Proteomic analysis of polyribosomes identifies splicing factors as potential regulators of translation during mitosis

PubMed Central

Hofmann, Sarah; Elman, Tamar; Shenoy, Anjana; Geiger, Tamar; Elkon, Ran; Ehrlich, Marcelo

2017-01-01

Abstract Precise regulation of mRNA translation is critical for proper cell division, but little is known about the factors that mediate it. To identify mRNA-binding proteins that regulate translation during mitosis, we analyzed the composition of polysomes from interphase and mitotic cells using unbiased quantitative mass-spectrometry (LC–MS/MS). We found that mitotic polysomes are enriched with a subset of proteins involved in RNA processing, including alternative splicing and RNA export. To demonstrate that these may indeed be regulators of translation, we focused on heterogeneous nuclear ribonucleoprotein C (hnRNP C) as a test case and confirmed that it is recruited to elongating ribosomes during mitosis. Then, using a combination of pulsed SILAC, metabolic labeling and ribosome profiling, we showed that knockdown of hnRNP C affects both global and transcript-specific translation rates and found that hnRNP C is specifically important for translation of mRNAs that encode ribosomal proteins and translation factors. Taken together, our results demonstrate how proteomic analysis of polysomes can provide insight into translation regulation under various cellular conditions of interest and suggest that hnRNP C facilitates production of translation machinery components during mitosis to provide daughter cells with the ability to efficiently synthesize proteins as they enter G1 phase. PMID:28460002

Identifying Human Factors Issues in Aircraft Maintenance Operations

NASA Technical Reports Server (NTRS)

Veinott, Elizabeth S.; Kanki, Barbara G.; Shafto, Michael G. (Technical Monitor)

1995-01-01

Maintenance operations incidents submitted to the Aviation Safety Reporting System (ASRS) between 1986-1992 were systematically analyzed in order to identify issues relevant to human factors and crew coordination. This exploratory analysis involved 95 ASRS reports which represented a wide range of maintenance incidents. The reports were coded and analyzed according to the type of error (e.g, wrong part, procedural error, non-procedural error), contributing factors (e.g., individual, within-team, cross-team, procedure, tools), result of the error (e.g., aircraft damage or not) as well as the operational impact (e.g., aircraft flown to destination, air return, delay at gate). The main findings indicate that procedural errors were most common (48.4%) and that individual and team actions contributed to the errors in more than 50% of the cases. As for operational results, most errors were either corrected after landing at the destination (51.6%) or required the flight crew to stop enroute (29.5%). Interactions among these variables are also discussed. This analysis is a first step toward developing a taxonomy of crew coordination problems in maintenance. By understanding what variables are important and how they are interrelated, we may develop intervention strategies that are better tailored to the human factor issues involved.

Factor Analysis of Therapist-Identified Treatment Targets in Community-Based Children's Mental Health.

PubMed

Love, Allison R; Okado, Izumi; Orimoto, Trina E; Mueller, Charles W

2018-01-01

The present study used exploratory and confirmatory factor analyses to identify underlying latent factors affecting variation in community therapists' endorsement of treatment targets. As part of a statewide practice management program, therapist completed monthly reports of treatment targets (up to 10 per month) for a sample of youth (n = 790) receiving intensive in-home therapy. Nearly 75 % of youth were diagnosed with multiple co-occurring disorders. Five factors emerged: Disinhibition, Societal Rules Evasion, Social Engagement Deficits, Emotional Distress, and Management of Biodevelopmental Outcomes. Using logistic regression, primary diagnosis predicted therapist selection of Disinhibition and Emotional Distress targets. Client age predicted endorsement of Societal Rules Evasion targets. Practice-to-research implications are discussed.

Proteomic analysis identifies insulin-like growth factor-binding protein-related protein-1 as a podocyte product.

PubMed

Matsumoto, Takayuki; Hess, Sonja; Kajiyama, Hiroshi; Sakairi, Toru; Saleem, Moin A; Mathieson, Peter W; Nojima, Yoshihisa; Kopp, Jeffrey B

2010-10-01

The podocyte secretory proteome may influence the phenotype of adjacent podocytes, endothelial cells, parietal epithelial cells, and tubular epithelial cells but has not been systematically characterized. We have initiated studies to characterize this proteome, with the goal of further understanding the podocyte cell biology. We cultured differentiated conditionally immortalized human podocytes and subjected the proteins in conditioned medium to mass spectrometry. At a false discovery rate of <3%, we identified 111 candidates from conditioned medium, including 44 proteins that have signal peptides or are described as secreted proteins in the UniProt database. As validation, we confirmed that one of these proteins, insulin-like growth factor-binding protein-related protein-1 (IGFBP-rP1), was expressed in mRNA and protein of cultured podocytes. In addition, transforming growth factor-β1 stimulation increased IGFBP-rP1 in conditioned medium. We analyzed IGFBP-rP1 glomerular expression in a mouse model of human immunodeficiency virus-associated nephropathy. IGFBP-rP1 was absent from podocytes of normal mice and was expressed in podocytes and pseudocrescents of transgenic mice, where it was coexpressed with desmin, a podocyte injury marker. We conclude that IGFBP-rP1 may be a product of injured podocytes. Further analysis of the podocyte secretory proteome may identify biomarkers of podocyte injury.

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

Identifying relationships between baseflow geochemistry and land use with synoptic sampling and R-Mode factor analysis

USGS Publications Warehouse

Wayland, Karen G.; Long, David T.; Hyndman, David W.; Pijanowski, Bryan C.; Woodhams, Sarah M.; Haak, Sheridan K.

2003-01-01

The relationship between land use and stream chemistry is often explored through synoptic sampling rivers at baseflow condition. However, base flow chemistry is likely to vary temporally and spatially with land use. The purpose of our study is to examine the usefulness of the synoptic sampling approach for identifying the relationship between complex land use configurations and stream water quality. This study compares biogeochemical data from three synoptic sampling events representing the temporal variability of baseflow chemistry and land use using R-mode factor analysis. Separate R-mode factor analyses of the data from individual sampling events yielded only two consistent factors. Agricultural activity was associated with elevated levels of Ca2+, Mg2+, alkalinity, and frequently K+, SO42-, and NO3-. Urban areas were associated with higher concentrations of Na+, K+, and Cl-. Other retained factors were not  consistent among sampling events, and some factors were difficult to interpret in the context of biogeochemical sources and processes. When all data were combined, further associations were revealed such as an inverse relationship between the proportion of wetlands and stream nitrate concentrations. We also found that barren lands were associated with elevated sulfate levels. This research suggests that an individual sampling event is unlikely to characterize adequately the complex processes controlling interactions between land uses and stream chemistry. Combining data collected over two years during three synoptic sampling events appears to enhance our ability to understand processes linking stream chemistry and land use.  

Using host-pathogen protein interactions to identify and characterize Francisella tularensis virulence factors.

PubMed

Wallqvist, Anders; Memišević, Vesna; Zavaljevski, Nela; Pieper, Rembert; Rajagopala, Seesandra V; Kwon, Keehwan; Yu, Chenggang; Hoover, Timothy A; Reifman, Jaques

2015-12-29

Francisella tularensis is a select bio-threat agent and one of the most virulent intracellular pathogens known, requiring just a few organisms to establish an infection. Although several virulence factors are known, we lack an understanding of virulence factors that act through host-pathogen protein interactions to promote infection. To address these issues in the highly infectious F. tularensis subsp. tularensis Schu S4 strain, we deployed a combined in silico, in vitro, and in vivo analysis to identify virulence factors and their interactions with host proteins to characterize bacterial infection mechanisms. We initially used comparative genomics and literature to identify and select a set of 49 putative and known virulence factors for analysis. Each protein was then subjected to proteome-scale yeast two-hybrid (Y2H) screens with human and murine cDNA libraries to identify potential host-pathogen protein-protein interactions. Based on the bacterial protein interaction profile with both hosts, we selected seven novel putative virulence factors for mutant construction and animal validation experiments. We were able to create five transposon insertion mutants and used them in an intranasal BALB/c mouse challenge model to establish 50 % lethal dose estimates. Three of these, ΔFTT0482c, ΔFTT1538c, and ΔFTT1597, showed attenuation in lethality and can thus be considered novel F. tularensis virulence factors. The analysis of the accompanying Y2H data identified intracellular protein trafficking between the early endosome to the late endosome as an important component in virulence attenuation for these virulence factors. Furthermore, we also used the Y2H data to investigate host protein binding of two known virulence factors, showing that direct protein binding was a component in the modulation of the inflammatory response via activation of mitogen-activated protein kinases and in the oxidative stress response. Direct interactions with specific host proteins and the

Proteomic analysis of polyribosomes identifies splicing factors as potential regulators of translation during mitosis.

PubMed

Aviner, Ranen; Hofmann, Sarah; Elman, Tamar; Shenoy, Anjana; Geiger, Tamar; Elkon, Ran; Ehrlich, Marcelo; Elroy-Stein, Orna

2017-06-02

Precise regulation of mRNA translation is critical for proper cell division, but little is known about the factors that mediate it. To identify mRNA-binding proteins that regulate translation during mitosis, we analyzed the composition of polysomes from interphase and mitotic cells using unbiased quantitative mass-spectrometry (LC-MS/MS). We found that mitotic polysomes are enriched with a subset of proteins involved in RNA processing, including alternative splicing and RNA export. To demonstrate that these may indeed be regulators of translation, we focused on heterogeneous nuclear ribonucleoprotein C (hnRNP C) as a test case and confirmed that it is recruited to elongating ribosomes during mitosis. Then, using a combination of pulsed SILAC, metabolic labeling and ribosome profiling, we showed that knockdown of hnRNP C affects both global and transcript-specific translation rates and found that hnRNP C is specifically important for translation of mRNAs that encode ribosomal proteins and translation factors. Taken together, our results demonstrate how proteomic analysis of polysomes can provide insight into translation regulation under various cellular conditions of interest and suggest that hnRNP C facilitates production of translation machinery components during mitosis to provide daughter cells with the ability to efficiently synthesize proteins as they enter G1 phase. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Identifying the critical success factors in the coverage of low vision services using the classification analysis and regression tree methodology.

PubMed

Chiang, Peggy Pei-Chia; Xie, Jing; Keeffe, Jill Elizabeth

2011-04-25

To identify the critical success factors (CSF) associated with coverage of low vision services. Data were collected from a survey distributed to Vision 2020 contacts, government, and non-government organizations (NGOs) in 195 countries. The Classification and Regression Tree Analysis (CART) was used to identify the critical success factors of low vision service coverage. Independent variables were sourced from the survey: policies, epidemiology, provision of services, equipment and infrastructure, barriers to services, human resources, and monitoring and evaluation. Socioeconomic and demographic independent variables: health expenditure, population statistics, development status, and human resources in general, were sourced from the World Health Organization (WHO), World Bank, and the United Nations (UN). The findings identified that having >50% of children obtaining devices when prescribed (χ(2) = 44; P < 0.000), multidisciplinary care (χ(2) = 14.54; P = 0.002), >3 rehabilitation workers per 10 million of population (χ(2) = 4.50; P = 0.034), higher percentage of population urbanized (χ(2) = 14.54; P = 0.002), a level of private investment (χ(2) = 14.55; P = 0.015), and being fully funded by government (χ(2) = 6.02; P = 0.014), are critical success factors associated with coverage of low vision services. This study identified the most important predictors for countries with better low vision coverage. The CART is a useful and suitable methodology in survey research and is a novel way to simplify a complex global public health issue in eye care.

Predictive factors for pericardial effusion identified by heart dose-volume histogram analysis in oesophageal cancer patients treated with chemoradiotherapy.

PubMed

Hayashi, K; Fujiwara, Y; Nomura, M; Kamata, M; Kojima, H; Kohzai, M; Sumita, K; Tanigawa, N

2015-02-01

To identify predictive factors for the development of pericardial effusion (PCE) in patients with oesophageal cancer treated with chemotherapy and radiotherapy (RT). From March 2006 to November 2012, patients with oesophageal cancer treated with chemoradiotherapy (CRT) using the following criteria were evaluated: radiation dose >50 Gy; heart included in the radiation field; dose-volume histogram (DVH) data available for analysis; no previous thoracic surgery; and no PCE before treatment. The diagnosis of PCE was independently determined by two radiologists. Clinical factors, the percentage of heart volume receiving >5-60 Gy in increments of 5 Gy (V5-60, respectively), maximum heart dose and mean heart dose were analysed. A total of 143 patients with oesophageal cancer were reviewed retrospectively. The median follow-up by CT was 15 months (range, 2.1-72.6 months) after RT. PCE developed in 55 patients (38.5%) after RT, and the median time to develop PCE was 3.5 months (range, 0.2-9.9 months). On univariate analysis, DVH parameters except for V60 were significantly associated with the development of PCE (p < 0.001). No clinical factor was significantly related to the development of PCE. Recursive partitioning analysis including all DVH parameters as variables showed a V10 cut-off value of 72.8% to be the most influential factor. The present results showed that DVH parameters are strong independent predictive factors for the development of PCE in patients with oesophageal cancer treated with CRT. A heart dosage was associated with the development of PCE with radiation and without prophylactic nodal irradiation.

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.

Application of Factor Analysis to Identify Dietary Patterns and Use of Factor Scores to Study Their Relationship with Nutritional Status of Adult Rural Populations

PubMed Central

Brahmam, G.N.V.; Vijayaraghavan, K.

2011-01-01

The prevalence of chronic energy deficiency (CED) among one-third of the Indian population is attributed to inadequacy of consumption of nutrients. However, considering the complexity of diets among Indians, the relationship between a particular dietary pattern and the nutritional status of the population has not been established so far. A community-based cross-sectional study was undertaken to assess estimates, at district level, of diet and nutritional status in Orissa State, India. Factor analysis was used for exploring the existence of consumption pattern of food and nutrients and their relationship with the nutritional status of rural adult population. Data on 2,864 adult men and 3,525 adult women in Orissa state revealed that there exists six patterns among food-groups explaining 59% of the total variation and three patterns among nutrients that explain 73% of the total variation among both adult men and women. The discriminant function analysis revealed that, overall, 53% of the men were correctly classified as either with chronic energy deficiency (CED) or without CED. Similarly, overall, 54% of the women were correctly classified as either with CED or without CED. The sensitivity of the model was 65% for both men and women, and the specificity was 46% and 41% respectively for men and women. In the case of classification of overweight/obesity, the prediction of the model was about 75% among both men and women, along with high sensitivity. Using factor analysis, the dietary patterns were identified from the food and nutrient intake data. There exists a strong relationship between the dietary patterns and the nutritional status of rural adults. These results will help identify the community people with CED and help planners formulate nutritional interventions accordingly. PMID:21957671

Identifying transcription factor functions and targets by phenotypic activation

PubMed Central

Chua, Gordon; Morris, Quaid D.; Sopko, Richelle; Robinson, Mark D.; Ryan, Owen; Chan, Esther T.; Frey, Brendan J.; Andrews, Brenda J.; Boone, Charles; Hughes, Timothy R.

2006-01-01

Mapping transcriptional regulatory networks is difficult because many transcription factors (TFs) are activated only under specific conditions. We describe a generic strategy for identifying genes and pathways induced by individual TFs that does not require knowledge of their normal activation cues. Microarray analysis of 55 yeast TFs that caused a growth phenotype when overexpressed showed that the majority caused increased transcript levels of genes in specific physiological categories, suggesting a mechanism for growth inhibition. Induced genes typically included established targets and genes with consensus promoter motifs, if known, indicating that these data are useful for identifying potential new target genes and binding sites. We identified the sequence 5′-TCACGCAA as a binding sequence for Hms1p, a TF that positively regulates pseudohyphal growth and previously had no known motif. The general strategy outlined here presents a straightforward approach to discovery of TF activities and mapping targets that could be adapted to any organism with transgenic technology. PMID:16880382

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

ERIC Educational Resources Information Center

Morgan, Bruce B.; And Others

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

Transcriptome analysis of Neisseria meningitidis in human whole blood and mutagenesis studies identify virulence factors involved in blood survival.

PubMed

Echenique-Rivera, Hebert; Muzzi, Alessandro; Del Tordello, Elena; Seib, Kate L; Francois, Patrice; Rappuoli, Rino; Pizza, Mariagrazia; Serruto, Davide

2011-05-01

During infection Neisseria meningitidis (Nm) encounters multiple environments within the host, which makes rapid adaptation a crucial factor for meningococcal survival. Despite the importance of invasion into the bloodstream in the meningococcal disease process, little is known about how Nm adapts to permit survival and growth in blood. To address this, we performed a time-course transcriptome analysis using an ex vivo model of human whole blood infection. We observed that Nm alters the expression of ≈30% of ORFs of the genome and major dynamic changes were observed in the expression of transcriptional regulators, transport and binding proteins, energy metabolism, and surface-exposed virulence factors. In particular, we found that the gene encoding the regulator Fur, as well as all genes encoding iron uptake systems, were significantly up-regulated. Analysis of regulated genes encoding for surface-exposed proteins involved in Nm pathogenesis allowed us to better understand mechanisms used to circumvent host defenses. During blood infection, Nm activates genes encoding for the factor H binding proteins, fHbp and NspA, genes encoding for detoxifying enzymes such as SodC, Kat and AniA, as well as several less characterized surface-exposed proteins that might have a role in blood survival. Through mutagenesis studies of a subset of up-regulated genes we were able to identify new proteins important for survival in human blood and also to identify additional roles of previously known virulence factors in aiding survival in blood. Nm mutant strains lacking the genes encoding the hypothetical protein NMB1483 and the surface-exposed proteins NalP, Mip and NspA, the Fur regulator, the transferrin binding protein TbpB, and the L-lactate permease LctP were sensitive to killing by human blood. This increased knowledge of how Nm responds to adaptation in blood could also be helpful to develop diagnostic and therapeutic strategies to control the devastating disease cause by

Transcriptome Analysis of Neisseria meningitidis in Human Whole Blood and Mutagenesis Studies Identify Virulence Factors Involved in Blood Survival

PubMed Central

Del Tordello, Elena; Seib, Kate L.; Francois, Patrice; Rappuoli, Rino; Pizza, Mariagrazia; Serruto, Davide

2011-01-01

During infection Neisseria meningitidis (Nm) encounters multiple environments within the host, which makes rapid adaptation a crucial factor for meningococcal survival. Despite the importance of invasion into the bloodstream in the meningococcal disease process, little is known about how Nm adapts to permit survival and growth in blood. To address this, we performed a time-course transcriptome analysis using an ex vivo model of human whole blood infection. We observed that Nm alters the expression of ≈30% of ORFs of the genome and major dynamic changes were observed in the expression of transcriptional regulators, transport and binding proteins, energy metabolism, and surface-exposed virulence factors. In particular, we found that the gene encoding the regulator Fur, as well as all genes encoding iron uptake systems, were significantly up-regulated. Analysis of regulated genes encoding for surface-exposed proteins involved in Nm pathogenesis allowed us to better understand mechanisms used to circumvent host defenses. During blood infection, Nm activates genes encoding for the factor H binding proteins, fHbp and NspA, genes encoding for detoxifying enzymes such as SodC, Kat and AniA, as well as several less characterized surface-exposed proteins that might have a role in blood survival. Through mutagenesis studies of a subset of up-regulated genes we were able to identify new proteins important for survival in human blood and also to identify additional roles of previously known virulence factors in aiding survival in blood. Nm mutant strains lacking the genes encoding the hypothetical protein NMB1483 and the surface-exposed proteins NalP, Mip and NspA, the Fur regulator, the transferrin binding protein TbpB, and the L-lactate permease LctP were sensitive to killing by human blood. This increased knowledge of how Nm responds to adaptation in blood could also be helpful to develop diagnostic and therapeutic strategies to control the devastating disease cause by

Integration analysis of quantitative proteomics and transcriptomics data identifies potential targets of frizzled-8 protein-related antiproliferative factor in vivo.

PubMed

Yang, Wei; Kim, Yongsoo; Kim, Taek-Kyun; Keay, Susan K; Kim, Kwang Pyo; Steen, Hanno; Freeman, Michael R; Hwang, Daehee; Kim, Jayoung

2012-12-01

What's known on the subject? and What does the study add? Interstitial cystitis (IC) is a prevalent and debilitating pelvic disorder generally accompanied by chronic pain combined with chronic urinating problems. Over one million Americans are affected, especially middle-aged women. However, its aetiology or mechanism remains unclear. No efficient drug has been provided to patients. Several urinary biomarker candidates have been identified for IC; among the most promising is antiproliferative factor (APF), whose biological activity is detectable in urine specimens from >94% of patients with both ulcerative and non-ulcerative IC. The present study identified several important mediators of the effect of APF on bladder cell physiology, suggesting several candidate drug targets against IC. In an attempt to identify potential proteins and genes regulated by APF in vivo, and to possibly expand the APF-regulated network identified by stable isotope labelling by amino acids in cell culture (SILAC), we performed an integration analysis of our own SILAC data and the microarray data of Gamper et al. (2009) BMC Genomics 10: 199. Notably, two of the proteins (i.e. MAPKSP1 and GSPT1) that are down-regulated by APF are involved in the activation of mTORC1, suggesting that the mammalian target of rapamycin (mTOR) pathway is potentially a critical pathway regulated by APF in vivo. Several components of the mTOR pathway are currently being studied as potential therapeutic targets in other diseases. Our analysis suggests that this pathway might also be relevant in the design of diagnostic tools and medications targeting IC. • To enhance our understanding of the interstitial cystitis urine biomarker antiproliferative factor (APF), as well as interstitial cystitis biology more generally at the systems level, we reanalyzed recently published large-scale quantitative proteomics and in vivo transcriptomics data sets using an integration analysis tool that we have developed. • To

Using fault tree analysis to identify contributing factors to engulfment in flowing grain in on-farm grain bins.

PubMed

Kingman, D M; Field, W E

2005-11-01

Findings reported by researchers at Illinois State University and Purdue University indicated that since 1980, an average of eight individuals per year have become engulfed and died in farm grain bins in the U.S. and Canada and that all these deaths are significant because they are believed to be preventable. During a recent effort to develop intervention strategies and recommendations for an ASAE farm grain bin safety standard, fault tree analysis (FTA) was utilized to identify contributing factors to engulfments in grain stored in on-farm grain bins. FTA diagrams provided a spatial perspective of the circumstances that occurred prior to engulfment incidents, a perspective never before presented in other hazard analyses. The FTA also demonstrated relationships and interrelationships of the contributing factors. FTA is a useful tool that should be applied more often in agricultural incident investigations to assist in the more complete understanding of the problem studied.

Serial analysis of gene expression identifies connective tissue growth factor expression as a prognostic biomarker in gallbladder cancer.

PubMed

Alvarez, Hector; Corvalan, Alejandro; Roa, Juan C; Argani, Pedram; Murillo, Francisco; Edwards, Jennifer; Beaty, Robert; Feldmann, Georg; Hong, Seung-Mo; Mullendore, Michael; Roa, Ivan; Ibañez, Luis; Pimentel, Fernando; Diaz, Alfonso; Riggins, Gregory J; Maitra, Anirban

2008-05-01

Gallbladder cancer (GBC) is an uncommon neoplasm in the United States, but one with high mortality rates. This malignancy remains largely understudied at the molecular level such that few targeted therapies or predictive biomarkers exist. We built the first series of serial analysis of gene expression (SAGE) libraries from GBC and nonneoplastic gallbladder mucosa, composed of 21-bp long-SAGE tags. SAGE libraries were generated from three stage-matched GBC patients (representing Hispanic/Latino, Native American, and Caucasian ethnicities, respectively) and one histologically alithiasic gallbladder. Real-time quantitative PCR was done on microdissected epithelium from five matched GBC and corresponding nonneoplastic gallbladder mucosa. Immunohistochemical analysis was done on a panel of 182 archival GBC in high-throughput tissue microarray format. SAGE tags corresponding to connective tissue growth factor (CTGF) transcripts were identified as differentially overexpressed in all pairwise comparisons of GBC (P < 0.001). Real-time quantitative PCR confirmed significant overexpression of CTGF transcripts in microdissected primary GBC (P < 0.05), but not in metastatic GBC, compared with nonneoplastic gallbladder epithelium. By immunohistochemistry, 66 of 182 (36%) GBC had high CTGF antigen labeling, which was significantly associated with better survival on univariate analysis (P = 0.0069, log-rank test). An unbiased analysis of the GBC transcriptome by SAGE has identified CTGF expression as a predictive biomarker of favorable prognosis in this malignancy. The SAGE libraries from GBC and nonneoplastic gallbladder mucosa are publicly available at the Cancer Genome Anatomy Project web site and should facilitate much needed research into this lethal neoplasm.

Identifying Factors for Worker Motivation in Zambia's Rural Health Facilities.

PubMed

Cross, Samuel S; Baernholdt, Dr Marianne

2017-01-01

Within Zambia there is a shortage of health workers in rural areas. This study aims to identify motivating factors for retaining rural health workers. Sixty rural health workers completed surveys and 46 were interviewed. They rated the importance of six motivating factors and discussed these and other factors in interviews. An interview was conducted with a Government Human Resources Manager (HR Manager) to elicit contextual information. All six factors were identified as being very important motivators, as were two additional factors. Additional career training was identified by many as the most important factor. Comparison of results and the HR Manager interview revealed that workers lacked knowledge about opportunities and that the HR manager was aware of barriers to career development. The Zambian government might better motivate and retain rural health workers by offering them any combination of identified factors, and by addressing the barriers to career development.

BIOELECTRICAL IMPEDANCE VECTOR ANALYSIS IDENTIFIES SARCOPENIA IN NURSING HOME RESIDENTS

USDA-ARS?s Scientific Manuscript database

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

Genome-wide characterization and expression analysis of citrus NUCLEAR FACTOR-Y (NF-Y) transcription factors identified a novel NF-YA gene involved in drought-stress response and tolerance.

PubMed

Pereira, Suzam L S; Martins, Cristina P S; Sousa, Aurizangela O; Camillo, Luciana R; Araújo, Caroline P; Alcantara, Grazielle M; Camargo, Danielle S; Cidade, Luciana C; de Almeida, Alex-Alan F; Costa, Marcio G C

2018-01-01

Nuclear factor Y (NF-Y) is a ubiquitous transcription factor found in eukaryotes. It is composed of three distinct subunits called NF-YA, NF-YB and NF-YC. NF-Ys have been identified as key regulators of multiple pathways in the control of development and tolerance to biotic and abiotic factors. The present study aimed to identify and characterize the complete repertoire of genes coding for NF-Y in citrus, as well as to perform the functional characterization of one of its members, namely CsNFYA5, in transgenic tobacco plants. A total of 22 genes coding for NF-Y were identified in the genomes of sweet orange (Citrus sinensis) and Clementine mandarin (C. clementina), including six CsNF-YAs, 11 CsNF-YBs and five CsNF-YCs. Phylogenetic analyses showed that there is a NF-Y orthologous in the Clementine genome for each sweet orange NF-Y gene; this was not observed when compared to Arabidopsis thaliana. CsNF-Y proteins shared the same conserved domains with their orthologous proteins in other organisms, including mouse. Analysis of gene expression by RNA-seq and EST data demonstrated that CsNF-Ys have a tissue-specific and stress inducible expression profile. qRT-PCR analysis revealed that CsNF-YA5 exhibits differential expression in response to water deficit in leaves and roots of citrus plants. Overexpression of CsNF-YA5 in transgenic tobacco plants contributed to the reduction of H2O2 production under dehydration conditions and increased plant growth and photosynthetic rate under normal conditions and drought stress. These biochemical and physiological responses to drought stress promoted by CsNF-YA5 may confer a productivity advantage in environments with frequent short-term soil water deficit.

Identifying the Factors That Predict Degree Completion for Entirely Online Community College Students

ERIC Educational Resources Information Center

Brock, Kishia R.

2014-01-01

The purpose of this research study was to identify demographic characteristics, academic factors, and student behaviors that contributed to successful degree and certificate completion for entirely online, nontraditional undergraduate students at a large community college. A discrete-time event history analysis was used to model the retention of…

Genome-wide analysis identifies chickpea (Cicer arietinum) heat stress transcription factors (Hsfs) responsive to heat stress at the pod development stage.

PubMed

Chidambaranathan, Parameswaran; Jagannadham, Prasanth Tej Kumar; Satheesh, Viswanathan; Kohli, Deshika; Basavarajappa, Santosh Halasabala; Chellapilla, Bharadwaj; Kumar, Jitendra; Jain, Pradeep Kumar; Srinivasan, R

2018-05-01

The heat stress transcription factors (Hsfs) play a prominent role in thermotolerance and eliciting the heat stress response in plants. Identification and expression analysis of Hsfs gene family members in chickpea would provide valuable information on heat stress responsive Hsfs. A genome-wide analysis of Hsfs gene family resulted in the identification of 22 Hsf genes in chickpea in both desi and kabuli genome. Phylogenetic analysis distinctly separated 12 A, 9 B, and 1 C class Hsfs, respectively. An analysis of cis-regulatory elements in the upstream region of the genes identified many stress responsive elements such as heat stress elements (HSE), abscisic acid responsive element (ABRE) etc. In silico expression analysis showed nine and three Hsfs were also expressed in drought and salinity stresses, respectively. Q-PCR expression analysis of Hsfs under heat stress at pod development and at 15 days old seedling stage showed that CarHsfA2, A6, and B2 were significantly upregulated in both the stages of crop growth and other four Hsfs (CarHsfA2, A6a, A6c, B2a) showed early transcriptional upregulation for heat stress at seedling stage of chickpea. These subclasses of Hsfs identified in this study can be further evaluated as candidate genes in the characterization of heat stress response in chickpea.

Identifying Dust Sources by Positive Matrix Factorization (PMF)

NASA Astrophysics Data System (ADS)

Engelbrecht, Johann P.

2010-05-01

This presentation is on the source attribution by Positive Matrix Factorization (PMF) of aerosol samples collected in Iraq, a major source of mineral dust in the Middle East. Globally transported mineral dust from North Africa, the Middle East, China, and elsewhere are routinely being sampled at high elevation monitoring sites such as those on the Canary Islands and Hawaii, and many ambient monitoring sites worldwide. Chemical results of these filter samples reflect differences in sources impacting at each site, further complicated by the regional geomorphology and meteorology. Trace elements, isotopes, elemental ratios, and mineralogy are generally being used to pinpoint geological source regions of natural and anthropogenic dusts. A receptor site is seldom impacted by only one source at a time. Dust palls are continually being modified by added dust from soils across which they migrate, also by particle segregation in the dust plume, and precipitation of the coarser particles. The result is that dust is a mixture, with contributions from different sources, each with a different chemical and mineralogical signature. PMF is a non-negative factorization procedure that produces only positive factor scores and loadings, in contrast to classical factor analysis (FA) and Principal Components Analysis (PCA). PMF enables us to resolve factors (chemical signatures) for source types contributing to the ambient chemical data set, and also models the source-type contributions to individual ambient samples. The latter can often be related to specific source regions. PMF was applied separately to two ambient data sets collected in Iraq in 2006, the one on Teflon membrane filters and the other on quartz fiber. Each of the filter types were previously analyzed for different chemical species: Teflon membrane for elements, by XRF and ICP-MS, while quartz fiber filters were analyzed for ions and carbon. [Engelbrecht et al. 2009] A set of 392 Teflon filter samples analyzed for 25

Using an interdisciplinary approach to identify factors that affect clinicians' compliance with evidence-based guidelines.

PubMed

Gurses, Ayse P; Marsteller, Jill A; Ozok, A Ant; Xiao, Yan; Owens, Sharon; Pronovost, Peter J

2010-08-01

Our objective was to identify factors that affect clinicians' compliance with the evidence-based guidelines using an interdisciplinary approach and develop a conceptual framework that can provide a comprehensive and practical guide for designing effective interventions. A literature review and a brainstorming session with 11 researchers from a variety of scientific disciplines were used to identify theoretical and conceptual models describing clinicians' guideline compliance. MEDLINE, EMBASE, CINAHL, and the bibliographies of the papers identified were used as data sources for identifying the relevant theoretical and conceptual models. Thirteen different models that originated from various disciplines including medicine, rural sociology, psychology, human factors and systems engineering, organizational management, marketing, and health education were identified. Four main categories of factors that affect compliance emerged from our analysis: clinician characteristics, guideline characteristics, system characteristics, and implementation characteristics. Based on these findings, we developed an interdisciplinary conceptual framework that specifies the expected interrelationships among these four categories of factors and their impact on clinicians' compliance. An interdisciplinary approach is needed to improve clinicians' compliance with evidence-based guidelines. The conceptual framework from this research can provide a comprehensive and systematic guide to identify barriers to guideline compliance and design effective interventions to improve patient safety.

Identifying a parsimonious model for predicting academic achievement in undergraduate medical education: A confirmatory factor analysis

PubMed Central

Ali, Syeda Kauser; Baig, Lubna Ansari; Violato, Claudio; Zahid, Onaiza

2017-01-01

Objectives: This study was conducted to adduce evidence of validity for admissions tests and processes and for identifying a parsimonious model that predicts students’ academic achievement in Medical College. Methods: Psychometric study done on admission data and assessment scores for five years of medical studies at Aga Khan University Medical College, Pakistan using confirmatory factor analysis (CFA) and structured equation modeling (SEM). Sample included 276 medical students admitted in 2003, 2004 and 2005. Results: The SEM supported the existence of covariance between verbal reasoning, science and clinical knowledge for predicting achievement in medical school employing Maximum Likelihood (ML) estimations (n=112). Fit indices: χ2 (21) = 59.70, p =<.0001; CFI=.873; RMSEA = 0.129; SRMR = 0.093. Conclusions: This study shows that in addition to biology and chemistry which have been traditionally used as major criteria for admission to medical colleges in Pakistan; mathematics has proven to be a better predictor for higher achievements in medical college. PMID:29067063

Identifying a parsimonious model for predicting academic achievement in undergraduate medical education: A confirmatory factor analysis.

PubMed

Ali, Syeda Kauser; Baig, Lubna Ansari; Violato, Claudio; Zahid, Onaiza

2017-01-01

This study was conducted to adduce evidence of validity for admissions tests and processes and for identifying a parsimonious model that predicts students' academic achievement in Medical College. Psychometric study done on admission data and assessment scores for five years of medical studies at Aga Khan University Medical College, Pakistan using confirmatory factor analysis (CFA) and structured equation modeling (SEM). Sample included 276 medical students admitted in 2003, 2004 and 2005. The SEM supported the existence of covariance between verbal reasoning, science and clinical knowledge for predicting achievement in medical school employing Maximum Likelihood (ML) estimations (n=112). Fit indices: χ 2 (21) = 59.70, p =<.0001; CFI=.873; RMSEA = 0.129; SRMR = 0.093. This study shows that in addition to biology and chemistry which have been traditionally used as major criteria for admission to medical colleges in Pakistan; mathematics has proven to be a better predictor for higher achievements in medical college.

Risk factors identified for certain lymphoma subtypes

Cancer.gov

In a large international collaborative analysis of risk factors for non-Hodgkin lymphoma (NHL), scientists were able to quantify risk associated with medical history, lifestyle factors, family history of blood or lymph-borne cancers, and occupation for 11

In Silico Analysis of Gene Expression Network Components Underlying Pigmentation Phenotypes in the Python Identified Evolutionarily Conserved Clusters of Transcription Factor Binding Sites

PubMed Central

2016-01-01

Color variation provides the opportunity to investigate the genetic basis of evolution and selection. Reptiles are less studied than mammals. Comparative genomics approaches allow for knowledge gained in one species to be leveraged for use in another species. We describe a comparative vertebrate analysis of conserved regulatory modules in pythons aimed at assessing bioinformatics evidence that transcription factors important in mammalian pigmentation phenotypes may also be important in python pigmentation phenotypes. We identified 23 python orthologs of mammalian genes associated with variation in coat color phenotypes for which we assessed the extent of pairwise protein sequence identity between pythons and mouse, dog, horse, cow, chicken, anole lizard, and garter snake. We next identified a set of melanocyte/pigment associated transcription factors (CREB, FOXD3, LEF-1, MITF, POU3F2, and USF-1) that exhibit relatively conserved sequence similarity within their DNA binding regions across species based on orthologous alignments across multiple species. Finally, we identified 27 evolutionarily conserved clusters of transcription factor binding sites within ~200-nucleotide intervals of the 1500-nucleotide upstream regions of AIM1, DCT, MC1R, MITF, MLANA, OA1, PMEL, RAB27A, and TYR from Python bivittatus. Our results provide insight into pigment phenotypes in pythons. PMID:27698666

In Silico Analysis of Gene Expression Network Components Underlying Pigmentation Phenotypes in the Python Identified Evolutionarily Conserved Clusters of Transcription Factor Binding Sites.

PubMed

Irizarry, Kristopher J L; Bryden, Randall L

2016-01-01

Color variation provides the opportunity to investigate the genetic basis of evolution and selection. Reptiles are less studied than mammals. Comparative genomics approaches allow for knowledge gained in one species to be leveraged for use in another species. We describe a comparative vertebrate analysis of conserved regulatory modules in pythons aimed at assessing bioinformatics evidence that transcription factors important in mammalian pigmentation phenotypes may also be important in python pigmentation phenotypes. We identified 23 python orthologs of mammalian genes associated with variation in coat color phenotypes for which we assessed the extent of pairwise protein sequence identity between pythons and mouse, dog, horse, cow, chicken, anole lizard, and garter snake. We next identified a set of melanocyte/pigment associated transcription factors (CREB, FOXD3, LEF-1, MITF, POU3F2, and USF-1) that exhibit relatively conserved sequence similarity within their DNA binding regions across species based on orthologous alignments across multiple species. Finally, we identified 27 evolutionarily conserved clusters of transcription factor binding sites within ~200-nucleotide intervals of the 1500-nucleotide upstream regions of AIM1, DCT, MC1R, MITF, MLANA, OA1, PMEL, RAB27A, and TYR from Python bivittatus . Our results provide insight into pigment phenotypes in pythons.

Qualitative Comparative Analysis: A Hybrid Method for Identifying Factors Associated with Program Effectiveness.

PubMed

Cragun, Deborah; Pal, Tuya; Vadaparampil, Susan T; Baldwin, Julie; Hampel, Heather; DeBate, Rita D

2016-07-01

Qualitative comparative analysis (QCA) was developed over 25 years ago to bridge the qualitative and quantitative research gap. Upon searching PubMed and the Journal of Mixed Methods Research , this review identified 30 original research studies that utilized QCA. Perceptions that QCA is complex and provides few relative advantages over other methods may be limiting QCA adoption. Thus, to overcome these perceptions, this article demonstrates how to perform QCA using data from fifteen institutions that implemented universal tumor screening (UTS) programs to identify patients at high risk for hereditary colorectal cancer. In this example, QCA revealed a combination of conditions unique to effective UTS programs. Results informed additional research and provided a model for improving patient follow-through after a positive screen.

Qualitative Comparative Analysis: A Hybrid Method for Identifying Factors Associated with Program Effectiveness

PubMed Central

Cragun, Deborah; Pal, Tuya; Vadaparampil, Susan T.; Baldwin, Julie; Hampel, Heather; DeBate, Rita D.

2015-01-01

Qualitative comparative analysis (QCA) was developed over 25 years ago to bridge the qualitative and quantitative research gap. Upon searching PubMed and the Journal of Mixed Methods Research, this review identified 30 original research studies that utilized QCA. Perceptions that QCA is complex and provides few relative advantages over other methods may be limiting QCA adoption. Thus, to overcome these perceptions, this article demonstrates how to perform QCA using data from fifteen institutions that implemented universal tumor screening (UTS) programs to identify patients at high risk for hereditary colorectal cancer. In this example, QCA revealed a combination of conditions unique to effective UTS programs. Results informed additional research and provided a model for improving patient follow-through after a positive screen. PMID:27429602

Establishing Factor Validity Using Variable Reduction in Confirmatory Factor Analysis.

ERIC Educational Resources Information Center

Hofmann, Rich

1995-01-01

Using a 21-statement attitude-type instrument, an iterative procedure for improving confirmatory model fit is demonstrated within the context of the EQS program of P. M. Bentler and maximum likelihood factor analysis. Each iteration systematically eliminates the poorest fitting statement as identified by a variable fit index. (SLD)

Systematic MicroRNA Analysis Identifies ATP6V0C as an Essential Host Factor for Human Cytomegalovirus Replication

PubMed Central

Pavelin, Jon; Reynolds, Natalie; Chiweshe, Stephen; Wu, Guanming; Tiribassi, Rebecca; Grey, Finn

2013-01-01

Recent advances in microRNA target identification have greatly increased the number of putative targets of viral microRNAs. However, it is still unclear whether all targets identified are biologically relevant. Here, we use a combined approach of RISC immunoprecipitation and focused siRNA screening to identify targets of HCMV encoded human cytomegalovirus that play an important role in the biology of the virus. Using both a laboratory and clinical strain of human cytomegalovirus, we identify over 200 putative targets of human cytomegalovirus microRNAs following infection of fibroblast cells. By comparing RISC-IP profiles of miRNA knockout viruses, we have resolved specific interactions between human cytomegalovirus miRNAs and the top candidate target transcripts and validated regulation by western blot analysis and luciferase assay. Crucially we demonstrate that miRNA target genes play important roles in the biology of human cytomegalovirus as siRNA knockdown results in marked effects on virus replication. The most striking phenotype followed knockdown of the top target ATP6V0C, which is required for endosomal acidification. siRNA knockdown of ATP6V0C resulted in almost complete loss of infectious virus production, suggesting that an HCMV microRNA targets a crucial cellular factor required for virus replication. This study greatly increases the number of identified targets of human cytomegalovirus microRNAs and demonstrates the effective use of combined miRNA target identification and focused siRNA screening for identifying novel host virus interactions. PMID:24385903

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

PubMed Central

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

2015-01-01

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

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…

Identifying Some Factors That Might Predispose Drug Abuse among Learners in a South African Township School

ERIC Educational Resources Information Center

Grobler, R.; Khatite, M.

2012-01-01

This study inquires into some of the factors that might predispose the use and abuse of drugs among secondary school learners in a township school. The objective of this research is to identify these factors and to offer a few suggestions on how the abuse may be prevented. A quantitative research strategy is used and a document analysis technique…

Global Biogeographic Analysis of Methanogenic Archaea Identifies Community-Shaping Environmental Factors of Natural Environments

PubMed Central

Wen, Xi; Yang, Sizhong; Horn, Fabian; Winkel, Matthias; Wagner, Dirk; Liebner, Susanne

2017-01-01

Methanogenic archaea are important for the global greenhouse gas budget since they produce methane under anoxic conditions in numerous natural environments such as oceans, estuaries, soils, and lakes. Whether and how environmental change will propagate into methanogenic assemblages of natural environments remains largely unknown owing to a poor understanding of global distribution patterns and environmental drivers of this specific group of microorganisms. In this study, we performed a meta-analysis targeting the biogeographic patterns and environmental controls of methanogenic communities using 94 public mcrA gene datasets. We show a global pattern of methanogenic archaea that is more associated with habitat filtering than with geographical dispersal. We identify salinity as the control on methanogenic community composition at global scale whereas pH and temperature are the major controls in non-saline soils and lakes. The importance of salinity for structuring methanogenic community composition is also reflected in the biogeography of methanogenic lineages and the physiological properties of methanogenic isolates. Linking methanogenic alpha-diversity with reported values of methane emission identifies estuaries as the most diverse methanogenic habitats with, however, minor contribution to the global methane budget. With salinity, temperature and pH our study identifies environmental drivers of methanogenic community composition facing drastic changes in many natural environments at the moment. However, consequences of this for the production of methane remain elusive owing to a lack of studies that combine methane production rate with community analysis. PMID:28769904

Identifying risk factors for refractory febrile neutropenia in patients with lung cancer.

PubMed

Fujita, Masaki; Tokunaga, Shoji; Ikegame, Satoshi; Harada, Eiji; Matsumoto, Takemasa; Uchino, Junji; Watanabe, Kentaro; Nakanishi, Yoichi

2012-02-01

Information about the development of febrile neutropenia in patients with solid tumors remains insufficient. In this study, we tried to identify the risk factors for refractory febrile neutropenia in patients with lung cancer. A total of 59 neutropenic fever episodes associated with anti-tumor chemotherapy for lung cancer were retrospectively analyzed. We compared patient characteristics according to their initial response to treatment with antibiotics. For 34 of 59 (58%) episodes a response to initial antibiotics was obtained whereas 25 of 59 (42%) were refractory to treatment. Multivariate analysis demonstrated independent risk factors for refractory febrile neutropenia with lung cancer. These risk factors were the severity of febrile neutropenia (odds ratio (OR) 6.11; 95% confidence interval (CI) 1.85-20.14) and C-reactive protein more than 10 mg/dl (OR 4.39; 95% CI 1.22-15.74). These factors could predict outcome for patients with lung cancer who develop refractory febrile neutropenia.

Meta-analysis identifies a MECOM gene as a novel predisposing factor of osteoporotic fracture

PubMed Central

Hwang, Joo-Yeon; Lee, Seung Hun; Go, Min Jin; Kim, Beom-Jun; Kou, Ikuyo; Ikegawa, Shiro; Guo, Yan; Deng, Hong-Wen; Raychaudhuri, Soumya; Kim, Young Jin; Oh, Ji Hee; Kim, Youngdoe; Moon, Sanghoon; Kim, Dong-Joon; Koo, Heejo; Cha, My-Jung; Lee, Min Hye; Yun, Ji Young; Yoo, Hye-Sook; Kang, Young-Ah; Cho, Eun-Hee; Kim, Sang-Wook; Oh, Ki Won; Kang, Moo II; Son, Ho Young; Kim, Shin-Yoon; Kim, Ghi Su; Han, Bok-Ghee; Cho, Yoon Shin; Cho, Myeong-Chan; Lee, Jong-Young; Koh, Jung-Min

2014-01-01

Background Osteoporotic fracture (OF) as a clinical endpoint is a major complication of osteoporosis. To screen for OF susceptibility genes, we performed a genome-wide association study and carried out de novo replication analysis of an East Asian population. Methods Association was tested using a logistic regression analysis. A meta-analysis was performed on the combined results using effect size and standard errors estimated for each study. Results In a combined meta-analysis of a discovery cohort (288 cases and 1139 controls), three hospital based sets in replication stage I (462 cases and 1745 controls), and an independent ethnic group in replication stage II (369 cases and 560 for controls), we identified a new locus associated with OF (rs784288 in the MECOM gene) that showed genome-wide significance (p=3.59×10−8; OR 1.39). RNA interference revealed that a MECOM knockdown suppresses osteoclastogenesis. Conclusions Our findings provide new insights into the genetic architecture underlying OF in East Asians. PMID:23349225

Genomic analysis of diffuse pediatric low-grade gliomas identifies recurrent oncogenic truncating rearrangements in the transcription factor MYBL1

PubMed Central

Ramkissoon, Lori A.; Horowitz, Peleg M.; Craig, Justin M.; Ramkissoon, Shakti H.; Rich, Benjamin E.; Schumacher, Steven E.; McKenna, Aaron; Lawrence, Michael S.; Bergthold, Guillaume; Brastianos, Priscilla K.; Tabak, Barbara; Ducar, Matthew D.; Van Hummelen, Paul; MacConaill, Laura E.; Pouissant-Young, Tina; Cho, Yoon-Jae; Taha, Hala; Mahmoud, Madeha; Bowers, Daniel C.; Margraf, Linda; Tabori, Uri; Hawkins, Cynthia; Packer, Roger J.; Hill, D. Ashley; Pomeroy, Scott L.; Eberhart, Charles G.; Dunn, Ian F.; Goumnerova, Liliana; Getz, Gad; Chan, Jennifer A.; Santagata, Sandro; Hahn, William C.; Stiles, Charles D.; Ligon, Azra H.; Kieran, Mark W.; Beroukhim, Rameen; Ligon, Keith L.

2013-01-01

Pediatric low-grade gliomas (PLGGs) are among the most common solid tumors in children but, apart from BRAF kinase mutations or duplications in specific subclasses, few genetic driver events are known. Diffuse PLGGs comprise a set of uncommon subtypes that exhibit invasive growth and are therefore especially challenging clinically. We performed high-resolution copy-number analysis on 44 formalin-fixed, paraffin-embedded diffuse PLGGs to identify recurrent alterations. Diffuse PLGGs exhibited fewer such alterations than adult low-grade gliomas, but we identified several significantly recurrent events. The most significant event, 8q13.1 gain, was observed in 28% of diffuse astrocytoma grade IIs and resulted in partial duplication of the transcription factor MYBL1 with truncation of its C-terminal negative-regulatory domain. A similar recurrent deletion-truncation breakpoint was identified in two angiocentric gliomas in the related gene v-myb avian myeloblastosis viral oncogene homolog (MYB) on 6q23.3. Whole-genome sequencing of a MYBL1-rearranged diffuse astrocytoma grade II demonstrated MYBL1 tandem duplication and few other events. Truncated MYBL1 transcripts identified in this tumor induced anchorage-independent growth in 3T3 cells and tumor formation in nude mice. Truncated transcripts were also expressed in two additional tumors with MYBL1 partial duplication. Our results define clinically relevant molecular subclasses of diffuse PLGGs and highlight a potential role for the MYB family in the biology of low-grade gliomas. PMID:23633565

Risk factors for baclofen pump infection in children: a multivariate analysis.

PubMed

Spader, Heather S; Bollo, Robert J; Bowers, Christian A; Riva-Cambrin, Jay

2016-06-01

OBJECTIVE Intrathecal baclofen infusion systems to manage severe spasticity and dystonia are associated with higher infection rates in children than in adults. Factors unique to this population, such as poor nutrition and physical limitations for pump placement, have been hypothesized as the reasons for this disparity. The authors assessed potential risk factors for infection in a multivariate analysis. METHODS Patients who underwent implantation of a programmable pump and intrathecal catheter for baclofen infusion at a single center between January 1, 2000, and March 1, 2012, were identified in this retrospective cohort study. The primary end point was infection. Potential risk factors investigated included preoperative (i.e., demographics, body mass index [BMI], gastrostomy tube, tracheostomy, previous spinal fusion), intraoperative (i.e., surgeon, antibiotics, pump size, catheter location), and postoperative (i.e., wound dehiscence, CSF leak, and number of revisions) factors. Univariate analysis was performed, and a multivariate logistic regression model was created to identify independent risk factors for infection. RESULTS A total of 254 patients were evaluated. The overall infection rate was 9.8%. Univariate analysis identified young age, shorter height, lower weight, dehiscence, CSF leak, and number of revisions within 6 months of pump placement as significantly associated with infection. Multivariate analysis identified young age, dehiscence, and number of revisions as independent risk factors for infection. CONCLUSIONS Young age, wound dehiscence, and number of revisions were independent risk factors for infection in this pediatric cohort. A low BMI and the presence of either a gastrostomy or tracheostomy were not associated with infection and may not be contraindications for this procedure.

Hospital Readmission and Social Risk Factors Identified from Physician Notes.

PubMed

Navathe, Amol S; Zhong, Feiran; Lei, Victor J; Chang, Frank Y; Sordo, Margarita; Topaz, Maxim; Navathe, Shamkant B; Rocha, Roberto A; Zhou, Li

2018-04-01

To evaluate the prevalence of seven social factors using physician notes as compared to claims and structured electronic health records (EHRs) data and the resulting association with 30-day readmissions. A multihospital academic health system in southeastern Massachusetts. An observational study of 49,319 patients with cardiovascular disease admitted from January 1, 2011, to December 31, 2013, using multivariable logistic regression to adjust for patient characteristics. All-payer claims, EHR data, and physician notes extracted from a centralized clinical registry. All seven social characteristics were identified at the highest rates in physician notes. For example, we identified 14,872 patient admissions with poor social support in physician notes, increasing the prevalence from 0.4 percent using ICD-9 codes and structured EHR data to 16.0 percent. Compared to an 18.6 percent baseline readmission rate, risk-adjusted analysis showed higher readmission risk for patients with housing instability (readmission rate 24.5 percent; p < .001), depression (20.6 percent; p < .001), drug abuse (20.2 percent; p = .01), and poor social support (20.0 percent; p = .01). The seven social risk factors studied are substantially more prevalent than represented in administrative data. Automated methods for analyzing physician notes may enable better identification of patients with social needs. © Health Research and Educational Trust.

Integrative transcriptome analysis identifies deregulated microRNA-transcription factor networks in lung adenocarcinoma

PubMed Central

Cinegaglia, Naiara C.; Andrade, Sonia Cristina S.; Tokar, Tomas; Pinheiro, Maísa; Severino, Fábio E.; Oliveira, Rogério A.; Hasimoto, Erica N.; Cataneo, Daniele C.; Cataneo, Antônio J.M.; Defaveri, Júlio; Souza, Cristiano P.; Marques, Márcia M.C.; Carvalho, Robson F.; Coutinho, Luiz L.; Gross, Jefferson L.; Rogatto, Silvia R.; Lam, Wan L.; Jurisica, Igor; Reis, Patricia P.

2016-01-01

Herein, we aimed at identifying global transcriptome microRNA (miRNA) changes and miRNA target genes in lung adenocarcinoma. Samples were selected as training (N = 24) and independent validation (N = 34) sets. Tissues were microdissected to obtain >90% tumor or normal lung cells, subjected to miRNA transcriptome sequencing and TaqMan quantitative PCR validation. We further integrated our data with published miRNA and mRNA expression datasets across 1,491 lung adenocarcinoma and 455 normal lung samples. We identified known and novel, significantly over- and under-expressed (p ≤ 0.01 and FDR≤0.1) miRNAs in lung adenocarcinoma compared to normal lung tissue: let-7a, miR-10a, miR-15b, miR-23b, miR-26a, miR-26b, miR-29a, miR-30e, miR-99a, miR-146b, miR-181b, miR-181c, miR-421, miR-181a, miR-574 and miR-1247. Validated miRNAs included let-7a-2, let-7a-3, miR-15b, miR-21, miR-155 and miR-200b; higher levels of miR-21 expression were associated with lower patient survival (p = 0.042). We identified a regulatory network including miR-15b and miR-155, and transcription factors with prognostic value in lung cancer. Our findings may contribute to the development of treatment strategies in lung adenocarcinoma. PMID:27081085

Evaluation of Parallel Analysis Methods for Determining the Number of Factors

ERIC Educational Resources Information Center

Crawford, Aaron V.; Green, Samuel B.; Levy, Roy; Lo, Wen-Juo; Scott, Lietta; Svetina, Dubravka; Thompson, Marilyn S.

2010-01-01

Population and sample simulation approaches were used to compare the performance of parallel analysis using principal component analysis (PA-PCA) and parallel analysis using principal axis factoring (PA-PAF) to identify the number of underlying factors. Additionally, the accuracies of the mean eigenvalue and the 95th percentile eigenvalue criteria…

IDENTIFYING ELEVEN FACTORS OF SERVICE MARKETING MIX (4PS) EFFECTIVE ON TENDENCY OF PATIENTS TOWARD PRIVATE HOSPITAL.

PubMed

Hosseini, Seyed Mojtaba; Etesaminia, Samira; Jafari, Mehrnoosh

2016-10-01

One of the important factors of correct management is to identify the reasons for patient tendency toward private hospitals. This study measures these factors based on service marketing mixes. This study used a cross sectional descriptive methodology. The study was conducted during 6 months in 2015. The studied population included patients of private hospitals in Tehran. Random sampling was used (n = 200). Data was collected by an author-made questionnaire for service marketing factors. Reliability and validity of the questionnaire were confirmed. Data analysis was done using factor analysis test in SPSS 20. The results showed that constant attendance of physicians and nurses has the highest effect (0.707%) on patient tendency toward private hospitals.

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

PubMed

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

2015-09-01

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

A Critical Analysis of Anesthesiology Podcasts: Identifying Determinants of Success.

