SAS Institute Inc.), the Turkey's studentized range test and Pearson correlation analysis were performed to detect between-group differences in VAS scores (Experiment 1), to identify correlations between VAS scores and BAPA scores (Experiment 2), and to analyze the characteristic features of facial attractiveness and gender differences (Experiment 3); the significance level was set at P=0.05. Results Experiment 1 revealed some differences in VAS scores according to professional characteristics. In Experiment 2, BAPA scores were found to behave similarly to subjective ratings of facial beauty, but showed a relatively weak correlation coefficient with the VAS scores. Experiment 3 found that the decisive factors for facial attractiveness were different for men and women. Composite images of attractive Indian male and female faces were constructed. Conclusions Our photogrammetric study, statistical analysis, and average composite faces of an Indian population provide valuable information about subjective perceptions of facial beauty and attractive facial structures in the Indian population. PMID:27019809

Automated Recognition of 3D Features in GPIR Images

NASA Technical Reports Server (NTRS)

Park, Han; Stough, Timothy; Fijany, Amir

2007-01-01

A method of automated recognition of three-dimensional (3D) features in images generated by ground-penetrating imaging radar (GPIR) is undergoing development. GPIR 3D images can be analyzed to detect and identify such subsurface features as pipes and other utility conduits. Until now, much of the analysis of GPIR images has been performed manually by expert operators who must visually identify and track each feature. The present method is intended to satisfy a need for more efficient and accurate analysis by means of algorithms that can automatically identify and track subsurface features, with minimal supervision by human operators. In this method, data from multiple sources (for example, data on different features extracted by different algorithms) are fused together for identifying subsurface objects. The algorithms of this method can be classified in several different ways. In one classification, the algorithms fall into three classes: (1) image-processing algorithms, (2) feature- extraction algorithms, and (3) a multiaxis data-fusion/pattern-recognition algorithm that includes a combination of machine-learning, pattern-recognition, and object-linking algorithms. The image-processing class includes preprocessing algorithms for reducing noise and enhancing target features for pattern recognition. The feature-extraction algorithms operate on preprocessed data to extract such specific features in images as two-dimensional (2D) slices of a pipe. Then the multiaxis data-fusion/ pattern-recognition algorithm identifies, classifies, and reconstructs 3D objects from the extracted features. In this process, multiple 2D features extracted by use of different algorithms and representing views along different directions are used to identify and reconstruct 3D objects. In object linking, which is an essential part of this process, features identified in successive 2D slices and located within a threshold radius of identical features in adjacent slices are linked in a directed-graph data structure. Relative to past approaches, this multiaxis approach offers the advantages of more reliable detections, better discrimination of objects, and provision of redundant information, which can be helpful in filling gaps in feature recognition by one of the component algorithms. The image-processing class also includes postprocessing algorithms that enhance identified features to prepare them for further scrutiny by human analysts (see figure). Enhancement of images as a postprocessing step is a significant departure from traditional practice, in which enhancement of images is a preprocessing step.

Comparison of Cultivable Acetic Acid Bacterial Microbiota in Organic and Conventional Apple Cider Vinegar.

