Resampling procedures to identify important SNPs using a consensus approach.

PubMed

Pardy, Christopher; Motyer, Allan; Wilson, Susan

2011-11-29

Our goal is to identify common single-nucleotide polymorphisms (SNPs) (minor allele frequency > 1%) that add predictive accuracy above that gained by knowledge of easily measured clinical variables. We take an algorithmic approach to predict each phenotypic variable using a combination of phenotypic and genotypic predictors. We perform our procedure on the first simulated replicate and then validate against the others. Our procedure performs well when predicting Q1 but is less successful for the other outcomes. We use resampling procedures where possible to guard against false positives and to improve generalizability. The approach is based on finding a consensus regarding important SNPs by applying random forests and the least absolute shrinkage and selection operator (LASSO) on multiple subsamples. Random forests are used first to discard unimportant predictors, narrowing our focus to roughly 100 important SNPs. A cross-validation LASSO is then used to further select variables. We combine these procedures to guarantee that cross-validation can be used to choose a shrinkage parameter for the LASSO. If the clinical variables were unavailable, this prefiltering step would be essential. We perform the SNP-based analyses simultaneously rather than one at a time to estimate SNP effects in the presence of other causal variants. We analyzed the first simulated replicate of Genetic Analysis Workshop 17 without knowledge of the true model. Post-conference knowledge of the simulation parameters allowed us to investigate the limitations of our approach. We found that many of the false positives we identified were substantially correlated with genuine causal SNPs.

An Approach to Identify and Characterize a Subunit Candidate Shigella Vaccine Antigen.

PubMed

Pore, Debasis; Chakrabarti, Manoj K

2016-01-01

Shigellosis remains a serious issue throughout the developing countries, particularly in children under the age of 5. Numerous strategies have been tested to develop vaccines targeting shigellosis; unfortunately despite several years of extensive research, no safe, effective, and inexpensive vaccine against shigellosis is available so far. Here, we illustrate in detail an approach to identify and establish immunogenic outer membrane proteins from Shigella flexneri 2a as subunit vaccine candidates.

Extending existing structural identifiability analysis methods to mixed-effects models.

PubMed

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

2018-01-01

The concept of structural identifiability for state-space models is expanded to cover mixed-effects state-space models. Two methods applicable for the analytical study of the structural identifiability of mixed-effects models are presented. The two methods are based on previously established techniques for non-mixed-effects models; namely the Taylor series expansion and the input-output form approach. By generating an exhaustive summary, and by assuming an infinite number of subjects, functions of random variables can be derived which in turn determine the distribution of the system's observation function(s). By considering the uniqueness of the analytical statistical moments of the derived functions of the random variables, the structural identifiability of the corresponding mixed-effects model can be determined. The two methods are applied to a set of examples of mixed-effects models to illustrate how they work in practice. Copyright © 2017 Elsevier Inc. All rights reserved.

Identifying patients with cost-related medication non-adherence: a big-data approach.

PubMed

Zhang, James X; Meltzer, David O

2016-08-01

Millions of Americans encounter access barriers to medication due to cost; however, to date, there is no effective screening tool that identifies patients at risk of cost-related medication non-adherence (CRN). By utilizing a big-data approach to combining the survey data and electronic health records (EHRs), this study aimed to develop a method of identifying patients at risk of CRN. CRN data were collected by surveying patients about CRN behaviors in the past 3 months. By matching the dates of patients' receipt of monthly Social Security (SS) payments and the dates of prescription orders for 559 Medicare beneficiaries who were primary SS claimants at high risk of hospitalization in an urban academic medical center, this study identified patients who ordered their outpatient prescription within 2 days of receipt of monthly SS payments in 2014. The predictive power of this information on CRN was assessed using multivariate logistic regression analysis. Among the 559 Medicare patients at high risk of hospitalization, 137 (25%) reported CRN. Among those with CRN, 96 (70%) had ordered prescriptions on receipt of SS payments one or more times in 2014. The area under the Receiver Operating Curve was 0.70 using the predictive model in multivariate logistic regression analysis. With a new approach to combining the survey data and EHR data, patients' behavior in delaying filling of prescription until funds from SS checks become available can be measured, providing some predictive value for cost-related medication non-adherence. The big-data approach is a valuable tool to identify patients at risk of CRN and can be further expanded to the general population and sub-populations, providing a meaningful risk-stratification for CRN and facilitating physician-patient communication to reduce CRN.

A Computer Vision Approach to Identify Einstein Rings and Arcs

NASA Astrophysics Data System (ADS)

Lee, Chien-Hsiu

2017-03-01

Einstein rings are rare gems of strong lensing phenomena; the ring images can be used to probe the underlying lens gravitational potential at every position angles, tightly constraining the lens mass profile. In addition, the magnified images also enable us to probe high-z galaxies with enhanced resolution and signal-to-noise ratios. However, only a handful of Einstein rings have been reported, either from serendipitous discoveries or or visual inspections of hundred thousands of massive galaxies or galaxy clusters. In the era of large sky surveys, an automated approach to identify ring pattern in the big data to come is in high demand. Here, we present an Einstein ring recognition approach based on computer vision techniques. The workhorse is the circle Hough transform that recognise circular patterns or arcs in the images. We propose a two-tier approach by first pre-selecting massive galaxies associated with multiple blue objects as possible lens, than use Hough transform to identify circular pattern. As a proof-of-concept, we apply our approach to SDSS, with a high completeness, albeit with low purity. We also apply our approach to other lenses in DES, HSC-SSP, and UltraVISTA survey, illustrating the versatility of our approach.

Screening and syndromic approaches to identify gonorrhea and chlamydial infection among women.

PubMed

Sloan, N L; Winikoff, B; Haberland, N; Coggins, C; Elias, C

2000-03-01

The standard diagnostic tools to identify sexually transmitted infections are often expensive and have laboratory and infrastructure requirements that make them unavailable to family planning and primary health-care clinics in developing countries. Therefore, inexpensive, accessible tools that rely on symptoms, signs, and/or risk factors have been developed to identify and treat reproductive tract infections without the need for laboratory diagnostics. Studies were reviewed that used standard diagnostic tests to identify gonorrhea and cervical chlamydial infection among women and that provided adequate information about the usefulness of the tools for screening. Aggregation of the studies' results suggest that risk factors, algorithms, and risk scoring for syndromic management are poor indicators of gonorrhea and chlamydial infection in samples of both low and high prevalence and, consequently, are not effective mechanisms with which to identify or manage these conditions. The development and evaluation of other approaches to identify gonorrhea and chlamydial infections, including inexpensive and simple laboratory screening tools, periodic universal treatment, and other alternatives must be given priority.

An integrated approach for identifying priority contaminant in ...

EPA Pesticide Factsheets

Environmental assessment of complex mixtures typically requires integration of chemical and biological measurements. This study demonstrates the use of a combination of instrumental chemical analyses, effects-based monitoring, and bio-effects prediction approaches to help identify potential hazards and priority contaminants in two Great Lakes Areas of Concern (AOCs), the Lower Green Bay/Fox River located near Green Bay, WI, USA and the Milwaukee River Estuary, located near Milwaukee, WI, USA. Fathead minnows were caged at four sites within each AOC (eight sites total). Following 4 d of in situ exposure, tissues and biofluids were sampled and used for targeted biological effects analyses. Additionally, 4 d composite water samples were collected concurrently at each caged fish site and analyzed for 134 analytes as well as evaluated for total estrogenic and androgenic activity using cell-based bioassays. Of the analytes examined, 75 were detected in composite samples from at least one site. Based on multiple analyses, one site in the East River and another site near a paper mill discharge from lower Green Bay/Fox River AOC, were prioritized due to their estrogenic and androgenic acitvity, respectively. The water samples from other sites generally did not exhibit significant estrogenic or androgenic activity, nor was there evidence for endocrine disruption in the fish exposed at these sites as indicated the the lack of alterations in ex vivo steroid production, c

GTA: a game theoretic approach to identifying cancer subnetwork markers.

PubMed

Farahmand, S; Goliaei, S; Ansari-Pour, N; Razaghi-Moghadam, Z

2016-03-01

The identification of genetic markers (e.g. genes, pathways and subnetworks) for cancer has been one of the most challenging research areas in recent years. A subset of these studies attempt to analyze genome-wide expression profiles to identify markers with high reliability and reusability across independent whole-transcriptome microarray datasets. Therefore, the functional relationships of genes are integrated with their expression data. However, for a more accurate representation of the functional relationships among genes, utilization of the protein-protein interaction network (PPIN) seems to be necessary. Herein, a novel game theoretic approach (GTA) is proposed for the identification of cancer subnetwork markers by integrating genome-wide expression profiles and PPIN. The GTA method was applied to three distinct whole-transcriptome breast cancer datasets to identify the subnetwork markers associated with metastasis. To evaluate the performance of our approach, the identified subnetwork markers were compared with gene-based, pathway-based and network-based markers. We show that GTA is not only capable of identifying robust metastatic markers, it also provides a higher classification performance. In addition, based on these GTA-based subnetworks, we identified a new bonafide candidate gene for breast cancer susceptibility.

Identifying Key Performance Indicators for Holistic Hospital Management with a Modified DEMATEL Approach

PubMed Central

Si, Sheng-Li; You, Xiao-Yue; Huang, Jia

2017-01-01

Performance analysis is an important way for hospitals to achieve higher efficiency and effectiveness in providing services to their customers. The performance of the healthcare system can be measured by many indicators, but it is difficult to improve them simultaneously due to the limited resources. A feasible way is to identify the central and influential indicators to improve healthcare performance in a stepwise manner. In this paper, we propose a hybrid multiple criteria decision making (MCDM) approach to identify key performance indicators (KPIs) for holistic hospital management. First, through integrating evidential reasoning approach and interval 2-tuple linguistic variables, various assessments of performance indicators provided by healthcare experts are modeled. Then, the decision making trial and evaluation laboratory (DEMATEL) technique is adopted to build an interactive network and visualize the causal relationships between the performance indicators. Finally, an empirical case study is provided to demonstrate the proposed approach for improving the efficiency of healthcare management. The results show that “accidents/adverse events”, “nosocomial infection”, ‘‘incidents/errors”, “number of operations/procedures” are significant influential indicators. Also, the indicators of “length of stay”, “bed occupancy” and “financial measures” play important roles in performance evaluation of the healthcare organization. The proposed decision making approach could be considered as a reference for healthcare administrators to enhance the performance of their healthcare institutions. PMID:28825613

Identifying Key Performance Indicators for Holistic Hospital Management with a Modified DEMATEL Approach.

PubMed

Si, Sheng-Li; You, Xiao-Yue; Liu, Hu-Chen; Huang, Jia

2017-08-19

Performance analysis is an important way for hospitals to achieve higher efficiency and effectiveness in providing services to their customers. The performance of the healthcare system can be measured by many indicators, but it is difficult to improve them simultaneously due to the limited resources. A feasible way is to identify the central and influential indicators to improve healthcare performance in a stepwise manner. In this paper, we propose a hybrid multiple criteria decision making (MCDM) approach to identify key performance indicators (KPIs) for holistic hospital management. First, through integrating evidential reasoning approach and interval 2-tuple linguistic variables, various assessments of performance indicators provided by healthcare experts are modeled. Then, the decision making trial and evaluation laboratory (DEMATEL) technique is adopted to build an interactive network and visualize the causal relationships between the performance indicators. Finally, an empirical case study is provided to demonstrate the proposed approach for improving the efficiency of healthcare management. The results show that "accidents/adverse events", "nosocomial infection", ''incidents/errors", "number of operations/procedures" are significant influential indicators. Also, the indicators of "length of stay", "bed occupancy" and "financial measures" play important roles in performance evaluation of the healthcare organization. The proposed decision making approach could be considered as a reference for healthcare administrators to enhance the performance of their healthcare institutions.