PubMed

Singh, Devin; Alam, Fahad; Matava, Clyde

2016-08-17

Audio and video podcasts have gained popularity in recent years. Increasingly, podcasts are being used in the field of medicine as a tool to disseminate information. This format has multiple advantages including highly accessible creation tools, low distribution costs, and portability for the user. However, despite its ongoing use in medical education, there are no data describing factors associated with the success or quality of podcasts. The goal of the study was to assess the landscape of anesthesia podcasts in Canada and develop a methodology for evaluating the quality of the podcast. To achieve our objective, we identified the scope of podcasts in anesthesia specifically, constructed an algorithmic model for measuring success, and identified factors linked to both successful podcasts and a peer-review process. Independent reviewers performed a systematic search of anesthesia-related podcasts on iTunes Canada. Data and metrics recorded for each podcast included podcast's authorship, number posted, podcast series duration, target audience, topics, and social media presence. Descriptive statistics summarized mined data, and univariate analysis was used to identify factors associated with podcast success and a peer-review process. Twenty-two podcasts related to anesthesia were included in the final analysis. Less than a third (6/22=27%) were still active. The median longevity of the podcasts' series was just 13 months (interquartile range: 1-39 months). Anesthesiologists were the target audience for 77% of podcast series with clinical topics being most commonly addressed. We defined a novel algorithm for measuring success: Podcast Success Index. Factors associated with a high Podcast Success Index included podcasts targeting fellows (Spearman R=0.434; P=.04), inclusion of professional topics (Spearman R=0.456-0.603; P=.01-.03), and the use of Twitter as a means of social media (Spearman R=0.453;P=.03). In addition, more than two-thirds (16/22=73%) of podcasts

A Critical Analysis of Anesthesiology Podcasts: Identifying Determinants of Success

PubMed Central

Singh, Devin; Matava, Clyde

2016-01-01

Background Audio and video podcasts have gained popularity in recent years. Increasingly, podcasts are being used in the field of medicine as a tool to disseminate information. This format has multiple advantages including highly accessible creation tools, low distribution costs, and portability for the user. However, despite its ongoing use in medical education, there are no data describing factors associated with the success or quality of podcasts. Objective The goal of the study was to assess the landscape of anesthesia podcasts in Canada and develop a methodology for evaluating the quality of the podcast. To achieve our objective, we identified the scope of podcasts in anesthesia specifically, constructed an algorithmic model for measuring success, and identified factors linked to both successful podcasts and a peer-review process. Methods Independent reviewers performed a systematic search of anesthesia-related podcasts on iTunes Canada. Data and metrics recorded for each podcast included podcast’s authorship, number posted, podcast series duration, target audience, topics, and social media presence. Descriptive statistics summarized mined data, and univariate analysis was used to identify factors associated with podcast success and a peer-review process. Results Twenty-two podcasts related to anesthesia were included in the final analysis. Less than a third (6/22=27%) were still active. The median longevity of the podcasts’ series was just 13 months (interquartile range: 1-39 months). Anesthesiologists were the target audience for 77% of podcast series with clinical topics being most commonly addressed. We defined a novel algorithm for measuring success: Podcast Success Index. Factors associated with a high Podcast Success Index included podcasts targeting fellows (Spearman R=0.434; P=.04), inclusion of professional topics (Spearman R=0.456-0.603; P=.01-.03), and the use of Twitter as a means of social media (Spearman R=0.453;P=.03). In addition, more

Analysis of Factors Influencing Creative Personality of Elementary School Students

ERIC Educational Resources Information Center

Park, Jongman; Kim, Minkee; Jang, Shinho

2017-01-01

This quantitative research examined factors that affect elementary students' creativity and how those factors correlate. Aiming to identify significant factors that affect creativity and to clarify the relationship between these factors by path analysis, this research was designed to be a stepping stone for creativity enhancement studies. Data…

Evaluation of redundancy analysis to identify signatures of local adaptation.

PubMed

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

2018-05-26

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

Identifying depressive symptom trajectory groups among Korean adults and psychosocial factors as group determinants.

PubMed

Kwon, Tae Yeon

2015-06-01

Longitudinal research is needed to examine the depressive symptom trajectories of different groups during adulthood and their antecedents and consequences, because depressive symptoms may be changeable and heterogeneous over time. This study examined the number of trajectory groups describing the depressive symptoms of Korean adults, as well as the shape of the trajectories and the association between trajectory group membership and psychosocial factors identified based on the ecosystem model. This study used Nagin's semi-parametric group-based modeling to analyze Year 1 to Year 7 data from Korea Welfare Panel Survey (N = 13,735), a nationally representative sample of community-dwelling adults. Three distinct trajectory groups were identified: a low stable depressive symptoms group, a moderate depressive symptoms group and a high depressive symptoms group. Result from multinominal logit analysis showed that all psychosocial factors except family relationships affected the likelihood of membership in the three depressive symptoms groups. Especially, self-esteem was the psychosocial factor with the largest impact on depressive symptom trajectory group membership. When screening for depressive symptoms, individuals with a low socioeconomic status should be a primary concern and intervention should be made available to them. Prevention or intervention with members of the identified trajectory groups would likely require integrative approaches targeting psychosocial factors across multiple contexts. © The Author(s) 2015.

A Path Analysis to Identify the Psychosocial Factors Influencing Physical Activity and Bone Health in Middle-School Girls

PubMed Central

Sharma, Shreela V.; Hoelscher, Deanna M.; Kelder, Steven H.; Diamond, Pamela M.; Day, R. Sue; Hergenroeder, Albert C.

2011-01-01

Background The purpose of this study was to identify pathways used by psychosocial factors to influence physical activity and bone health in middle-school girls. Methods Baseline data from the Incorporating More Physical Activity and Calcium in Teens (IMPACT) study collected in 2001 to 2003 were used. IMPACT was a 1 1/2 years nutrition and physical activity intervention study designed to improve bone density in 717 middle-school girls in Texas. Structural Equations Modeling was used to examine the interrelationships and identify the direct and indirect pathways used by various psychosocial and environmental factors to influence physical activity and bone health. Results Results show that physical activity self-efficacy and social support (friend, family engagement, and encouragement in physical activity) had a significant direct and indirect influence on physical activity with participation in sports teams as the mediator. Participation in sports teams had a direct effect on both physical activity (β= 0.20, P < .05) and bone health and (β=0.13, P < .05). Conclusion The current study identified several direct and indirect pathways that psychosocial factors use to influence physical activity and bone health among adolescent girls. These findings are critical for the development of effective interventions for promoting bone health in this population. PMID:19953837

A path analysis to identify the psychosocial factors influencing physical activity and bone health in middle-school girls.

PubMed

Sharma, Shreela V; Hoelscher, Deanna M; Kelder, Steven H; Diamond, Pamela M; Day, R Sue; Hergenroeder, Albert C

2009-09-01

The purpose of this study was to identify pathways used by psychosocial factors to influence physical activity and bone health in middle-school girls. Baseline data from the Incorporating More Physical Activity and Calcium in Teens (IMPACT) study collected in 2001 to 2003 were used. IMPACT was a 1 1/2 years nutrition and physical activity intervention study designed to improve bone density in 717 middle-school girls in Texas. Structural Equations Modeling was used to examine the interrelationships and identify the direct and indirect pathways used by various psychosocial and environmental factors to influence physical activity and bone health. Results show that physical activity self-efficacy and social support (friend, family engagement, and encouragement in physical activity) had a significant direct and indirect influence on physical activity with participation in sports teams as the mediator. Participation in sports teams had a direct effect on both physical activity (beta = 0.20, P < .05) and bone health and (beta = 0.13, P < .05). The current study identified several direct and indirect pathways that psychosocial factors use to influence physical activity and bone health among adolescent girls. These findings are critical for the development of effective interventions for promoting bone health in this population.

Global analysis of WRKY transcription factor superfamily in Setaria identifies potential candidates involved in abiotic stress signaling.

PubMed

Muthamilarasan, Mehanathan; Bonthala, Venkata S; Khandelwal, Rohit; Jaishankar, Jananee; Shweta, Shweta; Nawaz, Kashif; Prasad, Manoj

2015-01-01

Transcription factors (TFs) are major players in stress signaling and constitute an integral part of signaling networks. Among the major TFs, WRKY proteins play pivotal roles in regulation of transcriptional reprogramming associated with stress responses. In view of this, genome- and transcriptome-wide identification of WRKY TF family was performed in the C4model plants, Setaria italica (SiWRKY) and S. viridis (SvWRKY), respectively. The study identified 105 SiWRKY and 44 SvWRKY proteins that were computationally analyzed for their physicochemical properties. Sequence alignment and phylogenetic analysis classified these proteins into three major groups, namely I, II, and III with majority of WRKY proteins belonging to group II (53 SiWRKY and 23 SvWRKY), followed by group III (39 SiWRKY and 11 SvWRKY) and group I (10 SiWRKY and 6 SvWRKY). Group II proteins were further classified into 5 subgroups (IIa to IIe) based on their phylogeny. Domain analysis showed the presence of WRKY motif and zinc finger-like structures in these proteins along with additional domains in a few proteins. All SiWRKY genes were physically mapped on the S. italica genome and their duplication analysis revealed that 10 and 8 gene pairs underwent tandem and segmental duplications, respectively. Comparative mapping of SiWRKY and SvWRKY genes in related C4 panicoid genomes demonstrated the orthologous relationships between these genomes. In silico expression analysis of SiWRKY and SvWRKY genes showed their differential expression patterns in different tissues and stress conditions. Expression profiling of candidate SiWRKY genes in response to stress (dehydration and salinity) and hormone treatments (abscisic acid, salicylic acid, and methyl jasmonate) suggested the putative involvement of SiWRKY066 and SiWRKY082 in stress and hormone signaling. These genes could be potential candidates for further characterization to delineate their functional roles in abiotic stress signaling.

Evaluation of an inpatient fall risk screening tool to identify the most critical fall risk factors in inpatients.

PubMed

Hou, Wen-Hsuan; Kang, Chun-Mei; Ho, Mu-Hsing; Kuo, Jessie Ming-Chuan; Chen, Hsiao-Lien; Chang, Wen-Yin

2017-03-01

To evaluate the accuracy of the inpatient fall risk screening tool and to identify the most critical fall risk factors in inpatients. Variations exist in several screening tools applied in acute care hospitals for examining risk factors for falls and identifying high-risk inpatients. Secondary data analysis. A subset of inpatient data for the period from June 2011-June 2014 was extracted from the nursing information system and adverse event reporting system of an 818-bed teaching medical centre in Taipei. Data were analysed using descriptive statistics, receiver operating characteristic curve analysis and logistic regression analysis. During the study period, 205 fallers and 37,232 nonfallers were identified. The results revealed that the inpatient fall risk screening tool (cut-off point of ≥3) had a low sensitivity level (60%), satisfactory specificity (87%), a positive predictive value of 2·0% and a negative predictive value of 99%. The receiver operating characteristic curve analysis revealed an area under the curve of 0·805 (sensitivity, 71·8%; specificity, 78%). To increase the sensitivity values, the Youden index suggests at least 1·5 points to be the most suitable cut-off point for the inpatient fall risk screening tool. Multivariate logistic regression analysis revealed a considerably increased fall risk in patients with impaired balance and impaired elimination. The fall risk factor was also significantly associated with days of hospital stay and with admission to surgical wards. The findings can raise awareness about the two most critical risk factors for falls among future clinical nurses and other healthcare professionals and thus facilitate the development of fall prevention interventions. This study highlights the needs for redefining the cut-off points of the inpatient fall risk screening tool to effectively identify inpatients at a high risk of falls. Furthermore, inpatients with impaired balance and impaired elimination should be closely

Identifying context factors explaining physician's low performance in communication assessment: an explorative study in general practice.

PubMed

Essers, Geurt; van Dulmen, Sandra; van Weel, Chris; van der Vleuten, Cees; Kramer, Anneke

2011-12-13

Communication is a key competence for health care professionals. Analysis of registrar and GP communication performance in daily practice, however, suggests a suboptimal application of communication skills. The influence of context factors could reveal why communication performance levels, on average, do not appear adequate. The context of daily practice may require different skills or specific ways of handling these skills, whereas communication skills are mostly treated as generic. So far no empirical analysis of the context has been made. Our aim was to identify context factors that could be related to GP communication. A purposive sample of real-life videotaped GP consultations was analyzed (N = 17). As a frame of reference we chose the MAAS-Global, a widely used assessment instrument for medical communication. By inductive reasoning, we analyzed the GP behaviour in the consultation leading to poor item scores on the MAAS-Global. In these cases we looked for the presence of an intervening context factor, and how this might explain the actual GP communication behaviour. We reached saturation after having viewed 17 consultations. We identified 19 context factors that could potentially explain the deviation from generic recommendations on communication skills. These context factors can be categorized into doctor-related, patient-related, and consultation-related factors. Several context factors seem to influence doctor-patient communication, requiring the GP to apply communication skills differently from recommendations on communication. From this study we conclude that there is a need to explicitly account for context factors in the assessment of GP (and GP registrar) communication performance. The next step is to validate our findings.

Identifying Risk and Protective Factors in Recidivist Juvenile Offenders: A Decision Tree Approach

PubMed Central

Ortega-Campos, Elena; García-García, Juan; Gil-Fenoy, Maria José; Zaldívar-Basurto, Flor

2016-01-01

Research on juvenile justice aims to identify profiles of risk and protective factors in juvenile offenders. This paper presents a study of profiles of risk factors that influence young offenders toward committing sanctionable antisocial behavior (S-ASB). Decision tree analysis is used as a multivariate approach to the phenomenon of repeated sanctionable antisocial behavior in juvenile offenders in Spain. The study sample was made up of the set of juveniles who were charged in a court case in the Juvenile Court of Almeria (Spain). The period of study of recidivism was two years from the baseline. The object of study is presented, through the implementation of a decision tree. Two profiles of risk and protective factors are found. Risk factors associated with higher rates of recidivism are antisocial peers, age at baseline S-ASB, problems in school and criminality in family members. PMID:27611313

IDENTIFYING ELEVEN FACTORS OF SERVICE MARKETING MIX (4PS) EFFECTIVE ON TENDENCY OF PATIENTS TOWARD PRIVATE HOSPITAL

PubMed Central

Hosseini, Seyed Mojtaba; Etesaminia, Samira; Jafari, Mehrnoosh

2016-01-01

Introduction: One of the important factors of correct management is to identify the reasons for patient tendency toward private hospitals. This study measures these factors based on service marketing mixes. Patients and methods: This study used a cross sectional descriptive methodology. The study was conducted during 6 months in 2015. The studied population included patients of private hospitals in Tehran. Random sampling was used (n = 200). Data was collected by an author-made questionnaire for service marketing factors. Reliability and validity of the questionnaire were confirmed. Data analysis was done using factor analysis test in SPSS 20. Results: The results showed that constant attendance of physicians and nurses has the highest effect (0.707%) on patient tendency toward private hospitals. PMID:27999486

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

ERIC Educational Resources Information Center

Benligiray, Serdar; Onay, Ahmet

2017-01-01

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

Factor Analysis of Drawings: Application to College Student Models of the Greenhouse Effect

ERIC Educational Resources Information Center

Libarkin, Julie C.; Thomas, Stephen R.; Ording, Gabriel

2015-01-01

Exploratory factor analysis was used to identify models underlying drawings of the greenhouse effect made by over 200 entering university freshmen. Initial content analysis allowed deconstruction of drawings into salient features, with grouping of these features via factor analysis. A resulting 4-factor solution explains 62% of the data variance,…

Factor Analysis via Components Analysis

ERIC Educational Resources Information Center

Bentler, Peter M.; de Leeuw, Jan

2011-01-01

When the factor analysis model holds, component loadings are linear combinations of factor loadings, and vice versa. This interrelation permits us to define new optimization criteria and estimation methods for exploratory factor analysis. Although this article is primarily conceptual in nature, an illustrative example and a small simulation show…

Identifying risk factors associated with acquiring measles in an outbreak among age-appropriately vaccinated school children: a cohort analysis.

PubMed

O'Connor, Bernadette; Doyle, Sarah

2018-04-10

A measles outbreak occurred in age-appropriately vaccinated children in a school in a town in the South East of Ireland in September-November 2013. The purpose of this study was to investigate the risk factors associated with catching measles during the outbreak. Ninety-five children (4-5 years) in three classes, in the first year of primary school, were included in the study. Immunisation records on the South East Child Health Information System for first Measles Mumps and Rubella (MMR) vaccine for the 95 children were reviewed. Data collected included age at MMR, date of administration of MMR, MMR brand and batch number, and the General Practice at which MMR was administered. The risk factors analysed included age at vaccination, time of vaccination, class and the GP practice where MMR was administered. Statistical analysis was performed using Epi info 7 and SPSS v24. Thirteen children in the cohort developed measles during the outbreak. All children in the cohort were age-appropriately vaccinated, with one dose of MMR vaccine. Analysis demonstrated statistically significant differences in the relative risk of developing measles according to the class a child was in, and the General Practice at which they were vaccinated. The reason for intense measles activity in one class was not established. Although a concurrent investigation into cold chain and vaccine stock management did not identify a cause for the high relative risk of measles in children vaccinated, recommendations were made for improving cold chain and vaccine stock management in General Practices.

Influence maximization in time bounded network identifies transcription factors regulating perturbed pathways

PubMed Central

Jo, Kyuri; Jung, Inuk; Moon, Ji Hwan; Kim, Sun

2016-01-01

Motivation: To understand the dynamic nature of the biological process, it is crucial to identify perturbed pathways in an altered environment and also to infer regulators that trigger the response. Current time-series analysis methods, however, are not powerful enough to identify perturbed pathways and regulators simultaneously. Widely used methods include methods to determine gene sets such as differentially expressed genes or gene clusters and these genes sets need to be further interpreted in terms of biological pathways using other tools. Most pathway analysis methods are not designed for time series data and they do not consider gene-gene influence on the time dimension. Results: In this article, we propose a novel time-series analysis method TimeTP for determining transcription factors (TFs) regulating pathway perturbation, which narrows the focus to perturbed sub-pathways and utilizes the gene regulatory network and protein–protein interaction network to locate TFs triggering the perturbation. TimeTP first identifies perturbed sub-pathways that propagate the expression changes along the time. Starting points of the perturbed sub-pathways are mapped into the network and the most influential TFs are determined by influence maximization technique. The analysis result is visually summarized in TF-Pathway map in time clock. TimeTP was applied to PIK3CA knock-in dataset and found significant sub-pathways and their regulators relevant to the PIP3 signaling pathway. Availability and Implementation: TimeTP is implemented in Python and available at http://biohealth.snu.ac.kr/software/TimeTP/. Supplementary information: Supplementary data are available at Bioinformatics online. Contact: sunkim.bioinfo@snu.ac.kr PMID:27307609

A single factor underlies the metabolic syndrome: a confirmatory factor analysis.

PubMed

Pladevall, Manel; Singal, Bonita; Williams, L Keoki; Brotons, Carlos; Guyer, Heidi; Sadurni, Josep; Falces, Carles; Serrano-Rios, Manuel; Gabriel, Rafael; Shaw, Jonathan E; Zimmet, Paul Z; Haffner, Steven

2006-01-01

Confirmatory factor analysis (CFA) was used to test the hypothesis that the components of the metabolic syndrome are manifestations of a single common factor. Three different datasets were used to test and validate the model. The Spanish and Mauritian studies included 207 men and 203 women and 1,411 men and 1,650 women, respectively. A third analytical dataset including 847 men was obtained from a previously published CFA of a U.S. population. The one-factor model included the metabolic syndrome core components (central obesity, insulin resistance, blood pressure, and lipid measurements). We also tested an expanded one-factor model that included uric acid and leptin levels. Finally, we used CFA to compare the goodness of fit of one-factor models with the fit of two previously published four-factor models. The simplest one-factor model showed the best goodness-of-fit indexes (comparative fit index 1, root mean-square error of approximation 0.00). Comparisons of one-factor with four-factor models in the three datasets favored the one-factor model structure. The selection of variables to represent the different metabolic syndrome components and model specification explained why previous exploratory and confirmatory factor analysis, respectively, failed to identify a single factor for the metabolic syndrome. These analyses support the current clinical definition of the metabolic syndrome, as well as the existence of a single factor that links all of the core components.

Principal component analysis of normalized full spectrum mass spectrometry data in multiMS-toolbox: An effective tool to identify important factors for classification of different metabolic patterns and bacterial strains.

PubMed

Cejnar, Pavel; Kuckova, Stepanka; Prochazka, Ales; Karamonova, Ludmila; Svobodova, Barbora

2018-06-15

Explorative statistical analysis of mass spectrometry data is still a time-consuming step. We analyzed critical factors for application of principal component analysis (PCA) in mass spectrometry and focused on two whole spectrum based normalization techniques and their application in the analysis of registered peak data and, in comparison, in full spectrum data analysis. We used this technique to identify different metabolic patterns in the bacterial culture of Cronobacter sakazakii, an important foodborne pathogen. Two software utilities, the ms-alone, a python-based utility for mass spectrometry data preprocessing and peak extraction, and the multiMS-toolbox, an R software tool for advanced peak registration and detailed explorative statistical analysis, were implemented. The bacterial culture of Cronobacter sakazakii was cultivated on Enterobacter sakazakii Isolation Agar, Blood Agar Base and Tryptone Soya Agar for 24 h and 48 h and applied by the smear method on an Autoflex speed MALDI-TOF mass spectrometer. For three tested cultivation media only two different metabolic patterns of Cronobacter sakazakii were identified using PCA applied on data normalized by two different normalization techniques. Results from matched peak data and subsequent detailed full spectrum analysis identified only two different metabolic patterns - a cultivation on Enterobacter sakazakii Isolation Agar showed significant differences to the cultivation on the other two tested media. The metabolic patterns for all tested cultivation media also proved the dependence on cultivation time. Both whole spectrum based normalization techniques together with the full spectrum PCA allow identification of important discriminative factors in experiments with several variable condition factors avoiding any problems with improper identification of peaks or emphasis on bellow threshold peak data. The amounts of processed data remain still manageable. Both implemented software utilities are available

Secretome Analysis Identifies Potential Pathogenicity/Virulence Factors of Tilletia indica, a Quarantined Fungal Pathogen Inciting Karnal Bunt Disease in Wheat.

PubMed

Pandey, Vishakha; Singh, Manoj; Pandey, Dinesh; Marla, Soma; Kumar, Anil

2018-04-01

Tilletia indica is a smut fungus that incites Karnal bunt in wheat. It has been considered as quarantine pest in more than 70 countries. Despite its quarantine significance, there is meager knowledge regarding the molecular mechanisms of disease pathogenesis. Moreover, various disease management strategies have proven futile. Development of effective disease management strategy requires identification of pathogenicity/virulence factors. With this aim, the present study was conducted to compare the secretomes of T. indica isolates, that is, highly (TiK) and low (TiP) virulent isolates. About 120 and 95 protein spots were detected reproducibly in TiK and TiP secretome gel images. Nineteen protein spots, which were consistently observed as upregulated/differential in the secretome of TiK isolate, were selected for their identification by MALDI-TOF/TOF. Identified proteins exhibited homology with fungal proteins playing important role in fungal adhesion, penetration, invasion, protection against host-derived reactive oxygen species, production of virulence factors, cellular signaling, and degradation of host cell wall proteins and antifungal proteins. These results were complemented with T. indica genome sequence leading to identification of candidate pathogenicity/virulence factors homologs that were further subjected to sequence- and structure-based functional annotation. Thus, present study reports the first comparative secretome analysis of T. indica for identification of pathogenicity/virulence factors. This would provide insights into pathogenic mechanisms of T. indica and aid in devising effective disease management strategies. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Gene expression profiling combined with bioinformatics analysis identify biomarkers for Parkinson disease.

PubMed

Diao, Hongyu; Li, Xinxing; Hu, Sheng; Liu, Yunhui

2012-01-01

Parkinson disease (PD) progresses relentlessly and affects approximately 4% of the population aged over 80 years old. It is difficult to diagnose in its early stages. The purpose of our study is to identify molecular biomarkers for PD initiation using a computational bioinformatics analysis of gene expression. We downloaded the gene expression profile of PD from Gene Expression Omnibus and identified differentially coexpressed genes (DCGs) and dysfunctional pathways in PD patients compared to controls. Besides, we built a regulatory network by mapping the DCGs to known regulatory data between transcription factors (TFs) and target genes and calculated the regulatory impact factor of each transcription factor. As the results, a total of 1004 genes associated with PD initiation were identified. Pathway enrichment of these genes suggests that biological processes of protein turnover were impaired in PD. In the regulatory network, HLF, E2F1 and STAT4 were found have altered expression levels in PD patients. The expression levels of other transcription factors, NKX3-1, TAL1, RFX1 and EGR3, were not found altered. However, they regulated differentially expressed genes. In conclusion, we suggest that HLF, E2F1 and STAT4 may be used as molecular biomarkers for PD; however, more work is needed to validate our result.

Gene Expression Profiling Combined with Bioinformatics Analysis Identify Biomarkers for Parkinson Disease

PubMed Central

Diao, Hongyu; Li, Xinxing; Hu, Sheng; Liu, Yunhui

2012-01-01

Parkinson disease (PD) progresses relentlessly and affects approximately 4% of the population aged over 80 years old. It is difficult to diagnose in its early stages. The purpose of our study is to identify molecular biomarkers for PD initiation using a computational bioinformatics analysis of gene expression. We downloaded the gene expression profile of PD from Gene Expression Omnibus and identified differentially coexpressed genes (DCGs) and dysfunctional pathways in PD patients compared to controls. Besides, we built a regulatory network by mapping the DCGs to known regulatory data between transcription factors (TFs) and target genes and calculated the regulatory impact factor of each transcription factor. As the results, a total of 1004 genes associated with PD initiation were identified. Pathway enrichment of these genes suggests that biological processes of protein turnover were impaired in PD. In the regulatory network, HLF, E2F1 and STAT4 were found have altered expression levels in PD patients. The expression levels of other transcription factors, NKX3-1, TAL1, RFX1 and EGR3, were not found altered. However, they regulated differentially expressed genes. In conclusion, we suggest that HLF, E2F1 and STAT4 may be used as molecular biomarkers for PD; however, more work is needed to validate our result. PMID:23284986

Establishing Evidence for Internal Structure Using Exploratory Factor Analysis

ERIC Educational Resources Information Center

Watson, Joshua C.

2017-01-01

Exploratory factor analysis (EFA) is a data reduction technique used to condense data into smaller sets of summary variables by identifying underlying factors potentially accounting for patterns of collinearity among said variables. Using an illustrative example, the 5 general steps of EFA are described with best practices for decision making…

Pilot-Reported Beta-Blockers Identified by Forensic Toxicology Analysis of Postmortem Specimens.

PubMed

Canfield, Dennis V; Dubowski, Kurt M; Whinnery, James M; Forster, Estrella M

2018-01-01

This study compared beta-blockers reported by pilots with the medications found by postmortem toxicology analysis of specimens received from fatal aviation accidents between 1999 and 2015. Several studies have compared drugs using the standard approach: Compare the drug found by toxicology analysis with the drug reported by the pilot. This study uniquely examined first the pilot-reported medication and then compared it to that detected by toxicology analysis. This study will serve two purposes: (i) to determine the capability of a toxicology laboratory to detect reported medications, and (ii) to identify pilots with medications below detectable limits. All information required for this study was extracted from the Toxicology Data Base system and was searched using ToxFlo or SQL Server Management Studio. The following information was collected and analyzed: pilot-reported trade and/or generic drug, date specimens received, time of accident, type of aviation operations (CFR), state, pilot level, age, class of medical, specimen type, specimen concentration, dose reported, frequency reported associated with the accident, quantity reported, National Transportation Safety Board (NTSB) accident event number, and all NTSB reports. There were 319 pilots that either reported taking a beta-blocker or were found to be taking a beta-blocker by postmortem toxicology analysis. Time of death, therapeutic concentration and specimen type were found to be factors in the ability of the laboratory to detect beta-blockers. Beta-blockers taken by pilots will, in most cases, be found by a competent postmortem forensic toxicology laboratory at therapeutic concentrations. The dose taken by the pilot was not found to be a factor in the ability of the laboratory to identify beta-blockers. Time of dose, route of administration, specimen tested and therapeutic concentration of the drug were found to be factors in the ability of the laboratory to identify beta-blockers in postmortem specimens

Factors affecting job satisfaction in nurse faculty: a meta-analysis.

PubMed

Gormley, Denise K

2003-04-01

Evidence in the literature suggests job satisfaction can make a difference in keeping qualified workers on the job, but little research has been conducted focusing specifically on nursing faculty. Several studies have examined nurse faculty satisfaction in relationship to one or two influencing factors. These factors include professional autonomy, leader role expectations, organizational climate, perceived role conflict and role ambiguity, leadership behaviors, and organizational characteristics. This meta-analysis attempts to synthesize the various studies conducted on job satisfaction in nursing faculty and analyze which influencing factors have the greatest effect. The procedure used for this meta-analysis consisted of reviewing studies to identify factors influencing job satisfaction, research questions, sample size reported, instruments used for measurement of job satisfaction and influencing factors, and results of statistical analysis.

Identifying Causal Risk Factors for Violence among Discharged Patients

PubMed Central

Coid, Jeremy W.; Kallis, Constantinos; Doyle, Mike; Shaw, Jenny; Ullrich, Simone

2015-01-01

Background Structured Professional Judgement (SPJ) is routinely administered in mental health and criminal justice settings but cannot identify violence risk above moderate accuracy. There is no current evidence that violence can be prevented using SPJ. This may be explained by routine application of predictive instead of causal statistical models when standardising SPJ instruments. Methods We carried out a prospective cohort study of 409 male and female patients discharged from medium secure services in England and Wales to the community. Measures were taken at baseline (pre-discharge), 6 and 12 months post-discharge using the Historical, Clinical and Risk-20 items version 3 (HCR-20v3) and Structural Assessment of Protective Factors (SAPROF). Information on violence was obtained via the McArthur community violence instrument and the Police National Computer. Results In a lagged model, HCR-20v3 and SAPROF items were poor predictors of violence. Eight items of the HCR-20v3 and 4 SAPROF items did not predict violent behaviour better than chance. In re-analyses considering temporal proximity of risk/ protective factors (exposure) on violence (outcome), risk was elevated due to violent ideation (OR 6.98, 95% CI 13.85–12.65, P<0.001), instability (OR 5.41, 95% CI 3.44–8.50, P<0.001), and poor coping/ stress (OR 8.35, 95% CI 4.21–16.57, P<0.001). All 3 risk factors were explanatory variables which drove the association with violent outcome. Self-control (OR 0.13, 95% CI 0.08–0.24, P<0.001) conveyed protective effects and explained the association of other protective factors with violence. Conclusions Using two standardised SPJ instruments, predictive (lagged) methods could not identify risk and protective factors which must be targeted in interventions for discharged patients with severe mental illness. Predictive methods should be abandoned if the aim is to progress from risk assessment to effective risk management and replaced by methods which identify factors

Text mining factor analysis (TFA) in green tea patent data

NASA Astrophysics Data System (ADS)

Rahmawati, Sela; Suprijadi, Jadi; Zulhanif

2017-03-01

Factor analysis has become one of the most widely used multivariate statistical procedures in applied research endeavors across a multitude of domains. There are two main types of analyses based on factor analysis: Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). Both EFA and CFA aim to observed relationships among a group of indicators with a latent variable, but they differ fundamentally, a priori and restrictions made to the factor model. This method will be applied to patent data technology sector green tea to determine the development technology of green tea in the world. Patent analysis is useful in identifying the future technological trends in a specific field of technology. Database patent are obtained from agency European Patent Organization (EPO). In this paper, CFA model will be applied to the nominal data, which obtain from the presence absence matrix. While doing processing, analysis CFA for nominal data analysis was based on Tetrachoric matrix. Meanwhile, EFA model will be applied on a title from sector technology dominant. Title will be pre-processing first using text mining analysis.

Anthropometric data reduction using confirmatory factor analysis.

PubMed

Rohani, Jafri Mohd; Olusegun, Akanbi Gabriel; Rani, Mat Rebi Abdul

2014-01-01

The unavailability of anthropometric data especially in developing countries has remained a limiting factor towards the design of learning facilities with sufficient ergonomic consideration. Attempts to use anthropometric data from developed countries have led to provision of school facilities unfit for the users. The purpose of this paper is to use factor analysis to investigate the suitability of the collected anthropometric data as a database for school design in Nigerian tertiary institutions. Anthropometric data were collected from 288 male students in a Federal Polytechnic in North-West of Nigeria. Their age is between 18-25 years. Nine vertical anthropometric dimensions related to heights were collected using the conventional traditional equipment. Exploratory factor analysis was used to categorize the variables into a model consisting of two factors. Thereafter, confirmatory factor analysis was used to investigate the fit of the data to the proposed model. A just identified model, made of two factors, each with three variables was developed. The variables within the model accounted for 81% of the total variation of the entire data. The model was found to demonstrate adequate validity and reliability. Various measuring indices were used to verify that the model fits the data properly. The final model reveals that stature height and eye height sitting were the most stable variables for designs that have to do with standing and sitting construct. The study has shown the application of factor analysis in anthropometric data analysis. The study highlighted the relevance of these statistical tools to investigate variability among anthropometric data involving diverse population, which has not been widely used for analyzing previous anthropometric data. The collected data is therefore suitable for use while designing for Nigerian students.

Global analysis of WRKY transcription factor superfamily in Setaria identifies potential candidates involved in abiotic stress signaling

PubMed Central

Muthamilarasan, Mehanathan; Bonthala, Venkata S.; Khandelwal, Rohit; Jaishankar, Jananee; Shweta, Shweta; Nawaz, Kashif; Prasad, Manoj

2015-01-01

Transcription factors (TFs) are major players in stress signaling and constitute an integral part of signaling networks. Among the major TFs, WRKY proteins play pivotal roles in regulation of transcriptional reprogramming associated with stress responses. In view of this, genome- and transcriptome-wide identification of WRKY TF family was performed in the C4model plants, Setaria italica (SiWRKY) and S. viridis (SvWRKY), respectively. The study identified 105 SiWRKY and 44 SvWRKY proteins that were computationally analyzed for their physicochemical properties. Sequence alignment and phylogenetic analysis classified these proteins into three major groups, namely I, II, and III with majority of WRKY proteins belonging to group II (53 SiWRKY and 23 SvWRKY), followed by group III (39 SiWRKY and 11 SvWRKY) and group I (10 SiWRKY and 6 SvWRKY). Group II proteins were further classified into 5 subgroups (IIa to IIe) based on their phylogeny. Domain analysis showed the presence of WRKY motif and zinc finger-like structures in these proteins along with additional domains in a few proteins. All SiWRKY genes were physically mapped on the S. italica genome and their duplication analysis revealed that 10 and 8 gene pairs underwent tandem and segmental duplications, respectively. Comparative mapping of SiWRKY and SvWRKY genes in related C4 panicoid genomes demonstrated the orthologous relationships between these genomes. In silico expression analysis of SiWRKY and SvWRKY genes showed their differential expression patterns in different tissues and stress conditions. Expression profiling of candidate SiWRKY genes in response to stress (dehydration and salinity) and hormone treatments (abscisic acid, salicylic acid, and methyl jasmonate) suggested the putative involvement of SiWRKY066 and SiWRKY082 in stress and hormone signaling. These genes could be potential candidates for further characterization to delineate their functional roles in abiotic stress signaling. PMID:26635818

Human Factors Vehicle Displacement Analysis: Engineering In Motion

NASA Technical Reports Server (NTRS)

Atencio, Laura Ashley; Reynolds, David; Robertson, Clay

2010-01-01

While positioned on the launch pad at the Kennedy Space Center, tall stacked launch vehicles are exposed to the natural environment. Varying directional winds and vortex shedding causes the vehicle to sway in an oscillating motion. The Human Factors team recognizes that vehicle sway may hinder ground crew operation, impact the ground system designs, and ultimately affect launch availability . The objective of this study is to physically simulate predicted oscillation envelopes identified by analysis. and conduct a Human Factors Analysis to assess the ability to carry out essential Upper Stage (US) ground operator tasks based on predicted vehicle motion.

Proteomic Analysis of Mouse Oocytes Identifies PRMT7 as a Reprogramming Factor that Replaces SOX2 in the Induction of Pluripotent Stem Cells.

PubMed

Wang, Bingyuan; Pfeiffer, Martin J; Drexler, Hannes C A; Fuellen, Georg; Boiani, Michele

2016-08-05

The reprogramming process that leads to induced pluripotent stem cells (iPSCs) may benefit from adding oocyte factors to Yamanaka's reprogramming cocktail (OCT4, SOX2, KLF4, with or without MYC; OSK(M)). We previously searched for such facilitators of reprogramming (the reprogrammome) by applying label-free LC-MS/MS analysis to mouse oocytes, producing a catalog of 28 candidates that are (i) able to robustly access the cell nucleus and (ii) shared between mature mouse oocytes and pluripotent embryonic stem cells. In the present study, we hypothesized that our 28 reprogrammome candidates would also be (iii) abundant in mature oocytes, (iv) depleted after the oocyte-to-embryo transition, and (v) able to potentiate or replace the OSKM factors. Using LC-MS/MS and isotopic labeling methods, we found that the abundance profiles of the 28 proteins were below those of known oocyte-specific and housekeeping proteins. Of the 28 proteins, only arginine methyltransferase 7 (PRMT7) changed substantially during mouse embryogenesis and promoted the conversion of mouse fibroblasts into iPSCs. Specifically, PRMT7 replaced SOX2 in a factor-substitution assay, yielding iPSCs. These findings exemplify how proteomics can be used to prioritize the functional analysis of reprogrammome candidates. The LC-MS/MS data are available via ProteomeXchange with identifier PXD003093.

Examining evolving performance on the Force Concept Inventory using factor analysis

NASA Astrophysics Data System (ADS)

Semak, M. R.; Dietz, R. D.; Pearson, R. H.; Willis, C. W.

2017-06-01

The application of factor analysis to the Force Concept Inventory (FCI) has proven to be problematic. Some studies have suggested that factor analysis of test results serves as a helpful tool in assessing the recognition of Newtonian concepts by students. Other work has produced at best ambiguous results. For the FCI administered as a pre- and post-test, we see factor analysis as a tool by which the changes in conceptual associations made by our students may be gauged given the evolution of their response patterns. This analysis allows us to identify and track conceptual linkages, affording us insight as to how our students have matured due to instruction. We report on our analysis of 427 pre- and post-tests. The factor models for the pre- and post-tests are explored and compared along with the methodology by which these models were fit to the data. The post-test factor pattern is more aligned with an expert's interpretation of the questions' content, as it allows for a more readily identifiable relationship between factors and physical concepts. We discuss this evolution in the context of approaching the characteristics of an expert with force concepts. Also, we find that certain test items do not significantly contribute to the pre- or post-test factor models and attempt explanations as to why this is so. This may suggest that such questions may not be effective in probing the conceptual understanding of our students.

Factor Analysis of the Aberrant Behavior Checklist in Individuals with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Brinkley, Jason; Nations, Laura; Abramson, Ruth K.; Hall, Alicia; Wright, Harry H.; Gabriels, Robin; Gilbert, John R.; Pericak-Vance, Margaret A. O.; Cuccaro, Michael L.

2007-01-01

Exploratory factor analysis (varimax and promax rotations) of the aberrant behavior checklist-community version (ABC) in 275 individuals with Autism spectrum disorder (ASD) identified four- and five-factor solutions which accounted for greater than 70% of the variance. Confirmatory factor analysis (Lisrel 8.7) revealed indices of moderate fit for…

Factor Analysis and Counseling Research

ERIC Educational Resources Information Center

Weiss, David J.

1970-01-01

Topics discussed include factor analysis versus cluster analysis, analysis of Q correlation matrices, ipsativity and factor analysis, and tests for the significance of a correlation matrix prior to application of factor analytic techniques. Techniques for factor extraction discussed include principal components, canonical factor analysis, alpha…

Testing all six person-oriented principles in dynamic factor analysis.

PubMed

Molenaar, Peter C M

2010-05-01

All six person-oriented principles identified by Sterba and Bauer's Keynote Article can be tested by means of dynamic factor analysis in its current form. In particular, it is shown how complex interactions and interindividual differences/intraindividual change can be tested in this way. In addition, the necessity to use single-subject methods in the analysis of developmental processes is emphasized, and attention is drawn to the possibility to optimally treat developmental psychopathology by means of new computational techniques that can be integrated with dynamic factor analysis.

Using Multi-Group Confirmatory Factor Analysis to Evaluate Cross-Cultural Research: Identifying and Understanding Non-Invariance

ERIC Educational Resources Information Center

Brown, Gavin T. L.; Harris, Lois R.; O'Quin, Chrissie; Lane, Kenneth E.

2017-01-01

Multi-group confirmatory factor analysis (MGCFA) allows researchers to determine whether a research inventory elicits similar response patterns across samples. If statistical equivalence in responding is found, then scale score comparisons become possible and samples can be said to be from the same population. This paper illustrates the use of…

Identifying molecular subtypes related to clinicopathologic factors in pancreatic cancer

PubMed Central

2014-01-01

Background Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal tumors and usually presented with locally advanced and distant metastasis disease, which prevent curative resection or treatments. In this regard, we considered identifying molecular subtypes associated with clinicopathological factor as prognosis factors to stratify PDAC for appropriate treatment of patients. Results In this study, we identified three molecular subtypes which were significant on survival time and metastasis. We also identified significant genes and enriched pathways represented for each molecular subtype. Considering R0 resection patients included in each subtype, metastasis and survival times are significantly associated with subtype 1 and subtype 2. Conclusions We observed three PDAC molecular subtypes and demonstrated that those subtypes were significantly related with metastasis and survival time. The study may have utility in stratifying patients for cancer treatment. PMID:25560450

Burden of liver disease in Europe: epidemiology and analysis of risk factors to identify prevention policies.

PubMed

Pimpin, Laura; Cortez-Pinto, Helena; Negro, Francesco; Corbould, Emily; Lazarus, Jeffrey V; Webber, Laura; Sheron, Nick

2018-05-16

The burden of liver disease in Europe continues to grow. We aimed to describe the epidemiology of liver diseases and their risk factors in European countries, and identify public health interventions that could impact on these risk factors to reduce the burden of liver disease. As part of the HEPAHEALTH project, commissioned by EASL, we extracted information on historical and current prevalence and mortality from national and international literature and databases on liver disease in 35 countries in the WHO European region, as well as historical and recent prevalence data on their main determinants; alcohol consumption, obesity and hepatitis B and C virus infections. We extracted information from peer-reviewed and grey literature to identify public health interventions targeting these risk factors. The epidemiology of liver disease is diverse and countries cluster with similar pictures, although the exact composition of diseases and the trends in risk factors which drive them is varied. Prevalence and mortality data indicate that increasing cirrhosis and liver cancer may be linked to dramatic increases in harmful alcohol consumption in Northern European countries, and viral hepatitis epidemics in Eastern and Southern European countries. Countries with historically low levels of liver disease may experience an increase in non-alcoholic fatty liver disease in the future, given the rise of obesity across the majority of European countries. Interventions exist for curbing harmful alcohol use, reducing obesity, preventing or treating viral hepatitis, and screening for liver disease at an early stage. Liver disease in Europe is a serious issue, with increasing cirrhosis and liver cancer. The public health and hepatology communities are uniquely placed to implement measures aimed at reducing their causes: harmful alcohol consumption, child and adult obesity prevalence and chronic infection with hepatitis viruses, which will in turn reduce the burden of liver disease. The

Obesogenic family types identified through latent profile analysis.

PubMed

Martinson, Brian C; VazquezBenitez, Gabriela; Patnode, Carrie D; Hearst, Mary O; Sherwood, Nancy E; Parker, Emily D; Sirard, John; Pasch, Keryn E; Lytle, Leslie

2011-10-01

Obesity may cluster in families due to shared physical and social environments. This study aims to identify family typologies of obesity risk based on family environments. Using 2007-2008 data from 706 parent/youth dyads in Minnesota, we applied latent profile analysis and general linear models to evaluate associations between family typologies and body mass index (BMI) of youth and parents. Three typologies described most families with 18.8% "Unenriched/Obesogenic," 16.9% "Risky Consumer," and 64.3% "Healthy Consumer/Salutogenic." After adjustment for demographic and socioeconomic factors, parent BMI and youth BMI Z-scores were higher in unenriched/obesogenic families (BMI difference = 2.7, p < 0.01 and BMI Z-score difference = 0.51, p < 0.01, respectively) relative to the healthy consumer/salutogenic typology. In contrast, parent BMI and youth BMI Z-scores were similar in the risky consumer families relative to those in healthy consumer/salutogenic type. We can identify family types differing in obesity risks with implications for public health interventions.

A factor analysis of landscape pattern and structure metrics

Treesearch

Kurt H. Riitters; R.V. O' Neill; C.T. Hunsaker; James D. Wickham; D.H. Yankee; S.P. Timmins; K.B. Jones; B.L. Jackson

1995-01-01

Fifty-five metrics of landscape pattern and structure were calculated for 85 maps of land use and land cover. A multivariate factor analysis was used to identify the common axes (or dimensions) of pattern and structure which were measured by a reduced set of 26 metrics. The first six factors explained about 87% of the variation in the 26 landscape metrics. These...

Multivariate analysis of prognostic factors in synovial sarcoma.

PubMed

Koh, Kyoung Hwan; Cho, Eun Yoon; Kim, Dong Wook; Seo, Sung Wook

2009-11-01

Many studies have described the diversity of synovial sarcoma in terms of its biological characteristics and clinical features. Moreover, much effort has been expended on the identification of prognostic factors because of unpredictable behaviors of synovial sarcomas. However, with the exception of tumor size, published results have been inconsistent. We attempted to identify independent risk factors using survival analysis. Forty-one consecutive patients with synovial sarcoma were prospectively followed from January 1997 to March 2008. Overall and progression-free survival for age, sex, tumor size, tumor location, metastasis at presentation, histologic subtype, chemotherapy, radiation therapy, and resection margin were analyzed, and standard multivariate Cox proportional hazard regression analysis was used to evaluate potential prognostic factors. Tumor size (>5 cm), nonlimb-based tumors, metastasis at presentation, and a monophasic subtype were associated with poorer overall survival. Multivariate analysis showed metastasis at presentation and monophasic tumor subtype affected overall survival. For the progression-free survival, monophasic subtype was found to be only 1 prognostic factor. The study confirmed that histologic subtype is the single most important independent prognostic factors of synovial sarcoma regardless of tumor stage.

Factors influencing speech and language outcomes of children with early identified severe/profound hearing loss: Clinician-identified facilitators and barriers.

PubMed

Fulcher, Anne Nivelles; Purcell, Alison; Baker, Elise; Munro, Natalie

2015-06-01

Early identification of severe/profound childhood hearing loss (HL) gives these children access to hearing devices and early intervention to facilitate improved speech and language outcomes. Predicting which infants will go on to achieve such outcomes remains difficult. This study describes clinician identified malleable and non-malleable factors that may influence speech and language outcomes for children with severe/profound HL. Semi-structured interviews were conducted with six experienced auditory verbal clinicians. A collective case study design was implemented. The interviews were transcribed and coded into themes using constant comparative analysis. Clinicians identified that, for children with severe/profound HL, early identification, early amplification and commencing auditory-verbal intervention under 6 months of age may facilitate child progress. Possible barriers were living in rural/remote areas, the clinicians' lack of experience and confidence in providing intervention for infants under age 6-months and belonging to a family with a culturally and linguistically diverse (CALD) background. The results indicate that multiple factors need to be considered by clinicians working with children with HL and their families to determine how each child functions within their own environment and personal contexts, consistent with the International Classification of Functioning, Disability and Health (ICF) framework. Such an approach is likely to empower clinicians to carefully balance potential barriers to, and facilitators of, optimal speech and language outcomes for all children with HL.

Analysis of risk factors in the development of retinopathy of prematurity.

PubMed

Knezević, Sanja; Stojanović, Nadezda; Oros, Ana; Savić, Dragana; Simović, Aleksandra; Knezević, Jasmina

2011-01-01

Retinopathy of prematurity (ROP) is a multifactorial disease that occurs most frequently in very small and very sick preterm infants, and it has been identified as the major cause of childhood blindness. The aim of this study was to evaluate ROP incidence and risk factors associated with varying degrees of illness. The study was conducted at the Centre for Neonatology, Paediatric Clinic of the Clinical Centre Kragujevac, Serbia, in the period from June 2006 to December 2008. Ophthalmologic screening was performed in all children with body weight lower than 2000 g or gestational age lower than 36 weeks. We analyzed eighteen postnatal and six perinatal risk factors and the group correlations for each of the risk factors. Out of 317 children that were screened, 56 (17.7%) developed a mild form of ROP, while 68 (21.5%) developed a severe form. Univariate analysis revealed a large number of statistically significant risk factors for the development of ROP, especially the severe form. Multivariate logistical analysis further separated two independent risk factors: small birth weight (p = 0.001) and damage of central nervous system (p = 0.01). Independent risk factors for transition from mild to severe forms of ROP were identified as: small birth weight (p = 0.05) and perinatal risk factors (p = 0.02). Small birth weight and central nervous system damage were risk factors for the development of ROP, perinatal risk factors were identified as significant for transition from mild to severe form of ROP.

An Empirical Analysis of Factors Affecting Honors Program Completion Rates

ERIC Educational Resources Information Center

Savage, Hallie; Raehsler, Rod D.; Fiedor, Joseph

2014-01-01

One of the most important issues in any educational environment is identifying factors that promote academic success. A plethora of research on such factors exists across most academic fields, involving a wide range of student demographics, and the definition of student success varies across the range of studies published. The analysis in this…

Detecting Outliers in Factor Analysis Using the Forward Search Algorithm

ERIC Educational Resources Information Center

Mavridis, Dimitris; Moustaki, Irini

2008-01-01

In this article we extend and implement the forward search algorithm for identifying atypical subjects/observations in factor analysis models. The forward search has been mainly developed for detecting aberrant observations in regression models (Atkinson, 1994) and in multivariate methods such as cluster and discriminant analysis (Atkinson, Riani,…

Identifying socio-environmental factors that facilitate resilience among Canadian palliative family caregivers: a qualitative case study.

PubMed

Giesbrecht, Melissa; Wolse, Faye; Crooks, Valorie A; Stajduhar, Kelli

2015-06-01

In Canada, friends and family members are becoming increasingly responsible for providing palliative care in the home. This is resulting in some caregivers experiencing high levels of stress and burden that may ultimately surpass their ability to cope. Recent palliative care research has demonstrated the potential for caregiver resilience within such contexts. This research, however, is primarily focused on exploring individual-level factors that contribute to resilience, minimizing the inherent complexity of this concept, and how it is simultaneously influenced by one's social context. Therefore, our study aims to identify socio-environmental factors that contribute to palliative family caregiver resilience in the Canadian homecare context. Drawing on ethnographic fieldnotes and semistructured interviews with family caregivers, care recipients, and homecare nurses, this secondary analysis employs an intersectionality lens and qualitative case study approach to identify socio-environmental factors that facilitate family caregivers' capacity for resilience. Following a case study methodology, two cases are purposely selected for analysis. Findings demonstrate that family caregiver resilience is influenced not only by individual-level factors but also by the social environment, which sets the lived context from which caregiving roles are experienced. Thematic findings of the two case studies revealed six socio-environmental factors that play a role in shaping resilience: access to social networks, education/knowledge/awareness, employment status, housing status, geographic location, and life-course stage. Findings contribute to existing research on caregiver resilience by empirically demonstrating the role of socio-environmental factors in caregiving experiences. Furthermore, utilizing an intersectional approach, these findings build on existing notions that resilience is a multidimensional and complex process influenced by numerous related variables that intersect

Newly identified poor prognostic factors for adult T-cell leukemia-lymphoma treated with allogeneic hematopoietic stem cell transplantation.

PubMed

Tokunaga, Masahito; Uto, Hirofumi; Takeuchi, Shogo; Nakano, Nobuaki; Kubota, Ayumu; Tokunaga, Mayumi; Takatsuka, Yoshifusa; Seto, Masao; Ido, Akio; Utsunomiya, Atae

2017-01-01

To explore pre-transplantation prognostic factors for adult T-cell leukemia-lymphoma (ATL), we retrospectively analyzed allogeneic hematopoietic stem cell transplantation (allo-HSCT) in 70 patients at our institute (63 acute type and seven lymphoma type patients). Forty-five patients died after HSCT and the three-year overall survival (OS) rate was 35.2%. By univariate analysis, the adverse prognostic factors for OS were performance status ≥2, hematopoietic cell transplantation-specific comorbidity index (HCT-CI) score ≥3, European Group for Blood and Marrow Transplantation (EBMT) risk score ≥5, HSCT from an HLA-mismatched donor, serum soluble interleukin-2 receptor (sIL-2R) level ≥10,000 U/mL, lymphocyte count ≥4000/μL, and hemoglobin <9 g/dL at the time of HSCT. EBMT risk score and sIL-2R were identified as significant adverse prognostic factors using multivariate analysis. This analysis clearly demonstrates for the first time that HCT-CI and EBMT risk scores are reliable prognostic factors for ATL patients receiving allo-HSCT.

Use of clinical risk factors to identify postmenopausal women with vertebral fractures.

PubMed

Tobias, J H; Hutchinson, A P; Hunt, L P; McCloskey, E V; Stone, M D; Martin, J C; Thompson, P W; Palferman, T G; Bhalla, A K

2007-01-01

Previous studies have been unable to identify risk factors for prevalent vertebral fractures (VF), which are suitable for use in selection strategies intended to target high-risk sub-groups for diagnostic assessment. However, these studies generally consisted of large epidemiology surveys based on questionnaires and were only able to evaluate a limited number of risk factors. Here, we investigated whether a stronger relationship exists with prevalent VF when conventional risk factors are combined with additional information obtained from detailed one-to-one assessment. Women aged 65-75 registered at four geographically distinct GP practices were invited to participate (n=1,518), of whom 540 attended for assessment as follows: a questionnaire asking about risk factors for osteoporosis such as height loss compared to age 25 and history of non-vertebral fracture (NVF), the get-up-and-go test, Margolis back pain score, measurement of wall-tragus and rib-pelvis distances, and BMD as measured by the distal forearm BMD. A lateral thoraco-lumbar spine X-ray was obtained, which was subsequently scored for the presence of significant vertebral deformities. Of the 509 subjects who underwent spinal radiographs, 37 (7.3%) were found to have one or more VF. Following logistic regression analysis, the four most predictive clinical risk factors for prevalent VF were: height loss (P=0.006), past NVF (P=0.004), history of back pain (P=0.075) and age (P=0.05). BMD was also significantly associated with prevalent VF (P=0.002), but its inclusion did not affect associations with other variables. Factors elicited from detailed one-to-one assessment were not related to the risk of one or more prevalent VFs. The area under ROC curves derived from these regressions, which suggested that models for prevalent VF had modest predictive accuracy, were as follows: 0.68 (BMD), 0.74 (four clinical risk factors above) and 0.78 (clinical risk factors + BMD). Analyses were repeated in relation to the

Donor retention in health care in Iran: a factor analysis

PubMed Central

Aghababa, Sara; Nasiripour, Amir Ashkan; Maleki, Mohammadreza; Gohari, Mahmoodreza

2017-01-01

Background: Long-term financial support is essential for the survival of a charitable organization. Health charities need to identify the effective factors influencing donor retention. Methods: In the present study, the items of a questionnaire were derived from both literature review and semi-structured interviews related to donor retention. Using a purposive sampling, 300 academic and executive practitioners were selected. After the follow- up, a total of 243 usable questionnaires were prepared for factor analysis. The questionnaire was validated based on the face and content validity and reliability through Cronbach’s α-coefficient. Results: The results of exploratory factor analysis extracted 2 factors for retention: donor factor (variance = 33.841%; Cronbach’s α-coefficient = 90.2) and charity factor (variance = 29.038%; Cronbach’s α-coefficient = 82.8), respectively. Subsequently, confirmatory factor analysis was applied to support the overall reasonable fit. Conclusions: In this study, it was found that repeated monetary donations are supplied to the charitable organizations when both aspects of donor factor (retention factor and charity factor) for retention are taken into consideration. This model could provide a perspective for making sustainable donations and charitable giving PMID:28955663

Educational interventions for general practitioners to identify and manage depression as a suicide risk factor in young people: a systematic review and meta-analysis protocol.