PubMed

Štornik, Aleksandra; Skok, Barbara; Trček, Janja

2016-03-01

Organic apple cider vinegar is produced from apples that go through very restricted treatment in orchard. During the first stage of the process, the sugars from apples are fermented by yeasts to cider. The produced ethanol is used as a substrate by acetic acid bacteria in a second separated bioprocess. In both, the organic and conventional apple cider vinegars the ethanol oxidation to acetic acid is initiated by native microbiota that survived alcohol fermentation. We compared the cultivable acetic acid bacterial microbiota in the production of organic and conventional apple cider vinegars from a smoothly running oxidation cycle of a submerged industrial process. In this way we isolated and characterized 96 bacteria from organic and 72 bacteria from conventional apple cider vinegar. Using the restriction analysis of the PCR-amplified 16S-23S rRNA gene ITS regions, we identified four different Hae III and five different Hpa II restriction profiles for bacterial isolates from organic apple cider vinegar. Each type of restriction profile was further analyzed by sequence analysis of the 16S-23S rRNA gene ITS regions, resulting in identification of the following species: Acetobacter pasteurianus (71.90%), Acetobacter ghanensis (12.50%), Komagataeibacter oboediens (9.35%) and Komagataeibacter saccharivorans (6.25%). Using the same analytical approach in conventional apple cider vinegar, we identified only two different Hae III and two different Hpa II restriction profiles of the 16S‒23S rRNA gene ITS regions, which belong to the species Acetobacter pasteurianus (66.70%) and Komagataeibacter oboediens (33.30%). Yeasts that are able to resist 30 g/L of acetic acid were isolated from the acetic acid production phase and further identified by sequence analysis of the ITS1-5.8S rDNA‒ITS2 region as Candida ethanolica , Pichia membranifaciens and Saccharomycodes ludwigii . This study has shown for the first time that the bacterial microbiota for the industrial production of organic apple cider vinegar is clearly more heterogeneous than the bacterial microbiota for the industrial production of conventional apple cider vinegar. Further chemical analysis should reveal if a difference in microbiota composition influences the quality of different types of apple cider vinegar.

Identifying economics' place amongst academic disciplines: a science or a social science?

PubMed

Hudson, John

2017-01-01

Different academic disciplines exhibit different styles, including styles in journal titles. Using data from the 2014 Research Excellence Framework (REF) in the UK we are able to identify the stylistic trends of different disciplines using 155,552 journal titles across all disciplines. Cluster analysis is then used to group the different disciplines together. The resulting identification fits the social sciences, the sciences and the arts and humanities reasonably well. Economics overall, fits best with philosophy, but the linkage is weak. When we divided economics into papers published in theory, econometrics and the remaining journals, the first two link with mathematics and computer science, particularly econometrics, and thence the sciences. The rest of economics then links with business and thence the social sciences.

[RAPD analysis of four species of Cuscuta in Shandong Province].

PubMed

Lin, Huibin; Lin, Jianqun; Lin, Jianqiang

2003-01-01

To explore the genome difference of four species of Cuscuta in different hosts. RAPD was used by 50 primers. Four species of genus Cuscuta can be identified by 8 primers. Both Cuscuta chinensis and C. australis from Subg. Grammica had 3 bands whose molecular weights were 1.3 kb, 1.45 kb and 1.53 kb respectively. C. japonica and C. lupuliformis from Subg. Monogyna had a 1.48 kb specific band. Cuscuta of same subgenus had similar RAPD result and close genetic relationship. Same species of Cuscuta in different hosts showed DNA polymorphism. It indicated that hosts can affect genome of Cuscuta to some extent. RAPD can be used to identify the species of Cuscuta or same Cuscuta in different hosts.

Proteomic analysis of human dental cementum and alveolar bone.

PubMed

Salmon, Cristiane R; Tomazela, Daniela M; Ruiz, Karina Gonzales Silvério; Foster, Brian L; Paes Leme, Adriana Franco; Sallum, Enilson Antonio; Somerman, Martha J; Nociti, Francisco H