Identifying novel biomarkers in sarcoidosis using genome-based approaches

PubMed Central

Knox, Kenneth S.; Garcia, Joe G.N.

2015-01-01

Synopsis We briefly review conventional biomarkers used clinically to 1) support a diagnosis and 2) monitor disease progression in patients with sarcoidosis. We describe potential new biomarkers identified by genome-wide screening and the approaches to discover these biomarkers. PMID:26593137

POEM: Identifying Joint Additive Effects on Regulatory Circuits.

PubMed

Botzman, Maya; Nachshon, Aharon; Brodt, Avital; Gat-Viks, Irit

2016-01-01

Expression Quantitative Trait Locus (eQTL) mapping tackles the problem of identifying variation in DNA sequence that have an effect on the transcriptional regulatory network. Major computational efforts are aimed at characterizing the joint effects of several eQTLs acting in concert to govern the expression of the same genes. Yet, progress toward a comprehensive prediction of such joint effects is limited. For example, existing eQTL methods commonly discover interacting loci affecting the expression levels of a module of co-regulated genes. Such "modularization" approaches, however, are focused on epistatic relations and thus have limited utility for the case of additive (non-epistatic) effects. Here we present POEM (Pairwise effect On Expression Modules), a methodology for identifying pairwise eQTL effects on gene modules. POEM is specifically designed to achieve high performance in the case of additive joint effects. We applied POEM to transcription profiles measured in bone marrow-derived dendritic cells across a population of genotyped mice. Our study reveals widespread additive, trans-acting pairwise effects on gene modules, characterizes their organizational principles, and highlights high-order interconnections between modules within the immune signaling network. These analyses elucidate the central role of additive pairwise effect in regulatory circuits, and provide computational tools for future investigations into the interplay between eQTLs. The software described in this article is available at csgi.tau.ac.il/POEM/.

Identified Palliative Care Approach Needs with SPICT in Family Practice: A Preliminary Observational Study.

PubMed

Hamano, Jun; Oishi, Ai; Kizawa, Yoshiyuki

2018-02-09

Identifying patients who require palliative care approach is challenging for family physicians, even though several identification tools have been developed for this purpose. To explore the prevalence and characteristics of family practice patients who need palliative care approach as determined using Supportive and Palliative Care Indicators Tool (SPICT™, April 2015) in Japan. Single-center cross-sectional study. We enrolled all patients ≥65 years of age who visited the chief researcher's outpatient clinic in October 2016. We used Japanese version of SPICT (SPICT-J) to identify patients who need palliative care approach. We assessed patients' backgrounds and whether they had undergone advance care planning with their family physicians. This study included 87 patients (61 females) with a mean age of 79.0 ± 7.4 years. Eight patients (9.2%) were identified as needing palliative care approach. The mean age of patients who needed this approach was 82.3 ± 8.3 years and main underlying conditions were heart/vascular disease (37.5%), dementia/frailty (25.0%), and respiratory disease (12.5%). Only two of eight patients identified as needing palliative care approach had discussed advance care planning with their family physicians. In family practice, 9.2% of outpatients ≥65 years of age were identified as needing palliative care approach. Family physicians should carefully evaluate whether outpatients need palliative care approach.

A systematic approach to identify therapeutic effects of natural products based on human metabolite information.

PubMed

Noh, Kyungrin; Yoo, Sunyong; Lee, Doheon

2018-06-13

Natural products have been widely investigated in the drug development field. Their traditional use cases as medicinal agents and their resemblance of our endogenous compounds show the possibility of new drug development. Many researchers have focused on identifying therapeutic effects of natural products, yet the resemblance of natural products and human metabolites has been rarely touched. We propose a novel method which predicts therapeutic effects of natural products based on their similarity with human metabolites. In this study, we compare the structure, target and phenotype similarities between natural products and human metabolites to capture molecular and phenotypic properties of both compounds. With the generated similarity features, we train support vector machine model to identify similar natural product and human metabolite pairs. The known functions of human metabolites are then mapped to the paired natural products to predict their therapeutic effects. With our selected three feature sets, structure, target and phenotype similarities, our trained model successfully paired similar natural products and human metabolites. When applied to the natural product derived drugs, we could successfully identify their indications with high specificity and sensitivity. We further validated the found therapeutic effects of natural products with the literature evidence. These results suggest that our model can match natural products to similar human metabolites and provide possible therapeutic effects of natural products. By utilizing the similar human metabolite information, we expect to find new indications of natural products which could not be covered by previous in silico methods.

A Systematic Approach to Determining the Identifiability of Multistage Carcinogenesis Models.

PubMed

Brouwer, Andrew F; Meza, Rafael; Eisenberg, Marisa C

2017-07-01

Multistage clonal expansion (MSCE) models of carcinogenesis are continuous-time Markov process models often used to relate cancer incidence to biological mechanism. Identifiability analysis determines what model parameter combinations can, theoretically, be estimated from given data. We use a systematic approach, based on differential algebra methods traditionally used for deterministic ordinary differential equation (ODE) models, to determine identifiable combinations for a generalized subclass of MSCE models with any number of preinitation stages and one clonal expansion. Additionally, we determine the identifiable combinations of the generalized MSCE model with up to four clonal expansion stages, and conjecture the results for any number of clonal expansion stages. The results improve upon previous work in a number of ways and provide a framework to find the identifiable combinations for further variations on the MSCE models. Finally, our approach, which takes advantage of the Kolmogorov backward equations for the probability generating functions of the Markov process, demonstrates that identifiability methods used in engineering and mathematics for systems of ODEs can be applied to continuous-time Markov processes. © 2016 Society for Risk Analysis.

Identifying Immune Drivers of Gulf War Illness Using a Novel Daily Sampling Approach

DTIC Science & Technology

2017-10-01

AWARD NUMBER: W81XWH-12-1-0557 TITLE: Identifying Immune Drivers of Gulf War Illness Using a Novel Daily Sampling Approach PRINCIPAL...TITLE AND SUBTITLE Identifying Immune Drivers of Gulf War Illness Using A Novel 5a. CONTRACT NUMBER Daily Sampling Approach 5b. GRANT NUMBER...INTRODUCTION: The major aim of this research project is to identify aspects of the immune system that are dysregulated in veterans with Gulf War Illness

Identifying seizure onset zone from electrocorticographic recordings: A machine learning approach based on phase locking value.

PubMed

Elahian, Bahareh; Yeasin, Mohammed; Mudigoudar, Basanagoud; Wheless, James W; Babajani-Feremi, Abbas

2017-10-01

Using a novel technique based on phase locking value (PLV), we investigated the potential for features extracted from electrocorticographic (ECoG) recordings to serve as biomarkers to identify the seizure onset zone (SOZ). We computed the PLV between the phase of the amplitude of high gamma activity (80-150Hz) and the phase of lower frequency rhythms (4-30Hz) from ECoG recordings obtained from 10 patients with epilepsy (21 seizures). We extracted five features from the PLV and used a machine learning approach based on logistic regression to build a model that classifies electrodes as SOZ or non-SOZ. More than 96% of electrodes identified as the SOZ by our algorithm were within the resected area in six seizure-free patients. In four non-seizure-free patients, more than 31% of the identified SOZ electrodes by our algorithm were outside the resected area. In addition, we observed that the seizure outcome in non-seizure-free patients correlated with the number of non-resected SOZ electrodes identified by our algorithm. This machine learning approach, based on features extracted from the PLV, effectively identified electrodes within the SOZ. The approach has the potential to assist clinicians in surgical decision-making when pre-surgical intracranial recordings are utilized. Copyright © 2017 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

A Functional Genomics Approach to Identify Novel Breast Cancer Gene Targets in Yeast

DTIC Science & Technology

2004-05-01

AD Award Number: DAMD17-03-1-0232 TITLE: A Functional Genomics Approach to Identify Novel Breast Cancer Gene Targets in Yeast PRINCIPAL INVESTIGATOR...Approach to Identify Novel Breast DAMD17-03-1-0232 Cancer Gene Targets in Yeast 6. A UTHOR(S) Craig Bennett, Ph.D. 7. PERFORMING ORGANIZA TION NAME(S...Unlimited 13. ABSTRACT (Maximum 200 Words) We are using the yeast Saccharomyces cerevisiae to identify new cancer gene targets that interact with the

POEM: Identifying Joint Additive Effects on Regulatory Circuits

PubMed Central

Botzman, Maya; Nachshon, Aharon; Brodt, Avital; Gat-Viks, Irit

2016-01-01

Motivation: Expression Quantitative Trait Locus (eQTL) mapping tackles the problem of identifying variation in DNA sequence that have an effect on the transcriptional regulatory network. Major computational efforts are aimed at characterizing the joint effects of several eQTLs acting in concert to govern the expression of the same genes. Yet, progress toward a comprehensive prediction of such joint effects is limited. For example, existing eQTL methods commonly discover interacting loci affecting the expression levels of a module of co-regulated genes. Such “modularization” approaches, however, are focused on epistatic relations and thus have limited utility for the case of additive (non-epistatic) effects. Results: Here we present POEM (Pairwise effect On Expression Modules), a methodology for identifying pairwise eQTL effects on gene modules. POEM is specifically designed to achieve high performance in the case of additive joint effects. We applied POEM to transcription profiles measured in bone marrow-derived dendritic cells across a population of genotyped mice. Our study reveals widespread additive, trans-acting pairwise effects on gene modules, characterizes their organizational principles, and highlights high-order interconnections between modules within the immune signaling network. These analyses elucidate the central role of additive pairwise effect in regulatory circuits, and provide computational tools for future investigations into the interplay between eQTLs. Availability: The software described in this article is available at csgi.tau.ac.il/POEM/. PMID:27148351

A Systems Genetic Approach to Identify Low Dose Radiation-Induced Lymphoma Susceptibility/DOE2013FinalReport

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

Balmain, Allan; Song, Ihn Young

2013-05-15

The ultimate goal of this project is to identify the combinations of genetic variants that confer an individual's susceptibility to the effects of low dose (0.1 Gy) gamma-radiation, in particular with regard to tumor development. In contrast to the known effects of high dose radiation in cancer induction, the responses to low dose radiation (defined as 0.1 Gy or less) are much less well understood, and have been proposed to involve a protective anti-tumor effect in some in vivo scientific models. These conflicting results confound attempts to develop predictive models of the risk of exposure to low dose radiation, particularlymore » when combined with the strong effects of inherited genetic variants on both radiation effects and cancer susceptibility. We have used a Systems Genetics approach in mice that combines genetic background analysis with responses to low and high dose radiation, in order to develop insights that will allow us to reconcile these disparate observations. Using this comprehensive approach we have analyzed normal tissue gene expression (in this case the skin and thymus), together with the changes that take place in this gene expression architecture a) in response to low or high- dose radiation and b) during tumor development. Additionally, we have demonstrated that using our expression analysis approach in our genetically heterogeneous/defined radiation-induced tumor mouse models can uniquely identify genes and pathways relevant to human T-ALL, and uncover interactions between common genetic variants of genes which may lead to tumor susceptibility.« less

Current OCT Approaches Do Not Reliably Identify TCFAs

PubMed Central

Brezinski, Mark E.; Harjai, Kishore J

2017-01-01

It is now clearly established that Thin-Capped Fibroatheromas (TCFAs) lead to most Acute Coronary Syndromes (ACSs). The ability to selectively intervene on TCFAs predisposed to rupture and ACSs would dramatically alter the practice of cardiology. While the ability of OCT to identify thin walled plaques at micron scale resolutions has represented a major advance, it is a misconception that it can reliably identify TCFAs. One major reason is that the ‘diffuse border’ criteria currently used to determine ‘lipid plaque’ is almost undoubtedly from high scattering in the intima and not because of core composition (necrotic core). A second reason is that, rather than looking at lipid collections, studies need to be focused on identifying necrotic cores with OCT. Necrotic cores are characteristic of TCFAs and not lipid collections. Numerous other OCT approaches are available which can potentially accurately assess TCFAs, but these have not been aggressively pursed which we believe likely stems in part from the misconceptions over the efficacy of ‘diffuse borders’. PMID:29250457

A discrete wavelet spectrum approach for identifying non-monotonic trends in hydroclimate data

NASA Astrophysics Data System (ADS)

Sang, Yan-Fang; Sun, Fubao; Singh, Vijay P.; Xie, Ping; Sun, Jian

2018-01-01

The hydroclimatic process is changing non-monotonically and identifying its trends is a great challenge. Building on the discrete wavelet transform theory, we developed a discrete wavelet spectrum (DWS) approach for identifying non-monotonic trends in hydroclimate time series and evaluating their statistical significance. After validating the DWS approach using two typical synthetic time series, we examined annual temperature and potential evaporation over China from 1961-2013 and found that the DWS approach detected both the warming and the warming hiatus in temperature, and the reversed changes in potential evaporation. Further, the identified non-monotonic trends showed stable significance when the time series was longer than 30 years or so (i.e. the widely defined climate timescale). The significance of trends in potential evaporation measured at 150 stations in China, with an obvious non-monotonic trend, was underestimated and was not detected by the Mann-Kendall test. Comparatively, the DWS approach overcame the problem and detected those significant non-monotonic trends at 380 stations, which helped understand and interpret the spatiotemporal variability in the hydroclimatic process. Our results suggest that non-monotonic trends of hydroclimate time series and their significance should be carefully identified, and the DWS approach proposed has the potential for wide use in the hydrological and climate sciences.