PubMed

Tait, Lynda; Michail, Maria

2014-12-15

Suicide is a major public health problem and globally is the second leading cause of death in young adults. Globally, there are 164,000 suicides per year in young people under 25 years. Depression is a strong risk factor for suicide. Evidence shows that 45% of those completing suicide, including young adults, contact their general practitioner rather than a mental health professional in the month before their death. Further evidence indicates that risk factors or early warning signs of suicide in young people go undetected and untreated by general practitioners. Healthcare-based suicide prevention interventions targeted at general practitioners are designed to increase identification of at-risk young people. The rationale of this type of intervention is that early identification and improved clinical management of at-risk individuals will reduce morbidity and mortality. This systematic review will synthesise evidence on the effectiveness of education interventions for general practitioners in identifying and managing depression as a suicide risk factor in young people. We shall conduct a systematic review and meta-analysis following the Cochrane Handbook for Systematic Reviews of Interventions guidelines and conform to the reporting guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement recommendations. Electronic databases will be systematically searched for randomised controlled trials and quasi-experimental studies investigating the effectiveness of interventions for general practitioners in identifying and managing depression as a suicide risk factor in young people in comparison to any other intervention, no intervention, usual care or waiting list. Grey literature will be searched by screening trial registers. Only studies published in English will be included. No date restrictions will be applied. Two authors will independently screen titles and abstracts of potential studies. The primary outcome is

A data mining paradigm for identifying key factors in biological processes using gene expression data.

PubMed

Li, Jin; Zheng, Le; Uchiyama, Akihiko; Bin, Lianghua; Mauro, Theodora M; Elias, Peter M; Pawelczyk, Tadeusz; Sakowicz-Burkiewicz, Monika; Trzeciak, Magdalena; Leung, Donald Y M; Morasso, Maria I; Yu, Peng

2018-06-13

A large volume of biological data is being generated for studying mechanisms of various biological processes. These precious data enable large-scale computational analyses to gain biological insights. However, it remains a challenge to mine the data efficiently for knowledge discovery. The heterogeneity of these data makes it difficult to consistently integrate them, slowing down the process of biological discovery. We introduce a data processing paradigm to identify key factors in biological processes via systematic collection of gene expression datasets, primary analysis of data, and evaluation of consistent signals. To demonstrate its effectiveness, our paradigm was applied to epidermal development and identified many genes that play a potential role in this process. Besides the known epidermal development genes, a substantial proportion of the identified genes are still not supported by gain- or loss-of-function studies, yielding many novel genes for future studies. Among them, we selected a top gene for loss-of-function experimental validation and confirmed its function in epidermal differentiation, proving the ability of this paradigm to identify new factors in biological processes. In addition, this paradigm revealed many key genes in cold-induced thermogenesis using data from cold-challenged tissues, demonstrating its generalizability. This paradigm can lead to fruitful results for studying molecular mechanisms in an era of explosive accumulation of publicly available biological data.

Cluster analysis identifies three urodynamic patterns in patients with orthotopic neobladder reconstruction.

PubMed

Kim, Kwang Hyun; Yoon, Hyun Suk; Song, Wan; Choo, Hee Jung; Yoon, Hana; Chung, Woo Sik; Sim, Bong Suk; Lee, Dong Hyeon

2017-01-01

To classify patients with orthotopic neobladder based on urodynamic parameters using cluster analysis and to characterize the voiding function of each group. From January 2012 to November 2015, 142 patients with bladder cancer underwent radical cystectomy and Studer neobladder reconstruction at our institute. Of the 142 patients, 103 with complete urodynamic data and information on urinary functional outcomes were included in this study. K-means clustering was performed with urodynamic parameters which included maximal cystometric capacity, residual volume, maximal flow rate, compliance, and detrusor pressure at maximum flow rate. Three groups emerged by cluster analysis. Urodynamic parameters and urinary function outcomes were compared between three groups. Group 1 (n = 44) had ideal urodynamic parameters with a mean maximal bladder capacity of 513.3 ml and mean residual urine volume of 33.1 ml. Group 2 (n = 42) was characterized by small bladder capacity with low compliance. Patients in group 2 had higher rates of daytime incontinence and nighttime incontinence than patients in group 1. Group 3 (n = 17) was characterized by large residual urine volume with high compliance. When we examined gender differences in urodynamics and functional outcomes, residual urine volume and the rate of daytime incontinence were only marginally significant. However, females were significantly more likely to belong to group 2 or 3 (P = 0.003). In multivariate analysis to identify factors associated with group 1 which has the most ideal urodynamic pattern, age (OR 0.95, P = 0.017) and male gender (OR 7.57, P = 0.003) were identified as significant factors. While patients with ileal neobladder present with various voiding symptoms, three urodynamic patterns were identified by cluster analysis. Approximately half of patients had ideal urodynamic parameters. The other two groups were characterized by large residual urine and small capacity bladder with low compliance. Young age and male

Using Horn's Parallel Analysis Method in Exploratory Factor Analysis for Determining the Number of Factors

ERIC Educational Resources Information Center

Çokluk, Ömay; Koçak, Duygu

2016-01-01

In this study, the number of factors obtained from parallel analysis, a method used for determining the number of factors in exploratory factor analysis, was compared to that of the factors obtained from eigenvalue and scree plot--two traditional methods for determining the number of factors--in terms of consistency. Parallel analysis is based on…

RNA sequencing and pathway analysis identify tumor necrosis factor alpha driven small proline-rich protein dysregulation in chronic rhinosinusitis.

PubMed

Ramakrishnan, Vijay R; Gonzalez, Joseph R; Cooper, Sarah E; Barham, Henry P; Anderson, Catherine B; Larson, Eric D; Cool, Carlyne D; Diller, John D; Jones, Kenneth; Kinnamon, Sue C

2017-09-01

Chronic rhinosinusitis (CRS) is a heterogeneous inflammatory disorder in which many pathways contribute to end-organ disease. Small proline-rich proteins (SPRR) are polypeptides that have recently been shown to contribute to epithelial biomechanical properties relevant in T-helper type 2 inflammation. There is evidence that genetic polymorphism in SPRR genes may predict the development of asthma in children with atopy and, correlatively, that expression of SPRRs is increased under allergic conditions, which leads to epithelial barrier dysfunction in atopic disease. RNAs from uncinate tissue specimens from patients with CRS and control subjects were compared by RNA sequencing by using Ingenuity Pathway Analysis (n = 4 each), and quantitative polymerase chain reaction (PCR) (n = 15). A separate cohort of archived sinus tissue was examined by immunohistochemistry (n = 19). A statistically significant increase of SPRR expression in CRS sinus tissue was identified that was not a result of atopic presence. SPRR1 and SPRR2A expressions were markedly increased in patients with CRS (p < 0.01) on RNA sequencing, with confirmation by using real-time PCR. Immunohistochemistry of archived surgical samples demonstrated staining of SPRR proteins within squamous epithelium of both groups. Pathway analysis indicated tumor necrosis factor (TNF) alpha as a master regulator of the SPRR gene products. Expression of SPRR1 and of SPRR2A is increased in mucosal samples from patients with CRS and appeared as a downstream result of TNF alpha modulation, which possibly resulted in epithelial barrier dysfunction.

Identifying critical factors influencing the disposal of dead pigs by farmers in China.

PubMed

Wu, Linhai; Xu, Guoyan; Wang, Xiaoli

2016-01-01

Disposal of dead pigs by pig farmers may have a direct impact on pork safety, public health, and the ecological environment in China. Drawing on the existing literature, this study analyzed and summarized the main factors that could affect the disposal of dead pigs by pig farmers by conducting a survey of 654 pig farmers in Funing County, Jiangsu Province, China. The purpose of this analysis was to investigate the disposal of dead pigs in China and provide useful regulatory strategies for the government. The interrelationships among dimensions and factors that affect the disposal of dead pigs by farmers were analyzed, and critical factors were identified by a hybrid multi-criteria decision-making method, which is a combination of decision-making trial and evaluation laboratory (DEMATEL) and analytic network process (ANP). Our results demonstrated that production characteristics were the most important dimensions and that costs and profits, scale of farming, pattern of farming, knowledge of relevant laws and regulations, and knowledge of pig disease and prevention were the five most critical factors affecting the disposal of dead pigs by farmers in China at this stage. The significance of this study lies in further discussing some management policies for the Chinese government regarding strengthen regulation of disposing dead pigs.

Factor analysis of some socio-economic and demographic variables for Bangladesh.

PubMed

Islam, S M

1986-01-01

The author carries out an exploratory factor analysis of some socioeconomic and demographic variables for Bangladesh using the classical or common factor approach with the varimax rotation method. The socioeconomic and demographic indicators used in this study include literacy, rate of growth, female employment, economic development, urbanization, population density, childlessness, sex ratio, proportion of women ever married, and fertility. The 18 administrative districts of Bangladesh constitute the unit of analysis. 3 common factors--modernization, fertility, and social progress--are identified in this study to explain the correlations among the set of selected socioeconomic and demographic variables.

Determining the Number of Factors in P-Technique Factor Analysis

ERIC Educational Resources Information Center

Lo, Lawrence L.; Molenaar, Peter C. M.; Rovine, Michael

2017-01-01

Determining the number of factors is a critical first step in exploratory factor analysis. Although various criteria and methods for determining the number of factors have been evaluated in the usual between-subjects R-technique factor analysis, there is still question of how these methods perform in within-subjects P-technique factor analysis. A…

Application of Factor Analysis on the Financial Ratios of Indian Cement Industry and Validation of the Results by Cluster Analysis

NASA Astrophysics Data System (ADS)

De, Anupam; Bandyopadhyay, Gautam; Chakraborty, B. N.

2010-10-01

Financial ratio analysis is an important and commonly used tool in analyzing financial health of a firm. Quite a large number of financial ratios, which can be categorized in different groups, are used for this analysis. However, to reduce number of ratios to be used for financial analysis and regrouping them into different groups on basis of empirical evidence, Factor Analysis technique is being used successfully by different researches during the last three decades. In this study Factor Analysis has been applied over audited financial data of Indian cement companies for a period of 10 years. The sample companies are listed on the Stock Exchange India (BSE and NSE). Factor Analysis, conducted over 44 variables (financial ratios) grouped in 7 categories, resulted in 11 underlying categories (factors). Each factor is named in an appropriate manner considering the factor loads and constituent variables (ratios). Representative ratios are identified for each such factor. To validate the results of Factor Analysis and to reach final conclusion regarding the representative ratios, Cluster Analysis had been performed.

Relating genes to function: identifying enriched transcription factors using the ENCODE ChIP-Seq significance tool.

PubMed

Auerbach, Raymond K; Chen, Bin; Butte, Atul J

2013-08-01

Biological analysis has shifted from identifying genes and transcripts to mapping these genes and transcripts to biological functions. The ENCODE Project has generated hundreds of ChIP-Seq experiments spanning multiple transcription factors and cell lines for public use, but tools for a biomedical scientist to analyze these data are either non-existent or tailored to narrow biological questions. We present the ENCODE ChIP-Seq Significance Tool, a flexible web application leveraging public ENCODE data to identify enriched transcription factors in a gene or transcript list for comparative analyses. The ENCODE ChIP-Seq Significance Tool is written in JavaScript on the client side and has been tested on Google Chrome, Apple Safari and Mozilla Firefox browsers. Server-side scripts are written in PHP and leverage R and a MySQL database. The tool is available at http://encodeqt.stanford.edu. abutte@stanford.edu Supplementary material is available at Bioinformatics online.

Changes in snoring during natural sleep identified by acoustic crest factor analysis at different times of night.

PubMed

Hill, P D; Osman, E Z; Osborne, J E; Lee, B W

2000-12-01

Sleep nasendoscopy can be used to identify the site of snoring but questions remain about how well a short assessment during drug-induced sleep reflects the natural condition. To investigate the uniformity of snoring during natural sleep we studied five patients (three men, two women) referred by their GPs for treatment of their snoring. A digital audio tape recorder captured the free-field snore sound at different times of night in hospital. Acoustic Crest Factor values were calculated on the 15 recordings made, having previously demonstrated that high crest factor values distinguish palatal from non-palatal snoring at sleep nasendoscopy. Some recordings showed reproducibility, but others showed substantial changes between recordings an hour apart. We infer that the snoring mechanism may change in some individuals during the night, with or without a change of snore site. We conclude a single recording, as in sleep nasendoscopy, may not be representative.

[Facilitating the diagnosis of depression and burnout by identifying demographic and work-related risk and protective factors among nurses].

PubMed

Ádám, Szilvia; Nistor, Anikó; Nistor, Katalin; Cserháti, Zoltán; Mészáros, Veronika

2015-08-09

Depression and burnout are frequent comorbidities among nurses. Despite similar symptoms, their management differ. Therefore, their timely diagnosis is essential. To identify demographic and work-related risk and protective factors of burnout and depression, and facilitate their diagnosis. A cross-sectional study among 1,713 nurses was carried out. Depression and burnout were assessed by the shortened Beck Depression Questionnaire and Maclach Burnout Inventory, respectively. Risk and protective factors were explored using t-tests and analysis of variance. The prevalence of depression and moderate-to-high burnout was 35.1% and 34-74%, respectively. Having a partner/child and longer employment in the outpatient setting protected from burnout. Lack of a partner and male sex emerged as risk factors of depression and depersonalisation, respectively. High prevalence of depression and burnout among nurses poses a significant public health issue. Familiarity with the disease-specific risk and protective factors identified in this research may facilitate timely diagnosis and effective disease management.

Identifying Key Drivers of Return Reversal with Dynamical Bayesian Factor Graph

PubMed Central

Zhao, Shuai; Tong, Yunhai; Wang, Zitian; Tan, Shaohua

2016-01-01

In the stock market, return reversal occurs when investors sell overbought stocks and buy oversold stocks, reversing the stocks’ price trends. In this paper, we develop a new method to identify key drivers of return reversal by incorporating a comprehensive set of factors derived from different economic theories into one unified dynamical Bayesian factor graph. We then use the model to depict factor relationships and their dynamics, from which we make some interesting discoveries about the mechanism behind return reversals. Through extensive experiments on the US stock market, we conclude that among the various factors, the liquidity factors consistently emerge as key drivers of return reversal, which is in support of the theory of liquidity effect. Specifically, we find that stocks with high turnover rates or high Amihud illiquidity measures have a greater probability of experiencing return reversals. Apart from the consistent drivers, we find other drivers of return reversal that generally change from year to year, and they serve as important characteristics for evaluating the trends of stock returns. Besides, we also identify some seldom discussed yet enlightening inter-factor relationships, one of which shows that stocks in Finance and Insurance industry are more likely to have high Amihud illiquidity measures in comparison with those in other industries. These conclusions are robust for return reversals under different thresholds. PMID:27893780

Identifying Key Drivers of Return Reversal with Dynamical Bayesian Factor Graph.

PubMed

Zhao, Shuai; Tong, Yunhai; Wang, Zitian; Tan, Shaohua

2016-01-01

In the stock market, return reversal occurs when investors sell overbought stocks and buy oversold stocks, reversing the stocks' price trends. In this paper, we develop a new method to identify key drivers of return reversal by incorporating a comprehensive set of factors derived from different economic theories into one unified dynamical Bayesian factor graph. We then use the model to depict factor relationships and their dynamics, from which we make some interesting discoveries about the mechanism behind return reversals. Through extensive experiments on the US stock market, we conclude that among the various factors, the liquidity factors consistently emerge as key drivers of return reversal, which is in support of the theory of liquidity effect. Specifically, we find that stocks with high turnover rates or high Amihud illiquidity measures have a greater probability of experiencing return reversals. Apart from the consistent drivers, we find other drivers of return reversal that generally change from year to year, and they serve as important characteristics for evaluating the trends of stock returns. Besides, we also identify some seldom discussed yet enlightening inter-factor relationships, one of which shows that stocks in Finance and Insurance industry are more likely to have high Amihud illiquidity measures in comparison with those in other industries. These conclusions are robust for return reversals under different thresholds.

Meta-analysis of genome-wide association studies identifies genetic risk factors for stroke in African-Americans

PubMed Central

Carty, Cara L.; Keene, Keith L.; Cheng, Yu-Ching; Meschia, James F.; Chen, Wei-Min; Nalls, Mike; Bis, Joshua C.; Kittner, Steven J.; Rich, Stephen S.; Tajuddin, Salman; Zonderman, Alan B.; Evans, Michele K.; Langefeld, Carl D.; Gottesman, Rebecca; Mosley, Thomas H.; Shahar, Eyal; Woo, Daniel; Yaffe, Kristine; Liu, YongMei; Sale, Michèle M.; Dichgans, Martin; Malik, Rainer; Longstreth, WT; Mitchell, Braxton D.; Psaty, Bruce M.; Kooperberg, Charles; Reiner, Alexander; Worrall, Bradford B.; Fornage, Myriam

2015-01-01

Background and Purpose The majority of genome-wide association studies (GWAS) of stroke have focused on European-ancestry populations; however, none has been conducted in African-Americans despite the disproportionately high burden of stroke in this population. The Consortium of Minority Population genome-wide Association Studies of Stroke (COMPASS) was established to identify stroke susceptibility loci in minority populations. Methods Using METAL, we conducted meta-analyses of GWAS in 14,746 African-Americans (1,365 ischemic and 1,592 total stroke cases) from COMPASS, and tested SNPs with P<10−6 for validation in METASTROKE, a consortium of ischemic stroke genetic studies in European-ancestry populations. We also evaluated stroke loci previously identified in European-ancestry populations. Results The 15q21.3 locus linked with lipid levels and hypertension was associated with total stroke (rs4471613, P=3.9×10−8) in African-Americans. Nominal associations (P<10−6) for total or ischemic stroke were observed for 18 variants in or near genes implicated in cell cycle/ mRNA pre-splicing (PTPRG, CDC5L), platelet function (HPS4), blood-brain barrier permeability (CLDN17), immune response (ELTD1, WDFY4, IL1F10-IL1RN), and histone modification (HDAC9). Two of these loci achieved nominal significance in METASTROKE: 5q35.2 (P=0.03), and 1p31.1 (P=0.018). Four of 7 previously reported ischemic stroke loci (PITX2, HDAC9, CDKN2A/CDKN2B and ZFHX3) were nominally associated (P<0.05) with stroke in COMPASS. Conclusions We identified a novel SNP associated with total stroke in African-Americans and found that ischemic stroke loci identified in European-ancestry populations may also be relevant for African-Americans. Our findings support investigation of diverse populations to identify and characterize genetic risk factors, and the importance of shared genetic risk across populations. PMID:26089329

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

NASA Technical Reports Server (NTRS)

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

2002-01-01

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

Multivariate linear regression analysis to identify general factors for quantitative predictions of implant stability quotient values

PubMed Central

Huang, Hairong; Xu, Zanzan; Shao, Xianhong; Wismeijer, Daniel; Sun, Ping; Wang, Jingxiao

2017-01-01

Objectives This study identified potential general influencing factors for a mathematical prediction of implant stability quotient (ISQ) values in clinical practice. Methods We collected the ISQ values of 557 implants from 2 different brands (SICace and Osstem) placed by 2 surgeons in 336 patients. Surgeon 1 placed 329 SICace implants, and surgeon 2 placed 113 SICace implants and 115 Osstem implants. ISQ measurements were taken at T1 (immediately after implant placement) and T2 (before dental restoration). A multivariate linear regression model was used to analyze the influence of the following 11 candidate factors for stability prediction: sex, age, maxillary/mandibular location, bone type, immediate/delayed implantation, bone grafting, insertion torque, I-stage or II-stage healing pattern, implant diameter, implant length and T1-T2 time interval. Results The need for bone grafting as a predictor significantly influenced ISQ values in all three groups at T1 (weight coefficients ranging from -4 to -5). In contrast, implant diameter consistently influenced the ISQ values in all three groups at T2 (weight coefficients ranging from 3.4 to 4.2). Other factors, such as sex, age, I/II-stage implantation and bone type, did not significantly influence ISQ values at T2, and implant length did not significantly influence ISQ values at T1 or T2. Conclusions These findings provide a rational basis for mathematical models to quantitatively predict the ISQ values of implants in clinical practice. PMID:29084260

Identifying Environmental and Social Factors Predisposing to Pathological Gambling Combining Standard Logistic Regression and Logic Learning Machine.

PubMed

Parodi, Stefano; Dosi, Corrado; Zambon, Antonella; Ferrari, Enrico; Muselli, Marco

2017-12-01

Identifying potential risk factors for problem gambling (PG) is of primary importance for planning preventive and therapeutic interventions. We illustrate a new approach based on the combination of standard logistic regression and an innovative method of supervised data mining (Logic Learning Machine or LLM). Data were taken from a pilot cross-sectional study to identify subjects with PG behaviour, assessed by two internationally validated scales (SOGS and Lie/Bet). Information was obtained from 251 gamblers recruited in six betting establishments. Data on socio-demographic characteristics, lifestyle and cognitive-related factors, and type, place and frequency of preferred gambling were obtained by a self-administered questionnaire. The following variables associated with PG were identified: instant gratification games, alcohol abuse, cognitive distortion, illegal behaviours and having started gambling with a relative or a friend. Furthermore, the combination of LLM and LR indicated the presence of two different types of PG, namely: (a) daily gamblers, more prone to illegal behaviour, with poor money management skills and who started gambling at an early age, and (b) non-daily gamblers, characterised by superstitious beliefs and a higher preference for immediate reward games. Finally, instant gratification games were strongly associated with the number of games usually played. Studies on gamblers habitually frequently betting shops are rare. The finding of different types of PG by habitual gamblers deserves further analysis in larger studies. Advanced data mining algorithms, like LLM, are powerful tools and potentially useful in identifying risk factors for PG.

Organizational commitment and job satisfaction among nurses in Serbia: a factor analysis.

PubMed

Veličković, Vladica M; Višnjić, Aleksandar; Jović, Slađana; Radulović, Olivera; Šargić, Čedomir; Mihajlović, Jovan; Mladenović, Jelena

2014-01-01

One of the basic prerequisites of efficient organizational management in health institutions is certainly monitoring and measuring satisfaction of employees and their commitment to the health institution in which they work. The aim of this article was to identify and test factors that may have a predictive effect on job satisfaction and organizational commitment. We conducted a cross-sectional study that included 1,337 nurses from Serbia. Data were analyzed by using exploratory factor analysis, multivariate regressions, and descriptive statistics. The study identified three major factors of organizational commitment: affective commitment, disloyalty, and continuance commitment. The most important predictors of these factors were positive professional identification, extrinsic job satisfaction, and intrinsic job satisfaction (p < .0001). Predictors significantly affecting both job satisfaction and organizational commitment were identified as well; the most important of which was positive professional identification (p < .0001). This study identified the main factors affecting job satisfaction and organizational commitment of nurses, which formed a good basis for the creation of organizational management policy and human resource management policy in health institutions in Serbia. Copyright © 2014 Elsevier Inc. All rights reserved.

Prognostic factors in patients with spinal metastasis: a systematic review and meta-analysis.

PubMed

Luksanapruksa, Panya; Buchowski, Jacob M; Hotchkiss, William; Tongsai, Sasima; Wilartratsami, Sirichai; Chotivichit, Areesak

2017-05-01

Incidence of symptomatic spinal metastasis has increased owing to improvement in treatment of the disease. One of the key factors that influences decision-making is expected patient survival. To our knowledge, no systematic reviews or meta-analysis have been conducted that review independent prognostic factors in spinal metastases. This study aimed to determine independent prognostic factors that affect outcome in patients with metastatic spine disease. This is a systematic literature review and meta-analysis of publications for prognostic factors in spinal metastatic disease. Pooled patient results from cohort and observational studies. Meta-analysis for poor prognostic factors as determined by hazard ratio (HR) and 95% confidential interval (95% CI). We systematically searched relevant publications in PubMed and Embase. The following search terms were used: ("'spinal metastases'" OR "'vertebral metastases'" OR "spinal metastasis" OR 'vertebral metastases') AND ('"prognostic factors"' OR "'survival'"). Inclusion criteria were prospective and retrospective cohort series that report HR and 95% CI of independent prognostic factors from multivariate analysis. Two reviewers independently assessed all papers. The quality of included papers was assessed by using Newcastle-Ottawa Scale for cohort studies and publication bias was assessed by using funnel plot, Begg test, and Egger test. The prognostic factors that were mentioned in at least three publications were pooled. Meta-analysis was performed using HR and 95% CI as the primary outcomes of interest. Heterogeneity was assessed using the I 2 method. A total of 3,959 abstracts (1,382 from PubMed and 2,577 from Embase) were identified through database search and 40 publications were identified through review of cited publications. The reviewers selected a total of 51 studies for qualitative synthesis and 43 studies for meta-analysis. Seventeen poor prognostic factors were identified. These included presence of a

Naturalistic Cycling Study: Identifying Risk Factors for On-Road Commuter Cyclists

PubMed Central

Johnson, Marilyn; Charlton, Judith; Oxley, Jennifer; Newstead, Stuart

2010-01-01

The study aim was to identify risk factors for collisions/near-collisions involving on-road commuter cyclists and drivers. A naturalistic cycling study was conducted in Melbourne, Australia, with cyclists wearing helmet-mounted video cameras. Video recordings captured cyclists’ perspective of the road and traffic behaviours including head checks, reactions and manoeuvres. The 100-car naturalistic driving study analysis technique was adapted for data analysis and events were classified by severity: collision, near-collision and incident. Participants were adult cyclists and each filmed 12 hours of commuter cycling trips over a 4-week period. In total, 127 hours and 38 minutes were analysed for 13 participants, 54 events were identified: 2 collisions, 6 near-collisions and 46 incidents. Prior to events, 88.9% of cyclists travelled in a safe/legal manner. Sideswipe was the most frequent event type (40.7%). Most events occurred at an intersection/intersection-related location (70.3%). The vehicle driver was judged at fault in the majority of events (87.0%) and no post-event driver reaction was observed (83.3%). Cross tabulations revealed significant associations between event severity and: cyclist reaction, cyclist post-event manoeuvre, pre-event driver behaviour, other vehicle involved, driver reaction, visual obstruction, cyclist head check (left), event type and vehicle location (p<0.05). Frequent head checks suggest cyclists had high situational awareness and their reactive behaviour to driver actions led to successful avoidance of collisions/near-collisions. Strategies to improve driver awareness of on-road cyclists and to indicate early before turning/changing lanes when sharing the roadway with cyclists are discussed. Findings will contribute to the development of effective countermeasures to reduce cyclist trauma. PMID:21050610

Naturalistic cycling study: identifying risk factors for on-road commuter cyclists.

PubMed

Johnson, Marilyn; Charlton, Judith; Oxley, Jennifer; Newstead, Stuart

2010-01-01

The study aim was to identify risk factors for collisions/near-collisions involving on-road commuter cyclists and drivers. A naturalistic cycling study was conducted in Melbourne, Australia, with cyclists wearing helmet-mounted video cameras. Video recordings captured cyclists' perspective of the road and traffic behaviours including head checks, reactions and manoeuvres. The 100-car naturalistic driving study analysis technique was adapted for data analysis and events were classified by severity: collision, near-collision and incident. Participants were adult cyclists and each filmed 12 hours of commuter cycling trips over a 4-week period. In total, 127 hours and 38 minutes were analysed for 13 participants, 54 events were identified: 2 collisions, 6 near-collisions and 46 incidents. Prior to events, 88.9% of cyclists travelled in a safe/legal manner. Sideswipe was the most frequent event type (40.7%). Most events occurred at an intersection/intersection-related location (70.3%). The vehicle driver was judged at fault in the majority of events (87.0%) and no post-event driver reaction was observed (83.3%). Cross tabulations revealed significant associations between event severity and: cyclist reaction, cyclist post-event manoeuvre, pre-event driver behaviour, other vehicle involved, driver reaction, visual obstruction, cyclist head check (left), event type and vehicle location (p<0.05). Frequent head checks suggest cyclists had high situational awareness and their reactive behaviour to driver actions led to successful avoidance of collisions/near-collisions. Strategies to improve driver awareness of on-road cyclists and to indicate early before turning/changing lanes when sharing the roadway with cyclists are discussed. Findings will contribute to the development of effective countermeasures to reduce cyclist trauma.

Genome-wide analysis of gene expression and protein secretion of Babesia canis during virulent infection identifies potential pathogenicity factors.

PubMed

Eichenberger, Ramon M; Ramakrishnan, Chandra; Russo, Giancarlo; Deplazes, Peter; Hehl, Adrian B

2017-06-13

Infections of dogs with virulent strains of Babesia canis are characterized by rapid onset and high mortality, comparable to complicated human malaria. As in other apicomplexan parasites, most Babesia virulence factors responsible for survival and pathogenicity are secreted to the host cell surface and beyond where they remodel and biochemically modify the infected cell interacting with host proteins in a very specific manner. Here, we investigated factors secreted by B. canis during acute infections in dogs and report on in silico predictions and experimental analysis of the parasite's exportome. As a backdrop, we generated a fully annotated B. canis genome sequence of a virulent Hungarian field isolate (strain BcH-CHIPZ) underpinned by extensive genome-wide RNA-seq analysis. We find evidence for conserved factors in apicomplexan hemoparasites involved in immune-evasion (e.g. VESA-protein family), proteins secreted across the iRBC membrane into the host bloodstream (e.g. SA- and Bc28 protein families), potential moonlighting proteins (e.g. profilin and histones), and uncharacterized antigens present during acute crisis in dogs. The combined data provides a first predicted and partially validated set of potential virulence factors exported during fatal infections, which can be exploited for urgently needed innovative intervention strategies aimed at facilitating diagnosis and management of canine babesiosis.

NREL Analysis Identifies Where Commercial Customers Might Benefit from

Science.gov Websites

Battery Energy Storage | NREL | News | NREL NREL Analysis Identifies Where Commercial Customers Might Benefit from Battery Energy Storage News Release: NREL Analysis Identifies Where Commercial reduce operating costs for customers paying demand charges Commercial electricity customers who are

Identifying the principal driving factors of water ecosystem dependence and the corresponding indicator species in a pilot City, China

NASA Astrophysics Data System (ADS)

Zhao, C. S.; Shao, N. F.; Yang, S. T.; Xiang, H.; Lou, H. Z.; Sun, Y.; Yang, Z. Y.; Zhang, Y.; Yu, X. Y.; Zhang, C. B.; Yu, Q.

2018-01-01

The world's aquatic ecosystems yield numerous vital services, which are essential to human existence but have deteriorated seriously in recent years. By studying the mechanisms of interaction between ecosystems and habitat processes, the constraining factors can be identified, and this knowledge can be used to improve the success rate of ecological restoration initiatives. At present, there is insufficient data on the link between hydrological, water quality factors and the changes in the structure of aquatic communities to allow any meaningful study of driving factors of aquatic ecosystems. In this study, the typical monitoring stations were selected by fuzzy clustering analysis based on the spatial and temporal distribution characteristics of water ecology in Jinan City, the first pilot city for the construction of civilized aquatic ecosystems in China. The dominant species identification model was used to identify the dominant species of the aquatic community. The driving effect of hydrological and water quality factors on dominant species was analyzed by Canonical Correspondence Analysis. Then, the principal factors of aquatic ecosystem dependence were selected. The results showed that there were 10 typical monitoring stations out of 59 monitoring sites, which were representative of aquatic ecosystems, 9 dominant fish species, and 20 dominant invertebrate species. The selection of factors for aquatic ecosystem dependence in Jinan were highly influenced by its regional conditions. Chemical environmental parameters influence the temporal and spatial variation of invertebrate much more than that of fish in Jinan City. However, the methodologies coupling typical monitoring stations selection, dominant species determination and driving factors identification were certified to be a cost-effective way, which can provide in-deep theoretical and technical directions for the restoration of aquatic ecosystems elsewhere.

Identifying the bleeding trauma patient: predictive factors for massive transfusion in an Australasian trauma population.

PubMed

Hsu, Jeremy Ming; Hitos, Kerry; Fletcher, John P

2013-09-01

Military and civilian data would suggest that hemostatic resuscitation results in improved outcomes for exsanguinating patients. However, identification of those patients who are at risk of significant hemorrhage is not clearly defined. We attempted to identify factors that would predict the need for massive transfusion (MT) in an Australasian trauma population, by comparing those trauma patients who did receive massive transfusion with those who did not. Between 1985 and 2010, 1,686 trauma patients receiving at least 1 U of packed red blood cells were identified from our prospectively maintained trauma registry. Demographic, physiologic, laboratory, injury, and outcome variables were reviewed. Univariate analysis determined significant factors between those who received MT and those who did not. A predictive multivariate logistic regression model with backward conditional stepwise elimination was used for MT risk. Statistical analysis was performed using SPSS PASW. MT patients had a higher pulse rate, lower Glasgow Coma Scale (GCS) score, lower systolic blood pressure, lower hemoglobin level, higher Injury Severity Score (ISS), higher international normalized ratio (INR), and longer stay. Initial logistic regression identified base deficit (BD), INR, and hemoperitoneum at laparotomy as independent predictive variables. After assigning cutoff points of BD being greater than 5 and an INR of 1.5 or greater, a further model was created. A BD greater than 5 and either INR of 1.5 or greater or hemoperitoneum was associated with 51 times increase in MT risk (odds ratio, 51.6; 95% confidence interval, 24.9-95.8). The area under the receiver operating characteristic curve for the model was 0.859. From this study, a combination of BD, INR, and hemoperitoneum has demonstrated good predictability for MT. This tool may assist in the determination of those patients who might benefit from hemostatic resuscitation. Prognostic study, level III.

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.

Spatial analysis to identify hotspots of prevalence of schizophrenia.

PubMed

Moreno, Berta; García-Alonso, Carlos R; Negrín Hernández, Miguel A; Torres-González, Francisco; Salvador-Carulla, Luis

2008-10-01

The geographical distribution of mental health disorders is useful information for epidemiological research and health services planning. To determine the existence of geographical hotspots with a high prevalence of schizophrenia in a mental health area in Spain. The study included 774 patients with schizophrenia who were users of the community mental health care service in the area of South Granada. Spatial analysis (Kernel estimation) and Bayesian relative risks were used to locate potential hotspots. Availability and accessibility were both rated in each zone and spatial algebra was applied to identify hotspots in a particular zone. The age-corrected prevalence rate of schizophrenia was 2.86 per 1,000 population in the South Granada area. Bayesian analysis showed a relative risk varying from 0.43 to 2.33. The area analysed had a non-uniform spatial distribution of schizophrenia, with one main hotspot (zone S2). This zone had poor accessibility to and availability of mental health services. A municipality-based variation exists in the prevalence of schizophrenia and related disorders in the study area. Spatial analysis techniques are useful tools to analyse the heterogeneous distribution of a variable and to explain genetic/environmental factors in hotspots related with a lack of easy availability of and accessibility to adequate health care services.

Analysis of Adverse Events in Identifying GPS Human Factors Issues

NASA Technical Reports Server (NTRS)

Adams, Catherine A.; Hwoschinsky, Peter V.; Adams, Richard J.

2004-01-01

The purpose of this study was to analyze GPS related adverse events such as accidents and incidents (A/I), Aviation Safety Reporting System (ASRS) reports and Pilots Deviations (PDs) to create a framework for developing a human factors risk awareness program. Although the occurrence of directly related GPS accidents is small the frequency of PDs and ASRS reports indicated there is a growing problem with situational awareness in terminal airspace related to different types of GPs operational issues. This paper addresses the findings of the preliminary research and a brief discussion of some of the literature on related GPS and automation issues.

Validating the Copenhagen Psychosocial Questionnaire (COPSOQ-II) Using Set-ESEM: Identifying Psychosocial Risk Factors in a Sample of School Principals

PubMed Central

Dicke, Theresa; Marsh, Herbert W.; Riley, Philip; Parker, Philip D.; Guo, Jiesi; Horwood, Marcus

2018-01-01

School principals world-wide report high levels of strain and attrition resulting in a shortage of qualified principals. It is thus crucial to identify psychosocial risk factors that reflect principals' occupational wellbeing. For this purpose, we used the Copenhagen Psychosocial Questionnaire (COPSOQ-II), a widely used self-report measure covering multiple psychosocial factors identified by leading occupational stress theories. We evaluated the COPSOQ-II regarding factor structure and longitudinal, discriminant, and convergent validity using latent structural equation modeling in a large sample of Australian school principals (N = 2,049). Results reveal that confirmatory factor analysis produced marginally acceptable model fit. A novel approach we call set exploratory structural equation modeling (set-ESEM), where cross-loadings were only allowed within a priori defined sets of factors, fit well, and was more parsimonious than a full ESEM. Further multitrait-multimethod models based on the set-ESEM confirm the importance of a principal's psychosocial risk factors; Stressors and depression were related to demands and ill-being, while confidence and autonomy were related to wellbeing. We also show that working in the private sector was beneficial for showing a low psychosocial risk, while other demographics have little effects. Finally, we identify five latent risk profiles (high risk to no risk) of school principals based on all psychosocial factors. Overall the research presented here closes the theory application gap of a strong multi-dimensional measure of psychosocial risk-factors. PMID:29760670

Validating the Copenhagen Psychosocial Questionnaire (COPSOQ-II) Using Set-ESEM: Identifying Psychosocial Risk Factors in a Sample of School Principals.

PubMed

Dicke, Theresa; Marsh, Herbert W; Riley, Philip; Parker, Philip D; Guo, Jiesi; Horwood, Marcus

2018-01-01

School principals world-wide report high levels of strain and attrition resulting in a shortage of qualified principals. It is thus crucial to identify psychosocial risk factors that reflect principals' occupational wellbeing. For this purpose, we used the Copenhagen Psychosocial Questionnaire (COPSOQ-II), a widely used self-report measure covering multiple psychosocial factors identified by leading occupational stress theories. We evaluated the COPSOQ-II regarding factor structure and longitudinal, discriminant, and convergent validity using latent structural equation modeling in a large sample of Australian school principals ( N = 2,049). Results reveal that confirmatory factor analysis produced marginally acceptable model fit. A novel approach we call set exploratory structural equation modeling (set-ESEM), where cross-loadings were only allowed within a priori defined sets of factors, fit well, and was more parsimonious than a full ESEM. Further multitrait-multimethod models based on the set-ESEM confirm the importance of a principal's psychosocial risk factors; Stressors and depression were related to demands and ill-being, while confidence and autonomy were related to wellbeing. We also show that working in the private sector was beneficial for showing a low psychosocial risk, while other demographics have little effects. Finally, we identify five latent risk profiles (high risk to no risk) of school principals based on all psychosocial factors. Overall the research presented here closes the theory application gap of a strong multi-dimensional measure of psychosocial risk-factors.

The Promise of Virtual Teams: Identifying Key Factors in Effectiveness and Failure

ERIC Educational Resources Information Center

Horwitz, Frank M.; Bravington, Desmond; Silvis, Ulrik

2006-01-01

Purpose: The aim of the investigation is to identify enabling and disenabling factors in the development and operation of virtual teams; to evaluate the importance of factors such as team development, cross-cultural variables, leadership, communication and social cohesion as contributors to virtual team effectiveness. Design/methodology/approach:…

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

DTIC Science & Technology

2013-04-01

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

PTEN IDENTIFIED AS IMPORTANT RISK FACTOR OF CHRONIC OBSTRUCTIVE PULMONARY DISEASE

PubMed Central

Hosgood, H Dean; Menashe, Idan; He, Xingzhou; Chanock, Stephen; Lan, Qing

2009-01-01

Common genetic variation may play an important role in altering chronic obstructive pulmonary disease (COPD) risk. In Xuanwei, China, the COPD rate is more than twice the Chinese national average, and COPD is strongly associated with in-home coal use. To identify genetic variation that may be associated with COPD in a population with substantial in-home coal smoke exposures, we evaluated 1,261 single nucleotide polymorphisms (SNPs) in 380 candidate genes potentially relevant for cancer and other human diseases in a population-based case-control study in Xuanwei (53 cases; 107 controls). PTEN was the most significantly associated gene with COPD in a minP analysis using 20,000 permutations (P = 0.00005). SNP-based analyses found that homozygote variant carriers of PTEN rs701848 (ORTT = 0.12, 95%CI = 0.03 - 0.47) had a significant decreased risk of COPD. PTEN, or phosphatase and tensin homolog, is an important regulator of cell cycle progression and cellular survival via the AKT signaling pathway. Our exploratory analysis suggests that genetic variation in PTEN may be an important risk factor of COPD in Xuanwei. However, due to the small sample size, additional studies are needed to evaluate these associations within Xuanwei and other populations with coal smoke exposures. PMID:19625176

Identifying the necessary and sufficient number of risk factors for predicting academic failure.

PubMed

Lucio, Robert; Hunt, Elizabeth; Bornovalova, Marina

2012-03-01

Identifying the point at which individuals become at risk for academic failure (grade point average [GPA] < 2.0) involves an understanding of which and how many factors contribute to poor outcomes. School-related factors appear to be among the many factors that significantly impact academic success or failure. This study focused on 12 school-related factors. Using a thorough 5-step process, we identified which unique risk factors place one at risk for academic failure. Academic engagement, academic expectations, academic self-efficacy, homework completion, school relevance, school safety, teacher relationships (positive relationship), grade retention, school mobility, and school misbehaviors (negative relationship) were uniquely related to GPA even after controlling for all relevant covariates. Next, a receiver operating characteristic curve was used to determine a cutoff point for determining how many risk factors predict academic failure (GPA < 2.0). Results yielded a cutoff point of 2 risk factors for predicting academic failure, which provides a way for early identification of individuals who are at risk. Further implications of these findings are discussed. PsycINFO Database Record (c) 2012 APA, all rights reserved.

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

PubMed

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

2017-02-01

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

Analysis of horse race videos to identify intra-race risk factors for fatal distal limb fracture.

PubMed

Parkin, T D H; Clegg, P D; French, N P; Proudman, C J; Riggs, C M; Singer, E R; Webbon, P M; Morgan, K L

2006-04-17

The objective of this study was to identify risk factors, during racing, associated with imminent fatal distal limb fracture in Thoroughbreds. One hundred and nine cases of fatal distal limb fracture were identified from all 59 UK racecourses over a 2-year period (February 1999-January 2001). Three uninjured control horses were randomly selected from the same race as the case horse. Videos of races in which fractures occurred were viewed using a defined protocol. Fractures in flat races occurred at any time during the race, whereas 74% (45/61) of cases in national hunt type races occurred in the second half of races. More than 75% (79/103) of cases were spontaneous, i.e. there was no obvious external influence such as a fall at a fence or collision with another horse. Sixty-six percent (44/67) of horses, sustaining a forelimb fracture, fractured the forelimb they were using as lead leg at the time of fracture. When case and control horses were compared, horses that were: (a) making good progress through the race, (b) reluctant to start and (c) received encouragement in the final 10s before the time of fracture, were more likely to sustain a fracture.

Identifying the challenging factors in the transition from colleges of engineering to employment

NASA Astrophysics Data System (ADS)

Baytiyeh, Hoda; Naja, Mohamad

2012-03-01

The transition from university to a career in engineering is a challenging process. This study examined the perceptions of engineering graduates regarding the difficulties they encountered in their transition from the university to the workplace. Lebanese practising engineers (n=217), living around the world, were surveyed to identify their current employment situations and their attitudes toward their academic preparation. Factor analysis revealed three main challenges facing engineering graduates: communication; responsibility; self-confidence. Seventeen interviews were conducted to gather information on ways to facilitate this transition. Comments reflected the need for better collaboration between engineering schools and engineering firms. The results will provide insight for engineering colleges, faculty members and administrators into the challenges faced by graduates and their aspirations for a smoother transition into employment.

Identifying the hydrochemical characteristics of rivers and groundwater by multivariate statistical analysis in the Sanjiang Plain, China

NASA Astrophysics Data System (ADS)

Cao, Yingjie; Tang, Changyuan; Song, Xianfang; Liu, Changming; Zhang, Yinghua

2016-06-01

Two multivariate statistical technologies, factor analysis (FA) and discriminant analysis (DA), are applied to study the river and groundwater hydrochemistry and its controlling processes in the Sanjiang Plain of the northeast China. Factor analysis identifies five factors which account for 79.65 % of the total variance in the dataset. Four factors bearing specific meanings as the river and groundwater hydrochemistry controlling processes are divided into two groups, the "natural hydrochemistry evolution" group and the "pollution" group. The "natural hydrochemistry evolution" group includes the salinity factor (factor 1) caused by rock weathering and the residence time factor (factor 2) reflecting the groundwater traveling time. The "pollution" group represents the groundwater quality deterioration due to geogenic pollution caused by elevated Fe and Mn (factor 3) and elevated nitrate (NO3 -) introduced by human activities such as agriculture exploitations (factor 5). The hydrochemical difference and hydraulic connection among rivers (surface water, SW), shallow groundwater (SG) and deep groundwater (DG) group are evaluated by the factor scores obtained from FA and DA (Fisher's method). It is showed that the river water is characterized as low salinity and slight pollution, and the shallow groundwater has the highest salinity and severe pollution. The SW is well separated from SG and DG by Fisher's discriminant function, but the SG and DG can not be well separated showing their hydrochemical similarities, and emphasize hydraulic connections between SG and DG.

A case-control study to identify risk factors for totally implantable central venous port-related bloodstream infection.

PubMed

Lee, Guk Jin; Hong, Sook Hee; Roh, Sang Young; Park, Sa Rah; Lee, Myung Ah; Chun, Hoo Geun; Hong, Young Seon; Kang, Jin Hyoung; Kim, Sang Il; Kim, Youn Jeong; Chun, Ho Jong; Oh, Jung Suk

2014-07-01

To date, the risk factors for central venous port-related bloodstream infection (CVPBSI) in solid cancer patients have not been fully elucidated. We conducted this study in order to determine the risk factors for CVP-BSI in patients with solid cancer. A total of 1,642 patients with solid cancer received an implantable central venous port for delivery of chemotherapy between October 2008 and December 2011 in a single center. CVP-BSI was diagnosed in 66 patients (4%). We selected a control group of 130 patients, who were individually matched with respect to age, sex, and catheter insertion time. CVP-BSI occurred most frequently between September and November (37.9%). The most common pathogen was gram-positive cocci (n=35, 53.0%), followed by fungus (n=14, 21.2%). Multivariate analysis identified monthly catheter-stay as a risk factor for CVP-BSI (p=0.000), however, its risk was lower in primary gastrointestinal cancer than in other cancer (p=0.002). Initial metastatic disease and long catheter-stay were statistically significant factors affecting catheter life span (p=0.005 and p=0.000). Results of multivariate analysis showed that recent transfusion was a risk factor for mortality in patients with CVP-BSI (p=0.047). In analysis of the results with respect to risk factors, prolonged catheter-stay should be avoided as much as possible. It is necessary to be cautious of CVP-BSI in metastatic solid cancer, especially non-gastrointestinal cancer. In addition, avoidance of unnecessary transfusion is essential in order to reduce the mortality of CVP-BSI. Finally, considering the fact that confounding factors may have affected the results, conduct of a well-designed prospective controlled study is warranted.

In vivo insertion pool sequencing identifies virulence factors in a complex fungal–host interaction

PubMed Central

Uhse, Simon; Pflug, Florian G.; Stirnberg, Alexandra; Ehrlinger, Klaus; von Haeseler, Arndt

2018-01-01

Large-scale insertional mutagenesis screens can be powerful genome-wide tools if they are streamlined with efficient downstream analysis, which is a serious bottleneck in complex biological systems. A major impediment to the success of next-generation sequencing (NGS)-based screens for virulence factors is that the genetic material of pathogens is often underrepresented within the eukaryotic host, making detection extremely challenging. We therefore established insertion Pool-Sequencing (iPool-Seq) on maize infected with the biotrophic fungus U. maydis. iPool-Seq features tagmentation, unique molecular barcodes, and affinity purification of pathogen insertion mutant DNA from in vivo-infected tissues. In a proof of concept using iPool-Seq, we identified 28 virulence factors, including 23 that were previously uncharacterized, from an initial pool of 195 candidate effector mutants. Because of its sensitivity and quantitative nature, iPool-Seq can be applied to any insertional mutagenesis library and is especially suitable for genetically complex setups like pooled infections of eukaryotic hosts. PMID:29684023

What Makes Sports Fans Interactive? Identifying Factors Affecting Chat Interactions in Online Sports Viewing

PubMed Central

Yeo, Jaeryong; Lee, Juyeong

2016-01-01

Sports fans are able to watch games from many locations using TV services while interacting with other fans online. In this paper, we identify the factors that affect sports viewers’ online interactions. Using a large-scale dataset of more than 25 million chat messages from a popular social TV site for baseball, we extract various game-related factors, and investigate the relationships between these factors and fans’ interactions using a series of multiple regression analyses. As a result, we identify several factors that are significantly related to viewer interactions. In addition, we determine that the influence of these factors varies according to the user group; i.e., active vs. less active users, and loyal vs. non-loyal users. PMID:26849568

Combining Knowledge and Data Driven Insights for Identifying Risk Factors using Electronic Health Records

PubMed Central

Sun, Jimeng; Hu, Jianying; Luo, Dijun; Markatou, Marianthi; Wang, Fei; Edabollahi, Shahram; Steinhubl, Steven E.; Daar, Zahra; Stewart, Walter F.

2012-01-01

Background: The ability to identify the risk factors related to an adverse condition, e.g., heart failures (HF) diagnosis, is very important for improving care quality and reducing cost. Existing approaches for risk factor identification are either knowledge driven (from guidelines or literatures) or data driven (from observational data). No existing method provides a model to effectively combine expert knowledge with data driven insight for risk factor identification. Methods: We present a systematic approach to enhance known knowledge-based risk factors with additional potential risk factors derived from data. The core of our approach is a sparse regression model with regularization terms that correspond to both knowledge and data driven risk factors. Results: The approach is validated using a large dataset containing 4,644 heart failure cases and 45,981 controls. The outpatient electronic health records (EHRs) for these patients include diagnosis, medication, lab results from 2003–2010. We demonstrate that the proposed method can identify complementary risk factors that are not in the existing known factors and can better predict the onset of HF. We quantitatively compare different sets of risk factors in the context of predicting onset of HF using the performance metric, the Area Under the ROC Curve (AUC). The combined risk factors between knowledge and data significantly outperform knowledge-based risk factors alone. Furthermore, those additional risk factors are confirmed to be clinically meaningful by a cardiologist. Conclusion: We present a systematic framework for combining knowledge and data driven insights for risk factor identification. We demonstrate the power of this framework in the context of predicting onset of HF, where our approach can successfully identify intuitive and predictive risk factors beyond a set of known HF risk factors. PMID:23304365

Identifying associated factors with social capital using path analysis: A population-based survey in Tehran, Iran (Urban HEART-2).

PubMed

Asadi-Lari, Mohsen; Hassanzadeh, Jafar; Torabinia, Mansour; Vaez-Mahdavi, Mohammad Reza; Montazeri, Ali; Ghaem, Haleh; Menati, Rostam; Niazi, Mohsen; Kassani, Aziz

2016-01-01

Background: Social capital has been defined as norms, networks, and social links that facilitate collective actions. Social capital is related to a number of main social and public health variables. Therefore, the present study aimed to determine the factors associated with social capital among the residents of Tehran, Iran. Methods: In this large cross-sectional population-based study, 31531 residents aged 20 years and above were selected through multi-stage sampling method from 22 districts of Tehran in 2011. The social capital questionnaire, 28-item General Health Questionnaire (GHQ-28), and Short-Form Health Survey (SF-12) were used. Hypothetical causal models were designed to identify the pathways through which different variables influenced the components of social capital. Then, path analysis was conducted for identifying the determinants of social capital. Results: The most influential variables in 'individual trust' were job status (β=0.37, p=0.02), marital status (β=0.32, p=0.01), Physical Component Summary (PCS) (β=0.37, p=0.02), and age (β=0.34, p=0.03). On the other hand, education level (β=0.34, p=0.01), age (β=0.33, p=0.02), marital status (β=0.33, p=0.01), and job status (β=0.32, p=0.01) were effective in 'cohesion and social support'. Additionally, age (β=0.18, p=0.02), PCS (β=0.36, p=0.01), house ownership (β=0.23, p=0.03), and mental health (β=0.26, p=0.01) were influential in 'social trust/collective relations'. Conclusion: Social capital can be improved in communities by planning to improve education and occupation status, paying more attention to strengthening family bonds, and provision of local facilities and neighborhood bonds to reduce migration within the city.

Model-free arterial spin labelling for cerebral blood flow quantification: introduction of regional arterial input functions identified by factor analysis.

PubMed

Knutsson, Linda; Bloch, Karin Markenroth; Holtås, Stig; Wirestam, Ronnie; Ståhlberg, Freddy

2008-05-01

To identify regional arterial input functions (AIFs) using factor analysis of dynamic studies (FADS) when quantification of perfusion is performed using model-free arterial spin labelling. Five healthy volunteers and one patient were examined on a 3-T Philips unit using quantitative STAR labelling of arterial regions (QUASAR). Two sets of images were retrieved, one where the arterial signal had been crushed and another where it was retained. FADS was applied to the arterial signal curves to acquire the AIFs. Perfusion maps were obtained using block-circulant SVD deconvolution and regional AIFs obtained by FADS. In the volunteers, the ASL experiment was repeated within 24 h. The patient was also examined using dynamic susceptibility contrast MRI. In the healthy volunteers, CBF was 64+/-10 ml/[min 100 g] (mean+/-S.D.) in GM and 24+/-4 ml/[min 100 g] in WM, while the mean aBV was 0.94% in GM and 0.25% in WM. Good CBF image quality and reasonable quantitative CBF values were obtained using the combined QUASAR/FADS technique. We conclude that FADS may be a useful supplement in the evaluation of ASL data using QUASAR.

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

PubMed

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

2018-04-13

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

Anterior cruciate ligament injury: Identifying information sources and risk factor awareness among the general population.

PubMed

Nagano, Yasuharu; Yako-Suketomo, Hiroko; Natsui, Hiroaki

2018-01-01

Raising awareness on a disorder is important for its prevention and for promoting public health. However, for sports injuries like the anterior cruciate ligament (ACL) injury no studies have investigated the awareness on risk factors for injury and possible preventative measures in the general population. The sources of information among the population are also unclear. The purpose of the present study was to identify these aspects of public awareness about the ACL injury. A questionnaire was randomly distributed among the general population registered with a web based questionnaire supplier, to recruit 900 participants who were aware about the ACL injury. The questionnaire consisted of two parts: Question 1 asked them about their sources of information regarding the ACL injury; Question 2 asked them about the risk factors for ACL injury. Multivariate logistic regression was used to determine the information sources that provide a good understanding of the risk factors. The leading source of information for ACL injury was television (57.0%). However, the results of logistic regression analysis revealed that television was not an effective medium to create awareness about the risk factors, among the general population. Instead "Lecture by a coach", "Classroom session on Health", and "Newspaper" were significantly more effective in creating a good awareness of the risk factors (p < 0.001).

Sexual harassment: identifying risk factors.

PubMed

O'Hare, E A; O'Donohue, W

1998-12-01

A new model of the etiology of sexual harassment, the four-factor model, is presented and compared with several models of sexual harassment including the biological model, the organizational model, the sociocultural model, and the sex role spillover model. A number of risk factors associated with sexually harassing behavior are examined within the framework of the four-factor model of sexual harassment. These include characteristics of the work environment (e.g., sexist attitudes among co-workers, unprofessional work environment, skewed sex ratios in the workplace, knowledge of grievance procedures for sexual harassment incidents) as well as personal characteristics of the subject (e.g., physical attractiveness, job status, sex-role). Subjects were 266 university female faculty, staff, and students who completed the Sexual Experience Questionnaire to assess the experience of sexual harassment and a questionnaire designed to assess the risk factors stated above. Results indicated that the four-factor model is a better predictor of sexual harassment than the alternative models. The risk factors most strongly associated with sexual harassment were an unprofessional environment in the workplace, sexist atmosphere, and lack of knowledge about the organization's formal grievance procedures.

Epidermal growth factor gene is a newly identified candidate gene for gout.

PubMed

Han, Lin; Cao, Chunwei; Jia, Zhaotong; Liu, Shiguo; Liu, Zhen; Xin, Ruosai; Wang, Can; Li, Xinde; Ren, Wei; Wang, Xuefeng; Li, Changgui

2016-08-10

Chromosome 4q25 has been identified as a genomic region associated with gout. However, the associations of gout with the genes in this region have not yet been confirmed. Here, we performed two-stage analysis to determine whether variations in candidate genes in the 4q25 region are associated with gout in a male Chinese Han population. We first evaluated 96 tag single nucleotide polymorphisms (SNPs) in eight inflammatory/immune pathway- or glucose/lipid metabolism-related genes in the 4q25 region in 480 male gout patients and 480 controls. The SNP rs12504538, located in the elongation of very-long-chain-fatty-acid-like family member 6 gene (Elovl6), was found to be associated with gout susceptibility (Padjusted = 0.00595). In the second stage of analysis, we performed fine mapping analysis of 93 tag SNPs in Elovl6 and in the epidermal growth factor gene (EGF) and its flanking regions in 1017 male patients gout and 1897 healthy male controls. We observed a significant association between the T allele of EGF rs2298999 and gout (odds ratio = 0.77, 95% confidence interval = 0.67-0.88, Padjusted = 6.42 × 10(-3)). These results provide the first evidence for an association between the EGF rs2298999 C/T polymorphism and gout. Our findings should be validated in additional populations.

