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.

Singapore Primary Students' Pursuit of Multiple Achievement Goals: A Latent Profile Analysis

ERIC Educational Resources Information Center

Ning, Hoi Kwan

2018-01-01

Based on measures of approach and avoidance mastery and performance goals delineated in the 2 × 2 achievement goal framework, this study utilized a person-centered approach to examine Singapore primary students' (N = 819) multiple goals pursuit in the general school context. Latent profile analysis identified six types of students with distinct…

The Theory of Multiple Intelligences.

ERIC Educational Resources Information Center

Gardner, Howard

1987-01-01

The multiple intelligence theory is based on cultural contexts, biological analysis, developmental theories, and a vertical theory of faculties. Seven intelligences are identified: linguistic, logical mathematical, musical, spatial, bodily kinesthetic, interpersonal, and intrapersonal. The theory's educational implications are described,…

Multiple Primary Cancer Monograph

Cancer.gov

To identify groups of cancer survivors that are at increased risk for multiple primary cancers, investigators led an effort to provide the first comprehensive population-based analysis of the risk of subsequent cancer in the U.S., resulting in a monograph.

Time-Series Analysis: Assessing the Effects of Multiple Educational Interventions in a Small-Enrollment Course

NASA Astrophysics Data System (ADS)

Warren, Aaron R.

2009-11-01

Time-series designs are an alternative to pretest-posttest methods that are able to identify and measure the impacts of multiple educational interventions, even for small student populations. Here, we use an instrument employing standard multiple-choice conceptual questions to collect data from students at regular intervals. The questions are modified by asking students to distribute 100 Confidence Points among the options in order to indicate the perceived likelihood of each answer option being the correct one. Tracking the class-averaged ratings for each option produces a set of time-series. ARIMA (autoregressive integrated moving average) analysis is then used to test for, and measure, changes in each series. In particular, it is possible to discern which educational interventions produce significant changes in class performance. Cluster analysis can also identify groups of students whose ratings evolve in similar ways. A brief overview of our methods and an example are presented.

An Analysis of Student Affairs Professionals' Management of Role Conflict and Multiple Roles in Relation to Work/Life Balance

ERIC Educational Resources Information Center

Mayo, Nicole Lepone

2013-01-01

The purpose of this inquiry is to study how student affairs professionals manage role conflict in relation to work/life balance based on the challenging culture of the field. The underlying goals are to identify the barriers or challenges of managing multiple roles as a student affairs administrator and identify strategies to assist employees in…

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…

Multiple Trajectories of Successful Aging of Older and Younger Cohorts

ERIC Educational Resources Information Center

Hsu, Hui-Chuan; Jones, Bobby L.

2012-01-01

Purpose: The purpose of this study was to apply group-based trajectory analysis to identify multiple successful aging trajectories by multiple indicators and to examine the factors related to successful aging among the elderly population in Taiwan. Design and Methods: Nation-representative longitudinal data collected from 1993 to 2007 and…

Maltreatment histories of foster youth exiting out-of-home care through emancipation: a latent class analysis.

PubMed

Havlicek, Judy

2014-01-01

Little is known about maltreatment among foster youth transitioning to adulthood. Multiple entries into out-of-home care and unsuccessful attempts at reunification may nevertheless reflect extended exposure to chronic maltreatment and multiple types of victimization. This study used administrative data from the Illinois Department of Children and Family Services to identify all unduplicated allegations of maltreatment in a cohort of 801 foster youth transitioning to adulthood in the state of Illinois. A latent variable modeling approach generated profiles of maltreatment based on substantiated and unsubstantiated reports of maltreatment taken from state administrative data. Four indicators of maltreatment were included in the latent class analysis: multiple types of maltreatment, predominant type of maltreatment, chronicity, and number of different perpetrators. The analysis identified four subpopulations of foster youth in relation to maltreatment. Study findings highlight the heterogeneity of maltreatment in the lives of foster youth transitioning to adulthood and draw attention to a need to raise awareness among service providers to screen for chronic maltreatment and multiple types of victimization. © The Author(s) 2014.

Features of Coping with Disease in Iranian Multiple Sclerosis Patients: a Qualitative Study.

PubMed

Dehghani, Ali; Dehghan Nayeri, Nahid; Ebadi, Abbas

2018-03-01

Introduction: Coping with disease is of the main components improving the quality of life in multiple sclerosis patients. Identifying the characteristics of this concept is based on the experiences of patients. Using qualitative research is essential to improve the quality of life. This study was conducted to explore the features of coping with the disease in patients with multiple sclerosis. Method: In this conventional content analysis study, eleven multiple sclerosis patients from Iran MS Society in Tehran (Iran) participated. Purposive sampling was used to select participants. Data were gathered using semi structured interviews. To analyze data, a conventional content analysis approach was used to identify meaning units and to make codes and categories. Results: Results showed that features of coping with disease in multiple sclerosis patients consists of (a) accepting the current situation, (b) maintenance and development of human interactions, (c) self-regulation and (d) self-efficacy. Each of these categories is composed of sub-categories and codes that showed the perception and experience of patients about the coping with disease. Conclusion: Accordingly, a unique set of features regarding features of coping with the disease were identified among the patients with multiple sclerosis. Therefore, working to ensure the emergence of, and subsequent reinforcement of these features in MS patients can be an important step in improving the adjustment and quality of their lives.

Joint source based analysis of multiple brain structures in studying major depressive disorder

NASA Astrophysics Data System (ADS)

Ramezani, Mahdi; Rasoulian, Abtin; Hollenstein, Tom; Harkness, Kate; Johnsrude, Ingrid; Abolmaesumi, Purang

2014-03-01

We propose a joint Source-Based Analysis (jSBA) framework to identify brain structural variations in patients with Major Depressive Disorder (MDD). In this framework, features representing position, orientation and size (i.e. pose), shape, and local tissue composition are extracted. Subsequently, simultaneous analysis of these features within a joint analysis method is performed to generate the basis sources that show signi cant di erences between subjects with MDD and those in healthy control. Moreover, in a cross-validation leave- one-out experiment, we use a Fisher Linear Discriminant (FLD) classi er to identify individuals within the MDD group. Results show that we can classify the MDD subjects with an accuracy of 76% solely based on the information gathered from the joint analysis of pose, shape, and tissue composition in multiple brain structures.

Tensor decomposition-based and principal-component-analysis-based unsupervised feature extraction applied to the gene expression and methylation profiles in the brains of social insects with multiple castes.

PubMed

Taguchi, Y-H

2018-05-08

Even though coexistence of multiple phenotypes sharing the same genomic background is interesting, it remains incompletely understood. Epigenomic profiles may represent key factors, with unknown contributions to the development of multiple phenotypes, and social-insect castes are a good model for elucidation of the underlying mechanisms. Nonetheless, previous studies have failed to identify genes associated with aberrant gene expression and methylation profiles because of the lack of suitable methodology that can address this problem properly. A recently proposed principal component analysis (PCA)-based and tensor decomposition (TD)-based unsupervised feature extraction (FE) can solve this problem because these two approaches can deal with gene expression and methylation profiles even when a small number of samples is available. PCA-based and TD-based unsupervised FE methods were applied to the analysis of gene expression and methylation profiles in the brains of two social insects, Polistes canadensis and Dinoponera quadriceps. Genes associated with differential expression and methylation between castes were identified, and analysis of enrichment of Gene Ontology terms confirmed reliability of the obtained sets of genes from the biological standpoint. Biologically relevant genes, shown to be associated with significant differential gene expression and methylation between castes, were identified here for the first time. The identification of these genes may help understand the mechanisms underlying epigenetic control of development of multiple phenotypes under the same genomic conditions.

Network-Assisted Investigation of Combined Causal Signals from Genome-Wide Association Studies in Schizophrenia

PubMed Central

Jia, Peilin; Wang, Lily; Fanous, Ayman H.; Pato, Carlos N.; Edwards, Todd L.; Zhao, Zhongming

2012-01-01

With the recent success of genome-wide association studies (GWAS), a wealth of association data has been accomplished for more than 200 complex diseases/traits, proposing a strong demand for data integration and interpretation. A combinatory analysis of multiple GWAS datasets, or an integrative analysis of GWAS data and other high-throughput data, has been particularly promising. In this study, we proposed an integrative analysis framework of multiple GWAS datasets by overlaying association signals onto the protein-protein interaction network, and demonstrated it using schizophrenia datasets. Building on a dense module search algorithm, we first searched for significantly enriched subnetworks for schizophrenia in each single GWAS dataset and then implemented a discovery-evaluation strategy to identify module genes with consistent association signals. We validated the module genes in an independent dataset, and also examined them through meta-analysis of the related SNPs using multiple GWAS datasets. As a result, we identified 205 module genes with a joint effect significantly associated with schizophrenia; these module genes included a number of well-studied candidate genes such as DISC1, GNA12, GNA13, GNAI1, GPR17, and GRIN2B. Further functional analysis suggested these genes are involved in neuronal related processes. Additionally, meta-analysis found that 18 SNPs in 9 module genes had P meta<1×10−4, including the gene HLA-DQA1 located in the MHC region on chromosome 6, which was reported in previous studies using the largest cohort of schizophrenia patients to date. These results demonstrated our bi-directional network-based strategy is efficient for identifying disease-associated genes with modest signals in GWAS datasets. This approach can be applied to any other complex diseases/traits where multiple GWAS datasets are available. PMID:22792057

Causal mediation analysis with multiple mediators in the presence of treatment noncompliance.

PubMed

Park, Soojin; Kürüm, Esra

2018-05-20

Randomized experiments are often complicated because of treatment noncompliance. This challenge prevents researchers from identifying the mediated portion of the intention-to-treated (ITT) effect, which is the effect of the assigned treatment that is attributed to a mediator. One solution suggests identifying the mediated ITT effect on the basis of the average causal mediation effect among compliers when there is a single mediator. However, considering the complex nature of the mediating mechanisms, it is natural to assume that there are multiple variables that mediate through the causal path. Motivated by an empirical analysis of a data set collected in a randomized interventional study, we develop a method to estimate the mediated portion of the ITT effect when both multiple dependent mediators and treatment noncompliance exist. This enables researchers to make an informed decision on how to strengthen the intervention effect by identifying relevant mediators despite treatment noncompliance. We propose a nonparametric estimation procedure and provide a sensitivity analysis for key assumptions. We conduct a Monte Carlo simulation study to assess the finite sample performance of the proposed approach. The proposed method is illustrated by an empirical analysis of JOBS II data, in which a job training intervention was used to prevent mental health deterioration among unemployed individuals. Copyright © 2018 John Wiley & Sons, Ltd.

Integrative prescreening in analysis of multiple cancer genomic studies

PubMed Central

2012-01-01

Background In high throughput cancer genomic studies, results from the analysis of single datasets often suffer from a lack of reproducibility because of small sample sizes. Integrative analysis can effectively pool and analyze multiple datasets and provides a cost effective way to improve reproducibility. In integrative analysis, simultaneously analyzing all genes profiled may incur high computational cost. A computationally affordable remedy is prescreening, which fits marginal models, can be conducted in a parallel manner, and has low computational cost. Results An integrative prescreening approach is developed for the analysis of multiple cancer genomic datasets. Simulation shows that the proposed integrative prescreening has better performance than alternatives, particularly including prescreening with individual datasets, an intensity approach and meta-analysis. We also analyze multiple microarray gene profiling studies on liver and pancreatic cancers using the proposed approach. Conclusions The proposed integrative prescreening provides an effective way to reduce the dimensionality in cancer genomic studies. It can be coupled with existing analysis methods to identify cancer markers. PMID:22799431

Motivational and Volitional Variables Associated with Stages of Change for Exercise in Multiple Sclerosis: A Multiple Discriminant Analysis

ERIC Educational Resources Information Center

Chiu, Chung-Yi; Fitzgerald, Sandra D.; Strand, David M.; Muller, Veronica; Brooks, Jessica; Chan, Fong

2012-01-01

The main objective of this study was to determine whether motivational and volitional variables identified in the health action process approach (HAPA) model can be used to successfully differentiate people with multiple sclerosis (MS) in different stages of change for exercise and physical activity. Ex-post-facto design using multiple…

Screening of differentially expressed genes between multiple trauma patients with and without sepsis.

PubMed

Ji, S C; Pan, Y T; Lu, Q Y; Sun, Z Y; Liu, Y Z

2014-03-17

The purpose of this study was to identify critical genes associated with septic multiple trauma by comparing peripheral whole blood samples from multiple trauma patients with and without sepsis. A microarray data set was downloaded from the Gene Expression Omnibus (GEO) database. This data set included 70 samples, 36 from multiple trauma patients with sepsis and 34 from multiple trauma patients without sepsis (as a control set). The data were preprocessed, and differentially expressed genes (DEGs) were then screened for using packages of the R language. Functional analysis of DEGs was performed with DAVID. Interaction networks were then established for the most up- and down-regulated genes using HitPredict. Pathway-enrichment analysis was conducted for genes in the networks using WebGestalt. Fifty-eight DEGs were identified. The expression levels of PLAU (down-regulated) and MMP8 (up-regulated) presented the largest fold-changes, and interaction networks were established for these genes. Further analysis revealed that PLAT (plasminogen activator, tissue) and SERPINF2 (serpin peptidase inhibitor, clade F, member 2), which interact with PLAU, play important roles in the pathway of the component and coagulation cascade. We hypothesize that PLAU is a major regulator of the component and coagulation cascade, and down-regulation of PLAU results in dysfunction of the pathway, causing sepsis.

Supratentorial lesions contribute to trigeminal neuralgia in multiple sclerosis.

PubMed

Fröhlich, Kilian; Winder, Klemens; Linker, Ralf A; Engelhorn, Tobias; Dörfler, Arnd; Lee, De-Hyung; Hilz, Max J; Schwab, Stefan; Seifert, Frank

2018-06-01

Background It has been proposed that multiple sclerosis lesions afflicting the pontine trigeminal afferents contribute to trigeminal neuralgia in multiple sclerosis. So far, there are no imaging studies that have evaluated interactions between supratentorial lesions and trigeminal neuralgia in multiple sclerosis patients. Methods We conducted a retrospective study and sought multiple sclerosis patients with trigeminal neuralgia and controls in a local database. Multiple sclerosis lesions were manually outlined and transformed into stereotaxic space. We determined the lesion overlap and performed a voxel-wise subtraction analysis. Secondly, we conducted a voxel-wise non-parametric analysis using the Liebermeister test. Results From 12,210 multiple sclerosis patient records screened, we identified 41 patients with trigeminal neuralgia. The voxel-wise subtraction analysis yielded associations between trigeminal neuralgia and multiple sclerosis lesions in the pontine trigeminal afferents, as well as larger supratentorial lesion clusters in the contralateral insula and hippocampus. The non-parametric statistical analysis using the Liebermeister test yielded similar areas to be associated with multiple sclerosis-related trigeminal neuralgia. Conclusions Our study confirms previous data on associations between multiple sclerosis-related trigeminal neuralgia and pontine lesions, and showed for the first time an association with lesions in the insular region, a region involved in pain processing and endogenous pain modulation.

Partial genome assembly for a candidate division OP11 single cell from an anoxic spring (Zodletone Spring, Oklahoma).

PubMed

Youssef, Noha H; Blainey, Paul C; Quake, Stephen R; Elshahed, Mostafa S

2011-11-01

Members of candidate division OP11 are widely distributed in terrestrial and marine ecosystems, yet little information regarding their metabolic capabilities and ecological role within such habitats is currently available. Here, we report on the microfluidic isolation, multiple-displacement-amplification, pyrosequencing, and genomic analysis of a single cell (ZG1) belonging to candidate division OP11. Genome analysis of the ∼270-kb partial genome assembly obtained showed that it had no particular similarity to a specific phylum. Four hundred twenty-three open reading frames were identified, 46% of which had no function prediction. In-depth analysis revealed a heterotrophic lifestyle, with genes encoding endoglucanase, amylopullulanase, and laccase enzymes, suggesting a capacity for utilization of cellulose, starch, and, potentially, lignin, respectively. Genes encoding several glycolysis enzymes as well as formate utilization were identified, but no evidence for an electron transport chain was found. The presence of genes encoding various components of lipopolysaccharide biosynthesis indicates a Gram-negative bacterial cell wall. The partial genome also provides evidence for antibiotic resistance (β-lactamase, aminoglycoside phosphotransferase), as well as antibiotic production (bacteriocin) and extracellular bactericidal peptidases. Multiple mechanisms for stress response were identified, as were elements of type I and type IV secretion systems. Finally, housekeeping genes identified within the partial genome were used to demonstrate the OP11 affiliation of multiple hitherto unclassified genomic fragments from multiple database-deposited metagenomic data sets. These results provide the first glimpse into the lifestyle of a member of a ubiquitous, yet poorly understood bacterial candidate division.

Fine-mapping identifies multiple prostate cancer risk loci at 5p15, one of which associates with TERT expression

PubMed Central

Kote-Jarai, Zsofia; Saunders, Edward J.; Leongamornlert, Daniel A.; Tymrakiewicz, Malgorzata; Dadaev, Tokhir; Jugurnauth-Little, Sarah; Ross-Adams, Helen; Al Olama, Ali Amin; Benlloch, Sara; Halim, Silvia; Russel, Roslin; Dunning, Alison M.; Luccarini, Craig; Dennis, Joe; Neal, David E.; Hamdy, Freddie C.; Donovan, Jenny L.; Muir, Ken; Giles, Graham G.; Severi, Gianluca; Wiklund, Fredrik; Gronberg, Henrik; Haiman, Christopher A.; Schumacher, Fredrick; Henderson, Brian E.; Le Marchand, Loic; Lindstrom, Sara; Kraft, Peter; Hunter, David J.; Gapstur, Susan; Chanock, Stephen; Berndt, Sonja I.; Albanes, Demetrius; Andriole, Gerald; Schleutker, Johanna; Weischer, Maren; Canzian, Federico; Riboli, Elio; Key, Tim J.; Travis, Ruth C.; Campa, Daniele; Ingles, Sue A.; John, Esther M.; Hayes, Richard B.; Pharoah, Paul; Khaw, Kay-Tee; Stanford, Janet L.; Ostrander, Elaine A.; Signorello, Lisa B.; Thibodeau, Stephen N.; Schaid, Dan; Maier, Christiane; Vogel, Walther; Kibel, Adam S.; Cybulski, Cezary; Lubinski, Jan; Cannon-Albright, Lisa; Brenner, Hermann; Park, Jong Y.; Kaneva, Radka; Batra, Jyotsna; Spurdle, Amanda; Clements, Judith A.; Teixeira, Manuel R.; Govindasami, Koveela; Guy, Michelle; Wilkinson, Rosemary A.; Sawyer, Emma J.; Morgan, Angela; Dicks, Ed; Baynes, Caroline; Conroy, Don; Bojesen, Stig E.; Kaaks, Rudolf; Vincent, Daniel; Bacot, François; Tessier, Daniel C.; Easton, Douglas F.; Eeles, Rosalind A.

2013-01-01

Associations between single nucleotide polymorphisms (SNPs) at 5p15 and multiple cancer types have been reported. We have previously shown evidence for a strong association between prostate cancer (PrCa) risk and rs2242652 at 5p15, intronic in the telomerase reverse transcriptase (TERT) gene that encodes TERT. To comprehensively evaluate the association between genetic variation across this region and PrCa, we performed a fine-mapping analysis by genotyping 134 SNPs using a custom Illumina iSelect array or Sequenom MassArray iPlex, followed by imputation of 1094 SNPs in 22 301 PrCa cases and 22 320 controls in The PRACTICAL consortium. Multiple stepwise logistic regression analysis identified four signals in the promoter or intronic regions of TERT that independently associated with PrCa risk. Gene expression analysis of normal prostate tissue showed evidence that SNPs within one of these regions also associated with TERT expression, providing a potential mechanism for predisposition to disease. PMID:23535824

Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.

PubMed

Zhang, Futao; Xie, Dan; Liang, Meimei; Xiong, Momiao

2016-04-01

To date, most genetic analyses of phenotypes have focused on analyzing single traits or analyzing each phenotype independently. However, joint epistasis analysis of multiple complementary traits will increase statistical power and improve our understanding of the complicated genetic structure of the complex diseases. Despite their importance in uncovering the genetic structure of complex traits, the statistical methods for identifying epistasis in multiple phenotypes remains fundamentally unexplored. To fill this gap, we formulate a test for interaction between two genes in multiple quantitative trait analysis as a multiple functional regression (MFRG) in which the genotype functions (genetic variant profiles) are defined as a function of the genomic position of the genetic variants. We use large-scale simulations to calculate Type I error rates for testing interaction between two genes with multiple phenotypes and to compare the power with multivariate pairwise interaction analysis and single trait interaction analysis by a single variate functional regression model. To further evaluate performance, the MFRG for epistasis analysis is applied to five phenotypes of exome sequence data from the NHLBI's Exome Sequencing Project (ESP) to detect pleiotropic epistasis. A total of 267 pairs of genes that formed a genetic interaction network showed significant evidence of epistasis influencing five traits. The results demonstrate that the joint interaction analysis of multiple phenotypes has a much higher power to detect interaction than the interaction analysis of a single trait and may open a new direction to fully uncovering the genetic structure of multiple phenotypes.

Disease-specific molecular events in cortical multiple sclerosis lesions

PubMed Central

Wimmer, Isabella; Höftberger, Romana; Gerlach, Susanna; Haider, Lukas; Zrzavy, Tobias; Hametner, Simon; Mahad, Don; Binder, Christoph J.; Krumbholz, Markus; Bauer, Jan; Bradl, Monika

2013-01-01

Cortical lesions constitute an important part of multiple sclerosis pathology. Although inflammation appears to play a role in their formation, the mechanisms leading to demyelination and neurodegeneration are poorly understood. We aimed to identify some of these mechanisms by combining gene expression studies with neuropathological analysis. In our study, we showed that the combination of inflammation, plaque-like primary demyelination and neurodegeneration in the cortex is specific for multiple sclerosis and is not seen in other chronic inflammatory diseases mediated by CD8-positive T cells (Rasmussen’s encephalitis), B cells (B cell lymphoma) or complex chronic inflammation (tuberculous meningitis, luetic meningitis or chronic purulent meningitis). In addition, we performed genome-wide microarray analysis comparing micro-dissected active cortical multiple sclerosis lesions with those of tuberculous meningitis (inflammatory control), Alzheimer’s disease (neurodegenerative control) and with cortices of age-matched controls. More than 80% of the identified multiple sclerosis-specific genes were related to T cell-mediated inflammation, microglia activation, oxidative injury, DNA damage and repair, remyelination and regenerative processes. Finally, we confirmed by immunohistochemistry that oxidative damage in cortical multiple sclerosis lesions is associated with oligodendrocyte and neuronal injury, the latter also affecting axons and dendrites. Our study provides new insights into the complex mechanisms of neurodegeneration and regeneration in the cortex of patients with multiple sclerosis. PMID:23687122

Identifying Opportunities for Decision Support Systems in Support of Regional Resource Use Planning: An Approach Through Soft Systems Methodology.

PubMed

Zhu; Dale

2000-10-01

/ Regional resource use planning relies on key regional stakeholder groups using and having equitable access to appropriate social, economic, and environmental information and assessment tools. Decision support systems (DSS) can improve stakeholder access to such information and analysis tools. Regional resource use planning, however, is a complex process involving multiple issues, multiple assessment criteria, multiple stakeholders, and multiple values. There is a need for an approach to DSS development that can assist in understanding and modeling complex problem situations in regional resource use so that areas where DSSs could provide effective support can be identified, and the user requirements can be well established. This paper presents an approach based on the soft systems methodology for identifying DSS opportunities for regional resource use planning, taking the Central Highlands Region of Queensland, Australia, as a case study.

Multiple perspective vulnerability analysis of the power network

NASA Astrophysics Data System (ADS)

Wang, Shuliang; Zhang, Jianhua; Duan, Na

2018-02-01

To understand the vulnerability of the power network from multiple perspectives, multi-angle and multi-dimensional vulnerability analysis as well as community based vulnerability analysis are proposed in this paper. Taking into account of central China power grid as an example, correlation analysis of different vulnerability models is discussed. Then, vulnerabilities produced by different vulnerability metrics under the given vulnerability models and failure scenarios are analyzed. At last, applying the community detecting approach, critical areas of central China power grid are identified, Vulnerable and robust communities on both topological and functional perspective are acquired and analyzed. The approach introduced in this paper can be used to help decision makers develop optimal protection strategies. It will be also useful to give a multiple vulnerability analysis of the other infrastructure systems.

Computerized multiple image analysis on mammograms: performance improvement of nipple identification for registration of multiple views using texture convergence analyses

NASA Astrophysics Data System (ADS)

Zhou, Chuan; Chan, Heang-Ping; Sahiner, Berkman; Hadjiiski, Lubomir M.; Paramagul, Chintana

2004-05-01

Automated registration of multiple mammograms for CAD depends on accurate nipple identification. We developed two new image analysis techniques based on geometric and texture convergence analyses to improve the performance of our previously developed nipple identification method. A gradient-based algorithm is used to automatically track the breast boundary. The nipple search region along the boundary is then defined by geometric convergence analysis of the breast shape. Three nipple candidates are identified by detecting the changes along the gray level profiles inside and outside the boundary and the changes in the boundary direction. A texture orientation-field analysis method is developed to estimate the fourth nipple candidate based on the convergence of the tissue texture pattern towards the nipple. The final nipple location is determined from the four nipple candidates by a confidence analysis. Our training and test data sets consisted of 419 and 368 randomly selected mammograms, respectively. The nipple location identified on each image by an experienced radiologist was used as the ground truth. For 118 of the training and 70 of the test images, the radiologist could not positively identify the nipple, but provided an estimate of its location. These were referred to as invisible nipple images. In the training data set, 89.37% (269/301) of the visible nipples and 81.36% (96/118) of the invisible nipples could be detected within 1 cm of the truth. In the test data set, 92.28% (275/298) of the visible nipples and 67.14% (47/70) of the invisible nipples were identified within 1 cm of the truth. In comparison, our previous nipple identification method without using the two convergence analysis techniques detected 82.39% (248/301), 77.12% (91/118), 89.93% (268/298) and 54.29% (38/70) of the nipples within 1 cm of the truth for the visible and invisible nipples in the training and test sets, respectively. The results indicate that the nipple on mammograms can be detected accurately. This will be an important step towards automatic multiple image analysis for CAD techniques.

Missing data treatments matter: an analysis of multiple imputation for anterior cervical discectomy and fusion procedures.

PubMed

Ondeck, Nathaniel T; Fu, Michael C; Skrip, Laura A; McLynn, Ryan P; Cui, Jonathan J; Basques, Bryce A; Albert, Todd J; Grauer, Jonathan N

2018-04-09

The presence of missing data is a limitation of large datasets, including the National Surgical Quality Improvement Program (NSQIP). In addressing this issue, most studies use complete case analysis, which excludes cases with missing data, thus potentially introducing selection bias. Multiple imputation, a statistically rigorous approach that approximates missing data and preserves sample size, may be an improvement over complete case analysis. The present study aims to evaluate the impact of using multiple imputation in comparison with complete case analysis for assessing the associations between preoperative laboratory values and adverse outcomes following anterior cervical discectomy and fusion (ACDF) procedures. This is a retrospective review of prospectively collected data. Patients undergoing one-level ACDF were identified in NSQIP 2012-2015. Perioperative adverse outcome variables assessed included the occurrence of any adverse event, severe adverse events, and hospital readmission. Missing preoperative albumin and hematocrit values were handled using complete case analysis and multiple imputation. These preoperative laboratory levels were then tested for associations with 30-day postoperative outcomes using logistic regression. A total of 11,999 patients were included. Of this cohort, 63.5% of patients had missing preoperative albumin and 9.9% had missing preoperative hematocrit. When using complete case analysis, only 4,311 patients were studied. The removed patients were significantly younger, healthier, of a common body mass index, and male. Logistic regression analysis failed to identify either preoperative hypoalbuminemia or preoperative anemia as significantly associated with adverse outcomes. When employing multiple imputation, all 11,999 patients were included. Preoperative hypoalbuminemia was significantly associated with the occurrence of any adverse event and severe adverse events. Preoperative anemia was significantly associated with the occurrence of any adverse event, severe adverse events, and hospital readmission. Multiple imputation is a rigorous statistical procedure that is being increasingly used to address missing values in large datasets. Using this technique for ACDF avoided the loss of cases that may have affected the representativeness and power of the study and led to different results than complete case analysis. Multiple imputation should be considered for future spine studies. Copyright © 2018 Elsevier Inc. All rights reserved.

Role of Snf5 Mutations in Schwannomatosis Pain

DTIC Science & Technology

2016-10-01

National Multiple Sclerosis Society • Name: • Fatima Banine • Project Role: • Staff Scientist • Researcher Identifier (e.g. ORCID ID...and the subsequent data analysis and validation assays (e.g. qPCR) • Funding Support: • National Multiple Sclerosis Society • Name: • Scott...40,000 individuals worldwide. The disease is characterized by multiple peripheral nerve tumors, called schwannomas, and a predisposition to other

An omnibus test for family-based association studies with multiple SNPs and multiple phenotypes.

PubMed

Lasky-Su, Jessica; Murphy, Amy; McQueen, Matthew B; Weiss, Scott; Lange, Christoph

2010-06-01

We propose an omnibus family-based association test (MFBAT) that can be applied to multiple markers and multiple phenotypes and that has only one degree of freedom. The proposed test statistic extends current FBAT methodology to incorporate multiple markers as well as multiple phenotypes. Using simulation studies, power estimates for the proposed methodology are compared with the standard methodologies. On the basis of these simulations, we find that MFBAT substantially outperforms other methods, including haplotypic approaches and doing multiple tests with single single-nucleotide polymorphisms (SNPs) and single phenotypes. The practical relevance of the approach is illustrated by an application to asthma in which SNP/phenotype combinations are identified and reach overall significance that would not have been identified using other approaches. This methodology is directly applicable to cases in which there are multiple SNPs, such as candidate gene studies, cases in which there are multiple phenotypes, such as expression data, and cases in which there are multiple phenotypes and genotypes, such as genome-wide association studies that incorporate expression profiles as phenotypes. This program is available in the PBAT analysis package.

Molar Functional Relations and Clinical Behavior Analysis: Implications for Assessment and Treatment

ERIC Educational Resources Information Center

Waltz, Thomas J.; Follette, William C.

2009-01-01

The experimental analysis of behavior has identified several molar functional relations that are highly relevant to clinical behavior analysis. These include matching, discounting, momentum, and variability. Matching provides a broader analysis of how multiple sources of reinforcement influence how individuals choose to allocate their time and…

Multisite-multivariable sensitivity analysis of distributed watershed models: enhancing the perceptions from computationally frugal methods

USDA-ARS?s Scientific Manuscript database

This paper assesses the impact of different likelihood functions in identifying sensitive parameters of the highly parameterized, spatially distributed Soil and Water Assessment Tool (SWAT) watershed model for multiple variables at multiple sites. The global one-factor-at-a-time (OAT) method of Morr...

Psychosocial and Cognitive Functioning of Children with Specific Profiles of Maltreatment

ERIC Educational Resources Information Center

Pears, Katherine C.; Kim, Hyoun K.; Fisher, Philip A.

2008-01-01

Objective: Up to 90% of child welfare system cases involve multiple types of maltreatment; however, studies have rarely incorporated multiple dimensions of maltreatment. The present study employed a latent profile analysis to identify naturally occurring subgroups of children who had experienced maltreatment. Methods: Reports of maltreatment…

Risk Profiles of Children Entering Residential Care: A Cluster Analysis

ERIC Educational Resources Information Center

Hagaman, Jessica L.; Trout, Alexandra L.; Chmelka, M. Beth; Thompson, Ronald W.; Reid, Robert

2010-01-01

Children in residential care are a heterogeneous population, presenting various combinations of risks. Existing studies on these children suggest high variability across multiple domains (e.g., academics, behavior). Given this heterogeneity, it is important to begin to identify the combinations and patterns of multiple risks, or risk profiles,…

Meta-analysis of correlated traits via summary statistics from GWASs with an application in hypertension.

PubMed

Zhu, Xiaofeng; Feng, Tao; Tayo, Bamidele O; Liang, Jingjing; Young, J Hunter; Franceschini, Nora; Smith, Jennifer A; Yanek, Lisa R; Sun, Yan V; Edwards, Todd L; Chen, Wei; Nalls, Mike; Fox, Ervin; Sale, Michele; Bottinger, Erwin; Rotimi, Charles; Liu, Yongmei; McKnight, Barbara; Liu, Kiang; Arnett, Donna K; Chakravati, Aravinda; Cooper, Richard S; Redline, Susan

2015-01-08

Genome-wide association studies (GWASs) have identified many genetic variants underlying complex traits. Many detected genetic loci harbor variants that associate with multiple-even distinct-traits. Most current analysis approaches focus on single traits, even though the final results from multiple traits are evaluated together. Such approaches miss the opportunity to systemically integrate the phenome-wide data available for genetic association analysis. In this study, we propose a general approach that can integrate association evidence from summary statistics of multiple traits, either correlated, independent, continuous, or binary traits, which might come from the same or different studies. We allow for trait heterogeneity effects. Population structure and cryptic relatedness can also be controlled. Our simulations suggest that the proposed method has improved statistical power over single-trait analysis in most of the cases we studied. We applied our method to the Continental Origins and Genetic Epidemiology Network (COGENT) African ancestry samples for three blood pressure traits and identified four loci (CHIC2, HOXA-EVX1, IGFBP1/IGFBP3, and CDH17; p < 5.0 × 10(-8)) associated with hypertension-related traits that were missed by a single-trait analysis in the original report. Six additional loci with suggestive association evidence (p < 5.0 × 10(-7)) were also observed, including CACNA1D and WNT3. Our study strongly suggests that analyzing multiple phenotypes can improve statistical power and that such analysis can be executed with the summary statistics from GWASs. Our method also provides a way to study a cross phenotype (CP) association by using summary statistics from GWASs of multiple phenotypes. Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

A Multiple Streams analysis of the decisions to fund gender-neutral HPV vaccination in Canada.

PubMed

Shapiro, Gilla K; Guichon, Juliet; Prue, Gillian; Perez, Samara; Rosberger, Zeev

2017-07-01

In Canada, the human papillomavirus (HPV) vaccine is licensed and recommended for females and males. Although all Canadian jurisdictions fund school-based HPV vaccine programs for girls, only six jurisdictions fund school-based HPV vaccination for boys. The research aimed to analyze the factors that underpin government decisions to fund HPV vaccine for boys using a theoretical policy model, Kingdon's Multiple Streams framework. This approach assesses policy development by examining three concurrent, but independent, streams that guide analysis: Problem Stream, Policy Stream, and Politics Stream. Analysis from the Problem Stream highlights that males are affected by HPV-related diseases and are involved in transmitting HPV infection to their sexual partners. Policy Stream analysis makes clear that while the inclusion of males in HPV vaccine programs is suitable, equitable, and acceptable; there is debate regarding cost-effectiveness. Politics Stream analysis identifies the perspectives of six different stakeholder groups and highlights the contribution of government officials at the provincial and territorial level. Kingdon's Multiple Streams framework helps clarify the opportunities and barriers for HPV vaccine policy change. This analysis identified that the interpretation of cost-effectiveness models and advocacy of stakeholders such as citizen-advocates and HPV-affected politicians have been particularly important in galvanizing policy change. Copyright © 2017 Elsevier Inc. All rights reserved.

On-chip wavelength multiplexed detection of cancer DNA biomarkers in blood

PubMed Central

Cai, H.; Stott, M. A.; Ozcelik, D.; Parks, J. W.; Hawkins, A. R.; Schmidt, H.

2016-01-01

We have developed an optofluidic analysis system that processes biomolecular samples starting from whole blood and then analyzes and identifies multiple targets on a silicon-based molecular detection platform. We demonstrate blood filtration, sample extraction, target enrichment, and fluorescent labeling using programmable microfluidic circuits. We detect and identify multiple targets using a spectral multiplexing technique based on wavelength-dependent multi-spot excitation on an antiresonant reflecting optical waveguide chip. Specifically, we extract two types of melanoma biomarkers, mutated cell-free nucleic acids —BRAFV600E and NRAS, from whole blood. We detect and identify these two targets simultaneously using the spectral multiplexing approach with up to a 96% success rate. These results point the way toward a full front-to-back chip-based optofluidic compact system for high-performance analysis of complex biological samples. PMID:28058082

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

PubMed

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

2017-04-01

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

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/

Systematic genomic identification of colorectal cancer genes delineating advanced from early clinical stage and metastasis

PubMed Central

2013-01-01

Background Colorectal cancer is the third leading cause of cancer deaths in the United States. The initial assessment of colorectal cancer involves clinical staging that takes into account the extent of primary tumor invasion, determining the number of lymph nodes with metastatic cancer and the identification of metastatic sites in other organs. Advanced clinical stage indicates metastatic cancer, either in regional lymph nodes or in distant organs. While the genomic and genetic basis of colorectal cancer has been elucidated to some degree, less is known about the identity of specific cancer genes that are associated with advanced clinical stage and metastasis. Methods We compiled multiple genomic data types (mutations, copy number alterations, gene expression and methylation status) as well as clinical meta-data from The Cancer Genome Atlas (TCGA). We used an elastic-net regularized regression method on the combined genomic data to identify genetic aberrations and their associated cancer genes that are indicators of clinical stage. We ranked candidate genes by their regression coefficient and level of support from multiple assay modalities. Results A fit of the elastic-net regularized regression to 197 samples and integrated analysis of four genomic platforms identified the set of top gene predictors of advanced clinical stage, including: WRN, SYK, DDX5 and ADRA2C. These genetic features were identified robustly in bootstrap resampling analysis. Conclusions We conducted an analysis integrating multiple genomic features including mutations, copy number alterations, gene expression and methylation. This integrated approach in which one considers all of these genomic features performs better than any individual genomic assay. We identified multiple genes that robustly delineate advanced clinical stage, suggesting their possible role in colorectal cancer metastatic progression. PMID:24308539

Identifying and exploiting trait-relevant tissues with multiple functional annotations in genome-wide association studies

PubMed Central

Zhang, Shujun

2018-01-01

Genome-wide association studies (GWASs) have identified many disease associated loci, the majority of which have unknown biological functions. Understanding the mechanism underlying trait associations requires identifying trait-relevant tissues and investigating associations in a trait-specific fashion. Here, we extend the widely used linear mixed model to incorporate multiple SNP functional annotations from omics studies with GWAS summary statistics to facilitate the identification of trait-relevant tissues, with which to further construct powerful association tests. Specifically, we rely on a generalized estimating equation based algorithm for parameter inference, a mixture modeling framework for trait-tissue relevance classification, and a weighted sequence kernel association test constructed based on the identified trait-relevant tissues for powerful association analysis. We refer to our analytic procedure as the Scalable Multiple Annotation integration for trait-Relevant Tissue identification and usage (SMART). With extensive simulations, we show how our method can make use of multiple complementary annotations to improve the accuracy for identifying trait-relevant tissues. In addition, our procedure allows us to make use of the inferred trait-relevant tissues, for the first time, to construct more powerful SNP set tests. We apply our method for an in-depth analysis of 43 traits from 28 GWASs using tissue-specific annotations in 105 tissues derived from ENCODE and Roadmap. Our results reveal new trait-tissue relevance, pinpoint important annotations that are informative of trait-tissue relationship, and illustrate how we can use the inferred trait-relevant tissues to construct more powerful association tests in the Wellcome trust case control consortium study. PMID:29377896

Functional Magnetic Resonance Imaging with Concurrent Urodynamic Testing Identifies Brain Structures Involved in Micturition Cycle in Patients with Multiple Sclerosis.

PubMed

Khavari, Rose; Karmonik, Christof; Shy, Michael; Fletcher, Sophie; Boone, Timothy

2017-02-01

Neurogenic lower urinary tract dysfunction, which is common in patients with multiple sclerosis, has a significant impact on quality of life. In this study we sought to determine brain activity processes during the micturition cycle in female patients with multiple sclerosis and neurogenic lower urinary tract dysfunction. We report brain activity on functional magnetic resonance imaging and simultaneous urodynamic testing in 23 ambulatory female patients with multiple sclerosis. Individual functional magnetic resonance imaging activation maps at strong desire to void and at initiation of voiding were calculated and averaged at Montreal Neuroimaging Institute. Areas of significant activation were identified in these average maps. Subgroup analysis was performed in patients with elicitable neurogenic detrusor overactivity or detrusor-sphincter dyssynergia. Group analysis of all patients at strong desire to void yielded areas of activation in regions associated with executive function (frontal gyrus), emotional regulation (cingulate gyrus) and motor control (putamen, cerebellum and precuneus). Comparison of the average change in activation between previously reported healthy controls and patients with multiple sclerosis showed predominantly stronger, more focal activation in the former and lower, more diffused activation in the latter. Patients with multiple sclerosis who had demonstrable neurogenic detrusor overactivity and detrusor-sphincter dyssynergia showed a trend toward distinct brain activation at full urge and at initiation of voiding respectively. We successfully studied brain activation during the entire micturition cycle in female patients with neurogenic lower urinary tract dysfunction and multiple sclerosis using a concurrent functional magnetic resonance imaging/urodynamic testing platform. Understanding the central neural processes involved in specific parts of micturition in patients with neurogenic lower urinary tract dysfunction may identify areas of interest for future intervention. Copyright © 2017 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

The prevalence of postoperative pain and flare-up in single- and multiple-visit endodontic treatment: a systematic review.

PubMed

Sathorn, C; Parashos, P; Messer, H

2008-02-01

The aim of this systematic review was to assess the evidence regarding postoperative pain and flare-up of single- or multiple-visit root canal treatment. CENTRAL, MEDLINE and EMBASE databases were searched. Reference lists from identified articles were scanned. A forward search was undertaken on the authors of the identified articles. Papers that had cited these articles were also identified through Science Citation Index to identify potentially relevant subsequent primary research. The included clinical studies compared the prevalence/severity of postoperative pain or flare-up in single- and multiple-visit root canal treatment. Data in those studies were extracted independently. Sixteen studies fitted the inclusion criteria in the review, with sample size varying from 60 to 1012 cases. The prevalence of postoperative pain ranged from 3% to 58%. The heterogeneity amongst included studies was far too great to conduct meta-analysis and yield meaningful results. Compelling evidence indicating a significantly different prevalence of postoperative pain/flare-up of either single- or multiple-visit root canal treatment is lacking.

Schizophrenia-associated methylomic variation: molecular signatures of disease and polygenic risk burden across multiple brain regions.

PubMed

Viana, Joana; Hannon, Eilis; Dempster, Emma; Pidsley, Ruth; Macdonald, Ruby; Knox, Olivia; Spiers, Helen; Troakes, Claire; Al-Saraj, Safa; Turecki, Gustavo; Schalkwyk, Leonard C; Mill, Jonathan

2017-01-01

Genetic association studies provide evidence for a substantial polygenic component to schizophrenia, although the neurobiological mechanisms underlying the disorder remain largely undefined. Building on recent studies supporting a role for developmentally regulated epigenetic variation in the molecular aetiology of schizophrenia, this study aimed to identify epigenetic variation associated with both a diagnosis of schizophrenia and elevated polygenic risk burden for the disease across multiple brain regions. Genome-wide DNA methylation was quantified in 262 post-mortem brain samples, representing tissue from four brain regions (prefrontal cortex, striatum, hippocampus and cerebellum) from 41 schizophrenia patients and 47 controls. We identified multiple disease-associated and polygenic risk score-associated differentially methylated positions and regions, which are not enriched in genomic regions identified in genetic studies of schizophrenia and do not reflect direct genetic effects on DNA methylation. Our study represents the first analysis of epigenetic variation associated with schizophrenia across multiple brain regions and highlights the utility of polygenic risk scores for identifying molecular pathways associated with aetiological variation in complex disease. © The Author 2016. Published by Oxford University Press.

Item Analysis in Introductory Economics Testing.

ERIC Educational Resources Information Center

Tinari, Frank D.

1979-01-01

Computerized analysis of multiple choice test items is explained. Examples of item analysis applications in the introductory economics course are discussed with respect to three objectives: to evaluate learning; to improve test items; and to help improve classroom instruction. Problems, costs and benefits of the procedures are identified. (JMD)

OrthoVenn: a web server for genome wide comparison and annotation of orthologous clusters across multiple species

USDA-ARS?s Scientific Manuscript database

Genome wide analysis of orthologous clusters is an important component of comparative genomics studies. Identifying the overlap among orthologous clusters can enable us to elucidate the function and evolution of proteins across multiple species. Here, we report a web platform named OrthoVenn that i...

MixGF: spectral probabilities for mixture spectra from more than one peptide.

PubMed

Wang, Jian; Bourne, Philip E; Bandeira, Nuno

2014-12-01

In large-scale proteomic experiments, multiple peptide precursors are often cofragmented simultaneously in the same mixture tandem mass (MS/MS) spectrum. These spectra tend to elude current computational tools because of the ubiquitous assumption that each spectrum is generated from only one peptide. Therefore, tools that consider multiple peptide matches to each MS/MS spectrum can potentially improve the relatively low spectrum identification rate often observed in proteomics experiments. More importantly, data independent acquisition protocols promoting the cofragmentation of multiple precursors are emerging as alternative methods that can greatly improve the throughput of peptide identifications but their success also depends on the availability of algorithms to identify multiple peptides from each MS/MS spectrum. Here we address a fundamental question in the identification of mixture MS/MS spectra: determining the statistical significance of multiple peptides matched to a given MS/MS spectrum. We propose the MixGF generating function model to rigorously compute the statistical significance of peptide identifications for mixture spectra and show that this approach improves the sensitivity of current mixture spectra database search tools by a ≈30-390%. Analysis of multiple data sets with MixGF reveals that in complex biological samples the number of identified mixture spectra can be as high as 20% of all the identified spectra and the number of unique peptides identified only in mixture spectra can be up to 35.4% of those identified in single-peptide spectra. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

MixGF: Spectral Probabilities for Mixture Spectra from more than One Peptide*

PubMed Central

Wang, Jian; Bourne, Philip E.; Bandeira, Nuno

2014-01-01

In large-scale proteomic experiments, multiple peptide precursors are often cofragmented simultaneously in the same mixture tandem mass (MS/MS) spectrum. These spectra tend to elude current computational tools because of the ubiquitous assumption that each spectrum is generated from only one peptide. Therefore, tools that consider multiple peptide matches to each MS/MS spectrum can potentially improve the relatively low spectrum identification rate often observed in proteomics experiments. More importantly, data independent acquisition protocols promoting the cofragmentation of multiple precursors are emerging as alternative methods that can greatly improve the throughput of peptide identifications but their success also depends on the availability of algorithms to identify multiple peptides from each MS/MS spectrum. Here we address a fundamental question in the identification of mixture MS/MS spectra: determining the statistical significance of multiple peptides matched to a given MS/MS spectrum. We propose the MixGF generating function model to rigorously compute the statistical significance of peptide identifications for mixture spectra and show that this approach improves the sensitivity of current mixture spectra database search tools by a ≈30–390%. Analysis of multiple data sets with MixGF reveals that in complex biological samples the number of identified mixture spectra can be as high as 20% of all the identified spectra and the number of unique peptides identified only in mixture spectra can be up to 35.4% of those identified in single-peptide spectra. PMID:25225354

High Resolution Melt (HRM) analysis is an efficient tool to genotype EMS mutants in complex crop genomes.

PubMed

Lochlainn, Seosamh Ó; Amoah, Stephen; Graham, Neil S; Alamer, Khalid; Rios, Juan J; Kurup, Smita; Stoute, Andrew; Hammond, John P; Østergaard, Lars; King, Graham J; White, Phillip J; Broadley, Martin R

2011-12-08

Targeted Induced Loci Lesions IN Genomes (TILLING) is increasingly being used to generate and identify mutations in target genes of crop genomes. TILLING populations of several thousand lines have been generated in a number of crop species including Brassica rapa. Genetic analysis of mutants identified by TILLING requires an efficient, high-throughput and cost effective genotyping method to track the mutations through numerous generations. High resolution melt (HRM) analysis has been used in a number of systems to identify single nucleotide polymorphisms (SNPs) and insertion/deletions (IN/DELs) enabling the genotyping of different types of samples. HRM is ideally suited to high-throughput genotyping of multiple TILLING mutants in complex crop genomes. To date it has been used to identify mutants and genotype single mutations. The aim of this study was to determine if HRM can facilitate downstream analysis of multiple mutant lines identified by TILLING in order to characterise allelic series of EMS induced mutations in target genes across a number of generations in complex crop genomes. We demonstrate that HRM can be used to genotype allelic series of mutations in two genes, BraA.CAX1a and BraA.MET1.a in Brassica rapa. We analysed 12 mutations in BraA.CAX1.a and five in BraA.MET1.a over two generations including a back-cross to the wild-type. Using a commercially available HRM kit and the Lightscanner™ system we were able to detect mutations in heterozygous and homozygous states for both genes. Using HRM genotyping on TILLING derived mutants, it is possible to generate an allelic series of mutations within multiple target genes rapidly. Lines suitable for phenotypic analysis can be isolated approximately 8-9 months (3 generations) from receiving M3 seed of Brassica rapa from the RevGenUK TILLING service.

High Resolution Melt (HRM) analysis is an efficient tool to genotype EMS mutants in complex crop genomes

PubMed Central

2011-01-01

Background Targeted Induced Loci Lesions IN Genomes (TILLING) is increasingly being used to generate and identify mutations in target genes of crop genomes. TILLING populations of several thousand lines have been generated in a number of crop species including Brassica rapa. Genetic analysis of mutants identified by TILLING requires an efficient, high-throughput and cost effective genotyping method to track the mutations through numerous generations. High resolution melt (HRM) analysis has been used in a number of systems to identify single nucleotide polymorphisms (SNPs) and insertion/deletions (IN/DELs) enabling the genotyping of different types of samples. HRM is ideally suited to high-throughput genotyping of multiple TILLING mutants in complex crop genomes. To date it has been used to identify mutants and genotype single mutations. The aim of this study was to determine if HRM can facilitate downstream analysis of multiple mutant lines identified by TILLING in order to characterise allelic series of EMS induced mutations in target genes across a number of generations in complex crop genomes. Results We demonstrate that HRM can be used to genotype allelic series of mutations in two genes, BraA.CAX1a and BraA.MET1.a in Brassica rapa. We analysed 12 mutations in BraA.CAX1.a and five in BraA.MET1.a over two generations including a back-cross to the wild-type. Using a commercially available HRM kit and the Lightscanner™ system we were able to detect mutations in heterozygous and homozygous states for both genes. Conclusions Using HRM genotyping on TILLING derived mutants, it is possible to generate an allelic series of mutations within multiple target genes rapidly. Lines suitable for phenotypic analysis can be isolated approximately 8-9 months (3 generations) from receiving M3 seed of Brassica rapa from the RevGenUK TILLING service. PMID:22152063

Analysis of in vitro fertilization data with multiple outcomes using discrete time-to-event analysis

PubMed Central

Maity, Arnab; Williams, Paige; Ryan, Louise; Missmer, Stacey; Coull, Brent; Hauser, Russ

2014-01-01

In vitro fertilization (IVF) is an increasingly common method of assisted reproductive technology. Because of the careful observation and followup required as part of the procedure, IVF studies provide an ideal opportunity to identify and assess clinical and demographic factors along with environmental exposures that may impact successful reproduction. A major challenge in analyzing data from IVF studies is handling the complexity and multiplicity of outcome, resulting from both multiple opportunities for pregnancy loss within a single IVF cycle in addition to multiple IVF cycles. To date, most evaluations of IVF studies do not make use of full data due to its complex structure. In this paper, we develop statistical methodology for analysis of IVF data with multiple cycles and possibly multiple failure types observed for each individual. We develop a general analysis framework based on a generalized linear modeling formulation that allows implementation of various types of models including shared frailty models, failure specific frailty models, and transitional models, using standard software. We apply our methodology to data from an IVF study conducted at the Brigham and Women’s Hospital, Massachusetts. We also summarize the performance of our proposed methods based on a simulation study. PMID:24317880

Generalisation of the identity method for determination of high-order moments of multiplicity distributions with a software implementation

NASA Astrophysics Data System (ADS)

Maćkowiak-Pawłowska, Maja; Przybyła, Piotr

2018-05-01

The incomplete particle identification limits the experimentally-available phase space region for identified particle analysis. This problem affects ongoing fluctuation and correlation studies including the search for the critical point of strongly interacting matter performed on SPS and RHIC accelerators. In this paper we provide a procedure to obtain nth order moments of the multiplicity distribution using the identity method, generalising previously published solutions for n=2 and n=3. Moreover, we present an open source software implementation of this computation, called Idhim, that allows one to obtain the true moments of identified particle multiplicity distributions from the measured ones provided the response function of the detector is known.

Mitochondrial DNA and trade data support multiple origins of Helicoverpa armigera (Lepidoptera, Noctuidae) in Brazil

PubMed Central

Tay, Wee Tek; Walsh, Thomas K.; Downes, Sharon; Anderson, Craig; Jermiin, Lars S.; Wong, Thomas K. F.; Piper, Melissa C.; Chang, Ester Silva; Macedo, Isabella Barony; Czepak, Cecilia; Behere, Gajanan T.; Silvie, Pierre; Soria, Miguel F.; Frayssinet, Marie; Gordon, Karl H. J.

2017-01-01

The Old World bollworm Helicoverpa armigera is now established in Brazil but efforts to identify incursion origin(s) and pathway(s) have met with limited success due to the patchiness of available data. Using international agricultural/horticultural commodity trade data and mitochondrial DNA (mtDNA) cytochrome oxidase I (COI) and cytochrome b (Cyt b) gene markers, we inferred the origins and incursion pathways into Brazil. We detected 20 mtDNA haplotypes from six Brazilian states, eight of which were new to our 97 global COI-Cyt b haplotype database. Direct sequence matches indicated five Brazilian haplotypes had Asian, African, and European origins. We identified 45 parsimoniously informative sites and multiple substitutions per site within the concatenated (945 bp) nucleotide dataset, implying that probabilistic phylogenetic analysis methods are needed. High diversity and signatures of uniquely shared haplotypes with diverse localities combined with the trade data suggested multiple incursions and introduction origins in Brazil. Increasing agricultural/horticultural trade activities between the Old and New Worlds represents a significant biosecurity risk factor. Identifying pest origins will enable resistance profiling that reflects countries of origin to be included when developing a resistance management strategy, while identifying incursion pathways will improve biosecurity protocols and risk analysis at biosecurity hotspots including national ports. PMID:28350004

Mitochondrial DNA and trade data support multiple origins of Helicoverpa armigera (Lepidoptera, Noctuidae) in Brazil.

PubMed

Tay, Wee Tek; Walsh, Thomas K; Downes, Sharon; Anderson, Craig; Jermiin, Lars S; Wong, Thomas K F; Piper, Melissa C; Chang, Ester Silva; Macedo, Isabella Barony; Czepak, Cecilia; Behere, Gajanan T; Silvie, Pierre; Soria, Miguel F; Frayssinet, Marie; Gordon, Karl H J

2017-03-28

The Old World bollworm Helicoverpa armigera is now established in Brazil but efforts to identify incursion origin(s) and pathway(s) have met with limited success due to the patchiness of available data. Using international agricultural/horticultural commodity trade data and mitochondrial DNA (mtDNA) cytochrome oxidase I (COI) and cytochrome b (Cyt b) gene markers, we inferred the origins and incursion pathways into Brazil. We detected 20 mtDNA haplotypes from six Brazilian states, eight of which were new to our 97 global COI-Cyt b haplotype database. Direct sequence matches indicated five Brazilian haplotypes had Asian, African, and European origins. We identified 45 parsimoniously informative sites and multiple substitutions per site within the concatenated (945 bp) nucleotide dataset, implying that probabilistic phylogenetic analysis methods are needed. High diversity and signatures of uniquely shared haplotypes with diverse localities combined with the trade data suggested multiple incursions and introduction origins in Brazil. Increasing agricultural/horticultural trade activities between the Old and New Worlds represents a significant biosecurity risk factor. Identifying pest origins will enable resistance profiling that reflects countries of origin to be included when developing a resistance management strategy, while identifying incursion pathways will improve biosecurity protocols and risk analysis at biosecurity hotspots including national ports.

Mitochondrial DNA and trade data support multiple origins of Helicoverpa armigera (Lepidoptera, Noctuidae) in Brazil

NASA Astrophysics Data System (ADS)

Tay, Wee Tek; Walsh, Thomas K.; Downes, Sharon; Anderson, Craig; Jermiin, Lars S.; Wong, Thomas K. F.; Piper, Melissa C.; Chang, Ester Silva; Macedo, Isabella Barony; Czepak, Cecilia; Behere, Gajanan T.; Silvie, Pierre; Soria, Miguel F.; Frayssinet, Marie; Gordon, Karl H. J.

2017-03-01

The Old World bollworm Helicoverpa armigera is now established in Brazil but efforts to identify incursion origin(s) and pathway(s) have met with limited success due to the patchiness of available data. Using international agricultural/horticultural commodity trade data and mitochondrial DNA (mtDNA) cytochrome oxidase I (COI) and cytochrome b (Cyt b) gene markers, we inferred the origins and incursion pathways into Brazil. We detected 20 mtDNA haplotypes from six Brazilian states, eight of which were new to our 97 global COI-Cyt b haplotype database. Direct sequence matches indicated five Brazilian haplotypes had Asian, African, and European origins. We identified 45 parsimoniously informative sites and multiple substitutions per site within the concatenated (945 bp) nucleotide dataset, implying that probabilistic phylogenetic analysis methods are needed. High diversity and signatures of uniquely shared haplotypes with diverse localities combined with the trade data suggested multiple incursions and introduction origins in Brazil. Increasing agricultural/horticultural trade activities between the Old and New Worlds represents a significant biosecurity risk factor. Identifying pest origins will enable resistance profiling that reflects countries of origin to be included when developing a resistance management strategy, while identifying incursion pathways will improve biosecurity protocols and risk analysis at biosecurity hotspots including national ports.

Elastic-net regularization approaches for genome-wide association studies of rheumatoid arthritis.

PubMed

Cho, Seoae; Kim, Haseong; Oh, Sohee; Kim, Kyunga; Park, Taesung

2009-12-15

The current trend in genome-wide association studies is to identify regions where the true disease-causing genes may lie by evaluating thousands of single-nucleotide polymorphisms (SNPs) across the whole genome. However, many challenges exist in detecting disease-causing genes among the thousands of SNPs. Examples include multicollinearity and multiple testing issues, especially when a large number of correlated SNPs are simultaneously tested. Multicollinearity can often occur when predictor variables in a multiple regression model are highly correlated, and can cause imprecise estimation of association. In this study, we propose a simple stepwise procedure that identifies disease-causing SNPs simultaneously by employing elastic-net regularization, a variable selection method that allows one to address multicollinearity. At Step 1, the single-marker association analysis was conducted to screen SNPs. At Step 2, the multiple-marker association was scanned based on the elastic-net regularization. The proposed approach was applied to the rheumatoid arthritis (RA) case-control data set of Genetic Analysis Workshop 16. While the selected SNPs at the screening step are located mostly on chromosome 6, the elastic-net approach identified putative RA-related SNPs on other chromosomes in an increased proportion. For some of those putative RA-related SNPs, we identified the interactions with sex, a well known factor affecting RA susceptibility.

Identifying candidate genes for Type 2 Diabetes Mellitus and obesity through gene expression profiling in multiple tissues or cells.

PubMed

Chen, Junhui; Meng, Yuhuan; Zhou, Jinghui; Zhuo, Min; Ling, Fei; Zhang, Yu; Du, Hongli; Wang, Xiaoning

2013-01-01

Type 2 Diabetes Mellitus (T2DM) and obesity have become increasingly prevalent in recent years. Recent studies have focused on identifying causal variations or candidate genes for obesity and T2DM via analysis of expression quantitative trait loci (eQTL) within a single tissue. T2DM and obesity are affected by comprehensive sets of genes in multiple tissues. In the current study, gene expression levels in multiple human tissues from GEO datasets were analyzed, and 21 candidate genes displaying high percentages of differential expression were filtered out. Specifically, DENND1B, LYN, MRPL30, POC1B, PRKCB, RP4-655J12.3, HIBADH, and TMBIM4 were identified from the T2DM-control study, and BCAT1, BMP2K, CSRNP2, MYNN, NCKAP5L, SAP30BP, SLC35B4, SP1, BAP1, GRB14, HSP90AB1, ITGA5, and TOMM5 were identified from the obesity-control study. The majority of these genes are known to be involved in T2DM and obesity. Therefore, analysis of gene expression in various tissues using GEO datasets may be an effective and feasible method to determine novel or causal genes associated with T2DM and obesity.

Identification of multiple mRNA and DNA sequences from small tissue samples isolated by laser-assisted microdissection.

PubMed

Bernsen, M R; Dijkman, H B; de Vries, E; Figdor, C G; Ruiter, D J; Adema, G J; van Muijen, G N

1998-10-01

Molecular analysis of small tissue samples has become increasingly important in biomedical studies. Using a laser dissection microscope and modified nucleic acid isolation protocols, we demonstrate that multiple mRNA as well as DNA sequences can be identified from a single-cell sample. In addition, we show that the specificity of procurement of tissue samples is not compromised by smear contamination resulting from scraping of the microtome knife during sectioning of lesions. The procedures described herein thus allow for efficient RT-PCR or PCR analysis of multiple nucleic acid sequences from small tissue samples obtained by laser-assisted microdissection.

Predictors of postoperative outcomes of cubital tunnel syndrome treatments using multiple logistic regression analysis.

PubMed

Suzuki, Taku; Iwamoto, Takuji; Shizu, Kanae; Suzuki, Katsuji; Yamada, Harumoto; Sato, Kazuki

2017-05-01

This retrospective study was designed to investigate prognostic factors for postoperative outcomes for cubital tunnel syndrome (CubTS) using multiple logistic regression analysis with a large number of patients. Eighty-three patients with CubTS who underwent surgeries were enrolled. The following potential prognostic factors for disease severity were selected according to previous reports: sex, age, type of surgery, disease duration, body mass index, cervical lesion, presence of diabetes mellitus, Workers' Compensation status, preoperative severity, and preoperative electrodiagnostic testing. Postoperative severity of disease was assessed 2 years after surgery by Messina's criteria which is an outcome measure specifically for CubTS. Bivariate analysis was performed to select candidate prognostic factors for multiple linear regression analyses. Multiple logistic regression analysis was conducted to identify the association between postoperative severity and selected prognostic factors. Both bivariate and multiple linear regression analysis revealed only preoperative severity as an independent risk factor for poor prognosis, while other factors did not show any significant association. Although conflicting results exist regarding prognosis of CubTS, this study supports evidence from previous studies and concludes early surgical intervention portends the most favorable prognosis. Copyright © 2017 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

Cross-cancer genome-wide analysis of lung, ovary, breast, prostate and colorectal cancer reveals novel pleiotropic associations

PubMed Central

Fehringer, Gordon; Kraft, Peter; Pharoah, Paul D.; Eeles, Rosalind A.; Chatterjee, Nilanjan; Schumacher, Fred; Schildkraut, Joellen; Lindström, Sara; Brennan, Paul; Bickeböller, Heike; Houlston, Richard S.; Landi, Maria Teresa; Caporaso, Neil; Risch, Angela; Olama, Ali Amin Al; Berndt, Sonja I; Giovannucci, Edward; Grönberg, Henrik; Kote-Jarai, Zsofia; Ma, Jing; Muir, Kenneth; Stampfer, Meir; Stevens, Victoria L.; Wiklund, Fredrik; Willett, Walter; Goode, Ellen L.; Permuth, Jennifer; Risch, Harvey A.; Reid, Brett M.; Bezieau, Stephane; Brenner, Hermann; Chan, Andrew T.; Chang-Claude, Jenny; Hudson, Thomas J.; Kocarnik, Jonathan K.; Newcomb, Polly A.; Schoen, Robert E.; Slattery, Martha L.; White, Emily; Adank, Muriel A.; Ahsan, Habibul; Aittomäki, Kristiina; Baglietto, Laura; Blomquist, Carl; Canzian, Federico; Czene, Kamila; dos-Santos-Silva, Isabel; Eliassen, A. Heather; Figueroa, Jonine; Flesch-Janys, Dieter; Fletcher, Olivia; Garcia-Closas, Montserrat; Gaudet, Mia M.; Johnson, Nichola; Hall, Per; Hazra, Aditi; Hein, Rebecca; Hofman, Albert; Hopper, John L.; Irwanto, Astrid; Johansson, Mattias; Kaaks, Rudolf; Kibriya, Muhammad G.; Lichtner, Peter; Liu, Jianjun; Lund, Eiliv; Makalic, Enes; Meindl, Alfons; Müller-Myhsok, Bertram; Muranen, Taru A.; Nevanlinna, Heli; Peeters, Petra H.; Peto, Julian; Prentice, Ross L.; Rahman, Nazneen; Sanchez, Maria Jose; Schmidt, Daniel F.; Schmutzler, Rita K.; Southey, Melissa C.; Tamimi, Rulla; Travis, Ruth C.; Turnbull, Clare; Uitterlinden, Andre G.; Wang, Zhaoming; Whittemore, Alice S.; Yang, Xiaohong R.; Zheng, Wei; Rafnar, Thorunn; Gudmundsson, Julius; Stacey, Simon N.; Stefansson, Kari; Sulem, Patrick; Chen, Y. Ann; Tyrer, Jonathan P.; Christiani, David C.; Wei, Yongyue; Shen, Hongbing; Hu, Zhibin; Shu, Xiao-Ou; Shiraishi, Kouya; Takahashi, Atsushi; Bossé, Yohan; Obeidat, Ma’en; Nickle, David; Timens, Wim; Freedman, Matthew L.; Li, Qiyuan; Seminara, Daniela; Chanock, Stephen J.; Gong, Jian; Peters, Ulrike; Gruber, Stephen B.; Amos, Christopher I.; Sellers, Thomas A.; Easton, Douglas F.; Hunter, David J.; Haiman, Christopher A.; Henderson, Brian E.; Hung, Rayjean J.

2016-01-01

Identifying genetic variants with pleiotropic associations can uncover common pathways influencing multiple cancers. We took a two-staged approach to conduct genome-wide association studies for lung, ovary, breast, prostate and colorectal cancer from the GAME-ON/GECCO Network (61,851 cases, 61,820 controls) to identify pleiotropic loci. Findings were replicated in independent association studies (55,789 cases, 330,490 controls). We identified a novel pleiotropic association at 1q22 involving breast and lung squamous cell carcinoma, with eQTL analysis showing an association with ADAM15/THBS3 gene expression in lung. We also identified a known breast cancer locus CASP8/ALS2CR12 associated with prostate cancer, a known cancer locus at CDKN2B-AS1 with different variants associated with lung adenocarcinoma and prostate cancer and confirmed the associations of a breast BRCA2 locus with lung and serous ovarian cancer. This is the largest study to date examining pleiotropy across multiple cancer-associated loci, identifying common mechanisms of cancer development and progression. PMID:27197191

3D fluid-structure modelling and vibration analysis for fault diagnosis of Francis turbine using multiple ANN and multiple ANFIS

NASA Astrophysics Data System (ADS)

Saeed, R. A.; Galybin, A. N.; Popov, V.

2013-01-01

This paper discusses condition monitoring and fault diagnosis in Francis turbine based on integration of numerical modelling with several different artificial intelligence (AI) techniques. In this study, a numerical approach for fluid-structure (turbine runner) analysis is presented. The results of numerical analysis provide frequency response functions (FRFs) data sets along x-, y- and z-directions under different operating load and different position and size of faults in the structure. To extract features and reduce the dimensionality of the obtained FRF data, the principal component analysis (PCA) has been applied. Subsequently, the extracted features are formulated and fed into multiple artificial neural networks (ANN) and multiple adaptive neuro-fuzzy inference systems (ANFIS) in order to identify the size and position of the damage in the runner and estimate the turbine operating conditions. The results demonstrated the effectiveness of this approach and provide satisfactory accuracy even when the input data are corrupted with certain level of noise.

Identification of key regulators of pancreatic cancer progression through multidimensional systems-level analysis.

PubMed

Rajamani, Deepa; Bhasin, Manoj K

2016-05-03

Pancreatic cancer is an aggressive cancer with dismal prognosis, urgently necessitating better biomarkers to improve therapeutic options and early diagnosis. Traditional approaches of biomarker detection that consider only one aspect of the biological continuum like gene expression alone are limited in their scope and lack robustness in identifying the key regulators of the disease. We have adopted a multidimensional approach involving the cross-talk between the omics spaces to identify key regulators of disease progression. Multidimensional domain-specific disease signatures were obtained using rank-based meta-analysis of individual omics profiles (mRNA, miRNA, DNA methylation) related to pancreatic ductal adenocarcinoma (PDAC). These domain-specific PDAC signatures were integrated to identify genes that were affected across multiple dimensions of omics space in PDAC (genes under multiple regulatory controls, GMCs). To further pin down the regulators of PDAC pathophysiology, a systems-level network was generated from knowledge-based interaction information applied to the above identified GMCs. Key regulators were identified from the GMC network based on network statistics and their functional importance was validated using gene set enrichment analysis and survival analysis. Rank-based meta-analysis identified 5391 genes, 109 miRNAs and 2081 methylation-sites significantly differentially expressed in PDAC (false discovery rate ≤ 0.05). Bimodal integration of meta-analysis signatures revealed 1150 and 715 genes regulated by miRNAs and methylation, respectively. Further analysis identified 189 altered genes that are commonly regulated by miRNA and methylation, hence considered GMCs. Systems-level analysis of the scale-free GMCs network identified eight potential key regulator hubs, namely E2F3, HMGA2, RASA1, IRS1, NUAK1, ACTN1, SKI and DLL1, associated with important pathways driving cancer progression. Survival analysis on individual key regulators revealed that higher expression of IRS1 and DLL1 and lower expression of HMGA2, ACTN1 and SKI were associated with better survival probabilities. It is evident from the results that our hierarchical systems-level multidimensional analysis approach has been successful in isolating the converging regulatory modules and associated key regulatory molecules that are potential biomarkers for pancreatic cancer progression.

Addressing the targeting range of the ABILHAND-56 in relapsing-remitting multiple sclerosis: A mixed methods psychometric study.

PubMed

Cleanthous, Sophie; Strzok, Sara; Pompilus, Farrah; Cano, Stefan; Marquis, Patrick; Cohan, Stanley; Goldman, Myla D; Kresa-Reahl, Kiren; Petrillo, Jennifer; Castrillo-Viguera, Carmen; Cadavid, Diego; Chen, Shih-Yin

2018-01-01

ABILHAND, a manual ability patient-reported outcome instrument originally developed for stroke patients, has been used in multiple sclerosis clinical trials; however, psychometric analyses indicated the measure's limited measurement range and precision in higher-functioning multiple sclerosis patients. The purpose of this study was to identify candidate items to expand the measurement range of the ABILHAND-56, thus improving its ability to detect differences in manual ability in higher-functioning multiple sclerosis patients. A step-wise mixed methods design strategy was used, comprising two waves of patient interviews, a combination of qualitative (concept elicitation and cognitive debriefing) and quantitative (Rasch measurement theory) analytic techniques, and consultation interviews with three clinical neurologists specializing in multiple sclerosis. Original ABILHAND was well understood in this context of use. Eighty-two new manual ability concepts were identified. Draft supplementary items were generated and refined with patient and neurologist input. Rasch measurement theory psychometric analysis indicated supplementary items improved targeting to higher-functioning multiple sclerosis patients and measurement precision. The final pool of Early Multiple Sclerosis Manual Ability items comprises 20 items. The synthesis of qualitative and quantitative methods used in this study improves the ABILHAND content validity to more effectively identify manual ability changes in early multiple sclerosis and potentially help determine treatment effect in higher-functioning patients in clinical trials.

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

Andersen, Gary L.; Dubinsky, Eric A.

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

Large-scale gene-centric meta-analysis across 32 studies identifies multiple lipid loci

USDA-ARS?s Scientific Manuscript database

Genome-wide association studies (GWASs) have identified many SNPs underlying variations in plasma-lipid levels. We explore whether additional loci associated with plasma-lipid phenotypes, such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholest...

In the Context of Multiple Intelligences Theory, Intelligent Data Analysis of Learning Styles Was Based on Rough Set Theory

ERIC Educational Resources Information Center

Narli, Serkan; Ozgen, Kemal; Alkan, Huseyin

2011-01-01

The present study aims to identify the relationship between individuals' multiple intelligence areas and their learning styles with mathematical clarity using the concept of rough sets which is used in areas such as artificial intelligence, data reduction, discovery of dependencies, prediction of data significance, and generating decision…

What Is Successful Writing? An Investigation into the Multiple Ways Writers Can Write Successful Essays

ERIC Educational Resources Information Center

Crossley, Scott A.; Roscoe, Rod; McNamara, Danielle S.

