Descriptive Analysis in Education: A Guide for Researchers. NCEE 2017-4023

ERIC Educational Resources Information Center

Loeb, Susanna; Dynarski, Susan; McFarland, Daniel; Morris, Pamela; Reardon, Sean; Reber, Sarah

2017-01-01

Whether the goal is to identify and describe trends and variation in populations, create new measures of key phenomena, or describe samples in studies aimed at identifying causal effects, description plays a critical role in the scientific process in general and education research in particular. Descriptive analysis identifies patterns in data to…

Filtrates and Residues: Qualitative Analysis of Some Transition Metals.

ERIC Educational Resources Information Center

Kilner, Cary

1985-01-01

Describes a qualitative analysis laboratory in which students examine specific precipitates that can be used to identify copper, cobalt, nickel, and iron cations. The objective of the laboratory is to determine which test or sequence of tests unambiguously identifies each cation and to use the results to identify several unknowns. (JN)

Human Factors Process Task Analysis: Liquid Oxygen Pump Acceptance Test Procedure at the Advanced Technology Development Center

NASA Technical Reports Server (NTRS)

Diorio, Kimberly A.; Voska, Ned (Technical Monitor)

2002-01-01

This viewgraph presentation provides information on Human Factors Process Failure Modes and Effects Analysis (HF PFMEA). HF PFMEA includes the following 10 steps: Describe mission; Define System; Identify human-machine; List human actions; Identify potential errors; Identify factors that effect error; Determine likelihood of error; Determine potential effects of errors; Evaluate risk; Generate solutions (manage error). The presentation also describes how this analysis was applied to a liquid oxygen pump acceptance test.

Dan Says - Continuum Magazine | NREL

Science.gov Websites

vital role of providing technology-neutral analysis to ensure that innovations developed in the lab fit success-and NREL analysis is playing a major role. We are also identifying the connections among energy and financial front, NREL analysis leadership is helping to identify and overcome barriers with

Rumen fluid metabolomics analysis associated with feed efficiency on crossbred steers

USDA-ARS?s Scientific Manuscript database

The rumen has 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 fluid metabolomic analysis by LC-MS and multivariate/univariate statistical analysis were used to identify differences in r...

Chemical Discrimination of Cortex Phellodendri amurensis and Cortex Phellodendri chinensis by Multivariate Analysis Approach.

PubMed

Sun, Hui; Wang, Huiyu; Zhang, Aihua; Yan, Guangli; Han, Ying; Li, Yuan; Wu, Xiuhong; Meng, Xiangcai; Wang, Xijun

2016-01-01

As herbal medicines have an important position in health care systems worldwide, their current assessment, and quality control are a major bottleneck. Cortex Phellodendri chinensis (CPC) and Cortex Phellodendri amurensis (CPA) are widely used in China, however, how to identify species of CPA and CPC has become urgent. In this study, multivariate analysis approach was performed to the investigation of chemical discrimination of CPA and CPC. Principal component analysis showed that two herbs could be separated clearly. The chemical markers such as berberine, palmatine, phellodendrine, magnoflorine, obacunone, and obaculactone were identified through the orthogonal partial least squared discriminant analysis, and were identified tentatively by the accurate mass of quadruple-time-of-flight mass spectrometry. A total of 29 components can be used as the chemical markers for discrimination of CPA and CPC. Of them, phellodenrine is significantly higher in CPC than that of CPA, whereas obacunone and obaculactone are significantly higher in CPA than that of CPC. The present study proves that multivariate analysis approach based chemical analysis greatly contributes to the investigation of CPA and CPC, and showed that the identified chemical markers as a whole should be used to discriminate the two herbal medicines, and simultaneously the results also provided chemical information for their quality assessment. Multivariate analysis approach was performed to the investigate the herbal medicineThe chemical markers were identified through multivariate analysis approachA total of 29 components can be used as the chemical markers. UPLC-Q/TOF-MS-based multivariate analysis method for the herbal medicine samples Abbreviations used: CPC: Cortex Phellodendri chinensis, CPA: Cortex Phellodendri amurensis, PCA: Principal component analysis, OPLS-DA: Orthogonal partial least squares discriminant analysis, BPI: Base peaks ion intensity.

Sensitivity of BRCA1/2 testing in high-risk breast/ovarian/male breast cancer families: little contribution of comprehensive RNA/NGS panel testing.

PubMed

Byers, Helen; Wallis, Yvonne; van Veen, Elke M; Lalloo, Fiona; Reay, Kim; Smith, Philip; Wallace, Andrew J; Bowers, Naomi; Newman, William G; Evans, D Gareth

2016-11-01

The sensitivity of testing BRCA1 and BRCA2 remains unresolved as the frequency of deep intronic splicing variants has not been defined in high-risk familial breast/ovarian cancer families. This variant category is reported at significant frequency in other tumour predisposition genes, including NF1 and MSH2. We carried out comprehensive whole gene RNA analysis on 45 high-risk breast/ovary and male breast cancer families with no identified pathogenic variant on exonic sequencing and copy number analysis of BRCA1/2. In addition, we undertook variant screening of a 10-gene high/moderate risk breast/ovarian cancer panel by next-generation sequencing. DNA testing identified the causative variant in 50/56 (89%) breast/ovarian/male breast cancer families with Manchester scores of ≥50 with two variants being confirmed to affect splicing on RNA analysis. RNA sequencing of BRCA1/BRCA2 on 45 individuals from high-risk families identified no deep intronic variants and did not suggest loss of RNA expression as a cause of lost sensitivity. Panel testing in 42 samples identified a known RAD51D variant, a high-risk ATM variant in another breast ovary family and a truncating CHEK2 mutation. Current exonic sequencing and copy number analysis variant detection methods of BRCA1/2 have high sensitivity in high-risk breast/ovarian cancer families. Sequence analysis of RNA does not identify any variants undetected by current analysis of BRCA1/2. However, RNA analysis clarified the pathogenicity of variants of unknown significance detected by current methods. The low diagnostic uplift achieved through sequence analysis of the other known breast/ovarian cancer susceptibility genes indicates that further high-risk genes remain to be identified.

Combined approach for finding susceptibility genes in DISH/chondrocalcinosis families: whole-genome-wide linkage and IBS/IBD studies.

PubMed

Couto, Ana Rita; Parreira, Bruna; Thomson, Russell; Soares, Marta; Power, Deborah M; Stankovich, Jim; Armas, Jácome Bruges; Brown, Matthew A

2017-01-01

Twelve families with exuberant and early-onset calcium pyrophosphate dehydrate chondrocalcinosis (CC) and diffuse idiopathic skeletal hyperostosis (DISH), hereafter designated DISH/CC, were identified in Terceira Island, the Azores, Portugal. Ninety-two (92) individuals from these families were selected for whole-genome-wide linkage analysis. An identity-by-descent (IBD) analysis was performed in 10 individuals from 5 of the investigated pedigrees. The chromosome area with the maximal logarithm of the odds score (1.32; P =0.007) was not identified using the IBD/identity-by-state (IBS) analysis; therefore, it was not investigated further. From the IBD/IBS analysis, two candidate genes, LEMD3 and RSPO4 , were identified and sequenced. Nine genetic variants were identified in the RSPO4 gene; one regulatory variant (rs146447064) was significantly more frequent in control individuals than in DISH/CC patients ( P =0.03). Four variants were identified in LEMD3 , and the rs201930700 variant was further investigated using segregation analysis. None of the genetic variants in RSPO4 or LEMD3 segregated within the studied families. Therefore, although a major genetic effect was shown to determine DISH/CC occurrence within these families, the specific genetic variants involved were not identified.

Combined approach for finding susceptibility genes in DISH/chondrocalcinosis families: whole-genome-wide linkage and IBS/IBD studies

PubMed Central

Couto, Ana Rita; Parreira, Bruna; Thomson, Russell; Soares, Marta; Power, Deborah M; Stankovich, Jim; Armas, Jácome Bruges; Brown, Matthew A

2017-01-01

Twelve families with exuberant and early-onset calcium pyrophosphate dehydrate chondrocalcinosis (CC) and diffuse idiopathic skeletal hyperostosis (DISH), hereafter designated DISH/CC, were identified in Terceira Island, the Azores, Portugal. Ninety-two (92) individuals from these families were selected for whole-genome-wide linkage analysis. An identity-by-descent (IBD) analysis was performed in 10 individuals from 5 of the investigated pedigrees. The chromosome area with the maximal logarithm of the odds score (1.32; P=0.007) was not identified using the IBD/identity-by-state (IBS) analysis; therefore, it was not investigated further. From the IBD/IBS analysis, two candidate genes, LEMD3 and RSPO4, were identified and sequenced. Nine genetic variants were identified in the RSPO4 gene; one regulatory variant (rs146447064) was significantly more frequent in control individuals than in DISH/CC patients (P=0.03). Four variants were identified in LEMD3, and the rs201930700 variant was further investigated using segregation analysis. None of the genetic variants in RSPO4 or LEMD3 segregated within the studied families. Therefore, although a major genetic effect was shown to determine DISH/CC occurrence within these families, the specific genetic variants involved were not identified. PMID:29104755

Targeted Analysis of Whole Genome Sequence Data to Diagnose Genetic Cardiomyopathy

DOE PAGES

Golbus, Jessica R.; Puckelwartz, Megan J.; Dellefave-Castillo, Lisa; ...

2014-09-01

Background—Cardiomyopathy is highly heritable but genetically diverse. At present, genetic testing for cardiomyopathy uses targeted sequencing to simultaneously assess the coding regions of more than 50 genes. New genes are routinely added to panels to improve the diagnostic yield. With the anticipated $1000 genome, it is expected that genetic testing will shift towards comprehensive genome sequencing accompanied by targeted gene analysis. Therefore, we assessed the reliability of whole genome sequencing and targeted analysis to identify cardiomyopathy variants in 11 subjects with cardiomyopathy. Methods and Results—Whole genome sequencing with an average of 37× coverage was combined with targeted analysis focused onmore » 204 genes linked to cardiomyopathy. Genetic variants were scored using multiple prediction algorithms combined with frequency data from public databases. This pipeline yielded 1-14 potentially pathogenic variants per individual. Variants were further analyzed using clinical criteria and/or segregation analysis. Three of three previously identified primary mutations were detected by this analysis. In six subjects for whom the primary mutation was previously unknown, we identified mutations that segregated with disease, had clinical correlates, and/or had additional pathological correlation to provide evidence for causality. For two subjects with previously known primary mutations, we identified additional variants that may act as modifiers of disease severity. In total, we identified the likely pathological mutation in 9 of 11 (82%) subjects. We conclude that these pilot data demonstrate that ~30-40× coverage whole genome sequencing combined with targeted analysis is feasible and sensitive to identify rare variants in cardiomyopathy-associated genes.« less

76 FR 18510 - Notice of Request for Extension of Approval of an Information Collection; Gypsy Moth...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-04

... Development Center in Massachusetts so that it can be correctly identified through DNA analysis. (Since the... distinguished from each other. DNA analysis is the only way to accurately identify these insects.) The PPQ or... regulatory officials to identify and track specific specimens through the DNA identification tests that we...

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.

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

Golbus, Jessica R.; Puckelwartz, Megan J.; Dellefave-Castillo, Lisa

Background—Cardiomyopathy is highly heritable but genetically diverse. At present, genetic testing for cardiomyopathy uses targeted sequencing to simultaneously assess the coding regions of more than 50 genes. New genes are routinely added to panels to improve the diagnostic yield. With the anticipated $1000 genome, it is expected that genetic testing will shift towards comprehensive genome sequencing accompanied by targeted gene analysis. Therefore, we assessed the reliability of whole genome sequencing and targeted analysis to identify cardiomyopathy variants in 11 subjects with cardiomyopathy. Methods and Results—Whole genome sequencing with an average of 37× coverage was combined with targeted analysis focused onmore » 204 genes linked to cardiomyopathy. Genetic variants were scored using multiple prediction algorithms combined with frequency data from public databases. This pipeline yielded 1-14 potentially pathogenic variants per individual. Variants were further analyzed using clinical criteria and/or segregation analysis. Three of three previously identified primary mutations were detected by this analysis. In six subjects for whom the primary mutation was previously unknown, we identified mutations that segregated with disease, had clinical correlates, and/or had additional pathological correlation to provide evidence for causality. For two subjects with previously known primary mutations, we identified additional variants that may act as modifiers of disease severity. In total, we identified the likely pathological mutation in 9 of 11 (82%) subjects. We conclude that these pilot data demonstrate that ~30-40× coverage whole genome sequencing combined with targeted analysis is feasible and sensitive to identify rare variants in cardiomyopathy-associated genes.« less

Identifying the relevant features of the National Digital Cadastral Database (NDCDB) for spatial analysis by using the Delphi Technique

NASA Astrophysics Data System (ADS)

Halim, N. Z. A.; Sulaiman, S. A.; Talib, K.; Ng, E. G.

2018-02-01

This paper explains the process carried out in identifying the relevant features of the National Digital Cadastral Database (NDCDB) for spatial analysis. The research was initially a part of a larger research exercise to identify the significance of NDCDB from the legal, technical, role and land-based analysis perspectives. The research methodology of applying the Delphi technique is substantially discussed in this paper. A heterogeneous panel of 14 experts was created to determine the importance of NDCDB from the technical relevance standpoint. Three statements describing the relevant features of NDCDB for spatial analysis were established after three rounds of consensus building. It highlighted the NDCDB’s characteristics such as its spatial accuracy, functions, and criteria as a facilitating tool for spatial analysis. By recognising the relevant features of NDCDB for spatial analysis in this study, practical application of NDCDB for various analysis and purpose can be widely implemented.

Tissue Non-Specific Genes and Pathways Associated with Diabetes: An Expression Meta-Analysis.

PubMed

Mei, Hao; Li, Lianna; Liu, Shijian; Jiang, Fan; Griswold, Michael; Mosley, Thomas

2017-01-21

We performed expression studies to identify tissue non-specific genes and pathways of diabetes by meta-analysis. We searched curated datasets of the Gene Expression Omnibus (GEO) database and identified 13 and five expression studies of diabetes and insulin responses at various tissues, respectively. We tested differential gene expression by empirical Bayes-based linear method and investigated gene set expression association by knowledge-based enrichment analysis. Meta-analysis by different methods was applied to identify tissue non-specific genes and gene sets. We also proposed pathway mapping analysis to infer functions of the identified gene sets, and correlation and independent analysis to evaluate expression association profile of genes and gene sets between studies and tissues. Our analysis showed that PGRMC1 and HADH genes were significant over diabetes studies, while IRS1 and MPST genes were significant over insulin response studies, and joint analysis showed that HADH and MPST genes were significant over all combined data sets. The pathway analysis identified six significant gene sets over all studies. The KEGG pathway mapping indicated that the significant gene sets are related to diabetes pathogenesis. The results also presented that 12.8% and 59.0% pairwise studies had significantly correlated expression association for genes and gene sets, respectively; moreover, 12.8% pairwise studies had independent expression association for genes, but no studies were observed significantly different for expression association of gene sets. Our analysis indicated that there are both tissue specific and non-specific genes and pathways associated with diabetes pathogenesis. Compared to the gene expression, pathway association tends to be tissue non-specific, and a common pathway influencing diabetes development is activated through different genes at different tissues.

Regression Analysis of Physician Distribution to Identify Areas of Need: Some Preliminary Findings.

ERIC Educational Resources Information Center

Morgan, Bruce B.; And Others

A regression analysis was conducted of factors that help to explain the variance in physician distribution and which identify those factors that influence the maldistribution of physicians. Models were developed for different geographic areas to determine the most appropriate unit of analysis for the Western Missouri Area Health Education Center…

False Positive Functional Analysis Results as a Contributor of Treatment Failure during Functional Communication Training

ERIC Educational Resources Information Center

Mann, Amanda J.; Mueller, Michael M.

2009-01-01

Research has shown that functional analysis results are beneficial for treatment selection because they identify reinforcers for severe behavior that can then be used to reinforce replacement behaviors either differentially or noncontingently. Theoretically then, if a reinforcer is identified in a functional analysis erroneously, a well researched…

On the Use of Principal Component and Spectral Density Analysis to Evaluate the Community Multiscale Air Quality (CMAQ) Model

EPA Science Inventory

A 5 year (2002-2006) simulation of CMAQ covering the eastern United States is evaluated using principle component analysis in order to identify and characterize statistically significant patterns of model bias. Such analysis is useful in that in can identify areas of poor model ...

Lay Worker Health Literacy: A Concept Analysis and Operational Definition.

PubMed

Cadman, Kathleen Paco

2017-10-01

The concept of lay worker health literacy is created by concurrently analyzing and synthesizing two intersecting concepts, lay workers and health literacy. Articulation of this unique intersection is the result of implementing a simplified Wilson's Concept Analysis Procedure. This process incorporates the following components: a) selecting a concept, b) determining the aims/purposes of analysis, c) identifying all uses of the concept, d) determining defining attributes, e) identifying a model case, f) identifying borderline, related, contrary, and illegitimate cases, g) identifying antecedents and consequences, and h) defining empirical referents. Furthermore, as current literature provides no operational definition for lay worker health literacy, one is created to contribute cohesion to the concept. © 2017 Wiley Periodicals, Inc.

Phylogeographical analysis of the dominant multidrug-resistant H58 clade of Salmonella Typhi identifies inter- and intracontinental transmission events.

PubMed

Wong, Vanessa K; Baker, Stephen; Pickard, Derek J; Parkhill, Julian; Page, Andrew J; Feasey, Nicholas A; Kingsley, Robert A; Thomson, Nicholas R; Keane, Jacqueline A; Weill, François-Xavier; Edwards, David J; Hawkey, Jane; Harris, Simon R; Mather, Alison E; Cain, Amy K; Hadfield, James; Hart, Peter J; Thieu, Nga Tran Vu; Klemm, Elizabeth J; Glinos, Dafni A; Breiman, Robert F; Watson, Conall H; Kariuki, Samuel; Gordon, Melita A; Heyderman, Robert S; Okoro, Chinyere; Jacobs, Jan; Lunguya, Octavie; Edmunds, W John; Msefula, Chisomo; Chabalgoity, Jose A; Kama, Mike; Jenkins, Kylie; Dutta, Shanta; Marks, Florian; Campos, Josefina; Thompson, Corinne; Obaro, Stephen; MacLennan, Calman A; Dolecek, Christiane; Keddy, Karen H; Smith, Anthony M; Parry, Christopher M; Karkey, Abhilasha; Mulholland, E Kim; Campbell, James I; Dongol, Sabina; Basnyat, Buddha; Dufour, Muriel; Bandaranayake, Don; Naseri, Take Toleafoa; Singh, Shalini Pravin; Hatta, Mochammad; Newton, Paul; Onsare, Robert S; Isaia, Lupeoletalalei; Dance, David; Davong, Viengmon; Thwaites, Guy; Wijedoru, Lalith; Crump, John A; De Pinna, Elizabeth; Nair, Satheesh; Nilles, Eric J; Thanh, Duy Pham; Turner, Paul; Soeng, Sona; Valcanis, Mary; Powling, Joan; Dimovski, Karolina; Hogg, Geoff; Farrar, Jeremy; Holt, Kathryn E; Dougan, Gordon

2015-06-01

The emergence of multidrug-resistant (MDR) typhoid is a major global health threat affecting many countries where the disease is endemic. Here whole-genome sequence analysis of 1,832 Salmonella enterica serovar Typhi (S. Typhi) identifies a single dominant MDR lineage, H58, that has emerged and spread throughout Asia and Africa over the last 30 years. Our analysis identifies numerous transmissions of H58, including multiple transfers from Asia to Africa and an ongoing, unrecognized MDR epidemic within Africa itself. Notably, our analysis indicates that H58 lineages are displacing antibiotic-sensitive isolates, transforming the global population structure of this pathogen. H58 isolates can harbor a complex MDR element residing either on transmissible IncHI1 plasmids or within multiple chromosomal integration sites. We also identify new mutations that define the H58 lineage. This phylogeographical analysis provides a framework to facilitate global management of MDR typhoid and is applicable to similar MDR lineages emerging in other bacterial species.

Data from quantitative label free proteomics analysis of rat spleen.

PubMed

Dudekula, Khadar; Le Bihan, Thierry

2016-09-01

The dataset presented in this work has been obtained using a label-free quantitative proteomic analysis of rat spleen. A robust method for extraction of proteins from rat spleen tissue and LC-MS-MS analysis was developed using a urea and SDS-based buffer. Different fractionation methods were compared. A total of 3484 different proteins were identified from the pool of all experiments run in this study (a total of 2460 proteins with at least two peptides). A total of 1822 proteins were identified from nine non-fractionated pulse gels, 2288 proteins and 2864 proteins were identified by SDS-PAGE fractionation into three and five fractions respectively. The proteomics data are deposited in ProteomeXchange Consortium via PRIDE PXD003520, Progenesis and Maxquant output are presented in the supported information. The generated list of proteins under different regimes of fractionation allow assessing the nature of the identified proteins; variability in the quantitative analysis associated with the different sampling strategy and allow defining a proper number of replicates for future quantitative analysis.

Phylogeographical analysis of the dominant multidrug-resistant H58 clade of Salmonella Typhi identifies inter- and intracontinental transmission events

PubMed Central

Wong, Vanessa K; Baker, Stephen; Pickard, Derek J; Parkhill, Julian; Page, Andrew J; Feasey, Nicholas A; Kingsley, Robert A; Thomson, Nicholas R; Keane, Jacqueline A; Weill, François-Xavier; Edwards, David J; Hawkey, Jane; Harris, Simon R; Mather, Alison E; Cain, Amy K; Hadfield, James; Hart, Peter J; Thieu, Nga Tran Vu; Klemm, Elizabeth J; Glinos, Dafni A; Breiman, Robert F; Watson, Conall H; Kariuki, Samuel; Gordon, Melita A; Heyderman, Robert S; Okoro, Chinyere; Jacobs, Jan; Lunguya, Octavie; Edmunds, W John; Msefula, Chisomo; Chabalgoity, Jose A; Kama, Mike; Jenkins, Kylie; Dutta, Shanta; Marks, Florian; Campos, Josefina; Thompson, Corinne; Obaro, Stephen; MacLennan, Calman A; Dolecek, Christiane; Keddy, Karen H; Smith, Anthony M; Parry, Christopher M; Karkey, Abhilasha; Mulholland, E Kim; Campbell, James I; Dongol, Sabina; Basnyat, Buddha; Dufour, Muriel; Bandaranayake, Don; Naseri, Take Toleafoa; Singh, Shalini Pravin; Hatta, Mochammad; Newton, Paul; Onsare, Robert S; Isaia, Lupeoletalalei; Dance, David; Davong, Viengmon; Thwaites, Guy; Wijedoru, Lalith; Crump, John A; De Pinna, Elizabeth; Nair, Satheesh; Nilles, Eric J; Thanh, Duy Pham; Turner, Paul; Soeng, Sona; Valcanis, Mary; Powling, Joan; Dimovski, Karolina; Hogg, Geoff; Farrar, Jeremy; Holt, Kathryn E; Dougan, Gordon

2016-01-01

The emergence of multidrug-resistant (MDR) typhoid is a major global health threat affecting many countries where the disease is endemic. Here whole-genome sequence analysis of 1,832 Salmonella enterica serovar Typhi (S. Typhi) identifies a single dominant MDR lineage, H58, that has emerged and spread throughout Asia and Africa over the last 30 years. Our analysis identifies numerous transmissions of H58, including multiple transfers from Asia to Africa and an ongoing, unrecognized MDR epidemic within Africa itself. Notably, our analysis indicates that H58 lineages are displacing antibiotic-sensitive isolates, transforming the global population structure of this pathogen. H58 isolates can harbor a complex MDR element residing either on transmissible IncHI1 plasmids or within multiple chromosomal integration sites. We also identify new mutations that define the H58 lineage. This phylogeographical analysis provides a framework to facilitate global management of MDR typhoid and is applicable to similar MDR lineages emerging in other bacterial species. PMID:25961941

Microbiome Networks: A Systems Framework for Identifying Candidate Microbial Assemblages for Disease Management.

PubMed

Poudel, R; Jumpponen, A; Schlatter, D C; Paulitz, T C; Gardener, B B McSpadden; Kinkel, L L; Garrett, K A

2016-10-01

Network models of soil and plant microbiomes provide new opportunities for enhancing disease management, but also challenges for interpretation. We present a framework for interpreting microbiome networks, illustrating how observed network structures can be used to generate testable hypotheses about candidate microbes affecting plant health. The framework includes four types of network analyses. "General network analysis" identifies candidate taxa for maintaining an existing microbial community. "Host-focused analysis" includes a node representing a plant response such as yield, identifying taxa with direct or indirect associations with that node. "Pathogen-focused analysis" identifies taxa with direct or indirect associations with taxa known a priori as pathogens. "Disease-focused analysis" identifies taxa associated with disease. Positive direct or indirect associations with desirable outcomes, or negative associations with undesirable outcomes, indicate candidate taxa. Network analysis provides characterization not only of taxa with direct associations with important outcomes such as disease suppression, biofertilization, or expression of plant host resistance, but also taxa with indirect associations via their association with other key taxa. We illustrate the interpretation of network structure with analyses of microbiomes in the oak phyllosphere, and in wheat rhizosphere and bulk soil associated with the presence or absence of infection by Rhizoctonia solani.

Biomarker Analysis of Samples Visually Identified as Microbial in the Eocene Green River Formation: An Analogue for Mars.

PubMed

Olcott Marshall, Alison; Cestari, Nicholas A

2015-09-01

One of the major exploration targets for current and future Mars missions are lithofacies suggestive of biotic activity. Although such lithofacies are not confirmation of biotic activity, they provide a way to identify samples for further analyses. To test the efficacy of this approach, we identified carbonate samples from the Eocene Green River Formation as "microbial" or "non-microbial" based on the macroscale morphology of their laminations. These samples were then crushed and analyzed by gas chromatography/mass spectroscopy (GC/MS) to determine their lipid biomarker composition. GC/MS analysis revealed that carbonates visually identified as "microbial" contained a higher concentration of more diverse biomarkers than those identified as "non-microbial," suggesting that this could be a viable detection strategy for selecting samples for further analysis or caching on Mars.

Cross-cohort analysis identifies a TEAD4 ↔ MYCN positive-feedback loop as the core regulatory element of high-risk neuroblastoma. | Office of Cancer Genomics

Cancer.gov

High-risk neuroblastomas show a paucity of recurrent somatic mutations at diagnosis. As a result, the molecular basis for this aggressive phenotype remains elusive. Recent progress in regulatory network analysis helped us elucidate disease-driving mechanisms downstream of genomic alterations, including recurrent chromosomal alterations. Our analysis identified three molecular subtypes of high-risk neuroblastomas, consistent with chromosomal alterations, and identified subtype-specific master regulator (MR) proteins that were conserved across independent cohorts.

Identifying Students at Risk: An Examination of Computer-Adaptive Measures and Latent Class Growth Analysis

ERIC Educational Resources Information Center

Keller-Margulis, Milena; McQuillin, Samuel D.; Castañeda, Juan Javier; Ochs, Sarah; Jones, John H.

2018-01-01

Multitiered systems of support depend on screening technology to identify students at risk. The purpose of this study was to examine the use of a computer-adaptive test and latent class growth analysis (LCGA) to identify students at risk in reading with focus on the use of this methodology to characterize student performance in screening.…

Characterising volcanic cycles at Soufriere Hills Volcano, Montserrat: Time series analysis of multi-parameter satellite data

NASA Astrophysics Data System (ADS)

Flower, Verity J. B.; Carn, Simon A.

2015-10-01

The identification of cyclic volcanic activity can elucidate underlying eruption dynamics and aid volcanic hazard mitigation. Whilst satellite datasets are often analysed individually, here we exploit the multi-platform NASA A-Train satellite constellation to cross-correlate cyclical signals identified using complementary measurement techniques at Soufriere Hills Volcano (SHV), Montserrat. In this paper we present a Multi-taper (MTM) Fast Fourier Transform (FFT) analysis of coincident SO2 and thermal infrared (TIR) satellite measurements at SHV facilitating the identification of cyclical volcanic behaviour. These measurements were collected by the Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer (MODIS) (respectively) in the A-Train. We identify a correlating cycle in both the OMI and MODIS data (54-58 days), with this multi-week feature attributable to episodes of dome growth. The 50 day cycles were also identified in ground-based SO2 data at SHV, confirming the validity of our analysis and further corroborating the presence of this cycle at the volcano. In addition a 12 day cycle was identified in the OMI data, previously attributed to variable lava effusion rates on shorter timescales. OMI data also display a one week (7-8 days) cycle attributable to cyclical variations in viewing angle resulting from the orbital characteristics of the Aura satellite. Longer period cycles possibly relating to magma intrusion were identified in the OMI record (102-, 121-, and 159 days); in addition to a 238-day cycle identified in the MODIS data corresponding to periodic destabilisation of the lava dome. Through the analysis of reconstructions generated from cycles identified in the OMI and MODIS data, periods of unrest were identified, including the major dome collapse of 20th May 2006 and significant explosive event of 3rd January 2009. Our analysis confirms the potential for identification of cyclical volcanic activity through combined analysis of satellite data, which would be of particular value at poorly monitored volcanic systems.

Fault Tree Analysis Application for Safety and Reliability

NASA Technical Reports Server (NTRS)

Wallace, Dolores R.

2003-01-01

Many commercial software tools exist for fault tree analysis (FTA), an accepted method for mitigating risk in systems. The method embedded in the tools identifies a root as use in system components, but when software is identified as a root cause, it does not build trees into the software component. No commercial software tools have been built specifically for development and analysis of software fault trees. Research indicates that the methods of FTA could be applied to software, but the method is not practical without automated tool support. With appropriate automated tool support, software fault tree analysis (SFTA) may be a practical technique for identifying the underlying cause of software faults that may lead to critical system failures. We strive to demonstrate that existing commercial tools for FTA can be adapted for use with SFTA, and that applied to a safety-critical system, SFTA can be used to identify serious potential problems long before integrator and system testing.

Realist identification of group-level latent variables for perinatal social epidemiology theory building.

PubMed

Eastwood, John Graeme; Jalaludin, Bin Badrudin; Kemp, Lynn Ann; Phung, Hai Ngoc

2014-01-01

We have previously reported in this journal on an ecological study of perinatal depressive symptoms in South Western Sydney. In that article, we briefly reported on a factor analysis that was utilized to identify empirical indicators for analysis. In this article, we report on the mixed method approach that was used to identify those latent variables. Social epidemiology has been slow to embrace a latent variable approach to the study of social, political, economic, and cultural structures and mechanisms, partly for philosophical reasons. Critical realist ontology and epistemology have been advocated as an appropriate methodological approach to both theory building and theory testing in the health sciences. We describe here an emergent mixed method approach that uses qualitative methods to identify latent constructs followed by factor analysis using empirical indicators chosen to measure identified qualitative codes. Comparative analysis of the findings is reported together with a limited description of realist approaches to abstract reasoning.

Analysis of Performance Factors for Accounting and Finance Related Business Courses in a Distance Education Environment

ERIC Educational Resources Information Center

Benligiray, Serdar; Onay, Ahmet

2017-01-01

The objective of this study is to explore business courses performance factors with a focus on accounting and finance. Course score interrelations are assumed to represent interpretable constructs of these factors. Factor analysis is proposed to identify the constructs that explain the correlations. Factor analysis results identify three…

Identification of key genes associated with the effect of estrogen on ovarian cancer using microarray analysis.

PubMed

Zhang, Shi-tao; Zuo, Chao; Li, Wan-nan; Fu, Xue-qi; Xing, Shu; Zhang, Xiao-ping

2016-02-01

To identify key genes related to the effect of estrogen on ovarian cancer. Microarray data (GSE22600) were downloaded from Gene Expression Omnibus. Eight estrogen and seven placebo treatment samples were obtained using a 2 × 2 factorial designs, which contained 2 cell lines (PEO4 and 2008) and 2 treatments (estrogen and placebo). Differentially expressed genes were identified by Bayesian methods, and the genes with P < 0.05 and |log2FC (fold change)| ≥0.5 were chosen as cut-off criterion. Differentially co-expressed genes (DCGs) and differentially regulated genes (DRGs) were, respectively, identified by DCe function and DRsort function in DCGL package. Topological structure analysis was performed on the important transcriptional factors (TFs) and genes in transcriptional regulatory network using tYNA. Functional enrichment analysis was, respectively, performed for DEGs and the important genes using Gene Ontology and KEGG databases. In total, 465 DEGs were identified. Functional enrichment analysis of DEGs indicated that ACVR2B, LTBP1, BMP7 and MYC involved in TGF-beta signaling pathway. The 2285 DCG pairs and 357 DRGs were identified. Topological structure analysis showed that 52 important TFs and 65 important genes were identified. Functional enrichment analysis of the important genes showed that TP53 and MLH1 participated in DNA damage response and the genes (ACVR2B, LTBP1, BMP7 and MYC) involved in TGF-beta signaling pathway. TP53, MLH1, ACVR2B, LTBP1 and BMP7 might participate in the pathogenesis of ovarian cancer.

CrossTalk: The Journal of Defense Software Engineering. Volume 27, Number 1, January/February 2014

DTIC Science & Technology

2014-02-01

deficit in trustworthiness and will permit analysis on how this deficit needs to be overcome. This analysis will help identify adaptations that are...approaches to trustworthy analysis split into two categories: product-based and process-based. Product-based techniques [9] identify factors that...Criticalities may also be assigned to decompositions and contributions. 5. Evaluation and analysis : in this task the propagation rules of the NFR

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.

Identifying Social Trust in Cross-Country Analysis: Do We Really Measure the Same?

ERIC Educational Resources Information Center

Torpe, Lars; Lolle, Henrik

2011-01-01

Many see trust as an important social resource for the welfare of individuals as well as nations. It is therefore important to be able to identify trust and explain its sources. Cross-country survey analysis has been an important tool in this respect, and often one single variable is used to identify social trust understood as trust in strangers,…

An Analysis of Eruptions Detected by the LMSAL Eruption Patrol

NASA Astrophysics Data System (ADS)

Hurlburt, N. E.; Higgins, P. A.; Jaffey, S.

2014-12-01

Observations of the solar atmosphere reveals a wide range of real and apparent motions, from small scale jets and spicules to global-scale coronal mass ejections. Identifying and characterizing these motions are essential to advance our understanding the drivers of space weather. Automated and visual identifications are used in identifying CMEs. To date, the precursors to these — eruptions near the solar surface — have been identified primarily by visual inspection. Here we report on an analysis of the eruptions detected by the Eruption Patrol, a data mining module designed to automatically identify eruptions from data collected by Solar Dynamics Observatory's Atmospheric Imaging Assembly (SDO/AIA). We describe the module and use it both to explore relations with other solar events recorded in the Heliophysics Event Knowledgebase and to identify and access data collected by the Interface Region Imaging Spectrograph (IRIS) and Solar Optical Telescope (SOT) on Hinode for further analysis.

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...

The Use of Descriptive Analysis to Identify and Manipulate Schedules of Reinforcement in the Treatment of Food Refusal

ERIC Educational Resources Information Center

Casey, Sean D.; Cooper-Brown, Linda J.; Wacker, David P.; Rankin, Barbara E.

2006-01-01

The feeding behaviors of a child diagnosed with failure to thrive were assessed using descriptive analysis methodology to identify the schedules of reinforcement provided by the child's parents. This analysis revealed that the child's appropriate feeding behaviors (i.e., bite acceptance, self-feeding) were on a lean schedule of positive…

Strategic Plan: Initiating an Orthopaedic Residency at Womack Army Medical Center

DTIC Science & Technology

2006-06-07

outlining WAMC’s strategy: analysis of Porter’s Five Forces Model; a Strategic Map for discovering competitive advantages and disadvantages ; identifying a...Figure 6. Strategic Map of Advantages and Disadvantages ............................... 27 Figure 7. Directional Strategy...analysis; analysis of Porter’s Five Forces Model; a strategic map for discovering competitive advantages and disadvantages ; identifying a directional

Integrating environmental gap analysis with spatial conservation prioritization: a case study from Victoria, Australia.

PubMed

Sharafi, Seyedeh Mahdieh; Moilanen, Atte; White, Matt; Burgman, Mark

2012-12-15

Gap analysis is used to analyse reserve networks and their coverage of biodiversity, thus identifying gaps in biodiversity representation that may be filled by additional conservation measures. Gap analysis has been used to identify priorities for species and habitat types. When it is applied to identify gaps in the coverage of environmental variables, it embodies the assumption that combinations of environmental variables are effective surrogates for biodiversity attributes. The question remains of how to fill gaps in conservation systems efficiently. Conservation prioritization software can identify those areas outside existing conservation areas that contribute to the efficient covering of gaps in biodiversity features. We show how environmental gap analysis can be implemented using high-resolution information about environmental variables and ecosystem condition with the publicly available conservation prioritization software, Zonation. Our method is based on the conversion of combinations of environmental variables into biodiversity features. We also replicated the analysis by using Species Distribution Models (SDMs) as biodiversity features to evaluate the robustness and utility of our environment-based analysis. We apply the technique to a planning case study of the state of Victoria, Australia. Copyright © 2012 Elsevier Ltd. All rights reserved.

Glycomics meets artificial intelligence - Potential of glycan analysis for identification of seropositive and seronegative rheumatoid arthritis patients revealed.

PubMed

Chocholova, Erika; Bertok, Tomas; Jane, Eduard; Lorencova, Lenka; Holazova, Alena; Belicka, Ludmila; Belicky, Stefan; Mislovicova, Danica; Vikartovska, Alica; Imrich, Richard; Kasak, Peter; Tkac, Jan

2018-06-01

In this study, one hundred serum samples from healthy people and patients with rheumatoid arthritis (RA) were analyzed. Standard immunoassays for detection of 10 different RA markers and analysis of glycan markers on antibodies in 10 different assay formats with several lectins were applied for each serum sample. A dataset containing 2000 data points was data mined using artificial neural networks (ANN). We identified key RA markers, which can discriminate between healthy people and seropositive RA patients (serum containing autoantibodies) with accuracy of 83.3%. Combination of RA markers with glycan analysis provided much better discrimination accuracy of 92.5%. Immunoassays completely failed to identify seronegative RA patients (serum not containing autoantibodies), while glycan analysis correctly identified 43.8% of these patients. Further, we revealed other critical parameters for successful glycan analysis such as type of a sample, format of analysis and orientation of captured antibodies for glycan analysis. Copyright © 2018 Elsevier B.V. All rights reserved.

40 CFR 79.33 - Motor vehicle diesel fuel.

Code of Federal Regulations, 2010 CFR

2010-07-01

... data may be for such shorter period. (1) Hydrocarbon composition (aromatic content, olefin content, saturate content), with the methods of analysis identified; (2) Polynuclear organic material content, sulfur content, and trace element content, with the methods of analysis identified; (3) Distillation...

System review: a method for investigating medical errors in healthcare settings.

PubMed

Alexander, G L; Stone, T T

2000-01-01

System analysis is a process of evaluating objectives, resources, structure, and design of businesses. System analysis can be used by leaders to collaboratively identify breakthrough opportunities to improve system processes. In healthcare systems, system analysis can be used to review medical errors (system occurrences) that may place patients at risk for injury, disability, and/or death. This study utilizes a case management approach to identify medical errors. Utilizing an interdisciplinary approach, a System Review Team was developed to identify trends in system occurrences, facilitate communication, and enhance the quality of patient care by reducing medical errors.

Microarray analysis and scale-free gene networks identify candidate regulators in drought-stressed roots of loblolly pine (P. taeda L.)

PubMed Central

2011-01-01

Background Global transcriptional analysis of loblolly pine (Pinus taeda L.) is challenging due to limited molecular tools. PtGen2, a 26,496 feature cDNA microarray, was fabricated and used to assess drought-induced gene expression in loblolly pine propagule roots. Statistical analysis of differential expression and weighted gene correlation network analysis were used to identify drought-responsive genes and further characterize the molecular basis of drought tolerance in loblolly pine. Results Microarrays were used to interrogate root cDNA populations obtained from 12 genotype × treatment combinations (four genotypes, three watering regimes). Comparison of drought-stressed roots with roots from the control treatment identified 2445 genes displaying at least a 1.5-fold expression difference (false discovery rate = 0.01). Genes commonly associated with drought response in pine and other plant species, as well as a number of abiotic and biotic stress-related genes, were up-regulated in drought-stressed roots. Only 76 genes were identified as differentially expressed in drought-recovered roots, indicating that the transcript population can return to the pre-drought state within 48 hours. Gene correlation analysis predicts a scale-free network topology and identifies eleven co-expression modules that ranged in size from 34 to 938 members. Network topological parameters identified a number of central nodes (hubs) including those with significant homology (E-values ≤ 2 × 10-30) to 9-cis-epoxycarotenoid dioxygenase, zeatin O-glucosyltransferase, and ABA-responsive protein. Identified hubs also include genes that have been associated previously with osmotic stress, phytohormones, enzymes that detoxify reactive oxygen species, and several genes of unknown function. Conclusion PtGen2 was used to evaluate transcriptome responses in loblolly pine and was leveraged to identify 2445 differentially expressed genes responding to severe drought stress in roots. Many of the genes identified are known to be up-regulated in response to osmotic stress in pine and other plant species and encode proteins involved in both signal transduction and stress tolerance. Gene expression levels returned to control values within a 48-hour recovery period in all but 76 transcripts. Correlation network analysis indicates a scale-free network topology for the pine root transcriptome and identifies central nodes that may serve as drivers of drought-responsive transcriptome dynamics in the roots of loblolly pine. PMID:21609476

Literature mining, gene-set enrichment and pathway analysis for target identification in Behçet's disease.

PubMed

Wilson, Paul; Larminie, Christopher; Smith, Rona

2016-01-01

To use literature mining to catalogue Behçet's associated genes, and advanced computational methods to improve the understanding of the pathways and signalling mechanisms that lead to the typical clinical characteristics of Behçet's patients. To extend this technique to identify potential treatment targets for further experimental validation. Text mining methods combined with gene enrichment tools, pathway analysis and causal analysis algorithms. This approach identified 247 human genes associated with Behçet's disease and the resulting disease map, comprising 644 nodes and 19220 edges, captured important details of the relationships between these genes and their associated pathways, as described in diverse data repositories. Pathway analysis has identified how Behçet's associated genes are likely to participate in innate and adaptive immune responses. Causal analysis algorithms have identified a number of potential therapeutic strategies for further investigation. Computational methods have captured pertinent features of the prominent disease characteristics presented in Behçet's disease and have highlighted NOD2, ICOS and IL18 signalling as potential therapeutic strategies.

Patient complaints as a means to improve quality of hospital care. Results of a qualitative content analysis

PubMed

Hoffmann, Susanne; Dreher-Hummel, Thomas; Dollinger, Claudia; Frei, Irena Anna

2018-04-01

Background: Many hospitals have defined procedures for a complaint management. A systematic analysis of patient complaints helps to identify similar complaints and patterns so that targeted improvement measures can be derived (Gallagher & Mazor, 2015). Aim: Our three-month, nurse-led practice development project aimed 1) to identify complaints regarding communication issues, 2) to systemise and prioritise complaints regarding communication issues, and 3) to derive clinic-specific recommendations for improvement. Method: We analysed 273 complaints of patients documented by the quality management (secondary data analysis). Using content analysis and applying the coding taxonomy for inpatient complaints by Reader, Gillespie and Roberts (2014), we distinguished communication-related complaints. By further inductive differentiation of these complaints, we identified patterns and prioritised fields of action. Results: We identified 186 communication-related complaints divided into 16 subcategories. For each subcategory, improvement interventions were derived, discussed and prioritised. Conclusions: Thus, patient complaints provided an excellent opportunity for reflection and workplace learning for nurses. The analysis gave impulse to exemplify the subject “person-centered care” for nurses.

Integrated corridor management, concept development and foundational research. Task 5.5, identification of analysis needs.

DOT National Transportation Integrated Search

2006-08-28

Task 5 - Identify Corridor Types, Operational Approaches and Strategies, and Analysis Tools - is part of the overall foundational research to further the understanding of various aspects of Integrated Corridor Management (ICM) and to identify integra...

Transcriptomic meta-analysis identifies gene expression characteristics in various samples of HIV-infected patients with nonprogressive disease.

PubMed

Zhang, Le-Le; Zhang, Zi-Ning; Wu, Xian; Jiang, Yong-Jun; Fu, Ya-Jing; Shang, Hong

2017-09-12

A small proportion of HIV-infected patients remain clinically and/or immunologically stable for years, including elite controllers (ECs) who have undetectable viremia (<50 copies/ml) and long-term nonprogressors (LTNPs) who maintain normal CD4 + T cell counts for prolonged periods (>10 years). However, the mechanism of nonprogression needs to be further resolved. In this study, a transcriptome meta-analysis was performed on nonprogressor and progressor microarray data to identify differential transcriptome pathways and potential biomarkers. Using the INMEX (integrative meta-analysis of expression data) program, we performed the meta-analysis to identify consistently differentially expressed genes (DEGs) in nonprogressors and further performed functional interpretation (gene ontology analysis and pathway analysis) of the DEGs identified in the meta-analysis. Five microarray datasets (81 cases and 98 controls in total), including whole blood, CD4 + and CD8 + T cells, were collected for meta-analysis. We determined that nonprogressors have reduced expression of important interferon-stimulated genes (ISGs), CD38, lymphocyte activation gene 3 (LAG-3) in whole blood, CD4 + and CD8 + T cells. Gene ontology (GO) analysis showed a significant enrichment in DEGs that function in the type I interferon signaling pathway. Upregulated pathways, including the PI3K-Akt signaling pathway in whole blood, cytokine-cytokine receptor interaction in CD4 + T cells and the MAPK signaling pathway in CD8 + T cells, were identified in nonprogressors compared with progressors. In each metabolic functional category, the number of downregulated DEGs was more than the upregulated DEGs, and almost all genes were downregulated DEGs in the oxidative phosphorylation (OXPHOS) and tricarboxylic acid (TCA) cycle in the three types of samples. Our transcriptomic meta-analysis provides a comprehensive evaluation of the gene expression profiles in major blood types of nonprogressors, providing new insights in the understanding of HIV pathogenesis and developing strategies to delay HIV disease progression.

Neural network system and methods for analysis of organic materials and structures using spectral data

DOEpatents

Meyer, Bernd J.; Sellers, Jeffrey P.; Thomsen, Jan U.

1993-01-01

Apparatus and processes for recognizing and identifying materials. Characteristic spectra are obtained for the materials via spectroscopy techniques including nuclear magnetic resonance spectroscopy, infrared absorption analysis, x-ray analysis, mass spectroscopy and gas chromatography. Desired portions of the spectra may be selected and then placed in proper form and format for presentation to a number of input layer neurons in an offline neural network. The network is first trained according to a predetermined training process; it may then be employed to identify particular materials. Such apparatus and processes are particularly useful for recognizing and identifying organic compounds such as complex carbohydrates, whose spectra conventionally require a high level of training and many hours of hard work to identify, and are frequently indistinguishable from one another by human interpretation.

Chromosomal Microarray versus Karyotyping for Prenatal Diagnosis

PubMed Central

Wapner, Ronald J.; Martin, Christa Lese; Levy, Brynn; Ballif, Blake C.; Eng, Christine M.; Zachary, Julia M.; Savage, Melissa; Platt, Lawrence D.; Saltzman, Daniel; Grobman, William A.; Klugman, Susan; Scholl, Thomas; Simpson, Joe Leigh; McCall, Kimberly; Aggarwal, Vimla S.; Bunke, Brian; Nahum, Odelia; Patel, Ankita; Lamb, Allen N.; Thom, Elizabeth A.; Beaudet, Arthur L.; Ledbetter, David H.; Shaffer, Lisa G.; Jackson, Laird

2013-01-01

Background Chromosomal microarray analysis has emerged as a primary diagnostic tool for the evaluation of developmental delay and structural malformations in children. We aimed to evaluate the accuracy, efficacy, and incremental yield of chromosomal microarray analysis as compared with karyotyping for routine prenatal diagnosis. Methods Samples from women undergoing prenatal diagnosis at 29 centers were sent to a central karyotyping laboratory. Each sample was split in two; standard karyotyping was performed on one portion and the other was sent to one of four laboratories for chromosomal microarray. Results We enrolled a total of 4406 women. Indications for prenatal diagnosis were advanced maternal age (46.6%), abnormal result on Down’s syndrome screening (18.8%), structural anomalies on ultrasonography (25.2%), and other indications (9.4%). In 4340 (98.8%) of the fetal samples, microarray analysis was successful; 87.9% of samples could be used without tissue culture. Microarray analysis of the 4282 nonmosaic samples identified all the aneuploidies and unbalanced rearrangements identified on karyotyping but did not identify balanced translocations and fetal triploidy. In samples with a normal karyotype, microarray analysis revealed clinically relevant deletions or duplications in 6.0% with a structural anomaly and in 1.7% of those whose indications were advanced maternal age or positive screening results. Conclusions In the context of prenatal diagnostic testing, chromosomal microarray analysis identified additional, clinically significant cytogenetic information as compared with karyotyping and was equally efficacious in identifying aneuploidies and unbalanced rearrangements but did not identify balanced translocations and triploidies. (Funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development and others; ClinicalTrials.gov number, NCT01279733.) PMID:23215555

FLOCK cluster analysis of plasma cell flow cytometry data predicts bone marrow involvement by plasma cell neoplasia.

PubMed

Dorfman, David M; LaPlante, Charlotte D; Li, Betty

2016-09-01

We analyzed plasma cell populations in bone marrow samples from 353 patients with possible bone marrow involvement by a plasma cell neoplasm, using FLOCK (FLOw Clustering without K), an unbiased, automated, computational approach to identify cell subsets in multidimensional flow cytometry data. FLOCK identified discrete plasma cell populations in the majority of bone marrow specimens found by standard histologic and immunophenotypic criteria to be involved by a plasma cell neoplasm (202/208 cases; 97%), including 34 cases that were negative by standard flow cytometric analysis that included clonality assessment. FLOCK identified discrete plasma cell populations in only a minority of cases negative for involvement by a plasma cell neoplasm by standard histologic and immunophenotypic criteria (38/145 cases; 26%). Interestingly, 55% of the cases negative by standard analysis, but containing a FLOCK-identified discrete plasma cell population, were positive for monoclonal gammopathy by serum protein electrophoresis and immunofixation. FLOCK-identified and quantitated plasma cell populations accounted for 3.05% of total cells on average in cases positive for involvement by a plasma cell neoplasm by standard histologic and immunophenotypic criteria, and 0.27% of total cells on average in cases negative for involvement by a plasma cell neoplasm by standard histologic and immunophenotypic criteria (p<0.0001; area under the curve by ROC analysis=0.96). The presence of a FLOCK-identified discrete plasma cell population was predictive of the presence of plasma cell neoplasia with a sensitivity of 97%, compared with only 81% for standard flow cytometric analysis, and had specificity of 74%, PPV of 84% and NPV of 95%. FLOCK analysis, which has been shown to provide useful diagnostic information for evaluating patients with suspected systemic mastocytosis, is able to identify neoplastic plasma cell populations analyzed by flow cytometry, and may be helpful in the diagnostic evaluation of bone marrow samples for involvement by plasma cell neoplasia. Copyright © 2016 Elsevier Ltd. All rights reserved.

Genetic Architecture of Aluminum Tolerance in Rice (Oryza sativa) Determined through Genome-Wide Association Analysis and QTL Mapping

PubMed Central

Famoso, Adam N.; Zhao, Keyan; Clark, Randy T.; Tung, Chih-Wei; Wright, Mark H.; Bustamante, Carlos; Kochian, Leon V.; McCouch, Susan R.

2011-01-01

Aluminum (Al) toxicity is a primary limitation to crop productivity on acid soils, and rice has been demonstrated to be significantly more Al tolerant than other cereal crops. However, the mechanisms of rice Al tolerance are largely unknown, and no genes underlying natural variation have been reported. We screened 383 diverse rice accessions, conducted a genome-wide association (GWA) study, and conducted QTL mapping in two bi-parental populations using three estimates of Al tolerance based on root growth. Subpopulation structure explained 57% of the phenotypic variation, and the mean Al tolerance in Japonica was twice that of Indica. Forty-eight regions associated with Al tolerance were identified by GWA analysis, most of which were subpopulation-specific. Four of these regions co-localized with a priori candidate genes, and two highly significant regions co-localized with previously identified QTLs. Three regions corresponding to induced Al-sensitive rice mutants (ART1, STAR2, Nrat1) were identified through bi-parental QTL mapping or GWA to be involved in natural variation for Al tolerance. Haplotype analysis around the Nrat1 gene identified susceptible and tolerant haplotypes explaining 40% of the Al tolerance variation within the aus subpopulation, and sequence analysis of Nrat1 identified a trio of non-synonymous mutations predictive of Al sensitivity in our diversity panel. GWA analysis discovered more phenotype–genotype associations and provided higher resolution, but QTL mapping identified critical rare and/or subpopulation-specific alleles not detected by GWA analysis. Mapping using Indica/Japonica populations identified QTLs associated with transgressive variation where alleles from a susceptible aus or indica parent enhanced Al tolerance in a tolerant Japonica background. This work supports the hypothesis that selectively introgressing alleles across subpopulations is an efficient approach for trait enhancement in plant breeding programs and demonstrates the fundamental importance of subpopulation in interpreting and manipulating the genetics of complex traits in rice. PMID:21829395

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.

Research fronts analysis : A bibliometric to identify emerging fields of research

NASA Astrophysics Data System (ADS)

Miwa, Sayaka; Ando, Satoko

Research fronts analysis identifies emerging areas of research through observing co-clustering in highly-cited papers. This article introduces the concept of research fronts analysis, explains its methodology and provides case examples. It also demonstrates developing research fronts in Japan by looking at the past winners of Thomson Reuters Research Fronts Awards. Research front analysis is currently being used by the Japanese government to determine new trends in science and technology. Information professionals can also utilize this bibliometric as a research evaluation tool.

SRB thermal curtain design support

NASA Technical Reports Server (NTRS)

Lundblad, Wayne E.

1990-01-01

The objective during this time period was to perform a preliminary thermal analysis using some measured and estimated thermal properties on the angle-interlock materials. This preliminary thermal analysis is to serve as a guide for identifying any potential problems in blanket construction and identifying future tests.

BIOELECTRICAL IMPEDANCE VECTOR ANALYSIS IDENTIFIES SARCOPENIA IN NURSING HOME RESIDENTS

USDA-ARS?s Scientific Manuscript database

Loss of muscle mass and water shifts between body compartments are contributing factors to frailty in the elderly. The body composition changes are especially pronounced in institutionalized elderly. We investigated the ability of single-frequency bioelectrical impedance analysis (BIA) to identify b...

Information Science Panel joint meeting with Imaging Science Panel

NASA Technical Reports Server (NTRS)

1982-01-01

Specific activity in information extraction science (taken to include data handling) is needed to: help identify the bounds of practical missions; identify potential data handling and analysis scenarios; identify the required enabling technology; and identify the requirements for a design data base to be used by the disciplines in determining potential parameters for future missions. It was defined that specific analysis topics were a function of the discipline involved, and therefore no attempt was made to define any specific analysis developments required. Rather, it was recognized that a number of generic data handling requirements exist whose solutions cannot be typically supported by the disciplines. The areas of concern were therefore defined as: data handling aspects of system design considerations; enabling technology for data handling, with specific attention to rectification and registration; and enabling technology for analysis. Within each of these areas, the following topics were addressed: state of the art (current status and contributing factors); critical issues; and recommendations for research and/or development.

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

An Application of Instructional System Development to Determine Financial Management Education Needs for Logistics Management Positions.

DTIC Science & Technology

1976-09-01

The purpose of this research effort was to determine the financial management educational needs of USAF graduate logistics positions. Goal analysis...was used to identify financial management techniques and task analysis was used to develop a method to identify the use of financial management techniques...positions. The survey identified financial management techniques in five areas: cost accounting, capital budgeting, working capital, financial forecasting, and programming. (Author)

An independent component analysis confounding factor correction framework for identifying broad impact expression quantitative trait loci

PubMed Central

Ju, Jin Hyun; Crystal, Ronald G.

2017-01-01

Genome-wide expression Quantitative Trait Loci (eQTL) studies in humans have provided numerous insights into the genetics of both gene expression and complex diseases. While the majority of eQTL identified in genome-wide analyses impact a single gene, eQTL that impact many genes are particularly valuable for network modeling and disease analysis. To enable the identification of such broad impact eQTL, we introduce CONFETI: Confounding Factor Estimation Through Independent component analysis. CONFETI is designed to address two conflicting issues when searching for broad impact eQTL: the need to account for non-genetic confounding factors that can lower the power of the analysis or produce broad impact eQTL false positives, and the tendency of methods that account for confounding factors to model broad impact eQTL as non-genetic variation. The key advance of the CONFETI framework is the use of Independent Component Analysis (ICA) to identify variation likely caused by broad impact eQTL when constructing the sample covariance matrix used for the random effect in a mixed model. We show that CONFETI has better performance than other mixed model confounding factor methods when considering broad impact eQTL recovery from synthetic data. We also used the CONFETI framework and these same confounding factor methods to identify eQTL that replicate between matched twin pair datasets in the Multiple Tissue Human Expression Resource (MuTHER), the Depression Genes Networks study (DGN), the Netherlands Study of Depression and Anxiety (NESDA), and multiple tissue types in the Genotype-Tissue Expression (GTEx) consortium. These analyses identified both cis-eQTL and trans-eQTL impacting individual genes, and CONFETI had better or comparable performance to other mixed model confounding factor analysis methods when identifying such eQTL. In these analyses, we were able to identify and replicate a few broad impact eQTL although the overall number was small even when applying CONFETI. In light of these results, we discuss the broad impact eQTL that have been previously reported from the analysis of human data and suggest that considerable caution should be exercised when making biological inferences based on these reported eQTL. PMID:28505156

An independent component analysis confounding factor correction framework for identifying broad impact expression quantitative trait loci.

PubMed

Ju, Jin Hyun; Shenoy, Sushila A; Crystal, Ronald G; Mezey, Jason G

2017-05-01

Genome-wide expression Quantitative Trait Loci (eQTL) studies in humans have provided numerous insights into the genetics of both gene expression and complex diseases. While the majority of eQTL identified in genome-wide analyses impact a single gene, eQTL that impact many genes are particularly valuable for network modeling and disease analysis. To enable the identification of such broad impact eQTL, we introduce CONFETI: Confounding Factor Estimation Through Independent component analysis. CONFETI is designed to address two conflicting issues when searching for broad impact eQTL: the need to account for non-genetic confounding factors that can lower the power of the analysis or produce broad impact eQTL false positives, and the tendency of methods that account for confounding factors to model broad impact eQTL as non-genetic variation. The key advance of the CONFETI framework is the use of Independent Component Analysis (ICA) to identify variation likely caused by broad impact eQTL when constructing the sample covariance matrix used for the random effect in a mixed model. We show that CONFETI has better performance than other mixed model confounding factor methods when considering broad impact eQTL recovery from synthetic data. We also used the CONFETI framework and these same confounding factor methods to identify eQTL that replicate between matched twin pair datasets in the Multiple Tissue Human Expression Resource (MuTHER), the Depression Genes Networks study (DGN), the Netherlands Study of Depression and Anxiety (NESDA), and multiple tissue types in the Genotype-Tissue Expression (GTEx) consortium. These analyses identified both cis-eQTL and trans-eQTL impacting individual genes, and CONFETI had better or comparable performance to other mixed model confounding factor analysis methods when identifying such eQTL. In these analyses, we were able to identify and replicate a few broad impact eQTL although the overall number was small even when applying CONFETI. In light of these results, we discuss the broad impact eQTL that have been previously reported from the analysis of human data and suggest that considerable caution should be exercised when making biological inferences based on these reported eQTL.

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.

Bridging the gap between individual-level risk for HIV and structural determinants: using root cause analysis in strategic planning.

PubMed

Willard, Nancy; Chutuape, Kate; Stines, Stephanie; Ellen, Jonathan M

2012-01-01

HIV prevention efforts have expanded beyond individual-level interventions to address structural determinants of risk. Coalitions have been an important vehicle for addressing similar intractable and deeply rooted health-related issues. A root cause analysis process may aid coalitions in identifying fundamental, structural-level contributors to risk and in identifying appropriate solutions. For this article, strategic plans for 13 coalitions were analyzed both before and after a root cause analysis approach was applied to determine the coalitions' strategic plans potential impact and comprehensiveness. After root cause analysis, strategic plans trended toward targeting policies and practices rather than on single agency programmatic changes. Plans expanded to target multiple sectors and several changes within sectors to penetrate deeply into a sector or system. Findings suggest that root cause analysis may be a viable tool to assist coalitions in identifying structural determinants and possible solutions for HIV risk.

Proteomic analysis of bovine nucleolus.

PubMed

Patel, Amrutlal K; Olson, Doug; Tikoo, Suresh K

2010-09-01

Nucleolus is the most prominent subnuclear structure, which performs a wide variety of functions in the eukaryotic cellular processes. In order to understand the structural and functional role of the nucleoli in bovine cells, we analyzed the proteomic composition of the bovine nucleoli. The nucleoli were isolated from Madin Darby bovine kidney cells and subjected to proteomic analysis by LC-MS/MS after fractionation by SDS-PAGE and strong cation exchange chromatography. Analysis of the data using the Mascot database search and the GPM database search identified 311 proteins in the bovine nucleoli, which contained 22 proteins previously not identified in the proteomic analysis of human nucleoli. Analysis of the identified proteins using the GoMiner software suggested that the bovine nucleoli contained proteins involved in ribosomal biogenesis, cell cycle control, transcriptional, translational and post-translational regulation, transport, and structural organization. Copyright © 2010 Beijing Genomics Institute. Published by Elsevier Ltd. All rights reserved.

Gene-set analysis based on the pharmacological profiles of drugs to identify repurposing opportunities in schizophrenia.

PubMed

de Jong, Simone; Vidler, Lewis R; Mokrab, Younes; Collier, David A; Breen, Gerome

2016-08-01

Genome-wide association studies (GWAS) have identified thousands of novel genetic associations for complex genetic disorders, leading to the identification of potential pharmacological targets for novel drug development. In schizophrenia, 108 conservatively defined loci that meet genome-wide significance have been identified and hundreds of additional sub-threshold associations harbour information on the genetic aetiology of the disorder. In the present study, we used gene-set analysis based on the known binding targets of chemical compounds to identify the 'drug pathways' most strongly associated with schizophrenia-associated genes, with the aim of identifying potential drug repositioning opportunities and clues for novel treatment paradigms, especially in multi-target drug development. We compiled 9389 gene sets (2496 with unique gene content) and interrogated gene-based p-values from the PGC2-SCZ analysis. Although no single drug exceeded experiment wide significance (corrected p<0.05), highly ranked gene-sets reaching suggestive significance including the dopamine receptor antagonists metoclopramide and trifluoperazine and the tyrosine kinase inhibitor neratinib. This is a proof of principle analysis showing the potential utility of GWAS data of schizophrenia for the direct identification of candidate drugs and molecules that show polypharmacy. © The Author(s) 2016.