Key principles of community-based natural resource management: a synthesis and interpretation of identified effective approaches for managing the commons.

PubMed

Gruber, James S

2010-01-01

This article examines recent research on approaches to community-based environmental and natural resource management and reviews the commonalities and differences between these interdisciplinary and multistakeholder initiatives. To identify the most effective characteristics of Community-based natural resource management (CBNRM), I collected a multiplicity of perspectives from research teams and then grouped findings into a matrix of organizational principles and key characteristics. The matrix was initially vetted (or "field tested") by applying numerous case studies that were previously submitted to the World Bank International Workshop on CBNRM. These practitioner case studies were then compared and contrasted with the findings of the research teams. It is hoped that the developed matrix may be useful to researchers in further focusing research, understanding core characteristics of effective and sustainable CBNRM, providing practitioners with a framework for developing new CBNRM initiatives for managing the commons, and providing a potential resource for academic institutions during their evaluation of their practitioner-focused environmental management and leadership curriculum.

An Unbiased Approach to Identifying Tau Kinases That Phosphorylate Tau at Sites Associated with Alzheimer Disease

PubMed Central

Cavallini, Annalisa; Brewerton, Suzanne; Bell, Amanda; Sargent, Samantha; Glover, Sarah; Hardy, Clare; Moore, Roger; Calley, John; Ramachandran, Devaki; Poidinger, Michael; Karran, Eric; Davies, Peter; Hutton, Michael; Szekeres, Philip; Bose, Suchira

2013-01-01

Neurofibrillary tangles, one of the hallmarks of Alzheimer disease (AD), are composed of paired helical filaments of abnormally hyperphosphorylated tau. The accumulation of these proteinaceous aggregates in AD correlates with synaptic loss and severity of dementia. Identifying the kinases involved in the pathological phosphorylation of tau may identify novel targets for AD. We used an unbiased approach to study the effect of 352 human kinases on their ability to phosphorylate tau at epitopes associated with AD. The kinases were overexpressed together with the longest form of human tau in human neuroblastoma cells. Levels of total and phosphorylated tau (epitopes Ser(P)-202, Thr(P)-231, Ser(P)-235, and Ser(P)-396/404) were measured in cell lysates using AlphaScreen assays. GSK3α, GSK3β, and MAPK13 were found to be the most active tau kinases, phosphorylating tau at all four epitopes. We further dissected the effects of GSK3α and GSK3β using pharmacological and genetic tools in hTau primary cortical neurons. Pathway analysis of the kinases identified in the screen suggested mechanisms for regulation of total tau levels and tau phosphorylation; for example, kinases that affect total tau levels do so by inhibition or activation of translation. A network fishing approach with the kinase hits identified other key molecules putatively involved in tau phosphorylation pathways, including the G-protein signaling through the Ras family of GTPases (MAPK family) pathway. The findings identify novel tau kinases and novel pathways that may be relevant for AD and other tauopathies. PMID:23798682

A side-effect free method for identifying cancer drug targets.

PubMed

Ashraf, Md Izhar; Ong, Seng-Kai; Mujawar, Shama; Pawar, Shrikant; More, Pallavi; Paul, Somnath; Lahiri, Chandrajit

2018-04-27

Identifying effective drug targets, with little or no side effects, remains an ever challenging task. A potential pitfall of failing to uncover the correct drug targets, due to side effect of pleiotropic genes, might lead the potential drugs to be illicit and withdrawn. Simplifying disease complexity, for the investigation of the mechanistic aspects and identification of effective drug targets, have been done through several approaches of protein interactome analysis. Of these, centrality measures have always gained importance in identifying candidate drug targets. Here, we put forward an integrated method of analysing a complex network of cancer and depict the importance of k-core, functional connectivity and centrality (KFC) for identifying effective drug targets. Essentially, we have extracted the proteins involved in the pathways leading to cancer from the pathway databases which enlist real experimental datasets. The interactions between these proteins were mapped to build an interactome. Integrative analyses of the interactome enabled us to unearth plausible reasons for drugs being rendered withdrawn, thereby giving future scope to pharmaceutical industries to potentially avoid them (e.g. ESR1, HDAC2, F2, PLG, PPARA, RXRA, etc). Based upon our KFC criteria, we have shortlisted ten proteins (GRB2, FYN, PIK3R1, CBL, JAK2, LCK, LYN, SYK, JAK1 and SOCS3) as effective candidates for drug development.

An effective approach for annotation of protein families with low sequence similarity and conserved motifs: identifying GDSL hydrolases across the plant kingdom.

PubMed

Vujaklija, Ivan; Bielen, Ana; Paradžik, Tina; Biđin, Siniša; Goldstein, Pavle; Vujaklija, Dušica

2016-02-18

The massive accumulation of protein sequences arising from the rapid development of high-throughput sequencing, coupled with automatic annotation, results in high levels of incorrect annotations. In this study, we describe an approach to decrease annotation errors of protein families characterized by low overall sequence similarity. The GDSL lipolytic family comprises proteins with multifunctional properties and high potential for pharmaceutical and industrial applications. The number of proteins assigned to this family has increased rapidly over the last few years. In particular, the natural abundance of GDSL enzymes reported recently in plants indicates that they could be a good source of novel GDSL enzymes. We noticed that a significant proportion of annotated sequences lack specific GDSL motif(s) or catalytic residue(s). Here, we applied motif-based sequence analyses to identify enzymes possessing conserved GDSL motifs in selected proteomes across the plant kingdom. Motif-based HMM scanning (Viterbi decoding-VD and posterior decoding-PD) and the here described PD/VD protocol were successfully applied on 12 selected plant proteomes to identify sequences with GDSL motifs. A significant number of identified GDSL sequences were novel. Moreover, our scanning approach successfully detected protein sequences lacking at least one of the essential motifs (171/820) annotated by Pfam profile search (PfamA) as GDSL. Based on these analyses we provide a curated list of GDSL enzymes from the selected plants. CLANS clustering and phylogenetic analysis helped us to gain a better insight into the evolutionary relationship of all identified GDSL sequences. Three novel GDSL subfamilies as well as unreported variations in GDSL motifs were discovered in this study. In addition, analyses of selected proteomes showed a remarkable expansion of GDSL enzymes in the lycophyte, Selaginella moellendorffii. Finally, we provide a general motif-HMM scanner which is easily accessible through

Identifying the Educationally Influential Physician: A Systematic Review of Approaches

ERIC Educational Resources Information Center

Kronberger, Matthew P.; Bakken, Lori L.

2011-01-01

Introduction: Previous studies have indicated that educationally influential physicians' (EIPs) interactions with peers can lead to practice changes and improved patient outcomes. However, multiple approaches have been used to identify and investigate EIPs' informal or formal influence on practice, which creates study outcomes that are difficult…

An Immunohistochemical Approach to Identify the Sex of Young Marine Turtles.

PubMed

Tezak, Boris M; Guthrie, Kathleen; Wyneken, Jeanette

2017-08-01

Marine turtles exhibit temperature-dependent sex determination (TSD). During critical periods of embryonic development, the nest's thermal environment directs whether an embryo will develop as a male or female. At warmer sand temperatures, nests tend to produce female-biased sex ratios. The rapid increase of global temperature highlights the need for a clear assessment of its effects on sea turtle sex ratios. However, estimating hatchling sex ratios at rookeries remains imprecise due to the lack of sexual dimorphism in young marine turtles. We rely mainly upon laparoscopic procedures to verify hatchling sex; however, in some species, morphological sex can be ambiguous even at the histological level. Recent studies using immunohistochemical (IHC) techniques identified that embryonic snapping turtle (Chelydra serpentina) ovaries overexpressed a particular cold-induced RNA-binding protein in comparison to testes. This feature allows the identification of females vs. males. We modified this technique to successfully identify the sexes of loggerhead sea turtle (Caretta caretta) hatchlings, and independently confirmed the results by standard histological and laparoscopic methods that reliably identify sex in this species. We next tested the CIRBP IHC method on gonad samples from leatherback turtles (Dermochelys coriacea). Leatherbacks display delayed gonad differentiation, when compared to other sea turtles, making hatchling gonads difficult to sex using standard H&E stain histology. The IHC approach was successful in both C. caretta and D. coriacea samples, offering a much-needed tool to establish baseline hatchling sex ratios, particularly for assessing impacts of climate change effects on leatherback turtle hatchlings and sea turtle demographics. Anat Rec, 300:1512-1518, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

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:…

Identifying the Critical Links in Road Transportation Networks: Centrality-based approach utilizing structural properties

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

Chinthavali, Supriya

Surface transportation road networks share structural properties similar to other complex networks (e.g., social networks, information networks, biological networks, and so on). This research investigates the structural properties of road networks for any possible correlation with the traffic characteristics such as link flows those determined independently. Additionally, we define a criticality index for the links of the road network that identifies the relative importance in the network. We tested our hypotheses with two sample road networks. Results show that, correlation exists between the link flows and centrality measures of a link of the road (dual graph approach is followed) andmore » the criticality index is found to be effective for one test network to identify the vulnerable nodes.« less

A Multiple-Tracer Approach for Identifying Sewage Sources to an Urban Stream System

USGS Publications Warehouse

Hyer, Kenneth Edward

2007-01-01

sampling approach, 149 sites were sampled at least one time for indicator tracers; 52 of these sites also were sampled for confirmatory tracers at least one time. Through the analysis of multiple-tracer levels in the synoptic samples, three major sewage sources to the Accotink Creek stream network were identified, and several other minor sewage sources to the Accotink Creek system likely deserve additional investigation. Near the end of the synoptic sampling activities, three additional sampling methods were used to gain better understanding of the potential for sewage sources to the watershed. These additional sampling methods included optical brightener monitoring, intensive stream sampling using automated samplers, and additional sampling of several storm-drain networks. The samples obtained by these methods provided further understanding of possible sewage sources to the streams and a better understanding of the variability in the tracer concentrations at a given sampling site. Collectively, these additional sampling methods were a valuable complement to the synoptic sampling approach that was used for the bulk of this study. The study results provide an approach for local authorities to use in applying a relatively simple and inexpensive collection of tracers to locate sewage sources to streams. Although this multiple-tracer approach is effective in detecting sewage sources to streams, additional research is needed to better detect extremely low-volume sewage sources and better enable local authorities to identify the specific sources of the sewage once it is detected in a stream reach.

A genomic approach to identify hybrid incompatibility genes.