Exploratory factor analysis of borderline personality disorder criteria in hospitalized adolescents.

PubMed

Becker, Daniel F; McGlashan, Thomas H; Grilo, Carlos M

2006-01-01

The authors examined the factor structure of borderline personality disorder (BPD) in hospitalized adolescents and also sought to add to the theoretical and clinical understanding of any homogeneous components by determining whether they may be related to specific forms of Axis I pathology. Subjects were 123 adolescent inpatients, who were reliably assessed with structured diagnostic interviews for Diagnostic and Statistical Manual of Mental Disorders, Revised Third Edition Axes I and II disorders. Exploratory factor analysis identified BPD components, and logistic regression analyses tested whether these components were predictive of specific Axis I disorders. Factor analysis revealed a 4-factor solution that accounted for 67.0% of the variance. Factor 1 ("suicidal threats or gestures" and "emptiness or boredom") predicted depressive disorders and alcohol use disorders. Factor 2 ("affective instability," "uncontrolled anger," and "identity disturbance") predicted anxiety disorders and oppositional defiant disorder. Factor 3 ("unstable relationships" and "abandonment fears") predicted only anxiety disorders. Factor 4 ("impulsiveness" and "identity disturbance") predicted conduct disorder and substance use disorders. Exploratory factor analysis of BPD criteria in adolescent inpatients revealed 4 BPD factors that appear to differ from those reported for similar studies of adults. The factors represent components of self-negation, irritability, poorly modulated relationships, and impulsivity--each of which is associated with characteristic Axis I pathology. These findings shed light on the nature of BPD in adolescents and may also have implications for treatment.

RM-DEMATEL: a new methodology to identify the key factors in PM2.5.

PubMed

Chen, Yafeng; Liu, Jie; Li, Yunpeng; Sadiq, Rehan; Deng, Yong

2015-04-01

Weather system is a relative complex dynamic system, the factors of the system are mutually influenced PM2.5 concentration. In this paper, a new method is proposed to quantify the influence on PM2.5 by other factors in the weather system and identify the most important factors for PM2.5 with limited resources. The relation map (RM) is used to figure out the direct relation matrix of 14 factors in PM2.5. The decision making trial and evaluation laboratory(DEMATEL) is applied to calculate the causal relationship and extent to a mutual influence of 14 factors in PM2.5. According to the ranking results of our proposed method, the most important key factors is sulfur dioxide (SO2) and nitrogen oxides (NO(X)). In addition, the other factors, the ambient maximum temperature (T(max)), concentration of PM10, and wind direction (W(dir)), are important factors for PM2.5. The proposed method can also be applied to other environment management systems to identify key factors.

Identifying critical success factors (CSFs) of implementing building information modeling (BIM) in Malaysian construction industry

NASA Astrophysics Data System (ADS)

Yaakob, Mazri; Ali, Wan Nur Athirah Wan; Radzuan, Kamaruddin

2016-08-01

Building Information Modeling (BIM) is defined as existing from the earliest concept to demolition and it involves creating and using an intelligent 3D model to inform and communicate project decisions. This research aims to identify the critical success factors (CSFs) of BIM implementation in Malaysian construction industry. A literature review was done to explore previous BIM studies on definitions and history of BIM, construction issues, application of BIM in construction projects as well as benefits of BIM. A series of interviews with multidisciplinary Malaysian construction experts will be conducted purposely for data collection process guided by the research design and methodology approach of this study. The analysis of qualitative data from the process will be combined with criteria identified in the literature review in order to identify the CSFs. Finally, the CSFs of BIM implementation will be validated by further Malaysian industrialists during a workshop. The validated CSFs can be used as a term of reference for both Malaysian practitioners and academics towards measuring BIM effectiveness level in their organizations.

Hazardous drinking and military community functioning: identifying mediating risk factors.

PubMed

Foran, Heather M; Heyman, Richard E; Slep, Amy M Smith

2011-08-01

Hazardous drinking is a serious societal concern in military populations. Efforts to reduce hazardous drinking among military personnel have been limited in effectiveness. There is a need for a deeper understanding of how community-based prevention models apply to hazardous drinking in the military. Community-wide prevention efforts may be most effective in targeting community functioning (e.g., support from formal agencies, community cohesion) that impacts hazardous drinking via other proximal risk factors. The goal of the current study is to inform community-wide prevention efforts by testing a model of community functioning and mediating risk factors of hazardous drinking among active duty U.S. Air Force personnel. A large, representative survey sample of U.S. Air Force active duty members (N = 52,780) was collected at 82 bases worldwide. Hazardous drinking was assessed with the widely used Alcohol Use Disorders Identification Test (Saunders, Aasland, Babor, de la Fuente, & Grant, 1993). A variety of individual, family, and community measures were also assessed. Structural equation modeling was used to test a hypothesized model of community functioning, mediating risk factors and hazardous drinking. Depressive symptoms, perceived financial stress, and satisfaction with the U.S. Air Force were identified as significant mediators of the link between community functioning and hazardous drinking for men and women. Relationship satisfaction was also identified as a mediator for men. These results provide a framework for further community prevention research and suggest that prevention efforts geared at increasing aspects of community functioning (e.g., the U.S. Air Force Community Capacity model) may indirectly lead to reductions in hazardous drinking through other proximal risk factors.

Factors affecting construction performance: exploratory factor analysis

NASA Astrophysics Data System (ADS)

Soewin, E.; Chinda, T.

2018-04-01

The present work attempts to develop a multidimensional performance evaluation framework for a construction company by considering all relevant measures of performance. Based on the previous studies, this study hypothesizes nine key factors, with a total of 57 associated items. The hypothesized factors, with their associated items, are then used to develop questionnaire survey to gather data. The exploratory factor analysis (EFA) was applied to the collected data which gave rise 10 factors with 57 items affecting construction performance. The findings further reveal that the items constituting ten key performance factors (KPIs) namely; 1) Time, 2) Cost, 3) Quality, 4) Safety & Health, 5) Internal Stakeholder, 6) External Stakeholder, 7) Client Satisfaction, 8) Financial Performance, 9) Environment, and 10) Information, Technology & Innovation. The analysis helps to develop multi-dimensional performance evaluation framework for an effective measurement of the construction performance. The 10 key performance factors can be broadly categorized into economic aspect, social aspect, environmental aspect, and technology aspects. It is important to understand a multi-dimension performance evaluation framework by including all key factors affecting the construction performance of a company, so that the management level can effectively plan to implement an effective performance development plan to match with the mission and vision of the company.

Human factors evaluation of remote afterloading brachytherapy. Volume 2, Function and task analysis

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

Callan, J.R.; Gwynne, J.W. III; Kelly, T.T.

1995-05-01

A human factors project on the use of nuclear by-product material to treat cancer using remotely operated afterloaders was undertaken by the Nuclear Regulatory Commission. The purpose of the project was to identify factors that contribute to human error in the system for remote afterloading brachytherapy (RAB). This report documents the findings from the first phase of the project, which involved an extensive function and task analysis of RAB. This analysis identified the functions and tasks in RAB, made preliminary estimates of the likelihood of human error in each task, and determined the skills needed to perform each RAB task.more » The findings of the function and task analysis served as the foundation for the remainder of the project, which evaluated four major aspects of the RAB system linked to human error: human-system interfaces; procedures and practices; training and qualifications of RAB staff; and organizational practices and policies. At its completion, the project identified and prioritized areas for recommended NRC and industry attention based on all of the evaluations and analyses.« less

Extension Procedures for Confirmatory Factor Analysis

ERIC Educational Resources Information Center

Nagy, Gabriel; Brunner, Martin; Lüdtke, Oliver; Greiff, Samuel

2017-01-01

We present factor extension procedures for confirmatory factor analysis that provide estimates of the relations of common and unique factors with external variables that do not undergo factor analysis. We present identification strategies that build upon restrictions of the pattern of correlations between unique factors and external variables. The…

Biological risk factors for suicidal behaviors: a meta-analysis

PubMed Central

Chang, B P; Franklin, J C; Ribeiro, J D; Fox, K R; Bentley, K H; Kleiman, E M; Nock, M K

2016-01-01

Prior studies have proposed a wide range of potential biological risk factors for future suicidal behaviors. Although strong evidence exists for biological correlates of suicidal behaviors, it remains unclear if these correlates are also risk factors for suicidal behaviors. We performed a meta-analysis to integrate the existing literature on biological risk factors for suicidal behaviors and to determine their statistical significance. We conducted a systematic search of PubMed, PsycInfo and Google Scholar for studies that used a biological factor to predict either suicide attempt or death by suicide. Inclusion criteria included studies with at least one longitudinal analysis using a biological factor to predict either of these outcomes in any population through 2015. From an initial screen of 2541 studies we identified 94 cases. Random effects models were used for both meta-analyses and meta-regression. The combined effect of biological factors produced statistically significant but relatively weak prediction of suicide attempts (weighted mean odds ratio (wOR)=1.41; CI: 1.09–1.81) and suicide death (wOR=1.28; CI: 1.13–1.45). After accounting for publication bias, prediction was nonsignificant for both suicide attempts and suicide death. Only two factors remained significant after accounting for publication bias—cytokines (wOR=2.87; CI: 1.40–5.93) and low levels of fish oil nutrients (wOR=1.09; CI: 1.01–1.19). Our meta-analysis revealed that currently known biological factors are weak predictors of future suicidal behaviors. This conclusion should be interpreted within the context of the limitations of the existing literature, including long follow-up intervals and a lack of tests of interactions with other risk factors. Future studies addressing these limitations may more effectively test for potential biological risk factors. PMID:27622931

Identifying important motivational factors for professionals in Greek hospitals

PubMed Central

Kontodimopoulos, Nick; Paleologou, Victoria; Niakas, Dimitris

2009-01-01

Background The purpose of this study was to identify important motivational factors according to the views of health-care professionals in Greek hospitals and particularly to determine if these might differ in the public and private sectors. Methods A previously developed -and validated- instrument addressing four work-related motivators (job attributes, remuneration, co-workers and achievements) was used. Three categories of health care professionals, doctors (N = 354), nurses (N = 581) and office workers (N = 418), working in public and private hospitals, participated and motivation was compared across socio-demographic and occupational variables. Results The range of reported motivational factors was mixed and Maslow's conclusions that lower level motivational factors must be met before ascending to the next level were not confirmed. The highest ranked motivator for the entire sample, and by professional subgroup, was achievements (P < 0.001). Within subgroups, motivators were similar, and only one significant difference was observed, namely between doctors and nurses in respect to co-workers (P < 0.05). Remuneration (and salary in particular) was reported as a significant incentive only for professionals in managerial positions. Health professionals in private hospitals were motivated by all factors significantly more than their public-hospital counterparts. Conclusion The results are in agreement with the literature which focuses attention to management approaches employing both monetary and non-monetary incentives to motivate health care workers. This study showed that intrinsic factors are particularly important and should become a target for effective employee motivation. PMID:19754968

Proximity-Based Differential Single-Cell Analysis of the Niche to Identify Stem/Progenitor Cell Regulators.

PubMed

Silberstein, Lev; Goncalves, Kevin A; Kharchenko, Peter V; Turcotte, Raphael; Kfoury, Youmna; Mercier, Francois; Baryawno, Ninib; Severe, Nicolas; Bachand, Jacqueline; Spencer, Joel A; Papazian, Ani; Lee, Dongjun; Chitteti, Brahmananda Reddy; Srour, Edward F; Hoggatt, Jonathan; Tate, Tiffany; Lo Celso, Cristina; Ono, Noriaki; Nutt, Stephen; Heino, Jyrki; Sipilä, Kalle; Shioda, Toshihiro; Osawa, Masatake; Lin, Charles P; Hu, Guo-Fu; Scadden, David T

2016-10-06

Physiological stem cell function is regulated by secreted factors produced by niche cells. In this study, we describe an unbiased approach based on the differential single-cell gene expression analysis of mesenchymal osteolineage cells close to, and further removed from, hematopoietic stem/progenitor cells (HSPCs) to identify candidate niche factors. Mesenchymal cells displayed distinct molecular profiles based on their relative location. We functionally examined, among the genes that were preferentially expressed in proximal cells, three secreted or cell-surface molecules not previously connected to HSPC biology-the secreted RNase angiogenin, the cytokine IL18, and the adhesion molecule Embigin-and discovered that all of these factors are HSPC quiescence regulators. Therefore, our proximity-based differential single-cell approach reveals molecular heterogeneity within niche cells and can be used to identify novel extrinsic stem/progenitor cell regulators. Similar approaches could also be applied to other stem cell/niche pairs to advance the understanding of microenvironmental regulation of stem cell function. Copyright © 2016 Elsevier Inc. All rights reserved.

The combined use of dynamic factor analysis and wavelet analysis to evaluate latent factors controlling complex groundwater level fluctuations in a riverside alluvial aquifer

NASA Astrophysics Data System (ADS)

Oh, Yun-Yeong; Yun, Seong-Taek; Yu, Soonyoung; Hamm, Se-Yeong

2017-12-01

To identify and quantitatively evaluate complex latent factors controlling groundwater level (GWL) fluctuations in a riverside alluvial aquifer influenced by barrage construction, we developed the combined use of dynamic factor analysis (DFA) and wavelet analysis (WA). Time series data of GWL, river water level and precipitation were collected for 3 years (July 2012 to June 2015) from an alluvial aquifer underneath an agricultural area of the Nakdong river basin, South Korea. Based on the wavelet coefficients of the final approximation, the GWL data was clustered into three groups (WCG1 to WCG3). Two dynamic factors (DFs) were then extracted using DFA for each group; thus, six major factors were extracted. Next, the time-frequency variability of the extracted DFs was examined using multiresolution cross-correlation analysis (MRCCA) with the following steps: 1) major driving forces and their scales in GWL fluctuations were identified by comparing maximum correlation coefficients (rmax) between DFs and the GWL time series and 2) the results were supplemented using the wavelet transformed coherence (WTC) analysis between DFs and the hydrological time series. Finally, relative contributions of six major DFs to the GWL fluctuations could be quantitatively assessed by calculating the effective dynamic efficiency (Def). The characteristics and relevant process of the identified six DFs are: 1) WCG1DF4,1 as an indicative of seasonal agricultural pumping (scales = 64-128 days; rmax = 0.68-0.89; Def ≤ 23.1%); 2) WCG1DF4,4 representing the cycle of regional groundwater recharge (scales = 64-128 days; rmax = 0.98-1.00; Def ≤ 11.1%); 3) WCG2DF4,1 indicating the complex interaction between the episodes of precipitation and direct runoff (scales = 2-8 days; rmax = 0.82-0.91; Def ≤ 35.3%) and seasonal GW-RW interaction (scales = 64-128 days; rmax = 0.76-0.91; Def ≤ 14.2%); 4) WCG2DF4,4 reflecting the complex effects of seasonal pervasive pumping and the local recharge

Cellular signaling identifiability analysis: a case study.

PubMed

Roper, Ryan T; Pia Saccomani, Maria; Vicini, Paolo

2010-05-21

Two primary purposes for mathematical modeling in cell biology are (1) simulation for making predictions of experimental outcomes and (2) parameter estimation for drawing inferences from experimental data about unobserved aspects of biological systems. While the former purpose has become common in the biological sciences, the latter is less common, particularly when studying cellular and subcellular phenomena such as signaling-the focus of the current study. Data are difficult to obtain at this level. Therefore, even models of only modest complexity can contain parameters for which the available data are insufficient for estimation. In the present study, we use a set of published cellular signaling models to address issues related to global parameter identifiability. That is, we address the following question: assuming known time courses for some model variables, which parameters is it theoretically impossible to estimate, even with continuous, noise-free data? Following an introduction to this problem and its relevance, we perform a full identifiability analysis on a set of cellular signaling models using DAISY (Differential Algebra for the Identifiability of SYstems). We use our analysis to bring to light important issues related to parameter identifiability in ordinary differential equation (ODE) models. We contend that this is, as of yet, an under-appreciated issue in biological modeling and, more particularly, cell biology. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

A computational intelligent approach to multi-factor analysis of violent crime information system

NASA Astrophysics Data System (ADS)

Liu, Hongbo; Yang, Chao; Zhang, Meng; McLoone, Seán; Sun, Yeqing

2017-02-01

Various scientific studies have explored the causes of violent behaviour from different perspectives, with psychological tests, in particular, applied to the analysis of crime factors. The relationship between bi-factors has also been extensively studied including the link between age and crime. In reality, many factors interact to contribute to criminal behaviour and as such there is a need to have a greater level of insight into its complex nature. In this article we analyse violent crime information systems containing data on psychological, environmental and genetic factors. Our approach combines elements of rough set theory with fuzzy logic and particle swarm optimisation to yield an algorithm and methodology that can effectively extract multi-knowledge from information systems. The experimental results show that our approach outperforms alternative genetic algorithm and dynamic reduct-based techniques for reduct identification and has the added advantage of identifying multiple reducts and hence multi-knowledge (rules). Identified rules are consistent with classical statistical analysis of violent crime data and also reveal new insights into the interaction between several factors. As such, the results are helpful in improving our understanding of the factors contributing to violent crime and in highlighting the existence of hidden and intangible relationships between crime factors.

A comparative study to identify factors of caregiver burden between baby boomers and post baby boomers: a secondary analysis of a US online caregiver survey.

PubMed

Kim, Heejung; Lee, Sangeun; Cheon, Jooyoung; Hong, Soyun; Chang, Mido

2018-05-02

Baby boomers' position in the caregiving context is shifting from caregiver to care recipient as the population ages. While the unique characteristics of baby boomer caregivers are well established in caregiving literature, there is limited information about the next caregiving group after the baby boomers. In this study, the sociodemographic and caregiving-related characteristics of the two generations are compared and specific factors contributing to caregiver burden between baby boomer and post baby boomer caregivers are identified. This cross-sectional and correlational study used secondary analysis of data from the National Alliance for Caregiving and the American Association of Retired Persons. A structured online survey was conducted in 2014 with randomly selected samples (n = 1069) in the United States focusing on sociodemographics, caregiving-related characteristics, and burden of care. Descriptive statistics, multivariate linear regression analyses, and Steiger's Z-test were used to identify group differences in multivariate factors related to caregiver burden in two generational groups. Baby boomers and post baby boomers experienced caregiver burden to a similar degree. Caregiving-related factors are more likely to increase burden of care than sociodemographics in both groups. Caregiving without choice and spending longer hours on caregiving tasks were common factors that increased the burden in both generational groups (all p values < 0.01). However, post baby boomer caregivers reported additional challenges, such as unemployment during caregiving, the dual responsibility of both adult and child care, and a family relationship with the care recipient. Due to the aging population of baby boomers, post baby boomers encounter different challenges related to caregiving burden, which is often considered an additional workload in their life course. Current policy and program tailored to baby boomers should be re-designed to meet the different needs of

Assessment of the dimensionality of the Wijma delivery expectancy/experience questionnaire using factor analysis and Rasch analysis.

PubMed

Pallant, J F; Haines, H M; Green, P; Toohill, J; Gamble, J; Creedy, D K; Fenwick, J

2016-11-21

Fear of childbirth has negative consequences for a woman's physical and emotional wellbeing. The most commonly used measurement tool for childbirth fear is the Wijma Delivery Expectancy Questionnaire (WDEQ-A). Although originally conceptualized as unidimensional, subsequent investigations have suggested it is multidimensional. This study aimed to undertake a detailed psychometric assessment of the WDEQ-A; exploring the dimensionality and identifying possible subscales that may have clinical and research utility. WDEQ-A was administered to a sample of 1410 Australian women in mid-pregnancy. The dimensionality of WDEQ-A was explored using exploratory (EFA) and confirmatory factor analysis (CFA), and Rasch analysis. EFA identified a four factor solution. CFA failed to support the unidimensional structure of the original WDEQ-A, but confirmed the four factor solution identified by EFA. Rasch analysis was used to refine the four subscales (Negative emotions: five items; Lack of positive emotions: five items; Social isolation: four items; Moment of birth: three items). Each WDEQ-A Revised subscale showed good fit to the Rasch model and adequate internal consistency reliability. The correlation between Negative emotions and Lack of positive emotions was strong, however Moment of birth and Social isolation showed much lower intercorrelations, suggesting they should not be added to create a total score. This study supports the findings of other investigations that suggest the WDEQ-A is multidimensional and should not be used in its original form. The WDEQ-A Revised may provide researchers with a more refined, psychometrically sound tool to explore the differential impact of aspects of childbirth fear.

Community Violence, Protective Factors, and Adolescent Mental Health: A Profile Analysis

ERIC Educational Resources Information Center

Copeland-Linder, Nikeea; Lambert, Sharon F.; Ialongo, Nicholas S.

2010-01-01

This study examined interrelationships among community violence exposure, protective factors, and mental health in a sample of urban, predominantly African American adolescents (N = 504). Latent Profile Analysis was conducted to identify profiles of adolescents based on a combination of community violence exposure, self-worth, parental monitoring,…

Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency.

PubMed

Yeh, Hsiang-Yuan; Cheng, Shih-Wu; Lin, Yu-Chun; Yeh, Cheng-Yu; Lin, Shih-Fang; Soo, Von-Wun

2009-12-21

Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN) algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD) as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2) regulated by RUNX1 and STAT3 is correlated to the pathological stage. We provide a computational framework to reconstruct

Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency

PubMed Central

2009-01-01

Background Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. Results To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN) algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD) as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2) regulated by RUNX1 and STAT3 is correlated to the pathological stage. Conclusions We provide a

The Interest Checklist: a factor analysis.

PubMed

Klyczek, J P; Bauer-Yox, N; Fiedler, R C

1997-01-01

The purpose of this study was to determine whether the 80 items on the Interest Checklist empirically cluster into the five categories of interests described by Matsutsuyu, the developer of the tool. The Interest Checklist was administered to 367 subjects classified in three subgroups: students, working adults, and retired elderly persons. An 80-item correlation matrix was formed from the responses to the Interest Checklist for each subgroup and then used in a factor analysis model to identify the underlying structure or domains of interest. Results indicated that the Social Recreation theoretical category was empirically independent for all three subgroups; the Physical Sports and Cultural/Educational theoretical categories were empirically independent for only the college students and working adults; and the Manual Skills theoretical category was empirically independent for only the working adults. Although therapists should continue to be cautious in their interpretation of patients' Interest Checklist scores, the tool is useful for identifying patients' interests in order to choose meaningful activities for therapy.

[Introduction to Exploratory Factor Analysis (EFA)].

PubMed

Martínez, Carolina Méndez; Sepúlveda, Martín Alonso Rondón

2012-03-01

Exploratory Factor Analysis (EFA) has become one of the most frequently used statistical techniques, especially in the medical and social sciences. Given its popularity, it is essential to understand the basic concepts necessary for its proper application and to take into consideration the main strengths and weaknesses of this technique. To present in a clear and concise manner the main applications of this technique, to determine the basic requirements for its use providing a description step by step of its methodology, and to establish the elements that must be taken into account during its preparation in order to not incur in erroneous results and interpretations. Narrative review. This review identifies the basic concepts and briefly describes the objectives, design, assumptions, and methodology to achieve factor derivation, global adjustment evaluation, and adequate interpretation of results. Copyright © 2012 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.

Phenotypic factor analysis of psychopathology reveals a new body-related transdiagnostic factor.

PubMed

Pezzoli, Patrizia; Antfolk, Jan; Santtila, Pekka

2017-01-01

Comorbidity challenges the notion of mental disorders as discrete categories. An increasing body of literature shows that symptoms cut across traditional diagnostic boundaries and interact in shaping the latent structure of psychopathology. Using exploratory and confirmatory factor analysis, we reveal the latent sources of covariation among nine measures of psychopathological functioning in a population-based sample of 13024 Finnish twins and their siblings. By implementing unidimensional, multidimensional, second-order, and bifactor models, we illustrate the relationships between observed variables, specific, and general latent factors. We also provide the first investigation to date of measurement invariance of the bifactor model of psychopathology across gender and age groups. Our main result is the identification of a distinct "Body" factor, alongside the previously identified Internalizing and Externalizing factors. We also report relevant cross-disorder associations, especially between body-related psychopathology and trait anger, as well as substantial sex and age differences in observed and latent means. The findings expand the meta-structure of psychopathology, with implications for empirical and clinical practice, and demonstrate shared mechanisms underlying attitudes towards nutrition, self-image, sexuality and anger, with gender- and age-specific features.

Space Human Factors Engineering Gap Analysis Project Final Report

NASA Technical Reports Server (NTRS)

Hudy, Cynthia; Woolford, Barbara

2006-01-01

Humans perform critical functions throughout each phase of every space mission, beginning with the mission concept and continuing to post-mission analysis (Life Sciences Division, 1996). Space missions present humans with many challenges - the microgravity environment, relative isolation, and inherent dangers of the mission all present unique issues. As mission duration and distance from Earth increases, in-flight crew autonomy will increase along with increased complexity. As efforts for exploring the moon and Mars advance, there is a need for space human factors research and technology development to play a significant role in both on-orbit human-system interaction, as well as the development of mission requirements and needs before and after the mission. As part of the Space Human Factors Engineering (SHFE) Project within the Human Research Program (HRP), a six-month Gap Analysis Project (GAP) was funded to identify any human factors research gaps or knowledge needs. The overall aim of the project was to review the current state of human factors topic areas and requirements to determine what data, processes, or tools are needed to aid in the planning and development of future exploration missions, and also to prioritize proposals for future research and technology development.

Identifying mediating factors of moral reasoning in science education

NASA Astrophysics Data System (ADS)

Zeidler, Dana L.; Schafer, Larry E.

The purpose of this research was to examine how science content knowledge, moral reasoning ability, attitudes, and past experiences mediate the formation of moral judgments on environmental dilemmas. The study was conducted in two phases using environmental science majors and nonscience majors of college age. Phase One determined if environmental science majors exhibited higher levels of moral reasoning on nontechnical environmental social issues than on general social issues and examined the extent to which possible mediating factors accounted for differences in moral reasoning. Phase Two was qualitative in nature, the purpose of which was to observe and identify trends in conversations between subjects as to how certain mediating factors are revealed as people form moral judgments. The framework on which this study was constructed incorporates a progressive educational position; a position that views science education as being interdisciplinary, and a social means to a social end.

Epidermal growth factor gene is a newly identified candidate gene for gout

PubMed Central

Han, Lin; Cao, Chunwei; Jia, Zhaotong; Liu, Shiguo; Liu, Zhen; Xin, Ruosai; Wang, Can; Li, Xinde; Ren, Wei; Wang, Xuefeng; Li, Changgui

2016-01-01

Chromosome 4q25 has been identified as a genomic region associated with gout. However, the associations of gout with the genes in this region have not yet been confirmed. Here, we performed two-stage analysis to determine whether variations in candidate genes in the 4q25 region are associated with gout in a male Chinese Han population. We first evaluated 96 tag single nucleotide polymorphisms (SNPs) in eight inflammatory/immune pathway- or glucose/lipid metabolism-related genes in the 4q25 region in 480 male gout patients and 480 controls. The SNP rs12504538, located in the elongation of very-long-chain-fatty-acid-like family member 6 gene (Elovl6), was found to be associated with gout susceptibility (Padjusted = 0.00595). In the second stage of analysis, we performed fine mapping analysis of 93 tag SNPs in Elovl6 and in the epidermal growth factor gene (EGF) and its flanking regions in 1017 male patients gout and 1897 healthy male controls. We observed a significant association between the T allele of EGF rs2298999 and gout (odds ratio = 0.77, 95% confidence interval = 0.67–0.88, Padjusted = 6.42 × 10−3). These results provide the first evidence for an association between the EGF rs2298999 C/T polymorphism and gout. Our findings should be validated in additional populations. PMID:27506295

Meta-analysis identifies six new susceptibility loci for atrial fibrillation

PubMed Central

Ellinor, Patrick T; Lunetta, Kathryn L; Albert, Christine M; Glazer, Nicole L; Ritchie, Marylyn D; Smith, Albert V; Arking, Dan E; Müller-Nurasyid, Martina; Krijthe, Bouwe P; Lubitz, Steven A; Bis, Joshua C; Chung, Mina K; Dörr, Marcus; Ozaki, Kouichi; Roberts, Jason D; Smith, J Gustav; Pfeufer, Arne; Sinner, Moritz F; Lohman, Kurt; Ding, Jingzhong; Smith, Nicholas L; Smith, Jonathan D; Rienstra, Michiel; Rice, Kenneth M; Van Wagoner, David R; Magnani, Jared W; Wakili, Reza; Clauss, Sebastian; Rotter, Jerome I; Steinbeck, Gerhard; Launer, Lenore J; Davies, Robert W; Borkovich, Matthew; Harris, Tamara B; Lin, Honghuang; Völker, Uwe; Völzke, Henry; Milan, David J; Hofman, Albert; Boerwinkle, Eric; Chen, Lin Y; Soliman, Elsayed Z; Voight, Benjamin F; Li, Guo; Chakravarti, Aravinda; Kubo, Michiaki; Tedrow, Usha B; Rose, Lynda M; Ridker, Paul M; Conen, David; Tsunoda, Tatsuhiko; Furukawa, Tetsushi; Sotoodehnia, Nona; Xu, Siyan; Kamatani, Naoyuki; Levy, Daniel; Nakamura, Yusuke; Parvez, Babar; Mahida, Saagar; Furie, Karen L; Rosand, Jonathan; Muhammad, Raafia; Psaty, Bruce M; Meitinger, Thomas; Perz, Siegfried; Wichmann, H-Erich; Witteman, Jacqueline C M; Kao, W H Linda; Kathiresan, Sekar; Roden, Dan M; Uitterlinden, Andre G; Rivadeneira, Fernando; McKnight, Barbara; Sjögren, Marketa; Newman, Anne B; Liu, Yongmei; Gollob, Michael H; Melander, Olle; Tanaka, Toshihiro; Ch Stricker, Bruno H; Felix, Stephan B; Alonso, Alvaro; Darbar, Dawood; Barnard, John; Chasman, Daniel I; Heckbert, Susan R; Benjamin, Emelia J; Gudnason, Vilmundur; Kääb, Stefan

2012-01-01

Atrial fibrillation is a highly prevalent arrhythmia and a major risk factor for stroke, heart failure and death1. We conducted a genome-wide association study (GWAS) in individuals of European ancestry, including 6,707 with and 52,426 without atrial fibrillation. Six new atrial fibrillation susceptibility loci were identified and replicated in an additional sample of individuals of European ancestry, including 5,381 subjects with and 1 0,030 subjects without atrial fibrillation (P < 5 × 10−8). Four of the loci identified in Europeans were further replicated in silico in a GWAS of Japanese individuals, including 843 individuals with and 3,350 individuals without atrial fibrillation. The identified loci implicate candidate genes that encode transcription factors related to cardiopulmonary development, cardiac-expressed ion channels and cell signaling molecules. PMID:22544366

Logistic Regression and Path Analysis Method to Analyze Factors influencing Students’ Achievement

NASA Astrophysics Data System (ADS)

Noeryanti, N.; Suryowati, K.; Setyawan, Y.; Aulia, R. R.

2018-04-01

Students' academic achievement cannot be separated from the influence of two factors namely internal and external factors. The first factors of the student (internal factors) consist of intelligence (X1), health (X2), interest (X3), and motivation of students (X4). The external factors consist of family environment (X5), school environment (X6), and society environment (X7). The objects of this research are eighth grade students of the school year 2016/2017 at SMPN 1 Jiwan Madiun sampled by using simple random sampling. Primary data are obtained by distributing questionnaires. The method used in this study is binary logistic regression analysis that aims to identify internal and external factors that affect student’s achievement and how the trends of them. Path Analysis was used to determine the factors that influence directly, indirectly or totally on student’s achievement. Based on the results of binary logistic regression, variables that affect student’s achievement are interest and motivation. And based on the results obtained by path analysis, factors that have a direct impact on student’s achievement are students’ interest (59%) and students’ motivation (27%). While the factors that have indirect influences on students’ achievement, are family environment (97%) and school environment (37).

Identifying psychosocial predictors of medication non-adherence following acute coronary syndrome: A systematic review and meta-analysis.

PubMed

Crawshaw, Jacob; Auyeung, Vivian; Norton, Sam; Weinman, John

2016-11-01

Medication non-adherence following acute coronary syndrome (ACS) is associated with poor clinical outcomes. A systematic review and meta-analysis were undertaken to identify psychosocial factors associated with medication adherence in patients with ACS. A search of electronic databases (Cochrane Library, Medline, EMBASE, PsycINFO, Web of Science, International Pharmaceutical Abstracts, CINAHL, ASSIA, OpenGrey, EthOS and WorldCat) was undertaken to identify relevant articles published in English between 2000 and 2014. Articles were screened against our inclusion criteria and data on study design, sample characteristics, predictors, outcomes, analyses, key findings and study limitations were abstracted. Our search identified 3609 records, of which 17 articles met our inclusion criteria (15 independent studies). Eight out of ten studies found an association between depression and non-adherence. A meta-analysis revealed that depressed patients were twice as likely to be non-adherent compared to patients without depression (OR=2.00, 95% CI 1.57-3.33, p=0.015). Type D personality was found to predict non-adherence in both studies in which it was measured. Three out of three studies reported that treatment beliefs based on the Necessity-Concerns Framework predicted medication non-adherence and there was some evidence that social support was associated with better adherence. There was insufficient data to meta-analyse all other psychosocial factors identified. There was some evidence that psychosocial factors, particularly depression, were associated with medication adherence following ACS. Targeting depressive symptoms, screening for Type D personality, challenging maladaptive treatment beliefs, and providing better social support for patients may be useful strategies to improve medication adherence. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

The risk factors for avian influenza on poultry farms: a meta-analysis.

PubMed

Wang, Youming; Li, Peng; Wu, Yangli; Sun, Xiangdong; Yu, Kangzhen; Yu, Chuanhua; Qin, Aijian

2014-11-01

Avian influenza is a severe threat both to humans and poultry, but so far, no systematic review on the identification and evaluation of the risk factors of avian influenza infection has been published. The objective of this meta-analysis is to provide evidence for decision-making and further research on AI prevention through identifying the risk factors associated with AI infection on poultry farms. The results from 15 selected studies on risk factors for AI infections on poultry farms were analyzed quantitatively by meta-analysis. Open water source (OR=2.89), infections on nearby farms (OR=4.54), other livestock (OR=1.90) and disinfection of farm (OR=0.54) have significant association with AI infection on poultry farms. The subgroup analysis results indicate that there exist different risk factors for AI infections in different types of farms. The main risk factors for AI infection in poultry farms are environmental conditions (open water source, infections on nearby farms), keeping other livestock on the same farm and no disinfection of the farm. Copyright © 2014 Elsevier B.V. All rights reserved.

Factor analysis of the Hamilton Depression Rating Scale in Parkinson's disease.

PubMed

Broen, M P G; Moonen, A J H; Kuijf, M L; Dujardin, K; Marsh, L; Richard, I H; Starkstein, S E; Martinez-Martin, P; Leentjens, A F G

2015-02-01

Several studies have validated the Hamilton Depression Rating Scale (HAMD) in patients with Parkinson's disease (PD), and reported adequate reliability and construct validity. However, the factorial validity of the HAMD has not yet been investigated. The aim of our analysis was to explore the factor structure of the HAMD in a large sample of PD patients. A principal component analysis of the 17-item HAMD was performed on data of 341 PD patients, available from a previous cross sectional study on anxiety. An eigenvalue ≥1 was used to determine the number of factors. Factor loadings ≥0.4 in combination with oblique rotations were used to identify which variables made up the factors. Kaiser-Meyer-Olkin measure (KMO), Cronbach's alpha, Bartlett's test, communality, percentage of non-redundant residuals and the component correlation matrix were computed to assess factor validity. KMO verified the sample's adequacy for factor analysis and Cronbach's alpha indicated a good internal consistency of the total scale. Six factors had eigenvalues ≥1 and together explained 59.19% of the variance. The number of items per factor varied from 1 to 6. Inter-item correlations within each component were low. There was a high percentage of non-redundant residuals and low communality. This analysis demonstrates that the factorial validity of the HAMD in PD is unsatisfactory. This implies that the scale is not appropriate for studying specific symptom domains of depression based on factorial structure in a PD population. Copyright © 2014 Elsevier Ltd. All rights reserved.

Factor analysis and predictive validity of microcomputer-based tests

NASA Technical Reports Server (NTRS)

Kennedy, R. S.; Baltzley, D. R.; Turnage, J. J.; Jones, M. B.

1989-01-01

11 tests were selected from two microcomputer-based performance test batteries because previously these tests exhibited rapid stability (less than 10 min, of practice) and high retest reliability efficiencies (r greater than 0.707 for each 3 min. of testing). The battery was administered three times to each of 108 college students (48 men and 60 women) and a factor analysis was performed. Two of the three identified factors appear to be related to information processing ("encoding" and "throughput/decoding"), and the third named an "output/speed" factor. The spatial, memory, and verbal tests loaded on the "encoding" factor and included Grammatical Reasoning, Pattern Comparison, Continuous Recall, and Matrix Rotation. The "throughput/decoding" tests included perceptual/numerical tests like Math Processing, Code Substitution, and Pattern Comparison. The output speed factor was identified by Tapping and Reaction Time tests. The Wonderlic Personnel Test was group administered before the first and after the last administration of the performance tests. The multiple Rs in the total sample between combined Wonderlic as a criterion and less than 5 min. of microcomputer testing on Grammatical Reasoning and Math Processing as predictors ranged between 0.41 and 0.52 on the three test administrations. Based on these results, the authors recommend a core battery which, if time permits, would consist of two tests from each factor. Such a battery is now known to permit stable, reliable, and efficient assessment.

Exploring factors that influence work analysis data: A meta-analysis of design choices, purposes, and organizational context.

PubMed

DuVernet, Amy M; Dierdorff, Erich C; Wilson, Mark A

2015-09-01

Work analysis is fundamental to designing effective human resource systems. The current investigation extends previous research by identifying the differential effects of common design decisions, purposes, and organizational contexts on the data generated by work analyses. The effects of 19 distinct factors that span choices of descriptor, collection method, rating scale, and data source, as well as project purpose and organizational features, are explored. Meta-analytic results cumulated from 205 articles indicate that many of these variables hold significant consequences for work analysis data. Factors pertaining to descriptor choice, collection method, rating scale, and the purpose for conducting the work analysis each showed strong associations with work analysis data. The source of the work analysis information and organizational context in which it was conducted displayed fewer relationships. Findings can be used to inform choices work analysts make about methodology and postcollection evaluations of work analysis information. (c) 2015 APA, all rights reserved).

Exploratory Bi-factor Analysis: The Oblique Case.

PubMed

Jennrich, Robert I; Bentler, Peter M

2012-07-01

Bi-factor analysis is a form of confirmatory factor analysis originally introduced by Holzinger and Swineford (Psychometrika 47:41-54, 1937). The bi-factor model has a general factor, a number of group factors, and an explicit bi-factor structure. Jennrich and Bentler (Psychometrika 76:537-549, 2011) introduced an exploratory form of bi-factor analysis that does not require one to provide an explicit bi-factor structure a priori. They use exploratory factor analysis and a bifactor rotation criterion designed to produce a rotated loading matrix that has an approximate bi-factor structure. Among other things this can be used as an aid in finding an explicit bi-factor structure for use in a confirmatory bi-factor analysis. They considered only orthogonal rotation. The purpose of this paper is to consider oblique rotation and to compare it to orthogonal rotation. Because there are many more oblique rotations of an initial loading matrix than orthogonal rotations, one expects the oblique results to approximate a bi-factor structure better than orthogonal rotations and this is indeed the case. A surprising result arises when oblique bi-factor rotation methods are applied to ideal data.

Systematic analysis of mutation distribution in three dimensional protein structures identifies cancer driver genes.

PubMed

Fujimoto, Akihiro; Okada, Yukinori; Boroevich, Keith A; Tsunoda, Tatsuhiko; Taniguchi, Hiroaki; Nakagawa, Hidewaki

2016-05-26

Protein tertiary structure determines molecular function, interaction, and stability of the protein, therefore distribution of mutation in the tertiary structure can facilitate the identification of new driver genes in cancer. To analyze mutation distribution in protein tertiary structures, we applied a novel three dimensional permutation test to the mutation positions. We analyzed somatic mutation datasets of 21 types of cancers obtained from exome sequencing conducted by the TCGA project. Of the 3,622 genes that had ≥3 mutations in the regions with tertiary structure data, 106 genes showed significant skew in mutation distribution. Known tumor suppressors and oncogenes were significantly enriched in these identified cancer gene sets. Physical distances between mutations in known oncogenes were significantly smaller than those of tumor suppressors. Twenty-three genes were detected in multiple cancers. Candidate genes with significant skew of the 3D mutation distribution included kinases (MAPK1, EPHA5, ERBB3, and ERBB4), an apoptosis related gene (APP), an RNA splicing factor (SF1), a miRNA processing factor (DICER1), an E3 ubiquitin ligase (CUL1) and transcription factors (KLF5 and EEF1B2). Our study suggests that systematic analysis of mutation distribution in the tertiary protein structure can help identify cancer driver genes.

Systematic analysis of mutation distribution in three dimensional protein structures identifies cancer driver genes

PubMed Central

Fujimoto, Akihiro; Okada, Yukinori; Boroevich, Keith A.; Tsunoda, Tatsuhiko; Taniguchi, Hiroaki; Nakagawa, Hidewaki

2016-01-01

Protein tertiary structure determines molecular function, interaction, and stability of the protein, therefore distribution of mutation in the tertiary structure can facilitate the identification of new driver genes in cancer. To analyze mutation distribution in protein tertiary structures, we applied a novel three dimensional permutation test to the mutation positions. We analyzed somatic mutation datasets of 21 types of cancers obtained from exome sequencing conducted by the TCGA project. Of the 3,622 genes that had ≥3 mutations in the regions with tertiary structure data, 106 genes showed significant skew in mutation distribution. Known tumor suppressors and oncogenes were significantly enriched in these identified cancer gene sets. Physical distances between mutations in known oncogenes were significantly smaller than those of tumor suppressors. Twenty-three genes were detected in multiple cancers. Candidate genes with significant skew of the 3D mutation distribution included kinases (MAPK1, EPHA5, ERBB3, and ERBB4), an apoptosis related gene (APP), an RNA splicing factor (SF1), a miRNA processing factor (DICER1), an E3 ubiquitin ligase (CUL1) and transcription factors (KLF5 and EEF1B2). Our study suggests that systematic analysis of mutation distribution in the tertiary protein structure can help identify cancer driver genes. PMID:27225414

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

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

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

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

Risk factors for chronic and recurrent otitis media-a meta-analysis.

PubMed

Zhang, Yan; Xu, Min; Zhang, Jin; Zeng, Lingxia; Wang, Yanfei; Zheng, Qing Yin

2014-01-01

Risk factors associated with chronic otitis media (COM) and recurrent otitis media (ROM) have been investigated in previous studies. The objective of this study was to integrate the findings and determine the possible risk factors for COM/ROM based on our meta-analysis. A comprehensive search of electronic bibliographic databases (PubMed, Embase, CNKI and Wanfang database) from 1964 to Dec 2012, as well as a manual search of references of articles, was performed. A total of 2971 articles were searched, and 198 full-text articles were assessed for eligibility; 24 studies were eligible for this meta-analysis. Regarding risk factors for COM/ROM, there were two to nine different studies from which the odds ratios (ORs) could be pooled. The presence of allergy or atopy increased the risk of COM/ROM (OR, 1.36; 95% CI, 1.13-1.64; P = 0.001). An upper respiratory tract infection (URTI) significantly increased the risk of COM/ROM (OR, 6.59; 95% CI, 3.13-13.89; P<0.00001). Snoring appeared to be a significant risk factor for COM/ROM (OR, 1.96; 95% CI, 1.78-2.16; P<0.00001). A patient history of acute otitis media (AOM)/ROM increased the risk of COM/ROM (OR, 11.13; 95% CI, 1.06-116.44; P = 0.04). Passive smoke significantly increased the risk of COM/ROM (OR, 1.39; 95% CI, 1.02-1.89 P = 0.04). Low social status appeared to be a risk factor for COM/ROM (OR, 3.82; 95% CI, 1.11-13.15; P = 0.03). Our meta-analysis identified reliable conclusions that allergy/atopy, URTI, snoring, previous history of AOM/ROM, Second-hand smoke and low social status are important risk factors for COM/ROM. Other unidentified risk factors need to be identified in further studies with critical criteria.

Risk Factors for Chronic and Recurrent Otitis Media–A Meta-Analysis

PubMed Central

Zhang, Yan; Xu, Min; Zhang, Jin; Zeng, Lingxia; Wang, Yanfei; Zheng, Qing Yin

2014-01-01

Risk factors associated with chronic otitis media (COM) and recurrent otitis media (ROM) have been investigated in previous studies. The objective of this study was to integrate the findings and determine the possible risk factors for COM/ROM based on our meta-analysis. A comprehensive search of electronic bibliographic databases (PubMed, Embase, CNKI and Wanfang database) from 1964 to Dec 2012, as well as a manual search of references of articles, was performed. A total of 2971 articles were searched, and 198 full-text articles were assessed for eligibility; 24 studies were eligible for this meta-analysis. Regarding risk factors for COM/ROM, there were two to nine different studies from which the odds ratios (ORs) could be pooled. The presence of allergy or atopy increased the risk of COM/ROM (OR, 1.36; 95% CI, 1.13–1.64; P = 0.001). An upper respiratory tract infection (URTI) significantly increased the risk of COM/ROM (OR, 6.59; 95% CI, 3.13–13.89; P<0.00001). Snoring appeared to be a significant risk factor for COM/ROM (OR, 1.96; 95% CI, 1.78–2.16; P<0.00001). A patient history of acute otitis media (AOM)/ROM increased the risk of COM/ROM (OR, 11.13; 95% CI, 1.06–116.44; P = 0.04). Passive smoke significantly increased the risk of COM/ROM (OR, 1.39; 95% CI, 1.02–1.89 P = 0.04). Low social status appeared to be a risk factor for COM/ROM (OR, 3.82; 95% CI, 1.11–13.15; P = 0.03). Our meta-analysis identified reliable conclusions that allergy/atopy, URTI, snoring, previous history of AOM/ROM, Second-hand smoke and low social status are important risk factors for COM/ROM. Other unidentified risk factors need to be identified in further studies with critical criteria. PMID:24466073

Sparse multivariate factor analysis regression models and its applications to integrative genomics analysis.

PubMed

Zhou, Yan; Wang, Pei; Wang, Xianlong; Zhu, Ji; Song, Peter X-K

2017-01-01

The multivariate regression model is a useful tool to explore complex associations between two kinds of molecular markers, which enables the understanding of the biological pathways underlying disease etiology. For a set of correlated response variables, accounting for such dependency can increase statistical power. Motivated by integrative genomic data analyses, we propose a new methodology-sparse multivariate factor analysis regression model (smFARM), in which correlations of response variables are assumed to follow a factor analysis model with latent factors. This proposed method not only allows us to address the challenge that the number of association parameters is larger than the sample size, but also to adjust for unobserved genetic and/or nongenetic factors that potentially conceal the underlying response-predictor associations. The proposed smFARM is implemented by the EM algorithm and the blockwise coordinate descent algorithm. The proposed methodology is evaluated and compared to the existing methods through extensive simulation studies. Our results show that accounting for latent factors through the proposed smFARM can improve sensitivity of signal detection and accuracy of sparse association map estimation. We illustrate smFARM by two integrative genomics analysis examples, a breast cancer dataset, and an ovarian cancer dataset, to assess the relationship between DNA copy numbers and gene expression arrays to understand genetic regulatory patterns relevant to the disease. We identify two trans-hub regions: one in cytoband 17q12 whose amplification influences the RNA expression levels of important breast cancer genes, and the other in cytoband 9q21.32-33, which is associated with chemoresistance in ovarian cancer. © 2016 WILEY PERIODICALS, INC.

Impact of identifying factors which trigger bothersome tinnitus on the treatment outcome in tinnitus retraining therapy.

PubMed

Molini, Egisto; Faralli, Mario; Calzolaro, Lucia; Ricci, Giampietro

2014-01-01

The aim of this work was to ascertain any differences in the effectiveness of rehabilitation therapy in relation to the presence or absence of a known negative reinforcement responsible for the tinnitus-related pathology. Between 1 January 2001 and 31 December 2008, we recruited 294 subjects suffering from incapacitating tinnitus and/or hyperacusis. The patients underwent tinnitus retraining therapy (TRT) according to the methods described by Jastreboff and Hazell [Tinnitus Retraining Therapy: Implementing the Neurophysiological Model. Cambridge, Cambridge University Press, 2004, pp 121-133]. We clinically assessed the presence or absence of known phenomena of associative learning, regarding the presence of adverse events temporally correlated with tinnitus and the treatment outcome. The separate analysis of the 2 subgroups shows a statistically significant difference in the improvement rate between the group with a known triggering factor and the group without a triggering factor, with a preponderance of the former with a 91% improvement rate versus approximately 56% for the latter. In our study, the inability to identify factors triggering bothersome tinnitus negatively affected the treatment outcome in TRT. © 2014 S. Karger AG, Basel.

Identifying and reducing risk factors related to trainee-client sexual misconduct.

PubMed

Hamilton, J C; Spruill, J

1999-06-01

Sexual misconduct involving therapists-in-training and their clients is addressed. Personal and situational factors that may constitute risk factors for the development of inappropriate sexual activity between trainees and their clients are identified. Although there may be certain characteristics that put particular students at risk for such involvement, the authors believe this risk is more strongly related to systemic, programmatic, and pedagogic characteristics of the environments in which students train. Examples include, respectively, the decline of concern over transference and countertransference, failure to include education about client-therapist sexual attraction and the consequences of sexual misconduct in graduate psychology curricula, and the reluctance of supervisors to deal straightforwardly with trainees' sexual feelings. Suggestions for reducing risks for client-therapist sexual misconduct are directed toward these situational factors.

Nightmares in the general population: identifying potential causal factors.

PubMed

Rek, Stephanie; Sheaves, Bryony; Freeman, Daniel

2017-09-01

Nightmares are inherently distressing, prevent restorative sleep, and are associated with a number of psychiatric problems, but have rarely been the subject of empirical study. Negative affect, linked to stressful events, is generally considered the key trigger of nightmares; hence nightmares have most often been considered in the context of post-traumatic stress disorder (PTSD). However, many individuals with heightened negative affect do not have nightmares. The objective of this study was to identify mechanistically plausible factors, beyond negative affect, that may explain why individuals experience nightmares. 846 participants from the UK general population completed an online survey about nightmare occurrence and severity (pre-occupation, distress, and impairment), negative affect, worry, depersonalisation, hallucinatory experiences, paranoia, alcohol use, sleep duration, physical activity levels, PTSD symptoms, and stressful life events. Associations of nightmares with the putative predictive factors were tested controlling for levels of negative affect. Analyses were also repeated controlling for levels of PTSD and the recent occurrence of stressful life events. Nightmare occurrence, adjusting for negative affect, was associated with higher levels of worry, depersonalisation, hallucinatory experiences, paranoia, and sleep duration (odds ratios 1.25-1.45). Nightmare severity, controlling for negative affect, was associated with higher levels of worry, depersonalisation, hallucinatory experiences, and paranoia (R 2 s: 0.33-0.39). Alcohol use and physical activity levels were not associated with nightmares. The study identifies a number of potential predictors of the occurrence and severity of nightmares. Causal roles require testing in future longitudinal, experimental, and treatment studies.

Psychosocial risk and protective factors for depression in the dialysis population: a systematic review and meta-regression analysis.

PubMed

Chan, Ramony; Steel, Zachary; Brooks, Robert; Heung, Tracy; Erlich, Jonathan; Chow, Josephine; Suranyi, Michael

2011-11-01

Research into the association between psychosocial factors and depression in End-Stage Renal Disease (ESRD) has expanded considerably in recent years identifying a range of factors that may act as important risk and protective factors of depression for this population. The present study provides the first systematic review and meta-analysis of this body of research. Published studies reporting associations between any psychosocial factor and depression were identified and retrieved from Medline, Embase, and PsycINFO, by applying optimised search strategies. Mean effect sizes were calculated for the associations across five psychosocial constructs (social support, personality attributes, cognitive appraisal, coping process, stress/stressor). Multiple hierarchical meta-regression analysis was applied to examine the moderating effects of methodological and substantive factors on the strength of the observed associations. 57 studies covering 58 independent samples with 5956 participants were identified, resulting in 246 effect sizes of the association between a range of psychosocial factors and depression. The overall mean effect size (Pearsons correlation coefficient) of the association between psychosocial factor and depression was 0.36. The effect sizes between the five psychosocial constructs and depression ranged from medium (0.27) to large levels (0.46) with personality attributes (0.46) and cognitive appraisal (0.46) having the largest effect sizes. In the meta-regression analyses, identified demographic (gender, age, location of study) and treatment (type of dialysis) characteristics moderated the strength of the associations with depression. The current analysis documents a moderate to large association between the presence of psychosocial risk factors and depression in ESRD. 2011. Published by Elsevier Inc. All rights reserved.

Factors influencing patient compliance with therapeutic regimens in chronic heart failure: A critical incident technique analysis.

PubMed

Strömberg, A; Broström, A; Dahlström, U; Fridlund, B

1999-01-01

The aim of this study was to identify factors influencing compliance with prescribed treatment in patients with chronic heart failure. A qualitative design with a critical incident technique was used. Incidents were collected through interviews with 25 patients with heart failure strategically selected from a primary health care clinic, a medical ward, and a specialist clinic. Two hundred sixty critical incidents were identified in the interviews and 2 main areas emerged in the analysis: inward factors and outward factors. The inward factors described how compliance was influenced by the personality of the patient, the disease, and the treatment. The outward factors described how compliance was influenced by social activities, social relationships, and health care professionals. By identifying the inward and outward factors influencing patients with chronic heart failure, health care professionals can assess whether intervention is needed to increase compliance.

Proteomic analysis of Populus × euramericana (clone I-214) roots to identify key factors involved in zinc stress response.

PubMed

Romeo, Stefania; Trupiano, Dalila; Ariani, Andrea; Renzone, Giovanni; Scippa, Gabriella S; Scaloni, Andrea; Sebastiani, Luca

2014-07-15

Contamination of soil and water by heavy metals has become a widespread problem; environmental pollution by high zinc (Zn) concentration occurs frequently. Although poplar (Populus spp.) has been identified as suitable for phytoremediation approaches, its response to high Zn concentrations are still not clearly understood. For this reason, we investigated the effects of Zn in Populus×euramericana clone I-214 roots by proteomic analysis. Comparative experiments were conducted on rooted woody cuttings grown in nutrient solutions containing 1mM (treatment) or 1μM (control) Zn concentrations. A gel-based proteomic approach coupled with morphological and chemical analysis was used to identify differentially represented proteins in treated roots and to investigate the effect of Zn treatment on the poplar root system. Data shows that Zn was accumulated preferentially in roots, that the antioxidant system, the carbohydrate/energy and amino acid metabolisms were the main pathways modulated by Zn excess, and that mitochondria and vacuoles were the cellular organelles predominately affected by Zn stress. A coordination between cell death and proliferation/growth seems to occur under this condition to counteract the Zn-induced damage. Copyright © 2014 Elsevier GmbH. All rights reserved.

Multi-species comparative analysis of the equine ACE gene identifies a highly conserved potential transcription factor binding site in intron 16.

PubMed

Hamilton, Natasha A; Tammen, Imke; Raadsma, Herman W

2013-01-01

Angiotensin converting enzyme (ACE) is essential for control of blood pressure. The human ACE gene contains an intronic Alu indel (I/D) polymorphism that has been associated with variation in serum enzyme levels, although the functional mechanism has not been identified. The polymorphism has also been associated with cardiovascular disease, type II diabetes, renal disease and elite athleticism. We have characterized the ACE gene in horses of breeds selected for differing physical abilities. The equine gene has a similar structure to that of all known mammalian ACE genes. Nine common single nucleotide polymorphisms (SNPs) discovered in pooled DNA were found to be inherited in nine haplotypes. Three of these SNPs were located in intron 16, homologous to that containing the Alu polymorphism in the human. A highly conserved 18 bp sequence, also within that intron, was identified as being a potential binding site for the transcription factors Oct-1, HFH-1 and HNF-3β, and lies within a larger area of higher than normal homology. This putative regulatory element may contribute to regulation of the documented inter-individual variation in human circulating enzyme levels, for which a functional mechanism is yet to be defined. Two equine SNPs occurred within the conserved area in intron 16, although neither of them disrupted the putative binding site. We propose a possible regulatory mechanism of the ACE gene in mammalian species which was previously unknown. This advance will allow further analysis leading to a better understanding of the mechanisms underpinning the associations seen between the human Alu polymorphism and enzyme levels, cardiovascular disease states and elite athleticism.