Preferential Allele Expression Analysis Identifies Shared Germline and Somatic Driver Genes in Advanced Ovarian Cancer

PubMed Central

Halabi, Najeeb M.; Martinez, Alejandra; Al-Farsi, Halema; Mery, Eliane; Puydenus, Laurence; Pujol, Pascal; Khalak, Hanif G.; McLurcan, Cameron; Ferron, Gwenael; Querleu, Denis; Al-Azwani, Iman; Al-Dous, Eman; Mohamoud, Yasmin A.; Malek, Joel A.; Rafii, Arash

2016-01-01

Identifying genes where a variant allele is preferentially expressed in tumors could lead to a better understanding of cancer biology and optimization of targeted therapy. However, tumor sample heterogeneity complicates standard approaches for detecting preferential allele expression. We therefore developed a novel approach combining genome and transcriptome sequencing data from the same sample that corrects for sample heterogeneity and identifies significant preferentially expressed alleles. We applied this analysis to epithelial ovarian cancer samples consisting of matched primary ovary and peritoneum and lymph node metastasis. We find that preferentially expressed variant alleles include germline and somatic variants, are shared at a relatively high frequency between patients, and are in gene networks known to be involved in cancer processes. Analysis at a patient level identifies patient-specific preferentially expressed alleles in genes that are targets for known drugs. Analysis at a site level identifies patterns of site specific preferential allele expression with similar pathways being impacted in the primary and metastasis sites. We conclude that genes with preferentially expressed variant alleles can act as cancer drivers and that targeting those genes could lead to new therapeutic strategies. PMID:26735499

A framework to identify gene expression profiles in a model of inflammation induced by lipopolysaccharide after treatment with thalidomide

PubMed Central

2012-01-01

Background Thalidomide is an anti-inflammatory and anti-angiogenic drug currently used for the treatment of several diseases, including erythema nodosum leprosum, which occurs in patients with lepromatous leprosy. In this research, we use DNA microarray analysis to identify the impact of thalidomide on gene expression responses in human cells after lipopolysaccharide (LPS) stimulation. We employed a two-stage framework. Initially, we identified 1584 altered genes in response to LPS. Modulation of this set of genes was then analyzed in the LPS stimulated cells treated with thalidomide. Results We identified 64 genes with altered expression induced by thalidomide using the rank product method. In addition, the lists of up-regulated and down-regulated genes were investigated by means of bioinformatics functional analysis, which allowed for the identification of biological processes affected by thalidomide. Confirmatory analysis was done in five of the identified genes using real time PCR. Conclusions The results showed some genes that can further our understanding of the biological mechanisms in the action of thalidomide. Of the five genes evaluated with real time PCR, three were down regulated and two were up regulated confirming the initial results of the microarray analysis. PMID:22695124

On structural identifiability analysis of the cascaded linear dynamic systems in isotopically non-stationary 13C labelling experiments.

PubMed

Lin, Weilu; Wang, Zejian; Huang, Mingzhi; Zhuang, Yingping; Zhang, Siliang

2018-06-01

The isotopically non-stationary 13C labelling experiments, as an emerging experimental technique, can estimate the intracellular fluxes of the cell culture under an isotopic transient period. However, to the best of our knowledge, the issue of the structural identifiability analysis of non-stationary isotope experiments is not well addressed in the literature. In this work, the local structural identifiability analysis for non-stationary cumomer balance equations is conducted based on the Taylor series approach. The numerical rank of the Jacobian matrices of the finite extended time derivatives of the measured fractions with respect to the free parameters is taken as the criterion. It turns out that only one single time point is necessary to achieve the structural identifiability analysis of the cascaded linear dynamic system of non-stationary isotope experiments. The equivalence between the local structural identifiability of the cascaded linear dynamic systems and the local optimum condition of the nonlinear least squares problem is elucidated in the work. Optimal measurements sets can then be determined for the metabolic network. Two simulated metabolic networks are adopted to demonstrate the utility of the proposed method. Copyright © 2018 Elsevier Inc. All rights reserved.

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

Evaluation of Roadway Reallocation Projects: Analysis of Before-and-After Travel Speeds and Congestion Utilizing High-Resolution Bus Transit Data

DOT National Transportation Integrated Search

2017-11-01

The traditional process of identifying corridors for road diet improvements involves selecting potential corridors (mostly based on identifying fourlane roads) and conducting a traffic impact analysis of proposed changes on a selected roadway before ...

Cyberbullying: Implications for Principal Leadership

ERIC Educational Resources Information Center

Hvidston, David J.; Hvidston, Brynn A.; Range, Bret G.; Harbour, Clifford P.

2013-01-01

Cyberbullying has been identified by school leaders and researchers as one of the most serious adverse consequences of incorporating information technology into the classroom. This article examines the legal status of cyberbullying by conducting an analysis of selected federal appellate court opinions. This analysis identifies a set of legal…

SAMPLING AND ANALYSIS OF NANOMATERIALS IN THE ENVIRONMENT: A STATE-OF-THE-SCIENCE REVIEW

EPA Science Inventory

This state-of-the-science review was undertaken to identify and assess currently available sampling and analysis methods to identify and quantify the occurrence of nanomaterials in the environment. The environmental and human health risks associated with nanomaterials are largely...

Improving Family Forest Knowledge Transfer through Social Network Analysis

ERIC Educational Resources Information Center

Gorczyca, Erika L.; Lyons, Patrick W.; Leahy, Jessica E.; Johnson, Teresa R.; Straub, Crista L.

2012-01-01

To better engage Maine's family forest landowners our study used social network analysis: a computational social science method for identifying stakeholders, evaluating models of engagement, and targeting areas for enhanced partnerships. Interviews with researchers associated with a research center were conducted to identify how social network…

42 CFR 421.501 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-10-01

... licensed medical professional, for a billed item or service identified by data analysis techniques or probe... rate based on the results of a probe review prior to the initiation of complex medical review. Medical... licensed medical professional, for a billed item or service identified by data analysis techniques or probe...

42 CFR 421.501 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-10-01

... licensed medical professional, for a billed item or service identified by data analysis techniques or probe... rate based on the results of a probe review prior to the initiation of complex medical review. Medical... licensed medical professional, for a billed item or service identified by data analysis techniques or probe...

42 CFR 421.501 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-10-01

... licensed medical professional, for a billed item or service identified by data analysis techniques or probe... rate based on the results of a probe review prior to the initiation of complex medical review. Medical... licensed medical professional, for a billed item or service identified by data analysis techniques or probe...

Orbiter subsystem hardware/software interaction analysis. Volume 8: Forward reaction control system

NASA Technical Reports Server (NTRS)

Becker, D. D.

1980-01-01

The results of the orbiter hardware/software interaction analysis for the AFT reaction control system are presented. The interaction between hardware failure modes and software are examined in order to identify associated issues and risks. All orbiter subsystems and interfacing program elements which interact with the orbiter computer flight software are analyzed. The failure modes identified in the subsystem/element failure mode and effects analysis are discussed.

[Methods of a posteriori identification of food patterns in Brazilian children: a systematic review].

PubMed

Carvalho, Carolina Abreu de; Fonsêca, Poliana Cristina de Almeida; Nobre, Luciana Neri; Priore, Silvia Eloiza; Franceschini, Sylvia do Carmo Castro

2016-01-01

The objective of this study is to provide guidance for identifying dietary patterns using the a posteriori approach, and analyze the methodological aspects of the studies conducted in Brazil that identified the dietary patterns of children. Articles were selected from the Latin American and Caribbean Literature on Health Sciences, Scientific Electronic Library Online and Pubmed databases. The key words were: Dietary pattern; Food pattern; Principal Components Analysis; Factor analysis; Cluster analysis; Reduced rank regression. We included studies that identified dietary patterns of children using the a posteriori approach. Seven studies published between 2007 and 2014 were selected, six of which were cross-sectional and one cohort, Five studies used the food frequency questionnaire for dietary assessment; one used a 24-hour dietary recall and the other a food list. The method of exploratory approach used in most publications was principal components factor analysis, followed by cluster analysis. The sample size of the studies ranged from 232 to 4231, the values of the Kaiser-Meyer-Olkin test from 0.524 to 0.873, and Cronbach's alpha from 0.51 to 0.69. Few Brazilian studies identified dietary patterns of children using the a posteriori approach and principal components factor analysis was the technique most used.

Clinical proteomic analysis of scrub typhus infection.

PubMed

Park, Edmond Changkyun; Lee, Sang-Yeop; Yun, Sung Ho; Choi, Chi-Won; Lee, Hayoung; Song, Hyun Seok; Jun, Sangmi; Kim, Gun-Hwa; Lee, Chang-Seop; Kim, Seung Il

2018-01-01

Scrub typhus is an acute and febrile infectious disease caused by the Gram-negative α-proteobacterium Orientia tsutsugamushi from the family Rickettsiaceae that is widely distributed in Northern, Southern and Eastern Asia. In the present study, we analysed the serum proteome of scrub typhus patients to investigate specific clinical protein patterns in an attempt to explain pathophysiology and discover potential biomarkers of infection. Serum samples were collected from three patients (before and after treatment with antibiotics) and three healthy subjects. One-dimensional sodium dodecyl sulphate-polyacrylamide gel electrophoresis followed by liquid chromatography-tandem mass spectrometry was performed to identify differentially abundant proteins using quantitative proteomic approaches. Bioinformatic analysis was then performed using Ingenuity Pathway Analysis. Proteomic analysis identified 236 serum proteins, of which 32 were differentially expressed in normal subjects, naive scrub typhus patients and patients treated with antibiotics. Comparative bioinformatic analysis of the identified proteins revealed up-regulation of proteins involved in immune responses, especially complement system, following infection with O. tsutsugamushi , and normal expression was largely rescued by antibiotic treatment. This is the first proteomic study of clinical serum samples from scrub typhus patients. Proteomic analysis identified changes in protein expression upon infection with O. tsutsugamushi and following antibiotic treatment. Our results provide valuable information for further investigation of scrub typhus therapy and diagnosis.

Robust Selection Algorithm (RSA) for Multi-Omic Biomarker Discovery; Integration with Functional Network Analysis to Identify miRNA Regulated Pathways in Multiple Cancers.

PubMed

Sehgal, Vasudha; Seviour, Elena G; Moss, Tyler J; Mills, Gordon B; Azencott, Robert; Ram, Prahlad T

2015-01-01

MicroRNAs (miRNAs) play a crucial role in the maintenance of cellular homeostasis by regulating the expression of their target genes. As such, the dysregulation of miRNA expression has been frequently linked to cancer. With rapidly accumulating molecular data linked to patient outcome, the need for identification of robust multi-omic molecular markers is critical in order to provide clinical impact. While previous bioinformatic tools have been developed to identify potential biomarkers in cancer, these methods do not allow for rapid classification of oncogenes versus tumor suppressors taking into account robust differential expression, cutoffs, p-values and non-normality of the data. Here, we propose a methodology, Robust Selection Algorithm (RSA) that addresses these important problems in big data omics analysis. The robustness of the survival analysis is ensured by identification of optimal cutoff values of omics expression, strengthened by p-value computed through intensive random resampling taking into account any non-normality in the data and integration into multi-omic functional networks. Here we have analyzed pan-cancer miRNA patient data to identify functional pathways involved in cancer progression that are associated with selected miRNA identified by RSA. Our approach demonstrates the way in which existing survival analysis techniques can be integrated with a functional network analysis framework to efficiently identify promising biomarkers and novel therapeutic candidates across diseases.

Connectedness in the context of patient-provider relationships: a concept analysis.

PubMed

Phillips-Salimi, Celeste R; Haase, Joan E; Kooken, Wendy Carter

2012-01-01

This paper is a report of an analysis of the concept of connectedness. Previous attempts to conceptualize patient-provider relationships were limited in explaining how such relationships are fostered and maintained, and how they influence patient outcomes. Connectedness is a concept that may provide insights into the advantages of patient-provider relationships; however, the usefulness of this concept in health care is limited by its conceptual ambiguity. Although connectedness is widely used to describe other social relationships, little consistency exists among its definitions and measures. Sources identified through CINAHL, OVID, PubMed and PsychINFO databases and references lists of selected articles between 1983 and 2010. A hybrid concept analysis approach was used, involving a combination of traditional concept analysis strategies that included: describing historical conceptualizations, identifying attributes, critiquing existing definitions, examining boundaries and identifying antecedents and consequences. Using five distinct historical perspectives, seven attributes of connectedness were identified: intimacy, sense of belonging, caring, empathy, respect, trust and reciprocity. A broad definition of connectedness, which can be used in the context of patient-provider relationships, was developed. A preliminary theoretical framework of connectedness was derived from the identified antecedents, attributes and consequences. Research efforts to advance the concept of connectedness in patient-provider relationships have been hampered by a lack of conceptual clarity. This concept analysis offers a clearer understanding of connectedness, provides recommendations for future research and suggests practice implications. © 2011 Blackwell Publishing Ltd.

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.

Integrating genome-wide association study and expression quantitative trait loci data identifies multiple genes and gene set associated with neuroticism.

PubMed

Fan, Qianrui; Wang, Wenyu; Hao, Jingcan; He, Awen; Wen, Yan; Guo, Xiong; Wu, Cuiyan; Ning, Yujie; Wang, Xi; Wang, Sen; Zhang, Feng

2017-08-01

Neuroticism is a fundamental personality trait with significant genetic determinant. To identify novel susceptibility genes for neuroticism, we conducted an integrative analysis of genomic and transcriptomic data of genome wide association study (GWAS) and expression quantitative trait locus (eQTL) study. GWAS summary data was driven from published studies of neuroticism, totally involving 170,906 subjects. eQTL dataset containing 927,753 eQTLs were obtained from an eQTL meta-analysis of 5311 samples. Integrative analysis of GWAS and eQTL data was conducted by summary data-based Mendelian randomization (SMR) analysis software. To identify neuroticism associated gene sets, the SMR analysis results were further subjected to gene set enrichment analysis (GSEA). The gene set annotation dataset (containing 13,311 annotated gene sets) of GSEA Molecular Signatures Database was used. SMR single gene analysis identified 6 significant genes for neuroticism, including MSRA (p value=2.27×10 -10 ), MGC57346 (p value=6.92×10 -7 ), BLK (p value=1.01×10 -6 ), XKR6 (p value=1.11×10 -6 ), C17ORF69 (p value=1.12×10 -6 ) and KIAA1267 (p value=4.00×10 -6 ). Gene set enrichment analysis observed significant association for Chr8p23 gene set (false discovery rate=0.033). Our results provide novel clues for the genetic mechanism studies of neuroticism. Copyright © 2017. Published by Elsevier Inc.

A meta-analysis of public microarray data identifies biological regulatory networks in Parkinson's disease.

PubMed

Su, Lining; Wang, Chunjie; Zheng, Chenqing; Wei, Huiping; Song, Xiaoqing

2018-04-13

Parkinson's disease (PD) is a long-term degenerative disease that is caused by environmental and genetic factors. The networks of genes and their regulators that control the progression and development of PD require further elucidation. We examine common differentially expressed genes (DEGs) from several PD blood and substantia nigra (SN) microarray datasets by meta-analysis. Further we screen the PD-specific genes from common DEGs using GCBI. Next, we used a series of bioinformatics software to analyze the miRNAs, lncRNAs and SNPs associated with the common PD-specific genes, and then identify the mTF-miRNA-gene-gTF network. Our results identified 36 common DEGs in PD blood studies and 17 common DEGs in PD SN studies, and five of the genes were previously known to be associated with PD. Further study of the regulatory miRNAs associated with the common PD-specific genes revealed 14 PD-specific miRNAs in our study. Analysis of the mTF-miRNA-gene-gTF network about PD-specific genes revealed two feed-forward loops: one involving the SPRK2 gene, hsa-miR-19a-3p and SPI1, and the second involving the SPRK2 gene, hsa-miR-17-3p and SPI. The long non-coding RNA (lncRNA)-mediated regulatory network identified lncRNAs associated with PD-specific genes and PD-specific miRNAs. Moreover, single nucleotide polymorphism (SNP) analysis of the PD-specific genes identified two significant SNPs, and SNP analysis of the neurodegenerative disease-specific genes identified seven significant SNPs. Most of these SNPs are present in the 3'-untranslated region of genes and are controlled by several miRNAs. Our study identified a total of 53 common DEGs in PD patients compared with healthy controls in blood and brain datasets and five of these genes were previously linked with PD. Regulatory network analysis identified PD-specific miRNAs, associated long non-coding RNA and feed-forward loops, which contribute to our understanding of the mechanisms underlying PD. The SNPs identified in our study can determine whether a genetic variant is associated with PD. Overall, these findings will help guide our study of the complex molecular mechanism of PD.

Microarray Meta-Analysis Identifies Acute Lung Injury Biomarkers in Donor Lungs That Predict Development of Primary Graft Failure in Recipients

PubMed Central

Haitsma, Jack J.; Furmli, Suleiman; Masoom, Hussain; Liu, Mingyao; Imai, Yumiko; Slutsky, Arthur S.; Beyene, Joseph; Greenwood, Celia M. T.; dos Santos, Claudia

2012-01-01

Objectives To perform a meta-analysis of gene expression microarray data from animal studies of lung injury, and to identify an injury-specific gene expression signature capable of predicting the development of lung injury in humans. Methods We performed a microarray meta-analysis using 77 microarray chips across six platforms, two species and different animal lung injury models exposed to lung injury with or/and without mechanical ventilation. Individual gene chips were classified and grouped based on the strategy used to induce lung injury. Effect size (change in gene expression) was calculated between non-injurious and injurious conditions comparing two main strategies to pool chips: (1) one-hit and (2) two-hit lung injury models. A random effects model was used to integrate individual effect sizes calculated from each experiment. Classification models were built using the gene expression signatures generated by the meta-analysis to predict the development of lung injury in human lung transplant recipients. Results Two injury-specific lists of differentially expressed genes generated from our meta-analysis of lung injury models were validated using external data sets and prospective data from animal models of ventilator-induced lung injury (VILI). Pathway analysis of gene sets revealed that both new and previously implicated VILI-related pathways are enriched with differentially regulated genes. Classification model based on gene expression signatures identified in animal models of lung injury predicted development of primary graft failure (PGF) in lung transplant recipients with larger than 80% accuracy based upon injury profiles from transplant donors. We also found that better classifier performance can be achieved by using meta-analysis to identify differentially-expressed genes than using single study-based differential analysis. Conclusion Taken together, our data suggests that microarray analysis of gene expression data allows for the detection of “injury" gene predictors that can classify lung injury samples and identify patients at risk for clinically relevant lung injury complications. PMID:23071521

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

Comparative genome analysis identifies novel nucleic acid diagnostic targets for use in the specific detection of Haemophilus influenzae.

PubMed

Coughlan, Helena; Reddington, Kate; Tuite, Nina; Boo, Teck Wee; Cormican, Martin; Barrett, Louise; Smith, Terry J; Clancy, Eoin; Barry, Thomas

2015-10-01

Haemophilus influenzae is recognised as an important human pathogen associated with invasive infections, including bloodstream infection and meningitis. Currently used molecular-based diagnostic assays lack specificity in correctly detecting and identifying H. influenzae. As such, there is a need to develop novel diagnostic assays for the specific identification of H. influenzae. Whole genome comparative analysis was performed to identify putative diagnostic targets, which are unique in nucleotide sequence to H. influenzae. From this analysis, we identified 2H. influenzae putative diagnostic targets, phoB and pstA, for use in real-time PCR diagnostic assays. Real-time PCR diagnostic assays using these targets were designed and optimised to specifically detect and identify all 55H. influenzae strains tested. These novel rapid assays can be applied to the specific detection and identification of H. influenzae for use in epidemiological studies and could also enable improved monitoring of invasive disease caused by these bacteria. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

Cluster analysis of spontaneous preterm birth phenotypes identifies potential associations among preterm birth mechanisms

PubMed Central

Esplin, M Sean; Manuck, Tracy A.; Varner, Michael W.; Christensen, Bryce; Biggio, Joseph; Bukowski, Radek; Parry, Samuel; Zhang, Heping; Huang, Hao; Andrews, William; Saade, George; Sadovsky, Yoel; Reddy, Uma M.; Ilekis, John

2015-01-01

Objective We sought to employ an innovative tool based on common biological pathways to identify specific phenotypes among women with spontaneous preterm birth (SPTB), in order to enhance investigators' ability to identify to highlight common mechanisms and underlying genetic factors responsible for SPTB. Study Design A secondary analysis of a prospective case-control multicenter study of SPTB. All cases delivered a preterm singleton at SPTB ≤34.0 weeks gestation. Each woman was assessed for the presence of underlying SPTB etiologies. A hierarchical cluster analysis was used to identify groups of women with homogeneous phenotypic profiles. One of the phenotypic clusters was selected for candidate gene association analysis using VEGAS software. Results 1028 women with SPTB were assigned phenotypes. Hierarchical clustering of the phenotypes revealed five major clusters. Cluster 1 (N=445) was characterized by maternal stress, cluster 2 (N=294) by premature membrane rupture, cluster 3 (N=120) by familial factors, and cluster 4 (N=63) by maternal comorbidities. Cluster 5 (N=106) was multifactorial, characterized by infection (INF), decidual hemorrhage (DH) and placental dysfunction (PD). These three phenotypes were highly correlated by Chi-square analysis [PD and DH (p<2.2e-6); PD and INF (p=6.2e-10); INF and DH (p=0.0036)]. Gene-based testing identified the INS (insulin) gene as significantly associated with cluster 3 of SPTB. Conclusion We identified 5 major clusters of SPTB based on a phenotype tool and hierarchal clustering. There was significant correlation between several of the phenotypes. The INS gene was associated with familial factors underlying SPTB. PMID:26070700

Neural network system and methods for analysis of organic materials and structures using spectral data

DOEpatents

Meyer, B.J.; Sellers, J.P.; Thomsen, J.U.

1993-06-08

Apparatus and processes are described for recognizing and identifying materials. Characteristic spectra are obtained for the materials via spectroscopy techniques including nuclear magnetic resonance spectroscopy, infrared absorption analysis, x-ray analysis, mass spectroscopy and gas chromatography. Desired portions of the spectra may be selected and then placed in proper form and format for presentation to a number of input layer neurons in an offline neural network. The network is first trained according to a predetermined training process; it may then be employed to identify particular materials. Such apparatus and processes are particularly useful for recognizing and identifying organic compounds such as complex carbohydrates, whose spectra conventionally require a high level of training and many hours of hard work to identify, and are frequently indistinguishable from one another by human interpretation.

A Cross-Cancer Genetic Association Analysis of the DNA Repair and DNA Damage Signaling Pathways for Lung, Ovary, Prostate, Breast, and Colorectal Cancer.

PubMed

Scarbrough, Peter M; Weber, Rachel Palmieri; Iversen, Edwin S; Brhane, Yonathan; Amos, Christopher I; Kraft, Peter; Hung, Rayjean J; Sellers, Thomas A; Witte, John S; Pharoah, Paul; Henderson, Brian E; Gruber, Stephen B; Hunter, David J; Garber, Judy E; Joshi, Amit D; McDonnell, Kevin; Easton, Doug F; Eeles, Ros; Kote-Jarai, Zsofia; Muir, Kenneth; Doherty, Jennifer A; Schildkraut, Joellen M

2016-01-01

DNA damage is an established mediator of carcinogenesis, although genome-wide association studies (GWAS) have identified few significant loci. This cross-cancer site, pooled analysis was performed to increase the power to detect common variants of DNA repair genes associated with cancer susceptibility. We conducted a cross-cancer analysis of 60,297 single nucleotide polymorphisms, at 229 DNA repair gene regions, using data from the NCI Genetic Associations and Mechanisms in Oncology (GAME-ON) Network. Our analysis included data from 32 GWAS and 48,734 controls and 51,537 cases across five cancer sites (breast, colon, lung, ovary, and prostate). Because of the unavailability of individual data, data were analyzed at the aggregate level. Meta-analysis was performed using the Association analysis for SubSETs (ASSET) software. To test for genetic associations that might escape individual variant testing due to small effect sizes, pathway analysis of eight DNA repair pathways was performed using hierarchical modeling. We identified three susceptibility DNA repair genes, RAD51B (P < 5.09 × 10(-6)), MSH5 (P < 5.09 × 10(-6)), and BRCA2 (P = 5.70 × 10(-6)). Hierarchical modeling identified several pleiotropic associations with cancer risk in the base excision repair, nucleotide excision repair, mismatch repair, and homologous recombination pathways. Only three susceptibility loci were identified, which had all been previously reported. In contrast, hierarchical modeling identified several pleiotropic cancer risk associations in key DNA repair pathways. Results suggest that many common variants in DNA repair genes are likely associated with cancer susceptibility through small effect sizes that do not meet stringent significance testing criteria. ©2015 American Association for Cancer Research.

Drug target identification using network analysis: Taking active components in Sini decoction as an example

NASA Astrophysics Data System (ADS)

Chen, Si; Jiang, Hailong; Cao, Yan; Wang, Yun; Hu, Ziheng; Zhu, Zhenyu; Chai, Yifeng

2016-04-01

Identifying the molecular targets for the beneficial effects of active small-molecule compounds simultaneously is an important and currently unmet challenge. In this study, we firstly proposed network analysis by integrating data from network pharmacology and metabolomics to identify targets of active components in sini decoction (SND) simultaneously against heart failure. To begin with, 48 potential active components in SND against heart failure were predicted by serum pharmacochemistry, text mining and similarity match. Then, we employed network pharmacology including text mining and molecular docking to identify the potential targets of these components. The key enriched processes, pathways and related diseases of these target proteins were analyzed by STRING database. At last, network analysis was conducted to identify most possible targets of components in SND. Among the 25 targets predicted by network analysis, tumor necrosis factor α (TNF-α) was firstly experimentally validated in molecular and cellular level. Results indicated that hypaconitine, mesaconitine, higenamine and quercetin in SND can directly bind to TNF-α, reduce the TNF-α-mediated cytotoxicity on L929 cells and exert anti-myocardial cell apoptosis effects. We envisage that network analysis will also be useful in target identification of a bioactive compound.

Drug target identification using network analysis: Taking active components in Sini decoction as an example

PubMed Central

Chen, Si; Jiang, Hailong; Cao, Yan; Wang, Yun; Hu, Ziheng; Zhu, Zhenyu; Chai, Yifeng

2016-01-01

Identifying the molecular targets for the beneficial effects of active small-molecule compounds simultaneously is an important and currently unmet challenge. In this study, we firstly proposed network analysis by integrating data from network pharmacology and metabolomics to identify targets of active components in sini decoction (SND) simultaneously against heart failure. To begin with, 48 potential active components in SND against heart failure were predicted by serum pharmacochemistry, text mining and similarity match. Then, we employed network pharmacology including text mining and molecular docking to identify the potential targets of these components. The key enriched processes, pathways and related diseases of these target proteins were analyzed by STRING database. At last, network analysis was conducted to identify most possible targets of components in SND. Among the 25 targets predicted by network analysis, tumor necrosis factor α (TNF-α) was firstly experimentally validated in molecular and cellular level. Results indicated that hypaconitine, mesaconitine, higenamine and quercetin in SND can directly bind to TNF-α, reduce the TNF-α-mediated cytotoxicity on L929 cells and exert anti-myocardial cell apoptosis effects. We envisage that network analysis will also be useful in target identification of a bioactive compound. PMID:27095146

Expediting Combinatorial Data Set Analysis by Combining Human and Algorithmic Analysis.

PubMed

Stein, Helge Sören; Jiao, Sally; Ludwig, Alfred

2017-01-09

A challenge in combinatorial materials science remains the efficient analysis of X-ray diffraction (XRD) data and its correlation to functional properties. Rapid identification of phase-regions and proper assignment of corresponding crystal structures is necessary to keep pace with the improved methods for synthesizing and characterizing materials libraries. Therefore, a new modular software called htAx (high-throughput analysis of X-ray and functional properties data) is presented that couples human intelligence tasks used for "ground-truth" phase-region identification with subsequent unbiased verification by an algorithm to efficiently analyze which phases are present in a materials library. Identified phases and phase-regions may then be correlated to functional properties in an expedited manner. For the functionality of htAx to be proven, two previously published XRD benchmark data sets of the materials systems Al-Cr-Fe-O and Ni-Ti-Cu are analyzed by htAx. The analysis of ∼1000 XRD patterns takes less than 1 day with htAx. The proposed method reliably identifies phase-region boundaries and robustly identifies multiphase structures. The method also addresses the problem of identifying regions with previously unpublished crystal structures using a special daisy ternary plot.

Gene Expression Profiling of Gastric Cancer

PubMed Central

Marimuthu, Arivusudar; Jacob, Harrys K.C.; Jakharia, Aniruddha; Subbannayya, Yashwanth; Keerthikumar, Shivakumar; Kashyap, Manoj Kumar; Goel, Renu; Balakrishnan, Lavanya; Dwivedi, Sutopa; Pathare, Swapnali; Dikshit, Jyoti Bajpai; Maharudraiah, Jagadeesha; Singh, Sujay; Sameer Kumar, Ghantasala S; Vijayakumar, M.; Veerendra Kumar, Kariyanakatte Veeraiah; Premalatha, Chennagiri Shrinivasamurthy; Tata, Pramila; Hariharan, Ramesh; Roa, Juan Carlos; Prasad, T.S.K; Chaerkady, Raghothama; Kumar, Rekha Vijay; Pandey, Akhilesh

2015-01-01

Gastric cancer is the second leading cause of cancer death worldwide, both in men and women. A genomewide gene expression analysis was carried out to identify differentially expressed genes in gastric adenocarcinoma tissues as compared to adjacent normal tissues. We used Agilent’s whole human genome oligonucleotide microarray platform representing ~41,000 genes to carry out gene expression analysis. Two-color microarray analysis was employed to directly compare the expression of genes between tumor and normal tissues. Through this approach, we identified several previously known candidate genes along with a number of novel candidate genes in gastric cancer. Testican-1 (SPOCK1) was one of the novel molecules that was 10-fold upregulated in tumors. Using tissue microarrays, we validated the expression of testican-1 by immunohistochemical staining. It was overexpressed in 56% (160/282) of the cases tested. Pathway analysis led to the identification of several networks in which SPOCK1 was among the topmost networks of interacting genes. By gene enrichment analysis, we identified several genes involved in cell adhesion and cell proliferation to be significantly upregulated while those corresponding to metabolic pathways were significantly downregulated. The differentially expressed genes identified in this study are candidate biomarkers for gastric adenoacarcinoma. PMID:27030788

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

USE OF BIOASSAY-DIRECTED CHEMICAL ANALYSIS FOR IDENTIFYING MUTAGENIC COMPOUNDS IN URBAN AIR AND COMBUSTION EMISSIONS

EPA Science Inventory

Bioassay-directed chemical analysis fractionation has been used for 30 years to identify mutagenic classes of compounds in complex mixtures. Most studies have used the Salmonella (Ames) mutagenicity assay, and we have recently applied this methodology to two standard reference sa...

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…

A Large-Scale Multi-ancestry Genome-wide Study Accounting for Smoking Behavior Identifies Multiple Significant Loci for Blood Pressure.

PubMed

Sung, Yun J; Winkler, Thomas W; de Las Fuentes, Lisa; Bentley, Amy R; Brown, Michael R; Kraja, Aldi T; Schwander, Karen; Ntalla, Ioanna; Guo, Xiuqing; Franceschini, Nora; Lu, Yingchang; Cheng, Ching-Yu; Sim, Xueling; Vojinovic, Dina; Marten, Jonathan; Musani, Solomon K; Li, Changwei; Feitosa, Mary F; Kilpeläinen, Tuomas O; Richard, Melissa A; Noordam, Raymond; Aslibekyan, Stella; Aschard, Hugues; Bartz, Traci M; Dorajoo, Rajkumar; Liu, Yongmei; Manning, Alisa K; Rankinen, Tuomo; Smith, Albert Vernon; Tajuddin, Salman M; Tayo, Bamidele O; Warren, Helen R; Zhao, Wei; Zhou, Yanhua; Matoba, Nana; Sofer, Tamar; Alver, Maris; Amini, Marzyeh; Boissel, Mathilde; Chai, Jin Fang; Chen, Xu; Divers, Jasmin; Gandin, Ilaria; Gao, Chuan; Giulianini, Franco; Goel, Anuj; Harris, Sarah E; Hartwig, Fernando Pires; Horimoto, Andrea R V R; Hsu, Fang-Chi; Jackson, Anne U; Kähönen, Mika; Kasturiratne, Anuradhani; Kühnel, Brigitte; Leander, Karin; Lee, Wen-Jane; Lin, Keng-Hung; 'an Luan, Jian; McKenzie, Colin A; Meian, He; Nelson, Christopher P; Rauramaa, Rainer; Schupf, Nicole; Scott, Robert A; Sheu, Wayne H H; Stančáková, Alena; Takeuchi, Fumihiko; van der Most, Peter J; Varga, Tibor V; Wang, Heming; Wang, Yajuan; Ware, Erin B; Weiss, Stefan; Wen, Wanqing; Yanek, Lisa R; Zhang, Weihua; Zhao, Jing Hua; Afaq, Saima; Alfred, Tamuno; Amin, Najaf; Arking, Dan; Aung, Tin; Barr, R Graham; Bielak, Lawrence F; Boerwinkle, Eric; Bottinger, Erwin P; Braund, Peter S; Brody, Jennifer A; Broeckel, Ulrich; Cabrera, Claudia P; Cade, Brian; Caizheng, Yu; Campbell, Archie; Canouil, Mickaël; Chakravarti, Aravinda; Chauhan, Ganesh; Christensen, Kaare; Cocca, Massimiliano; Collins, Francis S; Connell, John M; de Mutsert, Renée; de Silva, H Janaka; Debette, Stephanie; Dörr, Marcus; Duan, Qing; Eaton, Charles B; Ehret, Georg; Evangelou, Evangelos; Faul, Jessica D; Fisher, Virginia A; Forouhi, Nita G; Franco, Oscar H; Friedlander, Yechiel; Gao, He; Gigante, Bruna; Graff, Misa; Gu, C Charles; Gu, Dongfeng; Gupta, Preeti; Hagenaars, Saskia P; Harris, Tamara B; He, Jiang; Heikkinen, Sami; Heng, Chew-Kiat; Hirata, Makoto; Hofman, Albert; Howard, Barbara V; Hunt, Steven; Irvin, Marguerite R; Jia, Yucheng; Joehanes, Roby; Justice, Anne E; Katsuya, Tomohiro; Kaufman, Joel; Kerrison, Nicola D; Khor, Chiea Chuen; Koh, Woon-Puay; Koistinen, Heikki A; Komulainen, Pirjo; Kooperberg, Charles; Krieger, Jose E; Kubo, Michiaki; Kuusisto, Johanna; Langefeld, Carl D; Langenberg, Claudia; Launer, Lenore J; Lehne, Benjamin; Lewis, Cora E; Li, Yize; Lim, Sing Hui; Lin, Shiow; Liu, Ching-Ti; Liu, Jianjun; Liu, Jingmin; Liu, Kiang; Liu, Yeheng; Loh, Marie; Lohman, Kurt K; Long, Jirong; Louie, Tin; Mägi, Reedik; Mahajan, Anubha; Meitinger, Thomas; Metspalu, Andres; Milani, Lili; Momozawa, Yukihide; Morris, Andrew P; Mosley, Thomas H; Munson, Peter; Murray, Alison D; Nalls, Mike A; Nasri, Ubaydah; Norris, Jill M; North, Kari; Ogunniyi, Adesola; Padmanabhan, Sandosh; Palmas, Walter R; Palmer, Nicholette D; Pankow, James S; Pedersen, Nancy L; Peters, Annette; Peyser, Patricia A; Polasek, Ozren; Raitakari, Olli T; Renström, Frida; Rice, Treva K; Ridker, Paul M; Robino, Antonietta; Robinson, Jennifer G; Rose, Lynda M; Rudan, Igor; Sabanayagam, Charumathi; Salako, Babatunde L; Sandow, Kevin; Schmidt, Carsten O; Schreiner, Pamela J; Scott, William R; Seshadri, Sudha; Sever, Peter; Sitlani, Colleen M; Smith, Jennifer A; Snieder, Harold; Starr, John M; Strauch, Konstantin; Tang, Hua; Taylor, Kent D; Teo, Yik Ying; Tham, Yih Chung; Uitterlinden, André G; Waldenberger, Melanie; Wang, Lihua; Wang, Ya X; Wei, Wen Bin; Williams, Christine; Wilson, Gregory; Wojczynski, Mary K; Yao, Jie; Yuan, Jian-Min; Zonderman, Alan B; Becker, Diane M; Boehnke, Michael; Bowden, Donald W; Chambers, John C; Chen, Yii-Der Ida; de Faire, Ulf; Deary, Ian J; Esko, Tõnu; Farrall, Martin; Forrester, Terrence; Franks, Paul W; Freedman, Barry I; Froguel, Philippe; Gasparini, Paolo; Gieger, Christian; Horta, Bernardo Lessa; Hung, Yi-Jen; Jonas, Jost B; Kato, Norihiro; Kooner, Jaspal S; Laakso, Markku; Lehtimäki, Terho; Liang, Kae-Woei; Magnusson, Patrik K E; Newman, Anne B; Oldehinkel, Albertine J; Pereira, Alexandre C; Redline, Susan; Rettig, Rainer; Samani, Nilesh J; Scott, James; Shu, Xiao-Ou; van der Harst, Pim; Wagenknecht, Lynne E; Wareham, Nicholas J; Watkins, Hugh; Weir, David R; Wickremasinghe, Ananda R; Wu, Tangchun; Zheng, Wei; Kamatani, Yoichiro; Laurie, Cathy C; Bouchard, Claude; Cooper, Richard S; Evans, Michele K; Gudnason, Vilmundur; Kardia, Sharon L R; Kritchevsky, Stephen B; Levy, Daniel; O'Connell, Jeff R; Psaty, Bruce M; van Dam, Rob M; Sims, Mario; Arnett, Donna K; Mook-Kanamori, Dennis O; Kelly, Tanika N; Fox, Ervin R; Hayward, Caroline; Fornage, Myriam; Rotimi, Charles N; Province, Michael A; van Duijn, Cornelia M; Tai, E Shyong; Wong, Tien Yin; Loos, Ruth J F; Reiner, Alex P; Rotter, Jerome I; Zhu, Xiaofeng; Bierut, Laura J; Gauderman, W James; Caulfield, Mark J; Elliott, Paul; Rice, Kenneth; Munroe, Patricia B; Morrison, Alanna C; Cupples, L Adrienne; Rao, Dabeeru C; Chasman, Daniel I

2018-03-01

Genome-wide association analysis advanced understanding of blood pressure (BP), a major risk factor for vascular conditions such as coronary heart disease and stroke. Accounting for smoking behavior may help identify BP loci and extend our knowledge of its genetic architecture. We performed genome-wide association meta-analyses of systolic and diastolic BP incorporating gene-smoking interactions in 610,091 individuals. Stage 1 analysis examined ∼18.8 million SNPs and small insertion/deletion variants in 129,913 individuals from four ancestries (European, African, Asian, and Hispanic) with follow-up analysis of promising variants in 480,178 additional individuals from five ancestries. We identified 15 loci that were genome-wide significant (p < 5 × 10 -8 ) in stage 1 and formally replicated in stage 2. A combined stage 1 and 2 meta-analysis identified 66 additional genome-wide significant loci (13, 35, and 18 loci in European, African, and trans-ancestry, respectively). A total of 56 known BP loci were also identified by our results (p < 5 × 10 -8 ). Of the newly identified loci, ten showed significant interaction with smoking status, but none of them were replicated in stage 2. Several loci were identified in African ancestry, highlighting the importance of genetic studies in diverse populations. The identified loci show strong evidence for regulatory features and support shared pathophysiology with cardiometabolic and addiction traits. They also highlight a role in BP regulation for biological candidates such as modulators of vascular structure and function (CDKN1B, BCAR1-CFDP1, PXDN, EEA1), ciliopathies (SDCCAG8, RPGRIP1L), telomere maintenance (TNKS, PINX1, AKTIP), and central dopaminergic signaling (MSRA, EBF2). Copyright © 2018 American Society of Human Genetics. All rights reserved.

Trends in public perceptions and preferences on energy and environmental policy

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

Farhar, B.C.

1993-02-01

This report presents selected results from a secondary analysis of public opinion surveys, taken at the national and state/local levels, relevant to energy and environmental policy choices. The data base used in the analysis includes about 2000 items from nearly 600 separate surveys conducted between 1979 and 1992. Answers to word-for-word questions were traced over time, permitting trend analysis. Patterns of response were also identified for findings from similarly worded survey items. The analysis identifies changes in public opinion concerning energy during the past 10 to 15 years.

Estimating Manpower, Personnel, and Training Requirements Early in the Weapon System Acquisition Process: An Application of the HARDMAN Methodology to the Army’s Division Support Weapon System

DTIC Science & Technology

1984-02-01

identifies the supply of personnel and training resources that can be expected at critical dates in the conceptual weapon system’s acquisition schedule...impact analysis matches demand to supply and identifies shortfalls in skills, new skill requirements, and high resource drivers. The tradeoff analysis...system. Step 5 - Conduct Impact Analysis The Impact Analysis determines the Army’s supply of those personnel and training resources required by the

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

White, Amanda M.; Daly, Don S.; Willse, Alan R.

The Automated Microarray Image Analysis (AMIA) Toolbox for MATLAB is a flexible, open-source microarray image analysis tool that allows the user to customize analysis of sets of microarray images. This tool provides several methods of identifying and quantify spot statistics, as well as extensive diagnostic statistics and images to identify poor data quality or processing. The open nature of this software allows researchers to understand the algorithms used to provide intensity estimates and to modify them easily if desired.

Identifying the Most Important 21st Century Workforce Competencies: An Analysis of the Occupational Information Network (O*NET). Research Report. ETS RR-13-21

ERIC Educational Resources Information Center

Burrus, Jeremy; Jackson, Teresa; Xi, Nuo; Steinberg, Jonathan

2013-01-01

To identify the most important competencies for college graduates to succeed in the 21st century workforce, we conducted an analysis of the Occupational Information Network (O*NET) database. O*NET is a large job analysis operated and maintained by the U.S. Department of Labor. We specifically analyzed ratings of the importance of abilities (52…

Structural Identifiability of Dynamic Systems Biology Models

PubMed Central

Villaverde, Alejandro F.

2016-01-01

A powerful way of gaining insight into biological systems is by creating a nonlinear differential equation model, which usually contains many unknown parameters. Such a model is called structurally identifiable if it is possible to determine the values of its parameters from measurements of the model outputs. Structural identifiability is a prerequisite for parameter estimation, and should be assessed before exploiting a model. However, this analysis is seldom performed due to the high computational cost involved in the necessary symbolic calculations, which quickly becomes prohibitive as the problem size increases. In this paper we show how to analyse the structural identifiability of a very general class of nonlinear models by extending methods originally developed for studying observability. We present results about models whose identifiability had not been previously determined, report unidentifiabilities that had not been found before, and show how to modify those unidentifiable models to make them identifiable. This method helps prevent problems caused by lack of identifiability analysis, which can compromise the success of tasks such as experiment design, parameter estimation, and model-based optimization. The procedure is called STRIKE-GOLDD (STRuctural Identifiability taKen as Extended-Generalized Observability with Lie Derivatives and Decomposition), and it is implemented in a MATLAB toolbox which is available as open source software. The broad applicability of this approach facilitates the analysis of the increasingly complex models used in systems biology and other areas. PMID:27792726

Framing life and death on YouTube: the strategic communication of organ donation messages by organ procurement organizations.

PubMed

VanderKnyff, Jeremy; Friedman, Daniela B; Tanner, Andrea

2015-01-01

Using a sample of YouTube videos posted on the YouTube channels of organ procurement organizations, a content analysis was conducted to identify the frames used to strategically communicate prodonation messages. A total of 377 videos were coded for general characteristics, format, speaker characteristics, organs discussed, structure, problem definition, and treatment. Principal components analysis identified message frames, and k-means cluster analysis established distinct groupings of videos on the basis of the strength of their relationship to message frames. Analysis of these frames and clusters found that organ procurement organizations present multiple, and sometimes competing, video types and message frames on YouTube. This study serves as important formative research that will inform future studies to measure the effectiveness of the distinct message frames and clusters identified.

Identifying influential factors of business process performance using dependency analysis

NASA Astrophysics Data System (ADS)

Wetzstein, Branimir; Leitner, Philipp; Rosenberg, Florian; Dustdar, Schahram; Leymann, Frank

2011-02-01

We present a comprehensive framework for identifying influential factors of business process performance. In particular, our approach combines monitoring of process events and Quality of Service (QoS) measurements with dependency analysis to effectively identify influential factors. The framework uses data mining techniques to construct tree structures to represent dependencies of a key performance indicator (KPI) on process and QoS metrics. These dependency trees allow business analysts to determine how process KPIs depend on lower-level process metrics and QoS characteristics of the IT infrastructure. The structure of the dependencies enables a drill-down analysis of single factors of influence to gain a deeper knowledge why certain KPI targets are not met.

Online Patient Education for Chronic Disease Management: Consumer Perspectives.

PubMed

Win, Khin Than; Hassan, Naffisah Mohd; Oinas-Kukkonen, Harri; Probst, Yasmine

2016-04-01

Patient education plays an important role in chronic disease management. The aim of this study is to identify patients' preferences in regard to the design features of effective online patient education (OPE) and the benefits. A review of the existing literature was conducted in order to identify the benefits of OPE and its essential design features. These design features were empirically tested by conducting survey with patients and caregivers. Reliability analysis, construct validity and regression analysis were performed for data analysis. The results identified patient-tailored information, interactivity, content credibility, clear presentation of content, use of multimedia and interpretability as the essential design features of online patient education websites for chronic disease management.

Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis

DTIC Science & Technology

2017-10-13

AWARD NUMBER: W81XWH-15-2-0032 TITLE: Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis...TITLE AND SUBTITLE 5a. CONTRACT NUMBER W81XWH-15-2-0032 5b. GRANT NUMBER Identifying Subgroups of Tinnitus Using Novel Resting State fMRI...Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT The subject of the project is FY14 PRMRP Topic Area – Tinnitus . The broad goal is

Human factors process failure modes and effects analysis (HF PFMEA) software tool

NASA Technical Reports Server (NTRS)

Chandler, Faith T. (Inventor); Relvini, Kristine M. (Inventor); Shedd, Nathaneal P. (Inventor); Valentino, William D. (Inventor); Philippart, Monica F. (Inventor); Bessette, Colette I. (Inventor)

2011-01-01

Methods, computer-readable media, and systems for automatically performing Human Factors Process Failure Modes and Effects Analysis for a process are provided. At least one task involved in a process is identified, where the task includes at least one human activity. The human activity is described using at least one verb. A human error potentially resulting from the human activity is automatically identified, the human error is related to the verb used in describing the task. A likelihood of occurrence, detection, and correction of the human error is identified. The severity of the effect of the human error is identified. The likelihood of occurrence, and the severity of the risk of potential harm is identified. The risk of potential harm is compared with a risk threshold to identify the appropriateness of corrective measures.

Large-scale integrative network-based analysis identifies common pathways disrupted by copy number alterations across cancers

PubMed Central

2013-01-01

Background Many large-scale studies analyzed high-throughput genomic data to identify altered pathways essential to the development and progression of specific types of cancer. However, no previous study has been extended to provide a comprehensive analysis of pathways disrupted by copy number alterations across different human cancers. Towards this goal, we propose a network-based method to integrate copy number alteration data with human protein-protein interaction networks and pathway databases to identify pathways that are commonly disrupted in many different types of cancer. Results We applied our approach to a data set of 2,172 cancer patients across 16 different types of cancers, and discovered a set of commonly disrupted pathways, which are likely essential for tumor formation in majority of the cancers. We also identified pathways that are only disrupted in specific cancer types, providing molecular markers for different human cancers. Analysis with independent microarray gene expression datasets confirms that the commonly disrupted pathways can be used to identify patient subgroups with significantly different survival outcomes. We also provide a network view of disrupted pathways to explain how copy number alterations affect pathways that regulate cell growth, cycle, and differentiation for tumorigenesis. Conclusions In this work, we demonstrated that the network-based integrative analysis can help to identify pathways disrupted by copy number alterations across 16 types of human cancers, which are not readily identifiable by conventional overrepresentation-based and other pathway-based methods. All the results and source code are available at http://compbio.cs.umn.edu/NetPathID/. PMID:23822816

Identifying causes of adverse events detected by an automated trigger tool through in-depth analysis.

PubMed

Muething, S E; Conway, P H; Kloppenborg, E; Lesko, A; Schoettker, P J; Seid, M; Kotagal, U

2010-10-01

To describe how in-depth analysis of adverse events can reveal underlying causes. Triggers for adverse events were developed using the hospital's computerised medical record (naloxone for opiate-related oversedation and administration of a glucose bolus while on insulin for insulin-related hypoglycaemia). Triggers were identified daily. Based on information from the medical record and interviews, a subject expert determined if an adverse drug event had occurred and then conducted a real-time analysis to identify event characteristics. Expert groups, consisting of frontline staff and specialist physicians, examined event characteristics and determined the apparent cause. 30 insulin-related hypoglycaemia events and 34 opiate-related oversedation events were identified by the triggers over 16 and 21 months, respectively. In the opinion of the experts, patients receiving continuous-infusion insulin and those receiving dextrose only via parenteral nutrition were at increased risk for insulin-related hypoglycaemia. Lack of standardisation in insulin-dosing decisions and variation regarding when and how much to adjust insulin doses in response to changing glucose levels were identified as common causes of the adverse events. Opiate-related oversedation events often occurred within 48 h of surgery. Variation in pain management in the operating room and post-anaesthesia care unit was identified by the experts as potential causes. Variations in practice, multiple services writing orders, multidrug regimens and variations in interpretation of patient assessments were also noted as potential contributing causes. Identification of adverse drug events through an automated trigger system, supplemented by in-depth analysis, can help identify targets for intervention and improvement.

Genetic Biomarkers of Barrett's Esophagus Susceptibility and Progression to Dysplasia and Cancer: A Systematic Review and Meta-Analysis.

PubMed

Findlay, John M; Middleton, Mark R; Tomlinson, Ian

2016-01-01

Barrett's esophagus (BE) is a common and important precursor lesion of esophageal adenocarcinoma (EAC). A third of patients with BE are asymptomatic, and our ability to predict the risk of progression of metaplasia to dysplasia and EAC (and therefore guide management) is limited. There is an urgent need for clinically useful biomarkers of susceptibility to both BE and risk of subsequent progression. This study aims to systematically identify, review, and meta-analyze genetic biomarkers reported to predict both. A systematic review of the PubMed and EMBASE databases was performed in May 2014. Study and evidence quality were appraised using the revised American Society of Clinical Oncology guidelines, and modified Recommendations for Tumor Marker Scores. Meta-analysis was performed for all markers assessed by more than one study. A total of 251 full-text articles were reviewed; 52 were included. A total of 33 germline markers of susceptibility were identified (level of evidence II-III); 17 were included. Five somatic markers of progression were identified; meta-analysis demonstrated significant associations for chromosomal instability (level of evidence II). One somatic marker of progression/relapse following photodynamic therapy was identified. However, a number of failings of methodology and reporting were identified. This is the first systematic review and meta-analysis to evaluate genetic biomarkers of BE susceptibility and risk of progression. While a number of limitations of study quality temper the utility of those markers identified, some-in particular, those identified by genome-wide association studies, and chromosomal instability for progression-appear plausible, although robust validation is required.

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.

Functional Analysis of Problem Behavior: A Systematic Approach for Identifying Idiosyncratic Variables

PubMed Central

Roscoe, Eileen M.; Schlichenmeyer, Kevin J.; Dube, William V.

2015-01-01

When inconclusive functional analysis (FA) outcomes occur, a number of modifications have been made to enhance the putative establishing operation or consequence associated with behavioral maintenance. However, a systematic method for identifying relevant events to test during modified FAs has not been evaluated. The purpose of this study was to develop and evaluate a technology for systematically identifying events to test in a modified FA after an initial FA led to inconclusive outcomes. Six individuals whose initial FA showed little or no responding or high levels only in the control condition participated. An indirect assessment (IA) questionnaire developed for identifying idiosyncratic variables was administered, and a descriptive analysis (DA) was conducted. Results from the IA only or a combination of the IA and DA were used to inform modified FA test and control conditions. Conclusive FA outcomes were obtained with five of the six participants during the modified FA phase. PMID:25930176

Potential ligand-binding residues in rat olfactory receptors identified by correlated mutation analysis

NASA Technical Reports Server (NTRS)

Singer, M. S.; Oliveira, L.; Vriend, G.; Shepherd, G. M.

1995-01-01

A family of G-protein-coupled receptors is believed to mediate the recognition of odor molecules. In order to identify potential ligand-binding residues, we have applied correlated mutation analysis to receptor sequences from the rat. This method identifies pairs of sequence positions where residues remain conserved or mutate in tandem, thereby suggesting structural or functional importance. The analysis supported molecular modeling studies in suggesting several residues in positions that were consistent with ligand-binding function. Two of these positions, dominated by histidine residues, may play important roles in ligand binding and could confer broad specificity to mammalian odor receptors. The presence of positive (overdominant) selection at some of the identified positions provides additional evidence for roles in ligand binding. Higher-order groups of correlated residues were also observed. Each group may interact with an individual ligand determinant, and combinations of these groups may provide a multi-dimensional mechanism for receptor diversity.

Spatial modeling of cutaneous leishmaniasis in the Andean region of Colombia.

PubMed

Pérez-Flórez, Mauricio; Ocampo, Clara Beatriz; Valderrama-Ardila, Carlos; Alexander, Neal

2016-06-27

The objective of this research was to identify environmental risk factors for cutaneous leishmaniasis (CL) in Colombia and map high-risk municipalities. The study area was the Colombian Andean region, comprising 715 rural and urban municipalities. We used 10 years of CL surveillance: 2000-2009. We used spatial-temporal analysis - conditional autoregressive Poisson random effects modelling - in a Bayesian framework to model the dependence of municipality-level incidence on land use, climate, elevation and population density. Bivariable spatial analysis identified rainforests, forests and secondary vegetation, temperature, and annual precipitation as positively associated with CL incidence. By contrast, livestock agroecosystems and temperature seasonality were negatively associated. Multivariable analysis identified land use - rainforests and agro-livestock - and climate - temperature, rainfall and temperature seasonality - as best predictors of CL. We conclude that climate and land use can be used to identify areas at high risk of CL and that this approach is potentially applicable elsewhere in Latin America.

Identifying the readiness of patients in implementing telemedicine in northern Louisiana for an oncology practice.

PubMed

Gurupur, Varadraj; Shettian, Kruparaj; Xu, Peixin; Hines, Scott; Desselles, Mitzi; Dhawan, Manish; Wan, Thomas Th; Raffenaud, Amanda; Anderson, Lindsey

2017-09-01

This study identified the readiness factors that may create challenges in the use of telemedicine among patients in northern Louisiana with cancer. To identify these readiness factors, the team of investigators developed 19 survey questions that were provided to the patients or to their caregivers. The team collected responses from 147 respondents from rural and urban residential backgrounds. These responses were used to identify the individuals' readiness for utilising telemedicine through factor analysis, Cronbach's alpha reliability test, analysis of variance and ordinary least squares regression. The analysis results indicated that the favourable factor (positive readiness item) had a mean value of 3.47, whereas the unfavourable factor (negative readiness item) had a mean value of 2.76. Cronbach's alpha reliability test provided an alpha value of 0.79. Overall, our study indicated a positive attitude towards the use of telemedicine in northern Louisiana.

Identifying Contingency Requirements using Obstacle Analysis on an Unpiloted Aerial Vehicle

NASA Technical Reports Server (NTRS)

Lutz, Robyn R.; Nelson, Stacy; Patterson-Hine, Ann; Frost, Chad R.; Tal, Doron

2005-01-01

This paper describes experience using Obstacle Analysis to identify contingency requirements on an unpiloted aerial vehicle. A contingency is an operational anomaly, and may or may not involve component failure. The challenges to this effort were: ( I ) rapid evolution of the system while operational, (2) incremental autonomy as capabilities were transferred from ground control to software control and (3) the eventual safety-criticality of such systems as they begin to fly over populated areas. The results reported here are preliminary but show that Obstacle Analysis helped (1) identify new contingencies that appeared as autonomy increased; (2) identify new alternatives for handling both previously known and new contingencies; and (3) investigate the continued validity of existing software requirements for contingency handling. Since many mobile, intelligent systems are built using a development process that poses the same challenges, the results appear to have applicability to other similar systems.

Single Marker and Haplotype-Based Association Analysis of Semolina and Pasta Colour in Elite Durum Wheat Breeding Lines Using a High-Density Consensus Map.

PubMed

N'Diaye, Amidou; Haile, Jemanesh K; Cory, Aron T; Clarke, Fran R; Clarke, John M; Knox, Ron E; Pozniak, Curtis J

2017-01-01

Association mapping is usually performed by testing the correlation between a single marker and phenotypes. However, because patterns of variation within genomes are inherited as blocks, clustering markers into haplotypes for genome-wide scans could be a worthwhile approach to improve statistical power to detect associations. The availability of high-density molecular data allows the possibility to assess the potential of both approaches to identify marker-trait associations in durum wheat. In the present study, we used single marker- and haplotype-based approaches to identify loci associated with semolina and pasta colour in durum wheat, the main objective being to evaluate the potential benefits of haplotype-based analysis for identifying quantitative trait loci. One hundred sixty-nine durum lines were genotyped using the Illumina 90K Infinium iSelect assay, and 12,234 polymorphic single nucleotide polymorphism (SNP) markers were generated and used to assess the population structure and the linkage disequilibrium (LD) patterns. A total of 8,581 SNPs previously localized to a high-density consensus map were clustered into 406 haplotype blocks based on the average LD distance of 5.3 cM. Combining multiple SNPs into haplotype blocks increased the average polymorphism information content (PIC) from 0.27 per SNP to 0.50 per haplotype. The haplotype-based analysis identified 12 loci associated with grain pigment colour traits, including the five loci identified by the single marker-based analysis. Furthermore, the haplotype-based analysis resulted in an increase of the phenotypic variance explained (50.4% on average) and the allelic effect (33.7% on average) when compared to single marker analysis. The presence of multiple allelic combinations within each haplotype locus offers potential for screening the most favorable haplotype series and may facilitate marker-assisted selection of grain pigment colour in durum wheat. These results suggest a benefit of haplotype-based analysis over single marker analysis to detect loci associated with colour traits in durum wheat.

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.

Identifying the "Right Stuff": An Exploration-Focused Astronaut Job Analysis

NASA Technical Reports Server (NTRS)

Barrett, J. D.; Holland, A. W.; Vessey, W. B.

2015-01-01

Industrial and organizational (I/O) psychologists play a key role in NASA astronaut candidate selection through the identification of the competencies necessary to successfully engage in the astronaut job. A set of psychosocial competencies, developed by I/O psychologists during a prior job analysis conducted in 1996 and updated in 2003, were identified as necessary for individuals working and living in the space shuttle and on the International Space Station (ISS). This set of competencies applied to the space shuttle and applies to current ISS missions, but may not apply to longer-duration or long-distance exploration missions. With the 2015 launch of the first 12- month ISS mission and the shift in the 2020s to missions beyond low earth orbit, the type of missions that astronauts will conduct and the environment in which they do their work will change dramatically, leading to new challenges for these crews. To support future astronaut selection, training, and research, I/O psychologists in NASA's Behavioral Health and Performance (BHP) Operations and Research groups engaged in a joint effort to conduct an updated analysis of the astronaut job for current and future operations. This project will result in the identification of behavioral competencies critical to performing the astronaut job, along with relative weights for each of the identified competencies, through the application of job analysis techniques. While this job analysis is being conducted according to job analysis best practices, the project poses a number of novel challenges. These challenges include the need to identify competencies for multiple mission types simultaneously, to evaluate jobs that have no incumbents as they have never before been conducted, and working with a very limited population of subject matter experts. Given these challenges, under the guidance of job analysis experts, we used the following methods to conduct the job analysis and identify the key competencies for current and potential future missions.

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.

A Job Analysis for K-8 Principals in a Nationwide Charter School System

ERIC Educational Resources Information Center

Cumings, Laura; Coryn, Chris L. S.

2009-01-01

Background: Although no single technique on its own can predict job performance, a job analysis is a customary approach for identifying the relevant knowledge, skills, abilities, and other characteristics (KSAO) necessary to successfully complete the job tasks of a position. Once the position requirements are identified, the hiring process is…

Analysis of MOOCs Practices from the Perspective of Learner Experiences and Quality Culture

ERIC Educational Resources Information Center

Ossiannilsson, Ebba; Altinay, Fahriye; Altinay, Zehra

2015-01-01

This explanatory analysis of the relevant literature seeks to identify factors affecting quality in massive open online courses (MOOCs). The paper highlights sub-dimensions of quality in MOOCs using the ladder of analytical abstraction. Communication, trust, collaboration, inclusiveness, innovation, and commitment are identified as key elements in…

Identifying Skill Requirements for GIS Positions: A Content Analysis of Job Advertisements

ERIC Educational Resources Information Center

Hong, Jung Eun

2016-01-01

This study identifies the skill requirements for geographic information system (GIS) positions, including GIS analysts, programmers/developers/engineers, specialists, and technicians, through a content analysis of 946 GIS job advertisements from 2007-2014. The results indicated that GIS job applicants need to possess high levels of GIS analysis…

Identifying Barriers in Implementing Outcomes-Based Assessment Program Review: A Grounded Theory Analysis

ERIC Educational Resources Information Center

Bresciani, Marilee J.

2011-01-01

The purpose of this grounded theory study was to identify the typical barriers encountered by faculty and administrators when implementing outcomes-based assessment program review. An analysis of interviews with faculty and administrators at nine institutions revealed a theory that faculty and administrators' promotion, tenure (if applicable),…

Transcriptome profiling to identify ATRA-responsive genes in human iPSC-derived endoderm for high-throughput point of departure analysis (SOT Annual Meeting)

EPA Science Inventory

Toxicological tipping points occur at chemical concentrations that overwhelm a cell’s adaptive response leading to permanent effects. We focused on retinoid signaling in differentiating endoderm to identify developmental pathways for tipping point analysis. Human induced pluripot...

Automatic image analysis and spot classification for detection of fruit fly infestation in hyperspectral images of mangoes

USDA-ARS?s Scientific Manuscript database

An algorithm has been developed to identify spots generated in hyperspectral images of mangoes infested with fruit fly larvae. The algorithm incorporates background removal, application of a Gaussian blur, thresholding, and particle count analysis to identify locations of infestations. Each of the f...

Social Network Analysis: A Simple but Powerful Tool for Identifying Teacher Leaders

ERIC Educational Resources Information Center

Smith, P. Sean; Trygstad, Peggy J.; Hayes, Meredith L.