2013-10-08

Dental cementum (DC) is a bone-like tissue covering the tooth root and responsible for attaching the tooth to the alveolar bone (AB) via the periodontal ligament (PDL). Studies have unsuccessfully tried to identify factors specific to DC versus AB, in an effort to better understand DC development and regeneration. The present study aimed to use matched human DC and AB samples (n=7) to generate their proteomes for comparative analysis. Bone samples were harvested from tooth extraction sites, whereas DC samples were obtained from the apical root portion of extracted third molars. Samples were denatured, followed by protein extraction reduction, alkylation and digestion for analysis by nanoAcquity HPLC system and LTQ-FT Ultra. Data analysis demonstrated that a total of 318 proteins were identified in AB and DC. In addition to shared proteins between these tissues, 105 and 83 proteins exclusive to AB or DC were identified, respectively. This is the first report analyzing the proteomic composition of human DC matrix and identifying putative unique and enriched proteins in comparison to alveolar bone. These findings may provide novel insights into developmental differences between DC and AB, and identify candidate biomarkers that may lead to more efficient and predictable therapies for periodontal regeneration. Periodontal disease is a highly prevalent disease affecting the world population, which involves breakdown of the tooth supporting tissues, the periodontal ligament, alveolar bone, and dental cementum. The lack of knowledge on specific factors that differentiate alveolar bone and dental cementum limits the development of more efficient and predictable reconstructive therapies. In order to better understand cementum development and potentially identify factors to improve therapeutic outcomes, we took the unique approach of using matched patient samples of dental cementum and alveolar bone to generate and compare a proteome list for each tissue. A potential biomarker for dental cementum was identified, superoxide dismutase 3 (SOD3), which is found in cementum and cementum-associated cells in mouse, pig, and human tissues. These findings may provide novel insights into developmental differences between alveolar bone and dental cementum, and represent the basis for improved and more predictable therapies. © 2013.

Data Mining of Network Logs

NASA Technical Reports Server (NTRS)

Collazo, Carlimar

2011-01-01

The statement of purpose is to analyze network monitoring logs to support the computer incident response team. Specifically, gain a clear understanding of the Uniform Resource Locator (URL) and its structure, and provide a way to breakdown a URL based on protocol, host name domain name, path, and other attributes. Finally, provide a method to perform data reduction by identifying the different types of advertisements shown on a webpage for incident data analysis. The procedures used for analysis and data reduction will be a computer program which would analyze the URL and identify and advertisement links from the actual content links.

On the identifiability of inertia parameters of planar Multi-Body Space Systems

NASA Astrophysics Data System (ADS)

Nabavi-Chashmi, Seyed Yaser; Malaek, Seyed Mohammad-Bagher

2018-04-01

This work describes a new formulation to study the identifiability characteristics of Serially Linked Multi-body Space Systems (SLMBSS). The process exploits the so called "Lagrange Formulation" to develop a linear form of Equations of Motion w.r.t the system Inertia Parameters (IPs). Having developed a specific form of regressor matrix, we aim to expedite the identification process. The new approach allows analytical as well as numerical identification and identifiability analysis for different SLMBSSs' configurations. Moreover, the explicit forms of SLMBSSs identifiable parameters are derived by analyzing the identifiability characteristics of the robot. We further show that any SLMBSS designed with Variable Configurations Joint allows all IPs to be identifiable through comparing two successive identification outcomes. This feature paves the way to design new class of SLMBSS for which accurate identification of all IPs is at hand. Different case studies reveal that proposed formulation provides fast and accurate results, as required by the space applications. Further studies might be necessary for cases where planar-body assumption becomes inaccurate.

Advances in Instrumental Analysis of Brominated Flame Retardants: Current Status and Future Perspectives

PubMed Central

2014-01-01

This review aims to highlight the recent advances and methodological improvements in instrumental techniques applied for the analysis of different brominated flame retardants (BFRs). The literature search strategy was based on the recent analytical reviews published on BFRs. The main selection criteria involved the successful development and application of analytical methods for determination of the target compounds in various environmental matrices. Different factors affecting chromatographic separation and mass spectrometric detection of brominated analytes were evaluated and discussed. Techniques using advanced instrumentation to achieve outstanding results in quantification of different BFRs and their metabolites/degradation products were highlighted. Finally, research gaps in the field of BFR analysis were identified and recommendations for future research were proposed. PMID:27433482

The Analysis of High School Students' Conceptions of Learning in Different Domains

ERIC Educational Resources Information Center

Sadi, Özlem

2015-01-01

The purpose of this study is to investigate whether or not conceptions of learning diverge in different science domains by identifying high school students' conceptions of learning in physics, chemistry and biology. The Conceptions of Learning Science (COLS) questionnaire was adapted for physics (Conceptions of Learning Physics, COLP), chemistry…

Sensory Clusters of Toddlers with Autism Spectrum Disorders: Differences in Affective Symptoms

ERIC Educational Resources Information Center

Ben-Sasson, A.; Cermak, S. A.; Orsmond, G. I.; Tager-Flusberg, H.; Kadlec, M. B.; Carter, A. S.