PubMed

Cooper, Jacob C; Phadnis, Nitin

2016-07-02

Uncovering the genetic and molecular basis of barriers to gene flow between populations is key to understanding how new species are born. Intrinsic postzygotic reproductive barriers such as hybrid sterility and hybrid inviability are caused by deleterious genetic interactions known as hybrid incompatibilities. The difficulty in identifying these hybrid incompatibility genes remains a rate-limiting step in our understanding of the molecular basis of speciation. We recently described how whole genome sequencing can be applied to identify hybrid incompatibility genes, even from genetically terminal hybrids. Using this approach, we discovered a new hybrid incompatibility gene, gfzf, between Drosophila melanogaster and Drosophila simulans, and found that it plays an essential role in cell cycle regulation. Here, we discuss the history of the hunt for incompatibility genes between these species, discuss the molecular roles of gfzf in cell cycle regulation, and explore how intragenomic conflict drives the evolution of fundamental cellular mechanisms that lead to the developmental arrest of hybrids.

A genomic approach to identify hybrid incompatibility genes

PubMed Central

Cooper, Jacob C.; Phadnis, Nitin

2016-01-01

ABSTRACT Uncovering the genetic and molecular basis of barriers to gene flow between populations is key to understanding how new species are born. Intrinsic postzygotic reproductive barriers such as hybrid sterility and hybrid inviability are caused by deleterious genetic interactions known as hybrid incompatibilities. The difficulty in identifying these hybrid incompatibility genes remains a rate-limiting step in our understanding of the molecular basis of speciation. We recently described how whole genome sequencing can be applied to identify hybrid incompatibility genes, even from genetically terminal hybrids. Using this approach, we discovered a new hybrid incompatibility gene, gfzf, between Drosophila melanogaster and Drosophila simulans, and found that it plays an essential role in cell cycle regulation. Here, we discuss the history of the hunt for incompatibility genes between these species, discuss the molecular roles of gfzf in cell cycle regulation, and explore how intragenomic conflict drives the evolution of fundamental cellular mechanisms that lead to the developmental arrest of hybrids. PMID:27230814

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

PubMed

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

2016-02-01

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

Genome wide approaches to identify protein-DNA interactions.

PubMed

Ma, Tao; Ye, Zhenqing; Wang, Liguo

2018-05-29

Transcription factors are DNA-binding proteins that play key roles in many fundamental biological processes. Unraveling their interactions with DNA is essential to identify their target genes and understand the regulatory network. Genome-wide identification of their binding sites became feasible thanks to recent progress in experimental and computational approaches. ChIP-chip, ChIP-seq, and ChIP-exo are three widely used techniques to demarcate genome-wide transcription factor binding sites. This review aims to provide an overview of these three techniques including their experiment procedures, computational approaches, and popular analytic tools. ChIP-chip, ChIP-seq, and ChIP-exo have been the major techniques to study genome-wide in vivo protein-DNA interaction. Due to the rapid development of next-generation sequencing technology, array-based ChIP-chip is deprecated and ChIP-seq has become the most widely used technique to identify transcription factor binding sites in genome-wide. The newly developed ChIP-exo further improves the spatial resolution to single nucleotide. Numerous tools have been developed to analyze ChIP-chip, ChIP-seq and ChIP-exo data. However, different programs may employ different mechanisms or underlying algorithms thus each will inherently include its own set of statistical assumption and bias. So choosing the most appropriate analytic program for a given experiment needs careful considerations. Moreover, most programs only have command line interface so their installation and usage will require basic computation expertise in Unix/Linux. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Strategies Identified as Effective by Mothers During Occupational Performance Coaching.

PubMed

Graham, Fiona; Rodger, Sylvia; Ziviani, Jenny; Jones, Virginia

2016-08-01

This study examined strategies mothers reported as effective in facilitating children's successful performance in activities they identified as goals during Occupational Performance Coaching (OPC). Twenty-nine mothers of children with occupational performance issues engaged in OPC. A random sample of 44 /157 (28%) coaching sessions were video-recorded from which the audio recording was analyzed using a general inductive approach to explore the nature of strategies reported as effective by mothers. Two major themes emerged: (1) Context-focused; or (2) Child-focused. Context-focused strategies were characterized by mothers' actions that made the performance context more conducive to children's success. The emphasis of mothers' intention in Context-focused strategies was achievement of the task with minimal stress. Context-focused strategies included subthemes of Adjust Manner, Create Distance, Add Structure and Routine, and Teach. Child-focused strategies required higher levels of engagement with children in the application of strategies and were focused on children's skill development. Subthemes included Collaboration and Offer Choice. Mothers engaged in coaching identified strategies which they found supported children's performance, attesting to the existing capacity of mothers in identifying and evaluating effective ways of enhancing children's performance. Findings suggest the potential of coaching as a capacity-building, context-based intervention to improve children's performance.

Identifiability and Performance Analysis of Output Over-sampling Approach to Direct Closed-loop Identification

NASA Astrophysics Data System (ADS)

Sun, Lianming; Sano, Akira

Output over-sampling based closed-loop identification algorithm is investigated in this paper. Some instinct properties of the continuous stochastic noise and the plant input, output in the over-sampling approach are analyzed, and they are used to demonstrate the identifiability in the over-sampling approach and to evaluate its identification performance. Furthermore, the selection of plant model order, the asymptotic variance of estimated parameters and the asymptotic variance of frequency response of the estimated model are also explored. It shows that the over-sampling approach can guarantee the identifiability and improve the performance of closed-loop identification greatly.

Simplified Screening Approach Identifies Mutated Proteins Expressed in Patient Tumors | Center for Cancer Research

Cancer.gov

Adoptive cell therapy using tumor-infiltrating lymphocytes (TILs) is a very effective treatment for patients with metastatic melanoma. In phase 2 clinical trials, up to 70 percent of patients with melanoma who received autologous TILs had considerable regressions of metastatic lesions. Recently, in another trial, 40 percent of patients treated had complete regressions of all measurable lesions lasting more than five years after treatment. Identifying antigens associated with TIL-mediated tumor regression has been a difficult task due to the diversity of these large lymphocyte populations and the complexity of current screening approaches.

Alternative approaches for identifying acute systemic toxicity: Moving from research to regulatory testing.

PubMed

Hamm, Jon; Sullivan, Kristie; Clippinger, Amy J; Strickland, Judy; Bell, Shannon; Bhhatarai, Barun; Blaauboer, Bas; Casey, Warren; Dorman, David; Forsby, Anna; Garcia-Reyero, Natàlia; Gehen, Sean; Graepel, Rabea; Hotchkiss, Jon; Lowit, Anna; Matheson, Joanna; Reaves, Elissa; Scarano, Louis; Sprankle, Catherine; Tunkel, Jay; Wilson, Dan; Xia, Menghang; Zhu, Hao; Allen, David

2017-06-01

Acute systemic toxicity testing provides the basis for hazard labeling and risk management of chemicals. A number of international efforts have been directed at identifying non-animal alternatives for in vivo acute systemic toxicity tests. A September 2015 workshop, Alternative Approaches for Identifying Acute Systemic Toxicity: Moving from Research to Regulatory Testing, reviewed the state-of-the-science of non-animal alternatives for this testing and explored ways to facilitate implementation of alternatives. Workshop attendees included representatives from international regulatory agencies, academia, nongovernmental organizations, and industry. Resources identified as necessary for meaningful progress in implementing alternatives included compiling and making available high-quality reference data, training on use and interpretation of in vitro and in silico approaches, and global harmonization of testing requirements. Attendees particularly noted the need to characterize variability in reference data to evaluate new approaches. They also noted the importance of understanding the mechanisms of acute toxicity, which could be facilitated by the development of adverse outcome pathways. Workshop breakout groups explored different approaches to reducing or replacing animal use for acute toxicity testing, with each group crafting a roadmap and strategy to accomplish near-term progress. The workshop steering committee has organized efforts to implement the recommendations of the workshop participants. Copyright © 2017 Elsevier Ltd. All rights reserved.

Alternative Approaches for Identifying Acute Systemic Toxicity: Moving from Research to Regulatory Testing

PubMed Central

Hamm, Jon; Sullivan, Kristie; Clippinger, Amy J.; Strickland, Judy; Bell, Shannon; Bhhatarai, Barun; Blaauboer, Bas; Casey, Warren; Dorman, David; Forsby, Anna; Garcia-Reyero, Natàlia; Gehen, Sean; Graepel, Rabea; Hotchkiss, Jon; Lowit, Anna; Matheson, Joanna; Reaves, Elissa; Scarano, Louis; Sprankle, Catherine; Tunkel, Jay; Wilson, Dan; Xia, Menghang; Zhu, Hao; Allen, David

2017-01-01

Acute systemic toxicity testing provides the basis for hazard labeling and risk management of chemicals. A number of international efforts have been directed at identifying non-animal alternatives for in vivo acute systemic toxicity tests. A September 2015 workshop, Alternative Approaches for Identifying Acute Systemic Toxicity: Moving from Research to Regulatory Testing, reviewed the state-of-the-science of non-animal alternatives for this testing and explored ways to facilitate implementation of alternatives. Workshop attendees included representatives from international regulatory agencies, academia, nongovernmental organizations, and industry. Resources identified as necessary for meaningful progress in implementing alternatives included compiling and making available high-quality reference data, training on use and interpretation of in vitro and in silico approaches, and global harmonization of testing requirements. Attendees particularly noted the need to characterize variability in reference data to evaluate new approaches. They also noted the importance of understanding the mechanisms of acute toxicity, which could be facilitated by the development of adverse outcome pathways. Workshop breakout groups explored different approaches to reducing or replacing animal use for acute toxicity testing, with each group crafting a roadmap and strategy to accomplish near-term progress. The workshop steering committee has organized efforts to implement the recommendations of the workshop participants. PMID:28069485

A comparison of approaches for finding minimum identifying codes on graphs

NASA Astrophysics Data System (ADS)

Horan, Victoria; Adachi, Steve; Bak, Stanley

2016-05-01

In order to formulate mathematical conjectures likely to be true, a number of base cases must be determined. However, many combinatorial problems are NP-hard and the computational complexity makes this research approach difficult using a standard brute force approach on a typical computer. One sample problem explored is that of finding a minimum identifying code. To work around the computational issues, a variety of methods are explored and consist of a parallel computing approach using MATLAB, an adiabatic quantum optimization approach using a D-Wave quantum annealing processor, and lastly using satisfiability modulo theory (SMT) and corresponding SMT solvers. Each of these methods requires the problem to be formulated in a unique manner. In this paper, we address the challenges of computing solutions to this NP-hard problem with respect to each of these methods.

An information-theoretic approach to assess practical identifiability of parametric dynamical systems.

PubMed

Pant, Sanjay; Lombardi, Damiano

2015-10-01

A new approach for assessing parameter identifiability of dynamical systems in a Bayesian setting is presented. The concept of Shannon entropy is employed to measure the inherent uncertainty in the parameters. The expected reduction in this uncertainty is seen as the amount of information one expects to gain about the parameters due to the availability of noisy measurements of the dynamical system. Such expected information gain is interpreted in terms of the variance of a hypothetical measurement device that can measure the parameters directly, and is related to practical identifiability of the parameters. If the individual parameters are unidentifiable, correlation between parameter combinations is assessed through conditional mutual information to determine which sets of parameters can be identified together. The information theoretic quantities of entropy and information are evaluated numerically through a combination of Monte Carlo and k-nearest neighbour methods in a non-parametric fashion. Unlike many methods to evaluate identifiability proposed in the literature, the proposed approach takes the measurement-noise into account and is not restricted to any particular noise-structure. Whilst computationally intensive for large dynamical systems, it is easily parallelisable and is non-intrusive as it does not necessitate re-writing of the numerical solvers of the dynamical system. The application of such an approach is presented for a variety of dynamical systems--ranging from systems governed by ordinary differential equations to partial differential equations--and, where possible, validated against results previously published in the literature. Copyright © 2015 Elsevier Inc. All rights reserved.