2018-01-01

Instructional teacher leadership is central to a vision of distributed leadership. However, identifying instructional teacher leaders can be a daunting task, particularly for administrators who find themselves either newly appointed or faced with high staff turnover. This article describes the use of social network analysis (SNA), a simple but…

CONDITIONAL PROBABILITY ANALYSIS APPROACH FOR IDENTIFYING BIOLOGICAL THRESHOLD OF IMPACT FOR SEDIMENTATION: APPICATION TO FRESHWATER STREAMS IN OREGON COAST RANGE ECOREGION

EPA Science Inventory

A conditional probability analysis (CPA) approach has been developed for identifying biological thresholds of impact for use in the development of geographic-specific water quality criteria for protection of aquatic life. This approach expresses the threshold as the likelihood ...

Revisiting a Meta-Analysis of Helpful Aspects of Therapy in a Community Counselling Service

ERIC Educational Resources Information Center

Quick, Emma L; Dowd, Claire; Spong, Sheila

2018-01-01

This small scale mixed methods study examines helpful events in a community counselling setting, categorising impacts of events according to Timulak's [(2007). Identifying core categories of client-identified impact of helpful events in psychotherapy: A qualitative meta-analysis. "Psychotherapy Research," 17, 305-314] meta-synthesis of…

Using Data Mining Results to Improve Educational Video Game Design

ERIC Educational Resources Information Center

Kerr, Deirdre

2015-01-01

This study uses information about in-game strategy use, identified through cluster analysis of actions in an educational video game, to make data-driven modifications to the game in order to reduce construct-irrelevant behavior. The examination of student strategies identified through cluster analysis indicated that (a) it was common for students…

Clinical Trial Registries Are of Minimal Use for Identifying Selective Outcome and Analysis Reporting

ERIC Educational Resources Information Center

Norris, Susan L.; Holmer, Haley K.; Fu, Rongwei; Ogden, Lauren A.; Viswanathan, Meera S.; Abou-Setta, Ahmed M.

2014-01-01

Objective: This study aimed to examine selective outcome reporting (SOR) and selective analysis reporting (SAR) in randomized controlled trials (RCTs) and to explore the usefulness of trial registries for identifying SOR and SAR. Study Design and Setting: We selected one "index outcome" for each of three comparative effectiveness reviews…

Identifying the Ethical Challenges Encountered by Information Technology Professionals Working within the Nevada Casino Industry

ERIC Educational Resources Information Center

Essig, Michael R.

2014-01-01

A thematic analysis qualitative study was used to identify the unethical challenges encountered by Information Technology (IT) professionals working within the Nevada casino industry. Fourteen current and former IT leaders working or who worked in the Nevada casino industry were interviewed. Using thematic analysis, nine themes regarding ethical…

Assessing the Utility of a Demand Assessment for Functional Analysis

ERIC Educational Resources Information Center

Roscoe, Eileen M.; Rooker, Griffin W.; Pence, Sacha T.; Longworth, Lynlea J.

2009-01-01

We evaluated the utility of an assessment for identifying tasks for the functional analysis demand condition with 4 individuals who had been diagnosed with autism. During the demand assessment, a therapist presented a variety of tasks, and observers measured problem behavior and compliance to identify demands associated with low levels of…

Genome wide association study (GWAS) for grain yield in rice cultivated under water deficit.

PubMed

Pantalião, Gabriel Feresin; Narciso, Marcelo; Guimarães, Cléber; Castro, Adriano; Colombari, José Manoel; Breseghello, Flavio; Rodrigues, Luana; Vianello, Rosana Pereira; Borba, Tereza Oliveira; Brondani, Claudio

2016-12-01

The identification of rice drought tolerant materials is crucial for the development of best performing cultivars for the upland cultivation system. This study aimed to identify markers and candidate genes associated with drought tolerance by Genome Wide Association Study analysis, in order to develop tools for use in rice breeding programs. This analysis was made with 175 upland rice accessions (Oryza sativa), evaluated in experiments with and without water restriction, and 150,325 SNPs. Thirteen SNP markers associated with yield under drought conditions were identified. Through stepwise regression analysis, eight SNP markers were selected and validated in silico, and when tested by PCR, two out of the eight SNP markers were able to identify a group of rice genotypes with higher productivity under drought. These results are encouraging for deriving markers for the routine analysis of marker assisted selection. From the drought experiment, including the genes inherited in linkage blocks, 50 genes were identified, from which 30 were annotated, and 10 were previously related to drought and/or abiotic stress tolerance, such as the transcription factors WRKY and Apetala2, and protein kinases.

FLOCK cluster analysis of mast cell event clustering by high-sensitivity flow cytometry predicts systemic mastocytosis.

PubMed

Dorfman, David M; LaPlante, Charlotte D; Pozdnyakova, Olga; Li, Betty

2015-11-01

In our high-sensitivity flow cytometric approach for systemic mastocytosis (SM), we identified mast cell event clustering as a new diagnostic criterion for the disease. To objectively characterize mast cell gated event distributions, we performed cluster analysis using FLOCK, a computational approach to identify cell subsets in multidimensional flow cytometry data in an unbiased, automated fashion. FLOCK identified discrete mast cell populations in most cases of SM (56/75 [75%]) but only a minority of non-SM cases (17/124 [14%]). FLOCK-identified mast cell populations accounted for 2.46% of total cells on average in SM cases and 0.09% of total cells on average in non-SM cases (P < .0001) and were predictive of SM, with a sensitivity of 75%, a specificity of 86%, a positive predictive value of 76%, and a negative predictive value of 85%. FLOCK analysis provides useful diagnostic information for evaluating patients with suspected SM, and may be useful for the analysis of other hematopoietic neoplasms. Copyright© by the American Society for Clinical Pathology.

Proteomic analysis of a rare urinary stone composed of calcium carbonate and calcium oxalate dihydrate: a case report.

PubMed

Kaneko, Kiyoko; Matsuta, Yosuke; Moriyama, Manabu; Yasuda, Makoto; Chishima, Noriharu; Yamaoka, Noriko; Fukuuchi, Tomoko; Miyazawa, Katsuhito; Suzuki, Koji

2014-03-01

The objective of the present study was to investigate the matrix protein of a rare urinary stone that contained calcium carbonate. A urinary stone was extracted from a 34-year-old male patient with metabolic alkalosis. After X-ray diffractometry and infrared analysis of the stone, proteomic analysis was carried out. The resulting mass spectra were evaluated with protein search software, and matrix proteins were identified. X-ray diffraction and infrared analysis confirmed that the stone contained calcium carbonate and calcium oxalate dihydrate. Of the identified 53 proteins, 24 have not been previously reported from calcium oxalate- or calcium phosphate-containing stones. The protease inhibitors and several proteins related to cell adhesion or the cytoskeleton were identified for the first time. We analyzed in detail a rare urinary stone composed of calcium carbonate and calcium oxalate dihydrate. Considering the formation of a calcium carbonate stone, the new identified proteins should play an important role on the urolithiasis process in alkaline condition. © 2013 The Japanese Urological Association.

[Using 2-DCOS to identify the molecular spectrum peaks for the isomer in the multi-component mixture gases Fourier transform infrared analysis].

PubMed

Zhao, An-Xin; Tang, Xiao-Jun; Zhang, Zhong-Hua; Liu, Jun-Hua

2014-10-01

The generalized two-dimensional correlation spectroscopy and Fourier transform infrared were used to identify hydrocarbon isomers in the mixed gases for absorption spectra resolution enhancement. The Fourier transform infrared spectrum of n-butane and iso-butane and the two-dimensional correlation infrared spectrum of concentration perturbation were used for analysis as an example. The all band and the main absorption peak wavelengths of Fourier transform infrared spectrum for single component gas showed that the spectra are similar, and if they were mixed together, absorption peaks overlap and peak is difficult to identify. The synchronous and asynchronous spectrum of two-dimensional correlation spectrum can clearly identify the iso-butane and normal butane and their respective characteristic absorption peak intensity. Iso-butane has strong absorption characteristics spectrum lines at 2,893, 2,954 and 2,893 cm(-1), and n-butane at 2,895 and 2,965 cm(-1). The analysis result in this paper preliminary verified that the two-dimensional infrared correlation spectroscopy can be used for resolution enhancement in Fourier transform infrared spectrum quantitative analysis.

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.

Cluster analysis in phenotyping a Portuguese population.

PubMed

Loureiro, C C; Sa-Couto, P; Todo-Bom, A; Bousquet, J

2015-09-03

Unbiased cluster analysis using clinical parameters has identified asthma phenotypes. Adding inflammatory biomarkers to this analysis provided a better insight into the disease mechanisms. This approach has not yet been applied to asthmatic Portuguese patients. To identify phenotypes of asthma using cluster analysis in a Portuguese asthmatic population treated in secondary medical care. Consecutive patients with asthma were recruited from the outpatient clinic. Patients were optimally treated according to GINA guidelines and enrolled in the study. Procedures were performed according to a standard evaluation of asthma. Phenotypes were identified by cluster analysis using Ward's clustering method. Of the 72 patients enrolled, 57 had full data and were included for cluster analysis. Distribution was set in 5 clusters described as follows: cluster (C) 1, early onset mild allergic asthma; C2, moderate allergic asthma, with long evolution, female prevalence and mixed inflammation; C3, allergic brittle asthma in young females with early disease onset and no evidence of inflammation; C4, severe asthma in obese females with late disease onset, highly symptomatic despite low Th2 inflammation; C5, severe asthma with chronic airflow obstruction, late disease onset and eosinophilic inflammation. In our study population, the identified clusters were mainly coincident with other larger-scale cluster analysis. Variables such as age at disease onset, obesity, lung function, FeNO (Th2 biomarker) and disease severity were important for cluster distinction. Copyright © 2015. Published by Elsevier España, S.L.U.

Featured Article: Transcriptional landscape analysis identifies differently expressed genes involved in follicle-stimulating hormone induced postmenopausal osteoporosis.

PubMed

Maasalu, Katre; Laius, Ott; Zhytnik, Lidiia; Kõks, Sulev; Prans, Ele; Reimann, Ene; Märtson, Aare

2017-01-01

Osteoporosis is a disorder associated with bone tissue reorganization, bone mass, and mineral density. Osteoporosis can severely affect postmenopausal women, causing bone fragility and osteoporotic fractures. The aim of the current study was to compare blood mRNA profiles of postmenopausal women with and without osteoporosis, with the aim of finding different gene expressions and thus targets for future osteoporosis biomarker studies. Our study consisted of transcriptome analysis of whole blood serum from 12 elderly female osteoporotic patients and 12 non-osteoporotic elderly female controls. The transcriptome analysis was performed with RNA sequencing technology. For data analysis, the edgeR package of R Bioconductor was used. Two hundred and fourteen genes were expressed differently in osteoporotic compared with non-osteoporotic patients. Statistical analysis revealed 20 differently expressed genes with a false discovery rate of less than 1.47 × 10 -4 among osteoporotic patients. The expression of 10 genes were up-regulated and 10 down-regulated. Further statistical analysis identified a potential osteoporosis mRNA biomarker pattern consisting of six genes: CACNA1G, ALG13, SBK1, GGT7, MBNL3, and RIOK3. Functional ingenuity pathway analysis identified the strongest candidate genes with regard to potential involvement in a follicle-stimulating hormone activated network of increased osteoclast activity and hypogonadal bone loss. The differentially expressed genes identified in this study may contribute to future research of postmenopausal osteoporosis blood biomarkers.

Linkage and association analysis of obesity traits reveals novel loci and interactions with dietary n-3 fatty acids in an Alaska Native (Yup’ik) population

PubMed Central

Vaughan, Laura Kelly; Wiener, Howard W.; Aslibekyan, Stella; Allison, David B.; Havel, Peter J.; Stanhope, Kimber L.; O’Brien, Diane M.; Hopkins, Scarlett E.; Lemas, Dominick J.; Boyer, Bert B.; Tiwari, Hemant K.

2015-01-01

Objective To identify novel genetic markers of obesity-related traits and to identify gene-diet interactions with n-3 polyunsaturated fatty acid (n-3 PUFA) intake in Yup’ik people. Material and Methods We measured body composition, plasma adipokines and ghrelin in 982 participants enrolled in the Center for Alaska Native Health Research (CANHR) Study. We conducted a genome-wide SNP linkage scan and targeted association analysis, fitting additional models to investigate putative gene-diet interactions. Finally, we performed bioinformatic analysis to uncover likely candidate genes within the identified linkage peaks. Results We observed evidence of linkage for all obesity-related traits, replicating previous results and identifying novel regions of interest for adiponectin (10q26.13-2) and thigh circumference (8q21.11-13). Bioinformatic analysis revealed DOCK1, PTPRE (10q26.13-2) and FABP4 (8q21.11-13) as putative candidate genes in the newly identified regions. Targeted SNP analysis under the linkage peaks identified associations between three SNPs and obesity-related traits: rs1007750 on chromosome 8 and thigh circumference (P=0.0005), rs878953 on chromosome 5 and thigh skinfold (P=0.0004), and rs1596854 on chromosome 11 for waist circumference (P=0.0003). Finally, we showed that n-3 PUFA modified the association between obesity related traits and two additional variants (rs2048417 on chromosome 3 for adiponectin, P for interaction=0.0006 and rs730414 on chromosome 11 for percentage body fat, P for interaction=0.0004). Conclusions This study presents evidence of novel genomic regions and gene-diet interactions that may contribute to the pathophysiology of obesity-related traits among Yup’ik people. PMID:25772781

Linkage and association analysis of obesity traits reveals novel loci and interactions with dietary n-3 fatty acids in an Alaska Native (Yup'ik) population.

PubMed

Vaughan, Laura Kelly; Wiener, Howard W; Aslibekyan, Stella; Allison, David B; Havel, Peter J; Stanhope, Kimber L; O'Brien, Diane M; Hopkins, Scarlett E; Lemas, Dominick J; Boyer, Bert B; Tiwari, Hemant K

2015-06-01

To identify novel genetic markers of obesity-related traits and to identify gene-diet interactions with n-3 polyunsaturated fatty acid (n-3 PUFA) intake in Yup'ik people. We measured body composition, plasma adipokines and ghrelin in 982 participants enrolled in the Center for Alaska Native Health Research (CANHR) Study. We conducted a genome-wide SNP linkage scan and targeted association analysis, fitting additional models to investigate putative gene-diet interactions. Finally, we performed bioinformatic analysis to uncover likely candidate genes within the identified linkage peaks. We observed evidence of linkage for all obesity-related traits, replicating previous results and identifying novel regions of interest for adiponectin (10q26.13-2) and thigh circumference (8q21.11-13). Bioinformatic analysis revealed DOCK1, PTPRE (10q26.13-2) and FABP4 (8q21.11-13) as putative candidate genes in the newly identified regions. Targeted SNP analysis under the linkage peaks identified associations between three SNPs and obesity-related traits: rs1007750 on chromosome 8 and thigh circumference (P=0.0005), rs878953 on chromosome 5 and thigh skinfold (P=0.0004), and rs1596854 on chromosome 11 for waist circumference (P=0.0003). Finally, we showed that n-3 PUFA modified the association between obesity related traits and two additional variants (rs2048417 on chromosome 3 for adiponectin, P for interaction=0.0006 and rs730414 on chromosome 11 for percentage body fat, P for interaction=0.0004). This study presents evidence of novel genomic regions and gene-diet interactions that may contribute to the pathophysiology of obesity-related traits among Yup'ik people. Copyright © 2015 Elsevier Inc. All rights reserved.

A genome-wide association study of corneal astigmatism: The CREAM Consortium.

PubMed

Shah, Rupal L; Li, Qing; Zhao, Wanting; Tedja, Milly S; Tideman, J Willem L; Khawaja, Anthony P; Fan, Qiao; Yazar, Seyhan; Williams, Katie M; Verhoeven, Virginie J M; Xie, Jing; Wang, Ya Xing; Hess, Moritz; Nickels, Stefan; Lackner, Karl J; Pärssinen, Olavi; Wedenoja, Juho; Biino, Ginevra; Concas, Maria Pina; Uitterlinden, André; Rivadeneira, Fernando; Jaddoe, Vincent W V; Hysi, Pirro G; Sim, Xueling; Tan, Nicholas; Tham, Yih-Chung; Sensaki, Sonoko; Hofman, Albert; Vingerling, Johannes R; Jonas, Jost B; Mitchell, Paul; Hammond, Christopher J; Höhn, René; Baird, Paul N; Wong, Tien-Yin; Cheng, Chinfsg-Yu; Teo, Yik Ying; Mackey, David A; Williams, Cathy; Saw, Seang-Mei; Klaver, Caroline C W; Guggenheim, Jeremy A; Bailey-Wilson, Joan E

2018-01-01

To identify genes and genetic markers associated with corneal astigmatism. A meta-analysis of genome-wide association studies (GWASs) of corneal astigmatism undertaken for 14 European ancestry (n=22,250) and 8 Asian ancestry (n=9,120) cohorts was performed by the Consortium for Refractive Error and Myopia. Cases were defined as having >0.75 diopters of corneal astigmatism. Subsequent gene-based and gene-set analyses of the meta-analyzed results of European ancestry cohorts were performed using VEGAS2 and MAGMA software. Additionally, estimates of single nucleotide polymorphism (SNP)-based heritability for corneal and refractive astigmatism and the spherical equivalent were calculated for Europeans using LD score regression. The meta-analysis of all cohorts identified a genome-wide significant locus near the platelet-derived growth factor receptor alpha ( PDGFRA ) gene: top SNP: rs7673984, odds ratio=1.12 (95% CI:1.08-1.16), p=5.55×10 -9 . No other genome-wide significant loci were identified in the combined analysis or European/Asian ancestry-specific analyses. Gene-based analysis identified three novel candidate genes for corneal astigmatism in Europeans-claudin-7 ( CLDN7 ), acid phosphatase 2, lysosomal ( ACP2 ), and TNF alpha-induced protein 8 like 3 ( TNFAIP8L3 ). In addition to replicating a previously identified genome-wide significant locus for corneal astigmatism near the PDGFRA gene, gene-based analysis identified three novel candidate genes, CLDN7 , ACP2 , and TNFAIP8L3 , that warrant further investigation to understand their role in the pathogenesis of corneal astigmatism. The much lower number of genetic variants and genes demonstrating an association with corneal astigmatism compared to published spherical equivalent GWAS analyses suggest a greater influence of rare genetic variants, non-additive genetic effects, or environmental factors in the development of astigmatism.

Co-fuse: a new class discovery analysis tool to identify and prioritize recurrent fusion genes from RNA-sequencing data.

PubMed

Paisitkriangkrai, Sakrapee; Quek, Kelly; Nievergall, Eva; Jabbour, Anissa; Zannettino, Andrew; Kok, Chung Hoow

2018-06-07

Recurrent oncogenic fusion genes play a critical role in the development of various cancers and diseases and provide, in some cases, excellent therapeutic targets. To date, analysis tools that can identify and compare recurrent fusion genes across multiple samples have not been available to researchers. To address this deficiency, we developed Co-occurrence Fusion (Co-fuse), a new and easy to use software tool that enables biologists to merge RNA-seq information, allowing them to identify recurrent fusion genes, without the need for exhaustive data processing. Notably, Co-fuse is based on pattern mining and statistical analysis which enables the identification of hidden patterns of recurrent fusion genes. In this report, we show that Co-fuse can be used to identify 2 distinct groups within a set of 49 leukemic cell lines based on their recurrent fusion genes: a multiple myeloma (MM) samples-enriched cluster and an acute myeloid leukemia (AML) samples-enriched cluster. Our experimental results further demonstrate that Co-fuse can identify known driver fusion genes (e.g., IGH-MYC, IGH-WHSC1) in MM, when compared to AML samples, indicating the potential of Co-fuse to aid the discovery of yet unknown driver fusion genes through cohort comparisons. Additionally, using a 272 primary glioma sample RNA-seq dataset, Co-fuse was able to validate recurrent fusion genes, further demonstrating the power of this analysis tool to identify recurrent fusion genes. Taken together, Co-fuse is a powerful new analysis tool that can be readily applied to large RNA-seq datasets, and may lead to the discovery of new disease subgroups and potentially new driver genes, for which, targeted therapies could be developed. The Co-fuse R source code is publicly available at https://github.com/sakrapee/co-fuse .

Cluster analysis of spontaneous preterm birth phenotypes identifies potential associations among preterm birth mechanisms.

PubMed

Esplin, M Sean; Manuck, Tracy A; Varner, Michael W; Christensen, Bryce; Biggio, Joseph; Bukowski, Radek; Parry, Samuel; Zhang, Heping; Huang, Hao; Andrews, William; Saade, George; Sadovsky, Yoel; Reddy, Uma M; Ilekis, John

2015-09-01

We sought to use an innovative tool that is based on common biologic pathways to identify specific phenotypes among women with spontaneous preterm birth (SPTB) to enhance investigators' ability to identify and to highlight common mechanisms and underlying genetic factors that are responsible for SPTB. We performed a secondary analysis of a prospective case-control multicenter study of SPTB. All cases delivered a preterm singleton at SPTB ≤34.0 weeks' gestation. Each woman was assessed for the presence of underlying SPTB causes. A hierarchic cluster analysis was used to identify groups of women with homogeneous phenotypic profiles. One of the phenotypic clusters was selected for candidate gene association analysis with the use of VEGAS software. One thousand twenty-eight women with SPTB were assigned phenotypes. Hierarchic clustering of the phenotypes revealed 5 major clusters. Cluster 1 (n = 445) was characterized by maternal stress; cluster 2 (n = 294) was characterized by premature membrane rupture; cluster 3 (n = 120) was characterized by familial factors, and cluster 4 (n = 63) was characterized by maternal comorbidities. Cluster 5 (n = 106) was multifactorial and characterized by infection (INF), decidual hemorrhage (DH), and placental dysfunction (PD). These 3 phenotypes were correlated highly by χ(2) analysis (PD and DH, P < 2.2e-6; PD and INF, P = 6.2e-10; INF and DH, (P = .0036). Gene-based testing identified the INS (insulin) gene as significantly associated with cluster 3 of SPTB. We identified 5 major clusters of SPTB based on a phenotype tool and hierarch clustering. There was significant correlation between several of the phenotypes. The INS gene was associated with familial factors that were underlying SPTB. Copyright © 2015 Elsevier Inc. All rights reserved.

Integrating Genetic and Gene Co-expression Analysis Identifies Gene Networks Involved in Alcohol and Stress Responses

PubMed Central

Luo, Jie; Xu, Pei; Cao, Peijian; Wan, Hongjian; Lv, Xiaonan; Xu, Shengchun; Wang, Gangjun; Cook, Melloni N.; Jones, Byron C.; Lu, Lu; Wang, Xusheng

2018-01-01

Although the link between stress and alcohol is well recognized, the underlying mechanisms of how they interplay at the molecular level remain unclear. The purpose of this study is to identify molecular networks underlying the effects of alcohol and stress responses, as well as their interaction on anxiety behaviors in the hippocampus of mice using a systems genetics approach. Here, we applied a gene co-expression network approach to transcriptomes of 41 BXD mouse strains under four conditions: stress, alcohol, stress-induced alcohol and control. The co-expression analysis identified 14 modules and characterized four expression patterns across the four conditions. The four expression patterns include up-regulation in no restraint stress and given an ethanol injection (NOE) but restoration in restraint stress followed by an ethanol injection (RSE; pattern 1), down-regulation in NOE but rescue in RSE (pattern 2), up-regulation in both restraint stress followed by a saline injection (RSS) and NOE, and further amplification in RSE (pattern 3), and up-regulation in RSS but reduction in both NOE and RSE (pattern 4). We further identified four functional subnetworks by superimposing protein-protein interactions (PPIs) to the 14 co-expression modules, including γ-aminobutyric acid receptor (GABA) signaling, glutamate signaling, neuropeptide signaling, cAMP-dependent signaling. We further performed module specificity analysis to identify modules that are specific to stress, alcohol, or stress-induced alcohol responses. Finally, we conducted causality analysis to link genetic variation to these identified modules, and anxiety behaviors after stress and alcohol treatments. This study underscores the importance of integrative analysis and offers new insights into the molecular networks underlying stress and alcohol responses. PMID:29674951

Development and testing of new candidate psoriatic arthritis screening questionnaires combining optimal questions from existing tools.

PubMed

Coates, Laura C; Walsh, Jessica; Haroon, Muhammad; FitzGerald, Oliver; Aslam, Tariq; Al Balushi, Farida; Burden, A D; Burden-Teh, Esther; Caperon, Anna R; Cerio, Rino; Chattopadhyay, Chandrabhusan; Chinoy, Hector; Goodfield, Mark J D; Kay, Lesley; Kelly, Stephen; Kirkham, Bruce W; Lovell, Christopher R; Marzo-Ortega, Helena; McHugh, Neil; Murphy, Ruth; Reynolds, Nick J; Smith, Catherine H; Stewart, Elizabeth J C; Warren, Richard B; Waxman, Robin; Wilson, Hilary E; Helliwell, Philip S

2014-09-01

Several questionnaires have been developed to screen for psoriatic arthritis (PsA), but head-to-head studies have found limitations. This study aimed to develop new questionnaires encompassing the most discriminative questions from existing instruments. Data from the CONTEST study, a head-to-head comparison of 3 existing questionnaires, were used to identify items with a Youden index score of ≥0.1. These were combined using 4 approaches: CONTEST (simple additions of questions), CONTESTw (weighting using logistic regression), CONTESTjt (addition of a joint manikin), and CONTESTtree (additional questions identified by classification and regression tree [CART] analysis). These candidate questionnaires were tested in independent data sets. Twelve individual questions with a Youden index score of ≥0.1 were identified, but 4 of these were excluded due to duplication and redundancy. Weighting for 2 of these questions was included in CONTESTw. Receiver operating characteristic (ROC) curve analysis showed that involvement in 6 joint areas on the manikin was predictive of PsA for inclusion in CONTESTjt. CART analysis identified a further 5 questions for inclusion in CONTESTtree. CONTESTtree was not significant on ROC curve analysis and discarded. The other 3 questionnaires were significant in all data sets, although CONTESTw was slightly inferior to the others in the validation data sets. Potential cut points for referral were also discussed. Of 4 candidate questionnaires combining existing discriminatory items to identify PsA in people with psoriasis, 3 were found to be significant on ROC curve analysis. Testing in independent data sets identified 2 questionnaires (CONTEST and CONTESTjt) that should be pursued for further prospective testing. Copyright © 2014 by the American College of Rheumatology.

Evaluation of redundancy analysis to identify signatures of local adaptation.

PubMed

Capblancq, Thibaut; Luu, Keurcien; Blum, Michael G B; Bazin, Eric

2018-05-26

Ordination is a common tool in ecology that aims at representing complex biological information in a reduced space. In landscape genetics, ordination methods such as principal component analysis (PCA) have been used to detect adaptive variation based on genomic data. Taking advantage of environmental data in addition to genotype data, redundancy analysis (RDA) is another ordination approach that is useful to detect adaptive variation. This paper aims at proposing a test statistic based on RDA to search for loci under selection. We compare redundancy analysis to pcadapt, which is a nonconstrained ordination method, and to a latent factor mixed model (LFMM), which is a univariate genotype-environment association method. Individual-based simulations identify evolutionary scenarios where RDA genome scans have a greater statistical power than genome scans based on PCA. By constraining the analysis with environmental variables, RDA performs better than PCA in identifying adaptive variation when selection gradients are weakly correlated with population structure. Additionally, we show that if RDA and LFMM have a similar power to identify genetic markers associated with environmental variables, the RDA-based procedure has the advantage to identify the main selective gradients as a combination of environmental variables. To give a concrete illustration of RDA in population genomics, we apply this method to the detection of outliers and selective gradients on an SNP data set of Populus trichocarpa (Geraldes et al., 2013). The RDA-based approach identifies the main selective gradient contrasting southern and coastal populations to northern and continental populations in the northwestern American coast. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

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

Developing an intelligence analysis process through social network analysis

NASA Astrophysics Data System (ADS)

Waskiewicz, Todd; LaMonica, Peter

2008-04-01

Intelligence analysts are tasked with making sense of enormous amounts of data and gaining an awareness of a situation that can be acted upon. This process can be extremely difficult and time consuming. Trying to differentiate between important pieces of information and extraneous data only complicates the problem. When dealing with data containing entities and relationships, social network analysis (SNA) techniques can be employed to make this job easier. Applying network measures to social network graphs can identify the most significant nodes (entities) and edges (relationships) and help the analyst further focus on key areas of concern. Strange developed a model that identifies high value targets such as centers of gravity and critical vulnerabilities. SNA lends itself to the discovery of these high value targets and the Air Force Research Laboratory (AFRL) has investigated several network measures such as centrality, betweenness, and grouping to identify centers of gravity and critical vulnerabilities. Using these network measures, a process for the intelligence analyst has been developed to aid analysts in identifying points of tactical emphasis. Organizational Risk Analyzer (ORA) and Terrorist Modus Operandi Discovery System (TMODS) are the two applications used to compute the network measures and identify the points to be acted upon. Therefore, the result of leveraging social network analysis techniques and applications will provide the analyst and the intelligence community with more focused and concentrated analysis results allowing them to more easily exploit key attributes of a network, thus saving time, money, and manpower.

How individual participant data meta-analyses have influenced trial design, conduct, and analysis.

PubMed

Tierney, Jayne F; Pignon, Jean-Pierre; Gueffyier, Francois; Clarke, Mike; Askie, Lisa; Vale, Claire L; Burdett, Sarah

2015-11-01

To demonstrate how individual participant data (IPD) meta-analyses have impacted directly on the design and conduct of trials and highlight other advantages IPD might offer. Potential examples of the impact of IPD meta-analyses on trials were identified at an international workshop, attended by individuals with experience in the conduct of IPD meta-analyses and knowledge of trials in their respective clinical areas. Experts in the field who did not attend were asked to provide any further examples. We then examined relevant trial protocols, publications, and Web sites to verify the impacts of the IPD meta-analyses. A subgroup of workshop attendees sought further examples and identified other aspects of trial design and conduct that may inform IPD meta-analyses. We identified 52 examples of IPD meta-analyses thought to have had a direct impact on the design or conduct of trials. After screening relevant trial protocols and publications, we identified 28 instances where IPD meta-analyses had clearly impacted on trials. They have influenced the selection of comparators and participants, sample size calculations, analysis and interpretation of subsequent trials, and the conduct and analysis of ongoing trials, sometimes in ways that would not possible with systematic reviews of aggregate data. We identified additional potential ways that IPD meta-analyses could be used to influence trials. IPD meta-analysis could be better used to inform the design, conduct, analysis, and interpretation of trials. Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.

How individual participant data meta-analyses have influenced trial design, conduct, and analysis

PubMed Central

Tierney, Jayne F.; Pignon, Jean-Pierre; Gueffyier, Francois; Clarke, Mike; Askie, Lisa; Vale, Claire L.; Burdett, Sarah; Alderson, P.; Askie, L.; Bennett, D.; Burdett, S.; Clarke, M.; Dias, S.; Emberson, J.; Gueyffier, F.; Iorio, A.; Macleod, M.; Mol, B.W.; Moons, C.; Parmar, M.; Perera, R.; Phillips, R.; Pignon, J.P.; Rees, J.; Reitsma, H.; Riley, R.; Rovers, M.; Rydzewska, L.; Schmid, C.; Shepperd, S.; Stenning, S.; Stewart, L.; Tierney, J.; Tudur Smith, C.; Vale, C.; Welge, J.; White, I.; Whiteley, W.

2015-01-01

Objectives To demonstrate how individual participant data (IPD) meta-analyses have impacted directly on the design and conduct of trials and highlight other advantages IPD might offer. Study Design and Setting Potential examples of the impact of IPD meta-analyses on trials were identified at an international workshop, attended by individuals with experience in the conduct of IPD meta-analyses and knowledge of trials in their respective clinical areas. Experts in the field who did not attend were asked to provide any further examples. We then examined relevant trial protocols, publications, and Web sites to verify the impacts of the IPD meta-analyses. A subgroup of workshop attendees sought further examples and identified other aspects of trial design and conduct that may inform IPD meta-analyses. Results We identified 52 examples of IPD meta-analyses thought to have had a direct impact on the design or conduct of trials. After screening relevant trial protocols and publications, we identified 28 instances where IPD meta-analyses had clearly impacted on trials. They have influenced the selection of comparators and participants, sample size calculations, analysis and interpretation of subsequent trials, and the conduct and analysis of ongoing trials, sometimes in ways that would not possible with systematic reviews of aggregate data. We identified additional potential ways that IPD meta-analyses could be used to influence trials. Conclusions IPD meta-analysis could be better used to inform the design, conduct, analysis, and interpretation of trials. PMID:26186982

Marketing analysis of a maternity service by a consumer.

PubMed

Crowley-Murphy, M

1996-07-01

Marketing analysis is a means of identifying consumer satisfaction, thus providing a means of exploiting weaknesses in competitors. As part of a graduate midwifery programme a small study was undertaken analysing marketing activities used by one competitor provider of maternity care services. The Marketing mix, Ansoff matrix and Gap analysis were the marketing tools used. Recommendations to midwifery service providers suggest using market research to identify consumer expectations and explore areas of both satisfaction and dissatisfaction.

Identification by random forest method of HLA class I amino acid substitutions associated with lower survival at day 100 in unrelated donor hematopoietic cell transplantation.

PubMed

Marino, S R; Lin, S; Maiers, M; Haagenson, M; Spellman, S; Klein, J P; Binkowski, T A; Lee, S J; van Besien, K

2012-02-01

The identification of important amino acid substitutions associated with low survival in hematopoietic cell transplantation (HCT) is hampered by the large number of observed substitutions compared with the small number of patients available for analysis. Random forest analysis is designed to address these limitations. We studied 2107 HCT recipients with good or intermediate risk hematological malignancies to identify HLA class I amino acid substitutions associated with reduced survival at day 100 post transplant. Random forest analysis and traditional univariate and multivariate analyses were used. Random forest analysis identified amino acid substitutions in 33 positions that were associated with reduced 100 day survival, including HLA-A 9, 43, 62, 63, 76, 77, 95, 97, 114, 116, 152, 156, 166 and 167; HLA-B 97, 109, 116 and 156; and HLA-C 6, 9, 11, 14, 21, 66, 77, 80, 95, 97, 99, 116, 156, 163 and 173. In all 13 had been previously reported by other investigators using classical biostatistical approaches. Using the same data set, traditional multivariate logistic regression identified only five amino acid substitutions associated with lower day 100 survival. Random forest analysis is a novel statistical methodology for analysis of HLA mismatching and outcome studies, capable of identifying important amino acid substitutions missed by other methods.

Differential gene expression analysis in glioblastoma cells and normal human brain cells based on GEO database.

PubMed

Wang, Anping; Zhang, Guibin

2017-11-01

The differentially expressed genes between glioblastoma (GBM) cells and normal human brain cells were investigated to performed pathway analysis and protein interaction network analysis for the differentially expressed genes. GSE12657 and GSE42656 gene chips, which contain gene expression profile of GBM were obtained from Gene Expression Omniub (GEO) database of National Center for Biotechnology Information (NCBI). The 'limma' data packet in 'R' software was used to analyze the differentially expressed genes in the two gene chips, and gene integration was performed using 'RobustRankAggreg' package. Finally, pheatmap software was used for heatmap analysis and Cytoscape, DAVID, STRING and KOBAS were used for protein-protein interaction, Gene Ontology (GO) and KEGG analyses. As results: i) 702 differentially expressed genes were identified in GSE12657, among those genes, 548 were significantly upregulated and 154 were significantly downregulated (p<0.01, fold-change >1), and 1,854 differentially expressed genes were identified in GSE42656, among the genes, 1,068 were significantly upregulated and 786 were significantly downregulated (p<0.01, fold-change >1). A total of 167 differentially expressed genes including 100 upregulated genes and 67 downregulated genes were identified after gene integration, and the genes showed significantly different expression levels in GBM compared with normal human brain cells (p<0.05). ii) Interactions between the protein products of 101 differentially expressed genes were identified using STRING and expression network was established. A key gene, called CALM3, was identified by Cytoscape software. iii) GO enrichment analysis showed that differentially expressed genes were mainly enriched in 'neurotransmitter:sodium symporter activity' and 'neurotransmitter transporter activity', which can affect the activity of neurotransmitter transportation. KEGG pathway analysis showed that the differentially expressed genes were mainly enriched in 'protein processing in endoplasmic reticulum', which can affect protein processing in endoplasmic reticulum. The results showed that: i) 167 differentially expressed genes were identified from two gene chips after integration; and ii) protein interaction network was established, and GO and KEGG pathway analyses were successfully performed to identify and annotate the key gene, which provide new insights for the studies on GBN at gene level.

Spiritual and ceremonial plants in North America: an assessment of Moerman's ethnobotanical database comparing Residual, Binomial, Bayesian and Imprecise Dirichlet Model (IDM) analysis.

PubMed

Turi, Christina E; Murch, Susan J

2013-07-09

Ethnobotanical research and the study of plants used for rituals, ceremonies and to connect with the spirit world have led to the discovery of many novel psychoactive compounds such as nicotine, caffeine, and cocaine. In North America, spiritual and ceremonial uses of plants are well documented and can be accessed online via the University of Michigan's Native American Ethnobotany Database. The objective of the study was to compare Residual, Bayesian, Binomial and Imprecise Dirichlet Model (IDM) analyses of ritual, ceremonial and spiritual plants in Moerman's ethnobotanical database and to identify genera that may be good candidates for the discovery of novel psychoactive compounds. The database was queried with the following format "Family Name AND Ceremonial OR Spiritual" for 263 North American botanical families. Spiritual and ceremonial flora consisted of 86 families with 517 species belonging to 292 genera. Spiritual taxa were then grouped further into ceremonial medicines and items categories. Residual, Bayesian, Binomial and IDM analysis were performed to identify over and under-utilized families. The 4 statistical approaches were in good agreement when identifying under-utilized families but large families (>393 species) were underemphasized by Binomial, Bayesian and IDM approaches for over-utilization. Residual, Binomial, and IDM analysis identified similar families as over-utilized in the medium (92-392 species) and small (<92 species) classes. The families Apiaceae, Asteraceae, Ericacea, Pinaceae and Salicaceae were identified as significantly over-utilized as ceremonial medicines in medium and large sized families. Analysis of genera within the Apiaceae and Asteraceae suggest that the genus Ligusticum and Artemisia are good candidates for facilitating the discovery of novel psychoactive compounds. The 4 statistical approaches were not consistent in the selection of over-utilization of flora. Residual analysis revealed overall trends that were supported by Binomial analysis when separated into small, medium and large families. The Bayesian, Binomial and IDM approaches identified different genera as potentially important. Species belonging to the genus Artemisia and Ligusticum were most consistently identified and may be valuable in future studies of the ethnopharmacology. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Feasibility and demonstration of a cloud-based RIID analysis system

NASA Astrophysics Data System (ADS)

Wright, Michael C.; Hertz, Kristin L.; Johnson, William C.; Sword, Eric D.; Younkin, James R.; Sadler, Lorraine E.

2015-06-01

A significant limitation in the operational utility of handheld and backpack radioisotope identifiers (RIIDs) is the inability of their onboard algorithms to accurately and reliably identify the isotopic sources of the measured gamma-ray energy spectrum. A possible solution is to move the spectral analysis computations to an external device, the cloud, where significantly greater capabilities are available. The implementation and demonstration of a prototype cloud-based RIID analysis system have shown this type of system to be feasible with currently available communication and computational technology. A system study has shown that the potential user community could derive significant benefits from an appropriately implemented cloud-based analysis system and has identified the design and operational characteristics required by the users and stakeholders for such a system. A general description of the hardware and software necessary to implement reliable cloud-based analysis, the value of the cloud expressed by the user community, and the aspects of the cloud implemented in the demonstrations are discussed.

Identifying the Role of National Digital Cadastral Database (ndcdb) in Malaysia and for Land-Based Analysis

NASA Astrophysics Data System (ADS)

Halim, N. Z. A.; Sulaiman, S. A.; Talib, K.; Yusof, O. M.; Wazir, M. A. M.; Adimin, M. K.

2017-10-01

This paper explains the process carried out in identifying the significant role of NDCDB in Malaysia specifically in the land-based analysis. The research was initially a part of a larger research exercise to identify the significance of NDCDB from the legal, technical, role and land-based analysis perspectives. The research methodology of applying the Delphi technique is substantially discussed in this paper. A heterogeneous panel of 14 experts was created to determine the importance of NDCDB from the role standpoint. Seven statements pertaining the significant role of NDCDB in Malaysia and land-based analysis were established after three rounds of consensus building. The agreed statements provided a clear definition to describe the important role of NDCDB in Malaysia and for land-based analysis, which was limitedly studied that lead to unclear perception to the general public and even the geospatial community. The connection of the statements with disaster management is discussed concisely at the end of the research.

Food and drug cues activate similar brain regions: a meta-analysis of functional MRI studies.

PubMed

Tang, D W; Fellows, L K; Small, D M; Dagher, A

2012-06-06

In healthy individuals, food cues can trigger hunger and feeding behavior. Likewise, smoking cues can trigger craving and relapse in smokers. Brain imaging studies report that structures involved in appetitive behaviors and reward, notably the insula, striatum, amygdala and orbital frontal cortex, tend to be activated by both visual food and smoking cues. Here, by carrying out a meta-analysis of human neuro-imaging studies, we investigate the neural network activated by: 1) food versus neutral cues (14 studies, 142 foci) 2) smoking versus neutral cues (15 studies, 176 foci) 3) smoking versus neutral cues when correlated with craving scores (7 studies, 108 foci). PubMed was used to identify cue-reactivity imaging studies that compared brain response to visual food or smoking cues to neutral cues. Fourteen articles were identified for the food meta-analysis and fifteen articles were identified for the smoking meta-analysis. Six articles were identified for the smoking cue correlated with craving analysis. Meta-analyses were carried out using activation likelihood estimation. Food cues were associated with increased blood oxygen level dependent (BOLD) response in the left amygdala, bilateral insula, bilateral orbital frontal cortex, and striatum. Smoking cues were associated with increased BOLD signal in the same areas, with the exception of the insula. However, the smoking meta-analysis of brain maps correlating cue-reactivity with subjective craving did identify the insula, suggesting that insula activation is only found when craving levels are high. The brain areas identified here are involved in learning, memory and motivation, and their cue-induced activity is an index of the incentive salience of the cues. Using meta-analytic techniques to combine a series of studies, we found that food and smoking cues activate comparable brain networks. There is significant overlap in brain regions responding to conditioned cues associated with natural and drug rewards. Copyright © 2012 Elsevier Inc. All rights reserved.

Identification of victims of the 1998 Taoyuan Airbus crash accident using DNA analysis.

PubMed

Hsu, C M; Huang, N E; Tsai, L C; Kao, L G; Chao, C H; Linacre, A; Lee, J C

1999-01-01

In February 1998 a civilian aeroplane carrying 196 individuals crashed in Taiwan and killed another 6 people on the ground. Although there were dental and medical records, fingerprints, photographic evidence and personal effects to identify some of the victims, DNA analysis was required to further identify severely damaged remains. From the 202 people known to have perished in the plane crash, a total of 685 fragments of human remains were subjected to DNA analysis. The analysis was carried out using nine microsatellite loci, plus amelogenin to cluster the 685 fragments into 202 groups, accounting for all the victims. To establish genetic relatedness of the victims to other victims and living relatives, additional DNA loci were used. In this case the paternity index was increased by using HLA DQA1 plus Polymarker. The same 16 DNA loci were used to test blood samples from 201 relatives to establish parent/child and sibling relationships. With the exception of 19 victims identified by non-genetic evidence, 183 victims were successfully identified by DNA typing with relatively high values of paternity index by the direct or indirect comparison of relatives. The 202 victims were from 37 different families, ranging in size from 2 to 13 members and 74 individuals known to be unrelated to any other victim. The DNA from living relatives was used to identify one member of a family group, from which other victims of the family could be identified. ABO blood group information was further used to confirm genetic relatedness within families. A comparison of the DNA profiling results to the ABO blood group of the victims showed no discrepancies with the exception of two mutations in the FGA locus. In cases of severely damaged victims from a plane crash, DNA analysis proved to be the best choice to identify victims.

Genome-Wide and Gene-Based Meta-Analyses Identify Novel Loci Influencing Blood Pressure Response to Hydrochlorothiazide.

PubMed

Salvi, Erika; Wang, Zhiying; Rizzi, Federica; Gong, Yan; McDonough, Caitrin W; Padmanabhan, Sandosh; Hiltunen, Timo P; Lanzani, Chiara; Zaninello, Roberta; Chittani, Martina; Bailey, Kent R; Sarin, Antti-Pekka; Barcella, Matteo; Melander, Olle; Chapman, Arlene B; Manunta, Paolo; Kontula, Kimmo K; Glorioso, Nicola; Cusi, Daniele; Dominiczak, Anna F; Johnson, Julie A; Barlassina, Cristina; Boerwinkle, Eric; Cooper-DeHoff, Rhonda M; Turner, Stephen T

2017-01-01

This study aimed to identify novel loci influencing the antihypertensive response to hydrochlorothiazide monotherapy. A genome-wide meta-analysis of blood pressure (BP) response to hydrochlorothiazide was performed in 1739 white hypertensives from 6 clinical trials within the International Consortium for Antihypertensive Pharmacogenomics Studies, making it the largest study to date of its kind. No signals reached genome-wide significance (P<5×10 - 8 ), and the suggestive regions (P<10 -5 ) were cross-validated in 2 black cohorts treated with hydrochlorothiazide. In addition, a gene-based analysis was performed on candidate genes with previous evidence of involvement in diuretic response, in BP regulation, or in hypertension susceptibility. Using the genome-wide meta-analysis approach, with validation in blacks, we identified 2 suggestive regulatory regions linked to gap junction protein α1 gene (GJA1) and forkhead box A1 gene (FOXA1), relevant for cardiovascular and kidney function. With the gene-based approach, we identified hydroxy-delta-5-steroid dehydrogenase, 3 β- and steroid δ-isomerase 1 gene (HSD3B1) as significantly associated with BP response (P<2.28×10 - 4 ). HSD3B1 encodes the 3β-hydroxysteroid dehydrogenase enzyme and plays a crucial role in the biosynthesis of aldosterone and endogenous ouabain. By amassing all of the available pharmacogenomic studies of BP response to hydrochlorothiazide, and using 2 different analytic approaches, we identified 3 novel loci influencing BP response to hydrochlorothiazide. The gene-based analysis, never before applied to pharmacogenomics of antihypertensive drugs to our knowledge, provided a powerful strategy to identify a locus of interest, which was not identified in the genome-wide meta-analysis because of high allelic heterogeneity. These data pave the way for future investigations on new pathways and drug targets to enhance the current understanding of personalized antihypertensive treatment. © 2016 American Heart Association, Inc.

A new GWAS and meta-analysis with 1000Genomes imputation identifies novel risk variants for colorectal cancer.

PubMed

Al-Tassan, Nada A; Whiffin, Nicola; Hosking, Fay J; Palles, Claire; Farrington, Susan M; Dobbins, Sara E; Harris, Rebecca; Gorman, Maggie; Tenesa, Albert; Meyer, Brian F; Wakil, Salma M; Kinnersley, Ben; Campbell, Harry; Martin, Lynn; Smith, Christopher G; Idziaszczyk, Shelley; Barclay, Ella; Maughan, Timothy S; Kaplan, Richard; Kerr, Rachel; Kerr, David; Buchanan, Daniel D; Buchannan, Daniel D; Win, Aung Ko; Hopper, John; Jenkins, Mark; Lindor, Noralane M; Newcomb, Polly A; Gallinger, Steve; Conti, David; Schumacher, Fred; Casey, Graham; Dunlop, Malcolm G; Tomlinson, Ian P; Cheadle, Jeremy P; Houlston, Richard S

2015-05-20

Genome-wide association studies (GWAS) of colorectal cancer (CRC) have identified 23 susceptibility loci thus far. Analyses of previously conducted GWAS indicate additional risk loci are yet to be discovered. To identify novel CRC susceptibility loci, we conducted a new GWAS and performed a meta-analysis with five published GWAS (totalling 7,577 cases and 9,979 controls of European ancestry), imputing genotypes utilising the 1000 Genomes Project. The combined analysis identified new, significant associations with CRC at 1p36.2 marked by rs72647484 (minor allele frequency [MAF] = 0.09) near CDC42 and WNT4 (P = 1.21 × 10(-8), odds ratio [OR] = 1.21 ) and at 16q24.1 marked by rs16941835 (MAF = 0.21, P = 5.06 × 10(-8); OR = 1.15) within the long non-coding RNA (lncRNA) RP11-58A18.1 and ~500 kb from the nearest coding gene FOXL1. Additionally we identified a promising association at 10p13 with rs10904849 intronic to CUBN (MAF = 0.32, P = 7.01 × 10(-8); OR = 1.14). These findings provide further insights into the genetic and biological basis of inherited genetic susceptibility to CRC. Additionally, our analysis further demonstrates that imputation can be used to exploit GWAS data to identify novel disease-causing variants.

Identification of Cronobacter species by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry with an optimized analysis method.

PubMed

Wang, Qi; Zhao, Xiao-Juan; Wang, Zi-Wei; Liu, Li; Wei, Yong-Xin; Han, Xiao; Zeng, Jing; Liao, Wan-Jin

2017-08-01

Rapid and precise identification of Cronobacter species is important for foodborne pathogen detection, however, commercial biochemical methods can only identify Cronobacter strains to genus level in most cases. To evaluate the power of mass spectrometry based on matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF MS) for Cronobacter species identification, 51 Cronobacter strains (eight reference and 43 wild strains) were identified by both MALDI-TOF MS and 16S rRNA gene sequencing. Biotyper RTC provided by Bruker identified all eight reference and 43 wild strains as Cronobacter species, which demonstrated the power of MALDI-TOF MS to identify Cronobacter strains to genus level. However, using the Bruker's database (6903 main spectra products) and Biotyper software, the MALDI-TOF MS analysis could not identify the investigated strains to species level. When MALDI-TOF MS analysis was performed using the combined in-house Cronobacter database and Bruker's database, bin setting, and unweighted pair group method with arithmetic mean (UPGMA) clustering, all the 51 strains were clearly identified into six Cronobacter species and the identification accuracy increased from 60% to 100%. We demonstrated that MALDI-TOF MS was reliable and easy-to-use for Cronobacter species identification and highlighted the importance of establishing a reliable database and improving the current data analysis methods by integrating the bin setting and UPGMA clustering. Copyright © 2017. Published by Elsevier B.V.

Uncertainty Reduction using Bayesian Inference and Sensitivity Analysis: A Sequential Approach to the NASA Langley Uncertainty Quantification Challenge

NASA Technical Reports Server (NTRS)

Sankararaman, Shankar

2016-01-01

This paper presents a computational framework for uncertainty characterization and propagation, and sensitivity analysis under the presence of aleatory and epistemic un- certainty, and develops a rigorous methodology for efficient refinement of epistemic un- certainty by identifying important epistemic variables that significantly affect the overall performance of an engineering system. The proposed methodology is illustrated using the NASA Langley Uncertainty Quantification Challenge (NASA-LUQC) problem that deals with uncertainty analysis of a generic transport model (GTM). First, Bayesian inference is used to infer subsystem-level epistemic quantities using the subsystem-level model and corresponding data. Second, tools of variance-based global sensitivity analysis are used to identify four important epistemic variables (this limitation specified in the NASA-LUQC is reflective of practical engineering situations where not all epistemic variables can be refined due to time/budget constraints) that significantly affect system-level performance. The most significant contribution of this paper is the development of the sequential refine- ment methodology, where epistemic variables for refinement are not identified all-at-once. Instead, only one variable is first identified, and then, Bayesian inference and global sensi- tivity calculations are repeated to identify the next important variable. This procedure is continued until all 4 variables are identified and the refinement in the system-level perfor- mance is computed. The advantages of the proposed sequential refinement methodology over the all-at-once uncertainty refinement approach are explained, and then applied to the NASA Langley Uncertainty Quantification Challenge problem.

Hydrothermal Liquefaction Treatment Hazard Analysis Report

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

Lowry, Peter P.; Wagner, Katie A.

Hazard analyses were performed to evaluate the modular hydrothermal liquefaction treatment system. The hazard assessment process was performed in 2 stages. An initial assessment utilizing Hazard Identification and Preliminary Hazards Analysis (PHA) techniques identified areas with significant or unique hazards (process safety-related hazards) that fall outside of the normal operating envelope of PNNL and warranted additional analysis. The subsequent assessment was based on a qualitative What-If analysis. The analysis was augmented, as necessary, by additional quantitative analysis for scenarios involving a release of hazardous material or energy with the potential for affecting the public. The following selected hazardous scenarios receivedmore » increased attention: •Scenarios involving a release of hazardous material or energy, controls were identified in the What-If analysis table that prevent the occurrence or mitigate the effects of the release. •Scenarios with significant consequences that could impact personnel outside the immediate operations area, quantitative analyses were performed to determine the potential magnitude of the scenario. The set of “critical controls” were identified for these scenarios (see Section 4) which prevent the occurrence or mitigate the effects of the release of events with significant consequences.« less

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.

Chiral Analysis of Isopulegol by Fourier Transform Molecular Rotational Spectroscopy

NASA Astrophysics Data System (ADS)

Evangelisti, Luca; Seifert, Nathan A.; Spada, Lorenzo; Pate, Brooks

2016-06-01

Chiral analysis on molecules with multiple chiral centers can be performed using pulsed-jet Fourier transform rotational spectroscopy. This analysis includes quantitative measurement of diastereomer products and, with the three wave mixing methods developed by Patterson, Schnell, and Doyle (Nature 497, 475-477 (2013)), quantitative determination of the enantiomeric excess of each diastereomer. The high resolution features enable to perform the analysis directly on complex samples without the need for chromatographic separation. Isopulegol has been chosen to show the capabilities of Fourier transform rotational spectroscopy for chiral analysis. Broadband rotational spectroscopy produces spectra with signal-to-noise ratio exceeding 1000:1. The ability to identify low-abundance (0.1-1%) diastereomers in the sample will be described. Methods to rapidly identify rotational spectra from isotopologues at natural abundance will be shown and the molecular structures obtained from this analysis will be compared to theory. The role that quantum chemistry calculations play in identifying structural minima and estimating their spectroscopic properties to aid spectral analysis will be described. Finally, the implementation of three wave mixing techniques to measure the enantiomeric excess of each diastereomer and determine the absolute configuration of the enantiomer in excess will be described.

Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer

PubMed Central

Michailidou, Kyriaki; Beesley, Jonathan; Lindstrom, Sara; Canisius, Sander; Dennis, Joe; Lush, Michael; Maranian, Mel J; Bolla, Manjeet K; Wang, Qin; Shah, Mitul; Perkins, Barbara J; Czene, Kamila; Eriksson, Mikael; Darabi, Hatef; Brand, Judith S; Bojesen, Stig E; Nordestgaard, Børge G; Flyger, Henrik; Nielsen, Sune F; Rahman, Nazneen; Turnbull, Clare; Fletcher, Olivia; Peto, Julian; Gibson, Lorna; dos-Santos-Silva, Isabel; Chang-Claude, Jenny; Flesch-Janys, Dieter; Rudolph, Anja; Eilber, Ursula; Behrens, Sabine; Nevanlinna, Heli; Muranen, Taru A; Aittomäki, Kristiina; Blomqvist, Carl; Khan, Sofia; Aaltonen, Kirsimari; Ahsan, Habibul; Kibriya, Muhammad G; Whittemore, Alice S; John, Esther M; Malone, Kathleen E; Gammon, Marilie D; Santella, Regina M; Ursin, Giske; Makalic, Enes; Schmidt, Daniel F; Casey, Graham; Hunter, David J; Gapstur, Susan M; Gaudet, Mia M; Diver, W Ryan; Haiman, Christopher A; Schumacher, Fredrick; Henderson, Brian E; Le Marchand, Loic; Berg, Christine D; Chanock, Stephen; Figueroa, Jonine; Hoover, Robert N; Lambrechts, Diether; Neven, Patrick; Wildiers, Hans; van Limbergen, Erik; Schmidt, Marjanka K; Broeks, Annegien; Verhoef, Senno; Cornelissen, Sten; Couch, Fergus J; Olson, Janet E; Hallberg, Emily; Vachon, Celine; Waisfisz, Quinten; Meijers-Heijboer, Hanne; Adank, Muriel A; van der Luijt, Rob B; Li, Jingmei; Liu, Jianjun; Humphreys, Keith; Kang, Daehee; Choi, Ji-Yeob; Park, Sue K; Yoo, Keun-Young; Matsuo, Keitaro; Ito, Hidemi; Iwata, Hiroji; Tajima, Kazuo; Guénel, Pascal; Truong, Thérèse; Mulot, Claire; Sanchez, Marie; Burwinkel, Barbara; Marme, Frederik; Surowy, Harald; Sohn, Christof; Wu, Anna H; Tseng, Chiu-chen; Van Den Berg, David; Stram, Daniel O; González-Neira, Anna; Benitez, Javier; Zamora, M Pilar; Perez, Jose Ignacio Arias; Shu, Xiao-Ou; Lu, Wei; Gao, Yu-Tang; Cai, Hui; Cox, Angela; Cross, Simon S; Reed, Malcolm WR; Andrulis, Irene L; Knight, Julia A; Glendon, Gord; Mulligan, Anna Marie; Sawyer, Elinor J; Tomlinson, Ian; Kerin, Michael J; Miller, Nicola; Lindblom, Annika; Margolin, Sara; Teo, Soo Hwang; Yip, Cheng Har; Taib, Nur Aishah Mohd; TAN, Gie-Hooi; Hooning, Maartje J; Hollestelle, Antoinette; Martens, John WM; Collée, J Margriet; Blot, William; Signorello, Lisa B; Cai, Qiuyin; Hopper, John L; Southey, Melissa C; Tsimiklis, Helen; Apicella, Carmel; Shen, Chen-Yang; Hsiung, Chia-Ni; Wu, Pei-Ei; Hou, Ming-Feng; Kristensen, Vessela N; Nord, Silje; Alnaes, Grethe I Grenaker; Giles, Graham G; Milne, Roger L; McLean, Catriona; Canzian, Federico; Trichopoulos, Dmitrios; Peeters, Petra; Lund, Eiliv; Sund, Malin; Khaw, Kay-Tee; Gunter, Marc J; Palli, Domenico; Mortensen, Lotte Maxild; Dossus, Laure; Huerta, Jose-Maria; Meindl, Alfons; Schmutzler, Rita K; Sutter, Christian; Yang, Rongxi; Muir, Kenneth; Lophatananon, Artitaya; Stewart-Brown, Sarah; Siriwanarangsan, Pornthep; Hartman, Mikael; Miao, Hui; Chia, Kee Seng; Chan, Ching Wan; Fasching, Peter A; Hein, Alexander; Beckmann, Matthias W; Haeberle, Lothar; Brenner, Hermann; Dieffenbach, Aida Karina; Arndt, Volker; Stegmaier, Christa; Ashworth, Alan; Orr, Nick; Schoemaker, Minouk J; Swerdlow, Anthony J; Brinton, Louise; Garcia-Closas, Montserrat; Zheng, Wei; Halverson, Sandra L; Shrubsole, Martha; Long, Jirong; Goldberg, Mark S; Labrèche, France; Dumont, Martine; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Grip, Mervi; Brauch, Hiltrud; Hamann, Ute; Brüning, Thomas; Radice, Paolo; Peterlongo, Paolo; Manoukian, Siranoush; Bernard, Loris; Bogdanova, Natalia V; Dörk, Thilo; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M; Devilee, Peter; Tollenaar, Robert AEM; Seynaeve, Caroline; Van Asperen, Christi J; Jakubowska, Anna; Lubinski, Jan; Jaworska, Katarzyna; Huzarski, Tomasz; Sangrajrang, Suleeporn; Gaborieau, Valerie; Brennan, Paul; McKay, James; Slager, Susan; Toland, Amanda E; Ambrosone, Christine B; Yannoukakos, Drakoulis; Kabisch, Maria; Torres, Diana; Neuhausen, Susan L; Anton-Culver, Hoda; Luccarini, Craig; Baynes, Caroline; Ahmed, Shahana; Healey, Catherine S; Tessier, Daniel C; Vincent, Daniel; Bacot, Francois; Pita, Guillermo; Alonso, M Rosario; Álvarez, Nuria; Herrero, Daniel; Simard, Jacques; Pharoah, Paul PDP; Kraft, Peter; Dunning, Alison M; Chenevix-Trench, Georgia; Hall, Per; Easton, Douglas F

2015-01-01

Genome wide association studies (GWAS) and large scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ~14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS comprising of 15,748 breast cancer cases and 18,084 controls, and 46,785 cases and 42,892 controls from 41 studies genotyped on a 200K custom array (iCOGS). Analyses were restricted to women of European ancestry. Genotypes for more than 11M SNPs were generated by imputation using the 1000 Genomes Project reference panel. We identified 15 novel loci associated with breast cancer at P<5×10−8. Combining association analysis with ChIP-Seq data in mammary cell lines and ChIA-PET chromatin interaction data in ENCODE, we identified likely target genes in two regions: SETBP1 on 18q12.3 and RNF115 and PDZK1 on 1q21.1. One association appears to be driven by an amino-acid substitution in EXO1. PMID:25751625

Distributed lags time series analysis versus linear correlation analysis (Pearson's r) in identifying the relationship between antipseudomonal antibiotic consumption and the susceptibility of Pseudomonas aeruginosa isolates in a single Intensive Care Unit of a tertiary hospital.

PubMed

Erdeljić, Viktorija; Francetić, Igor; Bošnjak, Zrinka; Budimir, Ana; Kalenić, Smilja; Bielen, Luka; Makar-Aušperger, Ksenija; Likić, Robert

2011-05-01

The relationship between antibiotic consumption and selection of resistant strains has been studied mainly by employing conventional statistical methods. A time delay in effect must be anticipated and this has rarely been taken into account in previous studies. Therefore, distributed lags time series analysis and simple linear correlation were compared in their ability to evaluate this relationship. Data on monthly antibiotic consumption for ciprofloxacin, piperacillin/tazobactam, carbapenems and cefepime as well as Pseudomonas aeruginosa susceptibility were retrospectively collected for the period April 2006 to July 2007. Using distributed lags analysis, a significant temporal relationship was identified between ciprofloxacin, meropenem and cefepime consumption and the resistance rates of P. aeruginosa isolates to these antibiotics. This effect was lagged for ciprofloxacin and cefepime [1 month (R=0.827, P=0.039) and 2 months (R=0.962, P=0.001), respectively] and was simultaneous for meropenem (lag 0, R=0.876, P=0.002). Furthermore, a significant concomitant effect of meropenem consumption on the appearance of multidrug-resistant P. aeruginosa strains (resistant to three or more representatives of classes of antibiotics) was identified (lag 0, R=0.992, P<0.001). This effect was not delayed and it was therefore identified both by distributed lags analysis and the Pearson's correlation coefficient. Correlation coefficient analysis was not able to identify relationships between antibiotic consumption and bacterial resistance when the effect was delayed. These results indicate that the use of diverse statistical methods can yield significantly different results, thus leading to the introduction of possibly inappropriate infection control measures. Copyright © 2010 Elsevier B.V. and the International Society of Chemotherapy. All rights reserved.