2008-01-01

Background: Individuals with autism spectrum disorders (ASDs) show variability in their sensory behaviors. In this study we identified clusters of toddlers with ASDs who shared sensory profiles and examined differences in affective symptoms across these clusters. Method: Using cluster analysis 170 toddlers with ASDs were grouped based on parent…

Identifying Differences in Early Mathematical Skills among Children in Head Start

ERIC Educational Resources Information Center

Wu, Qiong; Lei, Pui-wa; DiPerna, James C.; Morgan, Paul L.; Reid, Erin E.

2015-01-01

The purpose of this study was to examine early mathematical skill differences among preschool children in US Head Start classrooms. Latent class analysis based on six early mathematical subtest scores (i.e. counting aloud, measurement, counting objects, numbers and shapes, pattern recognition, and grouping) from a sample of 279 Head Start children…

Career Coping Styles: Differences in Career Attitudes among Secondary School Students

ERIC Educational Resources Information Center

Janeiro, Isabel N.; Marques, Jose Ferreira

2010-01-01

The types of difficulties associated with career attitudes were studied using Super's model of career maturity (1990) in a group of 620 Portuguese students from grades 9 and 12. A cluster analysis identified four styles with different patterns of association between time perspective, attributional beliefs, self-esteem and career attitudes. The…

An Analysis of State Autism Educational Assessment Practices and Requirements

ERIC Educational Resources Information Center

Barton, Erin E.; Harris, Bryn; Leech, Nancy; Stiff, Lillian; Choi, Gounah; Joel, Tiffany

2016-01-01

States differ in the procedures and criteria used to identify ASD. These differences are likely to impact the prevalence and age of identification for children with ASD. The purpose of the current study was to examine the specific state variations in ASD identification and eligibility criteria requirements. We examined variations by state in…

An Analysis of Learned Helplessness: Continuous Changes in Performance, Strategy, and Achievement Cognitions Following Failure

ERIC Educational Resources Information Center

Diener, Carol I.; Dweck, Carol S.

1978-01-01

Two studies examined the cognitive-motivational differences between helpless and mastery-oriented children by analyzing the effects of failure feedback on problem solving strategies during testing and identifying semantic differences in children's verbalizations following failure on task. Subjects were fifth graders of both sexes. (CM)

DEVELOPING A NATIONALLY CONSISTENT APPROACH FOR ASSESSING REGIONAL ASSOCIATIONS BETWEEN NUTRIENTS AND BENTHIC BIOLOGICAL CONDITION IN ESTUARINE WATERS. AN ANALYSIS USING NATIONAL COASTAL ASSESSMENT DATA

EPA Science Inventory

Identifying candidate water quality criteria in estuarine waters is confounded by differences among estuaries and biogeographic regions. Dealing with these differences is paramount to successfully addressing estuarine water quality impairment. As such, we outline an approach to...

All Different or All the Same? Exploring the Diversity of Professional Practices in Portuguese School Psychology

ERIC Educational Resources Information Center

Mendes, Sofia A.; Lasser, Jon; Abreu-Lima, Isabel M.; Almeida, Leandro S.

2017-01-01

Studies have generally characterized school psychologists as a relative homogenous population. Understanding the differences in professional practices and related variables is important for the development of the profession. Using a sample of 446 Portuguese school psychologists, this study used cluster analysis to identify distinct profiles of…

Analysis of non-Saccharomyces yeast populations isolated from grape musts from Sicily (Italy).