An integrated remote sensing approach for identifying ecological range sites. [parker mountain

NASA Technical Reports Server (NTRS)

Jaynes, R. A.

1983-01-01

A model approach for identifying ecological range sites was applied to high elevation sagebrush-dominated rangelands on Parker Mountain, in south-central Utah. The approach utilizes map information derived from both high altitude color infrared photography and LANDSAT digital data, integrated with soils, geological, and precipitation maps. Identification of the ecological range site for a given area requires an evaluation of all relevant environmental factors which combine to give that site the potential to produce characteristic types and amounts of vegetation. A table is presented which allows the user to determine ecological range site based upon an integrated use of the maps which were prepared. The advantages of identifying ecological range sites through an integrated photo interpretation/LANDSAT analysis are discussed.

Xtalk: a path-based approach for identifying crosstalk between signaling pathways

PubMed Central

Tegge, Allison N.; Sharp, Nicholas; Murali, T. M.

2016-01-01

Motivation: Cells communicate with their environment via signal transduction pathways. On occasion, the activation of one pathway can produce an effect downstream of another pathway, a phenomenon known as crosstalk. Existing computational methods to discover such pathway pairs rely on simple overlap statistics. Results: We present Xtalk, a path-based approach for identifying pairs of pathways that may crosstalk. Xtalk computes the statistical significance of the average length of multiple short paths that connect receptors in one pathway to the transcription factors in another. By design, Xtalk reports the precise interactions and mechanisms that support the identified crosstalk. We applied Xtalk to signaling pathways in the KEGG and NCI-PID databases. We manually curated a gold standard set of 132 crosstalking pathway pairs and a set of 140 pairs that did not crosstalk, for which Xtalk achieved an area under the receiver operator characteristic curve of 0.65, a 12% improvement over the closest competing approach. The area under the receiver operator characteristic curve varied with the pathway, suggesting that crosstalk should be evaluated on a pathway-by-pathway level. We also analyzed an extended set of 658 pathway pairs in KEGG and to a set of more than 7000 pathway pairs in NCI-PID. For the top-ranking pairs, we found substantial support in the literature (81% for KEGG and 78% for NCI-PID). We provide examples of networks computed by Xtalk that accurately recovered known mechanisms of crosstalk. Availability and implementation: The XTALK software is available at http://bioinformatics.cs.vt.edu/~murali/software. Crosstalk networks are available at http://graphspace.org/graphs?tags=2015-bioinformatics-xtalk. Contact: ategge@vt.edu, murali@cs.vt.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26400040

A Virtual Screening Approach For Identifying Plants with Anti H5N1 Neuraminidase Activity

PubMed Central

2016-01-01

Recent outbreaks of highly pathogenic and occasional drug-resistant influenza strains have highlighted the need to develop novel anti-influenza therapeutics. Here, we report computational and experimental efforts to identify influenza neuraminidase inhibitors from among the 3000 natural compounds in the Malaysian-Plants Natural-Product (NADI) database. These 3000 compounds were first docked into the neuraminidase active site. The five plants with the largest number of top predicted ligands were selected for experimental evaluation. Twelve specific compounds isolated from these five plants were shown to inhibit neuraminidase, including two compounds with IC50 values less than 92 μM. Furthermore, four of the 12 isolated compounds had also been identified in the top 100 compounds from the virtual screen. Together, these results suggest an effective new approach for identifying bioactive plant species that will further the identification of new pharmacologically active compounds from diverse natural-product resources. PMID:25555059

Maximal Predictability Approach for Identifying the Right Descriptors for Electrocatalytic Reactions.

PubMed

Krishnamurthy, Dilip; Sumaria, Vaidish; Viswanathan, Venkatasubramanian

2018-02-01

Density functional theory (DFT) calculations are being routinely used to identify new material candidates that approach activity near fundamental limits imposed by thermodynamics or scaling relations. DFT calculations are associated with inherent uncertainty, which limits the ability to delineate materials (distinguishability) that possess high activity. Development of error-estimation capabilities in DFT has enabled uncertainty propagation through activity-prediction models. In this work, we demonstrate an approach to propagating uncertainty through thermodynamic activity models leading to a probability distribution of the computed activity and thereby its expectation value. A new metric, prediction efficiency, is defined, which provides a quantitative measure of the ability to distinguish activity of materials and can be used to identify the optimal descriptor(s) ΔG opt . We demonstrate the framework for four important electrochemical reactions: hydrogen evolution, chlorine evolution, oxygen reduction and oxygen evolution. Future studies could utilize expected activity and prediction efficiency to significantly improve the prediction accuracy of highly active material candidates.

Identifying Effective Methods of Instruction for Adult Emergent Readers through Community-Based Research

ERIC Educational Resources Information Center

Blackmer, Rachel; Hayes-Harb, Rachel

2016-01-01

We present a community-based research project aimed at identifying effective methods and materials for teaching English literacy skills to adult English as a second language emergent readers. We conducted a quasi-experimental study whereby we evaluated the efficacy of two approaches, one based on current practices at the English Skills Learning…

New approaches for identifying and testing potential new anti-asthma agents.

PubMed

Licari, Amelia; Castagnoli, Riccardo; Brambilla, Ilaria; Marseglia, Alessia; Tosca, Maria Angela; Marseglia, Gian Luigi; Ciprandi, Giorgio

2018-01-01

Asthma is a chronic disease with significant heterogeneity in clinical features, disease severity, pattern of underlying disease mechanisms, and responsiveness to specific treatments. While the majority of asthmatic patients are controlled by standard pharmacological strategies, a significant subgroup has limited therapeutic options representing a major unmet need. Ongoing asthma research aims to better characterize distinct clinical phenotypes, molecular endotypes, associated reliable biomarkers, and also to develop a series of new effective targeted treatment modalities. Areas covered: The expanding knowledge on the pathogenetic mechanisms of asthma has allowed researchers to investigate a range of new treatment options matched to patient profiles. The aim of this review is to provide a comprehensive and updated overview of the currently available, new and developing approaches for identifying and testing potential treatment options for asthma management. Expert opinion: Future therapeutic strategies for asthma require the identification of reliable biomarkers that can help with diagnosis and endotyping, in order to determine the most effective drug for the right patient phenotype. Furthermore, in addition to the identification of clinical and inflammatory phenotypes, it is expected that a better understanding of the mechanisms of airway remodeling will likely optimize asthma targeted treatment.

Culling a clinical terminology: a systematic approach to identifying problematic content.

PubMed Central

Sable, J. H.; Nash, S. K.; Wang, A. Y.

2001-01-01

The College of American Pathologists and the National Health Service (NHS) in the United Kingdom are merging their respective clinical terminologies, SNOMED RT and Clinical Terms Version 3, into a new terminology, SNOMED CT. This requires mapping concept descriptions between the two existing terminologies. During the mapping process, many descriptions were identified as being potentially problematic. They require further review by the SNOMED editorial process before either (1) being incorporated into SNOMED CT, or (2) retired from active use. This article presents data on the concept descriptions that were identified as needing further review during the early phases of SNOMED CT development. Based on this work, we describe fourteen types of problematic terminology content. Identifying problematic terminology content can be approached in a systematic manner. PMID:11825253

Identifying apicoplast-targeting antimalarials using high-throughput compatible approaches

PubMed Central

Ekland, Eric H.; Schneider, Jessica; Fidock, David A.

2011-01-01

Malarial parasites have evolved resistance to all previously used therapies, and recent evidence suggests emerging resistance to the first-line artemisinins. To identify antimalarials with novel mechanisms of action, we have developed a high-throughput screen targeting the apicoplast organelle of Plasmodium falciparum. Antibiotics known to interfere with this organelle, such as azithromycin, exhibit an unusual phenotype whereby the progeny of drug-treated parasites die. Our screen exploits this phenomenon by assaying for “delayed death” compounds that exhibit a higher potency after two cycles of intraerythrocytic development compared to one. We report a primary assay employing parasites with an integrated copy of a firefly luciferase reporter gene and a secondary flow cytometry-based assay using a nucleic acid stain paired with a mitochondrial vital dye. Screening of the U.S. National Institutes of Health Clinical Collection identified known and novel antimalarials including kitasamycin. This inexpensive macrolide, used for agricultural applications, exhibited an in vitro IC50 in the 50 nM range, comparable to the 30 nM activity of our control drug, azithromycin. Imaging and pharmacologic studies confirmed kitasamycin action against the apicoplast, and in vivo activity was observed in a murine malaria model. These assays provide the foundation for high-throughput campaigns to identify novel chemotypes for combination therapies to treat multidrug-resistant malaria.—Ekland, E. H., Schneider, J., Fidock, D. A. Identifying apicoplast-targeting antimalarials using high-throughput compatible approaches. PMID:21746861

A clustering approach to identify severe bronchiolitis profiles in children

PubMed Central

Dumas, Orianne; Mansbach, Jonathan M; Jartti, Tuomas; Hasegawa, Kohei; Sullivan, Ashley F; Piedra, Pedro A; Camargo, Carlos A

2016-01-01

Objective Although bronchiolitis is generally considered a single disease, recent studies suggest heterogeneity. We aimed to identify severe bronchiolitis profiles using a clustering approach. Methods We analyzed data from two prospective, multi-center cohorts of children younger than 2 years hospitalized with bronchiolitis, one in the U.S. (2007–2010 winter seasons, n=2,207) and one in Finland (2008–2010 winter seasons, n=408). Severe bronchiolitis profiles were determined by latent class analysis, classifying children based on clinical factors and viral etiology. Results In the U.S. study, four profiles were identified. Profile A (12%) was characterized by history of wheezing and eczema, wheezing at the ED presentation and rhinovirus infection. Profile B (36%) included children with wheezing at the ED presentation, but, in contrast to profile A, most did not have history of wheezing or eczema; this profile had the largest probability of RSV-infection. Profile C (34%) was the most severely ill group, with longer hospital stay and moderate-to-severe retractions. Profile D (17%) had the least severe illness, including non-wheezing children with shorter length-of-stay. Two of these profiles (A and D) were replicated in the Finnish cohort; a third group (“BC”) included Finnish children with characteristics of profiles B and/or C in the U.S. population. Conclusion Several distinct clinical profiles (phenotypes) were identified by a clustering approach in two multicenter studies of children hospitalized for bronchiolitis. The observed heterogeneity has important implications for future research on the etiology, management and long-term outcomes of bronchiolitis, such as future risk of childhood asthma. PMID:27339060

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

PubMed

Zhu; Dale

2000-10-01

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

Online-Based Approaches to Identify Real Journals and Publishers from Hijacked Ones.

PubMed

Asadi, Amin; Rahbar, Nader; Asadi, Meisam; Asadi, Fahime; Khalili Paji, Kokab

2017-02-01

The aim of the present paper was to introduce some online-based approaches to evaluate scientific journals and publishers and to differentiate them from the hijacked ones, regardless of their disciplines. With the advent of open-access journals, many hijacked journals and publishers have deceitfully assumed the mantle of authenticity in order to take advantage of researchers and students. Although these hijacked journals and publishers can be identified through checking their advertisement techniques and their websites, these ways do not always result in their identification. There exist certain online-based approaches, such as using Master Journal List provided by Thomson Reuters, and Scopus database, and using the DOI of a paper, to certify the realness of a journal or publisher. It is indispensable that inexperienced students and researchers know these methods so as to identify hijacked journals and publishers with a higher level of probability.

A fluorescent approach for identifying P2X1 ligands

PubMed Central

Ruepp, Marc-David; Brozik, James A.; de Esch, Iwan J.P.; Farndale, Richard W.; Murrell-Lagnado, Ruth D.; Thompson, Andrew J.