2014-01-01

This study identifies multiple profiles of successful essays via a cluster analysis approach using linguistic features reported by a variety of natural language processing tools. The findings from the study indicate that there are four profiles of successful writers for the samples analyzed. These four profiles are linguistically distinct from one…

Ratiometric analysis of in vivo retinal layer thicknesses in multiple sclerosis

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

Multiplexed resequencing analysis to identify rare variants in pooled DNA with barcode indexing using next-generation sequencer.

PubMed

Mitsui, Jun; Fukuda, Yoko; Azuma, Kyo; Tozaki, Hirokazu; Ishiura, Hiroyuki; Takahashi, Yuji; Goto, Jun; Tsuji, Shoji

2010-07-01

We have recently found that multiple rare variants of the glucocerebrosidase gene (GBA) confer a robust risk for Parkinson disease, supporting the 'common disease-multiple rare variants' hypothesis. To develop an efficient method of identifying rare variants in a large number of samples, we applied multiplexed resequencing using a next-generation sequencer to identification of rare variants of GBA. Sixteen sets of pooled DNAs from six pooled DNA samples were prepared. Each set of pooled DNAs was subjected to polymerase chain reaction to amplify the target gene (GBA) covering 6.5 kb, pooled into one tube with barcode indexing, and then subjected to extensive sequence analysis using the SOLiD System. Individual samples were also subjected to direct nucleotide sequence analysis. With the optimization of data processing, we were able to extract all the variants from 96 samples with acceptable rates of false-positive single-nucleotide variants.

Microarray gene expression profiling analysis combined with bioinformatics in multiple sclerosis.

PubMed

Liu, Mingyuan; Hou, Xiaojun; Zhang, Ping; Hao, Yong; Yang, Yiting; Wu, Xiongfeng; Zhu, Desheng; Guan, Yangtai

2013-05-01

Multiple sclerosis (MS) is the most prevalent demyelinating disease and the principal cause of neurological disability in young adults. Recent microarray gene expression profiling studies have identified several genetic variants contributing to the complex pathogenesis of MS, however, expressional and functional studies are still required to further understand its molecular mechanism. The present study aimed to analyze the molecular mechanism of MS using microarray analysis combined with bioinformatics techniques. We downloaded the gene expression profile of MS from Gene Expression Omnibus (GEO) and analysed the microarray data using the differentially coexpressed genes (DCGs) and links package in R and Database for Annotation, Visualization and Integrated Discovery. The regulatory impact factor (RIF) algorithm was used to measure the impact factor of transcription factor. A total of 1,297 DCGs between MS patients and healthy controls were identified. Functional annotation indicated that these DCGs were associated with immune and neurological functions. Furthermore, the RIF result suggested that IKZF1, BACH1, CEBPB, EGR1, FOS may play central regulatory roles in controlling gene expression in the pathogenesis of MS. Our findings confirm the presence of multiple molecular alterations in MS and indicate the possibility for identifying prognostic factors associated with MS pathogenesis.

Configural Frequency Analysis as a Statistical Tool for Developmental Research.

ERIC Educational Resources Information Center

Lienert, Gustav A.; Oeveste, Hans Zur

1985-01-01

Configural frequency analysis (CFA) is suggested as a technique for longitudinal research in developmental psychology. Stability and change in answers to multiple choice and yes-no item patterns obtained with repeated measurements are identified by CFA and illustrated by developmental analysis of an item from Gorham's Proverb Test. (Author/DWH)

Criteria for the use of regression analysis for remote sensing of sediment and pollutants

NASA Technical Reports Server (NTRS)

Whitlock, C. H.; Kuo, C. Y.; Lecroy, S. R. (Principal Investigator)

1982-01-01

Data analysis procedures for quantification of water quality parameters that are already identified and are known to exist within the water body are considered. The liner multiple-regression technique was examined as a procedure for defining and calibrating data analysis algorithms for such instruments as spectrometers and multispectral scanners.

Joint Identification of Genetic Variants for Physical Activity in Korean Population

PubMed Central

Kim, Jayoun; Kim, Jaehee; Min, Haesook; Oh, Sohee; Kim, Yeonjung; Lee, Andy H.; Park, Taesung

2014-01-01

There has been limited research on genome-wide association with physical activity (PA). This study ascertained genetic associations between PA and 344,893 single nucleotide polymorphism (SNP) markers in 8842 Korean samples. PA data were obtained from a validated questionnaire that included information on PA intensity and duration. Metabolic equivalent of tasks were calculated to estimate the total daily PA level for each individual. In addition to single- and multiple-SNP association tests, a pathway enrichment analysis was performed to identify the biological significance of SNP markers. Although no significant SNP was found at genome-wide significance level via single-SNP association tests, 59 genetic variants mapped to 76 genes were identified via a multiple SNP approach using a bootstrap selection stability measure. Pathway analysis for these 59 variants showed that maturity onset diabetes of the young (MODY) was enriched. Joint identification of SNPs could enable the identification of multiple SNPs with good predictive power for PA and a pathway enriched for PA. PMID:25026172

Haplotype Analysis in Multiple Crosses to Identify a QTL Gene

PubMed Central

Wang, Xiaosong; Korstanje, Ron; Higgins, David; Paigen, Beverly

2004-01-01

Identifying quantitative trait locus (QTL) genes is a challenging task. Herein, we report using a two-step process to identify Apoa2 as the gene underlying Hdlq5, a QTL for plasma high-density lipoprotein cholesterol (HDL) levels on mouse chromosome 1. First, we performed a sequence analysis of the Apoa2 coding region in 46 genetically diverse mouse strains and found five different APOA2 protein variants, which we named APOA2a to APOA2e. Second, we conducted a haplotype analysis of the strains in 21 crosses that have so far detected HDL QTLs; we found that Hdlq5 was detected only in the nine crosses where one parent had the APOA2b protein variant characterized by an Ala61-to-Val61 substitution. We then found that strains with the APOA2b variant had significantly higher (P ≤ 0.002) plasma HDL levels than those with either the APOA2a or the APOA2c variant. These findings support Apoa2 as the underlying Hdlq5 gene and suggest the Apoa2 polymorphisms responsible for the Hdlq5 phenotype. Therefore, haplotype analysis in multiple crosses can be used to support a candidate QTL gene. PMID:15310659

Haplotype analysis in multiple crosses to identify a QTL gene.

PubMed

Wang, Xiaosong; Korstanje, Ron; Higgins, David; Paigen, Beverly

2004-09-01

Identifying quantitative trait locus (QTL) genes is a challenging task. Herein, we report using a two-step process to identify Apoa2 as the gene underlying Hdlq5, a QTL for plasma high-density lipoprotein cholesterol (HDL) levels on mouse chromosome 1. First, we performed a sequence analysis of the Apoa2 coding region in 46 genetically diverse mouse strains and found five different APOA2 protein variants, which we named APOA2a to APOA2e. Second, we conducted a haplotype analysis of the strains in 21 crosses that have so far detected HDL QTLs; we found that Hdlq5 was detected only in the nine crosses where one parent had the APOA2b protein variant characterized by an Ala61-to-Val61 substitution. We then found that strains with the APOA2b variant had significantly higher (P < or = 0.002) plasma HDL levels than those with either the APOA2a or the APOA2c variant. These findings support Apoa2 as the underlying Hdlq5 gene and suggest the Apoa2 polymorphisms responsible for the Hdlq5 phenotype. Therefore, haplotype analysis in multiple crosses can be used to support a candidate QTL gene.

Genetic association of impulsivity in young adults: a multivariate study

PubMed Central

Khadka, S; Narayanan, B; Meda, S A; Gelernter, J; Han, S; Sawyer, B; Aslanzadeh, F; Stevens, M C; Hawkins, K A; Anticevic, A; Potenza, M N; Pearlson, G D

2014-01-01

Impulsivity is a heritable, multifaceted construct with clinically relevant links to multiple psychopathologies. We assessed impulsivity in young adult (N~2100) participants in a longitudinal study, using self-report questionnaires and computer-based behavioral tasks. Analysis was restricted to the subset (N=426) who underwent genotyping. Multivariate association between impulsivity measures and single-nucleotide polymorphism data was implemented using parallel independent component analysis (Para-ICA). Pathways associated with multiple genes in components that correlated significantly with impulsivity phenotypes were then identified using a pathway enrichment analysis. Para-ICA revealed two significantly correlated genotype–phenotype component pairs. One impulsivity component included the reward responsiveness subscale and behavioral inhibition scale of the Behavioral-Inhibition System/Behavioral-Activation System scale, and the second impulsivity component included the non-planning subscale of the Barratt Impulsiveness Scale and the Experiential Discounting Task. Pathway analysis identified processes related to neurogenesis, nervous system signal generation/amplification, neurotransmission and immune response. We identified various genes and gene regulatory pathways associated with empirically derived impulsivity components. Our study suggests that gene networks implicated previously in brain development, neurotransmission and immune response are related to impulsive tendencies and behaviors. PMID:25268255

Multiple and substitute addictions involving prescription drugs misuse among 12th graders: gateway theory revisited with Market Basket Analysis.

PubMed

Jayawardene, Wasantha Parakrama; YoussefAgha, Ahmed Hassan

2014-01-01

This study aimed to identify the sequential patterns of drug use initiation, which included prescription drugs misuse (PDM), among 12th-grade students in Indiana. The study also tested the suitability of the data mining method Market Basket Analysis (MBA) to detect common drug use initiation sequences in large-scale surveys. Data from 2007 to 2009 Annual Surveys of Alcohol, Tobacco, and Other Drug Use by Indiana Children and Adolescents were used for this study. A close-ended, self-administered questionnaire was used to ask adolescents about the use of 21 substance categories and the age of first use. "Support%" and "confidence%" statistics of Market Basket Analysis detected multiple and substitute addictions, respectively. The lifetime prevalence of using any addictive substance was 73.3%, and it has been decreasing during past few years. Although the lifetime prevalence of PDM was 19.2%, it has been increasing. Males and whites were more likely to use drugs and engage in multiple addictions. Market Basket Analysis identified common drug use initiation sequences that involved 11 drugs. High levels of support existed for associations among alcohol, cigarettes, and marijuana, whereas associations that included prescription drugs had medium levels of support. Market Basket Analysis is useful for the detection of common substance use initiation sequences in large-scale surveys. Before initiation of prescription drugs, physicians should consider the adolescents' risk of addiction. Prevention programs should address multiple addictions, substitute addictions, common sequences in drug use initiation, sex and racial differences in PDM, and normative beliefs of parents and adolescents in relation to PDM.

Comprehensive analysis of "bath salts" purchased from California stores and the internet.

PubMed

Schneir, A; Ly, B T; Casagrande, K; Darracq, M; Offerman, S R; Thornton, S; Smollin, C; Vohra, R; Rangun, C; Tomaszewski, C; Gerona, R R

2014-08-01

To analyze the contents of "bath salt" products purchased from California stores and the Internet qualitatively and quantitatively in a comprehensive manner. A convenience sample of "bath salt" products were purchased in person by multiple authors at retail stores in six California cities and over the Internet (U.S. sites only), between August 11, 2011 and December 15, 2011. Liquid chromatography-time-of-flight mass spectrometry was utilized to identify and quantify all substances in the purchased products. Thirty-five "bath salt" products were purchased and analyzed. Prices ranged from $9.95 to 49.99 (U.S. dollars). Most products had a warning against use. The majority (32/35, 91%) had one (n = 15) or multiple cathinones (n = 17) present. Fourteen different cathinones were identified, 3,4-methylenedioxypyrovalerone (MDPV) being the most common. Multiple drugs found including cathinones (buphedrone, ethcathinone, ethylone, MDPBP, and PBP), other designer amines (ethylamphetamine, fluoramphetamine, and 5-IAI), and the antihistamine doxylamine had not been previously identified in U.S. "bath salt" products. Quantification revealed high stimulant content and in some cases dramatic differences in either total cathinone or synthetic stimulant content between products with the same declared weight and even between identically named and outwardly appearing products. Comprehensive analysis of "bath salts" purchased from California stores and the Internet revealed the products to consistently contain cathinones, alone, or in different combinations, sometimes in high quantity. Multiple cathinones and other drugs found had not been previously identified in U.S. "bath salt" products. High total stimulant content in some products and variable qualitative and quantitative composition amongst products were demonstrated.

Cross-Population Joint Analysis of eQTLs: Fine Mapping and Functional Annotation

PubMed Central

Wen, Xiaoquan; Luca, Francesca; Pique-Regi, Roger

2015-01-01

Mapping expression quantitative trait loci (eQTLs) has been shown as a powerful tool to uncover the genetic underpinnings of many complex traits at molecular level. In this paper, we present an integrative analysis approach that leverages eQTL data collected from multiple population groups. In particular, our approach effectively identifies multiple independent cis-eQTL signals that are consistent across populations, accounting for population heterogeneity in allele frequencies and linkage disequilibrium patterns. Furthermore, by integrating genomic annotations, our analysis framework enables high-resolution functional analysis of eQTLs. We applied our statistical approach to analyze the GEUVADIS data consisting of samples from five population groups. From this analysis, we concluded that i) jointly analysis across population groups greatly improves the power of eQTL discovery and the resolution of fine mapping of causal eQTL ii) many genes harbor multiple independent eQTLs in their cis regions iii) genetic variants that disrupt transcription factor binding are significantly enriched in eQTLs (p-value = 4.93 × 10-22). PMID:25906321

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

PubMed

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

2017-08-23

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

The Use of Multiple Correspondence Analysis to Explore Associations between Categories of Qualitative Variables in Healthy Ageing.

PubMed

Costa, Patrício Soares; Santos, Nadine Correia; Cunha, Pedro; Cotter, Jorge; Sousa, Nuno

2013-01-01

The main focus of this study was to illustrate the applicability of multiple correspondence analysis (MCA) in detecting and representing underlying structures in large datasets used to investigate cognitive ageing. Principal component analysis (PCA) was used to obtain main cognitive dimensions, and MCA was used to detect and explore relationships between cognitive, clinical, physical, and lifestyle variables. Two PCA dimensions were identified (general cognition/executive function and memory), and two MCA dimensions were retained. Poorer cognitive performance was associated with older age, less school years, unhealthier lifestyle indicators, and presence of pathology. The first MCA dimension indicated the clustering of general/executive function and lifestyle indicators and education, while the second association was between memory and clinical parameters and age. The clustering analysis with object scores method was used to identify groups sharing similar characteristics. The weaker cognitive clusters in terms of memory and executive function comprised individuals with characteristics contributing to a higher MCA dimensional mean score (age, less education, and presence of indicators of unhealthier lifestyle habits and/or clinical pathologies). MCA provided a powerful tool to explore complex ageing data, covering multiple and diverse variables, showing if a relationship exists and how variables are related, and offering statistical results that can be seen both analytically and visually.

Identification of milling and baking quality QTL in multiple soft wheat mapping populations.

PubMed

Cabrera, Antonio; Guttieri, Mary; Smith, Nathan; Souza, Edward; Sturbaum, Anne; Hua, Duc; Griffey, Carl; Barnett, Marla; Murphy, Paul; Ohm, Herb; Uphaus, Jim; Sorrells, Mark; Heffner, Elliot; Brown-Guedira, Gina; Van Sanford, David; Sneller, Clay

2015-11-01

Two mapping approaches were use to identify and validate milling and baking quality QTL in soft wheat. Two LG were consistently found important for multiple traits and we recommend the use marker-assisted selection on specific markers reported here. Wheat-derived food products require a range of characteristics. Identification and understanding of the genetic components controlling end-use quality of wheat is important for crop improvement. We assessed the underlying genetics controlling specific milling and baking quality parameters of soft wheat including flour yield, softness equivalent, flour protein, sucrose, sodium carbonate, water absorption and lactic acid, solvent retention capacities in a diversity panel and five bi-parental mapping populations. The populations were genotyped with SSR and DArT markers, with markers specific for the 1BL.1RS translocation and sucrose synthase gene. Association analysis and composite interval mapping were performed to identify quantitative trait loci (QTL). High heritability was observed for each of the traits evaluated, trait correlations were consistent over populations, and transgressive segregants were common in all bi-parental populations. A total of 26 regions were identified as potential QTL in the diversity panel and 74 QTL were identified across all five bi-parental mapping populations. Collinearity of QTL from chromosomes 1B and 2B was observed across mapping populations and was consistent with results from the association analysis in the diversity panel. Multiple regression analysis showed the importance of the two 1B and 2B regions and marker-assisted selection for the favorable alleles at these regions should improve quality.

An analysis of the multiple model adaptive control algorithm. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Greene, C. S.

1978-01-01

Qualitative and quantitative aspects of the multiple model adaptive control method are detailed. The method represents a cascade of something which resembles a maximum a posteriori probability identifier (basically a bank of Kalman filters) and a bank of linear quadratic regulators. Major qualitative properties of the MMAC method are examined and principle reasons for unacceptable behavior are explored.

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.

Consumer preference for mandarins: Implications of a sensory analysis

USDA-ARS?s Scientific Manuscript database

While consumption of mandarins has grown steadily in the United States, mandarin cultivars being produced and consumed have been changing. The goal of this research is to identify factors that impact consumer choice of mandarins. In this analysis, consumers were presented with multiple mandarins for...

Chemical analysis of plants that poison livestock: Successes, challenges, and opportunities

USDA-ARS?s Scientific Manuscript database

Poisonous plants have a devastating impact on the livestock industry, as well as human health. In order to fully understand the effects of poisonous plants, multiple scientific disciplines are required. Chemical analysis of plant secondary compounds is key to identifying the responsible toxins, char...

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 .

Progressing from Identification and Functional Analysis of Precursor Behavior to Treatment of Self-Injurious Behavior

ERIC Educational Resources Information Center

Dracobly, Joseph D.; Smith, Richard G.

2012-01-01

This multiple-study experiment evaluated the utility of assessing and treating severe self-injurious behavior (SIB) based on the outcomes of a functional analysis of precursor behavior. In Study 1, a precursor to SIB was identified using descriptive assessment and conditional probability analyses. In Study 2, a functional analysis of precursor…

Comparison of the phenolic composition of fruit juices by single step gradient HPLC analysis of multiple components versus multiple chromatographic runs optimised for individual families.

PubMed

Bremner, P D; Blacklock, C J; Paganga, G; Mullen, W; Rice-Evans, C A; Crozier, A

2000-06-01

After minimal sample preparation, two different HPLC methodologies, one based on a single gradient reversed-phase HPLC step, the other on multiple HPLC runs each optimised for specific components, were used to investigate the composition of flavonoids and phenolic acids in apple and tomato juices. The principal components in apple juice were identified as chlorogenic acid, phloridzin, caffeic acid and p-coumaric acid. Tomato juice was found to contain chlorogenic acid, caffeic acid, p-coumaric acid, naringenin and rutin. The quantitative estimates of the levels of these compounds, obtained with the two HPLC procedures, were very similar, demonstrating that either method can be used to analyse accurately the phenolic components of apple and tomato juices. Chlorogenic acid in tomato juice was the only component not fully resolved in the single run study and the multiple run analysis prior to enzyme treatment. The single run system of analysis is recommended for the initial investigation of plant phenolics and the multiple run approach for analyses where chromatographic resolution requires improvement.

Identifying Aspects of Parental Involvement that Affect the Academic Achievement of High School Students

ERIC Educational Resources Information Center

Roulette-McIntyre, Ovella; Bagaka's, Joshua G.; Drake, Daniel D.

2005-01-01

This study identified parental practices that relate positively to high school students' academic performance. Parents of 643 high school students participated in the study. Data analysis, using a multiple linear regression model, shows parent-school connection, student gender, and race are significant predictors of student academic performance.…

Multiple loci on 8q24 associated with prostate cancer susceptibility.

PubMed

Al Olama, Ali Amin; Kote-Jarai, Zsofia; Giles, Graham G; Guy, Michelle; Morrison, Jonathan; Severi, Gianluca; Leongamornlert, Daniel A; Tymrakiewicz, Malgorzata; Jhavar, Sameer; Saunders, Ed; Hopper, John L; Southey, Melissa C; Muir, Kenneth R; English, Dallas R; Dearnaley, David P; Ardern-Jones, Audrey T; Hall, Amanda L; O'Brien, Lynne T; Wilkinson, Rosemary A; Sawyer, Emma; Lophatananon, Artitaya; Horwich, Alan; Huddart, Robert A; Khoo, Vincent S; Parker, Christopher C; Woodhouse, Christopher J; Thompson, Alan; Christmas, Tim; Ogden, Chris; Cooper, Colin; Donovan, Jenny L; Hamdy, Freddie C; Neal, David E; Eeles, Rosalind A; Easton, Douglas F

2009-10-01

Previous studies have identified multiple loci on 8q24 associated with prostate cancer risk. We performed a comprehensive analysis of SNP associations across 8q24 by genotyping tag SNPs in 5,504 prostate cancer cases and 5,834 controls. We confirmed associations at three previously reported loci and identified additional loci in two other linkage disequilibrium blocks (rs1006908: per-allele OR = 0.87, P = 7.9 x 10(-8); rs620861: OR = 0.90, P = 4.8 x 10(-8)). Eight SNPs in five linkage disequilibrium blocks were independently associated with prostate cancer susceptibility.

Student experiences across multiple flipped courses in a single curriculum.

PubMed

Khanova, Julia; Roth, Mary T; Rodgers, Jo Ellen; McLaughlin, Jacqueline E

2015-10-01

The flipped classroom approach has garnered significant attention in health professions education, which has resulted in calls for curriculum-wide implementations of the model. However, research to support the development of evidence-based guidelines for large-scale flipped classroom implementations is lacking. This study was designed to examine how students experience the flipped classroom model of learning in multiple courses within a single curriculum, as well as to identify specific elements of flipped learning that students perceive as beneficial or challenging. A qualitative analysis of students' comments (n = 6010) from mid-course and end-of-course evaluations of 10 flipped courses (in 2012-2014) was conducted. Common and recurring themes were identified through systematic iterative coding and sorting using the constant comparison method. Multiple coders, agreement through consensus and member checking were utilised to ensure the trustworthiness of findings. Several themes emerged from the analysis: (i) the perceived advantages of flipped learning coupled with concerns about implementation; (ii) the benefits of pre-class learning and factors that negatively affect these benefits, such as quality and quantity of learning materials, as well as overall increase in workload, especially in the context of multiple concurrent flipped courses; (iii) the role of the instructor in the flipped learning environment, particularly in engaging students in active learning and ensuring instructional alignment, and (iv) the need for assessments that emphasise the application of knowledge and critical thinking skills. Analysis of data from 10 flipped courses provided insight into common patterns of student learning experiences specific to the flipped learning model within a single curriculum. The study points to the challenges associated with scaling the implementation of the flipped classroom across multiple courses. Several core elements critical to the effective design and implementation of the flipped classroom model are identified. © 2015 John Wiley & Sons Ltd.

Cross-Cancer Genome-Wide Analysis of Lung, Ovary, Breast, Prostate, and Colorectal Cancer Reveals Novel Pleiotropic Associations.

PubMed

Fehringer, Gordon; Kraft, Peter; Pharoah, Paul D; Eeles, Rosalind A; Chatterjee, Nilanjan; Schumacher, Fredrick R; Schildkraut, Joellen M; Lindström, Sara; Brennan, Paul; Bickeböller, Heike; Houlston, Richard S; Landi, Maria Teresa; Caporaso, Neil; Risch, Angela; Amin Al Olama, Ali; Berndt, Sonja I; Giovannucci, Edward L; Grönberg, Henrik; Kote-Jarai, Zsofia; Ma, Jing; Muir, Kenneth; Stampfer, Meir J; Stevens, Victoria L; Wiklund, Fredrik; Willett, Walter C; Goode, Ellen L; Permuth, Jennifer B; Risch, Harvey A; Reid, Brett M; Bezieau, Stephane; Brenner, Hermann; Chan, Andrew T; Chang-Claude, Jenny; Hudson, Thomas J; Kocarnik, Jonathan K; Newcomb, Polly A; Schoen, Robert E; Slattery, Martha L; White, Emily; Adank, Muriel A; Ahsan, Habibul; Aittomäki, Kristiina; Baglietto, Laura; Blomquist, Carl; Canzian, Federico; Czene, Kamila; Dos-Santos-Silva, Isabel; Eliassen, A Heather; Figueroa, Jonine D; Flesch-Janys, Dieter; Fletcher, Olivia; Garcia-Closas, Montserrat; Gaudet, Mia M; Johnson, Nichola; Hall, Per; Hazra, Aditi; Hein, Rebecca; Hofman, Albert; Hopper, John L; Irwanto, Astrid; Johansson, Mattias; Kaaks, Rudolf; Kibriya, Muhammad G; Lichtner, Peter; Liu, Jianjun; Lund, Eiliv; Makalic, Enes; Meindl, Alfons; Müller-Myhsok, Bertram; Muranen, Taru A; Nevanlinna, Heli; Peeters, Petra H; Peto, Julian; Prentice, Ross L; Rahman, Nazneen; Sanchez, Maria Jose; Schmidt, Daniel F; Schmutzler, Rita K; Southey, Melissa C; Tamimi, Rulla; Travis, Ruth C; Turnbull, Clare; Uitterlinden, Andre G; Wang, Zhaoming; Whittemore, Alice S; Yang, Xiaohong R; Zheng, Wei; Buchanan, Daniel D; Casey, Graham; Conti, David V; Edlund, Christopher K; Gallinger, Steven; Haile, Robert W; Jenkins, Mark; Le Marchand, Loïc; Li, Li; Lindor, Noralene M; Schmit, Stephanie L; Thibodeau, Stephen N; Woods, Michael O; Rafnar, Thorunn; Gudmundsson, Julius; Stacey, Simon N; Stefansson, Kari; Sulem, Patrick; Chen, Y Ann; Tyrer, Jonathan P; Christiani, David C; Wei, Yongyue; Shen, Hongbing; Hu, Zhibin; Shu, Xiao-Ou; Shiraishi, Kouya; Takahashi, Atsushi; Bossé, Yohan; Obeidat, Ma'en; Nickle, David; Timens, Wim; Freedman, Matthew L; Li, Qiyuan; Seminara, Daniela; Chanock, Stephen J; Gong, Jian; Peters, Ulrike; Gruber, Stephen B; Amos, Christopher I; Sellers, Thomas A; Easton, Douglas F; Hunter, David J; Haiman, Christopher A; Henderson, Brian E; Hung, Rayjean J

2016-09-01

Identifying genetic variants with pleiotropic associations can uncover common pathways influencing multiple cancers. We took a two-stage approach to conduct genome-wide association studies for lung, ovary, breast, prostate, and colorectal cancer from the GAME-ON/GECCO Network (61,851 cases, 61,820 controls) to identify pleiotropic loci. Findings were replicated in independent association studies (55,789 cases, 330,490 controls). We identified a novel pleiotropic association at 1q22 involving breast and lung squamous cell carcinoma, with eQTL analysis showing an association with ADAM15/THBS3 gene expression in lung. We also identified a known breast cancer locus CASP8/ALS2CR12 associated with prostate cancer, a known cancer locus at CDKN2B-AS1 with different variants associated with lung adenocarcinoma and prostate cancer, and confirmed the associations of a breast BRCA2 locus with lung and serous ovarian cancer. This is the largest study to date examining pleiotropy across multiple cancer-associated loci, identifying common mechanisms of cancer development and progression. Cancer Res; 76(17); 5103-14. ©2016 AACR. ©2016 American Association for Cancer Research.

Comparative analysis of transcriptome in two wheat genotypes with contrasting levels of drought tolerance

USDA-ARS?s Scientific Manuscript database

Drought tolerance is a complex trait that is governed by multiple genes. To identify the potential candidate genes, comparative analysis of drought stress-responsive transcriptome between drought-tolerant (Triticum aestivum Cv. C306) and drought-sensitive (Triticum aestivum Cv. WL711) genotypes was ...

Heading in the right direction: thermodynamics-based network analysis and pathway engineering.

PubMed

Ataman, Meric; Hatzimanikatis, Vassily

2015-12-01

Thermodynamics-based network analysis through the introduction of thermodynamic constraints in metabolic models allows a deeper analysis of metabolism and guides pathway engineering. The number and the areas of applications of thermodynamics-based network analysis methods have been increasing in the last ten years. We review recent applications of these methods and we identify the areas that such analysis can contribute significantly, and the needs for future developments. We find that organisms with multiple compartments and extremophiles present challenges for modeling and thermodynamics-based flux analysis. The evolution of current and new methods must also address the issues of the multiple alternatives in flux directionalities and the uncertainties and partial information from analytical methods. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Multiple Peer Group Self-Identification and Adolescent Tobacco Use

PubMed Central

Fuqua, Juliana L.; Gallaher, Peggy E.; Unger, Jennifer B.; Trinidad, Dennis R.; Sussman, Steve; Ortega, Enrique; Johnson, C. Anderson

2014-01-01

Associations between peer group self-identification and smoking were examined among 2,698 ethnically diverse middle school students in Los Angeles who self-identified with groups such as Rockers, Skaters, and Gamers. The sample was 47.1% male, 54.7% Latino, 25.4% Asian, 10.8% White, 9.1% Other ethnicity, and 59.3% children of immigrant parents. Multiple group self-identification was common: 84% identified with two or more groups and 65% identified with three or more groups. Logistic regression analyses indicated that as students endorsed more high-risk groups, the greater their risk of tobacco use. A classification tree analysis identified risk groups based on interactions among ethnicity, gender, and group self-identification. Psychographic targeting based on group self-identification could be useful to design more relevant smoking prevention messages for adolescents who identify with high-risk peer groups. PMID:22458850

Identifying Node Role in Social Network Based on Multiple Indicators

PubMed Central

Huang, Shaobin; Lv, Tianyang; Zhang, Xizhe; Yang, Yange; Zheng, Weimin; Wen, Chao

2014-01-01

It is a classic topic of social network analysis to evaluate the importance of nodes and identify the node that takes on the role of core or bridge in a network. Because a single indicator is not sufficient to analyze multiple characteristics of a node, it is a natural solution to apply multiple indicators that should be selected carefully. An intuitive idea is to select some indicators with weak correlations to efficiently assess different characteristics of a node. However, this paper shows that it is much better to select the indicators with strong correlations. Because indicator correlation is based on the statistical analysis of a large number of nodes, the particularity of an important node will be outlined if its indicator relationship doesn't comply with the statistical correlation. Therefore, the paper selects the multiple indicators including degree, ego-betweenness centrality and eigenvector centrality to evaluate the importance and the role of a node. The importance of a node is equal to the normalized sum of its three indicators. A candidate for core or bridge is selected from the great degree nodes or the nodes with great ego-betweenness centrality respectively. Then, the role of a candidate is determined according to the difference between its indicators' relationship with the statistical correlation of the overall network. Based on 18 real networks and 3 kinds of model networks, the experimental results show that the proposed methods perform quite well in evaluating the importance of nodes and in identifying the node role. PMID:25089823

Targeted quantitative analysis of Streptococcus pyogenes virulence factors by multiple reaction monitoring.

PubMed

Lange, Vinzenz; Malmström, Johan A; Didion, John; King, Nichole L; Johansson, Björn P; Schäfer, Juliane; Rameseder, Jonathan; Wong, Chee-Hong; Deutsch, Eric W; Brusniak, Mi-Youn; Bühlmann, Peter; Björck, Lars; Domon, Bruno; Aebersold, Ruedi

2008-08-01

In many studies, particularly in the field of systems biology, it is essential that identical protein sets are precisely quantified in multiple samples such as those representing differentially perturbed cell states. The high degree of reproducibility required for such experiments has not been achieved by classical mass spectrometry-based proteomics methods. In this study we describe the implementation of a targeted quantitative approach by which predetermined protein sets are first identified and subsequently quantified at high sensitivity reliably in multiple samples. This approach consists of three steps. First, the proteome is extensively mapped out by multidimensional fractionation and tandem mass spectrometry, and the data generated are assembled in the PeptideAtlas database. Second, based on this proteome map, peptides uniquely identifying the proteins of interest, proteotypic peptides, are selected, and multiple reaction monitoring (MRM) transitions are established and validated by MS2 spectrum acquisition. This process of peptide selection, transition selection, and validation is supported by a suite of software tools, TIQAM (Targeted Identification for Quantitative Analysis by MRM), described in this study. Third, the selected target protein set is quantified in multiple samples by MRM. Applying this approach we were able to reliably quantify low abundance virulence factors from cultures of the human pathogen Streptococcus pyogenes exposed to increasing amounts of plasma. The resulting quantitative protein patterns enabled us to clearly define the subset of virulence proteins that is regulated upon plasma exposure.

Identification of predictive markers of cytarabine response in AML by integrative analysis of gene-expression profiles with multiple phenotypes

PubMed Central

Lamba, Jatinder K; Crews, Kristine R; Pounds, Stanley B; Cao, Xueyuan; Gandhi, Varsha; Plunkett, William; Razzouk, Bassem I; Lamba, Vishal; Baker, Sharyn D; Raimondi, Susana C; Campana, Dario; Pui, Ching-Hon; Downing, James R; Rubnitz, Jeffrey E; Ribeiro, Raul C

2011-01-01

Aim To identify gene-expression signatures predicting cytarabine response by an integrative analysis of multiple clinical and pharmacological end points in acute myeloid leukemia (AML) patients. Materials & methods We performed an integrated analysis to associate the gene expression of diagnostic bone marrow blasts from acute myeloid leukemia (AML) patients treated in the discovery set (AML97; n = 42) and in the independent validation set (AML02; n = 46) with multiple clinical and pharmacological end points. Based on prior biological knowledge, we defined a gene to show a therapeutically beneficial (detrimental) pattern of association of its expression positively (negatively) correlated with favorable phenotypes such as intracellular cytarabine 5´-triphosphate levels, morphological response and event-free survival, and negatively (positively) correlated with unfavorable end points such as post-cytarabine DNA synthesis levels, minimal residual disease and cytarabine LC50. Results We identified 240 probe sets predicting a therapeutically beneficial pattern and 97 predicting detrimental pattern (p ≤ 0.005) in the discovery set. Of these, 60 were confirmed in the independent validation set. The validated probe sets correspond to genes involved in PIK3/PTEN/AKT/mTOR signaling, G-protein-coupled receptor signaling and leukemogenesis. This suggests that targeting these pathways as potential pharmacogenomic and therapeutic candidates could be useful for improving treatment outcomes in AML. Conclusion This study illustrates the power of integrated data analysis of genomic data as well as multiple clinical and pharmacologic end points in the identification of genes and pathways of biological relevance. PMID:21449673

Report: Analysis of Toxics Release Inventory Data Identifies Few Noncompliant Facilities

EPA Pesticide Factsheets

Report #18-P-0001, October 5, 2017. Noncompliance among facilities that must comply with multiple environmental laws or programs can be reduced by making minimal enhancements to EPA reporting software.

Change Strategies and Associated Implementation Challenges: An Analysis of Online Counselling Sessions.

PubMed

Rodda, Simone N; Hing, Nerilee; Hodgins, David C; Cheetham, Alison; Dickins, Marissa; Lubman, Dan I

2017-09-01

Self-change is the most frequent way people limit or reduce gambling involvement and often the first choice of people experiencing gambling-related problems. Less well known is the range of change strategies gamblers use and how these are selected, initiated or maintained. This study examined change strategies discussed in counselling transcripts from 149 clients who accessed a national online gambling help service in Australia. Using thematic analysis, we identified the presence of six change strategies; cash control and financial management, social support, avoiding or limiting gambling, alternative activities, changing thoughts and beliefs, and self-assessment and monitoring. Four implementation issues were also identified; a mismatch between need and strategy selection or maintenance; importance and readiness versus the cost of implementation; poor or unplanned transitions between strategies; and failure to review the helpfulness of strategies resulting in premature abandonment or unhelpful prolonged application. This study is the first to identify change strategies discussed in online counselling sessions. This study suggests change strategies are frequently discussed in online counselling sessions and we identified multiple new actions associated with change strategies that had not previously been identified. However, multiple implementation issues were identified and further work is required to determine the helpfulness of change strategies in terms of their selection, initiation and maintenance.

Differentially Variable Component Analysis (dVCA): Identifying Multiple Evoked Components using Trial-to-Trial Variability

NASA Technical Reports Server (NTRS)

Knuth, Kevin H.; Shah, Ankoor S.; Truccolo, Wilson; Ding, Ming-Zhou; Bressler, Steven L.; Schroeder, Charles E.

2003-01-01

Electric potentials and magnetic fields generated by ensembles of synchronously active neurons in response to external stimuli provide information essential to understanding the processes underlying cognitive and sensorimotor activity. Interpreting recordings of these potentials and fields is difficult as each detector records signals simultaneously generated by various regions throughout the brain. We introduce the differentially Variable Component Analysis (dVCA) algorithm, which relies on trial-to-trial variability in response amplitude and latency to identify multiple components. Using simulations we evaluate the importance of response variability to component identification, the robustness of dVCA to noise, and its ability to characterize single-trial data. Finally, we evaluate the technique using visually evoked field potentials recorded at incremental depths across the layers of cortical area VI, in an awake, behaving macaque monkey.

Significant Prognostic Factors for Completely Resected pN2 Non-small Cell Lung Cancer without Neoadjuvant Therapy

PubMed Central

Nakao, Masayuki; Mun, Mingyon; Nakagawa, Ken; Nishio, Makoto; Ishikawa, Yuichi; Okumura, Sakae

2015-01-01

Purpose: To identify prognostic factors for pathologic N2 (pN2) non-small cell lung cancer (NSCLC) treated by surgical resection. Methods: Between 1990 and 2009, 287 patients with pN2 NSCLC underwent curative resection at the Cancer Institute Hospital without preoperative treatment. Results: The 5-year overall survival (OS), cancer-specific survival (CSS), and recurrence-free survival (RFS) rates were 46%, 55% and 24%, respectively. The median follow-up time was 80 months. Multivariate analysis identified four independent predictors for poor OS: multiple-zone mediastinal lymph node metastasis (hazard ratio [HR], 1.616; p = 0.003); ipsilateral intrapulmonary metastasis (HR, 1.042; p = 0.002); tumor size >30 mm (HR, 1.013; p = 0.002); and clinical stage N1 or N2 (HR, 1.051; p = 0.030). Multivariate analysis identified three independent predictors for poor RFS: multiple-zone mediastinal lymph node metastasis (HR, 1.457; p = 0.011); ipsilateral intrapulmonary metastasis (HR, 1.040; p = 0.002); and tumor size >30 mm (HR, 1.008; p = 0.032). Conclusion: Multiple-zone mediastinal lymph node metastasis, ipsilateral intrapulmonary metastasis, and tumor size >30 mm were common independent prognostic factors of OS, CSS, and RFS in pN2 NSCLC. PMID:25740454

A multiple technique approach to the analysis of urinary calculi.

PubMed

Rodgers, A L; Nassimbeni, L R; Mulder, K J

1982-01-01

10 urinary calculi have been qualitatively and quantitatively analysed using X-ray diffraction, infra-red, scanning electron microscopy, X-ray fluorescence, atomic absorption and density gradient procedures. Constituents and compositional features which often go undetected due to limitations in the particular analytical procedure being used, have been identified and a detailed picture of each stone's composition and structure has been obtained. In all cases at least two components were detected suggesting that the multiple technique approach might cast some doubt as to the existence of "pure" stones. Evidence for a continuous, non-sequential deposition mechanism has been detected. In addition, the usefulness of each technique in the analysis of urinary stones has been assessed and the multiple technique approach has been evaluated as a whole.

A Mediation Analysis of a Tobacco Prevention Program for Adolescents in India: How Did Project MYTRI Work?

ERIC Educational Resources Information Center

Stigler, Melissa Harrell; Perry, Cheryl L.; Smolenski, Derek; Arora, Monika; Reddy, K. Srinath

2011-01-01

This article presents the results of a mediation analysis of Project MYTRI (Mobilizing Youth for Tobacco Related Initiatives in India), a randomized, controlled trial of a multiple-component, school-based tobacco prevention program for sixth- to ninth-graders (n = 14,085) in Delhi and Chennai, India. A mediation analysis identifies "how"…

Developing a national dental education research strategy: priorities, barriers and enablers

PubMed Central

Barton, Karen L; Dennis, Ashley A; Rees, Charlotte E

2017-01-01

Objectives This study aimed to identify national dental education research (DER) priorities for the next 3–5 years and to identify barriers and enablers to DER. Setting Scotland. Participants In this two-stage online questionnaire study, we collected data with multiple dental professions (eg, dentistry, dental nursing and dental hygiene) and stakeholder groups (eg, learners, clinicians, educators, managers, researchers and academics). Eighty-five participants completed the Stage 1 qualitative questionnaire and 649 participants the Stage 2 quantitative questionnaire. Results Eight themes were identified at Stage 1. Of the 24 DER priorities identified, the top three were: role of assessments in identifying competence; undergraduate curriculum prepares for practice and promoting teamwork. Following exploratory factor analysis, the 24 items loaded onto four factors: teamwork and professionalism, measuring and enhancing performance, dental workforce issues and curriculum integration and innovation. Barriers and enablers existed at multiple levels: individual, interpersonal, institutional structures and cultures and technology. Conclusions This priority setting exercise provides a necessary first step to developing a national DER strategy capturing multiple perspectives. Promoting DER requires improved resourcing alongside efforts to overcome peer stigma and lack of valuing and motivation. PMID:28360237

A Meta-analysis of Multiple Myeloma Risk Regions in African and European Ancestry Populations Identifies Putatively Functional Loci.

PubMed

Rand, Kristin A; Song, Chi; Dean, Eric; Serie, Daniel J; Curtin, Karen; Sheng, Xin; Hu, Donglei; Huff, Carol Ann; Bernal-Mizrachi, Leon; Tomasson, Michael H; Ailawadhi, Sikander; Singhal, Seema; Pawlish, Karen; Peters, Edward S; Bock, Cathryn H; Stram, Alex; Van Den Berg, David J; Edlund, Christopher K; Conti, David V; Zimmerman, Todd; Hwang, Amie E; Huntsman, Scott; Graff, John; Nooka, Ajay; Kong, Yinfei; Pregja, Silvana L; Berndt, Sonja I; Blot, William J; Carpten, John; Casey, Graham; Chu, Lisa; Diver, W Ryan; Stevens, Victoria L; Lieber, Michael R; Goodman, Phyllis J; Hennis, Anselm J M; Hsing, Ann W; Mehta, Jayesh; Kittles, Rick A; Kolb, Suzanne; Klein, Eric A; Leske, Cristina; Murphy, Adam B; Nemesure, Barbara; Neslund-Dudas, Christine; Strom, Sara S; Vij, Ravi; Rybicki, Benjamin A; Stanford, Janet L; Signorello, Lisa B; Witte, John S; Ambrosone, Christine B; Bhatti, Parveen; John, Esther M; Bernstein, Leslie; Zheng, Wei; Olshan, Andrew F; Hu, Jennifer J; Ziegler, Regina G; Nyante, Sarah J; Bandera, Elisa V; Birmann, Brenda M; Ingles, Sue A; Press, Michael F; Atanackovic, Djordje; Glenn, Martha J; Cannon-Albright, Lisa A; Jones, Brandt; Tricot, Guido; Martin, Thomas G; Kumar, Shaji K; Wolf, Jeffrey L; Deming Halverson, Sandra L; Rothman, Nathaniel; Brooks-Wilson, Angela R; Rajkumar, S Vincent; Kolonel, Laurence N; Chanock, Stephen J; Slager, Susan L; Severson, Richard K; Janakiraman, Nalini; Terebelo, Howard R; Brown, Elizabeth E; De Roos, Anneclaire J; Mohrbacher, Ann F; Colditz, Graham A; Giles, Graham G; Spinelli, John J; Chiu, Brian C; Munshi, Nikhil C; Anderson, Kenneth C; Levy, Joan; Zonder, Jeffrey A; Orlowski, Robert Z; Lonial, Sagar; Camp, Nicola J; Vachon, Celine M; Ziv, Elad; Stram, Daniel O; Hazelett, Dennis J; Haiman, Christopher A; Cozen, Wendy

2016-12-01

Genome-wide association studies (GWAS) in European populations have identified genetic risk variants associated with multiple myeloma. We performed association testing of common variation in eight regions in 1,318 patients with multiple myeloma and 1,480 controls of European ancestry and 1,305 patients with multiple myeloma and 7,078 controls of African ancestry and conducted a meta-analysis to localize the signals, with epigenetic annotation used to predict functionality. We found that variants in 7p15.3, 17p11.2, 22q13.1 were statistically significantly (P < 0.05) associated with multiple myeloma risk in persons of African ancestry and persons of European ancestry, and the variant in 3p22.1 was associated in European ancestry only. In a combined African ancestry-European ancestry meta-analysis, variation in five regions (2p23.3, 3p22.1, 7p15.3, 17p11.2, 22q13.1) was statistically significantly associated with multiple myeloma risk. In 3p22.1, the correlated variants clustered within the gene body of ULK4 Correlated variants in 7p15.3 clustered around an enhancer at the 3' end of the CDCA7L transcription termination site. A missense variant at 17p11.2 (rs34562254, Pro251Leu, OR, 1.32; P = 2.93 × 10 -7 ) in TNFRSF13B encodes a lymphocyte-specific protein in the TNF receptor family that interacts with the NF-κB pathway. SNPs correlated with the index signal in 22q13.1 cluster around the promoter and enhancer regions of CBX7 CONCLUSIONS: We found that reported multiple myeloma susceptibility regions contain risk variants important across populations, supporting the use of multiple racial/ethnic groups with different underlying genetic architecture to enhance the localization and identification of putatively functional alleles. A subset of reported risk loci for multiple myeloma has consistent effects across populations and is likely to be functional. Cancer Epidemiol Biomarkers Prev; 25(12); 1609-18. ©2016 AACR. ©2016 American Association for Cancer Research.

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.

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

ERIC Educational Resources Information Center

Ram, Nilam; Grimm, Kevin J.

2009-01-01

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

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.

On Holo-Hilbert Spectral Analysis: A Full Informational Spectral Representation for Nonlinear and Non-Stationary Data

NASA Technical Reports Server (NTRS)

Huang, Norden E.; Hu, Kun; Yang, Albert C. C.; Chang, Hsing-Chih; Jia, Deng; Liang, Wei-Kuang; Yeh, Jia Rong; Kao, Chu-Lan; Juan, Chi-Huang; Peng, Chung Kang;

On Holo-Hilbert spectral analysis: a full informational spectral representation for nonlinear and non-stationary data

PubMed Central

Huang, Norden E.; Hu, Kun; Yang, Albert C. C.; Chang, Hsing-Chih; Jia, Deng; Liang, Wei-Kuang; Yeh, Jia Rong; Kao, Chu-Lan; Juan, Chi-Hung; Peng, Chung Kang; Meijer, Johanna H.; Wang, Yung-Hung; Long, Steven R.; Wu, Zhauhua

2016-01-01

The Holo-Hilbert spectral analysis (HHSA) method is introduced to cure the deficiencies of traditional spectral analysis and to give a full informational representation of nonlinear and non-stationary data. It uses a nested empirical mode decomposition and Hilbert–Huang transform (HHT) approach to identify intrinsic amplitude and frequency modulations often present in nonlinear systems. Comparisons are first made with traditional spectrum analysis, which usually achieved its results through convolutional integral transforms based on additive expansions of an a priori determined basis, mostly under linear and stationary assumptions. Thus, for non-stationary processes, the best one could do historically was to use the time–frequency representations, in which the amplitude (or energy density) variation is still represented in terms of time. For nonlinear processes, the data can have both amplitude and frequency modulations (intra-mode and inter-mode) generated by two different mechanisms: linear additive or nonlinear multiplicative processes. As all existing spectral analysis methods are based on additive expansions, either a priori or adaptive, none of them could possibly represent the multiplicative processes. While the earlier adaptive HHT spectral analysis approach could accommodate the intra-wave nonlinearity quite remarkably, it remained that any inter-wave nonlinear multiplicative mechanisms that include cross-scale coupling and phase-lock modulations were left untreated. To resolve the multiplicative processes issue, additional dimensions in the spectrum result are needed to account for the variations in both the amplitude and frequency modulations simultaneously. HHSA accommodates all the processes: additive and multiplicative, intra-mode and inter-mode, stationary and non-stationary, linear and nonlinear interactions. The Holo prefix in HHSA denotes a multiple dimensional representation with both additive and multiplicative capabilities. PMID:26953180

Mark-recapture with multiple, non-invasive marks.

PubMed

Bonner, Simon J; Holmberg, Jason

2013-09-01

Non-invasive marks, including pigmentation patterns, acquired scars, and genetic markers, are often used to identify individuals in mark-recapture experiments. If animals in a population can be identified from multiple, non-invasive marks then some individuals may be counted twice in the observed data. Analyzing the observed histories without accounting for these errors will provide incorrect inference about the population dynamics. Previous approaches to this problem include modeling data from only one mark and combining estimators obtained from each mark separately assuming that they are independent. Motivated by the analysis of data from the ECOCEAN online whale shark (Rhincodon typus) catalog, we describe a Bayesian method to analyze data from multiple, non-invasive marks that is based on the latent-multinomial model of Link et al. (2010, Biometrics 66, 178-185). Further to this, we describe a simplification of the Markov chain Monte Carlo algorithm of Link et al. (2010, Biometrics 66, 178-185) that leads to more efficient computation. We present results from the analysis of the ECOCEAN whale shark data and from simulation studies comparing our method with the previous approaches. © 2013, The International Biometric Society.

The experiences of support persons of people newly diagnosed with multiple sclerosis: an interpretative phenomenological study.

PubMed

Strickland, Karen; Worth, Allison; Kennedy, Catriona

2015-12-01

This study explores the experience of the diagnosis of Multiple Sclerosis for the support person and identifies the impact on their lives. At the time of diagnosis, the support person may not be readily identified in a traditional caring role; however, the diagnosis itself brings with it the possibility of changes to the roles in the relationship and possible consequences for biographical construction. A hermeneutic phenomenological study. A convenience sample of nine support persons was interviewed between December 2008-March 2010. The data were analysed using interpretative phenomenological analysis. The participants in this study were often not readily identifiable as 'carers'; however, the diagnosis of Multiple Sclerosis implied a shift towards a caring role at some point in the future. The uncertainty surrounding the nature and progression of the condition left this identity hanging, incomplete and as such contributed to a liminal way of being. This paper reveals that biographical disruption is not limited to the person diagnosed with Multiple Sclerosis but that the support person also undergoes a transition to their sense of self to that of 'anticipatory carer'. The findings provide insight into the biographical and emotional impact of Multiple Sclerosis on the support persons early in the development of the condition. © 2015 John Wiley & Sons Ltd.

Combinations of Multiple Neuroimaging Markers using Logistic Regression for Auxiliary Diagnosis of Alzheimer Disease and Mild Cognitive Impairment.

PubMed

Mao, Nini; Liu, Yunting; Chen, Kewei; Yao, Li; Wu, Xia

2018-06-05

Multiple neuroimaging modalities have been developed providing various aspects of information on the human brain. Used together and properly, these complementary multimodal neuroimaging data integrate multisource information which can facilitate a diagnosis and improve the diagnostic accuracy. In this study, 3 types of brain imaging data (sMRI, FDG-PET, and florbetapir-PET) were fused in the hope to improve diagnostic accuracy, and multivariate methods (logistic regression) were applied to these trimodal neuroimaging indices. Then, the receiver-operating characteristic (ROC) method was used to analyze the outcomes of the logistic classifier, with either each index, multiples from each modality, or all indices from all 3 modalities, to investigate their differential abilities to identify the disease. With increasing numbers of indices within each modality and across modalities, the accuracy of identifying Alzheimer disease (AD) increases to varying degrees. For example, the area under the ROC curve is above 0.98 when all the indices from the 3 imaging data types are combined. Using a combination of different indices, the results confirmed the initial hypothesis that different biomarkers were potentially complementary, and thus the conjoint analysis of multiple information from multiple sources would improve the capability to identify diseases such as AD and mild cognitive impairment. © 2018 S. Karger AG, Basel.

Network meta-analysis of diagnostic test accuracy studies identifies and ranks the optimal diagnostic tests and thresholds for health care policy and decision-making.

PubMed

Owen, Rhiannon K; Cooper, Nicola J; Quinn, Terence J; Lees, Rosalind; Sutton, Alex J

2018-07-01

Network meta-analyses (NMA) have extensively been used to compare the effectiveness of multiple interventions for health care policy and decision-making. However, methods for evaluating the performance of multiple diagnostic tests are less established. In a decision-making context, we are often interested in comparing and ranking the performance of multiple diagnostic tests, at varying levels of test thresholds, in one simultaneous analysis. Motivated by an example of cognitive impairment diagnosis following stroke, we synthesized data from 13 studies assessing the efficiency of two diagnostic tests: Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA), at two test thresholds: MMSE <25/30 and <27/30, and MoCA <22/30 and <26/30. Using Markov chain Monte Carlo (MCMC) methods, we fitted a bivariate network meta-analysis model incorporating constraints on increasing test threshold, and accounting for the correlations between multiple test accuracy measures from the same study. We developed and successfully fitted a model comparing multiple tests/threshold combinations while imposing threshold constraints. Using this model, we found that MoCA at threshold <26/30 appeared to have the best true positive rate, whereas MMSE at threshold <25/30 appeared to have the best true negative rate. The combined analysis of multiple tests at multiple thresholds allowed for more rigorous comparisons between competing diagnostics tests for decision making. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

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

DTIC Science & Technology

2006-06-01

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

Factors associated with discontinuation of aripiprazole treatment after switching from other antipsychotics in patients with chronic schizophrenia: A prospective observational study.

PubMed

Takaesu, Yoshikazu; Kishimoto, Taishiro; Murakoshi, Akiko; Takahashi, Nobutada; Inoue, Yuichi

2016-02-28

The purpose of the study was to identify factors associated with discontinuation of aripiprazole after switching from other antipsychotics in patients with schizophrenia in real world clinical settings. From January 2011 to December 2012, a prospective, 48-week open-label study was undertaken. Thirty-eight subjects on antipsychotic monotherapy were switched to aripiprazole. Patients who discontinued aripiprazole were compared to those who continued with regards to demographic characteristics as well as treatment factors. Multiple regression analysis was conducted to identify predictors for aripiprazole discontinuation. Thirteen out of 38 patients (34.2%) discontinued aripiprazole during the follow up period. Nine patients (23.7%) discontinued aripiprazole due to worsening of psychotic symptoms. Multiple logistic regression analysis revealed that only the duration of previous antipsychotic treatment was associated with aripiprazole discontinuation after switching to aripiprazole. The receiver operating curve (ROC) analysis identified that the cut-off length for duration of illness to predict aripiprazole discontinuation was 10.5 years. Longer duration of illness was associated with aripiprazole discontinuation. Greater caution may be required when treating such patients with aripiprazole. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Genomic insights into the Acidobacteria reveal strategies for their success in terrestrial environments

PubMed Central

Trojan, Daniela; Roux, Simon; Herbold, Craig; Rattei, Thomas; Woebken, Dagmar

2018-01-01

Summary Members of the phylum Acidobacteria are abundant and ubiquitous across soils. We performed a large‐scale comparative genome analysis spanning subdivisions 1, 3, 4, 6, 8 and 23 (n = 24) with the goal to identify features to help explain their prevalence in soils and understand their ecophysiology. Our analysis revealed that bacteriophage integration events along with transposable and mobile elements influenced the structure and plasticity of these genomes. Low‐ and high‐affinity respiratory oxygen reductases were detected in multiple genomes, suggesting the capacity for growing across different oxygen gradients. Among many genomes, the capacity to use a diverse collection of carbohydrates, as well as inorganic and organic nitrogen sources (such as via extracellular peptidases), was detected – both advantageous traits in environments with fluctuating nutrient environments. We also identified multiple soil acidobacteria with the potential to scavenge atmospheric concentrations of H2, now encompassing mesophilic soil strains within the subdivision 1 and 3, in addition to a previously identified thermophilic strain in subdivision 4. This large‐scale acidobacteria genome analysis reveal traits that provide genomic, physiological and metabolic versatility, presumably allowing flexibility and versatility in the challenging and fluctuating soil environment. PMID:29327410

Radiogenomics: a systems biology approach to understanding genetic risk factors for radiotherapy toxicity ?

PubMed Central

Herskind, Carsten; Talbot, Christopher J.; Kerns, Sarah L.; Veldwijk, Marlon R.; Rosenstein, Barry S.; West, Catharine M. L.

2016-01-01

Adverse reactions in normal tissue after radiotherapy (RT) limit the dose that can be given to tumour cells. Since 80% of individual variation in clinical response is estimated to be caused by patient-related factors, identifying these factors might allow prediction of patients with increased risk of developing severe reactions. While inactivation of cell renewal is considered a major cause of toxicity in early-reacting normal tissues, complex interactions involving multiple cell types, cytokines, and hypoxia seem important for late reactions. Here, we review ‘omics’ approaches such as screening of genetic polymorphisms or gene expression analysis, and assess the potential of epigenetic factors, posttranslational modification, signal transduction, and metabolism. Furthermore, functional assays have suggested possible associations with clinical risk of adverse reaction. Pathway analysis incorporating different ‘omics’ approaches may be more efficient in identifying critical pathways than pathway analysis based on single ‘omics’ data sets. Integrating these pathways with functional assays may be powerful in identifying multiple subgroups of RT patients characterized by different mechanisms. Thus ‘omics’ and functional approaches may synergize if they are integrated into radiogenomics ‘systems biology’ to facilitate the goal of individualised radiotherapy. PMID:26944314

Dynamic motif occupancy (DynaMO) analysis identifies transcription factors and their binding sites driving dynamic biological processes

PubMed Central

Kuang, Zheng; Ji, Zhicheng

2018-01-01

Abstract Biological processes are usually associated with genome-wide remodeling of transcription driven by transcription factors (TFs). Identifying key TFs and their spatiotemporal binding patterns are indispensable to understanding how dynamic processes are programmed. However, most methods are designed to predict TF binding sites only. We present a computational method, dynamic motif occupancy analysis (DynaMO), to infer important TFs and their spatiotemporal binding activities in dynamic biological processes using chromatin profiling data from multiple biological conditions such as time-course histone modification ChIP-seq data. In the first step, DynaMO predicts TF binding sites with a random forests approach. Next and uniquely, DynaMO infers dynamic TF binding activities at predicted binding sites using their local chromatin profiles from multiple biological conditions. Another landmark of DynaMO is to identify key TFs in a dynamic process using a clustering and enrichment analysis of dynamic TF binding patterns. Application of DynaMO to the yeast ultradian cycle, mouse circadian clock and human neural differentiation exhibits its accuracy and versatility. We anticipate DynaMO will be generally useful for elucidating transcriptional programs in dynamic processes. PMID:29325176

Surveillance of traffic incident management-related occupational fatalities in Kentucky, 2005-2016.

PubMed

Bunn, T L; Slavova, S; Chandler, M; Hanner, N; Singleton, M

2018-05-19

Traffic incidents occurring on roadways require the coordinated effort of multiple responder and recovery entities, including communications, law enforcement, fire and rescue, emergency medical services, hazardous materials, transportation agencies, and towing and recovery. The objectives of this study were to (1) identify and characterize transportation incident management (TIM)-related occupational fatalities; (2) assess concordance of surveillance data sources in identifying TIM occupations, driver vs. pedestrian status, and occupational fatality incident location; and (3) determine and compare U.S. occupational fatality rates for TIM industries. The Kentucky Fatality Assessment and Control Evaluation (FACE) program analyzed 2005-2016 TIM occupational fatality data using multiple data sources: death certificate data, Collision Report Analysis for Safer Highways (CRASH) data, and media reports, among others. Literal text analysis was performed on FACE data, and a multiple linear regression model and SAS proc sgpanel were used to estimate and visualize the U.S. TIM occupational mortality trend lines and confidence bounds. There were 29 TIM fatalities from 2005 to 2015 in Kentucky; 41% of decedents were in the police protection occupation, and 21% each were in the fire protection and motor vehicle towing industries. Over one half of the TIM decedents were performing work activities as pedestrians when they died. Media reports identified the majority of the occupational fatalities as TIM related (28 of 29 TIM-related deaths); the use of death certificates as the sole surveillance data source only identified 17 of the 29 deaths as TIM related, and the use of CRASH data only identified 4 of the 29 deaths as TIM related. Injury scenario text analysis showed that law enforcement vehicle pursuit, towing and recovery vehicle loading, and disabled vehicle response were particular high-risk activities that led to TIM deaths. Using U.S. data, the motor vehicle towing industry had a significantly higher risk for occupational mortality compared to the fire protection and police protection industries. Multiple data sources are needed to comprehensively identify TIM fatalities and to examine the circumstances surrounding TIM fatalities, because no one data source in itself was adequate and undercounted the total number of TIM fatalities. The motor vehicle towing industry, in particular, is at elevated risk for occupational mortality, and targeted mandatory TIM training for the motor vehicle towing industry should be considered. In addition, enhanced law enforcement roadside safety training during vehicle pursuit and apprehension of suspects is recommended.

Finding Groups Using Model-Based Cluster Analysis: Heterogeneous Emotional Self-Regulatory Processes and Heavy Alcohol Use Risk

ERIC Educational Resources Information Center

Mun, Eun Young; von Eye, Alexander; Bates, Marsha E.; Vaschillo, Evgeny G.

2008-01-01

Model-based cluster analysis is a new clustering procedure to investigate population heterogeneity utilizing finite mixture multivariate normal densities. It is an inferentially based, statistically principled procedure that allows comparison of nonnested models using the Bayesian information criterion to compare multiple models and identify the…

Job Satisfaction in Mexican Faculty: An Analysis of its Predictor Variables. ASHE Annual Meeting Paper.

ERIC Educational Resources Information Center

Galaz-Fontes, Jesus Francisco; Gil-Anton, Manuel

This study examined overall job satisfaction among college faculty in Mexico. The study used data from a 1992-93 Carnegie International Faculty Survey. Secondary multiple regression analysis identified predictor variables for several faculty subgroups. Results were interpreted by differentiating between work-related and intrinsic factors, as well…

A Social Judgment Analysis of Information Source Preference Profiles: An Exploratory Study to Empirically Represent Media Selection Patterns.

ERIC Educational Resources Information Center

Stefl-Mabry, Joette

2003-01-01

Describes a study that empirically identified individual preferences profiles to understand information-seeking behavior among professional groups for six selected information sources. Highlights include Social Judgment Analysis; the development of the survey used, a copy of which is appended; hypotheses tested; results of multiple regression…

The Factor Structure of the English Language Development Assessment: A Confirmatory Factor Analysis

ERIC Educational Resources Information Center

Kuriakose, Anju

2011-01-01

This study investigated the internal factor structure of the English language development Assessment (ELDA) using confirmatory factor analysis. ELDA is an English language proficiency test developed by a consortium of multiple states and is used to identify and reclassify English language learners in kindergarten to grade 12. Scores on item…

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

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.

Integrative analysis of GWAS, eQTLs and meQTLs data suggests that multiple gene sets are associated with bone mineral density.

PubMed

Wang, W; Huang, S; Hou, W; Liu, Y; Fan, Q; He, A; Wen, Y; Hao, J; Guo, X; Zhang, F

2017-10-01

Several genome-wide association studies (GWAS) of bone mineral density (BMD) have successfully identified multiple susceptibility genes, yet isolated susceptibility genes are often difficult to interpret biologically. The aim of this study was to unravel the genetic background of BMD at pathway level, by integrating BMD GWAS data with genome-wide expression quantitative trait loci (eQTLs) and methylation quantitative trait loci (meQTLs) data METHOD: We employed the GWAS datasets of BMD from the Genetic Factors for Osteoporosis Consortium (GEFOS), analysing patients' BMD. The areas studied included 32 735 femoral necks, 28 498 lumbar spines, and 8143 forearms. Genome-wide eQTLs (containing 923 021 eQTLs) and meQTLs (containing 683 152 unique methylation sites with local meQTLs) data sets were collected from recently published studies. Gene scores were first calculated by summary data-based Mendelian randomisation (SMR) software and meQTL-aligned GWAS results. Gene set enrichment analysis (GSEA) was then applied to identify BMD-associated gene sets with a predefined significance level of 0.05. We identified multiple gene sets associated with BMD in one or more regions, including relevant known biological gene sets such as the Reactome Circadian Clock (GSEA p-value = 1.0 × 10 -4 for LS and 2.7 × 10 -2 for femoral necks BMD in eQTLs-based GSEA) and insulin-like growth factor receptor binding (GSEA p-value = 5.0 × 10 -4 for femoral necks and 2.6 × 10 -2 for lumbar spines BMD in meQTLs-based GSEA). Our results provided novel clues for subsequent functional analysis of bone metabolism, and illustrated the benefit of integrating eQTLs and meQTLs data into pathway association analysis for genetic studies of complex human diseases. Cite this article : W. Wang, S. Huang, W. Hou, Y. Liu, Q. Fan, A. He, Y. Wen, J. Hao, X. Guo, F. Zhang. Integrative analysis of GWAS, eQTLs and meQTLs data suggests that multiple gene sets are associated with bone mineral density. Bone Joint Res 2017;6:572-576. © 2017 Wang et al.

Clustering Multiple Sclerosis Subgroups with Multifractal Methods and Self-Organizing Map Algorithm

NASA Astrophysics Data System (ADS)

Karaca, Yeliz; Cattani, Carlo

Magnetic resonance imaging (MRI) is the most sensitive method to detect chronic nervous system diseases such as multiple sclerosis (MS). In this paper, Brownian motion Hölder regularity functions (polynomial, periodic (sine), exponential) for 2D image, such as multifractal methods were applied to MR brain images, aiming to easily identify distressed regions, in MS patients. With these regions, we have proposed an MS classification based on the multifractal method by using the Self-Organizing Map (SOM) algorithm. Thus, we obtained a cluster analysis by identifying pixels from distressed regions in MR images through multifractal methods and by diagnosing subgroups of MS patients through artificial neural networks.

Network Analysis of Rodent Transcriptomes in Spaceflight

NASA Technical Reports Server (NTRS)

Ramachandran, Maya; Fogle, Homer; Costes, Sylvain

2017-01-01

Network analysis methods leverage prior knowledge of cellular systems and the statistical and conceptual relationships between analyte measurements to determine gene connectivity. Correlation and conditional metrics are used to infer a network topology and provide a systems-level context for cellular responses. Integration across multiple experimental conditions and omics domains can reveal the regulatory mechanisms that underlie gene expression. GeneLab has assembled rich multi-omic (transcriptomics, proteomics, epigenomics, and epitranscriptomics) datasets for multiple murine tissues from the Rodent Research 1 (RR-1) experiment. RR-1 assesses the impact of 37 days of spaceflight on gene expression across a variety of tissue types, such as adrenal glands, quadriceps, gastrocnemius, tibalius anterior, extensor digitorum longus, soleus, eye, and kidney. Network analysis is particularly useful for RR-1 -omics datasets because it reinforces subtle relationships that may be overlooked in isolated analyses and subdues confounding factors. Our objective is to use network analysis to determine potential target nodes for therapeutic intervention and identify similarities with existing disease models. Multiple network algorithms are used for a higher confidence consensus.

Integrated Analysis of Pharmacologic, Clinical, and SNP Microarray Data using Projection onto the Most Interesting Statistical Evidence with Adaptive Permutation Testing

PubMed Central

Pounds, Stan; Cao, Xueyuan; Cheng, Cheng; Yang, Jun; Campana, Dario; Evans, William E.; Pui, Ching-Hon; Relling, Mary V.

2010-01-01

Powerful methods for integrated analysis of multiple biological data sets are needed to maximize interpretation capacity and acquire meaningful knowledge. We recently developed Projection Onto the Most Interesting Statistical Evidence (PROMISE). PROMISE is a statistical procedure that incorporates prior knowledge about the biological relationships among endpoint variables into an integrated analysis of microarray gene expression data with multiple biological and clinical endpoints. Here, PROMISE is adapted to the integrated analysis of pharmacologic, clinical, and genome-wide genotype data that incorporating knowledge about the biological relationships among pharmacologic and clinical response data. An efficient permutation-testing algorithm is introduced so that statistical calculations are computationally feasible in this higher-dimension setting. The new method is applied to a pediatric leukemia data set. The results clearly indicate that PROMISE is a powerful statistical tool for identifying genomic features that exhibit a biologically meaningful pattern of association with multiple endpoint variables. PMID:21516175

Nonlinear Predictive Models for Multiple Mediation Analysis: With an Application to Explore Ethnic Disparities in Anxiety and Depression Among Cancer Survivors.

PubMed

Yu, Qingzhao; Medeiros, Kaelen L; Wu, Xiaocheng; Jensen, Roxanne E

2018-04-02

Mediation analysis allows the examination of effects of a third variable (mediator/confounder) in the causal pathway between an exposure and an outcome. The general multiple mediation analysis method (MMA), proposed by Yu et al., improves traditional methods (e.g., estimation of natural and controlled direct effects) to enable consideration of multiple mediators/confounders simultaneously and the use of linear and nonlinear predictive models for estimating mediation/confounding effects. Previous studies find that compared with non-Hispanic cancer survivors, Hispanic survivors are more likely to endure anxiety and depression after cancer diagnoses. In this paper, we applied MMA on MY-Health study to identify mediators/confounders and quantify the indirect effect of each identified mediator/confounder in explaining ethnic disparities in anxiety and depression among cancer survivors who enrolled in the study. We considered a number of socio-demographic variables, tumor characteristics, and treatment factors as potential mediators/confounders and found that most of the ethnic differences in anxiety or depression between Hispanic and non-Hispanic white cancer survivors were explained by younger diagnosis age, lower education level, lower proportions of employment, less likely of being born in the USA, less insurance, and less social support among Hispanic patients.

Multiple fault separation and detection by joint subspace learning for the health assessment of wind turbine gearboxes

NASA Astrophysics Data System (ADS)

Du, Zhaohui; Chen, Xuefeng; Zhang, Han; Zi, Yanyang; Yan, Ruqiang

2017-09-01

The gearbox of a wind turbine (WT) has dominant failure rates and highest downtime loss among all WT subsystems. Thus, gearbox health assessment for maintenance cost reduction is of paramount importance. The concurrence of multiple faults in gearbox components is a common phenomenon due to fault induction mechanism. This problem should be considered before planning to replace the components of the WT gearbox. Therefore, the key fault patterns should be reliably identified from noisy observation data for the development of an effective maintenance strategy. However, most of the existing studies focusing on multiple fault diagnosis always suffer from inappropriate division of fault information in order to satisfy various rigorous decomposition principles or statistical assumptions, such as the smooth envelope principle of ensemble empirical mode decomposition and the mutual independence assumption of independent component analysis. Thus, this paper presents a joint subspace learning-based multiple fault detection (JSL-MFD) technique to construct different subspaces adaptively for different fault patterns. Its main advantage is its capability to learn multiple fault subspaces directly from the observation signal itself. It can also sparsely concentrate the feature information into a few dominant subspace coefficients. Furthermore, it can eliminate noise by simply performing coefficient shrinkage operations. Consequently, multiple fault patterns are reliably identified by utilizing the maximum fault information criterion. The superiority of JSL-MFD in multiple fault separation and detection is comprehensively investigated and verified by the analysis of a data set of a 750 kW WT gearbox. Results show that JSL-MFD is superior to a state-of-the-art technique in detecting hidden fault patterns and enhancing detection accuracy.

Classification and Clustering Methods for Multiple Environmental Factors in Gene-Environment Interaction: Application to the Multi-Ethnic Study of Atherosclerosis.

PubMed

Ko, Yi-An; Mukherjee, Bhramar; Smith, Jennifer A; Kardia, Sharon L R; Allison, Matthew; Diez Roux, Ana V

2016-11-01

There has been an increased interest in identifying gene-environment interaction (G × E) in the context of multiple environmental exposures. Most G × E studies analyze one exposure at a time, but we are exposed to multiple exposures in reality. Efficient analysis strategies for complex G × E with multiple environmental factors in a single model are still lacking. Using the data from the Multiethnic Study of Atherosclerosis, we illustrate a two-step approach for modeling G × E with multiple environmental factors. First, we utilize common clustering and classification strategies (e.g., k-means, latent class analysis, classification and regression trees, Bayesian clustering using Dirichlet Process) to define subgroups corresponding to distinct environmental exposure profiles. Second, we illustrate the use of an additive main effects and multiplicative interaction model, instead of the conventional saturated interaction model using product terms of factors, to study G × E with the data-driven exposure subgroups defined in the first step. We demonstrate useful analytical approaches to translate multiple environmental exposures into one summary class. These tools not only allow researchers to consider several environmental exposures in G × E analysis but also provide some insight into how genes modify the effect of a comprehensive exposure profile instead of examining effect modification for each exposure in isolation.

Critical Success Factors for E-Learning in Developing Countries: A Comparative Analysis between ICT Experts and Faculty

ERIC Educational Resources Information Center

Bhuasiri, Wannasiri; Xaymoungkhoun, Oudone; Zo, Hangjung; Rho, Jae Jeung; Ciganek, Andrew P.

2012-01-01

This study identifies the critical success factors that influence the acceptance of e-learning systems in developing countries. E-learning is a popular mode of delivering educational materials in higher education by universities throughout the world. This study identifies multiple factors that influence the success of e-learning systems from the…

Use of Case History Data for the Development of Equations in Predicting High Risk, Reading Disabled Students.