PubMed

Romancino, D P; Di Maio, S; Muriella, R; Oliva, D

2008-12-01

The aim of this study was to identify the non-Saccharomyces yeast populations present in the grape must microflora from wineries from different areas around the island of Sicily. Yeasts identification was conducted on 2575 colonies isolated from six musts, characterized using Wallerstein Laboratory (WL) nutrient agar, restriction analysis of the amplified 5.8S-internal transcribed spacer region and restriction profiles of amplified 26S rDNA. In those colonies, we identified 11 different yeast species originating from wine musts from two different geographical areas of the island of Sicily. We isolated non-Saccharomyces yeasts and described the microflora in grape musts from different areas of Sicily. Moreover, we discovered two new colony morphologies for yeasts on WL agar never previously described. This investigation is a first step in understanding the distribution of non-Saccharomyces yeasts in grape musts from Sicily. The contribution is important as a tool for monitoring the microflora in grape musts and for establishing a new non-Saccharomyces yeast collection; in the future, this collection will be used for understanding the significance of these yeasts in oenology.

Rett syndrome treatment in mouse models: searching for effective targets and strategies.

PubMed

Ricceri, Laura; De Filippis, Bianca; Laviola, Giovanni

2013-05-01

Rett syndrome (RTT) is a pervasive developmental disorder, primarily affecting girls with a prevalence of 1 in every 10,000 births; it represents the second most common cause of intellectual disability in females. Mutations in the gene encoding methyl-CpG-binding protein 2 (MECP2) have been identified as clear etiological factors in more than 90% of classical RTT cases. Whereas the mechanisms leading to the severe, progressive and specific neurological dysfunctions when this gene is mutated still remain to be elucidated, a series of different mouse models have been generated, bearing different Mecp2 mutation. Neurobehavioural analysis in these mouse lines have been carried out and phenotyping analysis can be now utilised to preclinically evaluate the effects of potential RTT treatments. This review summarizes the different results achieved in this research field taking into account different key targets identified to ameliorate RTT phenotype in mouse models, including those not directly downstream of MeCP2 and those limited to the early phases of postnatal development. This article is part of the Special Issue entitled 'Neurodevelopmental Disorders'. Copyright © 2012 Elsevier Ltd. All rights reserved.

Classification of juices and fermented beverages made from unripe, ripe and senescent apples based on the aromatic profile using chemometrics.

PubMed

Braga, Cíntia Maia; Zielinski, Acácio Antonio Ferreira; Silva, Karolline Marques da; de Souza, Frederico Koch Fernandes; Pietrowski, Giovana de Arruda Moura; Couto, Marcelo; Granato, Daniel; Wosiacki, Gilvan; Nogueira, Alessandro

2013-11-15

The aim of this study was to assess differences between apple juices and fermented apple beverages elaborated with fruits from different varieties and at different ripening stages in the aroma profile by using chemometrics. Ripening influenced the aroma composition of the apple juice and fermented apple. For all varieties, senescent fruits provided more aromatic fermented apple beverages. However, no significant difference was noticed in samples made of senescent or ripe fruits of the Lisgala variety. Regarding the juices, ripe Gala apple had the highest total aroma concentration. Ethanal was the major compound identified in all the samples, with values between 11.83mg/L (unripe Lisgala juice) and 81.05mg/L (ripe Gala juice). 3-Methyl-1-butanol was the major compound identified in the fermented juices. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were applied and classified the juices and fermented juices based on physicochemical and aroma profile, demonstrating their applicability as tools to monitor the quality of apple-based products. Copyright © 2013 Elsevier Ltd. All rights reserved.

Recent findings and technological advances in phosphoproteomics for cells and tissues.

PubMed

von Stechow, Louise; Francavilla, Chiara; Olsen, Jesper V

2015-01-01

Site-specific phosphorylation is a fast and reversible covalent post-translational modification that is tightly regulated in cells. The cellular machinery of enzymes that write, erase and read these modifications (kinases, phosphatases and phospho-binding proteins) is frequently deregulated in different diseases, including cancer. Large-scale studies of phosphoproteins - termed phosphoproteomics - strongly rely on the use of high-performance mass spectrometric instrumentation. This powerful technology has been applied to study a great number of phosphorylation-based phenotypes. Nevertheless, many technical and biological challenges have to be overcome to identify biologically relevant phosphorylation sites in cells and tissues. This review describes different technological strategies to identify and quantify phosphorylation sites with high accuracy, without significant loss of analysis speed and reproducibility in tissues and cells. Moreover, computational tools for analysis, integration and biological interpretation of phosphorylation events are discussed.