Multi-Species Comparative Analysis of the Equine ACE Gene Identifies a Highly Conserved Potential Transcription Factor Binding Site in Intron 16

PubMed Central

Hamilton, Natasha A.; Tammen, Imke; Raadsma, Herman W.

2013-01-01

Angiotensin converting enzyme (ACE) is essential for control of blood pressure. The human ACE gene contains an intronic Alu indel (I/D) polymorphism that has been associated with variation in serum enzyme levels, although the functional mechanism has not been identified. The polymorphism has also been associated with cardiovascular disease, type II diabetes, renal disease and elite athleticism. We have characterized the ACE gene in horses of breeds selected for differing physical abilities. The equine gene has a similar structure to that of all known mammalian ACE genes. Nine common single nucleotide polymorphisms (SNPs) discovered in pooled DNA were found to be inherited in nine haplotypes. Three of these SNPs were located in intron 16, homologous to that containing the Alu polymorphism in the human. A highly conserved 18 bp sequence, also within that intron, was identified as being a potential binding site for the transcription factors Oct-1, HFH-1 and HNF-3β, and lies within a larger area of higher than normal homology. This putative regulatory element may contribute to regulation of the documented inter-individual variation in human circulating enzyme levels, for which a functional mechanism is yet to be defined. Two equine SNPs occurred within the conserved area in intron 16, although neither of them disrupted the putative binding site. We propose a possible regulatory mechanism of the ACE gene in mammalian species which was previously unknown. This advance will allow further analysis leading to a better understanding of the mechanisms underpinning the associations seen between the human Alu polymorphism and enzyme levels, cardiovascular disease states and elite athleticism. PMID:23408978

Coexpression network analysis identifies transcriptional modules associated with genomic alterations in neuroblastoma.

PubMed

Yang, Liulin; Li, Yun; Wei, Zhi; Chang, Xiao

2018-06-01

Neuroblastoma is a highly complex and heterogeneous cancer in children. Acquired genomic alterations including MYCN amplification, 1p deletion and 11q deletion are important risk factors and biomarkers in neuroblastoma. Here, we performed a co-expression-based gene network analysis to study the intrinsic association between specific genomic changes and transcriptome organization. We identified multiple gene coexpression modules which are recurrent in two independent datasets and associated with functional pathways including nervous system development, cell cycle, immune system process and extracellular matrix/space. Our results also indicated that modules involved in nervous system development and cell cycle are highly associated with MYCN amplification and 1p deletion, while modules responding to immune system process are associated with MYCN amplification only. In summary, this integrated analysis provides novel insights into molecular heterogeneity and pathogenesis of neuroblastoma. This article is part of a Special Issue entitled: Accelerating Precision Medicine through Genetic and Genomic Big Data Analysis edited by Yudong Cai & Tao Huang. Copyright © 2017. Published by Elsevier B.V.

Pathway cross-talk network analysis identifies critical pathways in neonatal sepsis.

PubMed

Meng, Yu-Xiu; Liu, Quan-Hong; Chen, Deng-Hong; Meng, Ying

2017-06-01

Despite advances in neonatal care, sepsis remains a major cause of morbidity and mortality in neonates worldwide. Pathway cross-talk analysis might contribute to the inference of the driving forces in bacterial sepsis and facilitate a better understanding of underlying pathogenesis of neonatal sepsis. This study aimed to explore the critical pathways associated with the progression of neonatal sepsis by the pathway cross-talk analysis. By integrating neonatal transcriptome data with known pathway data and protein-protein interaction data, we systematically uncovered the disease pathway cross-talks and constructed a disease pathway cross-talk network for neonatal sepsis. Then, attract method was employed to explore the dysregulated pathways associated with neonatal sepsis. To determine the critical pathways in neonatal sepsis, rank product (RP) algorithm, centrality analysis and impact factor (IF) were introduced sequentially, which synthetically considered the differential expression of genes and pathways, pathways cross-talks and pathway parameters in the network. The dysregulated pathways with the highest IF values as well as RP<0.01 were defined as critical pathways in neonatal sepsis. By integrating three kinds of data, only 6919 common genes were included to perform the pathway cross-talk analysis. By statistic analysis, a total of 1249 significant pathway cross-talks were selected to construct the pathway cross-talk network. Moreover, 47 dys-regulated pathways were identified via attract method, 20 pathways were identified under RP<0.01, and the top 10 pathways with the highest IF were also screened from the pathway cross-talk network. Among them, we selected 8 common pathways, i.e. critical pathways. In this study, we systematically tracked 8 critical pathways involved in neonatal sepsis by integrating attract method and pathway cross-talk network. These pathways might be responsible for the host response in infection, and of great value for advancing

Using a Delphi Method to Identify Human Factors Contributing to Nursing Errors.

PubMed

Roth, Cheryl; Brewer, Melanie; Wieck, K Lynn

2017-07-01

The purpose of this study was to identify human factors associated with nursing errors. Using a Delphi technique, this study used feedback from a panel of nurse experts (n = 25) on an initial qualitative survey questionnaire followed by summarizing the results with feedback and confirmation. Synthesized factors regarding causes of errors were incorporated into a quantitative Likert-type scale, and the original expert panel participants were queried a second time to validate responses. The list identified 24 items as most common causes of nursing errors, including swamping and errors made by others that nurses are expected to recognize and fix. The responses provided a consensus top 10 errors list based on means with heavy workload and fatigue at the top of the list. The use of the Delphi survey established consensus and developed a platform upon which future study of nursing errors can evolve as a link to future solutions. This list of human factors in nursing errors should serve to stimulate dialogue among nurses about how to prevent errors and improve outcomes. Human and system failures have been the subject of an abundance of research, yet nursing errors continue to occur. © 2016 Wiley Periodicals, Inc.

Previously identified patellar tendinopathy risk factors differ between elite and sub-elite volleyball players.

PubMed

Janssen, I; Steele, J R; Munro, B J; Brown, N A T

2015-06-01

Patellar tendinopathy is the most common knee injury incurred in volleyball, with its prevalence in elite athletes more than three times that of their sub-elite counterparts. The purpose of this study was to determine whether patellar tendinopathy risk factors differed between elite and sub-elite male volleyball players. Nine elite and nine sub-elite male volleyball players performed a lateral stop-jump block movement. Maximum vertical jump, training history, muscle extensibility and strength, three-dimensional landing kinematics (250 Hz), along with lower limb neuromuscular activation patterns (1500 Hz), and patellar tendon loading were collected during each trial. Multivariate analyses of variance (P < 0.05) assessed for between-group differences in risk factors or patellar tendon loading. Significant interaction effects were further evaluated using post-hoc univariate analysis of variance tests. Landing kinematics, neuromuscular activation patterns, patellar tendon loading, and most of the previously identified risk factors did not differ between the elite and sub-elite players. However, elite players participated in a higher training volume and had less quadriceps extensibility than sub-elite players. Therefore, high training volume is likely the primary contributor to the injury discrepancy between elite and sub-elite volleyball players. Interventions designed to reduce landing frequency and improve quadriceps extensibility are recommended to reduce patellar tendinopathy prevalence in volleyball players. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Exploratory Bi-Factor Analysis: The Oblique Case

ERIC Educational Resources Information Center

Jennrich, Robert I.; Bentler, Peter M.

2012-01-01

Bi-factor analysis is a form of confirmatory factor analysis originally introduced by Holzinger and Swineford ("Psychometrika" 47:41-54, 1937). The bi-factor model has a general factor, a number of group factors, and an explicit bi-factor structure. Jennrich and Bentler ("Psychometrika" 76:537-549, 2011) introduced an exploratory form of bi-factor…

Bayesian Exploratory Factor Analysis

PubMed Central

Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James J.; Piatek, Rémi

2014-01-01

This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study confirms the validity of the approach. The method is used to produce interpretable low dimensional aggregates from a high dimensional set of psychological measurements. PMID:25431517

Microarray-based SNP genotyping to identify genetic risk factors of triple-negative breast cancer (TNBC) in South Indian population.

PubMed

Aravind Kumar, M; Singh, Vineeta; Naushad, Shaik Mohammad; Shanker, Uday; Lakshmi Narasu, M

2018-05-01

In the view of aggressive nature of Triple-Negative Breast cancer (TNBC) due to the lack of receptors (ER, PR, HER2) and high incidence of drug resistance associated with it, a case-control association study was conducted to identify the contributing genetic risk factors for Triple-negative breast cancer (TNBC). A total of 30 TNBC patients and 50 age and gender-matched controls of Indian origin were screened for 9,00,000 SNP markers using microarray-based SNP genotyping approach. The initial PLINK association analysis (p < 0.01, MAF 0.14-0.44, OR 10-24) identified 28 non-synonymous SNPs and one stop gain mutation in the exonic region as possible determinants of TNBC risk. All the 29 SNPs were annotated using ANNOVAR. The interactions between these markers were evaluated using Multifactor dimensionality reduction (MDR) analysis. The interactions were in the following order: exm408776 > exm1278309 > rs316389 > rs1651654 > rs635538 > exm1292477. Recursive partitioning analysis (RPA) was performed to construct decision tree useful in predicting TNBC risk. As shown in this analysis, rs1651654 and exm585172 SNPs are found to be determinants of TNBC risk. Artificial neural network model was used to generate the Receiver operating characteristic curves (ROC), which showed high sensitivity and specificity (AUC-0.94) of these markers. To conclude, among the 9,00,000 SNPs tested, CCDC42 exm1292477, ANXA3 exm408776, SASH1 exm585172 are found to be the most significant genetic predicting factors for TNBC. The interactions among exm408776, exm1278309, rs316389, rs1651654, rs635538, exm1292477 SNPs inflate the risk for TNBC further. Targeted analysis of these SNPs and genes alone also will have similar clinical utility in predicting TNBC.

An exploration of the structure of mentors' behavior in nursing education using exploratory factor analysis and Mokken scale analysis.

PubMed

Chen, Yanhua; Watson, Roger; Hilton, Andrea

2016-05-01

To understand nursing students' expectation from their mentors and assess mentors' performance, a scale of mentors' behavior was developed based on literature review and focus group in China. This study aims to explore the structure of mentors' behavior. A cross-sectional survey. Data were collected from nursing students in three hospitals in southwest China in 2014. A total of 669 pre-registered nursing students in their final year clinical learning participated in this study. Exploratory factor analysis and Mokken scale analysis was employed to explore the structure and hierarchical property of mentors' behavior. Three dimensions (professional development, facilitating learning and psychosocial support) were identified by factor analysis and confirmed by Mokken scaling analysis. The three sub-scales showed internal consistency reliability from 87% to 91%, and moderate to strong precision in ordering students' expectation about mentors' behavior and a small Mokken scale showing hierarchy was identified. Some insight into the structure of mentoring in nursing education has been obtained and a scale which could be used in the study of mentoring and in the preparation of mentors has been developed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Risk analysis of the thermal sterilization process. Analysis of factors affecting the thermal resistance of microorganisms.

PubMed

Akterian, S G; Fernandez, P S; Hendrickx, M E; Tobback, P P; Periago, P M; Martinez, A

1999-03-01

A risk analysis was applied to experimental heat resistance data. This analysis is an approach for processing experimental thermobacteriological data in order to study the variability of D and z values of target microorganisms depending on the deviations range of environmental factors, to determine the critical factors and to specify their critical tolerance. This analysis is based on sets of sensitivity functions applied to a specific case of experimental data related to the thermoresistance of Clostridium sporogenes and Bacillus stearothermophilus spores. The effect of the following factors was analyzed: the type of target microorganism; nature of the heating substrate; pH, temperature; type of acid employed and NaCl concentration. The type of target microorganism to be inactivated, the nature of the substrate (reference or real food) and the heating temperature were identified as critical factors, determining about 90% of the alteration of the microbiological risk. The effect of the type of acid used for the acidification of products and the concentration of NaCl can be assumed to be negligible factors for the purposes of engineering calculations. The critical non-uniformity in temperature during thermobacteriological studies was set as 0.5% and the critical tolerances of pH value and NaCl concentration were 5%. These results are related to a specific case study, for that reason their direct generalization is not correct.

Identifying Older Adults at Risk of Delirium Following Elective Surgery: A Systematic Review and Meta-Analysis.

PubMed

Watt, Jennifer; Tricco, Andrea C; Talbot-Hamon, Catherine; Pham, Ba'; Rios, Patricia; Grudniewicz, Agnes; Wong, Camilla; Sinclair, Douglas; Straus, Sharon E

2018-04-01

Postoperative delirium is a common preventable complication experienced by older adults undergoing elective surgery. In this systematic review and meta-analysis, we identified prognostic factors associated with the risk of postoperative delirium among older adults undergoing elective surgery. Medline, EMBASE, CINAHL, Cochrane Central Register of Controlled Trials, and AgeLine were searched for articles published between inception and April 21, 2016. A total of 5692 titles and abstracts were screened in duplicate for possible inclusion. Studies using any method for diagnosing delirium were eligible. Two reviewers independently completed all data extraction and quality assessments using the Cochrane Risk-of-Bias Tool for randomized controlled trials (RCTs) and the Newcastle-Ottawa Scale (NOS) for cohort studies. Random effects meta-analysis models were used to derive pooled effect estimates. Forty-one studies (9384 patients) reported delirium-related prognostic factors. Among our included studies, the pooled incidence of postoperative delirium was 18.4% (95% confidence interval [CI] 14.3-23.3%, number needed to follow [NNF] = 6). Geriatric syndromes were important predictors of delirium, namely history of delirium (odds ratio [OR] 6.4, 95% CI 2.2-17.9), frailty (OR 4.1, 95% CI 1.4-11.7), cognitive impairment (OR 2.7, 95% CI 1.9-3.8), impairment in activities of daily living (ADLs; OR 2.1, 95% CI 1.6-2.6), and impairment in instrumental activities of daily living (IADLs; OR 1.9, 95% CI 1.3-2.8). Potentially modifiable prognostic factors such as psychotropic medication use (OR 2.3, 95% CI 1.4-3.6) and smoking status (OR 1.8 95% CI 1.3-2.4) were also identified. Caregiver support was associated with lower odds of postoperative delirium (OR 0.69, 95% CI 0.52-0.91). Though caution must be used in interpreting meta-analyses of non-randomized studies due to the potential influence of unmeasured confounding, we identified potentially modifiable prognostic factors including

Electronic health record analysis via deep poisson factor models

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

Henao, Ricardo; Lu, James T.; Lucas, Joseph E.

Electronic Health Record (EHR) phenotyping utilizes patient data captured through normal medical practice, to identify features that may represent computational medical phenotypes. These features may be used to identify at-risk patients and improve prediction of patient morbidity and mortality. We present a novel deep multi-modality architecture for EHR analysis (applicable to joint analysis of multiple forms of EHR data), based on Poisson Factor Analysis (PFA) modules. Each modality, composed of observed counts, is represented as a Poisson distribution, parameterized in terms of hidden binary units. In-formation from different modalities is shared via a deep hierarchy of common hidden units. Activationmore » of these binary units occurs with probability characterized as Bernoulli-Poisson link functions, instead of more traditional logistic link functions. In addition, we demon-strate that PFA modules can be adapted to discriminative modalities. To compute model parameters, we derive efficient Markov Chain Monte Carlo (MCMC) inference that scales efficiently, with significant computational gains when compared to related models based on logistic link functions. To explore the utility of these models, we apply them to a subset of patients from the Duke-Durham patient cohort. We identified a cohort of over 12,000 patients with Type 2 Diabetes Mellitus (T2DM) based on diagnosis codes and laboratory tests out of our patient population of over 240,000. Examining the common hidden units uniting the PFA modules, we identify patient features that represent medical concepts. Experiments indicate that our learned features are better able to predict mortality and morbidity than clinical features identified previously in a large-scale clinical trial.« less

Electronic health record analysis via deep poisson factor models

DOE PAGES

Henao, Ricardo; Lu, James T.; Lucas, Joseph E.; ...

2016-01-01

Electronic Health Record (EHR) phenotyping utilizes patient data captured through normal medical practice, to identify features that may represent computational medical phenotypes. These features may be used to identify at-risk patients and improve prediction of patient morbidity and mortality. We present a novel deep multi-modality architecture for EHR analysis (applicable to joint analysis of multiple forms of EHR data), based on Poisson Factor Analysis (PFA) modules. Each modality, composed of observed counts, is represented as a Poisson distribution, parameterized in terms of hidden binary units. In-formation from different modalities is shared via a deep hierarchy of common hidden units. Activationmore » of these binary units occurs with probability characterized as Bernoulli-Poisson link functions, instead of more traditional logistic link functions. In addition, we demon-strate that PFA modules can be adapted to discriminative modalities. To compute model parameters, we derive efficient Markov Chain Monte Carlo (MCMC) inference that scales efficiently, with significant computational gains when compared to related models based on logistic link functions. To explore the utility of these models, we apply them to a subset of patients from the Duke-Durham patient cohort. We identified a cohort of over 12,000 patients with Type 2 Diabetes Mellitus (T2DM) based on diagnosis codes and laboratory tests out of our patient population of over 240,000. Examining the common hidden units uniting the PFA modules, we identify patient features that represent medical concepts. Experiments indicate that our learned features are better able to predict mortality and morbidity than clinical features identified previously in a large-scale clinical trial.« less

Genome-wide association studies identify genetic loci for low von Willebrand factor levels

PubMed Central

van Loon, Janine; Dehghan, Abbas; Weihong, Tang; Trompet, Stella; McArdle, Wendy L; Asselbergs, Folkert F W; Chen, Ming-Huei; Lopez, Lorna M; Huffman, Jennifer E; Leebeek, Frank W G; Basu, Saonli; Stott, David J; Rumley, Ann; Gansevoort, Ron T; Davies, Gail; Wilson, James J F; Witteman, Jacqueline C M; Cao, Xiting; de Craen, Anton J M; Bakker, Stephan J L; Psaty, Bruce M; Starr, John M; Hofman, Albert; Wouter Jukema, J; Deary, Ian J; Hayward, Caroline; van der Harst, Pim; Lowe, Gordon D O; Folsom, Aaron R; Strachan, David P; Smith, Nicolas; de Maat, Moniek P M; O'Donnell, Christopher

2016-01-01

Low von Willebrand factor (VWF) levels are associated with bleeding symptoms and are a diagnostic criterion for von Willebrand disease, the most common inherited bleeding disorder. To date, it is unclear which genetic loci are associated with reduced VWF levels. Therefore, we conducted a meta-analysis of genome-wide association studies to identify genetic loci associated with low VWF levels. For this meta-analysis, we included 31 149 participants of European ancestry from 11 community-based studies. From all participants, VWF antigen (VWF:Ag) measurements and genome-wide single-nucleotide polymorphism (SNP) scans were available. Each study conducted analyses using logistic regression of SNPs on dichotomized VWF:Ag measures (lowest 5% for blood group O and non-O) with an additive genetic model adjusted for age and sex. An inverse-variance weighted meta-analysis was performed for VWF:Ag levels. A total of 97 SNPs exceeded the genome-wide significance threshold of 5 × 10−8 and comprised five loci on four different chromosomes: 6q24 (smallest P-value 5.8 × 10−10), 9q34 (2.4 × 10−64), 12p13 (5.3 × 10−22), 12q23 (1.2 × 10−8) and 13q13 (2.6 × 10−8). All loci were within or close to genes, including STXBP5 (Syntaxin Binding Protein 5) (6q24), STAB5 (stabilin-5) (12q23), ABO (9q34), VWF (12p13) and UFM1 (ubiquitin-fold modifier 1) (13q13). Of these, UFM1 has not been previously associated with VWF:Ag levels. Four genes that were previously associated with VWF levels (VWF, ABO, STXBP5 and STAB2) were also associated with low VWF levels, and, in addition, we identified a new gene, UFM1, that is associated with low VWF levels. These findings point to novel mechanisms for the occurrence of low VWF levels. PMID:26486471

System analysis identifies distinct and common functional networks governed by transcription factor ASCL1, in glioma and small cell lung cancer.

PubMed

Donakonda, Sainitin; Sinha, Swati; Dighe, Shrinivas Nivrutti; Rao, Manchanahalli R Satyanarayana

2017-07-25

ASCL1 is a basic Helix-Loop-Helix transcription factor (TF), which is involved in various cellular processes like neuronal development and signaling pathways. Transcriptome profiling has shown that ASCL1 overexpression plays an important role in the development of glioma and Small Cell Lung Carcinoma (SCLC), but distinct and common molecular mechanisms regulated by ASCL1 in these cancers are unknown. In order to understand how it drives the cellular functional network in these two tumors, we generated a gene expression profile in a glioma cell line (U87MG) to identify ASCL1 gene targets by an si RNA silencing approach and then compared this with a publicly available dataset of similarly silenced SCLC (NCI-H1618 cells). We constructed TF-TF and gene-gene interactions, as well as protein interaction networks of ASCL1 regulated genes in glioma and SCLC cells. Detailed network analysis uncovered various biological processes governed by ASCL1 target genes in these two tumor cell lines. We find that novel ASCL1 functions related to mitosis and signaling pathways influencing development and tumor growth are affected in both glioma and SCLC cells. In addition, we also observed ASCL1 governed functional networks that are distinct to glioma and SCLC.

Identifying the impact of social determinants of health on disease rates using correlation analysis of area-based summary information.

PubMed

Song, Ruiguang; Hall, H Irene; Harrison, Kathleen McDavid; Sharpe, Tanya Telfair; Lin, Lillian S; Dean, Hazel D

2011-01-01

We developed a statistical tool that brings together standard, accessible, and well-understood analytic approaches and uses area-based information and other publicly available data to identify social determinants of health (SDH) that significantly affect the morbidity of a specific disease. We specified AIDS as the disease of interest and used data from the American Community Survey and the National HIV Surveillance System. Morbidity and socioeconomic variables in the two data systems were linked through geographic areas that can be identified in both systems. Correlation and partial correlation coefficients were used to measure the impact of socioeconomic factors on AIDS diagnosis rates in certain geographic areas. We developed an easily explained approach that can be used by a data analyst with access to publicly available datasets and standard statistical software to identify the impact of SDH. We found that the AIDS diagnosis rate was highly correlated with the distribution of race/ethnicity, population density, and marital status in an area. The impact of poverty, education level, and unemployment depended on other SDH variables. Area-based measures of socioeconomic variables can be used to identify risk factors associated with a disease of interest. When correlation analysis is used to identify risk factors, potential confounding from other variables must be taken into account.

Memory systems, processes, and tasks: taxonomic clarification via factor analysis.

PubMed

Bruss, Peter J; Mitchell, David B

2009-01-01

The nature of various memory systems was examined using factor analysis. We reanalyzed data from 11 memory tasks previously reported in Mitchell and Bruss (2003). Four well-defined factors emerged, closely resembling episodic and semantic memory and conceptual and perceptual implicit memory, in line with both memory systems and transfer-appropriate processing accounts. To explore taxonomic issues, we ran separate analyses on the implicit tasks. Using a cross-format manipulation (pictures vs. words), we identified 3 prototypical tasks. Word fragment completion and picture fragment identification tasks were "factor pure," tapping perceptual processes uniquely. Category exemplar generation revealed its conceptual nature, yielding both cross-format priming and a picture superiority effect. In contrast, word stem completion and picture naming were more complex, revealing attributes of both processes.

Repressor- and Activator-Type Ethylene Response Factors Functioning in Jasmonate Signaling and Disease Resistance Identified via a Genome-Wide Screen of Arabidopsis Transcription Factor Gene Expression[w

PubMed Central

McGrath, Ken C.; Dombrecht, Bruno; Manners, John M.; Schenk, Peer M.; Edgar, Cameron I.; Maclean, Donald J.; Scheible, Wolf-Rüdiger; Udvardi, Michael K.; Kazan, Kemal

2005-01-01

To identify transcription factors (TFs) involved in jasmonate (JA) signaling and plant defense, we screened 1,534 Arabidopsis (Arabidopsis thaliana) TFs by real-time quantitative reverse transcription-PCR for their altered transcript at 6 h following either methyl JA treatment or inoculation with the incompatible pathogen Alternaria brassicicola. We identified 134 TFs that showed a significant change in expression, including many APETALA2/ethylene response factor (AP2/ERF), MYB, WRKY, and NAC TF genes with unknown functions. Twenty TF genes were induced by both the pathogen and methyl JA and these included 10 members of the AP2/ERF TF family, primarily from the B1a and B3 subclusters. Functional analysis of the B1a TF AtERF4 revealed that AtERF4 acts as a novel negative regulator of JA-responsive defense gene expression and resistance to the necrotrophic fungal pathogen Fusarium oxysporum and antagonizes JA inhibition of root elongation. In contrast, functional analysis of the B3 TF AtERF2 showed that AtERF2 is a positive regulator of JA-responsive defense genes and resistance to F. oxysporum and enhances JA inhibition of root elongation. Our results suggest that plants coordinately express multiple repressor- and activator-type AP2/ERFs during pathogen challenge to modulate defense gene expression and disease resistance. PMID:16183832

Factors Associated with Fatal Occupational Accidents among Mexican Workers: A National Analysis

PubMed Central

Gonzalez-Delgado, Mery; Gómez-Dantés, Héctor; Fernández-Niño, Julián Alfredo; Robles, Eduardo; Borja, Víctor H.; Aguilar, Miriam

2015-01-01

Objective To identify the factors associated with fatal occupational injuries in Mexico in 2012 among workers affiliated with the Mexican Social Security Institute. Methods Analysis of secondary data using information from the National Occupational Risk Information System, with the consequence of the occupational injury (fatal versus non-fatal) as the response variable. The analysis included 406,222 non-fatal and 1,140 fatal injuries from 2012. The factors associated with the lethality of the injury were identified using a logistic regression model with the Firth approach. Results Being male (OR=5.86; CI95%: 4.22-8.14), age (OR=1.04; CI95%: 1.03-1.06), employed in the position for 1 to 10 years (versus less than 1 year) (OR=1.37; CI95%: 1.15-1.63), working as a facilities or machine operator or assembler (OR: 3.28; CI95%: 2.12- 5.07) and being a worker without qualifications (OR=1.96; CI95%: 1.18-3.24) (versus an office worker) were associated with fatality in the event of an injury. Additionally, companies classified as maximum risk (OR=1.90; CI 95%: 1.38-2.62), workplace conditions (OR=7.15; CI95%: 3.63-14.10) and factors related to the work environment (OR=9.18; CI95%:4.36-19.33) were identified as risk factors for fatality in the event of an occupational injury. Conclusions Fatality in the event of an occupational injury is associated with factors related to sociodemographics (age, sex and occupation), the work environment and workplace conditions. Worker protection policies should be created for groups with a higher risk of fatal occupational injuries in Mexico. PMID:25790063

Genome-Wide RNAi Screen Identifies Broadly-Acting Host Factors That Inhibit Arbovirus Infection

PubMed Central

Yasunaga, Ari; Hanna, Sheri L.; Li, Jianqing; Cho, Hyelim; Rose, Patrick P.; Spiridigliozzi, Anna; Gold, Beth; Diamond, Michael S.; Cherry, Sara

2014-01-01

Vector-borne viruses are an important class of emerging and re-emerging pathogens; thus, an improved understanding of the cellular factors that modulate infection in their respective vertebrate and insect hosts may aid control efforts. In particular, cell-intrinsic antiviral pathways restrict vector-borne viruses including the type I interferon response in vertebrates and the RNA interference (RNAi) pathway in insects. However, it is likely that additional cell-intrinsic mechanisms exist to limit these viruses. Since insects rely on innate immune mechanisms to inhibit virus infections, we used Drosophila as a model insect to identify cellular factors that restrict West Nile virus (WNV), a flavivirus with a broad and expanding geographical host range. Our genome-wide RNAi screen identified 50 genes that inhibited WNV infection. Further screening revealed that 17 of these genes were antiviral against additional flaviviruses, and seven of these were antiviral against other vector-borne viruses, expanding our knowledge of invertebrate cell-intrinsic immunity. Investigation of two newly identified factors that restrict diverse viruses, dXPO1 and dRUVBL1, in the Tip60 complex, demonstrated they contributed to antiviral defense at the organismal level in adult flies, in mosquito cells, and in mammalian cells. These data suggest the existence of broadly acting and functionally conserved antiviral genes and pathways that restrict virus infections in evolutionarily divergent hosts. PMID:24550726

Practical identifiability analysis of a minimal cardiovascular system model.

PubMed

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

2017-01-17

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

Factor Analysis of Intern Effectiveness

ERIC Educational Resources Information Center

Womack, Sid T.; Hannah, Shellie Louise; Bell, Columbus David

2012-01-01

Four factors in teaching intern effectiveness, as measured by a Praxis III-similar instrument, were found among observational data of teaching interns during the 2010 spring semester. Those factors were lesson planning, teacher/student reflection, fairness & safe environment, and professionalism/efficacy. This factor analysis was as much of a…

Some dissociating factors in the analysis of structural and functional progressive damage in open-angle glaucoma.

PubMed

Hudson, C J W; Kim, L S; Hancock, S A; Cunliffe, I A; Wild, J M

2007-05-01

To identify the presence, and origin, of any "dissociating factors" inherent to the techniques for evaluating progression that mask the relationship between structural and functional progression in open-angle glaucoma (OAG). 23 patients (14 with OAG and 9 with ocular hypertension (OHT)) who had received serial Heidelberg Retina Tomograph (HRT II) and Humphrey Field Analyser (HFA) examinations for >or=5 years (mean 78.4 months (SD 9.5), range 60-101 months) were identified. Evidence of progressive disease was retrospectively evaluated in one eye of each patient using the Topographic Change Analysis (TCA) and Glaucoma Progression Analysis (GPA) for the HRT II and HFA, respectively. Six patients were stable by both techniques; four exhibited both structural and functional progression; seven exhibited structural progression, only, and six showed functional progression, only. Three types of dissociating factors were identified. TCA failed to identify progressive structural damage in the presence of advanced optic nerve head damage. GPA failed to identify progressive functional damage at stimulus locations, with sensitivities exhibiting test-retest variability beyond the maximum stimulus luminance of the perimeter, and where a perimetric learning effect was apparent. The three dissociating factors accounted for nine of the 13 patients who exhibited a lack of concordance between structural and functional progressive damage.

Linking Strengths: Identifying and Exploring Protective Factor Clusters in Academically Resilient Low-Socioeconomic Urban Students of Color

ERIC Educational Resources Information Center

Morales, Erik E.

2010-01-01

Based on data from qualitative interviews with 50 high-achieving low-socioeconomic students of color, two "clusters" of important and symbiotic protective factors are identified and explored. Each cluster consists of a series of interrelated protective factors identified by the participants as crucial to their statistically exceptional academic…

Identifying Factors Associated with Maternal Deaths in Jharkhand, India: A Verbal Autopsy Study

PubMed Central

Pradhan, Manas Ranjan

2013-01-01

Maternal mortality has been identified as a priority issue in health policy and research in India. The country, with an annual decrease of maternal mortality rate by 4.9% since 1990, now records 63,000 maternal deaths a year. India tops the list of countries with high maternal mortality. Based on a verbal autopsy study of 403 maternal deaths, conducted in 2008, this paper explores the missed opportunities to save maternal lives, besides probing into the socioeconomic factors contributing to maternal deaths in Jharkhand, India. This cross-sectional study was carried out in two phases, and a multistage sampling design was used in selecting deaths for verbal autopsy. Informed consent was taken into consideration before verbal autopsy. The analytical approach includes bivariate analysis using SPSS 15, besides triangulation of qualitative and quantitative findings. Most of the deceased were poor (89%), non-literates (85%), and housewives (74%). Again, 80% died in the community/at home, 28% died during pregnancy while another 26% died during delivery. Any antenatal care was received by merely 28% women, and only 20% of the deliveries were conducted by skilled birth attendants (doctors and midwives). Delays in decision-making, travel, and treatment compounded by ignorance of obstetric complications, inadequate use of maternal healthcare services, poor healthcare infrastructure, and harmful rituals are the major contributing factors of maternal deaths in India. PMID:23930345

Identifying factors associated with maternal deaths in Jharkhand, India: a verbal autopsy study.

PubMed

Khan, Nizamuddin; Pradhan, Manas Ranjan

2013-06-01

Maternal mortality has been identified as a priority issue in health policy and research in India. The country, with an annual decrease of maternal mortality rate by 4.9% since 1990, now records 63,000 maternal deaths a year. India tops the list of countries with high maternal mortality. Based on a verbal autopsy study of 403 maternal deaths, conducted in 2008, this paper explores the missed opportunities to save maternal lives, besides probing into the socioeconomic factors contributing to maternal deaths in Jharkhand, India. This cross-sectional study was carried out in two phases, and a multistage sampling design was used in selecting deaths for verbal autopsy. Informed consent was taken into consideration before verbal autopsy. The analytical approach includes bivariate analysis using SPSS 15, besides triangulation of qualitative and quantitative findings. Most of the deceased were poor (89%), non-literates (85%), and housewives (74%). Again, 80% died in the community/at home, 28% died during pregnancy while another 26% died during delivery. Any antenatal care was received by merely 28% women, and only 20% of the deliveries were conducted by skilled birth attendants (doctors and midwives). Delays in decision-making, travel, and treatment compounded by ignorance of obstetric complications, inadequate use of maternal healthcare services, poor healthcare infrastructure, and harmful rituals are the major contributing factors of maternal deaths in India.

Epigenetic priors for identifying active transcription factor binding sites.

PubMed

Cuellar-Partida, Gabriel; Buske, Fabian A; McLeay, Robert C; Whitington, Tom; Noble, William Stafford; Bailey, Timothy L

2012-01-01

Accurate knowledge of the genome-wide binding of transcription factors in a particular cell type or under a particular condition is necessary for understanding transcriptional regulation. Using epigenetic data such as histone modification and DNase I, accessibility data has been shown to improve motif-based in silico methods for predicting such binding, but this approach has not yet been fully explored. We describe a probabilistic method for combining one or more tracks of epigenetic data with a standard DNA sequence motif model to improve our ability to identify active transcription factor binding sites (TFBSs). We convert each data type into a position-specific probabilistic prior and combine these priors with a traditional probabilistic motif model to compute a log-posterior odds score. Our experiments, using histone modifications H3K4me1, H3K4me3, H3K9ac and H3K27ac, as well as DNase I sensitivity, show conclusively that the log-posterior odds score consistently outperforms a simple binary filter based on the same data. We also show that our approach performs competitively with a more complex method, CENTIPEDE, and suggest that the relative simplicity of the log-posterior odds scoring method makes it an appealing and very general method for identifying functional TFBSs on the basis of DNA and epigenetic evidence. FIMO, part of the MEME Suite software toolkit, now supports log-posterior odds scoring using position-specific priors for motif search. A web server and source code are available at http://meme.nbcr.net. Utilities for creating priors are at http://research.imb.uq.edu.au/t.bailey/SD/Cuellar2011. t.bailey@uq.edu.au Supplementary data are available at Bioinformatics online.

Identifying Trajectories of Borderline Personality Features in Adolescence: Antecedent and Interactive Risk Factors.

PubMed

Haltigan, John D; Vaillancourt, Tracy

2016-03-01

To examine trajectories of adolescent borderline personality (BP) features in a normative-risk cohort (n = 566) of Canadian children assessed at ages 13, 14, 15, and 16 and childhood predictors of trajectory group membership assessed at ages 8, 10, 11, and 12. Data were drawn from the McMaster Teen Study, an on-going study examining relations among bullying, mental health, and academic achievement. Participants and their parents completed a battery of mental health and peer relations questionnaires at each wave of the study. Academic competence was assessed at age 8 (Grade 3). Latent class growth analysis, analysis of variance, and logistic regression were used to analyze the data. Three distinct BP features trajectory groups were identified: elevated or rising, intermediate or stable, and low or stable. Parent- and child-reported mental health symptoms, peer relations risk factors, and intra-individual risk factors were significant predictors of elevated or rising and intermediate or stable trajectory groups. Child-reported attention-deficit hyperactivity disorder (ADHD) and somatization symptoms uniquely predicted elevated or rising trajectory group membership, whereas parent-reported anxiety and child-reported ADHD symptoms uniquely predicted intermediate or stable trajectory group membership. Child-reported somatization symptoms was the only predictor to differentiate the intermediate or stable and elevated or rising trajectory groups (OR 1.15, 95% CI 1.04 to 1.28). Associations between child-reported reactive temperament and elevated BP features trajectory group membership were 10.23 times higher among children who were bullied, supporting a diathesis-stress pathway in the development of BP features for these youth. Findings demonstrate the heterogeneous course of BP features in early adolescence and shed light on the potential prodromal course of later borderline personality disorder. © The Author(s) 2015.

Robust Bayesian Factor Analysis

ERIC Educational Resources Information Center

Hayashi, Kentaro; Yuan, Ke-Hai

2003-01-01

Bayesian factor analysis (BFA) assumes the normal distribution of the current sample conditional on the parameters. Practical data in social and behavioral sciences typically have significant skewness and kurtosis. If the normality assumption is not attainable, the posterior analysis will be inaccurate, although the BFA depends less on the current…

Identifying barriers to patient acceptance of active surveillance: content analysis of online patient communications.

PubMed

Mishra, Mark V; Bennett, Michele; Vincent, Armon; Lee, Olivia T; Lallas, Costas D; Trabulsi, Edouard J; Gomella, Leonard G; Dicker, Adam P; Showalter, Timothy N

2013-01-01

Qualitative research aimed at identifying patient acceptance of active surveillance (AS) has been identified as a public health research priority. The primary objective of this study was to determine if analysis of a large-sample of anonymous internet conversations (ICs) could be utilized to identify unmet public needs regarding AS. English-language ICs regarding prostate cancer (PC) treatment with AS from 2002-12 were identified using a novel internet search methodology. Web spiders were developed to mine, aggregate, and analyze content from the world-wide-web for ICs centered on AS. Collection of ICs was not restricted to any specific geographic region of origin. NLP was used to evaluate content and perform a sentiment analysis. Conversations were scored as positive, negative, or neutral. A sentiment index (SI) was subsequently calculated according to the following formula to compare temporal trends in public sentiment towards AS: [(# Positive IC/#Total IC)-(#Negative IC/#Total IC) x 100]. A total of 464 ICs were identified. Sentiment increased from -13 to +2 over the study period. The increase sentiment has been driven by increased patient emphasis on quality-of-life factors and endorsement of AS by national medical organizations. Unmet needs identified in these ICs include: a gap between quantitative data regarding long-term outcomes with AS vs. conventional treatments, desire for treatment information from an unbiased specialist, and absence of public role models managed with AS. This study demonstrates the potential utility of online patient communications to provide insight into patient preferences and decision-making. Based on our findings, we recommend that multidisciplinary clinics consider including an unbiased specialist to present treatment options and that future decision tools for AS include quantitative data regarding outcomes after AS.

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

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

Novel histopathologic feature identified through image analysis augments stage II colorectal cancer clinical reporting

PubMed Central

Caie, Peter D.; Zhou, Ying; Turnbull, Arran K.; Oniscu, Anca; Harrison, David J.

2016-01-01

A number of candidate histopathologic factors show promise in identifying stage II colorectal cancer (CRC) patients at a high risk of disease-specific death, however they can suffer from low reproducibility and none have replaced classical pathologic staging. We developed an image analysis algorithm which standardized the quantification of specific histopathologic features and exported a multi-parametric feature-set captured without bias. The image analysis algorithm was executed across a training set (n = 50) and the resultant big data was distilled through decision tree modelling to identify the most informative parameters to sub-categorize stage II CRC patients. The most significant, and novel, parameter identified was the ‘sum area of poorly differentiated clusters’ (AreaPDC). This feature was validated across a second cohort of stage II CRC patients (n = 134) (HR = 4; 95% CI, 1.5– 11). Finally, the AreaPDC was integrated with the significant features within the clinical pathology report, pT stage and differentiation, into a novel prognostic index (HR = 7.5; 95% CI, 3–18.5) which improved upon current clinical staging (HR = 4.26; 95% CI, 1.7– 10.3). The identification of poorly differentiated clusters as being highly significant in disease progression presents evidence to suggest that these features could be the source of novel targets to decrease the risk of disease specific death. PMID:27322148

Risk Factors for Suicide Ideation Among Adolescents: Five-Year National Data Analysis.

PubMed

Im, Yeojin; Oh, Won-Oak; Suk, Minhyun

2017-06-01

This study identified risk factors for suicide ideation among adolescents through a secondary analysis using data collected over five years from the 5th-9th Korea Youth Risk Behavior Survey. We analyzed 370,568 students' responses to questions about suicidality. The risk factors for suicide ideation included demographic characteristics, such as gender (girls), low grades, low economic status, and not living with one or both parents. Behavioral and mental health risk factors affecting suicide ideation were depression, low sleep satisfaction, high stress, alcohol consumption, smoking, and sexual activity. Health care providers should particularly target adolescents manifesting the above risk factors when developing suicide prevention programs for them. Copyright © 2017 Elsevier Inc. All rights reserved.

Identifying effective factors on consumers' choice behavior toward green products: the case of Tehran, the capital of Iran.

PubMed

Rahnama, Hassan; Rajabpour, Shayan

2017-01-01

The environment is increasingly turning to a vital and very important issue for all people. By increasing environmental concerns as well as legislating and regulating rules on the protection of the environment and the emergence of green consumers, implementing green marketing approach for organizations seems to be more crucial and essential. As a result, the need for ecological products and green business activities compels companies to combine environmental issues with marketing strategies. The first step in the success of companies and organizations is to identify consumers and their consumption behaviors correctly and accurately. So, the purpose of this study is to identify effective factors for the choice of consumers of green products. We used consumption values (functional value, social value, emotional value, conditional value, epistemic value, and environmental value) as the effective factor for choosing green products. The original place of this research was in Tehran, capital city of Iran, which is one of the most polluted cities in the world due to environmental issues. The results from the survey questionnaires are analyzed using confirmatory factor analysis and structural equation modelling. The results indicated that functional value-price, functional value-quality, social value, epistemic value, and environmental value had significantly positive effects on the choice of green products; also, conditional value and emotional value had no influence on it. It was concluded that the main influential factors for consumers' choice behavior regarding green products included environmental value and epistemic value. This study emphasized the proper pricing of green products by producers and sellers.

Dietary patterns and risk of ductal carcinoma of the breast: a factor analysis in Uruguay.

PubMed

Ronco, Alvaro L; De Stefani, Eduardo; Deneo-Pellegrini, Hugo; Boffetta, Paolo; Aune, Dagfinn; Silva, Cecilia; Landó, Gabriel; Luaces, María E; Acosta, Gisele; Mendilaharsu, María

2010-01-01

Breast cancer (BC) shows very high incidence rates in Uruguayan women. The present factor analysis of ductal carcinoma of the breast, the most frequent histological type of this malignancy both in Uruguay and in the World, was conducted at a prepaid hospital of Montevideo, Uruguay. We identified 111 cases with ductal BC and 222 controls with normal mammograms. A factor analysis was conducted using 39 food groups, allowing retention of six factors analyzed through logistic regression in order to obtain odds ratios (OR) associated with ductal BC. The low fat and non-alcoholic beverage patterns were inversely associated (OR=0.30 and OR=0.45, respectively) with risk. Conversely, the fatty cheese pattern was positively associated (OR=4.17) as well as the fried white meat (OR=2.28) and Western patterns (OR 2.13). Ductal BC shared similar dietary risk patterns as those identified by studies not discriminating between histologic type of breast cancer.

Patient factors associated with increased acute care costs of hip fractures: a detailed analysis of 402 patients.

PubMed

Aigner, R; Meier Fedeler, T; Eschbach, D; Hack, J; Bliemel, C; Ruchholtz, S; Bücking, B

2016-12-01

The aim of the present study was to identify patient factors associated with higher costs in hip fracture patients. The mean costs of a prospectively observed sample of 402 patients were 8853 €. The ASA score, Charlson comorbidity index, and fracture location were associated with increased costs. Fractures of the proximal end of the femur (hip fractures) are of increasing incidence due to demographic changes. Relevant co-morbidities often present in these patients cause high complication rates and prolonged hospital stays, thus leading to high costs of acute care. The aim of this study was to perform a precise cost analysis of the actual hospital costs of hip fractures and to identify patient factors associated with increased costs. The basis of this analysis was a prospectively observed single-center trial, which included 402 patients with fractures of the proximal end of the femur. All potential cost factors were recorded as accurately as possible for each of the 402 patients individually, and statistical analysis was performed to identify associations between pre-existing patient factors and acute care costs. The mean total acute care costs per patient were 8853 ± 5676 € with ward costs (5828 ± 4294 €) and costs for surgical treatment (1972 ± 956 €) representing the major cost factors. The ASA score, Charlson comorbidity index, and fracture location were identified as influencing the costs of acute care for hip fracture treatment. Hip fractures are associated with high acute care costs. This study underlines the necessity of sophisticated risk-adjusted payment models based on specific patient factors. Economic aspects should be an integral part of future hip fracture research due to limited health care resources.

Risk factors associated with human Rift Valley fever infection: systematic review and meta-analysis.

PubMed

Nicholas, Dennis E; Jacobsen, Kathryn H; Waters, Nigel M

2014-12-01

To identify risk factors for human Rift Valley fever virus (RVFV) infection. A systematic review identified 17 articles reporting on 16 studies examining risk factors for RVFV. Pooled odds ratios (pOR) were calculated for exposures examined in four or more studies. Being male [pOR = 1.4 (1.0, 1.8)], contact with aborted animal tissue [pOR = 3.4 (1.6, 7.3)], birthing an animal [pOR = 3.2 (2.4, 4.2)], skinning an animal [pOR = 2.5 (1.9, 3.2)], slaughtering an animal [pOR = 2.4 (1.4, 4.1)] and drinking raw milk [pOR = 1.8 (1.2, 2.6)] were significantly associated with RVF infection after meta-analysis. Other potential risk factors include sheltering animals in the home and milking an animal, which may both involve contact with animal body fluids. Based on the identified risk factors, use of personal protective equipment and disinfectants by animal handlers may help reduce RVFV transmission during outbreaks. Milk pasteurisation and other possible preventive methods require further investigation. © 2014 John Wiley & Sons Ltd.

[Identifying clinical risk factors in recurrent idiopathic deep venous thrombosis].

PubMed

Del Río Solá, M Lourdes; González Fajardo, José Antonio; Vaquero Puerta, Carlos

2016-03-18

Oral anticoagulant therapy for more than 6 months in patients with an episode of idiopathic thromboembolic disease is controversial. The objective was to determine predictive clinical signs that identify patients at increased risk of thromboembolic recurrence after stopping anticoagulant therapy for 6 months after an episode of idiopathic deep vein thrombosis (DVT). A prospective study which included 306 consecutive patients with a first episode of idiopathic DVT from June 2012 to June 2014. Predictor variables of recurrent thromboembolic disease and episodes of recurrence during follow-up of the patients (28.42 months) were collected. We performed a multivariate analysis to analyze possible predictors (P<.20) and an analysis of Kaplan-Meier to establish mean recurrence-free survival. We identified 91 episodes of residual vein thrombosis on follow-up of the patients (37.5% men and 20.3% women) (OR 1.84; 95% CI 1.25-2.71). In the Cox regression analysis stratified by gender, variables showed significant presence of hyperechoic thrombus (P=.001) in males, and persistence of residual thrombus in women (P=.046). The mean recurrence-free survival was shorter in both groups. The presence of echogenic thrombus in men and the existence of residual DVT in women were 2 clinical signs associated with increased risk of thromboembolic recurrence after stopping anticoagulant therapy for 6 months after an episode of idiopathic DVT in our study. Copyright © 2015 Elsevier España, S.L.U. All rights reserved.

Identifying Trajectories of Adolescents' Depressive Phenomena: An Examination of Early Risk Factors

ERIC Educational Resources Information Center

Mazza, James J.; Fleming, Charles B.; Abbott, Robert D.; Haggerty, Kevin P.; Catalano, Richard F.

2010-01-01

Few studies have examined risk factors of childhood and early adolescent depressive symptomatology trajectories. This study examined self-report depressive symptomatology across a 6-year time period from 2nd to 8th grade to identify latent groups of individuals with similar patterns of depressive phenomena in a sample of 951 children (440 girls,…

Identifying Stress Transcription Factors Using Gene Expression and TF-Gene Association Data

PubMed Central

Wu, Wei-Sheng; Chen, Bor-Sen

2007-01-01

Unicellular organisms such as yeasts have evolved to survive environmental stresses by rapidly reorganizing the genomic expression program to meet the challenges of harsh environments. The complex adaptation mechanisms to stress remain to be elucidated. In this study, we developed Stress Transcription Factor Identification Algorithm (STFIA), which integrates gene expression and TF-gene association data to identify the stress transcription factors (TFs) of six kinds of stresses. We identified some general stress TFs that are in response to various stresses, and some specific stress TFs that are in response to one specific stress. The biological significance of our findings is validated by the literature. We found that a small number of TFs may be sufficient to control a wide variety of expression patterns in yeast under different stresses. Two implications can be inferred from this observation. First, the adaptation mechanisms to different stresses may have a bow-tie structure. Second, there may exist extensive regulatory cross-talk among different stress responses. In conclusion, this study proposes a network of the regulators of stress responses and their mechanism of action. PMID:20066130

Gene-based rare allele analysis identified a risk gene of Alzheimer's disease.

PubMed

Kim, Jong Hun; Song, Pamela; Lim, Hyunsun; Lee, Jae-Hyung; Lee, Jun Hong; Park, Sun Ah

2014-01-01

Alzheimer's disease (AD) has a strong propensity to run in families. However, the known risk genes excluding APOE are not clinically useful. In various complex diseases, gene studies have targeted rare alleles for unsolved heritability. Our study aims to elucidate previously unknown risk genes for AD by targeting rare alleles. We used data from five publicly available genetic studies from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the database of Genotypes and Phenotypes (dbGaP). A total of 4,171 cases and 9,358 controls were included. The genotype information of rare alleles was imputed using 1,000 genomes. We performed gene-based analysis of rare alleles (minor allele frequency≤3%). The genome-wide significance level was defined as meta P<1.8×10(-6) (0.05/number of genes in human genome = 0.05/28,517). ZNF628, which is located at chromosome 19q13.42, showed a genome-wide significant association with AD. The association of ZNF628 with AD was not dependent on APOE ε4. APOE and TREM2 were also significantly associated with AD, although not at genome-wide significance levels. Other genes identified by targeting common alleles could not be replicated in our gene-based rare allele analysis. We identified that rare variants in ZNF628 are associated with AD. The protein encoded by ZNF628 is known as a transcription factor. Furthermore, the associations of APOE and TREM2 with AD were highly significant, even in gene-based rare allele analysis, which implies that further deep sequencing of these genes is required in AD heritability studies.

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

ERIC Educational Resources Information Center

Saghazadeh, Amene; Rezaei, Nima

2017-01-01

Brain-derived neurotrophic factor (BDNF) plays an important role in activity-dependent synaptic plasticity. Altered blood BDNF levels have been frequently identified in people with autism spectrum disorders (ASD). There are however wide discrepancies in the evidence. Therefore, we performed the present systematic review and meta-analysis aimed at…

Chi-squared Automatic Interaction Detection Decision Tree Analysis of Risk Factors for Infant Anemia in Beijing, China

PubMed Central

Ye, Fang; Chen, Zhi-Hua; Chen, Jie; Liu, Fang; Zhang, Yong; Fan, Qin-Ying; Wang, Lin

2016-01-01

Background: In the past decades, studies on infant anemia have mainly focused on rural areas of China. With the increasing heterogeneity of population in recent years, available information on infant anemia is inconclusive in large cities of China, especially with comparison between native residents and floating population. This population-based cross-sectional study was implemented to determine the anemic status of infants as well as the risk factors in a representative downtown area of Beijing. Methods: As useful methods to build a predictive model, Chi-squared automatic interaction detection (CHAID) decision tree analysis and logistic regression analysis were introduced to explore risk factors of infant anemia. A total of 1091 infants aged 6–12 months together with their parents/caregivers living at Heping Avenue Subdistrict of Beijing were surveyed from January 1, 2013 to December 31, 2014. Results: The prevalence of anemia was 12.60% with a range of 3.47%–40.00% in different subgroup characteristics. The CHAID decision tree model has demonstrated multilevel interaction among risk factors through stepwise pathways to detect anemia. Besides the three predictors identified by logistic regression model including maternal anemia during pregnancy, exclusive breastfeeding in the first 6 months, and floating population, CHAID decision tree analysis also identified the fourth risk factor, the maternal educational level, with higher overall classification accuracy and larger area below the receiver operating characteristic curve. Conclusions: The infant anemic status in metropolis is complex and should be carefully considered by the basic health care practitioners. CHAID decision tree analysis has demonstrated a better performance in hierarchical analysis of population with great heterogeneity. Risk factors identified by this study might be meaningful in the early detection and prompt treatment of infant anemia in large cities. PMID:27174328

Chi-squared Automatic Interaction Detection Decision Tree Analysis of Risk Factors for Infant Anemia in Beijing, China.

PubMed

Ye, Fang; Chen, Zhi-Hua; Chen, Jie; Liu, Fang; Zhang, Yong; Fan, Qin-Ying; Wang, Lin

2016-05-20

In the past decades, studies on infant anemia have mainly focused on rural areas of China. With the increasing heterogeneity of population in recent years, available information on infant anemia is inconclusive in large cities of China, especially with comparison between native residents and floating population. This population-based cross-sectional study was implemented to determine the anemic status of infants as well as the risk factors in a representative downtown area of Beijing. As useful methods to build a predictive model, Chi-squared automatic interaction detection (CHAID) decision tree analysis and logistic regression analysis were introduced to explore risk factors of infant anemia. A total of 1091 infants aged 6-12 months together with their parents/caregivers living at Heping Avenue Subdistrict of Beijing were surveyed from January 1, 2013 to December 31, 2014. The prevalence of anemia was 12.60% with a range of 3.47%-40.00% in different subgroup characteristics. The CHAID decision tree model has demonstrated multilevel interaction among risk factors through stepwise pathways to detect anemia. Besides the three predictors identified by logistic regression model including maternal anemia during pregnancy, exclusive breastfeeding in the first 6 months, and floating population, CHAID decision tree analysis also identified the fourth risk factor, the maternal educational level, with higher overall classification accuracy and larger area below the receiver operating characteristic curve. The infant anemic status in metropolis is complex and should be carefully considered by the basic health care practitioners. CHAID decision tree analysis has demonstrated a better performance in hierarchical analysis of population with great heterogeneity. Risk factors identified by this study might be meaningful in the early detection and prompt treatment of infant anemia in large cities.

Genome-wide analysis of the bHLH gene family in planarians identifies factors required for adult neurogenesis and neuronal regeneration.

PubMed

Cowles, Martis W; Brown, David D R; Nisperos, Sean V; Stanley, Brianna N; Pearson, Bret J; Zayas, Ricardo M

2013-12-01

In contrast to most well-studied model organisms, planarians have a remarkable ability to completely regenerate a functional nervous system from a pluripotent stem cell population. Thus, planarians provide a powerful model to identify genes required for adult neurogenesis in vivo. We analyzed the basic helix-loop-helix (bHLH) family of transcription factors, many of which are crucial for nervous system development and have been implicated in human diseases. However, their potential roles in adult neurogenesis or central nervous system (CNS) function are not well understood. We identified 44 planarian bHLH homologs, determined their patterns of expression in the animal and assessed their functions using RNAi. We found nine bHLHs expressed in stem cells and neurons that are required for CNS regeneration. Our analyses revealed that homologs of coe, hes (hesl-3) and sim label progenitors in intact planarians, and following amputation we observed an enrichment of coe(+) and sim(+) progenitors near the wound site. RNAi knockdown of coe, hesl-3 or sim led to defects in CNS regeneration, including failure of the cephalic ganglia to properly pattern and a loss of expression of distinct neuronal subtype markers. Together, these data indicate that coe, hesl-3 and sim label neural progenitor cells, which serve to generate new neurons in uninjured or regenerating animals. Our study demonstrates that this model will be useful to investigate how stem cells interpret and respond to genetic and environmental cues in the CNS and to examine the role of bHLH transcription factors in adult tissue regeneration.