Development of a data independent acquisition mass spectrometry workflow to enable glycopeptide analysis without predefined glycan compositional knowledge.

PubMed

Lin, Chi-Hung; Krisp, Christoph; Packer, Nicolle H; Molloy, Mark P

2018-02-10

Glycoproteomics investigates glycan moieties in a site specific manner to reveal the functional roles of protein glycosylation. Identification of glycopeptides from data-dependent acquisition (DDA) relies on high quality MS/MS spectra of glycopeptide precursors and often requires manual validation to ensure confident assignments. In this study, we investigated pseudo-MRM (MRM-HR) and data-independent acquisition (DIA) as alternative acquisition strategies for glycopeptide analysis. These approaches allow data acquisition over the full MS/MS scan range allowing data re-analysis post-acquisition, without data re-acquisition. The advantage of MRM-HR over DDA for N-glycopeptide detection was demonstrated from targeted analysis of bovine fetuin where all three N-glycosylation sites were detected, which was not the case with DDA. To overcome the duty cycle limitation of MRM-HR acquisition needed for analysis of complex samples such as plasma we trialed DIA. This allowed development of a targeted DIA method to identify N-glycopeptides without pre-defined knowledge of the glycan composition, thus providing the potential to identify N-glycopeptides with unexpected structures. This workflow was demonstrated by detection of 59 N-glycosylation sites from 41 glycoproteins from a HILIC enriched human plasma tryptic digest. 21 glycoforms of IgG1 glycopeptides were identified including two truncated structures that are rarely reported. We developed a data-independent mass spectrometry workflow to identify specific glycopeptides from complex biological mixtures. The novelty is that this approach does not require glycan composition to be pre-defined, thereby allowing glycopeptides carrying unexpected glycans to be identified. This is demonstrated through the analysis of immunoglobulins in human plasma where we detected two IgG1 glycoforms that are rarely observed. Copyright © 2017 Elsevier B.V. All rights reserved.

Comparative genome analysis of a large Dutch Legionella pneumophila strain collection identifies five markers highly correlated with clinical strains

PubMed Central

2010-01-01

Background Discrimination between clinical and environmental strains within many bacterial species is currently underexplored. Genomic analyses have clearly shown the enormous variability in genome composition between different strains of a bacterial species. In this study we have used Legionella pneumophila, the causative agent of Legionnaire's disease, to search for genomic markers related to pathogenicity. During a large surveillance study in The Netherlands well-characterized patient-derived strains and environmental strains were collected. We have used a mixed-genome microarray to perform comparative-genome analysis of 257 strains from this collection. Results Microarray analysis indicated that 480 DNA markers (out of in total 3360 markers) showed clear variation in presence between individual strains and these were therefore selected for further analysis. Unsupervised statistical analysis of these markers showed the enormous genomic variation within the species but did not show any correlation with a pathogenic phenotype. We therefore used supervised statistical analysis to identify discriminating markers. Genetic programming was used both to identify predictive markers and to define their interrelationships. A model consisting of five markers was developed that together correctly predicted 100% of the clinical strains and 69% of the environmental strains. Conclusions A novel approach for identifying predictive markers enabling discrimination between clinical and environmental isolates of L. pneumophila is presented. Out of over 3000 possible markers, five were selected that together enabled correct prediction of all the clinical strains included in this study. This novel approach for identifying predictive markers can be applied to all bacterial species, allowing for better discrimination between strains well equipped to cause human disease and relatively harmless strains. PMID:20630115

Nonketotic hyperglycinemia: Functional assessment of missense variants in GLDC to understand phenotypes of the disease.

PubMed

Bravo-Alonso, Irene; Navarrete, Rosa; Arribas-Carreira, Laura; Perona, Almudena; Abia, David; Couce, María Luz; García-Cazorla, Angels; Morais, Ana; Domingo, Rosario; Ramos, María Antonia; Swanson, Michael A; Van Hove, Johan L K; Ugarte, Magdalena; Pérez, Belén; Pérez-Cerdá, Celia; Rodríguez-Pombo, Pilar

2017-06-01

The rapid analysis of genomic data is providing effective mutational confirmation in patients with clinical and biochemical hallmarks of a specific disease. This is the case for nonketotic hyperglycinemia (NKH), a Mendelian disorder causing seizures in neonates and early-infants, primarily due to mutations in the GLDC gene. However, understanding the impact of missense variants identified in this gene is a major challenge for the application of genomics into clinical practice. Herein, a comprehensive functional and structural analysis of 19 GLDC missense variants identified in a cohort of 26 NKH patients was performed. Mutant cDNA constructs were expressed in COS7 cells followed by enzymatic assays and Western blot analysis of the GCS P-protein to assess the residual activity and mutant protein stability. Structural analysis, based on molecular modeling of the 3D structure of GCS P-protein, was also performed. We identify hypomorphic variants that produce attenuated phenotypes with improved prognosis of the disease. Structural analysis allows us to interpret the effects of mutations on protein stability and catalytic activity, providing molecular evidence for clinical outcome and disease severity. Moreover, we identify an important number of mutants whose loss-of-functionality is associated with instability and, thus, are potential targets for rescue using folding therapeutic approaches. © 2017 Wiley Periodicals, Inc.

Using cluster analysis to identify phenotypes and validation of mortality in men with COPD.

PubMed

Chen, Chiung-Zuei; Wang, Liang-Yi; Ou, Chih-Ying; Lee, Cheng-Hung; Lin, Chien-Chung; Hsiue, Tzuen-Ren

2014-12-01

Cluster analysis has been proposed to examine phenotypic heterogeneity in chronic obstructive pulmonary disease (COPD). The aim of this study was to use cluster analysis to define COPD phenotypes and validate them by assessing their relationship with mortality. Male subjects with COPD were recruited to identify and validate COPD phenotypes. Seven variables were assessed for their relevance to COPD, age, FEV(1) % predicted, BMI, history of severe exacerbations, mMRC, SpO(2), and Charlson index. COPD groups were identified by cluster analysis and validated prospectively against mortality during a 4-year follow-up. Analysis of 332 COPD subjects identified five clusters from cluster A to cluster E. Assessment of the predictive validity of these clusters of COPD showed that cluster E patients had higher all cause mortality (HR 18.3, p < 0.0001), and respiratory cause mortality (HR 21.5, p < 0.0001) than those in the other four groups. Cluster E patients also had higher all cause mortality (HR 14.3, p = 0.0002) and respiratory cause mortality (HR 10.1, p = 0.0013) than patients in cluster D alone. COPD patient with severe airflow limitation, many symptoms, and a history of frequent severe exacerbations was a novel and distinct clinical phenotype predicting mortality in men with COPD.

Value of self-monitoring blood glucose pattern analysis in improving diabetes outcomes.

PubMed

Parkin, Christopher G; Davidson, Jaime A

2009-05-01

Self-monitoring of blood glucose (SMBG) is an important adjunct to hemoglobin A1c (HbA1c) testing. This action can distinguish between fasting, preprandial, and postprandial hyperglycemia; detect glycemic excursions; identify and monitor resolution of hypoglycemia; and provide immediate feedback to patients about the effect of food choices, activity, and medication on glycemic control. Pattern analysis is a systematic approach to identifying glycemic patterns within SMBG data and then taking appropriate action based upon those results. The use of pattern analysis involves: (1) establishing pre- and postprandial glucose targets; (2) obtaining data on glucose levels, carbohydrate intake, medication administration (type, dosages, timing), activity levels and physical/emotional stress; (3) analyzing data to identify patterns of glycemic excursions, assessing any influential factors, and implementing appropriate action(s); and (4) performing ongoing SMBG to assess the impact of any therapeutic changes made. Computer-based and paper-based data collection and management tools can be developed to perform pattern analysis for identifying patterns in SMBG data. This approach to interpreting SMBG data facilitates rational therapeutic adjustments in response to this information. Pattern analysis of SMBG data can be of equal or greater value than measurement of HbA1c levels. 2009 Diabetes Technology Society.

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.

Assessing Group Interaction with Social Language Network Analysis

NASA Astrophysics Data System (ADS)

Scholand, Andrew J.; Tausczik, Yla R.; Pennebaker, James W.

In this paper we discuss a new methodology, social language network analysis (SLNA), that combines tools from social language processing and network analysis to assess socially situated working relationships within a group. Specifically, SLNA aims to identify and characterize the nature of working relationships by processing artifacts generated with computer-mediated communication systems, such as instant message texts or emails. Because social language processing is able to identify psychological, social, and emotional processes that individuals are not able to fully mask, social language network analysis can clarify and highlight complex interdependencies between group members, even when these relationships are latent or unrecognized.

Multispectral analysis of ocean dumped materials

NASA Technical Reports Server (NTRS)

Johnson, R. W.

1977-01-01

Remotely sensed data were collected in conjunction with sea-truth measurements in three experiments in the New York Bight. Pollution features of primary interest were ocean dumped materials, such as sewage sludge and acid waste. Sewage-sludge and acid-waste plumes, including plumes from sewage sludge dumped by the 'line-dump' and 'spot-dump' methods, were located, identified, and mapped. Previously developed quantitative analysis techniques for determining quantitative distributions of materials in sewage sludge dumps were evaluated, along with multispectral analysis techniques developed to identify ocean dumped materials. Results of these experiments and the associated data analysis investigations are presented and discussed.

Detecting coupled collective motions in protein by independent subspace analysis

NASA Astrophysics Data System (ADS)

Sakuraba, Shun; Joti, Yasumasa; Kitao, Akio

2010-11-01

Protein dynamics evolves in a high-dimensional space, comprising aharmonic, strongly correlated motional modes. Such correlation often plays an important role in analyzing protein function. In order to identify significantly correlated collective motions, here we employ independent subspace analysis based on the subspace joint approximate diagonalization of eigenmatrices algorithm for the analysis of molecular dynamics (MD) simulation trajectories. From the 100 ns MD simulation of T4 lysozyme, we extract several independent subspaces in each of which collective modes are significantly correlated, and identify the other modes as independent. This method successfully detects the modes along which long-tailed non-Gaussian probability distributions are obtained. Based on the time cross-correlation analysis, we identified a series of events among domain motions and more localized motions in the protein, indicating the connection between the functionally relevant phenomena which have been independently revealed by experiments.

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

NAC transcription factor genes: genome-wide identification, phylogenetic, motif and cis-regulatory element analysis in pigeonpea (Cajanus cajan (L.) Millsp.).

PubMed

Satheesh, Viswanathan; Jagannadham, P Tej Kumar; Chidambaranathan, Parameswaran; Jain, P K; Srinivasan, R

2014-12-01

The NAC (NAM, ATAF and CUC) proteins are plant-specific transcription factors implicated in development and stress responses. In the present study 88 pigeonpea NAC genes were identified from the recently published draft genome of pigeonpea by using homology based and de novo prediction programmes. These sequences were further subjected to phylogenetic, motif and promoter analyses. In motif analysis, highly conserved motifs were identified in the NAC domain and also in the C-terminal region of the NAC proteins. A phylogenetic reconstruction using pigeonpea, Arabidopsis and soybean NAC genes revealed 33 putative stress-responsive pigeonpea NAC genes. Several stress-responsive cis-elements were identified through in silico analysis of the promoters of these putative stress-responsive genes. This analysis is the first report of NAC gene family in pigeonpea and will be useful for the identification and selection of candidate genes associated with stress tolerance.

Learning from examples - Generation and evaluation of decision trees for software resource analysis

NASA Technical Reports Server (NTRS)

Selby, Richard W.; Porter, Adam A.

1988-01-01

A general solution method for the automatic generation of decision (or classification) trees is investigated. The approach is to provide insights through in-depth empirical characterization and evaluation of decision trees for software resource data analysis. The trees identify classes of objects (software modules) that had high development effort. Sixteen software systems ranging from 3,000 to 112,000 source lines were selected for analysis from a NASA production environment. The collection and analysis of 74 attributes (or metrics), for over 4,700 objects, captured information about the development effort, faults, changes, design style, and implementation style. A total of 9,600 decision trees were automatically generated and evaluated. The trees correctly identified 79.3 percent of the software modules that had high development effort or faults, and the trees generated from the best parameter combinations correctly identified 88.4 percent of the modules on the average.

Interdisciplinary cognitive task analysis: a strategy to develop a comprehensive endoscopic retrograde cholangiopancreatography protocol for use in fellowship training.

PubMed

Canopy, Erin; Evans, Matt; Boehler, Margaret; Roberts, Nicole; Sanfey, Hilary; Mellinger, John

2015-10-01

Endoscopic retrograde cholangiopancreatography is a challenging procedure performed by surgeons and gastroenterologists. We employed cognitive task analysis to identify steps and decision points for this procedure. Standardized interviews were conducted with expert gastroenterologists (7) and surgeons (4) from 4 institutions. A procedural step and cognitive decision point protocol was created from audio-taped transcriptions and was refined by 5 additional surgeons. Conceptual elements, sequential actions, and decision points were iterated for 5 tasks: patient preparation, duodenal intubation, selective cannulation, imaging interpretation with related therapeutic intervention, and complication management. A total of 180 steps were identified. Gastroenterologists identified 34 steps not identified by surgeons, and surgeons identified 20 steps not identified by gastroenterologists. The findings suggest that for complex procedures performed by diverse practitioners, more experts may help delineate distinctive emphases differentiated by training background and type of practice. Copyright © 2015 Elsevier Inc. All rights reserved.

A meta-analysis of 87,040 individuals identifies 23 new susceptibility loci for prostate cancer.

PubMed

Al Olama, Ali Amin; Kote-Jarai, Zsofia; Berndt, Sonja I; Conti, David V; Schumacher, Fredrick; Han, Ying; Benlloch, Sara; Hazelett, Dennis J; Wang, Zhaoming; Saunders, Ed; Leongamornlert, Daniel; Lindstrom, Sara; Jugurnauth-Little, Sara; Dadaev, Tokhir; Tymrakiewicz, Malgorzata; Stram, Daniel O; Rand, Kristin; Wan, Peggy; Stram, Alex; Sheng, Xin; Pooler, Loreall C; Park, Karen; Xia, Lucy; Tyrer, Jonathan; Kolonel, Laurence N; Le Marchand, Loic; Hoover, Robert N; Machiela, Mitchell J; Yeager, Merideth; Burdette, Laurie; Chung, Charles C; Hutchinson, Amy; Yu, Kai; Goh, Chee; Ahmed, Mahbubl; Govindasami, Koveela; Guy, Michelle; Tammela, Teuvo L J; Auvinen, Anssi; Wahlfors, Tiina; Schleutker, Johanna; Visakorpi, Tapio; Leinonen, Katri A; Xu, Jianfeng; Aly, Markus; Donovan, Jenny; Travis, Ruth C; Key, Tim J; Siddiq, Afshan; Canzian, Federico; Khaw, Kay-Tee; Takahashi, Atsushi; Kubo, Michiaki; Pharoah, Paul; Pashayan, Nora; Weischer, Maren; Nordestgaard, Borge G; Nielsen, Sune F; Klarskov, Peter; Røder, Martin Andreas; Iversen, Peter; Thibodeau, Stephen N; McDonnell, Shannon K; Schaid, Daniel J; Stanford, Janet L; Kolb, Suzanne; Holt, Sarah; Knudsen, Beatrice; Coll, Antonio Hurtado; Gapstur, Susan M; Diver, W Ryan; Stevens, Victoria L; Maier, Christiane; Luedeke, Manuel; Herkommer, Kathleen; Rinckleb, Antje E; Strom, Sara S; Pettaway, Curtis; Yeboah, Edward D; Tettey, Yao; Biritwum, Richard B; Adjei, Andrew A; Tay, Evelyn; Truelove, Ann; Niwa, Shelley; Chokkalingam, Anand P; Cannon-Albright, Lisa; Cybulski, Cezary; Wokołorczyk, Dominika; Kluźniak, Wojciech; Park, Jong; Sellers, Thomas; Lin, Hui-Yi; Isaacs, William B; Partin, Alan W; Brenner, Hermann; Dieffenbach, Aida Karina; Stegmaier, Christa; Chen, Constance; Giovannucci, Edward L; Ma, Jing; Stampfer, Meir; Penney, Kathryn L; Mucci, Lorelei; John, Esther M; Ingles, Sue A; Kittles, Rick A; Murphy, Adam B; Pandha, Hardev; Michael, Agnieszka; Kierzek, Andrzej M; Blot, William; Signorello, Lisa B; Zheng, Wei; Albanes, Demetrius; Virtamo, Jarmo; Weinstein, Stephanie; Nemesure, Barbara; Carpten, John; Leske, Cristina; Wu, Suh-Yuh; Hennis, Anselm; Kibel, Adam S; Rybicki, Benjamin A; Neslund-Dudas, Christine; Hsing, Ann W; Chu, Lisa; Goodman, Phyllis J; Klein, Eric A; Zheng, S Lilly; Batra, Jyotsna; Clements, Judith; Spurdle, Amanda; Teixeira, Manuel R; Paulo, Paula; Maia, Sofia; Slavov, Chavdar; Kaneva, Radka; Mitev, Vanio; Witte, John S; Casey, Graham; Gillanders, Elizabeth M; Seminara, Daniella; Riboli, Elio; Hamdy, Freddie C; Coetzee, Gerhard A; Li, Qiyuan; Freedman, Matthew L; Hunter, David J; Muir, Kenneth; Gronberg, Henrik; Neal, David E; Southey, Melissa; Giles, Graham G; Severi, Gianluca; Cook, Michael B; Nakagawa, Hidewaki; Wiklund, Fredrik; Kraft, Peter; Chanock, Stephen J; Henderson, Brian E; Easton, Douglas F; Eeles, Rosalind A; Haiman, Christopher A

2014-10-01

Genome-wide association studies (GWAS) have identified 76 variants associated with prostate cancer risk predominantly in populations of European ancestry. To identify additional susceptibility loci for this common cancer, we conducted a meta-analysis of > 10 million SNPs in 43,303 prostate cancer cases and 43,737 controls from studies in populations of European, African, Japanese and Latino ancestry. Twenty-three new susceptibility loci were identified at association P < 5 × 10(-8); 15 variants were identified among men of European ancestry, 7 were identified in multi-ancestry analyses and 1 was associated with early-onset prostate cancer. These 23 variants, in combination with known prostate cancer risk variants, explain 33% of the familial risk for this disease in European-ancestry populations. These findings provide new regions for investigation into the pathogenesis of prostate cancer and demonstrate the usefulness of combining ancestrally diverse populations to discover risk loci for disease.

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.

Using Work Action Analysis to Identify Web-Portal Requirements for a Professional Development Program

ERIC Educational Resources Information Center

Nickles, George

2007-01-01

This article describes using Work Action Analysis (WAA) as a method for identifying requirements for a web-based portal that supports a professional development program. WAA is a cognitive systems engineering method for modeling multi-agent systems to support design and evaluation. A WAA model of the professional development program of the…

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...

Characterization and expression analysis of two cDNAs encoding Xa1 and oxysterol binding proteins in sorghum (Sorghum bicolor)

USDA-ARS?s Scientific Manuscript database

Using suppression subtractive hybridization (SSH) and subsequent microarray analysis, expression profiles of sorghum genes responsive to greenbug phloem-feeding were obtained and identified. Among the profiles, two cDNAs designated to MM73 and MM95 were identified to encode Xa1 (Xa1) and oxysterol ...

Temporal analysis and spatial mapping of Lymantria dispar nuclear polyhedrosis virus transcripts and in vitro translation polypeptides

Treesearch

James M. Slavicek

1991-01-01

Genomic expression of the Lymantriu dispar multinucleocapsid nuclear polyhedrosis virus (LdMNPV) was studied. Viral specific transcripts expressed in cell culture at various times from 2 through 72 h postinfection were identified and their genomic origins mapped through Northern analysis. Sixty-five distinct transcripts were identified in this...

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…

Becoming an Interdisciplinary Scientist: An Analysis of Students' Experiences in Three Computer Science Doctoral Programmes

ERIC Educational Resources Information Center

Calatrava Moreno, María del Carmen; Danowitz, Mary Ann

2016-01-01

The aim of this study was to identify how and why doctoral students do interdisciplinary research. A mixed-methods approach utilising bibliometric analysis of the publications of 195 students identified those who had published interdisciplinary research. This objective measurement of the interdisciplinarity, applying the Rao-Stirling index to Web…

The Use of Gap Analysis to Increase Student Completion Rates at Travelor Adult School

ERIC Educational Resources Information Center

Gil, Blanca Estela

2013-01-01

This project applied the gap analysis problem-solving framework (Clark & Estes, 2008) in order to help develop strategies to increase completion rates at Travelor Adult School. The purpose of the study was to identify whether the knowledge, motivation and organization barriers were contributing to the identified gap. A mixed method approached…

Identifying What Student Affairs Professionals Value: A Mixed Methods Analysis of Professional Competencies Listed in Job Descriptions

ERIC Educational Resources Information Center

Hoffman, John L.; Bresciani, Marilee J.

2012-01-01

This mixed method study explored the professional competencies that administrators expect from entry-, mid-, and senior-level professionals as reflected in 1,759 job openings posted in 2008. Knowledge, skill, and dispositional competencies were identified during the qualitative phase of the study. Statistical analysis of the prevalence of…

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...

Identifying Engineering Students' English Sentence Reading Comprehension Errors: Applying a Data Mining Technique

ERIC Educational Resources Information Center

Tsai, Yea-Ru; Ouyang, Chen-Sen; Chang, Yukon

2016-01-01

The purpose of this study is to propose a diagnostic approach to identify engineering students' English reading comprehension errors. Student data were collected during the process of reading texts of English for science and technology on a web-based cumulative sentence analysis system. For the analysis, the association-rule, data mining technique…

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

ERIC Educational Resources Information Center

Conn, Katharine M.

2017-01-01

In this article, I identify educational interventions with an impact on student learning in Sub-Saharan Africa. After a systematic literature search, I conducted a meta-analysis synthesizing 56 articles containing 66 separate experiments and quasi-experiments and 83 treatment arms. I evaluated 12 types of education interventions such as the…

Using Latent Class Analysis to Identify Academic and Behavioral Risk Status in Elementary Students

ERIC Educational Resources Information Center

King, Kathleen R.; Lembke, Erica S.; Reinke, Wendy M.

2016-01-01

Identifying classes of children on the basis of academic and behavior risk may have important implications for the allocation of intervention resources within Response to Intervention (RTI) and Multi-Tiered System of Support (MTSS) models. Latent class analysis (LCA) was conducted with a sample of 517 third grade students. Fall screening scores in…

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/

ADAGE signature analysis: differential expression analysis with data-defined gene sets.

PubMed

Tan, Jie; Huyck, Matthew; Hu, Dongbo; Zelaya, René A; Hogan, Deborah A; Greene, Casey S

2017-11-22

Gene set enrichment analysis and overrepresentation analyses are commonly used methods to determine the biological processes affected by a differential expression experiment. This approach requires biologically relevant gene sets, which are currently curated manually, limiting their availability and accuracy in many organisms without extensively curated resources. New feature learning approaches can now be paired with existing data collections to directly extract functional gene sets from big data. Here we introduce a method to identify perturbed processes. In contrast with methods that use curated gene sets, this approach uses signatures extracted from public expression data. We first extract expression signatures from public data using ADAGE, a neural network-based feature extraction approach. We next identify signatures that are differentially active under a given treatment. Our results demonstrate that these signatures represent biological processes that are perturbed by the experiment. Because these signatures are directly learned from data without supervision, they can identify uncurated or novel biological processes. We implemented ADAGE signature analysis for the bacterial pathogen Pseudomonas aeruginosa. For the convenience of different user groups, we implemented both an R package (ADAGEpath) and a web server ( http://adage.greenelab.com ) to run these analyses. Both are open-source to allow easy expansion to other organisms or signature generation methods. We applied ADAGE signature analysis to an example dataset in which wild-type and ∆anr mutant cells were grown as biofilms on the Cystic Fibrosis genotype bronchial epithelial cells. We mapped active signatures in the dataset to KEGG pathways and compared with pathways identified using GSEA. The two approaches generally return consistent results; however, ADAGE signature analysis also identified a signature that revealed the molecularly supported link between the MexT regulon and Anr. We designed ADAGE signature analysis to perform gene set analysis using data-defined functional gene signatures. This approach addresses an important gap for biologists studying non-traditional model organisms and those without extensive curated resources available. We built both an R package and web server to provide ADAGE signature analysis to the community.

Examples of testing global identifiability of biological and biomedical models with the DAISY software.

PubMed

Saccomani, Maria Pia; Audoly, Stefania; Bellu, Giuseppina; D'Angiò, Leontina

2010-04-01

DAISY (Differential Algebra for Identifiability of SYstems) is a recently developed computer algebra software tool which can be used to automatically check global identifiability of (linear and) nonlinear dynamic models described by differential equations involving polynomial or rational functions. Global identifiability is a fundamental prerequisite for model identification which is important not only for biological or medical systems but also for many physical and engineering systems derived from first principles. Lack of identifiability implies that the parameter estimation techniques may not fail but any obtained numerical estimates will be meaningless. The software does not require understanding of the underlying mathematical principles and can be used by researchers in applied fields with a minimum of mathematical background. We illustrate the DAISY software by checking the a priori global identifiability of two benchmark nonlinear models taken from the literature. The analysis of these two examples includes comparison with other methods and demonstrates how identifiability analysis is simplified by this tool. Thus we illustrate the identifiability analysis of other two examples, by including discussion of some specific aspects related to the role of observability and knowledge of initial conditions in testing identifiability and to the computational complexity of the software. The main focus of this paper is not on the description of the mathematical background of the algorithm, which has been presented elsewhere, but on illustrating its use and on some of its more interesting features. DAISY is available on the web site http://www.dei.unipd.it/ approximately pia/. 2010 Elsevier Ltd. All rights reserved.

Practical identifiability analysis of a minimal cardiovascular system model.

PubMed

Pironet, Antoine; Docherty, Paul D; Dauby, Pierre C; Chase, J Geoffrey; Desaive, Thomas

2017-01-17

Parameters of mathematical models of the cardiovascular system can be used to monitor cardiovascular state, such as total stressed blood volume status, vessel elastance and resistance. To do so, the model parameters have to be estimated from data collected at the patient's bedside. This work considers a seven-parameter model of the cardiovascular system and investigates whether these parameters can be uniquely determined using indices derived from measurements of arterial and venous pressures, and stroke volume. An error vector defined the residuals between the simulated and reference values of the seven clinically available haemodynamic indices. The sensitivity of this error vector to each model parameter was analysed, as well as the collinearity between parameters. To assess practical identifiability of the model parameters, profile-likelihood curves were constructed for each parameter. Four of the seven model parameters were found to be practically identifiable from the selected data. The remaining three parameters were practically non-identifiable. Among these non-identifiable parameters, one could be decreased as much as possible. The other two non-identifiable parameters were inversely correlated, which prevented their precise estimation. This work presented the practical identifiability analysis of a seven-parameter cardiovascular system model, from limited clinical data. The analysis showed that three of the seven parameters were practically non-identifiable, thus limiting the use of the model as a monitoring tool. Slight changes in the time-varying function modeling cardiac contraction and use of larger values for the reference range of venous pressure made the model fully practically identifiable. Copyright © 2017. Published by Elsevier B.V.

Late-Notice HIE Investigation

NASA Technical Reports Server (NTRS)

Hejduk, M. D.

2016-01-01

Provide a response to MOWG action item 1410-01: Analyze close approaches which have required mission team action on short notice. Determine why the approaches were identified later in the process than most other events. Method: Performed an analysis to determine whether there is any correlation between late notice event identification and space weather, sparse tracking, or high drag objects, which would allow preventive action to be taken Examined specific late notice events identified by missions as problematic to try to identify root cause and attempt to relate them to the correlation analysis.

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.

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

Farahani, Poupak; Chiu, Sally; Bowlus, Christopher L.

Obesity is a complex disease. To date, over 100 chromosomal loci for body weight, body fat, regional white adipose tissue weight, and other obesity-related traits have been identified in humans and in animal models. For most loci, the underlying genes are not yet identified; some of these chromosomal loci will be alleles of known obesity genes, whereas many will represent alleles of unknown genes. Microarray analysis allows simultaneous multiple gene and pathway discovery. cDNA and oligonucleotide arrays are commonly used to identify differentially expressed genes by surveys of large numbers of known and unnamed genes. Two papers previously identified genesmore » differentially expressed in adipose tissue of mouse models of obesity and diabetes by analysis of hybridization to Affymetrix oligonucleotide chips.« less

Identification of suitable genes contributes to lung adenocarcinoma clustering by multiple meta-analysis methods.

PubMed

Yang, Ze-Hui; Zheng, Rui; Gao, Yuan; Zhang, Qiang

2016-09-01

With the widespread application of high-throughput technology, numerous meta-analysis methods have been proposed for differential expression profiling across multiple studies. We identified the suitable differentially expressed (DE) genes that contributed to lung adenocarcinoma (ADC) clustering based on seven popular multiple meta-analysis methods. Seven microarray expression profiles of ADC and normal controls were extracted from the ArrayExpress database. The Bioconductor was used to perform the data preliminary preprocessing. Then, DE genes across multiple studies were identified. Hierarchical clustering was applied to compare the classification performance for microarray data samples. The classification efficiency was compared based on accuracy, sensitivity and specificity. Across seven datasets, 573 ADC cases and 222 normal controls were collected. After filtering out unexpressed and noninformative genes, 3688 genes were remained for further analysis. The classification efficiency analysis showed that DE genes identified by sum of ranks method separated ADC from normal controls with the best accuracy, sensitivity and specificity of 0.953, 0.969 and 0.932, respectively. The gene set with the highest classification accuracy mainly participated in the regulation of response to external stimulus (P = 7.97E-04), cyclic nucleotide-mediated signaling (P = 0.01), regulation of cell morphogenesis (P = 0.01) and regulation of cell proliferation (P = 0.01). Evaluation of DE genes identified by different meta-analysis methods in classification efficiency provided a new perspective to the choice of the suitable method in a given application. Varying meta-analysis methods always present varying abilities, so synthetic consideration should be taken when providing meta-analysis methods for particular research. © 2015 John Wiley & Sons Ltd.

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

Using qualitative comparative analysis in a systematic review of a complex intervention.

PubMed

Kahwati, Leila; Jacobs, Sara; Kane, Heather; Lewis, Megan; Viswanathan, Meera; Golin, Carol E

2016-05-04

Systematic reviews evaluating complex interventions often encounter substantial clinical heterogeneity in intervention components and implementation features making synthesis challenging. Qualitative comparative analysis (QCA) is a non-probabilistic method that uses mathematical set theory to study complex phenomena; it has been proposed as a potential method to complement traditional evidence synthesis in reviews of complex interventions to identify key intervention components or implementation features that might explain effectiveness or ineffectiveness. The objective of this study was to describe our approach in detail and examine the suitability of using QCA within the context of a systematic review. We used data from a completed systematic review of behavioral interventions to improve medication adherence to conduct two substantive analyses using QCA. The first analysis sought to identify combinations of nine behavior change techniques/components (BCTs) found among effective interventions, and the second analysis sought to identify combinations of five implementation features (e.g., agent, target, mode, time span, exposure) found among effective interventions. For each substantive analysis, we reframed the review's research questions to be designed for use with QCA, calibrated sets (i.e., transformed raw data into data used in analysis), and identified the necessary and/or sufficient combinations of BCTs and implementation features found in effective interventions. Our application of QCA for each substantive analysis is described in detail. We extended the original review findings by identifying seven combinations of BCTs and four combinations of implementation features that were sufficient for improving adherence. We found reasonable alignment between several systematic review steps and processes used in QCA except that typical approaches to study abstraction for some intervention components and features did not support a robust calibration for QCA. QCA was suitable for use within a systematic review of medication adherence interventions and offered insights beyond the single dimension stratifications used in the original completed review. Future prospective use of QCA during a review is needed to determine the optimal way to efficiently integrate QCA into existing approaches to evidence synthesis of complex interventions.

Variants for HDL-C, LDL-C and Triglycerides Identified from Admixture Mapping and Fine-Mapping Analysis in African-American Families

PubMed Central

Shetty, Priya B.; Tang, Hua; Feng, Tao; Tayo, Bamidele; Morrison, Alanna C.; Kardia, Sharon L.R.; Hanis, Craig L.; Arnett, Donna K.; Hunt, Steven C.; Boerwinkle, Eric; Rao, D.C.; Cooper, R.S.; Risch, Neil; Zhu, Xiaofeng

2015-01-01

Background Admixture mapping of lipids was followed-up by family-based association analysis to identify variants for cardiovascular disease in African-Americans. Methods and Results The present study conducted admixture mapping analysis for total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) and triglycerides. The analysis was performed in 1,905 unrelated African-American subjects from the National Heart, Lung and Blood Institute’s Family Blood Pressure Program. Regions showing admixture evidence were followed-up with family-based association analysis in 3,556 African-American subjects from the FBPP. The admixture mapping and family-based association analyses were adjusted for age, age2, sex, body-mass-index, and genome-wide mean ancestry to minimize the confounding due to population stratification. Regions that were suggestive of local ancestry association evidence were found on chromosomes 7 (LDL-C), 8 (HDL-C), 14 (triglycerides) and 19 (total cholesterol and triglycerides). In the fine-mapping analysis, 52,939 SNPs were tested and 11 SNPs (8 independent SNPs) showed nominal significant association with HDL-C (2 SNPs), LDL-C (4 SNPs) and triglycerides (5 SNPs). The family data was used in the fine-mapping to identify SNPs that showed novel associations with lipids and regions including genes with known associations for cardiovascular disease. Conclusions This study identified regions on chromosomes 7, 8, 14 and 19 and 11 SNPs from the fine-mapping analysis that were associated with HDL-C, LDL-C and triglycerides for further studies of cardiovascular disease in African-Americans. PMID:25552592

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.

Is It Feasible to Identify Natural Clusters of TSC-Associated Neuropsychiatric Disorders (TAND)?

PubMed

Leclezio, Loren; Gardner-Lubbe, Sugnet; de Vries, Petrus J

2018-04-01

Tuberous sclerosis complex (TSC) is a genetic disorder with multisystem involvement. The lifetime prevalence of TSC-Associated Neuropsychiatric Disorders (TAND) is in the region of 90% in an apparently unique, individual pattern. This "uniqueness" poses significant challenges for diagnosis, psycho-education, and intervention planning. To date, no studies have explored whether there may be natural clusters of TAND. The purpose of this feasibility study was (1) to investigate the practicability of identifying natural TAND clusters, and (2) to identify appropriate multivariate data analysis techniques for larger-scale studies. TAND Checklist data were collected from 56 individuals with a clinical diagnosis of TSC (n = 20 from South Africa; n = 36 from Australia). Using R, the open-source statistical platform, mean squared contingency coefficients were calculated to produce a correlation matrix, and various cluster analyses and exploratory factor analysis were examined. Ward's method rendered six TAND clusters with good face validity and significant convergence with a six-factor exploratory factor analysis solution. The "bottom-up" data-driven strategies identified a "scholastic" cluster of TAND manifestations, an "autism spectrum disorder-like" cluster, a "dysregulated behavior" cluster, a "neuropsychological" cluster, a "hyperactive/impulsive" cluster, and a "mixed/mood" cluster. These feasibility results suggest that a combination of cluster analysis and exploratory factor analysis methods may be able to identify clinically meaningful natural TAND clusters. Findings require replication and expansion in larger dataset, and could include quantification of cluster or factor scores at an individual level. Copyright © 2018 Elsevier Inc. All rights reserved.

Views of Canadian patients on or nearing dialysis and their caregivers: a thematic analysis.

PubMed

Barnieh, Lianne; King-Shier, Kathryn; Hemmelgarn, Brenda; Laupacis, Andreas; Manns, Liam; Manns, Braden

2014-01-01

Quality of life of patients receiving dialysis has been rated as poor. To synthesize the views of Canadian patients on or nearing dialysis, and those who care for them. Secondary analysis of a survey, distributed through dialysis centres, social media and the Kidney Foundation of Canada. Pan-Canadian convenience sample. Patients, their caregivers and health-care providers. Text responses to open-ended questions on topics relevant to end-stage renal disease. Statements related to needs, beliefs or feelings were identified, and were analysed by thematic content analysis. A total of 544 relevant statements from 189 respondents were included for the thematic content analysis. Four descriptive themes were identified through the content analysis: gaining knowledge, maintaining quality of life, sustaining psychosocial wellbeing and ensuring appropriate care. Respondents primarily identified a need for more information, better communication, increased psychosocial and financial support for patients and their families and a strong desire to maintain their previous lifestyle. Convenience sample; questions were originally asked with a different intent (to identify patient-important research issues). Patients on or nearing dialysis and their caregivers identified four major themes, gaining knowledge, maintaining quality of life, sustaining psychosocial wellbeing and ensuring appropriate care, several of which could be addressed by the health care system without requiring significant resources. These include the development of patient materials and resources, or sharing of existing resources across Canadian renal programs, along with adopting better communication strategies. Other concerns, such as the need for increased psychosocial and financial support, require consideration by health care funders.

Identification of key micro-organisms involved in Douchi fermentation by statistical analysis and their use in an experimental fermentation.

PubMed

Chen, C; Xiang, J Y; Hu, W; Xie, Y B; Wang, T J; Cui, J W; Xu, Y; Liu, Z; Xiang, H; Xie, Q

2015-11-01

To screen and identify safe micro-organisms used during Douchi fermentation, and verify the feasibility of producing high-quality Douchi using these identified micro-organisms. PCR-denaturing gradient gel electrophoresis (DGGE) and automatic amino-acid analyser were used to investigate the microbial diversity and free amino acids (FAAs) content of 10 commercial Douchi samples. The correlations between microbial communities and FAAs were analysed by statistical analysis. Ten strains with significant positive correlation were identified. Then an experiment on Douchi fermentation by identified strains was carried out, and the nutritional composition in Douchi was analysed. Results showed that FAAs and relative content of isoflavone aglycones in verification Douchi samples were generally higher than those in commercial Douchi samples. Our study indicated that fungi, yeasts, Bacillus and lactic acid bacteria were the key players in Douchi fermentation, and with identified probiotic micro-organisms participating in fermentation, a higher quality Douchi product was produced. This is the first report to analyse and confirm the key micro-organisms during Douchi fermentation by statistical analysis. This work proves fermentation micro-organisms to be the key influencing factor of Douchi quality, and demonstrates the feasibility of fermenting Douchi using identified starter micro-organisms. © 2015 The Society for Applied Microbiology.

Ancestry-based stratified analysis of Immunochip data identifies novel associations with celiac disease.

PubMed

Garcia-Etxebarria, Koldo; Jauregi-Miguel, Amaia; Romero-Garmendia, Irati; Plaza-Izurieta, Leticia; Legarda, Maria; Irastorza, Iñaki; Bilbao, Jose Ramon

2016-12-01

To identify candidate genes in celiac disease (CD), we reanalyzed the whole Immunochip CD cohort using a different approach that clusters individuals based on immunoancestry prior to disease association analysis, rather than by geographical origin. We detected 636 new associated SNPs (P<7.02 × 10 -07 ) and identified 5 novel genomic regions, extended 8 others previously identified and also detected 18 isolated signals defined by one or very few significant SNPs. To test whether we could identify putative candidate genes, we performed expression analyses of several genes from the top novel region (chr2:134533564-136169524), from a previously identified locus that is now extended, and a gene marked by an isolated SNP, in duodenum biopsies of active and treated CD patients, and non-celiac controls. In the largest novel region, CCNT2 and R3HDM1 were constitutively underexpressed in disease, even after gluten removal. Moreover, several genes within this region were coexpressed in patients, but not in controls. Other novel genes like KIF21B, REL and SORD also showed altered expression in active disease. Apart from the identification of novel CD loci, these results suggest that ancestry-based stratified analysis is an efficient strategy for association studies in complex diseases.

Veterinary Medicine and Multi-Omics Research for Future Nutrition Targets: Metabolomics and Transcriptomics of the Common Degenerative Mitral Valve Disease in Dogs.

PubMed

Li, Qinghong; Freeman, Lisa M; Rush, John E; Huggins, Gordon S; Kennedy, Adam D; Labuda, Jeffrey A; Laflamme, Dorothy P; Hannah, Steven S

2015-08-01

Canine degenerative mitral valve disease (DMVD) is the most common form of heart disease in dogs. The objective of this study was to identify cellular and metabolic pathways that play a role in DMVD by performing metabolomics and transcriptomics analyses on serum and tissue (mitral valve and left ventricle) samples previously collected from dogs with DMVD or healthy hearts. Gas or liquid chromatography followed by mass spectrophotometry were used to identify metabolites in serum. Transcriptomics analysis of tissue samples was completed using RNA-seq, and selected targets were confirmed by RT-qPCR. Random Forest analysis was used to classify the metabolites that best predicted the presence of DMVD. Results identified 41 known and 13 unknown serum metabolites that were significantly different between healthy and DMVD dogs, representing alterations in fat and glucose energy metabolism, oxidative stress, and other pathways. The three metabolites with the greatest single effect in the Random Forest analysis were γ-glutamylmethionine, oxidized glutathione, and asymmetric dimethylarginine. Transcriptomics analysis identified 812 differentially expressed transcripts in left ventricle samples and 263 in mitral valve samples, representing changes in energy metabolism, antioxidant function, nitric oxide signaling, and extracellular matrix homeostasis pathways. Many of the identified alterations may benefit from nutritional or medical management. Our study provides evidence of the growing importance of integrative approaches in multi-omics research in veterinary and nutritional sciences.

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

A spatial cluster analysis of tractor overturns in Kentucky from 1960 to 2002

USGS Publications Warehouse

Saman, D.M.; Cole, H.P.; Odoi, A.; Myers, M.L.; Carey, D.I.; Westneat, S.C.

2012-01-01

Background: Agricultural tractor overturns without rollover protective structures are the leading cause of farm fatalities in the United States. To our knowledge, no studies have incorporated the spatial scan statistic in identifying high-risk areas for tractor overturns. The aim of this study was to determine whether tractor overturns cluster in certain parts of Kentucky and identify factors associated with tractor overturns. Methods: A spatial statistical analysis using Kulldorff's spatial scan statistic was performed to identify county clusters at greatest risk for tractor overturns. A regression analysis was then performed to identify factors associated with tractor overturns. Results: The spatial analysis revealed a cluster of higher than expected tractor overturns in four counties in northern Kentucky (RR = 2.55) and 10 counties in eastern Kentucky (RR = 1.97). Higher rates of tractor overturns were associated with steeper average percent slope of pasture land by county (p = 0.0002) and a greater percent of total tractors with less than 40 horsepower by county (p<0.0001). Conclusions: This study reveals that geographic hotspots of tractor overturns exist in Kentucky and identifies factors associated with overturns. This study provides policymakers a guide to targeted county-level interventions (e.g., roll-over protective structures promotion interventions) with the intention of reducing tractor overturns in the highest risk counties in Kentucky. ?? 2012 Saman et al.

Identification of Uvaria sp by barcoding coupled with high-resolution melting analysis (Bar-HRM).

PubMed

Osathanunkul, M; Madesis, P; Ounjai, S; Pumiputavon, K; Somboonchai, R; Lithanatudom, P; Chaowasku, T; Wipasa, J; Suwannapoom, C

2016-01-13

DNA barcoding, which was developed about a decade ago, relies on short, standardized regions of the genome to identify plant and animal species. This method can be used to not only identify known species but also to discover novel ones. Numerous sequences are stored in online databases worldwide. One of the ways to save cost and time (by omitting the sequencing step) in species identification is to use available barcode data to design optimized primers for further analysis, such as high-resolution melting analysis (HRM). This study aimed to determine the effectiveness of the hybrid method Bar-HRM (DNA barcoding combined with HRM) to identify species that share similar external morphological features, rather than conduct traditional taxonomic identification that require major parts (leaf, flower, fruit) of the specimens. The specimens used for testing were those, which could not be identified at the species level and could either be Uvaria longipes or Uvaria wrayias, indicated by morphological identification. Primer pairs derived from chloroplast regions (matK, psbA-trnH, rbcL, and trnL) were used in the Bar-HRM. The results obtained from psbA-trnH primers were good enough to help in identifying the specimen while the rest were not. Bar-HRM analysis was proven to be a fast and cost-effective method for plant species identification.

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.

The application of artificial intelligence to microarray data: identification of a novel gene signature to identify bladder cancer progression.

PubMed

Catto, James W F; Abbod, Maysam F; Wild, Peter J; Linkens, Derek A; Pilarsky, Christian; Rehman, Ishtiaq; Rosario, Derek J; Denzinger, Stefan; Burger, Maximilian; Stoehr, Robert; Knuechel, Ruth; Hartmann, Arndt; Hamdy, Freddie C

2010-03-01

New methods for identifying bladder cancer (BCa) progression are required. Gene expression microarrays can reveal insights into disease biology and identify novel biomarkers. However, these experiments produce large datasets that are difficult to interpret. To develop a novel method of microarray analysis combining two forms of artificial intelligence (AI): neurofuzzy modelling (NFM) and artificial neural networks (ANN) and validate it in a BCa cohort. We used AI and statistical analyses to identify progression-related genes in a microarray dataset (n=66 tumours, n=2800 genes). The AI-selected genes were then investigated in a second cohort (n=262 tumours) using immunohistochemistry. We compared the accuracy of AI and statistical approaches to identify tumour progression. AI identified 11 progression-associated genes (odds ratio [OR]: 0.70; 95% confidence interval [CI], 0.56-0.87; p=0.0004), and these were more discriminate than genes chosen using statistical analyses (OR: 1.24; 95% CI, 0.96-1.60; p=0.09). The expression of six AI-selected genes (LIG3, FAS, KRT18, ICAM1, DSG2, and BRCA2) was determined using commercial antibodies and successfully identified tumour progression (concordance index: 0.66; log-rank test: p=0.01). AI-selected genes were more discriminate than pathologic criteria at determining progression (Cox multivariate analysis: p=0.01). Limitations include the use of statistical correlation to identify 200 genes for AI analysis and that we did not compare regression identified genes with immunohistochemistry. AI and statistical analyses use different techniques of inference to determine gene-phenotype associations and identify distinct prognostic gene signatures that are equally valid. We have identified a prognostic gene signature whose members reflect a variety of carcinogenic pathways that could identify progression in non-muscle-invasive BCa. 2009 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Job Literacy Analysis: A Practical Methodology for Use in Identifying Job-Related Literacy Skills.

ERIC Educational Resources Information Center

Norback, Judith Shaul; And Others

The Job Literacy Analysis (JLA) was developed in response to the need for analyzing the literacy requirements of various occupations in an effort to match the instruction to the job and to enhance the job relatedness of curricula. It is a systematic, comprehensive process for identifying the important literacy skills needed by workers to function…

Identifying and Measuring Dimensions of Urban Deprivation in Montreal: An Analysis of the 1996 Census Data.

ERIC Educational Resources Information Center

Langlois, Andre; Kitchen, Peter

2001-01-01

Used 1996 Canadian census data to examine the spatial structure and intensity of urban deprivation in Montreal. Analysis of 20 indicators of urban deprivation identified 6 main types of deprivation in the city and found that they were most visible on the Island of Montreal. Urban deprivation was not confined to the inner city. (SM)

Microsatellite analysis of the EU1 lineage of Phytophthora ramorum in Washington state nurseries, landscapes, and waterways

Treesearch

Katie Coats; Marianne Elliott; Gary Chastagner

2017-01-01

Microsatellite analysis initially identified genetic variations within the NA1 clonal lineage of Phytophthora ramorum; however, in Washington nurseries, the genetic population of P. ramorum has shifted and is now dominated by two other lineages, NA2 and EU1. In this study, recently identified markers that are more variable, and...

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

[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.

Identifying Innovative Interventions to Promote Healthy Eating Using Consumption-Oriented Food Supply Chain Analysis.

PubMed

Hawkes, Corinna

2009-07-01

The mapping and analysis of supply chains is a technique increasingly used to address problems in the food system. Yet such supply chain management has not yet been applied as a means of encouraging healthier diets. Moreover, most policies recommended to promote healthy eating focus on the consumer end of the chain. This article proposes a consumption-oriented food supply chain analysis to identify the changes needed in the food supply chain to create a healthier food environment, measured in terms of food availability, prices, and marketing. Along with established forms of supply chain analysis, the method is informed by a historical overview of how food supply chains have changed over time. The method posits that the actors and actions in the chain are affected by organizational, financial, technological, and policy incentives and disincentives, which can in turn be levered for change. It presents a preliminary example of the supply of Coca-Cola beverages into school vending machines and identifies further potential applications. These include fruit and vegetable supply chains, local food chains, supply chains for health-promoting versions of food products, and identifying financial incentives in supply chains for healthier eating.

Attention without intention: explicit processing and implicit goal-setting in family medicine residents' written reflections.

PubMed

Shaughnessy, Allen F; Allen, Lucas; Duggan, Ashley

2017-05-01

Reflection, a process of self-analysis to promote learning through better understanding of one's experiences, is often used to assess learners' metacognitive ability. However, writing reflective exercises, not submitted for assessment, may allow learners to explore their experiences and indicate learning and professional growth without explicitly connecting to intentional sense-making. To identify core components of learning about medicine or medical education from family medicine residents' written reflections. Family medicine residents' wrote reflections about their experiences throughout an academic year. Qualitative thematic analysis to identify core components in 767 reflections written by 33 residents. We identified four themes of learning: 'Elaborated reporting' and 'metacognitive monitoring' represent explicit, purposeful self-analysis that typically would be characterised as reflective learning about medicine. 'Simple reporting' and 'goal setting' signal an analysis of experience that indicates learning and professional growth but that is overlooked as a component of learning. Identified themes elucidate the explicit and implicit forms of written reflection as sense-making and learning. An expanded theoretical understanding of reflection as inclusive of conscious sense-making as well as implicit discovery better enables the art of physician self-development.

Centrality and Flow Vergence gradient based Path analysis of scientific literature: A case study of Biotechnology for Engineering

NASA Astrophysics Data System (ADS)

Lathabai, Hiran H.; Prabhakaran, Thara; Changat, Manoj

2015-07-01

Biotechnology, ever since its inception has had a huge impact on the society and its various applications have been intricately woven into the human web of life. Its evolution amidst all the other research realms vital to mankind is remarkable. In this paper, we intend to identify the radical innovations in Biotechnology for Engineering using network analyses. Centrality analysis and Path analysis are used for identifying important works. Existence of Flow Vergence effect in the scientific literature is revealed. Flow Vergence gradient, an arc metric derived from FV model, is utilised for Path analysis which detects pivotal papers of paradigm shift more accurately. A major paradigm shift has been identified in the business models of Biotechnology for Engineering - 'Capability to Connectivity' model. Evidence towards the adoption of business practices in BT firms by nanotechnology start-ups is also identified. The notion of critical divergence is introduced and the exhibition of interdisciplinary interaction in emerging fields due to critical divergence is discussed. Implications of above analyses which target: (i) Science and technology policy makers, (ii) industrialists and investors, (iii) researchers in academia as well as industry, are also discussed.

Comparing GWAS Results of Complex Traits Using Full Genetic Model and Additive Models for Revealing Genetic Architecture

PubMed Central

Monir, Md. Mamun; Zhu, Jun

2017-01-01

Most of the genome-wide association studies (GWASs) for human complex diseases have ignored dominance, epistasis and ethnic interactions. We conducted comparative GWASs for total cholesterol using full model and additive models, which illustrate the impacts of the ignoring genetic variants on analysis results and demonstrate how genetic effects of multiple loci could differ across different ethnic groups. There were 15 quantitative trait loci with 13 individual loci and 3 pairs of epistasis loci identified by full model, whereas only 14 loci (9 common loci and 5 different loci) identified by multi-loci additive model. Again, 4 full model detected loci were not detected using multi-loci additive model. PLINK-analysis identified two loci and GCTA-analysis detected only one locus with genome-wide significance. Full model identified three previously reported genes as well as several new genes. Bioinformatics analysis showed some new genes are related with cholesterol related chemicals and/or diseases. Analyses of cholesterol data and simulation studies revealed that the full model performs were better than the additive-model performs in terms of detecting power and unbiased estimations of genetic variants of complex traits. PMID:28079101

Identifying Innovative Interventions to Promote Healthy Eating Using Consumption-Oriented Food Supply Chain Analysis

PubMed Central

Hawkes, Corinna

2009-01-01

The mapping and analysis of supply chains is a technique increasingly used to address problems in the food system. Yet such supply chain management has not yet been applied as a means of encouraging healthier diets. Moreover, most policies recommended to promote healthy eating focus on the consumer end of the chain. This article proposes a consumption-oriented food supply chain analysis to identify the changes needed in the food supply chain to create a healthier food environment, measured in terms of food availability, prices, and marketing. Along with established forms of supply chain analysis, the method is informed by a historical overview of how food supply chains have changed over time. The method posits that the actors and actions in the chain are affected by organizational, financial, technological, and policy incentives and disincentives, which can in turn be levered for change. It presents a preliminary example of the supply of Coca-Cola beverages into school vending machines and identifies further potential applications. These include fruit and vegetable supply chains, local food chains, supply chains for health-promoting versions of food products, and identifying financial incentives in supply chains for healthier eating. PMID:23144674

Failure Mode and Effects Analysis: views of hospital staff in the UK.

PubMed

Shebl, Nada; Franklin, Bryony; Barber, Nick; Burnett, Susan; Parand, Anam

2012-01-01

To explore health care professionals' experiences and perceptions of Failure Mode and Effects Analysis (FMEA), a team-based, prospective risk analysis technique. Semi-structured interviews were conducted with 21 operational leads (20 pharmacists, one nurse) in medicines management teams of hospitals participating in a national quality improvement programme. Interviews were transcribed, coded and emergent themes identified using framework analysis. Themes identified included perceptions and experiences of participants with FMEA, validity and reliability issues, and FMEA's use in practice. FMEA was considered to be a structured but subjective process that helps health care professionals get together to identify high risk areas of care. Both positive and negative opinions were expressed, with the majority of interviewees expressing positive views towards FMEA in relation to its structured nature and the use of a multidisciplinary team. Other participants criticised FMEA for being subjective and lacking validity. Most likely to restrict its widespread use were its time consuming nature and its perceived lack of validity and reliability. FMEA is a subjective but systematic tool that helps identify high risk areas, but its time consuming nature, difficulty with the scores and perceived lack of validity and reliability may limit its widespread use.

Assessing the validity of prospective hazard analysis methods: a comparison of two techniques

PubMed Central

2014-01-01

Background Prospective Hazard Analysis techniques such as Healthcare Failure Modes and Effects Analysis (HFMEA) and Structured What If Technique (SWIFT) have the potential to increase safety by identifying risks before an adverse event occurs. Published accounts of their application in healthcare have identified benefits, but the reliability of some methods has been found to be low. The aim of this study was to examine the validity of SWIFT and HFMEA by comparing their outputs in the process of risk assessment, and comparing the results with risks identified by retrospective methods. Methods The setting was a community-based anticoagulation clinic, in which risk assessment activities had been previously performed and were available. A SWIFT and an HFMEA workshop were conducted consecutively on the same day by experienced experts. Participants were a mixture of pharmacists, administrative staff and software developers. Both methods produced lists of risks scored according to the method’s procedure. Participants’ views about the value of the workshops were elicited with a questionnaire. Results SWIFT identified 61 risks and HFMEA identified 72 risks. For both methods less than half the hazards were identified by the other method. There was also little overlap between the results of the workshops and risks identified by prior root cause analysis, staff interviews or clinical governance board discussions. Participants’ feedback indicated that the workshops were viewed as useful. Conclusions Although there was limited overlap, both methods raised important hazards. Scoping the problem area had a considerable influence on the outputs. The opportunity for teams to discuss their work from a risk perspective is valuable, but these methods cannot be relied upon in isolation to provide a comprehensive description. Multiple methods for identifying hazards should be used and data from different sources should be integrated to give a comprehensive view of risk in a system. PMID:24467813

Exploring relation types for literature-based discovery.

PubMed

Preiss, Judita; Stevenson, Mark; Gaizauskas, Robert

2015-09-01

Literature-based discovery (LBD) aims to identify "hidden knowledge" in the medical literature by: (1) analyzing documents to identify pairs of explicitly related concepts (terms), then (2) hypothesizing novel relations between pairs of unrelated concepts that are implicitly related via a shared concept to which both are explicitly related. Many LBD approaches use simple techniques to identify semantically weak relations between concepts, for example, document co-occurrence. These generate huge numbers of hypotheses, difficult for humans to assess. More complex techniques rely on linguistic analysis, for example, shallow parsing, to identify semantically stronger relations. Such approaches generate fewer hypotheses, but may miss hidden knowledge. The authors investigate this trade-off in detail, comparing techniques for identifying related concepts to discover which are most suitable for LBD. A generic LBD system that can utilize a range of relation types was developed. Experiments were carried out comparing a number of techniques for identifying relations. Two approaches were used for evaluation: replication of existing discoveries and the "time slicing" approach.(1) RESULTS: Previous LBD discoveries could be replicated using relations based either on document co-occurrence or linguistic analysis. Using relations based on linguistic analysis generated many fewer hypotheses, but a significantly greater proportion of them were candidates for hidden knowledge. The use of linguistic analysis-based relations improves accuracy of LBD without overly damaging coverage. LBD systems often generate huge numbers of hypotheses, which are infeasible to manually review. Improving their accuracy has the potential to make these systems significantly more usable. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association.

A case study in nonconformance and performance trend analysis

NASA Technical Reports Server (NTRS)

Maloy, Joseph E.; Newton, Coy P.

1990-01-01

As part of NASA's effort to develop an agency-wide approach to trend analysis, a pilot nonconformance and performance trending analysis study was conducted on the Space Shuttle auxiliary power unit (APU). The purpose of the study was to (1) demonstrate that nonconformance analysis can be used to identify repeating failures of a specific item (and the associated failure modes and causes) and (2) determine whether performance parameters could be analyzed and monitored to provide an indication of component or system degradation prior to failure. The nonconformance analysis of the APU did identify repeating component failures, which possibly could be reduced if key performance parameters were monitored and analyzed. The performance-trending analysis verified that the characteristics of hardware parameters can be effective in detecting degradation of hardware performance prior to failure.

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.

Fault identification of rotor-bearing system based on ensemble empirical mode decomposition and self-zero space projection analysis

NASA Astrophysics Data System (ADS)

Jiang, Fan; Zhu, Zhencai; Li, Wei; Zhou, Gongbo; Chen, Guoan

2014-07-01

Accurately identifying faults in rotor-bearing systems by analyzing vibration signals, which are nonlinear and nonstationary, is challenging. To address this issue, a new approach based on ensemble empirical mode decomposition (EEMD) and self-zero space projection analysis is proposed in this paper. This method seeks to identify faults appearing in a rotor-bearing system using simple algebraic calculations and projection analyses. First, EEMD is applied to decompose the collected vibration signals into a set of intrinsic mode functions (IMFs) for features. Second, these extracted features under various mechanical health conditions are used to design a self-zero space matrix according to space projection analysis. Finally, the so-called projection indicators are calculated to identify the rotor-bearing system's faults with simple decision logic. Experiments are implemented to test the reliability and effectiveness of the proposed approach. The results show that this approach can accurately identify faults in rotor-bearing systems.

Microsatellite markers identify three lineages of Phytophthora ramorum in US nurseries, yet single lineages in US forest and European nursery populations.

PubMed

Ivors, K; Garbelotto, M; Vries, I D E; Ruyter-Spira, C; Te Hekkert, B; Rosenzweig, N; Bonants, P

2006-05-01

Analysis of 12 polymorphic simple sequence repeats identified in the genome sequence of Phytophthora ramorum, causal agent of 'sudden oak death', revealed genotypic diversity to be significantly higher in nurseries (91% of total) than in forests (18% of total). Our analysis identified only two closely related genotypes in US forests, while the genetic structure of populations from European nurseries was of intermediate complexity, including multiple, closely related genotypes. Multilocus analysis determined populations in US forests reproduce clonally and are likely descendants of a single introduced individual. The 151 isolates analysed clustered in three clades. US forest and European nursery isolates clustered into two distinct clades, while one isolate from a US nursery belonged to a third novel clade. The combined microsatellite, sequencing and morphological analyses suggest the three clades represent distinct evolutionary lineages. All three clades were identified in some US nurseries, emphasizing the role of commercial plant trade in the movement of this pathogen.

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.

Spatial modeling of cutaneous leishmaniasis in the Andean region of Colombia

PubMed Central

Pérez-Flórez, Mauricio; Ocampo, Clara Beatriz; Valderrama-Ardila, Carlos; Alexander, Neal

2016-01-01

The objective of this research was to identify environmental risk factors for cutaneous leishmaniasis (CL) in Colombia and map high-risk municipalities. The study area was the Colombian Andean region, comprising 715 rural and urban municipalities. We used 10 years of CL surveillance: 2000-2009. We used spatial-temporal analysis - conditional autoregressive Poisson random effects modelling - in a Bayesian framework to model the dependence of municipality-level incidence on land use, climate, elevation and population density. Bivariable spatial analysis identified rainforests, forests and secondary vegetation, temperature, and annual precipitation as positively associated with CL incidence. By contrast, livestock agroecosystems and temperature seasonality were negatively associated. Multivariable analysis identified land use - rainforests and agro-livestock - and climate - temperature, rainfall and temperature seasonality - as best predictors of CL. We conclude that climate and land use can be used to identify areas at high risk of CL and that this approach is potentially applicable elsewhere in Latin America. PMID:27355214

Using multi-scale entropy and principal component analysis to monitor gears degradation via the motor current signature analysis

NASA Astrophysics Data System (ADS)

Aouabdi, Salim; Taibi, Mahmoud; Bouras, Slimane; Boutasseta, Nadir

2017-06-01

This paper describes an approach for identifying localized gear tooth defects, such as pitting, using phase currents measured from an induction machine driving the gearbox. A new tool of anomaly detection based on multi-scale entropy (MSE) algorithm SampEn which allows correlations in signals to be identified over multiple time scales. The motor current signature analysis (MCSA) in conjunction with principal component analysis (PCA) and the comparison of observed values with those predicted from a model built using nominally healthy data. The Simulation results show that the proposed method is able to detect gear tooth pitting in current signals.

Using factor analysis to identify neuromuscular synergies during treadmill walking

NASA Technical Reports Server (NTRS)

Merkle, L. A.; Layne, C. S.; Bloomberg, J. J.; Zhang, J. J.