Parent–Child Relationships in Stepfather Families and Adolescent Adjustment: A Latent Class Analysis

PubMed Central

Amato, Paul R.; King, Valarie; Thorsen, Maggie L.

2015-01-01

In the current study the authors drew on Waves I and III from Add Health to examine the closeness of parent–adolescent relationships in married mother–stepfather families (N = 1,934). They used latent class analysis to identify family constellations defined by adolescents’ relationships with all of their parents: mothers, stepfathers, and biological nonresident fathers. In particular, the authors (a) identified the most common underlying patterns of adolescent–parent relationships in stepfamilies; (b) determined the background characteristics that predict membership in these groups; and (c) examined how adolescents in these groups fare with respect to depressive symptoms, delinquency, and substance use. The results indicate that adolescents’ relationships can be represented with 4 latent classes. Adolescents in these classes differ on measures of adjustment, and many of these differences persist into the early adult years. PMID:27022199

Melissopalynological Characterization of North Algerian Honeys

PubMed Central

Nair, Samira; Meddah, Boumedienne; Aoues, Abdelkader

2013-01-01

A pollen analysis of Algerian honey was conducted on a total of 10 honey samples. The samples were prepared using the methodology described by Louveaux et al., that was then further adapted by Ohe et al. The samples were subsequently observed using light microscopy. A total of 36 pollen taxa were discovered and could be identified in the analyzed honey samples. Seventy percent of the studied samples belonged to the group ofmonofloral honeys represented by Eucalyptus globulus, Thymus vulgaris, Citrus sp. and Lavandula angustifolia. Multifloral honeys comprised 30% of the honey samples, with pollen grains of Lavandula stoechas (28.49%) standing out as the most prevalent. Based on cluster analysis, two different groups of honey were observed according to different pollen types found in the samples. The identified pollen spectrum of honey confirmed their botanical origin. PMID:28239099

Identification of novel BRCA founder mutations in Middle Eastern breast cancer patients using capture and Sanger sequencing analysis.

PubMed

Bu, Rong; Siraj, Abdul K; Al-Obaisi, Khadija A S; Beg, Shaham; Al Hazmi, Mohsen; Ajarim, Dahish; Tulbah, Asma; Al-Dayel, Fouad; Al-Kuraya, Khawla S

2016-09-01

Ethnic differences of breast cancer genomics have prompted us to investigate the spectra of BRCA1 and BRCA2 mutations in different populations. The prevalence and effect of BRCA 1 and BRCA 2 mutations in Middle Eastern population is not fully explored. To characterize the prevalence of BRCA mutations in Middle Eastern breast cancer patients, BRCA mutation screening was performed in 818 unselected breast cancer patients using Capture and/or Sanger sequencing. 19 short tandem repeat (STR) markers were used for founder mutation analysis. In our study, nine different types of deleterious mutation were identified in 28 (3.4%) cases, 25 (89.3%) cases in BRCA 1 and 3 (10.7%) cases in BRCA 2. Seven recurrent mutations identified accounted for 92.9% (26/28) of all the mutant cases. Haplotype analysis was performed to confirm c.1140 dupG and c.4136_4137delCT mutations as novel putative founder mutation, accounting for 46.4% (13/28) of all BRCA mutant cases and 1.6% (13/818) of all the breast cancer cases, respectively. Moreover, BRCA 1 mutation was significantly associated with BRCA 1 protein expression loss (p = 0.0005). Our finding revealed that a substantial number of BRCA mutations were identified in clinically high risk breast cancer from Middle East region. Identification of the mutation spectrum, prevalence and founder effect in Middle Eastern population facilitates genetic counseling, risk assessment and development of cost-effective screening strategy. © 2016 UICC.