The Infinitesimal Jackknife with Exploratory Factor Analysis

ERIC Educational Resources Information Center

Zhang, Guangjian; Preacher, Kristopher J.; Jennrich, Robert I.

2012-01-01

The infinitesimal jackknife, a nonparametric method for estimating standard errors, has been used to obtain standard error estimates in covariance structure analysis. In this article, we adapt it for obtaining standard errors for rotated factor loadings and factor correlations in exploratory factor analysis with sample correlation matrices. Both…

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

PubMed

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

2005-06-03

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

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

NASA Technical Reports Server (NTRS)

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

2015-01-01

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

Causes of accidents in terrain parks: an exploratory factor analysis of recreational freestylers' views.

PubMed

Carús, Luis

2014-03-01

This study examines ski and snowboard terrain park users' views on aspects associated with accidents by identifying and assessing variables that may influence the occurrence of accidents and the resulting injuries. The research was conducted in a major resort in the Spanish Pyrenees, using information gathered from freestyle skiers and snowboarders aged 6 or older. To identify interrelationships among variables and to group the variables belonging to unified concepts, an exploratory factor analysis was performed using varimax rotation. The results revealed 5 factors that grouped the measured variables that may influence the occurrence of accidents while freestyling in terrain parks. The park features, conditions of the activity, and the user's personal conditions were found to have the most substantial influence on the freestylers' perceptions. Variables identified as components of the main factors of accident risk in terrain parks should be incorporated into resort management communication and policies. © 2013 Wilderness Medical Society Published by Wilderness Medical Society All rights reserved.

Identifying factors associated with regular physical activity in leisure time among Canadian adolescents.

PubMed

Godin, Gaston; Anderson, Donna; Lambert, Léo-Daniel; Desharnais, Raymond

2005-01-01

The purpose of this study was to identify the factors explaining regular physical activity among Canadian adolescents. A cohort study conducted over a period of 2 years. A French-language high school located near Québec City. A cohort of 740 students (352 girls; 388 boys) aged 13.3 +/- 1.0 years at baseline. Psychosocial, life context, profile, and sociodemographic variables were assessed at baseline and 1 and 2 years after baseline. Exercising almost every day during leisure time at each measurement time was the dependent variable. The Generalized Estimating Equations (GEE) analysis indicated that exercising almost every day was significantly associated with a high intention to exercise (odds ratio [OR]: 8.33, confidence interval [CI] 95%: 5.26, 13.18), being satisfied with the activity practiced (OR: 2.07, CI 95%: 1.27, 3.38), perceived descriptive norm (OR: 1.82, CI 95%: 1.41, 2.35), being a boy (OR: 1.83, CI 95%: 1.37, 2.46), practicing "competitive" activities (OR: 1.80, CI 95%: 1.37, 2.36), eating a healthy breakfast (OR: 1.68, CI 95%: 1.09, 2.60), and normative beliefs (OR: 1.48, CI 95%: 1.14, 1.90). Specific GEE analysis for gender indicated slight but significant differences. This study provides evidence for the need to design interventions that are gender specific and that focus on increasing intention to exercise regularly.

Factor Retention in Exploratory Factor Analysis: A Comparison of Alternative Methods.

ERIC Educational Resources Information Center

Mumford, Karen R.; Ferron, John M.; Hines, Constance V.; Hogarty, Kristine Y.; Kromrey, Jeffery D.

This study compared the effectiveness of 10 methods of determining the number of factors to retain in exploratory common factor analysis. The 10 methods included the Kaiser rule and a modified Kaiser criterion, 3 variations of parallel analysis, 4 regression-based variations of the scree procedure, and the minimum average partial procedure. The…

Exploratory factor analysis in Rehabilitation Psychology: a content analysis.

PubMed

Roberson, Richard B; Elliott, Timothy R; Chang, Jessica E; Hill, Jessica N

2014-11-01

Our objective was to examine the use and quality of exploratory factor analysis (EFA) in articles published in Rehabilitation Psychology. Trained raters examined 66 separate exploratory factor analyses in 47 articles published between 1999 and April 2014. The raters recorded the aim of the EFAs, the distributional statistics, sample size, factor retention method(s), extraction and rotation method(s), and whether the pattern coefficients, structure coefficients, and the matrix of association were reported. The primary use of the EFAs was scale development, but the most widely used extraction and rotation method was principle component analysis, with varimax rotation. When determining how many factors to retain, multiple methods (e.g., scree plot, parallel analysis) were used most often. Many articles did not report enough information to allow for the duplication of their results. EFA relies on authors' choices (e.g., factor retention rules extraction, rotation methods), and few articles adhered to all of the best practices. The current findings are compared to other empirical investigations into the use of EFA in published research. Recommendations for improving EFA reporting practices in rehabilitation psychology research are provided.

To Identify the Important Soil Properties Affecting Dinoseb Adsorption with Statistical Analysis

PubMed Central

Guan, Yiqing; Wei, Jianhui; Zhang, Danrong; Zu, Mingjuan; Zhang, Liru

2013-01-01

Investigating the influences of soil characteristic factors on dinoseb adsorption parameter with different statistical methods would be valuable to explicitly figure out the extent of these influences. The correlation coefficients and the direct, indirect effects of soil characteristic factors on dinoseb adsorption parameter were analyzed through bivariate correlation analysis, and path analysis. With stepwise regression analysis the factors which had little influence on the adsorption parameter were excluded. Results indicate that pH and CEC had moderate relationship and lower direct effect on dinoseb adsorption parameter due to the multicollinearity with other soil factors, and organic carbon and clay contents were found to be the most significant soil factors which affect the dinoseb adsorption process. A regression is thereby set up to explore the relationship between the dinoseb adsorption parameter and the two soil factors: the soil organic carbon and clay contents. A 92% of the variation of dinoseb sorption coefficient could be attributed to the variation of the soil organic carbon and clay contents. PMID:23737715

Six Novel Loci Associated with Circulating VEGF Levels Identified by a Meta-analysis of Genome-Wide Association Studies

PubMed Central

Song, Ci; Nutile, Teresa; Vernon Smith, Albert; Concas, Maria Pina; Traglia, Michela; Barbieri, Caterina; Ndiaye, Ndeye Coumba; Stathopoulou, Maria G.; Lagou, Vasiliki; Maestrale, Giovanni Battista; Sala, Cinzia; Debette, Stephanie; Kovacs, Peter; Lind, Lars; Lamont, John; Fitzgerald, Peter; Tönjes, Anke; Gudnason, Vilmundur; Toniolo, Daniela; Pirastu, Mario; Bellenguez, Celine; Vasan, Ramachandran S.; Ingelsson, Erik; Leutenegger, Anne-Louise; Johnson, Andrew D.; DeStefano, Anita L.; Visvikis-Siest, Sophie; Seshadri, Sudha; Ciullo, Marina

2016-01-01

Vascular endothelial growth factor (VEGF) is an angiogenic and neurotrophic factor, secreted by endothelial cells, known to impact various physiological and disease processes from cancer to cardiovascular disease and to be pharmacologically modifiable. We sought to identify novel loci associated with circulating VEGF levels through a genome-wide association meta-analysis combining data from European-ancestry individuals and using a dense variant map from 1000 genomes imputation panel. Six discovery cohorts including 13,312 samples were analyzed, followed by in-silico and de-novo replication studies including an additional 2,800 individuals. A total of 10 genome-wide significant variants were identified at 7 loci. Four were novel loci (5q14.3, 10q21.3, 16q24.2 and 18q22.3) and the leading variants at these loci were rs114694170 (MEF2C, P = 6.79x10-13), rs74506613 (JMJD1C, P = 1.17x10-19), rs4782371 (ZFPM1, P = 1.59x10-9) and rs2639990 (ZADH2, P = 1.72x10-8), respectively. We also identified two new independent variants (rs34528081, VEGFA, P = 1.52x10-18; rs7043199, VLDLR-AS1, P = 5.12x10-14) at the 3 previously identified loci and strengthened the evidence for the four previously identified SNPs (rs6921438, LOC100132354, P = 7.39x10-1467; rs1740073, C6orf223, P = 2.34x10-17; rs6993770, ZFPM2, P = 2.44x10-60; rs2375981, KCNV2, P = 1.48x10-100). These variants collectively explained up to 52% of the VEGF phenotypic variance. We explored biological links between genes in the associated loci using Ingenuity Pathway Analysis that emphasized their roles in embryonic development and function. Gene set enrichment analysis identified the ERK5 pathway as enriched in genes containing VEGF associated variants. eQTL analysis showed, in three of the identified regions, variants acting as both cis and trans eQTLs for multiple genes. Most of these genes, as well as some of those in the associated loci, were involved in platelet biogenesis and functionality, suggesting the

Factors influencing societal response of nanotechnology: an expert stakeholder analysis

NASA Astrophysics Data System (ADS)

Gupta, Nidhi; Fischer, Arnout R. H.; van der Lans, Ivo A.; Frewer, Lynn J.

2012-05-01

Nanotechnology can be described as an emerging technology and, as has been the case with other emerging technologies such as genetic modification, different socio-psychological factors will potentially influence societal responses to its development and application. These factors will play an important role in how nanotechnology is developed and commercialised. This article aims to identify expert opinion on factors influencing societal response to applications of nanotechnology. Structured interviews with experts on nanotechnology from North West Europe were conducted using repertory grid methodology in conjunction with generalized Procrustes analysis to examine the psychological constructs underlying societal uptake of 15 key applications of nanotechnology drawn from different areas (e.g. medicine, agriculture and environment, chemical, food, military, sports, and cosmetics). Based on expert judgement, the main factors influencing societal response to different applications of nanotechnology will be the extent to which applications are perceived to be beneficial, useful, and necessary, and how 'real' and physically close to the end-user these applications are perceived to be by the public.

Identifying Success Factors in Community College Grants Awarded under the U.S. Department of Labor's Community-Based Job Training Grants Program, 2005-2008

ERIC Educational Resources Information Center

Garrison, Debra Linley

2010-01-01

This study provides an in-depth analysis of the Community-Based Job Training Grants awarded by the U.S. Department of Labor from 2005 to 2008. The primary research question is designed to identify the most important factors in meeting grant-training outcomes; however, numerous secondary questions were addressed to provide the reader with in-depth…

Gene expression patterns combined with bioinformatics analysis identify genes associated with cholangiocarcinoma.

PubMed

Li, Chen; Shen, Weixing; Shen, Sheng; Ai, Zhilong

2013-12-01

To explore the molecular mechanisms of cholangiocarcinoma (CC), microarray technology was used to find biomarkers for early detection and diagnosis. The gene expression profiles from 6 patients with CC and 5 normal controls were downloaded from Gene Expression Omnibus and compared. As a result, 204 differentially co-expressed genes (DCGs) in CC patients compared to normal controls were identified using a computational bioinformatics analysis. These genes were mainly involved in coenzyme metabolic process, peptidase activity and oxidation reduction. A regulatory network was constructed by mapping the DCGs to known regulation data. Four transcription factors, FOXC1, ZIC2, NKX2-2 and GCGR, were hub nodes in the network. In conclusion, this study provides a set of targets useful for future investigations into molecular biomarker studies. Copyright © 2013 Elsevier Ltd. All rights reserved.

Identifying the Factors That Facilitate or Hinder Advance Planning by Persons With Dementia

PubMed Central

Hirschman, Karen B.; Kapo, Jennifer M.; Karlawish, Jason H. T.

2009-01-01

We performed semistructured interviews with 30 family members of patients with advanced dementia to identify the factors that facilitate or hinder advance planning by persons with dementia. All interviews were analyzed using qualitative data analysis techniques. The majority (77%) of family members reported that their relative had some form of written advance directive, and at least half reported previous discussions about health care preferences (57%), living situation or placement issues (50%), and finances or estate planning (60%) with the patient. Family members reported some themes that prompted planning and others that were barriers to planning. Events that most often triggered planning were medical, living situation, or financial issues associated with a friend or family member of the patient (57%). Barriers to planning included both passive and active avoidance. The most common form of passive avoidance was not realizing the importance of planning until it was too late to have the discussion (63%). The most common form of active avoidance was avoiding the discussion (53%). These data suggest potentially remediable strategies to address barriers to advance planning discussions. PMID:18580595

Identifying protective and risk factors for injurious falls in patients hospitalized for acute care: a retrospective case-control study.

PubMed

Aryee, Emmanuel; James, Spencer L; Hunt, Guenola M; Ryder, Hilary F

2017-11-07

Admitted patients who fall and injure themselves during an acute hospitalization incur increased costs, morbidity, and mortality, but little research has been conducted on identifying inpatients at high risk to injure themselves in a fall. Falls risk assessment tools have been unsuccessful due to their low positive predictive value when applied broadly to entire hospital populations. We aimed to identify variables associated with the risk of or protection against injurious fall in the inpatient setting. We also aimed to test the variables in the ABCs mnemonic (Age > 85, Bones-orthopedic conditions, anti-Coagulation and recent surgery) for correlation with injurious fall. We performed a retrospective case-control study at an academic tertiary care center comparing admitted patients with injurious fall to admitted patients without fall. We collected data on the demographics, medical and fall history, outcomes, and discharge disposition of injured fallers and control patients. We performed multivariate analysis of potential risk factors for injurious fall with logistic regression to calculate adjusted odds ratios. We identified 117 injured fallers and 320 controls. There were no differences in age, anti-coagulation use or fragility fractures between cases and controls. In multivariate analysis, recent surgery (OR 0.46, p = 0.003) was protective; joint replacement (OR 5.58, P = 0.002), psychotropic agents (OR 2.23, p = 0.001), the male sex (OR 2.08, p = 0.003) and history of fall (OR 2.08, p = 0.02) were significantly associated with injurious fall. In this study, the variables in the ABCs parameters were among the variables not useful for identifying inpatients at risk of injuring themselves in a fall, while other non-ABCs variables demonstrated a significant association with injurious fall. Recent surgery was a protective factor, and practices around the care of surgical patients could be extrapolated to reduce the in-hospital fall rates.

Identifying the factors underlying discontinuation of triptans.

PubMed

Wells, Rebecca E; Markowitz, Shira Y; Baron, Eric P; Hentz, Joseph G; Kalidas, Kavita; Mathew, Paul G; Halker, Rashmi; Dodick, David W; Schwedt, Todd J

2014-02-01

To identify factors associated with triptan discontinuation among migraine patients. It is unclear why many migraine patients who are prescribed triptans discontinue this treatment. This study investigated correlates of triptan discontinuation with a focus on potentially modifiable factors to improve compliance. This multicenter cross-sectional survey (n = 276) was performed at US tertiary care headache clinics. Headache fellows who were members of the American Headache Society Headache Fellows Research Consortium recruited episodic and chronic migraine patients who were current triptan users (use within prior 3 months and for ≥1 year) or past triptan users (no use within 6 months; prior use within 2 years). Univariate analyses were first completed to compare current triptan users to past users for: migraine characteristics, other migraine treatments, triptan education, triptan efficacy, triptan side effects, type of prescribing provider, Migraine Disability Assessment (MIDAS) scores and Beck Depression Inventory (BDI) scores. Then, a multivariable logistic regression model was selected from all possible combinations of predictor variables to determine the factors that best correlated with triptan discontinuation. Compared with those still using triptans (n = 207), those who had discontinued use (n = 69) had higher rates of medication overuse (30 vs. 18%, P = .04) and were more likely to have ever used opioids for migraine treatment (57 vs. 38%, P = .006) as well as higher MIDAS (mean 63 vs. 37, P = .001) and BDI scores (mean 10.4 vs. 7.4, P = .009). Compared with discontinued users, current triptan users were more likely to have had their triptan prescribed by a specialist (neurologist, headache specialist, or pain specialist) (74 vs. 54%, P = .002) and were more likely to report headache resolution (53 vs. 14%, P < .001) or a reduction in pain intensity (71 vs. 28%, P < .001) most of the time from their triptan. On a 1

Study of risk factors for gastric cancer by populational databases analysis

PubMed Central

Ferrari, Fangio; Reis, Marco Antonio Moura

2013-01-01

AIM: To study the association between the incidence of gastric cancer and populational exposure to risk/protective factors through an analysis of international databases. METHODS: Open-access global databases concerning the incidence of gastric cancer and its risk/protective factors were identified through an extensive search on the Web. As its distribution was neither normal nor symmetric, the cancer incidence of each country was categorized according to ranges of percentile distribution. The association of each risk/protective factor with exposure was measured between the extreme ranges of the incidence of gastric cancer (under the 25th percentile and above the 75th percentile) by the use of the Mann-Whitney test, considering a significance level of 0.05. RESULTS: A variable amount of data omission was observed among all of the factors under study. A weak or nonexistent correlation between the incidence of gastric cancer and the study variables was shown by a visual analysis of scatterplot dispersion. In contrast, an analysis of categorized incidence revealed that the countries with the highest human development index (HDI) values had the highest rates of obesity in males and the highest consumption of alcohol, tobacco, fruits, vegetables and meat, which were associated with higher incidences of gastric cancer. There was no significant difference for the risk factors of obesity in females and fish consumption. CONCLUSION: Higher HDI values, coupled with a higher prevalence of male obesity and a higher per capita consumption of alcohol, tobacco, fruits, vegetables and meat, are associated with a higher incidence of gastric cancer based on an analysis of populational global data. PMID:24409066

Identifying drought response of semi-arid aeolian systems using near-surface luminescence profiles and changepoint analysis, Nebraska Sandhills.

NASA Astrophysics Data System (ADS)

Buckland, Catherine; Bailey, Richard; Thomas, David

2017-04-01

Two billion people living in drylands are affected by land degradation. Sediment erosion by wind and water removes fertile soil and destabilises landscapes. Vegetation disturbance is a key driver of dryland erosion caused by both natural and human forcings: drought, fire, land use, grazing pressure. A quantified understanding of vegetation cover sensitivities and resultant surface change to forcing factors is needed if the vegetation and landscape response to future climate change and human pressure are to be better predicted. Using quartz luminescence dating and statistical changepoint analysis (Killick & Eckley, 2014) this study demonstrates the ability to identify step-changes in depositional age of near-surface sediments. Lx/Tx luminescence profiles coupled with statistical analysis show the use of near-surface sediments in providing a high-resolution record of recent system response and aeolian system thresholds. This research determines how the environment has recorded and retained sedimentary evidence of drought response and land use disturbances over the last two hundred years across both individual landforms and the wider Nebraska Sandhills. Identifying surface deposition and comparing with records of climate, fire and land use changes allows us to assess the sensitivity and stability of the surface sediment to a range of forcing factors. Killick, R and Eckley, IA. (2014) "changepoint: An R Package for Changepoint Analysis." Journal of Statistical Software, (58) 1-19.

Molecular Analysis of Non-Small Cell Lung Cancer (NSCLC) Identifies Subsets with Different Sensitivity to Insulin like Growth Factor I Receptor (IGF-IR) Inhibition

PubMed Central

Gualberto, Antonio; Dolled-Filhart, Marisa; Gustavson, Mark; Christiansen, Jason; Wang, Yu-Fen; Hixon, Mary L.; Reynolds, Jennifer; McDonald, Sandra; Ang, Agnes; Rimm, David L.; Langer, Corey J.; Blakely, Johnetta; Garland, Linda; Paz-Ares, Luis G.; Karp, Daniel D.; Lee, Adrian V.

2010-01-01

Purpose Identify molecular determinants of sensitivity of NSCLC to anti-insulin like growth factor receptor (IGF-IR) therapy. Experimental Design 216 tumor samples were investigated. 165 consisted of retrospective analyses of banked tissue and an additional 51 were from patients enrolled in a phase 2 study of figitumumab (F), a monoclonal antibody against the IGF-IR, in stage IIIb/IV NSCLC. Biomarkers assessed included IGF-IR, EGFR, IGF-2, IGF-2R, IRS-1, IRS-2, vimentin and E-cadherin. Sub-cellular localization of IRS-1 and phosphorylation levels of MAPK and Akt1 were also analyzed. Results IGF-IR was differentially expressed across histological subtypes (P=0.04), with highest levels observed in squamous cell tumors. Elevated IGF-IR expression was also observed in a small number of squamous cell tumors responding to chemotherapy combined with F (p=0.008). Since no other biomarker/response interaction was observed using classical histological sub-typing, a molecular approach was undertaken to segment NSCLC into mechanism-based subpopulations. Principal component analysis and unsupervised Bayesian clustering identified 3 NSCLC subsets that resembled the steps of the epithelial-to-mesenchymal transition: E-cadherin high/IRS-1 low (Epithelial-like), E-cadherin intermediate/IRS-1 high (Transitional) and E-cadherin low/IRS-1 low (Mesenchymal-like). Several markers of the IGF-IR pathway were over-expressed in the Transitional subset. Furthermore, a higher response rate to the combination of chemotherapy and F was observed in Transitional tumors (71%) compared to those in the Mesenchymal-like subset (32%, p=0.03). Only one Epithelial-like tumor was identified in the phase 2 study, suggesting that advanced NSCLC has undergone significant de-differentiation at diagnosis. Conclusion NSCLC comprises molecular subsets with differential sensitivity to IGF-IR inhibition. PMID:20670944

GenSSI 2.0: multi-experiment structural identifiability analysis of SBML models.

PubMed

Ligon, Thomas S; Fröhlich, Fabian; Chis, Oana T; Banga, Julio R; Balsa-Canto, Eva; Hasenauer, Jan

2018-04-15

Mathematical modeling using ordinary differential equations is used in systems biology to improve the understanding of dynamic biological processes. The parameters of ordinary differential equation models are usually estimated from experimental data. To analyze a priori the uniqueness of the solution of the estimation problem, structural identifiability analysis methods have been developed. We introduce GenSSI 2.0, an advancement of the software toolbox GenSSI (Generating Series for testing Structural Identifiability). GenSSI 2.0 is the first toolbox for structural identifiability analysis to implement Systems Biology Markup Language import, state/parameter transformations and multi-experiment structural identifiability analysis. In addition, GenSSI 2.0 supports a range of MATLAB versions and is computationally more efficient than its previous version, enabling the analysis of more complex models. GenSSI 2.0 is an open-source MATLAB toolbox and available at https://github.com/genssi-developer/GenSSI. thomas.ligon@physik.uni-muenchen.de or jan.hasenauer@helmholtz-muenchen.de. Supplementary data are available at Bioinformatics online.

Regression Analysis to Identify Factors Associated with Urinary Iodine Concentration at the Sub-National Level in India, Ghana, and Senegal

PubMed Central

Knowles, Jacky; Kupka, Roland; Dumble, Sam; Garrett, Greg S.; Pandav, Chandrakant S.; Yadav, Kapil; Touré, Ndeye Khady; Foriwa Amoaful, Esi; Gorstein, Jonathan

2018-01-01

Single and multiple variable regression analyses were conducted using data from stratified, cluster sample design, iodine surveys in India, Ghana, and Senegal to identify factors associated with urinary iodine concentration (UIC) among women of reproductive age (WRA) at the national and sub-national level. Subjects were survey household respondents, typically WRA. For all three countries, UIC was significantly different (p < 0.05) by household salt iodine category. Other significant differences were by strata and by household vulnerability to poverty in India and Ghana. In multiple variable regression analysis, UIC was significantly associated with strata and household salt iodine category in India and Ghana (p < 0.001). Estimated UIC was 1.6 (95% confidence intervals (CI) 1.3, 2.0) times higher (India) and 1.4 (95% CI 1.2, 1.6) times higher (Ghana) among WRA from households using adequately iodised salt than among WRA from households using non-iodised salt. Other significant associations with UIC were found in India, with having heard of iodine deficiency (1.2 times higher; CI 1.1, 1.3; p < 0.001) and having improved dietary diversity (1.1 times higher, CI 1.0, 1.2; p = 0.015); and in Ghana, with the level of tomato paste consumption the previous week (p = 0.029) (UIC for highest consumption level was 1.2 times lowest level; CI 1.1, 1.4). No significant associations were found in Senegal. Sub-national data on iodine status are required to assess equity of access to optimal iodine intake and to develop strategic responses as needed. PMID:29690505

Risk factors for gastric cancer in Latin-America: a meta-analysis

PubMed Central

Bonequi, Patricia; Meneses-González, Fernando; Correa, Pelayo; Rabkin, Charles S.; Camargo, M. Constanza

2013-01-01

Background Latin America has among the highest gastric cancer incidence rates in the world, for reasons that are still unknown. In order to identify region-specific risk factors for gastric cancer, we conducted a meta-analysis summarizing published literature. Methods Searches of PubMed and regional databases for relevant studies published up to December 2011 yielded a total of 29 independent case-control studies. We calculated summary odds ratios (OR) for risk factors reported in at least five studies, including socioeconomic status (education), lifestyle habits (smoking and alcohol use), dietary factors (consumption of fruits, total vegetables, green vegetables, chili pepper, total meat, processed meat, red meat, fish and salt) and host genetic variants (IL1B-511T, IL1B-31C, IL1RN*2, TNFA-308A, TP53 codon 72 Arg and GSTM1 null). Study-specific ORs were extracted and summarized using random-effects models. Results Chili pepper was the only region-specific factor reported in at least five studies. Consistent with multifactorial pathogenesis, smoking, alcohol use, high consumption of red meat or processed meat, excessive salt intake and carriage of IL1RN*2 were each associated with a moderate increase in gastric cancer risk. Conversely, higher levels of education, fruit consumption, and total vegetable consumption were each associated with a moderately decreased risk. The other exposures were not significantly associated. No prospective study data were identified. Conclusion Risk factor associations for gastric cancer in Latin America are based on case-control comparisons that have uncertain reliability, particularly with regard to diet; the specific factors identified and their magnitudes of association are largely similar to those globally recognized. Future studies should emphasize prospective data collection and focus on region-specific exposures that may explain high gastric cancer risk. PMID:23224270

Analysis of risk factors for cluster behavior of dental implant failures.

PubMed

Chrcanovic, Bruno Ramos; Kisch, Jenö; Albrektsson, Tomas; Wennerberg, Ann

2017-08-01

Some studies indicated that implant failures are commonly concentrated in few patients. To identify and analyze cluster behavior of dental implant failures among subjects of a retrospective study. This retrospective study included patients receiving at least three implants only. Patients presenting at least three implant failures were classified as presenting a cluster behavior. Univariate and multivariate logistic regression models and generalized estimating equations analysis evaluated the effect of explanatory variables on the cluster behavior. There were 1406 patients with three or more implants (8337 implants, 592 failures). Sixty-seven (4.77%) patients presented cluster behavior, with 56.8% of all implant failures. The intake of antidepressants and bruxism were identified as potential negative factors exerting a statistically significant influence on a cluster behavior at the patient-level. The negative factors at the implant-level were turned implants, short implants, poor bone quality, age of the patient, the intake of medicaments to reduce the acid gastric production, smoking, and bruxism. A cluster pattern among patients with implant failure is highly probable. Factors of interest as predictors for implant failures could be a number of systemic and local factors, although a direct causal relationship cannot be ascertained. © 2017 Wiley Periodicals, Inc.

The Animadora Project: Identifying factors related to the promotion of physical activity among Mexican Americans with diabetes

PubMed Central

Ingram, Maia; Ruis, Maricruz; Mayorga, Maria Theresa; Rosales, Cecilia

2015-01-01

Purpose There is a dearth of information about factors related to physical activity among Mexican Americans with diabetes. Self efficacy and social support are associated with physical activity, however little is known about their role within different cultural groups. Design Focus groups were used to identify factors that motivate walking. Setting Two Mexican American communities located in Tucson, Arizona. Subjects Individuals who attended diabetes education. Intervention A community-based provider organized walking groups with people who previously attended diabetes classes. Walkers participated in focus groups exploring themes related to their experience. Measures Self efficacy, social support, and collective efficacy. Grounded theory was used to analyze focus group results using two rounds of analysis; the first identifying references to self efficacy and social support and the second adding collective efficacy as a theoretical basis for walking. Results Among 43 eligible participants, 20 participated in focus groups. Social support was expressed as commitment and companionship. Walkers demonstrated a high level of self efficacy for walking. Development of group identity/social cohesion was also a motivator to walk. Collective efficacy emerged as an applicable theoretical model encompassing these themes and their interrelationship. Conclusion Collective efficacy, or the belief that the group can improve their lives through collective effort, is a viable theoretical construct in the development of physical activity interventions targeting Mexican Americans with diabetes. PMID:19601479

Risk Factors for Child Malnutrition in Bangladesh: A Multilevel Analysis of a Nationwide Population-Based Survey.

PubMed

Chowdhury, Mohammad Rocky Khan; Rahman, Mohammad Shafiur; Khan, Mohammad Mubarak Hossain; Mondal, Mohammad Nazrul Islam; Rahman, Mohammad Mosiur; Billah, Baki

2016-05-01

To identify the prevalence and risk factors of child malnutrition in Bangladesh. Data was extracted from the Bangladesh Demographic Health Survey (2011). The outcome measures were stunting, wasting, and underweight. χ(2) analysis was performed to find the association of outcome variables with selected factors. Multilevel logistic regression models with a random intercept at each of the household and community levels were used to identify the risk factors of stunting, wasting, and underweight. From the 2011 survey, 7568 children less than 5 years of age were included in the current analysis. The overall prevalence of stunting, wasting, and underweight was 41.3% (95% CI 39.0-42.9). The χ(2) test and multilevel logistic regression analysis showed that the variables age, sex, mother's body mass index, mother's educational status, father's educational status, place of residence, socioeconomic status, community status, religion, region of residence, and food security are significant factors of child malnutrition. Children with poor socioeconomic and community status were at higher risk of malnutrition. Children from food insecure families were more likely to be malnourished. Significant community- and household-level variations were found. The prevalence of child malnutrition is still high in Bangladesh, and the risk was assessed at several multilevel factors. Therefore, prevention of malnutrition should be given top priority as a major public health intervention. Copyright © 2016 Elsevier Inc. All rights reserved.

Community violence, protective factors, and adolescent mental health: a profile analysis.

PubMed

Copeland-Linder, Nikeea; Lambert, Sharon F; Ialongo, Nicholas S

2010-01-01

This study examined interrelationships among community violence exposure, protective factors, and mental health in a sample of urban, predominantly African American adolescents (N = 504). Latent Profile Analysis was conducted to identify profiles of adolescents based on a combination of community violence exposure, self-worth, parental monitoring, and parental involvement and to examine whether these profiles differentially predict adolescents' depressive symptoms and aggressive behavior. Three classes were identified-a vulnerable class, a moderate risk/medium protection class, and a moderate risk/high protection class. The classes differentially predicted depressive symptoms but not aggressive behavior for boys and girls. The class with the highest community violence exposure also had the lowest self-worth.

Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS)

NASA Technical Reports Server (NTRS)

Alexander, Tiffaney Miller

2017-01-01

Research results have shown that more than half of aviation, aerospace and aeronautics mishaps incidents are attributed to human error. As a part of Safety within space exploration ground processing operations, the identification and/or classification of underlying contributors and causes of human error must be identified, in order to manage human error. This research provides a framework and methodology using the Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS), as an analysis tool to identify contributing factors, their impact on human error events, and predict the Human Error probabilities (HEPs) of future occurrences. This research methodology was applied (retrospectively) to six (6) NASA ground processing operations scenarios and thirty (30) years of Launch Vehicle related mishap data. This modifiable framework can be used and followed by other space and similar complex operations.

Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS)

NASA Technical Reports Server (NTRS)

Alexander, Tiffaney Miller

2017-01-01

Research results have shown that more than half of aviation, aerospace and aeronautics mishaps/incidents are attributed to human error. As a part of Safety within space exploration ground processing operations, the identification and/or classification of underlying contributors and causes of human error must be identified, in order to manage human error. This research provides a framework and methodology using the Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS), as an analysis tool to identify contributing factors, their impact on human error events, and predict the Human Error probabilities (HEPs) of future occurrences. This research methodology was applied (retrospectively) to six (6) NASA ground processing operations scenarios and thirty (30) years of Launch Vehicle related mishap data. This modifiable framework can be used and followed by other space and similar complex operations.

Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS)

NASA Technical Reports Server (NTRS)

Alexander, Tiffaney Miller

2017-01-01

Research results have shown that more than half of aviation, aerospace and aeronautics mishaps incidents are attributed to human error. As a part of Quality within space exploration ground processing operations, the identification and or classification of underlying contributors and causes of human error must be identified, in order to manage human error.This presentation will provide a framework and methodology using the Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS), as an analysis tool to identify contributing factors, their impact on human error events, and predict the Human Error probabilities (HEPs) of future occurrences. This research methodology was applied (retrospectively) to six (6) NASA ground processing operations scenarios and thirty (30) years of Launch Vehicle related mishap data. This modifiable framework can be used and followed by other space and similar complex operations.

What is hypomania? Tetrachoric factor analysis and kernel estimation of DSM-IV hypomanic symptoms.

PubMed

Benazzi, Franco

2009-11-01

The DSM-IV definition of hypomania, which relies on clinical consensus and historical tradition, includes several "nonspecific" symptoms. The aim of this study was to identify the core symptoms of DSM-IV hypomania. In an outpatient private practice, 266 bipolar II disorder (BP-II) and 138 major depressive disorder (MDD) remitted patients were interviewed by a bipolar-trained psychiatrist, for different study goals. Patients were questioned, using the Structured Clinical Interview for DSM-IV, about the most common symptoms and duration of recent threshold and subthreshold hypomanic episodes. Data were recorded between 2002 and 2006. Four different samples, assessed with the same methodology, were pooled for the present analyses. Tetrachoric factor analysis was used to identify core hypomanic symptoms. Distribution of symptoms by kernel estimation was inspected for bimodality. Validity of core hypomania was tested by receiver operating characteristic (ROC) analysis. The distribution of subthreshold and threshold hypomanic episodes did not show bimodality. Tetrachoric factor analysis found 2 uncorrelated factors: factor 1 included the "classic" symptoms elevated mood, inflated self-esteem, decreased need for sleep, talkativeness, and increase in goal-directed activity (overactivity); factor 2 included the "nonspecific" symptoms irritable mood, racing/crowded thoughts, and distractibility. Factor 1 discriminatory accuracy for distinguishing BP-II versus MDD was high (ROC area = 0.94). The distribution of the 5-symptom episodes of factor 1 showed clear-cut bimodality. Similar results were found for episodes limited to 3 behavioral symptoms of factor 1 (decreased need for sleep, talkativeness, and overactivity) and 4 behavioral symptoms of factor 1 (adding elevated mood), with high discriminatory accuracy. A core, categorical DSM-IV hypomania was found that included 3 to 5 symptoms, ie, behavioral symptoms and elevated mood. Behavioral symptoms (overactivity domain

Exploratory factor analysis of the functional movement screen in elite athletes.

PubMed

Li, Yongming; Wang, Xiong; Chen, Xiaoping; Dai, Boyi

2015-01-01

The functional movement screen is developed to examine individuals' movement patterns through 7 functional tasks. The purpose of this study was to identify the internal consistency and factor structure of the 7 tasks of the functional movement screen in elite athletes; 290 elite athletes from a variety of Chinese national teams were assessed using the functional movement screen. Cronbach's alpha was calculated for the scores of the 7 tasks. Exploratory factor analysis was performed to explore the factor structure of the functional movement screen. The mean and standard deviation of the sum score were 15.2 ± 3.0. A low Cronbach's alpha (0.58) was found for the scores of the 7 tasks. Exploratory factor analysis extracted 2 factors with eigenvalues greater than 1, and these 2 factors explained 47.3% of the total variance. The first factor had a high loading on the rotatory stability (loading = 0.99) and low loadings on the other 6 tasks (loading range: 0.04-0.34). The second factor had high loadings on the deep squat, hurdle step and inline lunge (loading range: 0.46-0.61) and low loadings on the other 3 tasks (loading range: 0.12-0.32). The 7 tasks of the functional movement screen had low internal consistency and were not indicators of a single factor. Evidence for unidimensionality was not found for the functional movement screen in elite athletes. More attention should be paid to the score of each task rather than the sum score when we interpret the functional movement screen scores.

Identifying RNA splicing factors using IFT genes in Chlamydomonas reinhardtii.

PubMed

Lin, Huawen; Zhang, Zhengyan; Iomini, Carlo; Dutcher, Susan K

2018-03-01

Intraflagellar transport moves proteins in and out of flagella/cilia and it is essential for the assembly of these organelles. Using whole-genome sequencing, we identified splice site mutations in two IFT genes, IFT81 ( fla9 ) and IFT121 ( ift121-2 ), which lead to flagellar assembly defects in the unicellular green alga Chlamydomonas reinhardtii The splicing defects in these ift mutants are partially corrected by mutations in two conserved spliceosome proteins, DGR14 and FRA10. We identified a dgr14 deletion mutant, which suppresses the 3' splice site mutation in IFT81 , and a frameshift mutant of FRA10 , which suppresses the 5' splice site mutation in IFT121 Surprisingly, we found dgr14-1 and fra10 mutations suppress both splice site mutations. We suggest these two proteins are involved in facilitating splice site recognition/interaction; in their absence some splice site mutations are tolerated. Nonsense mutations in SMG1 , which is involved in nonsense-mediated decay, lead to accumulation of aberrant transcripts and partial restoration of flagellar assembly in the ift mutants. The high density of introns and the conservation of noncore splicing factors, together with the ease of scoring the ift mutant phenotype, make Chlamydomonas an attractive organism to identify new proteins involved in splicing through suppressor screening. © 2018 The Authors.

Modifiable risk factors for schizophrenia and autism--shared risk factors impacting on brain development.

PubMed

Hamlyn, Jess; Duhig, Michael; McGrath, John; Scott, James

2013-05-01

Schizophrenia and autism are two poorly understood clinical syndromes that differ in age of onset and clinical profile. However, recent genetic and epidemiological research suggests that these two neurodevelopmental disorders share certain risk factors. The aims of this review are to describe modifiable risk factors that have been identified in both disorders, and, where available, collate salient systematic reviews and meta-analyses that have examined shared risk factors. Based on searches of Medline, Embase and PsycINFO, inspection of review articles and expert opinion, we first compiled a set of candidate modifiable risk factors associated with autism. Where available, we next collated systematic-reviews (with or without meta-analyses) related to modifiable risk factors associated with both autism and schizophrenia. We identified three modifiable risk factors that have been examined in systematic reviews for both autism and schizophrenia. Advanced paternal age was reported as a risk factor for schizophrenia in a single meta-analysis and as a risk factor in two meta-analyses for autism. With respect to pregnancy and birth complications, for autism one meta-analysis identified maternal diabetes and bleeding during pregnancy as risks factors for autism whilst a meta-analysis of eight studies identified obstetric complications as a risk factor for schizophrenia. Migrant status was identified as a risk factor for both autism and schizophrenia. Two separate meta-analyses were identified for each disorder. Despite distinct clinical phenotypes, the evidence suggests that at least some non-genetic risk factors are shared between these two syndromes. In particular, exposure to drugs, nutritional excesses or deficiencies and infectious agents lend themselves to public health interventions. Studies are now needed to quantify any increase in risk of either autism or schizophrenia that is associated with these modifiable environmental factors. Copyright © 2012 Elsevier Inc

Genome-wide RNAi screening identifies host restriction factors critical for in vivo AAV transduction

PubMed Central

Mano, Miguel; Ippodrino, Rudy; Zentilin, Lorena; Zacchigna, Serena; Giacca, Mauro

2015-01-01

Viral vectors based on the adeno-associated virus (AAV) hold great promise for in vivo gene transfer; several unknowns, however, still limit the vectors’ broader and more efficient application. Here, we report the results of a high-throughput, whole-genome siRNA screening aimed at identifying cellular factors regulating AAV transduction. We identified 1,483 genes affecting vector efficiency more than 4-fold and up to 50-fold, either negatively or positively. Most of these factors have not previously been associated to AAV infection. The most effective siRNAs were independent from the virus serotype or analyzed cell type and were equally evident for single-stranded and self-complementary AAV vectors. A common characteristic of the most effective siRNAs was the induction of cellular DNA damage and activation of a cell cycle checkpoint. This information can be exploited for the development of more efficient AAV-based gene delivery procedures. Administration of the most effective siRNAs identified by the screening to the liver significantly improved in vivo AAV transduction efficiency. PMID:26305933

Dimensional Model for Estimating Factors influencing Childhood Obesity: Path Analysis Based Modeling

PubMed Central

Kheirollahpour, Maryam; Shohaimi, Shamarina

2014-01-01

The main objective of this study is to identify and develop a comprehensive model which estimates and evaluates the overall relations among the factors that lead to weight gain in children by using structural equation modeling. The proposed models in this study explore the connection among the socioeconomic status of the family, parental feeding practice, and physical activity. Six structural models were tested to identify the direct and indirect relationship between the socioeconomic status and parental feeding practice general level of physical activity, and weight status of children. Finally, a comprehensive model was devised to show how these factors relate to each other as well as to the body mass index (BMI) of the children simultaneously. Concerning the methodology of the current study, confirmatory factor analysis (CFA) was applied to reveal the hidden (secondary) effect of socioeconomic factors on feeding practice and ultimately on the weight status of the children and also to determine the degree of model fit. The comprehensive structural model tested in this study suggested that there are significant direct and indirect relationships among variables of interest. Moreover, the results suggest that parental feeding practice and physical activity are mediators in the structural model. PMID:25097878

Identifying inaccuracy of MS Project using system analysis

NASA Astrophysics Data System (ADS)

Fachrurrazi; Husin, Saiful; Malahayati, Nurul; Irzaidi

2018-05-01

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

Identifying the causes of water crises: A configurational frequency analysis of 22 basins world wide

NASA Astrophysics Data System (ADS)

Srinivasan, V.; Gorelick, S.; Lambin, E.; Rozelle, S.; Thompson, B.

2010-12-01

Freshwater "scarcity" has been identified as being a major problem world-wide, but it is surprisingly hard to assess if water is truly scarce at a global or even regional scale. Most empirical water research remains location specific. Characterizing water problems, transferring lessons across regions, to develop a synthesized global view of water issues remains a challenge. In this study we attempt a systematic understanding of water problems across regions. We compared case studies of basins across different regions of the world using configurational frequency analysis. Because water crises are multi-symptom and multi-causal, a major challenge was to categorize water problems so as to make comparisons across cases meaningful. In this study, we focused strictly on water unsustainability, viz. the inability to sustain current levels of the anthropogenic (drinking water, food, power, livelihood) and natural (aquatic species, wetlands) into the future. For each case, the causes of three outcome variables, groundwater declines, surface water declines and aquatic ecosystem declines, were classified and coded. We conducted a meta-analysis in which clusters of peer-reviewed papers by interdisciplinary teams were considered to ensure that the results were not biased towards factors privileged by any one discipline. Based on our final sample of 22 case study river basins, some clear patterns emerged. The meta-analysis suggests that water resources managers have long overemphasized the factors governing supply of water resources and while insufficient attention has been paid to the factors driving demand. Overall, uncontrolled increase in demand was twice as frequent as declines in availability due to climate change or decreased recharge. Moreover, groundwater and surface water declines showed distinct causal pathways. Uncontrolled increases in demand due to lack of credible enforcement were a key factor driving groundwater declines; while increased upstream abstractions

A multi-factor GIS method to identify optimal geographic locations for electric vehicle (EV) charging stations

NASA Astrophysics Data System (ADS)

Zhang, Yongqin; Iman, Kory

2018-05-01

Fuel-based transportation is one of the major contributors to poor air quality in the United States. Electric Vehicle (EV) is potentially the cleanest transportation technology to our environment. This research developed a spatial suitability model to identify optimal geographic locations for installing EV charging stations for travelling public. The model takes into account a variety of positive and negative factors to identify prime locations for installing EV charging stations in Wasatch Front, Utah, where automobile emission causes severe air pollution due to atmospheric inversion condition near the valley floor. A walkable factor grid was created to store index scores from input factor layers to determine prime locations. 27 input factors including land use, demographics, employment centers etc. were analyzed. Each factor layer was analyzed to produce a summary statistic table to determine the site suitability. Potential locations that exhibit high EV charging usage were identified and scored. A hot spot map was created to demonstrate high, moderate, and low suitability areas for installing EV charging stations. A spatially well distributed EV charging system was then developed, aiming to reduce "range anxiety" from traveling public. This spatial methodology addresses the complex problem of locating and establishing a robust EV charging station infrastructure for decision makers to build a clean transportation infrastructure, and eventually improve environment pollution.

Quantitative analysis of titanium-induced artifacts and correlated factors during micro-CT scanning.

PubMed

Li, Jun Yuan; Pow, Edmond Ho Nang; Zheng, Li Wu; Ma, Li; Kwong, Dora Lai Wan; Cheung, Lim Kwong

2014-04-01

To investigate the impact of cover screw, resin embedment, and implant angulation on artifact of microcomputed tomography (micro-CT) scanning for implant. A total of twelve implants were randomly divided into 4 groups: (i) implant only; (ii) implant with cover screw; (iii) implant with resin embedment; and (iv) implants with cover screw and resin embedment. Implants angulation at 0°, 45°, and 90° were scanned by micro-CT. Images were assessed, and the ratio of artifact volume to total volume (AV/TV) was calculated. A multiple regression analysis in stepwise model was used to determine the significance of different factors. One-way ANOVA was performed to identify which combination of factors could minimize the artifact. In the regression analysis, implant angulation was identified as the best predictor for artifact among the factors (P < 0.001). Resin embedment also had significant effect on artifact volume (P = 0.028), while cover screw had not (P > 0.05). Non-embedded implants with the axis parallel to X-ray source of micro-CT produced minimal artifact. Implant angulation and resin embedment affected the artifact volume of micro-CT scanning for implant, while cover screw did not. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Factor Analysis of Drawings: Application to college student models of the greenhouse effect

NASA Astrophysics Data System (ADS)

Libarkin, Julie C.; Thomas, Stephen R.; Ording, Gabriel

2015-09-01

Exploratory factor analysis was used to identify models underlying drawings of the greenhouse effect made by over 200 entering university freshmen. Initial content analysis allowed deconstruction of drawings into salient features, with grouping of these features via factor analysis. A resulting 4-factor solution explains 62% of the data variance, suggesting that 4 archetype models of the greenhouse effect dominate thinking within this population. Factor scores, indicating the extent to which each student's drawing aligned with representative models, were compared to performance on conceptual understanding and attitudes measures, demographics, and non-cognitive features of drawings. Student drawings were also compared to drawings made by scientists to ascertain the extent to which models reflect more sophisticated and accurate models. Results indicate that student and scientist drawings share some similarities, most notably the presence of some features of the most sophisticated non-scientific model held among the study population. Prior knowledge, prior attitudes, gender, and non-cognitive components are also predictive of an individual student's model. This work presents a new technique for analyzing drawings, with general implications for the use of drawings in investigating student conceptions.

Identifying Environmental Risk Factors of Cholera in a Coastal Area with Geospatial Technologies

PubMed Central

Xu, Min; Cao, Chunxiang; Wang, Duochun; Kan, Biao

2014-01-01

Satellites contribute significantly to environmental quality and public health. Environmental factors are important indicators for the prediction of disease outbreaks. This study reveals the environmental factors associated with cholera in Zhejiang, a coastal province of China, using both Remote Sensing (RS) and Geographic information System (GIS). The analysis validated the correlation between the indirect satellite measurements of sea surface temperature (SST), sea surface height (SSH) and ocean chlorophyll concentration (OCC) and the local cholera magnitude based on a ten-year monthly data from the year 1999 to 2008. Cholera magnitude has been strongly affected by the concurrent variables of SST and SSH, while OCC has a one-month time lag effect. A cholera prediction model has been established based on the sea environmental factors. The results of hot spot analysis showed the local cholera magnitude in counties significantly associated with the estuaries and rivers. PMID:25551518

Identifying environmental risk factors of cholera in a coastal area with geospatial technologies.

PubMed

Xu, Min; Cao, Chunxiang; Wang, Duochun; Kan, Biao

2014-12-29

Satellites contribute significantly to environmental quality and public health. Environmental factors are important indicators for the prediction of disease outbreaks. This study reveals the environmental factors associated with cholera in Zhejiang, a coastal province of China, using both Remote Sensing (RS) and Geographic information System (GIS). The analysis validated the correlation between the indirect satellite measurements of sea surface temperature (SST), sea surface height (SSH) and ocean chlorophyll concentration (OCC) and the local cholera magnitude based on a ten-year monthly data from the year 1999 to 2008. Cholera magnitude has been strongly affected by the concurrent variables of SST and SSH, while OCC has a one-month time lag effect. A cholera prediction model has been established based on the sea environmental factors. The results of hot spot analysis showed the local cholera magnitude in counties significantly associated with the estuaries and rivers.

Meta-analysis of the predictive factors of postpartum fatigue.

PubMed

Badr, Hanan A; Zauszniewski, Jaclene A

2017-08-01

Nearly 64% of new mothers are affected by fatigue during the postpartum period, making it the most common problem that a woman faces as she adapts to motherhood. Postpartum fatigue can lead to serious negative effects on the mother's health and the newborn's development and interfere with mother-infant interaction. The aim of this meta-analysis was to identify predictive factors of postpartum fatigue and to document the magnitude of their effects using effect sizes. We used two search engines, PubMed and Google Scholar, to identify studies that met three inclusion criteria: (a) the article was written in English, (b) the article studied the predictive factors of postpartum fatigue, and (c) the article included information about the validity and reliability of the instruments used in the research. Nine articles met these inclusion criteria. The direction and strength of correlation coefficients between predictive factors and postpartum fatigue were examined across the studies to determine their effect sizes. Measurement of predictor variables occurred from 3days to 6months postpartum. Correlations reported between predictive factors and postpartum fatigue were as follows: small effect size (r range =0.10 to 0.29) for education level, age, postpartum hemorrhage, infection, and child care difficulties; medium effect size (r range =0.30 to 0.49) for physiological illness, low ferritin level, low hemoglobin level, sleeping problems, stress and anxiety, and breastfeeding problems; and large effect size (r range =0.50+) for depression. Postpartum fatigue is a common condition that can lead to serious health problems for a new mother and her newborn. Therefore, increased knowledge concerning factors that influence the onset of postpartum fatigue is needed for early identification of new mothers who may be at risk. Appropriate treatments, interventions, information, and support can then be initiated to prevent or minimize the postpartum fatigue. Copyright © 2017 Elsevier

Factor analysis of financial and operational performance measures of non-profit hospitals.

PubMed

Das, Dhiman

2009-01-01

To understand the important dimensions of the financial and operational performance of non-profit hospitals. Secondary data for non-profit US hospitals between 1996 and 2004. I use iterative principal factor analysis of hospitals' financial and operational ratios for each year of the study. For factor interpretation, I use oblique rotation. Financial ratios were created using cost report data from HCRIS 2552-96 available from the Centers for Medicaid & Medicare Services (CMS). I identify five factors--capital structure, profitability, activity, liquidity, and an operational factor--that explain most of the variation in the performance of non-profit hospitals. I also find that capital structure is more important than profitability in determining the performance of these hospitals. The importance of capital structure highlights a significant shift in the organization of the non-profit hospitals' finances.

Risk factors for pedicled flap necrosis in hand soft tissue reconstruction: a multivariate logistic regression analysis.

PubMed

Gong, Xu; Cui, Jianli; Jiang, Ziping; Lu, Laijin; Li, Xiucun

2018-03-01

Few clinical retrospective studies have reported the risk factors of pedicled flap necrosis in hand soft tissue reconstruction. The aim of this study was to identify non-technical risk factors associated with pedicled flap perioperative necrosis in hand soft tissue reconstruction via a multivariate logistic regression analysis. For patients with hand soft tissue reconstruction, we carefully reviewed hospital records and identified 163 patients who met the inclusion criteria. The characteristics of these patients, flap transfer procedures and postoperative complications were recorded. Eleven predictors were identified. The correlations between pedicled flap necrosis and risk factors were analysed using a logistic regression model. Of 163 skin flaps, 125 flaps survived completely without any complications. The pedicled flap necrosis rate in hands was 11.04%, which included partial flap necrosis (7.36%) and total flap necrosis (3.68%). Soft tissue defects in fingers were noted in 68.10% of all cases. The logistic regression analysis indicated that the soft tissue defect site (P = 0.046, odds ratio (OR) = 0.079, confidence interval (CI) (0.006, 0.959)), flap size (P = 0.020, OR = 1.024, CI (1.004, 1.045)) and postoperative wound infection (P < 0.001, OR = 17.407, CI (3.821, 79.303)) were statistically significant risk factors for pedicled flap necrosis of the hand. Soft tissue defect site, flap size and postoperative wound infection were risk factors associated with pedicled flap necrosis in hand soft tissue defect reconstruction. © 2017 Royal Australasian College of Surgeons.

Success Factors of European Syndromic Surveillance Systems: A Worked Example of Applying Qualitative Comparative Analysis.

PubMed

Ziemann, Alexandra; Fouillet, Anne; Brand, Helmut; Krafft, Thomas

2016-01-01

Syndromic surveillance aims at augmenting traditional public health surveillance with timely information. To gain a head start, it mainly analyses existing data such as from web searches or patient records. Despite the setup of many syndromic surveillance systems, there is still much doubt about the benefit of the approach. There are diverse interactions between performance indicators such as timeliness and various system characteristics. This makes the performance assessment of syndromic surveillance systems a complex endeavour. We assessed if the comparison of several syndromic surveillance systems through Qualitative Comparative Analysis helps to evaluate performance and identify key success factors. We compiled case-based, mixed data on performance and characteristics of 19 syndromic surveillance systems in Europe from scientific and grey literature and from site visits. We identified success factors by applying crisp-set Qualitative Comparative Analysis. We focused on two main areas of syndromic surveillance application: seasonal influenza surveillance and situational awareness during different types of potentially health threatening events. We found that syndromic surveillance systems might detect the onset or peak of seasonal influenza earlier if they analyse non-clinical data sources. Timely situational awareness during different types of events is supported by an automated syndromic surveillance system capable of analysing multiple syndromes. To our surprise, the analysis of multiple data sources was no key success factor for situational awareness. We suggest to consider these key success factors when designing or further developing syndromic surveillance systems. Qualitative Comparative Analysis helped interpreting complex, mixed data on small-N cases and resulted in concrete and practically relevant findings.

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

PubMed

Saghazadeh, Amene; Rezaei, Nima

2017-04-01

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

The in vitro real-time oscillation monitoring system identifies potential entrainment factors for circadian clocks

PubMed Central

Nakahata, Yasukazu; Akashi, Makoto; Trcka, Daniel; Yasuda, Akio; Takumi, Toru

2006-01-01

Background Circadian rhythms are endogenous, self-sustained oscillations with approximately 24-hr rhythmicity that are manifested in various physiological and metabolic processes. The circadian organization of these processes in mammals is governed by the master oscillator within the suprachiasmatic nuclei (SCN) of the hypothalamus. Recent findings revealed that circadian oscillators exist in most organs, tissues, and even in immortalized cells, and that the oscillators in peripheral tissues are likely to be coordinated by SCN, the master oscillator. Some candidates for endogenous entrainment factors have sporadically been reported, however, their details remain mainly obscure. Results We developed the in vitro real-time oscillation monitoring system (IV-ROMS) by measuring the activity of luciferase coupled to the oscillatory gene promoter using photomultiplier tubes and applied this system to screen and identify factors able to influence circadian rhythmicity. Using this IV-ROMS as the primary screening of entrainment factors for circadian clocks, we identified 12 candidates as the potential entrainment factor in a total of 299 peptides and bioactive lipids. Among them, four candidates (endothelin-1, all-trans retinoic acid, 9-cis retinoic acid, and 13-cis retinoic acid) have already been reported as the entrainment factors in vivo and in vitro. We demonstrated that one of the novel candidates, 15-deoxy-Δ12,14-prostaglandin J2 (15d-PGJ2), a natural ligand of the peroxisome proliferator-activated receptor-γ (PPAR-γ), triggers the rhythmic expression of endogenous clock genes in NIH3T3 cells. Furthermore, we showed that 15d-PGJ2 transiently induces Cry1, Cry2, and Rorα mRNA expressions and that 15d-PGJ2-induced entrainment signaling pathway is PPAR-γ – and MAPKs (ERK, JNK, p38MAPK)-independent. Conclusion Here, we identified 15d-PGJ2 as an entrainment factor in vitro. Using our developed IV-ROMS to screen 299 compounds, we found eight novel and four known

Human factors evaluation of teletherapy: Function and task analysis. Volume 2

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

Kaye, R.D.; Henriksen, K.; Jones, R.