ERIC Educational Resources Information Center

Stratton, Beverly D.; And Others

Demographic data on 92 subjects identified as having reading problems were used to develop equations useful in identifying high risk, reading disabled students. Multiple linear regression analysis of the data indicated that reading disability (1) had a significant positive relationship with birth order and number of siblings; (2) had a positive…

Analysis of the resilience of team performance during a nuclear emergency response exercise.

PubMed

Gomes, José Orlando; Borges, Marcos R S; Huber, Gilbert J; Carvalho, Paulo Victor R

2014-05-01

The current work presents results from a cognitive task analysis (CTA) of a nuclear disaster simulation. Audio-visual records were collected from an emergency room team composed of individuals from 26 different agencies as they responded to multiple scenarios in a simulated nuclear disaster. This simulation was part of a national emergency response training activity for a nuclear power plant located in a developing country. The objectives of this paper are to describe sources of resilience and brittleness in these activities, identify cues of potential improvements for future emergency simulations, and leveraging the resilience of the emergency response system in case of a real disaster. Multiple CTA techniques were used to gain a better understanding of the cognitive dimensions of the activity and to identify team coordination and crisis management patterns that emerged from the simulation exercises. Copyright © 2013 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Effect of partition board color on mood and autonomic nervous function.

PubMed

Sakuragi, Sokichi; Sugiyama, Yoshiki

2011-12-01

The purpose of this study was to evaluate the effects of the presence or absence (control) of a partition board and its color (red, yellow, blue) on subjective mood ratings and changes in autonomic nervous system indicators induced by a video game task. The increase in the mean Profile of Mood States (POMS) Fatigue score and mean Oppressive feeling rating after the task was lowest with the blue partition board. Multiple-regression analysis identified oppressive feeling and error scores on the second half of the task as statistically significant contributors to Fatigue. While explanatory variables were limited to the physiological indices, multiple-regression analysis identified a significant contribution of autonomic reactivity (assessed by heart rate variability) to Fatigue. These results suggest that a blue partition board would reduce task-induced subjective fatigue, in part by lowering the oppressive feeling of being enclosed during the task, possibly by increasing autonomic reactivity.

integIRTy: a method to identify genes altered in cancer by accounting for multiple mechanisms of regulation using item response theory.

PubMed

Tong, Pan; Coombes, Kevin R

2012-11-15

Identifying genes altered in cancer plays a crucial role in both understanding the mechanism of carcinogenesis and developing novel therapeutics. It is known that there are various mechanisms of regulation that can lead to gene dysfunction, including copy number change, methylation, abnormal expression, mutation and so on. Nowadays, all these types of alterations can be simultaneously interrogated by different types of assays. Although many methods have been proposed to identify altered genes from a single assay, there is no method that can deal with multiple assays accounting for different alteration types systematically. In this article, we propose a novel method, integration using item response theory (integIRTy), to identify altered genes by using item response theory that allows integrated analysis of multiple high-throughput assays. When applied to a single assay, the proposed method is more robust and reliable than conventional methods such as Student's t-test or the Wilcoxon rank-sum test. When used to integrate multiple assays, integIRTy can identify novel-altered genes that cannot be found by looking at individual assay separately. We applied integIRTy to three public cancer datasets (ovarian carcinoma, breast cancer, glioblastoma) for cross-assay type integration which all show encouraging results. The R package integIRTy is available at the web site http://bioinformatics.mdanderson.org/main/OOMPA:Overview. kcoombes@mdanderson.org. Supplementary data are available at Bioinformatics online.

Structural-Vibration-Response Data Analysis

NASA Technical Reports Server (NTRS)

Smith, W. R.; Hechenlaible, R. N.; Perez, R. C.

1983-01-01

Computer program developed as structural-vibration-response data analysis tool for use in dynamic testing of Space Shuttle. Program provides fast and efficient time-domain least-squares curve-fitting procedure for reducing transient response data to obtain structural model frequencies and dampings from free-decay records. Procedure simultaneously identifies frequencies, damping values, and participation factors for noisy multiple-response records.

Conflagration Analysis System II: Bibliography.

DTIC Science & Technology

1985-04-01

Therefore, it is Lmportant to examine both the reinforcement and the supplemental considerations Eor the quantitative methods for conflagration...and the meaningful quantitative factors for conflagration analysis are determined, the relevatn literature will be brought into the nainstream of the... quantitative :hods. Fire Development in Multiple Structures From a purely analytical view, the research identified in the literature fire development in

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.

A Critical Examination of the Introduction of Drug Detection Dogs for Policing of Illicit Drugs in New South Wales, Australia Using Kingdon's "Multiple Streams" Heuristic

ERIC Educational Resources Information Center

Lancaster, Kari; Ritter, Alison; Hughes, Caitlin; Hoppe, Robert

2017-01-01

This paper critically analyses the introduction of drug detection dogs as a tool for policing of illicit drugs in New South Wales, Australia. Using Kingdon's "multiple streams" heuristic as a lens for analysis, we identify how the issue of drugs policing became prominent on the policy agenda, and the conditions under which the…

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.

A multiple-dimension liquid chromatography coupled with mass spectrometry data strategy for the rapid discovery and identification of unknown compounds from a Chinese herbal formula (Er-xian decoction).

PubMed

Wang, Caihong; Zhang, Jinlan; Wu, Caisheng; Wang, Zhe

2017-10-06

It is very important to rapidly discover and identify the multiple components of traditional Chinese medicine (TCM) formula. High performance liquid chromatography with high resolution tandem mass spectrometry (HPLC-HRMS/MS) has been widely used to analyze TCM formula and contains multiple-dimension data including retention time (RT), high resolution mass (HRMS), multiple-stage mass spectrometric (MS n ), and isotope intensity distribution (IID) data. So it is very necessary to exploit a useful strategy to utilize multiple-dimension data to rapidly probe structural information and identify chemical compounds. In this study, a new strategy to initiatively use the multiple-dimension LC-MS data has been developed to discover and identify unknown compounds of TCM in many styles. The strategy guarantees the fast discovery of candidate structural information and provides efficient structure clues for identification. The strategy contains four steps in sequence: (1) to discover potential compounds and obtain sub-structure information by the mass spectral tree similarity filter (MTSF) technique, based on HRMS and MS n data; (2) to classify potential compounds into known chemical classes by discriminant analysis (DA) on the basis of RT and HRMS data; (3) to hit the candidate structural information of compounds by intersection sub-structure between MTSF and DA (M,D-INSS); (4) to annotate and confirm candidate structures by IID data. This strategy allowed for the high exclusion efficiency (greater than 41%) of irrelevant ions in er-xian decoction (EXD) while providing accurate structural information of 553 potential compounds and identifying 66 candidates, therefore accelerating and simplifying the discovery and identification of unknown compounds in TCM formula. Copyright © 2017 Elsevier B.V. All rights reserved.

Identification of FGF7 as a novel susceptibility locus for chronic obstructive pulmonary disease.

PubMed

Brehm, John M; Hagiwara, Koichi; Tesfaigzi, Yohannes; Bruse, Shannon; Mariani, Thomas J; Bhattacharya, Soumyaroop; Boutaoui, Nadia; Ziniti, John P; Soto-Quiros, Manuel E; Avila, Lydiana; Cho, Michael H; Himes, Blanca; Litonjua, Augusto A; Jacobson, Francine; Bakke, Per; Gulsvik, Amund; Anderson, Wayne H; Lomas, David A; Forno, Erick; Datta, Soma; Silverman, Edwin K; Celedón, Juan C

2011-12-01

Traditional genome-wide association studies (GWASs) of large cohorts of subjects with chronic obstructive pulmonary disease (COPD) have successfully identified novel candidate genes, but several other plausible loci do not meet strict criteria for genome-wide significance after correction for multiple testing. The authors hypothesise that by applying unbiased weights derived from unique populations we can identify additional COPD susceptibility loci. Methods The authors performed a homozygosity haplotype analysis on a group of subjects with and without COPD to identify regions of conserved homozygosity haplotype (RCHHs). Weights were constructed based on the frequency of these RCHHs in case versus controls, and used to adjust the p values from a large collaborative GWAS of COPD. The authors identified 2318 RCHHs, of which 576 were significantly (p<0.05) over-represented in cases. After applying the weights constructed from these regions to a collaborative GWAS of COPD, the authors identified two single nucleotide polymorphisms (SNPs) in a novel gene (fibroblast growth factor-7 (FGF7)) that gained genome-wide significance by the false discovery rate method. In a follow-up analysis, both SNPs (rs12591300 and rs4480740) were significantly associated with COPD in an independent population (combined p values of 7.9E-7 and 2.8E-6, respectively). In another independent population, increased lung tissue FGF7 expression was associated with worse measures of lung function. Weights constructed from a homozygosity haplotype analysis of an isolated population successfully identify novel genetic associations from a GWAS on a separate population. This method can be used to identify promising candidate genes that fail to meet strict correction for multiple testing.

A network analysis of the Chinese medicine Lianhua-Qingwen formula to identify its main effective components.

PubMed

Wang, Chun-Hua; Zhong, Yi; Zhang, Yan; Liu, Jin-Ping; Wang, Yue-Fei; Jia, Wei-Na; Wang, Guo-Cai; Li, Zheng; Zhu, Yan; Gao, Xiu-Mei

2016-02-01

Chinese medicine is known to treat complex diseases with multiple components and multiple targets. However, the main effective components and their related key targets and functions remain to be identified. Herein, a network analysis method was developed to identify the main effective components and key targets of a Chinese medicine, Lianhua-Qingwen Formula (LQF). The LQF is commonly used for the prevention and treatment of viral influenza in China. It is composed of 11 herbs, gypsum and menthol with 61 compounds being identified in our previous work. In this paper, these 61 candidate compounds were used to find their related targets and construct the predicted-target (PT) network. An influenza-related protein-protein interaction (PPI) network was constructed and integrated with the PT network. Then the compound-effective target (CET) network and compound-ineffective target network (CIT) were extracted, respectively. A novel approach was developed to identify effective components by comparing CET and CIT networks. As a result, 15 main effective components were identified along with 61 corresponding targets. 7 of these main effective components were further experimentally validated to have antivirus efficacy in vitro. The main effective component-target (MECT) network was further constructed with main effective components and their key targets. Gene Ontology (GO) analysis of the MECT network predicted key functions such as NO production being modulated by the LQF. Interestingly, five effective components were experimentally tested and exhibited inhibitory effects on NO production in the LPS induced RAW 264.7 cell. In summary, we have developed a novel approach to identify the main effective components in a Chinese medicine LQF and experimentally validated some of the predictions.

HRCT findings of collagen vascular disease-related interstitial pneumonia (CVD-IP): a comparative study among individual underlying diseases.

PubMed

Tanaka, N; Kunihiro, Y; Kubo, M; Kawano, R; Oishi, K; Ueda, K; Gondo, T

2018-05-29

To identify characteristic high-resolution computed tomography (CT) findings for individual collagen vascular disease (CVD)-related interstitial pneumonias (IPs). The HRCT findings of 187 patients with CVD, including 55 patients with rheumatoid arthritis (RA), 50 with systemic sclerosis (SSc), 46 with polymyositis/dermatomyositis (PM/DM), 15 with mixed connective tissue disease, 11 with primary Sjögren's syndrome, and 10 with systemic lupus erythematosus, were evaluated. Lung parenchymal abnormalities were compared among CVDs using χ 2 test, Kruskal-Wallis test, and multiple logistic regression analysis. A CT-pathology correlation was performed in 23 patients. In RA-IP, honeycombing was identified as the significant indicator based on multiple logistic regression analyses. Traction bronchiectasis (81.8%) was further identified as the most frequent finding based on χ 2 test. In SSc IP, lymph node enlargement and oesophageal dilatation were identified as the indicators based on multiple logistic regression analyses, and ground-glass opacity (GGO) was the most extensive based on Kruskal-Wallis test, which reflects the higher frequency of the pathological nonspecific interstitial pneumonia (NSIP) pattern present in the CT-pathology correlation. In PM/DM IP, airspace consolidation and the absence of honeycombing were identified as the indicators based on multiple logistic regression analyses, and predominance of consolidation over GGO (32.6%) and predominant subpleural distribution of GGO/consolidation (41.3%) were further identified as the most frequent findings based on χ 2 test, which reflects the higher frequency of the pathological NSIP and/or the organising pneumonia patterns present in the CT-pathology correlation. Several characteristic high-resolution CT findings with utility for estimating underlying CVD were identified. Copyright © 2018 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Real-world persistence with fingolimod for the treatment of multiple sclerosis: A systematic review and meta-analysis.

PubMed

Kantor, Daniel; Johnson, Kristen; Vieira, Maria Cecilia; Signorovitch, James; Li, Nanxin; Gao, Wei; Koo, Valerie; Duchesneau, Emilie; Herrera, Vivian

2018-05-15

To systematically review reports of fingolimod persistence in the treatment of relapsing-remitting multiple sclerosis (RRMS) across data sources and practice settings, and to develop a consensus estimate of the 1-year real-world persistence rate. A systematic literature review was conducted (MEDLINE, EMBASE, and abstracts from selected conferences [2013-2015]) to identify observational studies reporting 1-year fingolimod persistence among adult patients with RRMS (sample size ≥50). A random-effects meta-analysis was performed to estimate a synthesized 1-year persistence rate and to assess heterogeneity across studies. Of 527 publications identified, 25 real-world studies reporting 1-year fingolimod persistence rates were included. The studies included patients from different data sources (e.g., administrative claims, electronic medical records, or registries), used different definitions of persistence (e.g., based on prescriptions refills, patient report, or prescription orders), and spanned multiple geographic regions. Reported 1-year persistence rates ranged from 72%-100%, and exhibited statistical evidence of heterogeneity (I 2  = 93% of the variability due to heterogeneity across studies). The consensus estimate of the 1-year persistence rate was 82% (95% confidence interval: 79%-85%). Across heterogeneous study designs and patient populations found in real-world studies, the consensus 1-year fingolimod persistence rate exceeded 80%, consistent with persistence rates identified in the recently-completed trial, PREFERMS. Copyright © 2018. Published by Elsevier B.V.

Discrimination of biological and chemical threat simulants in residue mixtures on multiple substrates.

PubMed

Gottfried, Jennifer L

2011-07-01

The potential of laser-induced breakdown spectroscopy (LIBS) to discriminate biological and chemical threat simulant residues prepared on multiple substrates and in the presence of interferents has been explored. The simulant samples tested include Bacillus atrophaeus spores, Escherichia coli, MS-2 bacteriophage, α-hemolysin from Staphylococcus aureus, 2-chloroethyl ethyl sulfide, and dimethyl methylphosphonate. The residue samples were prepared on polycarbonate, stainless steel and aluminum foil substrates by Battelle Eastern Science and Technology Center. LIBS spectra were collected by Battelle on a portable LIBS instrument developed by A3 Technologies. This paper presents the chemometric analysis of the LIBS spectra using partial least-squares discriminant analysis (PLS-DA). The performance of PLS-DA models developed based on the full LIBS spectra, and selected emission intensities and ratios have been compared. The full-spectra models generally provided better classification results based on the inclusion of substrate emission features; however, the intensity/ratio models were able to correctly identify more types of simulant residues in the presence of interferents. The fusion of the two types of PLS-DA models resulted in a significant improvement in classification performance for models built using multiple substrates. In addition to identifying the major components of residue mixtures, minor components such as growth media and solvents can be identified with an appropriately designed PLS-DA model.

A Three-Step Latent Class Analysis to Identify How Different Patterns of Teen Dating Violence and Psychosocial Factors Influence Mental Health.

PubMed

Choi, Hye Jeong; Weston, Rebecca; Temple, Jeff R

2017-04-01

Although multiple forms (i.e., physical, threatening, psychological, sexual, and relational abuse) and patterns (i.e., perpetration and victimization) of violence can co-occur, most existing research examines these experiences individually. Thus, the purpose of this study is to investigate: (1) homogenous subgroups based on victimization and perpetration of multiple forms of teen dating violence; (2) predictors of membership in these subgroups; and (3) mental health consequences associated with membership in each subgroup. Nine hundred eighteen adolescents in the 9 th or 10 th grade at seven public high schools in Texas participated in the survey (56 % female, White: 30 %, Hispanic: 32 %, African American: 29 %, others: 9 %). A three-step latent class analysis was employed. Five latent teen dating violence classes were identified: (1) nonviolence; (2) emotional/verbal abuse; (3) forced sexual contact; (4) psychological + physical violence; and (5) psychological abuse. Females, African Americans, and youth who had higher acceptance of couple violence scores and whose parents had less education were more likely to members of dating violence classes compared with the nonviolence class. Adolescents who experienced multiple types of dating violence reported greater mental health concerns. Prevention programs may benefit by identifying the homogenous subgroups of teen dating violence and targeting adolescent teen dating violence accordingly.

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

USGS Publications Warehouse

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

1998-01-01

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

KinView: A visual comparative sequence analysis tool for integrated kinome research

PubMed Central

McSkimming, Daniel Ian; Dastgheib, Shima; Baffi, Timothy R.; Byrne, Dominic P.; Ferries, Samantha; Scott, Steven Thomas; Newton, Alexandra C.; Eyers, Claire E.; Kochut, Krzysztof J.; Eyers, Patrick A.

2017-01-01

Multiple sequence alignments (MSAs) are a fundamental analysis tool used throughout biology to investigate relationships between protein sequence, structure, function, evolutionary history, and patterns of disease-associated variants. However, their widespread application in systems biology research is currently hindered by the lack of user-friendly tools to simultaneously visualize, manipulate and query the information conceptualized in large sequence alignments, and the challenges in integrating MSAs with multiple orthogonal data such as cancer variants and post-translational modifications, which are often stored in heterogeneous data sources and formats. Here, we present the Multiple Sequence Alignment Ontology (MSAOnt), which represents a profile or consensus alignment in an ontological format. Subsets of the alignment are easily selected through the SPARQL Protocol and RDF Query Language for downstream statistical analysis or visualization. We have also created the Kinome Viewer (KinView), an interactive integrative visualization that places eukaryotic protein kinase cancer variants in the context of natural sequence variation and experimentally determined post-translational modifications, which play central roles in the regulation of cellular signaling pathways. Using KinView, we identified differential phosphorylation patterns between tyrosine and serine/threonine kinases in the activation segment, a major kinase regulatory region that is often mutated in proliferative diseases. We discuss cancer variants that disrupt phosphorylation sites in the activation segment, and show how KinView can be used as a comparative tool to identify differences and similarities in natural variation, cancer variants and post-translational modifications between kinase groups, families and subfamilies. Based on KinView comparisons, we identify and experimentally characterize a regulatory tyrosine (Y177PLK4) in the PLK4 C-terminal activation segment region termed the P+1 loop. To further demonstrate the application of KinView in hypothesis generation and testing, we formulate and validate a hypothesis explaining a novel predicted loss-of-function variant (D523NPKCβ) in the regulatory spine of PKCβ, a recently identified tumor suppressor kinase. KinView provides a novel, extensible interface for performing comparative analyses between subsets of kinases and for integrating multiple types of residue specific annotations in user friendly formats. PMID:27731453

Generating cancelable fingerprint templates.

PubMed

Ratha, Nalini K; Chikkerur, Sharat; Connell, Jonathan H; Bolle, Ruud M

2007-04-01

Biometrics-based authentication systems offer obvious usability advantages over traditional password and token-based authentication schemes. However, biometrics raises several privacy concerns. A biometric is permanently associated with a user and cannot be changed. Hence, if a biometric identifier is compromised, it is lost forever and possibly for every application where the biometric is used. Moreover, if the same biometric is used in multiple applications, a user can potentially be tracked from one application to the next by cross-matching biometric databases. In this paper, we demonstrate several methods to generate multiple cancelable identifiers from fingerprint images to overcome these problems. In essence, a user can be given as many biometric identifiers as needed by issuing a new transformation "key." The identifiers can be cancelled and replaced when compromised. We empirically compare the performance of several algorithms such as Cartesian, polar, and surface folding transformations of the minutiae positions. It is demonstrated through multiple experiments that we can achieve revocability and prevent cross-matching of biometric databases. It is also shown that the transforms are noninvertible by demonstrating that it is computationally as hard to recover the original biometric identifier from a transformed version as by randomly guessing. Based on these empirical results and a theoretical analysis we conclude that feature-level cancelable biometric construction is practicable in large biometric deployments.

Developing a national dental education research strategy: priorities, barriers and enablers.

PubMed

Ajjawi, Rola; Barton, Karen L; Dennis, Ashley A; Rees, Charlotte E

2017-03-29

This study aimed to identify national dental education research (DER) priorities for the next 3-5 years and to identify barriers and enablers to DER. Scotland. In this two-stage online questionnaire study, we collected data with multiple dental professions (eg, dentistry, dental nursing and dental hygiene) and stakeholder groups (eg, learners, clinicians, educators, managers, researchers and academics). Eighty-five participants completed the Stage 1 qualitative questionnaire and 649 participants the Stage 2 quantitative questionnaire. Eight themes were identified at Stage 1. Of the 24 DER priorities identified, the top three were: role of assessments in identifying competence; undergraduate curriculum prepares for practice and promoting teamwork. Following exploratory factor analysis, the 24 items loaded onto four factors: teamwork and professionalism, measuring and enhancing performance, dental workforce issues and curriculum integration and innovation. Barriers and enablers existed at multiple levels: individual, interpersonal, institutional structures and cultures and technology. This priority setting exercise provides a necessary first step to developing a national DER strategy capturing multiple perspectives. Promoting DER requires improved resourcing alongside efforts to overcome peer stigma and lack of valuing and motivation. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Evaluation of longitudinal tracking and data mining for an imaging informatics-based multiple sclerosis e-folder (Conference Presentation)

NASA Astrophysics Data System (ADS)

Ma, Kevin C.; Forsyth, Sydney; Amezcua, Lilyana; Liu, Brent J.

2017-03-01

We have designed and developed a multiple sclerosis eFolder system for patient data storage, image viewing, and automatic lesion quantification results to allow patient tracking. The web-based system aims to be integrated in DICOM-compliant clinical and research environments to aid clinicians in patient treatments and data analysis. The system quantifies lesion volumes, identify and register lesion locations to track shifts in volume and quantity of lesions in a longitudinal study. We aim to evaluate the two most important features of the system, data mining and longitudinal lesion tracking, to demonstrate the MS eFolder's capability in improving clinical workflow efficiency and outcome analysis for research. In order to evaluate data mining capabilities, we have collected radiological and neurological data from 72 patients, 36 Caucasian and 36 Hispanic matched by gender, disease duration, and age. Data analysis on those patients based on ethnicity is performed, and analysis results are displayed by the system's web-based user interface. The data mining module is able to successfully separate Hispanic and Caucasian patients and compare their disease profiles. For longitudinal lesion tracking, we have collected 4 longitudinal cases and simulated different lesion growths over the next year. As a result, the eFolder is able to detect changes in lesion volume and identifying lesions with the most changes. Data mining and lesion tracking evaluation results show high potential of eFolder's usefulness in patientcare and informatics research for multiple sclerosis.

What Does Empowerment in Literacy Education Look Like? An Analysis of a Family Literacy Program for Guatemalan Maya Families

ERIC Educational Resources Information Center

Schoorman, Dilys; Zainuddin, Hanizah

2008-01-01

Educators in the field of "family literacy" have identified multiple approaches to family literacy programs (FLPs), and have underscored the need to identify and make explicit the philosophical orientations of their own programs. This was the task undertaken in this article, which focused on a FLP in south Florida that served the needs…

The Image of Women in the National Education Text Books in Jordan

ERIC Educational Resources Information Center

Al-Khalidi, Nasiema Mustafa Sadeq

2016-01-01

The study aimed to identify the image of women and how it was dealt with in the National Education books in Jordan, where the content of the National Education books analyzed and for multiple age stages, also it addressed the content analysis of images, concepts and fees, activities and evaluation to identify the image of women in the family, at…

Physical activity and exercise training in multiple sclerosis: a review and content analysis of qualitative research identifying perceived determinants and consequences.

PubMed

Learmonth, Yvonne C; Motl, Robert W

2016-01-01

This systematic review was conducted to provide rich and deep evidence of the perceived determinants and consequences of physical activity and exercise based on qualitative research in multiple sclerosis (MS). Electronic databases and article reference lists were searched to identify qualitative studies of physical activity and exercise in MS. Studies were included if they were written in English and examined consequences/determinants of physical activity in persons with MS. Content analysis of perceived determinants and consequences of physical activity and exercise was undertaken using an inductive analysis guided by the Physical Activity for people with Disabilities framework and Social Cognitive Theory, respectively. Nineteen articles were reviewed. The most commonly identified perceived barriers of physical activity and exercise were related to the environmental (i.e. minimal or no disabled facilities, and minimal or conflicting advice from healthcare professionals) and related to personal barriers (i.e. fatigue, and fear and apprehension). The most commonly identified perceived facilitators of physical activity were related to the environment (i.e. the type of exercise modality and peer support) and related to personal facilitators (i.e. appropriate exercise and feelings of accomplishment). The most commonly identified perceived beneficial consequences of physical activity and exercise were maintaining physical functions, increased social participation and feelings of self-management and control. The most commonly identified perceived adverse consequences were increased fatigue and feelings of frustration and lost control. Results will inform future research on the perceived determinants and consequences of physical activity and exercise in those with MS and can be adopted for developing professional education and interventions for physical activity and exercise in MS. Physical activity and exercise behaviour in people with multiple sclerosis (MS) is subject to a number of modifiable determinants. Healthcare professionals working to promote physical activity and exercise in those with MS should choose to endorse the positive benefits of participation. Future physical activity interventions for those with MS may be improved by incorporating behavioural management strategies.

A Pragmatic Cognitive System Engineering Approach to Model Dynamic Human Decision-Making Activities in Intelligent and Automated Systems

DTIC Science & Technology

2003-10-01

Among the procedures developed to identify cognitive processes, there are the Cognitive Task Analysis (CTA) and the Cognitive Work Analysis (CWA...of Cognitive Task Design. [11] Potter, S.S., Roth, E.M., Woods, D.D., and Elm, W.C. (2000). Cognitive Task Analysis as Bootstrapping Multiple...Converging Techniques, In Schraagen, Chipman, and Shalin (Eds.). Cognitive Task Analysis . Mahwah, NJ: Lawrence Erlbaum Associates. [12] Roth, E.M

An efficient approach to understanding and predicting the effects of multiple task characteristics on performance.

PubMed

Richardson, Miles

2017-04-01

In ergonomics there is often a need to identify and predict the separate effects of multiple factors on performance. A cost-effective fractional factorial approach to understanding the relationship between task characteristics and task performance is presented. The method has been shown to provide sufficient independent variability to reveal and predict the effects of task characteristics on performance in two domains. The five steps outlined are: selection of performance measure, task characteristic identification, task design for user trials, data collection, regression model development and task characteristic analysis. The approach can be used for furthering knowledge of task performance, theoretical understanding, experimental control and prediction of task performance. Practitioner Summary: A cost-effective method to identify and predict the separate effects of multiple factors on performance is presented. The five steps allow a better understanding of task factors during the design process.

Histogram analysis parameters identify multiple associations between DWI and DCE MRI in head and neck squamous cell carcinoma.

PubMed

Meyer, Hans Jonas; Leifels, Leonard; Schob, Stefan; Garnov, Nikita; Surov, Alexey

2018-01-01

Nowadays, multiparametric investigations of head and neck squamous cell carcinoma (HNSCC) are established. These approaches can better characterize tumor biology and behavior. Diffusion weighted imaging (DWI) can by means of apparent diffusion coefficient (ADC) quantitatively characterize different tissue compartments. Dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) reflects perfusion and vascularization of tissues. Recently, a novel approach of data acquisition, namely histogram analysis of different images is a novel diagnostic approach, which can provide more information of tissue heterogeneity. The purpose of this study was to analyze possible associations between DWI, and DCE parameters derived from histogram analysis in patients with HNSCC. Overall, 34 patients, 9 women and 25 men, mean age, 56.7±10.2years, with different HNSCC were involved in the study. DWI was obtained by using of an axial echo planar imaging sequence with b-values of 0 and 800s/mm 2 . Dynamic T1w DCE sequence after intravenous application of contrast medium was performed for estimation of the following perfusion parameters: volume transfer constant (K trans ), volume of the extravascular extracellular leakage space (Ve), and diffusion of contrast medium from the extravascular extracellular leakage space back to the plasma (Kep). Both ADC and perfusion parameters maps were processed offline in DICOM format with custom-made Matlab-based application. Thereafter, polygonal ROIs were manually drawn on the transferred maps on each slice. For every parameter, mean, maximal, minimal, and median values, as well percentiles 10th, 25th, 75th, 90th, kurtosis, skewness, and entropy were estimated. Сorrelation analysis identified multiple statistically significant correlations between the investigated parameters. Ve related parameters correlated well with different ADC values. Especially, percentiles 10 and 75, mode, and median values showed stronger correlations in comparison to other parameters. Thereby, the calculated correlation coefficients ranged from 0.62 to 0.69. Furthermore, K trans related parameters showed multiple slightly to moderate significant correlations with different ADC values. Strongest correlations were identified between ADC P75 and K trans min (p=0.58, P=0.0007), and ADC P75 and K trans P10 (p=0.56, P=0.001). Only four K ep related parameters correlated statistically significant with ADC fractions. Strongest correlation was found between K ep max and ADC mode (p=-0.47, P=0.008). Multiple statistically significant correlations between, DWI and DCE MRI parameters derived from histogram analysis were identified in HNSCC. Copyright © 2017 Elsevier Inc. All rights reserved.

Software forecasting as it is really done: A study of JPL software engineers

NASA Technical Reports Server (NTRS)

Griesel, Martha Ann; Hihn, Jairus M.; Bruno, Kristin J.; Fouser, Thomas J.; Tausworthe, Robert C.

1993-01-01

This paper presents a summary of the results to date of a Jet Propulsion Laboratory internally funded research task to study the costing process and parameters used by internally recognized software cost estimating experts. Protocol Analysis and Markov process modeling were used to capture software engineer's forecasting mental models. While there is significant variation between the mental models that were studied, it was nevertheless possible to identify a core set of cost forecasting activities, and it was also found that the mental models cluster around three forecasting techniques. Further partitioning of the mental models revealed clustering of activities, that is very suggestive of a forecasting lifecycle. The different forecasting methods identified were based on the use of multiple-decomposition steps or multiple forecasting steps. The multiple forecasting steps involved either forecasting software size or an additional effort forecast. Virtually no subject used risk reduction steps in combination. The results of the analysis include: the identification of a core set of well defined costing activities, a proposed software forecasting life cycle, and the identification of several basic software forecasting mental models. The paper concludes with a discussion of the implications of the results for current individual and institutional practices.

SeqFIRE: a web application for automated extraction of indel regions and conserved blocks from protein multiple sequence alignments.

PubMed

Ajawatanawong, Pravech; Atkinson, Gemma C; Watson-Haigh, Nathan S; Mackenzie, Bryony; Baldauf, Sandra L

2012-07-01

Analyses of multiple sequence alignments generally focus on well-defined conserved sequence blocks, while the rest of the alignment is largely ignored or discarded. This is especially true in phylogenomics, where large multigene datasets are produced through automated pipelines. However, some of the most powerful phylogenetic markers have been found in the variable length regions of multiple alignments, particularly insertions/deletions (indels) in protein sequences. We have developed Sequence Feature and Indel Region Extractor (SeqFIRE) to enable the automated identification and extraction of indels from protein sequence alignments. The program can also extract conserved blocks and identify fast evolving sites using a combination of conservation and entropy. All major variables can be adjusted by the user, allowing them to identify the sets of variables most suited to a particular analysis or dataset. Thus, all major tasks in preparing an alignment for further analysis are combined in a single flexible and user-friendly program. The output includes a numbered list of indels, alignments in NEXUS format with indels annotated or removed and indel-only matrices. SeqFIRE is a user-friendly web application, freely available online at www.seqfire.org/.

iGC-an integrated analysis package of gene expression and copy number alteration.

PubMed

Lai, Yi-Pin; Wang, Liang-Bo; Wang, Wei-An; Lai, Liang-Chuan; Tsai, Mong-Hsun; Lu, Tzu-Pin; Chuang, Eric Y

2017-01-14

With the advancement in high-throughput technologies, researchers can simultaneously investigate gene expression and copy number alteration (CNA) data from individual patients at a lower cost. Traditional analysis methods analyze each type of data individually and integrate their results using Venn diagrams. Challenges arise, however, when the results are irreproducible and inconsistent across multiple platforms. To address these issues, one possible approach is to concurrently analyze both gene expression profiling and CNAs in the same individual. We have developed an open-source R/Bioconductor package (iGC). Multiple input formats are supported and users can define their own criteria for identifying differentially expressed genes driven by CNAs. The analysis of two real microarray datasets demonstrated that the CNA-driven genes identified by the iGC package showed significantly higher Pearson correlation coefficients with their gene expression levels and copy numbers than those genes located in a genomic region with CNA. Compared with the Venn diagram approach, the iGC package showed better performance. The iGC package is effective and useful for identifying CNA-driven genes. By simultaneously considering both comparative genomic and transcriptomic data, it can provide better understanding of biological and medical questions. The iGC package's source code and manual are freely available at https://www.bioconductor.org/packages/release/bioc/html/iGC.html .

Classifying Patients with Chronic Pelvic Pain into Levels of Biopsychosocial Dysfunction Using Latent Class Modeling of Patient Reported Outcome Measures

PubMed Central

Fenton, Bradford W.; Grey, Scott F.; Tossone, Krystel; McCarroll, Michele; Von Gruenigen, Vivian E.

2015-01-01

Chronic pelvic pain affects multiple aspects of a patient's physical, social, and emotional functioning. Latent class analysis (LCA) of Patient Reported Outcome Measures Information System (PROMIS) domains has the potential to improve clinical insight into these patients' pain. Based on the 11 PROMIS domains applied to n=613 patients referred for evaluation in a chronic pelvic pain specialty center, exploratory factor analysis (EFA) was used to identify unidimensional superdomains. Latent profile analysis (LPA) was performed to identify the number of homogeneous classes present and to further define the pain classification system. The EFA combined the 11 PROMIS domains into four unidimensional superdomains of biopsychosocial dysfunction: Pain, Negative Affect, Fatigue, and Social Function. Based on multiple fit criteria, a latent class model revealed four distinct classes of CPP: No dysfunction (3.2%); Low Dysfunction (17.8%); Moderate Dysfunction (53.2%); and High Dysfunction (25.8%). This study is the first description of a novel approach to the complex disease process such as chronic pelvic pain and was validated by demographic, medical, and psychosocial variables. In addition to an essentially normal class, three classes of increasing biopsychosocial dysfunction were identified. The LCA approach has the potential for application to other complex multifactorial disease processes. PMID:26355825

Dynamic motif occupancy (DynaMO) analysis identifies transcription factors and their binding sites driving dynamic biological processes.

PubMed

Kuang, Zheng; Ji, Zhicheng; Boeke, Jef D; Ji, Hongkai

2018-01-09

Biological processes are usually associated with genome-wide remodeling of transcription driven by transcription factors (TFs). Identifying key TFs and their spatiotemporal binding patterns are indispensable to understanding how dynamic processes are programmed. However, most methods are designed to predict TF binding sites only. We present a computational method, dynamic motif occupancy analysis (DynaMO), to infer important TFs and their spatiotemporal binding activities in dynamic biological processes using chromatin profiling data from multiple biological conditions such as time-course histone modification ChIP-seq data. In the first step, DynaMO predicts TF binding sites with a random forests approach. Next and uniquely, DynaMO infers dynamic TF binding activities at predicted binding sites using their local chromatin profiles from multiple biological conditions. Another landmark of DynaMO is to identify key TFs in a dynamic process using a clustering and enrichment analysis of dynamic TF binding patterns. Application of DynaMO to the yeast ultradian cycle, mouse circadian clock and human neural differentiation exhibits its accuracy and versatility. We anticipate DynaMO will be generally useful for elucidating transcriptional programs in dynamic processes. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Substituting values for censored data from Texas, USA, reservoirs inflated and obscured trends in analyses commonly used for water quality target development.

PubMed

Grantz, Erin; Haggard, Brian; Scott, J Thad

2018-06-12

We calculated four median datasets (chlorophyll a, Chl a; total phosphorus, TP; and transparency) using multiple approaches to handling censored observations, including substituting fractions of the quantification limit (QL; dataset 1 = 1QL, dataset 2 = 0.5QL) and statistical methods for censored datasets (datasets 3-4) for approximately 100 Texas, USA reservoirs. Trend analyses of differences between dataset 1 and 3 medians indicated percent difference increased linearly above thresholds in percent censored data (%Cen). This relationship was extrapolated to estimate medians for site-parameter combinations with %Cen > 80%, which were combined with dataset 3 as dataset 4. Changepoint analysis of Chl a- and transparency-TP relationships indicated threshold differences up to 50% between datasets. Recursive analysis identified secondary thresholds in dataset 4. Threshold differences show that information introduced via substitution or missing due to limitations of statistical methods biased values, underestimated error, and inflated the strength of TP thresholds identified in datasets 1-3. Analysis of covariance identified differences in linear regression models relating transparency-TP between datasets 1, 2, and the more statistically robust datasets 3-4. Study findings identify high-risk scenarios for biased analytical outcomes when using substitution. These include high probability of median overestimation when %Cen > 50-60% for a single QL, or when %Cen is as low 16% for multiple QL's. Changepoint analysis was uniquely vulnerable to substitution effects when using medians from sites with %Cen > 50%. Linear regression analysis was less sensitive to substitution and missing data effects, but differences in model parameters for transparency cannot be discounted and could be magnified by log-transformation of the variables.

Insight into Genotype-Phenotype Associations through eQTL Mapping in Multiple Cell Types in Health and Immune-Mediated Disease

PubMed Central

Peters, James E.; Lyons, Paul A.; Lee, James C.; Richard, Arianne C.; Fortune, Mary D.; Newcombe, Paul J.; Richardson, Sylvia; Smith, Kenneth G. C.

2016-01-01

Genome-wide association studies (GWAS) have transformed our understanding of the genetics of complex traits such as autoimmune diseases, but how risk variants contribute to pathogenesis remains largely unknown. Identifying genetic variants that affect gene expression (expression quantitative trait loci, or eQTLs) is crucial to addressing this. eQTLs vary between tissues and following in vitro cellular activation, but have not been examined in the context of human inflammatory diseases. We performed eQTL mapping in five primary immune cell types from patients with active inflammatory bowel disease (n = 91), anti-neutrophil cytoplasmic antibody-associated vasculitis (n = 46) and healthy controls (n = 43), revealing eQTLs present only in the context of active inflammatory disease. Moreover, we show that following treatment a proportion of these eQTLs disappear. Through joint analysis of expression data from multiple cell types, we reveal that previous estimates of eQTL immune cell-type specificity are likely to have been exaggerated. Finally, by analysing gene expression data from multiple cell types, we find eQTLs not previously identified by database mining at 34 inflammatory bowel disease-associated loci. In summary, this parallel eQTL analysis in multiple leucocyte subsets from patients with active disease provides new insights into the genetic basis of immune-mediated diseases. PMID:27015630

Concordant integrative gene set enrichment analysis of multiple large-scale two-sample expression data sets.

PubMed

Lai, Yinglei; Zhang, Fanni; Nayak, Tapan K; Modarres, Reza; Lee, Norman H; McCaffrey, Timothy A

2014-01-01

Gene set enrichment analysis (GSEA) is an important approach to the analysis of coordinate expression changes at a pathway level. Although many statistical and computational methods have been proposed for GSEA, the issue of a concordant integrative GSEA of multiple expression data sets has not been well addressed. Among different related data sets collected for the same or similar study purposes, it is important to identify pathways or gene sets with concordant enrichment. We categorize the underlying true states of differential expression into three representative categories: no change, positive change and negative change. Due to data noise, what we observe from experiments may not indicate the underlying truth. Although these categories are not observed in practice, they can be considered in a mixture model framework. Then, we define the mathematical concept of concordant gene set enrichment and calculate its related probability based on a three-component multivariate normal mixture model. The related false discovery rate can be calculated and used to rank different gene sets. We used three published lung cancer microarray gene expression data sets to illustrate our proposed method. One analysis based on the first two data sets was conducted to compare our result with a previous published result based on a GSEA conducted separately for each individual data set. This comparison illustrates the advantage of our proposed concordant integrative gene set enrichment analysis. Then, with a relatively new and larger pathway collection, we used our method to conduct an integrative analysis of the first two data sets and also all three data sets. Both results showed that many gene sets could be identified with low false discovery rates. A consistency between both results was also observed. A further exploration based on the KEGG cancer pathway collection showed that a majority of these pathways could be identified by our proposed method. This study illustrates that we can improve detection power and discovery consistency through a concordant integrative analysis of multiple large-scale two-sample gene expression data sets.

Crawler Solids Unknown Analysis

NASA Technical Reports Server (NTRS)

Frandsen, Athela

2016-01-01

Crawler Transporter (CT) #2 has been undergoing refurbishment to carry the Space Launch System (SLS). After returning to normal operation, multiple filters of the gear box lubrication system failed/clogged and went on bypass during a test run to the launch pad. Analysis of the filters was done in large part with polarized light microscopy (PLM) to identify the filter contaminates and the source of origin.

Developing a Placement Exam for Spanish Heritage Language Learners: Item Analysis and Learner Characteristics

ERIC Educational Resources Information Center

Wilson, Damian Vergara

2012-01-01

This paper illustrates a method of item analysis used to identify discriminating multiple-choice items in placement data. The data come from two rounds of pilots given to both SHL students and Spanish as a Second Language (SSL) students. In the first round, 104 items were administered to 507 students. After discarding poor items, the second round…

Combining results of multiple search engines in proteomics.

PubMed

Shteynberg, David; Nesvizhskii, Alexey I; Moritz, Robert L; Deutsch, Eric W

2013-09-01

A crucial component of the analysis of shotgun proteomics datasets is the search engine, an algorithm that attempts to identify the peptide sequence from the parent molecular ion that produced each fragment ion spectrum in the dataset. There are many different search engines, both commercial and open source, each employing a somewhat different technique for spectrum identification. The set of high-scoring peptide-spectrum matches for a defined set of input spectra differs markedly among the various search engine results; individual engines each provide unique correct identifications among a core set of correlative identifications. This has led to the approach of combining the results from multiple search engines to achieve improved analysis of each dataset. Here we review the techniques and available software for combining the results of multiple search engines and briefly compare the relative performance of these techniques.

Combining Results of Multiple Search Engines in Proteomics*

PubMed Central

Shteynberg, David; Nesvizhskii, Alexey I.; Moritz, Robert L.; Deutsch, Eric W.

2013-01-01

A crucial component of the analysis of shotgun proteomics datasets is the search engine, an algorithm that attempts to identify the peptide sequence from the parent molecular ion that produced each fragment ion spectrum in the dataset. There are many different search engines, both commercial and open source, each employing a somewhat different technique for spectrum identification. The set of high-scoring peptide-spectrum matches for a defined set of input spectra differs markedly among the various search engine results; individual engines each provide unique correct identifications among a core set of correlative identifications. This has led to the approach of combining the results from multiple search engines to achieve improved analysis of each dataset. Here we review the techniques and available software for combining the results of multiple search engines and briefly compare the relative performance of these techniques. PMID:23720762

Identifying Impacts Using Adaptive Fiber Bragg Grating Demodulator for Structural Health Monitoring Applications

NASA Astrophysics Data System (ADS)

Kirikera, G. R.; Balogun, O.; Krishnaswamy, S.

2008-02-01

A network of Fiber-Bragg Grating (FBG) sensors is developed as part of a Structural Health Monitoring system to identify impact damage. The sensor signals are adaptively demodulated using two-wave mixing (TWM) technology. The signals from multiple FBG sensors are multiplexed into a single TWM demodulator. The FBG sensor network is mounted on a plate, and the structure is subjected to impacts generated by dropping small ball bearings. Impact locations are identified based on time frequency analysis.

Biostatistics Series Module 10: Brief Overview of Multivariate Methods.

PubMed

Hazra, Avijit; Gogtay, Nithya

2017-01-01

Multivariate analysis refers to statistical techniques that simultaneously look at three or more variables in relation to the subjects under investigation with the aim of identifying or clarifying the relationships between them. These techniques have been broadly classified as dependence techniques, which explore the relationship between one or more dependent variables and their independent predictors, and interdependence techniques, that make no such distinction but treat all variables equally in a search for underlying relationships. Multiple linear regression models a situation where a single numerical dependent variable is to be predicted from multiple numerical independent variables. Logistic regression is used when the outcome variable is dichotomous in nature. The log-linear technique models count type of data and can be used to analyze cross-tabulations where more than two variables are included. Analysis of covariance is an extension of analysis of variance (ANOVA), in which an additional independent variable of interest, the covariate, is brought into the analysis. It tries to examine whether a difference persists after "controlling" for the effect of the covariate that can impact the numerical dependent variable of interest. Multivariate analysis of variance (MANOVA) is a multivariate extension of ANOVA used when multiple numerical dependent variables have to be incorporated in the analysis. Interdependence techniques are more commonly applied to psychometrics, social sciences and market research. Exploratory factor analysis and principal component analysis are related techniques that seek to extract from a larger number of metric variables, a smaller number of composite factors or components, which are linearly related to the original variables. Cluster analysis aims to identify, in a large number of cases, relatively homogeneous groups called clusters, without prior information about the groups. The calculation intensive nature of multivariate analysis has so far precluded most researchers from using these techniques routinely. The situation is now changing with wider availability, and increasing sophistication of statistical software and researchers should no longer shy away from exploring the applications of multivariate methods to real-life data sets.

Taking Multiple Exposure Into Account Can Improve Assessment of Chemical Risks.

PubMed

Clerc, Frédéric; Bertrand, Nicolas Jean Hyacinthe; La Rocca, Bénédicte

2017-12-15

During work, operators may be exposed to several chemicals simultaneously. Most exposure assessment approaches only determine exposure levels for each substance individually. However, such individual-substance approaches may not correctly estimate the toxicity of 'cocktails' of chemicals, as the toxicity of a cocktail may differ from the toxicity of substances on their own. This study presents an approach that can better take into account multiple exposure when assessing chemical risks. Almost 30000 work situations, monitored between 2005 and 2014 and recorded in two French databases, were analysed using MiXie software. The algorithms employed in MiXie can identify toxicological classes associated with several substances, based on the additivity of the selected effects of each substance. The results of our retrospective analysis show that MiXie was able to identify almost 20% more potentially hazardous situations than identified using a single-substance approach. It therefore appears essential to review the ways in which multiple exposure is taken into account during risk assessment. © The Author(s) 2017. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

Dysregulation of NRXN1 by mutant MIR8485 leads to calcium overload in pre-synapses inducing neurodegeneration in Multiple sclerosis.

PubMed

Kattimani, Yogita; Veerappa, Avinash M

2018-04-09

To identify Damaging mutations in microRNAs (miRNAs) and 3' untranslated regions (UTRs) of target genes to establish Multiple sclerosis (MS) disease pathway. Female aged 16, with Relapsing Remitting Multiple sclerosis (RRMS) was reported with initial symptoms of blurred vision, severe immobility, upper and lower limb numbness and backache. Whole Exome Sequencing (WES) and disease pathway analysis was performed to identify mutations in miRNAs and UTRs. We identified Deleterious/Damaging multibase mutations in MIR8485 and NRXN1. miR-8485 was found carrying frameshift homozygous deletion of bases CA, while NRXN1 was found carrying nonframeshift homozygous substitution of bases CT to TC in exon 8 replacing Serine with Leucine. Mutations in miR-8485 and NRXN1 was found to alter calcium homeostasis and NRXN1/NLGN1 cell adhesion molecule binding affinities. The miR-8485 mutation leads to overexpression of NRXN1 altering pre-synaptic Ca 2+ homeostasis, inducing neurodegeneration. Copyright © 2018 Elsevier B.V. All rights reserved.

Gene Expression Profiling of Multiple Leiomyomata Uteri and Matched Normal Tissue from a Single Patient

PubMed Central

Dimitrova, Irina K.; Richer, Jennifer K.; Rudolph, Michael C.; Spoelstra, Nicole S.; Reno, Elaine M.; Medina, Theresa M.; Bradford, Andrew P.

2009-01-01

Objective To identify differentially expressed genes between fibroid and adjacent normal myometrium in an identical hormonal and genetic background. Design Array analysis of 3 leiomyomata and matched adjacent normal myometrium in a single patient. Setting University of Colorado Hospital. Patient(s) A single female undergoing medically indicated hysterectomy for symptomatic fibroids. Interventions(s) mRNA isolation and microarray analysis, reverse-transcriptase polymerase chain reaction, western blotting and immunohistochemistry. Main Outcome Measure(s) Changes in mRNA and protein levels in leiomyomata and matched normal myometrium. Result(s) Expression of 197 genes was increased and 619 decreased, significantly by at least 2 fold, in leiomyomata relative to normal myometrium. Expression profiles between tumors were similar and normal myometrial samples showed minimal variation. Changes in, and variation of, expression of selected genes were confirmed in additional normal and leiomyoma samples from multiple patients. Conclusion(s) Analysis of multiple tumors from a single patient confirmed changes in expression of genes described in previous, apparently disparate, studies and identified novel targets. Gene expression profiles in leiomyomata are consistent with increased activation of mitogenic pathways and inhibition of apoptosis. Down-regulation of genes implicated in invasion and metastasis, of cancers, was observed in fibroids. This expression pattern may underlie the benign nature of uterine leiomyomata and may aid in the differential diagnosis of leiomyosarcoma. PMID:18672237

Dynamic changes in global microRNAome and transcriptome reveal complex miRNA-mRNA regulated host response to Japanese Encephalitis Virus in microglial cells

PubMed Central

Kumari, Bharti; Jain, Pratistha; Das, Shaoli; Ghosal, Suman; Hazra, Bibhabasu; Trivedi, Ashish Chandra; Basu, Anirban; Chakrabarti, Jayprokas; Vrati, Sudhanshu; Banerjee, Arup

2016-01-01

Microglia cells in the brain play essential role during Japanese Encephalitis Virus (JEV) infection and may lead to change in microRNA (miRNA) and mRNA profile. These changes may together control disease outcome. Using Affymetrix microarray platform, we profiled cellular miRNA and mRNA expression at multiple time points during viral infection in human microglial (CHME3) cells. In silico analysis of microarray data revealed a phased pattern of miRNAs expression, associated with JEV replication and provided unique signatures of infection. Target prediction and pathway enrichment analysis identified anti correlation between differentially expressed miRNA and the gene expression at multiple time point which ultimately affected diverse signaling pathways including Notch signaling pathways in microglia. Activation of Notch pathway during JEV infection was demonstrated in vitro and in vivo. The expression of a subset of miRNAs that target multiple genes in Notch signaling pathways were suppressed and their overexpression could affect JEV induced immune response. Further analysis provided evidence for the possible presence of cellular competing endogenous RNA (ceRNA) associated with innate immune response. Collectively, our data provide a uniquely comprehensive view of the changes in the host miRNAs induced by JEV during cellular infection and identify Notch pathway in modulating microglia mediated inflammation. PMID:26838068

Dynamic changes in global microRNAome and transcriptome reveal complex miRNA-mRNA regulated host response to Japanese Encephalitis Virus in microglial cells.

PubMed

Kumari, Bharti; Jain, Pratistha; Das, Shaoli; Ghosal, Suman; Hazra, Bibhabasu; Trivedi, Ashish Chandra; Basu, Anirban; Chakrabarti, Jayprokas; Vrati, Sudhanshu; Banerjee, Arup

2016-02-03

Microglia cells in the brain play essential role during Japanese Encephalitis Virus (JEV) infection and may lead to change in microRNA (miRNA) and mRNA profile. These changes may together control disease outcome. Using Affymetrix microarray platform, we profiled cellular miRNA and mRNA expression at multiple time points during viral infection in human microglial (CHME3) cells. In silico analysis of microarray data revealed a phased pattern of miRNAs expression, associated with JEV replication and provided unique signatures of infection. Target prediction and pathway enrichment analysis identified anti correlation between differentially expressed miRNA and the gene expression at multiple time point which ultimately affected diverse signaling pathways including Notch signaling pathways in microglia. Activation of Notch pathway during JEV infection was demonstrated in vitro and in vivo. The expression of a subset of miRNAs that target multiple genes in Notch signaling pathways were suppressed and their overexpression could affect JEV induced immune response. Further analysis provided evidence for the possible presence of cellular competing endogenous RNA (ceRNA) associated with innate immune response. Collectively, our data provide a uniquely comprehensive view of the changes in the host miRNAs induced by JEV during cellular infection and identify Notch pathway in modulating microglia mediated inflammation.

Decomposition of the Total Effect in the Presence of Multiple Mediators and Interactions.

PubMed

Bellavia, Andrea; Valeri, Linda

2018-06-01

Mediation analysis allows decomposing a total effect into a direct effect of the exposure on the outcome and an indirect effect operating through a number of possible hypothesized pathways. Recent studies have provided formal definitions of direct and indirect effects when multiple mediators are of interest and have described parametric and semiparametric methods for their estimation. Investigating direct and indirect effects with multiple mediators, however, can be challenging in the presence of multiple exposure-mediator and mediator-mediator interactions. In this paper we derive a decomposition of the total effect that unifies mediation and interaction when multiple mediators are present. We illustrate the properties of the proposed framework in a secondary analysis of a pragmatic trial for the treatment of schizophrenia. The decomposition is employed to investigate the interplay of side effects and psychiatric symptoms in explaining the effect of antipsychotic medication on quality of life in schizophrenia patients. Our result offers a valuable tool to identify the proportions of total effect due to mediation and interaction when more than one mediator is present, providing the finest decomposition of the total effect that unifies multiple mediators and interactions.

A Benefit-Risk Analysis Approach to Capture Regulatory Decision-Making: Multiple Myeloma.

PubMed

Raju, G K; Gurumurthi, Karthik; Domike, Reuben; Kazandjian, Dickran; Landgren, Ola; Blumenthal, Gideon M; Farrell, Ann; Pazdur, Richard; Woodcock, Janet

2018-01-01

Drug regulators around the world make decisions about drug approvability based on qualitative benefit-risk analysis. In this work, a quantitative benefit-risk analysis approach captures regulatory decision-making about new drugs to treat multiple myeloma (MM). MM assessments have been based on endpoints such as time to progression (TTP), progression-free survival (PFS), and objective response rate (ORR) which are different than benefit-risk analysis based on overall survival (OS). Twenty-three FDA decisions on MM drugs submitted to FDA between 2003 and 2016 were identified and analyzed. The benefits and risks were quantified relative to comparators (typically the control arm of the clinical trial) to estimate whether the median benefit-risk was positive or negative. A sensitivity analysis was demonstrated using ixazomib to explore the magnitude of uncertainty. FDA approval decision outcomes were consistent and logical using this benefit-risk framework. © 2017 American Society for Clinical Pharmacology and Therapeutics.

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

Multiple fingerprinting analyses in quality control of Cassiae Semen polysaccharides.

PubMed

Cheng, Jing; He, Siyu; Wan, Qiang; Jing, Pu

2018-03-01

Quality control issue overshadows potential health benefits of Cassiae Semen due to the analytic limitations. In this study, multiple-fingerprint analysis integrated with several chemometrics was performed to assess the polysaccharide quality of Cassiae Semen harvested from different locations. FT-IR, HPLC, and GC fingerprints of polysaccharide extracts from the authentic source were established as standard profiles, applying to assess the quality of foreign sources. Analyses of FT-IR fingerprints of polysaccharide extracts using either Pearson correlation analysis or principal component analysis (PCA), or HPLC fingerprints of partially hydrolyzed polysaccharides with PCA, distinguished the foreign sources from the authentic source. However, HPLC or GC fingerprints of completely hydrolyzed polysaccharides couldn't identify all foreign sources and the methodology using GC is quite limited in determining the monosaccharide composition. This indicates that FT-IR/HPLC fingerprints of non/partially-hydrolyzed polysaccharides, respectively, accompanied by multiple chemometrics methods, might be potentially applied in detecting and differentiating sources of Cassiae Semen. Copyright © 2018 Elsevier B.V. All rights reserved.

Real-Time Visualization of Network Behaviors for Situational Awareness

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

Best, Daniel M.; Bohn, Shawn J.; Love, Douglas V.

Plentiful, complex, and dynamic data make understanding the state of an enterprise network difficult. Although visualization can help analysts understand baseline behaviors in network traffic and identify off-normal events, visual analysis systems often do not scale well to operational data volumes (in the hundreds of millions to billions of transactions per day) nor to analysis of emergent trends in real-time data. We present a system that combines multiple, complementary visualization techniques coupled with in-stream analytics, behavioral modeling of network actors, and a high-throughput processing platform called MeDICi. This system provides situational understanding of real-time network activity to help analysts takemore » proactive response steps. We have developed these techniques using requirements gathered from the government users for which the tools are being developed. By linking multiple visualization tools to a streaming analytic pipeline, and designing each tool to support a particular kind of analysis (from high-level awareness to detailed investigation), analysts can understand the behavior of a network across multiple levels of abstraction.« less

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

Computational Identification of Tissue-Specific Splicing Regulatory Elements in Human Genes from RNA-Seq Data.

PubMed

Badr, Eman; ElHefnawi, Mahmoud; Heath, Lenwood S

2016-01-01

Alternative splicing is a vital process for regulating gene expression and promoting proteomic diversity. It plays a key role in tissue-specific expressed genes. This specificity is mainly regulated by splicing factors that bind to specific sequences called splicing regulatory elements (SREs). Here, we report a genome-wide analysis to study alternative splicing on multiple tissues, including brain, heart, liver, and muscle. We propose a pipeline to identify differential exons across tissues and hence tissue-specific SREs. In our pipeline, we utilize the DEXSeq package along with our previously reported algorithms. Utilizing the publicly available RNA-Seq data set from the Human BodyMap project, we identified 28,100 differentially used exons across the four tissues. We identified tissue-specific exonic splicing enhancers that overlap with various previously published experimental and computational databases. A complicated exonic enhancer regulatory network was revealed, where multiple exonic enhancers were found across multiple tissues while some were found only in specific tissues. Putative combinatorial exonic enhancers and silencers were discovered as well, which may be responsible for exon inclusion or exclusion across tissues. Some of the exonic enhancers are found to be co-occurring with multiple exonic silencers and vice versa, which demonstrates a complicated relationship between tissue-specific exonic enhancers and silencers.

Debunking Occam's razor: Diagnosing multiple genetic diseases in families by whole-exome sequencing.

PubMed

Balci, T B; Hartley, T; Xi, Y; Dyment, D A; Beaulieu, C L; Bernier, F P; Dupuis, L; Horvath, G A; Mendoza-Londono, R; Prasad, C; Richer, J; Yang, X-R; Armour, C M; Bareke, E; Fernandez, B A; McMillan, H J; Lamont, R E; Majewski, J; Parboosingh, J S; Prasad, A N; Rupar, C A; Schwartzentruber, J; Smith, A C; Tétreault, M; Innes, A M; Boycott, K M

2017-09-01

Recent clinical whole exome sequencing (WES) cohorts have identified unanticipated multiple genetic diagnoses in single patients. However, the frequency of multiple genetic diagnoses in families is largely unknown. We set out to identify the rate of multiple genetic diagnoses in probands and their families referred for analysis in two national research programs in Canada. We retrospectively analyzed WES results for 802 undiagnosed probands referred over the past 5 years in either the FORGE or Care4Rare Canada WES initiatives. Of the 802 probands, 226 (28.2%) were diagnosed based on mutations in known disease genes. Eight (3.5%) had two or more genetic diagnoses explaining their clinical phenotype, a rate in keeping with the large published studies (average 4.3%; 1.4 - 7.2%). Seven of the 8 probands had family members with one or more of the molecularly diagnosed diseases. Consanguinity and multisystem disease appeared to increase the likelihood of multiple genetic diagnoses in a family. Our findings highlight the importance of comprehensive clinical phenotyping of family members to ultimately provide accurate genetic counseling. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A Network Pharmacology Approach to Determine the Active Components and Potential Targets of Curculigo Orchioides in the Treatment of Osteoporosis.

PubMed

Wang, Nani; Zhao, Guizhi; Zhang, Yang; Wang, Xuping; Zhao, Lisha; Xu, Pingcui; Shou, Dan

2017-10-27

BACKGROUND Osteoporosis is a complex bone disorder with a genetic predisposition, and is a cause of health problems worldwide. In China, Curculigo orchioides (CO) has been widely used as a herbal medicine in the prevention and treatment of osteoporosis. However, research on the mechanism of action of CO is still lacking. The aim of this study was to identify the absorbable components, potential targets, and associated treatment pathways of CO using a network pharmacology approach. MATERIAL AND METHODS We explored the chemical components of CO and used the five main principles of drug absorption to identify absorbable components. Targets for the therapeutic actions of CO were obtained from the PharmMapper server database. Pathway enrichment analysis was performed using the Comparative Toxicogenomics Database (CTD). Cytoscape was used to visualize the multiple components-multiple target-multiple pathways-multiple disease network for CO. RESULTS We identified 77 chemical components of CO, of which 32 components could be absorbed in the blood. These potential active components of CO regulated 83 targets and affected 58 pathways. Data analysis showed that the genes for estrogen receptor alpha (ESR1) and beta (ESR2), and the gene for 11 beta-hydroxysteroid dehydrogenase type 1, or cortisone reductase (HSD11B1) were the main targets of CO. Endocrine regulatory factors and factors regulating calcium reabsorption, steroid hormone biosynthesis, and metabolic pathways were related to these main targets and to ten corresponding compounds. CONCLUSIONS The network pharmacology approach used in our study has attempted to explain the mechanisms for the effects of CO in the prevention and treatment of osteoporosis, and provides an alternative approach to the investigation of the effects of this complex compound.

Time-correlated neutron analysis of a multiplying HEU source

NASA Astrophysics Data System (ADS)

Miller, E. C.; Kalter, J. M.; Lavelle, C. M.; Watson, S. M.; Kinlaw, M. T.; Chichester, D. L.; Noonan, W. A.

2015-06-01

The ability to quickly identify and characterize special nuclear material remains a national security challenge. In counter-proliferation applications, identifying the neutron multiplication of a sample can be a good indication of the level of threat. Currently neutron multiplicity measurements are performed with moderated 3He proportional counters. These systems rely on the detection of thermalized neutrons, a process which obscures both energy and time information from the source. Fast neutron detectors, such as liquid scintillators, have the ability to detect events on nanosecond time scales, providing more information on the temporal structure of the arriving signal, and provide an alternative method for extracting information from the source. To explore this possibility, a series of measurements were performed on the Idaho National Laboratory's MARVEL assembly, a configurable HEU source. The source assembly was measured in a variety of different HEU configurations and with different reflectors, covering a range of neutron multiplications from 2 to 8. The data was collected with liquid scintillator detectors and digitized for offline analysis. A gap based approach for identifying the bursts of detected neutrons associated with the same fission chain was used. Using this approach, we are able to study various statistical properties of individual fission chains. One of these properties is the distribution of neutron arrival times within a given burst. We have observed two interesting empirical trends. First, this distribution exhibits a weak, but definite, dependence on source multiplication. Second, there are distinctive differences in the distribution depending on the presence and type of reflector. Both of these phenomena might prove to be useful when assessing an unknown source. The physical origins of these phenomena can be illuminated with help of MCNPX-PoliMi simulations.

Analysis of Gene Expression Profiles of Soft Tissue Sarcoma Using a Combination of Knowledge-Based Filtering with Integration of Multiple Statistics

PubMed Central

Doi, Ayano; Ichinohe, Risa; Ikuyo, Yoriko; Takahashi, Teruyoshi; Marui, Shigetaka; Yasuhara, Koji; Nakamura, Tetsuro; Sugita, Shintaro; Sakamoto, Hiromi; Yoshida, Teruhiko; Hasegawa, Tadashi

2014-01-01

The diagnosis and treatment of soft tissue sarcomas (STS) have been difficult. Of the diverse histological subtypes, undifferentiated pleomorphic sarcoma (UPS) is particularly difficult to diagnose accurately, and its classification per se is still controversial. Recent advances in genomic technologies provide an excellent way to address such problems. However, it is often difficult, if not impossible, to identify definitive disease-associated genes using genome-wide analysis alone, primarily because of multiple testing problems. In the present study, we analyzed microarray data from 88 STS patients using a combination method that used knowledge-based filtering and a simulation based on the integration of multiple statistics to reduce multiple testing problems. We identified 25 genes, including hypoxia-related genes (e.g., MIF, SCD1, P4HA1, ENO1, and STAT1) and cell cycle- and DNA repair-related genes (e.g., TACC3, PRDX1, PRKDC, and H2AFY). These genes showed significant differential expression among histological subtypes, including UPS, and showed associations with overall survival. STAT1 showed a strong association with overall survival in UPS patients (logrank p = 1.84×10−6 and adjusted p value 2.99×10−3 after the permutation test). According to the literature, the 25 genes selected are useful not only as markers of differential diagnosis but also as prognostic/predictive markers and/or therapeutic targets for STS. Our combination method can identify genes that are potential prognostic/predictive factors and/or therapeutic targets in STS and possibly in other cancers. These disease-associated genes deserve further preclinical and clinical validation. PMID:25188299

Distinct brain imaging characteristics of autoantibody-mediated CNS conditions and multiple sclerosis.

PubMed

Jurynczyk, Maciej; Geraldes, Ruth; Probert, Fay; Woodhall, Mark R; Waters, Patrick; Tackley, George; DeLuca, Gabriele; Chandratre, Saleel; Leite, Maria I; Vincent, Angela; Palace, Jacqueline

2017-03-01

Brain imaging characteristics of MOG antibody disease are largely unknown and it is unclear whether they differ from those of multiple sclerosis and AQP4 antibody disease. The aim of this study was to identify brain imaging discriminators between those three inflammatory central nervous system diseases in adults and children to support diagnostic decisions, drive antibody testing and generate disease mechanism hypotheses. Clinical brain scans of 83 patients with brain lesions (67 in the training and 16 in the validation cohort, 65 adults and 18 children) with MOG antibody (n = 26), AQP4 antibody disease (n = 26) and multiple sclerosis (n = 31) recruited from Oxford neuromyelitis optica and multiple sclerosis clinical services were retrospectively and anonymously scored on a set of 29 predefined magnetic resonance imaging features by two independent raters. Principal component analysis was used to perform an overview of patients without a priori knowledge of the diagnosis. Orthogonal partial least squares discriminant analysis was used to build models separating diagnostic groups and identify best classifiers, which were then tested on an independent cohort set. Adults and children with MOG antibody disease frequently had fluffy brainstem lesions, often located in pons and/or adjacent to fourth ventricle. Children across all conditions showed more frequent bilateral, large, brainstem and deep grey matter lesions. MOG antibody disease spontaneously separated from multiple sclerosis but overlapped with AQP4 antibody disease. Multiple sclerosis was discriminated from MOG antibody disease and from AQP4 antibody disease with high predictive values, while MOG antibody disease could not be accurately discriminated from AQP4 antibody disease. Best classifiers between MOG antibody disease and multiple sclerosis were similar in adults and children, and included ovoid lesions adjacent to the body of lateral ventricles, Dawson's fingers, T1 hypointense lesions (multiple sclerosis), fluffy lesions and three lesions or less (MOG antibody). In the validation cohort patients with antibody-mediated conditions were differentiated from multiple sclerosis with high accuracy. Both antibody-mediated conditions can be clearly separated from multiple sclerosis on conventional brain imaging, both in adults and children. The overlap between MOG antibody oligodendrocytopathy and AQP4 antibody astrocytopathy suggests that the primary immune target is not the main substrate for brain lesion characteristics. This is also supported by the clear distinction between multiple sclerosis and MOG antibody disease both considered primary demyelinating conditions. We identify discriminatory features, which may be useful in classifying atypical multiple sclerosis, seronegative neuromyelitis optica spectrum disorders and relapsing acute disseminated encephalomyelitis, and characterizing cohorts for antibody discovery. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Decision Making Configurations: An Alternative to the Centralization/Decentralization Conceptualization.

ERIC Educational Resources Information Center

Cullen, John B.; Perrewe, Pamela L.

1981-01-01

Used factors identified in the literature as predictors of centralization/decentralization as potential discriminating variables among several decision making configurations in university affiliated professional schools. The model developed from multiple discriminant analysis had reasonable success in classifying correctly only the decentralized…

Antecedents of Coping with the Disease in Patients with Multiple Sclerosis: A Qualitative Content Analysis

PubMed Central

Dehghani, Ali; Dehghan Nayeri, Nahid; Ebadi, Abbas

2017-01-01

ABSTRACT Background: Due to many physical and mental disorders that occur in multiple sclerosis patients, identifying the factors affecting coping based on the experiences of patients using qualitative study is essential to improve their quality of life. This study was conducted to explore the antecedents of coping with the disease in patients with multiple sclerosis. Methods: This is a qualitative study conducted on 11 patients with multiple sclerosis in 2015 in Tehran, Iran. These patients were selected based on purposive sampling. Data were collected using semi-structured and in-depth interviews and coded. These data were analyzed using the conventional content analysis. The rigor of qualitative data using the criteria proposed by Guba and Lincoln were assessed. Results: Five main categories were revealed: (1) social support, (2) lenience, (3) reliance on faith, (4) knowledge of multiple sclerosis and modeling, and (5) economic and environmental situation. Each category had several distinct sub-categories. Conclusions: The results of this study showed that coping with multiple sclerosis is a complex, multidimensional and contextual concept that is affected by various factors in relation to the context of Iran. The findings of the study can provide the healthcare professionals with deeper recognition and understanding of these antecedents to improve successful coping in Iranian patients suffering from multiple sclerosis. PMID:28097178

Molecular characterization of enterohemorrhagic Escherichia coli O157:H7 isolates dispersed across Japan by pulsed-field gel electrophoresis and multiple-locus variable-number tandem repeat analysis.

PubMed

Pei, Yingxin; Terajima, Jun; Saito, Yasunori; Suzuki, Reiko; Takai, Nobuko; Izumiya, Hidemasa; Morita-Ishihara, Tomoko; Ohnishi, Makoto; Miura, Masashi; Iyoda, Sunao; Mitobe, Jiro; Wang, Binyou; Watanabe, Haruo

2008-01-01

We identified seven distinct subtypes of enterohemorrhagic Escherichia coli (EHEC) O157:H7 isolates that were derived from sporadic cases and outbreaks from multiple prefectures in Japan in 2005. A surveillance system utilizing pulsed-field gel electrophoresis (PFGE), PulseNet Japan, was used. Some strains showed indistinguishable PFGE patterns using another restriction enzyme (BlnI or SpeI) in each subtype of EHEC O157:H7 isolates that were routinely subtyped by the XbaI PFGE pattern. In order to examine the genotypic relatedness of these strains, we carried out a multiple-locus variable-number tandem repeat (VNTR) analysis (MLVA). By using the MLVA system, we found that three of seven subtypes of EHEC O157:H7 strains that were isolated from sporadic cases dispersed across multiple prefectures within a few months showed indistinguishable PFGE patterns and identical MLVA types. Strains belonging to the other four subtypes of EHEC O157:H7 in the PFGE analysis were further classified into different clusters of EHEC O157:H7. Therefore, compared to PFGE, MLVA showed greater discriminatory power with respect to analysis of the isolates in this study.

Statistical technique for analysing functional connectivity of multiple spike trains.

PubMed

Masud, Mohammad Shahed; Borisyuk, Roman

2011-03-15

A new statistical technique, the Cox method, used for analysing functional connectivity of simultaneously recorded multiple spike trains is presented. This method is based on the theory of modulated renewal processes and it estimates a vector of influence strengths from multiple spike trains (called reference trains) to the selected (target) spike train. Selecting another target spike train and repeating the calculation of the influence strengths from the reference spike trains enables researchers to find all functional connections among multiple spike trains. In order to study functional connectivity an "influence function" is identified. This function recognises the specificity of neuronal interactions and reflects the dynamics of postsynaptic potential. In comparison to existing techniques, the Cox method has the following advantages: it does not use bins (binless method); it is applicable to cases where the sample size is small; it is sufficiently sensitive such that it estimates weak influences; it supports the simultaneous analysis of multiple influences; it is able to identify a correct connectivity scheme in difficult cases of "common source" or "indirect" connectivity. The Cox method has been thoroughly tested using multiple sets of data generated by the neural network model of the leaky integrate and fire neurons with a prescribed architecture of connections. The results suggest that this method is highly successful for analysing functional connectivity of simultaneously recorded multiple spike trains. Copyright © 2011 Elsevier B.V. All rights reserved.

Prognostic Validation of SKY92 and Its Combination With ISS in an Independent Cohort of Patients With Multiple Myeloma.