1998-01-01

Neuroscientists are often interested in grouping variables to facilitate understanding of a particular phenomenon. Factor analysis is a powerful statistical technique that groups variables into conceptually meaningful clusters, but remains underutilized by neuroscience researchers presumably due to its complicated concepts and procedures. This paper illustrates an application of factor analysis to identify coordinated patterns of whole-body muscle activation during treadmill walking. Ten male subjects walked on a treadmill (6.4 km/h) for 20 s during which surface electromyographic (EMG) activity was obtained from the left side sternocleidomastoid, neck extensors, erector spinae, and right side biceps femoris, rectus femoris, tibialis anterior, and medial gastrocnemius. Factor analysis revealed 65% of the variance of seven muscles sampled aligned with two orthogonal factors, labeled 'transition control' and 'loading'. These two factors describe coordinated patterns of muscular activity across body segments that would not be evident by evaluating individual muscle patterns. The results show that factor analysis can be effectively used to explore relationships among muscle patterns across all body segments to increase understanding of the complex coordination necessary for smooth and efficient locomotion. We encourage neuroscientists to consider using factor analysis to identify coordinated patterns of neuromuscular activation that would be obscured using more traditional EMG analyses.

Analysis and Derivation of Allocations for Fiber Contaminants in Liquid Bipropellant Systems

NASA Technical Reports Server (NTRS)

Lowrey, N. M; ibrahim, K. Y.

2012-01-01

An analysis was performed to identify the engineering rationale for the existing particulate limits in MSFC-SPEC-164, Cleanliness of Components for Use in Oxygen, Fuel, and Pneumatic Systems, determine the applicability of this rationale to fibers, identify potential risks that may result from fiber contamination in liquid oxygen/fuel bipropellant systems, and bound each of these risks. The objective of this analysis was to determine whether fiber contamination exceeding the established quantitative limits for particulate can be tolerated in these systems and, if so, to derive and recommend quantitative allocations for fibers beyond the limits established for other particulate. Knowledge gaps were identified that limit a complete understanding of the risk of promoted ignition from an accumulation of fibers in a gaseous oxygen system.

Journal rankings by citation analysis in health sciences librarianship.

PubMed Central

Fang, M L

1989-01-01

The purpose of this study was to identify objectively a hierarchical ranking of journals for health sciences librarians with faculty status. Such a guideline can indicate a journal's value for promotion and tenure consideration. Lists of recent research articles (1982-1986) in health sciences librarianship, and articles written by health sciences librarians, were compiled by searching Social SCISEARCH and MEDLINE. The journals publishing those articles are presented. Results show BMLA as the most prominent journal in the field. Therefore, citations from articles in BMLA from 1982 to 1986 were chosen as a sample for citation analysis. Citation analysis was employed to identify the most frequently cited journals. Some characteristics of the citations in BMLA are also discussed. The ranking of journals based on citation frequency, as a result, was identified. PMID:2655785

SigTree: A Microbial Community Analysis Tool to Identify and Visualize Significantly Responsive Branches in a Phylogenetic Tree.

PubMed

Stevens, John R; Jones, Todd R; Lefevre, Michael; Ganesan, Balasubramanian; Weimer, Bart C

2017-01-01

Microbial community analysis experiments to assess the effect of a treatment intervention (or environmental change) on the relative abundance levels of multiple related microbial species (or operational taxonomic units) simultaneously using high throughput genomics are becoming increasingly common. Within the framework of the evolutionary phylogeny of all species considered in the experiment, this translates to a statistical need to identify the phylogenetic branches that exhibit a significant consensus response (in terms of operational taxonomic unit abundance) to the intervention. We present the R software package SigTree , a collection of flexible tools that make use of meta-analysis methods and regular expressions to identify and visualize significantly responsive branches in a phylogenetic tree, while appropriately adjusting for multiple comparisons.

Software analysis handbook: Software complexity analysis and software reliability estimation and prediction

NASA Technical Reports Server (NTRS)

Lee, Alice T.; Gunn, Todd; Pham, Tuan; Ricaldi, Ron

1994-01-01

This handbook documents the three software analysis processes the Space Station Software Analysis team uses to assess space station software, including their backgrounds, theories, tools, and analysis procedures. Potential applications of these analysis results are also presented. The first section describes how software complexity analysis provides quantitative information on code, such as code structure and risk areas, throughout the software life cycle. Software complexity analysis allows an analyst to understand the software structure, identify critical software components, assess risk areas within a software system, identify testing deficiencies, and recommend program improvements. Performing this type of analysis during the early design phases of software development can positively affect the process, and may prevent later, much larger, difficulties. The second section describes how software reliability estimation and prediction analysis, or software reliability, provides a quantitative means to measure the probability of failure-free operation of a computer program, and describes the two tools used by JSC to determine failure rates and design tradeoffs between reliability, costs, performance, and schedule.

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.

Comprehensive Analysis of CBFβ-MYH11 Fusion Transcripts in Acute Myeloid Leukemia by RT-PCR Analysis

PubMed Central

Kadkol, ShriHari S.; Bruno, Annette; Dodge, Carol; Lindgren, Valerie; Ravandi, Farhad

2004-01-01

CBFβ-MYH11 fusion transcripts are expressed in acute myeloid leukemias of the M4Eo subtype. Patients who express CBFβ-MYH11 fusion transcripts respond favorably to high-dose chemotherapy and are generally spared allogeneic bone marrow transplantation. Hence it is important to identify this fusion in all patients with acute myeloid leukemia M4Eo leukemia. The fusion can be detected by cytogenetics, fluorescence in-situ hybridization (FISH), or by molecular analysis with RT-PCR. Multiple fusion transcripts arising as a result of various breakpoints in the CBFβ and MYH11 have been identified. In this report we describe a comprehensive RT-PCR assay to identify all known fusion transcripts and provide an algorithm for molecular analysis of CBFβ-MYH11 fusions from patient specimens. Further, identification of the fusion transcript by such an assay would help in the diagnosis and follow up of patients with cryptic inversion 16 translocations (such as patient 2 in this report) not detected by standard cytogenetics or FISH and for rational design of probes for quantitative analysis by real-time PCR. PMID:14736823

A Thematic Analysis of Online Discussion Boards for Vasectomy.

PubMed

Samplaski, Mary K

2018-01-01

To examine posts on Internet discussion groups related to vasectomies, and identify common ideas through a structured theme analysis. Internet discussion boards were identified using the search term "vasectomy." Three discussion boards were identified as having the most posts and were chosen for analysis. Using an iterative and structured analysis process, each post was analyzed using thematic analysis in 3 steps (open coding, axial coding, and selective coding) to determine common themes. A total of 129 posts were analyzed. The most common posts related to changes in sexual function after vasectomy. The second most common theme was pain after vasectomy. There were also posts about considerations before vasectomy, planning for postvasectomy care, what to expect after vasectomy, potential issues after vasectomy and how to manage these, and feelings about vasectomy. Some of the information present did not have a factual basis. Posts dedicated to postvasectomy pain and sexual dysfunction were of the highest quantity. There was no medical provider input to these discussion boards. Educational efforts should be targeted to these areas and should include a health-care professional. Copyright © 2017 Elsevier Inc. All rights reserved.

Brain-Derived Neurotrophic Factor Levels in Autism: A Systematic Review and Meta-Analysis.

PubMed

Saghazadeh, Amene; Rezaei, Nima

2017-04-01

Brain-derived neurotrophic factor (BDNF) plays an important role in activity-dependent synaptic plasticity. Altered blood BDNF levels have been frequently identified in people with autism spectrum disorders (ASD). There are however wide discrepancies in the evidence. Therefore, we performed the present systematic review and meta-analysis aimed at qualitative and quantitative synthesis of studies that measured blood BDNF levels in ASD and control subjects. Observational studies were identified through electronic database searching and also hand-searching of reference lists of relevant articles. A total of 183 papers were initially identified for review and eventually twenty studies were included in the meta-analysis. A meta-analysis of blood BDNF in 887 patients with ASD and 901 control subjects demonstrated significantly higher BDNF levels in ASD compared to controls with the SMD of 0.47 (95% CI 0.07-0.86, p = 0.02). In addition subgroup meta-analyses were performed based on the BDNF specimen. The present meta-analysis study led to conclusion that BDNF might play role in autism initiation/ propagation and therefore it can be considered as a possible biomarker of ASD.

INTERNAL HAZARDS ANALYSIS FOR LICENSE APPLICATION

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

R.J. Garrett

2005-02-17

The purpose of this internal hazards analysis is to identify and document the internal hazards and potential initiating events associated with preclosure operations of the repository at Yucca Mountain. Internal hazards are those hazards presented by the operation of the facility and by its associated processes that can potentially lead to a radioactive release or cause a radiological hazard. In contrast to external hazards, internal hazards do not involve natural phenomena and external man-made hazards. This internal hazards analysis was performed in support of the preclosure safety analysis and the License Application for the Yucca Mountain Project. The methodology formore » this analysis provides a systematic means to identify internal hazards and potential initiating events that may result in a radiological hazard or radiological release during the repository preclosure period. These hazards are documented in tables of potential internal hazards and potential initiating events (Section 6.6) for input to the repository event sequence categorization process. The results of this analysis will undergo further screening and analysis based on the criteria that apply to the performance of event sequence analyses for the repository preclosure period. The evolving design of the repository will be re-evaluated periodically to ensure that internal hazards that have not been previously evaluated are identified.« less

Systems Analysis of NASA Aviation Safety Program: Final Report

NASA Technical Reports Server (NTRS)

Jones, Sharon M.; Reveley, Mary S.; Withrow, Colleen A.; Evans, Joni K.; Barr, Lawrence; Leone, Karen

2013-01-01

A three-month study (February to April 2010) of the NASA Aviation Safety (AvSafe) program was conducted. This study comprised three components: (1) a statistical analysis of currently available civilian subsonic aircraft data from the National Transportation Safety Board (NTSB), the Federal Aviation Administration (FAA), and the Aviation Safety Information Analysis and Sharing (ASIAS) system to identify any significant or overlooked aviation safety issues; (2) a high-level qualitative identification of future safety risks, with an assessment of the potential impact of the NASA AvSafe research on the National Airspace System (NAS) based on these risks; and (3) a detailed, top-down analysis of the NASA AvSafe program using an established and peer-reviewed systems analysis methodology. The statistical analysis identified the top aviation "tall poles" based on NTSB accident and FAA incident data from 1997 to 2006. A separate examination of medical helicopter accidents in the United States was also conducted. Multiple external sources were used to develop a compilation of ten "tall poles" in future safety issues/risks. The top-down analysis of the AvSafe was conducted by using a modification of the Gibson methodology. Of the 17 challenging safety issues that were identified, 11 were directly addressed by the AvSafe program research portfolio.

Independent Orbiter Assessment (IOA): Analysis of the manned maneuvering unit

NASA Technical Reports Server (NTRS)

Bailey, P. S.

1986-01-01

Results of the Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL) are presented. The IOA approach features a top-down analysis of the hardware to determine failure modes, criticality, and potential critical items (PCIs). To preserve indepedence, this analysis was accomplished without reliance upon the results contained within the NASA FMEA/CIL documentation. This report documents the independent analysis results corresponding to the Manned Maneuvering Unit (MMU) hardware. The MMU is a propulsive backpack, operated through separate hand controllers that input the pilot's translational and rotational maneuvering commands to the control electronics and then to the thrusters. The IOA analysis process utilized available MMU hardware drawings and schematics for defining hardware subsystems, assemblies, components, and hardware items. Final levels of detail were evaluated and analyzed for possible failure modes and effects. Criticality was assigned based upon the worst case severity of the effect for each identified failure mode. The IOA analysis of the MMU found that the majority of the PCIs identified are resultant from the loss of either the propulsion or control functions, or are resultant from inability to perform an immediate or future mission. The five most severe criticalities identified are all resultant from failures imposed on the MMU hand controllers which have no redundancy within the MMU.

Method of identifying hairpin DNA probes by partial fold analysis

DOEpatents

Miller, Benjamin L [Penfield, NY; Strohsahl, Christopher M [Saugerties, NY

2009-10-06

Method of identifying molecular beacons in which a secondary structure prediction algorithm is employed to identify oligonucleotide sequences within a target gene having the requisite hairpin structure. Isolated oligonucleotides, molecular beacons prepared from those oligonucleotides, and their use are also disclosed.

Method of identifying hairpin DNA probes by partial fold analysis

DOEpatents

Miller, Benjamin L.; Strohsahl, Christopher M.

2008-10-28

Methods of identifying molecular beacons in which a secondary structure prediction algorithm is employed to identify oligonucleotide sequences within a target gene having the requisite hairpin structure. Isolated oligonucleotides, molecular beacons prepared from those oligonucleotides, and their use are also disclosed.

Single Marker and Haplotype-Based Association Analysis of Semolina and Pasta Colour in Elite Durum Wheat Breeding Lines Using a High-Density Consensus Map

PubMed Central

Haile, Jemanesh K.; Cory, Aron T.; Clarke, Fran R.; Clarke, John M.; Knox, Ron E.; Pozniak, Curtis J.

2017-01-01

Association mapping is usually performed by testing the correlation between a single marker and phenotypes. However, because patterns of variation within genomes are inherited as blocks, clustering markers into haplotypes for genome-wide scans could be a worthwhile approach to improve statistical power to detect associations. The availability of high-density molecular data allows the possibility to assess the potential of both approaches to identify marker-trait associations in durum wheat. In the present study, we used single marker- and haplotype-based approaches to identify loci associated with semolina and pasta colour in durum wheat, the main objective being to evaluate the potential benefits of haplotype-based analysis for identifying quantitative trait loci. One hundred sixty-nine durum lines were genotyped using the Illumina 90K Infinium iSelect assay, and 12,234 polymorphic single nucleotide polymorphism (SNP) markers were generated and used to assess the population structure and the linkage disequilibrium (LD) patterns. A total of 8,581 SNPs previously localized to a high-density consensus map were clustered into 406 haplotype blocks based on the average LD distance of 5.3 cM. Combining multiple SNPs into haplotype blocks increased the average polymorphism information content (PIC) from 0.27 per SNP to 0.50 per haplotype. The haplotype-based analysis identified 12 loci associated with grain pigment colour traits, including the five loci identified by the single marker-based analysis. Furthermore, the haplotype-based analysis resulted in an increase of the phenotypic variance explained (50.4% on average) and the allelic effect (33.7% on average) when compared to single marker analysis. The presence of multiple allelic combinations within each haplotype locus offers potential for screening the most favorable haplotype series and may facilitate marker-assisted selection of grain pigment colour in durum wheat. These results suggest a benefit of haplotype-based analysis over single marker analysis to detect loci associated with colour traits in durum wheat. PMID:28135299

Meta-analysis of gene expression patterns in animal models of prenatal alcohol exposure suggests role for protein synthesis inhibition and chromatin remodeling

PubMed Central

Rogic, Sanja; Wong, Albertina; Pavlidis, Paul

2017-01-01

Background Prenatal alcohol exposure (PAE) can result in an array of morphological, behavioural and neurobiological deficits that can range in their severity. Despite extensive research in the field and a significant progress made, especially in understanding the range of possible malformations and neurobehavioral abnormalities, the molecular mechanisms of alcohol responses in development are still not well understood. There have been multiple transcriptomic studies looking at the changes in gene expression after PAE in animal models, however there is a limited apparent consensus among the reported findings. In an effort to address this issue, we performed a comprehensive re-analysis and meta-analysis of all suitable, publically available expression data sets. Methods We assembled ten microarray data sets of gene expression after PAE in mouse and rat models consisting of samples from a total of 63 ethanol-exposed and 80 control animals. We re-analyzed each data set for differential expression and then used the results to perform meta-analyses considering all data sets together or grouping them by time or duration of exposure (pre- and post-natal, acute and chronic, respectively). We performed network and Gene Ontology enrichment analysis to further characterize the identified signatures. Results For each sub-analysis we identified signatures of differential expressed genes that show support from multiple studies. Overall, the changes in gene expression were more extensive after acute ethanol treatment during prenatal development than in other models. Considering the analysis of all the data together, we identified a robust core signature of 104 genes down-regulated after PAE, with no up-regulated genes. Functional analysis reveals over-representation of genes involved in protein synthesis, mRNA splicing and chromatin organization. Conclusions Our meta-analysis shows that existing studies, despite superficial dissimilarity in findings, share features that allow us to identify a common core signature set of transcriptome changes in PAE. This is an important step to identifying the biological processes that underlie the etiology of FASD. PMID:26996386

SFRP1 is a possible candidate for epigenetic therapy in non-small cell lung cancer.

PubMed

Taguchi, Y-H; Iwadate, Mitsuo; Umeyama, Hideaki

2016-08-12

Non-small cell lung cancer (NSCLC) remains a lethal disease despite many proposed treatments. Recent studies have indicated that epigenetic therapy, which targets epigenetic effects, might be a new therapeutic methodology for NSCLC. However, it is not clear which objects (e.g., genes) this treatment specifically targets. Secreted frizzled-related proteins (SFRPs) are promising candidates for epigenetic therapy in many cancers, but there have been no reports of SFRPs targeted by epigenetic therapy for NSCLC. This study performed a meta-analysis of reprogrammed NSCLC cell lines instead of the direct examination of epigenetic therapy treatment to identify epigenetic therapy targets. In addition, mRNA expression/promoter methylation profiles were processed by recently proposed principal component analysis based unsupervised feature extraction and categorical regression analysis based feature extraction. The Wnt/β-catenin signalling pathway was extensively enriched among 32 genes identified by feature extraction. Among the genes identified, SFRP1 was specifically indicated to target β-catenin, and thus might be targeted by epigenetic therapy in NSCLC cell lines. A histone deacetylase inhibitor might reactivate SFRP1 based upon the re-analysis of a public domain data set. Numerical computation validated the binding of SFRP1 to WNT1 to suppress Wnt signalling pathway activation in NSCLC. The meta-analysis of reprogrammed NSCLC cell lines identified SFRP1 as a promising target of epigenetic therapy for NSCLC.

An integrated one-step system to extract, analyze and annotate all relevant information from image-based cell screening of chemical libraries.

PubMed

Rabal, Obdulia; Link, Wolfgang; Serelde, Beatriz G; Bischoff, James R; Oyarzabal, Julen

2010-04-01

Here we report the development and validation of a complete solution to manage and analyze the data produced by image-based phenotypic screening campaigns of small-molecule libraries. In one step initial crude images are analyzed for multiple cytological features, statistical analysis is performed and molecules that produce the desired phenotypic profile are identified. A naïve Bayes classifier, integrating chemical and phenotypic spaces, is built and utilized during the process to assess those images initially classified as "fuzzy"-an automated iterative feedback tuning. Simultaneously, all this information is directly annotated in a relational database containing the chemical data. This novel fully automated method was validated by conducting a re-analysis of results from a high-content screening campaign involving 33 992 molecules used to identify inhibitors of the PI3K/Akt signaling pathway. Ninety-two percent of confirmed hits identified by the conventional multistep analysis method were identified using this integrated one-step system as well as 40 new hits, 14.9% of the total, originally false negatives. Ninety-six percent of true negatives were properly recognized too. A web-based access to the database, with customizable data retrieval and visualization tools, facilitates the posterior analysis of annotated cytological features which allows identification of additional phenotypic profiles; thus, further analysis of original crude images is not required.

U.S. Army physical demands study: Identification and validation of the physically demanding tasks of combat arms occupations.

PubMed

Sharp, Marilyn A; Cohen, Bruce S; Boye, Michael W; Foulis, Stephen A; Redmond, Jan E; Larcom, Kathleen; Hydren, Jay R; Gebhardt, Deborah L; Canino, Maria C; Warr, Bradley J; Zambraski, Edward J

2017-11-01

In 2013, the U.S. Army began developing physical tests to predict a recruit's ability to perform the critical, physically demanding tasks (CPDTs) of combat arms jobs previously not open to women. The purpose of this paper is to describe the methodology and results of analyses of the accuracy and inclusiveness of the critical physically demanding task list. While the job analysis included seven combat arms jobs, only data from the 19D Cavalry Scout occupation are presented as the process was similar for all seven jobs. Job analysis METHODS: As the foundation, senior subject matter experts from each job reviewed materials and reached consensus on the CPDTs and performance standards for each job. The list was reviewed by Army leadership and provided to the researchers. The job analysis consisted of reviewing job and task related documents and field manuals, observing >900 soldiers performing the 32 CPDTs, conducting two focus groups for each job, and analyzing responses to widely distributed job analysis questionnaires. Of the 32 CPDTs identified for seven combat jobs, nine were relevant to 19D soldiers. Focus group discussions and job analysis questionnaire results supported the tasks and standards identified by subject matter experts while also identifying additional tasks. The tasks identified by subject matter experts were representative of the physically demanding aspects of the 19D occupation. Published by Elsevier Ltd.

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

PubMed

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

2012-07-01

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

Applying Qualitative Hazard Analysis to Support Quantitative Safety Analysis for Proposed Reduced Wake Separation Conops

NASA Technical Reports Server (NTRS)

Shortle, John F.; Allocco, Michael

2005-01-01

This paper describes a scenario-driven hazard analysis process to identify, eliminate, and control safety-related risks. Within this process, we develop selective criteria to determine the applicability of applying engineering modeling to hypothesized hazard scenarios. This provides a basis for evaluating and prioritizing the scenarios as candidates for further quantitative analysis. We have applied this methodology to proposed concepts of operations for reduced wake separation for closely spaced parallel runways. For arrivals, the process identified 43 core hazard scenarios. Of these, we classified 12 as appropriate for further quantitative modeling, 24 that should be mitigated through controls, recommendations, and / or procedures (that is, scenarios not appropriate for quantitative modeling), and 7 that have the lowest priority for further analysis.

Annual Status Report (Fiscal Year 2011) Composite Analysis of Low-Level Waste Disposal in the Central Plateau at the Hanford Site

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

Nichols, W. E.

2012-03-12

In accordance with the U.S. Department of Energy (DOE) requirements in DOE O 435.1 Chg 11, and as implemented by DOE/RL-2000-29, Rev. 22, the DOE Richland Operations Office (DOE-RL) has prepared this annual summary of the composite analysis for fiscal year (FY) 2011 as originally reported in PNNL-118003 (henceforth referred to as the Composite Analysis). The main emphasis of DOE/RL-2000-29, Rev. 2 is to identify additional data and information to enhance the Composite Analysis and the subsequent PNNL-11800 Addendum 14 (hereinafter referred to as the Addendum), and to address secondary issues identified during the review of the Composite Analysis.

GoIFISH: a system for the quantification of single cell heterogeneity from IFISH images.

PubMed

Trinh, Anne; Rye, Inga H; Almendro, Vanessa; Helland, Aslaug; Russnes, Hege G; Markowetz, Florian

2014-08-26

Molecular analysis has revealed extensive intra-tumor heterogeneity in human cancer samples, but cannot identify cell-to-cell variations within the tissue microenvironment. In contrast, in situ analysis can identify genetic aberrations in phenotypically defined cell subpopulations while preserving tissue-context specificity. GoIFISHGoIFISH is a widely applicable, user-friendly system tailored for the objective and semi-automated visualization, detection and quantification of genomic alterations and protein expression obtained from fluorescence in situ analysis. In a sample set of HER2-positive breast cancers GoIFISHGoIFISH is highly robust in visual analysis and its accuracy compares favorably to other leading image analysis methods. GoIFISHGoIFISH is freely available at www.sourceforge.net/projects/goifish/.

Three novel approaches to structural identifiability analysis in mixed-effects models.

PubMed

Janzén, David L I; Jirstrand, Mats; Chappell, Michael J; Evans, Neil D

2016-05-06

Structural identifiability is a concept that considers whether the structure of a model together with a set of input-output relations uniquely determines the model parameters. In the mathematical modelling of biological systems, structural identifiability is an important concept since biological interpretations are typically made from the parameter estimates. For a system defined by ordinary differential equations, several methods have been developed to analyse whether the model is structurally identifiable or otherwise. Another well-used modelling framework, which is particularly useful when the experimental data are sparsely sampled and the population variance is of interest, is mixed-effects modelling. However, established identifiability analysis techniques for ordinary differential equations are not directly applicable to such models. In this paper, we present and apply three different methods that can be used to study structural identifiability in mixed-effects models. The first method, called the repeated measurement approach, is based on applying a set of previously established statistical theorems. The second method, called the augmented system approach, is based on augmenting the mixed-effects model to an extended state-space form. The third method, called the Laplace transform mixed-effects extension, is based on considering the moment invariants of the systems transfer function as functions of random variables. To illustrate, compare and contrast the application of the three methods, they are applied to a set of mixed-effects models. Three structural identifiability analysis methods applicable to mixed-effects models have been presented in this paper. As method development of structural identifiability techniques for mixed-effects models has been given very little attention, despite mixed-effects models being widely used, the methods presented in this paper provides a way of handling structural identifiability in mixed-effects models previously not possible. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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.

Identification of speech transients using variable frame rate analysis and wavelet packets.

PubMed

Rasetshwane, Daniel M; Boston, J Robert; Li, Ching-Chung

2006-01-01

Speech transients are important cues for identifying and discriminating speech sounds. Yoo et al. and Tantibundhit et al. were successful in identifying speech transients and, emphasizing them, improving the intelligibility of speech in noise. However, their methods are computationally intensive and unsuitable for real-time applications. This paper presents a method to identify and emphasize speech transients that combines subband decomposition by the wavelet packet transform with variable frame rate (VFR) analysis and unvoiced consonant detection. The VFR analysis is applied to each wavelet packet to define a transitivity function that describes the extent to which the wavelet coefficients of that packet are changing. Unvoiced consonant detection is used to identify unvoiced consonant intervals and the transitivity function is amplified during these intervals. The wavelet coefficients are multiplied by the transitivity function for that packet, amplifying the coefficients localized at times when they are changing and attenuating coefficients at times when they are steady. Inverse transform of the modified wavelet packet coefficients produces a signal corresponding to speech transients similar to the transients identified by Yoo et al. and Tantibundhit et al. A preliminary implementation of the algorithm runs more efficiently.

Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer.

PubMed

Michailidou, Kyriaki; Beesley, Jonathan; Lindstrom, Sara; Canisius, Sander; Dennis, Joe; Lush, Michael J; Maranian, Mel J; Bolla, Manjeet K; Wang, Qin; Shah, Mitul; Perkins, Barbara J; Czene, Kamila; Eriksson, Mikael; Darabi, Hatef; Brand, Judith S; Bojesen, Stig E; Nordestgaard, Børge G; Flyger, Henrik; Nielsen, Sune F; Rahman, Nazneen; Turnbull, Clare; Fletcher, Olivia; Peto, Julian; Gibson, Lorna; dos-Santos-Silva, Isabel; Chang-Claude, Jenny; Flesch-Janys, Dieter; Rudolph, Anja; Eilber, Ursula; Behrens, Sabine; Nevanlinna, Heli; Muranen, Taru A; Aittomäki, Kristiina; Blomqvist, Carl; Khan, Sofia; Aaltonen, Kirsimari; Ahsan, Habibul; Kibriya, Muhammad G; Whittemore, Alice S; John, Esther M; Malone, Kathleen E; Gammon, Marilie D; Santella, Regina M; Ursin, Giske; Makalic, Enes; Schmidt, Daniel F; Casey, Graham; Hunter, David J; Gapstur, Susan M; Gaudet, Mia M; Diver, W Ryan; Haiman, Christopher A; Schumacher, Fredrick; Henderson, Brian E; Le Marchand, Loic; Berg, Christine D; Chanock, Stephen J; Figueroa, Jonine; Hoover, Robert N; Lambrechts, Diether; Neven, Patrick; Wildiers, Hans; van Limbergen, Erik; Schmidt, Marjanka K; Broeks, Annegien; Verhoef, Senno; Cornelissen, Sten; Couch, Fergus J; Olson, Janet E; Hallberg, Emily; Vachon, Celine; Waisfisz, Quinten; Meijers-Heijboer, Hanne; Adank, Muriel A; van der Luijt, Rob B; Li, Jingmei; Liu, Jianjun; Humphreys, Keith; Kang, Daehee; Choi, Ji-Yeob; Park, Sue K; Yoo, Keun-Young; Matsuo, Keitaro; Ito, Hidemi; Iwata, Hiroji; Tajima, Kazuo; Guénel, Pascal; Truong, Thérèse; Mulot, Claire; Sanchez, Marie; Burwinkel, Barbara; Marme, Frederik; Surowy, Harald; Sohn, Christof; Wu, Anna H; Tseng, Chiu-chen; Van Den Berg, David; Stram, Daniel O; González-Neira, Anna; Benitez, Javier; Zamora, M Pilar; Perez, Jose Ignacio Arias; Shu, Xiao-Ou; Lu, Wei; Gao, Yu-Tang; Cai, Hui; Cox, Angela; Cross, Simon S; Reed, Malcolm W R; Andrulis, Irene L; Knight, Julia A; Glendon, Gord; Mulligan, Anna Marie; Sawyer, Elinor J; Tomlinson, Ian; Kerin, Michael J; Miller, Nicola; Lindblom, Annika; Margolin, Sara; Teo, Soo Hwang; Yip, Cheng Har; Taib, Nur Aishah Mohd; Tan, Gie-Hooi; Hooning, Maartje J; Hollestelle, Antoinette; Martens, John W M; Collée, J Margriet; Blot, William; Signorello, Lisa B; Cai, Qiuyin; Hopper, John L; Southey, Melissa C; Tsimiklis, Helen; Apicella, Carmel; Shen, Chen-Yang; Hsiung, Chia-Ni; Wu, Pei-Ei; Hou, Ming-Feng; Kristensen, Vessela N; Nord, Silje; Alnaes, Grethe I Grenaker; Giles, Graham G; Milne, Roger L; McLean, Catriona; Canzian, Federico; Trichopoulos, Dimitrios; Peeters, Petra; Lund, Eiliv; Sund, Malin; Khaw, Kay-Tee; Gunter, Marc J; Palli, Domenico; Mortensen, Lotte Maxild; Dossus, Laure; Huerta, Jose-Maria; Meindl, Alfons; Schmutzler, Rita K; Sutter, Christian; Yang, Rongxi; Muir, Kenneth; Lophatananon, Artitaya; Stewart-Brown, Sarah; Siriwanarangsan, Pornthep; Hartman, Mikael; Miao, Hui; Chia, Kee Seng; Chan, Ching Wan; Fasching, Peter A; Hein, Alexander; Beckmann, Matthias W; Haeberle, Lothar; Brenner, Hermann; Dieffenbach, Aida Karina; Arndt, Volker; Stegmaier, Christa; Ashworth, Alan; Orr, Nick; Schoemaker, Minouk J; Swerdlow, Anthony J; Brinton, Louise; Garcia-Closas, Montserrat; Zheng, Wei; Halverson, Sandra L; Shrubsole, Martha; Long, Jirong; Goldberg, Mark S; Labrèche, France; Dumont, Martine; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Grip, Mervi; Brauch, Hiltrud; Hamann, Ute; Brüning, Thomas; Radice, Paolo; Peterlongo, Paolo; Manoukian, Siranoush; Bernard, Loris; Bogdanova, Natalia V; Dörk, Thilo; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M; Devilee, Peter; Tollenaar, Robert A E M; Seynaeve, Caroline; Van Asperen, Christi J; Jakubowska, Anna; Lubinski, Jan; Jaworska, Katarzyna; Huzarski, Tomasz; Sangrajrang, Suleeporn; Gaborieau, Valerie; Brennan, Paul; McKay, James; Slager, Susan; Toland, Amanda E; Ambrosone, Christine B; Yannoukakos, Drakoulis; Kabisch, Maria; Torres, Diana; Neuhausen, Susan L; Anton-Culver, Hoda; Luccarini, Craig; Baynes, Caroline; Ahmed, Shahana; Healey, Catherine S; Tessier, Daniel C; Vincent, Daniel; Bacot, Francois; Pita, Guillermo; Alonso, M Rosario; Álvarez, Nuria; Herrero, Daniel; Simard, Jacques; Pharoah, Paul P D P; Kraft, Peter; Dunning, Alison M; Chenevix-Trench, Georgia; Hall, Per; Easton, Douglas F

2015-04-01

Genome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ∼14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising 15,748 breast cancer cases and 18,084 controls together with 46,785 cases and 42,892 controls from 41 studies genotyped on a 211,155-marker custom array (iCOGS). Analyses were restricted to women of European ancestry. We generated genotypes for more than 11 million SNPs by imputation using the 1000 Genomes Project reference panel, and we identified 15 new loci associated with breast cancer at P < 5 × 10(-8). Combining association analysis with ChIP-seq chromatin binding data in mammary cell lines and ChIA-PET chromatin interaction data from ENCODE, we identified likely target genes in two regions: SETBP1 at 18q12.3 and RNF115 and PDZK1 at 1q21.1. One association appears to be driven by an amino acid substitution encoded in EXO1.

Feasibility study of modern airships, phase 1. Volume 1: Summary and mission analysis (tasks 2 and 4)

NASA Technical Reports Server (NTRS)

Bloetscher, F.

1975-01-01

The histroy, potential mission application, and designs of lighter-than-air (LTA) vehicles are researched and evaluated. Missions are identified to which airship vehicles are potentially suited. Results of the mission analysis are combined with the findings of a parametric analysis to formulate the mission/vehicle combinations recommended for further study. Current transportation systems are surveyed and potential areas of competition are identified as well as potential missions resulting from limitations of these systems. Potential areas of military usage are included.

CPTAC researchers report first large-scale integrated proteomic and genomic analysis of a human cancer | Office of Cancer Clinical Proteomics Research

Cancer.gov

Investigators from the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) who comprehensively analyzed 95 human colorectal tumor samples, have determined how gene alterations identified in previous analyses of the same samples are expressed at the protein level. The integration of proteomic and genomic data, or proteogenomics, provides a more comprehensive view of the biological features that drive cancer than genomic analysis alone and may help identify the most important targets for cancer detection and intervention.

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.

CADDIS Volume 4. Data Analysis: Basic Principles & Issues

EPA Pesticide Factsheets

Use of inferential statistics in causal analysis, introduction to data independence and autocorrelation, methods to identifying and control for confounding variables, references for the Basic Principles section of Data Analysis.

Acoustic Emission Analysis of Shuttle Thermal Protection System

NASA Technical Reports Server (NTRS)

Lane, John; Hooker, Jeffery; Immer, Christopher; Walker, James

2004-01-01

Acoustic emission (AE) signals generated from projectile impacts on reinforced and advanced carbon/carbon (RCC and ACC) panels, fired from a compressed-gas gun, identify the type and severity of damage sustained by the target. This type of testing is vital in providing the required "return to flight" (RTF) data needed to ensure continued and safe operation of NASA's Space Shuttle fleet. The gas gun at Kennedy Space Center is capable of propelling 12-inch by 3-inch cylinders of external tank (ET) foam at exit velocities exceeding 1,000 feet per second. Conventional AE analysis techniques require time domain processing of impulse data, along with amplitude distribution analysis. It is well known that identical source excitations can produce a wide range of AE signals amplitudes. In order to satisfy RTF goals, it is necessary to identify impact energy levels above and below damage thresholds. Spectral analysis techniques involving joint time frequency analysis (JTFA) are used to reinforce time domain AE analysis. JTFA analysis of the AE signals consists of short-time Fourier transforms (STFT) and the Huang-Hilbert transform (HHT). The HHT provides a very good measure of the instantaneous frequency of impulse events dominated by a single component. Identifying failure modes and cracking of fibers from flexural and/or extensional mode acoustic signals will help support in-flight as well as postflight impact analysis.

Postpartum stressors: a content analysis.

PubMed

Jevitt, Cecilia M; Groer, Maureen W; Crist, Nancy F; Gonzalez, Lois; Wagner, V Doreen

2012-05-01

A qualitative content analysis was conducted on narratives written by 127 mothers at four to six weeks postpartum. This study aimed to identify and compare postpartum stressors to the Tennessee Postpartum Stress Scale (TPSS). The TPSS is a guide to common postpartum stressors and an instrument to assess postpartum stress. Most participants in this study were white (91%), married (72%), and not working (70%). Eighteen stressor categories aggregated into two themes: Stressors Arising within the Maternal-Newborn Dyad and Stressors External to the Maternal-Newborn Dyad. Sixteen of 20 items on the TPSS were identified in the narratives. No stressor categories outside the TPSS were identified.

Regularized Generalized Canonical Correlation Analysis

ERIC Educational Resources Information Center

Tenenhaus, Arthur; Tenenhaus, Michel

2011-01-01

Regularized generalized canonical correlation analysis (RGCCA) is a generalization of regularized canonical correlation analysis to three or more sets of variables. It constitutes a general framework for many multi-block data analysis methods. It combines the power of multi-block data analysis methods (maximization of well identified criteria) and…

40 CFR 35.927-1 - Infiltration/inflow analysis.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 1 2011-07-01 2011-07-01 false Infiltration/inflow analysis. 35.927-1... Infiltration/inflow analysis. (a) The infiltration/inflow analysis shall demonstrate the nonexistence or possible existence of excessive infiltration/inflow in the sewer system. The analysis should identify the...

40 CFR 35.927-1 - Infiltration/inflow analysis.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 1 2010-07-01 2010-07-01 false Infiltration/inflow analysis. 35.927-1... Infiltration/inflow analysis. (a) The infiltration/inflow analysis shall demonstrate the nonexistence or possible existence of excessive infiltration/inflow in the sewer system. The analysis should identify the...

40 CFR 35.927-1 - Infiltration/inflow analysis.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 1 2013-07-01 2013-07-01 false Infiltration/inflow analysis. 35.927-1... Infiltration/inflow analysis. (a) The infiltration/inflow analysis shall demonstrate the nonexistence or possible existence of excessive infiltration/inflow in the sewer system. The analysis should identify the...

40 CFR 35.927-1 - Infiltration/inflow analysis.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 1 2012-07-01 2012-07-01 false Infiltration/inflow analysis. 35.927-1... Infiltration/inflow analysis. (a) The infiltration/inflow analysis shall demonstrate the nonexistence or possible existence of excessive infiltration/inflow in the sewer system. The analysis should identify the...

40 CFR 35.927-1 - Infiltration/inflow analysis.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 1 2014-07-01 2014-07-01 false Infiltration/inflow analysis. 35.927-1... Infiltration/inflow analysis. (a) The infiltration/inflow analysis shall demonstrate the nonexistence or possible existence of excessive infiltration/inflow in the sewer system. The analysis should identify the...

14 CFR 417.309 - Flight safety system analysis.

Code of Federal Regulations, 2012 CFR

2012-01-01

... system anomaly occurring and all of its effects as determined by the single failure point analysis and... termination system. (c) Single failure point. A command control system must undergo an analysis that... fault tree analysis or a failure modes effects and criticality analysis; (2) Identify all possible...

14 CFR 417.309 - Flight safety system analysis.

Code of Federal Regulations, 2010 CFR

2010-01-01

... system anomaly occurring and all of its effects as determined by the single failure point analysis and... termination system. (c) Single failure point. A command control system must undergo an analysis that... fault tree analysis or a failure modes effects and criticality analysis; (2) Identify all possible...

14 CFR 417.309 - Flight safety system analysis.

Code of Federal Regulations, 2013 CFR

2013-01-01

... system anomaly occurring and all of its effects as determined by the single failure point analysis and... termination system. (c) Single failure point. A command control system must undergo an analysis that... fault tree analysis or a failure modes effects and criticality analysis; (2) Identify all possible...

14 CFR 417.309 - Flight safety system analysis.

Code of Federal Regulations, 2014 CFR

2014-01-01

... system anomaly occurring and all of its effects as determined by the single failure point analysis and... termination system. (c) Single failure point. A command control system must undergo an analysis that... fault tree analysis or a failure modes effects and criticality analysis; (2) Identify all possible...

14 CFR 417.309 - Flight safety system analysis.

Code of Federal Regulations, 2011 CFR

2011-01-01

... system anomaly occurring and all of its effects as determined by the single failure point analysis and... termination system. (c) Single failure point. A command control system must undergo an analysis that... fault tree analysis or a failure modes effects and criticality analysis; (2) Identify all possible...

Dehydration of Methylcyclohexanol Isomers in the Undergraduate Organic Laboratory and Product Analysis by Gas Chromatography-Mass Spectroscopy (GC-MS)

ERIC Educational Resources Information Center

Clennan, Malgorzata M.; Clennan, Edward L.

2011-01-01

Dehydrations of "cis"- and "trans"-2-methylcyclohexanol mixtures were carried out with 60% sulfuric acid at 78-80 [degrees]C as a function of time and the products were identified by gas chromatography-mass spectroscopy (GC-MS) analysis. The compounds identified in the reaction mixtures include alkenes, 1-, 3-, and 4-methylcyclohexenes and…

Identify temporal trend of air temperature and its impact on forest stream flow in Lower Mississippi River Alluvial Valley using wavelet analysis

Treesearch

Ying Ouyang; Prem B. Parajuli; Yide Li; Theodor D. Leininger; Gary Feng

2017-01-01

Characterization of stream flow is essential to water resource management, water supply planning, environmental protection, and ecological restoration; while air temperature variation due to climate change can exacerbate stream flow and add instability to the flow. In this study, the wavelet analysis technique was employed to identify temporal trend of air temperature...

Quality Control of True Height Profiles Obtained Automatically from Digital Ionograms.

DTIC Science & Technology

1982-05-01

nece.,ssary and Identify by block number) Ionosphere Digisonde Electron Density Profile Ionogram Autoscaling ARTIST 2 , ABSTRACT (Continue on reverae...analysis technique currently used with the ionogram traces scaled automatically by the ARTIST software [Reinisch and Huang, 1983; Reinisch et al...19841, and the generalized polynomial analysis technique POLAN [Titheridge, 1985], using the same ARTIST -identified ionogram traces. 2. To determine how

GIS Analysis of Available Data to Identify regions in the U.S. Where Shallow Ground Water Supplies are Particularly Vulnerable to Contamination by Releases to Biofuels from Underground Storage Tanks

EPA Science Inventory

GIS analysis of available data to identify regions in the U.S. where shallow ground water supplies are particularly vulnerable to contamination by releases of biofuels from underground storage tanks. In this slide presentation, GIS was used to perform a simple numerical and ...

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…

Integrated Immunotherapy for Breast Cancer

DTIC Science & Technology

2013-09-01

that promotes appropriate cellular signals. For example, recent studies by Mohtashami et al have shown that expression of two critical Notch ligands...aggregate analysis for DC populations is identified in other tumors/cancers (10). We also have begun banking tumor associated stromal RNA , healthy stromal... RNA , as well as tumor RNA for future analysis on microarray or RNAseq to identify unique markers which may be influencing DC clustering or maturation

Relationships between Communication Variables and Scores in Team Training Exercises.

DTIC Science & Technology

1982-01-01

against instructor grades for individuals, subteams, and teams. Communication .- rates on the intership circuit tended to be negatively...communications because communications are essential to ASW operations and are of high frequency. In earlier work in this project, Bell (in press) identified...giving these variables an arbitrarily high weight in the factor analysis. A more appropriate analysis is needed to identify useful categories of ASW

Modulating Calcium Signals to Boost AON Exon Skipping for DMD

DTIC Science & Technology

2016-10-01

RNA Seq analysis to identify mechanisms of activity and specificity in order to guide discovery of second-generation skipping drugs or combinations...with greater activity. 15. SUBJECT TERMS Exon skipping, Dantrolene, Calcium, Duchenne, Dytrophy, Dystrophin, anti-sense-oligonucleatide, DMD, RNA ...for a subset of very rare mutations. Finally, we hypothesize that by combining chemical genomics with RNA Seq analysis we can begin to identify

A Latent Class Analysis of Weight-Related Health Behaviors among 2-and 4-Year College Students and Associated Risk of Obesity

ERIC Educational Resources Information Center

Mathur, Charu; Stigler, Melissa; Lust, Katherine; Laska, Melissa

2014-01-01

Little is known about the complex patterning of weight-related health behaviors in 2-and 4-year college students. The objective of this study was to identify and describe unique classes of weight-related health behaviors among college students. Latent class analysis was used to identify homogenous, mutually exclusive classes of nine health…

Graphical Displays Assist In Analysis Of Failures

NASA Technical Reports Server (NTRS)

Pack, Ginger; Wadsworth, David; Razavipour, Reza

1995-01-01

Failure Environment Analysis Tool (FEAT) computer program enables people to see and better understand effects of failures in system. Uses digraph models to determine what will happen to system if set of failure events occurs and to identify possible causes of selected set of failures. Digraphs or engineering schematics used. Also used in operations to help identify causes of failures after they occur. Written in C language.

Dealing with missing standard deviation and mean values in meta-analysis of continuous outcomes: a systematic review.

PubMed

Weir, Christopher J; Butcher, Isabella; Assi, Valentina; Lewis, Stephanie C; Murray, Gordon D; Langhorne, Peter; Brady, Marian C

2018-03-07

Rigorous, informative meta-analyses rely on availability of appropriate summary statistics or individual participant data. For continuous outcomes, especially those with naturally skewed distributions, summary information on the mean or variability often goes unreported. While full reporting of original trial data is the ideal, we sought to identify methods for handling unreported mean or variability summary statistics in meta-analysis. We undertook two systematic literature reviews to identify methodological approaches used to deal with missing mean or variability summary statistics. Five electronic databases were searched, in addition to the Cochrane Colloquium abstract books and the Cochrane Statistics Methods Group mailing list archive. We also conducted cited reference searching and emailed topic experts to identify recent methodological developments. Details recorded included the description of the method, the information required to implement the method, any underlying assumptions and whether the method could be readily applied in standard statistical software. We provided a summary description of the methods identified, illustrating selected methods in example meta-analysis scenarios. For missing standard deviations (SDs), following screening of 503 articles, fifteen methods were identified in addition to those reported in a previous review. These included Bayesian hierarchical modelling at the meta-analysis level; summary statistic level imputation based on observed SD values from other trials in the meta-analysis; a practical approximation based on the range; and algebraic estimation of the SD based on other summary statistics. Following screening of 1124 articles for methods estimating the mean, one approximate Bayesian computation approach and three papers based on alternative summary statistics were identified. Illustrative meta-analyses showed that when replacing a missing SD the approximation using the range minimised loss of precision and generally performed better than omitting trials. When estimating missing means, a formula using the median, lower quartile and upper quartile performed best in preserving the precision of the meta-analysis findings, although in some scenarios, omitting trials gave superior results. Methods based on summary statistics (minimum, maximum, lower quartile, upper quartile, median) reported in the literature facilitate more comprehensive inclusion of randomised controlled trials with missing mean or variability summary statistics within meta-analyses.

The DACUM Job Analysis Process.

ERIC Educational Resources Information Center

Dofasco, Inc., Hamilton (Ontario).

This document explains the DACUM (Developing A Curriculum) process for analyzing task-based jobs to: identify where standard operating procedures are required; identify duplicated low value added tasks; develop performance standards; create job descriptions; and identify the elements that must be included in job-specific training programs. The…

A genome-wide association study of corneal astigmatism: The CREAM Consortium

PubMed Central

Shah, Rupal L.; Li, Qing; Zhao, Wanting; Tedja, Milly S.; Tideman, J. Willem L.; Khawaja, Anthony P.; Fan, Qiao; Yazar, Seyhan; Williams, Katie M.; Verhoeven, Virginie J.M.; Xie, Jing; Wang, Ya Xing; Hess, Moritz; Nickels, Stefan; Lackner, Karl J.; Pärssinen, Olavi; Wedenoja, Juho; Biino, Ginevra; Concas, Maria Pina; Uitterlinden, André; Rivadeneira, Fernando; Jaddoe, Vincent W.V.; Hysi, Pirro G.; Sim, Xueling; Tan, Nicholas; Tham, Yih-Chung; Sensaki, Sonoko; Hofman, Albert; Vingerling, Johannes R.; Jonas, Jost B.; Mitchell, Paul; Hammond, Christopher J.; Höhn, René; Baird, Paul N.; Wong, Tien-Yin; Cheng, Chinfsg-Yu; Teo, Yik Ying; Mackey, David A.; Williams, Cathy; Saw, Seang-Mei; Klaver, Caroline C.W.; Bailey-Wilson, Joan E.

2018-01-01

Purpose To identify genes and genetic markers associated with corneal astigmatism. Methods A meta-analysis of genome-wide association studies (GWASs) of corneal astigmatism undertaken for 14 European ancestry (n=22,250) and 8 Asian ancestry (n=9,120) cohorts was performed by the Consortium for Refractive Error and Myopia. Cases were defined as having >0.75 diopters of corneal astigmatism. Subsequent gene-based and gene-set analyses of the meta-analyzed results of European ancestry cohorts were performed using VEGAS2 and MAGMA software. Additionally, estimates of single nucleotide polymorphism (SNP)-based heritability for corneal and refractive astigmatism and the spherical equivalent were calculated for Europeans using LD score regression. Results The meta-analysis of all cohorts identified a genome-wide significant locus near the platelet-derived growth factor receptor alpha (PDGFRA) gene: top SNP: rs7673984, odds ratio=1.12 (95% CI:1.08–1.16), p=5.55×10−9. No other genome-wide significant loci were identified in the combined analysis or European/Asian ancestry-specific analyses. Gene-based analysis identified three novel candidate genes for corneal astigmatism in Europeans—claudin-7 (CLDN7), acid phosphatase 2, lysosomal (ACP2), and TNF alpha-induced protein 8 like 3 (TNFAIP8L3). Conclusions In addition to replicating a previously identified genome-wide significant locus for corneal astigmatism near the PDGFRA gene, gene-based analysis identified three novel candidate genes, CLDN7, ACP2, and TNFAIP8L3, that warrant further investigation to understand their role in the pathogenesis of corneal astigmatism. The much lower number of genetic variants and genes demonstrating an association with corneal astigmatism compared to published spherical equivalent GWAS analyses suggest a greater influence of rare genetic variants, non-additive genetic effects, or environmental factors in the development of astigmatism. PMID:29422769

A Sleeping Beauty forward genetic screen identifies new genes and pathways driving osteosarcoma development and metastasis

PubMed Central

Moriarity, Branden S; Otto, George M; Rahrmann, Eric P; Rathe, Susan K; Wolf, Natalie K; Weg, Madison T; Manlove, Luke A; LaRue, Rebecca S; Temiz, Nuri A; Molyneux, Sam D; Choi, Kwangmin; Holly, Kevin J; Sarver, Aaron L; Scott, Milcah C; Forster, Colleen L; Modiano, Jaime F; Khanna, Chand; Hewitt, Stephen M; Khokha, Rama; Yang, Yi; Gorlick, Richard; Dyer, Michael A; Largaespada, David A

2016-01-01

Osteosarcomas are sarcomas of the bone, derived from osteoblasts or their precursors, with a high propensity to metastasize. Osteosarcoma is associated with massive genomic instability, making it problematic to identify driver genes using human tumors or prototypical mouse models, many of which involve loss of Trp53 function. To identify the genes driving osteosarcoma development and metastasis, we performed a Sleeping Beauty (SB) transposon-based forward genetic screen in mice with and without somatic loss of Trp53. Common insertion site (CIS) analysis of 119 primary tumors and 134 metastatic nodules identified 232 sites associated with osteosarcoma development and 43 sites associated with metastasis, respectively. Analysis of CIS-associated genes identified numerous known and new osteosarcoma-associated genes enriched in the ErbB, PI3K-AKT-mTOR and MAPK signaling pathways. Lastly, we identified several oncogenes involved in axon guidance, including Sema4d and Sema6d, which we functionally validated as oncogenes in human osteosarcoma. PMID:25961939

Risk Analysis Methods for Deepwater Port Oil Transfer Systems

DOT National Transportation Integrated Search

1976-06-01

This report deals with the risk analysis methodology for oil spills from the oil transfer systems in deepwater ports. Failure mode and effect analysis in combination with fault tree analysis are identified as the methods best suited for the assessmen...

Policy Analysis of Road Traffic Injury Prevention in Iran

PubMed Central

Azami-Aghdash, Saber; Gorji, Hassan Abolghasem; Shabaninejad, Hosein; Sadeghi-Bazargani, Homayoun

2017-01-01

Introduction Due to the large number of Road Traffic Injuries (RTIs) in Iran, authorities have implemented a number of policies for the prevention of RTIs. However, a scientific analysis of these policies has thus far been neglected. Therefore, this study was conducted for policy analysis of RTIs prevention in Iran. Methods This qualitative study with a case study approach was conducted in Iran during 2016 in two phases: First, by reviewing literature and documents of the past ten years, policies that have been executed to prevent RTIs in Iran were identified. In the second phase of the study, the identified policies were ranked by prioritization matrices. The two policies with the highest scores were selected. ‘Policy triangle framework’ was used for Policy analyzing. Stakeholders of these policies (42 people) were interviewed. Data were analyzed manually by implementing Content-Analysis methods. Results The policies of “pupil liaisons” and “safety belt” were selected for analysis from thirteen potential identified polices. The results of some studies revealed that safety belts had not been properly used in Iran (less than 80%). There was an eight-year hiatus between the approval of the safety belts policy and implementation of this policy. Eight actors were identified for safety belts policy. Lack of diligence in implementation of the policy, failing to pay adequate attention to education and the culture of driving, and failing to select an organization for the implementation of the policy, were identified as the main weaknesses of this policy. For ‘pupil liaisons’ policy, five actors were identified. Following the implementation of this policy, the number of penalties was reduced (17.9%). Neglecting scientific findings and individual-based nature of the policy were identified as the primary weaknesses of this policy. Conclusions Taking serious measures to properly execute the policy, educating people, selecting an efficient organization that is responsible for the implementation of the policies, and using international experience are the measures that can be taken to reduce the number of RTIs in the country. PMID:28243417

Comparative transcriptome analysis and identification of candidate effectors in two related rust species (Gymnosporangium yamadae and Gymnosporangium asiaticum).

PubMed

Tao, Si-Qi; Cao, Bin; Tian, Cheng-Ming; Liang, Ying-Mei

2017-08-23

Rust fungi constitute the largest group of plant fungal pathogens. However, a paucity of data, including genomic sequences, transcriptome sequences, and associated molecular markers, hinders the development of inhibitory compounds and prevents their analysis from an evolutionary perspective. Gymnosporangium yamadae and G. asiaticum are two closely related rust fungal species, which are ecologically and economically important pathogens that cause apple rust and pear rust, respectively, proved to be devastating to orchards. In this study, we investigated the transcriptomes of these two Gymnosporangium species during the telial stage of their lifecycles. The aim of this study was to understand the evolutionary patterns of these two related fungi and to identify genes that developed by selection. The transcriptomes of G. yamadae and G. asiaticum were generated from a mixture of RNA from three biological replicates of each species. We obtained 49,318 and 54,742 transcripts, with N50 values of 1957 and 1664, for G. yamadae and G. asiaticum, respectively. We also identified a repertoire of candidate effectors and other gene families associated with pathogenicity. A total of 4947 pairs of putative orthologues between the two species were identified. Estimation of the non-synonymous/synonymous substitution rate ratios for these orthologues identified 116 pairs with Ka/Ks values greater than1 that are under positive selection and 170 pairs with Ka/Ks values of 1 that are under neutral selection, whereas the remaining 4661 genes are subjected to purifying selection. We estimate that the divergence time between the two species is approximately 5.2 Mya. This study constitutes a de novo assembly and comparative analysis between the transcriptomes of the two rust species G. yamadae and G. asiaticum. The results identified several orthologous genes, and many expressed genes were identified by annotation. Our analysis of Ka/Ks ratios identified orthologous genes subjected to positive or purifying selection. An evolutionary analysis of these two species provided a relatively precise divergence time. Overall, the information obtained in this study increases the genetic resources available for research on the genetic diversity of the Gymnosporangium genus.

Autocorrelation and cross-correlation in time series of homicide and attempted homicide

NASA Astrophysics Data System (ADS)

Machado Filho, A.; da Silva, M. F.; Zebende, G. F.

2014-04-01

We propose in this paper to establish the relationship between homicides and attempted homicides by a non-stationary time-series analysis. This analysis will be carried out by Detrended Fluctuation Analysis (DFA), Detrended Cross-Correlation Analysis (DCCA), and DCCA cross-correlation coefficient, ρ(n). Through this analysis we can identify a positive cross-correlation between homicides and attempted homicides. At the same time, looked at from the point of view of autocorrelation (DFA), this analysis can be more informative depending on time scale. For short scale (days), we cannot identify auto-correlations, on the scale of weeks DFA presents anti-persistent behavior, and for long time scales (n>90 days) DFA presents a persistent behavior. Finally, the application of this new type of statistical analysis proved to be efficient and, in this sense, this paper can contribute to a more accurate descriptive statistics of crime.

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.

Risk analysis of hematopoietic stem cell transplant process: failure mode, effect, and criticality analysis and hazard analysis critical control point methods integration based on guidelines to good manufacturing practice for medicinal product ANNEX 20 (February 2008).

PubMed

Gianassi, S; Bisin, S; Bindi, B; Spitaleri, I; Bambi, F

2010-01-01

The collection and handling of hematopoietic stem cells (HSCs) must meet high quality requirements. An integrated Quality Risk Management can help to identify and contain potential risks related to HSC production. Risk analysis techniques allow one to "weigh" identified hazards, considering the seriousness of their effects, frequency, and detectability, seeking to prevent the most harmful hazards. The Hazard Analysis Critical Point, recognized as the most appropriate technique to identify risks associated with physical, chemical, and biological hazards for cellular products, consists of classifying finished product specifications and limits of acceptability, identifying all off-specifications, defining activities that can cause them, and finally establishing both a monitoring system for each Critical Control Point and corrective actions for deviations. The severity of possible effects on patients, as well as the occurrence and detectability of critical parameters, are measured on quantitative scales (Risk Priority Number [RPN]). Risk analysis was performed with this technique on manipulation process of HPC performed at our blood center. The data analysis showed that hazards with higher values of RPN with greater impact on the process are loss of dose and tracking; technical skills of operators and manual transcription of data were the most critical parameters. Problems related to operator skills are handled by defining targeted training programs, while other critical parameters can be mitigated with the use of continuous control systems. The blood center management software was completed by a labeling system with forms designed to be in compliance with standards in force and by starting implementation of a cryopreservation management module. Copyright 2010 Elsevier Inc. All rights reserved.

Meta-Analysis of Placental Transcriptome Data Identifies a Novel Molecular Pathway Related to Preeclampsia.

PubMed

van Uitert, Miranda; Moerland, Perry D; Enquobahrie, Daniel A; Laivuori, Hannele; van der Post, Joris A M; Ris-Stalpers, Carrie; Afink, Gijs B

2015-01-01

Studies using the placental transcriptome to identify key molecules relevant for preeclampsia are hampered by a relatively small sample size. In addition, they use a variety of bioinformatics and statistical methods, making comparison of findings challenging. To generate a more robust preeclampsia gene expression signature, we performed a meta-analysis on the original data of 11 placenta RNA microarray experiments, representing 139 normotensive and 116 preeclamptic pregnancies. Microarray data were pre-processed and analyzed using standardized bioinformatics and statistical procedures and the effect sizes were combined using an inverse-variance random-effects model. Interactions between genes in the resulting gene expression signature were identified by pathway analysis (Ingenuity Pathway Analysis, Gene Set Enrichment Analysis, Graphite) and protein-protein associations (STRING). This approach has resulted in a comprehensive list of differentially expressed genes that led to a 388-gene meta-signature of preeclamptic placenta. Pathway analysis highlights the involvement of the previously identified hypoxia/HIF1A pathway in the establishment of the preeclamptic gene expression profile, while analysis of protein interaction networks indicates CREBBP/EP300 as a novel element central to the preeclamptic placental transcriptome. In addition, there is an apparent high incidence of preeclampsia in women carrying a child with a mutation in CREBBP/EP300 (Rubinstein-Taybi Syndrome). The 388-gene preeclampsia meta-signature offers a vital starting point for further studies into the relevance of these genes (in particular CREBBP/EP300) and their concomitant pathways as biomarkers or functional molecules in preeclampsia. This will result in a better understanding of the molecular basis of this disease and opens up the opportunity to develop rational therapies targeting the placental dysfunction causal to preeclampsia.

Variants for HDL-C, LDL-C, and triglycerides identified from admixture mapping and fine-mapping analysis in African American families.

PubMed

Shetty, Priya B; Tang, Hua; Feng, Tao; Tayo, Bamidele; Morrison, Alanna C; Kardia, Sharon L R; Hanis, Craig L; Arnett, Donna K; Hunt, Steven C; Boerwinkle, Eric; Rao, Dabeeru C; Cooper, Richard S; Risch, Neil; Zhu, Xiaofeng

2015-02-01

Admixture mapping of lipids was followed-up by family-based association analysis to identify variants for cardiovascular disease in African Americans. The present study conducted admixture mapping analysis for total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides. The analysis was performed in 1905 unrelated African American subjects from the National Heart, Lung and Blood Institute's Family Blood Pressure Program (FBPP). Regions showing admixture evidence were followed-up with family-based association analysis in 3556 African American subjects from the FBPP. The admixture mapping and family-based association analyses were adjusted for age, age(2), sex, body mass index, and genome-wide mean ancestry to minimize the confounding caused by population stratification. Regions that were suggestive of local ancestry association evidence were found on chromosomes 7 (low-density lipoprotein cholesterol), 8 (high-density lipoprotein cholesterol), 14 (triglycerides), and 19 (total cholesterol and triglycerides). In the fine-mapping analysis, 52 939 single-nucleotide polymorphisms (SNPs) were tested and 11 SNPs (8 independent SNPs) showed nominal significant association with high-density lipoprotein cholesterol (2 SNPs), low-density lipoprotein cholesterol (4 SNPs), and triglycerides (5 SNPs). The family data were used in the fine-mapping to identify SNPs that showed novel associations with lipids and regions, including genes with known associations for cardiovascular disease. This study identified regions on chromosomes 7, 8, 14, and 19 and 11 SNPs from the fine-mapping analysis that were associated with high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides for further studies of cardiovascular disease in African Americans. © 2014 American Heart Association, Inc.

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

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

PubMed

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

2008-05-15

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

Systematic analysis of molecular mechanisms for HCC metastasis via text mining approach.

PubMed

Zhen, Cheng; Zhu, Caizhong; Chen, Haoyang; Xiong, Yiru; Tan, Junyuan; Chen, Dong; Li, Jin

2017-02-21

To systematically explore the molecular mechanism for hepatocellular carcinoma (HCC) metastasis and identify regulatory genes with text mining methods. Genes with highest frequencies and significant pathways related to HCC metastasis were listed. A handful of proteins such as EGFR, MDM2, TP53 and APP, were identified as hub nodes in PPI (protein-protein interaction) network. Compared with unique genes for HBV-HCCs, genes particular to HCV-HCCs were less, but may participate in more extensive signaling processes. VEGFA, PI3KCA, MAPK1, MMP9 and other genes may play important roles in multiple phenotypes of metastasis. Genes in abstracts of HCC-metastasis literatures were identified. Word frequency analysis, KEGG pathway and PPI network analysis were performed. Then co-occurrence analysis between genes and metastasis-related phenotypes were carried out. Text mining is effective for revealing potential regulators or pathways, but the purpose of it should be specific, and the combination of various methods will be more useful.

Genome-wide transcriptional analysis of flagellar regeneration in Chlamydomonas reinhardtii identifies orthologs of ciliary disease genes

NASA Technical Reports Server (NTRS)

Stolc, Viktor; Samanta, Manoj Pratim; Tongprasit, Waraporn; Marshall, Wallace F.