2015-01-01

There are no commercially available, small, receptor-specific P2X1 ligands. There are several synthetic derivatives of the natural agonist ATP and some structurally-complex antagonists including compounds such as PPADS, NTP-ATP, suramin and its derivatives (e.g. NF279, NF449). NF449 is the most potent and selective ligand, but potencies of many others are not particularly high and they can also act at other P2X, P2Y and non-purinergic receptors. While there is clearly scope for further work on P2X1 receptor pharmacology, screening can be difficult owing to rapid receptor desensitisation. To reduce desensitisation substitutions can be made within the N-terminus of the P2X1 receptor, but these could also affect ligand properties. An alternative is the use of fluorescent voltage-sensitive dyes that respond to membrane potential changes resulting from channel opening. Here we utilised this approach in conjunction with fragment-based drug-discovery. Using a single concentration (300 μM) we identified 46 novel leads from a library of 1443 fragments (hit rate = 3.2%). These hits were independently validated by measuring concentration-dependence with the same voltage-sensitive dye, and by visualising the competition of hits with an Alexa-647-ATP fluorophore using confocal microscopy; confocal yielded kon (1.142 × 106 M−1 s−1) and koff (0.136 s−1) for Alexa-647-ATP (Kd = 119 nM). The identified hit fragments had promising structural diversity. In summary, the measurement of functional responses using voltage-sensitive dyes was flexible and cost-effective because labelled competitors were not needed, effects were independent of a specific binding site, and both agonist and antagonist actions were probed in a single assay. The method is widely applicable and could be applied to all P2X family members, as well as other voltage-gated and ligand-gated ion channels. This article is part of the Special Issue entitled ‘Fluorescent Tools in Neuropharmacology�

A fluorescent approach for identifying P2X1 ligands.

PubMed

Ruepp, Marc-David; Brozik, James A; de Esch, Iwan J P; Farndale, Richard W; Murrell-Lagnado, Ruth D; Thompson, Andrew J

2015-11-01

There are no commercially available, small, receptor-specific P2X1 ligands. There are several synthetic derivatives of the natural agonist ATP and some structurally-complex antagonists including compounds such as PPADS, NTP-ATP, suramin and its derivatives (e.g. NF279, NF449). NF449 is the most potent and selective ligand, but potencies of many others are not particularly high and they can also act at other P2X, P2Y and non-purinergic receptors. While there is clearly scope for further work on P2X1 receptor pharmacology, screening can be difficult owing to rapid receptor desensitisation. To reduce desensitisation substitutions can be made within the N-terminus of the P2X1 receptor, but these could also affect ligand properties. An alternative is the use of fluorescent voltage-sensitive dyes that respond to membrane potential changes resulting from channel opening. Here we utilised this approach in conjunction with fragment-based drug-discovery. Using a single concentration (300 μM) we identified 46 novel leads from a library of 1443 fragments (hit rate = 3.2%). These hits were independently validated by measuring concentration-dependence with the same voltage-sensitive dye, and by visualising the competition of hits with an Alexa-647-ATP fluorophore using confocal microscopy; confocal yielded kon (1.142 × 10(6) M(-1) s(-1)) and koff (0.136 s(-1)) for Alexa-647-ATP (Kd = 119 nM). The identified hit fragments had promising structural diversity. In summary, the measurement of functional responses using voltage-sensitive dyes was flexible and cost-effective because labelled competitors were not needed, effects were independent of a specific binding site, and both agonist and antagonist actions were probed in a single assay. The method is widely applicable and could be applied to all P2X family members, as well as other voltage-gated and ligand-gated ion channels. This article is part of the Special Issue entitled 'Fluorescent Tools in Neuropharmacology'. Copyright �

Different approaches for identifying important concepts in probabilistic biomedical text summarization.

PubMed

Moradi, Milad; Ghadiri, Nasser

2018-01-01

Automatic text summarization tools help users in the biomedical domain to acquire their intended information from various textual resources more efficiently. Some of biomedical text summarization systems put the basis of their sentence selection approach on the frequency of concepts extracted from the input text. However, it seems that exploring other measures rather than the raw frequency for identifying valuable contents within an input document, or considering correlations existing between concepts, may be more useful for this type of summarization. In this paper, we describe a Bayesian summarization method for biomedical text documents. The Bayesian summarizer initially maps the input text to the Unified Medical Language System (UMLS) concepts; then it selects the important ones to be used as classification features. We introduce six different feature selection approaches to identify the most important concepts of the text and select the most informative contents according to the distribution of these concepts. We show that with the use of an appropriate feature selection approach, the Bayesian summarizer can improve the performance of biomedical summarization. Using the Recall-Oriented Understudy for Gisting Evaluation (ROUGE) toolkit, we perform extensive evaluations on a corpus of scientific papers in the biomedical domain. The results show that when the Bayesian summarizer utilizes the feature selection methods that do not use the raw frequency, it can outperform the biomedical summarizers that rely on the frequency of concepts, domain-independent and baseline methods. Copyright © 2017 Elsevier B.V. All rights reserved.

Translational informatics approach for identifying the functional molecular communicators linking coronary artery disease, infection and inflammation

PubMed Central

SHARMA, ANKIT; GHATGE, MADANKUMAR; MUNDKUR, LAKSHMI; VANGALA, RAJANI KANTH

2016-01-01

Translational informatics approaches are required for the integration of diverse and accumulating data to enable the administration of effective translational medicine specifically in complex diseases such as coronary artery disease (CAD). In the current study, a novel approach for elucidating the association between infection, inflammation and CAD was used. Genes for CAD were collected from the CAD-gene database and those for infection and inflammation were collected from the UniProt database. The cytomegalovirus (CMV)-induced genes were identified from the literature and the CAD-associated clinical phenotypes were obtained from the Unified Medical Language System. A total of 55 gene ontologies (GO) termed functional communicator ontologies were identifed in the gene sets linking clinical phenotypes in the diseasome network. The network topology analysis suggested that important functions including viral entry, cell adhesion, apoptosis, inflammatory and immune responses networked with clinical phenotypes. Microarray data was extracted from the Gene Expression Omnibus (dataset: GSE48060) for highly networked disease myocardial infarction. Further analysis of differentially expressed genes and their GO terms suggested that CMV infection may trigger a xenobiotic response, oxidative stress, inflammation and immune modulation. Notably, the current study identified γ-glutamyl transferase (GGT)-5 as a potential biomarker with an odds ratio of 1.947, which increased to 2.561 following the addition of CMV and CMV-neutralizing antibody (CMV-NA) titers. The C-statistics increased from 0.530 for conventional risk factors (CRFs) to 0.711 for GGT in combination with the above mentioned infections and CRFs. Therefore, the translational informatics approach used in the current study identified a potential molecular mechanism for CMV infection in CAD, and a potential biomarker for risk prediction. PMID:27035874

Learn the Lagrangian: A Vector-Valued RKHS Approach to Identifying Lagrangian Systems.

PubMed

Cheng, Ching-An; Huang, Han-Pang

2016-12-01

We study the modeling of Lagrangian systems with multiple degrees of freedom. Based on system dynamics, canonical parametric models require ad hoc derivations and sometimes simplification for a computable solution; on the other hand, due to the lack of prior knowledge in the system's structure, modern nonparametric models in machine learning face the curse of dimensionality, especially in learning large systems. In this paper, we bridge this gap by unifying the theories of Lagrangian systems and vector-valued reproducing kernel Hilbert space. We reformulate Lagrangian systems with kernels that embed the governing Euler-Lagrange equation-the Lagrangian kernels-and show that these kernels span a subspace capturing the Lagrangian's projection as inverse dynamics. By such property, our model uses only inputs and outputs as in machine learning and inherits the structured form as in system dynamics, thereby removing the need for the mundane derivations for new systems as well as the generalization problem in learning from scratches. In effect, it learns the system's Lagrangian, a simpler task than directly learning the dynamics. To demonstrate, we applied the proposed kernel to identify the robot inverse dynamics in simulations and experiments. Our results present a competitive novel approach to identifying Lagrangian systems, despite using only inputs and outputs.

Identifying technology innovations for marginalized smallholders-A conceptual approach.

PubMed

Malek, Mohammad Abdul; Gatzweiler, Franz W; Von Braun, Joachim

2017-05-01

This paper adds a contribution in the existing literature in terms of theoretical and conceptual background for the identification of idle potentials of marginal rural areas and people by means of technological and institutional innovations. The approach follows ex-ante assessment for identifying suitable technology and institutional innovations for marginalized smallholders in marginal areas-divided into three main parts (mapping, surveying and evaluating) and several steps. Finally, it contributes to the inclusion of marginalized smallholders by an improved way of understanding the interactions between technology needs, farming systems, ecological resources and poverty characteristics in the different segments of the poor, and to link these insights with productivity enhancing technologies.

Missing defects? A comparison of microscopic and macroscopic approaches to identifying linear enamel hypoplasia.

PubMed

Hassett, Brenna R

2014-03-01

Linear enamel hypoplasia (LEH), the presence of linear defects of dental enamel formed during periods of growth disruption, is frequently analyzed in physical anthropology as evidence for childhood health in the past. However, a wide variety of methods for identifying and interpreting these defects in archaeological remains exists, preventing easy cross-comparison of results from disparate studies. This article compares a standard approach to identifying LEH using the naked eye to the evidence of growth disruption observed microscopically from the enamel surface. This comparison demonstrates that what is interpreted as evidence of growth disruption microscopically is not uniformly identified with the naked eye, and provides a reference for the level of consistency between the number and timing of defects identified using microscopic versus macroscopic approaches. This is done for different tooth types using a large sample of unworn permanent teeth drawn from several post-medieval London burial assemblages. The resulting schematic diagrams showing where macroscopic methods achieve more or less similar results to microscopic methods are presented here and clearly demonstrate that "naked-eye" methods of identifying growth disruptions do not identify LEH as often as microscopic methods in areas where perikymata are more densely packed. Copyright © 2013 Wiley Periodicals, Inc.

A phase coherence approach to identifying co-located earthquakes and tremor

NASA Astrophysics Data System (ADS)

Hawthorne, J. C.; Ampuero, J.-P.

2018-05-01

We present and use a phase coherence approach to identify seismic signals that have similar path effects but different source time functions: co-located earthquakes and tremor. The method used is a phase coherence-based implementation of empirical matched field processing, modified to suit tremor analysis. It works by comparing the frequency-domain phases of waveforms generated by two sources recorded at multiple stations. We first cross-correlate the records of the two sources at a single station. If the sources are co-located, this cross-correlation eliminates the phases of the Green's function. It leaves the relative phases of the source time functions, which should be the same across all stations so long as the spatial extent of the sources are small compared with the seismic wavelength. We therefore search for cross-correlation phases that are consistent across stations as an indication of co-located sources. We also introduce a method to obtain relative locations between the two sources, based on back-projection of interstation phase coherence. We apply this technique to analyse two tremor-like signals that are thought to be composed of a number of earthquakes. First, we analyse a 20 s long seismic precursor to a M 3.9 earthquake in central Alaska. The analysis locates the precursor to within 2 km of the mainshock, and it identifies several bursts of energy—potentially foreshocks or groups of foreshocks—within the precursor. Second, we examine several minutes of volcanic tremor prior to an eruption at Redoubt Volcano. We confirm that the tremor source is located close to repeating earthquakes identified earlier in the tremor sequence. The amplitude of the tremor diminishes about 30 s before the eruption, but the phase coherence results suggest that the tremor may persist at some level through this final interval.

A physarum-inspired prize-collecting steiner tree approach to identify subnetworks for drug repositioning.