PubMed

van Beers, Erik H; van Vliet, Martin H; Kuiper, Rowan; de Best, Leonie; Anderson, Kenneth C; Chari, Ajai; Jagannath, Sundar; Jakubowiak, Andrzej; Kumar, Shaji K; Levy, Joan B; Auclair, Daniel; Lonial, Sagar; Reece, Donna; Richardson, Paul; Siegel, David S; Stewart, A Keith; Trudel, Suzanne; Vij, Ravi; Zimmerman, Todd M; Fonseca, Rafael

2017-09-01

High risk and low risk multiple myeloma patients follow a very different clinical course as reflected in their PFS and OS. To be clinically useful, methodologies used to identify high and low risk disease must be validated in representative independent clinical data and available so that patients can be managed appropriately. A recent analysis has indicated that SKY92 combined with the International Staging System (ISS) identifies patients with different risk disease with high sensitivity. Here we computed the performance of eight gene expression based classifiers SKY92, UAMS70, UAMS80, IFM15, Proliferation Index, Centrosome Index, Cancer Testis Antigen and HM19 as well as the combination of SKY92/ISS in an independent cohort of 91 newly diagnosed MM patients. The classifiers identified between 9%-21% of patients as high risk, with hazard ratios (HRs) between 1.9 and 8.2. Among the eight signatures, SKY92 identified the largest proportion of patients (21%) also with the highest HR (8.2). Our analysis also validated the combination SKY92/ISS for identification of three classes; low risk (42%), intermediate risk (37%) and high risk (21%). Between low risk and high risk classes the HR is >10. Copyright © 2017 Elsevier Inc. All rights reserved.

Rare Variant Association Test with Multiple Phenotypes

PubMed Central

Lee, Selyeong; Won, Sungho; Kim, Young Jin; Kim, Yongkang; Kim, Bong-Jo; Park, Taesung

2016-01-01

Although genome-wide association studies (GWAS) have now discovered thousands of genetic variants associated with common traits, such variants cannot explain the large degree of “missing heritability,” likely due to rare variants. The advent of next generation sequencing technology has allowed rare variant detection and association with common traits, often by investigating specific genomic regions for rare variant effects on a trait. Although multiply correlated phenotypes are often concurrently observed in GWAS, most studies analyze only single phenotypes, which may lessen statistical power. To increase power, multivariate analyses, which consider correlations between multiple phenotypes, can be used. However, few existing multi-variant analyses can identify rare variants for assessing multiple phenotypes. Here, we propose Multivariate Association Analysis using Score Statistics (MAAUSS), to identify rare variants associated with multiple phenotypes, based on the widely used Sequence Kernel Association Test (SKAT) for a single phenotype. We applied MAAUSS to Whole Exome Sequencing (WES) data from a Korean population of 1,058 subjects, to discover genes associated with multiple traits of liver function. We then assessed validation of those genes by a replication study, using an independent dataset of 3,445 individuals. Notably, we detected the gene ZNF620 among five significant genes. We then performed a simulation study to compare MAAUSS's performance with existing methods. Overall, MAAUSS successfully conserved type 1 error rates and in many cases, had a higher power than the existing methods. This study illustrates a feasible and straightforward approach for identifying rare variants correlated with multiple phenotypes, with likely relevance to missing heritability. PMID:28039885

Physical and mental health status of survivors of multiple cancer diagnoses: findings from the National Health Interview Survey.

PubMed

Andrykowski, Michael A

2012-07-15

Little research has identified the physical and mental health status of survivors of multiple primary cancer diagnoses. By using data from the population-based 2009 National Health Information Survey, 154 survivors of multiple primary cancer diagnoses, 1427 survivors of a single cancer diagnosis, and 25,004 individuals without a history of cancer diagnosis were identified. The multiple cancer group was compared with the single cancer and no cancer groups with regard to physical and mental health status using analysis of covariance and binary logistic regression. Relative to the no cancer group, the multiple cancer group reported significantly poorer mental health status, greater lifetime, recent, and current prevalence of a variety of medical conditions and comorbidities, and more health-related disability. Although observed group differences between the multiple cancer and single cancer groups were less pronounced than those between the multiple cancer and no cancer groups, a consistent pattern was also evident; the multiple cancer group reported significantly poorer status relative to the single cancer group across a range of mental and physical health and illness-related disability indices. Diagnosis of 2 or more primary cancers (excluding nonmelanoma skin cancers) is associated with increased risk for poorer physical and mental health status over and above that associated with diagnosis of a single primary cancer. Survivors of multiple and single primary cancer diagnoses should be considered as distinct subgroups, and increased attention should be devoted to the unique status and needs of survivors of multiple primary cancer diagnoses. Copyright © 2011 American Cancer Society.

Whole Genome Sequencing for Genomics-Guided Investigations of Escherichia coli O157:H7 Outbreaks.

PubMed

Rusconi, Brigida; Sanjar, Fatemeh; Koenig, Sara S K; Mammel, Mark K; Tarr, Phillip I; Eppinger, Mark

2016-01-01

Multi isolate whole genome sequencing (WGS) and typing for outbreak investigations has become a reality in the post-genomics era. We applied this technology to strains from Escherichia coli O157:H7 outbreaks. These include isolates from seven North America outbreaks, as well as multiple isolates from the same patient and from different infected individuals in the same household. Customized high-resolution bioinformatics sequence typing strategies were developed to assess the core genome and mobilome plasticity. Sequence typing was performed using an in-house single nucleotide polymorphism (SNP) discovery and validation pipeline. Discriminatory power becomes of particular importance for the investigation of isolates from outbreaks in which macrogenomic techniques such as pulse-field gel electrophoresis or multiple locus variable number tandem repeat analysis do not differentiate closely related organisms. We also characterized differences in the phage inventory, allowing us to identify plasticity among outbreak strains that is not detectable at the core genome level. Our comprehensive analysis of the mobilome identified multiple plasmids that have not previously been associated with this lineage. Applied phylogenomics approaches provide strong molecular evidence for exceptionally little heterogeneity of strains within outbreaks and demonstrate the value of intra-cluster comparisons, rather than basing the analysis on archetypal reference strains. Next generation sequencing and whole genome typing strategies provide the technological foundation for genomic epidemiology outbreak investigation utilizing its significantly higher sample throughput, cost efficiency, and phylogenetic relatedness accuracy. These phylogenomics approaches have major public health relevance in translating information from the sequence-based survey to support timely and informed countermeasures. Polymorphisms identified in this work offer robust phylogenetic signals that index both short- and long-term evolution and can complement currently employed typing schemes for outbreak ex- and inclusion, diagnostics, surveillance, and forensic studies.

Whole Genome Sequencing for Genomics-Guided Investigations of Escherichia coli O157:H7 Outbreaks

PubMed Central

Rusconi, Brigida; Sanjar, Fatemeh; Koenig, Sara S. K.; Mammel, Mark K.; Tarr, Phillip I.; Eppinger, Mark

2016-01-01

Multi isolate whole genome sequencing (WGS) and typing for outbreak investigations has become a reality in the post-genomics era. We applied this technology to strains from Escherichia coli O157:H7 outbreaks. These include isolates from seven North America outbreaks, as well as multiple isolates from the same patient and from different infected individuals in the same household. Customized high-resolution bioinformatics sequence typing strategies were developed to assess the core genome and mobilome plasticity. Sequence typing was performed using an in-house single nucleotide polymorphism (SNP) discovery and validation pipeline. Discriminatory power becomes of particular importance for the investigation of isolates from outbreaks in which macrogenomic techniques such as pulse-field gel electrophoresis or multiple locus variable number tandem repeat analysis do not differentiate closely related organisms. We also characterized differences in the phage inventory, allowing us to identify plasticity among outbreak strains that is not detectable at the core genome level. Our comprehensive analysis of the mobilome identified multiple plasmids that have not previously been associated with this lineage. Applied phylogenomics approaches provide strong molecular evidence for exceptionally little heterogeneity of strains within outbreaks and demonstrate the value of intra-cluster comparisons, rather than basing the analysis on archetypal reference strains. Next generation sequencing and whole genome typing strategies provide the technological foundation for genomic epidemiology outbreak investigation utilizing its significantly higher sample throughput, cost efficiency, and phylogenetic relatedness accuracy. These phylogenomics approaches have major public health relevance in translating information from the sequence-based survey to support timely and informed countermeasures. Polymorphisms identified in this work offer robust phylogenetic signals that index both short- and long-term evolution and can complement currently employed typing schemes for outbreak ex- and inclusion, diagnostics, surveillance, and forensic studies. PMID:27446025

The Multiple Correspondence Analysis Method and Brain Functional Connectivity: Its Application to the Study of the Non-linear Relationships of Motor Cortex and Basal Ganglia.

PubMed

Rodriguez-Sabate, Clara; Morales, Ingrid; Sanchez, Alberto; Rodriguez, Manuel

2017-01-01

The complexity of basal ganglia (BG) interactions is often condensed into simple models mainly based on animal data and that present BG in closed-loop cortico-subcortical circuits of excitatory/inhibitory pathways which analyze the incoming cortical data and return the processed information to the cortex. This study was aimed at identifying functional relationships in the BG motor-loop of 24 healthy-subjects who provided written, informed consent and whose BOLD-activity was recorded by MRI methods. The analysis of the functional interaction between these centers by correlation techniques and multiple linear regression showed non-linear relationships which cannot be suitably addressed with these methods. The multiple correspondence analysis (MCA), an unsupervised multivariable procedure which can identify non-linear interactions, was used to study the functional connectivity of BG when subjects were at rest. Linear methods showed different functional interactions expected according to current BG models. MCA showed additional functional interactions which were not evident when using lineal methods. Seven functional configurations of BG were identified with MCA, two involving the primary motor and somatosensory cortex, one involving the deepest BG (external-internal globus pallidum, subthalamic nucleus and substantia nigral), one with the input-output BG centers (putamen and motor thalamus), two linking the input-output centers with other BG (external pallidum and subthalamic nucleus), and one linking the external pallidum and the substantia nigral. The results provide evidence that the non-linear MCA and linear methods are complementary and should be best used in conjunction to more fully understand the nature of functional connectivity of brain centers.

Identification of multiple sclerosis patients at highest risk of cognitive impairment using an integrated brain magnetic resonance imaging assessment approach.

PubMed

Uher, T; Vaneckova, M; Sormani, M P; Krasensky, J; Sobisek, L; Dusankova, J Blahova; Seidl, Z; Havrdova, E; Kalincik, T; Benedict, R H B; Horakova, D

2017-02-01

While impaired cognitive performance is common in multiple sclerosis (MS), it has been largely underdiagnosed. Here a magnetic resonance imaging (MRI) screening algorithm is proposed to identify patients at highest risk of cognitive impairment. The objective was to examine whether assessment of lesion burden together with whole brain atrophy on MRI improves our ability to identify cognitively impaired MS patients. Of the 1253 patients enrolled in the study, 1052 patients with all cognitive, volumetric MRI and clinical data available were included in the analysis. Brain MRI and neuropsychological assessment with the Brief International Cognitive Assessment for Multiple Sclerosis were performed. Multivariable logistic regression and individual prediction analysis were used to investigate the associations between MRI markers and cognitive impairment. The results of the primary analysis were validated at two subsequent time points (months 12 and 24). The prevalence of cognitive impairment was greater in patients with low brain parenchymal fraction (BPF) (<0.85) and high T2 lesion volume (T2-LV) (>3.5 ml) than in patients with high BPF (>0.85) and low T2-LV (<3.5 ml), with an odds ratio (OR) of 6.5 (95% CI 4.4-9.5). Low BPF together with high T2-LV identified in 270 (25.7%) patients predicted cognitive impairment with 83% specificity, 82% negative predictive value, 51% sensitivity and 75% overall accuracy. The risk of confirmed cognitive decline over the follow-up was greater in patients with high T2-LV (OR 2.1; 95% CI 1.1-3.8) and low BPF (OR 2.6; 95% CI 1.4-4.7). The integrated MRI assessment of lesion burden and brain atrophy may improve the stratification of MS patients who may benefit from cognitive assessment. © 2016 EAN.

Using Discursis to enhance the qualitative analysis of hospital pharmacist-patient interactions.

PubMed

Chevalier, Bernadette A M; Watson, Bernadette M; Barras, Michael A; Cottrell, William N; Angus, Daniel J

2018-01-01

Pharmacist-patient communication during medication counselling has been successfully investigated using Communication Accommodation Theory (CAT). Communication researchers in other healthcare professions have utilised Discursis software as an adjunct to their manual qualitative analysis processes. Discursis provides a visual, chronological representation of communication exchanges and identifies patterns of interactant engagement. The aim of this study was to describe how Discursis software was used to enhance previously conducted qualitative analysis of pharmacist-patient interactions (by visualising pharmacist-patient speech patterns, episodes of engagement, and identifying CAT strategies employed by pharmacists within these episodes). Visual plots from 48 transcribed audio recordings of pharmacist-patient exchanges were generated by Discursis. Representative plots were selected to show moderate-high and low- level speaker engagement. Details of engagement were investigated for pharmacist application of CAT strategies (approximation, interpretability, discourse management, emotional expression, and interpersonal control). Discursis plots allowed for identification of distinct patterns occurring within pharmacist-patient exchanges. Moderate-high pharmacist-patient engagement was characterised by multiple off-diagonal squares while alternating single coloured squares depicted low engagement. Engagement episodes were associated with multiple CAT strategies such as discourse management (open-ended questions). Patterns reflecting pharmacist or patient speaker dominance were dependant on clinical setting. Discursis analysis of pharmacist-patient interactions, a novel application of the technology in health communication, was found to be an effective visualisation tool to pin-point episodes for CAT analysis. Discursis has numerous practical and theoretical applications for future health communication research and training. Researchers can use the software to support qualitative analysis where large data sets can be quickly reviewed to identify key areas for concentrated analysis. Because Discursis plots are easily generated from audio recorded transcripts, they are conducive as teaching tools for both students and practitioners to assess and develop their communication skills.

Programs to reduce teen pregnancy, sexually transmitted infections, and associated sexual risk behaviors: a systematic review.

PubMed

Goesling, Brian; Colman, Silvie; Trenholm, Christopher; Terzian, Mary; Moore, Kristin

2014-05-01

This systematic review provides a comprehensive, updated assessment of programs with evidence of effectiveness in reducing teen pregnancy, sexually transmitted infections (STIs), or associated sexual risk behaviors. The review was conducted in four steps. First, multiple literature search strategies were used to identify relevant studies released from 1989 through January 2011. Second, identified studies were screened against prespecified eligibility criteria. Third, studies were assessed by teams of two trained reviewers for the quality and execution of their research designs. Fourth, for studies that passed the quality assessment, the review team extracted and analyzed information on the research design, study sample, evaluation setting, and program impacts. A total of 88 studies met the review criteria for study quality and were included in the data extraction and analysis. The studies examined a range of programs delivered in diverse settings. Most studies had mixed-gender and predominately African-American research samples (70% and 51%, respectively). Randomized controlled trials accounted for the large majority (87%) of included studies. Most studies (76%) included multiple follow-ups, with sample sizes ranging from 62 to 5,244. Analysis of the study impact findings identified 31 programs with evidence of effectiveness. Research conducted since the late 1980s has identified more than two dozen teen pregnancy and STI prevention programs with evidence of effectiveness. Key strengths of this research are the large number of randomized controlled trials, the common use of multiple follow-up periods, and attention to a broad range of programs delivered in diverse settings. Two main gaps are a lack of replication studies and the need for more research on Latino youth and other high-risk populations. In addressing these gaps, researchers must overcome common limitations in study design, analysis, and reporting that have negatively affected prior research. Copyright © 2014 Society for Adolescent Health and Medicine. All rights reserved.

Balancing precision and risk: should multiple detection methods be analyzed separately in N-mixture models?

USGS Publications Warehouse

Graves, Tabitha A.; Royle, J. Andrew; Kendall, Katherine C.; Beier, Paul; Stetz, Jeffrey B.; Macleod, Amy C.

2012-01-01

Using multiple detection methods can increase the number, kind, and distribution of individuals sampled, which may increase accuracy and precision and reduce cost of population abundance estimates. However, when variables influencing abundance are of interest, if individuals detected via different methods are influenced by the landscape differently, separate analysis of multiple detection methods may be more appropriate. We evaluated the effects of combining two detection methods on the identification of variables important to local abundance using detections of grizzly bears with hair traps (systematic) and bear rubs (opportunistic). We used hierarchical abundance models (N-mixture models) with separate model components for each detection method. If both methods sample the same population, the use of either data set alone should (1) lead to the selection of the same variables as important and (2) provide similar estimates of relative local abundance. We hypothesized that the inclusion of 2 detection methods versus either method alone should (3) yield more support for variables identified in single method analyses (i.e. fewer variables and models with greater weight), and (4) improve precision of covariate estimates for variables selected in both separate and combined analyses because sample size is larger. As expected, joint analysis of both methods increased precision as well as certainty in variable and model selection. However, the single-method analyses identified different variables and the resulting predicted abundances had different spatial distributions. We recommend comparing single-method and jointly modeled results to identify the presence of individual heterogeneity between detection methods in N-mixture models, along with consideration of detection probabilities, correlations among variables, and tolerance to risk of failing to identify variables important to a subset of the population. The benefits of increased precision should be weighed against those risks. The analysis framework presented here will be useful for other species exhibiting heterogeneity by detection method.

Programming Probabilistic Structural Analysis for Parallel Processing Computer

NASA Technical Reports Server (NTRS)

Sues, Robert H.; Chen, Heh-Chyun; Twisdale, Lawrence A.; Chamis, Christos C.; Murthy, Pappu L. N.

1991-01-01

The ultimate goal of this research program is to make Probabilistic Structural Analysis (PSA) computationally efficient and hence practical for the design environment by achieving large scale parallelism. The paper identifies the multiple levels of parallelism in PSA, identifies methodologies for exploiting this parallelism, describes the development of a parallel stochastic finite element code, and presents results of two example applications. It is demonstrated that speeds within five percent of those theoretically possible can be achieved. A special-purpose numerical technique, the stochastic preconditioned conjugate gradient method, is also presented and demonstrated to be extremely efficient for certain classes of PSA problems.

MicroRNAs in urine are not biomarkers of multiple myeloma.

PubMed

Sedlaříková, Lenka; Bešše, Lenka; Novosadová, Soňa; Kubaczková, Veronika; Radová, Lenka; Staník, Michal; Krejčí, Marta; Hájek, Roman; Ševčíková, Sabina

2015-09-23

In this study, we aimed to identify microRNA from urine of multiple myeloma patients that could serve as a biomarker for the disease. Analysis of urine samples was performed using Serum/Plasma Focus PCR MicroRNA Panel (Exiqon) and verified using individual TaqMan miRNA assays for qPCR. We found 20 deregulated microRNA (p < 0.05); for further validation, we chose 8 of them. Nevertheless, only differences in expression levels of miR-22-3p remained close to statistical significance. Our preliminary results did not confirm urine microRNA as a potential biomarker for multiple myeloma.

An in-depth analysis identifies two new independent signals in 11q23.3 associated with vitiligo in the Chinese Han population.

PubMed

Zhao, Suli; Fang, Fang; Tang, Xianfa; Dou, Jinfa; Wang, Wenjun; Zheng, Xiaodong; Sun, Liangdan; Zhang, Anping

2017-10-01

Vitiligo is an autoimmune disease, characterized by progressive loss of skin pigmentation, which is caused by the interactions of multiple factors, such as heredity, immunity and environment. Recently, a single nucleotide polymorphism (SNP) rs638893 at 11q23.3 region was identified as a risk factor for vitiligo in genome-wide association studies and multiple SNPs in this region have been associated with other autoimmune diseases. This study aims to identify additional susceptibility variants associated with vitiligo at 11q23.3 in the Chinese Han population. We selected and genotyped 26 SNPs at 11q23.3 in an independent cohort including 2924 cases and 4048 controls using the Sequenom MassArray iPLEX ® system. Bonferroni adjustment was used for multiple comparisons and P value <1.92×10 -3 (0.05/26) was considered statistically significant. The A allele of rs613791 and G allele of rs523604 located in CXCR5 were observed to be significantly associated with vitiligo (OR=1.21, 95% CI: 1.11-1.31, P=1.20×10 -5 ; OR=1.14, 95% CI: 1.07-1.23, P=1.90×10 -4 , respectively). The C allele of rs638893 (a previously reported one) located upstream of DDX6 was also significantly associated with vitiligo (OR=1.25, 95% CI: 1.12-1.38, P=3.04×10 -5 ). The genotypes distribution of 3 SNPs also showed significant differences between case and control (rs613791: P=7.00×10 -6 , rs523604: P=4.00×10 -3 , rs638893: P=1.20×10 -5 , respectively). The two newly identified SNPs (rs613791 and rs523604) showed independent associations with vitiligo by linkage disequilibrium analysis and conditional logistic regression. The study identified two new independent signals in the associated locus 11q23.3 for vitiligo. The presence of multiple independent variants emphasizes an important role of this region in disease susceptibility. Copyright © 2017 Japanese Society for Investigative Dermatology. Published by Elsevier B.V. All rights reserved.

Ovarian stimulation length, number of follicles higher than 17 mm and estradiol on the day of human chorionic gonadotropin administration are risk factors for multiple pregnancy in intrauterine insemination

PubMed Central

MELO, MARCO A.B.; SIMÓN, CARLOS; REMOHÍ, JOSÉ; PELLICER, ANTONIO; MESEGUER, MARCOS

2007-01-01

Aim:  The aim of the present study was to identify the risk factors, their prognostic value on multiple pregnancies (MP) prediction and their thresholds in women undergoing controlled ovarian hyperstimulation (COH) with follicle stimulating hormone (FSH) and intrauterine insemination (IUI). Methods:  A case‐control study was carried out by identifying in our database all the pregnancies reached by donor and conjugal IUI (DIUI and CIUI, respectively), and compared cycle features, patients’ characteristics and sperm analysis results between women achieving single pregnancy (SP) versus MP. The number of gestational sacs, follicular sizes and estradiol levels on the human chorionic gonadotropin (hCG) administration day, COH length and semen parameters were obtained from each cycle and compared. Student's t‐tests for mean comparisons, receiver–operator curve (ROC) analysis to determine the predictive value of each parameter on MP achievement and multiple regression analysis to determine single parameter influence were carried out. Results:  Women with MP in IUI stimulated cycles reached the adequate size of the dominant follicle (17 mm) significantly earlier than those achieving SP. Also, the mean follicles number, and estradiol levels on the hCG day were higher in the CIUI and DIUI MP group. Nevertheless, only ROC curve analysis revealed good prognostic value for estradiol and follicles higher than 17 mm. Multiple regression analysis confirmed these results. No feature of the basic sperm analysis, either in the ejaculate or in the prepared sample, was different or predictive of MP. When using donor sperm, different thresholds of follicle number, stimulation length and estradiol in the prediction of MP were noted, in comparison with CIUI. Conclusions:  MP in stimulated IUI cycles are closely associated to stimulation length, number of developed follicles higher than 17 mm on the day of hCG administration and estradiol levels. Also, estradiol has a good predictive value over MP in IUI stimulated cycles. The establishment of clinical thresholds will certainly help in the management of these couples to avoid undesired multiple pregnancies by canceling cycles or converting them into in vitro fertilization procedures. (Reprod Med Biol 2007; 6: 19–26) PMID:29699262

Comprehensive Characterization of Cancer Driver Genes and Mutations.

PubMed

Bailey, Matthew H; Tokheim, Collin; Porta-Pardo, Eduard; Sengupta, Sohini; Bertrand, Denis; Weerasinghe, Amila; Colaprico, Antonio; Wendl, Michael C; Kim, Jaegil; Reardon, Brendan; Ng, Patrick Kwok-Shing; Jeong, Kang Jin; Cao, Song; Wang, Zixing; Gao, Jianjiong; Gao, Qingsong; Wang, Fang; Liu, Eric Minwei; Mularoni, Loris; Rubio-Perez, Carlota; Nagarajan, Niranjan; Cortés-Ciriano, Isidro; Zhou, Daniel Cui; Liang, Wen-Wei; Hess, Julian M; Yellapantula, Venkata D; Tamborero, David; Gonzalez-Perez, Abel; Suphavilai, Chayaporn; Ko, Jia Yu; Khurana, Ekta; Park, Peter J; Van Allen, Eliezer M; Liang, Han; Lawrence, Michael S; Godzik, Adam; Lopez-Bigas, Nuria; Stuart, Josh; Wheeler, David; Getz, Gad; Chen, Ken; Lazar, Alexander J; Mills, Gordon B; Karchin, Rachel; Ding, Li

2018-04-05

Identifying molecular cancer drivers is critical for precision oncology. Multiple advanced algorithms to identify drivers now exist, but systematic attempts to combine and optimize them on large datasets are few. We report a PanCancer and PanSoftware analysis spanning 9,423 tumor exomes (comprising all 33 of The Cancer Genome Atlas projects) and using 26 computational tools to catalog driver genes and mutations. We identify 299 driver genes with implications regarding their anatomical sites and cancer/cell types. Sequence- and structure-based analyses identified >3,400 putative missense driver mutations supported by multiple lines of evidence. Experimental validation confirmed 60%-85% of predicted mutations as likely drivers. We found that >300 MSI tumors are associated with high PD-1/PD-L1, and 57% of tumors analyzed harbor putative clinically actionable events. Our study represents the most comprehensive discovery of cancer genes and mutations to date and will serve as a blueprint for future biological and clinical endeavors. Published by Elsevier Inc.

Pan-cancer genome and transcriptome analyses of 1,699 paediatric leukaemias and solid tumours | Office of Cancer Genomics

Cancer.gov

Analysis of molecular aberrations across multiple cancer types, known as pan-cancer analysis, identifies commonalities and differences in key biological processes that are dysregulated in cancer cells from diverse lineages. Pan-cancer analyses have been performed for adult1–4 but not paediatric cancers, which commonly occur in developing mesodermic rather than adult epithelial tissues5.

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.

Structural comparison of four different antibodies interacting with human papillomavirus 16 and mechanisms of neutralization

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

Guan, Jian; Bywaters, Stephanie M.; Brendle, Sarah A.

2015-09-15

Cryo-electron microscopy (cryo-EM) was used to solve the structures of human papillomavirus type 16 (HPV16) complexed with fragments of antibody (Fab) from three different neutralizing monoclonals (mAbs): H16.1A, H16.14J, and H263.A2. The structure-function analysis revealed predominantly monovalent binding of each Fab with capsid interactions that involved multiple loops from symmetry related copies of the major capsid protein. The residues identified in each Fab-virus interface map to a conformational groove on the surface of the capsomer. In addition to the known involvement of the FG and HI loops, the DE loop was also found to constitute the core of each epitope.more » Surprisingly, the epitope mapping also identified minor contributions by EF and BC loops. Complementary immunological assays included mAb and Fab neutralization. The specific binding characteristics of mAbs correlated with different neutralizing behaviors in pre- and post-attachment neutralization assays. - Highlights: • We present HPV16-Fab complexes from neutralizing mAbs: H16.1A, H16.14J, and H263.A2. • The structure-function analysis revealed predominantly monovalent binding of each mAb. • Capsid–Fab interactions involved multiple loops from symmetry related L1 proteins. • Besides the known FG and HI loops, epitope mapping also identified DE, EF, and BC loops. • Neutralizing assays complement the structures to show multiple neutralization mechanisms.« less

Evaluation of DNA mixtures from database search.

PubMed

Chung, Yuk-Ka; Hu, Yue-Qing; Fung, Wing K

2010-03-01

With the aim of bridging the gap between DNA mixture analysis and DNA database search, a novel approach is proposed to evaluate the forensic evidence of DNA mixtures when the suspect is identified by the search of a database of DNA profiles. General formulae are developed for the calculation of the likelihood ratio for a two-person mixture under general situations including multiple matches and imperfect evidence. The influence of the prior probabilities on the weight of evidence under the scenario of multiple matches is demonstrated by a numerical example based on Hong Kong data. Our approach is shown to be capable of presenting the forensic evidence of DNA mixtures in a comprehensive way when the suspect is identified through database search.

Predictors of job tenure in a lumber-plywood mill

Treesearch

Charles H. Wolf

1973-01-01

Multiple discriminant analysis was used to identify biographic and employment history variables associated with job tenure in a lumber-plywood mill. Several variables-friends and relatives, type of housing, commuting distance, and prior work experience in the wood industry-were found to be significant.

Sarcocystis neurona encephalitis in a dog.

PubMed

Cooley, A J; Barr, B; Rejmanek, D

2007-11-01

A 1.5-year-old male Feist dog was presented to a veterinarian for reluctance to stand on the hind legs. Treatment included dexamethasone and resulted in a favorable initial response, but posterior paresis returned and progressed to recumbency, hyperesthesia, and attempts to bite the owner. The dog was euthanized. The brain was negative for rabies by fluorescent antibody analysis. Multiple foci of encephalitis were found in the cerebrum and particularly in the cerebellum. Protozoa morphologically consistent with Sarcocystis sp. were identified at sites of intense inflammation and malacia. Additionally, multiple schizonts were identified in areas without inflammation. Immunohistochemistry using both polyclonal and monoclonal antibodies specific for Sarcocystis neurona was strongly positive. No reaction to polyclonal antisera for Toxoplasma gondii or Neospora caninum was found. Polymerase chain reaction confirmed that the protozoa were S. neurona. Additional aberrant hosts for S. neurona other than horses have been identified, but S. neurona encephalitis has not been documented previously in the dog.

Prognostic factors for early severity in a childhood multiple sclerosis cohort.

PubMed

Mikaeloff, Yann; Caridade, Guillaume; Assi, Saada; Suissa, Samy; Tardieu, Marc

2006-09-01

The goal was to identify prognostic factors for an early severe course in a cohort of patients with childhood-onset multiple sclerosis, for the construction of a predictive tool. The cohort consisted of 197 children from the French Kid Sclérose en Plaques neuropediatric cohort with relapsing/remitting multiple sclerosis beginning before the age of 16 years. Patients were included from 1990 to 2003. We used multivariate survival analysis (Cox model) to evaluate the prognostic value of clinical, MRI, and biological covariates at onset for the occurrence of a third attack or severe disability ("severity" outcome). The cohort was monitored for a mean of 5.5 +/- 3.6 years. The "severity" outcome was recorded for 144 patients (73%). The risk of severity was higher for girls, for a time between the first and second attacks of < 1 year, for childhood-onset multiple sclerosis MRI criteria at onset, for an absence of severe mental state changes at onset, and for a progressive course. A derived childhood-onset multiple sclerosis potential index for early severity was found to have a positive predictive value for severity of > 35% for the upper 2 quartiles. The clinical and MRI prognostic factors for early severity that were identified were used as the basis of a predictive tool, which will be validated in another cohort. This tool should make it possible to identify subgroups at risk of early severe disease and should facilitate therapeutic studies.

An integrated, ethically driven environmental model of clinical decision making in emergency settings.

PubMed

Wolf, Lisa

2013-02-01

To explore the relationship between multiple variables within a model of critical thinking and moral reasoning. A quantitative descriptive correlational design using a purposive sample of 200 emergency nurses. Measured variables were accuracy in clinical decision-making, moral reasoning, perceived care environment, and demographics. Analysis was by bivariate correlation using Pearson's product-moment correlation coefficients, chi square and multiple linear regression analysis. The elements as identified in the integrated ethically-driven environmental model of clinical decision-making (IEDEM-CD) corrected depict moral reasoning and environment of care as factors significantly affecting accuracy in decision-making. The integrated, ethically driven environmental model of clinical decision making is a framework useful for predicting clinical decision making accuracy for emergency nurses in practice, with further implications in education, research and policy. A diagnostic and therapeutic framework for identifying and remediating individual and environmental challenges to accurate clinical decision making. © 2012, The Author. International Journal of Nursing Knowledge © 2012, NANDA International.

Cross-species identification of genomic drivers of squamous cell carcinoma development across preneoplastic intermediates

PubMed Central

Chitsazzadeh, Vida; Coarfa, Cristian; Drummond, Jennifer A.; Nguyen, Tri; Joseph, Aaron; Chilukuri, Suneel; Charpiot, Elizabeth; Adelmann, Charles H.; Ching, Grace; Nguyen, Tran N.; Nicholas, Courtney; Thomas, Valencia D.; Migden, Michael; MacFarlane, Deborah; Thompson, Erika; Shen, Jianjun; Takata, Yoko; McNiece, Kayla; Polansky, Maxim A.; Abbas, Hussein A.; Rajapakshe, Kimal; Gower, Adam; Spira, Avrum; Covington, Kyle R.; Xiao, Weimin; Gunaratne, Preethi; Pickering, Curtis; Frederick, Mitchell; Myers, Jeffrey N.; Shen, Li; Yao, Hui; Su, Xiaoping; Rapini, Ronald P.; Wheeler, David A.; Hawk, Ernest T.; Flores, Elsa R.; Tsai, Kenneth Y.

2016-01-01

Cutaneous squamous cell carcinoma (cuSCC) comprises 15–20% of all skin cancers, accounting for over 700,000 cases in USA annually. Most cuSCC arise in association with a distinct precancerous lesion, the actinic keratosis (AK). To identify potential targets for molecularly targeted chemoprevention, here we perform integrated cross-species genomic analysis of cuSCC development through the preneoplastic AK stage using matched human samples and a solar ultraviolet radiation-driven Hairless mouse model. We identify the major transcriptional drivers of this progression sequence, showing that the key genomic changes in cuSCC development occur in the normal skin to AK transition. Our data validate the use of this ultraviolet radiation-driven mouse cuSCC model for cross-species analysis and demonstrate that cuSCC bears deep molecular similarities to multiple carcinogen-driven SCCs from diverse sites, suggesting that cuSCC may serve as an effective, accessible model for multiple SCC types and that common treatment and prevention strategies may be feasible. PMID:27574101

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

PubMed Central

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

2015-01-01

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

Multiple-locus variable number of tandem repeat analysis (MLVA) of Irish verocytotoxigenic Escherichia coli O157 from feedlot cattle: uncovering strain dissemination routes.

PubMed

Murphy, Mary; Minihan, Donal; Buckley, James F; O'Mahony, Micheál; Whyte, Paul; Fanning, Séamus

2008-01-24

The identification of the routes of dissemination of Escherichia coli (E. coli) O157 through a cohort of cattle is a critical step to control this pathogen at farm level. The aim of this study was to identify potential routes of dissemination of E. coli O157 using Multiple-Locus Variable number of tandem repeat Analysis (MLVA). Thirty-eight environmental and sixteen cattle faecal isolates, which were detected in four adjacent pens over a four-month period were sub-typed. MLVA could separate these isolates into broadly defined clusters consisting of twelve MLVA types. Strain diversity was observed within pens, individual cattle and the environment. Application of MLVA is a broadly useful and convenient tool when applied to uncover the dissemination of E. coli O157 in the environment and in supporting improved on-farm management of this important pathogen. These data identified diverse strain types based on amplification of VNTR markers in each case.

Whole transcriptome analysis using next-generation sequencing of model species Setaria viridis to support C4 photosynthesis research.

PubMed

Xu, Jiajia; Li, Yuanyuan; Ma, Xiuling; Ding, Jianfeng; Wang, Kai; Wang, Sisi; Tian, Ye; Zhang, Hui; Zhu, Xin-Guang

2013-09-01

Setaria viridis is an emerging model species for genetic studies of C4 photosynthesis. Many basic molecular resources need to be developed to support for this species. In this paper, we performed a comprehensive transcriptome analysis from multiple developmental stages and tissues of S. viridis using next-generation sequencing technologies. Sequencing of the transcriptome from multiple tissues across three developmental stages (seed germination, vegetative growth, and reproduction) yielded a total of 71 million single end 100 bp long reads. Reference-based assembly using Setaria italica genome as a reference generated 42,754 transcripts. De novo assembly generated 60,751 transcripts. In addition, 9,576 and 7,056 potential simple sequence repeats (SSRs) covering S. viridis genome were identified when using the reference based assembled transcripts and the de novo assembled transcripts, respectively. This identified transcripts and SSR provided by this study can be used for both reverse and forward genetic studies based on S. viridis.

An integrative system biology approach to unravel potential drug candidates for multiple age related disorders.

PubMed

Srivastava, Isha; Khurana, Pooja; Yadav, Mohini; Hasija, Yasha

2017-12-01

Aging, though an inevitable part of life, is becoming a worldwide social and economic problem. Healthy aging is usually marked by low probability of age related disorders. Good therapeutic approaches are still in need to cure age related disorders. Occurrence of more than one ARD in an individual, expresses the need of discovery of such target proteins, which can affect multiple ARDs. Advanced scientific and medical research technologies throughout last three decades have arrived to the point where lots of key molecular determinants affect human disorders can be examined thoroughly. In this study, we designed and executed an approach to prioritize drugs that may target multiple age related disorders. Our methodology, focused on the analysis of biological pathways and protein protein interaction networks that may contribute to the pharmacology of age related disorders, included various steps such as retrieval and analysis of data, protein-protein interaction network analysis, and statistical and comparative analysis of topological coefficients, pathway, and functional enrichment analysis, and identification of drug-target proteins. We assume that the identified molecular determinants may be prioritized for further screening as novel drug targets to cure multiple ARDs. Based on the analysis, an online tool named as 'ARDnet' has been developed to construct and demonstrate ARD interactions at the level of PPI, ARDs and ARDs protein interaction, ARDs pathway interaction and drug-target interaction. The tool is freely made available at http://genomeinformatics.dtu.ac.in/ARDNet/Index.html. Copyright © 2017 Elsevier B.V. All rights reserved.

Structure of the human gene encoding the protein repair L-isoaspartyl (D-aspartyl) O-methyltransferase.

PubMed

DeVry, C G; Tsai, W; Clarke, S

1996-11-15

The protein L-isoaspartyl/D-aspartyl O-methyltransferase (EC 2.1.1.77) catalyzes the first step in the repair of proteins damaged in the aging process by isomerization or racemization reactions at aspartyl and asparaginyl residues. A single gene has been localized to human chromosome 6 and multiple transcripts arising through alternative splicing have been identified. Restriction enzyme mapping, subcloning, and DNA sequence analysis of three overlapping clones from a human genomic library in bacteriophage P1 indicate that the gene spans approximately 60 kb and is composed of 8 exons interrupted by 7 introns. Analysis of intron/exon splice junctions reveals that all of the donor and acceptor splice sites are in agreement with the mammalian consensus splicing sequence. Determination of transcription initiation sites by primer extension analysis of poly(A)+ mRNA from human brain identifies multiple start sites, with a major site 159 nucleotides upstream from the ATG start codon. Sequence analysis of the 5'-untranslated region demonstrates several potential cis-acting DNA elements including SP1, ETF, AP1, AP2, ARE, XRE, CREB, MED-1, and half-palindromic ERE motifs. The promoter of this methyltransferase gene lacks an identifiable TATA box but is characterized by a CpG island which begins approximately 723 nucleotides upstream of the major transcriptional start site and extends through exon 1 and into the first intron. These features are characteristic of housekeeping genes and are consistent with the wide tissue distribution observed for this methyltransferase activity.

Integrative radiogenomic analysis for multicentric radiophenotype in glioblastoma

PubMed Central

Kong, Doo-Sik; Kim, Jinkuk; Lee, In-Hee; Kim, Sung Tae; Seol, Ho Jun; Lee, Jung-Il; Park, Woong-Yang; Ryu, Gyuha; Wang, Zichen; Ma'ayan, Avi; Nam, Do-Hyun

2016-01-01

We postulated that multicentric glioblastoma (GBM) represents more invasiveness form than solitary GBM and has their own genomic characteristics. From May 2004 to June 2010 we retrospectively identified 51 treatment-naïve GBM patients with available clinical information from the Samsung Medical Center data registry. Multicentricity of the tumor was defined as the presence of multiple foci on the T1 contrast enhancement of MR images or having high signal for multiple lesions without contiguity of each other on the FLAIR image. Kaplan-Meier survival analysis demonstrated that multicentric GBM had worse prognosis than solitary GBM (median, 16.03 vs. 20.57 months, p < 0.05). Copy number variation (CNV) analysis revealed there was an increase in 11 regions, and a decrease in 17 regions, in the multicentric GBM. Gene expression profiling identified 738 genes to be increased and 623 genes to be decreased in the multicentric radiophenotype (p < 0.001). Integration of the CNV and expression datasets identified twelve representative genes: CPM, LANCL2, LAMP1, GAS6, DCUN1D2, CDK4, AGAP2, TSPAN33, PDLIM1, CLDN12, and GTPBP10 having high correlation across CNV, gene expression and patient outcome. Network and enrichment analyses showed that the multicentric tumor had elevated fibrotic signaling pathways compared with a more proliferative and mitogenic signal in the solitary tumors. Noninvasive radiological imaging together with integrative radiogenomic analysis can provide an important tool in helping to advance personalized therapy for the more clinically aggressive subset of GBM. PMID:26863628

Cross-species multiple environmental stress responses: An integrated approach to identify candidate genes for multiple stress tolerance in sorghum (Sorghum bicolor (L.) Moench) and related model species

PubMed Central

Modise, David M.; Gemeildien, Junaid; Ndimba, Bongani K.; Christoffels, Alan

2018-01-01

Background Crop response to the changing climate and unpredictable effects of global warming with adverse conditions such as drought stress has brought concerns about food security to the fore; crop yield loss is a major cause of concern in this regard. Identification of genes with multiple responses across environmental stresses is the genetic foundation that leads to crop adaptation to environmental perturbations. Methods In this paper, we introduce an integrated approach to assess candidate genes for multiple stress responses across-species. The approach combines ontology based semantic data integration with expression profiling, comparative genomics, phylogenomics, functional gene enrichment and gene enrichment network analysis to identify genes associated with plant stress phenotypes. Five different ontologies, viz., Gene Ontology (GO), Trait Ontology (TO), Plant Ontology (PO), Growth Ontology (GRO) and Environment Ontology (EO) were used to semantically integrate drought related information. Results Target genes linked to Quantitative Trait Loci (QTLs) controlling yield and stress tolerance in sorghum (Sorghum bicolor (L.) Moench) and closely related species were identified. Based on the enriched GO terms of the biological processes, 1116 sorghum genes with potential responses to 5 different stresses, such as drought (18%), salt (32%), cold (20%), heat (8%) and oxidative stress (25%) were identified to be over-expressed. Out of 169 sorghum drought responsive QTLs associated genes that were identified based on expression datasets, 56% were shown to have multiple stress responses. On the other hand, out of 168 additional genes that have been evaluated for orthologous pairs, 90% were conserved across species for drought tolerance. Over 50% of identified maize and rice genes were responsive to drought and salt stresses and were co-located within multifunctional QTLs. Among the total identified multi-stress responsive genes, 272 targets were shown to be co-localized within QTLs associated with different traits that are responsive to multiple stresses. Ontology mapping was used to validate the identified genes, while reconstruction of the phylogenetic tree was instrumental to infer the evolutionary relationship of the sorghum orthologs. The results also show specific genes responsible for various interrelated components of drought response mechanism such as drought tolerance, drought avoidance and drought escape. Conclusions We submit that this approach is novel and to our knowledge, has not been used previously in any other research; it enables us to perform cross-species queries for genes that are likely to be associated with multiple stress tolerance, as a means to identify novel targets for engineering stress resistance in sorghum and possibly, in other crop species. PMID:29590108

Exploring High-D Spaces with Multiform Matrices and Small Multiples

PubMed Central

MacEachren, Alan; Dai, Xiping; Hardisty, Frank; Guo, Diansheng; Lengerich, Gene

2011-01-01

We introduce an approach to visual analysis of multivariate data that integrates several methods from information visualization, exploratory data analysis (EDA), and geovisualization. The approach leverages the component-based architecture implemented in GeoVISTA Studio to construct a flexible, multiview, tightly (but generically) coordinated, EDA toolkit. This toolkit builds upon traditional ideas behind both small multiples and scatterplot matrices in three fundamental ways. First, we develop a general, MultiForm, Bivariate Matrix and a complementary MultiForm, Bivariate Small Multiple plot in which different bivariate representation forms can be used in combination. We demonstrate the flexibility of this approach with matrices and small multiples that depict multivariate data through combinations of: scatterplots, bivariate maps, and space-filling displays. Second, we apply a measure of conditional entropy to (a) identify variables from a high-dimensional data set that are likely to display interesting relationships and (b) generate a default order of these variables in the matrix or small multiple display. Third, we add conditioning, a kind of dynamic query/filtering in which supplementary (undisplayed) variables are used to constrain the view onto variables that are displayed. Conditioning allows the effects of one or more well understood variables to be removed from the analysis, making relationships among remaining variables easier to explore. We illustrate the individual and combined functionality enabled by this approach through application to analysis of cancer diagnosis and mortality data and their associated covariates and risk factors. PMID:21947129

Hemorrhage and Subsequent Allogenic Red Blood Cell Transfusion are Associated With Characteristic Monocyte Messenger RNA Expression Patterns in Patients After Multiple Injury—A Genome Wide View

PubMed Central

Bogner, Viktoria; Baker, Henry V.; Kanz, Karl-Georg; Moldawer, L. L.; Mutschler, Wolf; Biberthaler, Peter

2014-01-01

Introduction As outcome to severe trauma is frequently affected by massive blood loss and consecutive hemorrhagic shock, replacement of red blood cell (RBC) units remains indispensable. Administration of RBC units is an independent risk factor for adverse outcome in patients with trauma. The impact of massive blood transfusion or uncrossmatched blood transfusion on the patients’ immune response in the early posttraumatic period remains unclear. Material Thirteen patients presenting with blunt multiple injuries (Injury Severity Score >16) were studied. Monocytes were obtained on admission and at 6, 12, 24, 48, and 72 hours after trauma. Biotinylated complementary RNA targets were hybridized to Affymetrix HG U 133A microarrays. The data were analyzed by a supervised analysis based on whether the patients received massive blood transfusions, and then subsequently, by hierarchical clustering, and by Ingenuity pathway analysis. Results Supervised analysis identified 224 probe sets to be differentially expressed (p < 0.001) in patients who received massive blood transfusion, when compared with those who did not. In addition, 331 probe sets were found differentially expressed (p < 0.001) in patients who received uncrossmatched RBC units in comparison with those who exclusively gained crossmatched ones. Functional pathway analysis of the respectively identified gene expression profiles suggests a contributory role by the AKT/PI3Kinase pathway, the mitogen-activated protein-kinase pathway, the Ubiquitin pathway, and the diverse inflammatory networks. Conclusion We exhibited for the first time a serial, sequential screening analysis of monocyte messenger RNA expression patterns in patients with multiple trauma indicating a strongly significant association between the patients’ genomic response in blood monocytes and massive or uncross-matched RBC substitution. PMID:19820587

Development of the Policy Indicator Checklist: A Tool to Identify and Measure Policies for Calorie-Dense Foods and Sugar-Sweetened Beverages Across Multiple Settings

PubMed Central

Hallett, Allen M.; Parker, Nathan; Kudia, Ousswa; Kao, Dennis; Modelska, Maria; Rifai, Hanadi; O’Connor, Daniel P.

2015-01-01

Objectives. We developed the policy indicator checklist (PIC) to identify and measure policies for calorie-dense foods and sugar-sweetened beverages to determine how policies are clustered across multiple settings. Methods. In 2012 and 2013 we used existing literature, policy documents, government recommendations, and instruments to identify key policies. We then developed the PIC to examine the policy environments across 3 settings (communities, schools, and early care and education centers) in 8 communities participating in the Childhood Obesity Research Demonstration Project. Results. Principal components analysis revealed 5 components related to calorie-dense food policies and 4 components related to sugar-sweetened beverage policies. Communities with higher youth and racial/ethnic minority populations tended to have fewer and weaker policy environments concerning calorie-dense foods and healthy foods and beverages. Conclusions. The PIC was a helpful tool to identify policies that promote healthy food environments across multiple settings and to measure and compare the overall policy environments across communities. There is need for improved coordination across settings, particularly in areas with greater concentration of youths and racial/ethnic minority populations. Policies to support healthy eating are not equally distributed across communities, and disparities continue to exist in nutrition policies. PMID:25790397

Development of the policy indicator checklist: a tool to identify and measure policies for calorie-dense foods and sugar-sweetened beverages across multiple settings.

PubMed

Lee, Rebecca E; Hallett, Allen M; Parker, Nathan; Kudia, Ousswa; Kao, Dennis; Modelska, Maria; Rifai, Hanadi; O'Connor, Daniel P

2015-05-01

We developed the policy indicator checklist (PIC) to identify and measure policies for calorie-dense foods and sugar-sweetened beverages to determine how policies are clustered across multiple settings. In 2012 and 2013 we used existing literature, policy documents, government recommendations, and instruments to identify key policies. We then developed the PIC to examine the policy environments across 3 settings (communities, schools, and early care and education centers) in 8 communities participating in the Childhood Obesity Research Demonstration Project. Principal components analysis revealed 5 components related to calorie-dense food policies and 4 components related to sugar-sweetened beverage policies. Communities with higher youth and racial/ethnic minority populations tended to have fewer and weaker policy environments concerning calorie-dense foods and healthy foods and beverages. The PIC was a helpful tool to identify policies that promote healthy food environments across multiple settings and to measure and compare the overall policy environments across communities. There is need for improved coordination across settings, particularly in areas with greater concentration of youths and racial/ethnic minority populations. Policies to support healthy eating are not equally distributed across communities, and disparities continue to exist in nutrition policies.

Visually Exploring Transportation Schedules.

PubMed

Palomo, Cesar; Guo, Zhan; Silva, Cláudio T; Freire, Juliana

2016-01-01

Public transportation schedules are designed by agencies to optimize service quality under multiple constraints. However, real service usually deviates from the plan. Therefore, transportation analysts need to identify, compare and explain both eventual and systemic performance issues that must be addressed so that better timetables can be created. The purely statistical tools commonly used by analysts pose many difficulties due to the large number of attributes at trip- and station-level for planned and real service. Also challenging is the need for models at multiple scales to search for patterns at different times and stations, since analysts do not know exactly where or when relevant patterns might emerge and need to compute statistical summaries for multiple attributes at different granularities. To aid in this analysis, we worked in close collaboration with a transportation expert to design TR-EX, a visual exploration tool developed to identify, inspect and compare spatio-temporal patterns for planned and real transportation service. TR-EX combines two new visual encodings inspired by Marey's Train Schedule: Trips Explorer for trip-level analysis of frequency, deviation and speed; and Stops Explorer for station-level study of delay, wait time, reliability and performance deficiencies such as bunching. To tackle overplotting and to provide a robust representation for a large numbers of trips and stops at multiple scales, the system supports variable kernel bandwidths to achieve the level of detail required by users for different tasks. We justify our design decisions based on specific analysis needs of transportation analysts. We provide anecdotal evidence of the efficacy of TR-EX through a series of case studies that explore NYC subway service, which illustrate how TR-EX can be used to confirm hypotheses and derive new insights through visual exploration.

Memory training interventions for older adults: a meta-analysis.

PubMed

Gross, Alden L; Parisi, Jeanine M; Spira, Adam P; Kueider, Alexandra M; Ko, Jean Y; Saczynski, Jane S; Samus, Quincy M; Rebok, George W

2012-01-01

A systematic review and meta-analysis of memory training research was conducted to characterize the effect of memory strategies on memory performance among cognitively intact, community-dwelling older adults, and to identify characteristics of individuals and of programs associated with improved memory. The review identified 402 publications, of which 35 studies met criteria for inclusion. The overall effect size estimate, representing the mean standardized difference in pre-post change between memory-trained and control groups, was 0.31 standard deviations (SD; 95% confidence interval (CI): 0.22, 0.39). The pre-post training effect for memory-trained interventions was 0.43 SD (95% CI: 0.29, 0.57) and the practice effect for control groups was 0.06 SD (95% CI: 0.05, 0.16). Among 10 distinct memory strategies identified in studies, meta-analytic methods revealed that training multiple strategies was associated with larger training gains (p=0.04), although this association did not reach statistical significance after adjusting for multiple comparisons. Treatment gains among memory-trained individuals were not better after training in any particular strategy, or by the average age of participants, session length, or type of control condition. These findings can inform the design of future memory training programs for older adults.

MODi: a powerful and convenient web server for identifying multiple post-translational peptide modifications from tandem mass spectra.

PubMed

Kim, Sangtae; Na, Seungjin; Sim, Ji Woong; Park, Heejin; Jeong, Jaeho; Kim, Hokeun; Seo, Younghwan; Seo, Jawon; Lee, Kong-Joo; Paek, Eunok

2006-07-01

MOD(i) (http://modi.uos.ac.kr/modi/) is a powerful and convenient web service that facilitates the interpretation of tandem mass spectra for identifying post-translational modifications (PTMs) in a peptide. It is powerful in that it can interpret a tandem mass spectrum even when hundreds of modification types are considered and the number of potential PTMs in a peptide is large, in contrast to most of the methods currently available for spectra interpretation that limit the number of PTM sites and types being used for PTM analysis. For example, using MOD(i), one can consider for analysis both the entire PTM list published on the unimod webpage (http://www.unimod.org) and user-defined PTMs simultaneously, and one can also identify multiple PTM sites in a spectrum. MOD(i) is convenient in that it can take various input file formats such as .mzXML, .dta, .pkl and .mgf files, and it is equipped with a graphical tool called MassPective developed to display MOD(i)'s output in a user-friendly manner and helps users understand MOD(i)'s output quickly. In addition, one can perform manual de novo sequencing using MassPective.

A Unified Framework for Association Analysis with Multiple Related Phenotypes

PubMed Central

Stephens, Matthew

2013-01-01

We consider the problem of assessing associations between multiple related outcome variables, and a single explanatory variable of interest. This problem arises in many settings, including genetic association studies, where the explanatory variable is genotype at a genetic variant. We outline a framework for conducting this type of analysis, based on Bayesian model comparison and model averaging for multivariate regressions. This framework unifies several common approaches to this problem, and includes both standard univariate and standard multivariate association tests as special cases. The framework also unifies the problems of testing for associations and explaining associations – that is, identifying which outcome variables are associated with genotype. This provides an alternative to the usual, but conceptually unsatisfying, approach of resorting to univariate tests when explaining and interpreting significant multivariate findings. The method is computationally tractable genome-wide for modest numbers of phenotypes (e.g. 5–10), and can be applied to summary data, without access to raw genotype and phenotype data. We illustrate the methods on both simulated examples, and to a genome-wide association study of blood lipid traits where we identify 18 potential novel genetic associations that were not identified by univariate analyses of the same data. PMID:23861737

Cross-reactivity profiles of legumes and tree nuts using the xMAP® multiplex food allergen detection assay.

PubMed

Cho, Chung Y; Oles, Carolyn; Nowatzke, William; Oliver, Kerry; Garber, Eric A E

2017-10-01

The homology between proteins in legumes and tree nuts makes it common for individuals with food allergies to be allergic to multiple legumes and tree nuts. This propensity for allergenic and antigenic cross-reactivity means that commonly employed commercial immunodiagnostic assays (e.g., dipsticks) for the detection of food allergens may not always accurately detect, identify, and quantitate legumes and tree nuts unless additional orthogonal analytical methods or secondary measures of analysis are employed. The xMAP ® Multiplex Food Allergen Detection Assay (FADA) was used to determine the cross-reactivity patterns and the utility of multi-antibody antigenic profiling to distinguish between legumes and tree nuts. Pure legumes and tree nuts extracted using buffered detergent displayed a high level of cross-reactivity that decreased upon dilution or by using a buffer (UD buffer) designed to increase the stringency of binding conditions and reduce the occurrence of false positives due to plant-derived lectins. Testing for unexpected food allergens or the screening for multiple food allergens often involves not knowing the identity of the allergen present, its concentration, or the degree of modification during processing. As such, the analytical response measured may represent multiple antigens of varying antigenicity (cross-reactivity). This problem of multiple potential analytes is usually unresolved and the focus becomes the primary analyte, the antigen the antibody was raised against, or quantitative interpretation of the content of the analytical sample problematic. The alternative solution offered here to this problem is the use of an antigenic profile as generated by the xMAP FADA using multiple antibodies (bead sets). By comparing the antigenic profile to standards, the allergen may be identified along with an estimate of the concentration present. Cluster analysis of the xMAP FADA data was also performed and agreed with the known phylogeny of the legumes and tree nuts being analyzed. Graphical abstract The use of cluster analysis to compare the multi-antigen profiles of food allergens.

Syndrome disintegration: Exome sequencing reveals that Fitzsimmons syndrome is a co-occurrence of multiple events.

PubMed

Armour, Christine M; Smith, Amanda; Hartley, Taila; Chardon, Jodi Warman; Sawyer, Sarah; Schwartzentruber, Jeremy; Hennekam, Raoul; Majewski, Jacek; Bulman, Dennis E; Suri, Mohnish; Boycott, Kym M

2016-07-01

In 1987 Fitzsimmons and Guilbert described identical male twins with progressive spastic paraplegia, brachydactyly with cone shaped epiphyses, short stature, dysarthria, and "low-normal" intelligence. In subsequent years, four other patients, including one set of female identical twins, a single female child, and a single male individual were described with the same features, and the eponym Fitzsimmons syndrome was adopted (OMIM #270710). We performed exome analysis of the patient described in 2009, and one of the original twins from 1987, the only patients available from the literature. No single genetic etiology exists that explains Fitzsimmons syndrome; however, multiple different genetic causes were identified. Specifically, the twins described by Fitzsimmons had heterozygous mutations in the SACS gene, the gene responsible for autosomal recessive spastic ataxia of Charlevoix Saguenay (ARSACS), as well as a heterozygous mutation in the TRPS1, the gene responsible in Trichorhinophalangeal syndrome type 1 (TRPS1 type 1) which includes brachydactyly as a feature. A TBL1XR1 mutation was identified in the patient described in 2009 as contributing to his cognitive impairment and autistic features with no genetic cause identified for his spasticity or brachydactyly. The findings show that these individuals have multiple different etiologies giving rise to a similar phenotype, and that "Fitzsimmons syndrome" is in fact not one single syndrome. Over time, we anticipate that continued careful phenotyping with concomitant genome-wide analysis will continue to identify the causes of many rare syndromes, but it will also highlight that previously delineated clinical entities are, in fact, not syndromes at all. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Functional grouping and cortical–subcortical interactions in emotion: A meta-analysis of neuroimaging studies

PubMed Central

Kober, Hedy; Barrett, Lisa Feldman; Joseph, Josh; Bliss-Moreau, Eliza; Lindquist, Kristen; Wager, Tor D.

2009-01-01

We performed an updated quantitative meta-analysis of 162 neuroimaging studies of emotion using a novel multi-level kernel-based approach, focusing on locating brain regions consistently activated in emotional tasks and their functional organization into distributed functional groups, independent of semantically defined emotion category labels (e.g., “anger,” “fear”). Such brain-based analyses are critical if our ways of labeling emotions are to be evaluated and revised based on consistency with brain data. Consistent activations were limited to specific cortical sub-regions, including multiple functional areas within medial, orbital, and inferior lateral frontal cortices. Consistent with a wealth of animal literature, multiple subcortical activations were identified, including amygdala, ventral striatum, thalamus, hypothalamus, and periaqueductal gray. We used multivariate parcellation and clustering techniques to identify groups of co-activated brain regions across studies. These analyses identified six distributed functional groups, including medial and lateral frontal groups, two posterior cortical groups, and paralimbic and core limbic/brainstem groups. These functional groups provide information on potential organization of brain regions into large-scale networks. Specific follow-up analyses focused on amygdala, periaqueductal gray (PAG), and hypothalamic (Hy) activations, and identified frontal cortical areas co-activated with these core limbic structures. While multiple areas of frontal cortex co-activated with amygdala sub-regions, a specific region of dorsomedial prefrontal cortex (dmPFC, Brodmann’s Area 9/32) was the only area co-activated with both PAG and Hy. Subsequent mediation analyses were consistent with a pathway from dmPFC through PAG to Hy. These results suggest that medial frontal areas are more closely associated with core limbic activation than their lateral counterparts, and that dmPFC may play a particularly important role in the cognitive generation of emotional states. PMID:18579414

Estimating Water Levels with Google Earth Engine

NASA Astrophysics Data System (ADS)

Lucero, E.; Russo, T. A.; Zentner, M.; May, J.; Nguy-Robertson, A. L.

2016-12-01

Reservoirs serve multiple functions and are vital for storage, electricity generation, and flood control. For many areas, traditional ground-based reservoir measurements may not be available or data dissemination may be problematic. Consistent monitoring of reservoir levels in data-poor areas can be achieved through remote sensing, providing information to researchers and the international community. Estimates of trends and relative reservoir volume can be used to identify water supply vulnerability, anticipate low power generation, and predict flood risk. Image processing with automated cloud computing provides opportunities to study multiple geographic areas in near real-time. We demonstrate the prediction capability of a cloud environment for identifying water trends at reservoirs in the US, and then apply the method to data-poor areas in North Korea, Iran, Azerbaijan, Zambia, and India. The Google Earth Engine cloud platform hosts remote sensing data and can be used to automate reservoir level estimation with multispectral imagery. We combine automated cloud-based analysis from Landsat image classification to identify reservoir surface area trends and radar altimetry to identify reservoir level trends. The study estimates water level trends using three years of data from four domestic reservoirs to validate the remote sensing method, and five foreign reservoirs to demonstrate the method application. We report correlations between ground-based reservoir level measurements in the US and our remote sensing methods, and correlations between the cloud analysis and altimetry data for reservoirs in data-poor areas. The availability of regular satellite imagery and an automated, near real-time application method provides the necessary datasets for further temporal analysis, reservoir modeling, and flood forecasting. All statements of fact, analysis, or opinion are those of the author and do not reflect the official policy or position of the Department of Defense or any of its components or the U.S. Government

Serum Albumin and Disease Severity of Non-Cystic Fibrosis Bronchiectasis.

PubMed

Lee, Seung Jun; Kim, Hyo-Jung; Kim, Ju-Young; Ju, Sunmi; Lim, Sujin; Yoo, Jung Wan; Nam, Sung-Jin; Lee, Gi Dong; Cho, Hyun Seop; Kim, Rock Bum; Cho, Yu Ji; Jeong, Yi Yeong; Kim, Ho Cheol; Lee, Jong Deog

2017-08-01

A clinical classification system has been developed to define the severity and predict the prognosis of subjects with non-cystic fibrosis (CF) bronchiectasis. We aimed to identify laboratory parameters that are correlated with the bronchiectasis severity index (BSI) and FACED score. The medical records of 107 subjects with non-CF bronchiectasis for whom BSI and FACED scores could be calculated were retrospectively reviewed. The correlations between the laboratory parameters and BSI or FACED score were assessed, and multiple-linear regression analysis was performed to identify variables independently associated with BSI and FACED score. An additional subgroup analysis was performed according to sex. Among all of the enrolled subjects, 49 (45.8%) were male and 58 (54.2%) were female. The mean BSI and FACED scores were 9.43 ± 3.81 and 1.92 ± 1.59, respectively. The serum albumin level (r = -0.49), bilirubin level (r = -0.31), C-reactive protein level (r = 0.22), hemoglobin level (r = -0.2), and platelet/lymphocyte ratio (r = 0.31) were significantly correlated with BSI. Meanwhile, serum albumin (r = -0.37) and bilirubin level (r = -0.25) showed a significant correlation with the FACED score. Multiple-linear regression analysis showed that the serum bilirubin level was independently associated with BSI, and the serum albumin level was independently associated with both scoring systems. Subgroup analysis revealed that the level of uric acid was also a significant variable independently associated with the BSI in male bronchiectasis subjects. Several laboratory variables were identified as possible prognostic factors for non-CF bronchiectasis. Among them, the serum albumin level exhibited the strongest correlation and was identified as an independent variable associated with the BSI and FACED scores. Copyright © 2017 by Daedalus Enterprises.

Biogeographical Analysis of Chemical Co-Occurrence Data to Identify Priorities for Mixtures Research

EPA Science Inventory

A challenge with multiple chemical risk assessment is the need to consider the joint behavior of chemicals in mixtures. To address this need, pharmacologists and toxicologists have developed methods over the years to evaluate and test chemical interaction. In practice, however, t...

Integrated Analysis of Genetic and Proteomic Data Identifies Biomarkers Associated with Adverse Events Following Smallpox Vaccination

EPA Science Inventory

Complex clinical outcomes, such as adverse reaction to vaccination, arise from the concerted interactions among the myriad components of a biological system. Therefore, comprehensive etiological models can be developed only through the integrated study of multiple types of experi...

Morphological characteristics associated with rupture risk of multiple intracranial aneurysms.

PubMed

Wang, Guang-Xian; Liu, Lan-Lan; Wen, Li; Cao, Yun-Xing; Pei, Yu-Chun; Zhang, Dong

2017-10-01

To identify the morphological parameters that are related to intracranial aneurysms (IAs) rupture using a case-control model. A total of 107 patients with multiple IAs and aneurysmal subarachnoid hemorrhage between August 2011 and February 2017 were enrolled in this study. Characteristics of IAs location, shape, neck width, perpendicular height, depth, maximum size, flow angle, parent vessel diameter (PVD), aspect ratio (AR) and size ratio (SR) were evaluated using CT angiography. Multiple logistic regression analysis was used to identify the independent risk factors associated with IAs rupture. Receiver operating characteristic curve analysis was performed on the final model, and the optimal thresholds were obtained. IAs located in the internal carotid artery (ICA) was associated with a negative risk of rupture, whereas AR, SR1 (height/PVD) and SR2 (depth/PVD) were associated with increased risk of rupture. When SR was calculated differently, the odds ratio values of these factors were also different. The receiver operating characteristic curve showed that AR, SR1 and SR2 had cut-off values of 1.01, 1.48 and 1.40, respectively. SR3 (maximum size/PVD) was not associated with IAs rupture. IAs located in the ICA are associated with a negative risk of rupture, while high AR (>1.01), SR1 (>1.48) or SR2 (>1.40) are risk factors for multiple IAs rupture. Copyright © 2017 Hainan Medical University. Production and hosting by Elsevier B.V. All rights reserved.

A county-level cross-sectional analysis of positive deviance to assess multiple population health outcomes in Indiana.

PubMed

Hendryx, Michael; Guerra-Reyes, Lucia; Holland, Benjamin D; McGinnis, Michael Dean; Meanwell, Emily; Middlestadt, Susan E; Yoder, Karen M

2017-10-11

To test a positive deviance method to identify counties that are performing better than statistical expectations on a set of population health indicators. Quantitative, cross-sectional county-level secondary analysis of risk variables and outcomes in Indiana. Data are analysed using multiple linear regression to identify counties performing better or worse than expected given traditional risk indicators, with a focus on 'positive deviants' or counties performing better than expected. Counties in Indiana (n=92) constitute the unit of analysis. Per cent adult obesity, per cent fair/poor health, low birth weight per cent, per cent with diabetes, years of potential life lost, colorectal cancer incidence rate and circulatory disease mortality rate. County performance that outperforms expectations is for the most part outcome specific. But there are a few counties that performed particularly well across most measures. The positive deviance approach provides a means for state and local public health departments to identify places that show better health outcomes despite demographic, social, economic or behavioural disadvantage. These places may serve as case studies or models for subsequent investigations to uncover best practices in the face of adversity and generalise effective approaches to other areas. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Identification of multiple interacting alleles conferring low glycerol and high ethanol yield in Saccharomyces cerevisiae ethanolic fermentation

PubMed Central

2013-01-01

Background Genetic engineering of industrial microorganisms often suffers from undesirable side effects on essential functions. Reverse engineering is an alternative strategy to improve multifactorial traits like low glycerol/high ethanol yield in yeast fermentation. Previous rational engineering of this trait always affected essential functions like growth and stress tolerance. We have screened Saccharomyces cerevisiae biodiversity for specific alleles causing lower glycerol/higher ethanol yield, assuming higher compatibility with normal cellular functionality. Previous work identified ssk1E330N…K356N as causative allele in strain CBS6412, which displayed the lowest glycerol/ethanol ratio. Results We have now identified a unique segregant, 26B, that shows similar low glycerol/high ethanol production as the superior parent, but lacks the ssk1E330N…K356N allele. Using segregants from the backcross of 26B with the inferior parent strain, we applied pooled-segregant whole-genome sequence analysis and identified three minor quantitative trait loci (QTLs) linked to low glycerol/high ethanol production. Within these QTLs, we identified three novel alleles of known regulatory and structural genes of glycerol metabolism, smp1R110Q,P269Q, hot1P107S,H274Y and gpd1L164P as causative genes. All three genes separately caused a significant drop in the glycerol/ethanol production ratio, while gpd1L164P appeared to be epistatically suppressed by other alleles in the superior parent. The order of potency in reducing the glycerol/ethanol ratio of the three alleles was: gpd1L164P > hot1P107S,H274Y ≥ smp1R110Q,P269Q. Conclusions Our results show that natural yeast strains harbor multiple specific alleles of genes controlling essential functions, that are apparently compatible with survival in the natural environment. These newly identified alleles can be used as gene tools for engineering industrial yeast strains with multiple subtle changes, minimizing the risk of negatively affecting other essential functions. The gene tools act at the transcriptional, regulatory or structural gene level, distributing the impact over multiple targets and thus further minimizing possible side-effects. In addition, the results suggest polygenic analysis of complex traits as a promising new avenue to identify novel components involved in cellular functions, including those important in industrial applications. PMID:23759206

Genome Sequencing and Comparative Analysis of Stenotrophomonas acidaminiphila Reveal Evolutionary Insights Into Sulfamethoxazole Resistance.

PubMed

Huang, Yao-Ting; Chen, Jia-Min; Ho, Bing-Ching; Wu, Zong-Yen; Kuo, Rita C; Liu, Po-Yu

2018-01-01

Stenotrophomonas acidaminiphila is an aerobic, glucose non-fermentative, Gram-negative bacterium that been isolated from various environmental sources, particularly aquatic ecosystems. Although resistance to multiple antimicrobial agents has been reported in S. acidaminiphila , the mechanisms are largely unknown. Here, for the first time, we report the complete genome and antimicrobial resistome analysis of a clinical isolate S. acidaminiphila SUNEO which is resistant to sulfamethoxazole. Comparative analysis among closely related strains identified common and strain-specific genes. In particular, comparison with a sulfamethoxazole-sensitive strain identified a mutation within the sulfonamide-binding site of folP in SUNEO, which may reduce the binding affinity of sulfamethoxazole. Selection pressure analysis indicated folP in SUNEO is under purifying selection, which may be owing to long-term administration of sulfonamide against Stenotrophomonas .

OrthoMCL: Identification of Ortholog Groups for Eukaryotic Genomes

PubMed Central

Li, Li; Stoeckert, Christian J.; Roos, David S.

2003-01-01

The identification of orthologous groups is useful for genome annotation, studies on gene/protein evolution, comparative genomics, and the identification of taxonomically restricted sequences. Methods successfully exploited for prokaryotic genome analysis have proved difficult to apply to eukaryotes, however, as larger genomes may contain multiple paralogous genes, and sequence information is often incomplete. OrthoMCL provides a scalable method for constructing orthologous groups across multiple eukaryotic taxa, using a Markov Cluster algorithm to group (putative) orthologs and paralogs. This method performs similarly to the INPARANOID algorithm when applied to two genomes, but can be extended to cluster orthologs from multiple species. OrthoMCL clusters are coherent with groups identified by EGO, but improved recognition of “recent” paralogs permits overlapping EGO groups representing the same gene to be merged. Comparison with previously assigned EC annotations suggests a high degree of reliability, implying utility for automated eukaryotic genome annotation. OrthoMCL has been applied to the proteome data set from seven publicly available genomes (human, fly, worm, yeast, Arabidopsis, the malaria parasite Plasmodium falciparum, and Escherichia coli). A Web interface allows queries based on individual genes or user-defined phylogenetic patterns (http://www.cbil.upenn.edu/gene-family). Analysis of clusters incorporating P. falciparum genes identifies numerous enzymes that were incompletely annotated in first-pass annotation of the parasite genome. PMID:12952885

Patient experience in the emergency department: inconsistencies in the ethic and duty of care.

PubMed

Moss, Cheryle; Nelson, Katherine; Connor, Margaret; Wensley, Cynthia; McKinlay, Eileen; Boulton, Amohia

2015-01-01

To understand how people who present on multiple occasions to the emergency department experience their health professionals' moral comportment (ethic of care and duty of care); and to understand the consequences of this for 'people who present on multiple occasions' ongoing choices in care. People (n = 34) with chronic illness who had multiple presentations were interviewed about the role that emergency departments played within their lives and health-illness journey. Unprompted, all participants shared views about the appropriateness or inappropriateness of the care they received from the health professionals in the emergency departments they had attended. These responses raised the imperative for specific analysis of the data regarding the need for and experience of an ethic of care. Qualitative description of interview data (stage 3 of a multimethod study). The methods included further analysis of existing interviews, exploration of relevant literature, use of Tronto's ethic of care as a theoretical framework for analysis, thematic analysis of people who present on multiple occasions' texts and explication of health professionals' moral positions in relation to present on multiple occasions' experiences. Four moral comportment positions attributed by the people who present on multiple occasions to the health professionals in emergency department were identified: 'sustained and enmeshed ethic and duty of care', 'consistent duty of care', 'interrupted or mixed duty and ethic of care', and 'care in breach of both the ethic and duty of care'. People who present on multiple occasions are an important group of consumers who attend the emergency department. Tronto's phases/moral elements in an ethic of care are useful as a framework for coding qualitative texts. Investigation into the bases, outcomes and contextual circumstances that stimulate the different modes of moral comportment is needed. Findings carry implications for emergency department care of people who present on multiple occasions and for emergency department health professionals to increase awareness of their moral comportment in care. © 2014 John Wiley & Sons Ltd.