1995-07-01

As a treatment methodology, teletherapy selectively destroys cancerous and other tissue by exposure to an external beam of ionizing radiation. Sources of radiation are either a radioactive isotope, typically Cobalt-60 (Co-60), or a linear accelerator. Records maintained by the NRC have identified instances of teletherapy misadministration where the delivered radiation dose has differed from the radiation prescription (e.g., instances where fractions were delivered to the wrong patient, to the wrong body part, or were too great or too little with respect to the defined treatment volume). Both human error and machine malfunction have led to misadministrations. Effective and safe treatmentmore » requires a concern for precision and consistency of human-human and human-machine interactions throughout the course of therapy. The present study is the first part of a series of human factors evaluations for identifying the root causes that lead to human error in the teletherapy environment. The human factors evaluations included: (1) a function and task analysis of teletherapy activities, (2) an evaluation of the human-system interfaces, (3) an evaluation of procedures used by teletherapy staff, (4) an evaluation of the training and qualifications of treatment staff (excluding the oncologists), (5) an evaluation of organizational practices and policies, and (6) an identification of problems and alternative approaches for NRC and industry attention. The present report addresses the function and task analysis of teletherapy activities and provides the foundation for the conduct of the subsequent evaluations. The report includes sections on background, methodology, a description of the function and task analysis, and use of the task analysis findings for the subsequent tasks. The function and task analysis data base also is included.« less

A meta-analysis of factors affecting trust in human-robot interaction.

PubMed

Hancock, Peter A; Billings, Deborah R; Schaefer, Kristin E; Chen, Jessie Y C; de Visser, Ewart J; Parasuraman, Raja

2011-10-01

We evaluate and quantify the effects of human, robot, and environmental factors on perceived trust in human-robot interaction (HRI). To date, reviews of trust in HRI have been qualitative or descriptive. Our quantitative review provides a fundamental empirical foundation to advance both theory and practice. Meta-analytic methods were applied to the available literature on trust and HRI. A total of 29 empirical studies were collected, of which 10 met the selection criteria for correlational analysis and 11 for experimental analysis. These studies provided 69 correlational and 47 experimental effect sizes. The overall correlational effect size for trust was r = +0.26,with an experimental effect size of d = +0.71. The effects of human, robot, and environmental characteristics were examined with an especial evaluation of the robot dimensions of performance and attribute-based factors. The robot performance and attributes were the largest contributors to the development of trust in HRI. Environmental factors played only a moderate role. Factors related to the robot itself, specifically, its performance, had the greatest current association with trust, and environmental factors were moderately associated. There was little evidence for effects of human-related factors. The findings provide quantitative estimates of human, robot, and environmental factors influencing HRI trust. Specifically, the current summary provides effect size estimates that are useful in establishing design and training guidelines with reference to robot-related factors of HRI trust. Furthermore, results indicate that improper trust calibration may be mitigated by the manipulation of robot design. However, many future research needs are identified.

Independent Pre-Transplant Recipient Cancer Risk Factors after Kidney Transplantation and the Utility of G-Chart Analysis for Clinical Process Control.

PubMed

Schrem, Harald; Schneider, Valentin; Kurok, Marlene; Goldis, Alon; Dreier, Maren; Kaltenborn, Alexander; Gwinner, Wilfried; Barthold, Marc; Liebeneiner, Jan; Winny, Markus; Klempnauer, Jürgen; Kleine, Moritz

2016-01-01

The aim of this study is to identify independent pre-transplant cancer risk factors after kidney transplantation and to assess the utility of G-chart analysis for clinical process control. This may contribute to the improvement of cancer surveillance processes in individual transplant centers. 1655 patients after kidney transplantation at our institution with a total of 9,425 person-years of follow-up were compared retrospectively to the general German population using site-specific standardized-incidence-ratios (SIRs) of observed malignancies. Risk-adjusted multivariable Cox regression was used to identify independent pre-transplant cancer risk factors. G-chart analysis was applied to determine relevant differences in the frequency of cancer occurrences. Cancer incidence rates were almost three times higher as compared to the matched general population (SIR = 2.75; 95%-CI: 2.33-3.21). Significantly increased SIRs were observed for renal cell carcinoma (SIR = 22.46), post-transplant lymphoproliferative disorder (SIR = 8.36), prostate cancer (SIR = 2.22), bladder cancer (SIR = 3.24), thyroid cancer (SIR = 10.13) and melanoma (SIR = 3.08). Independent pre-transplant risk factors for cancer-free survival were age <52.3 years (p = 0.007, Hazard ratio (HR): 0.82), age >62.6 years (p = 0.001, HR: 1.29), polycystic kidney disease other than autosomal dominant polycystic kidney disease (ADPKD) (p = 0.001, HR: 0.68), high body mass index in kg/m2 (p<0.001, HR: 1.04), ADPKD (p = 0.008, HR: 1.26) and diabetic nephropathy (p = 0.004, HR = 1.51). G-chart analysis identified relevant changes in the detection rates of cancer during aftercare with no significant relation to identified risk factors for cancer-free survival (p<0.05). Risk-adapted cancer surveillance combined with prospective G-chart analysis likely improves cancer surveillance schemes by adapting processes to identified risk factors and by using G-chart alarm signals to trigger Kaizen events and audits for root

Factors affecting the retention of nurses. A survival analysis.

PubMed

Alonazi, Noufa A; Omar, Maye A

2013-03-01

To identify and explore factors that mostly influence nurses' turnover and retention, and to estimate the length of employment for nurses in the hospital. This is a retrospective cohort study examining the standard Exit Questionnaires completed by all the female pediatric nurses who joined and left the hospital during the period between January 2006 and October 2010. The Developed Questionnaires where completed by nurses who were still employees in October 2010. The nurses who left the job will be considered as events and the nurses who are still working will be considered as censored. The study took place at the Pediatric Department, Prince Sultan Military Medical City (PSMMC), Riyadh, Saudi Arabia. A total of 254 nurses were included in the study. Most of the nurses left their jobs due to family reasons (39.7%) followed by other reasons (37.3%). Seventy five percent of all the pediatric nurses remained in their jobs, on average, for 2.2 years. Both simple and multivariate analysis indicated a strong positive correlation between length of employment (turnover) and the demographic and organization factors. This study has identified several factors that played a key role in staff retention, which can help in predicting nursing turnover at PSMMC. The findings of this study could help PSMMC and its Nursing Administration, in particular, to understand the seriousness of the high turnover rates, to develop and implement strategies to reduce this problem, and improve the retention of nursing staff.

Transcriptional Network Analysis Identifies BACH1 as a Master Regulator of Breast Cancer Bone Metastasis

PubMed Central

Liang, Yajun; Wu, Heng; Lei, Rong; Chong, Robert A.; Wei, Yong; Lu, Xin; Tagkopoulos, Ilias; Kung, Sun-Yuan; Yang, Qifeng; Hu, Guohong; Kang, Yibin

2012-01-01

The application of functional genomic analysis of breast cancer metastasis has led to the identification of a growing number of organ-specific metastasis genes, which often function in concert to facilitate different steps of the metastatic cascade. However, the gene regulatory network that controls the expression of these metastasis genes remains largely unknown. Here, we demonstrate a computational approach for the deconvolution of transcriptional networks to discover master regulators of breast cancer bone metastasis. Several known regulators of breast cancer bone metastasis such as Smad4 and HIF1 were identified in our analysis. Experimental validation of the networks revealed BACH1, a basic leucine zipper transcription factor, as the common regulator of several functional metastasis genes, including MMP1 and CXCR4. Ectopic expression of BACH1 enhanced the malignance of breast cancer cells, and conversely, BACH1 knockdown significantly reduced bone metastasis. The expression of BACH1 and its target genes was linked to the higher risk of breast cancer recurrence in patients. This study established BACH1 as the master regulator of breast cancer bone metastasis and provided a paradigm to identify molecular determinants in complex pathological processes. PMID:22875853

Meta-Analysis of Genome-Wide Association Studies for Abdominal Aortic Aneurysm Identifies Four New Disease-Specific Risk Loci

PubMed Central

Tromp, Gerard; Kuivaniemi, Helena; Gretarsdottir, Solveig; Baas, Annette F.; Giusti, Betti; Strauss, Ewa; van‘t Hof, Femke N.G.; Webb, Thomas R.; Erdman, Robert; Ritchie, Marylyn D.; Elmore, James R.; Verma, Anurag; Pendergrass, Sarah; Kullo, Iftikhar J.; Ye, Zi; Peissig, Peggy L.; Gottesman, Omri; Verma, Shefali S.; Malinowski, Jennifer; Rasmussen-Torvik, Laura J.; Borthwick, Kenneth M.; Smelser, Diane T.; Crosslin, David R.; de Andrade, Mariza; Ryer, Evan J.; McCarty, Catherine A.; Böttinger, Erwin P.; Pacheco, Jennifer A.; Crawford, Dana C.; Carrell, David S.; Gerhard, Glenn S.; Franklin, David P.; Carey, David J.; Phillips, Victoria L.; Williams, Michael J.A.; Wei, Wenhua; Blair, Ross; Hill, Andrew A.; Vasudevan, Thodor M.; Lewis, David R.; Thomson, Ian A.; Krysa, Jo; Hill, Geraldine B.; Roake, Justin; Merriman, Tony R.; Oszkinis, Grzegorz; Galora, Silvia; Saracini, Claudia; Abbate, Rosanna; Pulli, Raffaele; Pratesi, Carlo; Saratzis, Athanasios; Verissimo, Ana R.; Bumpstead, Suzannah; Badger, Stephen A.; Clough, Rachel E.; Cockerill, Gillian; Hafez, Hany; Scott, D. Julian A.; Futers, T. Simon; Romaine, Simon P.R.; Bridge, Katherine; Griffin, Kathryn J.; Bailey, Marc A.; Smith, Alberto; Thompson, Matthew M.; van Bockxmeer, Frank M.; Matthiasson, Stefan E.; Thorleifsson, Gudmar; Thorsteinsdottir, Unnur; Blankensteijn, Jan D.; Teijink, Joep A.W.; Wijmenga, Cisca; de Graaf, Jacqueline; Kiemeney, Lambertus A.; Lindholt, Jes S.; Hughes, Anne; Bradley, Declan T.; Stirrups, Kathleen; Golledge, Jonathan; Norman, Paul E.; Powell, Janet T.; Humphries, Steve E.; Hamby, Stephen E.; Goodall, Alison H.; Nelson, Christopher P.; Sakalihasan, Natzi; Courtois, Audrey; Ferrell, Robert E.; Eriksson, Per; Folkersen, Lasse; Franco-Cereceda, Anders; Eicher, John D.; Johnson, Andrew D.; Betsholtz, Christer; Ruusalepp, Arno; Franzén, Oscar; Schadt, Eric E.; Björkegren, Johan L.M.; Lipovich, Leonard; Drolet, Anne M.; Verhoeven, Eric L.; Zeebregts, Clark J.; Geelkerken, Robert H.; van Sambeek, Marc R.; van Sterkenburg, Steven M.; de Vries, Jean-Paul; Stefansson, Kari; Thompson, John R.; de Bakker, Paul I.W.; Deloukas, Panos; Sayers, Robert D.; Harrison, Seamus C.; van Rij, Andre M.; Samani, Nilesh J.

2017-01-01

Rationale: Abdominal aortic aneurysm (AAA) is a complex disease with both genetic and environmental risk factors. Together, 6 previously identified risk loci only explain a small proportion of the heritability of AAA. Objective: To identify additional AAA risk loci using data from all available genome-wide association studies. Methods and Results: Through a meta-analysis of 6 genome-wide association study data sets and a validation study totaling 10 204 cases and 107 766 controls, we identified 4 new AAA risk loci: 1q32.3 (SMYD2), 13q12.11 (LINC00540), 20q13.12 (near PCIF1/MMP9/ZNF335), and 21q22.2 (ERG). In various database searches, we observed no new associations between the lead AAA single nucleotide polymorphisms and coronary artery disease, blood pressure, lipids, or diabetes mellitus. Network analyses identified ERG, IL6R, and LDLR as modifiers of MMP9, with a direct interaction between ERG and MMP9. Conclusions: The 4 new risk loci for AAA seem to be specific for AAA compared with other cardiovascular diseases and related traits suggesting that traditional cardiovascular risk factor management may only have limited value in preventing the progression of aneurysmal disease. PMID:27899403

Severe vascular calcification and tumoral calcinosis in a family with hyperphosphatemia: a fibroblast growth factor 23 mutation identified by exome sequencing

PubMed Central

Shah, Anuja; Miller, Clinton J.; Nast, Cynthia C.; Adams, Mark D.; Truitt, Barbara; Tayek, John A.; Tong, Lili; Mehtani, Parag; Monteon, Francisco; Sedor, John R.; Clinkenbeard, Erica L.; White, Kenneth; Mehrotra, Rajnish; LaPage, Janine; Dickson, Patricia; Adler, Sharon G.; Iyengar, Sudha K.

2014-01-01

Background Tumoral calcinosis is an autosomal recessive disorder characterized by ectopic calcification and hyperphosphatemia. Methods We describe a family with tumoral calcinosis requiring amputations. The predominant metabolic anomaly identified in three affected family members was hyperphosphatemia. Biochemical and phenotypic analysis of 13 kindred members, together with exome analysis of 6 members, was performed. Results We identified a novel Q67K mutation in fibroblast growth factor 23 (FGF23), segregating with a null (deletion) allele on the other FGF23 homologue in three affected members. Affected siblings had high circulating plasma C-terminal FGF23 levels, but undetectable intact FGF23 or N-terminal FGF23, leading to loss of FGF23 function. Conclusions This suggests that in human, as in experimental models, severe prolonged hyperphosphatemia may be sufficient to produce bone differentiation proteins in vascular cells, and vascular calcification severe enough to require amputation. Genetic modifiers may contribute to the phenotypic variation within and between families. PMID:25378588

Phylogenetic Factor Analysis.

PubMed

Tolkoff, Max R; Alfaro, Michael E; Baele, Guy; Lemey, Philippe; Suchard, Marc A

2018-05-01

Phylogenetic comparative methods explore the relationships between quantitative traits adjusting for shared evolutionary history. This adjustment often occurs through a Brownian diffusion process along the branches of the phylogeny that generates model residuals or the traits themselves. For high-dimensional traits, inferring all pair-wise correlations within the multivariate diffusion is limiting. To circumvent this problem, we propose phylogenetic factor analysis (PFA) that assumes a small unknown number of independent evolutionary factors arise along the phylogeny and these factors generate clusters of dependent traits. Set in a Bayesian framework, PFA provides measures of uncertainty on the factor number and groupings, combines both continuous and discrete traits, integrates over missing measurements and incorporates phylogenetic uncertainty with the help of molecular sequences. We develop Gibbs samplers based on dynamic programming to estimate the PFA posterior distribution, over 3-fold faster than for multivariate diffusion and a further order-of-magnitude more efficiently in the presence of latent traits. We further propose a novel marginal likelihood estimator for previously impractical models with discrete data and find that PFA also provides a better fit than multivariate diffusion in evolutionary questions in columbine flower development, placental reproduction transitions and triggerfish fin morphometry.

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

PubMed

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

2017-09-01

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

Organisational Issues for E-Learning: Critical Success Factors as Identified by HE Practitioners

ERIC Educational Resources Information Center

McPherson, Maggie; Nunes, Miguel Baptista

2006-01-01

Purpose: The purpose of this paper is to report on a research project that identified organisational critical success factors (CSFs) for e-learning implementation in higher education (HE). These CSFs can be used as a theoretical foundation upon which to base decision-making and strategic thinking about e-learning. Design/methodology/approach: The…

Identifying influential individuals on intensive care units: using cluster analysis to explore culture.

PubMed

Fong, Allan; Clark, Lindsey; Cheng, Tianyi; Franklin, Ella; Fernandez, Nicole; Ratwani, Raj; Parker, Sarah Henrickson

2017-07-01

The objective of this paper is to identify attribute patterns of influential individuals in intensive care units using unsupervised cluster analysis. Despite the acknowledgement that culture of an organisation is critical to improving patient safety, specific methods to shift culture have not been explicitly identified. A social network analysis survey was conducted and an unsupervised cluster analysis was used. A total of 100 surveys were gathered. Unsupervised cluster analysis was used to group individuals with similar dimensions highlighting three general genres of influencers: well-rounded, knowledge and relational. Culture is created locally by individual influencers. Cluster analysis is an effective way to identify common characteristics among members of an intensive care unit team that are noted as highly influential by their peers. To change culture, identifying and then integrating the influencers in intervention development and dissemination may create more sustainable and effective culture change. Additional studies are ongoing to test the effectiveness of utilising these influencers to disseminate patient safety interventions. This study offers an approach that can be helpful in both identifying and understanding influential team members and may be an important aspect of developing methods to change organisational culture. © 2017 John Wiley & Sons Ltd.

Job satisfaction of nurses and identifying factors of job satisfaction in Slovenian Hospitals.

PubMed

Lorber, Mateja; Skela Savič, Brigita

2012-06-01

To determine the level of job satisfaction of nursing professionals in Slovenian hospitals and factors influencing job satisfaction in nursing. The study included 4 hospitals selected from the hospital list comprising 26 hospitals in Slovenia. The employees of these hospitals represent 29.8% and 509 employees included in the study represent 6% of all employees in nursing in Slovenian hospitals. One structured survey questionnaire was administered to the leaders and the other to employees, both consisting 154 items evaluated on a 5 point Likert-type scale. We examined the correlation between independent variables (age, number of years of employment, behavior of leaders, personal characteristics of leaders, and managerial competencies of leaders) and the dependent variable (job satisfaction - satisfaction with the work, coworkers, management, pay, etc) by applying correlation analysis and multivariate regression analysis. In addition, factor analysis was used to establish characteristic components of the variables measured. We found a medium level of job satisfaction in both leaders (3.49±0.5) and employees (3.19±0.6), however, there was a significant difference between their estimates (t=3.237; P=lt;0.001). Job satisfaction was explained by age (Plt;0.05; β=0.091), years of employment (Plt;0.05; β=0.193), personal characteristics of leaders (Plt;0.001; β=0.158), and managerial competencies of leaders (Plt;0.000; β=0.634) in 46% of cases. The factor analysis yielded four factors explaining 64% of the total job satisfaction variance. Satisfied employees play a crucial role in an organization's success, so health care organizations must be aware of the importance of employees' job satisfaction. It is recommended to monitor employees' job satisfaction levels on an annual basis.

Job satisfaction of nurses and identifying factors of job satisfaction in Slovenian Hospitals

PubMed Central

Lorber, Mateja; Skela Savič, Brigita

2012-01-01

Aim To determine the level of job satisfaction of nursing professionals in Slovenian hospitals and factors influencing job satisfaction in nursing. Methods The study included 4 hospitals selected from the hospital list comprising 26 hospitals in Slovenia. The employees of these hospitals represent 29.8% and 509 employees included in the study represent 6% of all employees in nursing in Slovenian hospitals. One structured survey questionnaire was administered to the leaders and the other to employees, both consisting 154 items evaluated on a 5 point Likert-type scale. We examined the correlation between independent variables (age, number of years of employment, behavior of leaders, personal characteristics of leaders, and managerial competencies of leaders) and the dependent variable (job satisfaction – satisfaction with the work, coworkers, management, pay, etc) by applying correlation analysis and multivariate regression analysis. In addition, factor analysis was used to establish characteristic components of the variables measured. Results We found a medium level of job satisfaction in both leaders (3.49 ± 0.5) and employees (3.19 ± 0.6), however, there was a significant difference between their estimates (t = 3.237; P = <0.001). Job satisfaction was explained by age (P < 0.05; β = 0.091), years of employment (P < 0.05; β = 0.193), personal characteristics of leaders (P < 0.001; β = 0.158), and managerial competencies of leaders (P < 0.000; β = 0.634) in 46% of cases. The factor analysis yielded four factors explaining 64% of the total job satisfaction variance. Conclusion Satisfied employees play a crucial role in an organization’s success, so health care organizations must be aware of the importance of employees’ job satisfaction. It is recommended to monitor employees’ job satisfaction levels on an annual basis. PMID:22661140

Systems analysis of multiple regulator perturbations allows discovery of virulence factors in Salmonella

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

Yoon, Hyunjin; Ansong, Charles; McDermott, Jason E.

Background: Systemic bacterial infections are highly regulated and complex processes that are orchestrated by numerous virulence factors. Genes that are coordinately controlled by the set of regulators required for systemic infection are potentially required for pathogenicity. Results: In this study we present a systems biology approach in which sample-matched multi-omic measurements of fourteen virulence-essential regulator mutants were coupled with computational network analysis to efficiently identify Salmonella virulence factors. Immunoblot experiments verified network-predicted virulence factors and a subset was determined to be secreted into the host cytoplasm, suggesting that they are virulence factors directly interacting with host cellular components. Two ofmore » these, SrfN and PagK2, were required for full mouse virulence and were shown to be translocated independent of either of the type III secretion systems in Salmonella or the type III injectisome-related flagellar mechanism. Conclusions: Integrating multi-omic datasets from Salmonella mutants lacking virulence regulators not only identified novel virulence factors but also defined a new class of translocated effectors involved in pathogenesis. The success of this strategy at discovery of known and novel virulence factors suggests that the approach may have applicability for other bacterial pathogens.« less

Identifying predictive factors for long-term complications following button battery impactions: A case series and literature review.

PubMed

Eliason, Michael J; Melzer, Jonathan M; Winters, Jessica R; Gallagher, Thomas Q

2016-08-01

To complement a case series review of button battery impactions managed at our single military tertiary care center with a thorough literature review of laboratory research and clinical cases to develop a protocol to optimize patient care. Specifically, to identify predictive factors of long-term complications which can be used by the pediatric otolaryngologist to guide patient management after button battery impactions. A retrospective review of the Department of Defense's electronic medical record systems was conducted to identify patients with button battery ingestions and then characterize their treatment course. A thorough literature review complemented the lessons learned to identify potentially predictive clinical measures for long-term complications. Eight patients were identified as being treated for button battery impaction in the aerodigestive tract with two sustaining long-term complications. The median age of the patients treated was 33 months old and the median estimated time of impaction in the aerodigestive tract prior to removal was 10.5 h. Time of impaction, anatomic direction of the battery's negative pole, and identifying specific battery parameters were identified as factors that may be employed to predict sequelae. Based on case reviews, advancements in battery manufacturing, and laboratory research, there are distinct clinical factors that should be assessed at the time of initial therapy to guide follow-up management to minimize potential catastrophic sequelae of button battery ingestion. Published by Elsevier Ireland Ltd.

Identifying at-risk profiles and protective factors for problem gambling: A longitudinal study across adolescence and early adulthood.

PubMed

Allami, Youssef; Vitaro, Frank; Brendgen, Mara; Carbonneau, René; Tremblay, Richard E

2018-05-01

Past studies have identified various risk and protective factors for problem gambling (PG). However, no study has examined the interplay between these factors using a combination of person-centered and variable-centered approaches embedded within a longitudinal design. The present study aimed to (a) identify distinct profiles in early adolescence based on a set of risk factors commonly associated with PG (impulsivity, depression, anxiety, drug-alcohol use, aggressiveness, and antisociality), (b) explore the difference in reported gambling problems between these profiles during midadolescence and early adulthood, and (c) identify family- and peer-related variables that could operate as protective or compensatory factors in this context. Two samples were used: (a) a population sample (N = 1,033) living in low socioeconomic-status neighborhoods and (b) a population sample (N = 3,017) representative of students attending Quebec schools. Latent profile analyses were conducted to identify at-risk profiles based on individual risk factors measured at age 12 years. Negative binomial regression models were estimated to compare profiles in terms of their reported gambling problems at ages 16 and 23. Finally, family- and peer-related variables measured at age 14 were included to test their protective or compensatory role with respect to the link between at-risk profiles and gambling problems. Four profiles were identified: well-adjusted, internalizing, externalizing, and comorbid. Compared to the well-adjusted profile, the externalizing and comorbid profiles reported more gambling problems at ages 16 and 23, but the internalizing profile did not differ significantly. Various protective and compensatory factors emerged for each profile at both time points. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Individual and Work-Related Factors Influencing Burnout of Mental Health Professionals: A Meta-Analysis

ERIC Educational Resources Information Center

Lim, Nayoung; Kim, Eun Kyoung; Kim, Hyunjung; Yang, Eunjoo; Lee, Sang Min

2010-01-01

The current study identifies and assesses individual and work-related factors as correlates of burnout among mental health professionals. Results of a meta-analysis indicate that age and work setting variables are the most significant indicators of emotional exhaustion and depersonalization. In terms of level of personal accomplishment, the age…

Identifying critical success factors for designing selection processes into postgraduate specialty training: the case of UK general practice.

PubMed

Plint, Simon; Patterson, Fiona

2010-06-01

The UK national recruitment process into general practice training has been developed over several years, with incremental introduction of stages which have been piloted and validated. Previously independent processes, which encouraged multiple applications and produced inconsistent outcomes, have been replaced by a robust national process which has high reliability and predictive validity, and is perceived to be fair by candidates and allocates applicants equitably across the country. Best selection practice involves a job analysis which identifies required competencies, then designs reliable assessment methods to measure them, and over the long term ensures that the process has predictive validity against future performance. The general practitioner recruitment process introduced machine markable short listing assessments for the first time in the UK postgraduate recruitment context, and also adopted selection centre workplace simulations. The key success factors have been identified as corporate commitment to the goal of a national process, with gradual convergence maintaining locus of control rather than the imposition of change without perceived legitimate authority.

A risk-factor analysis of medical litigation judgments related to fall injuries in Korea.

PubMed

Kim, Insook; Won, Seonae; Lee, Mijin; Lee, Won

2018-01-01

The aim of this study was to find out the risk factors through analysis of seven medical malpractice judgments related to fall injuries. The risk factors were analysed by using the framework that approaches falls from a systems perspective and comprised people, organisational or environmental factors, with each factor being comprised of subfactors. The risk factors found in each of the seven judgments were aggregated into one framework. The risk factors related to patients (i.e. the people factor) were age, pain, related disease, activities and functional status, urination state, cognitive function impairment, past history of fall, blood transfusion, sleep endoscopy state and uncooperative attitude. The risk factors related to the medical staff and caregivers (i.e. people factor) were observation negligence, no fall prevention activities and negligence in managing high-risk group for fall. Organisational risk factors were a lack of workforce, a lack of training, neglecting the management of the high-risk group, neglecting the management of caregivers and the absence of a fall prevention procedure. Regarding the environment, the risk factors were found to be the emergency room, chairs without a backrest and the examination table. Identifying risk factors is essential for preventing fall accidents, since falls are preventable patient-safety incidents. Falls do not happen as a result of a single risk factor. Therefore, a systems approach is effective to identify risk factors, especially organisational and environmental factors.

Search Strategy to Identify Dental Survival Analysis Articles Indexed in MEDLINE.

PubMed

Layton, Danielle M; Clarke, Michael

2016-01-01

Articles reporting survival outcomes (time-to-event outcomes) in patients over time are challenging to identify in the literature. Research shows the words authors use to describe their dental survival analyses vary, and that allocation of medical subject headings by MEDLINE indexers is inconsistent. Together, this undermines accurate article identification. The present study aims to develop and validate a search strategy to identify dental survival analyses indexed in MEDLINE (Ovid). A gold standard cohort of articles was identified to derive the search terms, and an independent gold standard cohort of articles was identified to test and validate the proposed search strategies. The first cohort included all 6,955 articles published in the 50 dental journals with the highest impact factors in 2008, of which 95 articles were dental survival articles. The second cohort included all 6,514 articles published in the 50 dental journals with the highest impact factors for 2012, of which 148 were dental survival articles. Each cohort was identified by a systematic hand search. Performance parameters of sensitivity, precision, and number needed to read (NNR) for the search strategies were calculated. Sensitive, precise, and optimized search strategies were developed and validated. The performances of the search strategy maximizing sensitivity were 92% sensitivity, 14% precision, and 7.11 NNR; the performances of the strategy maximizing precision were 93% precision, 10% sensitivity, and 1.07 NNR; and the performances of the strategy optimizing the balance between sensitivity and precision were 83% sensitivity, 24% precision, and 4.13 NNR. The methods used to identify search terms were objective, not subjective. The search strategies were validated in an independent group of articles that included different journals and different publication years. Across the three search strategies, dental survival articles can be identified with sensitivity up to 92%, precision up to 93

Comparative Proteome Analysis in Schizosaccharomyces pombe Identifies Metabolic Targets to Improve Protein Production and Secretion*

PubMed Central

Hung, Chien-Wen; Klein, Tobias; Cassidy, Liam; Linke, Dennis; Lange, Sabrina; Anders, Uwe; Bureik, Matthias; Heinzle, Elmar; Schneider, Konstantin; Tholey, Andreas

2016-01-01

Protein secretion in yeast is a complex process and its efficiency depends on a variety of parameters. We performed a comparative proteome analysis of a set of Schizosaccharomyces pombe strains producing the α-glucosidase maltase in increasing amounts to investigate the overall proteomic response of the cell to the burden of protein production along the various steps of protein production and secretion. Proteome analysis of these strains, utilizing an isobaric labeling/two dimensional LC-MALDI MS approach, revealed complex changes, from chaperones and secretory transport machinery to proteins controlling transcription and translation. We also found an unexpectedly high amount of changes in enzyme levels of the central carbon metabolism and a significant up-regulation of several amino acid biosyntheses. These amino acids were partially underrepresented in the cellular protein compared with the composition of the model protein. Additional feeding of these amino acids resulted in a 1.5-fold increase in protein secretion. Membrane fluidity was identified as a second bottleneck for high-level protein secretion and addition of fluconazole to the culture caused a significant decrease in ergosterol levels, whereas protein secretion could be further increased by a factor of 2.1. In summary, we show that high level protein secretion causes global changes of protein expression levels in the cell and that precursor availability and membrane composition limit protein secretion in this yeast. In this respect, comparative proteome analysis is a powerful tool to identify targets for an efficient increase of protein production and secretion in S. pombe. Data are available via ProteomeXchange with identifiers PXD002693 and PXD003016. PMID:27477394

Genome-wide analysis of the WRKY transcription factors in aegilops tauschii.

PubMed

Ma, Jianhui; Zhang, Daijing; Shao, Yun; Liu, Pei; Jiang, Lina; Li, Chunxi

2014-01-01

The WRKY transcription factors (TFs) play important roles in responding to abiotic and biotic stress in plants. However, due to its unfinished genome sequencing, relatively few WRKY TFs with full-length coding sequences (CDSs) have been identified in wheat. Instead, the Aegilops tauschii genome, which is the D-genome progenitor of the hexaploid wheat genome, provides important resources for the discovery of new genes. In this study, we performed a bioinformatics analysis to identify WRKY TFs with full-length CDSs from the A. tauschii genome. A detailed evolutionary analysis for all these TFs was conducted, and quantitative real-time PCR was carried out to investigate the expression patterns of the abiotic stress-related WRKY TFs under different abiotic stress conditions in A. tauschii seedlings. A total of 93 WRKY TFs were identified from A. tauschii, and 79 of them were found to be newly discovered genes compared with wheat. Gene phylogeny, gene structure and chromosome location of the 93 WRKY TFs were fully analyzed. These studies provide a global view of the WRKY TFs from A. tauschii and a firm foundation for further investigations in both A. tauschii and wheat. © 2015 S. Karger AG, Basel.

Integrated microarray and ChIP analysis identifies multiple Foxa2 dependent target genes in the notochord.

PubMed

Tamplin, Owen J; Cox, Brian J; Rossant, Janet

2011-12-15

The node and notochord are key tissues required for patterning of the vertebrate body plan. Understanding the gene regulatory network that drives their formation and function is therefore important. Foxa2 is a key transcription factor at the top of this genetic hierarchy and finding its targets will help us to better understand node and notochord development. We performed an extensive microarray-based gene expression screen using sorted embryonic notochord cells to identify early notochord-enriched genes. We validated their specificity to the node and notochord by whole mount in situ hybridization. This provides the largest available resource of notochord-expressed genes, and therefore candidate Foxa2 target genes in the notochord. Using existing Foxa2 ChIP-seq data from adult liver, we were able to identify a set of genes expressed in the notochord that had associated regions of Foxa2-bound chromatin. Given that Foxa2 is a pioneer transcription factor, we reasoned that these sites might represent notochord-specific enhancers. Candidate Foxa2-bound regions were tested for notochord specific enhancer function in a zebrafish reporter assay and 7 novel notochord enhancers were identified. Importantly, sequence conservation or predictive models could not have readily identified these regions. Mutation of putative Foxa2 binding elements in two of these novel enhancers abrogated reporter expression and confirmed their Foxa2 dependence. The combination of highly specific gene expression profiling and genome-wide ChIP analysis is a powerful means of understanding developmental pathways, even for small cell populations such as the notochord. Copyright © 2011 Elsevier Inc. All rights reserved.

Human error and commercial aviation accidents: an analysis using the human factors analysis and classification system.

PubMed

Shappell, Scott; Detwiler, Cristy; Holcomb, Kali; Hackworth, Carla; Boquet, Albert; Wiegmann, Douglas A

2007-04-01

The aim of this study was to extend previous examinations of aviation accidents to include specific aircrew, environmental, supervisory, and organizational factors associated with two types of commercial aviation (air carrier and commuter/ on-demand) accidents using the Human Factors Analysis and Classification System (HFACS). HFACS is a theoretically based tool for investigating and analyzing human error associated with accidents and incidents. Previous research has shown that HFACS can be reliably used to identify human factors trends associated with military and general aviation accidents. Using data obtained from both the National Transportation Safety Board and the Federal Aviation Administration, 6 pilot-raters classified aircrew, supervisory, organizational, and environmental causal factors associated with 1020 commercial aviation accidents that occurred over a 13-year period. The majority of accident causal factors were attributed to aircrew and the environment, with decidedly fewer associated with supervisory and organizational causes. Comparisons were made between HFACS causal categories and traditional situational variables such as visual conditions, injury severity, and regional differences. These data will provide support for the continuation, modification, and/or development of interventions aimed at commercial aviation safety. HFACS provides a tool for assessing human factors associated with accidents and incidents.

Bayesian inference of the number of factors in gene-expression analysis: application to human virus challenge studies

PubMed Central

2010-01-01

Background Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques for sparse factor analysis, with application to gene-expression data from three virus challenge studies. Particular attention is placed on employing the Beta Process (BP), the Indian Buffet Process (IBP), and related sparseness-promoting techniques to infer a proper number of factors. The posterior density function on the model parameters is computed using Gibbs sampling and variational Bayesian (VB) analysis. Results Time-evolving gene-expression data are considered for respiratory syncytial virus (RSV), Rhino virus, and influenza, using blood samples from healthy human subjects. These data were acquired in three challenge studies, each executed after receiving institutional review board (IRB) approval from Duke University. Comparisons are made between several alternative means of per-forming nonparametric factor analysis on these data, with comparisons as well to sparse-PCA and Penalized Matrix Decomposition (PMD), closely related non-Bayesian approaches. Conclusions Applying the Beta Process to the factor scores, or to the singular values of a pseudo-SVD construction, the proposed algorithms infer the number of factors in gene-expression data. For real data the "true" number of factors is unknown; in our simulations we consider a range of noise variances, and the proposed Bayesian models inferred the number of factors accurately relative to other methods in the literature, such as sparse-PCA and PMD. We have also identified a "pan-viral" factor of importance for each of the three viruses considered in this study. We have identified a set of genes associated with this pan-viral factor, of interest for early detection of such viruses based upon the host response, as quantified via gene-expression data. PMID:21062443

Bayesian inference of the number of factors in gene-expression analysis: application to human virus challenge studies.

PubMed

Chen, Bo; Chen, Minhua; Paisley, John; Zaas, Aimee; Woods, Christopher; Ginsburg, Geoffrey S; Hero, Alfred; Lucas, Joseph; Dunson, David; Carin, Lawrence

2010-11-09

Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques for sparse factor analysis, with application to gene-expression data from three virus challenge studies. Particular attention is placed on employing the Beta Process (BP), the Indian Buffet Process (IBP), and related sparseness-promoting techniques to infer a proper number of factors. The posterior density function on the model parameters is computed using Gibbs sampling and variational Bayesian (VB) analysis. Time-evolving gene-expression data are considered for respiratory syncytial virus (RSV), Rhino virus, and influenza, using blood samples from healthy human subjects. These data were acquired in three challenge studies, each executed after receiving institutional review board (IRB) approval from Duke University. Comparisons are made between several alternative means of per-forming nonparametric factor analysis on these data, with comparisons as well to sparse-PCA and Penalized Matrix Decomposition (PMD), closely related non-Bayesian approaches. Applying the Beta Process to the factor scores, or to the singular values of a pseudo-SVD construction, the proposed algorithms infer the number of factors in gene-expression data. For real data the "true" number of factors is unknown; in our simulations we consider a range of noise variances, and the proposed Bayesian models inferred the number of factors accurately relative to other methods in the literature, such as sparse-PCA and PMD. We have also identified a "pan-viral" factor of importance for each of the three viruses considered in this study. We have identified a set of genes associated with this pan-viral factor, of interest for early detection of such viruses based upon the host response, as quantified via gene-expression data.

Risk factors in laparoscopic cholecystectomy: a multivariate analysis.

PubMed

Kanakala, Venkatesh; Borowski, David W; Pellen, Michael G C; Dronamraju, Shridhar S; Woodcock, Sean A A; Seymour, Keith; Attwood, Stephen E A; Horgan, Liam F

2011-01-01

Laparoscopic cholecystectomy (LC) is the operation of choice in the treatment of symptomatic gallstone disease. The aim of this study is to identify risk factors for LC, outcomes include operating time, length of stay, conversion rate, morbidity and mortality. All patients undergoing LC between 1998 and 2007 in a single district general hospital. Risk factors were examined using uni- and multivariate analysis. 2117 patients underwent LC, with 1706 (80.6%) patients operated on electively. Male patients were older, had more co-morbidity and more emergency surgery than females. The median post-operative hospital stay was one day, and was positively correlated with the complexity of surgery. Conversion rates were higher in male patients (OR 1.47, p = 0.047) than in females, and increased with co-morbidity. Emergency surgery (OR 1.75, p = 0.005), male gender (OR 1.68, p = 0.005), increasing co-morbidity and complexity of surgery were all positively associated with the incidence of complications (153/2117 [7.2%]), whereas only male gender was significantly associated with mortality (OR 5.71, p = 0.025). Adverse outcome from LC is particularly associated with male gender, but also the patient's co-morbidity, complexity and urgency of surgery. Risk-adjusted outcome analysis is desirable to ensure an informed consent process. Copyright © 2011 Surgical Associates Ltd. Published by Elsevier Ltd. All rights reserved.

Analysis of factors that influencing the interest of Bali State Polytechnic’s students in entrepreneurship

NASA Astrophysics Data System (ADS)

Ayuni, N. W. D.; Sari, I. G. A. M. K. K.

2018-01-01

The high rate of unemployment results the economic growth to be hampered. To solve this situation, the government try to change the students’ mindset from becoming a job seeker to become a job creator or entrepreneur. One real action that usually been held in Bali State Polytechnic is Student Entrepreneurial Program. The purpose of this research is to identify and analyze the factors that influence the interest of Bali State Polytechnic’s Students in entrepreneurship, especially in the Entrepreneurial Student Program. Method used in this research is Factor Analysis including Bartlett Test, Kaiser-Mayer Olkin (KMO), Measure of Sampling Adequacy (MSA), factor extraction using Principal Component Analysis (PCA), factor selection using eigen value and scree plot, and factor rotation using orthogonal rotation varimax. Result shows that there are four factors that influencing the interest of Bali State Polytechnic’s Students in Entrepreneurship which are Contextual Factor (including Entrepreneurship Training, Academic Support, Perceived Confidence, and Economic Challenge), Self Efficacy Factor (including Leadership, Mental Maturity, Relation with Entrepreneur, and Authority), Subjective Norm Factor (including Support of Important Relative, Support of Friends, and Family Role), and Attitude Factor (including Self Realization).

Comparisons of Exploratory and Confirmatory Factor Analysis.

ERIC Educational Resources Information Center

Daniel, Larry G.

Historically, most researchers conducting factor analysis have used exploratory methods. However, more recently, confirmatory factor analytic methods have been developed that can directly test theory either during factor rotation using "best fit" rotation methods or during factor extraction, as with the LISREL computer programs developed…

Success Factors of European Syndromic Surveillance Systems: A Worked Example of Applying Qualitative Comparative Analysis

PubMed Central

Ziemann, Alexandra; Fouillet, Anne; Brand, Helmut; Krafft, Thomas

2016-01-01

Introduction Syndromic surveillance aims at augmenting traditional public health surveillance with timely information. To gain a head start, it mainly analyses existing data such as from web searches or patient records. Despite the setup of many syndromic surveillance systems, there is still much doubt about the benefit of the approach. There are diverse interactions between performance indicators such as timeliness and various system characteristics. This makes the performance assessment of syndromic surveillance systems a complex endeavour. We assessed if the comparison of several syndromic surveillance systems through Qualitative Comparative Analysis helps to evaluate performance and identify key success factors. Materials and Methods We compiled case-based, mixed data on performance and characteristics of 19 syndromic surveillance systems in Europe from scientific and grey literature and from site visits. We identified success factors by applying crisp-set Qualitative Comparative Analysis. We focused on two main areas of syndromic surveillance application: seasonal influenza surveillance and situational awareness during different types of potentially health threatening events. Results We found that syndromic surveillance systems might detect the onset or peak of seasonal influenza earlier if they analyse non-clinical data sources. Timely situational awareness during different types of events is supported by an automated syndromic surveillance system capable of analysing multiple syndromes. To our surprise, the analysis of multiple data sources was no key success factor for situational awareness. Conclusions We suggest to consider these key success factors when designing or further developing syndromic surveillance systems. Qualitative Comparative Analysis helped interpreting complex, mixed data on small-N cases and resulted in concrete and practically relevant findings. PMID:27182731

Spatial analysis of leprosy incidence and associated socioeconomic factors.

PubMed

Cury, Maria Rita de Cassia Oliveira; Paschoal, Vania Del'Arco; Nardi, Susilene Maria Tonelli; Chierotti, Ana Patrícia; Rodrigues Júnior, Antonio Luiz; Chiaravalloti-Neto, Francisco

2012-02-01

To identify clusters of the major occurrences of leprosy and their associated socioeconomic and demographic factors. Cases of leprosy that occurred between 1998 and 2007 in São José do Rio Preto (southeastern Brazil) were geocodified and the incidence rates were calculated by census tract. A socioeconomic classification score was obtained using principal component analysis of socioeconomic variables. Thematic maps to visualize the spatial distribution of the incidence of leprosy with respect to socioeconomic levels and demographic density were constructed using geostatistics. While the incidence rate for the entire city was 10.4 cases per 100,000 inhabitants annually between 1998 and 2007, the incidence rates of individual census tracts were heterogeneous, with values that ranged from 0 to 26.9 cases per 100,000 inhabitants per year. Areas with a high leprosy incidence were associated with lower socioeconomic levels. There were identified clusters of leprosy cases, however there was no association between disease incidence and demographic density. There was a disparity between the places where the majority of ill people lived and the location of healthcare services. The spatial analysis techniques utilized identified the poorer neighborhoods of the city as the areas with the highest risk for the disease. These data show that health departments must prioritize politico-administrative policies to minimize the effects of social inequality and improve the standards of living, hygiene, and education of the population in order to reduce the incidence of leprosy.

Genome-wide identification and expression analysis of TCP transcription factors in Gossypium raimondii.

PubMed

Ma, Jun; Wang, Qinglian; Sun, Runrun; Xie, Fuliang; Jones, Don C; Zhang, Baohong

2014-10-16

Plant-specific TEOSINTE-BRANCHED1/CYCLOIDEA/PCF (TCP) transcription factors play versatile functions in multiple aspects of plant growth and development. However, no systematical study has been performed in cotton. In this study, we performed for the first time the genome-wide identification and expression analysis of the TCP transcription factor family in Gossypium raimondii. A total of 38 non-redundant cotton TCP encoding genes were identified. The TCP transcription factors were divided into eleven subgroups based on phylogenetic analysis. Most TCP genes within the same subfamily demonstrated similar exon and intron organization and the motif structures were highly conserved among the subfamilies. Additionally, the chromosomal distribution pattern revealed that TCP genes were unevenly distributed across 11 out of the 13 chromosomes; segmental duplication is a predominant duplication event for TCP genes and the major contributor to the expansion of TCP gene family in G. raimondii. Moreover, the expression profiles of TCP genes shed light on their functional divergence.

Genome-wide identification and expression analysis of TCP transcription factors in Gossypium raimondii

PubMed Central

Ma, Jun; Wang, Qinglian; Sun, Runrun; Xie, Fuliang; Jones, Don C.; Zhang, Baohong

2014-01-01

Plant-specific TEOSINTE-BRANCHED1/CYCLOIDEA/PCF (TCP) transcription factors play versatile functions in multiple aspects of plant growth and development. However, no systematical study has been performed in cotton. In this study, we performed for the first time the genome-wide identification and expression analysis of the TCP transcription factor family in Gossypium raimondii. A total of 38 non-redundant cotton TCP encoding genes were identified. The TCP transcription factors were divided into eleven subgroups based on phylogenetic analysis. Most TCP genes within the same subfamily demonstrated similar exon and intron organization and the motif structures were highly conserved among the subfamilies. Additionally, the chromosomal distribution pattern revealed that TCP genes were unevenly distributed across 11 out of the 13 chromosomes; segmental duplication is a predominant duplication event for TCP genes and the major contributor to the expansion of TCP gene family in G. raimondii. Moreover, the expression profiles of TCP genes shed light on their functional divergence. PMID:25322260

Design Factors Affecting the Reaction Time for Identifying Toilet Signs: A Preliminary Study.

PubMed

Chen, Yi-Lang; Sie, Cai-Cin

2016-04-01

This study focused on the manner in which design factors affect the reaction time for identifying toilet signs. Taiwanese university students and staff members (50 men, 50 women; M age = 23.5 year, SD = 5.7) participated in the study. The 36 toilet signs were modified on three factors (six presenting styles, two figure-ground exchanges, and three colors), and the reaction time data of all participants were collected when the signs were presented in a simulation onscreen. Participants were quickest when reading Chinese text, followed by graphics and English texts. The findings also showed that men and women had different reaction times across various design combinations. These findings can serve as a reference for practically designing toilet signs, since design factors can lead to difficulties with comprehension based on reaction time measurements. © The Author(s) 2016.

A CRITERION FACTOR ANALYSIS OF THE SIXTEEN PERSONALITY FACTOR QUESTIONNAIRE.

ERIC Educational Resources Information Center

MAZER, GILBERT E.

THE CORRELATION OF REPORTED VARIATIONS IN COUNSELOR PRACTICES WITH WELL-IDENTIFIED PERSONALITY TRAITS WAS STUDIED. THE SIXTEEN PERSONALITY FACTOR QUESTIONNAIRE (WHICH MEASURES 15 PERSONALITY TRAITS AND INTELLIGENCE) AND THE INVENTORY OF COUNSELING PRACTICES (WHICH EVALUATES 75 COUNSELING PRACTICES) WERE GIVEN TO 120 GRADUATE GUIDANCE STUDENTS AT…

Integrative Analysis of GWASs, Human Protein Interaction, and Gene Expression Identified Gene Modules Associated With BMDs

PubMed Central

He, Hao; Zhang, Lei; Li, Jian; Wang, Yu-Ping; Zhang, Ji-Gang; Shen, Jie; Guo, Yan-Fang

2014-01-01

Context: To date, few systems genetics studies in the bone field have been performed. We designed our study from a systems-level perspective by integrating genome-wide association studies (GWASs), human protein-protein interaction (PPI) network, and gene expression to identify gene modules contributing to osteoporosis risk. Methods: First we searched for modules significantly enriched with bone mineral density (BMD)-associated genes in human PPI network by using 2 large meta-analysis GWAS datasets through a dense module search algorithm. One included 7 individual GWAS samples (Meta7). The other was from the Genetic Factors for Osteoporosis Consortium (GEFOS2). One was assigned as a discovery dataset and the other as an evaluation dataset, and vice versa. Results: In total, 42 modules and 129 modules were identified significantly in both Meta7 and GEFOS2 datasets for femoral neck and spine BMD, respectively. There were 3340 modules identified for hip BMD only in Meta7. As candidate modules, they were assessed for the biological relevance to BMD by gene set enrichment analysis in 2 expression profiles generated from circulating monocytes in subjects with low versus high BMD values. Interestingly, there were 2 modules significantly enriched in monocytes from the low BMD group in both gene expression datasets (nominal P value <.05). Two modules had 16 nonredundant genes. Functional enrichment analysis revealed that both modules were enriched for genes involved in Wnt receptor signaling and osteoblast differentiation. Conclusion: We highlighted 2 modules and novel genes playing important roles in the regulation of bone mass, providing important clues for therapeutic approaches for osteoporosis. PMID:25119315

Schizophrenia with prominent catatonic features ('catatonic schizophrenia'). II. Factor analysis of the catatonic syndrome.

PubMed

Ungvari, Gabor S; Goggins, William; Leung, Siu-Kau; Gerevich, Jozsef

2007-03-30

Previous factor analyses of catatonia have yielded conflicting results for several reasons including small and/or diagnostically heterogeneous samples and incomparability or lack of standardized assessment. This study examined the factor structure of catatonia in a large, diagnostically homogenous sample of patients with chronic schizophrenia using standardized rating instruments. A random sample of 225 Chinese inpatients diagnosed with schizophrenia according to DSM-IV criteria were selected from the long-stay wards of a psychiatric hospital. They were assessed with a battery of rating scales measuring psychopathology, extrapyramidal motor status, and level of functioning. Catatonia was rated using the Bush-Francis Catatonia Rating Scale. Factor analysis using principal component analysis and Varimax rotation with Kaiser normalization was performed. Four factors were identified with Eigenvalues of 3.27, 2.58, 2.28 and 1.88. The percentage of variance explained by each of the four factors was 15.9%, 12.0%, 11.8% and 10.2% respectively, and together they explained 49.9% of the total variance. Factor 1 loaded on "negative/withdrawn" phenomena, Factor 2 on "automatic" phenomena, Factor 3 on "repetitive/echo" phenomena and Factor 4 on "agitated/resistive" phenomena. In multivariate linear regression analysis negative symptoms and akinesia were associated with 'negative' catatonic symptoms, antipsychotic doses and atypical antipsychotics with 'automatic' symptoms, length of current admission, severity of psychopathology and younger age at onset with 'repetitive' symptoms and age, poor functioning and severity of psychopathology with 'agitated' catatonic symptom scores. The results support recent findings that four main factors underlie catatonic signs/symptoms in chronic schizophrenia.

Bootstrap Standard Error Estimates in Dynamic Factor Analysis

ERIC Educational Resources Information Center

Zhang, Guangjian; Browne, Michael W.

2010-01-01

Dynamic factor analysis summarizes changes in scores on a battery of manifest variables over repeated measurements in terms of a time series in a substantially smaller number of latent factors. Algebraic formulae for standard errors of parameter estimates are more difficult to obtain than in the usual intersubject factor analysis because of the…

Factor Analysis of the Autism Spectrum Screening Questionnaire

ERIC Educational Resources Information Center

Posserud, Britt; Lundervold, Astri J.; Steijnen, Maaike C.; Verhoeven, Sophie; Stormark, Kjell Morten; Gillberg, Christopher

2008-01-01

The present study investigated the factor structure of parent and teacher Autism Spectrum Screening Questionnaire (ASSQ) in a population of 7-9 years old children. For validation purposes, factors derived were correlated with results on the Strengths and Difficulties Questionnaire (SDQ). A three-factor solution was identified on both parent and…

Risk factors for incidental durotomy during lumbar surgery: a retrospective study by multivariate analysis.

PubMed

Chen, Zhixiang; Shao, Peng; Sun, Qizhao; Zhao, Dong

2015-03-01

The purpose of the present study was to use a prospectively collected data to evaluate the rate of incidental durotomy (ID) during lumbar surgery and determine the associated risk factors by using univariate and multivariate analysis. We retrospectively reviewed 2184 patients who underwent lumbar surgery from January 1, 2009 to December 31, 2011 at a single hospital. Patients with ID (n=97) were compared with the patients without ID (n=2019). The influences of several potential risk factors that might affect the occurrence of ID were assessed using univariate and multivariate analyses. The overall incidence of ID was 4.62%. Univariate analysis demonstrated that older age, diabetes, lumbar central stenosis, posterior approach, revision surgery, prior lumber surgery and minimal invasive surgery are risk factors for ID during lumbar surgery. However, multivariate analysis identified older age, prior lumber surgery, revision surgery, and minimally invasive surgery as independent risk factors. Older age, prior lumber surgery, revision surgery, and minimal invasive surgery were independent risk factors for ID during lumbar surgery. These findings may guide clinicians making future surgical decisions regarding ID and aid in the patient counseling process to alleviate risks and complications. Copyright © 2015 Elsevier B.V. All rights reserved.

Diversity Outbred Mice Identify Population-Based Exposure Thresholds and Genetic Factors that Influence Benzene-Induced Genotoxicity

PubMed Central

Gatti, Daniel M.; Morgan, Daniel L.; Kissling, Grace E.; Shockley, Keith R.; Knudsen, Gabriel A.; Shepard, Kim G.; Price, Herman C.; King, Deborah; Witt, Kristine L.; Pedersen, Lars C.; Munger, Steven C.; Svenson, Karen L.; Churchill, Gary A.

2014-01-01

Background Inhalation of benzene at levels below the current exposure limit values leads to hematotoxicity in occupationally exposed workers. Objective We sought to evaluate Diversity Outbred (DO) mice as a tool for exposure threshold assessment and to identify genetic factors that influence benzene-induced genotoxicity. Methods We exposed male DO mice to benzene (0, 1, 10, or 100 ppm; 75 mice/exposure group) via inhalation for 28 days (6 hr/day for 5 days/week). The study was repeated using two independent cohorts of 300 animals each. We measured micronuclei frequency in reticulocytes from peripheral blood and bone marrow and applied benchmark concentration modeling to estimate exposure thresholds. We genotyped the mice and performed linkage analysis. Results We observed a dose-dependent increase in benzene-induced chromosomal damage and estimated a benchmark concentration limit of 0.205 ppm benzene using DO mice. This estimate is an order of magnitude below the value estimated using B6C3F1 mice. We identified a locus on Chr 10 (31.87 Mb) that contained a pair of overexpressed sulfotransferases that were inversely correlated with genotoxicity. Conclusions The genetically diverse DO mice provided a reproducible response to benzene exposure. The DO mice display interindividual variation in toxicity response and, as such, may more accurately reflect the range of response that is observed in human populations. Studies using DO mice can localize genetic associations with high precision. The identification of sulfotransferases as candidate genes suggests that DO mice may provide additional insight into benzene-induced genotoxicity. Citation French JE, Gatti DM, Morgan DL, Kissling GE, Shockley KR, Knudsen GA, Shepard KG, Price HC, King D, Witt KL, Pedersen LC, Munger SC, Svenson KL, Churchill GA. 2015. Diversity Outbred mice identify population-based exposure thresholds and genetic factors that influence benzene-induced genotoxicity. Environ Health Perspect 123:237�

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

PubMed

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

2018-04-01

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

Identifying risk factors for victimization among male prisoners in Taiwan.

PubMed

Kuo, Shih-Ya; Cuvelier, Steven J; Huang, Yung-Shun

2014-02-01

This study identified risk factors for prison victimization in Taiwan with an application of Western literature and assessed the extent of its applicability in an Eastern context. The sample was drawn from four male prisons located in Northern, Central, Southern, and Eastern Taiwan; a total of 1,181 valid surveys were collected. The results generally support the major findings of the extant Western studies. Crowding, however, was not significantly associated with the risk of victimization in any of the statistical models, which might be related to the different experiences and living conditions in the free community between Taiwanese and American inmates. This study generated clear policy implications, which may reduce prison victimization and engender a greater sense of well-being in the prison environment.