2005-01-01

The important role that cilia and flagella play in human disease creates an urgent need to identify genes involved in ciliary assembly and function. The strong and specific induction of flagellar-coding genes during flagellar regeneration in Chlamydomonas reinhardtii suggests that transcriptional profiling of such cells would reveal new flagella-related genes. We have conducted a genome-wide analysis of RNA transcript levels during flagellar regeneration in Chlamydomonas by using maskless photolithography method-produced DNA oligonucleotide microarrays with unique probe sequences for all exons of the 19,803 predicted genes. This analysis represents previously uncharacterized whole-genome transcriptional activity profiling study in this important model organism. Analysis of strongly induced genes reveals a large set of known flagellar components and also identifies a number of important disease-related proteins as being involved with cilia and flagella, including the zebrafish polycystic kidney genes Qilin, Reptin, and Pontin, as well as the testis-expressed tubby-like protein TULP2.

Computational Methods to Work as First-Pass Filter in Deleterious SNP Analysis of Alkaptonuria

PubMed Central

Magesh, R.; George Priya Doss, C.

2012-01-01

A major challenge in the analysis of human genetic variation is to distinguish functional from nonfunctional SNPs. Discovering these functional SNPs is one of the main goals of modern genetics and genomics studies. There is a need to effectively and efficiently identify functionally important nsSNPs which may be deleterious or disease causing and to identify their molecular effects. The prediction of phenotype of nsSNPs by computational analysis may provide a good way to explore the function of nsSNPs and its relationship with susceptibility to disease. In this context, we surveyed and compared variation databases along with in silico prediction programs to assess the effects of deleterious functional variants on protein functions. In other respects, we attempted these methods to work as first-pass filter to identify the deleterious substitutions worth pursuing for further experimental research. In this analysis, we used the existing computational methods to explore the mutation-structure-function relationship in HGD gene causing alkaptonuria. PMID:22606059

BDA: A novel method for identifying defects in body-centered cubic crystals.

PubMed

Möller, Johannes J; Bitzek, Erik

2016-01-01

The accurate and fast identification of crystallographic defects plays a key role for the analysis of atomistic simulation output data. For face-centered cubic (fcc) metals, most existing structure analysis tools allow for the direct distinction of common defects, such as stacking faults or certain low-index surfaces. For body-centered cubic (bcc) metals, on the other hand, a robust way to identify such defects is currently not easily available. We therefore introduce a new method for analyzing atomistic configurations of bcc metals, the BCC Defect Analysis (BDA). It uses existing structure analysis algorithms and combines their results to uniquely distinguish between typical defects in bcc metals. In essence, the BDA method offers the following features:•Identification of typical defect structures in bcc metals.•Reduction of erroneously identified defects by iterative comparison to the defects in the atom's neighborhood.•Availability as ready-to-use Python script for the widespread visualization tool OVITO [http://ovito.org].

Partial least squares based identification of Duchenne muscular dystrophy specific genes.

PubMed

An, Hui-bo; Zheng, Hua-cheng; Zhang, Li; Ma, Lin; Liu, Zheng-yan

2013-11-01

Large-scale parallel gene expression analysis has provided a greater ease for investigating the underlying mechanisms of Duchenne muscular dystrophy (DMD). Previous studies typically implemented variance/regression analysis, which would be fundamentally flawed when unaccounted sources of variability in the arrays existed. Here we aim to identify genes that contribute to the pathology of DMD using partial least squares (PLS) based analysis. We carried out PLS-based analysis with two datasets downloaded from the Gene Expression Omnibus (GEO) database to identify genes contributing to the pathology of DMD. Except for the genes related to inflammation, muscle regeneration and extracellular matrix (ECM) modeling, we found some genes with high fold change, which have not been identified by previous studies, such as SRPX, GPNMB, SAT1, and LYZ. In addition, downregulation of the fatty acid metabolism pathway was found, which may be related to the progressive muscle wasting process. Our results provide a better understanding for the downstream mechanisms of DMD.

Cost accounting for end-of-life care: recommendations to the field by the Cost Accounting Workgroup.

PubMed

Seninger, Stephen; Smith, Dean G

2004-01-01

Accurate measurement of economic costs is prerequisite to progress in improving the care delivered to Americans during the last stage of life. The Robert Wood Johnson Excellence in End-of-Life Care national program assembled a Cost Accounting Workgroup to identify accurate and meaningful methods to measure palliative and end-of-life health care use and costs. Eight key issues were identified: (1) planning the cost analysis; (2) identifying the perspective for cost analysis; (3) describing the end-of-life care program; (4) identifying the appropriate comparison group; (5) defining the period of care to be studied; (6) identifying the units of health care services; (7) assigning monetary values to health care service units; and (8) calculating costs. Economic principles of cost measurement and cost measurement issues encountered by practitioners were reviewed and incorporated into a set of recommendations.

Quantitative DNA Methylation Analysis Identifies a Single CpG Dinucleotide Important for ZAP-70 Expression and Predictive of Prognosis in Chronic Lymphocytic Leukemia

PubMed Central

Claus, Rainer; Lucas, David M.; Stilgenbauer, Stephan; Ruppert, Amy S.; Yu, Lianbo; Zucknick, Manuela; Mertens, Daniel; Bühler, Andreas; Oakes, Christopher C.; Larson, Richard A.; Kay, Neil E.; Jelinek, Diane F.; Kipps, Thomas J.; Rassenti, Laura Z.; Gribben, John G.; Döhner, Hartmut; Heerema, Nyla A.; Marcucci, Guido; Plass, Christoph; Byrd, John C.

2012-01-01

Purpose Increased ZAP-70 expression predicts poor prognosis in chronic lymphocytic leukemia (CLL). Current methods for accurately measuring ZAP-70 expression are problematic, preventing widespread application of these tests in clinical decision making. We therefore used comprehensive DNA methylation profiling of the ZAP-70 regulatory region to identify sites important for transcriptional control. Patients and Methods High-resolution quantitative DNA methylation analysis of the entire ZAP-70 gene regulatory regions was conducted on 247 samples from patients with CLL from four independent clinical studies. Results Through this comprehensive analysis, we identified a small area in the 5′ regulatory region of ZAP-70 that showed large variability in methylation in CLL samples but was universally methylated in normal B cells. High correlation with mRNA and protein expression, as well as activity in promoter reporter assays, revealed that within this differentially methylated region, a single CpG dinucleotide and neighboring nucleotides are particularly important in ZAP-70 transcriptional regulation. Furthermore, by using clustering approaches, we identified a prognostic role for this site in four independent data sets of patients with CLL using time to treatment, progression-free survival, and overall survival as clinical end points. Conclusion Comprehensive quantitative DNA methylation analysis of the ZAP-70 gene in CLL identified important regions responsible for transcriptional regulation. In addition, loss of methylation at a specific single CpG dinucleotide in the ZAP-70 5′ regulatory sequence is a highly predictive and reproducible biomarker of poor prognosis in this disease. This work demonstrates the feasibility of using quantitative specific ZAP-70 methylation analysis as a relevant clinically applicable prognostic test in CLL. PMID:22564988

Identification and fine mapping of a stay-green gene (Brnye1) in pakchoi (Brassica campestris L. ssp. chinensis).

PubMed

Wang, Nan; Liu, Zhiyong; Zhang, Yun; Li, Chengyu; Feng, Hui

2018-03-01

Using bulked segregant analysis combined with next-generation sequencing, we delimited the Brnye1 gene responsible for the stay-green trait of nye in pakchoi. Sequence analysis identified Bra019346 as the candidate gene. "Stay-green" refers to a plant trait whereby leaves remain green during senescence. This trait is useful in the cultivation of pakchoi (Brassica campestris L. ssp. chinensis), which is marketed as a green leaf product. This study aimed to identify the gene responsible for the stay-green trait in pakchoi. We identified a stay-green mutant in pakchoi, which we termed "nye". Genetic analysis revealed that the stay-green trait is controlled by a single recessive gene, Brnye1. Using the BSA-seq method, a 3.0-Mb candidate region was mapped on chromosome A03, which helped us localize Brnye1 to an 81.01-kb interval between SSR markers SSRWN27 and SSRWN30 via linkage analysis in an F 2 population. We identified 12 genes in this region, 11 of which were annotated based on the Brassica rapa annotation database, and one was a functionally unknown gene. An orthologous gene of the Arabidopsis gene AtNYE1, Bra019346, was identified as the potential candidate for Brnye1. Sequence analysis revealed a 40-bp insertion in the second exon of Bra019346 in nye, which generated the TAA stop codon. A candidate gene-specific Indel marker in 1561 F 2 individuals showed perfect cosegregation with Brnye1 in the nye mutant. These results provide a foundation for uncovering the molecular mechanism of the stay-green trait in pakchoi.

Association of methionine synthase gene polymorphisms with wool production and quality traits in Chinese Merino population.

PubMed

Rong, E G; Yang, H; Zhang, Z W; Wang, Z P; Yan, X H; Li, H; Wang, N

2015-10-01

Methionine synthase (MTR) plays a crucial role in maintaining homeostasis of intracellular methionine, folate, and homocysteine, and its activity correlates with DNA methylation in many mammalian tissues. Our previous genomewide association study identified that 1 SNP located in the gene was associated with several wool production and quality traits in Chinese Merino. To confirm the potential involvement of the gene in sheep wool production and quality traits, we performed sheep tissue expression profiling, SNP detection, and association analysis with sheep wool production and quality traits. The semiquantitative reverse transcription PCR analysis showed that the gene was differentially expressed in skin from Merino and Kazak sheep. The sequencing analysis identified a total of 13 SNP in the gene from Chinese Merino sheep. Comparison of the allele frequencies revealed that these 13 identified SNP were significantly different among the 6 tested Chinese Merino strains ( < 0.001). Linkage disequilibrium analysis showed that SNP 3 to 11 were strongly linked in a single haplotype block in the tested population. Association analysis showed that SNP 2 to 11 were significantly associated with the average wool fiber diameter and the fineness SD and that SNP 4 to 11 were significantly associated with the CV of fiber diameter trait ( < 0.05). Single nucleotide polymorphism 2 and SNP 5 to 12 were weakly associated with wool crimp. Similarly, the haplotypes derived from these 13 identified SNP were also significantly associated with the average wool fiber diameter, fineness SD, and the CV of fiber diameter ( < 0.05). Our results suggest that is a candidate gene for sheep wool production and quality traits, and the identified SNP might be used in sheep breeding.

Topology based data analysis identifies a subgroup of breast cancers with a unique mutational profile and excellent survival.

PubMed

Nicolau, Monica; Levine, Arnold J; Carlsson, Gunnar

2011-04-26

High-throughput biological data, whether generated as sequencing, transcriptional microarrays, proteomic, or other means, continues to require analytic methods that address its high dimensional aspects. Because the computational part of data analysis ultimately identifies shape characteristics in the organization of data sets, the mathematics of shape recognition in high dimensions continues to be a crucial part of data analysis. This article introduces a method that extracts information from high-throughput microarray data and, by using topology, provides greater depth of information than current analytic techniques. The method, termed Progression Analysis of Disease (PAD), first identifies robust aspects of cluster analysis, then goes deeper to find a multitude of biologically meaningful shape characteristics in these data. Additionally, because PAD incorporates a visualization tool, it provides a simple picture or graph that can be used to further explore these data. Although PAD can be applied to a wide range of high-throughput data types, it is used here as an example to analyze breast cancer transcriptional data. This identified a unique subgroup of Estrogen Receptor-positive (ER(+)) breast cancers that express high levels of c-MYB and low levels of innate inflammatory genes. These patients exhibit 100% survival and no metastasis. No supervised step beyond distinction between tumor and healthy patients was used to identify this subtype. The group has a clear and distinct, statistically significant molecular signature, it highlights coherent biology but is invisible to cluster methods, and does not fit into the accepted classification of Luminal A/B, Normal-like subtypes of ER(+) breast cancers. We denote the group as c-MYB(+) breast cancer.

Identification of key target genes and pathways in laryngeal carcinoma

PubMed Central

Liu, Feng; Du, Jintao; Liu, Jun; Wen, Bei

2016-01-01

The purpose of the present study was to screen the key genes associated with laryngeal carcinoma and to investigate the molecular mechanism of laryngeal carcinoma progression. The gene expression profile of GSE10935 [Gene Expression Omnibus (GEO) accession number], including 12 specimens from laryngeal papillomas and 12 specimens from normal laryngeal epithelia controls, was downloaded from the GEO database. Differentially expressed genes (DEGs) were screened in laryngeal papillomas compared with normal controls using Limma package in R language, followed by Gene Ontology (GO) enrichment analysis and pathway enrichment analysis. Furthermore, the protein-protein interaction (PPI) network of DEGs was constructed using Cytoscape software and modules were analyzed using MCODE plugin from the PPI network. Furthermore, significant biological pathway regions (sub-pathway) were identified by using iSubpathwayMiner analysis. A total of 67 DEGs were identified, including 27 up-regulated genes and 40 down-regulated genes and they were involved in different GO terms and pathways. PPI network analysis revealed that Ras association (RalGDS/AF-6) domain family member 1 (RASSF1) was a hub protein. The sub-pathway analysis identified 9 significantly enriched sub-pathways, including glycolysis/gluconeogenesis and nitrogen metabolism. Genes such as phosphoglycerate kinase 1 (PGK1), carbonic anhydrase II (CA2), and carbonic anhydrase XII (CA12) whose node degrees were >10 were identified in the disease risk sub-pathway. Genes in the sub-pathway, such as RASSF1, PGK1, CA2 and CA12 were presumed to serve critical roles in laryngeal carcinoma. The present study identified DEGs and their sub-pathways in the disease, which may serve as potential targets for treatment of laryngeal carcinoma. PMID:27446427

Nano-LC-ESI MS/MS analysis of proteins in dried sea dragon Solenognathus hardwickii and bioinformatic analysis of its protein expression profiling.

PubMed

Zhang, Dong-Mei; Feng, Li-Xing; Li, Lu; Liu, Miao; Jiang, Bao-Hong; Yang, Min; Li, Guo-Qiang; Wu, Wan-Ying; Guo, De-An; Liu, Xuan

2016-09-01

The sea dragon Solenognathus hardwickii has long been used as a traditional Chinese medicine for the treatment of various diseases, such as male impotency. To gain a comprehensive insight into the protein components of the sea dragon, shotgun proteomic analysis of its protein expression profiling was conducted in the present study. Proteins were extracted from dried sea dragon using a trichloroacetic acid/acetone precipitation method and then separated by SDS-PAGE. The protein bands were cut from the gel and digested by trypsin to generate peptide mixture. The peptide fragments were then analyzed using nano liquid chromatography tandem mass spectrometry (nano-LC-ESI MS/MS). 810 proteins and 1 577 peptides were identified in the dried sea dragon. The identified proteins exhibited molecular weight values ranging from 1 900 to 3 516 900 Da and pI values from 3.8 to 12.18. Bioinformatic analysis was conducted using the DAVID Bioinformatics Resources 6.7 Gene Ontology (GO) analysis tool to explore possible functions of the identified proteins. Ascribed functions of the proteins mainly included intracellular non-membrane-bound organelle, non-membrane-bounded organelle, cytoskeleton, structural molecule activity, calcium ion binding and etc. Furthermore, possible signal networks of the identified proteins were predicted using STRING (Search Tool for the Retrieval of Interacting Genes) database. Ribosomal protein synthesis was found to play an important role in the signal network. The results of this study, to best of our knowledge, were the first to provide a reference proteome profile for the sea dragon, and would aid in the understanding of the expression and functions of the identified proteins. Copyright © 2016 China Pharmaceutical University. Published by Elsevier B.V. All rights reserved.

Genome-wide Annotation, Identification, and Global Transcriptomic Analysis of Regulatory or Small RNA Gene Expression in Staphylococcus aureus

PubMed Central

Weiss, Andy; Broach, William H.; Wiemels, Richard E.; Mogen, Austin B.; Rice, Kelly C.

2016-01-01

ABSTRACT In Staphylococcus aureus, hundreds of small regulatory or small RNAs (sRNAs) have been identified, yet this class of molecule remains poorly understood and severely understudied. sRNA genes are typically absent from genome annotation files, and as a consequence, their existence is often overlooked, particularly in global transcriptomic studies. To facilitate improved detection and analysis of sRNAs in S. aureus, we generated updated GenBank files for three commonly used S. aureus strains (MRSA252, NCTC 8325, and USA300), in which we added annotations for >260 previously identified sRNAs. These files, the first to include genome-wide annotation of sRNAs in S. aureus, were then used as a foundation to identify novel sRNAs in the community-associated methicillin-resistant strain USA300. This analysis led to the discovery of 39 previously unidentified sRNAs. Investigating the genomic loci of the newly identified sRNAs revealed a surprising degree of inconsistency in genome annotation in S. aureus, which may be hindering the analysis and functional exploration of these elements. Finally, using our newly created annotation files as a reference, we perform a global analysis of sRNA gene expression in S. aureus and demonstrate that the newly identified tsr25 is the most highly upregulated sRNA in human serum. This study provides an invaluable resource to the S. aureus research community in the form of our newly generated annotation files, while at the same time presenting the first examination of differential sRNA expression in pathophysiologically relevant conditions. PMID:26861020

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.

Biomechanical Factors Associated With Jump Height: A Comparison of Cross-Sectional and Pre-to-Posttraining Change Findings.

PubMed

Marshall, Brendan M; Moran, Kieran A

2015-12-01

Previous studies investigating the biomechanical factors associated with maximal countermovement jump height have typically used cross-sectional data. An alternative but less common approach is to use pre-to-posttraining change data, where the relationship between an improvement in jump height and a change in a factor is examined more directly. Our study compared the findings of these approaches. Such an evaluation is necessary because cross-sectional studies are currently a primary source of information for coaches when examining what factors to train to enhance performance. The countermovement jump of 44 males was analyzed before and after an 8-week training intervention. Correlations with jump height were calculated using both cross-sectional (pretraining data only) and pre-to-posttraining change data. Eight factors identified in the cross-sectional analysis were not significantly correlated with a change in jump height in the pre-to-post analysis. Additionally, only 6 of 11 factors identified in the pre-to-post analysis were identified in the cross-sectional analysis. These findings imply that (a) not all factors identified in a cross-sectional analysis may be critical to jump height improvement and (b) cross-sectional analyses alone may not provide an insight into all of the potential factors to train to enhance jump height. Coaches must be aware of these limitations when examining cross-sectional studies to identify factors to train to enhance jump ability. Additional findings highlight that although exercises prescribed to improve jump height should aim to enhance concentric power production at all joints, a particular emphasis on enhancing hip joint peak power may be warranted.

A Healthcare Utilization Analysis Framework for Hot Spotting and Contextual Anomaly Detection

PubMed Central

Hu, Jianying; Wang, Fei; Sun, Jimeng; Sorrentino, Robert; Ebadollahi, Shahram

2012-01-01

Patient medical records today contain vast amount of information regarding patient conditions along with treatment and procedure records. Systematic healthcare resource utilization analysis leveraging such observational data can provide critical insights to guide resource planning and improve the quality of care delivery while reducing cost. Of particular interest to providers are hot spotting: the ability to identify in a timely manner heavy users of the systems and their patterns of utilization so that targeted intervention programs can be instituted, and anomaly detection: the ability to identify anomalous utilization cases where the patients incurred levels of utilization that are unexpected given their clinical characteristics which may require corrective actions. Past work on medical utilization pattern analysis has focused on disease specific studies. We present a framework for utilization analysis that can be easily applied to any patient population. The framework includes two main components: utilization profiling and hot spotting, where we use a vector space model to represent patient utilization profiles, and apply clustering techniques to identify utilization groups within a given population and isolate high utilizers of different types; and contextual anomaly detection for utilization, where models that map patient’s clinical characteristics to the utilization level are built in order to quantify the deviation between the expected and actual utilization levels and identify anomalies. We demonstrate the effectiveness of the framework using claims data collected from a population of 7667 diabetes patients. Our analysis demonstrates the usefulness of the proposed approaches in identifying clinically meaningful instances for both hot spotting and anomaly detection. In future work we plan to incorporate additional sources of observational data including EMRs and disease registries, and develop analytics models to leverage temporal relationships among medical encounters to provide more in-depth insights. PMID:23304306

A healthcare utilization analysis framework for hot spotting and contextual anomaly detection.

PubMed

Hu, Jianying; Wang, Fei; Sun, Jimeng; Sorrentino, Robert; Ebadollahi, Shahram

2012-01-01

Patient medical records today contain vast amount of information regarding patient conditions along with treatment and procedure records. Systematic healthcare resource utilization analysis leveraging such observational data can provide critical insights to guide resource planning and improve the quality of care delivery while reducing cost. Of particular interest to providers are hot spotting: the ability to identify in a timely manner heavy users of the systems and their patterns of utilization so that targeted intervention programs can be instituted, and anomaly detection: the ability to identify anomalous utilization cases where the patients incurred levels of utilization that are unexpected given their clinical characteristics which may require corrective actions. Past work on medical utilization pattern analysis has focused on disease specific studies. We present a framework for utilization analysis that can be easily applied to any patient population. The framework includes two main components: utilization profiling and hot spotting, where we use a vector space model to represent patient utilization profiles, and apply clustering techniques to identify utilization groups within a given population and isolate high utilizers of different types; and contextual anomaly detection for utilization, where models that map patient's clinical characteristics to the utilization level are built in order to quantify the deviation between the expected and actual utilization levels and identify anomalies. We demonstrate the effectiveness of the framework using claims data collected from a population of 7667 diabetes patients. Our analysis demonstrates the usefulness of the proposed approaches in identifying clinically meaningful instances for both hot spotting and anomaly detection. In future work we plan to incorporate additional sources of observational data including EMRs and disease registries, and develop analytics models to leverage temporal relationships among medical encounters to provide more in-depth insights.

Independent Prognostic Factors for Acute Organophosphorus Pesticide Poisoning.

PubMed

Tang, Weidong; Ruan, Feng; Chen, Qi; Chen, Suping; Shao, Xuebo; Gao, Jianbo; Zhang, Mao

2016-07-01

Acute organophosphorus pesticide poisoning (AOPP) is becoming a significant problem and a potential cause of human mortality because of the abuse of organophosphate compounds. This study aims to determine the independent prognostic factors of AOPP by using multivariate logistic regression analysis. The clinical data for 71 subjects with AOPP admitted to our hospital were retrospectively analyzed. This information included the Acute Physiology and Chronic Health Evaluation II (APACHE II) scores, 6-h post-admission blood lactate levels, post-admission 6-h lactate clearance rates, admission blood cholinesterase levels, 6-h post-admission blood cholinesterase levels, cholinesterase activity, blood pH, and other factors. Univariate analysis and multivariate logistic regression analyses were conducted to identify all prognostic factors and independent prognostic factors, respectively. A receiver operating characteristic curve was plotted to analyze the testing power of independent prognostic factors. Twelve of 71 subjects died. Admission blood lactate levels, 6-h post-admission blood lactate levels, post-admission 6-h lactate clearance rates, blood pH, and APACHE II scores were identified as prognostic factors for AOPP according to the univariate analysis, whereas only 6-h post-admission blood lactate levels, post-admission 6-h lactate clearance rates, and blood pH were independent prognostic factors identified by multivariate logistic regression analysis. The receiver operating characteristic analysis suggested that post-admission 6-h lactate clearance rates were of moderate diagnostic value. High 6-h post-admission blood lactate levels, low blood pH, and low post-admission 6-h lactate clearance rates were independent prognostic factors identified by multivariate logistic regression analysis. Copyright © 2016 by Daedalus Enterprises.

Economic evaluations of alcohol prevention interventions: Is the evidence sufficient? A review of methodological challenges.

PubMed

Hill, Sarah R; Vale, Luke; Hunter, David; Henderson, Emily; Oluboyede, Yemi

2017-12-01

Public health interventions have unique characteristics compared to health technologies, which present additional challenges for economic evaluation (EE). High quality EEs that are able to address the particular methodological challenges are important for public health decision-makers. In England, they are even more pertinent given the transition of public health responsibilities in 2013 from the National Health Service to local government authorities where new agents are shaping policy decisions. Addressing alcohol misuse is a globally prioritised public health issue. This article provides a systematic review of EE and priority-setting studies for interventions to prevent and reduce alcohol misuse published internationally over the past decade (2006-2016). This review appraises the EE and priority-setting evidence to establish whether it is sufficient to meet the informational needs of public health decision-makers. 619 studies were identified via database searches. 7 additional studies were identified via hand searching journals, grey literature and reference lists. 27 met inclusion criteria. Methods identified included cost-utility analysis (18), cost-effectiveness analysis (6), cost-benefit analysis (CBA) (1), cost-consequence analysis (CCA) (1) and return-on-investment (1). The review identified a lack of consideration of methodological challenges associated with evaluating public health interventions and limited use of methods such as CBA and CCA which have been recommended as potentially useful for EE in public health. No studies using other specific priority-setting tools were identified. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Validation of a robust proteomic analysis carried out on formalin-fixed paraffin-embedded tissues of the pancreas obtained from mouse and human.

PubMed

Kojima, Kyoko; Bowersock, Gregory J; Kojima, Chinatsu; Klug, Christopher A; Grizzle, William E; Mobley, James A

2012-11-01

A number of reports have recently emerged with focus on extraction of proteins from formalin-fixed paraffin-embedded (FFPE) tissues for MS analysis; however, reproducibility and robustness as compared to flash frozen controls is generally overlooked. The goal of this study was to identify and validate a practical and highly robust approach for the proteomics analysis of FFPE tissues. FFPE and matched frozen pancreatic tissues obtained from mice (n = 8) were analyzed using 1D-nanoLC-MS(MS)(2) following work up with commercially available kits. The chosen approach for FFPE tissues was found to be highly comparable to that of frozen. In addition, the total number of unique peptides identified between the two groups was highly similar, with 958 identified for FFPE and 1070 identified for frozen, with protein identifications that corresponded by approximately 80%. This approach was then applied to archived human FFPE pancreatic cancer specimens (n = 11) as compared to uninvolved tissues (n = 8), where 47 potential pancreatic ductal adenocarcinoma markers were identified as significantly increased, of which 28 were previously reported. Further, these proteins share strongly overlapping pathway associations to pancreatic cancer that include estrogen receptor α. Together, these data support the validation of an approach for the proteomic analysis of FFPE tissues that is straightforward and highly robust, which can also be effectively applied toward translational studies of disease. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteomic analysis of papaya (Carica papaya L.) displaying typical sticky disease symptoms.

PubMed

Rodrigues, Silas P; Ventura, José A; Aguilar, Clemente; Nakayasu, Ernesto S; Almeida, Igor C; Fernandes, Patricia M B; Zingali, Russolina B

2011-07-01

Papaya (Carica papaya L.) hosts the only described laticifer-infecting virus (Papaya meleira virus, PMeV), which is the causal agent of papaya sticky disease. To understand the systemic effects of PMeV in papaya, we conducted a comprehensive proteomic analysis of leaf samples from healthy and diseased plants grown under field conditions. First, a reference 2-DE map was established for proteins from healthy samples. A total of 486 reproducible spots were identified, and MALDI-TOF-MS/MS data identified 275 proteins accounting for 159 distinct proteins from 231 spots that were annotated. Second, the differential expression of proteins from healthy and diseased leaves was determined through parallel experiments, using 2-DE and DIGE followed by MALDI-TOF-MS/MS and LC-IonTrap-MS/MS, respectively. Conventional 2-DE analysis revealed 75 differentially expressed proteins. Of those, 48 proteins were identified, with 26 being upregulated (U) and 22 downregulated (D). In general, metabolism-related proteins were downregulated, and stress-responsive proteins were upregulated. This expression pattern was corroborated by the results of the DIGE analysis, which identified 79 differentially expressed proteins, with 23 identified (17 U and 6 D). Calreticulin and the proteasome subunits 20S and RPT5a were shown to be upregulated during infection by both 2-DE and DIGE analyses. These data may help shed light on plant responses against stresses and viral infections. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Interrelatedness of Proactive Coping, Reactive Coping, and Learned Resourcefulness

ERIC Educational Resources Information Center

Moring, John; Fuhrman, Robert; Zauszniewski, Jaclene A.

2011-01-01

Research has identified that coping strategies used by individuals depend on temporal locations of stressors. Dispositional attributes are also identified as predictors of coping. The current study identified commonalities of proactive coping, reactive coping, and learned resourcefulness measures. The analysis yielded three factors reflective of…

Analysis of potential protein-modifying variants in 9000 endometriosis patients and 150000 controls of European ancestry.

PubMed

Sapkota, Yadav; Vivo, Immaculata De; Steinthorsdottir, Valgerdur; Fassbender, Amelie; Bowdler, Lisa; Buring, Julie E; Edwards, Todd L; Jones, Sarah; O, Dorien; Peterse, Daniëlle; Rexrode, Kathryn M; Ridker, Paul M; Schork, Andrew J; Thorleifsson, Gudmar; Wallace, Leanne M; Kraft, Peter; Morris, Andrew P; Nyholt, Dale R; Edwards, Digna R Velez; Nyegaard, Mette; D'Hooghe, Thomas; Chasman, Daniel I; Stefansson, Kari; Missmer, Stacey A; Montgomery, Grant W

2017-09-12

Genome-wide association (GWA) studies have identified 19 independent common risk loci for endometriosis. Most of the GWA variants are non-coding and the genes responsible for the association signals have not been identified. Herein, we aimed to assess the potential role of protein-modifying variants in endometriosis using exome-array genotyping in 7164 cases and 21005 controls, and a replication set of 1840 cases and 129016 controls of European ancestry. Results in the discovery sample identified significant evidence for association with coding variants in single-variant (rs1801232-CUBN) and gene-level (CIITA and PARP4) meta-analyses, but these did not survive replication. In the combined analysis, there was genome-wide significant evidence for rs13394619 (P = 2.3 × 10 -9 ) in GREB1 at 2p25.1 - a locus previously identified in a GWA meta-analysis of European and Japanese samples. Despite sufficient power, our results did not identify any protein-modifying variants (MAF > 0.01) with moderate or large effect sizes in endometriosis, although these variants may exist in non-European populations or in high-risk families. The results suggest continued discovery efforts should focus on genotyping large numbers of surgically-confirmed endometriosis cases and controls, and/or sequencing high-risk families to identify novel rare variants to provide greater insights into the molecular pathogenesis of the disease.

Implementation of quality by design principles in the development of microsponges as drug delivery carriers: Identification and optimization of critical factors using multivariate statistical analyses and design of experiments studies.

PubMed

Simonoska Crcarevska, Maja; Dimitrovska, Aneta; Sibinovska, Nadica; Mladenovska, Kristina; Slavevska Raicki, Renata; Glavas Dodov, Marija

2015-07-15

Microsponges drug delivery system (MDDC) was prepared by double emulsion-solvent-diffusion technique using rotor-stator homogenization. Quality by design (QbD) concept was implemented for the development of MDDC with potential to be incorporated into semisolid dosage form (gel). Quality target product profile (QTPP) and critical quality attributes (CQA) were defined and identified, accordingly. Critical material attributes (CMA) and Critical process parameters (CPP) were identified using quality risk management (QRM) tool, failure mode, effects and criticality analysis (FMECA). CMA and CPP were identified based on results obtained from principal component analysis (PCA-X&Y) and partial least squares (PLS) statistical analysis along with literature data, product and process knowledge and understanding. FMECA identified amount of ethylcellulose, chitosan, acetone, dichloromethane, span 80, tween 80 and water ratio in primary/multiple emulsions as CMA and rotation speed and stirrer type used for organic solvent removal as CPP. The relationship between identified CPP and particle size as CQA was described in the design space using design of experiments - one-factor response surface method. Obtained results from statistically designed experiments enabled establishment of mathematical models and equations that were used for detailed characterization of influence of identified CPP upon MDDC particle size and particle size distribution and their subsequent optimization. Copyright © 2015 Elsevier B.V. All rights reserved.

MALDI-TOF Mass Spectrometry as a Useful Tool for Identification of Enterococcus spp. from Wild Birds and Differentiation of Closely Related Species.

PubMed

Stępień-Pyśniak, Dagmara; Hauschild, Tomasz; Różański, Paweł; Marek, Agnieszka

2017-06-28

The aim of this study was to explore the accuracy and feasibility of matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) in identifying bacteria from environmental sources, as compared with rpoA gene sequencing, and to evaluate the occurrence of bacteria of the genus Enterococcus in wild birds. In addition, a phyloproteomic analysis of certain Enterococcus species with spectral relationships was performed. The enterococci were isolated from 25 species of wild birds in central Europe (Poland). Proteomic (MALDI-TOF MS) and genomic ( rpoA gene sequencing) methods were used to identify all the isolates. Using MALDI-TOF MS, all 54 (100%) isolates were identified as Enterococcus spp. Among these, 51 (94.4%) isolates were identified to the species level (log(score) > or =2.0), and three isolates (5.6%) were identified at a level of probable genus identification (log(score) 1.88-1.927). Phylogenetic analysis based on rpoA sequences confirmed that all enterococci had been correctly identified. Enterococcus faecalis was the most prevalent enterococcal species (50%) and Enterococcus faecium (33.3%) the second most frequent species, followed by Enterococcus hirae (9.3%), Enterococcus durans (3.7%), and Enterococcus casseliflavus (3.7%). The phyloproteomic analysis of the spectral profiles of the isolates showed that MALDI-TOF MS is able to differentiate among similar species of the genus Enterococcus .

GEAR: genomic enrichment analysis of regional DNA copy number changes.

PubMed

Kim, Tae-Min; Jung, Yu-Chae; Rhyu, Mun-Gan; Jung, Myeong Ho; Chung, Yeun-Jun

2008-02-01

We developed an algorithm named GEAR (genomic enrichment analysis of regional DNA copy number changes) for functional interpretation of genome-wide DNA copy number changes identified by array-based comparative genomic hybridization. GEAR selects two types of chromosomal alterations with potential biological relevance, i.e. recurrent and phenotype-specific alterations. Then it performs functional enrichment analysis using a priori selected functional gene sets to identify primary and clinical genomic signatures. The genomic signatures identified by GEAR represent functionally coordinated genomic changes, which can provide clues on the underlying molecular mechanisms related to the phenotypes of interest. GEAR can help the identification of key molecular functions that are activated or repressed in the tumor genomes leading to the improved understanding on the tumor biology. GEAR software is available with online manual in the website, http://www.systemsbiology.co.kr/GEAR/.

Contingency Space Analysis: An Alternative Method for Identifying Contingent Relations from Observational Data

PubMed Central

Martens, Brian K; DiGennaro, Florence D; Reed, Derek D; Szczech, Frances M; Rosenthal, Blair D

2008-01-01

Descriptive assessment methods have been used in applied settings to identify consequences for problem behavior, thereby aiding in the design of effective treatment programs. Consensus has not been reached, however, regarding the types of data or analytic strategies that are most useful for describing behavior–consequence relations. One promising approach involves the analysis of conditional probabilities from sequential recordings of behavior and events that follow its occurrence. In this paper we review several strategies for identifying contingent relations from conditional probabilities, and propose an alternative strategy known as a contingency space analysis (CSA). Step-by-step procedures for conducting and interpreting a CSA using sample data are presented, followed by discussion of the potential use of a CSA for conducting descriptive assessments, informing intervention design, and evaluating changes in reinforcement contingencies following treatment. PMID:18468280

Quantifiable and objective approach to organizational performance enhancement.

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

Scholand, Andrew Joseph; Tausczik, Yla R.

This report describes a new methodology, social language network analysis (SLNA), that combines tools from social language processing and network analysis to identify socially situated relationships between individuals which, though subtle, are highly influential. Specifically, SLNA aims to identify and characterize the nature of working relationships by processing artifacts generated with computer-mediated communication systems, such as instant message texts or emails. Because social language processing is able to identify psychological, social, and emotional processes that individuals are not able to fully mask, social language network analysis can clarify and highlight complex interdependencies between group members, even when these relationships aremore » latent or unrecognized. This report outlines the philosophical antecedents of SLNA, the mechanics of preprocessing, processing, and post-processing stages, and some example results obtained by applying this approach to a 15-month corporate discussion archive.« less

Identification of faulty sensor using relative partial decomposition via independent component analysis

NASA Astrophysics Data System (ADS)

Wang, Z.; Quek, S. T.

2015-07-01

Performance of any structural health monitoring algorithm relies heavily on good measurement data. Hence, it is necessary to employ robust faulty sensor detection approaches to isolate sensors with abnormal behaviour and exclude the highly inaccurate data in the subsequent analysis. The independent component analysis (ICA) is implemented to detect the presence of sensors showing abnormal behaviour. A normalized form of the relative partial decomposition contribution (rPDC) is proposed to identify the faulty sensor. Both additive and multiplicative types of faults are addressed and the detectability illustrated using a numerical and an experimental example. An empirical method to establish control limits for detecting and identifying the type of fault is also proposed. The results show the effectiveness of the ICA and rPDC method in identifying faulty sensor assuming that baseline cases are available.

Requirements Analysis and Modeling with Problem Frames and SysML: A Case Study

NASA Astrophysics Data System (ADS)

Colombo, Pietro; Khendek, Ferhat; Lavazza, Luigi

Requirements analysis based on Problem Frames is getting an increasing attention in the academic community and has the potential to become of relevant interest also for industry. However the approach lacks an adequate notational support and methodological guidelines, and case studies that demonstrate its applicability to problems of realistic complexity are still rare. These weaknesses may hinder its adoption. This paper aims at contributing towards the elimination of these weaknesses. We report on an experience in analyzing and specifying the requirements of a controller for traffic lights of an intersection using Problem Frames in combination with SysML. The analysis was performed by decomposing the problem, addressing the identified sub-problems, and recomposing them while solving the identified interferences. The experience allowed us to identify certain guidelines for decomposition and re-composition patterns.

Systems Theoretic Process Analysis Applied to an Offshore Supply Vessel Dynamic Positioning System

DTIC Science & Technology

2016-06-01

additional safety issues that were either not identified or inadequately mitigated through the use of Fault Tree Analysis and Failure Modes and...Techniques ...................................................................................................... 15 1.3.1. Fault Tree Analysis...49 3.2. Fault Tree Analysis Comparison

Assessment of stem cell differentiation based on genome-wide expression profiles.

PubMed

Godoy, Patricio; Schmidt-Heck, Wolfgang; Hellwig, Birte; Nell, Patrick; Feuerborn, David; Rahnenführer, Jörg; Kattler, Kathrin; Walter, Jörn; Blüthgen, Nils; Hengstler, Jan G

2018-07-05

In recent years, protocols have been established to differentiate stem and precursor cells into more mature cell types. However, progress in this field has been hampered by difficulties to assess the differentiation status of stem cell-derived cells in an unbiased manner. Here, we present an analysis pipeline based on published data and methods to quantify the degree of differentiation and to identify transcriptional control factors explaining differences from the intended target cells or tissues. The pipeline requires RNA-Seq or gene array data of the stem cell starting population, derived 'mature' cells and primary target cells or tissue. It consists of a principal component analysis to represent global expression changes and to identify possible problems of the dataset that require special attention, such as: batch effects; clustering techniques to identify gene groups with similar features; over-representation analysis to characterize biological motifs and transcriptional control factors of the identified gene clusters; and metagenes as well as gene regulatory networks for quantitative cell-type assessment and identification of influential transcription factors. Possibilities and limitations of the analysis pipeline are illustrated using the example of human embryonic stem cell and human induced pluripotent cells to generate 'hepatocyte-like cells'. The pipeline quantifies the degree of incomplete differentiation as well as remaining stemness and identifies unwanted features, such as colon- and fibroblast-associated gene clusters that are absent in real hepatocytes but typically induced by currently available differentiation protocols. Finally, transcription factors responsible for incomplete and unwanted differentiation are identified. The proposed method is widely applicable and allows an unbiased and quantitative assessment of stem cell-derived cells.This article is part of the theme issue 'Designer human tissue: coming to a lab near you'. © 2018 The Author(s).

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.

Lean methodology for performance improvement in the trauma discharge process.

PubMed

O'Mara, Michael Shaymus; Ramaniuk, Aliaksandr; Graymire, Vickie; Rozzell, Monica; Martin, Stacey

2014-07-01

High-volume, complex services such as trauma and acute care surgery are at risk for inefficiency. Lean process improvement can reduce health care waste. Lean allows a structured look at processes not easily amenable to analysis. We applied lean methodology to the current state of communication and discharge planning on an urban trauma service, citing areas for improvement. A lean process mapping event was held. The process map was used to identify areas for immediate analysis and intervention-defining metrics for the stakeholders. After intervention, new performance was assessed by direct data evaluation. The process was completed with an analysis of effect and plans made for addressing future focus areas. The primary area of concern identified was interservice communication. Changes centering on a standardized morning report structure reduced the number of consult questions unanswered from 67% to 34% (p = 0.0021). Physical therapy rework was reduced from 35% to 19% (p = 0.016). Patients admitted to units not designated to the trauma service had 1.6 times longer stays (p < 0.0001). The lean process lasted 8 months, and three areas for new improvement were identified: (1) the off-unit patients; (2) patients with length of stay more than 15 days contribute disproportionately to length of stay; and (3) miscommunication exists around patient education at discharge. Lean process improvement is a viable means of health care analysis. When applied to a trauma service with 4,000 admissions annually, lean identifies areas ripe for improvement. Our inefficiencies surrounded communication and patient localization. Strategies arising from the input of all stakeholders led to real solutions for communication through a face-to-face morning report and identified areas for ongoing improvement. This focuses resource use and identifies areas for improvement of throughput in care delivery.

Cloning and analysis of fetal ovary microRNAs in cattle.

PubMed

Tripurani, Swamy K; Xiao, Caide; Salem, Mohamed; Yao, Jianbo

2010-07-01

Ovarian folliculogenesis and early embryogenesis are complex processes, which require tightly regulated expression and interaction of a multitude of genes. Small endogenous RNA molecules, termed microRNAs (miRNAs), are involved in the regulation of gene expression during folliculogenesis and early embryonic development. To identify miRNAs in bovine oocytes/ovaries, a bovine fetal ovary miRNA library was constructed. Sequence analysis of random clones from the library identified 679 miRNA sequences, which represent 58 distinct bovine miRNAs. Of these distinct miRNAs, 42 are known bovine miRNAs present in the miRBase database and the remaining 16 miRNAs include 15 new bovine miRNAs that are homologous to miRNAs identified in other species, and one novel miRNA, which does not match any miRNAs in the database. The precursor sequences for 14 of the new 15 miRNAs as well as the novel miRNA were identified from the bovine genome database and their hairpin structures were predicted. Expression analysis of the 58 miRNAs in fetal ovaries in comparison to somatic tissue pools identified 8 miRNAs predominantly expressed in fetal ovaries. Further analysis of the eight miRNAs in germinal vesicle (GV) stage oocytes identified two miRNAs (bta-mir424 and bta-mir-10b), that are highly abundant in GV oocytes. Both miRNAs show similar expression patterns during oocyte maturation and preimplantation development of bovine embryos, being abundant in GV and MII stage oocytes, as well as in early stage embryos (until 16-cell stage). The amount of the novel miRNA is relatively small in oocytes and early cleavage embryos but greater in blastocysts, suggesting a role of this miRNA in blastocyst cell differentiation. Copyright 2010 Elsevier B.V. All rights reserved.

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

In silico pathway analysis in cervical carcinoma reveals potential new targets for treatment

PubMed Central

van Dam, Peter A.; van Dam, Pieter-Jan H. H.; Rolfo, Christian; Giallombardo, Marco; van Berckelaer, Christophe; Trinh, Xuan Bich; Altintas, Sevilay; Huizing, Manon; Papadimitriou, Kostas; Tjalma, Wiebren A. A.; van Laere, Steven

2016-01-01

An in silico pathway analysis was performed in order to improve current knowledge on the molecular drivers of cervical cancer and detect potential targets for treatment. Three publicly available Affymetrix gene expression data-sets (GSE5787, GSE7803, GSE9750) were retrieved, vouching for a total of 9 cervical cancer cell lines (CCCLs), 39 normal cervical samples, 7 CIN3 samples and 111 cervical cancer samples (CCSs). Predication analysis of microarrays was performed in the Affymetrix sets to identify cervical cancer biomarkers. To select cancer cell-specific genes the CCSs were compared to the CCCLs. Validated genes were submitted to a gene set enrichment analysis (GSEA) and Expression2Kinases (E2K). In the CCSs a total of 1,547 probe sets were identified that were overexpressed (FDR < 0.1). Comparing to CCCLs 560 probe sets (481 unique genes) had a cancer cell-specific expression profile, and 315 of these genes (65%) were validated. GSEA identified 5 cancer hallmarks enriched in CCSs (P < 0.01 and FDR < 0.25) showing that deregulation of the cell cycle is a major component of cervical cancer biology. E2K identified a protein-protein interaction (PPI) network of 162 nodes (including 20 drugable kinases) and 1626 edges. This PPI-network consists of 5 signaling modules associated with MYC signaling (Module 1), cell cycle deregulation (Module 2), TGFβ-signaling (Module 3), MAPK signaling (Module 4) and chromatin modeling (Module 5). Potential targets for treatment which could be identified were CDK1, CDK2, ABL1, ATM, AKT1, MAPK1, MAPK3 among others. The present study identified important driver pathways in cervical carcinogenesis which should be assessed for their potential therapeutic drugability. PMID:26701206

Identification of MicroRNAs in Helicoverpa armigera and Spodoptera litura Based on Deep Sequencing and Homology Analysis

PubMed Central

Ge, Xie; Zhang, Yong; Jiang, Jianhao; Zhong, Yi; Yang, Xiaonan; Li, Zhiqian; Huang, Yongping; Tan, Anjiang

2013-01-01

The current identification of microRNAs (miRNAs) in insects is largely dependent on genome sequences. However, the lack of available genome sequences inhibits the identification of miRNAs in various insect species. In this study, we used a miRNA database of the silkworm Bombyx mori as a reference to identify miRNAs in Helicoverpa armigera and Spodoptera litura using deep sequencing and homology analysis. Because all three species belong to the Lepidoptera, the experiment produced reliable results. Our study identified 97 and 91 conserved miRNAs in H. armigera and S. litura, respectively. Using the genome of B. mori and BAC sequences of H. armigera as references, 1 novel miRNA and 8 novel miRNA candidates were identified in H. armigera, and 4 novel miRNA candidates were identified in S. litura. An evolutionary analysis revealed that most of the identified miRNAs were insect-specific, and more than 20 miRNAs were Lepidoptera-specific. The investigation of the expression patterns of miR-2a, miR-34, miR-2796-3p and miR-11 revealed their potential roles in insect development. miRNA target prediction revealed that conserved miRNA target sites exist in various genes in the 3 species. Conserved miRNA target sites for the Hsp90 gene among the 3 species were validated in the mammalian 293T cell line using a dual-luciferase reporter assay. Our study provides a new approach with which to identify miRNAs in insects lacking genome information and contributes to the functional analysis of insect miRNAs. PMID:23289012

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

Identification of common immunodominant antigens of Eimeria tenella, Eimeria acervulina and Eimeria maxima by immunoproteomic analysis

PubMed Central

Liu, Jianhua; Li, Wenyu; Ji, Yihong; Tian, Di; Tian, Lu; Yang, Xinchao; Xu, Lixin; Yan, Ruofeng; Li, Xiangrui; Song, Xiaokai

2017-01-01

Clinical chicken coccidiosis is mostly caused by simultaneous infection of several Eimeria species, and host immunity against Eimeria is species-specific. It is urgent to identify common immunodominant antigen of Eimeria for developing multivalent anticoccidial vaccines. In this study, sporozoite proteins of Eimeria tenella, Eimeria acervulina and Eimeria maxima were analyzed by two-dimensional electrophoresis (2DE). Western bot analysis was performed on the yielded 2DE gel using antisera of E. tenella E. acervulina and E. maxima respectively. Next, the detected immunodominant spots were identified by comparing the data from MALDI-TOF-MS/MS with available databases. Finally, Eimeria common antigens were identified by comparing amino acid sequence between the three Eimeria species. The results showed that analysis by 2DE of sporozoite proteins detected 629, 626 and 632 protein spots from E. tenella, E. acervulina and E. maxima respectively. Western bot analysis revealed 50 (E. tenella), 64 (E. acervulina) and 57 (E. maxima) immunodominant spots from the sporozoite 2DE gels of the three Eimeria species. The immunodominant spots were identified as 33, 27 and 25 immunodominant antigens of E. tenella, E. acervulina and E. maxima respectively. Fifty-four immunodominant proteins were identified as 18 ortholog proteins among the three Eimeria species. Finally, 5 of the 18 ortholog proteins were identified as common immunodominant antigens including elongation factor 2 (EF-2), 14-3-3 protein, ubiquitin-conjugating enzyme domain-containing protein (UCE) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH). In conclusion, our results not only provide Eimeria sporozoite immunodominant antigen map and additional immunodominant antigens, but also common immunodominant antigens for developing multivalent anticoccidial vaccines. PMID:28432276

Identification of common immunodominant antigens of Eimeria tenella, Eimeria acervulina and Eimeria maxima by immunoproteomic analysis.

PubMed

Liu, Lianrui; Huang, Xinmei; Liu, Jianhua; Li, Wenyu; Ji, Yihong; Tian, Di; Tian, Lu; Yang, Xinchao; Xu, Lixin; Yan, Ruofeng; Li, Xiangrui; Song, Xiaokai

2017-05-23

Clinical chicken coccidiosis is mostly caused by simultaneous infection of several Eimeria species, and host immunity against Eimeria is species-specific. It is urgent to identify common immunodominant antigen of Eimeria for developing multivalent anticoccidial vaccines. In this study, sporozoite proteins of Eimeria tenella, Eimeria acervulina and Eimeria maxima were analyzed by two-dimensional electrophoresis (2DE). Western bot analysis was performed on the yielded 2DE gel using antisera of E. tenella E. acervulina and E. maxima respectively. Next, the detected immunodominant spots were identified by comparing the data from MALDI-TOF-MS/MS with available databases. Finally, Eimeria common antigens were identified by comparing amino acid sequence between the three Eimeria species. The results showed that analysis by 2DE of sporozoite proteins detected 629, 626 and 632 protein spots from E. tenella, E. acervulina and E. maxima respectively. Western bot analysis revealed 50 (E. tenella), 64 (E. acervulina) and 57 (E. maxima) immunodominant spots from the sporozoite 2DE gels of the three Eimeria species. The immunodominant spots were identified as 33, 27 and 25 immunodominant antigens of E. tenella, E. acervulina and E. maxima respectively. Fifty-four immunodominant proteins were identified as 18 ortholog proteins among the three Eimeria species. Finally, 5 of the 18 ortholog proteins were identified as common immunodominant antigens including elongation factor 2 (EF-2), 14-3-3 protein, ubiquitin-conjugating enzyme domain-containing protein (UCE) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH). In conclusion, our results not only provide Eimeria sporozoite immunodominant antigen map and additional immunodominant antigens, but also common immunodominant antigens for developing multivalent anticoccidial vaccines.

An Exploratory Study on Using Principal-Component Analysis and Confirmatory Factor Analysis to Identify Bolt-On Dimensions: The EQ-5D Case Study.

PubMed

Finch, Aureliano Paolo; Brazier, John Edward; Mukuria, Clara; Bjorner, Jakob Bue

2017-12-01

Generic preference-based measures such as the EuroQol five-dimensional questionnaire (EQ-5D) are used in economic evaluation, but may not be appropriate for all conditions. When this happens, a possible solution is adding bolt-ons to expand their descriptive systems. Using review-based methods, studies published to date claimed the relevance of bolt-ons in the presence of poor psychometric results. This approach does not identify the specific dimensions missing from the Generic preference-based measure core descriptive system, and is inappropriate for identifying dimensions that might improve the measure generically. This study explores the use of principal-component analysis (PCA) and confirmatory factor analysis (CFA) for bolt-on identification in the EQ-5D. Data were drawn from the international Multi-Instrument Comparison study, which is an online survey on health and well-being measures in five countries. Analysis was based on a pool of 92 items from nine instruments. Initial content analysis provided a theoretical framework for PCA results interpretation and CFA model development. PCA was used to investigate the underlining dimensional structure and whether EQ-5D items were represented in the identified constructs. CFA was used to confirm the structure. CFA was cross-validated in random halves of the sample. PCA suggested a nine-component solution, which was confirmed by CFA. This included psychological symptoms, physical functioning, and pain, which were covered by the EQ-5D, and satisfaction, speech/cognition,relationships, hearing, vision, and energy/sleep which were not. These latter factors may represent relevant candidate bolt-ons. PCA and CFA appear useful methods for identifying potential bolt-ons dimensions for an instrument such as the EQ-5D. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

RADC SCAT automated sneak circuit analysis tool

NASA Astrophysics Data System (ADS)

Depalma, Edward L.

The sneak circuit analysis tool (SCAT) provides a PC-based system for real-time identification (during the design phase) of sneak paths and design concerns. The tool utilizes an expert system shell to assist the analyst so that prior experience with sneak analysis is not necessary for performance. Both sneak circuits and design concerns are targeted by this tool, with both digital and analog circuits being examined. SCAT focuses the analysis at the assembly level, rather than the entire system, so that most sneak problems can be identified and corrected by the responsible design engineer in a timely manner. The SCAT program identifies the sneak circuits to the designer, who then decides what course of action is necessary.

Multicollinearity in Regression Analyses Conducted in Epidemiologic Studies

PubMed Central

Vatcheva, Kristina P.; Lee, MinJae; McCormick, Joseph B.; Rahbar, Mohammad H.

2016-01-01

The adverse impact of ignoring multicollinearity on findings and data interpretation in regression analysis is very well documented in the statistical literature. The failure to identify and report multicollinearity could result in misleading interpretations of the results. A review of epidemiological literature in PubMed from January 2004 to December 2013, illustrated the need for a greater attention to identifying and minimizing the effect of multicollinearity in analysis of data from epidemiologic studies. We used simulated datasets and real life data from the Cameron County Hispanic Cohort to demonstrate the adverse effects of multicollinearity in the regression analysis and encourage researchers to consider the diagnostic for multicollinearity as one of the steps in regression analysis. PMID:27274911

Multicollinearity in Regression Analyses Conducted in Epidemiologic Studies.

PubMed

Vatcheva, Kristina P; Lee, MinJae; McCormick, Joseph B; Rahbar, Mohammad H

2016-04-01

The adverse impact of ignoring multicollinearity on findings and data interpretation in regression analysis is very well documented in the statistical literature. The failure to identify and report multicollinearity could result in misleading interpretations of the results. A review of epidemiological literature in PubMed from January 2004 to December 2013, illustrated the need for a greater attention to identifying and minimizing the effect of multicollinearity in analysis of data from epidemiologic studies. We used simulated datasets and real life data from the Cameron County Hispanic Cohort to demonstrate the adverse effects of multicollinearity in the regression analysis and encourage researchers to consider the diagnostic for multicollinearity as one of the steps in regression analysis.

Genome-wide Annotation, Identification, and Global Transcriptomic Analysis of Regulatory or Small RNA Gene Expression in Staphylococcus aureus.

PubMed

Carroll, Ronan K; Weiss, Andy; Broach, William H; Wiemels, Richard E; Mogen, Austin B; Rice, Kelly C; Shaw, Lindsey N

2016-02-09

In Staphylococcus aureus, hundreds of small regulatory or small RNAs (sRNAs) have been identified, yet this class of molecule remains poorly understood and severely understudied. sRNA genes are typically absent from genome annotation files, and as a consequence, their existence is often overlooked, particularly in global transcriptomic studies. To facilitate improved detection and analysis of sRNAs in S. aureus, we generated updated GenBank files for three commonly used S. aureus strains (MRSA252, NCTC 8325, and USA300), in which we added annotations for >260 previously identified sRNAs. These files, the first to include genome-wide annotation of sRNAs in S. aureus, were then used as a foundation to identify novel sRNAs in the community-associated methicillin-resistant strain USA300. This analysis led to the discovery of 39 previously unidentified sRNAs. Investigating the genomic loci of the newly identified sRNAs revealed a surprising degree of inconsistency in genome annotation in S. aureus, which may be hindering the analysis and functional exploration of these elements. Finally, using our newly created annotation files as a reference, we perform a global analysis of sRNA gene expression in S. aureus and demonstrate that the newly identified tsr25 is the most highly upregulated sRNA in human serum. This study provides an invaluable resource to the S. aureus research community in the form of our newly generated annotation files, while at the same time presenting the first examination of differential sRNA expression in pathophysiologically relevant conditions. Despite a large number of studies identifying regulatory or small RNA (sRNA) genes in Staphylococcus aureus, their annotation is notably lacking in available genome files. In addition to this, there has been a considerable lack of cross-referencing in the wealth of studies identifying these elements, often leading to the same sRNA being identified multiple times and bearing multiple names. In this work, we have consolidated and curated known sRNA genes from the literature and mapped them to their position on the S. aureus genome, creating new genome annotation files. These files can now be used by the scientific community at large in experiments to search for previously undiscovered sRNA genes and to monitor sRNA gene expression by transcriptome sequencing (RNA-seq). We demonstrate this application, identifying 39 new sRNAs and studying their expression during S. aureus growth in human serum. Copyright © 2016 Carroll et al.

Tailored interventions to overcome identified barriers to change: effects on professional practice and health care outcomes

PubMed Central

Baker, Richard; Camosso-Stefinovic, Janette; Gillies, Clare; Shaw, Elizabeth J; Cheater, Francine; Flottorp, Signe; Robertson, Noelle

2014-01-01

Background In the previous version of this review, the effectiveness of interventions tailored to barriers to change was found to be uncertain. Objectives To assess the effectiveness of interventions tailored to address identified barriers to change on professional practice or patient outcomes. Search methods For this update, in addition to the EPOC Register and pending files, we searched the following databases without language restrictions, from inception until August 2007: MEDLINE, EMBASE, CINAHL, BNI and HMIC. We searched the National Research Register to November 2007. We undertook further searches to October 2009 to identify potentially eligible published or ongoing trials. Selection criteria Randomised controlled trials (RCTs) of interventions tailored to address prospectively identified barriers to change that reported objectively measured professional practice or healthcare outcomes in which at least one group received an intervention designed to address prospectively identified barriers to change. Data collection and analysis Two reviewers independently assessed quality and extracted data. We undertook quantitative and qualitative analyses. The quantitative analyses had two elements. We carried out a meta-regression to compare interventions tailored to address identified barriers to change with either no interventions or an intervention(s) not tailored to the barriers.We carried out heterogeneity analyses to investigate sources of differences in the effectiveness of interventions. These included the effects of: risk of bias, concealment of allocation, rigour of barrier analysis, use of theory, complexity of interventions, and the reported presence of administrative constraints. Main results We included 26 studies comparing an intervention tailored to address identified barriers to change to no intervention or an intervention(s) not tailored to the barriers. The effect sizes of these studies varied both across and within studies. Twelve studies provided enough data to be included in the quantitative analysis. A meta-regression model was fitted adjusting for baseline odds by fitting it as a covariate, to obtain the pooled odds ratio of 1.54 (95% CI, 1.16 to 2.01) from Bayesian analysis and 1.52 (95% CI, 1.27 to 1.82, P < 0.001) from classical analysis. The heterogeneity analyses found that no study attributes investigated were significantly associated with effectiveness of the interventions. Authors’ conclusions Interventions tailored to prospectively identified barriers are more likely to improve professional practice than no intervention or dissemination of guidelines. However, the methods used to identify barriers and tailor interventions to address them need further development. Research is required to determine the effectiveness of tailored interventions in comparison with other interventions. PMID:20238340

Use of eQTL Analysis for the Discovery of Target Genes Identified by GWAS

DTIC Science & Technology

2013-04-01

the biologic pathways affected by these inherited factors, and ultimately to identify targets for disease prediction, risk stratification and...quality using an Agilent chip technology. Cases having a RIN number of 7.0 or greater were considered good quality. Once completed, the optimum set of...AD_________________ Award Number: W81XWH-11-1-0261 TITLE: Use of eQTL Analysis for the Discovery of

Mathematical analysis techniques for modeling the space network activities

NASA Technical Reports Server (NTRS)

Foster, Lisa M.

1992-01-01

The objective of the present work was to explore and identify mathematical analysis techniques, and in particular, the use of linear programming. This topic was then applied to the Tracking and Data Relay Satellite System (TDRSS) in order to understand the space network better. Finally, a small scale version of the system was modeled, variables were identified, data was gathered, and comparisons were made between actual and theoretical data.

Cardiothoracic ratio for prediction of left ventricular dilation: a systematic review and pooled analysis.

PubMed

Loomba, Rohit S; Shah, Parinda H; Nijhawan, Karan; Aggarwal, Saurabh; Arora, Rohit

2015-03-01

Increased cardiothoracic ratio noted on chest radiographs often prompts concern and further evaluation with additional imaging. This study pools available data assessing the utility of cardiothoracic ratio in predicting left ventricular dilation. A systematic review of the literature was conducted to identify studies comparing cardiothoracic ratio by chest x-ray to left ventricular dilation by echocardiography. Electronic databases were used to identify studies which were then assessed for quality and bias, with those with adequate quality and minimal bias ultimately being included in the pooled analysis. The pooled data were used to determine the sensitivity, specificity, positive predictive value and negative predictive value of cardiomegaly in predicting left ventricular dilation. A total of six studies consisting of 466 patients were included in this analysis. Cardiothoracic ratio had 83.3% sensitivity, 45.4% specificity, 43.5% positive predictive value and 82.7% negative predictive value. When a secondary analysis was conducted with a pediatric study excluded, a total of five studies consisting of 371 patients were included. Cardiothoracic ratio had 86.2% sensitivity, 25.2% specificity, 42.5% positive predictive value and 74.0% negative predictive value. Cardiothoracic ratio as determined by chest radiograph is sensitive but not specific for identifying left ventricular dilation. Cardiothoracic ratio also has a strong negative predictive value for identifying left ventricular dilation.

Combined Bisulfite Restriction Analysis for brain tissue identification.

PubMed

Samsuwan, Jarunya; Muangsub, Tachapol; Yanatatsaneejit, Pattamawadee; Mutirangura, Apiwat; Kitkumthorn, Nakarin

2018-05-01

According to the tissue-specific methylation database (doi: 10.1016/j.gene.2014.09.060), methylation at CpG locus cg03096975 in EML2 has been preliminarily proven to be specific to brain tissue. In this study, we enlarged sample size and developed a technique for identifying brain tissue in aged samples. Combined Bisulfite Restriction Analysis-for EML2 (COBRA-EML2) technique was established and validated in various organ samples obtained from 108 autopsies. In addition, this technique was also tested for its reliability, minimal DNA concentration detected, and use in aged samples and in samples obtained from specific brain compartments and spinal cord. COBRA-EML2 displayed 100% sensitivity and specificity for distinguishing brain tissue from other tissues, showed high reliability, was capable of detecting minimal DNA concentration (0.015ng/μl), could be used for identifying brain tissue in aged samples. In summary, COBRA-EML2 is a technique to identify brain tissue. This analysis is useful in criminal cases since it can identify the vital organ tissues from small samples acquired from criminal scenes. The results from this analysis can be counted as a medical and forensic marker supporting criminal investigations, and as one of the evidences in court rulings. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

Trans-Ethnic Meta-Analysis Identifies Common and Rare Variants Associated with Hepatocyte Growth Factor Levels in the Multi-Ethnic Study of Atherosclerosis (MESA)

PubMed Central

Larson, Nicholas B.; Berardi, Cecilia; Decker, Paul A.; Wassel, Christina L.; Kirsch, Phillip S.; Pankow, James S.; Sale, Michele M.; de Andrade, Mariza; Sicotte, Hugues; Tang, Weihong; Hanson, Naomi Q.; Tsai, Michael Y.; Taylor, Kent D.; Bielinski, Suzette J.