Analysis of the SOS response of Vibrio and other bacteria with multiple chromosomes.

PubMed

Sanchez-Alberola, Neus; Campoy, Susana; Barbé, Jordi; Erill, Ivan

2012-02-03

The SOS response is a well-known regulatory network present in most bacteria and aimed at addressing DNA damage. It has also been linked extensively to stress-induced mutagenesis, virulence and the emergence and dissemination of antibiotic resistance determinants. Recently, the SOS response has been shown to regulate the activity of integrases in the chromosomal superintegrons of the Vibrionaceae, which encompasses a wide range of pathogenic species harboring multiple chromosomes. Here we combine in silico and in vitro techniques to perform a comparative genomics analysis of the SOS regulon in the Vibrionaceae, and we extend the methodology to map this transcriptional network in other bacterial species harboring multiple chromosomes. Our analysis provides the first comprehensive description of the SOS response in a family (Vibrionaceae) that includes major human pathogens. It also identifies several previously unreported members of the SOS transcriptional network, including two proteins of unknown function. The analysis of the SOS response in other bacterial species with multiple chromosomes uncovers additional regulon members and reveals that there is a conserved core of SOS genes, and that specialized additions to this basic network take place in different phylogenetic groups. Our results also indicate that across all groups the main elements of the SOS response are always found in the large chromosome, whereas specialized additions are found in the smaller chromosomes and plasmids. Our findings confirm that the SOS response of the Vibrionaceae is strongly linked with pathogenicity and dissemination of antibiotic resistance, and suggest that the characterization of the newly identified members of this regulon could provide key insights into the pathogenesis of Vibrio. The persistent location of key SOS genes in the large chromosome across several bacterial groups confirms that the SOS response plays an essential role in these organisms and sheds light into the mechanisms of evolution of global transcriptional networks involved in adaptability and rapid response to environmental changes, suggesting that small chromosomes may act as evolutionary test beds for the rewiring of transcriptional networks.

Identification of aberrant gene expression associated with aberrant promoter methylation in primordial germ cells between E13 and E16 rat F3 generation vinclozolin lineage.

PubMed

Taguchi, Y-h

2015-01-01

Transgenerational epigenetics (TGE) are currently considered important in disease, but the mechanisms involved are not yet fully understood. TGE abnormalities expected to cause disease are likely to be initiated during development and to be mediated by aberrant gene expression associated with aberrant promoter methylation that is heritable between generations. However, because methylation is removed and then re-established during development, it is not easy to identify promoter methylation abnormalities by comparing normal lineages with those expected to exhibit TGE abnormalities. This study applied the recently proposed principal component analysis (PCA)-based unsupervised feature extraction to previously reported and publically available gene expression/promoter methylation profiles of rat primordial germ cells, between E13 and E16 of the F3 generation vinclozolin lineage that are expected to exhibit TGE abnormalities, to identify multiple genes that exhibited aberrant gene expression/promoter methylation during development. The biological feasibility of the identified genes were tested via enrichment analyses of various biological concepts including pathway analysis, gene ontology terms and protein-protein interactions. All validations suggested superiority of the proposed method over three conventional and popular supervised methods that employed t test, limma and significance analysis of microarrays, respectively. The identified genes were globally related to tumors, the prostate, kidney, testis and the immune system and were previously reported to be related to various diseases caused by TGE. Among the genes reported by PCA-based unsupervised feature extraction, we propose that chemokine signaling pathways and leucine rich repeat proteins are key factors that initiate transgenerational epigenetic-mediated diseases, because multiple genes included in these two categories were identified in this study.

Identification of aberrant gene expression associated with aberrant promoter methylation in primordial germ cells between E13 and E16 rat F3 generation vinclozolin lineage

PubMed Central

2015-01-01

Background Transgenerational epigenetics (TGE) are currently considered important in disease, but the mechanisms involved are not yet fully understood. TGE abnormalities expected to cause disease are likely to be initiated during development and to be mediated by aberrant gene expression associated with aberrant promoter methylation that is heritable between generations. However, because methylation is removed and then re-established during development, it is not easy to identify promoter methylation abnormalities by comparing normal lineages with those expected to exhibit TGE abnormalities. Methods This study applied the recently proposed principal component analysis (PCA)-based unsupervised feature extraction to previously reported and publically available gene expression/promoter methylation profiles of rat primordial germ cells, between E13 and E16 of the F3 generation vinclozolin lineage that are expected to exhibit TGE abnormalities, to identify multiple genes that exhibited aberrant gene expression/promoter methylation during development. Results The biological feasibility of the identified genes were tested via enrichment analyses of various biological concepts including pathway analysis, gene ontology terms and protein-protein interactions. All validations suggested superiority of the proposed method over three conventional and popular supervised methods that employed t test, limma and significance analysis of microarrays, respectively. The identified genes were globally related to tumors, the prostate, kidney, testis and the immune system and were previously reported to be related to various diseases caused by TGE. Conclusions Among the genes reported by PCA-based unsupervised feature extraction, we propose that chemokine signaling pathways and leucine rich repeat proteins are key factors that initiate transgenerational epigenetic-mediated diseases, because multiple genes included in these two categories were identified in this study. PMID:26677731

Multiple Phenotype Association Tests Using Summary Statistics in Genome-Wide Association Studies

PubMed Central

Liu, Zhonghua; Lin, Xihong

2017-01-01

Summary We study in this paper jointly testing the associations of a genetic variant with correlated multiple phenotypes using the summary statistics of individual phenotype analysis from Genome-Wide Association Studies (GWASs). We estimated the between-phenotype correlation matrix using the summary statistics of individual phenotype GWAS analyses, and developed genetic association tests for multiple phenotypes by accounting for between-phenotype correlation without the need to access individual-level data. Since genetic variants often affect multiple phenotypes differently across the genome and the between-phenotype correlation can be arbitrary, we proposed robust and powerful multiple phenotype testing procedures by jointly testing a common mean and a variance component in linear mixed models for summary statistics. We computed the p-values of the proposed tests analytically. This computational advantage makes our methods practically appealing in large-scale GWASs. We performed simulation studies to show that the proposed tests maintained correct type I error rates, and to compare their powers in various settings with the existing methods. We applied the proposed tests to a GWAS Global Lipids Genetics Consortium summary statistics data set and identified additional genetic variants that were missed by the original single-trait analysis. PMID:28653391

Multiple phenotype association tests using summary statistics in genome-wide association studies.

PubMed

Liu, Zhonghua; Lin, Xihong

2018-03-01

We study in this article jointly testing the associations of a genetic variant with correlated multiple phenotypes using the summary statistics of individual phenotype analysis from Genome-Wide Association Studies (GWASs). We estimated the between-phenotype correlation matrix using the summary statistics of individual phenotype GWAS analyses, and developed genetic association tests for multiple phenotypes by accounting for between-phenotype correlation without the need to access individual-level data. Since genetic variants often affect multiple phenotypes differently across the genome and the between-phenotype correlation can be arbitrary, we proposed robust and powerful multiple phenotype testing procedures by jointly testing a common mean and a variance component in linear mixed models for summary statistics. We computed the p-values of the proposed tests analytically. This computational advantage makes our methods practically appealing in large-scale GWASs. We performed simulation studies to show that the proposed tests maintained correct type I error rates, and to compare their powers in various settings with the existing methods. We applied the proposed tests to a GWAS Global Lipids Genetics Consortium summary statistics data set and identified additional genetic variants that were missed by the original single-trait analysis. © 2017, The International Biometric Society.

A longitudinal examination of the interrelationship of multiple health behaviors.

PubMed

deRuiter, Wayne K; Cairney, John; Leatherdale, Scott T; Faulkner, Guy E J

2014-09-01

Evaluating the interrelationship of health behaviors could assist in the development of effective public health interventions. Furthermore, the ability to identify cognitive mediators that may influence multiple behavioral changes requires evaluation. To evaluate covariation among health behaviors, specifically alcohol consumption, leisure-time physical activity, and smoking, and examine whether mastery acts as a mediating social-cognitive mechanism that facilitates multiple health behavior change in a longitudinal analysis. In 2010, secondary data analysis was conducted on the first seven cycles of the Canadian National Population Health Survey. Data collection began in 1994-1995 and has continued biennially. At the time of this analysis, only seven cycles of data (2006-2007) were available. Parallel process growth curve models were used to analyze covariation between health behaviors and the potential mediating effects of perceived mastery. Increases in leisure-time physical activity were associated with reductions in tobacco use, whereas declines in alcohol consumption were associated with decreases in tobacco use. Covariation between alcohol consumption and leisure-time physical activity did not reach statistical significance. For the most part, mastery was unsuccessful in mediating the interrelationship of multiple behavioral changes. Health behaviors are not independent but rather interrelated. In order to optimize limited prevention resources, these results suggest that population-level intervention efforts targeting multiple modifiable behavioral risk factors may not need to occur simultaneously. Crown Copyright © 2014. Published by Elsevier Inc. All rights reserved.

Multiple pregnancies achieved with IVF/ICSI and risk of specific congenital malformations: a meta-analysis of cohort studies.

PubMed

Zheng, Zan; Chen, Letao; Yang, Tubao; Yu, Hong; Wang, Hua; Qin, Jiabi

2018-04-01

Studies comparing risk of specific congenital malformations (CM) between multiple pregnancies resulting from IVF/intracytoplasmic sperm injection (ICSI) and those conceived naturally report conflicting results; furthermore, there is a lack of a complete overview. This meta-analysis aimed to address which types of CM are increased in IVF/ICSI multiple pregnancies compared with those conceived naturally. All studies testing the association between IVF/ICSI multiple pregnancies and specific CM identified in various databases were considered. The literature search yielded 856 records, of which 21 cohort studies were included for analysis. Overall, multiple pregnancies achieved with IVF/ICSI experienced a significantly higher risk of chromosomal defects (relative risk [RR] = 1.36; 95% confidence interval [CI]: 1.04-1.77), urogenital (RR = 1.18; 95% CI: 1.03-1.36) and circulatory (RR = 1.22; 95% CI: 1.01-1.47) system malformations. However, the remaining specific CM, such as cleft lip and/or palate, eye, ear, face and neck, respiratory, musculoskeletal, nervous and digestive system malformations, were similar in the two groups. No substantial heterogeneity was observed for most outcomes except for digestive (P = 0.094; I 2 = 38.3%) and circulatory (P = 0.070; I 2 = 35.2%) system malformations. These findings provide additional information on risks of IVF/ICSI for use when counselling patients. Copyright © 2018 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

Statistical testing and power analysis for brain-wide association study.

PubMed

Gong, Weikang; Wan, Lin; Lu, Wenlian; Ma, Liang; Cheng, Fan; Cheng, Wei; Grünewald, Stefan; Feng, Jianfeng

2018-04-05

The identification of connexel-wise associations, which involves examining functional connectivities between pairwise voxels across the whole brain, is both statistically and computationally challenging. Although such a connexel-wise methodology has recently been adopted by brain-wide association studies (BWAS) to identify connectivity changes in several mental disorders, such as schizophrenia, autism and depression, the multiple correction and power analysis methods designed specifically for connexel-wise analysis are still lacking. Therefore, we herein report the development of a rigorous statistical framework for connexel-wise significance testing based on the Gaussian random field theory. It includes controlling the family-wise error rate (FWER) of multiple hypothesis testings using topological inference methods, and calculating power and sample size for a connexel-wise study. Our theoretical framework can control the false-positive rate accurately, as validated empirically using two resting-state fMRI datasets. Compared with Bonferroni correction and false discovery rate (FDR), it can reduce false-positive rate and increase statistical power by appropriately utilizing the spatial information of fMRI data. Importantly, our method bypasses the need of non-parametric permutation to correct for multiple comparison, thus, it can efficiently tackle large datasets with high resolution fMRI images. The utility of our method is shown in a case-control study. Our approach can identify altered functional connectivities in a major depression disorder dataset, whereas existing methods fail. A software package is available at https://github.com/weikanggong/BWAS. Copyright © 2018 Elsevier B.V. All rights reserved.

Optimization of selective breeding through analysis of morphological traits in Chinese sea bass (Lateolabrax maculatus).

PubMed

Wang, W; Ma, C Y; Chen, W; Ma, H Y; Zhang, H; Meng, Y Y; Ni, Y; Ma, L B

2016-08-19

Determining correlations between certain traits of economic importance constitutes an essential component of selective activities. In this study, our aim was to provide effective indicators for breeding programs of Lateolabrax maculatus, an important aquaculture species in China. We analyzed correlations between 20 morphometric traits and body weight, using correlation and path analyses. The results indicated that the correlations among all 21 traits were highly significant, with the highest correlation coefficient identified between total length and body weight. The path analysis indicated that total length (X 1 ), body width (X 5 ), distance from first dorsal fin origin to anal fin origin (X 10 ), snout length (X 16 ), eye diameter (X 17 ), eye cross (X 18 ), and slanting distance from snout tip to first dorsal fin origin (X 19 ) significantly affected body weight (Y) directly. The following multiple-regression equation was obtained using stepwise multiple-regression analysis: Y = -472.108 + 1.065X 1 + 7.728X 5 + 1.973X 10 - 7.024X 16 - 4.400X 17 - 3.338X 18 + 2.138X 19 , with an adjusted multiple-correlation coefficient of 0.947. Body width had the largest determinant coefficient, as well as the highest positive direct correlation with body weight. At the same time, high indirect effects with six other morphometric traits on L. maculatus body weight, through body width, were identified. Hence, body width could be a key factor that efficiently indicates significant effects on body weight in L. maculatus.

Metric Selection for Evaluation of Human Supervisory Control Systems

DTIC Science & Technology

2009-12-01

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

MIT/Draper Technology Development Partnership Project: Systems Analysis and On-Station Propulsion Subsystem Design.

DTIC Science & Technology

1998-08-04

manufacturing Military and commercial applications Large market developing for multiple- satellite constellations Will have a high demand if...identified, and market assessments for five different possible projects are discussed. Lessons learned during the first semester of project work are...24 1.2.6 Market Assessments of Five Concepts 26 1.2.7 Project Selection 28 Chapter 2 Requirements Analysis and Top-Level System Architecture 30

Interaction of Hb Grey Lynn (Vientiane) [α91(FG3)Leu>Phe (α1)] with Hb E [β26(B8) Glu>Lys] and α(+)-thalassemia: Molecular and Hematological Analysis.

PubMed

Singha, Kritsada; Fucharoen, Goonnapa; Fucharoen, Supan

2015-01-01

Hemoglobin (Hb) Grey Lynn is a Hb variant caused by a mutation at codon 91 of α1-globin gene whereas Hb E is a common β-globin chain variant among Southeast Asian population. We report two hitherto undescribed conditions of Hb Grey Lynn found in Thai individuals. The study was done on two unrelated Thai subjects. Hematological parameters were recorded and Hb analysis was carried out using automated Hb analyzers. Mutations were identified by DNA analysis. Hematological features of the patients were compared with those of various forms of Hb Grey Lynn documented previously. Hb and DNA analyses identified a heterozygous Hb Grey Lynn in one patient and a double heterozygous Hb Grey Lynn and Hb E with α(+)-thalassemia in another. Interaction of α(Grey Lynn) with β(E) chains leads to the formation of a new Hb variant, namely the Hb Grey Lynn E (α(GL)2β(E)2), detectable by liquid chromatography (10.3%) but masked by Hb E on capillary electrophoresis. Interaction of these multiple globin gene defects could lead to complex hemoglobinopathies requiring combined analysis with multiple Hb analyzers followed by DNA testing to provide accurate diagnosis of the cases.

Multiple receptor conformation docking, dock pose clustering and 3D QSAR studies on human poly(ADP-ribose) polymerase-1 (PARP-1) inhibitors.

PubMed

Fatima, Sabiha; Jatavath, Mohan Babu; Bathini, Raju; Sivan, Sree Kanth; Manga, Vijjulatha

2014-10-01

Poly(ADP-ribose) polymerase-1 (PARP-1) functions as a DNA damage sensor and signaling molecule. It plays a vital role in the repair of DNA strand breaks induced by radiation and chemotherapeutic drugs; inhibitors of this enzyme have the potential to improve cancer chemotherapy or radiotherapy. Three-dimensional quantitative structure activity relationship (3D QSAR) models were developed using comparative molecular field analysis, comparative molecular similarity indices analysis and docking studies. A set of 88 molecules were docked into the active site of six X-ray crystal structures of poly(ADP-ribose)polymerase-1 (PARP-1), by a procedure called multiple receptor conformation docking (MRCD), in order to improve the 3D QSAR models through the analysis of binding conformations. The docked poses were clustered to obtain the best receptor binding conformation. These dock poses from clustering were used for 3D QSAR analysis. Based on MRCD and QSAR information, some key features have been identified that explain the observed variance in the activity. Two receptor-based QSAR models were generated; these models showed good internal and external statistical reliability that is evident from the [Formula: see text], [Formula: see text] and [Formula: see text]. The identified key features enabled us to design new PARP-1 inhibitors.

Ants regulate colony spatial organization using multiple chemical road-signs

PubMed Central

Heyman, Yael; Shental, Noam; Brandis, Alexander; Hefetz, Abraham; Feinerman, Ofer

2017-01-01

Communication provides the basis for social life. In ant colonies, the prevalence of local, often chemically mediated, interactions introduces strong links between communication networks and the spatial distribution of ants. It is, however, unknown how ants identify and maintain nest chambers with distinct functions. Here, we combine individual tracking, chemical analysis and machine learning to decipher the chemical signatures present on multiple nest surfaces. We present evidence for several distinct chemical ‘road-signs' that guide the ants' movements within the dark nest. These chemical signatures can be used to classify nest chambers with different functional roles. Using behavioural manipulations, we demonstrate that at least three of these chemical signatures are functionally meaningful and allow ants from different task groups to identify their specific nest destinations, thus facilitating colony coordination and stabilization. The use of multiple chemicals that assist spatiotemporal guidance, segregation and pattern formation is abundant in multi-cellular organisms. Here, we provide a rare example for the use of these principles in the ant colony. PMID:28569746

Ants regulate colony spatial organization using multiple chemical road-signs.

PubMed

Heyman, Yael; Shental, Noam; Brandis, Alexander; Hefetz, Abraham; Feinerman, Ofer

2017-06-01

Communication provides the basis for social life. In ant colonies, the prevalence of local, often chemically mediated, interactions introduces strong links between communication networks and the spatial distribution of ants. It is, however, unknown how ants identify and maintain nest chambers with distinct functions. Here, we combine individual tracking, chemical analysis and machine learning to decipher the chemical signatures present on multiple nest surfaces. We present evidence for several distinct chemical 'road-signs' that guide the ants' movements within the dark nest. These chemical signatures can be used to classify nest chambers with different functional roles. Using behavioural manipulations, we demonstrate that at least three of these chemical signatures are functionally meaningful and allow ants from different task groups to identify their specific nest destinations, thus facilitating colony coordination and stabilization. The use of multiple chemicals that assist spatiotemporal guidance, segregation and pattern formation is abundant in multi-cellular organisms. Here, we provide a rare example for the use of these principles in the ant colony.

The causes of hypopituitarism in the absence of abnormal pituitary imaging.

PubMed

Wilson, V; Mallipedhi, A; Stephens, J W; Redfern, R M; Price, D E

2014-01-01

Hypopituitarism in the absence of a history of pituitary pathology or abnormal pituitary imaging is rare. To identify the cause of hypopituitarism in individuals in whom pituitary imaging was normal. Retrospective analysis of electronic patient record. A review of the pituitary function in the 506 patients on the Morriston Hospital pituitary database revealed 230 had some degree of hypopituitarism and of these, 21 (9%) had normal pituitary imaging. Of this group, six patients had a past medical history of subarachnoid haemorrhage, head injury or meningitis, and mainly suffered from a deficiency of antidiuretic hormone. One patient had a stroke resulting in multiple anterior hormone deficiencies and six individuals had idiopathic cranial diabetes insipidus (DI). Subsequent investigations of the remaining eight patients with normal pituitary imaging revealed that two had neurosarcoidosis both of whom had panhypopituitarism. Four patients had haemochromatosis which resulted in gonadotropin deficiency in two, DI in one and panhypopituitarism in the other. There were two individuals with confirmed hypopituitarism and multiple hormone deficiencies in which no cause could be identified. These results show that hypopituitarism in the absence of pituitary pathology or an identifiable cause is rare. In patients with multiple anterior pituitary hormone deficiencies haemochromatosis and sarcoidosis should be considered.

Identifying potential conflict associated with oil and gas exploration in Texas state coastal waters: A multicriteria spatial analysis.

PubMed

Brody, Samuel D; Grover, Himanshu; Bernhardt, Sarah; Tang, Zhenghong; Whitaker, Bianca; Spence, Colin

2006-10-01

Recent interest in expanding offshore oil production within waters of the United States has been met with opposition by groups concerned with recreational, environmental, and aesthetic values associated with the coastal zone. Although the proposition of new oil platforms off the coast has generated conflict over how coastal resources should be utilized, little research has been conducted on where these user conflicts might be most intense and which sites might be most suitable for locating oil production facilities in light of the multiple, and often times, competing interests. In this article, we develop a multiple-criteria spatial decision support tool that identifies the potential degree of conflict associated with oil and gas production activities for existing lease tracts in the coastal margin of Texas. We use geographic information systems to measure and map a range of potentially competing representative values impacted by establishing energy extraction infrastructure and then spatially identify which leased tracts are the least contentious sites for oil and gas production in Texas state waters. Visual and statistical results indicate that oil and gas lease blocks within the study area vary in their potential to generate conflict among multiple stakeholders.

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.

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.

Dynamic regulation of genetic pathways and targets during aging in Caenorhabditis elegans.

PubMed

He, Kan; Zhou, Tao; Shao, Jiaofang; Ren, Xiaoliang; Zhao, Zhongying; Liu, Dahai

2014-03-01

Numerous genetic targets and some individual pathways associated with aging have been identified using the worm model. However, less is known about the genetic mechanisms of aging in genome wide, particularly at the level of multiple pathways as well as the regulatory networks during aging. Here, we employed the gene expression datasets of three time points during aging in Caenorhabditis elegans (C. elegans) and performed the approach of gene set enrichment analysis (GSEA) on each dataset between adjacent stages. As a result, multiple genetic pathways and targets were identified as significantly down- or up-regulated. Among them, 5 truly aging-dependent signaling pathways including MAPK signaling pathway, mTOR signaling pathway, Wnt signaling pathway, TGF-beta signaling pathway and ErbB signaling pathway as well as 12 significantly associated genes were identified with dynamic expression pattern during aging. On the other hand, the continued declines in the regulation of several metabolic pathways have been demonstrated to display age-related changes. Furthermore, the reconstructed regulatory networks based on three of aging related Chromatin immunoprecipitation experiments followed by sequencing (ChIP-seq) datasets and the expression matrices of 154 involved genes in above signaling pathways provide new insights into aging at the multiple pathways level. The combination of multiple genetic pathways and targets needs to be taken into consideration in future studies of aging, in which the dynamic regulation would be uncovered.

From Molecules to Cells to Organisms: Understanding Health and Disease with Multidimensional Single-Cell Methods

NASA Astrophysics Data System (ADS)

Candia, Julián

2013-03-01

The multidimensional nature of many single-cell measurements (e.g. multiple markers measured simultaneously using Fluorescence-Activated Cell Sorting (FACS) technologies) offers unprecedented opportunities to unravel emergent phenomena that are governed by the cooperative action of multiple elements across different scales, from molecules and proteins to cells and organisms. We will discuss an integrated analysis framework to investigate multicolor FACS data from different perspectives: Singular Value Decomposition to achieve an effective dimensional reduction in the data representation, machine learning techniques to separate different patient classes and improve diagnosis, as well as a novel cell-similarity network analysis method to identify cell subpopulations in an unbiased manner. Besides FACS data, this framework is versatile: in this vein, we will demonstrate an application to the multidimensional single-cell shape analysis of healthy and prematurely aged cells.

Conceptual Design and Performance Analysis for a Large Civil Compound Helicopter

NASA Technical Reports Server (NTRS)

Russell, Carl; Johnson, Wayne

2012-01-01

A conceptual design study of a large civil compound helicopter is presented. The objective is to determine how a compound helicopter performs when compared to both a conventional helicopter and a tiltrotor using a design mission that is shorter than optimal for a tiltrotor and longer than optimal for a helicopter. The designs are generated and analyzed using conceptual design software and are further evaluated with a comprehensive rotorcraft analysis code. Multiple metrics are used to determine the suitability of each design for the given mission. Plots of various trade studies and parameter sweeps as well as comprehensive analysis results are presented. The results suggest that the compound helicopter examined for this study would not be competitive with a tiltrotor or conventional helicopter, but multiple possibilities are identified for improving the performance of the compound helicopter in future research.

Estimating differential expression from multiple indicators

PubMed Central

Ilmjärv, Sten; Hundahl, Christian Ansgar; Reimets, Riin; Niitsoo, Margus; Kolde, Raivo; Vilo, Jaak; Vasar, Eero; Luuk, Hendrik

2014-01-01

Regardless of the advent of high-throughput sequencing, microarrays remain central in current biomedical research. Conventional microarray analysis pipelines apply data reduction before the estimation of differential expression, which is likely to render the estimates susceptible to noise from signal summarization and reduce statistical power. We present a probe-level framework, which capitalizes on the high number of concurrent measurements to provide more robust differential expression estimates. The framework naturally extends to various experimental designs and target categories (e.g. transcripts, genes, genomic regions) as well as small sample sizes. Benchmarking in relation to popular microarray and RNA-sequencing data-analysis pipelines indicated high and stable performance on the Microarray Quality Control dataset and in a cell-culture model of hypoxia. Experimental-data-exhibiting long-range epigenetic silencing of gene expression was used to demonstrate the efficacy of detecting differential expression of genomic regions, a level of analysis not embraced by conventional workflows. Finally, we designed and conducted an experiment to identify hypothermia-responsive genes in terms of monotonic time-response. As a novel insight, hypothermia-dependent up-regulation of multiple genes of two major antioxidant pathways was identified and verified by quantitative real-time PCR. PMID:24586062

Selection of multiple umbrella species for functional and taxonomic diversity to represent urban biodiversity.

PubMed

Sattler, T; Pezzatti, G B; Nobis, M P; Obrist, M K; Roth, T; Moretti, M

2014-04-01

Surrogates, such as umbrella species, are commonly used to reduce the complexity of quantifying biodiversity for conservation purposes. The presence of umbrella species is often indicative of high taxonomic diversity; however, functional diversity is now recognized as an important metric for biodiversity and thus should be considered when choosing umbrella species. We identified umbrella species associated with high taxonomic and functional biodiversity in urban areas in Switzerland. We analyzed 39,752 individuals of 574 animal species from 96 study plots and 1397 presences of 262 plant species from 58 plots. Thirty-one biodiversity measures of 7 taxonomic groups (plants, spiders, bees, ground beetles, lady bugs, weevils and birds) were included in within- and across-taxa analyses. Sixteen measures were taxonomical (species richness and species diversity), whereas 15 were functional (species traits including mobility, resource use, and reproduction). We used indicator value analysis to identify umbrella species associated with single or multiple biodiversity measures. Many umbrella species were indicators of high biodiversity within their own taxonomic group (from 33.3% in weevils to 93.8% in birds), to a lesser extent they were indicators across taxa. Principal component analysis revealed that umbrella species for multiple measures of biodiversity represented different aspects of biodiversity, especially with respect to measures of taxonomic and functional diversity. Thus, even umbrella species for multiple measures of biodiversity were complementary in the biodiversity aspects they represented. Thus, the choice of umbrella species based solely on taxonomic diversity is questionable and may not represent biodiversity comprehensively. Our results suggest that, depending on conservation priorities, managers should choose multiple and complementary umbrella species to assess the state of biodiversity. © 2013 Society for Conservation Biology.

Health care administrators' perspectives on the role of absorptive capacity for strategic change initiatives: a qualitative study.

PubMed

Kash, Bita A; Spaulding, Aaron; Gamm, Larry; Johnson, Christopher E

2013-01-01

The dimensions of absorptive capacity (ACAP) are defined, and the importance of ACAP is established in the management literature, but the concept has not been applied to health care organizations attempting to implement multiple strategic initiatives. The aim of this study was to test the utility of ACAP by analyzing health care administrators' experiences with multiple strategic initiatives within two health systems. Results are drawn from administrators' assessments of multiple initiatives within two health systems using in-depth personal interviews with a total of 61 health care administrators. Data analysis was performed following deductive qualitative analysis guidelines. Interview transcripts were coded based on the four dimensions of ACAP: acquiring, assimilating, internalizing/transforming, and exploiting knowledge. Furthermore, we link results related to utilization of management resources, including number of key personnel involved and time consumption, to dimensions of ACAP. Participants' description of multiple strategic change initiatives confirmed the importance of the four ACAP dimensions. ACAP can be a useful framework to assess organizational capacity with respect to the organization's ability to concurrently implement multiple strategic initiatives. This capacity specifically revolves around human capital requirements from upper management based on the initiatives' location or stage within the ACAP framework. Strategic change initiatives in health care can be usefully viewed from an ACAP perspective. There is a tendency for those strategic initiatives ranking higher in priority and time consumption to reflect more advanced dimensions of ACAP (assimilate and transform), whereas few initiatives were identified in the ACAP "exploit" dimension. This may suggest that health care leaders tend to no longer identify as strategic initiatives those innovations that have moved to the exploitation stage or that less attention is given to the exploitation elements of a strategic initiative than to the earlier stages.

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

A SIMPLE POLYMERASE CHAIN REACTION-SEQUENCING ANALYSIS CAPABLE OF IDENTIFYING MULTIPLE MEDICALLY RELEVANT FILAMENTOUS FUNGAL SPECIES

EPA Science Inventory

Due to the accumulating evidence that suggests that numerous unhealthy conditions in the indoor environment are the result of abnormal growth of the filamentous fungi (mold) in and on building surfaces, it is necessary to accurately determine the organisms responsible for these m...

Illusory Intelligences?

ERIC Educational Resources Information Center

White, John

2008-01-01

Howard Gardner's theory of Multiple Intelligences has had a huge influence on school education. But its credentials lack justification, as the first section of this paper shows via a detailed philosophical analysis of how the intelligences are identified. If we want to make sense of the theory, we need to turn from a philosophical to a historical…

FAD: Filtering, Analyzing, and Diagnosing Reading Difficulties

ERIC Educational Resources Information Center

Mokhtari, Kouider; Niederhauser, Dale S.; Beschorner, Elizabeth A.; Edwards, Patricia A.

2011-01-01

In this article, the authors introduce a data analysis procedure, abbreviated as FAD, to help literacy professionals who work with children in clinical or classroom settings identify and interpret patterns of assessment data with the goal of determining children's literacy strengths and needs. The procedure uses data from multiple literacy…

Insights into Students' Conceptual Understanding Using Textual Analysis: A Case Study in Signal Processing

ERIC Educational Resources Information Center

Goncher, Andrea M.; Jayalath, Dhammika; Boles, Wageeh

2016-01-01

Concept inventory tests are one method to evaluate conceptual understanding and identify possible misconceptions. The multiple-choice question format, offering a choice between a correct selection and common misconceptions, can provide an assessment of students' conceptual understanding in various dimensions. Misconceptions of some engineering…

Rural Economic Development: What Makes Rural Communities Grow?

ERIC Educational Resources Information Center

Aldrich, Lorna; Kusmin, Lorin

This report identifies local factors that foster rural economic growth. A review of the literature revealed potential indicators of county economic growth, and those indicators were then tested against data for nonmetro counties during the 1980s using multiple regression analysis. The principal variables examined included demographic and labor…

Identifying the Factors That Influence Change in SEBD Using Logistic Regression Analysis

ERIC Educational Resources Information Center

Camilleri, Liberato; Cefai, Carmel

2013-01-01

Multiple linear regression and ANOVA models are widely used in applications since they provide effective statistical tools for assessing the relationship between a continuous dependent variable and several predictors. However these models rely heavily on linearity and normality assumptions and they do not accommodate categorical dependent…

Factors Influencing New York Doctoral Graduate Student Satisfaction: A Quantitative Multiple Regression Analysis

ERIC Educational Resources Information Center

Nwenyi, Sabina E.

2013-01-01

Higher education administrators face challenges in providing a welcoming environment for doctoral students in higher education institutions. Administrators need to identify factors influencing satisfaction of this group of students to provide a supportive environment, reduce attrition rates, and promote persistence. The purpose of this…

A Social-Ecological Analysis of the Self-Determination Literature

ERIC Educational Resources Information Center

Shogren, Karrie A.

2013-01-01

This paper uses a social-ecological lens to examine self-determination research, attempting to organize what is known (and unknown) about contextual factors that have the potential to impact the development and expression of self-determined behavior in people with disabilities across multiple ecological systems. Identifying and categorizing the…

Identification of Nonadaptive MBA Writers through the Use of Linguistic Analysis

ERIC Educational Resources Information Center

Divoky, James J.; Rothermel, Mary Anne

2009-01-01

Samples of formal business reports and business memos were obtained from MBA students in multiple disciplines. The samples were analyzed in terms of their relative cohesion, concreteness of wording, causal relationships, intentional referencing, and readability. A classification function based on these measures was then used to identify entering…

Draft genome sequence analysis of multidrug-resistant Escherichia coli strains isolated in 2013 from humans and chickens in Nigeria

USDA-ARS?s Scientific Manuscript database

Here, we present the draft genome sequences of nine multidrug-resistant Escherichia coli isolated from humans (n=6) and chicken carcass (n=3) from Lagos, Nigeria in 2013. Multiple extended-spectrum beta-lactamase (ESBL) genes were identified in these isolates. ...

Probabilistic characterization of sleep architecture: home based study on healthy volunteers.

PubMed

Garcia-Molina, Gary; Vissapragada, Sreeram; Mahadevan, Anandi; Goodpaster, Robert; Riedner, Brady; Bellesi, Michele; Tononi, Giulio

2016-08-01

The quantification of sleep architecture has high clinical value for diagnostic purposes. While the clinical standard to assess sleep architecture is in-lab based polysomnography, higher ecological validity can be obtained with multiple sleep recordings at home. In this paper, we use a dataset composed of fifty sleep EEG recordings at home (10 per study participant for five participants) to analyze the sleep stage transition dynamics using Markov chain based modeling. The statistical analysis of the duration of continuous sleep stage bouts is also analyzed to identify the speed of transition between sleep stages. This analysis identified two types of NREM states characterized by fast and slow exit rates which from the EEG analysis appear to correspond to shallow and deep sleep respectively.

Evaluation of 19,460 Wheat Accessions Conserved in the Indian National Genebank to Identify New Sources of Resistance to Rust and Spot Blotch Diseases.

PubMed

Kumar, Sundeep; Archak, Sunil; Tyagi, R K; Kumar, Jagdish; Vk, Vikas; Jacob, Sherry R; Srinivasan, Kalyani; Radhamani, J; Parimalan, R; Sivaswamy, M; Tyagi, Sandhya; Yadav, Mamata; Kumari, Jyotisna; Deepali; Sharma, Sandeep; Bhagat, Indoo; Meeta, Madhu; Bains, N S; Chowdhury, A K; Saha, B C; Bhattacharya, P M; Kumari, Jyoti; Singh, M C; Gangwar, O P; Prasad, P; Bharadwaj, S C; Gogoi, Robin; Sharma, J B; Gm, Sandeep Kumar; Saharan, M S; Bag, Manas; Roy, Anirban; Prasad, T V; Sharma, R K; Dutta, M; Sharma, Indu; Bansal, K C

2016-01-01

A comprehensive germplasm evaluation study of wheat accessions conserved in the Indian National Genebank was conducted to identify sources of rust and spot blotch resistance. Genebank accessions comprising three species of wheat-Triticum aestivum, T. durum and T. dicoccum were screened sequentially at multiple disease hotspots, during the 2011-14 crop seasons, carrying only resistant accessions to the next step of evaluation. Wheat accessions which were found to be resistant in the field were then assayed for seedling resistance and profiled using molecular markers. In the primary evaluation, 19,460 accessions were screened at Wellington (Tamil Nadu), a hotspot for wheat rusts. We identified 4925 accessions to be resistant and these were further evaluated at Gurdaspur (Punjab), a hotspot for stripe rust and at Cooch Behar (West Bengal), a hotspot for spot blotch. The second round evaluation identified 498 accessions potentially resistant to multiple rusts and 868 accessions potentially resistant to spot blotch. Evaluation of rust resistant accessions for seedling resistance against seven virulent pathotypes of three rusts under artificial epiphytotic conditions identified 137 accessions potentially resistant to multiple rusts. Molecular analysis to identify different combinations of genetic loci imparting resistance to leaf rust, stem rust, stripe rust and spot blotch using linked molecular markers, identified 45 wheat accessions containing known resistance genes against all three rusts as well as a QTL for spot blotch resistance. The resistant germplasm accessions, particularly against stripe rust, identified in this study can be excellent potential candidates to be employed for breeding resistance into the background of high yielding wheat cultivars through conventional or molecular breeding approaches, and are expected to contribute toward food security at national and global levels.

Evaluation of 19,460 Wheat Accessions Conserved in the Indian National Genebank to Identify New Sources of Resistance to Rust and Spot Blotch Diseases

PubMed Central

Jacob, Sherry R.; Srinivasan, Kalyani; Radhamani, J.; Parimalan, R.; Sivaswamy, M.; Tyagi, Sandhya; Yadav, Mamata; Kumari, Jyotisna; Deepali; Sharma, Sandeep; Bhagat, Indoo; Meeta, Madhu; Bains, N. S.; Chowdhury, A. K.; Saha, B. C.; Bhattacharya, P. M.; Kumari, Jyoti; Singh, M. C.; Gangwar, O. P.; Prasad, P.; Bharadwaj, S. C.; Gogoi, Robin; Sharma, J. B.; GM, Sandeep Kumar; Saharan, M. S.; Bag, Manas; Roy, Anirban; Prasad, T. V.; Sharma, R. K.; Dutta, M.; Sharma, Indu; Bansal, K. C.

2016-01-01

A comprehensive germplasm evaluation study of wheat accessions conserved in the Indian National Genebank was conducted to identify sources of rust and spot blotch resistance. Genebank accessions comprising three species of wheat–Triticum aestivum, T. durum and T. dicoccum were screened sequentially at multiple disease hotspots, during the 2011–14 crop seasons, carrying only resistant accessions to the next step of evaluation. Wheat accessions which were found to be resistant in the field were then assayed for seedling resistance and profiled using molecular markers. In the primary evaluation, 19,460 accessions were screened at Wellington (Tamil Nadu), a hotspot for wheat rusts. We identified 4925 accessions to be resistant and these were further evaluated at Gurdaspur (Punjab), a hotspot for stripe rust and at Cooch Behar (West Bengal), a hotspot for spot blotch. The second round evaluation identified 498 accessions potentially resistant to multiple rusts and 868 accessions potentially resistant to spot blotch. Evaluation of rust resistant accessions for seedling resistance against seven virulent pathotypes of three rusts under artificial epiphytotic conditions identified 137 accessions potentially resistant to multiple rusts. Molecular analysis to identify different combinations of genetic loci imparting resistance to leaf rust, stem rust, stripe rust and spot blotch using linked molecular markers, identified 45 wheat accessions containing known resistance genes against all three rusts as well as a QTL for spot blotch resistance. The resistant germplasm accessions, particularly against stripe rust, identified in this study can be excellent potential candidates to be employed for breeding resistance into the background of high yielding wheat cultivars through conventional or molecular breeding approaches, and are expected to contribute toward food security at national and global levels. PMID:27942031

Construct validity and frequency of euphoria sclerotica in multiple sclerosis.

PubMed

Fishman, Inna; Benedict, Ralph H B; Bakshi, Rohit; Priore, Roger; Weinstock-Guttman, Bianca

2004-01-01

Using the Neuropsychiatric Inventory (NPI), we studied euphoria and other behavioral changes in 75 consecutive, unselected multiple sclerosis (MS) patients and 25 healthy controls. We also assessed disease duration, clinical course, physical disability, personality, depression, insight, cognition, and caregiver distress. Factor analysis identified a cluster of symptoms--labeled euphoria/disinhibition--similar to the euphoria sclerotica syndrome originally described by Charcot and others. The euphoria/disinhibition factor score was elevated in 9% of patients and associated with secondary-progressive course, low agreeableness, poor insight, impaired cognition, and high caregiver distress. Thus, we used the NPI to validate the euphoria syndrome in multiple sclerosis (MS) and determined its frequency, and its neurological and psychological correlates.

Joint analysis of multiple high-dimensional data types using sparse matrix approximations of rank-1 with applications to ovarian and liver cancer.

PubMed

Okimoto, Gordon; Zeinalzadeh, Ashkan; Wenska, Tom; Loomis, Michael; Nation, James B; Fabre, Tiphaine; Tiirikainen, Maarit; Hernandez, Brenda; Chan, Owen; Wong, Linda; Kwee, Sandi

2016-01-01

Technological advances enable the cost-effective acquisition of Multi-Modal Data Sets (MMDS) composed of measurements for multiple, high-dimensional data types obtained from a common set of bio-samples. The joint analysis of the data matrices associated with the different data types of a MMDS should provide a more focused view of the biology underlying complex diseases such as cancer that would not be apparent from the analysis of a single data type alone. As multi-modal data rapidly accumulate in research laboratories and public databases such as The Cancer Genome Atlas (TCGA), the translation of such data into clinically actionable knowledge has been slowed by the lack of computational tools capable of analyzing MMDSs. Here, we describe the Joint Analysis of Many Matrices by ITeration (JAMMIT) algorithm that jointly analyzes the data matrices of a MMDS using sparse matrix approximations of rank-1. The JAMMIT algorithm jointly approximates an arbitrary number of data matrices by rank-1 outer-products composed of "sparse" left-singular vectors (eigen-arrays) that are unique to each matrix and a right-singular vector (eigen-signal) that is common to all the matrices. The non-zero coefficients of the eigen-arrays identify small subsets of variables for each data type (i.e., signatures) that in aggregate, or individually, best explain a dominant eigen-signal defined on the columns of the data matrices. The approximation is specified by a single "sparsity" parameter that is selected based on false discovery rate estimated by permutation testing. Multiple signals of interest in a given MDDS are sequentially detected and modeled by iterating JAMMIT on "residual" data matrices that result from a given sparse approximation. We show that JAMMIT outperforms other joint analysis algorithms in the detection of multiple signatures embedded in simulated MDDS. On real multimodal data for ovarian and liver cancer we show that JAMMIT identified multi-modal signatures that were clinically informative and enriched for cancer-related biology. Sparse matrix approximations of rank-1 provide a simple yet effective means of jointly reducing multiple, big data types to a small subset of variables that characterize important clinical and/or biological attributes of the bio-samples from which the data were acquired.

Satellite Remote Sensing of Harmful Algal Blooms (HABs) and a Potential Synthesized Framework

PubMed Central

Shen, Li; Xu, Huiping; Guo, Xulin

2012-01-01

Harmful algal blooms (HABs) are severe ecological disasters threatening aquatic systems throughout the World, which necessitate scientific efforts in detecting and monitoring them. Compared with traditional in situ point observations, satellite remote sensing is considered as a promising technique for studying HABs due to its advantages of large-scale, real-time, and long-term monitoring. The present review summarizes the suitability of current satellite data sources and different algorithms for detecting HABs. It also discusses the spatial scale issue of HABs. Based on the major problems identified from previous literature, including the unsystematic understanding of HABs, the insufficient incorporation of satellite remote sensing, and a lack of multiple oceanographic explanations of the mechanisms causing HABs, this review also attempts to provide a comprehensive understanding of the complicated mechanism of HABs impacted by multiple oceanographic factors. A potential synthesized framework can be established by combining multiple accessible satellite remote sensing approaches including visual interpretation, spectra analysis, parameters retrieval and spatial-temporal pattern analysis. This framework aims to lead to a systematic and comprehensive monitoring of HABs based on satellite remote sensing from multiple oceanographic perspectives. PMID:22969372

Clinical and molecular evaluation of SHOX/PAR1 duplications in Leri-Weill dyschondrosteosis (LWD) and idiopathic short stature (ISS).

PubMed

Benito-Sanz, S; Barroso, E; Heine-Suñer, D; Hisado-Oliva, A; Romanelli, V; Rosell, J; Aragones, A; Caimari, M; Argente, J; Ross, J L; Zinn, A R; Gracia, R; Lapunzina, P; Campos-Barros, A; Heath, K E

2011-02-01

Léri-Weill dyschondrosteosis (LWD) is a skeletal dysplasia characterized by disproportionate short stature and the Madelung deformity of the forearm. SHOX mutations and pseudoautosomal region 1 deletions encompassing SHOX or its enhancers have been identified in approximately 60% of LWD and approximately 15% of idiopathic short stature (ISS) individuals. Recently SHOX duplications have been described in LWD/ISS but also in individuals with other clinical manifestations, thus questioning their pathogenicity. The objective of the study was to investigate the pathogenicity of SHOX duplications in LWD and ISS. Multiplex ligation-dependent probe amplification is routinely used in our unit to analyze for SHOX/pseudoautosomal region 1 copy number changes in LWD/ISS referrals. Quantitative PCR, microsatellite marker, and fluorescence in situ hybridization analysis were undertaken to confirm all identified duplications. During the routine analysis of 122 LWD and 613 ISS referrals, a total of four complete and 10 partial SHOX duplications or multiple copy number (n > 3) as well as one duplication of the SHOX 5' flanking region were identified in nine LWD and six ISS cases. Partial SHOX duplications appeared to have a more deleterious effect on skeletal dysplasia and height gain than complete SHOX duplications. Importantly, no increase in SHOX copy number was identified in 340 individuals with normal stature or 104 overgrowth referrals. MLPA analysis of SHOX/PAR1 led to the identification of partial and complete SHOX duplications or multiple copies associated with LWD or ISS, suggesting that they may represent an additional class of mutations implicated in the molecular etiology of these clinical entities.

Which Measurement of Blood Pressure Is More Associated With Albuminuria in Patients With Type 2 Diabetes: Central Blood Pressure or Peripheral Blood Pressure?

PubMed

Kitagawa, Noriyuki; Okada, Hiroshi; Tanaka, Muhei; Hashimoto, Yoshitaka; Kimura, Toshihiro; Nakano, Koji; Yamazaki, Masahiro; Hasegawa, Goji; Nakamura, Naoto; Fukui, Michiaki

2016-08-01

The aim of this study was to investigate whether central systolic blood pressure (SBP) was associated with albuminuria, defined as urinary albumin excretion (UAE) ≥30 mg/g creatinine, and, if so, whether the relationship of central SBP with albuminuria was stronger than that of peripheral SBP in patients with type 2 diabetes. The authors performed a cross-sectional study in 294 outpatients with type 2 diabetes. The relationship between peripheral SBP or central SBP and UAE using regression analysis was evaluated, and the odds ratios of peripheral SBP or central SBP were calculated to identify albuminuria using logistic regression model. Moreover, the area under the receiver operating characteristic curve (AUC) of central SBP was compared with that of peripheral SBP to identify albuminuria. Multiple regression analysis demonstrated that peripheral SBP (β=0.255, P<.0001) or central SBP (r=0.227, P<.0001) was associated with UAE. Multiple logistic regression analysis demonstrated that peripheral SBP (odds ratio, 1.029; 95% confidence interval, 1.016-1.043) or central SBP (odds ratio, 1.022; 95% confidence interval, 1.011-1.034) was associated with an increased odds of albuminuria. In addition, AUC of peripheral SBP was significantly greater than that of central SBP to identify albuminuria (P=0.035). Peripheral SBP is superior to central SBP in identifying albuminuria, although both peripheral and central SBP are associated with UAE in patients with type 2 diabetes. © 2016 Wiley Periodicals, Inc.

Regularized rare variant enrichment analysis for case-control exome sequencing data.

PubMed

Larson, Nicholas B; Schaid, Daniel J

2014-02-01

Rare variants have recently garnered an immense amount of attention in genetic association analysis. However, unlike methods traditionally used for single marker analysis in GWAS, rare variant analysis often requires some method of aggregation, since single marker approaches are poorly powered for typical sequencing study sample sizes. Advancements in sequencing technologies have rendered next-generation sequencing platforms a realistic alternative to traditional genotyping arrays. Exome sequencing in particular not only provides base-level resolution of genetic coding regions, but also a natural paradigm for aggregation via genes and exons. Here, we propose the use of penalized regression in combination with variant aggregation measures to identify rare variant enrichment in exome sequencing data. In contrast to marginal gene-level testing, we simultaneously evaluate the effects of rare variants in multiple genes, focusing on gene-based least absolute shrinkage and selection operator (LASSO) and exon-based sparse group LASSO models. By using gene membership as a grouping variable, the sparse group LASSO can be used as a gene-centric analysis of rare variants while also providing a penalized approach toward identifying specific regions of interest. We apply extensive simulations to evaluate the performance of these approaches with respect to specificity and sensitivity, comparing these results to multiple competing marginal testing methods. Finally, we discuss our findings and outline future research. © 2013 WILEY PERIODICALS, INC.

Integrated analysis of miRNA and mRNA expression data identifies multiple miRNAs regulatory networks for the tumorigenesis of colorectal cancer.

PubMed

Xu, Peng; Wang, Junhua; Sun, Bo; Xiao, Zhongdang

2018-06-15

Investigating the potential biological function of differential changed genes through integrating multiple omics data including miRNA and mRNA expression profiles, is always hot topic. However, how to evaluate the repression effect on target genes integrating miRNA and mRNA expression profiles are not fully solved. In this study, we provide an analyzing method by integrating both miRNAs and mRNAs expression data simultaneously. Difference analysis was adopted based on the repression score, then significantly repressed mRNAs were screened out by DEGseq. Pathway analysis for the significantly repressed mRNAs shows that multiple pathways such as MAPK signaling pathway, TGF-beta signaling pathway and so on, may correlated to the colorectal cancer(CRC). Focusing on the MAPK signaling pathway, a miRNA-mRNA network that centering the cell fate genes was constructed. Finally, the miRNA-mRNAs that potentially important in the CRC carcinogenesis were screened out and scored by impact index. Copyright © 2018 Elsevier B.V. All rights reserved.

Family-Based Rare Variant Association Analysis: A Fast and Efficient Method of Multivariate Phenotype Association Analysis.

PubMed

Wang, Longfei; Lee, Sungyoung; Gim, Jungsoo; Qiao, Dandi; Cho, Michael; Elston, Robert C; Silverman, Edwin K; Won, Sungho

2016-09-01

Family-based designs have been repeatedly shown to be powerful in detecting the significant rare variants associated with human diseases. Furthermore, human diseases are often defined by the outcomes of multiple phenotypes, and thus we expect multivariate family-based analyses may be very efficient in detecting associations with rare variants. However, few statistical methods implementing this strategy have been developed for family-based designs. In this report, we describe one such implementation: the multivariate family-based rare variant association tool (mFARVAT). mFARVAT is a quasi-likelihood-based score test for rare variant association analysis with multiple phenotypes, and tests both homogeneous and heterogeneous effects of each variant on multiple phenotypes. Simulation results show that the proposed method is generally robust and efficient for various disease models, and we identify some promising candidate genes associated with chronic obstructive pulmonary disease. The software of mFARVAT is freely available at http://healthstat.snu.ac.kr/software/mfarvat/, implemented in C++ and supported on Linux and MS Windows. © 2016 WILEY PERIODICALS, INC.

Circular RNA expression in basal cell carcinoma.

PubMed

Sand, Michael; Bechara, Falk G; Sand, Daniel; Gambichler, Thilo; Hahn, Stephan A; Bromba, Michael; Stockfleth, Eggert; Hessam, Schapoor

2016-05-01

Circular RNAs (circRNAs), are nonprotein coding RNAs consisting of a circular loop with multiple miRNA, binding sites called miRNA response elements (MREs), functioning as miRNA sponges. This study was performed to identify differentially expressed circRNAs and their MREs in basal cell carcinoma (BCC). Microarray circRNA expression profiles were acquired from BCC and control followed by qRT-PCR validation. Bioinformatical target prediction revealed multiple MREs. Sequence analysis was performed concerning MRE interaction potential with the BCC miRNome. We identified 23 upregulated and 48 downregulated circRNAs with 354 miRNA response elements capable of sequestering miRNA target sequences of the BCC miRNome. The present study describes a variety of circRNAs that are potentially involved in the molecular pathogenesis of BCC.

Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis.

PubMed

Sawcer, Stephen; Hellenthal, Garrett; Pirinen, Matti; Spencer, Chris C A; Patsopoulos, Nikolaos A; Moutsianas, Loukas; Dilthey, Alexander; Su, Zhan; Freeman, Colin; Hunt, Sarah E; Edkins, Sarah; Gray, Emma; Booth, David R; Potter, Simon C; Goris, An; Band, Gavin; Oturai, Annette Bang; Strange, Amy; Saarela, Janna; Bellenguez, Céline; Fontaine, Bertrand; Gillman, Matthew; Hemmer, Bernhard; Gwilliam, Rhian; Zipp, Frauke; Jayakumar, Alagurevathi; Martin, Roland; Leslie, Stephen; Hawkins, Stanley; Giannoulatou, Eleni; D'alfonso, Sandra; Blackburn, Hannah; Martinelli Boneschi, Filippo; Liddle, Jennifer; Harbo, Hanne F; Perez, Marc L; Spurkland, Anne; Waller, Matthew J; Mycko, Marcin P; Ricketts, Michelle; Comabella, Manuel; Hammond, Naomi; Kockum, Ingrid; McCann, Owen T; Ban, Maria; Whittaker, Pamela; Kemppinen, Anu; Weston, Paul; Hawkins, Clive; Widaa, Sara; Zajicek, John; Dronov, Serge; Robertson, Neil; Bumpstead, Suzannah J; Barcellos, Lisa F; Ravindrarajah, Rathi; Abraham, Roby; Alfredsson, Lars; Ardlie, Kristin; Aubin, Cristin; Baker, Amie; Baker, Katharine; Baranzini, Sergio E; Bergamaschi, Laura; Bergamaschi, Roberto; Bernstein, Allan; Berthele, Achim; Boggild, Mike; Bradfield, Jonathan P; Brassat, David; Broadley, Simon A; Buck, Dorothea; Butzkueven, Helmut; Capra, Ruggero; Carroll, William M; Cavalla, Paola; Celius, Elisabeth G; Cepok, Sabine; Chiavacci, Rosetta; Clerget-Darpoux, Françoise; Clysters, Katleen; Comi, Giancarlo; Cossburn, Mark; Cournu-Rebeix, Isabelle; Cox, Mathew B; Cozen, Wendy; Cree, Bruce A C; Cross, Anne H; Cusi, Daniele; Daly, Mark J; Davis, Emma; de Bakker, Paul I W; Debouverie, Marc; D'hooghe, Marie Beatrice; Dixon, Katherine; Dobosi, Rita; Dubois, Bénédicte; Ellinghaus, David; Elovaara, Irina; Esposito, Federica; Fontenille, Claire; Foote, Simon; Franke, Andre; Galimberti, Daniela; Ghezzi, Angelo; Glessner, Joseph; Gomez, Refujia; Gout, Olivier; Graham, Colin; Grant, Struan F A; Guerini, Franca Rosa; Hakonarson, Hakon; Hall, Per; Hamsten, Anders; Hartung, Hans-Peter; Heard, Rob N; Heath, Simon; Hobart, Jeremy; Hoshi, Muna; Infante-Duarte, Carmen; Ingram, Gillian; Ingram, Wendy; Islam, Talat; Jagodic, Maja; Kabesch, Michael; Kermode, Allan G; Kilpatrick, Trevor J; Kim, Cecilia; Klopp, Norman; Koivisto, Keijo; Larsson, Malin; Lathrop, Mark; Lechner-Scott, Jeannette S; Leone, Maurizio A; Leppä, Virpi; Liljedahl, Ulrika; Bomfim, Izaura Lima; Lincoln, Robin R; Link, Jenny; Liu, Jianjun; Lorentzen, Aslaug R; Lupoli, Sara; Macciardi, Fabio; Mack, Thomas; Marriott, Mark; Martinelli, Vittorio; Mason, Deborah; McCauley, Jacob L; Mentch, Frank; Mero, Inger-Lise; Mihalova, Tania; Montalban, Xavier; Mottershead, John; Myhr, Kjell-Morten; Naldi, Paola; Ollier, William; Page, Alison; Palotie, Aarno; Pelletier, Jean; Piccio, Laura; Pickersgill, Trevor; Piehl, Fredrik; Pobywajlo, Susan; Quach, Hong L; Ramsay, Patricia P; Reunanen, Mauri; Reynolds, Richard; Rioux, John D; Rodegher, Mariaemma; Roesner, Sabine; Rubio, Justin P; Rückert, Ina-Maria; Salvetti, Marco; Salvi, Erika; Santaniello, Adam; Schaefer, Catherine A; Schreiber, Stefan; Schulze, Christian; Scott, Rodney J; Sellebjerg, Finn; Selmaj, Krzysztof W; Sexton, David; Shen, Ling; Simms-Acuna, Brigid; Skidmore, Sheila; Sleiman, Patrick M A; Smestad, Cathrine; Sørensen, Per Soelberg; Søndergaard, Helle Bach; Stankovich, Jim; Strange, Richard C; Sulonen, Anna-Maija; Sundqvist, Emilie; Syvänen, Ann-Christine; Taddeo, Francesca; Taylor, Bruce; Blackwell, Jenefer M; Tienari, Pentti; Bramon, Elvira; Tourbah, Ayman; Brown, Matthew A; Tronczynska, Ewa; Casas, Juan P; Tubridy, Niall; Corvin, Aiden; Vickery, Jane; Jankowski, Janusz; Villoslada, Pablo; Markus, Hugh S; Wang, Kai; Mathew, Christopher G; Wason, James; Palmer, Colin N A; Wichmann, H-Erich; Plomin, Robert; Willoughby, Ernest; Rautanen, Anna; Winkelmann, Juliane; Wittig, Michael; Trembath, Richard C; Yaouanq, Jacqueline; Viswanathan, Ananth C; Zhang, Haitao; Wood, Nicholas W; Zuvich, Rebecca; Deloukas, Panos; Langford, Cordelia; Duncanson, Audrey; Oksenberg, Jorge R; Pericak-Vance, Margaret A; Haines, Jonathan L; Olsson, Tomas; Hillert, Jan; Ivinson, Adrian J; De Jager, Philip L; Peltonen, Leena; Stewart, Graeme J; Hafler, David A; Hauser, Stephen L; McVean, Gil; Donnelly, Peter; Compston, Alastair

2011-08-10

Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis.

Identification of More Feasible MicroRNA-mRNA Interactions within Multiple Cancers Using Principal Component Analysis Based Unsupervised Feature Extraction.

PubMed

Taguchi, Y-H

2016-05-10

MicroRNA(miRNA)-mRNA interactions are important for understanding many biological processes, including development, differentiation and disease progression, but their identification is highly context-dependent. When computationally derived from sequence information alone, the identification should be verified by integrated analyses of mRNA and miRNA expression. The drawback of this strategy is the vast number of identified interactions, which prevents an experimental or detailed investigation of each pair. In this paper, we overcome this difficulty by the recently proposed principal component analysis (PCA)-based unsupervised feature extraction (FE), which reduces the number of identified miRNA-mRNA interactions that properly discriminate between patients and healthy controls without losing biological feasibility. The approach is applied to six cancers: hepatocellular carcinoma, non-small cell lung cancer, esophageal squamous cell carcinoma, prostate cancer, colorectal/colon cancer and breast cancer. In PCA-based unsupervised FE, the significance does not depend on the number of samples (as in the standard case) but on the number of features, which approximates the number of miRNAs/mRNAs. To our knowledge, we have newly identified miRNA-mRNA interactions in multiple cancers based on a single common (universal) criterion. Moreover, the number of identified interactions was sufficiently small to be sequentially curated by literature searches.

A novel approach to identify genes that determine grain protein deviation in cereals.

PubMed

Mosleth, Ellen F; Wan, Yongfang; Lysenko, Artem; Chope, Gemma A; Penson, Simon P; Shewry, Peter R; Hawkesford, Malcolm J

2015-06-01

Grain yield and protein content were determined for six wheat cultivars grown over 3 years at multiple sites and at multiple nitrogen (N) fertilizer inputs. Although grain protein content was negatively correlated with yield, some grain samples had higher protein contents than expected based on their yields, a trait referred to as grain protein deviation (GPD). We used novel statistical approaches to identify gene transcripts significantly related to GPD across environments. The yield and protein content were initially adjusted for nitrogen fertilizer inputs and then adjusted for yield (to remove the negative correlation with protein content), resulting in a parameter termed corrected GPD. Significant genetic variation in corrected GPD was observed for six cultivars grown over a range of environmental conditions (a total of 584 samples). Gene transcript profiles were determined in a subset of 161 samples of developing grain to identify transcripts contributing to GPD. Principal component analysis (PCA), analysis of variance (ANOVA) and means of scores regression (MSR) were used to identify individual principal components (PCs) correlating with GPD alone. Scores of the selected PCs, which were significantly related to GPD and protein content but not to the yield and significantly affected by cultivar, were identified as reflecting a multivariate pattern of gene expression related to genetic variation in GPD. Transcripts with consistent variation along the selected PCs were identified by an approach hereby called one-block means of scores regression (one-block MSR). © 2014 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

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.

West syndrome in a patient with Schinzel-Giedion syndrome.

PubMed

Miyake, Fuyu; Kuroda, Yukiko; Naruto, Takuya; Ohashi, Ikuko; Takano, Kyoko; Kurosawa, Kenji

2015-06-01

Schinzel-Giedion syndrome is a rare recognizable malformation syndrome defined by characteristic facial features, profound developmental delay, severe growth failure, and multiple congenital anomalies. The causative gene of Schinzel-Giedion syndrome, SETBP1, has been identified, but limited cases have been confirmed by molecular analysis. We present a 9-month-old girl affected by West syndrome with Schinzel-Giedion syndrome. Congenital severe hydronephrosis, typical facial features, and multiple anomalies suggested a clinical diagnosis of Schinzel-Giedion syndrome. Hypsarrhythmia occurred at 7 months of age and was temporarily controlled by adrenocorticotropic hormone (ACTH) therapy during 5 weeks. SETBP1 mutational analysis showed the presence of a recurrent mutation, p.Ile871Thr. The implications in management of Schinzel-Giedion syndrome are discussed. © The Author(s) 2014.

Testing multiple statistical hypotheses resulted in spurious associations: a study of astrological signs and health.

PubMed

Austin, Peter C; Mamdani, Muhammad M; Juurlink, David N; Hux, Janet E

2006-09-01

To illustrate how multiple hypotheses testing can produce associations with no clinical plausibility. We conducted a study of all 10,674,945 residents of Ontario aged between 18 and 100 years in 2000. Residents were randomly assigned to equally sized derivation and validation cohorts and classified according to their astrological sign. Using the derivation cohort, we searched through 223 of the most common diagnoses for hospitalization until we identified two for which subjects born under one astrological sign had a significantly higher probability of hospitalization compared to subjects born under the remaining signs combined (P<0.05). We tested these 24 associations in the independent validation cohort. Residents born under Leo had a higher probability of gastrointestinal hemorrhage (P=0.0447), while Sagittarians had a higher probability of humerus fracture (P=0.0123) compared to all other signs combined. After adjusting the significance level to account for multiple comparisons, none of the identified associations remained significant in either the derivation or validation cohort. Our analyses illustrate how the testing of multiple, non-prespecified hypotheses increases the likelihood of detecting implausible associations. Our findings have important implications for the analysis and interpretation of clinical studies.

A Next-Generation Sequencing Strategy for Evaluating the Most Common Genetic Abnormalities in Multiple Myeloma.

PubMed

Jiménez, Cristina; Jara-Acevedo, María; Corchete, Luis A; Castillo, David; Ordóñez, Gonzalo R; Sarasquete, María E; Puig, Noemí; Martínez-López, Joaquín; Prieto-Conde, María I; García-Álvarez, María; Chillón, María C; Balanzategui, Ana; Alcoceba, Miguel; Oriol, Albert; Rosiñol, Laura; Palomera, Luis; Teruel, Ana I; Lahuerta, Juan J; Bladé, Joan; Mateos, María V; Orfão, Alberto; San Miguel, Jesús F; González, Marcos; Gutiérrez, Norma C; García-Sanz, Ramón

2017-01-01

Identification and characterization of genetic alterations are essential for diagnosis of multiple myeloma and may guide therapeutic decisions. Currently, genomic analysis of myeloma to cover the diverse range of alterations with prognostic impact requires fluorescence in situ hybridization (FISH), single nucleotide polymorphism arrays, and sequencing techniques, which are costly and labor intensive and require large numbers of plasma cells. To overcome these limitations, we designed a targeted-capture next-generation sequencing approach for one-step identification of IGH translocations, V(D)J clonal rearrangements, the IgH isotype, and somatic mutations to rapidly identify risk groups and specific targetable molecular lesions. Forty-eight newly diagnosed myeloma patients were tested with the panel, which included IGH and six genes that are recurrently mutated in myeloma: NRAS, KRAS, HRAS, TP53, MYC, and BRAF. We identified 14 of 17 IGH translocations previously detected by FISH and three confirmed translocations not detected by FISH, with the additional advantage of breakpoint identification, which can be used as a target for evaluating minimal residual disease. IgH subclass and V(D)J rearrangements were identified in 77% and 65% of patients, respectively. Mutation analysis revealed the presence of missense protein-coding alterations in at least one of the evaluating genes in 16 of 48 patients (33%). This method may represent a time- and cost-effective diagnostic method for the molecular characterization of multiple myeloma. Copyright © 2017 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

Multiple Food-Animal-Borne Route in Transmission of Antibiotic-Resistant Salmonella Newport to Humans

PubMed Central

Pan, Hang; Paudyal, Narayan; Li, Xiaoliang; Fang, Weihuan; Yue, Min

2018-01-01

Characterization of transmission routes of Salmonella among various food-animal reservoirs and their antibiogram is crucial for appropriate intervention and medical treatment. Here, we analyzed 3728 Salmonella enterica serovar Newport (S. Newport) isolates collected from various food-animals, retail meats and humans in the United States between 1996 and 2015, based on their minimum inhibitory concentration (MIC) toward 27 antibiotics. Random Forest and Hierarchical Clustering statistic was used to group the isolates according to their MICs. Classification and Regression Tree (CART) analysis was used to identify the appropriate antibiotic and its cut-off value between human- and animal-population. Two distinct populations were revealed based on the MICs of individual strain by both methods, with the animal population having significantly higher MICs which correlates to antibiotic-resistance (AR) phenotype. Only ∼9.7% (267/2763) human isolates could be attributed to food–animal origins. Furthermore, the isolates of animal origin had less diverse antibiogram than human isolates (P < 0.001), suggesting multiple sources involved in human infections. CART identified trimethoprim-sulfamethoxazole to be the best classifier for differentiating the animal and human isolates. Additionally, two typical AR patterns, MDR-Amp and Tet-SDR dominant in bovine- or turkey-population, were identified, indicating that distinct food-animal sources could be involved in human infections. The AR analysis suggested fluoroquinolones (i.e., ciprofloxacin), but not extended-spectrum cephalosporins (i.e., ceftriaxone, cefoxitin), is the adaptive choice for empirical therapy. Antibiotic-resistant S. Newport from humans has multiple origins, with distinct food-animal-borne route contributing to a significant proportion of heterogeneous isolates. PMID:29410657

Reporting of analyses from randomized controlled trials with multiple arms: a systematic review.

PubMed

Baron, Gabriel; Perrodeau, Elodie; Boutron, Isabelle; Ravaud, Philippe

2013-03-27

Multiple-arm randomized trials can be more complex in their design, data analysis, and result reporting than two-arm trials. We conducted a systematic review to assess the reporting of analyses in reports of randomized controlled trials (RCTs) with multiple arms. The literature in the MEDLINE database was searched for reports of RCTs with multiple arms published in 2009 in the core clinical journals. Two reviewers extracted data using a standardized extraction form. In total, 298 reports were identified. Descriptions of the baseline characteristics and outcomes per group were missing in 45 reports (15.1%) and 48 reports (16.1%), respectively. More than half of the articles (n = 171, 57.4%) reported that a planned global test comparison was used (that is, assessment of the global differences between all groups), but 67 (39.2%) of these 171 articles did not report details of the planned analysis. Of the 116 articles reporting a global comparison test, 12 (10.3%) did not report the analysis as planned. In all, 60% of publications (n = 180) described planned pairwise test comparisons (that is, assessment of the difference between two groups), but 20 of these 180 articles (11.1%) did not report the pairwise test comparisons. Of the 204 articles reporting pairwise test comparisons, the comparisons were not planned for 44 (21.6%) of them. Less than half the reports (n = 137; 46%) provided baseline and outcome data per arm and reported the analysis as planned. Our findings highlight discrepancies between the planning and reporting of analyses in reports of multiple-arm trials.

RNA-Seq Meta-analysis identifies genes in skeletal muscle associated with gain and intake across a multi-season study of crossbred beef steers.

PubMed

Keel, Brittney N; Zarek, Christina M; Keele, John W; Kuehn, Larry A; Snelling, Warren M; Oliver, William T; Freetly, Harvey C; Lindholm-Perry, Amanda K

2018-06-04

Feed intake and body weight gain are economically important inputs and outputs of beef production systems. The purpose of this study was to discover differentially expressed genes that will be robust for feed intake and gain across a large segment of the cattle industry. Transcriptomic studies often suffer from issues with reproducibility and cross-validation. One way to improve reproducibility is by integrating multiple datasets via meta-analysis. RNA sequencing (RNA-Seq) was performed on longissimus dorsi muscle from 80 steers (5 cohorts, each with 16 animals) selected from the outside fringe of a bivariate gain and feed intake distribution to understand the genes and pathways involved in feed efficiency. In each cohort, 16 steers were selected from one of four gain and feed intake phenotypes (n = 4 per phenotype) in a 2 × 2 factorial arrangement with gain and feed intake as main effect variables. Each cohort was analyzed as a single experiment using a generalized linear model and results from the 5 cohort analyses were combined in a meta-analysis to identify differentially expressed genes (DEG) across the cohorts. A total of 51 genes were differentially expressed for the main effect of gain, 109 genes for the intake main effect, and 11 genes for the gain x intake interaction (P corrected  < 0.05). A jackknife sensitivity analysis showed that, in general, the meta-analysis produced robust DEGs for the two main effects and their interaction. Pathways identified from over-represented genes included mitochondrial energy production and oxidative stress pathways for the main effect of gain due to DEG including GPD1, NDUFA6, UQCRQ, ACTC1, and MGST3. For intake, metabolic pathways including amino acid biosynthesis and degradation were identified, and for the interaction analysis the pathways identified included GADD45, pyridoxal 5'phosphate salvage, and caveolar mediated endocytosis signaling. Variation among DEG identified by cohort suggests that environment and breed may play large roles in the expression of genes associated with feed efficiency in the muscle of beef cattle. Meta-analyses of transcriptome data from groups of animals over multiple cohorts may be necessary to elucidate the genetics contributing these types of biological phenotypes.

Unraveling novel broad-spectrum antibacterial targets in food and waterborne pathogens using comparative genomics and protein interaction network analysis.

PubMed

Jadhav, Ankush; Shanmugham, Buvaneswari; Rajendiran, Anjana; Pan, Archana

2014-10-01

Food and waterborne diseases are a growing concern in terms of human morbidity and mortality worldwide, even in the 21st century, emphasizing the need for new therapeutic interventions for these diseases. The current study aims at prioritizing broad-spectrum antibacterial targets, present in multiple food and waterborne bacterial pathogens, through a comparative genomics strategy coupled with a protein interaction network analysis. The pathways unique and common to all the pathogens under study (viz., methane metabolism, d-alanine metabolism, peptidoglycan biosynthesis, bacterial secretion system, two-component system, C5-branched dibasic acid metabolism), identified by comparative metabolic pathway analysis, were considered for the analysis. The proteins/enzymes involved in these pathways were prioritized following host non-homology analysis, essentiality analysis, gut flora non-homology analysis and protein interaction network analysis. The analyses revealed a set of promising broad-spectrum antibacterial targets, present in multiple food and waterborne pathogens, which are essential for bacterial survival, non-homologous to host and gut flora, and functionally important in the metabolic network. The identified broad-spectrum candidates, namely, integral membrane protein/virulence factor (MviN), preprotein translocase subunits SecB and SecG, carbon storage regulator (CsrA), and nitrogen regulatory protein P-II 1 (GlnB), contributed by the peptidoglycan pathway, bacterial secretion systems and two-component systems, were also found to be present in a wide range of other disease-causing bacteria. Cytoplasmic proteins SecG, CsrA and GlnB were considered as drug targets, while membrane proteins MviN and SecB were classified as vaccine targets. The identified broad-spectrum targets can aid in the design and development of antibacterial agents not only against food and waterborne pathogens but also against other pathogens. Copyright © 2014 Elsevier B.V. All rights reserved.