PubMed

Sun, Yahui; Hameed, Pathima Nusrath; Verspoor, Karin; Halgamuge, Saman

2016-12-05

Drug repositioning can reduce the time, costs and risks of drug development by identifying new therapeutic effects for known drugs. It is challenging to reposition drugs as pharmacological data is large and complex. Subnetwork identification has already been used to simplify the visualization and interpretation of biological data, but it has not been applied to drug repositioning so far. In this paper, we fill this gap by proposing a new Physarum-inspired Prize-Collecting Steiner Tree algorithm to identify subnetworks for drug repositioning. Drug Similarity Networks (DSN) are generated using the chemical, therapeutic, protein, and phenotype features of drugs. In DSNs, vertex prizes and edge costs represent the similarities and dissimilarities between drugs respectively, and terminals represent drugs in the cardiovascular class, as defined in the Anatomical Therapeutic Chemical classification system. A new Physarum-inspired Prize-Collecting Steiner Tree algorithm is proposed in this paper to identify subnetworks. We apply both the proposed algorithm and the widely-used GW algorithm to identify subnetworks in our 18 generated DSNs. In these DSNs, our proposed algorithm identifies subnetworks with an average Rand Index of 81.1%, while the GW algorithm can only identify subnetworks with an average Rand Index of 64.1%. We select 9 subnetworks with high Rand Index to find drug repositioning opportunities. 10 frequently occurring drugs in these subnetworks are identified as candidates to be repositioned for cardiovascular diseases. We find evidence to support previous discoveries that nitroglycerin, theophylline and acarbose may be able to be repositioned for cardiovascular diseases. Moreover, we identify seven previously unknown drug candidates that also may interact with the biological cardiovascular system. These discoveries show our proposed Prize-Collecting Steiner Tree approach as a promising strategy for drug repositioning.

An Integrated Approach Identifies Mediators of Local Recurrence in Head and Neck Squamous Carcinoma.

PubMed

Citron, Francesca; Armenia, Joshua; Franchin, Giovanni; Polesel, Jerry; Talamini, Renato; D'Andrea, Sara; Sulfaro, Sandro; Croce, Carlo M; Klement, William; Otasek, David; Pastrello, Chiara; Tokar, Tomas; Jurisica, Igor; French, Deborah; Bomben, Riccardo; Vaccher, Emanuela; Serraino, Diego; Belletti, Barbara; Vecchione, Andrea; Barzan, Luigi; Baldassarre, Gustavo

2017-07-15

Purpose: Head and neck squamous cell carcinomas (HNSCCs) cause more than 300,000 deaths worldwide each year. Locoregional and distant recurrences represent worse prognostic events and accepted surrogate markers of patients' overall survival. No valid biomarker and salvage therapy exist to identify and treat patients at high-risk of recurrence. We aimed to verify if selected miRNAs could be used as biomarkers of recurrence in HNSCC. Experimental Design: A NanoString array was used to identify miRNAs associated with locoregional recurrence in 44 patients with HNSCC. Bioinformatic approaches validated the signature and identified potential miRNA targets. Validation experiments were performed using an independent cohort of primary HNSCC samples and a panel of HNSCC cell lines. In vivo experiments validated the in vitro results. Results: Our data identified a four-miRNA signature that classified HNSCC patients at high- or low-risk of recurrence. These miRNAs collectively impinge on the epithelial-mesenchymal transition process. In silico and wet lab approaches showed that miR-9, expressed at high levels in recurrent HNSCC, targets SASH1 and KRT13, whereas miR-1, miR-133, and miR-150, expressed at low levels in recurrent HNSCC, collectively target SP1 and TGFβ pathways. A six-gene signature comprising these targets identified patients at high risk of recurrences, as well. Combined pharmacological inhibition of SP1 and TGFβ pathways induced HNSCC cell death and, when timely administered, prevented recurrence formation in a preclinical model of HNSCC recurrence. Conclusions: By integrating different experimental approaches and competences, we identified critical mediators of recurrence formation in HNSCC that may merit to be considered for future clinical development. Clin Cancer Res; 23(14); 3769-80. ©2017 AACR . ©2017 American Association for Cancer Research.

A probabilistic approach to identify putative drug targets in biochemical networks.

PubMed

Murabito, Ettore; Smallbone, Kieran; Swinton, Jonathan; Westerhoff, Hans V; Steuer, Ralf

2011-06-06

Network-based drug design holds great promise in clinical research as a way to overcome the limitations of traditional approaches in the development of drugs with high efficacy and low toxicity. This novel strategy aims to study how a biochemical network as a whole, rather than its individual components, responds to specific perturbations in different physiological conditions. Proteins exerting little control over normal cells and larger control over altered cells may be considered as good candidates for drug targets. The application of network-based drug design would greatly benefit from using an explicit computational model describing the dynamics of the system under investigation. However, creating a fully characterized kinetic model is not an easy task, even for relatively small networks, as it is still significantly hampered by the lack of data about kinetic mechanisms and parameters values. Here, we propose a Monte Carlo approach to identify the differences between flux control profiles of a metabolic network in different physiological states, when information about the kinetics of the system is partially or totally missing. Based on experimentally accessible information on metabolic phenotypes, we develop a novel method to determine probabilistic differences in the flux control coefficients between the two observable phenotypes. Knowledge of how differences in flux control are distributed among the different enzymatic steps is exploited to identify points of fragility in one of the phenotypes. Using a prototypical cancerous phenotype as an example, we demonstrate how our approach can assist researchers in developing compounds with high efficacy and low toxicity. © 2010 The Royal Society

Neuroimaging and Neuromodulation: Complementary Approaches for Identifying the Neuronal Correlates of Tinnitus

PubMed Central

Langguth, Berthold; Schecklmann, Martin; Lehner, Astrid; Landgrebe, Michael; Poeppl, Timm Benjamin; Kreuzer, Peter Michal; Schlee, Winfried; Weisz, Nathan; Vanneste, Sven; De Ridder, Dirk

2012-01-01

An inherent limitation of functional imaging studies is their correlational approach. More information about critical contributions of specific brain regions can be gained by focal transient perturbation of neural activity in specific regions with non-invasive focal brain stimulation methods. Functional imaging studies have revealed that tinnitus is related to alterations in neuronal activity of central auditory pathways. Modulation of neuronal activity in auditory cortical areas by repetitive transcranial magnetic stimulation (rTMS) can reduce tinnitus loudness and, if applied repeatedly, exerts therapeutic effects, confirming the relevance of auditory cortex activation for tinnitus generation and persistence. Measurements of oscillatory brain activity before and after rTMS demonstrate that the same stimulation protocol has different effects on brain activity in different patients, presumably related to interindividual differences in baseline activity in the clinically heterogeneous study cohort. In addition to alterations in auditory pathways, imaging techniques also indicate the involvement of non-auditory brain areas, such as the fronto-parietal “awareness” network and the non-tinnitus-specific distress network consisting of the anterior cingulate cortex, anterior insula, and amygdale. Involvement of the hippocampus and the parahippocampal region putatively reflects the relevance of memory mechanisms in the persistence of the phantom percept and the associated distress. Preliminary studies targeting the dorsolateral prefrontal cortex, the dorsal anterior cingulate cortex, and the parietal cortex with rTMS and with transcranial direct current stimulation confirm the relevance of the mentioned non-auditory networks. Available data indicate the important value added by brain stimulation as a complementary approach to neuroimaging for identifying the neuronal correlates of the various clinical aspects of tinnitus. PMID:22509155

Approach to identifying pollutant source and matching flow field

NASA Astrophysics Data System (ADS)

Liping, Pang; Yu, Zhang; Hongquan, Qu; Tao, Hu; Wei, Wang

2013-07-01

Accidental pollution events often threaten people's health and lives, and it is necessary to identify a pollutant source rapidly so that prompt actions can be taken to prevent the spread of pollution. But this identification process is one of the difficulties in the inverse problem areas. This paper carries out some studies on this issue. An approach using single sensor information with noise was developed to identify a sudden continuous emission trace pollutant source in a steady velocity field. This approach first compares the characteristic distance of the measured concentration sequence to the multiple hypothetical measured concentration sequences at the sensor position, which are obtained based on a source-three-parameter multiple hypotheses. Then we realize the source identification by globally searching the optimal values with the objective function of the maximum location probability. Considering the large amount of computation load resulting from this global searching, a local fine-mesh source search method based on priori coarse-mesh location probabilities is further used to improve the efficiency of identification. Studies have shown that the flow field has a very important influence on the source identification. Therefore, we also discuss the impact of non-matching flow fields with estimation deviation on identification. Based on this analysis, a method for matching accurate flow field is presented to improve the accuracy of identification. In order to verify the practical application of the above method, an experimental system simulating a sudden pollution process in a steady flow field was set up and some experiments were conducted when the diffusion coefficient was known. The studies showed that the three parameters (position, emission strength and initial emission time) of the pollutant source in the experiment can be estimated by using the method for matching flow field and source identification.

A Mixed Methods Approach to Identify Cognitive Warning Signs for Suicide Attempts.

PubMed

Adler, Abby; Bush, Ashley; Barg, Frances K; Weissinger, Guy; Beck, Aaron T; Brown, Gregory K

2016-01-01

This study used a mixed methods approach to examine pathways to suicidal behavior by identifying cognitive warning signs that occurred within 1 day of a suicide attempt. Transcripts of cognitive therapy sessions from 35 patients who attempted suicide were analyzed using a modified grounded theory approach. Cognitive themes emerging from these transcripts included: state hopelessness, focus on escape, suicide as a solution, fixation on suicide, and aloneness. Differences in demographic and baseline diagnostic and symptom data were explored in relation to each cognitive theme. We propose a potential conceptual model of cognitive warning signs for suicide attempts that requires further testing.

Identifying influential spreaders in complex networks through local effective spreading paths

NASA Astrophysics Data System (ADS)

Wang, Xiaojie; Zhang, Xue; Yi, Dongyun; Zhao, Chengli

2017-05-01

How to effectively identify a set of influential spreaders in complex networks is of great theoretical and practical value, which can help to inhibit the rapid spread of epidemics, promote the sales of products by word-of-mouth advertising, and so on. A naive strategy is to select the top ranked nodes as identified by some centrality indices, and other strategies are mainly based on greedy methods and heuristic methods. However, most of those approaches did not concern the connections between nodes. Usually, the distances between the selected spreaders are very close, leading to a serious overlapping of their influence. As a consequence, the global influence of the spreaders in networks will be greatly reduced, which largely restricts the performance of those methods. In this paper, a simple and efficient method is proposed to identify a set of discrete yet influential spreaders. By analyzing the spreading paths in the network, we present the concept of effective spreading paths and measure the influence of nodes via expectation calculation. The numerical analysis in undirected and directed networks all show that our proposed method outperforms many other centrality-based and heuristic benchmarks, especially in large-scale networks. Besides, experimental results on different spreading models and parameters demonstrates the stability and wide applicability of our method.

Identifying Mother-Child Interaction Styles Using a Person-Centered Approach.

PubMed

Nelson, Jackie A; O'Brien, Marion; Grimm, Kevin J; Leerkes, Esther M

2014-05-01

Parent-child conflict in the context of a supportive relationship has been discussed as a potentially constructive interaction pattern; the current study is the first to test this using a holistic analytic approach. Interaction styles, defined as mother-child conflict in the context of maternal sensitivity, were identified and described with demographic and stress-related characteristics of families. Longitudinal associations were tested between interaction styles and children's later social competence. Participants included 814 partnered mothers with a first-grade child. Latent profile analysis identified agreeable , dynamic , and disconnected interaction styles. Mothers' intimacy with a partner, depressive symptoms, and authoritarian childrearing beliefs, along with children's later conflict with a best friend and externalizing problems, were associated with group membership. Notably, the dynamic style, characterized by high sensitivity and high conflict, included families who experienced psychological and relational stressors. Findings are discussed with regard to how family stressors shape parent-child interaction patterns.

A machine learning based approach to identify protected health information in Chinese clinical text.