2015-01-01

Summary Hepatocyte growth factor (HGF) is a mesenchyme-derived pleiotropic factor that regulates cell growth, motility, mitogenesis, and morphogenesis in a variety of cells, and increased serum levels of HGF have been linked to a number of clinical and subclinical cardiovascular disease phenotypes. However, little is currently known regarding what genetic factors influence HGF levels, despite evidence of substantial genetic contributions to HGF variation. Based upon ethnicity-stratified single-variant association analysis and trans-ethnic meta-analysis of 6201 participants of the Multi-Ethnic Study of Atherosclerosis (MESA), we discovered five statistically significant common and low-frequency variants: HGF missense polymorphism rs5745687 (p.E299K) as well as four variants (rs16844364, rs4690098, rs114303452, rs3748034) within or in proximity to HGFAC. We also identified two significant ethnicity-specific gene-level associations (A1BG in African Americans; FASN in Chinese Americans) based upon low-frequency/rare variants, while meta-analysis of gene-level results identified a significant association for HGFAC. However, identified single-variant associations explained modest proportions of the total trait variation and were not significantly associated with coronary artery calcium or coronary heart disease. Our findings indicate genetic factors influencing circulating HGF levels may be complex and ethnically diverse. PMID:25998175

Identification of microRNA-like RNAs from Curvularia lunata associated with maize leaf spot by bioinformation analysis and deep sequencing.

PubMed

Liu, Tong; Hu, John; Zuo, Yuhu; Jin, Yazhong; Hou, Jumei

2016-04-01

Deep sequencing of small RNAs is a useful tool to identify novel small RNAs that may be involved in fungal growth and pathogenesis. In this study, we used HiSeq deep sequencing to identify 747,487 unique small RNAs from Curvularia lunata. Among these small RNAs were 1012 microRNA-like RNAs (milRNAs), which are similar to other known microRNAs, and 48 potential novel milRNAs without homologs in other organisms have been identified using the miRBase© database. We used quantitative PCR to analyze the expression of four of these milRNAs from C. lunata at different developmental stages. The analysis revealed several changes associated with germinating conidia and mycelial growth, suggesting that these milRNAs may play a role in pathogen infection and mycelial growth. A total of 8334 target mRNAs for the 1012 milRNAs that were identified, and 256 target mRNAs for the 48 novel milRNAs were predicted by computational analysis. These target mRNAs of milRNAs were also performed by gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis. To our knowledge, this study is the first report of C. lunata's milRNA profiles. This information will provide a better understanding of pathogen development and infection mechanism.

Ellagitannin composition of blackberry as determined by HPLC-ESI-MS and MALDI-TOF-MS.

PubMed

Hager, Tiffany J; Howard, Luke R; Liyanage, Rohana; Lay, Jackson O; Prior, Ronald L

2008-02-13

Blackberries ( Rubus sp.) were evaluated by high-performance liquid chromatography-electrospray ionization-mass spectrometry (HPLC-ESI-MS) and matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF-MS) to identify the ellagitannins present in flesh, torus (receptacle tissue), and seeds. Most ellagitannins were present (or detectable) only in seed tissues. Ellagitannins identified by HPLC-ESI-MS in the seeds included pedunculagin, casuarictin/potentillin, castalagin/vescalagin, lambertianin A/sanguiin H-6, lambertianin C, and lambertianin D. For several of the ellagitannins, isomeric separation was also obtained. The MALDI-TOF-MS analysis was primarily utilized to evaluate and identify high molecular mass (>1000 Da) ellagitannins. The MALDI analysis verified the presence of the ellagitannins identified by HPLC-ESI-MS including lambertianin A/sanguiin H-6, lambertianin C, and lambertianin D, but the analysis also indicated the presence of several other compounds that were most likely ellagitannins based on the patterns observed in the masses (i.e., loss or addition of a gallic acid moiety to a known ellagitannin). This study determined the presence of several possible isomeric forms of ellagitannins previously unidentified in fruit and presents a possible analytical HPLC method for the analysis of the major ellagitannins present in the fruit.

Cerebrospinal fluid metabolomic profiling in tuberculous and viral meningitis: Screening potential markers for differential diagnosis.

PubMed

Li, Zihui; Du, Boping; Li, Jing; Zhang, Jinli; Zheng, Xiaojing; Jia, Hongyan; Xing, Aiying; Sun, Qi; Liu, Fei; Zhang, Zongde

2017-03-01

Tuberculous meningitis (TBM) is the most severe and frequent form of central nervous system tuberculosis. The current lack of efficient diagnostic tests makes it difficult to differentiate TBM from other common types of meningitis, especially viral meningitis (VM). Metabolomics is an important tool to identify disease-specific biomarkers. However, little metabolomic information is available on adult TBM. We used 1 H nuclear magnetic resonance-based metabolomics to investigate the metabolic features of the CSF from 18 TBM and 20 VM patients. Principal component analysis and orthogonal signal correction-partial least squares-discriminant analysis (OSC-PLS-DA) were applied to analyze profiling data. Metabolites were identified using the Human Metabolome Database and pathway analysis was performed with MetaboAnalyst 3.0. The OSC-PLS-DA model could distinguish TBM from VM with high reliability. A total of 25 key metabolites that contributed to their discrimination were identified, including some, such as betaine and cyclohexane, rarely reported before in TBM. Pathway analysis indicated that amino acid and energy metabolism was significantly different in the CSF of TBM compared with VM. Twenty-five key metabolites identified in our study may be potential biomarkers for TBM differential diagnosis and are worthy of further investigation. Copyright © 2017 Elsevier B.V. All rights reserved.

Clinical and Epidemiological Characteristics of Suicides Committed in Medellin, Colombia.

PubMed

Ortega, Paula Andrea; Manrique, Ruben Darío; Tovilla Zarate, Carlos Alfonso; López Jaramillo, Carlos; Cuartas, Jorge Mauricio

2014-01-01

The purpose of this study was to identify the characteristics of individuals who committed suicide in Medellín between 2008 and 2010, and to identify variables related to the type of events. A retrospective and descriptive analysis was conducted on data provided by the National Institute of Legal Medicine and Forensic Sciences. In addition, a univariate and bivariate analysis was used to identify the sociodemographic and medical-legal characteristics of the deceased. Multiple correspondence analysis was also used in order to establish typologies. The information was analyzed using STATA 11.0. Of the 389 cases occurring between 2008 and 2010, 84.6% (n=329) were men. The male to female ratio was 5:1; 64% of the cases occurred in people aged 18-45 years; 6.7% occurred in children under 18, with hanging being the method most chosen by the victims (48.3%). Exploratory analysis was used to identify a possible association between the use of violent methods and events occurring in the housing and social strata 1, 2 and 3. Some factors could be associated with suicide, providing data that could consolidate health intervention strategies in our population. Copyright © 2013 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.

Genome-Wide DNA Methylation Analysis and Epigenetic Variations Associated with Congenital Aortic Valve Stenosis (AVS).

PubMed

Radhakrishna, Uppala; Albayrak, Samet; Alpay-Savasan, Zeynep; Zeb, Amna; Turkoglu, Onur; Sobolewski, Paul; Bahado-Singh, Ray O

2016-01-01

Congenital heart defect (CHD) is the most common cause of death from congenital anomaly. Among several candidate epigenetic mechanisms, DNA methylation may play an important role in the etiology of CHDs. We conducted a genome-wide DNA methylation analysis using an Illumina Infinium 450k human methylation assay in a cohort of 24 newborns who had aortic valve stenosis (AVS), with gestational-age matched controls. The study identified significantly-altered CpG methylation at 59 sites in 52 genes in AVS subjects as compared to controls (either hypermethylated or demethylated). Gene Ontology analysis identified biological processes and functions for these genes including positive regulation of receptor-mediated endocytosis. Consistent with prior clinical data, the molecular function categories as determined using DAVID identified low-density lipoprotein receptor binding, lipoprotein receptor binding and identical protein binding to be over-represented in the AVS group. A significant epigenetic change in the APOA5 and PCSK9 genes known to be involved in AVS was also observed. A large number CpG methylation sites individually demonstrated good to excellent diagnostic accuracy for the prediction of AVS status, thus raising possibility of molecular screening markers for this disorder. Using epigenetic analysis we were able to identify genes significantly involved in the pathogenesis of AVS.

Genome-Wide DNA Methylation Analysis and Epigenetic Variations Associated with Congenital Aortic Valve Stenosis (AVS)

PubMed Central

Radhakrishna, Uppala; Albayrak, Samet; Alpay-Savasan, Zeynep; Zeb, Amna; Turkoglu, Onur; Sobolewski, Paul; Bahado-Singh, Ray O.

2016-01-01

Congenital heart defect (CHD) is the most common cause of death from congenital anomaly. Among several candidate epigenetic mechanisms, DNA methylation may play an important role in the etiology of CHDs. We conducted a genome-wide DNA methylation analysis using an Illumina Infinium 450k human methylation assay in a cohort of 24 newborns who had aortic valve stenosis (AVS), with gestational-age matched controls. The study identified significantly-altered CpG methylation at 59 sites in 52 genes in AVS subjects as compared to controls (either hypermethylated or demethylated). Gene Ontology analysis identified biological processes and functions for these genes including positive regulation of receptor-mediated endocytosis. Consistent with prior clinical data, the molecular function categories as determined using DAVID identified low-density lipoprotein receptor binding, lipoprotein receptor binding and identical protein binding to be over-represented in the AVS group. A significant epigenetic change in the APOA5 and PCSK9 genes known to be involved in AVS was also observed. A large number CpG methylation sites individually demonstrated good to excellent diagnostic accuracy for the prediction of AVS status, thus raising possibility of molecular screening markers for this disorder. Using epigenetic analysis we were able to identify genes significantly involved in the pathogenesis of AVS. PMID:27152866

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.

Stingray Failure Mode, Effects and Criticality Analysis: WEC Risk Registers

DOE Data Explorer

Ken Rhinefrank

2016-07-25

Analysis method to systematically identify all potential failure modes and their effects on the Stingray WEC system. This analysis is incorporated early in the development cycle such that the mitigation of the identified failure modes can be achieved cost effectively and efficiently. The FMECA can begin once there is enough detail to functions and failure modes of a given system, and its interfaces with other systems. The FMECA occurs coincidently with the design process and is an iterative process which allows for design changes to overcome deficiencies in the analysis.Risk Registers for major subsystems completed according to the methodology described in "Failure Mode Effects and Criticality Analysis Risk Reduction Program Plan.pdf" document below, in compliance with the DOE Risk Management Framework developed by NREL.

Method of analysis of asbestiform minerals by thermoluminescence

DOEpatents

Fisher, Gerald L.; Bradley, Edward W.

1980-01-01

A method for the qualitative and quantitative analysis of asbestiform minerals, including the steps of subjecting a sample to be analyzed to the thermoluminescent analysis, annealing the sample, subjecting the sample to ionizing radiation, and subjecting the sample to a second thermoluminescent analysis. Glow curves are derived from the two thermoluminescent analyses and their shapes then compared to established glow curves of known asbestiform minerals to identify the type of asbestiform in the sample. Also, during at least one of the analyses, the thermoluminescent response for each sample is integrated during a linear heating period of the analysis in order to derive the total thermoluminescence per milligram of sample. This total is a measure of the quantity of asbestiform in the sample and may also be used to identify the source of the sample.

Chemical hazards database and detection system for Microgravity and Materials Processing Facility (MMPF)

NASA Technical Reports Server (NTRS)

Steele, Jimmy; Smith, Robert E.

1991-01-01

The ability to identify contaminants associated with experiments and facilities is directly related to the safety of the Space Station. A means of identifying these contaminants has been developed through this contracting effort. The delivered system provides a listing of the materials and/or chemicals associated with each facility, information as to the contaminant's physical state, a list of the quantity and/or volume of each suspected contaminant, a database of the toxicological hazards associated with each contaminant, a recommended means of rapid identification of the contaminants under operational conditions, a method of identifying possible failure modes and effects analysis associated with each facility, and a fault tree-type analysis that will provide a means of identifying potential hazardous conditions related to future planned missions.

Identification of estrogen-responsive genes using a genome-wide analysis of promoter elements for transcription factor binding sites.

PubMed

Kamalakaran, Sitharthan; Radhakrishnan, Senthil K; Beck, William T

2005-06-03

We developed a pipeline to identify novel genes regulated by the steroid hormone-dependent transcription factor, estrogen receptor, through a systematic analysis of upstream regions of all human and mouse genes. We built a data base of putative promoter regions for 23,077 human and 19,984 mouse transcripts from National Center for Biotechnology Information annotation and 8793 human and 6785 mouse promoters from the Data Base of Transcriptional Start Sites. We used this data base of putative promoters to identify potential targets of estrogen receptor by identifying estrogen response elements (EREs) in their promoters. Our program correctly identified EREs in genes known to be regulated by estrogen in addition to several new genes whose putative promoters contained EREs. We validated six genes (KIAA1243, NRIP1, MADH9, NME3, TPD52L, and ABCG2) to be estrogen-responsive in MCF7 cells using reverse transcription PCR. To allow for extensibility of our program in identifying targets of other transcription factors, we have built a Web interface to access our data base and programs. Our Web-based program for Promoter Analysis of Genome, PAGen@UIC, allows a user to identify putative target genes for vertebrate transcription factors through the analysis of their upstream sequences. The interface allows the user to search the human and mouse promoter data bases for potential target genes containing one or more listed transcription factor binding sites (TFBSs) in their upstream elements, using either regular expression-based consensus or position weight matrices. The data base can also be searched for promoters harboring user-defined TFBSs given as a consensus or a position weight matrix. Furthermore, the user can retrieve putative promoter sequences for any given gene together with identified TFBSs located on its promoter. Orthologous promoters are also analyzed to determine conserved elements.

WE-G-BRA-07: Analyzing the Safety Implications of a Brachytherapy Process Improvement Project Utilizing a Novel System-Theory-Based Hazard-Analysis Technique

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

Tang, A; Samost, A; Viswanathan, A

Purpose: To investigate the hazards in cervical-cancer HDR brachytherapy using a novel hazard-analysis technique, System Theoretic Process Analysis (STPA). The applicability and benefit of STPA to the field of radiation oncology is demonstrated. Methods: We analyzed the tandem and ring HDR procedure through observations, discussions with physicists and physicians, and the use of a previously developed process map. Controllers and their respective control actions were identified and arranged into a hierarchical control model of the system, modeling the workflow from applicator insertion through initiating treatment delivery. We then used the STPA process to identify potentially unsafe control actions. Scenarios weremore » then generated from the identified unsafe control actions and used to develop recommendations for system safety constraints. Results: 10 controllers were identified and included in the final model. From these controllers 32 potentially unsafe control actions were identified, leading to more than 120 potential accident scenarios, including both clinical errors (e.g., using outdated imaging studies for planning), and managerial-based incidents (e.g., unsafe equipment, budget, or staffing decisions). Constraints identified from those scenarios include common themes, such as the need for appropriate feedback to give the controllers an adequate mental model to maintain safe boundaries of operations. As an example, one finding was that the likelihood of the potential accident scenario of the applicator breaking during insertion might be reduced by establishing a feedback loop of equipment-usage metrics and equipment-failure reports to the management controller. Conclusion: The utility of STPA in analyzing system hazards in a clinical brachytherapy system was demonstrated. This technique, rooted in system theory, identified scenarios both technical/clinical and managerial in nature. These results suggest that STPA can be successfully used to analyze safety in brachytherapy and may prove to be an alternative to other hazard analysis techniques.« less

Love as a Battlefield: Attachment and Relationship Dynamics in Couples Identified for Male Partner Violence

ERIC Educational Resources Information Center

Allison, Colleen J.; Bartholomew, Kim; Mayseless, Ofra; Dutton, Donald G.

2008-01-01

The authors explored the attachment dynamics of heterosexual couples identified for male partner violence. Based on semistructured interviews, participants were assessed for attachment orientations. Based on a thematic analysis of the interviews, two strategies for regulating distance within these relationships were identified: pursuit and…

The efficacy of wire and glue hair snares in identifying mesocarnivores

Treesearch

William J. Zielinski; Fredrick V. Schlexer; Kristine L. Pilgrim; Michael K. Schwartz

2006-01-01

Track plates and cameras are proven methods for detecting and identifying fishers (Martes pennant) and other mesocarnivores. But these methods are inadequate to achieve demographic and population-monitoring objectives that require identifying sex and individuals. Although noninvasive collection of biological material for genetic analysis (i.e.,...

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.

Main propulsion functional path analysis for performance monitoring fault detection and annunciation

NASA Technical Reports Server (NTRS)

Keesler, E. L.

1974-01-01

A total of 48 operational flight instrumentation measurements were identified for use in performance monitoring and fault detection. The Operational Flight Instrumentation List contains all measurements identified for fault detection and annunciation. Some 16 controller data words were identified for use in fault detection and annunciation.

How to Perform an Ethical Risk Analysis (eRA).

PubMed

Hansson, Sven Ove

2018-02-26

Ethical analysis is often needed in the preparation of policy decisions on risk. A three-step method is proposed for performing an ethical risk analysis (eRA). In the first step, the people concerned are identified and categorized in terms of the distinct but compatible roles of being risk-exposed, a beneficiary, or a decisionmaker. In the second step, a more detailed classification of roles and role combinations is performed, and ethically problematic role combinations are identified. In the third step, further ethical deliberation takes place, with an emphasis on individual risk-benefit weighing, distributional analysis, rights analysis, and power analysis. Ethical issues pertaining to subsidiary risk roles, such as those of experts and journalists, are also treated in this phase. An eRA should supplement, not replace, a traditional risk analysis that puts emphasis on the probabilities and severities of undesirable events but does not cover ethical issues such as agency, interpersonal relationships, and justice. © 2018 Society for Risk Analysis.

Health Seeking in Men: A Concept Analysis.

PubMed

Hooper, Gwendolyn L; Quallich, Susanne A

2016-01-01

This article describes the analysis of the concept of health seeking in men. Men have shorter life expectancies and utilize health services less often than women, leading to poor health outcomes, but a gendered basis for health seeking remains poorly defined. Walker and Avant’s framework was used to guide this concept analysis. Literature published in English from 1990-2015 was reviewed. Thematic analysis identified attributes, antecedents, and consequences of the concept. Based on the analysis, a contemporary definition for health seeking in men was constructed, rooted in the concept of health. The definition is based on the concept analysis and the defining attributes that were identified. This analysis provides a definition specifically for health seeking in American men, making it more specific and gender-based than the parent concept of “health.” This concept analysis provides conceptual clarity that can guide development of a conceptual framework that may be uniquely relevant to providers in urology. Further exploration will uncover specific cultural, social, sexual, and geographic perspectives.

Causal inference in nonlinear systems: Granger causality versus time-delayed mutual information

NASA Astrophysics Data System (ADS)

Li, Songting; Xiao, Yanyang; Zhou, Douglas; Cai, David

2018-05-01

The Granger causality (GC) analysis has been extensively applied to infer causal interactions in dynamical systems arising from economy and finance, physics, bioinformatics, neuroscience, social science, and many other fields. In the presence of potential nonlinearity in these systems, the validity of the GC analysis in general is questionable. To illustrate this, here we first construct minimal nonlinear systems and show that the GC analysis fails to infer causal relations in these systems—it gives rise to all types of incorrect causal directions. In contrast, we show that the time-delayed mutual information (TDMI) analysis is able to successfully identify the direction of interactions underlying these nonlinear systems. We then apply both methods to neuroscience data collected from experiments and demonstrate that the TDMI analysis but not the GC analysis can identify the direction of interactions among neuronal signals. Our work exemplifies inference hazards in the GC analysis in nonlinear systems and suggests that the TDMI analysis can be an appropriate tool in such a case.

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.

Low levels of serum serotonin and amino acids identified in migraine patients.

PubMed

Ren, Caixia; Liu, Jia; Zhou, Juntuo; Liang, Hui; Wang, Yayun; Sun, Yinping; Ma, Bin; Yin, Yuxin

2018-02-05

Migraine is a highly disabling primary headache associated with a high socioeconomic burden and a generally high prevalence. The clinical management of migraine remains a challenge. This study was undertaken to identify potential serum biomarkers of migraine. Using Liquid Chromatography coupled to Mass Spectrometry (LC-MS), the metabolomic profile of migraine was compared with healthy individuals. Principal component analysis (PCA) and Orthogonal partial least squares-discriminant analysis (orthoPLS-DA) showed the metabolomic profile of migraine is distinguishable from controls. Volcano plot analysis identified 10 serum metabolites significantly decreased during migraine. One of these was serotonin, and the other 9 were amino acids. Pathway analysis and enrichment analysis showed tryptophan metabolism (serotonin metabolism), arginine and proline metabolism, and aminoacyl-tRNA biosynthesis are the three most prominently altered pathways in migraine. ROC curve analysis indicated Glycyl-l-proline, N-Methyl-dl-Alanine and l-Methionine are potential sensitive and specific biomarkers for migraine. Our results show Glycyl-l-proline, N-Methyl-dl-Alanine and l-Methionine may be as specific or more specific for migraine than serotonin which is the traditional biomarker of migraine. We propose that therapeutic manipulation of these metabolites or metabolic pathways may be helpful in the prevention and treatment of migraine. Copyright © 2018 Elsevier Inc. All rights reserved.

The Role of Spatial Analysis in Detecting the Consequence of the Factory Sites : Case Study of Assalaya Factory-Sudan

NASA Astrophysics Data System (ADS)

Khair, Amar Sharaf Eldin; Purwanto; RyaSunoko, Henna; Abdullah, Omer Adam

2018-02-01

Spatial analysis is considered as one of the most important science for identifying the most appropriate site for industrialization and also to alleviate the environmental ramifications caused by factories. This study aims at analyzing the Assalaya sugarcane factory site by the use of spatial analysis to determine whether it has ramification on the White Nile River. The methodology employed for this study is Global Position System (GPS) to identify the coordinate system of the study phenomena and other relative factors. The study will also make use Geographical Information System (GIS) to implement the spatial analysis. Satellite data (LandsatDem-Digital Elevation Model) will be considered for the study area and factory in identifying the consequences by analyzing the location of the factory through several features such as hydrological, contour line and geological analysis. Data analysis reveals that the factory site is inappropriate and according to observation on the ground it has consequences on the White Nile River. Based on the finding, the study recommended some suggestions to avoid the aftermath of any factory in general. We have to take advantage of this new technological method to aid in selecting most apt locations for industries that will create an ambient environment.

Spectra-first feature analysis in clinical proteomics - A case study in renal cancer.

PubMed

Goh, Wilson Wen Bin; Wong, Limsoon

2016-10-01

In proteomics, useful signal may be unobserved or lost due to the lack of confident peptide-spectral matches. Selection of differential spectra, followed by associative peptide/protein mapping may be a complementary strategy for improving sensitivity and comprehensiveness of analysis (spectra-first paradigm). This approach is complementary to the standard approach where functional analysis is performed only on the finalized protein list assembled from identified peptides from the spectra (protein-first paradigm). Based on a case study of renal cancer, we introduce a simple spectra-binning approach, MZ-bin. We demonstrate that differential spectra feature selection using MZ-bin is class-discriminative and can trace relevant proteins via spectra associative mapping. Moreover, proteins identified in this manner are more biologically coherent than those selected directly from the finalized protein list. Analysis of constituent peptides per protein reveals high expression inconsistency, suggesting that the measured protein expressions are in fact, poor approximations of true protein levels. Moreover, analysis at the level of constituent peptides may provide higher resolution insight into the underlying biology: Via MZ-bin, we identified for the first time differential splice forms for the known renal cancer marker MAPT. We conclude that the spectra-first analysis paradigm is a complementary strategy to the traditional protein-first paradigm and can provide deeper level insight.

A hierarchical approach employing metabolic and gene expression profiles to identify the pathways that confer cytotoxicity in HepG2 cells

PubMed Central

Li, Zheng; Srivastava, Shireesh; Yang, Xuerui; Mittal, Sheenu; Norton, Paul; Resau, James; Haab, Brian; Chan, Christina

2007-01-01

Background Free fatty acids (FFA) and tumor necrosis factor alpha (TNF-α) have been implicated in the pathogenesis of many obesity-related metabolic disorders. When human hepatoblastoma cells (HepG2) were exposed to different types of FFA and TNF-α, saturated fatty acid was found to be cytotoxic and its toxicity was exacerbated by TNF-α. In order to identify the processes associated with the toxicity of saturated FFA and TNF-α, the metabolic and gene expression profiles were measured to characterize the cellular states. A computational model was developed to integrate these disparate data to reveal the underlying pathways and mechanisms involved in saturated fatty acid toxicity. Results A hierarchical framework consisting of three stages was developed to identify the processes and genes that regulate the toxicity. First, discriminant analysis identified that fatty acid oxidation and intracellular triglyceride accumulation were the most relevant in differentiating the cytotoxic phenotype. Second, gene set enrichment analysis (GSEA) was applied to the cDNA microarray data to identify the transcriptionally altered pathways and processes. Finally, the genes and gene sets that regulate the metabolic responses identified in step 1 were identified by integrating the expression of the enriched gene sets and the metabolic profiles with a multi-block partial least squares (MBPLS) regression model. Conclusion The hierarchical approach suggested potential mechanisms involved in mediating the cytotoxic and cytoprotective pathways, as well as identified novel targets, such as NADH dehydrogenases, aldehyde dehydrogenases 1A1 (ALDH1A1) and endothelial membrane protein 3 (EMP3) as modulator of the toxic phenotypes. These predictions, as well as, some specific targets that were suggested by the analysis were experimentally validated. PMID:17498300

Building-level analyses to prospectively detect influenza outbreaks in long-term care facilities: New York City, 2013-2014.

PubMed

Levin-Rector, Alison; Nivin, Beth; Yeung, Alice; Fine, Annie D; Greene, Sharon K

2015-08-01

Timely outbreak detection is necessary to successfully control influenza in long-term care facilities (LTCFs) and other institutions. To supplement nosocomial outbreak reports, calls from infection control staff, and active laboratory surveillance, the New York City (NYC) Department of Health and Mental Hygiene implemented an automated building-level analysis to proactively identify LTCFs with laboratory-confirmed influenza activity. Geocoded addresses of LTCFs in NYC were compared with geocoded residential addresses for all case-patients with laboratory-confirmed influenza reported through passive surveillance. An automated daily analysis used the geocoded building identification number, approximate text matching, and key-word searches to identify influenza in residents of LTCFs for review and follow-up by surveillance coordinators. Our aim was to determine whether the building analysis improved prospective outbreak detection during the 2013-2014 influenza season. Of 119 outbreaks identified in LTCFs, 109 (92%) were ever detected by the building analysis, and 55 (46%) were first detected by the building analysis. Of the 5,953 LTCF staff and residents who received antiviral prophylaxis during the 2013-2014 season, 929 (16%) were at LTCFs where outbreaks were initially detected by the building analysis. A novel building-level analysis improved influenza outbreak identification in LTCFs in NYC, prompting timely infection control measures. Copyright © 2015 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

Genome-wide analysis identifies chickpea (Cicer arietinum) heat stress transcription factors (Hsfs) responsive to heat stress at the pod development stage.

PubMed

Chidambaranathan, Parameswaran; Jagannadham, Prasanth Tej Kumar; Satheesh, Viswanathan; Kohli, Deshika; Basavarajappa, Santosh Halasabala; Chellapilla, Bharadwaj; Kumar, Jitendra; Jain, Pradeep Kumar; Srinivasan, R

2018-05-01

The heat stress transcription factors (Hsfs) play a prominent role in thermotolerance and eliciting the heat stress response in plants. Identification and expression analysis of Hsfs gene family members in chickpea would provide valuable information on heat stress responsive Hsfs. A genome-wide analysis of Hsfs gene family resulted in the identification of 22 Hsf genes in chickpea in both desi and kabuli genome. Phylogenetic analysis distinctly separated 12 A, 9 B, and 1 C class Hsfs, respectively. An analysis of cis-regulatory elements in the upstream region of the genes identified many stress responsive elements such as heat stress elements (HSE), abscisic acid responsive element (ABRE) etc. In silico expression analysis showed nine and three Hsfs were also expressed in drought and salinity stresses, respectively. Q-PCR expression analysis of Hsfs under heat stress at pod development and at 15 days old seedling stage showed that CarHsfA2, A6, and B2 were significantly upregulated in both the stages of crop growth and other four Hsfs (CarHsfA2, A6a, A6c, B2a) showed early transcriptional upregulation for heat stress at seedling stage of chickpea. These subclasses of Hsfs identified in this study can be further evaluated as candidate genes in the characterization of heat stress response in chickpea.

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.

Independent Pre-Transplant Recipient Cancer Risk Factors after Kidney Transplantation and the Utility of G-Chart Analysis for Clinical Process Control.

PubMed

Schrem, Harald; Schneider, Valentin; Kurok, Marlene; Goldis, Alon; Dreier, Maren; Kaltenborn, Alexander; Gwinner, Wilfried; Barthold, Marc; Liebeneiner, Jan; Winny, Markus; Klempnauer, Jürgen; Kleine, Moritz

2016-01-01

The aim of this study is to identify independent pre-transplant cancer risk factors after kidney transplantation and to assess the utility of G-chart analysis for clinical process control. This may contribute to the improvement of cancer surveillance processes in individual transplant centers. 1655 patients after kidney transplantation at our institution with a total of 9,425 person-years of follow-up were compared retrospectively to the general German population using site-specific standardized-incidence-ratios (SIRs) of observed malignancies. Risk-adjusted multivariable Cox regression was used to identify independent pre-transplant cancer risk factors. G-chart analysis was applied to determine relevant differences in the frequency of cancer occurrences. Cancer incidence rates were almost three times higher as compared to the matched general population (SIR = 2.75; 95%-CI: 2.33-3.21). Significantly increased SIRs were observed for renal cell carcinoma (SIR = 22.46), post-transplant lymphoproliferative disorder (SIR = 8.36), prostate cancer (SIR = 2.22), bladder cancer (SIR = 3.24), thyroid cancer (SIR = 10.13) and melanoma (SIR = 3.08). Independent pre-transplant risk factors for cancer-free survival were age <52.3 years (p = 0.007, Hazard ratio (HR): 0.82), age >62.6 years (p = 0.001, HR: 1.29), polycystic kidney disease other than autosomal dominant polycystic kidney disease (ADPKD) (p = 0.001, HR: 0.68), high body mass index in kg/m2 (p<0.001, HR: 1.04), ADPKD (p = 0.008, HR: 1.26) and diabetic nephropathy (p = 0.004, HR = 1.51). G-chart analysis identified relevant changes in the detection rates of cancer during aftercare with no significant relation to identified risk factors for cancer-free survival (p<0.05). Risk-adapted cancer surveillance combined with prospective G-chart analysis likely improves cancer surveillance schemes by adapting processes to identified risk factors and by using G-chart alarm signals to trigger Kaizen events and audits for root-cause analysis of relevant detection rate changes. Further, comparative G-chart analysis would enable benchmarking of cancer surveillance processes between centers.

Independent Pre-Transplant Recipient Cancer Risk Factors after Kidney Transplantation and the Utility of G-Chart Analysis for Clinical Process Control

PubMed Central

Kurok, Marlene; Goldis, Alon; Dreier, Maren; Kaltenborn, Alexander; Gwinner, Wilfried; Barthold, Marc; Liebeneiner, Jan; Winny, Markus; Klempnauer, Jürgen; Kleine, Moritz

2016-01-01

Background The aim of this study is to identify independent pre-transplant cancer risk factors after kidney transplantation and to assess the utility of G-chart analysis for clinical process control. This may contribute to the improvement of cancer surveillance processes in individual transplant centers. Patients and Methods 1655 patients after kidney transplantation at our institution with a total of 9,425 person-years of follow-up were compared retrospectively to the general German population using site-specific standardized-incidence-ratios (SIRs) of observed malignancies. Risk-adjusted multivariable Cox regression was used to identify independent pre-transplant cancer risk factors. G-chart analysis was applied to determine relevant differences in the frequency of cancer occurrences. Results Cancer incidence rates were almost three times higher as compared to the matched general population (SIR = 2.75; 95%-CI: 2.33–3.21). Significantly increased SIRs were observed for renal cell carcinoma (SIR = 22.46), post-transplant lymphoproliferative disorder (SIR = 8.36), prostate cancer (SIR = 2.22), bladder cancer (SIR = 3.24), thyroid cancer (SIR = 10.13) and melanoma (SIR = 3.08). Independent pre-transplant risk factors for cancer-free survival were age <52.3 years (p = 0.007, Hazard ratio (HR): 0.82), age >62.6 years (p = 0.001, HR: 1.29), polycystic kidney disease other than autosomal dominant polycystic kidney disease (ADPKD) (p = 0.001, HR: 0.68), high body mass index in kg/m2 (p<0.001, HR: 1.04), ADPKD (p = 0.008, HR: 1.26) and diabetic nephropathy (p = 0.004, HR = 1.51). G-chart analysis identified relevant changes in the detection rates of cancer during aftercare with no significant relation to identified risk factors for cancer-free survival (p<0.05). Conclusions Risk-adapted cancer surveillance combined with prospective G-chart analysis likely improves cancer surveillance schemes by adapting processes to identified risk factors and by using G-chart alarm signals to trigger Kaizen events and audits for root-cause analysis of relevant detection rate changes. Further, comparative G-chart analysis would enable benchmarking of cancer surveillance processes between centers. PMID:27398803

Case management information systems: how to put the pieces together now and beyond year 2000.

PubMed

Matthews, P

1999-01-01

Healthcare organizations must establish the goals and objectives of their case management processes before functional and system requirements can be defined. A gap analysis will identify existing systems that can be used to support case management as well as areas in need of systems support. The gap analysis will also identify short-term tactical projects and long-term strategic initiatives supporting the automation of case management. The projects resulting from the gap analysis must be incorporated into the organization's business and information systems plan and budget to ensure appropriate funding and prioritization.

Mining featured biomarkers associated with prostatic carcinoma based on bioinformatics.

PubMed

Piao, Guanying; Wu, Jiarui

2013-11-01

To analyze the differentially expressed genes and identify featured biomarkers from prostatic carcinoma. The software "Significance Analysis of Microarray" (SAM) was used to identify the differentially coexpressed genes (DCGs). The DCGs existed in two datasets were analyzed by GO (Gene Ontology) functional annotation. A total of 389 DCGs were obtained. By GO analysis, we found these DCGs were closely related with the acinus development, TGF-β receptor and signal transduction pathways. Furthermore, five featured biomarkers were discovered by interaction analysis. These important signal pathways and oncogenes may provide potential therapeutic targets for prostatic carcinoma.

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.

Exploratory Mediation Analysis via Regularization

PubMed Central

Serang, Sarfaraz; Jacobucci, Ross; Brimhall, Kim C.; Grimm, Kevin J.

2017-01-01

Exploratory mediation analysis refers to a class of methods used to identify a set of potential mediators of a process of interest. Despite its exploratory nature, conventional approaches are rooted in confirmatory traditions, and as such have limitations in exploratory contexts. We propose a two-stage approach called exploratory mediation analysis via regularization (XMed) to better address these concerns. We demonstrate that this approach is able to correctly identify mediators more often than conventional approaches and that its estimates are unbiased. Finally, this approach is illustrated through an empirical example examining the relationship between college acceptance and enrollment. PMID:29225454

Coevolution analysis of Hepatitis C virus genome to identify the structural and functional dependency network of viral proteins

NASA Astrophysics Data System (ADS)

Champeimont, Raphaël; Laine, Elodie; Hu, Shuang-Wei; Penin, Francois; Carbone, Alessandra

2016-05-01

A novel computational approach of coevolution analysis allowed us to reconstruct the protein-protein interaction network of the Hepatitis C Virus (HCV) at the residue resolution. For the first time, coevolution analysis of an entire viral genome was realized, based on a limited set of protein sequences with high sequence identity within genotypes. The identified coevolving residues constitute highly relevant predictions of protein-protein interactions for further experimental identification of HCV protein complexes. The method can be used to analyse other viral genomes and to predict the associated protein interaction networks.

Science Alert Demonstration with a Rover Traverse Science Data Analysis System

NASA Technical Reports Server (NTRS)

Castano, R.; Estlin, T.; Gaines, D.; Castano, A.; Bornstein, B.; Anderson, R. C.; Judd, M.; Stough, T.; Wagstaff, K.

2005-01-01

The Onboard Autonomous Science Investigation System (OASIS) evaluates geologic data gathered by a planetary rover. This analysis is used to prioritize the data for transmission, so that the data with the highest science value is transmitted to Earth. In addition, the onboard analysis results are used to identify science opportunities. A planning and scheduling component of the system enables the rover to take advantage of the identified science opportunity. OASIS is a NASA-funded research project that is currently being tested on the FIDO rover at JPL for the use on future missions.

Quantitative phosphoproteomic analysis of host responses in human lung epithelial (A549) cells during influenza virus infection.

PubMed

Dapat, Clyde; Saito, Reiko; Suzuki, Hiroshi; Horigome, Tsuneyoshi

2014-01-22

The emergence of antiviral drug-resistant influenza viruses highlights the need for alternative therapeutic strategies. Elucidation of host factors required during virus infection provides information not only on the signaling pathways involved but also on the identification of novel drug targets. RNA interference screening method had been utilized by several studies to determine these host factors; however, proteomics data on influenza host factors are currently limited. In this study, quantitative phosphoproteomic analysis of human lung cell line (A549) infected with 2009 pandemic influenza virus A (H1N1) virus was performed. Phosphopeptides were enriched from tryptic digests of total protein of infected and mock-infected cells using a titania column on an automated purification system followed by iTRAQ labeling. Identification and quantitative analysis of iTRAQ-labeled phosphopeptides were performed using LC-MS/MS. We identified 366 phosphorylation sites on 283 proteins. Of these, we detected 43 upregulated and 35 downregulated proteins during influenza virus infection. Gene ontology enrichment analysis showed that majority of the identified proteins are phosphoproteins involved in RNA processing, immune system process and response to infection. Host-virus interaction network analysis had identified 23 densely connected subnetworks. Of which, 13 subnetworks contained proteins with altered phosphorylation levels during by influenza virus infection. Our results will help to identify potential drug targets that can be pursued for influenza antiviral drug development. Copyright © 2013 Elsevier B.V. All rights reserved.

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.

Global Sensitivity Analysis for Process Identification under Model Uncertainty

NASA Astrophysics Data System (ADS)

Ye, M.; Dai, H.; Walker, A. P.; Shi, L.; Yang, J.

2015-12-01

The environmental system consists of various physical, chemical, and biological processes, and environmental models are always built to simulate these processes and their interactions. For model building, improvement, and validation, it is necessary to identify important processes so that limited resources can be used to better characterize the processes. While global sensitivity analysis has been widely used to identify important processes, the process identification is always based on deterministic process conceptualization that uses a single model for representing a process. However, environmental systems are complex, and it happens often that a single process may be simulated by multiple alternative models. Ignoring the model uncertainty in process identification may lead to biased identification in that identified important processes may not be so in the real world. This study addresses this problem by developing a new method of global sensitivity analysis for process identification. The new method is based on the concept of Sobol sensitivity analysis and model averaging. Similar to the Sobol sensitivity analysis to identify important parameters, our new method evaluates variance change when a process is fixed at its different conceptualizations. The variance considers both parametric and model uncertainty using the method of model averaging. The method is demonstrated using a synthetic study of groundwater modeling that considers recharge process and parameterization process. Each process has two alternative models. Important processes of groundwater flow and transport are evaluated using our new method. The method is mathematically general, and can be applied to a wide range of environmental problems.

Whole-exome sequencing identifies USH2A mutations in a pseudo-dominant Usher syndrome family.

PubMed

Zheng, Sui-Lian; Zhang, Hong-Liang; Lin, Zhen-Lang; Kang, Qian-Yan

2015-10-01

Usher syndrome (USH) is an autosomal recessive (AR) multi-sensory degenerative disorder leading to deaf-blindness. USH is clinically subdivided into three subclasses, and 10 genes have been identified thus far. Clinical and genetic heterogeneities in USH make a precise diagnosis difficult. A dominant‑like USH family in successive generations was identified, and the present study aimed to determine the genetic predisposition of this family. Whole‑exome sequencing was performed in two affected patients and an unaffected relative. Systematic data were analyzed by bioinformatic analysis to remove the candidate mutations via step‑wise filtering. Direct Sanger sequencing and co‑segregation analysis were performed in the pedigree. One novel and two known mutations in the USH2A gene were identified, and were further confirmed by direct sequencing and co‑segregation analysis. The affected mother carried compound mutations in the USH2A gene, while the unaffected father carried a heterozygous mutation. The present study demonstrates that whole‑exome sequencing is a robust approach for the molecular diagnosis of disorders with high levels of genetic heterogeneity.

Comparison of Ribotyping, Randomly Amplified Polymorphic DNA Analysis, and Pulsed-Field Gel Electrophoresis in Typing of Lactobacillus rhamnosus and L. casei Strains

PubMed Central

Tynkkynen, Soile; Satokari, Reetta; Saarela, Maria; Mattila-Sandholm, Tiina; Saxelin, Maija

1999-01-01

A total of 24 strains, biochemically identified as members of the Lactobacillus casei group, were identified by PCR with species-specific primers. The same set of strains was typed by randomly amplified polymorphic DNA (RAPD) analysis, ribotyping, and pulsed-field gel electrophoresis (PFGE) in order to compare the discriminatory power of the methods. Species-specific primers for L. rhamnosus and L. casei identified the type strain L. rhamnosus ATCC 7469 and the neotype strain L. casei ATCC 334, respectively, but did not give any signal with the recently revived species L. zeae, which contains the type strain ATCC 15820 and the strain ATCC 393, which was previously classified as L. casei. Our results are in accordance with the suggested new classification of the L. casei group. Altogether, 21 of the 24 strains studied were identified with the species-specific primers. In strain typing, PFGE was the most discriminatory method, revealing 17 genotypes for the 24 strains studied. Ribotyping and RAPD analysis yielded 15 and 12 genotypes, respectively. PMID:10473394

Comparison of ribotyping, randomly amplified polymorphic DNA analysis, and pulsed-field gel electrophoresis in typing of Lactobacillus rhamnosus and L. casei strains.

PubMed

Tynkkynen, S; Satokari, R; Saarela, M; Mattila-Sandholm, T; Saxelin, M

1999-09-01

A total of 24 strains, biochemically identified as members of the Lactobacillus casei group, were identified by PCR with species-specific primers. The same set of strains was typed by randomly amplified polymorphic DNA (RAPD) analysis, ribotyping, and pulsed-field gel electrophoresis (PFGE) in order to compare the discriminatory power of the methods. Species-specific primers for L. rhamnosus and L. casei identified the type strain L. rhamnosus ATCC 7469 and the neotype strain L. casei ATCC 334, respectively, but did not give any signal with the recently revived species L. zeae, which contains the type strain ATCC 15820 and the strain ATCC 393, which was previously classified as L. casei. Our results are in accordance with the suggested new classification of the L. casei group. Altogether, 21 of the 24 strains studied were identified with the species-specific primers. In strain typing, PFGE was the most discriminatory method, revealing 17 genotypes for the 24 strains studied. Ribotyping and RAPD analysis yielded 15 and 12 genotypes, respectively.

India Allele Finder: a web-based annotation tool for identifying common alleles in next-generation sequencing data of Indian origin.

PubMed

Zhang, Jimmy F; James, Francis; Shukla, Anju; Girisha, Katta M; Paciorkowski, Alex R

2017-06-27

We built India Allele Finder, an online searchable database and command line tool, that gives researchers access to variant frequencies of Indian Telugu individuals, using publicly available fastq data from the 1000 Genomes Project. Access to appropriate population-based genomic variant annotation can accelerate the interpretation of genomic sequencing data. In particular, exome analysis of individuals of Indian descent will identify population variants not reflected in European exomes, complicating genomic analysis for such individuals. India Allele Finder offers improved ease-of-use to investigators seeking to identify and annotate sequencing data from Indian populations. We describe the use of India Allele Finder to identify common population variants in a disease quartet whole exome dataset, reducing the number of candidate single nucleotide variants from 84 to 7. India Allele Finder is freely available to investigators to annotate genomic sequencing data from Indian populations. Use of India Allele Finder allows efficient identification of population variants in genomic sequencing data, and is an example of a population-specific annotation tool that simplifies analysis and encourages international collaboration in genomics research.

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.

Molecular characterization of Trichinella species from wild animals in Israel.

PubMed

Erster, Oran; Roth, Asael; King, Roni; Markovics, Alex

2016-11-15

Trichinellosis is a worldwide disease caused by nematode worms of the genus Trichinella, frequently diagnosed in Israel. However, the identity of the Israeli isolates have not been studied. Here we describe the molecular characterization of 58 isolates collected from jackals (Canis aureus), wild boar (Sus scrofa), foxes (Vulpes vulpes) and a wolf (Canis lupus) in central and northern Israel. Isolates were analyzed using the multiplex PCR analysis encompassing expansion segment V (ESV) and internal sequence 1 (ITS-1) markers, which identified 52 of the 58 samples. Out of the six unidentified samples, four were successfully identified using extended PCR assays for ESV and ITS-1, developed in this study. Our analysis identified 44 isolates as T. britovi, 8 as T. spiralis, four mixed infections, and two isolates were not identified. Clonal analysis of the ITS-1 sequences from six isolates confirmed the initial identification of four mixed infections. These results show that the prevalent species in Israel are T. britovi and T. spiralis, with nearly 7% (4 of 58) incidence of mixed infection. Copyright © 2016 Elsevier B.V. All rights reserved.

Parallel mRNA, proteomics and miRNA expression analysis in cell line models of the intestine.

PubMed

O'Sullivan, Finbarr; Keenan, Joanne; Aherne, Sinead; O'Neill, Fiona; Clarke, Colin; Henry, Michael; Meleady, Paula; Breen, Laura; Barron, Niall; Clynes, Martin; Horgan, Karina; Doolan, Padraig; Murphy, Richard

2017-11-07

To identify miRNA-regulated proteins differentially expressed between Caco2 and HT-29: two principal cell line models of the intestine. Exponentially growing Caco-2 and HT-29 cells were harvested and prepared for mRNA, miRNA and proteomic profiling. mRNA microarray profiling analysis was carried out using the Affymetrix GeneChip Human Gene 1.0 ST array. miRNA microarray profiling analysis was carried out using the Affymetrix Genechip miRNA 3.0 array. Quantitative Label-free LC-MS/MS proteomic analysis was performed using a Dionex Ultimate 3000 RSLCnano system coupled to a hybrid linear ion trap/Orbitrap mass spectrometer. Peptide identities were validated in Proteome Discoverer 2.1 and were subsequently imported into Progenesis QI software for further analysis. Hierarchical cluster analysis for all three parallel datasets (miRNA, proteomics, mRNA) was conducted in the R software environment using the Euclidean distance measure and Ward's clustering algorithm. The prediction of miRNA and oppositely correlated protein/mRNA interactions was performed using TargetScan 6.1. GO biological process, molecular function and cellular component enrichment analysis was carried out for the DE miRNA, protein and mRNA lists via the Pathway Studio 11.3 Web interface using their Mammalian database. Differential expression (DE) profiling comparing the intestinal cell lines HT-29 and Caco-2 identified 1795 Genes, 168 Proteins and 160 miRNAs as DE between the two cell lines. At the gene level, 1084 genes were upregulated and 711 were downregulated in the Caco-2 cell line relative to the HT-29 cell line. At the protein level, 57 proteins were found to be upregulated and 111 downregulated in the Caco-2 cell line relative to the HT-29 cell line. Finally, at the miRNAs level, 104 were upregulated and 56 downregulated in the Caco-2 cell line relative to the HT-29 cell line. Gene ontology (GO) analysis of the DE mRNA identified cell adhesion, migration and ECM organization, cellular lipid and cholesterol metabolic processes, small molecule transport and a range of responses to external stimuli, while similar analysis of the DE protein list identified gene expression/transcription, epigenetic mechanisms, DNA replication, differentiation and translation ontology categories. The DE protein and gene lists were found to share 15 biological processes including for example epithelial cell differentiation [ P value ≤ 1.81613E-08 (protein list); P ≤ 0.000434311 (gene list)] and actin filament bundle assembly [ P value ≤ 0.001582797 (protein list); P ≤ 0.002733714 (gene list)]. Analysis was conducted on the three data streams acquired in parallel to identify targets undergoing potential miRNA translational repression identified 34 proteins, whose respective mRNAs were detected but no change in expression was observed. Of these 34 proteins, 27 proteins downregulated in the Caco-2 cell line relative to the HT-29 cell line and predicted to be targeted by 19 unique anti-correlated/upregulated microRNAs and 7 proteins upregulated in the Caco-2 cell line relative to the HT-29 cell line and predicted to be targeted by 15 unique anti-correlated/downregulated microRNAs. This first study providing "tri-omics" analysis of the principal intestinal cell line models Caco-2 and HT-29 has identified 34 proteins potentially undergoing miRNA translational repression.

Parallel mRNA, proteomics and miRNA expression analysis in cell line models of the intestine

PubMed Central

O’Sullivan, Finbarr; Keenan, Joanne; Aherne, Sinead; O’Neill, Fiona; Clarke, Colin; Henry, Michael; Meleady, Paula; Breen, Laura; Barron, Niall; Clynes, Martin; Horgan, Karina; Doolan, Padraig; Murphy, Richard

2017-01-01

AIM To identify miRNA-regulated proteins differentially expressed between Caco2 and HT-29: two principal cell line models of the intestine. METHODS Exponentially growing Caco-2 and HT-29 cells were harvested and prepared for mRNA, miRNA and proteomic profiling. mRNA microarray profiling analysis was carried out using the Affymetrix GeneChip Human Gene 1.0 ST array. miRNA microarray profiling analysis was carried out using the Affymetrix Genechip miRNA 3.0 array. Quantitative Label-free LC-MS/MS proteomic analysis was performed using a Dionex Ultimate 3000 RSLCnano system coupled to a hybrid linear ion trap/Orbitrap mass spectrometer. Peptide identities were validated in Proteome Discoverer 2.1 and were subsequently imported into Progenesis QI software for further analysis. Hierarchical cluster analysis for all three parallel datasets (miRNA, proteomics, mRNA) was conducted in the R software environment using the Euclidean distance measure and Ward’s clustering algorithm. The prediction of miRNA and oppositely correlated protein/mRNA interactions was performed using TargetScan 6.1. GO biological process, molecular function and cellular component enrichment analysis was carried out for the DE miRNA, protein and mRNA lists via the Pathway Studio 11.3 Web interface using their Mammalian database. RESULTS Differential expression (DE) profiling comparing the intestinal cell lines HT-29 and Caco-2 identified 1795 Genes, 168 Proteins and 160 miRNAs as DE between the two cell lines. At the gene level, 1084 genes were upregulated and 711 were downregulated in the Caco-2 cell line relative to the HT-29 cell line. At the protein level, 57 proteins were found to be upregulated and 111 downregulated in the Caco-2 cell line relative to the HT-29 cell line. Finally, at the miRNAs level, 104 were upregulated and 56 downregulated in the Caco-2 cell line relative to the HT-29 cell line. Gene ontology (GO) analysis of the DE mRNA identified cell adhesion, migration and ECM organization, cellular lipid and cholesterol metabolic processes, small molecule transport and a range of responses to external stimuli, while similar analysis of the DE protein list identified gene expression/transcription, epigenetic mechanisms, DNA replication, differentiation and translation ontology categories. The DE protein and gene lists were found to share 15 biological processes including for example epithelial cell differentiation [P value ≤ 1.81613E-08 (protein list); P ≤ 0.000434311 (gene list)] and actin filament bundle assembly [P value ≤ 0.001582797 (protein list); P ≤ 0.002733714 (gene list)]. Analysis was conducted on the three data streams acquired in parallel to identify targets undergoing potential miRNA translational repression identified 34 proteins, whose respective mRNAs were detected but no change in expression was observed. Of these 34 proteins, 27 proteins downregulated in the Caco-2 cell line relative to the HT-29 cell line and predicted to be targeted by 19 unique anti-correlated/upregulated microRNAs and 7 proteins upregulated in the Caco-2 cell line relative to the HT-29 cell line and predicted to be targeted by 15 unique anti-correlated/downregulated microRNAs. CONCLUSION This first study providing “tri-omics” analysis of the principal intestinal cell line models Caco-2 and HT-29 has identified 34 proteins potentially undergoing miRNA translational repression. PMID:29151691

Citation analysis in journal rankings: medical informatics in the library and information science literature.

PubMed Central

Vishwanatham, R

1998-01-01

Medical informatics is an interdisciplinary field. Medical informatics articles will be found in the literature of various disciplines including library and information science publications. The purpose of this study was to provide an objectively ranked list of journals that publish medical informatics articles relevant to library and information science. Library Literature, Library and Information Science Abstracts, and Social Science Citation Index were used to identify articles published on the topic of medical informatics and to identify a ranked list of journals. This study also used citation analysis to identify the most frequently cited journals relevant to library and information science. PMID:9803294

A Modified Delphi to Identify the Significant Works Pertaining to the Understanding of Reading Comprehension and Content Analysis of the Identified Works

ERIC Educational Resources Information Center

Zunker, Norma D.; Pearce, Daniel L.

2012-01-01

The first part of this study explored the significant works pertaining to the understanding of reading comprehension using a Modified Delphi Method. A panel of reading comprehension experts identified 19 works they considered to be significant to the understanding of reading comprehension. The panel of experts identified the reasons they…

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.

Exome-chip association analysis reveals an Asian-specific missense variant in PAX4 associated with type 2 diabetes in Chinese individuals.

PubMed

Cheung, Chloe Y Y; Tang, Clara S; Xu, Aimin; Lee, Chi-Ho; Au, Ka-Wing; Xu, Lin; Fong, Carol H Y; Kwok, Kelvin H M; Chow, Wing-Sun; Woo, Yu-Cho; Yuen, Michele M A; Hai, JoJo S H; Jin, Ya-Li; Cheung, Bernard M Y; Tan, Kathryn C B; Cherny, Stacey S; Zhu, Feng; Zhu, Tong; Thomas, G Neil; Cheng, Kar-Keung; Jiang, Chao-Qiang; Lam, Tai-Hing; Tse, Hung-Fat; Sham, Pak-Chung; Lam, Karen S L

2017-01-01

Genome-wide association studies (GWASs) have identified many common type 2 diabetes-associated variants, mostly at the intronic or intergenic regions. Recent advancements of exome-array genotyping platforms have opened up a novel means for detecting the associations of low-frequency or rare coding variants with type 2 diabetes. We conducted an exomechip association analysis to identify additional type 2 diabetes susceptibility variants in the Chinese population. An exome-chip association study was conducted by genotyping 5640 Chinese individuals from Hong Kong, using a custom designed exome array, the Asian Exomechip. Single variant association analysis was conducted on 77,468 single nucleotide polymorphisms (SNPs). Fifteen SNPs were subsequently genotyped for replication analysis in an independent Chinese cohort comprising 12,362 individuals from Guangzhou. A combined analysis involving 7189 cases and 10,813 controls was performed. In the discovery stage, an Asian-specific coding variant rs2233580 (p.Arg192His) in PAX4, and two variants at the known loci, CDKN2B-AS1 and KCNQ1, were significantly associated with type 2 diabetes with exome-wide significance (p discovery  < 6.45 × 10 -7 ). The risk allele (T) of PAX4 rs2233580 was associated with a younger age at diabetes diagnosis. This variant was replicated in an independent cohort and demonstrated a stronger association that reached genome-wide significance (p meta-analysis [p meta ] = 3.74 × 10 -15 ) in the combined analysis. We identified the association of a PAX4 Asian-specific missense variant rs2233580 with type 2 diabetes in an exome-chip association analysis, supporting the involvement of PAX4 in the pathogenesis of type 2 diabetes. Our findings suggest PAX4 is a possible effector gene of the 7q32 locus, previously identified from GWAS in Asians.

Payload analysis for space shuttle applications (study 2.2). Volume 3: Payload system operations analysis (task 2.2.1). [payload system operations analysis for shuttles and space tugs

NASA Technical Reports Server (NTRS)

1972-01-01

The technical and cost analysis that was performed for the payload system operations analysis is presented. The technical analysis consists of the operations for the payload/shuttle and payload/tug, and the spacecraft analysis which includes sortie, automated, and large observatory type payloads. The cost analysis includes the costing tradeoffs of the various payload design concepts and traffic models. The overall objectives of this effort were to identify payload design and operational concepts for the shuttle which will result in low cost design, and to examine the low cost design concepts to identify applicable design guidelines. The operations analysis examined several past and current NASA and DoD satellite programs to establish a shuttle operations model. From this model the analysis examined the payload/shuttle flow and determined facility concepts necessary for effective payload/shuttle ground operations. The study of the payload/tug operations was an examination of the various flight timelines for missions requiring the tug.

Concept Analysis of Spirituality: An Evolutionary Approach.

PubMed

Weathers, Elizabeth; McCarthy, Geraldine; Coffey, Alice

2016-04-01

The aim of this article is to clarify the concept of spirituality for future nursing research. Previous concept analyses of spirituality have mostly reviewed the conceptual literature with little consideration of the empirical literature. The literature reviewed in prior concept analyses extends from 1972 to 2005, with no analysis conducted in the past 9 years. Rodgers' evolutionary framework was used to review both the theoretical and empirical literature pertaining to spirituality. Evolutionary concept analysis is a formal method of philosophical inquiry, in which papers are analyzed to identify attributes, antecedents, and consequences of the concept. Empirical and conceptual literature. Three defining attributes of spirituality were identified: connectedness, transcendence, and meaning in life. A conceptual definition of spirituality was proposed based on the findings. Also, four antecedents and five primary consequences of spirituality were identified. Spirituality is a complex concept. This concept analysis adds some clarification by proposing a definition of spirituality that is underpinned by both conceptual and empirical research. Furthermore, exemplars of spirituality, based on prior qualitative research, are presented to support the findings. Hence, the findings of this analysis could guide future nursing research on spirituality. © 2015 Wiley Periodicals, Inc.

Centre of pressure patterns in the golf swing: individual-based analysis.

PubMed

Ball, Kevin; Best, Russell

2012-06-01

Weight transfer has been identified as important in group-based analyses. The aim of this study was to extend this work by examining the importance of weight transfer in the golf swing on an individual basis. Five professional and amateur golfers performed 50 swings with the driver, hitting a ball into a net. The golfer's centre of pressure position and velocity, parallel with the line of shot, were measured by two force plates at eight swing events that were identified from high-speed video. The relationships between these parameters and club head velocity at ball contact were examined using regression statistics. The results did support the use of group-based analysis, with all golfers returning significant relationships. However, results were also individual-specific, with golfers returning different combinations of significant factors. Furthermore, factors not identified in group-based analysis were significant on an individual basis. The most consistent relationship was a larger weight transfer range associated with a larger club head velocity (p < 0.05). All golfers also returned at least one significant relationship with rate of weight transfer at swing events (p < 0.01). Individual-based analysis should form part of performance-based biomechanical analysis of sporting skills.

More than meets the eye: Using cognitive work analysis to identify design requirements for future rail level crossing systems.

PubMed

Salmon, Paul M; Lenné, Michael G; Read, Gemma J M; Mulvihill, Christine M; Cornelissen, Miranda; Walker, Guy H; Young, Kristie L; Stevens, Nicholas; Stanton, Neville A

2016-03-01

An increasing intensity of operations means that the longstanding safety issue of rail level crossings is likely to become worse in the transport systems of the future. It has been suggested that the failure to prevent collisions may be, in part, due to a lack of systems thinking during design, crash analysis, and countermeasure development. This paper presents a systems analysis of current active rail level crossing systems in Victoria, Australia that was undertaken to identify design requirements to improve safety in future rail level crossing environments. Cognitive work analysis was used to analyse rail level crossing systems using data derived from a range of activities. Overall the analysis identified a range of instances where modification or redesign in line with systems thinking could potentially improve behaviour and safety. A notable finding is that there are opportunities for redesign outside of the physical rail level crossing infrastructure, including improved data systems, in-vehicle warnings and modifications to design processes, standards and guidelines. The implications for future rail level crossing systems are discussed. Copyright © 2015 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Proteomic analysis reveals diverse proline hydroxylation-mediated oxygen-sensing cellular pathways in cancer cells

PubMed Central

Liu, Bing; Gao, Yankun; Ruan, Hai-Bin; Chen, Yue

2016-01-01

Proline hydroxylation is a critical cellular mechanism regulating oxygen-response pathways in tumor initiation and progression. Yet, its substrate diversity and functions remain largely unknown. Here, we report a system-wide analysis to characterize proline hydroxylation substrates in cancer cells using an immunoaffinity-purification assisted proteomics strategy. We identified 562 sites from 272 proteins in HeLa cells. Bioinformatic analysis revealed that proline hydroxylation substrates are significantly enriched with mRNA processing and stress-response cellular pathways with canonical and diverse flanking sequence motifs. Structural analysis indicates a significant enrichment of proline hydroxylation participating in the secondary structure of substrate proteins. Our study identified and validated Brd4, a key transcription factor, as a novel proline hydroxylation substrate. Functional analysis showed that the inhibition of proline hydroxylation pathway significantly reduced the proline hydroxylation abundance on Brd4 and affected Brd4-mediated transcriptional activity as well as cell proliferation in AML leukemia cells. Taken together, our study identified a broad regulatory role of proline hydroxylation in cellular oxygen-sensing pathways and revealed potentially new targets that dynamically respond to hypoxia microenvironment in tumor cells. PMID:27764789

Systems-Dynamic Analysis for Neighborhood Study

EPA Science Inventory

Systems-dynamic analysis (or system dynamics (SD)) helps planners identify interrelated impacts of transportation and land-use policies on neighborhood-scale economic outcomes for households and businesses, among other applications. This form of analysis can show benefits and tr...

Failure-Modes-And-Effects Analysis Of Software Logic

NASA Technical Reports Server (NTRS)

Garcia, Danny; Hartline, Thomas; Minor, Terry; Statum, David; Vice, David

1996-01-01

Rigorous analysis applied early in design effort. Method of identifying potential inadequacies and modes and effects of failures caused by inadequacies (failure-modes-and-effects analysis or "FMEA" for short) devised for application to software logic.