Burnout, stress and satisfaction among Australian and New Zealand radiation oncology trainees.

PubMed

Leung, John; Rioseco, Pilar

2017-02-01

To evaluate the incidence of burnout among radiation oncology trainees in Australia and New Zealand and the stress and satisfaction factors related to burnout. A survey of trainees was conducted in mid-2015. There were 42 Likert scale questions on stress, 14 Likert scale questions on satisfaction and the Maslach Burnout Inventory-Human Services Survey assessed burnout. A principal component analysis identified specific stress and satisfaction areas. Categorical variables for the stress and satisfaction factors were computed. Associations between respondent's characteristics and stress and satisfaction subscales were examined by independent sample t-tests and analysis of variance. Effect sizes were calculated using Cohens's d when significant mean differences were observed. This was also done for respondent characteristics and the three burnout subscales. Multiple regression analyses were performed. The response rate was 81.5%. The principal component analysis for stress identified five areas: demands on time, professional development/training, delivery demands, interpersonal demands and administration/organizational issues. There were no significant differences by demographic group or area of interest after P-values were adjusted for the multiple tests conducted. The principal component analysis revealed two satisfaction areas: resources/professional activities and value/delivery of services. There were no significant differences by demographic characteristics or area of interest in the level of satisfaction after P-values were adjusted for the multiple tests conducted. The burnout results revealed 49.5% of respondents scored highly in emotional exhaustion and/or depersonalization and 13.1% had burnout in all three measures. Multiple regression analysis revealed the stress subscales 'demands on time' and 'interpersonal demands' were associated with emotional exhaustion. 'Interpersonal demands' was also associated with depersonalization and correlated negatively with personal accomplishment. The satisfaction of value/delivery of services subscale was associated with higher levels of personal accomplishment. There is a significant level of burnout among radiation oncology trainees in Australia and New Zealand. Further work addressing intervention would be appropriate to reduce levels of burnout. © 2016 The Authors. Journal of Medical Imaging and Radiation Oncology published by John Wiley & Sons Australia, Ltd on behalf of The Royal Australian and New Zealand College of Radiologists.

Global molecular identification from graphs. Neutral and ionized main-group diatomic molecules.

PubMed

James, Bryan; Caviness, Ken; Geach, Jonathan; Walters, Chris; Hefferlin, Ray

2002-01-01

Diophantine equations and inequalities are presented for main-group closed-shell diatomic molecules. Specifying various bond types (covalent, dative, ionic, van der Waals) and multiplicities, it becomes possible to identify all possible molecules. While many of the identified species are probably unstable under normal conditions, they are interesting and present a challenge for computational or experimental analysis. Ionized molecules with net charges of -1, 1, and 2 are also identified. The analysis applies to molecules with atoms from periods 2 and 3 but can be generalized by substituting isovalent atoms. When closed-shell neutral diatomics are positioned in the chemical space (with axes enumerating the numbers of valence electrons of the free atoms), it is seen that they lie on a few parallel isoelectronic series.

Towards a Methodology for Identifying Program Constraints During Requirements Analysis

NASA Technical Reports Server (NTRS)

Romo, Lilly; Gates, Ann Q.; Della-Piana, Connie Kubo

1997-01-01

Requirements analysis is the activity that involves determining the needs of the customer, identifying the services that the software system should provide and understanding the constraints on the solution. The result of this activity is a natural language document, typically referred to as the requirements definition document. Some of the problems that exist in defining requirements in large scale software projects includes synthesizing knowledge from various domain experts and communicating this information across multiple levels of personnel. One approach that addresses part of this problem is called context monitoring and involves identifying the properties of and relationships between objects that the system will manipulate. This paper examines several software development methodologies, discusses the support that each provide for eliciting such information from experts and specifying the information, and suggests refinements to these methodologies.

A Unified Analysis of Structured Sonar-terrain Data using Bayesian Functional Mixed Models.

PubMed

Zhu, Hongxiao; Caspers, Philip; Morris, Jeffrey S; Wu, Xiaowei; Müller, Rolf

2018-01-01

Sonar emits pulses of sound and uses the reflected echoes to gain information about target objects. It offers a low cost, complementary sensing modality for small robotic platforms. While existing analytical approaches often assume independence across echoes, real sonar data can have more complicated structures due to device setup or experimental design. In this paper, we consider sonar echo data collected from multiple terrain substrates with a dual-channel sonar head. Our goals are to identify the differential sonar responses to terrains and study the effectiveness of this dual-channel design in discriminating targets. We describe a unified analytical framework that achieves these goals rigorously, simultaneously, and automatically. The analysis was done by treating the echo envelope signals as functional responses and the terrain/channel information as covariates in a functional regression setting. We adopt functional mixed models that facilitate the estimation of terrain and channel effects while capturing the complex hierarchical structure in data. This unified analytical framework incorporates both Gaussian models and robust models. We fit the models using a full Bayesian approach, which enables us to perform multiple inferential tasks under the same modeling framework, including selecting models, estimating the effects of interest, identifying significant local regions, discriminating terrain types, and describing the discriminatory power of local regions. Our analysis of the sonar-terrain data identifies time regions that reflect differential sonar responses to terrains. The discriminant analysis suggests that a multi- or dual-channel design achieves target identification performance comparable with or better than a single-channel design.

A Unified Analysis of Structured Sonar-terrain Data using Bayesian Functional Mixed Models

PubMed Central

Zhu, Hongxiao; Caspers, Philip; Morris, Jeffrey S.; Wu, Xiaowei; Müller, Rolf

2017-01-01

Sonar emits pulses of sound and uses the reflected echoes to gain information about target objects. It offers a low cost, complementary sensing modality for small robotic platforms. While existing analytical approaches often assume independence across echoes, real sonar data can have more complicated structures due to device setup or experimental design. In this paper, we consider sonar echo data collected from multiple terrain substrates with a dual-channel sonar head. Our goals are to identify the differential sonar responses to terrains and study the effectiveness of this dual-channel design in discriminating targets. We describe a unified analytical framework that achieves these goals rigorously, simultaneously, and automatically. The analysis was done by treating the echo envelope signals as functional responses and the terrain/channel information as covariates in a functional regression setting. We adopt functional mixed models that facilitate the estimation of terrain and channel effects while capturing the complex hierarchical structure in data. This unified analytical framework incorporates both Gaussian models and robust models. We fit the models using a full Bayesian approach, which enables us to perform multiple inferential tasks under the same modeling framework, including selecting models, estimating the effects of interest, identifying significant local regions, discriminating terrain types, and describing the discriminatory power of local regions. Our analysis of the sonar-terrain data identifies time regions that reflect differential sonar responses to terrains. The discriminant analysis suggests that a multi- or dual-channel design achieves target identification performance comparable with or better than a single-channel design. PMID:29749977

Comparative transcriptome analysis of pepper (Capsicum annuum) revealed common regulons in multiple stress conditions and hormone treatments.

PubMed

Lee, Sanghyeob; Choi, Doil

2013-09-01

Global transcriptome analysis revealed common regulons for biotic/abiotic stresses, and some of these regulons encoding signaling components in both stresses were newly identified in this study. In this study, we aimed to identify plant responses to multiple stress conditions and discover the common regulons activated under a variety of stress conditions. Global transcriptome analysis revealed that salicylic acid (SA) may affect the activation of abiotic stress-responsive genes in pepper. Our data indicate that methyl jasmonate (MeJA) and ethylene (ET)-responsive genes were primarily activated by biotic stress, while abscisic acid (ABA)-responsive genes were activated under both types of stresses. We also identified differentially expressed gene (DEG) responses to specific stress conditions. Biotic stress induces more DEGs than those induced by abiotic and hormone applications. The clustering analysis using DEGs indicates that there are common regulons for biotic or abiotic stress conditions. Although SA and MeJA have an antagonistic effect on gene expression levels, SA and MeJA show a largely common regulation as compared to the regulation at the DEG expression level induced by other hormones. We also monitored the expression profiles of DEG encoding signaling components. Twenty-two percent of these were commonly expressed in both stress conditions. The importance of this study is that several genes commonly regulated by both stress conditions may have future applications for creating broadly stress-tolerant pepper plants. This study revealed that there are complex regulons in pepper plant to both biotic and abiotic stress conditions.

Novel PLS3 variants in X-linked osteoporosis: Exploring bone material properties.

PubMed

Balasubramanian, Meena; Fratzl-Zelman, Nadja; O'Sullivan, Rory; Bull, Mary; Fa Peel, Nicola; Pollitt, Rebecca C; Jones, Rebecca; Milne, Elizabeth; Smith, Kath; Roschger, Paul; Klaushofer, Klaus; Bishop, Nicholas J

2018-05-07

Idiopathic Juvenile Osteoporosis (IJO) refers to significantly lower than expected bone mass manifesting in childhood with no identifiable aetiology. IJO classically presents in early pubertal period with multiple fractures including metaphyseal and vertebral crush fractures, and low bone-mass. Here we describe two patients and provide information on their clinical phenotype, genotype and bone material analysis in one of the patients. Patient 1: 40-year old adult male diagnosed with IJO in childhood who re-presented with a hip fracture as an adult. Genetic analysis identified a pathogenic PLS3 hemizygous variant, c.1765del in exon 16. Patient 2: 15-year old boy with multiple vertebral fractures and bone biopsy findings suggestive of IJO who also has a diagnosis of autism spectrum disorder. Genetic analysis identified a maternally inherited PLS3 pathogenic c.1295T>A variant in exon 12. Analyses of the transiliac bone sample revealed severe reduction of trabecular volume and bone turnover indices and elevated bone matrix mineralisation. We propose that genetic testing for PLS3 should be undertaken in patients presenting with a current or previous history of IJO as this has implications for genetic counselling and cascade screening. The extensive evaluation of the transiliac biopsy sample of Patient 2 revealed a novel bone phenotype. This report includes a review of IJO and genetic causes of osteoporosis, and suggests that existing cases of IJO should be screened for PLS3. Through analysis of bone material properties in Patient 2, we can conclude that PLS3 does have a role in bone mineralisation. © 2018 Wiley Periodicals, Inc.

A Systematic Review and Meta-Analysis of the Brief Cognitive Assessment for Multiple Sclerosis (BICAMS).

PubMed

Corfield, Freya; Langdon, Dawn

2018-06-19

Multiple sclerosis (MS) is a neurological disease of the central nervous system which can lead to a range of severe physical disabilities. A large proportion of those affected will experience cognitive impairment, which is associated with a worse prognosis. Effective assessment of cognition in MS has been problematic due to a lack of suitable scales. The Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) was developed in 2010 as part of an international endeavour to facilitate cognitive assessment. The aim of this systematic review and meta-analysis was to synthesise the available literature published as part of the BICAMS international validation protocol. A literature search conducted using PubMed, PsycINFO and Google Scholar identified 16 studies for inclusion in the systematic review, 14 of which could be included in a meta-analysis. BICAMS has been widely validated across 11 languages and 14 individual cultures and locations. The meta-analysis demonstrated that BICAMS identified significantly reduced cognitive functioning in adults with MS compared to healthy controls. This was true for all three cognitive domains assessed by BICAMS: information processing speed (g = 0.943, 95% CI 0.839, 1.046, g < 0.001), immediate verbal recall memory (g = 0.688, 95% CI 0.554, 0.822, p < 0.001) and immediate visual recall memory (g = 0.635, 95% CI 0.534, 0.736, p < 0.001). BICAMS has been widely applied across cultures and languages to assess cognition in MS. BICAMS offers a feasible, cost-effective means of assessing cognition in MS worldwide. Further validation studies are underway to support this project.

Flow Analysis Tool White Paper

NASA Technical Reports Server (NTRS)

Boscia, Nichole K.

2012-01-01

Faster networks are continually being built to accommodate larger data transfers. While it is intuitive to think that implementing faster networks will result in higher throughput rates, this is often not the case. There are many elements involved in data transfer, many of which are beyond the scope of the network itself. Although networks may get bigger and support faster technologies, the presence of other legacy components, such as older application software or kernel parameters, can often cause bottlenecks. Engineers must be able to identify when data flows are reaching a bottleneck that is not imposed by the network and then troubleshoot it using the tools available to them. The current best practice is to collect as much information as possible on the network traffic flows so that analysis is quick and easy. Unfortunately, no single method of collecting this information can sufficiently capture the whole endto- end picture. This becomes even more of a hurdle when large, multi-user systems are involved. In order to capture all the necessary information, multiple data sources are required. This paper presents a method for developing a flow analysis tool to effectively collect network flow data from multiple sources and provide that information to engineers in a clear, concise way for analysis. The purpose of this method is to collect enough information to quickly (and automatically) identify poorly performing flows along with the cause of the problem. The method involves the development of a set of database tables that can be populated with flow data from multiple sources, along with an easyto- use, web-based front-end interface to help network engineers access, organize, analyze, and manage all the information.

The ability of clinical balance measures to identify falls risk in multiple sclerosis: a systematic review and meta-analysis.

PubMed

Quinn, Gillian; Comber, Laura; Galvin, Rose; Coote, Susan

2018-05-01

To determine the ability of clinical measures of balance to distinguish fallers from non-fallers and to determine their predictive validity in identifying those at risk of falls. AMED, CINAHL, Medline, Scopus, PubMed Central and Google Scholar. First search: July 2015. Final search: October 2017. Inclusion criteria were studies of adults with a definite multiple sclerosis diagnosis, a clinical balance assessment and method of falls recording. Data were extracted independently by two reviewers. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 scale and the modified Newcastle-Ottawa Quality Assessment Scale. Statistical analysis was conducted for the cross-sectional studies using Review Manager 5. The mean difference with 95% confidence interval in balance outcomes between fallers and non-fallers was used as the mode of analysis. We included 33 studies (19 cross-sectional, 5 randomised controlled trials, 9 prospective) with a total of 3901 participants, of which 1917 (49%) were classified as fallers. The balance measures most commonly reported were the Berg Balance Scale, Timed Up and Go and Falls Efficacy Scale International. Meta-analysis demonstrated fallers perform significantly worse than non-fallers on all measures analysed except the Timed Up and Go Cognitive ( p < 0.05), but discriminative ability of the measures is commonly not reported. Of those reported, the Activities-specific Balance Confidence Scale had the highest area under the receiver operating characteristic curve value (0.92), but without reporting corresponding measures of clinical utility. Clinical measures of balance differ significantly between fallers and non-fallers but have poor predictive ability for falls risk in people with multiple sclerosis.

Clinical reasoning: concept analysis.

PubMed

Simmons, Barbara

2010-05-01

This paper is a report of a concept analysis of clinical reasoning in nursing. Clinical reasoning is an ambiguous term that is often used synonymously with decision-making and clinical judgment. Clinical reasoning has not been clearly defined in the literature. Healthcare settings are increasingly filled with uncertainty, risk and complexity due to increased patient acuity, multiple comorbidities, and enhanced use of technology, all of which require clinical reasoning. Data sources. Literature for this concept analysis was retrieved from several databases, including CINAHL, PubMed, PsycINFO, ERIC and OvidMEDLINE, for the years 1980 to 2008. Rodgers's evolutionary method of concept analysis was used because of its applicability to concepts that are still evolving. Multiple terms have been used synonymously to describe the thinking skills that nurses use. Research in the past 20 years has elucidated differences among these terms and identified the cognitive processes that precede judgment and decision-making. Our concept analysis defines one of these terms, 'clinical reasoning,' as a complex process that uses cognition, metacognition, and discipline-specific knowledge to gather and analyse patient information, evaluate its significance, and weigh alternative actions. This concept analysis provides a middle-range descriptive theory of clinical reasoning in nursing that helps clarify meaning and gives direction for future research. Appropriate instruments to operationalize the concept need to be developed. Research is needed to identify additional variables that have an impact on clinical reasoning and what are the consequences of clinical reasoning in specific situations.

An augmented parametric response map with consideration of image registration error: towards guidance of locally adaptive radiotherapy

NASA Astrophysics Data System (ADS)

Lausch, Anthony; Chen, Jeff; Ward, Aaron D.; Gaede, Stewart; Lee, Ting-Yim; Wong, Eugene

2014-11-01

Parametric response map (PRM) analysis is a voxel-wise technique for predicting overall treatment outcome, which shows promise as a tool for guiding personalized locally adaptive radiotherapy (RT). However, image registration error (IRE) introduces uncertainty into this analysis which may limit its use for guiding RT. Here we extend the PRM method to include an IRE-related PRM analysis confidence interval and also incorporate multiple graded classification thresholds to facilitate visualization. A Gaussian IRE model was used to compute an expected value and confidence interval for PRM analysis. The augmented PRM (A-PRM) was evaluated using CT-perfusion functional image data from patients treated with RT for glioma and hepatocellular carcinoma. Known rigid IREs were simulated by applying one thousand different rigid transformations to each image set. PRM and A-PRM analyses of the transformed images were then compared to analyses of the original images (ground truth) in order to investigate the two methods in the presence of controlled IRE. The A-PRM was shown to help visualize and quantify IRE-related analysis uncertainty. The use of multiple graded classification thresholds also provided additional contextual information which could be useful for visually identifying adaptive RT targets (e.g. sub-volume boosts). The A-PRM should facilitate reliable PRM guided adaptive RT by allowing the user to identify if a patient’s unique IRE-related PRM analysis uncertainty has the potential to influence target delineation.

Bayesian bivariate meta-analysis of correlated effects: Impact of the prior distributions on the between-study correlation, borrowing of strength, and joint inferences

PubMed Central

Bujkiewicz, Sylwia; Riley, Richard D

2016-01-01

Multivariate random-effects meta-analysis allows the joint synthesis of correlated results from multiple studies, for example, for multiple outcomes or multiple treatment groups. In a Bayesian univariate meta-analysis of one endpoint, the importance of specifying a sensible prior distribution for the between-study variance is well understood. However, in multivariate meta-analysis, there is little guidance about the choice of prior distributions for the variances or, crucially, the between-study correlation, ρB; for the latter, researchers often use a Uniform(−1,1) distribution assuming it is vague. In this paper, an extensive simulation study and a real illustrative example is used to examine the impact of various (realistically) vague prior distributions for ρB and the between-study variances within a Bayesian bivariate random-effects meta-analysis of two correlated treatment effects. A range of diverse scenarios are considered, including complete and missing data, to examine the impact of the prior distributions on posterior results (for treatment effect and between-study correlation), amount of borrowing of strength, and joint predictive distributions of treatment effectiveness in new studies. Two key recommendations are identified to improve the robustness of multivariate meta-analysis results. First, the routine use of a Uniform(−1,1) prior distribution for ρB should be avoided, if possible, as it is not necessarily vague. Instead, researchers should identify a sensible prior distribution, for example, by restricting values to be positive or negative as indicated by prior knowledge. Second, it remains critical to use sensible (e.g. empirically based) prior distributions for the between-study variances, as an inappropriate choice can adversely impact the posterior distribution for ρB, which may then adversely affect inferences such as joint predictive probabilities. These recommendations are especially important with a small number of studies and missing data. PMID:26988929

Individual risk factors for deep infection and compromised fracture healing after intramedullary nailing of tibial shaft fractures: a single centre experience of 480 patients.

PubMed

Metsemakers, W-J; Handojo, K; Reynders, P; Sermon, A; Vanderschot, P; Nijs, S

2015-04-01

Despite modern advances in the treatment of tibial shaft fractures, complications including nonunion, malunion, and infection remain relatively frequent. A better understanding of these injuries and its complications could lead to prevention rather than treatment strategies. A retrospective study was performed to identify risk factors for deep infection and compromised fracture healing after intramedullary nailing (IMN) of tibial shaft fractures. Between January 2000 and January 2012, 480 consecutive patients with 486 tibial shaft fractures were enrolled in the study. Statistical analysis was performed to determine predictors of deep infection and compromised fracture healing. Compromised fracture healing was subdivided in delayed union and nonunion. The following independent variables were selected for analysis: age, sex, smoking, obesity, diabetes, American Society of Anaesthesiologists (ASA) classification, polytrauma, fracture type, open fractures, Gustilo type, primary external fixation (EF), time to nailing (TTN) and reaming. As primary statistical evaluation we performed a univariate analysis, followed by a multiple logistic regression model. Univariate regression analysis revealed similar risk factors for delayed union and nonunion, including fracture type, open fractures and Gustilo type. Factors affecting the occurrence of deep infection in this model were primary EF, a prolonged TTN, open fractures and Gustilo type. Multiple logistic regression analysis revealed polytrauma as the single risk factor for nonunion. With respect to delayed union, no risk factors could be identified. In the same statistical model, deep infection was correlated with primary EF. The purpose of this study was to evaluate risk factors of poor outcome after IMN of tibial shaft fractures. The univariate regression analysis showed that the nature of complications after tibial shaft nailing could be multifactorial. This was not confirmed in a multiple logistic regression model, which only revealed polytrauma and primary EF as risk factors for nonunion and deep infection, respectively. Future strategies should focus on prevention in high-risk populations such as polytrauma patients treated with EF. Copyright © 2014 Elsevier Ltd. All rights reserved.

Application of principal component analysis (PCA) as a sensory assessment tool for fermented food products.

PubMed

Ghosh, Debasree; Chattopadhyay, Parimal

2012-06-01

The objective of the work was to use the method of quantitative descriptive analysis (QDA) to describe the sensory attributes of the fermented food products prepared with the incorporation of lactic cultures. Panellists were selected and trained to evaluate various attributes specially color and appearance, body texture, flavor, overall acceptability and acidity of the fermented food products like cow milk curd and soymilk curd, idli, sauerkraut and probiotic ice cream. Principal component analysis (PCA) identified the six significant principal components that accounted for more than 90% of the variance in the sensory attribute data. Overall product quality was modelled as a function of principal components using multiple least squares regression (R (2) = 0.8). The result from PCA was statistically analyzed by analysis of variance (ANOVA). These findings demonstrate the utility of quantitative descriptive analysis for identifying and measuring the fermented food product attributes that are important for consumer acceptability.

The confounding effects of hybridization on phylogenetic estimation in the New Zealand cicada genus Kikihia.

PubMed

Banker, Sarah E; Wade, Elizabeth J; Simon, Chris

2017-11-01

Phylogenetic studies of multiple independently inherited nuclear genes considered in combination with patterns of inheritance of organelle DNA have provided considerable insight into the history of species evolution. In particular, investigations of cicadas in the New Zealand genus Kikihia have identified interesting cases where mitochondrial DNA (mtDNA) crosses species boundaries in some species pairs but not others. Previous phylogenetic studies focusing on mtDNA largely corroborated Kikihia species groups identified by song, morphology and ecology with the exception of a unique South Island mitochondrial haplotype clade-the Westlandica group. This newly identified group consists of diverse taxa previously classified as belonging to three different sub-generic clades. We sequenced five nuclear loci from multiple individuals from every species of Kikihia to assess the nuclear gene concordance for this newly-identified mtDNA lineage. Bayes Factor analysis of the constrained phylogeny suggests some support for the mtDNA-based hypotheses, despite the fact that neither concatenation nor multiple species tree methods resolve the Westlandica group as monophyletic. The nuclear analyses suggest a geographic distinction between clearly defined monophyletic North Island clades and unresolved South Island clades. We suggest that more extreme habitat modification on South Island during the Pliocene and Pleistocene resulted in secondary contact and hybridization between species pairs and a series of mitochondrial capture events followed by subsequent lineage evolution. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

QTL variations for growth-related traits in eight distinct families of common carp (Cyprinus carpio).

PubMed

Lv, Weihua; Zheng, Xianhu; Kuang, Youyi; Cao, Dingchen; Yan, Yunqin; Sun, Xiaowen

2016-05-05

Comparing QTL analyses of multiple pair-mating families can provide a better understanding of important allelic variations and distributions. However, most QTL mapping studies in common carp have been based on analyses of individual families. In order to improve our understanding of heredity and variation of QTLs in different families and identify important QTLs, we performed QTL analysis of growth-related traits in multiple segregating families. We completed a genome scan for QTLs that affect body weight (BW), total length (TL), and body thickness (BT) of 522 individuals from eight full-sib families using 250 microsatellites evenly distributed across 50 chromosomes. Sib-pair and half-sib model mapping identified 165 QTLs on 30 linkage groups. Among them, 10 (genome-wide P <0.01 or P < 0.05) and 28 (chromosome-wide P < 0.01) QTLs exhibited significant evidence of linkage, while the remaining 127 exhibited a suggestive effect on the above three traits at a chromosome-wide (P < 0.05) level. Multiple QTLs obtained from different families affect BW, TL, and BT and locate at close or identical positions. It suggests that same genetic factors may control variability in these traits. Furthermore, the results of the comparative QTL analysis of multiple families showed that one QTL was common in four of the eight families, nine QTLs were detected in three of the eight families, and 26 QTLs were found common to two of the eight families. These common QTLs are valuable candidates in marker-assisted selection. A large number of QTLs were detected in the common carp genome and associated with growth-related traits. Some of the QTLs of different growth-related traits were identified at similar chromosomal regions, suggesting a role for pleiotropy and/or tight linkage and demonstrating a common genetic basis of growth trait variations. The results have set up an example for comparing QTLs in common carp and provided insights into variations in the identified QTLs affecting body growth. Discovery of these common QTLs between families and growth-related traits represents an important step towards understanding of quantitative genetic variation in common carp.

An Improved Wake Vortex Tracking Algorithm for Multiple Aircraft

NASA Technical Reports Server (NTRS)

Switzer, George F.; Proctor, Fred H.; Ahmad, Nashat N.; LimonDuparcmeur, Fanny M.

2010-01-01

The accurate tracking of vortex evolution from Large Eddy Simulation (LES) data is a complex and computationally intensive problem. The vortex tracking requires the analysis of very large three-dimensional and time-varying datasets. The complexity of the problem is further compounded by the fact that these vortices are embedded in a background turbulence field, and they may interact with the ground surface. Another level of complication can arise, if vortices from multiple aircrafts are simulated. This paper presents a new technique for post-processing LES data to obtain wake vortex tracks and wake intensities. The new approach isolates vortices by defining "regions of interest" (ROI) around each vortex and has the ability to identify vortex pairs from multiple aircraft. The paper describes the new methodology for tracking wake vortices and presents application of the technique for single and multiple aircraft.

Better Informing Decision Making with Multiple Outcomes Cost-Effectiveness Analysis under Uncertainty in Cost-Disutility Space

PubMed Central

McCaffrey, Nikki; Agar, Meera; Harlum, Janeane; Karnon, Jonathon; Currow, David; Eckermann, Simon

2015-01-01

Introduction Comparing multiple, diverse outcomes with cost-effectiveness analysis (CEA) is important, yet challenging in areas like palliative care where domains are unamenable to integration with survival. Generic multi-attribute utility values exclude important domains and non-health outcomes, while partial analyses—where outcomes are considered separately, with their joint relationship under uncertainty ignored—lead to incorrect inference regarding preferred strategies. Objective The objective of this paper is to consider whether such decision making can be better informed with alternative presentation and summary measures, extending methods previously shown to have advantages in multiple strategy comparison. Methods Multiple outcomes CEA of a home-based palliative care model (PEACH) relative to usual care is undertaken in cost disutility (CDU) space and compared with analysis on the cost-effectiveness plane. Summary measures developed for comparing strategies across potential threshold values for multiple outcomes include: expected net loss (ENL) planes quantifying differences in expected net benefit; the ENL contour identifying preferred strategies minimising ENL and their expected value of perfect information; and cost-effectiveness acceptability planes showing probability of strategies minimising ENL. Results Conventional analysis suggests PEACH is cost-effective when the threshold value per additional day at home ( 1) exceeds $1,068 or dominated by usual care when only the proportion of home deaths is considered. In contrast, neither alternative dominate in CDU space where cost and outcomes are jointly considered, with the optimal strategy depending on threshold values. For example, PEACH minimises ENL when 1=$2,000 and 2=$2,000 (threshold value for dying at home), with a 51.6% chance of PEACH being cost-effective. Conclusion Comparison in CDU space and associated summary measures have distinct advantages to multiple domain comparisons, aiding transparent and robust joint comparison of costs and multiple effects under uncertainty across potential threshold values for effect, better informing net benefit assessment and related reimbursement and research decisions. PMID:25751629

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

DAMe: a toolkit for the initial processing of datasets with PCR replicates of double-tagged amplicons for DNA metabarcoding analyses.

PubMed

Zepeda-Mendoza, Marie Lisandra; Bohmann, Kristine; Carmona Baez, Aldo; Gilbert, M Thomas P

2016-05-03

DNA metabarcoding is an approach for identifying multiple taxa in an environmental sample using specific genetic loci and taxa-specific primers. When combined with high-throughput sequencing it enables the taxonomic characterization of large numbers of samples in a relatively time- and cost-efficient manner. One recent laboratory development is the addition of 5'-nucleotide tags to both primers producing double-tagged amplicons and the use of multiple PCR replicates to filter erroneous sequences. However, there is currently no available toolkit for the straightforward analysis of datasets produced in this way. We present DAMe, a toolkit for the processing of datasets generated by double-tagged amplicons from multiple PCR replicates derived from an unlimited number of samples. Specifically, DAMe can be used to (i) sort amplicons by tag combination, (ii) evaluate PCR replicates dissimilarity, and (iii) filter sequences derived from sequencing/PCR errors, chimeras, and contamination. This is attained by calculating the following parameters: (i) sequence content similarity between the PCR replicates from each sample, (ii) reproducibility of each unique sequence across the PCR replicates, and (iii) copy number of the unique sequences in each PCR replicate. We showcase the insights that can be obtained using DAMe prior to taxonomic assignment, by applying it to two real datasets that vary in their complexity regarding number of samples, sequencing libraries, PCR replicates, and used tag combinations. Finally, we use a third mock dataset to demonstrate the impact and importance of filtering the sequences with DAMe. DAMe allows the user-friendly manipulation of amplicons derived from multiple samples with PCR replicates built in a single or multiple sequencing libraries. It allows the user to: (i) collapse amplicons into unique sequences and sort them by tag combination while retaining the sample identifier and copy number information, (ii) identify sequences carrying unused tag combinations, (iii) evaluate the comparability of PCR replicates of the same sample, and (iv) filter tagged amplicons from a number of PCR replicates using parameters of minimum length, copy number, and reproducibility across the PCR replicates. This enables an efficient analysis of complex datasets, and ultimately increases the ease of handling datasets from large-scale studies.

Fast discovery and visualization of conserved regions in DNA sequences using quasi-alignment

PubMed Central

2013-01-01

Background Next Generation Sequencing techniques are producing enormous amounts of biological sequence data and analysis becomes a major computational problem. Currently, most analysis, especially the identification of conserved regions, relies heavily on Multiple Sequence Alignment and its various heuristics such as progressive alignment, whose run time grows with the square of the number and the length of the aligned sequences and requires significant computational resources. In this work, we present a method to efficiently discover regions of high similarity across multiple sequences without performing expensive sequence alignment. The method is based on approximating edit distance between segments of sequences using p-mer frequency counts. Then, efficient high-throughput data stream clustering is used to group highly similar segments into so called quasi-alignments. Quasi-alignments have numerous applications such as identifying species and their taxonomic class from sequences, comparing sequences for similarities, and, as in this paper, discovering conserved regions across related sequences. Results In this paper, we show that quasi-alignments can be used to discover highly similar segments across multiple sequences from related or different genomes efficiently and accurately. Experiments on a large number of unaligned 16S rRNA sequences obtained from the Greengenes database show that the method is able to identify conserved regions which agree with known hypervariable regions in 16S rRNA. Furthermore, the experiments show that the proposed method scales well for large data sets with a run time that grows only linearly with the number and length of sequences, whereas for existing multiple sequence alignment heuristics the run time grows super-linearly. Conclusion Quasi-alignment-based algorithms can detect highly similar regions and conserved areas across multiple sequences. Since the run time is linear and the sequences are converted into a compact clustering model, we are able to identify conserved regions fast or even interactively using a standard PC. Our method has many potential applications such as finding characteristic signature sequences for families of organisms and studying conserved and variable regions in, for example, 16S rRNA. PMID:24564200

Fast discovery and visualization of conserved regions in DNA sequences using quasi-alignment.

PubMed

Nagar, Anurag; Hahsler, Michael

2013-01-01

Next Generation Sequencing techniques are producing enormous amounts of biological sequence data and analysis becomes a major computational problem. Currently, most analysis, especially the identification of conserved regions, relies heavily on Multiple Sequence Alignment and its various heuristics such as progressive alignment, whose run time grows with the square of the number and the length of the aligned sequences and requires significant computational resources. In this work, we present a method to efficiently discover regions of high similarity across multiple sequences without performing expensive sequence alignment. The method is based on approximating edit distance between segments of sequences using p-mer frequency counts. Then, efficient high-throughput data stream clustering is used to group highly similar segments into so called quasi-alignments. Quasi-alignments have numerous applications such as identifying species and their taxonomic class from sequences, comparing sequences for similarities, and, as in this paper, discovering conserved regions across related sequences. In this paper, we show that quasi-alignments can be used to discover highly similar segments across multiple sequences from related or different genomes efficiently and accurately. Experiments on a large number of unaligned 16S rRNA sequences obtained from the Greengenes database show that the method is able to identify conserved regions which agree with known hypervariable regions in 16S rRNA. Furthermore, the experiments show that the proposed method scales well for large data sets with a run time that grows only linearly with the number and length of sequences, whereas for existing multiple sequence alignment heuristics the run time grows super-linearly. Quasi-alignment-based algorithms can detect highly similar regions and conserved areas across multiple sequences. Since the run time is linear and the sequences are converted into a compact clustering model, we are able to identify conserved regions fast or even interactively using a standard PC. Our method has many potential applications such as finding characteristic signature sequences for families of organisms and studying conserved and variable regions in, for example, 16S rRNA.

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

Fingerprint Analysis: Moving Toward Multiattribute Determination via Individual Markers.

PubMed

Brunelle, Erica; Huynh, Crystal; Alin, Eden; Eldridge, Morgan; Le, Anh Minh; Halámková, Lenka; Halámek, Jan

2018-01-02

Forensic science will be forever revolutionized if law enforcement can identify personal attributes of a person of interest solely from a fingerprint. For the past 2 years, the goal of our group has been to establish a way to identify originator attributes, specifically biological sex, from a single analyte. To date, an enzymatic assay and two chemical assays have been developed for the analysis of multiple analytes. In this manuscript, two additional assays have been developed. This time, however, the assays utilize only one amino acid each. The enzymatic assay targets alanine and employs alanine transaminase (ALT), pyruvate oxidase (POx), and horseradish peroxidase (HRP). The other, a chemical assay, is known as the Sakaguchi test and targets arginine. It is important to note that alanine has a significantly higher concentration than arginine in the fingerprint content of both males and females. Both assays proved to be capable of accurately differentiating between male and female fingerprints, regardless of their respective average concentration. The ability to target a single analyte will transform forensic science as each originator attribute can be correlated to a different analyte. This would then lead to the possibility of identifying multiple attributes from a single fingerprint sample. Ultimately, this would allow for a profile of a person of interest to be established without the need for time-consuming lab processes.

Memory training interventions for older adults: A meta-analysis

PubMed Central

Gross, Alden L.; Parisi, Jeanine M.; Spira, Adam P.; Kueider, Alexandra M.; Ko, Jean Y.; Saczynski, Jane S.; Samus, Quincy M.; Rebok, George W.

2012-01-01

A systematic review and meta-analysis of memory training research was conducted to characterize the effect of memory strategies on memory performance among cognitively intact, community-dwelling older adults, and to identify characteristics of individuals and of programs associated with improved memory. The review identified 402 publications, of which 35 studies met criteria for inclusion. The overall effect size estimate, representing the mean standardized difference in pre-post change between memory-trained and control groups, was 0.31 standard deviations (SD; 95% confidence interval (CI): 0.22, 0.39). The pre-post training effect for memory-trained interventions was 0.43 SD (95% CI: 0.29, 0.57) and the practice effect for control groups was 0.06 SD (95% CI: -0.05, 0.16). Among 10 distinct memory strategies identified in studies, meta-analytic methods revealed that training multiple strategies was associated with larger training gains (p=0.04), although this association did not reach statistical significance after adjusting for multiple comparisons. Treatment gains among memory-trained individuals were not better after training in any particular strategy, or by the average age of participants, session length, or type of control condition. These findings can inform the design of future memory training programs for older adults. PMID:22423647

Fall-related self-efficacy, not balance and mobility performance, is related to accidental falls in chronic stroke survivors with low bone mineral density

PubMed Central

Pang, Marco Y.C.; Eng, Janice J.

2011-01-01

Introduction Chronic stroke survivors with low bone mineral density (BMD) are particularly prone to fragility fractures. The purpose of this study was to identify the determinants of balance, mobility and falls in this sub-group of stroke patients. Methods Thirty nine chronic stroke survivors with low hip BMD (T-score <-1.0) were studied. Each subject was evaluated for: balance, mobility, leg muscle strength, spasticity, and falls-related self-efficacy. Any falls in the past 12 months were also recorded. Multiple regression analysis was used to identify the determinants of balance and mobility performance whereas logistic regression was used to identify the determinants of falls. Results Multiple regression analysis revealed that after adjusting for basic demographics, falls-related self-efficacy remained independently associated with balance/mobility performance (R2=0.494, P<0.001). Logistic regression showed that falls-related self-efficacy, but not balance and mobility performance, was a significant determinant of falls (odds ratio: 0.18, P=0.04). Conclusions Falls-related self-efficacy, but not mobility and balance performance, was the most important determinant of accidental falls. This psychological factor should not be overlooked in the prevention of fragility fractures among chronic stroke survivors with low hip BMD. PMID:18097709

Genetic analysis of a Chinese family with members affected with Usher syndrome type II and Waardenburg syndrome type IV.

PubMed

Wang, Xueling; Lin, Xiao-Jiang; Tang, Xiangrong; Chai, Yong-Chuan; Yu, De-Hong; Chen, Dong-Ye; Wu, Hao

2017-11-01

The purpose of this study was to identify the genetic causes of a family presenting with multiple symptoms overlapping Usher syndrome type II (USH2) and Waardenburg syndrome type IV (WS4). Targeted next-generation sequencing including the exon and flanking intron sequences of 79 deafness genes was performed on the proband. Co-segregation of the disease phenotype and the detected variants were confirmed in all family members by PCR amplification and Sanger sequencing. The affected members of this family had two different recessive disorders, USH2 and WS4. By targeted next-generation sequencing, we identified that USH2 was caused by a novel missense mutation, p.V4907D in GPR98; whereas WS4 due to p.V185M in EDNRB. This is the first report of homozygous p.V185M mutation in EDNRB in patient with WS4. This study reported a Chinese family with multiple independent and overlapping phenotypes. In condition, molecular level analysis was efficient to identify the causative variant p.V4907D in GPR98 and p.V185M in EDNRB, also was helpful to confirm the clinical diagnosis of USH2 and WS4. Copyright © 2017 Elsevier B.V. All rights reserved.

A latent class analysis of poly-marijuana use among young adults.

PubMed

Krauss, Melissa J; Rajbhandari, Biva; Sowles, Shaina J; Spitznagel, Edward L; Cavazos-Rehg, Patricia

2017-12-01

With more states legalizing marijuana use, the marijuana industry has grown, introducing a variety of marijuana products. Our study explores the use of multiple marijuana products (poly-marijuana use) and the characteristics associated with this behavior. Past-month marijuana users aged 18-34years were surveyed online via an existing online panel (n=2444). Participants answered questions about past-month use of three types of marijuana (plant-based, concentrates, edibles), marijuana use patterns, and driving after use. Latent class analysis was used to identify subgroups of marijuana users. Four classes of marijuana users were identified: Light plant users, who used only plant-based products infrequently and were unlikely to drive after use (32%); Heavy plant users, who used mainly plant-based products frequently, multiple times per day, and were likely to drive after use (37%); Plant and concentrates users, who used plant-based products heavily and concentrates at least infrequently, used multiple times per day, and were likely to drive after use (20%); Light plant and edibles users, who used both products infrequently and were unlikely to drive after use (10%). Those in legal marijuana states were more likely to belong to the poly-marijuana groups. Our findings reflect the increase in popularity of new marijuana products in legal states and suggest that heavy user groups, including concentrates users, are associated with driving after use. As various forms of marijuana use increases, monitoring and surveillance of the use of multiple types of marijuana will be important for determining potential varying impacts on physiological and social consequences. Copyright © 2017 Elsevier Ltd. All rights reserved.

Note-Taking Interventions for College Students: A Synthesis and Meta-Analysis of the Literature

ERIC Educational Resources Information Center

Reed, Deborah K.; Rimel, Hillary; Hallett, Abigail

2016-01-01

Although note taking is frequently described as an important skill for postsecondary success, there have been few note-taking intervention studies involving multiple sessions spanning more than one week. In a systematic search, we identified seven peer-reviewed articles reporting 10 intervention studies published from 1990-2014. The only…

CBCL Pediatric Bipolar Disorder Profile and ADHD: Comorbidity and Quantitative Trait Loci Analysis

ERIC Educational Resources Information Center

McGough, James J.; Loo, Sandra K.; McCracken, James T.; Dang, Jeffery; Clark, Shaunna; Nelson, Stanley F.; Smalley, Susan L.

2008-01-01

The pediatric bipolar disorder profile of the Child Behavior checklist is used to differentiate patterns of comorbidity and to search for quantitative trait loci in multiple affected ADHD sibling pairs. The CBCL-PBD profiling identified 8 percent of individuals with severe psychopathology and increased rates of oppositional defiant, conduct and…

An Analysis of Gendered Attitudes and Responses to Employability Training

ERIC Educational Resources Information Center

Willott, John; Stevenson, Jacqueline

2006-01-01

Training programmes for unemployed people are often designed to meet the identified vocational skill needs of businesses. We describe research across a number of projects in Leeds (United Kingdom) providing training to unemployed and marginalised adults. The focus was on those with multiple barriers to accessing and sustaining training and…

The Latent Classes of Subclinical ADHD Symptoms: Convergences of Multiple Informant Reports

ERIC Educational Resources Information Center

Kobor, Andrea; Takacs, Adam; Urban, Robert; Csepe, Valeria

2012-01-01

The purpose of the present study was to conduct latent class analysis on the Hyperactivity scale of the Strengths and Difficulties Questionnaire in order to identify distinct subgroups of subclinical ADHD in a multi-informant framework. We hypothesized a similar structure between teachers and parents, and differences in symptom severity across…

Introgression of chromosome segments from multiple alien species in wheat breeding lines with wheat streak mosaic virus resistance

USDA-ARS?s Scientific Manuscript database

Pyramiding of alien-derived Wheat streak mosaic virus (WSMV) resistance and resistance enhancing genes in wheat is a costeffective and environmentally safe strategy for disease control. PCR-based markers and cytogenetic analysis with genomic in situ hybridisation were applied to identify alien chrom...

Analysis of Objective Factors Related to a Successful Outcome on the National Examination for Occupational Therapists

ERIC Educational Resources Information Center

Zadnik, Mary; Lawson, Sonia; DeLany, Janet V.; Parente, Frederick; Archer, Kristin R.

2017-01-01

Purpose: To identify academic and demographic variables related to a successful outcome on the national certification exam for occupational therapists (National Board for Certification in Occupational Therapy [NBCOT] exam) at one academic institution with the expectation that it could be replicated with multiple institutions. Method: Binary…

To Dream the Impossible Dream: College Graduation in Four Years

ERIC Educational Resources Information Center

Raikes, Mark H.; Berling, Victoria L.; Davis, Jody M.

2012-01-01

The cost of higher education continues to climb, while calls for increased institutional accountability and the value of a "four-year degree" are ever present. This research sought to identify factors by which consumers might predict four-year graduation rates at institutions within the CCCU. A hierarchical multiple regression analysis of data…

Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer. | Office of Cancer Genomics

Cancer.gov

We report a comprehensive analysis of 412 muscle-invasive bladder cancers characterized by multiple TCGA analytical platforms. Fifty-eight genes were significantly mutated, and the overall mutational load was associated with APOBEC-signature mutagenesis. Clustering by mutation signature identified a high-mutation subset with 75% 5-year survival.

Exploring Teacher Leadership in a Rural, Secondary School: Reciprocal Learning Teams as a Catalyst for Emergent Leadership

ERIC Educational Resources Information Center

Cherkowski, Sabre; Schnellert, Leyton

2017-01-01

The purpose of this case study was to examine how teachers experienced professional development as collaborative inquiry, and how their experiences contributed to their development as teacher leaders. Three overarching themes were identified through iterative qualitative analysis of multiple data sources including interviews, observations,…

Multiple Mediation Analysis of the Relationship between Rapid Naming and Reading

ERIC Educational Resources Information Center

Poulsen, Mads; Juul, Holger; Elbro, Carsten

2015-01-01

It is well established that rapid automatised naming (RAN) correlates with reading ability. Despite several attempts, no single component process (mediator) has been identified that fully accounts for the correlation. The present paper estimated the explanatory value of several mediators for the RAN--reading correlation. One hundred and sixty-nine…

Instructional Leadership of High School Assistant Principals in Northern California

ERIC Educational Resources Information Center

Garrard, John Christian Timothy

2013-01-01

To identify how high school assistant principals in large suburban schools serve as instructional leaders and how they develop these skills, this research utilized a multiple-case study design, followed by a cross-case analysis of the data. This research explores the instructional leadership of three female comprehensive high school assistant…

[Keys to preventing accidents in children in the school context].

PubMed

Gabari Gambarte, M Inés; Sáenz Mendía, Raquel

2016-11-02

To learn about children's perception of the causes and prevention strategies involved in school accidents. The sample included 584 school children aged 8-9 years from Navarra. A mixed design was chosen by questionnaire with three open-response questions and one multiple-choice assessment. Analysis was performed in two phases: 1) qualitative development of categories and dimensions of the responses of narrative content, and 2) quantitative variables for recoding correlational analysis. 22 categories emerged, which make up three perceptual dimensions: 1) attribution of causality (5), 2) identification of mechanisms of avoidance (11), and 3) development of coping strategies (6). The correlation intra-variables portray varying degrees: on the one hand, moderate positive numbers (r>0.5) in allocating and identifying causality avoidance mechanisms and, on the other hand, high positive correlation values (r>0.7) referred to developing coping strategies. Children are able to identify accidents as a health problem. They question the multiplicity of elements involved and relate the origin and kind of accident to prevention and support mechanisms. Copyright © 2016 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

Genome-Wide Analysis of Polymorphisms Associated with Cytokine Responses in Smallpox Vaccine Recipients

PubMed Central

Kennedy, Richard B.; Ovsyannikova, Inna G.; Pankratz, V. Shane; Haralambieva, Iana H.; Vierkant, Robert A.; Poland, Gregory A.

2014-01-01

The role that genetics plays in response to infection or disease is becoming increasingly clear as we learn more about immunogenetics and host-pathogen interactions. Here we report a genome-wide analysis of the effects of host genetic variation on cytokine responses to vaccinia virus stimulation in smallpox vaccine recipients. Our data show that vaccinia stimulation of immune individuals results in secretion of inflammatory and Th1 cytokines. We identified multiple SNPs significantly associated with variations in cytokine secretion. These SNPs are found in genes with known immune function, as well as in genes encoding for proteins involved in signal transduction, cytoskeleton, membrane channels and ion transport, as well as others with no previously identified connection to immune responses. The large number of significant SNP associations implies that cytokine secretion in response to vaccinia virus is a complex process controlled by multiple genes and gene families. Follow-up studies to replicate these findings and then pursue mechanistic studies will provide a greater understanding of how genetic variation influences vaccine responses. PMID:22610502

Discovering communicative competencies in a nonspeaking child with autism.

PubMed

Stiegler, Lillian N

2007-10-01

This article is intended to demonstrate that adapted conversation analysis (CA) and speech act analysis (SAA) may be applied by speech-language pathologists (SLPs) to (a) identify communicative competencies in nonspeaking children with autism spectrum disorder (ASD), especially during particularly successful interactions, and (b) identify communicative patterns that are exhibited by interventionists and communication partners that may positively or negatively impact interactions with such children. A case example involving an 8-year-old boy with autism and the author, an SLP, is explicated. A videotaped segment from an intervention session was transcribed and subjected to adapted forms of CA and SAA. CA and SAA helped reveal several underlying competencies in the boy's communicative output, including an awareness of conversational structure and sequence, diversity of communicative acts, functional use of gaze and smile behavior, and the ability to spontaneously initiate interactions. Observations regarding the SLP's interactive style included the use of multiple instances of "asking" as well as multiple "derailments" of the boy's obvious communicative bids. CA and SAA may be adapted to gain a clearer picture of what takes place during especially positive communicative interactions with nonspeaking children with ASD.

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.

Damage detection of structures identified with deterministic-stochastic models using seismic data.

PubMed

Huang, Ming-Chih; Wang, Yen-Po; Chang, Ming-Lian

2014-01-01

A deterministic-stochastic subspace identification method is adopted and experimentally verified in this study to identify the equivalent single-input-multiple-output system parameters of the discrete-time state equation. The method of damage locating vector (DLV) is then considered for damage detection. A series of shaking table tests using a five-storey steel frame has been conducted. Both single and multiple damage conditions at various locations have been considered. In the system identification analysis, either full or partial observation conditions have been taken into account. It has been shown that the damaged stories can be identified from global responses of the structure to earthquakes if sufficiently observed. In addition to detecting damage(s) with respect to the intact structure, identification of new or extended damages of the as-damaged counterpart has also been studied. This study gives further insights into the scheme in terms of effectiveness, robustness, and limitation for damage localization of frame systems.

A new multiple regression model to identify multi-family houses with a high prevalence of sick building symptoms "SBS", within the healthy sustainable house study in Stockholm (3H).

PubMed

Engvall, Karin; Hult, M; Corner, R; Lampa, E; Norbäck, D; Emenius, G

2010-01-01

The aim was to develop a new model to identify residential buildings with higher frequencies of "SBS" than expected, "risk buildings". In 2005, 481 multi-family buildings with 10,506 dwellings in Stockholm were studied by a new stratified random sampling. A standardised self-administered questionnaire was used to assess "SBS", atopy and personal factors. The response rate was 73%. Statistical analysis was performed by multiple logistic regressions. Dwellers owning their building reported less "SBS" than those renting. There was a strong relationship between socio-economic factors and ownership. The regression model, ended up with high explanatory values for age, gender, atopy and ownership. Applying our model, 9% of all residential buildings in Stockholm were classified as "risk buildings" with the highest proportion in houses built 1961-1975 (26%) and lowest in houses built 1985-1990 (4%). To identify "risk buildings", it is necessary to adjust for ownership and population characteristics.

WebMOTIFS: automated discovery, filtering and scoring of DNA sequence motifs using multiple programs and Bayesian approaches

PubMed Central

Romer, Katherine A.; Kayombya, Guy-Richard; Fraenkel, Ernest

2007-01-01

WebMOTIFS provides a web interface that facilitates the discovery and analysis of DNA-sequence motifs. Several studies have shown that the accuracy of motif discovery can be significantly improved by using multiple de novo motif discovery programs and using randomized control calculations to identify the most significant motifs or by using Bayesian approaches. WebMOTIFS makes it easy to apply these strategies. Using a single submission form, users can run several motif discovery programs and score, cluster and visualize the results. In addition, the Bayesian motif discovery program THEME can be used to determine the class of transcription factors that is most likely to regulate a set of sequences. Input can be provided as a list of gene or probe identifiers. Used with the default settings, WebMOTIFS accurately identifies biologically relevant motifs from diverse data in several species. WebMOTIFS is freely available at http://fraenkel.mit.edu/webmotifs. PMID:17584794

High-Throughput Analysis of Promoter Occupancy Reveals New Targets for Arx, a Gene Mutated in Mental Retardation and Interneuronopathies

PubMed Central

Quillé, Marie-Lise; Hirchaud, Edouard; Baron, Daniel; Benech, Caroline; Guihot, Jeanne; Placet, Morgane; Mignen, Olivier; Férec, Claude; Houlgatte, Rémi; Friocourt, Gaëlle

2011-01-01

Genetic investigations of X-linked intellectual disabilities have implicated the ARX (Aristaless-related homeobox) gene in a wide spectrum of disorders extending from phenotypes characterised by severe neuronal migration defects such as lissencephaly, to mild or moderate forms of mental retardation without apparent brain abnormalities but with associated features of dystonia and epilepsy. Analysis of Arx spatio-temporal localisation profile in mouse revealed expression in telencephalic structures, mainly restricted to populations of GABAergic neurons at all stages of development. Furthermore, studies of the effects of ARX loss of function in humans and animal models revealed varying defects, suggesting multiple roles of this gene during brain development. However, to date, little is known about how ARX functions as a transcription factor and the nature of its targets. To better understand its role, we combined chromatin immunoprecipitation and mRNA expression with microarray analysis and identified a total of 1006 gene promoters bound by Arx in transfected neuroblastoma (N2a) cells and in mouse embryonic brain. Approximately 24% of Arx-bound genes were found to show expression changes following Arx overexpression or knock-down. Several of the Arx target genes we identified are known to be important for a variety of functions in brain development and some of them suggest new functions for Arx. Overall, these results identified multiple new candidate targets for Arx and should help to better understand the pathophysiological mechanisms of intellectual disability and epilepsy associated with ARX mutations. PMID:21966449

Using Discursis to enhance the qualitative analysis of hospital pharmacist-patient interactions

PubMed Central

Barras, Michael A.; Angus, Daniel J.

2018-01-01

Introduction Pharmacist-patient communication during medication counselling has been successfully investigated using Communication Accommodation Theory (CAT). Communication researchers in other healthcare professions have utilised Discursis software as an adjunct to their manual qualitative analysis processes. Discursis provides a visual, chronological representation of communication exchanges and identifies patterns of interactant engagement. Aim The aim of this study was to describe how Discursis software was used to enhance previously conducted qualitative analysis of pharmacist-patient interactions (by visualising pharmacist-patient speech patterns, episodes of engagement, and identifying CAT strategies employed by pharmacists within these episodes). Methods Visual plots from 48 transcribed audio recordings of pharmacist-patient exchanges were generated by Discursis. Representative plots were selected to show moderate-high and low- level speaker engagement. Details of engagement were investigated for pharmacist application of CAT strategies (approximation, interpretability, discourse management, emotional expression, and interpersonal control). Results Discursis plots allowed for identification of distinct patterns occurring within pharmacist-patient exchanges. Moderate-high pharmacist-patient engagement was characterised by multiple off-diagonal squares while alternating single coloured squares depicted low engagement. Engagement episodes were associated with multiple CAT strategies such as discourse management (open-ended questions). Patterns reflecting pharmacist or patient speaker dominance were dependant on clinical setting. Discussion and conclusions Discursis analysis of pharmacist-patient interactions, a novel application of the technology in health communication, was found to be an effective visualisation tool to pin-point episodes for CAT analysis. Discursis has numerous practical and theoretical applications for future health communication research and training. Researchers can use the software to support qualitative analysis where large data sets can be quickly reviewed to identify key areas for concentrated analysis. Because Discursis plots are easily generated from audio recorded transcripts, they are conducive as teaching tools for both students and practitioners to assess and develop their communication skills. PMID:29787568

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

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

Borek, Dominika; Bromberg, Raquel; Hattne, Johan

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

The indirect costs of multiple sclerosis: systematic review and meta-analysis.

PubMed

Stawowczyk, Ewa; Malinowski, Krzysztof Piotr; Kawalec, Paweł; Moćko, Paweł

2015-01-01

The aim of this systematic review is to collect and summarize all current data on the indirect costs related to absenteeism and presenteeism associated with multiple sclerosis. Searches were conducted using Medline, Embase and Centre for Reviews and Dissemination databases. All collected costs were recalculated to average annual cost per patient, expressed in 2014 prices US$ using the consumer price index and purchasing power parity (scenario 1) and expressed as proportion of specific gross domestic product in current local currency unit to adjust for country's development (scenario 2). Identified studies were then analyzed in order to assess their possible inclusion in the meta-analysis. The authors identified 63 records, of which 23 were eligible for meta-analysis. Overall indirect cost per patient calculated in scenario 1 was as high as US$20,167 with US$22,197 in Europe, US$17,382 in North America and US$153 in Asia. Overall indirect cost per patient calculated in scenario 2 was equal to US$16,939, with US$19,612 in Europe, US$11,592 in North America and US$899 in Asia. Overall indirect costs varied from US$3726 for patients with EDSS score less than 3 to US$19,264 for patients with Expanded Disability Status Scale score grater that 7. This review revealed the great economic burden of multiple sclerosis on society. The authors observed a great variety of the considered components of indirect costs and their definitions. Costs were higher for Europe than for other continents and were also higher for patients with a higher Expanded Disability Status Scale score.

Automated detection of inaccurate and imprecise transitions in peptide quantification by multiple reaction monitoring mass spectrometry.

PubMed

Abbatiello, Susan E; Mani, D R; Keshishian, Hasmik; Carr, Steven A

2010-02-01

Multiple reaction monitoring mass spectrometry (MRM-MS) of peptides with stable isotope-labeled internal standards (SISs) is increasingly being used to develop quantitative assays for proteins in complex biological matrices. These assays can be highly precise and quantitative, but the frequent occurrence of interferences requires that MRM-MS data be manually reviewed, a time-intensive process subject to human error. We developed an algorithm that identifies inaccurate transition data based on the presence of interfering signal or inconsistent recovery among replicate samples. The algorithm objectively evaluates MRM-MS data with 2 orthogonal approaches. First, it compares the relative product ion intensities of the analyte peptide to those of the SIS peptide and uses a t-test to determine if they are significantly different. A CV is then calculated from the ratio of the analyte peak area to the SIS peak area from the sample replicates. The algorithm identified problematic transitions and achieved accuracies of 94%-100%, with a sensitivity and specificity of 83%-100% for correct identification of errant transitions. The algorithm was robust when challenged with multiple types of interferences and problematic transitions. This algorithm for automated detection of inaccurate and imprecise transitions (AuDIT) in MRM-MS data reduces the time required for manual and subjective inspection of data, improves the overall accuracy of data analysis, and is easily implemented into the standard data-analysis work flow. AuDIT currently works with results exported from MRM-MS data-processing software packages and may be implemented as an analysis tool within such software.

DNA methylome signature in rheumatoid arthritis.

PubMed

Nakano, Kazuhisa; Whitaker, John W; Boyle, David L; Wang, Wei; Firestein, Gary S

2013-01-01

Epigenetics can influence disease susceptibility and severity. While DNA methylation of individual genes has been explored in autoimmunity, no unbiased systematic analyses have been reported. Therefore, a genome-wide evaluation of DNA methylation loci in fibroblast-like synoviocytes (FLS) isolated from the site of disease in rheumatoid arthritis (RA) was performed. Genomic DNA was isolated from six RA and five osteoarthritis (OA) FLS lines and evaluated using the Illumina HumanMethylation450 chip. Cluster analysis of data was performed and corrected using Benjamini-Hochberg adjustment for multiple comparisons. Methylation was confirmed by pyrosequencing and gene expression was determined by qPCR. Pathway analysis was performed using the Kyoto Encyclopedia of Genes and Genomes. RA and control FLS segregated based on DNA methylation, with 1859 differentially methylated loci. Hypomethylated loci were identified in key genes relevant to RA, such as CHI3L1, CASP1, STAT3, MAP3K5, MEFV and WISP3. Hypermethylation was also observed, including TGFBR2 and FOXO1. Hypomethylation of individual genes was associated with increased gene expression. Grouped analysis identified 207 hypermethylated or hypomethylated genes with multiple differentially methylated loci, including COL1A1, MEFV and TNF. Hypomethylation was increased in multiple pathways related to cell migration, including focal adhesion, cell adhesion, transendothelial migration and extracellular matrix interactions. Confirmatory studies with OA and normal FLS also demonstrated segregation of RA from control FLS based on methylation pattern. Differentially methylated genes could alter FLS gene expression and contribute to the pathogenesis of RA. DNA methylation of critical genes suggests that RA FLS are imprinted and implicate epigenetic contributions to inflammatory arthritis.

Automated Detection of Inaccurate and Imprecise Transitions in Peptide Quantification by Multiple Reaction Monitoring Mass Spectrometry

PubMed Central

Abbatiello, Susan E.; Mani, D. R.; Keshishian, Hasmik; Carr, Steven A.

2010-01-01

BACKGROUND Multiple reaction monitoring mass spectrometry (MRM-MS) of peptides with stable isotope–labeled internal standards (SISs) is increasingly being used to develop quantitative assays for proteins in complex biological matrices. These assays can be highly precise and quantitative, but the frequent occurrence of interferences requires that MRM-MS data be manually reviewed, a time-intensive process subject to human error. We developed an algorithm that identifies inaccurate transition data based on the presence of interfering signal or inconsistent recovery among replicate samples. METHODS The algorithm objectively evaluates MRM-MS data with 2 orthogonal approaches. First, it compares the relative product ion intensities of the analyte peptide to those of the SIS peptide and uses a t-test to determine if they are significantly different. A CV is then calculated from the ratio of the analyte peak area to the SIS peak area from the sample replicates. RESULTS The algorithm identified problematic transitions and achieved accuracies of 94%–100%, with a sensitivity and specificity of 83%–100% for correct identification of errant transitions. The algorithm was robust when challenged with multiple types of interferences and problematic transitions. CONCLUSIONS This algorithm for automated detection of inaccurate and imprecise transitions (AuDIT) in MRM-MS data reduces the time required for manual and subjective inspection of data, improves the overall accuracy of data analysis, and is easily implemented into the standard data-analysis work flow. AuDIT currently works with results exported from MRM-MS data-processing software packages and may be implemented as an analysis tool within such software. PMID:20022980

The OncoArray Consortium: A Network for Understanding the Genetic Architecture of Common Cancers.

PubMed

Amos, Christopher I; Dennis, Joe; Wang, Zhaoming; Byun, Jinyoung; Schumacher, Fredrick R; Gayther, Simon A; Casey, Graham; Hunter, David J; Sellers, Thomas A; Gruber, Stephen B; Dunning, Alison M; Michailidou, Kyriaki; Fachal, Laura; Doheny, Kimberly; Spurdle, Amanda B; Li, Yafang; Xiao, Xiangjun; Romm, Jane; Pugh, Elizabeth; Coetzee, Gerhard A; Hazelett, Dennis J; Bojesen, Stig E; Caga-Anan, Charlisse; Haiman, Christopher A; Kamal, Ahsan; Luccarini, Craig; Tessier, Daniel; Vincent, Daniel; Bacot, François; Van Den Berg, David J; Nelson, Stefanie; Demetriades, Stephen; Goldgar, David E; Couch, Fergus J; Forman, Judith L; Giles, Graham G; Conti, David V; Bickeböller, Heike; Risch, Angela; Waldenberger, Melanie; Brüske-Hohlfeld, Irene; Hicks, Belynda D; Ling, Hua; McGuffog, Lesley; Lee, Andrew; Kuchenbaecker, Karoline; Soucy, Penny; Manz, Judith; Cunningham, Julie M; Butterbach, Katja; Kote-Jarai, Zsofia; Kraft, Peter; FitzGerald, Liesel; Lindström, Sara; Adams, Marcia; McKay, James D; Phelan, Catherine M; Benlloch, Sara; Kelemen, Linda E; Brennan, Paul; Riggan, Marjorie; O'Mara, Tracy A; Shen, Hongbing; Shi, Yongyong; Thompson, Deborah J; Goodman, Marc T; Nielsen, Sune F; Berchuck, Andrew; Laboissiere, Sylvie; Schmit, Stephanie L; Shelford, Tameka; Edlund, Christopher K; Taylor, Jack A; Field, John K; Park, Sue K; Offit, Kenneth; Thomassen, Mads; Schmutzler, Rita; Ottini, Laura; Hung, Rayjean J; Marchini, Jonathan; Amin Al Olama, Ali; Peters, Ulrike; Eeles, Rosalind A; Seldin, Michael F; Gillanders, Elizabeth; Seminara, Daniela; Antoniou, Antonis C; Pharoah, Paul D P; Chenevix-Trench, Georgia; Chanock, Stephen J; Simard, Jacques; Easton, Douglas F

2017-01-01

Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers, and cancer-related traits. The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers, and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background. The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis. Results from these analyses will enable researchers to identify new susceptibility loci, perform fine-mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental, and lifestyle-related exposures. Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. Cancer Epidemiol Biomarkers Prev; 26(1); 126-35. ©2016 AACR. ©2016 American Association for Cancer Research.

The OncoArray Consortium: a Network for Understanding the Genetic Architecture of Common Cancers

PubMed Central

Amos, Christopher I.; Dennis, Joe; Wang, Zhaoming; Byun, Jinyoung; Schumacher, Fredrick R.; Gayther, Simon A.; Casey, Graham; Hunter, David J.; Sellers, Thomas A.; Gruber, Stephen B.; Dunning, Alison M.; Michailidou, Kyriaki; Fachal, Laura; Doheny, Kimberly; Spurdle, Amanda B.; Li, Yafang; Xiao, Xiangjun; Romm, Jane; Pugh, Elizabeth; Coetzee, Gerhard A.; Hazelett, Dennis J.; Bojesen, Stig E.; Caga-Anan, Charlisse; Haiman, Christopher A.; Kamal, Ahsan; Luccarini, Craig; Tessier, Daniel; Vincent, Daniel; Bacot, François; Van Den Berg, David J.; Nelson, Stefanie; Demetriades, Stephen; Goldgar, David E.; Couch, Fergus J.; Forman, Judith L.; Giles, Graham G.; Conti, David V.; Bickeböller, Heike; Risch, Angela; Waldenberger, Melanie; Brüske, Irene; Hicks, Belynda D.; Ling, Hua; McGuffog, Lesley; Lee, Andrew; Kuchenbaecker, Karoline B.; Soucy, Penny; Manz, Judith; Cunningham, Julie M.; Butterbach, Katja; Kote-Jarai, Zsofia; Kraft, Peter; FitzGerald, Liesel M.; Lindström, Sara; Adams, Marcia; McKay, James D.; Phelan, Catherine M.; Benlloch, Sara; Kelemen, Linda E.; Brennan, Paul; Riggan, Marjorie; O’Mara, Tracy A.; Shen, Hongbin; Shi, Yongyong; Thompson, Deborah J.; Goodman, Marc T.; Nielsen, Sune F.; Berchuck, Andrew; Laboissiere, Sylvie; Schmit, Stephanie L.; Shelford, Tameka; Edlund, Christopher K.; Taylor, Jack A.; Field, John K.; Park, Sue K.; Offit, Kenneth; Thomassen, Mads; Schmutzler, Rita; Ottini, Laura; Hung, Rayjean J.; Marchini, Jonathan; Al Olama, Ali Amin; Peters, Ulrike; Eeles, Rosalind A.; Seldin, Michael F.; Gillanders, Elizabeth; Seminara, Daniela; Antoniou, Antonis C.; Pharoah, Paul D.; Chenevix-Trench, Georgia; Chanock, Stephen J.; Simard, Jacques; Easton, Douglas F.

2016-01-01

Background Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers and cancer related traits. Methods The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background. Results The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis. Conclusions Results from these analyses will enable researchers to identify new susceptibility loci, perform fine mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental and lifestyle related exposures. Impact Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. PMID:27697780

Advanced correlation grid: Analysis and visualisation of functional connectivity among multiple spike trains.

PubMed

Masud, Mohammad Shahed; Borisyuk, Roman; Stuart, Liz

2017-07-15

This study analyses multiple spike trains (MST) data, defines its functional connectivity and subsequently visualises an accurate diagram of connections. This is a challenging problem. For example, it is difficult to distinguish the common input and the direct functional connection of two spike trains. The new method presented in this paper is based on the traditional pairwise cross-correlation function (CCF) and a new combination of statistical techniques. First, the CCF is used to create the Advanced Correlation Grid (ACG) correlation where both the significant peak of the CCF and the corresponding time delay are used for detailed analysis of connectivity. Second, these two features of functional connectivity are used to classify connections. Finally, the visualization technique is used to represent the topology of functional connections. Examples are presented in the paper to demonstrate the new Advanced Correlation Grid method and to show how it enables discrimination between (i) influence from one spike train to another through an intermediate spike train and (ii) influence from one common spike train to another pair of analysed spike trains. The ACG method enables scientists to automatically distinguish between direct connections from spurious connections such as common source connection and indirect connection whereas existing methods require in-depth analysis to identify such connections. The ACG is a new and effective method for studying functional connectivity of multiple spike trains. This method can identify accurately all the direct connections and can distinguish common source and indirect connections automatically. Copyright © 2017 Elsevier B.V. All rights reserved.

Anti-inflammatory genes associated with multiple sclerosis: a gene expression study.

PubMed

Perga, S; Montarolo, F; Martire, S; Berchialla, P; Malucchi, S; Bertolotto, A

2015-02-15

Multiple sclerosis (MS) is an autoimmune inflammatory disease of the central nervous system caused by a complex interaction between multiple genes and environmental factors. HLA region is the strongest susceptibility locus, but recent huge genome-wide association studies identified new susceptibility genes. Among these, BACH2, PTGER4, RGS1 and ZFP36L1 were highlighted. Here, a gene expression analysis revealed that three of them, namely BACH2, PTGER4 and ZFP36L1, are down-regulated in MS patients' blood cells compared to healthy subjects. Interestingly, all these genes are involved in the immune system regulation with predominant anti-inflammatory role and their reduction could predispose to MS development. Copyright © 2015 Elsevier B.V. All rights reserved.

Quantitative perceptual differences among over-the-counter vaginal products using a standardized methodology: implications for microbicide development☆

PubMed Central

Mahan, Ellen D.; Morrow, Kathleen M.; Hayes, John E.

2015-01-01

Background Increasing prevalence of HIV infection among women worldwide has motivated the development of female-initiated prevention methods, including gel-based microbicides. User acceptability is vital for microbicide success; however, varying cultural vaginal practices indicate multiple formulations must be developed to appeal to different populations. Perceptual attributes of microbicides have been identified as primary drivers of acceptability; however, previous studies do not allow for direct comparison of these qualities between multiple formulations. Study Design Six vaginal products were analyzed ex vivo using descriptive analysis. Perceptual attributes of samples were identified by trained participants (n=10) and rated quantitatively using scales based on a panel-developed lexicon. Data were analyzed using two-way ANOVAs for each attribute; product differences were assessed via Tukey’s honestly significant difference test. Results Significant differences were found between products for multiple attributes. Patterns were also seen for attributes across intended product usage (i.e., contraceptive, moisturizer or lubricant). For example, Options© Gynol II® (Caldwell Consumer Health, LLC) was significantly stickier and grainier than other products. Conclusions Descriptive analysis, a quantitative approach that is based on consensus lexicon usage among participants, successfully quantified perceptual differences among vaginal products. Since perceptual attributes of products can be directly compared quantitatively, this study represents a novel approach that could be used to inform rational design of microbicides. PMID:21757061

Quantitative perceptual differences among over-the-counter vaginal products using a standardized methodology: implications for microbicide development.

PubMed

Mahan, Ellen D; Morrow, Kathleen M; Hayes, John E

2011-08-01

Increasing prevalence of HIV infection among women worldwide has motivated the development of female-initiated prevention methods, including gel-based microbicides. User acceptability is vital for microbicide success; however, varying cultural vaginal practices indicate multiple formulations must be developed to appeal to different populations. Perceptual attributes of microbicides have been identified as primary drivers of acceptability; however, previous studies do not allow for direct comparison of these qualities between multiple formulations. Six vaginal products were analyzed ex vivo using descriptive analysis. Perceptual attributes of samples were identified by trained participants (n=10) and rated quantitatively using scales based on a panel-developed lexicon. Data were analyzed using two-way ANOVAs for each attribute; product differences were assessed via Tukey's honestly significant difference test. Significant differences were found between products for multiple attributes. Patterns were also seen for attributes across intended product usage (i.e., contraceptive, moisturizer or lubricant). For example, Options© Gynol II® (Caldwell Consumer Health, LLC) was significantly stickier and grainier than other products. Descriptive analysis, a quantitative approach that is based on consensus lexicon usage among participants, successfully quantified perceptual differences among vaginal products. Since perceptual attributes of products can be directly compared quantitatively, this study represents a novel approach that could be used to inform rational design of microbicides. Copyright © 2011 Elsevier Inc. All rights reserved.

Sparse representation of whole-brain fMRI signals for identification of functional networks.