MONKEY: Identifying conserved transcription-factor binding sitesin multiple alignments using a binding site-specific evolutionarymodel

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

Moses, Alan M.; Chiang, Derek Y.; Pollard, Daniel A.

2004-10-28

We introduce a method (MONKEY) to identify conserved transcription-factor binding sites in multispecies alignments. MONKEY employs probabilistic models of factor specificity and binding site evolution, on which basis we compute the likelihood that putative sites are conserved and assign statistical significance to each hit. Using genomes from the genus Saccharomyces, we illustrate how the significance of real sites increases with evolutionary distance and explore the relationship between conservation and function.

Risk factors for new onset diabetes mellitus after liver transplantation: A meta-analysis.

PubMed

Li, Da-Wei; Lu, Tian-Fei; Hua, Xiang-Wei; Dai, Hui-Juan; Cui, Xiao-Lan; Zhang, Jian-Jian; Xia, Qiang

2015-05-28

To determine the risk factors for new-onset diabetes mellitus (NODM) after liver transplantation by conducting a systematic review and meta-analysis. We electronically searched the databases of MEDLINE, EMBASE and the Cochrane Library from January 1980 to December 2013 to identify relevant studies reporting risk factors for NODM after liver transplantation. Two authors independently assessed the trials for inclusion and extracted the data. Discrepancies were resolved in consultation with a third reviewer. All statistical analyses were performed with the RevMan5.0 software (The Cochrane Collaboration, Oxford, United Kingdom). Pooled odds ratios (OR) or weighted mean differences (WMD) with 95% confidence intervals (CIs) were calculated using either a fixed effects or a random effects model, based on the presence (I (2) < 50%) or absence (I (2) > 50%) of significant heterogeneity. Twenty studies with 4580 patients were included in the meta-analysis, all of which were retrospective. The meta-analysis identified the following significant risk factors: hepatitis C virus (HCV) infection (OR = 2.68; 95%CI: 1.92-3.72); a family history of diabetes (OR = 1.69, 95%CI: 1.09-2.63, P < 0.00001); male gender (OR = 1.53; 95%CI: 1.24-1.90; P < 0.0001); impaired fasting glucose (IFG; OR = 3.27; 95%CI: 1.84-5.81; P < 0.0001); a family history of diabetes (OR = 1.69; 95%CI: 1.09-2.63; P = 0.02); use of tacrolimus (OR = 1.34; 95%CI: 1.03-1.76; P = 0.03) and body mass index (BMI)(WMD = 1.19, 95%CI: 0.69-1.68, P < 0.00001). Other factors, such as hepatitis B virus infection and alcoholism, were not found to be associated with the incidence of NODM. The study showed that HCV infection, IFG, a family history of diabetes, male gender, tacrolimus and BMI are risk factors for NODM after liver transplantation.

How Factor Analysis Can Be Used in Classification.

ERIC Educational Resources Information Center

Harman, Harry H.

This is a methodological study that suggests a taxometric technique for objective classification of yeasts. It makes use of the minres method of factor analysis and groups strains of yeast according to their factor profiles. The similarities are judged in the higher-dimensional space determined by the factor analysis, but otherwise rely on the…

Pediatric malignant hyperthermia: risk factors, morbidity, and mortality identified from the Nationwide Inpatient Sample and Kids' Inpatient Database.

PubMed

Salazar, Jose H; Yang, Jingyan; Shen, Liang; Abdullah, Fizan; Kim, Tae W

2014-12-01

Malignant Hyperthermia (MH) is a potentially fatal metabolic disorder. Due to its rarity, limited evidence exists about risk factors, morbidity, and mortality especially in children. Using the Nationwide Inpatient Sample and the Kid's Inpatient Database (KID), admissions with the ICD-9 code for MH (995.86) were extracted for patients 0-17 years of age. Demographic characteristics were analyzed. Logistic regression was performed to identify patient and hospital characteristics associated with mortality. A subset of patients with a surgical ICD-9 code in the KID was studied to calculate the prevalence of MH in the dataset. A total of 310 pediatric admissions were seen in 13 nonoverlapping years of data. Patients had a mortality of 2.9%. Male sex was predominant (64.8%), and 40.5% of the admissions were treated at centers not identified as children's hospitals. The most common associated diagnosis was rhabdomyolysis, which was present in 26 cases. Regression with the outcome of mortality did not yield significant differences between demographic factors, age, sex race, or hospital type, pediatric vs nonpediatric. Within a surgical subset of 530,449 admissions, MH was coded in 55, giving a rate of 1.04 cases per 10,000 cases. This study is the first to combine two large databases to study MH in the pediatric population. The analysis provides an insight into the risk factors, comorbidities, mortality, and prevalence of MH in the United States population. Until more methodologically rigorous, large-scale studies are done, the use of databases will continue to be the optimal method to study rare diseases. © 2014 John Wiley & Sons Ltd.

Identifying crash contributory factors at urban roundabouts and using association rules to explore their relationships to different crash types.

PubMed

Montella, Alfonso

2011-07-01

The use of roundabouts improves intersection safety by eliminating or altering conflict types, reducing crash severity, and causing drivers to reduce speeds. However, roundabout performances can degrade if precautions are not taken during either the design or the operation phase. Therefore, additional information on the safety of the roundabouts is extremely helpful for planners and designers in identifying existing deficiencies and in refining the design criteria currently being used. The aim of the paper was to investigate the crash contributory factors in 15 urban roundabouts located in Italy and to study the interdependences between these factors. The crash data refer to the period 2003-2008. The identification of the crash contributory factors was based on site inspections and rigorous analyses performed by a team of specialists with a relevant road safety engineering background. Each roundabout was inspected once every year from 2004 to 2009, both in daytime and in nighttime. Overall, 62 different contributory factors and 2156 total contributory factors were identified. In 51 crashes, a single contributory factor was found, whereas in the other 223 crashes, a combination of contributory factors was identified. Given the large amount of data, the interdependences between the contributory factors and between the contributory factors and the different crash types were explored by an association discovery. Association discovery is the identification of sets of items (i.e., crash contributory factors and crash types in our study) that occur together in a given event (i.e., a crash in our study). The rules were filtered by support, confidence, and lift. As a result, 112 association rules were discovered. Overall, numerous contributory factors related to the road and environment deficiencies but not related to the road user or to the vehicle were identified. The most important factors related to geometric design were the radius of deflection and the deviation angle

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

PubMed

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

2017-11-01

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

Genome-Wide miRNA Analysis Identifies miR-188-3p as a Novel Prognostic Marker and Molecular Factor Involved in Colorectal Carcinogenesis.

PubMed

Pichler, Martin; Stiegelbauer, Verena; Vychytilova-Faltejskova, Petra; Ivan, Cristina; Ling, Hui; Winter, Elke; Zhang, Xinna; Goblirsch, Matthew; Wulf-Goldenberg, Annika; Ohtsuka, Masahisa; Haybaeck, Johannes; Svoboda, Marek; Okugawa, Yoshinaga; Gerger, Armin; Hoefler, Gerald; Goel, Ajay; Slaby, Ondrej; Calin, George Adrian

2017-03-01

Purpose: Characterization of colorectal cancer transcriptome by high-throughput techniques has enabled the discovery of several differentially expressed genes involving previously unreported miRNA abnormalities. Here, we followed a systematic approach on a global scale to identify miRNAs as clinical outcome predictors and further validated them in the clinical and experimental setting. Experimental Design: Genome-wide miRNA sequencing data of 228 colorectal cancer patients from The Cancer Genome Atlas dataset were analyzed as a screening cohort to identify miRNAs significantly associated with survival according to stringent prespecified criteria. A panel of six miRNAs was further validated for their prognostic utility in a large independent validation cohort ( n = 332). In situ hybridization and functional experiments in a panel of colorectal cancer cell lines and xenografts further clarified the role of clinical relevant miRNAs. Results: Six miRNAs (miR-92b-3p, miR-188-3p, miR-221-5p, miR-331-3p, miR-425-3p, and miR-497-5p) were identified as strong predictors of survival in the screening cohort. High miR-188-3p expression proves to be an independent prognostic factor [screening cohort: HR = 4.137; 95% confidence interval (CI), 1.568-10.917; P = 0.004; validation cohort: HR = 1.538; 95% CI, 1.107-2.137; P = 0.010, respectively]. Forced miR-188-3p expression increased migratory behavior of colorectal cancer cells in vitro and metastases formation in vivo ( P < 0.05). The promigratory role of miR-188-3p is mediated by direct interaction with MLLT4, a novel identified player involved in colorectal cancer cell migration. Conclusions: miR-188-3p is a novel independent prognostic factor in colorectal cancer patients, which can be partly explained by its effect on MLLT4 expression and migration of cancer cells. Clin Cancer Res; 23(5); 1323-33. ©2016 AACR . ©2016 American Association for Cancer Research.

Genome-Wide miRNA Analysis Identifies miR-188-3p as a Novel Prognostic Marker and Molecular Factor Involved in Colorectal Carcinogenesis

PubMed Central

Pichler, Martin; Stiegelbauer, Verena; Vychytilova-Faltejskova, Petra; Ivan, Cristina; Ling, Hui; Winter, Elke; Zhang, Xinna; Goblirsch, Matthew; Wulf-Goldenberg, Annika; Ohtsuka, Masahisa; Haybaeck, Johannes; Svoboda, Marek; Okugawa, Yoshinaga; Gerger, Armin; Hoefler, Gerald; Goel, Ajay; Slaby, Ondrej; Calin, George Adrian

2017-01-01

Purpose Characterization of colorectal cancer transcriptome by high-throughput techniques has enabled the discovery of several differentially expressed genes involving previously unreported miRNA abnormalities. Here, we followed a systematic approach on a global scale to identify miRNAs as clinical outcome predictors and further validated them in the clinical and experimental setting. Experimental Design Genome-wide miRNA sequencing data of 228 colorectal cancer patients from The Cancer Genome Atlas dataset were analyzed as a screening cohort to identify miRNAs significantly associated with survival according to stringent prespecified criteria. A panel of six miRNAs was further validated for their prognostic utility in a large independent validation cohort (n = 332). In situ hybridization and functional experiments in a panel of colorectal cancer cell lines and xenografts further clarified the role of clinical relevant miRNAs. Results Six miRNAs (miR-92b-3p, miR-188-3p, miR-221-5p, miR-331-3p, miR-425-3p, and miR-497-5p) were identified as strong predictors of survival in the screening cohort. High miR-188-3p expression proves to be an independent prognostic factor [screening cohort: HR = 4.137; 95% confidence interval (CI), 1.568–10.917; P = 0.004; validation cohort: HR = 1.538; 95% CI, 1.107–2.137; P = 0.010, respectively]. Forced miR-188-3p expression increased migratory behavior of colorectal cancer cells in vitro and metastases formation in vivo (P < 0.05). The promigratory role of miR-188-3p is mediated by direct interaction with MLLT4, a novel identified player involved in colorectal cancer cell migration. Conclusions miR-188-3p is a novel independent prognostic factor in colorectal cancer patients, which can be partly explained by its effect on MLLT4 expression and migration of cancer cells. PMID:27601590

An exploratory factor analysis of inflammatory and coagulation markers associated with femoral artery atherosclerosis in the San Diego Population Study.

PubMed

Egnot, Natalie Suder; Barinas-Mitchell, Emma; Criqui, Michael H; Allison, Matthew A; Ix, Joachim H; Jenny, Nancy S; Wassel, Christina L

2018-04-01

Several biomarkers of inflammation and coagulation have been implicated in lower extremity atherosclerosis. We utilized an exploratory factor analysis (EFA) to identify distinct factors derived from circulating inflammatory and coagulation biomarkers then examined the associations of these factors with measures of lower extremity subclinical atherosclerosis, including the ankle-brachial index (ABI), common and superficial femoral intima-media thickness (IMT), and atherosclerotic plaque presence, burden, and characteristics. The San Diego Population Study (SDPS) is a prospective, community-living, multi-ethnic cohort of 1103 men and women averaged age 70. Regression analysis was used to assess cross-sectional associations between the identified groupings of biomarkers (factors) and the ABI and femoral artery atherosclerosis measurements. Two biomarker factors emerged from the factor analysis. Factor 1 consisting of C-reactive protein (CRP), interleukin (IL)-6, and fibrinogen was significantly associated with higher odds (OR = 1.99, p < 0.01) of a borderline ABI value (0.91-0.99), while Factor 2 containing D-dimer and pentraxin (PTX)-3 was significantly associated with higher common femoral artery (CFA) IMT (β = 0.23, p < 0.01) and lower ABI (β = -0.03, p < 0.01). Two groupings of biomarkers were identified via EFA of seven circulating biomarkers of inflammation and coagulation. These distinct groups are differentially associated with markers of lower extremity subclinical atherosclerosis. Our findings suggest that high inflammatory and coagulation burden were better markers of more severe lower-extremity disease as indicated by low ABI rather than early atherosclerotic lesion development in the femoral artery. Copyright © 2018 Elsevier Ltd. All rights reserved.

A Case-Control Study to Identify Risk Factors Associated with Avian Influenza Subtype H9N2 on Commercial Poultry Farms in Pakistan

PubMed Central

Chaudhry, Mamoona; Rashid, Hamad B.; Thrusfield, Michael; Welburn, Sue; Bronsvoort, Barend MdeC.

2015-01-01

A 1:1 matched case-control study was conducted to identify risk factors for avian influenza subtype H9N2 infection on commercial poultry farms in 16 districts of Punjab, and 1 administrative unit of Pakistan. One hundred and thirty-three laboratory confirmed positive case farms were matched on the date of sample submission with 133 negative control farms. The association between a series of farm-level characteristics and the presence or absence of H9N2 was assessed by univariable analysis. Characteristics associated with H9N2 risk that passed the initial screening were included in a multivariable conditional logistic regression model. Manual and automated approaches were used, which produced similar models. Key risk factors from all approaches included selling of eggs/birds directly to live bird retail stalls, being near case/infected farms, a previous history of infectious bursal disease (IBD) on the farm and having cover on the water storage tanks. The findings of current study are in line with results of many other studies conducted in various countries to identify similar risk factors for AI subtype H9N2 infection. Enhancing protective measures and controlling risks identified in this study could reduce spread of AI subtype H9N2 and other AI viruses between poultry farms in Pakistan. PMID:25774768

Regression Analysis to Identify Factors Associated with Household Salt Iodine Content at the Sub-National Level in Bangladesh, India, Ghana and Senegal

PubMed Central

Knowles, Jacky; Kupka, Roland; Dumble, Sam; Garrett, Greg S.; Pandav, Chandrakant S.; Yadav, Kapil; Nahar, Baitun; Touré, Ndeye Khady; Amoaful, Esi Foriwa; Gorstein, Jonathan

2018-01-01

Regression analyses of data from stratified, cluster sample, household iodine surveys in Bangladesh, India, Ghana and Senegal were conducted to identify factors associated with household access to adequately iodised salt. For all countries, in single variable analyses, household salt iodine was significantly different (p < 0.05) between strata (geographic areas with representative data, defined by survey design), and significantly higher (p < 0.05) among households: with better living standard scores, where the respondent knew about iodised salt and/or looked for iodised salt at purchase, using salt bought in a sealed package, or using refined grain salt. Other country-level associations were also found. Multiple variable analyses showed a significant association between salt iodine and strata (p < 0.001) in India, Ghana and Senegal and that salt grain type was significantly associated with estimated iodine content in all countries (p < 0.001). Salt iodine relative to the reference (coarse salt) ranged from 1.3 (95% CI 1.2, 1.5) times higher for fine salt in Senegal to 3.6 (95% CI 2.6, 4.9) times higher for washed and 6.5 (95% CI 4.9, 8.8) times higher for refined salt in India. Sub-national data are required to monitor equity of access to adequately iodised salt. Improving household access to refined iodised salt in sealed packaging, would improve iodine intake from household salt in all four countries in this analysis, particularly in areas where there is significant small-scale salt production. PMID:29671774

Analysis of factors influencing safety management for metro construction in China.

PubMed

Yu, Q Z; Ding, L Y; Zhou, C; Luo, H B

2014-07-01

With the rapid development of urbanization in China, the number and size of metro construction projects are increasing quickly. At the same time, and increasing number of accidents in metro construction make it a disturbing focus of social attention. In order to improve safety management in metro construction, an investigation of the participants' perspectives on safety factors in China metro construction has been conducted to identify the key safety factors, and their ranking consistency among the main participants, including clients, consultants, designers, contractors and supervisors. The result of factor analysis indicates that there are five key factors which influence the safety of metro construction including safety attitude, construction site safety, government supervision, market restrictions and task unpredictability. In addition, ANOVA and Spearman rank correlation coefficients were performed to test the consistency of the means rating and the ranking of safety factors. The results indicated that the main participants have significant disagreement about the importance of safety factors on more than half of the items. Suggestions and recommendations on practical countermeasures to improve metro construction safety management in China are proposed. Copyright © 2013 Elsevier Ltd. All rights reserved.

SNPs in putative regulatory regions identified by human mouse comparative sequencing and transcription factor binding site data

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

Banerjee, Poulabi; Bahlo, Melanie; Schwartz, Jody R.

2002-01-01

Genome wide disease association analysis using SNPs is being explored as a method for dissecting complex genetic traits and a vast number of SNPs have been generated for this purpose. As there are cost and throughput limitations of genotyping large numbers of SNPs and statistical issues regarding the large number of dependent tests on the same data set, to make association analysis practical it has been proposed that SNPs should be prioritized based on likely functional importance. The most easily identifiable functional SNPs are coding SNPs (cSNPs) and accordingly cSNPs have been screened in a number of studies. SNPs inmore » gene regulatory sequences embedded in noncoding DNA are another class of SNPs suggested for prioritization due to their predicted quantitative impact on gene expression. The main challenge in evaluating these SNPs, in contrast to cSNPs is a lack of robust algorithms and databases for recognizing regulatory sequences in noncoding DNA. Approaches that have been previously used to delineate noncoding sequences with gene regulatory activity include cross-species sequence comparisons and the search for sequences recognized by transcription factors. We combined these two methods to sift through mouse human genomic sequences to identify putative gene regulatory elements and subsequently localized SNPs within these sequences in a 1 Megabase (Mb) region of human chromosome 5q31, orthologous to mouse chromosome 11 containing the Interleukin cluster.« less

Co-expression analysis identifies CRC and AP1 the regulator of Arabidopsis fatty acid biosynthesis.

PubMed

Han, Xinxin; Yin, Linlin; Xue, Hongwei

2012-07-01

Fatty acids (FAs) play crucial rules in signal transduction and plant development, however, the regulation of FA metabolism is still poorly understood. To study the relevant regulatory network, fifty-eight FA biosynthesis genes including de novo synthases, desaturases and elongases were selected as "guide genes" to construct the co-expression network. Calculation of the correlation between all Arabidopsis thaliana (L.) genes with each guide gene by Arabidopsis co-expression dating mining tools (ACT) identifies 797 candidate FA-correlated genes. Gene ontology (GO) analysis of these co-expressed genes showed they are tightly correlated to photosynthesis and carbohydrate metabolism, and function in many processes. Interestingly, 63 transcription factors (TFs) were identified as candidate FA biosynthesis regulators and 8 TF families are enriched. Two TF genes, CRC and AP1, both correlating with 8 FA guide genes, were further characterized. Analyses of the ap1 and crc mutant showed the altered total FA composition of mature seeds. The contents of palmitoleic acid, stearic acid, arachidic acid and eicosadienoic acid are decreased, whereas that of oleic acid is increased in ap1 and crc seeds, which is consistent with the qRT-PCR analysis revealing the suppressed expression of the corresponding guide genes. In addition, yeast one-hybrid analysis and electrophoretic mobility shift assay (EMSA) revealed that CRC can bind to the promoter regions of KCS7 and KCS15, indicating that CRC may directly regulate FA biosynthesis. © 2012 Institute of Botany, Chinese Academy of Sciences.

Independent Pre-Transplant Recipient Cancer Risk Factors after Kidney Transplantation and the Utility of G-Chart Analysis for Clinical Process Control

PubMed Central

Kurok, Marlene; Goldis, Alon; Dreier, Maren; Kaltenborn, Alexander; Gwinner, Wilfried; Barthold, Marc; Liebeneiner, Jan; Winny, Markus; Klempnauer, Jürgen; Kleine, Moritz

2016-01-01

Background The aim of this study is to identify independent pre-transplant cancer risk factors after kidney transplantation and to assess the utility of G-chart analysis for clinical process control. This may contribute to the improvement of cancer surveillance processes in individual transplant centers. Patients and Methods 1655 patients after kidney transplantation at our institution with a total of 9,425 person-years of follow-up were compared retrospectively to the general German population using site-specific standardized-incidence-ratios (SIRs) of observed malignancies. Risk-adjusted multivariable Cox regression was used to identify independent pre-transplant cancer risk factors. G-chart analysis was applied to determine relevant differences in the frequency of cancer occurrences. Results Cancer incidence rates were almost three times higher as compared to the matched general population (SIR = 2.75; 95%-CI: 2.33–3.21). Significantly increased SIRs were observed for renal cell carcinoma (SIR = 22.46), post-transplant lymphoproliferative disorder (SIR = 8.36), prostate cancer (SIR = 2.22), bladder cancer (SIR = 3.24), thyroid cancer (SIR = 10.13) and melanoma (SIR = 3.08). Independent pre-transplant risk factors for cancer-free survival were age <52.3 years (p = 0.007, Hazard ratio (HR): 0.82), age >62.6 years (p = 0.001, HR: 1.29), polycystic kidney disease other than autosomal dominant polycystic kidney disease (ADPKD) (p = 0.001, HR: 0.68), high body mass index in kg/m2 (p<0.001, HR: 1.04), ADPKD (p = 0.008, HR: 1.26) and diabetic nephropathy (p = 0.004, HR = 1.51). G-chart analysis identified relevant changes in the detection rates of cancer during aftercare with no significant relation to identified risk factors for cancer-free survival (p<0.05). Conclusions Risk-adapted cancer surveillance combined with prospective G-chart analysis likely improves cancer surveillance schemes by adapting processes to identified risk factors and by using G-chart alarm

Risk Factors of Mortality from All Asbestos-Related Diseases: A Competing Risk Analysis.

PubMed

Abós-Herràndiz, Rafael; Rodriguez-Blanco, Teresa; Garcia-Allas, Isabel; Rosell-Murphy, Isabel-Magdalena; Albertí-Casas, Constança; Tarrés, Josep; Krier-Günther, Illona; Martinez-Artés, Xavier; Orriols, Ramon; Grimau-Malet, Isidre; Canela-Soler, Jaume

2017-01-01

The mortality from all malignant and nonmalignant asbestos-related diseases remains unknown. The authors assessed the incidence and risk factors for all asbestos-related deaths. The sample included 544 patients from an asbestos-exposed community in the area of Barcelona (Spain), between Jan 1, 1970, and Dec 31, 2006. Competing risk regression through a subdistribution hazard analysis was used to estimate risk factors for the outcomes. Asbestos-related deaths were observed in 167 (30.7%) patients and 57.5% of these deaths were caused by some type of mesothelioma. The incidence rate after diagnosis was 3,600 per 100,000 person-years. In 7.5% of patients death was non-asbestos-related, while pleural and peritoneal mesothelioma were identified in 87 (16.0%) and 18 (3.3%) patients, respectively. Age, sex, household exposure, cumulative nonmalignant asbestos-related disease, and single malignant pathology were identified as risk factors for asbestos-related death. These findings suggest the need to develop a preventive approach to the community and to improve the clinical follow-up process of these patients.

Quantitative label-free proteomic analysis of human urine to identify novel candidate protein biomarkers for schistosomiasis.

PubMed

Onile, Olugbenga Samson; Calder, Bridget; Soares, Nelson C; Anumudu, Chiaka I; Blackburn, Jonathan M

2017-11-01

Schistosomiasis is a chronic neglected tropical disease that is characterized by continued inflammatory challenges to the exposed population and it has been established as a possible risk factor in the aetiology of bladder cancer. Improved diagnosis of schistosomiasis and its associated pathology is possible through mass spectrometry to identify biomarkers among the infected population, which will influence early detection of the disease and its subtle morbidity. A high-throughput proteomic approach was used to analyse human urine samples for 49 volunteers from Eggua, a schistosomiasis endemic community in South-West, Nigeria. The individuals were previously screened for Schistosoma haematobium and structural bladder pathologies via microscopy and ultrasonography respectively. Samples were categorised into schistosomiasis, schistosomiasis with bladder pathology, bladder pathology, and a normal healthy control group. These samples were analysed to identify potential protein biomarkers. A total of 1306 proteins and 9701 unique peptides were observed in this study (FDR = 0.01). Fifty-four human proteins were found to be potential biomarkers for schistosomiasis and bladder pathologies due to schistosomiasis by label-free quantitative comparison between groups. Thirty-six (36) parasite-derived potential biomarkers were also identified, which include some existing putative schistosomiasis biomarkers that have been previously reported. Some of these proteins include Elongation factor 1 alpha, phosphopyruvate hydratase, histone H4 and heat shock proteins (HSP 60, HSP 70). These findings provide an in-depth analysis of potential schistosoma and human host protein biomarkers for diagnosis of chronic schistosomiasis caused by Schistosoma haematobium and its pathogenesis.

De novo Transcriptome Analysis of Miscanthus lutarioriparius Identifies Candidate Genes in Rhizome Development

PubMed Central

Hu, Ruibo; Yu, Changjiang; Wang, Xiaoyu; Jia, Chunlin; Pei, Shengqiang; He, Kang; He, Guo; Kong, Yingzhen; Zhou, Gongke

2017-01-01

HIGHLIGHT De novo transcriptome profiling of five tissues reveals candidate genes putatively involved in rhizome development in M. lutarioriparius. Miscanthus lutarioriparius is a promising lignocellulosic feedstock for second-generation bioethanol production. However, the genomic resource for this species is relatively limited thus hampers our understanding of the molecular mechanisms underlying many important biological processes. In this study, we performed the first de novo transcriptome analysis of five tissues (leaf, stem, root, lateral bud and rhizome bud) of M. lutarioriparius with an emphasis to identify putative genes involved in rhizome development. Approximately 66 gigabase (GB) paired-end clean reads were obtained and assembled into 169,064 unigenes with an average length of 759 bp. Among these unigenes, 103,899 (61.5%) were annotated in seven public protein databases. Differential gene expression profiling analysis revealed that 4,609, 3,188, 1,679, 1,218, and 1,077 genes were predominantly expressed in root, leaf, stem, lateral bud, and rhizome bud, respectively. Their expression patterns were further classified into 12 distinct clusters. Pathway enrichment analysis revealed that genes predominantly expressed in rhizome bud were mainly involved in primary metabolism and hormone signaling and transduction pathways. Noteworthy, 19 transcription factors (TFs) and 16 hormone signaling pathway-related genes were identified to be predominantly expressed in rhizome bud compared with the other tissues, suggesting putative roles in rhizome formation and development. In addition, a predictive regulatory network was constructed between four TFs and six auxin and abscisic acid (ABA) -related genes. Furthermore, the expression of 24 rhizome-specific genes was further validated by quantitative real-time RT-PCR (qRT-PCR) analysis. Taken together, this study provide a global portrait of gene expression across five different tissues and reveal preliminary insights

Risk factors for persistent problems following acute whiplash injury: update of a systematic review and meta-analysis.

PubMed

Walton, David M; Macdermid, Joy C; Giorgianni, Anthony A; Mascarenhas, Joanna C; West, Stephen C; Zammit, Caroline A

2013-02-01

Systematic review and meta-analysis. To update a previous review and meta-analysis on risk factors for persistent problems following whiplash secondary to a motor vehicle accident. Prognosis in whiplash-associated disorder (WAD) has become an active area of research, perhaps owing to the difficulty of treating chronic problems. A previously published review and meta-analysis of prognostic factors included primary sources up to May 2007. Since that time, more research has become available, and an update to that original review is warranted. A systematic search of international databases was conducted, with rigorous inclusion criteria focusing on studies published between May 2007 and May 2012. Articles were scored, and data were extracted and pooled to estimate the odds ratio for any factor that had at least 3 independent data points in the literature. Four new cohorts (n = 1121) were identified. In combination with findings of a previous review, 12 variables were found to be significant predictors of poor outcome following whiplash, 9 of which were new (n = 2) or revised (n = 7) as a result of additional data. The significant variables included high baseline pain intensity (greater than 5.5/10), report of headache at inception, less than postsecondary education, no seatbelt in use during the accident, report of low back pain at inception, high Neck Disability Index score (greater than 14.5/50), preinjury neck pain, report of neck pain at inception (regardless of intensity), high catastrophizing, female sex, WAD grade 2 or 3, and WAD grade 3 alone. Those variables robust to publication bias included high pain intensity, female sex, report of headache at inception, less than postsecondary education, high Neck Disability Index score, and WAD grade 2 or 3. Three existing variables (preaccident history of headache, rear-end collision, older age) and 1 additional novel variable (collision severity) were refined or added in this updated review but showed no significant

Potential Psychosocial Risk Factors for Chronic TMD: Descriptive Data and Empirically Identified Domains from the OPPERA Case-Control Study

PubMed Central

Fillingim, Roger B.; Ohrbach, Richard; Greenspan, Joel D.; Knott, Charles; Dubner, Ronald; Bair, Eric; Baraian, Cristina; Slade, Gary D.; Maixner, William

2011-01-01

Case-control studies have consistently associated psychosocial factors with chronic pain in general, and with temporomandibular disorders (TMD) specifically. Moreover, a handful of prospective studies suggest that pre-existing psychosocial characteristics represent risk factors for new onset TMD. The current study presents psychosocial findings from the baseline case-control study of the Orofacial Pain Prospective Evaluation and Risk Assessment (OPPERA) cooperative agreement. For this study, 1,633 TMD-free controls and 185 TMD cases completed a battery of psychosocial instruments assessing general psychosocial adjustment and personality, affective distress, psychosocial stress, somatic awareness, and pain coping and catastrophizing. In bivariate and demographically-adjusted analyses, odds of TMD were associated with higher levels of psychosocial symptoms, affective distress, somatic awareness, and pain catastrophizing. Among controls, significant gender and ethnic group differences in psychosocial measures were observed, consistent with previous findings. Principal component analysis was undertaken to identify latent constructs revealing four components: stress and negative affectivity, global psychosocial symptoms, passive pain coping, and active pain coping. These findings provide further evidence of associations between psychosocial factors and TMD. Future prospective analyses in the OPPERA cohort will determine if the premorbid presence of these psychosocial factors predicts increased risk for developing new-onset TMD. PMID:22074752

Identification of Analytical Factors Affecting Complex Proteomics Profiles Acquired in a Factorial Design Study with Analysis of Variance: Simultaneous Component Analysis.

PubMed

Mitra, Vikram; Govorukhina, Natalia; Zwanenburg, Gooitzen; Hoefsloot, Huub; Westra, Inge; Smilde, Age; Reijmers, Theo; van der Zee, Ate G J; Suits, Frank; Bischoff, Rainer; Horvatovich, Péter

2016-04-19

Complex shotgun proteomics peptide profiles obtained in quantitative differential protein expression studies, such as in biomarker discovery, may be affected by multiple experimental factors. These preanalytical factors may affect the measured protein abundances which in turn influence the outcome of the associated statistical analysis and validation. It is therefore important to determine which factors influence the abundance of peptides in a complex proteomics experiment and to identify those peptides that are most influenced by these factors. In the current study we analyzed depleted human serum samples to evaluate experimental factors that may influence the resulting peptide profile such as the residence time in the autosampler at 4 °C, stopping or not stopping the trypsin digestion with acid, the type of blood collection tube, different hemolysis levels, differences in clotting times, the number of freeze-thaw cycles, and different trypsin/protein ratios. To this end we used a two-level fractional factorial design of resolution IV (2(IV)(7-3)). The design required analysis of 16 samples in which the main effects were not confounded by two-factor interactions. Data preprocessing using the Threshold Avoiding Proteomics Pipeline (Suits, F.; Hoekman, B.; Rosenling, T.; Bischoff, R.; Horvatovich, P. Anal. Chem. 2011, 83, 7786-7794, ref 1) produced a data-matrix containing quantitative information on 2,559 peaks. The intensity of the peaks was log-transformed, and peaks having intensities of a low t-test significance (p-value > 0.05) and a low absolute fold ratio (<2) between the two levels of each factor were removed. The remaining peaks were subjected to analysis of variance (ANOVA)-simultaneous component analysis (ASCA). Permutation tests were used to identify which of the preanalytical factors influenced the abundance of the measured peptides most significantly. The most important preanalytical factors affecting peptide intensity were (1) the hemolysis level

Factors influencing societal response of nanotechnology: an expert stakeholder analysis.

PubMed

Gupta, Nidhi; Fischer, Arnout R H; van der Lans, Ivo A; Frewer, Lynn J

2012-05-01

Nanotechnology can be described as an emerging technology and, as has been the case with other emerging technologies such as genetic modification, different socio-psychological factors will potentially influence societal responses to its development and application. These factors will play an important role in how nanotechnology is developed and commercialised. This article aims to identify expert opinion on factors influencing societal response to applications of nanotechnology. Structured interviews with experts on nanotechnology from North West Europe were conducted using repertory grid methodology in conjunction with generalized Procrustes analysis to examine the psychological constructs underlying societal uptake of 15 key applications of nanotechnology drawn from different areas (e.g. medicine, agriculture and environment, chemical, food, military, sports, and cosmetics). Based on expert judgement, the main factors influencing societal response to different applications of nanotechnology will be the extent to which applications are perceived to be beneficial, useful, and necessary, and how 'real' and physically close to the end-user these applications are perceived to be by the public. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11051-012-0857-x) contains supplementary material, which is available to authorized users.

Dynamic factor analysis for estimating ground water arsenic trends.

PubMed

Kuo, Yi-Ming; Chang, Fi-John

2010-01-01

Drinking ground water containing high arsenic (As) concentrations has been associated with blackfoot disease and the occurrence of cancer along the southwestern coast of Taiwan. As a result, 28 ground water observation wells were installed to monitor the ground water quality in this area. Dynamic factor analysis (DFA) is used to identify common trends that represent unexplained variability in ground water As concentrations of decommissioned wells and to investigate whether explanatory variables (total organic carbon [TOC], As, alkalinity, ground water elevation, and rainfall) affect the temporal variation in ground water As concentration. The results of the DFA show that rainfall dilutes As concentration in areas under aquacultural and agricultural use. Different combinations of geochemical variables (As, alkalinity, and TOC) of nearby monitoring wells affected the As concentrations of the most decommissioned wells. Model performance was acceptable for 11 wells (coefficient of efficiency >0.50), which represents 52% (11/21) of the decommissioned wells. Based on DFA results, we infer that surface water recharge may be effective for diluting the As concentration, especially in the areas that are relatively far from the coastline. We demonstrate that DFA can effectively identify the important factors and common effects representing unexplained variability common to decommissioned wells on As variation in ground water and extrapolate information from existing monitoring wells to the nearby decommissioned wells.

A Review of CEFA Software: Comprehensive Exploratory Factor Analysis Program

ERIC Educational Resources Information Center

Lee, Soon-Mook

2010-01-01

CEFA 3.02(Browne, Cudeck, Tateneni, & Mels, 2008) is a factor analysis computer program designed to perform exploratory factor analysis. It provides the main properties that are needed for exploratory factor analysis, namely a variety of factoring methods employing eight different discrepancy functions to be minimized to yield initial…

Determination of important topographic factors for landslide mapping analysis using MLP network.

PubMed

Alkhasawneh, Mutasem Sh; Ngah, Umi Kalthum; Tay, Lea Tien; Mat Isa, Nor Ashidi; Al-batah, Mohammad Subhi

2013-01-01

Landslide is one of the natural disasters that occur in Malaysia. Topographic factors such as elevation, slope angle, slope aspect, general curvature, plan curvature, and profile curvature are considered as the main causes of landslides. In order to determine the dominant topographic factors in landslide mapping analysis, a study was conducted and presented in this paper. There are three main stages involved in this study. The first stage is the extraction of extra topographic factors. Previous landslide studies had identified mainly six topographic factors. Seven new additional factors have been proposed in this study. They are longitude curvature, tangential curvature, cross section curvature, surface area, diagonal line length, surface roughness, and rugosity. The second stage is the specification of the weight of each factor using two methods. The methods are multilayer perceptron (MLP) network classification accuracy and Zhou's algorithm. At the third stage, the factors with higher weights were used to improve the MLP performance. Out of the thirteen factors, eight factors were considered as important factors, which are surface area, longitude curvature, diagonal length, slope angle, elevation, slope aspect, rugosity, and profile curvature. The classification accuracy of multilayer perceptron neural network has increased by 3% after the elimination of five less important factors.

Determination of Important Topographic Factors for Landslide Mapping Analysis Using MLP Network

PubMed Central

Alkhasawneh, Mutasem Sh.; Ngah, Umi Kalthum; Mat Isa, Nor Ashidi; Al-batah, Mohammad Subhi

2013-01-01

Landslide is one of the natural disasters that occur in Malaysia. Topographic factors such as elevation, slope angle, slope aspect, general curvature, plan curvature, and profile curvature are considered as the main causes of landslides. In order to determine the dominant topographic factors in landslide mapping analysis, a study was conducted and presented in this paper. There are three main stages involved in this study. The first stage is the extraction of extra topographic factors. Previous landslide studies had identified mainly six topographic factors. Seven new additional factors have been proposed in this study. They are longitude curvature, tangential curvature, cross section curvature, surface area, diagonal line length, surface roughness, and rugosity. The second stage is the specification of the weight of each factor using two methods. The methods are multilayer perceptron (MLP) network classification accuracy and Zhou's algorithm. At the third stage, the factors with higher weights were used to improve the MLP performance. Out of the thirteen factors, eight factors were considered as important factors, which are surface area, longitude curvature, diagonal length, slope angle, elevation, slope aspect, rugosity, and profile curvature. The classification accuracy of multilayer perceptron neural network has increased by 3% after the elimination of five less important factors. PMID:24453846

Conceptualizing age-friendly community characteristics in a sample of urban elders: an exploratory factor analysis.

PubMed

Smith, Richard J; Lehning, Amanda J; Dunkle, Ruth E

2013-01-01

Accurate conceptualization and measurement of age-friendly community characteristics would help to reduce barriers to documenting the effects on elders of interventions to create such communities. This article contributes to the measurement of age-friendly communities through an exploratory factor analysis of items reflecting an existing US Environmental Protection Agency policy framework. From a sample of urban elders (n = 1,376), we identified 6 factors associated with demographic and health characteristics: access to business and leisure, social interaction, access to health care, neighborhood problems, social support, and community engagement. Future research should explore the effects of these factors across contexts and populations.

Gene-centric Meta-analysis in 87,736 Individuals of European Ancestry Identifies Multiple Blood-Pressure-Related Loci

PubMed Central

Tragante, Vinicius; Barnes, Michael R.; Ganesh, Santhi K.; Lanktree, Matthew B.; Guo, Wei; Franceschini, Nora; Smith, Erin N.; Johnson, Toby; Holmes, Michael V.; Padmanabhan, Sandosh; Karczewski, Konrad J.; Almoguera, Berta; Barnard, John; Baumert, Jens; Chang, Yen-Pei Christy; Elbers, Clara C.; Farrall, Martin; Fischer, Mary E.; Gaunt, Tom R.; Gho, Johannes M.I.H.; Gieger, Christian; Goel, Anuj; Gong, Yan; Isaacs, Aaron; Kleber, Marcus E.; Leach, Irene Mateo; McDonough, Caitrin W.; Meijs, Matthijs F.L.; Melander, Olle; Nelson, Christopher P.; Nolte, Ilja M.; Pankratz, Nathan; Price, Tom S.; Shaffer, Jonathan; Shah, Sonia; Tomaszewski, Maciej; van der Most, Peter J.; Van Iperen, Erik P.A.; Vonk, Judith M.; Witkowska, Kate; Wong, Caroline O.L.; Zhang, Li; Beitelshees, Amber L.; Berenson, Gerald S.; Bhatt, Deepak L.; Brown, Morris; Burt, Amber; Cooper-DeHoff, Rhonda M.; Connell, John M.; Cruickshanks, Karen J.; Curtis, Sean P.; Davey-Smith, George; Delles, Christian; Gansevoort, Ron T.; Guo, Xiuqing; Haiqing, Shen; Hastie, Claire E.; Hofker, Marten H.; Hovingh, G. Kees; Kim, Daniel S.; Kirkland, Susan A.; Klein, Barbara E.; Klein, Ronald; Li, Yun R.; Maiwald, Steffi; Newton-Cheh, Christopher; O’Brien, Eoin T.; Onland-Moret, N. Charlotte; Palmas, Walter; Parsa, Afshin; Penninx, Brenda W.; Pettinger, Mary; Vasan, Ramachandran S.; Ranchalis, Jane E.; M Ridker, Paul; Rose, Lynda M.; Sever, Peter; Shimbo, Daichi; Steele, Laura; Stolk, Ronald P.; Thorand, Barbara; Trip, Mieke D.; van Duijn, Cornelia M.; Verschuren, W. Monique; Wijmenga, Cisca; Wyatt, Sharon; Young, J. Hunter; Zwinderman, Aeilko H.; Bezzina, Connie R.; Boerwinkle, Eric; Casas, Juan P.; Caulfield, Mark J.; Chakravarti, Aravinda; Chasman, Daniel I.; Davidson, Karina W.; Doevendans, Pieter A.; Dominiczak, Anna F.; FitzGerald, Garret A.; Gums, John G.; Fornage, Myriam; Hakonarson, Hakon; Halder, Indrani; Hillege, Hans L.; Illig, Thomas; Jarvik, Gail P.; Johnson, Julie A.; Kastelein, John J.P.; Koenig, Wolfgang; Kumari, Meena; März, Winfried; Murray, Sarah S.; O’Connell, Jeffery R.; Oldehinkel, Albertine J.; Pankow, James S.; Rader, Daniel J.; Redline, Susan; Reilly, Muredach P.; Schadt, Eric E.; Kottke-Marchant, Kandice; Snieder, Harold; Snyder, Michael; Stanton, Alice V.; Tobin, Martin D.; Uitterlinden, André G.; van der Harst, Pim; van der Schouw, Yvonne T.; Samani, Nilesh J.; Watkins, Hugh; Johnson, Andrew D.; Reiner, Alex P.; Zhu, Xiaofeng; de Bakker, Paul I.W.; Levy, Daniel; Asselbergs, Folkert W.; Munroe, Patricia B.; Keating, Brendan J.

2014-01-01

Blood pressure (BP) is a heritable risk factor for cardiovascular disease. To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP), and pulse pressure (PP), we genotyped ∼50,000 SNPs in up to 87,736 individuals of European ancestry and combined these in a meta-analysis. We replicated findings in an independent set of 68,368 individuals of European ancestry. Our analyses identified 11 previously undescribed associations in independent loci containing 31 genes including PDE1A, HLA-DQB1, CDK6, PRKAG2, VCL, H19, NUCB2, RELA, HOXC@ complex, FBN1, and NFAT5 at the Bonferroni-corrected array-wide significance threshold (p < 6 × 10−7) and confirmed 27 previously reported associations. Bioinformatic analysis of the 11 loci provided support for a putative role in hypertension of several genes, such as CDK6 and NUCB2. Analysis of potential pharmacological targets in databases of small molecules showed that ten of the genes are predicted to be a target for small molecules. In summary, we identified previously unknown loci associated with BP. Our findings extend our understanding of genes involved in BP regulation, which may provide new targets for therapeutic intervention or drug response stratification. PMID:24560520

Functional Genomic Screen Identifies Klebsiella pneumoniae Factors Implicated in Blocking Nuclear Factor κB (NF-κB) Signaling*

PubMed Central

Tomás, Anna; Lery, Leticia; Regueiro, Verónica; Pérez-Gutiérrez, Camino; Martínez, Verónica; Moranta, David; Llobet, Enrique; González-Nicolau, Mar; Insua, Jose L.; Tomas, Juan M.; Sansonetti, Philippe J.; Tournebize, Régis; Bengoechea, José A.

2015-01-01

Klebsiella pneumoniae is an etiologic agent of community-acquired and nosocomial pneumonia. It has been shown that K. pneumoniae infections are characterized by reduced early inflammatory response. Recently our group has shown that K. pneumoniae dampens the activation of inflammatory responses by antagonizing the activation of the NF-κB canonical pathway. Our results revealed that K. pneumoniae capsule polysaccharide (CPS) was necessary but not sufficient to attenuate inflammation. To identify additional Klebsiella factors required to dampen inflammation, we standardized and applied a high-throughput gain-of-function screen to examine a Klebsiella transposon mutant library. We identified 114 mutants that triggered the activation of NF-κB. Two gene ontology categories accounted for half of the loci identified in the screening: metabolism and transport genes (32% of the mutants) and envelope-related genes (17%). Characterization of the mutants revealed that the lack of the enterobactin siderophore was linked to a reduced CPS expression, which in turn underlined the NF-κB activation induced by the mutant. The lipopolysaccharide (LPS) O-polysaccharide and the pullulanase (PulA) type 2 secretion system (T2SS) are required for full effectiveness of the immune evasion. Importantly, these factors do not play a redundant role. The fact that LPS O-polysaccharide and T2SS mutant-induced responses were dependent on TLR2-TLR4-MyD88 activation suggested that LPS O-polysaccharide and PulA perturbed Toll-like receptor (TLR)-dependent recognition of K. pneumoniae. Finally, we demonstrate that LPS O-polysaccharide and pulA mutants are attenuated in the pneumonia mouse model. We propose that LPS O-polysaccharide and PulA T2SS could be new targets for the design of new antimicrobials. Increasing TLR-governed defense responses might provide also selective alternatives for the management of K. pneumoniae pneumonia. PMID:25971969

How to identify the key factors that affect driver perception of accident risk. A comparison between Italian and Spanish driver behavior.

PubMed

de Oña, Juan; de Oña, Rocio; Eboli, Laura; Forciniti, Carmen; Mazzulla, Gabriella

2014-12-01

Road crashes can be caused by different factors, including infrastructure, vehicles, and human variables. Many research studies have focused solely on identifying the key factors that cause road crashes. From these studies, it emerged that human factors have the most relevant impact on accident severity. More specifically, accident severity depends on several factors related directly to the driver, i.e., driving experience, driver's socio-economic characteristics, and driving behavior and attitudes. In this paper, we investigate driver behaviors and attitudes while driving and specifically focus on different methods for identifying the factors that most affect the driver's perception of accident risk. To this end, we designed and conducted a survey in two different European contexts: the city of Cosenza, which is located in the south of Italy, and the city of Granada, which is located in the south of Spain. Samples of drivers were contacted for their opinions on certain aspects of driving rules and attitudes while driving, and different types of questions were addressed to the drivers to assess their judgments of these aspects. Consequently, different methods of data analysis were applied to determine the aspects that heavily influence driver perception of accident risk. An experiment based on the stated preferences (SP) was carried out with the drivers, and the SP data were analyzed using an ordered probit (OP) model. Interesting findings emerged from different analyses of the data and from the comparisons among the data collected in the two different territorial contexts. We found that both Italian and Spanish drivers consider driving in an altered psychophysical state and violating the overtaking rules to be the most risky behaviors. Copyright © 2014 Elsevier Ltd. All rights reserved.

Quantitative analysis of factors that affect oil pipeline network accident based on Bayesian networks: A case study in China

NASA Astrophysics Data System (ADS)

Zhang, Chao; Qin, Ting Xin; Huang, Shuai; Wu, Jian Song; Meng, Xin Yan

2018-06-01

Some factors can affect the consequences of oil pipeline accident and their effects should be analyzed to improve emergency preparation and emergency response. Although there are some qualitative analysis models of risk factors' effects, the quantitative analysis model still should be researched. In this study, we introduce a Bayesian network (BN) model of risk factors' effects analysis in an oil pipeline accident case that happened in China. The incident evolution diagram is built to identify the risk factors. And the BN model is built based on the deployment rule for factor nodes in BN and the expert knowledge by Dempster-Shafer evidence theory. Then the probabilities of incident consequences and risk factors' effects can be calculated. The most likely consequences given by this model are consilient with the case. Meanwhile, the quantitative estimations of risk factors' effects may provide a theoretical basis to take optimal risk treatment measures for oil pipeline management, which can be used in emergency preparation and emergency response.

Can Link Analysis Be Applied to Identify Behavioral Patterns in Train Recorder Data?

PubMed

Strathie, Ailsa; Walker, Guy H

2016-03-01

A proof-of-concept analysis was conducted to establish whether link analysis could be applied to data from on-train recorders to detect patterns of behavior that could act as leading indicators of potential safety issues. On-train data recorders capture data about driving behavior on thousands of routine journeys every day and offer a source of untapped data that could be used to offer insights into human behavior. Data from 17 journeys undertaken by six drivers on the same route over a 16-hr period were analyzed using link analysis, and four key metrics were examined: number of links, network density, diameter, and sociometric status. The results established that link analysis can be usefully applied to data captured from on-vehicle recorders. The four metrics revealed key differences in normal driver behavior. These differences have promising construct validity as leading indicators. Link analysis is one method that could be usefully applied to exploit data routinely gathered by on-vehicle data recorders. It facilitates a proactive approach to safety based on leading indicators, offers a clearer understanding of what constitutes normal driving behavior, and identifies trends at the interface of people and systems, which is currently a key area of strategic risk. These research findings have direct applications in the field of transport data monitoring. They offer a means of automatically detecting patterns in driver behavior that could act as leading indicators of problems during operation and that could be used in the proactive monitoring of driver competence, risk management, and even infrastructure design. © 2015, Human Factors and Ergonomics Society.

Performance Analysis: Work Control Events Identified January - August 2010

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

De Grange, C E; Freeman, J W; Kerr, C E

2011-01-14

This performance analysis evaluated 24 events that occurred at LLNL from January through August 2010. The analysis identified areas of potential work control process and/or implementation weaknesses and several common underlying causes. Human performance improvement and safety culture factors were part of the causal analysis of each event and were analyzed. The collective significance of all events in 2010, as measured by the occurrence reporting significance category and by the proportion of events that have been reported to the DOE ORPS under the ''management concerns'' reporting criteria, does not appear to have increased in 2010. The frequency of reporting inmore » each of the significance categories has not changed in 2010 compared to the previous four years. There is no change indicating a trend in the significance category and there has been no increase in the proportion of occurrences reported in the higher significance category. Also, the frequency of events, 42 events reported through August 2010, is not greater than in previous years and is below the average of 63 occurrences per year at LLNL since 2006. Over the previous four years, an average of 43% of the LLNL's reported occurrences have been reported as either ''management concerns'' or ''near misses.'' In 2010, 29% of the occurrences have been reported as ''management concerns'' or ''near misses.'' This rate indicates that LLNL is now reporting fewer ''management concern'' and ''near miss'' occurrences compared to the previous four years. From 2008 to the present, LLNL senior management has undertaken a series of initiatives to strengthen the work planning and control system with the primary objective to improve worker safety. In 2008, the LLNL Deputy Director established the Work Control Integrated Project Team to develop the core requirements and graded elements of an institutional work planning and control system. By the end of that year this system was documented and implementation had begun

Risk factor and cost accounting analysis for dialysis patients in Taiwan.

PubMed

Su, Bin-Guang; Tsai, Kai-Li; Yeh, Shu-Hsing; Ho, Yi-Yi; Liu, Shin-Yi; Rivers, Patrick A

2010-05-01

According to the 2004 US Renal Data System's annual report, the incidence rate of chronic renal failure in Taiwan increased from 120 to 352 per million populations between 1990 and 2003. This incidence rate is the highest in the world. The prevalence rate, which ranks number two in the world (Japan ranks number one), also increased from 384 to 1630 per million populations. Based on 2005 Taiwan national statistics, there were 52,958 end-stage renal disease (ESRD) patients receiving routine dialysis treatment. This number, which comprised less than 0.2% of the total population and consumed $2.6 billion New Taiwan dollars, was more than 6.12% of the total annual spending of national health insurance during 2005. Dialysis expenditures for patients with ESRD rank the highest among all major injuries (traumas) and diseases. This article identifies and discusses the risk factors associated with consumption of medical resources during dialysis. Instead of using reimbursement data to estimate cost, as seen in previous studies, this study uses cost data within organizations and focuses on evaluating and predicting the resource consumption pattern for dialysis patients with different risk factors. Multiple regression analysis was used to identify 23 risk factors for routine dialysis patients. Of these risk factors, six were associated with the increase of dialysis cost: age (i.e. 75 years old and older), liver function disorder, hypertension, bile-duct disorder, cancer and high blood lipids. Patients with liver function disorder incurred much higher costs for injection medication and supplies. Hypertensive patients incurred higher costs for injection medication, supplies and oral medication. Patients with bile-duct disorder incurred a significant difference in check-up costs (i.e. costs were higher for those aged 75 years and older than those who were younger than 30 years of age). Cancer patients also incurred significant differences in cost of medical supplies. Patients

Study on the factors affecting the quality of public bus transportation service in Bali Province using factor analysis

NASA Astrophysics Data System (ADS)

Susilawati, M.; Nilakusmawati, D. P. E.

2017-06-01

The volume of mobility flows are increasing day by day and the condition of the number of people using private transport modes contribute to traffic congestion. With the limited capacity of the road, one of the alternatives solution to reduce congestion is to optimize the use of public transport. The purposes of this study are to determine the factors that influence user’s satisfaction on the quality of public bus transportation service and determine variables that became identifier on the dominant factor affecting user’s satisfaction. The study was conducted for the public bus transportation between districts in the province of Bali, which is among the eight regencies and one municipality, using a questionnaire as a data collection instrument. Service variables determinant of user’s satisfaction in this study, described in 25 questions, which were analyzed using factor analysis. The results showed there were six factors that explain the satisfaction of users of public transport in Bali, with a total diversity of data that can be parsed by 61.436%. These factors are: Safety and comfort, Responsiveness, Capacity, Tangible, Safety, Reliability. The dominant factor affecting public transport user satisfaction is the safety and comfort, with the most influential variable is feeling concerned about the personal safety of users when on the bus.

Obesity as a risk factor for developing functional limitation among older adults: A conditional inference tree analysis.

PubMed

Cheng, Feon W; Gao, Xiang; Bao, Le; Mitchell, Diane C; Wood, Craig; Sliwinski, Martin J; Smiciklas-Wright, Helen; Still, Christopher D; Rolston, David D K; Jensen, Gordon L

2017-07-01

To examine the risk factors of developing functional decline and make probabilistic predictions by using a tree-based method that allows higher order polynomials and interactions of the risk factors. The conditional inference tree analysis, a data mining approach, was used to construct a risk stratification algorithm for developing functional limitation based on BMI and other potential risk factors for disability in 1,951 older adults without functional limitations at baseline (baseline age 73.1 ± 4.2 y). We also analyzed the data with multivariate stepwise logistic regression and compared the two approaches (e.g., cross-validation). Over a mean of 9.2 ± 1.7 years of follow-up, 221 individuals developed functional limitation. Higher BMI, age, and comorbidity were consistently identified as significant risk factors for functional decline using both methods. Based on these factors, individuals were stratified into four risk groups via the conditional inference tree analysis. Compared to the low-risk group, all other groups had a significantly higher risk of developing functional limitation. The odds ratio comparing two extreme categories was 9.09 (95% confidence interval: 4.68, 17.6). Higher BMI, age, and comorbid disease were consistently identified as significant risk factors for functional decline among older individuals across all approaches and analyses. © 2017 The Obesity Society.

Physics Metacognition Inventory Part II: Confirmatory factor analysis and Rasch analysis

NASA Astrophysics Data System (ADS)

Taasoobshirazi, Gita; Bailey, MarLynn; Farley, John

2015-11-01

The Physics Metacognition Inventory was developed to measure physics students' metacognition for problem solving. In one of our earlier studies, an exploratory factor analysis provided evidence of preliminary construct validity, revealing six components of students' metacognition when solving physics problems including knowledge of cognition, planning, monitoring, evaluation, debugging, and information management. The college students' scores on the inventory were found to be reliable and related to students' physics motivation and physics grade. However, the results of the exploratory factor analysis indicated that the questionnaire could be revised to improve its construct validity. The goal of this study was to revise the questionnaire and establish its construct validity through a confirmatory factor analysis. In addition, a Rasch analysis was applied to the data to better understand the psychometric properties of the inventory and to further evaluate the construct validity. Results indicated that the final, revised inventory is a valid, reliable, and efficient tool for assessing student metacognition for physics problem solving.