Analysis of whole exome sequencing with cardiometabolic traits using family-based linkage and association in the IRAS Family Study

PubMed Central

Tabb, Keri L.; Hellwege, Jacklyn N.; Palmer, Nicholette D.; Dimitrov, Latchezar; Sajuthi, Satria; Taylor, Kent D.; NG, Maggie C.Y.; Hawkins, Gregory A.; Chen, Yii-Der Ida; Brown, W. Mark; McWilliams, David; Williams, Adrienne; Lorenzo, Carlos; Norris, Jill M.; Long, Jirong; Rotter, Jerome I.; Curran, Joanne E.; Blangero, John; Wagenknecht, Lynne E.; Langefeld, Carl D.; Bowden, Donald W.

2017-01-01

Summary Family-based methods are a potentially powerful tool to identify trait-defining genetic variants in extended families, particularly when used to complement conventional association analysis. We utilized two-point linkage analysis and single variant association analysis to evaluate whole exome sequencing (WES) data from 1,205 Hispanic Americans (78 families) from the Insulin Resistance Atherosclerosis Family Study. WES identified 211,612 variants above the minor allele frequency threshold of ≥0.005. These variants were tested for linkage and/or association with 50 cardiometabolic traits after quality control checks. Two-point linkage analysis yielded 10,580,600 LOD scores with 1,148 LOD scores ≥3, 183 LOD scores ≥4, and 29 LOD scores ≥5. The maximal novel LOD score was 5.50 for rs2289043:T>C, in UNC5C with subcutaneous adipose tissue volume. Association analysis identified 13 variants attaining genome-wide significance (p<5×10-08), with the strongest association between rs651821:C>T in APOA5, and triglyceride levels (p=3.67×10-10). Overall, there was a 5.2-fold increase in the number of informative variants detected by WES compared to exome chip analysis in this population, nearly 30% of which were novel variants relative to dbSNP build 138. Thus, integration of results from two-point linkage and single-variant association analysis from WES data enabled identification of novel signals potentially contributing to cardiometabolic traits. PMID:28067407

Role of CFTR mutation analysis in the diagnostic algorithm for cystic fibrosis.

PubMed

Ratkiewicz, Michelle; Pastore, Matthew; McCoy, Karen Sharrock; Thompson, Rohan; Hayes, Don; Sheikh, Shahid Ijaz

2017-04-01

The cystic fibrosis transmembrane conductance regulator (CFTR) gene mutation identification is being used with increased frequency to aid in the diagnosis of cystic fibrosis (CF) in those suspected with CF. Aim of this study was to identify diagnostic outcomes when CFTR mutational analysis was used in CF diagnosis. CFTR mutational analysis results were also compared with sweat chloride results. This study was done on all patients at our institution who had CFTR mutation analysis over a sevenyear period since August 2006. A total of 315 patients underwent CFTR mutational analysis. Fifty-one (16.2%) patients had two mutations identified. Among them 32 had positive sweat chloride levels (≥60 mmol/L), while seven had borderline sweat chloride levels (40-59 mmol/L). An additional 70 patients (22.3%) had only one mutation identified. Among them eight had positive sweat chloride levels, and 17 had borderline sweat chloride levels. Fifty-five patients (17.5%) without CFTR mutations had either borderline (n=45) or positive (n=10) sweat chloride results. Three patients with a CF phenotype had negative CFTR analysis but elevated sweat chloride levels. In eighty-three patients (26.4%) CFTR mutational analysis was done without corresponding sweat chloride testing. Although CFTR mutation analysis has improved the diagnostic capability for CF, its use either as the first step or the only test to diagnose CFTR dysfunction should be discouraged and CF diagnostic guidelines need to be followed.

High-Resolution Melting Curve Analysis of the 16S Ribosomal Gene to Detect and Identify Pathogenic and Saprophytic Leptospira species in Colombian Isolates

PubMed Central

Peláez Sánchez, Ronald G.; Quintero, Juan Álvaro López; Pereira, Martha María; Agudelo-Flórez, Piedad

2017-01-01

It is important to identify the circulating Leptospira agent to enhance the performance of serodiagnostic tests by incorporating specific antigens of native species, develop vaccines that take into account the species/serovars circulating in different regions, and optimize prevention and control strategies. The objectives of this study were to develop a polymerase chain reaction (PCR)–high-resolution melting (HRM) assay for differentiating between species of the genus Leptospira and to verify its usefulness in identifying unknown samples to species level. A set of primers from the initial region of the 16S ribosomal gene was designed to detect and differentiate the 22 species of Leptospira. Eleven reference strains were used as controls to establish the reference species and differential melting curves. Twenty-five Colombian Leptospira isolates were studied to evaluate the usefulness of the PCR–HRM assay in identifying unknown samples to species level. This identification was confirmed by sequencing and phylogenetic analysis of the 16S ribosomal gene. Eleven Leptospira species were successfully identified, except for Leptospira meyeri/Leptospira yanagawae because the sequences were 100% identical. The 25 isolates from humans, animals, and environmental water sources were identified as Leptospira santarosai (twelve), Leptospira interrogans (nine), and L. meyeri/L. yanagawae (four). The species verification was 100% concordant between PCR–HRM and phylogenetic analysis of the 16S ribosomal gene. The PCR–HRM assay designed in this study is a useful tool for identifying Leptospira species from isolates. PMID:28500802

Structural and mechanistic analysis of a β-glycoside phosphorylase identified by screening a metagenomic library.

PubMed

Macdonald, Spencer S; Patel, Ankoor; Larmour, Veronica L C; Morgan-Lang, Connor; Hallam, Steven J; Mark, Brian L; Withers, Stephen G

2018-03-02

Glycoside phosphorylases have considerable potential as catalysts for the assembly of useful glycans for products ranging from functional foods and prebiotics to novel materials. However, the substrate diversity of currently identified phosphorylases is relatively small, limiting their practical applications. To address this limitation, we developed a high-throughput screening approach using the activated substrate 2,4-dinitrophenyl β-d-glucoside (DNPGlc) and inorganic phosphate for identifying glycoside phosphorylase activity and used it to screen a large insert metagenomic library. The initial screen, based on release of 2,4-dinitrophenyl from DNPGlc in the presence of phosphate, identified the gene bglP, encoding a retaining β-glycoside phosphorylase from the CAZy GH3 family. Kinetic and mechanistic analysis of the gene product, BglP, confirmed a double displacement ping-pong mechanism involving a covalent glycosyl-enzyme intermediate. X-ray crystallographic analysis provided insights into the phosphate-binding mode and identified a key glutamine residue in the active site important for substrate recognition. Substituting this glutamine for a serine swapped the substrate specificity from glucoside to N -acetylglucosaminide. In summary, we present a high-throughput screening approach for identifying β-glycoside phosphorylases, which was robust, simple to implement, and useful in identifying active clones within a metagenomics library. Implementation of this screen enabled discovery of a new glycoside phosphorylase class and has paved the way to devising simple ways in which enzyme specificity can be encoded and swapped, which has implications for biotechnological applications. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

Comparison of mosquito control programs in seven urban sites in Africa, the Middle East, and the Americas.

PubMed

Impoinvil, Daniel E; Ahmad, Sajjad; Troyo, Adriana; Keating, Joseph; Githeko, Andrew K; Mbogo, Charles M; Kibe, Lydiah; Githure, John I; Gad, Adel M; Hassan, Ali N; Orshan, Laor; Warburg, Alon; Calderón-Arguedas, Olger; Sánchez-Loría, Victoria M; Velit-Suarez, Rosanna; Chadee, Dave D; Novak, Robert J; Beier, John C

2007-10-01

Mosquito control programs at seven urban sites in Kenya, Egypt, Israel, Costa Rica, and Trinidad are described and compared. Site-specific urban and disease characteristics, organizational diagrams, and strengths, weaknesses, obstacles and threats (SWOT) analysis tools are used to provide a descriptive assessment of each mosquito control program, and provide a comparison of the factors affecting mosquito abatement. The information for SWOT analysis is collected from surveys, focus-group discussions, and personal communication. SWOT analysis identified various issues affecting the efficiency and sustainability of mosquito control operations. The main outcome of our work was the description and comparison of mosquito control operations within the context of each study site's biological, social, political, management, and economic conditions. The issues identified in this study ranged from lack of inter-sector collaboration to operational issues of mosquito control efforts. A lack of sustainable funding for mosquito control was a common problem for most sites. Many unique problems were also identified, which included lack of mosquito surveillance, lack of law enforcement, and negative consequences of human behavior. Identifying common virtues and shortcomings of mosquito control operations is useful in identifying "best practices" for mosquito control operations, thus leading to better control of mosquito biting and mosquito-borne disease transmission.

Parallel analysis of tagged deletion mutants efficiently identifies genes involved in endoplasmic reticulum biogenesis.

PubMed

Wright, Robin; Parrish, Mark L; Cadera, Emily; Larson, Lynnelle; Matson, Clinton K; Garrett-Engele, Philip; Armour, Chris; Lum, Pek Yee; Shoemaker, Daniel D

2003-07-30

Increased levels of HMG-CoA reductase induce cell type- and isozyme-specific proliferation of the endoplasmic reticulum. In yeast, the ER proliferations induced by Hmg1p consist of nuclear-associated stacks of smooth ER membranes known as karmellae. To identify genes required for karmellae assembly, we compared the composition of populations of homozygous diploid S. cerevisiae deletion mutants following 20 generations of growth with and without karmellae. Using an initial population of 1,557 deletion mutants, 120 potential mutants were identified as a result of three independent experiments. Each experiment produced a largely non-overlapping set of potential mutants, suggesting that differences in specific growth conditions could be used to maximize the comprehensiveness of similar parallel analysis screens. Only two genes, UBC7 and YAL011W, were identified in all three experiments. Subsequent analysis of individual mutant strains confirmed that each experiment was identifying valid mutations, based on the mutant's sensitivity to elevated HMG-CoA reductase and inability to assemble normal karmellae. The largest class of HMG-CoA reductase-sensitive mutations was a subset of genes that are involved in chromatin structure and transcriptional regulation, suggesting that karmellae assembly requires changes in transcription or that the presence of karmellae may interfere with normal transcriptional regulation. Copyright 2003 John Wiley & Sons, Ltd.

Comparison of mosquito control programs in seven urban sites in Africa, the Middle East, and the Americas

PubMed Central

Impoinvil, Daniel E.; Ahmad, Sajjad; Troyo, Adriana; Keating, Joseph; Githeko, Andrew K.; Mbogo, Charles M; Kibe, Lydiah; Githure, John I.; Gad, Adel M.; Hassan, Ali N.; Orshan, Laor; Warburg, Alon; Calderón-Arguedas, Olger; Sánchez-Loría, Victoria M.; Velit-Suarez, Rosanna; Chadee, Dave D.; Novak, Robert J.; Beier, John C.

2007-01-01

Mosquito control programs at seven urban sites in Kenya, Egypt, Israel, Costa Rica, and Trinidad are described and compared. Site-specific urban and disease characteristics, organizational diagrams, and strengths, weaknesses, obstacles and threats (SWOT) analysis tools are used to provide a descriptive assessment of each mosquito control program, and provide a comparison of the factors affecting mosquito abatement. The information for SWOT analysis is collected from surveys, focus group discussions, and personal communication. SWOT analysis identified various issues affecting the efficiency and sustainability of mosquito control operations. The main outcome of our work was the description and comparison of mosquito control operations within the context of each study site’s biological, social, political, management, and economic conditions. The issues identified in this study ranged from lack of inter-sector collaboration to operational issues of mosquito control efforts. A lack of sustainable funding for mosquito control was a common problem for most sites. Many unique problems were also identified, which included lack of mosquito surveillance, lack of law enforcement, and negative consequences of human behavior. Identifying common virtues and shortcomings of mosquito control operations is useful in identifying “best practices” for mosquito control operations, thus leading to better control of mosquito biting and mosquito-borne disease transmission. PMID:17316882

Deliberate teaching tools for clinical teaching encounters: A critical scoping review and thematic analysis to establish definitional clarity.

PubMed

Sidhu, Navdeep S; Edwards, Morgan

2018-04-27

We conducted a scoping review of tools designed to add structure to clinical teaching, with a thematic analysis to establish definitional clarity. Six thousand and forty nine citations were screened, 434 reviewed for eligibility, and 230 identified as meeting study inclusion criteria. Eighty-nine names and 51 definitions were identified. Based on a post facto thematic analysis, we propose that these tools be named "deliberate teaching tools" (DTTs) and defined as "frameworks that enable clinicians to have a purposeful and considered approach to teaching encounters by incorporating elements identified with good teaching practice." We identified 46 DTTs in the literature, with 38 (82.6%) originally described for the medical setting. Forty justification articles consisted of 16 feedback surveys, 13 controlled trials, seven pre-post intervention studies with no control group, and four observation studies. Current evidence of efficacy is not entirely conclusive, and many studies contain methodology flaws. Forty-nine clarification articles comprised 12 systematic reviews and 37 narrative reviews. The most number of DTTs described by any review was four. A common design theme was identified in approximately three-quarters of DTTs. Applicability of DTTs to specific alternate settings should be considered in context, and appropriately designed justification studies are warranted to demonstrate efficacy.

Using whole-exome sequencing to identify variants inherited from mosaic parents

PubMed Central

Rios, Jonathan J; Delgado, Mauricio R

2015-01-01

Whole-exome sequencing (WES) has allowed the discovery of genes and variants causing rare human disease. This is often achieved by comparing nonsynonymous variants between unrelated patients, and particularly for sporadic or recessive disease, often identifies a single or few candidate genes for further consideration. However, despite the potential for this approach to elucidate the genetic cause of rare human disease, a majority of patients fail to realize a genetic diagnosis using standard exome analysis methods. Although genetic heterogeneity contributes to the difficulty of exome sequence analysis between patients, it remains plausible that rare human disease is not caused by de novo or recessive variants. Multiple human disorders have been described for which the variant was inherited from a phenotypically normal mosaic parent. Here we highlight the potential for exome sequencing to identify a reasonable number of candidate genes when dominant disease variants are inherited from a mosaic parent. We show the power of WES to identify a limited number of candidate genes using this disease model and how sequence coverage affects identification of mosaic variants by WES. We propose this analysis as an alternative to discover genetic causes of rare human disorders for which typical WES approaches fail to identify likely pathogenic variants. PMID:24986828

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

Some dissociating factors in the analysis of structural and functional progressive damage in open-angle glaucoma.

PubMed

Hudson, C J W; Kim, L S; Hancock, S A; Cunliffe, I A; Wild, J M

2007-05-01

To identify the presence, and origin, of any "dissociating factors" inherent to the techniques for evaluating progression that mask the relationship between structural and functional progression in open-angle glaucoma (OAG). 23 patients (14 with OAG and 9 with ocular hypertension (OHT)) who had received serial Heidelberg Retina Tomograph (HRT II) and Humphrey Field Analyser (HFA) examinations for >or=5 years (mean 78.4 months (SD 9.5), range 60-101 months) were identified. Evidence of progressive disease was retrospectively evaluated in one eye of each patient using the Topographic Change Analysis (TCA) and Glaucoma Progression Analysis (GPA) for the HRT II and HFA, respectively. Six patients were stable by both techniques; four exhibited both structural and functional progression; seven exhibited structural progression, only, and six showed functional progression, only. Three types of dissociating factors were identified. TCA failed to identify progressive structural damage in the presence of advanced optic nerve head damage. GPA failed to identify progressive functional damage at stimulus locations, with sensitivities exhibiting test-retest variability beyond the maximum stimulus luminance of the perimeter, and where a perimetric learning effect was apparent. The three dissociating factors accounted for nine of the 13 patients who exhibited a lack of concordance between structural and functional progressive damage.

Genome-wide association analysis of seedling root development in maize (Zea mays L.).

PubMed

Pace, Jordon; Gardner, Candice; Romay, Cinta; Ganapathysubramanian, Baskar; Lübberstedt, Thomas

2015-02-05

Plants rely on the root system for anchorage to the ground and the acquisition and absorption of nutrients critical to sustaining productivity. A genome wide association analysis enables one to analyze allelic diversity of complex traits and identify superior alleles. 384 inbred lines from the Ames panel were genotyped with 681,257 single nucleotide polymorphism markers using Genotyping-by-Sequencing technology and 22 seedling root architecture traits were phenotyped. Utilizing both a general linear model and mixed linear model, a GWAS study was conducted identifying 268 marker trait associations (p ≤ 5.3×10(-7)). Analysis of significant SNP markers for multiple traits showed that several were located within gene models with some SNP markers localized within regions of previously identified root quantitative trait loci. Gene model GRMZM2G153722 located on chromosome 4 contained nine significant markers. This predicted gene is expressed in roots and shoots. This study identifies putatively associated SNP markers associated with root traits at the seedling stage. Some SNPs were located within or near (<1 kb) gene models. These gene models identify possible candidate genes involved in root development at the seedling stage. These and respective linked or functional markers could be targets for breeders for marker assisted selection of seedling root traits.

Cellular signaling identifiability analysis: a case study.

PubMed

Roper, Ryan T; Pia Saccomani, Maria; Vicini, Paolo

2010-05-21

Two primary purposes for mathematical modeling in cell biology are (1) simulation for making predictions of experimental outcomes and (2) parameter estimation for drawing inferences from experimental data about unobserved aspects of biological systems. While the former purpose has become common in the biological sciences, the latter is less common, particularly when studying cellular and subcellular phenomena such as signaling-the focus of the current study. Data are difficult to obtain at this level. Therefore, even models of only modest complexity can contain parameters for which the available data are insufficient for estimation. In the present study, we use a set of published cellular signaling models to address issues related to global parameter identifiability. That is, we address the following question: assuming known time courses for some model variables, which parameters is it theoretically impossible to estimate, even with continuous, noise-free data? Following an introduction to this problem and its relevance, we perform a full identifiability analysis on a set of cellular signaling models using DAISY (Differential Algebra for the Identifiability of SYstems). We use our analysis to bring to light important issues related to parameter identifiability in ordinary differential equation (ODE) models. We contend that this is, as of yet, an under-appreciated issue in biological modeling and, more particularly, cell biology. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

14 CFR 437.55 - Hazard analysis.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 4 2013-01-01 2013-01-01 false Hazard analysis. 437.55 Section 437.55... TRANSPORTATION LICENSING EXPERIMENTAL PERMITS Safety Requirements § 437.55 Hazard analysis. (a) A permittee must... safety of property resulting from each permitted flight. This hazard analysis must— (1) Identify and...

14 CFR 437.55 - Hazard analysis.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 4 2012-01-01 2012-01-01 false Hazard analysis. 437.55 Section 437.55... TRANSPORTATION LICENSING EXPERIMENTAL PERMITS Safety Requirements § 437.55 Hazard analysis. (a) A permittee must... safety of property resulting from each permitted flight. This hazard analysis must— (1) Identify and...

Participant Interaction in Asynchronous Learning Environments: Evaluating Interaction Analysis Methods

ERIC Educational Resources Information Center

Blanchette, Judith

2012-01-01

The purpose of this empirical study was to determine the extent to which three different objective analytical methods--sequence analysis, surface cohesion analysis, and lexical cohesion analysis--can most accurately identify specific characteristics of online interaction. Statistically significant differences were found in all points of…

Upgrade and interpersonal skills training at American Airlines

NASA Technical Reports Server (NTRS)

Estridge, W. W.; Mansfield, J. L.

1980-01-01

Segments of the interpersonal skills training audio visual program are presented. The program was developed to train customer contact personnel with specific emphasis on transactional analysis in customer treatment. Concepts of transactional analysis are summarized in terms of the make up of the personality, identified as the three ego states. These ego states are identified as the parent, the adult, and the child. Synopses of four of the tape programs are given.

Geometric Theory of Moving Grid Wavefront Sensor

DTIC Science & Technology

1977-06-30

Identify by block numbot) Adaptive Optics WaVefront Sensor Geometric Optics Analysis Moving Ronchi Grid "ABSTRACT (Continue an revere sdde If nooessaY...ad Identify by block nucber)A geometric optics analysis is made for a wavefront sensor that uses a moving Ronchi grid. It is shown that by simple data... optical systems being considered or being developed -3 for imaging an object through a turbulent atmosphere. Some of these use a wavefront sensor to

Genome-wide meta-analysis identifies new susceptibility loci for migraine.

PubMed

Anttila, Verneri; Winsvold, Bendik S; Gormley, Padhraig; Kurth, Tobias; Bettella, Francesco; McMahon, George; Kallela, Mikko; Malik, Rainer; de Vries, Boukje; Terwindt, Gisela; Medland, Sarah E; Todt, Unda; McArdle, Wendy L; Quaye, Lydia; Koiranen, Markku; Ikram, M Arfan; Lehtimäki, Terho; Stam, Anine H; Ligthart, Lannie; Wedenoja, Juho; Dunham, Ian; Neale, Benjamin M; Palta, Priit; Hamalainen, Eija; Schürks, Markus; Rose, Lynda M; Buring, Julie E; Ridker, Paul M; Steinberg, Stacy; Stefansson, Hreinn; Jakobsson, Finnbogi; Lawlor, Debbie A; Evans, David M; Ring, Susan M; Färkkilä, Markus; Artto, Ville; Kaunisto, Mari A; Freilinger, Tobias; Schoenen, Jean; Frants, Rune R; Pelzer, Nadine; Weller, Claudia M; Zielman, Ronald; Heath, Andrew C; Madden, Pamela A F; Montgomery, Grant W; Martin, Nicholas G; Borck, Guntram; Göbel, Hartmut; Heinze, Axel; Heinze-Kuhn, Katja; Williams, Frances M K; Hartikainen, Anna-Liisa; Pouta, Anneli; van den Ende, Joyce; Uitterlinden, Andre G; Hofman, Albert; Amin, Najaf; Hottenga, Jouke-Jan; Vink, Jacqueline M; Heikkilä, Kauko; Alexander, Michael; Muller-Myhsok, Bertram; Schreiber, Stefan; Meitinger, Thomas; Wichmann, Heinz Erich; Aromaa, Arpo; Eriksson, Johan G; Traynor, Bryan; Trabzuni, Daniah; Rossin, Elizabeth; Lage, Kasper; Jacobs, Suzanne B R; Gibbs, J Raphael; Birney, Ewan; Kaprio, Jaakko; Penninx, Brenda W; Boomsma, Dorret I; van Duijn, Cornelia; Raitakari, Olli; Jarvelin, Marjo-Riitta; Zwart, John-Anker; Cherkas, Lynn; Strachan, David P; Kubisch, Christian; Ferrari, Michel D; van den Maagdenberg, Arn M J M; Dichgans, Martin; Wessman, Maija; Smith, George Davey; Stefansson, Kari; Daly, Mark J; Nyholt, Dale R; Chasman, Daniel; Palotie, Aarno

2013-08-01

Migraine is the most common brain disorder, affecting approximately 14% of the adult population, but its molecular mechanisms are poorly understood. We report the results of a meta-analysis across 29 genome-wide association studies, including a total of 23,285 individuals with migraine (cases) and 95,425 population-matched controls. We identified 12 loci associated with migraine susceptibility (P<5×10(-8)). Five loci are new: near AJAP1 at 1p36, near TSPAN2 at 1p13, within FHL5 at 6q16, within C7orf10 at 7p14 and near MMP16 at 8q21. Three of these loci were identified in disease subgroup analyses. Brain tissue expression quantitative trait locus analysis suggests potential functional candidate genes at four loci: APOA1BP, TBC1D7, FUT9, STAT6 and ATP5B.

Psychological profiling of offender characteristics from crime behaviors in serial rape offences.

PubMed

Kocsis, Richard N; Cooksey, Ray W; Irwin, Harvey J

2002-04-01

Criminal psychological profiling has progressively been incorporated into police procedures despite a dearth of empirical research. Indeed, in the study of serial violent crimes for the purpose of psychological profiling, very few original, quantitative, academically reviewed studies actually exist. This article reports on the analysis of 62 incidents of serial sexual assault. The statistical procedure of multidimensional scaling was employed in the analysis of this data, which in turn produced a five-cluster model of serial rapist behavior. First, a central cluster of behaviors were identified that represent common behaviors to all patterns of serial rape. Second, four distinct outlying patterns were identified as demonstrating distinct offence styles, these being assigned the following descriptive labels brutality, intercourse, chaotic, and ritual. Furthermore, analysis of these patterns also identified distinct offender characteristics that allow for the use of empirically robust offender profiles in future serial rape investigations.

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

Temporal trends and bioavailability assessment of heavy metals in the sediments of Deception Bay, Queensland, Australia.

PubMed

Brady, James P; Ayoko, Godwin A; Martens, Wayde N; Goonetilleke, Ashantha

2014-12-15

Thirteen sites in Deception Bay, Queensland, Australia were sampled three times over a period of 7 months and assessed for contamination by a range of heavy metals, primarily As, Cd, Cr, Cu, Pb and Hg. Fraction analysis, enrichment factors and Principal Components Analysis-Absolute Principal Component Scores (PCA-APCS) analysis were conducted in order to identify the potential bioavailability of these elements of concern and their sources. Hg and Te were identified as the elements of highest enrichment in Deception Bay while marine sediments, shipping and antifouling agents were identified as the sources of the Weak Acid Extractable Metals (WE-M), with antifouling agents showing long residence time for mercury contamination. This has significant implications for the future of monitoring and regulation of heavy metal contamination within Deception Bay. Copyright © 2014 Elsevier Ltd. All rights reserved.

Analysis of waterborne paints by gas chromatography-mass spectrometry with a temperature-programmable pyrolyzer.

PubMed

Nakamura, S; Takino, M; Daishima, S

2001-04-06

Gas chromatography-mass spectrometry (GC-MS) with a temperature-programmable pyrolyzer was used for the analysis of waterborne paints. Evolved gas analysis (EGA) profiles of the waterborne paints were obtained by this temperature-programmed pyrolysis directly coupled with MS via a deactivated metal capillary tube. The EGA profile suggested the optimal thermal desorption conditions for solvents and additives and the subsequent optimal pyrolysis temperature for the remaining polymeric material. Polymers were identified from pyrograms with the assistance of a new polymer library. The solvents were identified from the electron ionization mass spectra with the corresponding chemical ionization mass spectra. The additive was identified as zinc pyrithione by comparison with authentic standard. Zinc pyrithione cannot be analyzed by GC-MS as it is. However, the thermal decomposition products of zinc pyrithione could be detected. The information on the decomposition temperature and products was useful for the identification of the original compound.

Clavibacter michiganensis subsp. phaseoli subsp. nov., pathogenic in bean.

PubMed

González, Ana J; Trapiello, Estefanía

2014-05-01

A yellow Gram-reaction-positive bacterium isolated from bean seeds (Phaseolus vulgaris L.) was identified as Clavibacter michiganensis by 16S rRNA gene sequencing. Molecular methods were employed in order to identify the subspecies. Such methods included the amplification of specific sequences by PCR, 16S amplified rDNA restriction analysis (ARDRA), RFLP and multilocus sequence analysis as well as the analysis of biochemical and phenotypic traits including API 50CH and API ZYM results. The results showed that strain LPPA 982T did not represent any known subspecies of C. michiganensis. Pathogenicity tests revealed that the strain is a bean pathogen causing a newly identified bacterial disease that we name bacterial bean leaf yellowing. On the basis of these results, strain LPPA 982T is regarded as representing a novel subspecies for which the name Clavibacter michiganensis subsp. phaseoli subsp. nov. is proposed. The type strain is LPPA 982T (=CECT 8144T=LMG 27667T).

[Polymorphic loci and polymorphism analysis of short tandem repeats within XNP gene].

PubMed

Liu, Qi-Ji; Gong, Yao-Qin; Guo, Chen-Hong; Chen, Bing-Xi; Li, Jiang-Xia; Guo, Yi-Shou

2002-01-01

To select polymorphic short tandem repeat markers within X-linked nuclear protein (XNP) gene, genomic clones which contain XNP gene were recognized by homologous analysis with XNP cDNA. By comparing the cDNA with genomic DNA, non-exonic sequences were identified, and short tandem repeats were selected from non-exonic sequences by using BCM search Launcher. Polymorphisms of the short tandem repeats in Chinese population were evaluated by PCR amplification and PAGE. Five short tandem repeats were identified from XNP gene, two of which were polymorphic. Four and 11 alleles were observed in Chinese population for XNPSTR1 and XNPSTR4, respectively. Heterozygosities were 47% for XNPSTR1 and 70% for XNPSTR4. XNPSTR1 and XNPSTR4 localized within 3' end and intron 10, respectively. Two polymorphic short tandem repeats have been identified within XNP gene and will be useful for linkage analysis and gene diagnosis of XNP gene.

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

Moral deliberation and nursing ethics cases: elements of a methodological proposal.

PubMed

Schneider, Dulcinéia Ghizoni; Ramos, Flávia Regina Souza

2012-11-01

A qualitative study with an exploratory, descriptive and documentary design that was conducted with the objective of identifying the elements to constitute a method for the analysis of accusations of and proceedings for professional ethics infringements. The method is based on underlying elements identified inductively during analysis of professional ethics hearings judged by and filed in the archives of the Regional Nursing Board of Santa Catarina, Brazil, between 1999 and 2007. The strategies developed were based on the results of an analysis of the findings of fact (occurrences/infractions, causes and outcomes) contained in the records of 128 professional ethics hearings and on the structural elements (statements, rules and practices) identified in five example professional ethics cases. The strategies suggested for evaluating accusations of ethics infringements and the procedures involved in deliberating on ethics hearings constitute a generic proposal that will require adaptation to the context of specific professional ethics accusations.

High-Throughput Single-Cell RNA Sequencing and Data Analysis.

PubMed

Sagar; Herman, Josip Stefan; Pospisilik, John Andrew; Grün, Dominic

2018-01-01

Understanding biological systems at a single cell resolution may reveal several novel insights which remain masked by the conventional population-based techniques providing an average readout of the behavior of cells. Single-cell transcriptome sequencing holds the potential to identify novel cell types and characterize the cellular composition of any organ or tissue in health and disease. Here, we describe a customized high-throughput protocol for single-cell RNA-sequencing (scRNA-seq) combining flow cytometry and a nanoliter-scale robotic system. Since scRNA-seq requires amplification of a low amount of endogenous cellular RNA, leading to substantial technical noise in the dataset, downstream data filtering and analysis require special care. Therefore, we also briefly describe in-house state-of-the-art data analysis algorithms developed to identify cellular subpopulations including rare cell types as well as to derive lineage trees by ordering the identified subpopulations of cells along the inferred differentiation trajectories.

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.

A methodology to enhance electromagnetic compatibility in joint military operations

NASA Astrophysics Data System (ADS)

Buckellew, William R.

The development and validation of an improved methodology to identify, characterize, and prioritize potential joint EMI (electromagnetic interference) interactions and identify and develop solutions to reduce the effects of the interference are discussed. The methodology identifies potential EMI problems using results from field operations, historical data bases, and analytical modeling. Operational expertise, engineering analysis, and testing are used to characterize and prioritize the potential EMI problems. Results can be used to resolve potential EMI during the development and acquisition of new systems and to develop engineering fixes and operational workarounds for systems already employed. The analytic modeling portion of the methodology is a predictive process that uses progressive refinement of the analysis and the operational electronic environment to eliminate noninterfering equipment pairs, defer further analysis on pairs lacking operational significance, and resolve the remaining EMI problems. Tests are conducted on equipment pairs to ensure that the analytical models provide a realistic description of the predicted interference.

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.

A systematic review of nurse-related social network analysis studies.

PubMed

Benton, D C; Pérez-Raya, F; Fernández-Fernández, M P; González-Jurado, M A

2015-09-01

Nurses frequently work as part of both uni- and multidisciplinary teams. Communication between team members is critical in the delivery of quality care. Social network analysis is increasingly being used to explore such communication. To explore the use of social network analysis involving nurses either as subjects of the study or as researchers. Standard systematic review procedures were applied to identify nurse-related studies that utilize social network analysis. A comparative thematic approach to synthesis was used. Both published and grey literature written in English, Spanish and Portuguese between January 1965 and December 2013 were identified via a structured search of CINAHL, SciELO and PubMed. In addition, Google and Yahoo search engines were used to identify additional grey literature using the same search strategy. Forty-three primary studies were identified with literature from North America dominating the published work. So far it would appear that no author or group of authors have developed a programme of research in the nursing field using the social network analysis approach although several authors may be in the process of doing so. The dominance of literature from North America may be viewed as problematic as the underlying structures and themes may be an artefact of cultural communication norms from this region. The use of social network analysis in relation to nursing and by nurse researchers has increased rapidly over the past two decades. The lack of longitudinal studies and the absence of replication across multiple sites should be seen as an opportunity for further research. This analytical approach is relatively new in the field of nursing but does show considerable promise in offering insights into the way information flows between individuals, teams, institutions and other structures. An understanding of these structures provides a means of improving communication. © 2014 International Council of Nurses.

Large-scale genome-wide analysis identifies genetic variants associated with cardiac structure and function

PubMed Central

Wild, Philipp S.; Felix, Janine F.; Schillert, Arne; Chen, Ming-Huei; Leening, Maarten J.G.; Völker, Uwe; Großmann, Vera; Brody, Jennifer A.; Irvin, Marguerite R.; Shah, Sanjiv J.; Pramana, Setia; Lieb, Wolfgang; Schmidt, Reinhold; Stanton, Alice V.; Malzahn, Dörthe; Lyytikäinen, Leo-Pekka; Tiller, Daniel; Smith, J. Gustav; Di Tullio, Marco R.; Musani, Solomon K.; Morrison, Alanna C.; Pers, Tune H.; Morley, Michael; Kleber, Marcus E.; Aragam, Jayashri; Bis, Joshua C.; Bisping, Egbert; Broeckel, Ulrich; Cheng, Susan; Deckers, Jaap W.; Del Greco M, Fabiola; Edelmann, Frank; Fornage, Myriam; Franke, Lude; Friedrich, Nele; Harris, Tamara B.; Hofer, Edith; Hofman, Albert; Huang, Jie; Hughes, Alun D.; Kähönen, Mika; investigators, KNHI; Kruppa, Jochen; Lackner, Karl J.; Lannfelt, Lars; Laskowski, Rafael; Launer, Lenore J.; Lindgren, Cecilia M.; Loley, Christina; Mayet, Jamil; Medenwald, Daniel; Morris, Andrew P.; Müller, Christian; Müller-Nurasyid, Martina; Nappo, Stefania; Nilsson, Peter M.; Nuding, Sebastian; Nutile, Teresa; Peters, Annette; Pfeufer, Arne; Pietzner, Diana; Pramstaller, Peter P.; Raitakari, Olli T.; Rice, Kenneth M.; Rotter, Jerome I.; Ruohonen, Saku T.; Sacco, Ralph L.; Samdarshi, Tandaw E.; Sharp, Andrew S.P.; Shields, Denis C.; Sorice, Rossella; Sotoodehnia, Nona; Stricker, Bruno H.; Surendran, Praveen; Töglhofer, Anna M.; Uitterlinden, André G.; Völzke, Henry; Ziegler, Andreas; Münzel, Thomas; März, Winfried; Cappola, Thomas P.; Hirschhorn, Joel N.; Mitchell, Gary F.; Smith, Nicholas L.; Fox, Ervin R.; Dueker, Nicole D.; Jaddoe, Vincent W.V.; Melander, Olle; Lehtimäki, Terho; Ciullo, Marina; Hicks, Andrew A.; Lind, Lars; Gudnason, Vilmundur; Pieske, Burkert; Barron, Anthony J.; Zweiker, Robert; Schunkert, Heribert; Ingelsson, Erik; Liu, Kiang; Arnett, Donna K.; Psaty, Bruce M.; Blankenberg, Stefan; Larson, Martin G.; Felix, Stephan B.; Franco, Oscar H.; Zeller, Tanja; Vasan, Ramachandran S.; Dörr, Marcus

2017-01-01

BACKGROUND. Understanding the genetic architecture of cardiac structure and function may help to prevent and treat heart disease. This investigation sought to identify common genetic variations associated with inter-individual variability in cardiac structure and function. METHODS. A GWAS meta-analysis of echocardiographic traits was performed, including 46,533 individuals from 30 studies (EchoGen consortium). The analysis included 16 traits of left ventricular (LV) structure, and systolic and diastolic function. RESULTS. The discovery analysis included 21 cohorts for structural and systolic function traits (n = 32,212) and 17 cohorts for diastolic function traits (n = 21,852). Replication was performed in 5 cohorts (n = 14,321) and 6 cohorts (n = 16,308), respectively. Besides 5 previously reported loci, the combined meta-analysis identified 10 additional genome-wide significant SNPs: rs12541595 near MTSS1 and rs10774625 in ATXN2 for LV end-diastolic internal dimension; rs806322 near KCNRG, rs4765663 in CACNA1C, rs6702619 near PALMD, rs7127129 in TMEM16A, rs11207426 near FGGY, rs17608766 in GOSR2, and rs17696696 in CFDP1 for aortic root diameter; and rs12440869 in IQCH for Doppler transmitral A-wave peak velocity. Findings were in part validated in other cohorts and in GWAS of related disease traits. The genetic loci showed associations with putative signaling pathways, and with gene expression in whole blood, monocytes, and myocardial tissue. CONCLUSION. The additional genetic loci identified in this large meta-analysis of cardiac structure and function provide insights into the underlying genetic architecture of cardiac structure and warrant follow-up in future functional studies. FUNDING. For detailed information per study, see Acknowledgments. PMID:28394258

Gene-based meta-analysis of genome-wide association study data identifies independent single-nucleotide polymorphisms in ANXA6 as being associated with systemic lupus erythematosus in Asian populations.

PubMed

Zhang, Jing; Zhang, Lu; Zhang, Yan; Yang, Jing; Guo, Mengbiao; Sun, Liangdan; Pan, Hai-Feng; Hirankarn, Nattiya; Ying, Dingge; Zeng, Shuai; Lee, Tsz Leung; Lau, Chak Sing; Chan, Tak Mao; Leung, Alexander Moon Ho; Mok, Chi Chiu; Wong, Sik Nin; Lee, Ka Wing; Ho, Marco Hok Kung; Lee, Pamela Pui Wah; Chung, Brian Hon-Yin; Chong, Chun Yin; Wong, Raymond Woon Sing; Mok, Mo Yin; Wong, Wilfred Hing Sang; Tong, Kwok Lung; Tse, Niko Kei Chiu; Li, Xiang-Pei; Avihingsanon, Yingyos; Rianthavorn, Pornpimol; Deekajorndej, Thavatchai; Suphapeetiporn, Kanya; Shotelersuk, Vorasuk; Ying, Shirley King Yee; Fung, Samuel Ka Shun; Lai, Wai Ming; Garcia-Barceló, Maria-Mercè; Cherny, Stacey S; Sham, Pak Chung; Cui, Yong; Yang, Sen; Ye, Dong Qing; Zhang, Xue-Jun; Lau, Yu Lung; Yang, Wanling

2015-11-01

Previous genome-wide association studies (GWAS), which were mainly based on single-variant analysis, have identified many systemic lupus erythematosus (SLE) susceptibility loci. However, the genetic architecture of this complex disease is far from being understood. The aim of this study was to investigate whether using a gene-based analysis may help to identify novel loci, by considering global evidence of association from a gene or a genomic region rather than focusing on evidence for individual variants. Based on the results of a meta-analysis of 2 GWAS of SLE conducted in 2 Asian cohorts, we performed an in-depth gene-based analysis followed by replication in a total of 4,626 patients and 7,466 control subjects of Asian ancestry. Differential allelic expression was measured by pyrosequencing. More than one-half of the reported SLE susceptibility loci showed evidence of independent effects, and this finding is important for understanding the mechanisms of association and explaining disease heritability. ANXA6 was detected as a novel SLE susceptibility gene, with several single-nucleotide polymorphisms (SNPs) contributing independently to the association with disease. The risk allele of rs11960458 correlated significantly with increased expression of ANXA6 in peripheral blood mononuclear cells from heterozygous healthy control subjects. Several other associated SNPs may also regulate ANXA6 expression, according to data obtained from public databases. Higher expression of ANXA6 in patients with SLE was also reported previously. Our study demonstrated the merit of using gene-based analysis to identify novel susceptibility loci, especially those with independent effects, and also demonstrated the widespread presence of loci with independent effects in SLE susceptibility genes. © 2015, American College of Rheumatology.

Diagnostic fragment-ion-based and extension strategy coupled to DFIs intensity analysis for identification of chlorogenic acids isomers in Flos Lonicerae Japonicae by HPLC-ESI-MS(n).

PubMed

Zhang, Jia-Yu; Zhang, Qian; Li, Ning; Wang, Zi-Jian; Lu, Jian-Qiu; Qiao, Yan-Jiang

2013-01-30

A method of modified diagnostic fragment-ion-based extension strategy (DFIBES) coupled to DFIs (diagnostic fragmentation ions) intensity analysis was successfully established to simultaneously screen and identify the chlorogenic acids (CGAs) in Flos Lonicerae Japonicae (FLJ) by HPLC-ESI-MS(n). DFIs, such as m/z 191 [quinic acid-H](-), m/z 179 [caffeic acid-H](-) and m/z 173 [quinic acid-H-H2O](-) were determined or proposed from the fragmentation patterns analysis of corresponding reference substances for every chemical family of CGAs. A "structure extension" method was then proposed based on the well-demonstrated fragmentation patterns and was successively applied into the rapid screening of CGAs in FLJ. Considering that substitution isomerism is a common phenomenon, a full ESI-MS(n) fragmentation analysis according to the intensity of DFIs has been performed to identify the CGA isomers. Based on the DFIs and intensity analysis, 41 peaks attributed to CGAs including 4 caffeoylquinic acids (CQA), 7 CQA glycosides, 6 dicaffeoylquinic acids (DiCQA), 10 DiCQA glycosides, 1 tricaffeoylquinic acids (TriCQA), 4p-coumaroylquinic acids (pCoQA), 3 feruloylquinic acids (FQA) and 6 caffeoylferuloylquinic acids (CFQA) were identified preliminarily in a 65-min chromatographic run. It was the first time to systematically report the presence of CGAs in FLJ, especially for CQA glycosides, DiCQA glycosides, TriCQA, pCoQA and CFQA. All the results indicated that the method of developed DFIBES coupled to DFIs analysis was feasible, reliable and universal for screening and identifying the constituents with the same carbon skeletons especially the isomeric compounds from the complex extract of TCMs. Copyright © 2012 Elsevier B.V. All rights reserved.

Targets of perioperative fluid therapy and their effects on postoperative outcome: a systematic review and meta-analysis.

PubMed

Berger, M M; Gradwohl-Matis, I; Brunauer, A; Ulmer, H; Dünser, M W

2015-07-01

Perioperative fluid management plays a fundamental role in maintaining organ perfusion, and is considered to affect morbidity and mortality. Targets according to which fluid therapy should be administered are poorly defined. This systematic review aimed to identify specific targets for perioperative fluid therapy. The PubMed database (January 1993-December 2013) and reference lists were searched to identify clinical trials which evaluated specific targets of perioperative fluid therapy and reported clinically relevant perioperative endpoints in adult patients. Only studies in which targeted fluid therapy was the sole intervention were included into the main data analysis. A pooled data analysis was used to compare mortality between goal-directed fluid therapy and control interventions. Thirty-six clinical studies were selected. Sixteen studies including 1224 patients specifically evaluated targeted fluid therapy and were included into the main data analysis. Three specific targets for perioperative fluid therapy were identified: a systolic or pulse pressure variation <10-12%, an increase in stroke volume <10%, and a corrected flow time of 0.35-0.4 s in combination with an increase in stroke volume <10%. Targeting any one of these goals resulted in less postoperative complications (pooled data analysis: OR 0.53; CI95, 0.34-0.83; P=0.005) and a shorter length of intensive care unit/hospital stay, but no difference in postoperative mortality (pooled data analysis: OR 0.61; CI95, 0.33-1.11; P=0.12). This systematic review identified three goals for perioperative fluid administration, targeting of which appeared to be associated with less postoperative complications and shorter intensive care unit/hospital lengths of stay. Perioperative mortality remained unaffected.

Issues in Biomedical Research Data Management and Analysis: Needs and Barriers

PubMed Central

Anderson, Nicholas R.; Lee, E. Sally; Brockenbrough, J. Scott; Minie, Mark E.; Fuller, Sherrilynne; Brinkley, James; Tarczy-Hornoch, Peter

2007-01-01

Objectives A. Identify the current state of data management needs of academic biomedical researchers. B. Explore their anticipated data management and analysis needs. C. Identify barriers to addressing those needs. Design A multimodal needs analysis was conducted using a combination of an online survey and in-depth one-on-one semi-structured interviews. Subjects were recruited via an e-mail list representing a wide range of academic biomedical researchers in the Pacific Northwest. Measurements The results from 286 survey respondents were used to provide triangulation of the qualitative analysis of data gathered from 15 semi-structured in-depth interviews. Results Three major themes were identified: 1) there continues to be widespread use of basic general-purpose applications for core data management; 2) there is broad perceived need for additional support in managing and analyzing large datasets; and 3) the barriers to acquiring currently available tools are most commonly related to financial burdens on small labs and unmet expectations of institutional support. Conclusion Themes identified in this study suggest that at least some common data management needs will best be served by improving access to basic level tools such that researchers can solve their own problems. Additionally, institutions and informaticians should focus on three components: 1) facilitate and encourage the use of modern data exchange models and standards, enabling researchers to leverage a common layer of interoperability and analysis; 2) improve the ability of researchers to maintain provenance of data and models as they evolve over time though tools and the leveraging of standards; and 3) develop and support information management service cores that could assist in these previous components while providing researchers with unique data analysis and information design support within a spectrum of informatics capabilities. PMID:17460139

Comparison of linkage analysis methods for genome-wide scanning of extended pedigrees, with application to the TG/HDL-C ratio in the Framingham Heart Study

PubMed Central

Horne, Benjamin D; Malhotra, Alka; Camp, Nicola J

2003-01-01

Background High triglycerides (TG) and low high-density lipoprotein cholesterol (HDL-C) jointly increase coronary disease risk. We performed linkage analysis for TG/HDL-C ratio in the Framingham Heart Study data as a quantitative trait, using methods implemented in LINKAGE, GENEHUNTER (GH), MCLINK, and SOLAR. Results were compared to each other and to those from a previous evaluation using SOLAR for TG/HDL-C ratio on this sample. We also investigated linked pedigrees in each region using by-pedigree analysis. Results Fourteen regions with at least suggestive linkage evidence were identified, including some that may increase and some that may decrease coronary risk. Ten of the 14 regions were identified by more than one analysis, and several of these regions were not previously detected. The best regions identified for each method were on chromosomes 2 (LOD = 2.29, MCLINK), 5 (LOD = 2.65, GH), 7 (LOD = 2.67, SOLAR), and 22 (LOD = 3.37, LINKAGE). By-pedigree multi-point LOD values in MCLINK showed linked pedigrees for all five regions, ranging from 3 linked pedigrees (chromosome 5) to 14 linked pedigrees (chromosome 7), and suggested localizations of between 9 cM and 27 cM in size. Conclusion Reasonable concordance was found across analysis methods. No single method identified all regions, either by full sample LOD or with by-pedigree analysis. Concordance across methods appeared better at the pedigree level, with many regions showing by-pedigree support in MCLINK when no evidence was observed in the full sample. Thus, investigating by-pedigree linkage evidence may provide a useful tool for evaluating linkage regions. PMID:14975161

Comparison of linkage analysis methods for genome-wide scanning of extended pedigrees, with application to the TG/HDL-C ratio in the Framingham Heart Study.

PubMed

Horne, Benjamin D; Malhotra, Alka; Camp, Nicola J

2003-12-31

High triglycerides (TG) and low high-density lipoprotein cholesterol (HDL-C) jointly increase coronary disease risk. We performed linkage analysis for TG/HDL-C ratio in the Framingham Heart Study data as a quantitative trait, using methods implemented in LINKAGE, GENEHUNTER (GH), MCLINK, and SOLAR. Results were compared to each other and to those from a previous evaluation using SOLAR for TG/HDL-C ratio on this sample. We also investigated linked pedigrees in each region using by-pedigree analysis. Fourteen regions with at least suggestive linkage evidence were identified, including some that may increase and some that may decrease coronary risk. Ten of the 14 regions were identified by more than one analysis, and several of these regions were not previously detected. The best regions identified for each method were on chromosomes 2 (LOD = 2.29, MCLINK), 5 (LOD = 2.65, GH), 7 (LOD = 2.67, SOLAR), and 22 (LOD = 3.37, LINKAGE). By-pedigree multi-point LOD values in MCLINK showed linked pedigrees for all five regions, ranging from 3 linked pedigrees (chromosome 5) to 14 linked pedigrees (chromosome 7), and suggested localizations of between 9 cM and 27 cM in size. Reasonable concordance was found across analysis methods. No single method identified all regions, either by full sample LOD or with by-pedigree analysis. Concordance across methods appeared better at the pedigree level, with many regions showing by-pedigree support in MCLINK when no evidence was observed in the full sample. Thus, investigating by-pedigree linkage evidence may provide a useful tool for evaluating linkage regions.

A Gap Analysis Needs Assessment Tool to Drive a Care Delivery and Research Agenda for Integration of Care and Sharing of Best Practices Across a Health System.

PubMed

Golden, Sherita Hill; Hager, Daniel; Gould, Lois J; Mathioudakis, Nestoras; Pronovost, Peter J

2017-01-01

In a complex health system, it is important to establish a systematic and data-driven approach to identifying needs. The Diabetes Clinical Community (DCC) of Johns Hopkins Medicine's Armstrong Institute for Patient Safety and Quality developed a gap analysis tool and process to establish the system's current state of inpatient diabetes care. The collectively developed tool assessed the following areas: program infrastructure; protocols, policies, and order sets; patient and health care professional education; and automated data access. For the purposes of this analysis, gaps were defined as those instances in which local resources, infrastructure, or processes demonstrated a variance against the current national evidence base or institutionally defined best practices. Following the gap analysis, members of the DCC, in collaboration with health system leadership, met to identify priority areas in order to integrate and synergize diabetes care resources and efforts to enhance quality and reduce disparities in care across the system. Key gaps in care identified included lack of standardized glucose management policies, lack of standardized training of health care professionals in inpatient diabetes management, and lack of access to automated data collection and analysis. These results were used to gain resources to support collaborative diabetes health system initiatives and to successfully obtain federal research funding to develop and pilot a pragmatic diabetes educational intervention. At a health system level, the summary format of this gap analysis tool is an effective method to clearly identify disparities in care to focus efforts and resources to improve care delivery. Copyright © 2016 The Joint Commission. Published by Elsevier Inc. All rights reserved.

A 2-year study of Gram stain competency assessment in 40 clinical laboratories.

PubMed

Goodyear, Nancy; Kim, Sara; Reeves, Mary; Astion, Michael L

2006-01-01

We used a computer-based competency assessment tool for Gram stain interpretation to assess the performance of 278 laboratory staff from 40 laboratories on 40 multiple-choice questions. We report test reliability, mean scores, median, item difficulty, discrimination, and analysis of the highest- and lowest-scoring questions. The questions were reliable (KR-20 coefficient, 0.80). Overall mean score was 88% (range, 63%-98%). When categorized by cell type, the means were host cells, 93%; other cells (eg, yeast), 92%; gram-positive, 90%; and gram-negative, 88%. When categorized by type of interpretation, the means were other (eg, underdecolorization), 92%; identify by structure (eg, bacterial morphologic features), 91%; and identify by name (eg, genus and species), 87%. Of the 6 highest-scoring questions (mean scores, > or = 99%) 5 were identify by structure and 1 was identify by name. Of the 6 lowest-scoring questions (mean scores, < 75%) 5 were gram-negative and 1 was host cells. By type of interpretation, 2 were identify by structure and 4 were identify by name. Computer-based Gram stain competency assessment examinations are reliable. Our analysis helps laboratories identify areas for continuing education in Gram stain interpretation and will direct future revisions of the tests.

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.

An Actor-Network Theory Analysis of Policy Innovation for Smoke-Free Places: Understanding Change in Complex Systems

PubMed Central

Borland, Ron; Coghill, Ken

2010-01-01

Complex, transnational issues like the tobacco epidemic are major challenges that defy analysis and management by conventional methods, as are other public health issues, such as those associated with global food distribution and climate change. We examined the evolution of indoor smoke-free regulations, a tobacco control policy innovation, and identified the key attributes of those jurisdictions that successfully pursued this innovation and those that to date have not. In doing so, we employed the actor-network theory, a comprehensive framework for the analysis of fundamental system change. Through our analysis, we identified approaches to help overcome some systemic barriers to the solution of the tobacco problem and comment on other complex transnational problems. PMID:20466949

Comparison of dislocation content measured with transmission electron microscopy and micro-Laue diffraction based streak analysis

DOE PAGES

Zhang, C.; Balachandran, S.; Eisenlohr, P.; ...

2017-10-04

The subsurface dislocation content in a Ti-5Al-2.5Sn (wt%) uniaxial tension sample deformed at ambient temperature was characterized by peak streak analysis of micro-Laue diffraction patterns collected non-destructively by differential aperture X-raymicroscopy, and with focused ion beam transmission electron microscopy of material in the same volume. This comparison reveals that micro-Laue diffraction streak analysis based on an edge dislocation assumption can accurately identify the dominant dislocation slip system history (Burgers vector and plane observed by TEM), despite the fact that dislocations have predominantly screw character. As a result, other dislocations identified by TEM were not convincingly discernible from the peak streakmore » analysis.« less

Co-authorship network analysis in health research: method and potential use.

PubMed

Fonseca, Bruna de Paula Fonseca E; Sampaio, Ricardo Barros; Fonseca, Marcus Vinicius de Araújo; Zicker, Fabio

2016-04-30

Scientific collaboration networks are a hallmark of contemporary academic research. Researchers are no longer independent players, but members of teams that bring together complementary skills and multidisciplinary approaches around common goals. Social network analysis and co-authorship networks are increasingly used as powerful tools to assess collaboration trends and to identify leading scientists and organizations. The analysis reveals the social structure of the networks by identifying actors and their connections. This article reviews the method and potential applications of co-authorship network analysis in health. The basic steps for conducting co-authorship studies in health research are described and common network metrics are presented. The application of the method is exemplified by an overview of the global research network for Chikungunya virus vaccines.

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

Supplemental Hazard Analysis and Risk Assessment - Hydrotreater

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

Lowry, Peter P.; Wagner, Katie A.

A supplemental hazard analysis was conducted and quantitative risk assessment performed in response to an independent review comment received by the Pacific Northwest National Laboratory (PNNL) from the U.S. Department of Energy Pacific Northwest Field Office (PNSO) against the Hydrotreater/Distillation Column Hazard Analysis Report issued in April 2013. The supplemental analysis used the hazardous conditions documented by the previous April 2013 report as a basis. The conditions were screened and grouped for the purpose of identifying whether additional prudent, practical hazard controls could be identified, using a quantitative risk evaluation to assess the adequacy of the controls and establish amore » lower level of concern for the likelihood of potential serious accidents. Calculations were performed to support conclusions where necessary.« less

An actor-network theory analysis of policy innovation for smoke-free places: understanding change in complex systems.

PubMed

Young, David; Borland, Ron; Coghill, Ken

2010-07-01

Complex, transnational issues like the tobacco epidemic are major challenges that defy analysis and management by conventional methods, as are other public health issues, such as those associated with global food distribution and climate change. We examined the evolution of indoor smoke-free regulations, a tobacco control policy innovation, and identified the key attributes of those jurisdictions that successfully pursued this innovation and those that to date have not. In doing so, we employed the actor-network theory, a comprehensive framework for the analysis of fundamental system change. Through our analysis, we identified approaches to help overcome some systemic barriers to the solution of the tobacco problem and comment on other complex transnational problems.

Comparison of dislocation content measured with transmission electron microscopy and micro-Laue diffraction based streak analysis

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

Zhang, C.; Balachandran, S.; Eisenlohr, P.

The subsurface dislocation content in a Ti-5Al-2.5Sn (wt%) uniaxial tension sample deformed at ambient temperature was characterized by peak streak analysis of micro-Laue diffraction patterns collected non-destructively by differential aperture X-raymicroscopy, and with focused ion beam transmission electron microscopy of material in the same volume. This comparison reveals that micro-Laue diffraction streak analysis based on an edge dislocation assumption can accurately identify the dominant dislocation slip system history (Burgers vector and plane observed by TEM), despite the fact that dislocations have predominantly screw character. As a result, other dislocations identified by TEM were not convincingly discernible from the peak streakmore » analysis.« less

School Foodservice Personnel's Struggle with Using Labels to Identify Whole-Grain Foods

ERIC Educational Resources Information Center

Chu, Yen Li; Orsted, Mary; Marquart, Len; Reicks, Marla

2012-01-01

Objective: To describe how school foodservice personnel use current labeling methods to identify whole-grain products and the influence on purchasing for school meals. Methods: Focus groups explored labeling methods to identify whole-grain products and barriers to incorporating whole-grain foods in school meals. Qualitative analysis procedures and…

Identification and Assessment of Taiwanese Children's Conceptions of Learning Mathematics

ERIC Educational Resources Information Center

Chiu, Mei-Shiu

2012-01-01

The aim of the present study was to identify children's conceptions of learning mathematics and to assess the identified conceptions. Children's conceptions are identified by interviewing 73 grade 5 students in Taiwan. The interviews are analyzed using qualitative data analysis methods, which results in a structure of 5 major conceptions, each…

Identifying and Assessing Self-Images in Drawings by Delinquent Adolescents (in 2 Parts).

ERIC Educational Resources Information Center

Silver, Rawley; Ellison, JoAnne

1995-01-01

Examines assumption that art therapists can objectively identify self-images in drawings by troubled adolescents without talking to these youth. Findings suggest that discussion, though preferable, is not required for identifying self-images. Analysis of adolescents' drawings indicates that structured art assessment can be useful in evaluating…

Examining the Psychometric Properties of the Identify as a Professional Social Worker Subscale

ERIC Educational Resources Information Center

Farmer, Antoinette Y.

2017-01-01

The purpose of this study was to examine the psychometric properties of the Identify as a Professional Social Worker Subscale, which assessed the Council on Social Work Education--prescribed competency "identify as a professional social worker and conduct oneself accordingly." The results of confirmatory factory analysis indicated that…

A Systematic Approach to Determining the Identifiability of Multistage Carcinogenesis Models.

PubMed

Brouwer, Andrew F; Meza, Rafael; Eisenberg, Marisa C

2017-07-01

Multistage clonal expansion (MSCE) models of carcinogenesis are continuous-time Markov process models often used to relate cancer incidence to biological mechanism. Identifiability analysis determines what model parameter combinations can, theoretically, be estimated from given data. We use a systematic approach, based on differential algebra methods traditionally used for deterministic ordinary differential equation (ODE) models, to determine identifiable combinations for a generalized subclass of MSCE models with any number of preinitation stages and one clonal expansion. Additionally, we determine the identifiable combinations of the generalized MSCE model with up to four clonal expansion stages, and conjecture the results for any number of clonal expansion stages. The results improve upon previous work in a number of ways and provide a framework to find the identifiable combinations for further variations on the MSCE models. Finally, our approach, which takes advantage of the Kolmogorov backward equations for the probability generating functions of the Markov process, demonstrates that identifiability methods used in engineering and mathematics for systems of ODEs can be applied to continuous-time Markov processes. © 2016 Society for Risk Analysis.

Evidence of recombination and positive selection in cetacean papillomaviruses.

PubMed

Robles-Sikisaka, Refugio; Rivera, Rebecca; Nollens, Hendrik H; St Leger, Judy; Durden, Wendy N; Stolen, Megan; Burchell, Jennifer; Wellehan, James F X

2012-06-05

Papillomaviruses (PVs) are small DNA viruses that have been associated with increased epithelial proliferation. Over one hundred PV types have been identified in humans; however, only three have been identified in bottlenose dolphins (Tursiops truncatus) to date. Using rolling circle amplification and degenerate PCR, we identified four novel PV genomes of bottlenose dolphins. TtPV4, TtPV5 and TtPV6 were identified in genital lesions while TtPV7 was identified in normal genital mucosa. Bayesian analysis of the full-length L1 genes found that TtPV4 and TtPV7 group within the Upsilonpapillomavirus genus while TtPV5 and TtPV6 group with Omikronpapillomavirus. However, analysis of the E1 gene did not distinguish these genera, implying that these genes may not share a common history, consistent with recombination. Recombination analyses identified several probable events. Signals of positive selection were found mostly in the E1 and E2 genes. Recombination and diversifying selection pressures constitute important driving forces of cetacean PV evolution. Copyright © 2012 Elsevier Inc. All rights reserved.

Applying Multivariate Adaptive Splines to Identify Genes With Expressions Varying After Diagnosis in Microarray Experiments.

PubMed

Duan, Fenghai; Xu, Ye

2017-01-01

To analyze a microarray experiment to identify the genes with expressions varying after the diagnosis of breast cancer. A total of 44 928 probe sets in an Affymetrix microarray data publicly available on Gene Expression Omnibus from 249 patients with breast cancer were analyzed by the nonparametric multivariate adaptive splines. Then, the identified genes with turning points were grouped by K-means clustering, and their network relationship was subsequently analyzed by the Ingenuity Pathway Analysis. In total, 1640 probe sets (genes) were reliably identified to have turning points along with the age at diagnosis in their expression profiling, of which 927 expressed lower after turning points and 713 expressed higher after the turning points. K-means clustered them into 3 groups with turning points centering at 54, 62.5, and 72, respectively. The pathway analysis showed that the identified genes were actively involved in various cancer-related functions or networks. In this article, we applied the nonparametric multivariate adaptive splines method to a publicly available gene expression data and successfully identified genes with expressions varying before and after breast cancer diagnosis.

Evidence of recombination and positive selection in cetacean papillomaviruses

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

Robles-Sikisaka, Refugio, E-mail: refugio.robles1@gmail.com; Rivera, Rebecca, E-mail: RRivera@hswri.org; Nollens, Hendrik H., E-mail: Hendrik.Nollens@SeaWorld.com

2012-06-05

Papillomaviruses (PVs) are small DNA viruses that have been associated with increased epithelial proliferation. Over one hundred PV types have been identified in humans; however, only three have been identified in bottlenose dolphins (Tursiops truncatus) to date. Using rolling circle amplification and degenerate PCR, we identified four novel PV genomes of bottlenose dolphins. TtPV4, TtPV5 and TtPV6 were identified in genital lesions while TtPV7 was identified in normal genital mucosa. Bayesian analysis of the full-length L1 genes found that TtPV4 and TtPV7 group within the Upsilonpapillomavirus genus while TtPV5 and TtPV6 group with Omikronpapillomavirus. However, analysis of the E1 genemore » did not distinguish these genera, implying that these genes may not share a common history, consistent with recombination. Recombination analyses identified several probable events. Signals of positive selection were found mostly in the E1 and E2 genes. Recombination and diversifying selection pressures constitute important driving forces of cetacean PV evolution.« less