PubMed

Lv, Jinglei; Jiang, Xi; Li, Xiang; Zhu, Dajiang; Chen, Hanbo; Zhang, Tuo; Zhang, Shu; Hu, Xintao; Han, Junwei; Huang, Heng; Zhang, Jing; Guo, Lei; Liu, Tianming

2015-02-01

There have been several recent studies that used sparse representation for fMRI signal analysis and activation detection based on the assumption that each voxel's fMRI signal is linearly composed of sparse components. Previous studies have employed sparse coding to model functional networks in various modalities and scales. These prior contributions inspired the exploration of whether/how sparse representation can be used to identify functional networks in a voxel-wise way and on the whole brain scale. This paper presents a novel, alternative methodology of identifying multiple functional networks via sparse representation of whole-brain task-based fMRI signals. Our basic idea is that all fMRI signals within the whole brain of one subject are aggregated into a big data matrix, which is then factorized into an over-complete dictionary basis matrix and a reference weight matrix via an effective online dictionary learning algorithm. Our extensive experimental results have shown that this novel methodology can uncover multiple functional networks that can be well characterized and interpreted in spatial, temporal and frequency domains based on current brain science knowledge. Importantly, these well-characterized functional network components are quite reproducible in different brains. In general, our methods offer a novel, effective and unified solution to multiple fMRI data analysis tasks including activation detection, de-activation detection, and functional network identification. Copyright © 2014 Elsevier B.V. All rights reserved.

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

Multiple-Purpose Subsonic Naval Aircraft (MPSNA): Multiple Application Propfan Study (MAPS)

NASA Technical Reports Server (NTRS)

Engelbeck, R. M.; Havey, C. T.; Klamka, A.; Mcneil, C. L.; Paige, M. A.

1986-01-01

Study requirements, assumptions and guidelines were identified regarding carrier suitability, aircraft missions, technology availability, and propulsion considerations. Conceptual designs were executed for two missions, a full multimission aircraft and a minimum mission aircraft using three different propulsion systems, the UnDucted Fan (UDF), the Propfan and an advanced Turbofan. Detailed aircraft optimization was completed on those configurations yielding gross weight performance and carrier spot factors. Propfan STOVL conceptual designs were exercised also to show the effects of STOVL on gross weight, spot factor and cost. An advanced technology research plan was generated to identify additional investigation opportunities from an airframe contractors standpoint. Life cycle cost analysis was accomplished yielding a comparison of the UDF and propfan configurations against each other as well as against a turbofan with equivalent state of the art turbo-machinery.

Serum Metabolomic Profiling in Acute Alcoholic Hepatitis Identifies Multiple Dysregulated Pathways

PubMed Central

Rachakonda, Vikrant; Gabbert, Charles; Raina, Amit; Bell, Lauren N.; Cooper, Sara; Malik, Shahid; Behari, Jaideep

2014-01-01

Background and Objectives While animal studies have implicated derangements of global energy homeostasis in the pathogenesis of acute alcoholic hepatitis (AAH), the relevance of these findings to the development of human AAH remains unclear. Using global, unbiased serum metabolomics analysis, we sought to characterize alterations in metabolic pathways associated with severe AAH and identify potential biomarkers for disease prognosis. Methods This prospective, case-control study design included 25 patients with severe AAH and 25 ambulatory patients with alcoholic cirrhosis. Serum samples were collected within 24 hours of the index clinical encounter. Global, unbiased metabolomics profiling was performed. Patients were followed for 180 days after enrollment to determine survival. Results Levels of 234 biochemicals were altered in subjects with severe AAH. Random-forest analysis, principal component analysis, and integrated hierarchical clustering methods demonstrated that metabolomics profiles separated the two cohorts with 100% accuracy. Severe AAH was associated with enhanced triglyceride lipolysis, impaired mitochondrial fatty acid beta oxidation, and upregulated omega oxidation. Low levels of multiple lysolipids and related metabolites suggested decreased plasma membrane remodeling in severe AAH. While most measured bile acids were increased in severe AAH, low deoxycholate and glycodeoxycholate levels indicated intestinal dysbiosis. Several changes in substrate utilization for energy homeostasis were identified in severe AAH, including increased glucose consumption by the pentose phosphate pathway, altered tricarboxylic acid (TCA) cycle activity, and enhanced peptide catabolism. Finally, altered levels of small molecules related to glutathione metabolism and antioxidant vitamin depletion were observed in patients with severe AAH. Univariable logistic regression revealed 15 metabolites associated with 180-day survival in severe AAH. Conclusion Severe AAH is characterized by a distinct metabolic phenotype spanning multiple pathways. Metabolomics profiling revealed a panel of biomarkers for disease prognosis, and future studies are planned to validate these findings in larger cohorts of patients with severe AAH. PMID:25461442

Identifying metabolites related to nitrogen mineralisation using 1H NMR spectroscopy

NASA Astrophysics Data System (ADS)

. T McDonald, Noeleen; Graham, Stewart; Watson, Catherine; Gordon, Alan; Lalor, Stan; Laughlin, Ronnie; Elliott, Chris; . P Wall, David

2015-04-01

Exploring new analysis techniques to enhance our knowledge of the various metabolites within our soil systems is imperative. Principally, this knowledge would allow us to link key metabolites with functional influences on critical nutrient processes, such as the nitrogen (N) mineralisation in soils. Currently there are few studies that utilize proton nuclear magnetic resonance spectroscopy (1H NMR) to characterize multiple metabolites within a soil sample. The aim of this research study was to examine the effectiveness of 1H NMR for isolating multiple metabolites that are related to the mineralizable N (MN) capacity across a range of 35 Irish grassland soils. Soils were measured for MN using the standard seven day anaerobic incubation (AI-7). Additionally, soils were also analysed for a range of physio-chemical properties [e.g. total N, total C, mineral N, texture and soil organic matter (SOM)]. Proton NMR analysis was carried on these soils by extracting with 40% methanol:water, lyophilizing and reconstituting in deuterium oxide and recording the NMR spectra on a 400MHz Bruker AVANCE III spectrometer. Once the NMR data were spectrally processed and analysed using multivariate statistical analysis, seven metabolites were identified as having significant relationships with MN (glucose, trimethylamine, glutamic acid, serine, aspartic acid, 4-aminohippuirc acid and citric acid). Following quantification, glucose was shown to explain the largest percentage variability in MN (72%). These outcomes suggest that sources of labile carbon are essential in regulating N mineralisation and the capacity of plant available N derived from SOM-N pools in these soils. Although, smaller in concentration, the amino acids; 4-aminohippuirc acid, glutamic acid and serine also significantly (P<0.05) explained 43%, 27% and 19% of the variability in MN, respectively. This novel study highlights the effectiveness of using 1H NMR as a practical approach to profile multiple metabolites in soils simultaneously, and increasing the potential to identify those related to various soil processes.

Chemical Analysis of Plants that Poison Livestock: Successes, Challenges, and Opportunities.

PubMed

Welch, Kevin D; Lee, Stephen T; Cook, Daniel; Gardner, Dale R; Pfister, James A

2018-04-04

Poisonous plants have a devastating impact on the livestock industry as well as human health. To fully understand the effects of poisonous plants, multiple scientific disciplines are required. Chemical analysis of plant secondary compounds is key to identifying the responsible toxins, characterizing their metabolism, and understanding their effects on animals and humans. In this review, we highlight some of the successes in studying poisonous plants and mitigating their toxic effects. We also highlight some of the remaining challenges and opportunities with regards to the chemical analysis of poisonous plants.

Older age, higher perceived disability and depressive symptoms predict the amount and severity of work-related difficulties in persons with multiple sclerosis.

PubMed

Raggi, Alberto; Giovannetti, Ambra Mara; Schiavolin, Silvia; Brambilla, Laura; Brenna, Greta; Confalonieri, Paolo Agostino; Cortese, Francesca; Frangiamore, Rita; Leonardi, Matilde; Mantegazza, Renato Emilio; Moscatelli, Marco; Ponzio, Michela; Torri Clerici, Valentina; Zaratin, Paola; De Torres, Laura

2018-04-16

This cross-sectional study aims to identify the predictors of work-related difficulties in a sample of employed persons with multiple sclerosis as addressed with the Multiple Sclerosis Questionnaire for Job Difficulties. Hierarchical linear regression analysis was conducted to identify predictors of work difficulties: predictors included demographic variables (age, formal education), disease duration and severity, perceived disability and psychological variables (cognitive dysfunction, depression and anxiety). The targets were the questionnaire's overall score and its six subscales. A total of 177 participants (108 females, aged 21-63) were recruited. Age, perceived disability and depression were direct and significant predictors of the questionnaire total score, and the final model explained 43.7% of its variation. The models built on the questionnaire's subscales show that perceived disability and depression were direct and significant predictors of most of its subscales. Our results show that, among patients with multiple sclerosis, those who were older, with higher perceived disability and higher depression symptoms have more and more severe work-related difficulties. The Multiple Sclerosis Questionnaire for Job Difficulties can be fruitfully exploited to plan tailored actions to limit the likelihood of near-future job loss in persons of working age with multiple sclerosis. Implications for rehabilitation Difficulties with work are common among people with multiple sclerosis and are usually addressed in terms of unemployment or job loss. The Multiple Sclerosis Questionnaire for Job Difficulties is a disease-specific questionnaire developed to address the amount and severity of work-related difficulties. We found that work-related difficulties were associated to older age, higher perceived disability and depressive symptoms. Mental health issues and perceived disability should be consistently included in future research targeting work-related difficulties.

Differential Network Analysis Reveals Evolutionary Complexity in Secondary Metabolism of Rauvolfia serpentina over Catharanthus roseus

PubMed Central

Pathania, Shivalika; Bagler, Ganesh; Ahuja, Paramvir S.

2016-01-01

Comparative co-expression analysis of multiple species using high-throughput data is an integrative approach to determine the uniformity as well as diversification in biological processes. Rauvolfia serpentina and Catharanthus roseus, both members of Apocyanacae family, are reported to have remedial properties against multiple diseases. Despite of sharing upstream of terpenoid indole alkaloid pathway, there is significant diversity in tissue-specific synthesis and accumulation of specialized metabolites in these plants. This led us to implement comparative co-expression network analysis to investigate the modules and genes responsible for differential tissue-specific expression as well as species-specific synthesis of metabolites. Toward these goals differential network analysis was implemented to identify candidate genes responsible for diversification of metabolites profile. Three genes were identified with significant difference in connectivity leading to differential regulatory behavior between these plants. These genes may be responsible for diversification of secondary metabolism, and thereby for species-specific metabolite synthesis. The network robustness of R. serpentina, determined based on topological properties, was also complemented by comparison of gene-metabolite networks of both plants, and may have evolved to have complex metabolic mechanisms as compared to C. roseus under the influence of various stimuli. This study reveals evolution of complexity in secondary metabolism of R. serpentina, and key genes that contribute toward diversification of specific metabolites. PMID:27588023

Differential Network Analysis Reveals Evolutionary Complexity in Secondary Metabolism of Rauvolfia serpentina over Catharanthus roseus.

PubMed

Pathania, Shivalika; Bagler, Ganesh; Ahuja, Paramvir S

2016-01-01

Comparative co-expression analysis of multiple species using high-throughput data is an integrative approach to determine the uniformity as well as diversification in biological processes. Rauvolfia serpentina and Catharanthus roseus, both members of Apocyanacae family, are reported to have remedial properties against multiple diseases. Despite of sharing upstream of terpenoid indole alkaloid pathway, there is significant diversity in tissue-specific synthesis and accumulation of specialized metabolites in these plants. This led us to implement comparative co-expression network analysis to investigate the modules and genes responsible for differential tissue-specific expression as well as species-specific synthesis of metabolites. Toward these goals differential network analysis was implemented to identify candidate genes responsible for diversification of metabolites profile. Three genes were identified with significant difference in connectivity leading to differential regulatory behavior between these plants. These genes may be responsible for diversification of secondary metabolism, and thereby for species-specific metabolite synthesis. The network robustness of R. serpentina, determined based on topological properties, was also complemented by comparison of gene-metabolite networks of both plants, and may have evolved to have complex metabolic mechanisms as compared to C. roseus under the influence of various stimuli. This study reveals evolution of complexity in secondary metabolism of R. serpentina, and key genes that contribute toward diversification of specific metabolites.

Analysis of Brassica oleracea early stage abiotic stress responses reveals tolerance in multiple crop types and for multiple sources of stress.

PubMed

Beacham, Andrew M; Hand, Paul; Pink, David Ac; Monaghan, James M

2017-12-01

Brassica oleracea includes a number of important crop types such as cabbage, cauliflower, broccoli and kale. Current climate conditions and weather patterns are causing significant losses in these crops, meaning that new cultivars with improved tolerance of one or more abiotic stress types must be sought. In this study, genetically fixed B. oleracea lines belonging to a Diversity Fixed Foundation Set (DFFS) were assayed for their response to seedling stage-imposed drought, flood, salinity, heat and cold stress. Significant (P ≤ 0.05) variation in stress tolerance response was found for each stress, for each of four measured variables (relative fresh weight, relative dry weight, relative leaf number and relative plant height). Lines tolerant to multiple stresses were found to belong to several different crop types. There was no overall correlation between the responses to the different stresses. Abiotic stress tolerance was identified in multiple B. oleracea crop types, with some lines exhibiting resistance to multiple stresses. For each stress, no one crop type appeared significantly more or less tolerant than others. The results are promising for the development of more environmentally robust lines of different B. oleracea crops by identifying tolerant material and highlighting the relationship between responses to different stresses. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Who do we think we are? Analysing the content and form of identity work in the English National Health Service.

PubMed

McDermott, Imelda; Checkland, Kath; Harrison, Stephen; Snow, Stephanie; Coleman, Anna

2013-01-01

The language used by National Health Service (NHS) "commissioning" managers when discussing their roles and responsibilities can be seen as a manifestation of "identity work", defined as a process of identifying. This paper aims to offer a novel approach to analysing "identity work" by triangulation of multiple analytical methods, combining analysis of the content of text with analysis of its form. Fairclough's discourse analytic methodology is used as a framework. Following Fairclough, the authors use analytical methods associated with Halliday's systemic functional linguistics. While analysis of the content of interviews provides some information about NHS Commissioners' perceptions of their roles and responsibilities, analysis of the form of discourse that they use provides a more detailed and nuanced view. Overall, the authors found that commissioning managers have a higher level of certainty about what commissioning is not rather than what commissioning is; GP managers have a high level of certainty of their identity as a GP rather than as a manager; and both GP managers and non-GP managers oscillate between multiple identities depending on the different situations they are in. This paper offers a novel approach to triangulation, based not on the usual comparison of multiple data sources, but rather based on the application of multiple analytical methods to a single source of data. This paper also shows the latent uncertainty about the nature of commissioning enterprise in the English NHS.

Analysis of Plasminogen Genetic Variants in Multiple Sclerosis Patients

PubMed Central

Sadovnick, A. Dessa; Traboulsee, Anthony L.; Bernales, Cecily Q.; Ross, Jay P.; Forwell, Amanda L.; Yee, Irene M.; Guillot-Noel, Lena; Fontaine, Bertrand; Cournu-Rebeix, Isabelle; Alcina, Antonio; Fedetz, Maria; Izquierdo, Guillermo; Matesanz, Fuencisla; Hilven, Kelly; Dubois, Bénédicte; Goris, An; Astobiza, Ianire; Alloza, Iraide; Antigüedad, Alfredo; Vandenbroeck, Koen; Akkad, Denis A.; Aktas, Orhan; Blaschke, Paul; Buttmann, Mathias; Chan, Andrew; Epplen, Joerg T.; Gerdes, Lisa-Ann; Kroner, Antje; Kubisch, Christian; Kümpfel, Tania; Lohse, Peter; Rieckmann, Peter; Zettl, Uwe K.; Zipp, Frauke; Bertram, Lars; Lill, Christina M; Fernandez, Oscar; Urbaneja, Patricia; Leyva, Laura; Alvarez-Cermeño, Jose Carlos; Arroyo, Rafael; Garagorri, Aroa M.; García-Martínez, Angel; Villar, Luisa M.; Urcelay, Elena; Malhotra, Sunny; Montalban, Xavier; Comabella, Manuel; Berger, Thomas; Fazekas, Franz; Reindl, Markus; Schmied, Mascha C.; Zimprich, Alexander; Vilariño-Güell, Carles

2016-01-01

Multiple sclerosis (MS) is a prevalent neurological disease of complex etiology. Here, we describe the characterization of a multi-incident MS family that nominated a rare missense variant (p.G420D) in plasminogen (PLG) as a putative genetic risk factor for MS. Genotyping of PLG p.G420D (rs139071351) in 2160 MS patients, and 886 controls from Canada, identified 10 additional probands, two sporadic patients and one control with the variant. Segregation in families harboring the rs139071351 variant, identified p.G420D in 26 out of 30 family members diagnosed with MS, 14 unaffected parents, and 12 out of 30 family members not diagnosed with disease. Despite considerably reduced penetrance, linkage analysis supports cosegregation of PLG p.G420D and disease. Genotyping of PLG p.G420D in 14446 patients, and 8797 controls from Canada, France, Spain, Germany, Belgium, and Austria failed to identify significant association with disease (P = 0.117), despite an overall higher prevalence in patients (OR = 1.32; 95% CI = 0.93–1.87). To assess whether additional rare variants have an effect on MS risk, we sequenced PLG in 293 probands, and genotyped all rare variants in cases and controls. This analysis identified nine rare missense variants, and although three of them were exclusively observed in MS patients, segregation does not support pathogenicity. PLG is a plausible biological candidate for MS owing to its involvement in immune system response, blood-brain barrier permeability, and myelin degradation. Moreover, components of its activation cascade have been shown to present increased activity or expression in MS patients compared to controls; further studies are needed to clarify whether PLG is involved in MS susceptibility. PMID:27194806

Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis

PubMed Central

Sawcer, Stephen; Hellenthal, Garrett; Pirinen, Matti; Spencer, Chris C.A.; Patsopoulos, Nikolaos A.; Moutsianas, Loukas; Dilthey, Alexander; Su, Zhan; Freeman, Colin; Hunt, Sarah E.; Edkins, Sarah; Gray, Emma; Booth, David R.; Potter, Simon C.; Goris, An; Band, Gavin; Oturai, Annette Bang; Strange, Amy; Saarela, Janna; Bellenguez, Céline; Fontaine, Bertrand; Gillman, Matthew; Hemmer, Bernhard; Gwilliam, Rhian; Zipp, Frauke; Jayakumar, Alagurevathi; Martin, Roland; Leslie, Stephen; Hawkins, Stanley; Giannoulatou, Eleni; D’alfonso, Sandra; Blackburn, Hannah; Boneschi, Filippo Martinelli; Liddle, Jennifer; Harbo, Hanne F.; Perez, Marc L.; Spurkland, Anne; Waller, Matthew J; Mycko, Marcin P.; Ricketts, Michelle; Comabella, Manuel; Hammond, Naomi; Kockum, Ingrid; McCann, Owen T.; Ban, Maria; Whittaker, Pamela; Kemppinen, Anu; Weston, Paul; Hawkins, Clive; Widaa, Sara; Zajicek, John; Dronov, Serge; Robertson, Neil; Bumpstead, Suzannah J.; Barcellos, Lisa F.; Ravindrarajah, Rathi; Abraham, Roby; Alfredsson, Lars; Ardlie, Kristin; Aubin, Cristin; Baker, Amie; Baker, Katharine; Baranzini, Sergio E.; Bergamaschi, Laura; Bergamaschi, Roberto; Bernstein, Allan; Berthele, Achim; Boggild, Mike; Bradfield, Jonathan P.; Brassat, David; Broadley, Simon A.; Buck, Dorothea; Butzkueven, Helmut; Capra, Ruggero; Carroll, William M.; Cavalla, Paola; Celius, Elisabeth G.; Cepok, Sabine; Chiavacci, Rosetta; Clerget-Darpoux, Françoise; Clysters, Katleen; Comi, Giancarlo; Cossburn, Mark; Cournu-Rebeix, Isabelle; Cox, Mathew B.; Cozen, Wendy; Cree, Bruce A.C.; Cross, Anne H.; Cusi, Daniele; Daly, Mark J.; Davis, Emma; de Bakker, Paul I.W.; Debouverie, Marc; D’hooghe, Marie Beatrice; Dixon, Katherine; Dobosi, Rita; Dubois, Bénédicte; Ellinghaus, David; Elovaara, Irina; Esposito, Federica; Fontenille, Claire; Foote, Simon; Franke, Andre; Galimberti, Daniela; Ghezzi, Angelo; Glessner, Joseph; Gomez, Refujia; Gout, Olivier; Graham, Colin; Grant, Struan F.A.; Guerini, Franca Rosa; Hakonarson, Hakon; Hall, Per; Hamsten, Anders; Hartung, Hans-Peter; Heard, Rob N.; Heath, Simon; Hobart, Jeremy; Hoshi, Muna; Infante-Duarte, Carmen; Ingram, Gillian; Ingram, Wendy; Islam, Talat; Jagodic, Maja; Kabesch, Michael; Kermode, Allan G.; Kilpatrick, Trevor J.; Kim, Cecilia; Klopp, Norman; Koivisto, Keijo; Larsson, Malin; Lathrop, Mark; Lechner-Scott, Jeannette S.; Leone, Maurizio A.; Leppä, Virpi; Liljedahl, Ulrika; Bomfim, Izaura Lima; Lincoln, Robin R.; Link, Jenny; Liu, Jianjun; Lorentzen, Åslaug R.; Lupoli, Sara; Macciardi, Fabio; Mack, Thomas; Marriott, Mark; Martinelli, Vittorio; Mason, Deborah; McCauley, Jacob L.; Mentch, Frank; Mero, Inger-Lise; Mihalova, Tania; Montalban, Xavier; Mottershead, John; Myhr, Kjell-Morten; Naldi, Paola; Ollier, William; Page, Alison; Palotie, Aarno; Pelletier, Jean; Piccio, Laura; Pickersgill, Trevor; Piehl, Fredrik; Pobywajlo, Susan; Quach, Hong L.; Ramsay, Patricia P.; Reunanen, Mauri; Reynolds, Richard; Rioux, John D.; Rodegher, Mariaemma; Roesner, Sabine; Rubio, Justin P.; Rückert, Ina-Maria; Salvetti, Marco; Salvi, Erika; Santaniello, Adam; Schaefer, Catherine A.; Schreiber, Stefan; Schulze, Christian; Scott, Rodney J.; Sellebjerg, Finn; Selmaj, Krzysztof W.; Sexton, David; Shen, Ling; Simms-Acuna, Brigid; Skidmore, Sheila; Sleiman, Patrick M.A.; Smestad, Cathrine; Sørensen, Per Soelberg; Søndergaard, Helle Bach; Stankovich, Jim; Strange, Richard C.; Sulonen, Anna-Maija; Sundqvist, Emilie; Syvänen, Ann-Christine; Taddeo, Francesca; Taylor, Bruce; Blackwell, Jenefer M.; Tienari, Pentti; Bramon, Elvira; Tourbah, Ayman; Brown, Matthew A.; Tronczynska, Ewa; Casas, Juan P.; Tubridy, Niall; Corvin, Aiden; Vickery, Jane; Jankowski, Janusz; Villoslada, Pablo; Markus, Hugh S.; Wang, Kai; Mathew, Christopher G.; Wason, James; Palmer, Colin N.A.; Wichmann, H-Erich; Plomin, Robert; Willoughby, Ernest; Rautanen, Anna; Winkelmann, Juliane; Wittig, Michael; Trembath, Richard C.; Yaouanq, Jacqueline; Viswanathan, Ananth C.; Zhang, Haitao; Wood, Nicholas W.; Zuvich, Rebecca; Deloukas, Panos; Langford, Cordelia; Duncanson, Audrey; Oksenberg, Jorge R.; Pericak-Vance, Margaret A.; Haines, Jonathan L.; Olsson, Tomas; Hillert, Jan; Ivinson, Adrian J.; De Jager, Philip L.; Peltonen, Leena; Stewart, Graeme J.; Hafler, David A.; Hauser, Stephen L.; McVean, Gil; Donnelly, Peter; Compston, Alastair

2011-01-01

Multiple sclerosis (OMIM 126200) is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability.1 Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals;2,3 and systematic attempts to identify linkage in multiplex families have confirmed that variation within the Major Histocompatibility Complex (MHC) exerts the greatest individual effect on risk.4 Modestly powered Genome-Wide Association Studies (GWAS)5-10 have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects play a key role in disease susceptibility.11 Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the Class I region. Immunologically relevant genes are significantly over-represented amongst those mapping close to the identified loci and particularly implicate T helper cell differentiation in the pathogenesis of multiple sclerosis. PMID:21833088

Interpretation and use of evidence in state policymaking: a qualitative analysis

PubMed Central

Apollonio, Dorie E; Bero, Lisa A

2017-01-01

Introduction Researchers advocating for evidence-informed policy have attempted to encourage policymakers to develop a greater understanding of research and researchers to develop a better understanding of the policymaking process. Our aim was to apply findings drawn from studies of the policymaking process, specifically the theory of policy windows, to identify strategies used to integrate evidence into policymaking and points in the policymaking process where evidence was more or less relevant. Methods Our observational study relied on interviews conducted with 24 policymakers from the USA who had been trained to interpret scientific research in multiple iterations of an evidence-based workshop. Participants were asked to describe cases where they had been involved in making health policy and to provide examples in which research was used, either successfully or unsuccessfully. Interviews were transcribed, independently coded by multiple members of the study team and analysed for content using key words, concepts identified by participants and concepts arising from review of the texts. Results Our results suggest that policymakers who focused on health issues used multiple strategies to encourage evidence-informed policymaking. The respondents used a strict definition of what constituted evidence, and relied on their experience with research to discourage the use of less rigorous research. Their experience suggested that evidence was less useful in identifying problems, encouraging political action or ensuring feasibility and more useful in developing policy alternatives. Conclusions Past research has suggested multiple strategies to increase the use of evidence in policymaking, including the development of rapid-response research and policy-oriented summaries of data. Our findings suggest that these strategies may be most relevant to the policymaking stream, which develops policy alternatives. In addition, we identify several strategies that policymakers and researchers can apply to encourage evidence-informed policymaking. PMID:28219958

Non-destructive testing of full-length bonded rock bolts based on HHT signal analysis

NASA Astrophysics Data System (ADS)

Shi, Z. M.; Liu, L.; Peng, M.; Liu, C. C.; Tao, F. J.; Liu, C. S.

2018-04-01

Full-length bonded rock bolts are commonly used in mining, tunneling and slope engineering because of their simple design and resistance to corrosion. However, the length of a rock bolt and grouting quality do not often meet the required design standards in practice because of the concealment and complexity of bolt construction. Non-destructive testing is preferred when testing a rock bolt's quality because of the convenience, low cost and wide detection range. In this paper, a signal analysis method for the non-destructive sound wave testing of full-length bonded rock bolts is presented, which is based on the Hilbert-Huang transform (HHT). First, we introduce the HHT analysis method to calculate the bolt length and identify defect locations based on sound wave reflection test signals, which includes decomposing the test signal via empirical mode decomposition (EMD), selecting the intrinsic mode functions (IMF) using the Pearson Correlation Index (PCI) and calculating the instantaneous phase and frequency via the Hilbert transform (HT). Second, six model tests are conducted using different grouting defects and bolt protruding lengths to verify the effectiveness of the HHT analysis method. Lastly, the influence of the bolt protruding length on the test signal, identification of multiple reflections from defects, bolt end and protruding end, and mode mixing from EMD are discussed. The HHT analysis method can identify the bolt length and grouting defect locations from signals that contain noise at multiple reflected interfaces. The reflection from the long protruding end creates an irregular test signal with many frequency peaks on the spectrum. The reflections from defects barely change the original signal because they are low energy, which cannot be adequately resolved using existing methods. The HHT analysis method can identify reflections from the long protruding end of the bolt and multiple reflections from grouting defects based on mutations in the instantaneous frequency, which makes weak reflections more noticeable. The mode mixing phenomenon is observed in several tests, but this does not markedly affect the identification results due to the simple medium in bolt tests. The mode mixing can be reduced by ensemble EMD (EEMD) or complete ensemble EMD with adaptive noise (CEEMDAN), which are powerful tools to used analyze the test signal in a complex medium and may play an important role in future studies. The HHT bolt signal analysis method is a self-adaptive and automatic process, which can be programed as analysis software and will make bolt tests more convenient in practice.

Success factors for strategic change initiatives: a qualitative study of healthcare administrators' perspectives.

PubMed

Kash, Bita Arbab; Spaulding, Aaron; Johnson, Christopher E; Gamm, Larry

2014-01-01

Success factors related to the implementation of change initiatives are well documented and discussed in the management literature, but they are seldom studied in healthcare organizations engaged in multiple strategic change initiatives. The purpose of this study was to identify key success factors related to implementation of change initiatives based on rich qualitative data gathered from health leader interviews at two large health systems implementing multiple change initiatives. In-depth personal interviews with 61 healthcare leaders in the two large systems were conducted and inductive qualitative analysis was employed to identify success factors associated with 13 change initiatives. Results from this analysis were compared to success factors identified in the literature, and generalizations were drawn that add significantly to the management literature, especially to that in the healthcare sector. Ten specific success factors were identified for the implementation of change initiatives. The top three success factors were (1) culture and values, (2) business processes, and (3) people and engagement. Two of the identified success factors are unique to the healthcare sector and not found in the literature on change models: service quality and client satisfaction (ranked fourth of 10) and access to information (ranked ninth). Results demonstrate the importance of human resource functions, alignment of culture and values with change, and business processes that facilitate effective communication and access to information to achieve many change initiatives. The responses also suggest opportunities for leaders of healthcare organizations to more formally recognize the degree to which various change initiatives are dependent on one another.

An indicator of cancer: downregulation of monoamine oxidase-A in multiple organs and species.

PubMed

Rybaczyk, Leszek A; Bashaw, Meredith J; Pathak, Dorothy R; Huang, Kun

2008-03-20

Identifying consistent changes in cellular function that occur in multiple types of cancer could revolutionize the way cancer is treated. Previous work has produced promising results such as the identification of p53. Recently drugs that affect serotonin reuptake were shown to reduce the risk of colon cancer in man. Here, we analyze an ensemble of cancer datasets focusing on genes involved in the serotonergic pathway. Genechip datasets consisting of cancerous tissue from human, mouse, rat, or zebrafish were extracted from the GEO database. We first compared gene expression between cancerous tissues and normal tissues for each type of cancer and then identified changes that were common to a variety of cancer types. Our analysis found that significant downregulation of MAO-A, the enzyme that metabolizes serotonin, occurred in multiple tissues from humans, rodents, and fish. MAO-A expression was decreased in 95.4% of human cancer patients and 94.2% of animal cancer cases compared to the non-cancerous controls. These are the first findings that identify a single reliable change in so many different cancers. Future studies should investigate links between MAO-A suppression and the development of cancer to determine the extent that MAO-A suppression contributes to increased cancer risk.

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

Discovering transnosological molecular basis of human brain diseases using biclustering analysis of integrated gene expression data.

PubMed

Cha, Kihoon; Hwang, Taeho; Oh, Kimin; Yi, Gwan-Su

2015-01-01

It has been reported that several brain diseases can be treated as transnosological manner implicating possible common molecular basis under those diseases. However, molecular level commonality among those brain diseases has been largely unexplored. Gene expression analyses of human brain have been used to find genes associated with brain diseases but most of those studies were restricted either to an individual disease or to a couple of diseases. In addition, identifying significant genes in such brain diseases mostly failed when it used typical methods depending on differentially expressed genes. In this study, we used a correlation-based biclustering approach to find coexpressed gene sets in five neurodegenerative diseases and three psychiatric disorders. By using biclustering analysis, we could efficiently and fairly identified various gene sets expressed specifically in both single and multiple brain diseases. We could find 4,307 gene sets correlatively expressed in multiple brain diseases and 3,409 gene sets exclusively specified in individual brain diseases. The function enrichment analysis of those gene sets showed many new possible functional bases as well as neurological processes that are common or specific for those eight diseases. This study introduces possible common molecular bases for several brain diseases, which open the opportunity to clarify the transnosological perspective assumed in brain diseases. It also showed the advantages of correlation-based biclustering analysis and accompanying function enrichment analysis for gene expression data in this type of investigation.

Discovering transnosological molecular basis of human brain diseases using biclustering analysis of integrated gene expression data

PubMed Central

2015-01-01

Background It has been reported that several brain diseases can be treated as transnosological manner implicating possible common molecular basis under those diseases. However, molecular level commonality among those brain diseases has been largely unexplored. Gene expression analyses of human brain have been used to find genes associated with brain diseases but most of those studies were restricted either to an individual disease or to a couple of diseases. In addition, identifying significant genes in such brain diseases mostly failed when it used typical methods depending on differentially expressed genes. Results In this study, we used a correlation-based biclustering approach to find coexpressed gene sets in five neurodegenerative diseases and three psychiatric disorders. By using biclustering analysis, we could efficiently and fairly identified various gene sets expressed specifically in both single and multiple brain diseases. We could find 4,307 gene sets correlatively expressed in multiple brain diseases and 3,409 gene sets exclusively specified in individual brain diseases. The function enrichment analysis of those gene sets showed many new possible functional bases as well as neurological processes that are common or specific for those eight diseases. Conclusions This study introduces possible common molecular bases for several brain diseases, which open the opportunity to clarify the transnosological perspective assumed in brain diseases. It also showed the advantages of correlation-based biclustering analysis and accompanying function enrichment analysis for gene expression data in this type of investigation. PMID:26043779

A knowledge-driven interaction analysis reveals potential neurodegenerative mechanism of multiple sclerosis susceptibility.

PubMed

Bush, W S; McCauley, J L; DeJager, P L; Dudek, S M; Hafler, D A; Gibson, R A; Matthews, P M; Kappos, L; Naegelin, Y; Polman, C H; Hauser, S L; Oksenberg, J; Haines, J L; Ritchie, M D

2011-07-01

Gene-gene interactions are proposed as an important component of the genetic architecture of complex diseases, and are just beginning to be evaluated in the context of genome-wide association studies (GWAS). In addition to detecting epistasis, a benefit to interaction analysis is that it also increases power to detect weak main effects. We conducted a knowledge-driven interaction analysis of a GWAS of 931 multiple sclerosis (MS) trios to discover gene-gene interactions within established biological contexts. We identify heterogeneous signals, including a gene-gene interaction between CHRM3 (muscarinic cholinergic receptor 3) and MYLK (myosin light-chain kinase) (joint P=0.0002), an interaction between two phospholipase C-β isoforms, PLCβ1 and PLCβ4 (joint P=0.0098), and a modest interaction between ACTN1 (actinin alpha 1) and MYH9 (myosin heavy chain 9) (joint P=0.0326), all localized to calcium-signaled cytoskeletal regulation. Furthermore, we discover a main effect (joint P=5.2E-5) previously unidentified by single-locus analysis within another related gene, SCIN (scinderin), a calcium-binding cytoskeleton regulatory protein. This work illustrates that knowledge-driven interaction analysis of GWAS data is a feasible approach to identify new genetic effects. The results of this study are among the first gene-gene interactions and non-immune susceptibility loci for MS. Further, the implicated genes cluster within inter-related biological mechanisms that suggest a neurodegenerative component to MS.

Multiplicative Effects of Social and Psychological Risk Factors on College Students' Suicidal Behaviors.

PubMed

Assari, Shervin

2018-05-17

Less is known about the multiplicative effects of social and psychological risk and protective factors of suicidality on college campuses. The current study aimed to investigate the multiplicative effects of social (identifying oneself as gay/lesbian, financial difficulty, violence victimization, and religiosity) and psychological (anxiety, depression, problem alcohol use, drug use) and risk/protective factors on suicidal behaviors among college students in the United States. Using a cross-sectional design, the Healthy Mind Study (HMS; 2016⁻2017), is a national online survey of college students in the United States. Social (identifying oneself as gay/lesbian, violence victimization, financial difficulty, and religiosity) and psychological (anxiety, depression, problem alcohol use, and drug use) risk/protective factors were assessed among 27,961 individuals. Three aspects of suicidality, including ideation, plan, and attempt, were also assessed. Logistic regression models were used for data analysis. Financial difficulty, violence victimization, identifying oneself as gay/lesbian, anxiety, depression, and drug use increased, while religiosity reduced the odds of suicidal behaviors. Multiplicative effects were found between the following social and psychological risk factors: (1) financial difficulty and anxiety; (2) financial difficulty and depression; (3) depression and drug use; (4) problem alcohol use and drug use; and (5) depression and problem alcohol use. There is a considerable overlap in the social and psychological processes, such as financial stress, mood disorders, and substance use problems, on risk of suicide in college students. As social and psychological risk factors do not operate independently, comprehensive suicidal risk evaluations that simultaneously address multiple social and psychological risk factors may be superior to programs that only address a single risk factor.

From Principal Component to Direct Coupling Analysis of Coevolution in Proteins: Low-Eigenvalue Modes are Needed for Structure Prediction

PubMed Central

Cocco, Simona; Monasson, Remi; Weigt, Martin

2013-01-01

Various approaches have explored the covariation of residues in multiple-sequence alignments of homologous proteins to extract functional and structural information. Among those are principal component analysis (PCA), which identifies the most correlated groups of residues, and direct coupling analysis (DCA), a global inference method based on the maximum entropy principle, which aims at predicting residue-residue contacts. In this paper, inspired by the statistical physics of disordered systems, we introduce the Hopfield-Potts model to naturally interpolate between these two approaches. The Hopfield-Potts model allows us to identify relevant ‘patterns’ of residues from the knowledge of the eigenmodes and eigenvalues of the residue-residue correlation matrix. We show how the computation of such statistical patterns makes it possible to accurately predict residue-residue contacts with a much smaller number of parameters than DCA. This dimensional reduction allows us to avoid overfitting and to extract contact information from multiple-sequence alignments of reduced size. In addition, we show that low-eigenvalue correlation modes, discarded by PCA, are important to recover structural information: the corresponding patterns are highly localized, that is, they are concentrated in few sites, which we find to be in close contact in the three-dimensional protein fold. PMID:23990764

Harnessing Connectivity in a Large-Scale Small-Molecule Sensitivity Dataset.

PubMed

Seashore-Ludlow, Brinton; Rees, Matthew G; Cheah, Jaime H; Cokol, Murat; Price, Edmund V; Coletti, Matthew E; Jones, Victor; Bodycombe, Nicole E; Soule, Christian K; Gould, Joshua; Alexander, Benjamin; Li, Ava; Montgomery, Philip; Wawer, Mathias J; Kuru, Nurdan; Kotz, Joanne D; Hon, C Suk-Yee; Munoz, Benito; Liefeld, Ted; Dančík, Vlado; Bittker, Joshua A; Palmer, Michelle; Bradner, James E; Shamji, Alykhan F; Clemons, Paul A; Schreiber, Stuart L

2015-11-01

Identifying genetic alterations that prime a cancer cell to respond to a particular therapeutic agent can facilitate the development of precision cancer medicines. Cancer cell-line (CCL) profiling of small-molecule sensitivity has emerged as an unbiased method to assess the relationships between genetic or cellular features of CCLs and small-molecule response. Here, we developed annotated cluster multidimensional enrichment analysis to explore the associations between groups of small molecules and groups of CCLs in a new, quantitative sensitivity dataset. This analysis reveals insights into small-molecule mechanisms of action, and genomic features that associate with CCL response to small-molecule treatment. We are able to recapitulate known relationships between FDA-approved therapies and cancer dependencies and to uncover new relationships, including for KRAS-mutant cancers and neuroblastoma. To enable the cancer community to explore these data, and to generate novel hypotheses, we created an updated version of the Cancer Therapeutic Response Portal (CTRP v2). We present the largest CCL sensitivity dataset yet available, and an analysis method integrating information from multiple CCLs and multiple small molecules to identify CCL response predictors robustly. We updated the CTRP to enable the cancer research community to leverage these data and analyses. ©2015 American Association for Cancer Research.

Super-Resolution Imaging Strategies for Cell Biologists Using a Spinning Disk Microscope

PubMed Central

Hosny, Neveen A.; Song, Mingying; Connelly, John T.; Ameer-Beg, Simon; Knight, Martin M.; Wheeler, Ann P.

2013-01-01

In this study we use a spinning disk confocal microscope (SD) to generate super-resolution images of multiple cellular features from any plane in the cell. We obtain super-resolution images by using stochastic intensity fluctuations of biological probes, combining Photoactivation Light-Microscopy (PALM)/Stochastic Optical Reconstruction Microscopy (STORM) methodologies. We compared different image analysis algorithms for processing super-resolution data to identify the most suitable for analysis of particular cell structures. SOFI was chosen for X and Y and was able to achieve a resolution of ca. 80 nm; however higher resolution was possible >30 nm, dependant on the super-resolution image analysis algorithm used. Our method uses low laser power and fluorescent probes which are available either commercially or through the scientific community, and therefore it is gentle enough for biological imaging. Through comparative studies with structured illumination microscopy (SIM) and widefield epifluorescence imaging we identified that our methodology was advantageous for imaging cellular structures which are not immediately at the cell-substrate interface, which include the nuclear architecture and mitochondria. We have shown that it was possible to obtain two coloured images, which highlights the potential this technique has for high-content screening, imaging of multiple epitopes and live cell imaging. PMID:24130668

Selective attention to temporal features on nested time scales.

PubMed

Henry, Molly J; Herrmann, Björn; Obleser, Jonas

2015-02-01

Meaningful auditory stimuli such as speech and music often vary simultaneously along multiple time scales. Thus, listeners must selectively attend to, and selectively ignore, separate but intertwined temporal features. The current study aimed to identify and characterize the neural network specifically involved in this feature-selective attention to time. We used a novel paradigm where listeners judged either the duration or modulation rate of auditory stimuli, and in which the stimulation, working memory demands, response requirements, and task difficulty were held constant. A first analysis identified all brain regions where individual brain activation patterns were correlated with individual behavioral performance patterns, which thus supported temporal judgments generically. A second analysis then isolated those brain regions that specifically regulated selective attention to temporal features: Neural responses in a bilateral fronto-parietal network including insular cortex and basal ganglia decreased with degree of change of the attended temporal feature. Critically, response patterns in these regions were inverted when the task required selectively ignoring this feature. The results demonstrate how the neural analysis of complex acoustic stimuli with multiple temporal features depends on a fronto-parietal network that simultaneously regulates the selective gain for attended and ignored temporal features. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Performance Analysis of MIMO Relay Network via Propagation Measurement in L-Shaped Corridor Environment

NASA Astrophysics Data System (ADS)

Lertwiram, Namzilp; Tran, Gia Khanh; Mizutani, Keiichi; Sakaguchi, Kei; Araki, Kiyomichi

Setting relays can address the shadowing problem between a transmitter (Tx) and a receiver (Rx). Moreover, the Multiple-Input Multiple-Output (MIMO) technique has been introduced to improve wireless link capacity. The MIMO technique can be applied in relay network to enhance system performance. However, the efficiency of relaying schemes and relay placement have not been well investigated with experiment-based study. This paper provides a propagation measurement campaign of a MIMO two-hop relay network in 5GHz band in an L-shaped corridor environment with various relay locations. Furthermore, this paper proposes a Relay Placement Estimation (RPE) scheme to identify the optimum relay location, i.e. the point at which the network performance is highest. Analysis results of channel capacity show that relaying technique is beneficial over direct transmission in strong shadowing environment while it is ineffective in non-shadowing environment. In addition, the optimum relay location estimated with the RPE scheme also agrees with the location where the network achieves the highest performance as identified by network capacity. Finally, the capacity analysis shows that two-way MIMO relay employing network coding has the best performance while cooperative relaying scheme is not effective due to shadowing effect weakening the signal strength of the direct link.

Notch sensitivity and stress redistribution in three ceramic-matrix composites

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

Mackin, T.J.; He, M.Y.; Evans, A.G.

Fiber-reinforced ceramic-matrix composites (CMCs) depend upon inelastic mechanisms to diffuse stress concentrations associated with holes, notches, and cracks. These mechanisms consist of fiber debonding and pullout, multiple matrix cracking, and shear band formation. In order to understand these effects, experiments have bee conducted on several double-edge-notched CMCs that exhibit different stress redistribution mechanisms. Stresses have been measured an d mechanisms identified by using a combination of methods including X0-ray imaging, edge replication, and thermoelastic analysis. Multiple matrix cracking was found to be the most effective stress redistribution mechanism.

Experiences in autotuning matrix multiplication for energy minimization on GPUs

DOE PAGES

Anzt, Hartwig; Haugen, Blake; Kurzak, Jakub; ...

2015-05-20

In this study, we report extensive results and analysis of autotuning the computationally intensive graphics processing units kernel for dense matrix–matrix multiplication in double precision. In contrast to traditional autotuning and/or optimization for runtime performance only, we also take the energy efficiency into account. For kernels achieving equal performance, we show significant differences in their energy balance. We also identify the memory throughput as the most influential metric that trades off performance and energy efficiency. Finally, as a result, the performance optimal case ends up not being the most efficient kernel in overall resource use.

Prediction of jump phenomena in roll-coupled maneuvers of airplanes

NASA Technical Reports Server (NTRS)

Schy, A. A.; Hannah, M. E.

1976-01-01

An easily computerized analytical method is developed for identifying critical airplane maneuvers in which nonlinear rotational coupling effects may cause sudden jumps in the response to pilot's control inputs. Fifth and ninth degree polynomials for predicting multiple pseudo-steady states of roll-coupled maneuvers are derived. The program calculates the pseudo-steady solutions and their stability. The occurrence of jump-like responses for several airplanes and a variety of maneuvers is shown to correlate well with the appearance of multiple stable solutions for critical control combinations. The analysis is extended to include aerodynamics nonlinear in angle of attack.

Integrating data from multiple sources for data completeness in a web-based registry for pediatric renal transplantation--the CERTAIN Registry.

PubMed

Köster, Lennart; Krupka, Kai; Höcker, Britta; Rahmel, Axel; Samuel, Undine; Zanen, Wouter; Opelz, Gerhard; Süsal, Caner; Döhler, Bernd; Plotnicki, Lukasz; Kohl, Christian D; Knaup, Petra; Tönshoff, Burkhard

2015-01-01

Patient registries are a useful tool to measure outcomes and compare the effectiveness of therapies in a specific patient population. High data quality and completeness are therefore advantageous for registry analysis. Data integration from multiple sources may increase completeness of the data. The pediatric renal transplantation registry CERTAIN identified Eurotransplant (ET) and the Collaborative Transplant Study (CTS) as possible partners for data exchange. Import and export interfaces with CTS and ET were implemented. All parties reached their projected goals and benefit from the exchange.

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.

Scenario and multiple criteria decision analysis for energy and environmental security of military and industrial installations.

PubMed

Karvetski, Christopher W; Lambert, James H; Linkov, Igor

2011-04-01

Military and industrial facilities need secure and reliable power generation. Grid outages can result in cascading infrastructure failures as well as security breaches and should be avoided. Adding redundancy and increasing reliability can require additional environmental, financial, logistical, and other considerations and resources. Uncertain scenarios consisting of emergent environmental conditions, regulatory changes, growth of regional energy demands, and other concerns result in further complications. Decisions on selecting energy alternatives are made on an ad hoc basis. The present work integrates scenario analysis and multiple criteria decision analysis (MCDA) to identify combinations of impactful emergent conditions and to perform a preliminary benefits analysis of energy and environmental security investments for industrial and military installations. Application of a traditional MCDA approach would require significant stakeholder elicitations under multiple uncertain scenarios. The approach proposed in this study develops and iteratively adjusts a scoring function for investment alternatives to find the scenarios with the most significant impacts on installation security. A robust prioritization of investment alternatives can be achieved by integrating stakeholder preferences and focusing modeling and decision-analytical tools on a few key emergent conditions and scenarios. The approach is described and demonstrated for a campus of several dozen interconnected industrial buildings within a major installation. Copyright © 2010 SETAC.

Identification of molecular markers associated with mite resistance in coconut (Cocos nucifera L.).

PubMed

Shalini, K V; Manjunatha, S; Lebrun, P; Berger, A; Baudouin, L; Pirany, N; Ranganath, R M; Prasad, D Theertha

2007-01-01

Coconut mite (Aceria guerreronis 'Keifer') has become a major threat to Indian coconut (Coçcos nucifera L.) cultivators and the processing industry. Chemical and biological control measures have proved to be costly, ineffective, and ecologically undesirable. Planting mite-resistant coconut cultivars is the most effective method of preventing yield loss and should form a major component of any integrated pest management stratagem. Coconut genotypes, and mite-resistant and -susceptible accessions were collected from different parts of South India. Thirty-two simple sequence repeat (SSR) and 7 RAPD primers were used for molecular analyses. In single-marker analysis, 9 SSR and 4 RAPD markers associated with mite resistance were identified. In stepwise multiple regression analysis of SSRs, a combination of 6 markers showed 100% association with mite infestation. Stepwise multiple regression analysis for RAPD data revealed that a combination of 3 markers accounted for 83.86% of mite resistance in the selected materials. Combined stepwise multiple regression analysis of RAPD and SSR data showed that a combination of 5 markers explained 100% of the association with mite resistance in coconut. Markers associated with mite resistance are important in coconut breeding programs and will facilitate the selection of mite-resistant plants at an early stage as well as mother plants for breeding programs.

PFAAT version 2.0: a tool for editing, annotating, and analyzing multiple sequence alignments.

PubMed

Caffrey, Daniel R; Dana, Paul H; Mathur, Vidhya; Ocano, Marco; Hong, Eun-Jong; Wang, Yaoyu E; Somaroo, Shyamal; Caffrey, Brian E; Potluri, Shobha; Huang, Enoch S

2007-10-11

By virtue of their shared ancestry, homologous sequences are similar in their structure and function. Consequently, multiple sequence alignments are routinely used to identify trends that relate to function. This type of analysis is particularly productive when it is combined with structural and phylogenetic analysis. Here we describe the release of PFAAT version 2.0, a tool for editing, analyzing, and annotating multiple sequence alignments. Support for multiple annotations is a key component of this release as it provides a framework for most of the new functionalities. The sequence annotations are accessible from the alignment and tree, where they are typically used to label sequences or hyperlink them to related databases. Sequence annotations can be created manually or extracted automatically from UniProt entries. Once a multiple sequence alignment is populated with sequence annotations, sequences can be easily selected and sorted through a sophisticated search dialog. The selected sequences can be further analyzed using statistical methods that explicitly model relationships between the sequence annotations and residue properties. Residue annotations are accessible from the alignment viewer and are typically used to designate binding sites or properties for a particular residue. Residue annotations are also searchable, and allow one to quickly select alignment columns for further sequence analysis, e.g. computing percent identities. Other features include: novel algorithms to compute sequence conservation, mapping conservation scores to a 3D structure in Jmol, displaying secondary structure elements, and sorting sequences by residue composition. PFAAT provides a framework whereby end-users can specify knowledge for a protein family in the form of annotation. The annotations can be combined with sophisticated analysis to test hypothesis that relate to sequence, structure and function.

Network-directed cis-mediator analysis of normal prostate tissue expression profiles reveals downstream regulatory associations of prostate cancer susceptibility loci.

PubMed

Larson, Nicholas B; McDonnell, Shannon K; Fogarty, Zach; Larson, Melissa C; Cheville, John; Riska, Shaun; Baheti, Saurabh; Weber, Alexandra M; Nair, Asha A; Wang, Liang; O'Brien, Daniel; Davila, Jaime; Schaid, Daniel J; Thibodeau, Stephen N

2017-10-17

Large-scale genome-wide association studies have identified multiple single-nucleotide polymorphisms associated with risk of prostate cancer. Many of these genetic variants are presumed to be regulatory in nature; however, follow-up expression quantitative trait loci (eQTL) association studies have to-date been restricted largely to cis -acting associations due to study limitations. While trans -eQTL scans suffer from high testing dimensionality, recent evidence indicates most trans -eQTL associations are mediated by cis -regulated genes, such as transcription factors. Leveraging a data-driven gene co-expression network, we conducted a comprehensive cis -mediator analysis using RNA-Seq data from 471 normal prostate tissue samples to identify downstream regulatory associations of previously identified prostate cancer risk variants. We discovered multiple trans -eQTL associations that were significantly mediated by cis -regulated transcripts, four of which involved risk locus 17q12, proximal transcription factor HNF1B , and target trans -genes with known HNF response elements ( MIA2 , SRC , SEMA6A , KIF12 ). We additionally identified evidence of cis -acting down-regulation of MSMB via rs10993994 corresponding to reduced co-expression of NDRG1 . The majority of these cis -mediator relationships demonstrated trans -eQTL replicability in 87 prostate tissue samples from the Gene-Tissue Expression Project. These findings provide further biological context to known risk loci and outline new hypotheses for investigation into the etiology of prostate cancer.

Advanced multivariate data analysis to determine the root cause of trisulfide bond formation in a novel antibody–peptide fusion

PubMed Central

Goldrick, Stephen; Holmes, William; Bond, Nicholas J.; Lewis, Gareth; Kuiper, Marcel; Turner, Richard

2017-01-01

ABSTRACT Product quality heterogeneities, such as a trisulfide bond (TSB) formation, can be influenced by multiple interacting process parameters. Identifying their root cause is a major challenge in biopharmaceutical production. To address this issue, this paper describes the novel application of advanced multivariate data analysis (MVDA) techniques to identify the process parameters influencing TSB formation in a novel recombinant antibody–peptide fusion expressed in mammalian cell culture. The screening dataset was generated with a high‐throughput (HT) micro‐bioreactor system (AmbrTM 15) using a design of experiments (DoE) approach. The complex dataset was firstly analyzed through the development of a multiple linear regression model focusing solely on the DoE inputs and identified the temperature, pH and initial nutrient feed day as important process parameters influencing this quality attribute. To further scrutinize the dataset, a partial least squares model was subsequently built incorporating both on‐line and off‐line process parameters and enabled accurate predictions of the TSB concentration at harvest. Process parameters identified by the models to promote and suppress TSB formation were implemented on five 7 L bioreactors and the resultant TSB concentrations were comparable to the model predictions. This study demonstrates the ability of MVDA to enable predictions of the key performance drivers influencing TSB formation that are valid also upon scale‐up. Biotechnol. Bioeng. 2017;114: 2222–2234. © 2017 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc. PMID:28500668

A meta-analysis of multiple myeloma risk regions in African and European ancestry populations identifies putatively functional loci

PubMed Central

Rand, Kristin A.; Song, Chi; Dean, Eric; Serie, Daniel J.; Curtin, Karen; Sheng, Xin; Hu, Donglei; Huff, Carol Ann; Bernal-Mizrachi, Leon; Tomasson, Michael H.; Ailawadhi, Sikander; Singhal, Seema; Pawlish, Karen; Peters, Edward S.; Bock, Cathryn H.; Stram, Alex; Van Den Berg, David J; Edlund, Christopher K.; V.Conti, David; Zimmerman, Todd; Hwang, Amie E.; Huntsman, Scott; Graff, John; Nooka, Ajay; Kong, Yinfei; Pregja, Silvana L.; Berndt, Sonja I.; Blot, William J.; Carpten, John; Casey, Graham; Chu, Lisa; Diver, W. Ryan; Stevens, Victoria L.; Lieber, Michael R.; Goodman, Phyllis J.; Hennis, Anselm J.M.; Hsing, Ann W.; Mehta, Jayesh; Kittles, Rick A.; Kolb, Suzanne; Klein, Eric A.; Leske, Cristina; Murphy, Adam B.; Nemesure, Barbara; Neslund-Dudas, Christine; Strom, Sara S.; Vij, Ravi; Rybicki, Benjamin A.; Stanford, Janet L.; Signorello, Lisa B.; Witte, John S.; Ambrosone, Christine B.; Bhatti, Parveen; John, Esther M.; Bernstein, Leslie; Zheng, Wei; Olshan, Andrew F.; Hu, Jennifer J.; Ziegler, Regina G.; Nyante, Sarah J.; Bandera, Elisa V.; Birmann, Brenda M.; Ingles, Sue A.; Press, Michael F.; Atanackovic, Djordje; Glenn, Martha J.; Cannon-Albright, Lisa A.; Jones, Brandt; Tricot, Guido; Martin, Thomas G.; Kumar, Shaji K.; Wolf, Jeffrey L.; Deming, Sandra L.; Rothman, Nathaniel; Brooks-Wilson, Angela R.; Rajkumar, S. Vincent; Kolonel, Laurence N.; Chanock, Stephen J.; Slager, Susan L.; Severson, Richard K.; Janakiraman, Nalini; Terebelo, Howard R.; Brown, Elizabeth E.; De Roos, Anneclaire J.; Mohrbacher, Ann F.; Colditz, Graham A.; Giles, Graham G.; Spinelli, John J.; Chiu, Brian C.; Munshi, Nikhil C.; Anderson, Kenneth C.; Levy, Joan; Zonder, Jeffrey A.; Orlowski, Robert Z.; Lonial, Sagar; Camp, Nicola J.; Vachon, Celine M.; Ziv, Elad; Stram, Daniel O.; Hazelett, Dennis J.; Haiman, Christopher A.; Cozen, Wendy

2017-01-01

Background Genome-wide association studies (GWAS) in European populations have identified genetic risk variants associated with multiple myeloma (MM). Methods We performed association testing of common variation in eight regions in 1,264 MM patients and 1,479 controls of European ancestry (EA) and 1,305 MM patients and 7,078 controls of African ancestry (AA) and conducted a meta-analysis to localize the signals, with epigenetic annotation used to predict functionality. Results We found that variants in 7p15.3, 17p11.2, 22q13.1 were statistically significantly (p<0.05) associated with MM risk in AAs and EAs and the variant in 3p22.1 was associated in EAs only. In a combined AA-EA meta-analysis, variation in five regions (2p23.3, 3p22.1, 7p15.3, 17p11.2, 22q13.1) was statistically signficantly associated with MM risk. In 3p22.1, the correlated variants clustered within the gene body of ULK4. Correlated variants in 7p15.3 clustered around an enhancer at the 3′ end of the CDCA7L transcription termination site. A missense variant at 17p11.2 (rs34562254, Pro251Leu, OR=1.32, p=2.93×10−7) in TNFRSF13B, encodes a lymphocyte-specific protein in the tumor necrosis factor receptor family that interacts with the NF-κB pathway. SNPs correlated with the index signal in 22q13.1 cluster around the promoter and enhancer regions of CBX7. Conclusions We found that reported MM susceptibility regions contain risk variants important across populations supporting the use of multiple racial/ethnic groups with different underlying genetic architecture to enhance the localization and identification of putatively functional alleles. Impact A subset of reported risk loci for multiple myeloma have consistent affects across populations and are likely to be functional. PMID:27587788

Deciphering the associations between gene expression and copy number alteration using a sparse double Laplacian shrinkage approach

PubMed Central

Shi, Xingjie; Zhao, Qing; Huang, Jian; Xie, Yang; Ma, Shuangge

2015-01-01

Motivation: Both gene expression levels (GEs) and copy number alterations (CNAs) have important biological implications. GEs are partly regulated by CNAs, and much effort has been devoted to understanding their relations. The regulation analysis is challenging with one gene expression possibly regulated by multiple CNAs and one CNA potentially regulating the expressions of multiple genes. The correlations among GEs and among CNAs make the analysis even more complicated. The existing methods have limitations and cannot comprehensively describe the regulation. Results: A sparse double Laplacian shrinkage method is developed. It jointly models the effects of multiple CNAs on multiple GEs. Penalization is adopted to achieve sparsity and identify the regulation relationships. Network adjacency is computed to describe the interconnections among GEs and among CNAs. Two Laplacian shrinkage penalties are imposed to accommodate the network adjacency measures. Simulation shows that the proposed method outperforms the competing alternatives with more accurate marker identification. The Cancer Genome Atlas data are analysed to further demonstrate advantages of the proposed method. Availability and implementation: R code is available at http://works.bepress.com/shuangge/49/ Contact: shuangge.ma@yale.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26342102

FIA: An Open Forensic Integration Architecture for Composing Digital Evidence

NASA Astrophysics Data System (ADS)

Raghavan, Sriram; Clark, Andrew; Mohay, George

The analysis and value of digital evidence in an investigation has been the domain of discourse in the digital forensic community for several years. While many works have considered different approaches to model digital evidence, a comprehensive understanding of the process of merging different evidence items recovered during a forensic analysis is still a distant dream. With the advent of modern technologies, pro-active measures are integral to keeping abreast of all forms of cyber crimes and attacks. This paper motivates the need to formalize the process of analyzing digital evidence from multiple sources simultaneously. In this paper, we present the forensic integration architecture (FIA) which provides a framework for abstracting the evidence source and storage format information from digital evidence and explores the concept of integrating evidence information from multiple sources. The FIA architecture identifies evidence information from multiple sources that enables an investigator to build theories to reconstruct the past. FIA is hierarchically composed of multiple layers and adopts a technology independent approach. FIA is also open and extensible making it simple to adapt to technological changes. We present a case study using a hypothetical car theft case to demonstrate the concepts and illustrate the value it brings into the field.

Interventional effects for mediation analysis with multiple mediators

PubMed Central

Vansteelandt, Stijn; Daniel, Rhian M.

2016-01-01

The mediation formula for the identification of natural (in)direct effects has facilitated mediation analyses that better respect the nature of the data, with greater consideration of the need for confounding control. The default assumptions on which it relies are strong, however. In particular, they are known to be violated when confounders of the mediator–outcome association are affected by the exposure. This complicates extensions of counterfactual-based mediation analysis to settings that involve repeatedly measured mediators, or multiple correlated mediators. VanderWeele, Vansteelandt, and Robins21 introduced so-called interventional (in)direct effects. These can be identified under much weaker conditions than natural (in)direct effects, but have the drawback of not adding up to the total effect. In this article, we adapt their proposal in order to achieve an exact decomposition of the total effect, and extend it to the multiple mediator setting. Interestingly, the proposed effects capture the path-specific effects of an exposure on an outcome that are mediated by distinct mediators, even when – as often – the structural dependence between the multiple mediators is unknown; for instance, when the direction of the causal effects between the mediators is unknown, or there may be unmeasured common causes of the mediators. PMID:27922534

Interventional Effects for Mediation Analysis with Multiple Mediators.

PubMed

Vansteelandt, Stijn; Daniel, Rhian M

2017-03-01

The mediation formula for the identification of natural (in)direct effects has facilitated mediation analyses that better respect the nature of the data, with greater consideration of the need for confounding control. The default assumptions on which it relies are strong, however. In particular, they are known to be violated when confounders of the mediator-outcome association are affected by the exposure. This complicates extensions of counterfactual-based mediation analysis to settings that involve repeatedly measured mediators, or multiple correlated mediators. VanderWeele, Vansteelandt, and Robins introduced so-called interventional (in)direct effects. These can be identified under much weaker conditions than natural (in)direct effects, but have the drawback of not adding up to the total effect. In this article, we adapt their proposal to achieve an exact decomposition of the total effect, and extend it to the multiple mediator setting. Interestingly, the proposed effects capture the path-specific effects of an exposure on an outcome that are mediated by distinct mediators, even when-as often-the structural dependence between the multiple mediators is unknown, for instance, when the direction of the causal effects between the mediators is unknown, or there may be unmeasured common causes of the mediators.

Limited Agreement of Independent RNAi Screens for Virus-Required Host Genes Owes More to False-Negative than False-Positive Factors

PubMed Central

Wang, Zhishi; Craven, Mark; Newton, Michael A.; Ahlquist, Paul

2013-01-01

Systematic, genome-wide RNA interference (RNAi) analysis is a powerful approach to identify gene functions that support or modulate selected biological processes. An emerging challenge shared with some other genome-wide approaches is that independent RNAi studies often show limited agreement in their lists of implicated genes. To better understand this, we analyzed four genome-wide RNAi studies that identified host genes involved in influenza virus replication. These studies collectively identified and validated the roles of 614 cell genes, but pair-wise overlap among the four gene lists was only 3% to 15% (average 6.7%). However, a number of functional categories were overrepresented in multiple studies. The pair-wise overlap of these enriched-category lists was high, ∼19%, implying more agreement among studies than apparent at the gene level. Probing this further, we found that the gene lists implicated by independent studies were highly connected in interacting networks by independent functional measures such as protein-protein interactions, at rates significantly higher than predicted by chance. We also developed a general, model-based approach to gauge the effects of false-positive and false-negative factors and to estimate, from a limited number of studies, the total number of genes involved in a process. For influenza virus replication, this novel statistical approach estimates the total number of cell genes involved to be ∼2,800. This and multiple other aspects of our experimental and computational results imply that, when following good quality control practices, the low overlap between studies is primarily due to false negatives rather than false-positive gene identifications. These results and methods have implications for and applications to multiple forms of genome-wide analysis. PMID:24068911

Quantifying site-specific physical heterogeneity within an estuarine seascape

USGS Publications Warehouse

Kennedy, Cristina G.; Mather, Martha E.; Smith, Joseph M.

2017-01-01

Quantifying physical heterogeneity is essential for meaningful ecological research and effective resource management. Spatial patterns of multiple, co-occurring physical features are rarely quantified across a seascape because of methodological challenges. Here, we identified approaches that measured total site-specific heterogeneity, an often overlooked aspect of estuarine ecosystems. Specifically, we examined 23 metrics that quantified four types of common physical features: (1) river and creek confluences, (2) bathymetric variation including underwater drop-offs, (3) land features such as islands/sandbars, and (4) major underwater channel networks. Our research at 40 sites throughout Plum Island Estuary (PIE) provided solutions to two problems. The first problem was that individual metrics that measured heterogeneity of a single physical feature showed different regional patterns. We solved this first problem by combining multiple metrics for a single feature using a within-physical feature cluster analysis. With this approach, we identified sites with four different types of confluences and three different types of underwater drop-offs. The second problem was that when multiple physical features co-occurred, new patterns of total site-specific heterogeneity were created across the seascape. This pattern of total heterogeneity has potential ecological relevance to structure-oriented predators. To address this second problem, we identified sites with similar types of total physical heterogeneity using an across-physical feature cluster analysis. Then, we calculated an additive heterogeneity index, which integrated all physical features at a site. Finally, we tested if site-specific additive heterogeneity index values differed for across-physical feature clusters. In PIE, the sites with the highest additive heterogeneity index values were clustered together and corresponded to sites where a fish predator, adult striped bass (Morone saxatilis), aggregated in a related acoustic tracking study. In summary, we have shown general approaches to quantifying site-specific heterogeneity.

Network-based analysis of differentially expressed genes in cerebrospinal fluid (CSF) and blood reveals new candidate genes for multiple sclerosis

PubMed Central

Safari-Alighiarloo, Nahid; Taghizadeh, Mohammad; Tabatabaei, Seyyed Mohammad; Namaki, Saeed

2016-01-01

Background The involvement of multiple genes and missing heritability, which are dominant in complex diseases such as multiple sclerosis (MS), entail using network biology to better elucidate their molecular basis and genetic factors. We therefore aimed to integrate interactome (protein–protein interaction (PPI)) and transcriptomes data to construct and analyze PPI networks for MS disease. Methods Gene expression profiles in paired cerebrospinal fluid (CSF) and peripheral blood mononuclear cells (PBMCs) samples from MS patients, sampled in relapse or remission and controls, were analyzed. Differentially expressed genes which determined only in CSF (MS vs. control) and PBMCs (relapse vs. remission) separately integrated with PPI data to construct the Query-Query PPI (QQPPI) networks. The networks were further analyzed to investigate more central genes, functional modules and complexes involved in MS progression. Results The networks were analyzed and high centrality genes were identified. Exploration of functional modules and complexes showed that the majority of high centrality genes incorporated in biological pathways driving MS pathogenesis. Proteasome and spliceosome were also noticeable in enriched pathways in PBMCs (relapse vs. remission) which were identified by both modularity and clique analyses. Finally, STK4, RB1, CDKN1A, CDK1, RAC1, EZH2, SDCBP genes in CSF (MS vs. control) and CDC37, MAP3K3, MYC genes in PBMCs (relapse vs. remission) were identified as potential candidate genes for MS, which were the more central genes involved in biological pathways. Discussion This study showed that network-based analysis could explicate the complex interplay between biological processes underlying MS. Furthermore, an experimental validation of candidate genes can lead to identification of potential therapeutic targets. PMID:28028462

Complete genomic screen in Parkinson disease: evidence for multiple genes.

PubMed

Scott, W K; Nance, M A; Watts, R L; Hubble, J P; Koller, W C; Lyons, K; Pahwa, R; Stern, M B; Colcher, A; Hiner, B C; Jankovic, J; Ondo, W G; Allen, F H; Goetz, C G; Small, G W; Masterman, D; Mastaglia, F; Laing, N G; Stajich, J M; Slotterbeck, B; Booze, M W; Ribble, R C; Rampersaud, E; West, S G; Gibson, R A; Middleton, L T; Roses, A D; Haines, J L; Scott, B L; Vance, J M; Pericak-Vance, M A

2001-11-14

The relative contribution of genes vs environment in idiopathic Parkinson disease (PD) is controversial. Although genetic studies have identified 2 genes in which mutations cause rare single-gene variants of PD and observational studies have suggested a genetic component, twin studies have suggested that little genetic contribution exists in the common forms of PD. To identify genetic risk factors for idiopathic PD. Genetic linkage study conducted 1995-2000 in which a complete genomic screen (n = 344 markers) was performed in 174 families with multiple individuals diagnosed as having idiopathic PD, identified through probands in 13 clinic populations in the continental United States and Australia. A total of 870 family members were studied: 378 diagnosed as having PD, 379 unaffected by PD, and 113 with unclear status. Logarithm of odds (lod) scores generated from parametric and nonparametric genetic linkage analysis. Two-point parametric maximum parametric lod score (MLOD) and multipoint nonparametric lod score (LOD) linkage analysis detected significant evidence for linkage to 5 distinct chromosomal regions: chromosome 6 in the parkin gene (MLOD = 5.07; LOD = 5.47) in families with at least 1 individual with PD onset at younger than 40 years, chromosomes 17q (MLOD = 2.28; LOD = 2.62), 8p (MLOD = 2.01; LOD = 2.22), and 5q (MLOD = 2.39; LOD = 1.50) overall and in families with late-onset PD, and chromosome 9q (MLOD = 1.52; LOD = 2.59) in families with both levodopa-responsive and levodopa-nonresponsive patients. Our data suggest that the parkin gene is important in early-onset PD and that multiple genetic factors may be important in the development of idiopathic late-onset PD.

DEIsoM: a hierarchical Bayesian model for identifying differentially expressed isoforms using biological replicates

PubMed Central

Peng, Hao; Yang, Yifan; Zhe, Shandian; Wang, Jian; Gribskov, Michael; Qi, Yuan

2017-01-01

Abstract Motivation High-throughput mRNA sequencing (RNA-Seq) is a powerful tool for quantifying gene expression. Identification of transcript isoforms that are differentially expressed in different conditions, such as in patients and healthy subjects, can provide insights into the molecular basis of diseases. Current transcript quantification approaches, however, do not take advantage of the shared information in the biological replicates, potentially decreasing sensitivity and accuracy. Results We present a novel hierarchical Bayesian model called Differentially Expressed Isoform detection from Multiple biological replicates (DEIsoM) for identifying differentially expressed (DE) isoforms from multiple biological replicates representing two conditions, e.g. multiple samples from healthy and diseased subjects. DEIsoM first estimates isoform expression within each condition by (1) capturing common patterns from sample replicates while allowing individual differences, and (2) modeling the uncertainty introduced by ambiguous read mapping in each replicate. Specifically, we introduce a Dirichlet prior distribution to capture the common expression pattern of replicates from the same condition, and treat the isoform expression of individual replicates as samples from this distribution. Ambiguous read mapping is modeled as a multinomial distribution, and ambiguous reads are assigned to the most probable isoform in each replicate. Additionally, DEIsoM couples an efficient variational inference and a post-analysis method to improve the accuracy and speed of identification of DE isoforms over alternative methods. Application of DEIsoM to an hepatocellular carcinoma (HCC) dataset identifies biologically relevant DE isoforms. The relevance of these genes/isoforms to HCC are supported by principal component analysis (PCA), read coverage visualization, and the biological literature. Availability and implementation The software is available at https://github.com/hao-peng/DEIsoM Contact pengh@alumni.purdue.edu Supplementary information Supplementary data are available at Bioinformatics online. PMID:28595376

Co-LncRNA: investigating the lncRNA combinatorial effects in GO annotations and KEGG pathways based on human RNA-Seq data

PubMed Central

Zhao, Zheng; Bai, Jing; Wu, Aiwei; Wang, Yuan; Zhang, Jinwen; Wang, Zishan; Li, Yongsheng; Xu, Juan; Li, Xia

2015-01-01

Long non-coding RNAs (lncRNAs) are emerging as key regulators of diverse biological processes and diseases. However, the combinatorial effects of these molecules in a specific biological function are poorly understood. Identifying co-expressed protein-coding genes of lncRNAs would provide ample insight into lncRNA functions. To facilitate such an effort, we have developed Co-LncRNA, which is a web-based computational tool that allows users to identify GO annotations and KEGG pathways that may be affected by co-expressed protein-coding genes of a single or multiple lncRNAs. LncRNA co-expressed protein-coding genes were first identified in publicly available human RNA-Seq datasets, including 241 datasets across 6560 total individuals representing 28 tissue types/cell lines. Then, the lncRNA combinatorial effects in a given GO annotations or KEGG pathways are taken into account by the simultaneous analysis of multiple lncRNAs in user-selected individual or multiple datasets, which is realized by enrichment analysis. In addition, this software provides a graphical overview of pathways that are modulated by lncRNAs, as well as a specific tool to display the relevant networks between lncRNAs and their co-expressed protein-coding genes. Co-LncRNA also supports users in uploading their own lncRNA and protein-coding gene expression profiles to investigate the lncRNA combinatorial effects. It will be continuously updated with more human RNA-Seq datasets on an annual basis. Taken together, Co-LncRNA provides a web-based application for investigating lncRNA combinatorial effects, which could shed light on their biological roles and could be a valuable resource for this community. Database URL: http://www.bio-bigdata.com/Co-LncRNA/ PMID:26363020

High-throughput screening (HTS) and hit validation to identify small molecule inhibitors with activity against NS3/4A proteases from multiple hepatitis C virus genotypes.

PubMed

Lee, Hyun; Zhu, Tian; Patel, Kavankumar; Zhang, Yan-Yan; Truong, Lena; Hevener, Kirk E; Gatuz, Joseph L; Subramanya, Gitanjali; Jeong, Hyun-Young; Uprichard, Susan L; Johnson, Michael E

2013-01-01

Development of drug-resistant mutations has been a major problem with all currently developed Hepatitis C Virus (HCV) NS3/4A inhibitors, including the two FDA approved drugs, significantly reducing the efficacy of these inhibitors. The high incidence of drug-resistance mutations and the limited utility of these inhibitors against only genotype 1 highlight the need for novel, broad-spectrum HCV therapies. Here we used high-throughput screening (HTS) to identify low molecular weight inhibitors against NS3/4A from multiple genotypes. A total of 40,967 compounds from four structurally diverse molecular libraries were screened by HTS using fluorescence-based enzymatic assays, followed by an orthogonal binding analysis using surface plasmon resonance (SPR) to eliminate false positives. A novel small molecule compound was identified with an IC50 value of 2.2 µM against the NS3/4A from genotype 1b. Mode of inhibition analysis subsequently confirmed this compound to be a competitive inhibitor with respect to the substrate, indicating direct binding to the protease active site, rather than to the allosteric binding pocket that was discovered to be the binding site of a few recently discovered small molecule inhibitors. This newly discovered inhibitor also showed promising inhibitory activity against the NS3/4As from three other HCV genotypes, as well as five common drug-resistant mutants of genotype 1b NS3/4A. The inhibitor was selective for NS3 from multiple HCV genotypes over two human serine proteases, and a whole cell lysate assay confirmed inhibitory activity in the cellular environment. This compound provides a lead for further development of potentially broader spectrum inhibitors.

Detecting disease-predisposing variants: the haplotype method.

PubMed Central

Valdes, A M; Thomson, G

1997-01-01

For many HLA-associated diseases, multiple alleles-- and, in some cases, multiple loci--have been suggested as the causative agents. The haplotype method for identifying disease-predisposing amino acids in a genetic region is a stratification analysis. We show that, for each haplotype combination containing all the amino acid sites involved in the disease process, the relative frequencies of amino acid variants at sites not involved in disease but in linkage disequilibrium with the disease-predisposing sites are expected to be the same in patients and controls. The haplotype method is robust to mode of inheritance and penetrance of the disease and can be used to determine unequivocally whether all amino acid sites involved in the disease have not been identified. Using a resampling technique, we developed a statistical test that takes account of the nonindependence of the sites sampled. Further, when multiple sites in the genetic region are involved in disease, the test statistic gives a closer fit to the null expectation when some--compared with none--of the true predisposing factors are included in the haplotype analysis. Although the haplotype method cannot distinguish between very highly correlated sites in one population, ethnic comparisons may help identify the true predisposing factors. The haplotype method was applied to insulin-dependent diabetes mellitus (IDDM) HLA class II DQA1-DQB1 data from Caucasian, African, and Japanese populations. Our results indicate that the combination DQA1#52 (Arg predisposing) DQB1#57 (Asp protective), which has been proposed as an important IDDM agent, does not include all the predisposing elements. With rheumatoid arthritis HLA class II DRB1 data, the results were consistent with the shared-epitope hypothesis. PMID:9042931

Turning challenges into design principles: Telemonitoring systems for patients with multiple chronic conditions.

PubMed

Sultan, Mehwish; Kuluski, Kerry; McIsaac, Warren J; Cafazzo, Joseph A; Seto, Emily

2018-01-01

People with multiple chronic conditions often struggle with managing their health. The purpose of this research was to identify specific challenges of patients with multiple chronic conditions and to use the findings to form design principles for a telemonitoring system tailored for these patients. Semi-structured interviews with 15 patients with multiple chronic conditions and 10 clinicians were conducted to gain an understanding of their needs and preferences for a smartphone-based telemonitoring system. The interviews were analyzed using a conventional content analysis technique, resulting in six themes. Design principles developed from the themes included that the system must be modular to accommodate various combinations of conditions, reinforce a routine, consolidate record keeping, as well as provide actionable feedback to the patients. Designing an application for multiple chronic conditions is complex due to variability in patient conditions, and therefore, design principles developed in this study can help with future innovations aimed to help manage this population.

Perspectives of Patients, Clinicians, and Health System Leaders on Changes Needed to Improve the Health Care and Outcomes of Older Adults With Multiple Chronic Conditions.

PubMed

Ferris, Rosie; Blaum, Caroline; Kiwak, Eliza; Austin, Janet; Esterson, Jessica; Harkless, Gene; Oftedahl, Gary; Parchman, Michael; Van Ness, Peter H; Tinetti, Mary E

2018-06-01

To ascertain perspectives of multiple stakeholders on contributors to inappropriate care for older adults with multiple chronic conditions. Perspectives of 36 purposively sampled patients, clinicians, health systems, and payers were elicited. Data analysis followed a constant comparative method. Structural factors triggering burden and fragmentation include disease-based quality metrics and need to interact with multiple clinicians. The key cultural barrier identified is the assumption that "physicians know best." Inappropriate decision making may result from inattention to trade-offs and adherence to multiple disease guidelines. Stakeholders recommended changes in culture, structure, and decision making. Care options and quality metrics should reflect a focus on patients' priorities. Clinician-patient partnerships should reflect patients knowing their health goals and clinicians knowing how to achieve them. Access to specialty expertise should not require visits. Stakeholders' recommendations suggest health care redesigns that incorporate patients' health priorities into care decisions and realign relationships across patients and clinicians.

Multiple large solar lentigos on the upper back as clinical markers of past severe sunburn: a case-control study.

PubMed

Derancourt, C; Bourdon-Lanoy, E; Grob, J-J; Guillaume, J-C; Bernard, P; Bastuji-Garin, S

2007-01-01

Multiple solar lentigos commonly seen on the upper back and shoulders of adults are classically considered as a sign of photodamage, although epidemiological studies are scarce. To assess whether these lesions are clinical markers of past severe sunburn. A case-control study in two outpatient dermatology clinics in French university hospitals. Past episodes of moderate and severe sunburn were compared between 145 adult patients with multiple solar lentigos on the upper back and 145 matched controls. In multivariate analysis adjusted for potential confounders, recalled episodes of sunburn during childhood, adolescence and adulthood were independently associated with the presence of multiple solar lentigos (adjusted odds ratios, 95% confidence intervals: 2.3 (1.1-5.2) and 28.1 (10.4-75.6) for moderate and severe sunburn, respectively). Multiple solar lentigos on the upper back and shoulders of adults are potential clinical markers of past severe sunburn which may thus be used to identify a population at higher risk of developing cutaneous malignant melanoma.

Understanding genetics: Analysis of secondary students' conceptual status

NASA Astrophysics Data System (ADS)

Tsui, Chi-Yan; Treagust, David F.

2007-02-01

This article explores the conceptual change of students in Grades 10 and 12 in three Australian senior high schools when the teachers included computer multimedia to a greater or lesser extent in their teaching of a genetics course. The study, underpinned by a multidimensional conceptual-change framework, used an interpretive approach and a case-based design with multiple data collection methods. Over 4-8 weeks, the students learned genetics in classroom lessons that included BioLogica activities, which feature multiple representations. Results of the online tests and interview tasks revealed that most students improved their understanding of genetics as evidenced in the development of genetics reasoning. However, using Thorley's (1990) status analysis categories, a cross-case analysis of the gene conceptions of 9 of the 26 students interviewed indicated that only 4 students' postinstructional conceptions were intelligible-plausible-fruitful. Students' conceptual change was consistent with classroom teaching and learning. Findings suggested that multiple representations supported conceptual understanding of genetics but not in all students. It was also shown that status can be a viable hallmark enabling researchers to identify students' conceptual change that would otherwise be less accessible. Thorley's method for analyzing conceptual status is discussed.

An Updated Meta-Analysis of Risk of Multiple Sclerosis following Infectious Mononucleosis

PubMed Central

Handel, Adam E.; Williamson, Alexander J.; Disanto, Giulio; Handunnetthi, Lahiru; Giovannoni, Gavin; Ramagopalan, Sreeram V.

2010-01-01

Background Multiple sclerosis (MS) appears to develop in genetically susceptible individuals as a result of environmental exposures. Epstein-Barr virus (EBV) infection is an almost universal finding among individuals with MS. Symptomatic EBV infection as manifested by infectious mononucleosis (IM) has been shown in a previous meta-analysis to be associated with the risk of MS, however a number of much larger studies have since been published. Methods/Principal Findings We performed a Medline search to identify articles published since the original meta-analysis investigating MS risk following IM. A total of 18 articles were included in this study, including 19390 MS patients and 16007 controls. We calculated the relative risk of MS following IM using a generic inverse variance with random effects model. This showed that the risk of MS was strongly associated with IM (relative risk (RR) 2.17; 95% confidence interval 1.97–2.39; p<10−54). Discussion Our results establish firmly that a history of infectious mononucleosis significantly increases the risk of multiple sclerosis. Future work should focus on the mechanism of this association and interaction with other risk factors. PMID:20824132

Global Profiling and Novel Structure Discovery Using Multiple Neutral Loss/Precursor Ion Scanning Combined with Substructure Recognition and Statistical Analysis (MNPSS): Characterization of Terpene-Conjugated Curcuminoids in Curcuma longa as a Case Study.

PubMed

Qiao, Xue; Lin, Xiong-hao; Ji, Shuai; Zhang, Zheng-xiang; Bo, Tao; Guo, De-an; Ye, Min

2016-01-05

To fully understand the chemical diversity of an herbal medicine is challenging. In this work, we describe a new approach to globally profile and discover novel compounds from an herbal extract using multiple neutral loss/precursor ion scanning combined with substructure recognition and statistical analysis. Turmeric (the rhizomes of Curcuma longa L.) was used as an example. This approach consists of three steps: (i) multiple neutral loss/precursor ion scanning to obtain substructure information; (ii) targeted identification of new compounds by extracted ion current and substructure recognition; and (iii) untargeted identification using total ion current and multivariate statistical analysis to discover novel structures. Using this approach, 846 terpecurcumins (terpene-conjugated curcuminoids) were discovered from turmeric, including a number of potentially novel compounds. Furthermore, two unprecedented compounds (terpecurcumins X and Y) were purified, and their structures were identified by NMR spectroscopy. This study extended the application of mass spectrometry to global profiling of natural products in herbal medicines and could help chemists to rapidly discover novel compounds from a complex matrix.

Comparative transcript profiling of fertile and sterile flower buds from multiple-allele-inherited male sterility in Chinese cabbage (Brassica campestris L. ssp. pekinensis).

PubMed

Zhou, Xue; Liu, Zhiyong; Ji, Ruiqin; Feng, Hui

2017-10-01

We studied the underlying causes of multiple-allele-inherited male sterility in Chinese cabbage (Brassica campestris L. ssp. pekinensis) by identifying differentially expressed genes (DEGs) related to pollen sterility between fertile and sterile flower buds. In this work, we verified the stages of sterility microscopically and then performed transcriptome analysis of mRNA isolated from fertile and sterile buds using Illumina HiSeq 2000 platform sequencing. Approximately 80% of ~229 million high-quality paired-end reads were uniquely mapped to the reference genome. In sterile buds, 699 genes were significantly up-regulated and 4096 genes were down-regulated. Among the DEGs, 28 pollen cell wall-related genes, 54 transcription factor genes, 45 phytohormone-related genes, 20 anther and pollen-related genes, 212 specifically expressed transcripts, and 417 DEGs located on linkage group A07 were identified. Six transcription factor genes BrAMS, BrMS1, BrbHLH089, BrbHLH091, BrAtMYB103, and BrANAC025 were identified as putative sterility-related genes. The weak auxin signal that is regulated by BrABP1 may be one of the key factors causing pollen sterility observed here. Moreover, several significantly enriched GO terms such as "cell wall organization or biogenesis" (GO:0071554), "intrinsic to membrane" (GO:0031224), "integral to membrane" (GO:0016021), "hydrolase activity, acting on ester bonds" (GO:0016788), and one significantly enriched pathway "starch and sucrose metabolism" (ath00500) were identified in this work. qRT-PCR, PCR, and in situ hybridization experiments validated our RNA-seq transcriptome analysis as accurate and reliable. This study will lay the foundation for elucidating the molecular mechanism(s) that underly sterility and provide valuable information for studying multiple-allele-inherited male sterility in the Chinese cabbage line 'AB01'.

Genetic stability of Brucella abortus isolates from an outbreak by multiple-locus variable-number tandem repeat analysis (MLVA16)

PubMed Central

2014-01-01

Background Brucellosis caused by Brucella abortus is one of the most important zoonoses in the world. Multiple-locus variable-number tandem repeat analysis (MLVA16) has been shown be a useful tool to epidemiological traceback studies in B. abortus infection. Thus, the present study aimed (i) to evaluate the genetic diversity of B. abortus isolates from a brucellosis outbreak, and (ii) to investigate the in vivo stability of the MLVA16 markers. Results Three-hundred and seventy-five clinical samples, including 275 vaginal swabs and 100 milk samples, were cultured from a brucellosis outbreak in a cattle herd, which adopted RB51 vaccination and test-and-slaughter policies. Thirty-seven B. abortus isolates were obtained, eight from milk and twenty-nine from post-partum/abortion vaginal swabs, which were submitted to biotyping and genotyping by MLVA16. Twelve B. abortus isolates obtained from vaginal swabs were identified as RB51. Twenty four isolates, seven obtained from milk samples and seventeen from vaginal swabs, were identified as B. abortus biovar 3, while one isolate from vaginal swabs was identified as B. abortus biovar 1. Three distinct genotypes were observed during the brucellosis outbreak: RB observed in all isolates identified as RB51; W observed in all B. abortus biovar 3 isolates; and Z observed in the single B. abortus biovar 1 isolate. Epidemiological and molecular data show that the B. abortus biovar 1 genotype Z strain is not related to the B. abortus biovar 3 genotype W isolates, and represents a new introduction B. abortus during the outbreak. Conclusions The results of the present study on typing of multiple clinical B. abortus isolates from the same outbreak over a sixteen month period indicate the in vivo stability of MLVA16 markers, a low genetic diversity among B. abortus isolates and the usefulness of MLVA16 for epidemiological studies of bovine brucellosis. PMID:25015840

Modeled interactive effects of precipitation, temperature, and [CO2] on ecosystem carbon and water dynamics in different climatic zones

Treesearch

Yiqi Luo; Dieter Gerten; Guerric Le Maire; William J. Parton; Ensheng Weng; Xuhui Zhou; Cindy Keough; Claus Beier; Philippe Ciais; Wolfgang Cramer; Jeffrey S. Dukes; Bridget Emmett; Paul J. Hanson; Alan Knapp; Sune Linder; Dan Nepstad; Lindsey. Rustad

2008-01-01

Interactive effects of multiple global change factors on ecosystem processes are complex. It is relatively expensive to explore those interactions in manipulative experiments. We conducted a modeling analysis to identify potentially important interactions and to stimulate hypothesis formulation for experimental research. Four models were used to quantify interactive...

Model Analysis of Fine Structures of Student Models: An Example with Newton's Third Law.

ERIC Educational Resources Information Center

Bao, Lei; Hogg, Kirsten; Zollman, Dean

2002-01-01

Studies the role of context in students' uses of alternative conceptual models by using Newton's third law. Identifies four contextual features that are frequently used by students in their reasoning. Probes the effects of specific contextual features on student reasoning using a multiple-choice survey. (Contains 39 references.) (Author/YDS)

The Counseling Opportunity Structure: Examining Correlates of Four-Year College-Going Rates

ERIC Educational Resources Information Center

Engberg, Mark E.; Gilbert, Aliza J.

2014-01-01

This study examines the relationships between the normative and resource dimensions of a high school counseling department and four-year college-going rates. Utilizing data from the High School Longitudinal Study of 2009 (HSLS: 09), we employ multiple regression and latent class analysis to identify salient factors related to the college-going…

Which Variables Associated with Data-Driven Instruction Are Believed to Best Predict Urban Student Achievement?

ERIC Educational Resources Information Center

Greer, Wil

2013-01-01

This study identified the variables associated with data-driven instruction (DDI) that are perceived to best predict student achievement. Of the DDI variables discussed in the literature, 51 of them had a sufficient enough research base to warrant statistical analysis. Of them, 26 were statistically significant. Multiple regression and an…

US exposure to multiple landscape stressors and climate change

Treesearch

Becky K. Kerns; John B. Kim; Jeffrey D. Kline; Michelle A. Day

2016-01-01

We examined landscape exposure to wildfire potential, insects and disease risk, and urban and exurban development for the conterminous US (CONUS). Our analysis relied on spatial data used by federal agencies to evaluate these stressors nationally. We combined stressor data with a climate change exposure metric to identify when temperature is likely to depart from...

Aggressive Students and High School Dropout: An Event History Analysis

ERIC Educational Resources Information Center

Orozco, Steven R.

2016-01-01

Aggressive students often struggle in multiple domains of their school functioning and are at increased risk for high school dropout. Research has identified a variety of warning flags which are strong predictors of high school dropout. While it is known that aggressive students exhibit many of these warning flags, there is little research which…

Restructuring Schools in Chester Upland, Pennsylvania: An Analysis of State and District Efforts. ECS Policy Brief

ERIC Educational Resources Information Center

Rhim, Lauren Morando

2005-01-01

Restructuring is a process initiated to substantively change the governance, operation and instruction of public schools or districts identified as failing. There are multiple definitions of restructuring, but the common thread binding all restructuring models is a substantive change of the standard operating procedures of a school or an entire…

Cloning and characterization of a novel oocyte-specific gene encoding an F-Box protein in rainbow trout (Oncorhynchus mykiss)

USDA-ARS?s Scientific Manuscript database

Oocyte-specific genes play critical roles in oogenesis, folliculogenesis and early embryonic development. Through analysis of expressed sequence tags (ESTs) from a rainbow trout oocyte cDNA library, we identified a novel transcript which is represented by multiple ESTs derived only from the oocyte c...

Using Additional Analyses to Clarify the Functions of Problem Behavior: An Analysis of Two Cases

ERIC Educational Resources Information Center

Payne, Steven W.; Dozier, Claudia L.; Neidert, Pamela L.; Jowett, Erica S.; Newquist, Matthew H.

2014-01-01

Functional analyses (FA) have proven useful for identifying contingencies that influence problem behavior. Research has shown that some problem behavior may only occur in specific contexts or be influenced by multiple or idiosyncratic variables. When these contexts or sources of influence are not assessed in an FA, further assessment may be…

The Heart of School Improvement: A Multi-Site Case Study of Leadership for Teacher Learning in Vietnam

ERIC Educational Resources Information Center

Tran, Ngoc H.; Hallinger, Philip; Truong, Thang

2018-01-01

This study addressed the research question: How do Vietnamese principals lead the professional learning of teachers? The research was comprised of a multiple-site case study of leadership and teacher learning in four Vietnamese schools. Qualitative data analysis aimed at identifying modal practices adopted by these Vietnamese principals to lead…

Lessons for Co-Innovation in Agricultural Innovation Systems: A Multiple Case Study Analysis and a Conceptual Model

ERIC Educational Resources Information Center

Fielke, Simon J.; Botha, Neels; Reid, Janet; Gray, David; Blackett, Paula; Park, Nicola; Williams, Tracy

2018-01-01

Purpose: This paper highlights important lessons for co-innovation drawn from three ex-post case study innovation projects implemented within three sub-sectors of the primary industry sector in New Zealand. Design/methodology/approach: The characteristics that fostered co-innovation in each innovation project case study were identified from…

Chair Perceptions of Trust between Mentor and Mentee in Online Doctoral Dissertation Mentoring

ERIC Educational Resources Information Center

Rademaker, Linnea L.; Duffy, Jennifer O'Connor; Wetzler, Elizabeth; Zaikina-Montgomery, Helen

2016-01-01

We explored online dissertation chairs' perceptions of trust in the mentor-mentee relationship, as trust was identified as a crucial factor in the success of doctoral students. Through the implementation of a multiple-case study, and a qualitative, online questionnaire, and through qualitative data analysis, we discovered 16 chairs' perceptions of…

Authentic Early Experience in Medical Education: A Socio-Cultural Analysis Identifying Important Variables in Learning Interactions within Workplaces

ERIC Educational Resources Information Center

Yardley, Sarah; Brosnan, Caragh; Richardson, Jane; Hays, Richard

2013-01-01

This paper addresses the question "what are the variables influencing social interactions and learning during Authentic Early Experience (AEE)?" AEE is a complex educational intervention for new medical students. Following critique of the existing literature, multiple qualitative methods were used to create a study framework conceptually…

Gene- and pathway-based association tests for multiple traits with GWAS summary statistics.

PubMed

Kwak, Il-Youp; Pan, Wei

2017-01-01

To identify novel genetic variants associated with complex traits and to shed new insights on underlying biology, in addition to the most popular single SNP-single trait association analysis, it would be useful to explore multiple correlated (intermediate) traits at the gene- or pathway-level by mining existing single GWAS or meta-analyzed GWAS data. For this purpose, we present an adaptive gene-based test and a pathway-based test for association analysis of multiple traits with GWAS summary statistics. The proposed tests are adaptive at both the SNP- and trait-levels; that is, they account for possibly varying association patterns (e.g. signal sparsity levels) across SNPs and traits, thus maintaining high power across a wide range of situations. Furthermore, the proposed methods are general: they can be applied to mixed types of traits, and to Z-statistics or P-values as summary statistics obtained from either a single GWAS or a meta-analysis of multiple GWAS. Our numerical studies with simulated and real data demonstrated the promising performance of the proposed methods. The methods are implemented in R package aSPU, freely and publicly available at: https://cran.r-project.org/web/packages/aSPU/ CONTACT: weip@biostat.umn.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Structured association analysis leads to insight into Saccharomyces cerevisiae gene regulation by finding multiple contributing eQTL hotspots associated with functional gene modules.

PubMed

Curtis, Ross E; Kim, Seyoung; Woolford, John L; Xu, Wenjie; Xing, Eric P

2013-03-21

Association analysis using genome-wide expression quantitative trait locus (eQTL) data investigates the effect that genetic variation has on cellular pathways and leads to the discovery of candidate regulators. Traditional analysis of eQTL data via pairwise statistical significance tests or linear regression does not leverage the availability of the structural information of the transcriptome, such as presence of gene networks that reveal correlation and potentially regulatory relationships among the study genes. We employ a new eQTL mapping algorithm, GFlasso, which we have previously developed for sparse structured regression, to reanalyze a genome-wide yeast dataset. GFlasso fully takes into account the dependencies among expression traits to suppress false positives and to enhance the signal/noise ratio. Thus, GFlasso leverages the gene-interaction network to discover the pleiotropic effects of genetic loci that perturb the expression level of multiple (rather than individual) genes, which enables us to gain more power in detecting previously neglected signals that are marginally weak but pleiotropically significant. While eQTL hotspots in yeast have been reported previously as genomic regions controlling multiple genes, our analysis reveals additional novel eQTL hotspots and, more interestingly, uncovers groups of multiple contributing eQTL hotspots that affect the expression level of functional gene modules. To our knowledge, our study is the first to report this type of gene regulation stemming from multiple eQTL hotspots. Additionally, we report the results from in-depth bioinformatics analysis for three groups of these eQTL hotspots: ribosome biogenesis, telomere silencing, and retrotransposon biology. We suggest candidate regulators for the functional gene modules that map to each group of hotspots. Not only do we find that many of these candidate regulators contain mutations in the promoter and coding regions of the genes, in the case of the Ribi group, we provide experimental evidence suggesting that the identified candidates do regulate the target genes predicted by GFlasso. Thus, this structured association analysis of a yeast eQTL dataset via GFlasso, coupled with extensive bioinformatics analysis, discovers a novel regulation pattern between multiple eQTL hotspots and functional gene modules. Furthermore, this analysis demonstrates the potential of GFlasso as a powerful computational tool for eQTL studies that exploit the rich structural information among expression traits due to correlation, regulation, or other forms of biological dependencies.

Single Molecule Cluster Analysis Identifies Signature Dynamic Conformations along the Splicing Pathway

PubMed Central

Blanco, Mario R.; Martin, Joshua S.; Kahlscheuer, Matthew L.; Krishnan, Ramya; Abelson, John; Laederach, Alain; Walter, Nils G.

2016-01-01

The spliceosome is the dynamic RNA-protein machine responsible for faithfully splicing introns from precursor messenger RNAs (pre-mRNAs). Many of the dynamic processes required for the proper assembly, catalytic activation, and disassembly of the spliceosome as it acts on its pre-mRNA substrate remain poorly understood, a challenge that persists for many biomolecular machines. Here, we developed a fluorescence-based Single Molecule Cluster Analysis (SiMCAn) tool to dissect the manifold conformational dynamics of a pre-mRNA through the splicing cycle. By clustering common dynamic behaviors derived from selectively blocked splicing reactions, SiMCAn was able to identify signature conformations and dynamic behaviors of multiple ATP-dependent intermediates. In addition, it identified a conformation adopted late in splicing by a 3′ splice site mutant, invoking a mechanism for substrate proofreading. SiMCAn presents a novel framework for interpreting complex single molecule behaviors that should prove widely useful for the comprehensive analysis of a plethora of dynamic cellular machines. PMID:26414013

Breast Cancer and Modifiable Lifestyle Factors in Argentinean Women: Addressing Missing Data in a Case-Control Study

PubMed Central

Coquet, Julia Becaria; Tumas, Natalia; Osella, Alberto Ruben; Tanzi, Matteo; Franco, Isabella; Diaz, Maria Del Pilar

2016-01-01

A number of studies have evidenced the effect of modifiable lifestyle factors such as diet, breastfeeding and nutritional status on breast cancer risk. However, none have addressed the missing data problem in nutritional epidemiologic research in South America. Missing data is a frequent problem in breast cancer studies and epidemiological settings in general. Estimates of effect obtained from these studies may be biased, if no appropriate method for handling missing data is applied. We performed Multiple Imputation for missing values on covariates in a breast cancer case-control study of Córdoba (Argentina) to optimize risk estimates. Data was obtained from a breast cancer case control study from 2008 to 2015 (318 cases, 526 controls). Complete case analysis and multiple imputation using chained equations were the methods applied to estimate the effects of a Traditional dietary pattern and other recognized factors associated with breast cancer. Physical activity and socioeconomic status were imputed. Logistic regression models were performed. When complete case analysis was performed only 31% of women were considered. Although a positive association of Traditional dietary pattern and breast cancer was observed from both approaches (complete case analysis OR=1.3, 95%CI=1.0-1.7; multiple imputation OR=1.4, 95%CI=1.2-1.7), effects of other covariates, like BMI and breastfeeding, were only identified when multiple imputation was considered. A Traditional dietary pattern, BMI and breastfeeding are associated with the occurrence of breast cancer in this Argentinean population when multiple imputation is appropriately performed. Multiple Imputation is suggested in Latin America’s epidemiologic studies to optimize effect estimates in the future. PMID:27892664

Multiscale Feature Analysis of Salivary Gland Branching Morphogenesis

PubMed Central

Baydil, Banu; Daley, William P.; Larsen, Melinda; Yener, Bülent

2012-01-01

Pattern formation in developing tissues involves dynamic spatio-temporal changes in cellular organization and subsequent evolution of functional adult structures. Branching morphogenesis is a developmental mechanism by which patterns are generated in many developing organs, which is controlled by underlying molecular pathways. Understanding the relationship between molecular signaling, cellular behavior and resulting morphological change requires quantification and categorization of the cellular behavior. In this study, tissue-level and cellular changes in developing salivary gland in response to disruption of ROCK-mediated signaling by are modeled by building cell-graphs to compute mathematical features capturing structural properties at multiple scales. These features were used to generate multiscale cell-graph signatures of untreated and ROCK signaling disrupted salivary gland organ explants. From confocal images of mouse submandibular salivary gland organ explants in which epithelial and mesenchymal nuclei were marked, a multiscale feature set capturing global structural properties, local structural properties, spectral, and morphological properties of the tissues was derived. Six feature selection algorithms and multiway modeling of the data was performed to identify distinct subsets of cell graph features that can uniquely classify and differentiate between different cell populations. Multiscale cell-graph analysis was most effective in classification of the tissue state. Cellular and tissue organization, as defined by a multiscale subset of cell-graph features, are both quantitatively distinct in epithelial and mesenchymal cell types both in the presence and absence of ROCK inhibitors. Whereas tensor analysis demonstrate that epithelial tissue was affected the most by inhibition of ROCK signaling, significant multiscale changes in mesenchymal tissue organization were identified with this analysis that were not identified in previous biological studies. We here show how to define and calculate a multiscale feature set as an effective computational approach to identify and quantify changes at multiple biological scales and to distinguish between different states in developing tissues. PMID:22403724

Network neighborhood analysis with the multi-node topological overlap measure.

PubMed

Li, Ai; Horvath, Steve

2007-01-15

The goal of neighborhood analysis is to find a set of genes (the neighborhood) that is similar to an initial 'seed' set of genes. Neighborhood analysis methods for network data are important in systems biology. If individual network connections are susceptible to noise, it can be advantageous to define neighborhoods on the basis of a robust interconnectedness measure, e.g. the topological overlap measure. Since the use of multiple nodes in the seed set may lead to more informative neighborhoods, it can be advantageous to define multi-node similarity measures. The pairwise topological overlap measure is generalized to multiple network nodes and subsequently used in a recursive neighborhood construction method. A local permutation scheme is used to determine the neighborhood size. Using four network applications and a simulated example, we provide empirical evidence that the resulting neighborhoods are biologically meaningful, e.g. we use neighborhood analysis to identify brain cancer related genes. An executable Windows program and tutorial for multi-node topological overlap measure (MTOM) based analysis can be downloaded from the webpage (http://www.genetics.ucla.edu/labs/horvath/MTOM/).

Analysis of the SOS response of Vibrio and other bacteria with multiple chromosomes

PubMed Central

2012-01-01

Background The SOS response is a well-known regulatory network present in most bacteria and aimed at addressing DNA damage. It has also been linked extensively to stress-induced mutagenesis, virulence and the emergence and dissemination of antibiotic resistance determinants. Recently, the SOS response has been shown to regulate the activity of integrases in the chromosomal superintegrons of the Vibrionaceae, which encompasses a wide range of pathogenic species harboring multiple chromosomes. Here we combine in silico and in vitro techniques to perform a comparative genomics analysis of the SOS regulon in the Vibrionaceae, and we extend the methodology to map this transcriptional network in other bacterial species harboring multiple chromosomes. Results Our analysis provides the first comprehensive description of the SOS response in a family (Vibrionaceae) that includes major human pathogens. It also identifies several previously unreported members of the SOS transcriptional network, including two proteins of unknown function. The analysis of the SOS response in other bacterial species with multiple chromosomes uncovers additional regulon members and reveals that there is a conserved core of SOS genes, and that specialized additions to this basic network take place in different phylogenetic groups. Our results also indicate that across all groups the main elements of the SOS response are always found in the large chromosome, whereas specialized additions are found in the smaller chromosomes and plasmids. Conclusions Our findings confirm that the SOS response of the Vibrionaceae is strongly linked with pathogenicity and dissemination of antibiotic resistance, and suggest that the characterization of the newly identified members of this regulon could provide key insights into the pathogenesis of Vibrio. The persistent location of key SOS genes in the large chromosome across several bacterial groups confirms that the SOS response plays an essential role in these organisms and sheds light into the mechanisms of evolution of global transcriptional networks involved in adaptability and rapid response to environmental changes, suggesting that small chromosomes may act as evolutionary test beds for the rewiring of transcriptional networks. PMID:22305460

Multiple fMRI system-level baseline connectivity is disrupted in patients with consciousness alterations.

PubMed

Demertzi, Athena; Gómez, Francisco; Crone, Julia Sophia; Vanhaudenhuyse, Audrey; Tshibanda, Luaba; Noirhomme, Quentin; Thonnard, Marie; Charland-Verville, Vanessa; Kirsch, Murielle; Laureys, Steven; Soddu, Andrea

2014-03-01

In healthy conditions, group-level fMRI resting state analyses identify ten resting state networks (RSNs) of cognitive relevance. Here, we aim to assess the ten-network model in severely brain-injured patients suffering from disorders of consciousness and to identify those networks which will be most relevant to discriminate between patients and healthy subjects. 300 fMRI volumes were obtained in 27 healthy controls and 53 patients in minimally conscious state (MCS), vegetative state/unresponsive wakefulness syndrome (VS/UWS) and coma. Independent component analysis (ICA) reduced data dimensionality. The ten networks were identified by means of a multiple template-matching procedure and were tested on neuronality properties (neuronal vs non-neuronal) in a data-driven way. Univariate analyses detected between-group differences in networks' neuronal properties and estimated voxel-wise functional connectivity in the networks, which were significantly less identifiable in patients. A nearest-neighbor "clinical" classifier was used to determine the networks with high between-group discriminative accuracy. Healthy controls were characterized by more neuronal components compared to patients in VS/UWS and in coma. Compared to healthy controls, fewer patients in MCS and VS/UWS showed components of neuronal origin for the left executive control network, default mode network (DMN), auditory, and right executive control network. The "clinical" classifier indicated the DMN and auditory network with the highest accuracy (85.3%) in discriminating patients from healthy subjects. FMRI multiple-network resting state connectivity is disrupted in severely brain-injured patients suffering from disorders of consciousness. When performing ICA, multiple-network testing and control for neuronal properties of the identified RSNs can advance fMRI system-level characterization. Automatic data-driven patient classification is the first step towards future single-subject objective diagnostics based on fMRI resting state acquisitions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Multiple Intravenous Infusions Phase 1b

PubMed Central

Cassano-Piché, A; Fan, M; Sabovitch, S; Masino, C; Easty, AC

2012-01-01

Background Minimal research has been conducted into the potential patient safety issues related to administering multiple intravenous (IV) infusions to a single patient. Previous research has highlighted that there are a number of related safety risks. In Phase 1a of this study, an analysis of 2 national incident-reporting databases (Institute for Safe Medical Practices Canada and United States Food and Drug Administration MAUDE) found that a high percentage of incidents associated with the administration of multiple IV infusions resulted in patient harm. Objectives The primary objectives of Phase 1b of this study were to identify safety issues with the potential to cause patient harm stemming from the administration of multiple IV infusions; and to identify how nurses are being educated on key principles required to safely administer multiple IV infusions. Data Sources and Review Methods A field study was conducted at 12 hospital clinical units (sites) across Ontario, and telephone interviews were conducted with program coordinators or instructors from both the Ontario baccalaureate nursing degree programs and the Ontario postgraduate Critical Care Nursing Certificate programs. Data were analyzed using Rasmussen’s 1997 Risk Management Framework and a Health Care Failure Modes and Effects Analysis. Results Twenty-two primary patient safety issues were identified with the potential to directly cause patient harm. Seventeen of these (critical issues) were categorized into 6 themes. A cause-consequence tree was established to outline all possible contributing factors for each critical issue. Clinical recommendations were identified for immediate distribution to, and implementation by, Ontario hospitals. Future investigation efforts were planned for Phase 2 of the study. Limitations This exploratory field study identifies the potential for errors, but does not describe the direct observation of such errors, except in a few cases where errors were observed. Not all issues are known in advance, and the frequency of errors is too low to be observed in the time allotted and with the limited sample of observations. Conclusions The administration of multiple IV infusions to a single patient is a complex task with many potential associated patient safety risks. Improvements to infusion and infusion-related technology, education standards, clinical best practice guidelines, hospital policies, and unit work practices are required to reduce the risk potential. This report makes several recommendations to Ontario hospitals so that they can develop an awareness of the issues highlighted in this report and minimize some of the risks. Further investigation of mitigating strategies is required and will be undertaken in Phase 2 of this research. Plain Language Summary Patients, particularly in critical care environments, often require multiple intravenous (IV) medications via large volumetric or syringe infusion pumps. The infusion of multiple IV medications is not without risk; unintended errors during these complex procedures have resulted in patient harm. However, the range of associated risks and the factors contributing to these risks are not well understood. Health Quality Ontario’s Ontario Health Technology Advisory Committee commissioned the Health Technology Safety Research Team at the University Health Network to conduct a multi-phase study to identify and mitigate the risks associated with multiple IV infusions. Some of the questions addressed by the team were as follows: What is needed to reduce the risk of errors for individuals who are receiving a lot of medications? What strategies work best? The initial report, Multiple Intravenous Infusions Phase 1a: Situation Scan Summary Report, summarizes the interim findings based on a literature review, an incident database review, and a technology scan. The Health Technology Safety Research Team worked in close collaboration with the Institute for Safe Medication Practices Canada on an exploratory study to understand the risks associated with multiple IV infusions and the degree to which nurses are educated to help mitigate them. The current report, Multiple Intravenous Infusions Phase 1b: Practice and Training Scan, presents the findings of a field study of 12 hospital clinical units across Ontario, as well as 13 interviews with educators from baccalaureate-level nursing degree programs and postgraduate Critical Care Nursing Certificate programs. It makes 9 recommendations that emphasize best practices for the administration of multiple IV infusions and pertain to secondary infusions, line identification, line set-up and removal, and administering IV bolus medications. The Health Technology Safety Research Team has also produced an associated report for hospitals entitled Mitigating the Risks Associated With Multiple IV Infusions: Recommendations Based on a Field Study of Twelve Ontario Hospitals, which highlights the 9 interim recommendations and provides a brief rationale for each one. PMID:23074426

Development of a systematic strategy for the global identification and classification of the chemical constituents and metabolites of Kai-Xin-San based on liquid chromatography with quadrupole time-of-flight mass spectrometry combined with multiple data-processing approaches.

PubMed

Wang, Xiaotong; Liu, Jing; Yang, Xiaomei; Zhang, Qian; Zhang, Yiwen; Li, Qing; Bi, Kaishun

2018-03-30

To rapidly identify and classify complicated components and metabolites for traditional Chinese medicines, a liquid chromatography with quadrupole time-of-flight mass spectrometry method combined with multiple data-processing approaches was established. In this process, Kai-Xin-San, a widely used classic traditional Chinese medicine preparation, was chosen as a model prescription. Initially, the fragmentation patterns, diagnostic product ions and neutral loss of each category of compounds were summarized by collision-induced dissociation analysis of representative standards. In vitro, the multiple product ions filtering technique was utilized to identify the chemical constituents for globally covering trace components. With this strategy, 108 constituents were identified, and compounds database was successfully established. In vivo, the prototype compounds were extracted based on the established database, and the neutral loss filtering technique combined with the drug metabolism reaction rules was employed to identify metabolites. Overall, 69 constituents including prototype and metabolites were characterized in rat plasma and nine constituents were firstly characterized in rat brain, which may be the potential active constituents resulting in curative effects by synergistic interaction. In conclusion, this study provides a generally applicable strategy to global metabolite identification for the complicated components in complex matrix and a chemical basis for further pharmacological research of Kai-Xin-San. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Genetic control and comparative genomic analysis of flowering time in Setaria (Poaceae).

PubMed

Mauro-Herrera, Margarita; Wang, Xuewen; Barbier, Hugues; Brutnell, Thomas P; Devos, Katrien M; Doust, Andrew N

2013-02-01

We report the first study on the genetic control of flowering in Setaria, a panicoid grass closely related to switchgrass, and in the same subfamily as maize and sorghum. A recombinant inbred line mapping population derived from a cross between domesticated Setaria italica (foxtail millet) and its wild relative Setaria viridis (green millet), was grown in eight trials with varying environmental conditions to identify a small number of quantitative trait loci (QTL) that control differences in flowering time. Many of the QTL across trials colocalize, suggesting that the genetic control of flowering in Setaria is robust across a range of photoperiod and other environmental factors. A detailed comparison of QTL for flowering in Setaria, sorghum, and maize indicates that several of the major QTL regions identified in maize and sorghum are syntenic orthologs with Setaria QTL, although the maize large effect QTL on chromosome 10 is not. Several Setaria QTL intervals had multiple LOD peaks and were composed of multiple syntenic blocks, suggesting that observed QTL represent multiple tightly linked loci. Candidate genes from flowering time pathways identified in rice and Arabidopsis were identified in Setaria QTL intervals, including those involved in the CONSTANS photoperiod pathway. However, only three of the approximately seven genes cloned for flowering time in maize colocalized with Setaria QTL. This suggests that variation in flowering time in separate grass lineages is controlled by a combination of conserved and lineage specific genes.

Genetic Control and Comparative Genomic Analysis of Flowering Time in Setaria (Poaceae)

PubMed Central

Mauro-Herrera, Margarita; Wang, Xuewen; Barbier, Hugues; Brutnell, Thomas P.; Devos, Katrien M.; Doust, Andrew N.

2013-01-01

We report the first study on the genetic control of flowering in Setaria, a panicoid grass closely related to switchgrass, and in the same subfamily as maize and sorghum. A recombinant inbred line mapping population derived from a cross between domesticated Setaria italica (foxtail millet) and its wild relative Setaria viridis (green millet), was grown in eight trials with varying environmental conditions to identify a small number of quantitative trait loci (QTL) that control differences in flowering time. Many of the QTL across trials colocalize, suggesting that the genetic control of flowering in Setaria is robust across a range of photoperiod and other environmental factors. A detailed comparison of QTL for flowering in Setaria, sorghum, and maize indicates that several of the major QTL regions identified in maize and sorghum are syntenic orthologs with Setaria QTL, although the maize large effect QTL on chromosome 10 is not. Several Setaria QTL intervals had multiple LOD peaks and were composed of multiple syntenic blocks, suggesting that observed QTL represent multiple tightly linked loci. Candidate genes from flowering time pathways identified in rice and Arabidopsis were identified in Setaria QTL intervals, including those involved in the CONSTANS photoperiod pathway. However, only three of the approximately seven genes cloned for flowering time in maize colocalized with Setaria QTL. This suggests that variation in flowering time in separate grass lineages is controlled by a combination of conserved and lineage specific genes. PMID:23390604

Horizontal Dissemination of Antimicrobial Resistance Determinants in Multiple Salmonella Serotypes following Isolation from the Commercial Swine Operation Environment after Manure Application.

PubMed

Pornsukarom, Suchawan; Thakur, Siddhartha

2017-10-15

The aim of this study was to characterize the plasmids carrying antimicrobial resistance (AMR) determinants in multiple Salmonella serotypes recovered from the commercial swine farm environment after manure application on land. Manure and soil samples were collected on day 0 before and after manure application on six farms in North Carolina, and sequential soil samples were recollected on days 7, 14, and 21 from the same plots. All environmental samples were processed for Salmonella , and their plasmid contents were further characterized. A total of 14 isolates including Salmonella enterica serotypes Johannesburg ( n = 2), Ohio ( n = 2), Rissen ( n = 1), Typhimurium var5- ( n = 5), Worthington ( n = 3), and 4,12:i:- ( n = 1), representing different farms, were selected for plasmid analysis. Antimicrobial susceptibility testing was done by broth microdilution against a panel of 14 antimicrobials on the 14 confirmed transconjugants after conjugation assays. The plasmids were isolated by modified alkaline lysis, and PCRs were performed on purified plasmid DNA to identify the AMR determinants and the plasmid replicon types. The plasmids were sequenced for further analysis and to compare profiles and create phylogenetic trees. A class 1 integron with an ANT(2″)-Ia- aadA2 cassette was detected in the 50-kb IncN plasmids identified in S Worthington isolates. We identified 100-kb and 90-kb IncI1 plasmids in S Johannesburg and S Rissen isolates carrying the bla CMY-2 and tet (A) genes, respectively. An identical 95-kb IncF plasmid was widely disseminated among the different serotypes and across different farms. Our study provides evidence on the importance of horizontal dissemination of resistance determinants through plasmids of multiple Salmonella serotypes distributed across commercial swine farms after manure application. IMPORTANCE The horizontal gene transfer of antimicrobial resistance (AMR) determinants located on plasmids is considered to be the main reason for the rapid proliferation and spread of drug resistance. The deposition of manure generated in swine production systems into the environment is identified as a potential source of AMR dissemination. In this study, AMR gene-carrying plasmids were detected in multiple Salmonella serotypes across different commercial swine farms in North Carolina. The plasmid profiles were characterized based on Salmonella serotype donors and incompatibility (Inc) groups. We found that different Inc plasmids showed evidence of AMR gene transfer in multiple Salmonella serotypes. We detected an identical 95-kb plasmid that was widely distributed across swine farms in North Carolina. These conjugable resistance plasmids were able to persist on land after swine manure application. Our study provides strong evidence of AMR determinant dissemination present in plasmids of multiple Salmonella serotypes in the environment after manure application. Copyright © 2017 American Society for Microbiology.

Identifying the Multiple Intelligences of Your Students

ERIC Educational Resources Information Center

McClellan, Joyce A.; Conti, Gary J.

2008-01-01

One way of addressing individual differences among adult learners is to identify the Multiple Intelligences of the learner. Multiple Intelligences refers to the concept developed by Howard Gardner that challenges the traditional view of intelligence and explains the presence of nine different Multiple Intelligences. The purpose of this study was…

The allostatic impact of chronic ethanol on gene expression: A genetic analysis of chronic intermittent ethanol treatment in the BXD cohort

PubMed Central

van der Vaart, Andrew D.; Wolstenholme, Jennifer T.; Smith, Maren L.; Harris, Guy M.; Lopez, Marcelo F.; Wolen, Aaron R.; Becker, Howard C.; Williams, Robert W.; Miles, Michael F.

2016-01-01

The transition from acute to chronic ethanol exposure leads to lasting behavioral and physiological changes such as increased consumption, dependence, and withdrawal. Changes in brain gene expression are hypothesized to underlie these adaptive responses to ethanol. Previous studies on acute ethanol identified genetic variation in brain gene expression networks and behavioral responses to ethanol across the BXD panel of recombinant inbred mice. In this work, we have performed the first joint genetic and genomic analysis of transcriptome shifts in response to chronic intermittent ethanol (CIE) by vapor chamber exposure in a BXD cohort. CIE treatment is known to produce significant and sustained changes in ethanol consumption with repeated cycles of ethanol vapor. Using Affymetrix microarray analysis of prefrontal cortex (PFC) and nucleus accumbens (NAC) RNA, we compared CIE expression responses to those seen following acute ethanol treatment, and to voluntary ethanol consumption. Gene expression changes in PFC and NAC after CIE overlapped significantly across brain regions and with previously published expression following acute ethanol. Genes highly modulated by CIE were enriched for specific biological processes including synaptic transmission, neuron ensheathment, intracellular signaling, and neuronal projection development. Expression quantitative trait locus (eQTL) analyses identified genomic loci associated with ethanol-induced transcriptional changes with largely distinct loci identified between brain regions. Correlating CIE-regulated genes to ethanol consumption data identified specific genes highly associated with variation in the increase in drinking seen with repeated cycles of CIE. In particular, multiple myelin-related genes were identified. Furthermore, genetic variance in or near dynamin3 (Dnm3) on Chr1 at ~164 Mb may have a major regulatory role in CIE-responsive gene expression. Dnm3 expression correlates significantly with ethanol consumption, is contained in a highly ranked functional group of CIE-regulated genes in the NAC, and has a cis-eQTL within a genomic region linked with multiple CIE-responsive genes. PMID:27838001

Meta-analysis identifies gene-by-environment interactions as demonstrated in a study of 4,965 mice.

PubMed

Kang, Eun Yong; Han, Buhm; Furlotte, Nicholas; Joo, Jong Wha J; Shih, Diana; Davis, Richard C; Lusis, Aldons J; Eskin, Eleazar

2014-01-01

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study.

Meta-Analysis Identifies Gene-by-Environment Interactions as Demonstrated in a Study of 4,965 Mice

PubMed Central

Joo, Jong Wha J.; Shih, Diana; Davis, Richard C.; Lusis, Aldons J.; Eskin, Eleazar

2014-01-01

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study. PMID:24415945

Epsilon-Q: An Automated Analyzer Interface for Mass Spectral Library Search and Label-Free Protein Quantification.

PubMed

Cho, Jin-Young; Lee, Hyoung-Joo; Jeong, Seul-Ki; Paik, Young-Ki

2017-12-01

Mass spectrometry (MS) is a widely used proteome analysis tool for biomedical science. In an MS-based bottom-up proteomic approach to protein identification, sequence database (DB) searching has been routinely used because of its simplicity and convenience. However, searching a sequence DB with multiple variable modification options can increase processing time, false-positive errors in large and complicated MS data sets. Spectral library searching is an alternative solution, avoiding the limitations of sequence DB searching and allowing the detection of more peptides with high sensitivity. Unfortunately, this technique has less proteome coverage, resulting in limitations in the detection of novel and whole peptide sequences in biological samples. To solve these problems, we previously developed the "Combo-Spec Search" method, which uses manually multiple references and simulated spectral library searching to analyze whole proteomes in a biological sample. In this study, we have developed a new analytical interface tool called "Epsilon-Q" to enhance the functions of both the Combo-Spec Search method and label-free protein quantification. Epsilon-Q performs automatically multiple spectral library searching, class-specific false-discovery rate control, and result integration. It has a user-friendly graphical interface and demonstrates good performance in identifying and quantifying proteins by supporting standard MS data formats and spectrum-to-spectrum matching powered by SpectraST. Furthermore, when the Epsilon-Q interface is combined with the Combo-Spec search method, called the Epsilon-Q system, it shows a synergistic function by outperforming other sequence DB search engines for identifying and quantifying low-abundance proteins in biological samples. The Epsilon-Q system can be a versatile tool for comparative proteome analysis based on multiple spectral libraries and label-free quantification.

Identifying maternal and infant factors associated with newborn size in rural Bangladesh by partial least squares (PLS) regression analysis

PubMed Central

Rahman, Md. Jahanur; Shamim, Abu Ahmed; Klemm, Rolf D. W.; Labrique, Alain B.; Rashid, Mahbubur; Christian, Parul; West, Keith P.

2017-01-01

Birth weight, length and circumferences of the head, chest and arm are key measures of newborn size and health in developing countries. We assessed maternal socio-demographic factors associated with multiple measures of newborn size in a large rural population in Bangladesh using partial least squares (PLS) regression method. PLS regression, combining features from principal component analysis and multiple linear regression, is a multivariate technique with an ability to handle multicollinearity while simultaneously handling multiple dependent variables. We analyzed maternal and infant data from singletons (n = 14,506) born during a double-masked, cluster-randomized, placebo-controlled maternal vitamin A or β-carotene supplementation trial in rural northwest Bangladesh. PLS regression results identified numerous maternal factors (parity, age, early pregnancy MUAC, living standard index, years of education, number of antenatal care visits, preterm delivery and infant sex) significantly (p<0.001) associated with newborn size. Among them, preterm delivery had the largest negative influence on newborn size (Standardized β = -0.29 − -0.19; p<0.001). Scatter plots of the scores of first two PLS components also revealed an interaction between newborn sex and preterm delivery on birth size. PLS regression was found to be more parsimonious than both ordinary least squares regression and principal component regression. It also provided more stable estimates than the ordinary least squares regression and provided the effect measure of the covariates with greater accuracy as it accounts for the correlation among the covariates and outcomes. Therefore, PLS regression is recommended when either there are multiple outcome measurements in the same study, or the covariates are correlated, or both situations exist in a dataset. PMID:29261760

Identifying maternal and infant factors associated with newborn size in rural Bangladesh by partial least squares (PLS) regression analysis.

PubMed

Kabir, Alamgir; Rahman, Md Jahanur; Shamim, Abu Ahmed; Klemm, Rolf D W; Labrique, Alain B; Rashid, Mahbubur; Christian, Parul; West, Keith P

2017-01-01

Birth weight, length and circumferences of the head, chest and arm are key measures of newborn size and health in developing countries. We assessed maternal socio-demographic factors associated with multiple measures of newborn size in a large rural population in Bangladesh using partial least squares (PLS) regression method. PLS regression, combining features from principal component analysis and multiple linear regression, is a multivariate technique with an ability to handle multicollinearity while simultaneously handling multiple dependent variables. We analyzed maternal and infant data from singletons (n = 14,506) born during a double-masked, cluster-randomized, placebo-controlled maternal vitamin A or β-carotene supplementation trial in rural northwest Bangladesh. PLS regression results identified numerous maternal factors (parity, age, early pregnancy MUAC, living standard index, years of education, number of antenatal care visits, preterm delivery and infant sex) significantly (p<0.001) associated with newborn size. Among them, preterm delivery had the largest negative influence on newborn size (Standardized β = -0.29 - -0.19; p<0.001). Scatter plots of the scores of first two PLS components also revealed an interaction between newborn sex and preterm delivery on birth size. PLS regression was found to be more parsimonious than both ordinary least squares regression and principal component regression. It also provided more stable estimates than the ordinary least squares regression and provided the effect measure of the covariates with greater accuracy as it accounts for the correlation among the covariates and outcomes. Therefore, PLS regression is recommended when either there are multiple outcome measurements in the same study, or the covariates are correlated, or both situations exist in a dataset.

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.

Widespread genetic heterogeneity in multiple myeloma: implications for targeted therapy

PubMed Central

Lohr, Jens G.; Stojanov, Petar; Carter, Scott L.; Cruz-Gordillo, Peter; Lawrence, Michael S.; Auclair, Daniel; Sougnez, Carrie; Knoechel, Birgit; Gould, Joshua; Saksena, Gordon; Cibulskis, Kristian; McKenna, Aaron; Chapman, Michael A.; Straussman, Ravid; Levy, Joan; Perkins, Louise M.; Keats, Jonathan J.; Schumacher, Steven E.; Rosenberg, Mara; Getz, Gad

2014-01-01

SUMMARY We performed massively parallel sequencing of paired tumor/normal samples from 203 multiple myeloma (MM) patients and identified significantly mutated genes and copy number alterations, and discovered putative tumor suppressor genes by determining homozygous deletions and loss-of-heterozygosity. We observed frequent mutations in KRAS (particularly in previously treated patients), NRAS, BRAF, FAM46C, TP53 and DIS3 (particularly in non-hyperdiploid MM). Mutations were often present in subclonal populations, and multiple mutations within the same pathway (e.g. KRAS, NRAS and BRAF) were observed in the same patient. In vitro modeling predicts only partial treatment efficacy of targeting subclonal mutations, and even growth promotion of non-mutated subclones in some cases. These results emphasize the importance of heterogeneity analysis for treatment decisions. PMID:24434212

Widespread genetic heterogeneity in multiple myeloma: implications for targeted therapy.

PubMed

Lohr, Jens G; Stojanov, Petar; Carter, Scott L; Cruz-Gordillo, Peter; Lawrence, Michael S; Auclair, Daniel; Sougnez, Carrie; Knoechel, Birgit; Gould, Joshua; Saksena, Gordon; Cibulskis, Kristian; McKenna, Aaron; Chapman, Michael A; Straussman, Ravid; Levy, Joan; Perkins, Louise M; Keats, Jonathan J; Schumacher, Steven E; Rosenberg, Mara; Getz, Gad; Golub, Todd R

2014-01-13

We performed massively parallel sequencing of paired tumor/normal samples from 203 multiple myeloma (MM) patients and identified significantly mutated genes and copy number alterations and discovered putative tumor suppressor genes by determining homozygous deletions and loss of heterozygosity. We observed frequent mutations in KRAS (particularly in previously treated patients), NRAS, BRAF, FAM46C, TP53, and DIS3 (particularly in nonhyperdiploid MM). Mutations were often present in subclonal populations, and multiple mutations within the same pathway (e.g., KRAS, NRAS, and BRAF) were observed in the same patient. In vitro modeling predicts only partial treatment efficacy of targeting subclonal mutations, and even growth promotion of nonmutated subclones in some cases. These results emphasize the importance of heterogeneity analysis for treatment decisions. Copyright © 2014 Elsevier Inc. All rights reserved.

Petrology of the Crystalline Rocks Hosting the Santa Fe Impact Structure

NASA Technical Reports Server (NTRS)

Schrader, C. M.; Cohen, B. A.

2010-01-01

We collected samples from within the area of shatter cone occurrence and for approximately 8 kilometers (map distance) along the roadway. Our primary goal is to date the impact. Our secondary goal is to use the petrology and Ar systematics to provide further insight into size and scale of the impact. Our approach is to: Conduct a detailed petrology study to identify lithologies that share petrologic characteristics and tectonic histories but with differing degrees of shock. Obtain micro-cores of K-bearing minerals from multiple samples for Ar-40/Ar-39 analysis. Examine the Ar diffusion patterns for multiple minerals in multiple shocked and control samples. This will help us to better understand outcrop and regional scale relationships among rocks and their responses to the impact event.

An update on MS Nurse PROfessional, an ongoing project of the European Multiple Sclerosis Platform.

PubMed

Winslow, Anne

2016-12-01

Within the multidisciplinary team required to manage people with multiple sclerosis (MS) effectively, the nurse is the central component of coordinated care and support. A 2009 survey led by the European Multiple Sclerosis Platform, an umbrella organization of national MS associations, identified variance and disparity across Europe in the nursing care of MS patients. This led to development of MS Nurse PROfessional, a continuing medical education-accredited modular online learning program endorsed and approved by leading international nursing and professional groups, and people with MS, as a tool to support the evolving role of the European MS nurse. Analysis of participant experience and nurse practice to date has been overwhelmingly positive. Expansion of MS Nurse PRO is underway or planned for future.

Multiple Access Schemes for Lunar Missions

NASA Technical Reports Server (NTRS)

Deutsch, Leslie; Hamkins, Jon; Stocklin, Frank J.

2010-01-01

Two years ago, the NASA Coding, Modulation, and Link Protocol (CMLP) study was completed. The study, led by the authors of this paper, recommended codes, modulation schemes, and desired attributes of link protocols for all space communication links in NASA's future space architecture. Portions of the NASA CMLP team were reassembled to resolve one open issue: the use of multiple access (MA) communication from the lunar surface. The CMLP-MA team analyzed and simulated two candidate multiple access schemes that were identified in the original CMLP study: Code Division MA (CDMA) and Frequency Division MA (FDMA) based on a bandwidth-efficient Continuous Phase Modulation (CPM) with a superimposed Pseudo-Noise (PN) ranging signal (CPM/PN). This paper summarizes the results of the analysis and simulation of the CMLP-MA study and describes the final recommendations.

The Relational Impact of Multiple Sclerosis: An Integrative Review of the Literature Using a Cognitive Analytic Framework.

PubMed

Blundell Jones, Joanna; Walsh, Sue; Isaac, Claire

2017-12-01

This integrative literature review uses cognitive analytic therapy (CAT) theory to examine the impact of a chronic illness, multiple sclerosis (MS), on relationships and mental health. Electronic searches were conducted in six medical and social science databases. Thirty-eight articles met inclusion criteria, and also satisfied quality criteria. Articles revealed that MS-related demands change care needs and alter relationships. Using a CAT framework, the MS literature was analysed, and five key patterns of relating to oneself and to others were identified. A diagrammatic formulation is proposed that interconnects these patterns with wellbeing and suggests potential "exits" to improve mental health, for example, assisting families to minimise overprotection. Application of CAT analysis to the literature clarifies relational processes that may affect mental health among individuals with MS, which hopefully will inform how services assist in reducing unhelpful patterns and improve coping. Further investigation of the identified patterns is needed.

Work-Related Burn Injuries Hospitalized in US Burn Centers: 2002 to 2011.

PubMed

Huang, Zhenna; Friedman, Lee S

2017-03-01

To develop a comprehensive definition to identify work-related burns in the National Burn Repository (NBR) based on multiple fields and describes injuries by occupation. The NBR, which is an inpatient dataset, was used to compare type and severity of burn injuries by occupation. Using the definition developed for this analysis, 22,969 burn injuries were identified as work-related. In contrast, the single work-related field intended to capture occupational injuries only captured 4696 cases. The highest numbers of burns were observed in construction/extraction, food preparation, and durable goods production occupations. Occupations with a mean total body surface area (TBSA) burned greater than 10% include transportation and material-moving, architecture and engineering, and arts/design/entertainment/sports/media occupations. The NBR dataset should be further utilized for occupational burn injury investigations and multiple fields should be considered for case ascertainment.

A generalized Grubbs-Beck test statistic for detecting multiple potentially influential low outliers in flood series

USGS Publications Warehouse

Cohn, T.A.; England, J.F.; Berenbrock, C.E.; Mason, R.R.; Stedinger, J.R.; Lamontagne, J.R.

2013-01-01

he Grubbs-Beck test is recommended by the federal guidelines for detection of low outliers in flood flow frequency computation in the United States. This paper presents a generalization of the Grubbs-Beck test for normal data (similar to the Rosner (1983) test; see also Spencer and McCuen (1996)) that can provide a consistent standard for identifying multiple potentially influential low flows. In cases where low outliers have been identified, they can be represented as “less-than” values, and a frequency distribution can be developed using censored-data statistical techniques, such as the Expected Moments Algorithm. This approach can improve the fit of the right-hand tail of a frequency distribution and provide protection from lack-of-fit due to unimportant but potentially influential low flows (PILFs) in a flood series, thus making the flood frequency analysis procedure more robust.

A generalized Grubbs-Beck test statistic for detecting multiple potentially influential low outliers in flood series

NASA Astrophysics Data System (ADS)

Cohn, T. A.; England, J. F.; Berenbrock, C. E.; Mason, R. R.; Stedinger, J. R.; Lamontagne, J. R.

2013-08-01

The Grubbs-Beck test is recommended by the federal guidelines for detection of low outliers in flood flow frequency computation in the United States. This paper presents a generalization of the Grubbs-Beck test for normal data (similar to the Rosner (1983) test; see also Spencer and McCuen (1996)) that can provide a consistent standard for identifying multiple potentially influential low flows. In cases where low outliers have been identified, they can be represented as "less-than" values, and a frequency distribution can be developed using censored-data statistical techniques, such as the Expected Moments Algorithm. This approach can improve the fit of the right-hand tail of a frequency distribution and provide protection from lack-of-fit due to unimportant but potentially influential low flows (PILFs) in a flood series, thus making the flood frequency analysis procedure more robust.

Higher moments of net-proton multiplicity distributions in a heavy-ion event pile-up scenario

NASA Astrophysics Data System (ADS)

Garg, P.; Mishra, D. K.

2017-10-01

High-luminosity modern accelerators, like the Relativistic Heavy Ion Collider (RHIC) at Brookhaven National Laboratory (BNL) and Large Hadron Collider (LHC) at European Organization for Nuclear Research (CERN), inherently have event pile-up scenarios which significantly contribute to physics events as a background. While state-of-the-art tracking algorithms and detector concepts take care of these event pile-up scenarios, several offline analytical techniques are used to remove such events from the physics analysis. It is still difficult to identify the remaining pile-up events in an event sample for physics analysis. Since the fraction of these events is significantly small, it may not be as serious of an issue for other analyses as it would be for an event-by-event analysis. Particularly when the characteristics of the multiplicity distribution are observable, one needs to be very careful. In the present work, we demonstrate how a small fraction of residual pile-up events can change the moments and their ratios of an event-by-event net-proton multiplicity distribution, which are sensitive to the dynamical fluctuations due to the QCD critical point. For this study, we assume that the individual event-by-event proton and antiproton multiplicity distributions follow Poisson, negative binomial, or binomial distributions. We observe a significant effect in cumulants and their ratios of net-proton multiplicity distributions due to pile-up events, particularly at lower energies. It might be crucial to estimate the fraction of pile-up events in the data sample while interpreting the experimental observable for the critical point.

Comparative analysis of diguanylate cyclase and phosphodiesterase genes in Klebsiella pneumoniae.

PubMed

Cruz, Diana P; Huertas, Mónica G; Lozano, Marcela; Zárate, Lina; Zambrano, María Mercedes

2012-07-09

Klebsiella pneumoniae can be found in environmental habitats as well as in hospital settings where it is commonly associated with nosocomial infections. One of the factors that contribute to virulence is its capacity to form biofilms on diverse biotic and abiotic surfaces. The second messenger Bis-(3'-5')-cyclic dimeric GMP (c-di-GMP) is a ubiquitous signal in bacteria that controls biofilm formation as well as several other cellular processes. The cellular levels of this messenger are controlled by c-di-GMP synthesis and degradation catalyzed by diguanylate cyclase (DGC) and phophodiesterase (PDE) enzymes, respectively. Many bacteria contain multiple copies of these proteins with diverse organizational structure that highlight the complex regulatory mechanisms of this signaling network. This work was undertaken to identify DGCs and PDEs and analyze the domain structure of these proteins in K. pneumoniae. A search for conserved GGDEF and EAL domains in three sequenced K. pneumoniae genomes showed that there were multiple copies of GGDEF and EAL containing proteins. Both single domain and hybrid GGDEF proteins were identified: 21 in K. pneumoniae Kp342, 18 in K. pneumoniae MGH 78578 and 17 in K. pneumoniae NTUH-K2044. The majority had only the GGDEF domain, most with the GGEEF motif, and hybrid proteins containing both GGDEF and EAL domains were also found. The I site for allosteric control was identified only in single GGDEF domain proteins and not in hybrid proteins. EAL-only proteins, containing either intact or degenerate domains, were also identified: 15 in Kp342, 15 in MGH 78578 and 10 in NTUH-K2044. Several input sensory domains and transmembrane segments were identified, which together indicate complex regulatory circuits that in many cases can be membrane associated. The comparative analysis of proteins containing GGDEF/EAL domains in K. pneumoniae showed that most copies were shared among the three strains and that some were unique to a particular strain. The multiplicity of these proteins and the diversity of structural characteristics suggest that the c-di-GMP network in this enteric bacterium is highly complex and reflects the importance of having diverse mechanisms to control cellular processes in environments as diverse as soils or plants and clinical settings.

Multiple Loci are associated with dilated cardiomyopathy in Irish wolfhounds.

PubMed

Philipp, Ute; Vollmar, Andrea; Häggström, Jens; Thomas, Anne; Distl, Ottmar

2012-01-01

Dilated cardiomyopathy (DCM) is a highly prevalent and often lethal disease in Irish wolfhounds. Complex segregation analysis indicated different loci involved in pathogenesis. Linear fixed and mixed models were used for the genome-wide association study. Using 106 DCM cases and 84 controls we identified one SNP significantly associated with DCM on CFA37 and five SNPs suggestively associated with DCM on CFA1, 10, 15, 21 and 17. On CFA37 MOGAT1 and ACSL3 two enzymes of the lipid metabolism were located near the identified SNP.

Multiple Loci Are Associated with Dilated Cardiomyopathy in Irish Wolfhounds

PubMed Central

Philipp, Ute; Vollmar, Andrea; Häggström, Jens; Thomas, Anne; Distl, Ottmar

2012-01-01

Dilated cardiomyopathy (DCM) is a highly prevalent and often lethal disease in Irish wolfhounds. Complex segregation analysis indicated different loci involved in pathogenesis. Linear fixed and mixed models were used for the genome-wide association study. Using 106 DCM cases and 84 controls we identified one SNP significantly associated with DCM on CFA37 and five SNPs suggestively associated with DCM on CFA1, 10, 15, 21 and 17. On CFA37 MOGAT1 and ACSL3 two enzymes of the lipid metabolism were located near the identified SNP. PMID:22761652

ABC transporters and the proteasome complex are implicated in susceptibility to Stevens-Johnson syndrome and toxic epidermal necrolysis across multiple drugs.

PubMed

Nicoletti, Paola; Bansal, Mukesh; Lefebvre, Celine; Guarnieri, Paolo; Shen, Yufeng; Pe'er, Itsik; Califano, Andrea; Floratos, Aris

2015-01-01

Stevens-Johnson syndrome (SJS) and Toxic Epidermal Necrolysis (TEN) represent rare but serious adverse drug reactions (ADRs). Both are characterized by distinctive blistering lesions and significant mortality rates. While there is evidence for strong drug-specific genetic predisposition related to HLA alleles, recent genome wide association studies (GWAS) on European and Asian populations have failed to identify genetic susceptibility alleles that are common across multiple drugs. We hypothesize that this is a consequence of the low to moderate effect size of individual genetic risk factors. To test this hypothesis we developed Pointer, a new algorithm that assesses the aggregate effect of multiple low risk variants on a pathway using a gene set enrichment approach. A key advantage of our method is the capability to associate SNPs with genes by exploiting physical proximity as well as by using expression quantitative trait loci (eQTLs) that capture information about both cis- and trans-acting regulatory effects. We control for known bias-inducing aspects of enrichment based analyses, such as: 1) gene length, 2) gene set size, 3) presence of biologically related genes within the same linkage disequilibrium (LD) region, and, 4) genes shared among multiple gene sets. We applied this approach to publicly available SJS/TEN genome-wide genotype data and identified the ABC transporter and Proteasome pathways as potentially implicated in the genetic susceptibility of non-drug-specific SJS/TEN. We demonstrated that the innovative SNP-to-gene mapping phase of the method was essential in detecting the significant enrichment for those pathways. Analysis of an independent gene expression dataset provides supportive functional evidence for the involvement of Proteasome pathways in SJS/TEN cutaneous lesions. These results suggest that Pointer provides a useful framework for the integrative analysis of pharmacogenetic GWAS data, by increasing the power to detect aggregate effects of multiple low risk variants. The software is available for download at https://sourceforge.net/projects/pointergsa/.

Very Low Food Security in US Households Is Predicted by Complex Patterns of Health, Economics, and Service Participation.

PubMed

Choi, Seul Ki; Fram, Maryah S; Frongillo, Edward A

2017-10-01

Background: Very low food security (VLFS) happens at the intersection of nuanced and complex patterns of risk characteristics across multiple domains. Little is known about the idiosyncratic situations that lead households to experience VLFS. Objective: We used classification and regression tree (CART) analysis, which can handle complex combinations of predictors, to identify patterns of characteristics that distinguish VLFS households in the United States from other households. Methods: Data came from 3 surveys, the 2011-2014 National Health Interview Survey (NHIS), the 2005-2012 NHANES, and the 2002-2012 Current Population Survey (CPS), with sample participants aged ≥18 y and households with income <300% of the federal poverty line. Survey participants were stratified into households with children, adult-only households, and older-adult households (NHIS, CPS) or individuals aged 18-64 y and individuals aged ≥65 y (NHANES). Household food security was measured with the use of the 10-item US Adult Food Security Scale. Variables from multiple domains, including sociodemographic characteristics, health, health care, and participation in social welfare and food assistance programs, were considered as predictors. The 3 data sources were analyzed separately with the use of CART analysis. Results: Household experiences of VLFS were associated with different predictors for different types of households and often occurred at the intersection of multiple characteristics spanning unmet medical needs, poor health, disability, limitation, depressive symptoms, low income, and food assistance program participation. These predictors built complex trees with various combinations in different types of households. Conclusions: This study showed that multiple characteristics across multiple domains distinguished VLFS households. Flexible and nonlinear methods focusing on a wide range of risk characteristics should be used to identify VLFS households and to inform policies and programs that can address VLFS households' various needs. © 2017 American Society for Nutrition.

Graduate medical education competencies for international health electives: A qualitative study.

PubMed

Nordhues, Hannah C; Bashir, M Usmaan; Merry, Stephen P; Sawatsky, Adam P

2017-11-01

Residency programs offer international health electives (IHEs), providing multiple educational benefits. This study aimed to identify how IHEs fulfill the Accreditation Council for Graduate Medical Education (ACGME) core competencies. We conducted a thematic analysis of post-rotation reflective reports from residents who participated in IHEs through the Mayo International Health Program. We coded reports using a codebook created from the ACGME competencies. Using a constant comparative method, we identified significant themes within each competency. Residents from 40 specialties participated in 377 IHEs in 56 countries from 2001 to 2014. Multiple themes were identified within each of the six ACGME core competencies: Patient Care and Procedural Skills (4), Medical Knowledge (5), Practice-Based Learning and Improvement (3), Interpersonal and Communication Skills (5), Professionalism (4), and Systems-Based Practice and Improvement (3). Themes included improving physical exam and procedural skills, providing care in resource-limited setting, gaining knowledge of tropical and non-tropical diseases, identifying socioeconomic determinants of health, engaging in the education of others, and increasing communication across cultures and multidisciplinary teams. Through IHEs, residents advanced their knowledge, skills, and attitudes in each of the six ACGME competencies. These data can be used for development of IHE competencies and milestones for resident assessment.

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.