PubMed

Du, Liting; Xia, Chenxi; Deng, Zhaohua; Lu, Gary; Xia, Shuxu; Ma, Jingdong

2018-08-01

With the increasing application of electronic health records (EHRs) in the world, protecting private information in clinical text has drawn extensive attention from healthcare providers to researchers. De-identification, the process of identifying and removing protected health information (PHI) from clinical text, has been central to the discourse on medical privacy since 2006. While de-identification is becoming the global norm for handling medical records, there is a paucity of studies on its application on Chinese clinical text. Without efficient and effective privacy protection algorithms in place, the use of indispensable clinical information would be confined. We aimed to (i) describe the current process for PHI in China, (ii) propose a machine learning based approach to identify PHI in Chinese clinical text, and (iii) validate the effectiveness of the machine learning algorithm for de-identification in Chinese clinical text. Based on 14,719 discharge summaries from regional health centers in Ya'an City, Sichuan province, China, we built a conditional random fields (CRF) model to identify PHI in clinical text, and then used the regular expressions to optimize the recognition results of the PHI categories with fewer samples. We constructed a Chinese clinical text corpus with PHI tags through substantial manual annotation, wherein the descriptive statistics of PHI manifested its wide range and diverse categories. The evaluation showed with a high F-measure of 0.9878 that our CRF-based model had a good performance for identifying PHI in Chinese clinical text. The rapid adoption of EHR in the health sector has created an urgent need for tools that can parse patient specific information from Chinese clinical text. Our application of CRF algorithms for de-identification has shown the potential to meet this need by offering a highly accurate and flexible solution to analyzing Chinese clinical text. Copyright © 2018 Elsevier B.V. All rights reserved.

Identifying determinants of effective complementary feeding behaviour change interventions in developing countries

PubMed Central

Fabrizio, Cecilia S; van Liere, Marti; Pelto, Gretel

2014-01-01

As stunting moves to the forefront of the global agenda, there is substantial evidence that behaviour change interventions (BCI) can improve infant feeding practices and growth. However, this evidence has not been translated into improved outcomes on a national level because we do not know enough about what makes these interventions work, for whom, when, why, at what cost and for how long. Our objective was to examine the design and implementation of complementary feeding BCI, from the peer-reviewed literature, to identify generalisable key determinants. We identified 29 studies that evaluated BCI efficacy or effectiveness, were conducted in developing countries, and reported outcomes on infant and young children aged 6–24 months. Two potential determinants emerged: (1) effective studies used formative research to identify cultural barriers and enablers to optimal feeding practices, to shape the intervention strategy, and to formulate appropriate messages and mediums for delivery; (2) effective studies delineated the programme impact pathway to the target behaviour change and assessed intermediary behaviour changes to learn what worked. We found that BCI that used these developmental and implementation processes could be effective despite heterogeneous approaches and design components. Our analysis was constrained, however, by the limited published data on how design and implementation were carried out, perhaps because of publishing space limits. Information on cost-effectiveness, sustainability and scalability was also very limited. We suggest a more comprehensive reporting process and a more strategic research agenda to enable generalisable evidence to accumulate. PMID:24798264

Identifying Core Mobile Learning Faculty Competencies Based Integrated Approach: A Delphi Study

ERIC Educational Resources Information Center

Elbarbary, Rafik Said

2015-01-01

This study is based on the integrated approach as a concept framework to identify, categorize, and rank a key component of mobile learning core competencies for Egyptian faculty members in higher education. The field investigation framework used four rounds Delphi technique to determine the importance rate of each component of core competencies…

A general model-based design of experiments approach to achieve practical identifiability of pharmacokinetic and pharmacodynamic models.

PubMed

Galvanin, Federico; Ballan, Carlo C; Barolo, Massimiliano; Bezzo, Fabrizio

2013-08-01

The use of pharmacokinetic (PK) and pharmacodynamic (PD) models is a common and widespread practice in the preliminary stages of drug development. However, PK-PD models may be affected by structural identifiability issues intrinsically related to their mathematical formulation. A preliminary structural identifiability analysis is usually carried out to check if the set of model parameters can be uniquely determined from experimental observations under the ideal assumptions of noise-free data and no model uncertainty. However, even for structurally identifiable models, real-life experimental conditions and model uncertainty may strongly affect the practical possibility to estimate the model parameters in a statistically sound way. A systematic procedure coupling the numerical assessment of structural identifiability with advanced model-based design of experiments formulations is presented in this paper. The objective is to propose a general approach to design experiments in an optimal way, detecting a proper set of experimental settings that ensure the practical identifiability of PK-PD models. Two simulated case studies based on in vitro bacterial growth and killing models are presented to demonstrate the applicability and generality of the methodology to tackle model identifiability issues effectively, through the design of feasible and highly informative experiments.

Identifying and characterizing hepatitis C virus hotspots in Massachusetts: a spatial epidemiological approach.

PubMed

Stopka, Thomas J; Goulart, Michael A; Meyers, David J; Hutcheson, Marga; Barton, Kerri; Onofrey, Shauna; Church, Daniel; Donahue, Ashley; Chui, Kenneth K H

2017-04-20

Hepatitis C virus (HCV) infections have increased during the past decade but little is known about geographic clustering patterns. We used a unique analytical approach, combining geographic information systems (GIS), spatial epidemiology, and statistical modeling to identify and characterize HCV hotspots, statistically significant clusters of census tracts with elevated HCV counts and rates. We compiled sociodemographic and HCV surveillance data (n = 99,780 cases) for Massachusetts census tracts (n = 1464) from 2002 to 2013. We used a five-step spatial epidemiological approach, calculating incremental spatial autocorrelations and Getis-Ord Gi* statistics to identify clusters. We conducted logistic regression analyses to determine factors associated with the HCV hotspots. We identified nine HCV clusters, with the largest in Boston, New Bedford/Fall River, Worcester, and Springfield (p < 0.05). In multivariable analyses, we found that HCV hotspots were independently and positively associated with the percent of the population that was Hispanic (adjusted odds ratio [AOR]: 1.07; 95% confidence interval [CI]: 1.04, 1.09) and the percent of households receiving food stamps (AOR: 1.83; 95% CI: 1.22, 2.74). HCV hotspots were independently and negatively associated with the percent of the population that were high school graduates or higher (AOR: 0.91; 95% CI: 0.89, 0.93) and the percent of the population in the "other" race/ethnicity category (AOR: 0.88; 95% CI: 0.85, 0.91). We identified locations where HCV clusters were a concern, and where enhanced HCV prevention, treatment, and care can help combat the HCV epidemic in Massachusetts. GIS, spatial epidemiological and statistical analyses provided a rigorous approach to identify hotspot clusters of disease, which can inform public health policy and intervention targeting. Further studies that incorporate spatiotemporal cluster analyses, Bayesian spatial and geostatistical models, spatially weighted regression

Identifying western yellow-billed cuckoo breeding habitat with a dual modelling approach

USGS Publications Warehouse

Johnson, Matthew J.; Hatten, James R.; Holmes, Jennifer A.; Shafroth, Patrick B.

2017-01-01

The western population of the yellow-billed cuckoo (Coccyzus americanus) was recently listed as threatened under the federal Endangered Species Act. Yellow-billed cuckoo conservation efforts require the identification of features and area requirements associated with high quality, riparian forest habitat at spatial scales that range from nest microhabitat to landscape, as well as lower-suitability areas that can be enhanced or restored. Spatially explicit models inform conservation efforts by increasing ecological understanding of a target species, especially at landscape scales. Previous yellow-billed cuckoo modelling efforts derived plant-community maps from aerial photography, an expensive and oftentimes inconsistent approach. Satellite models can remotely map vegetation features (e.g., vegetation density, heterogeneity in vegetation density or structure) across large areas with near perfect repeatability, but they usually cannot identify plant communities. We used aerial photos and satellite imagery, and a hierarchical spatial scale approach, to identify yellow-billed cuckoo breeding habitat along the Lower Colorado River and its tributaries. Aerial-photo and satellite models identified several key features associated with yellow-billed cuckoo breeding locations: (1) a 4.5 ha core area of dense cottonwood-willow vegetation, (2) a large native, heterogeneously dense forest (72 ha) around the core area, and (3) moderately rough topography. The odds of yellow-billed cuckoo occurrence decreased rapidly as the amount of tamarisk cover increased or when cottonwood-willow vegetation was limited. We achieved model accuracies of 75–80% in the project area the following year after updating the imagery and location data. The two model types had very similar probability maps, largely predicting the same areas as high quality habitat. While each model provided unique information, a dual-modelling approach provided a more complete picture of yellow-billed cuckoo habitat

A New Approach to Identifying the Drivers of Regulation Compliance Using Multivariate Behavioural Models

PubMed Central

Thomas, Alyssa S.; Milfont, Taciano L.; Gavin, Michael C.

2016-01-01

Non-compliance with fishing regulations can undermine management effectiveness. Previous bivariate approaches were unable to untangle the complex mix of factors that may influence fishers’ compliance decisions, including enforcement, moral norms, perceived legitimacy of regulations and the behaviour of others. We compared seven multivariate behavioural models of fisher compliance decisions using structural equation modeling. An online survey of over 300 recreational fishers tested the ability of each model to best predict their compliance with two fishing regulations (daily and size limits). The best fitting model for both regulations was composed solely of psycho-social factors, with social norms having the greatest influence on fishers’ compliance behaviour. Fishers’ attitude also directly affected compliance with size limit, but to a lesser extent. On the basis of these findings, we suggest behavioural interventions to target social norms instead of increasing enforcement for the focal regulations in the recreational blue cod fishery in the Marlborough Sounds, New Zealand. These interventions could include articles in local newspapers and fishing magazines highlighting the extent of regulation compliance as well as using respected local fishers to emphasize the benefits of compliance through public meetings or letters to the editor. Our methodological approach can be broadly applied by natural resource managers as an effective tool to identify drivers of compliance that can then guide the design of interventions to decrease illegal resource use. PMID:27727292

A tripartite approach identifies the major sunflower seed albumins.

PubMed

Jayasena, Achala S; Franke, Bastian; Rosengren, Johan; Mylne, Joshua S

2016-03-01

We have used a combination of genomic, transcriptomic, and proteomic approaches to identify the napin-type albumin genes in sunflower and define their contributions to the seed albumin pool. Seed protein content is determined by the expression of what are typically large gene families. A major class of seed storage proteins is the napin-type, water soluble albumins. In this work we provide a comprehensive analysis of the napin-type albumin content of the common sunflower (Helianthus annuus) by analyzing a draft genome, a transcriptome and performing a proteomic analysis of the seed albumin fraction. We show that although sunflower contains at least 26 genes for napin-type albumins, only 15 of these are present at the mRNA level. We found protein evidence for 11 of these but the albumin content of mature seeds is dominated by the encoded products of just three genes. So despite high genetic redundancy for albumins, only a small sub-set of this gene family contributes to total seed albumin content. The three genes identified as producing the majority of sunflower seed albumin are potential future candidates for manipulation through genetics and breeding.

A multi-indicator approach for identifying shoreline sewage pollution hotspots adjacent to coral reefs.

PubMed

Abaya, Leilani M; Wiegner, Tracy N; Colbert, Steven L; Beets, James P; Carlson, Kaile'a M; Kramer, K Lindsey; Most, Rebecca; Couch, Courtney S

2018-04-01

Sewage pollution is contributing to the global decline of coral reefs. Identifying locations where it is entering waters near reefs is therefore a management priority. Our study documented shoreline sewage pollution hotspots in a coastal community with a fringing coral reef (Puakō, Hawai'i) using dye tracer studies, sewage indicator measurements, and a pollution scoring tool. Sewage reached shoreline waters within 9 h to 3 d. Fecal indicator bacteria concentrations were high and variable, and δ 15 N macroalgal values were indicative of sewage at many stations. Shoreline nutrient concentrations were two times higher than those in upland groundwater. Pollution hotspots were identified with a scoring tool using three sewage indicators. It confirmed known locations of sewage pollution from dye tracer studies. Our study highlights the need for a multi-indicator approach and scoring tool to identify sewage pollution hotspots. This approach will be useful for other coastal communities grappling with sewage pollution. Copyright © 2018 Elsevier Ltd. All rights reserved.

Data Reduction Approaches for Dissecting Transcriptional Effects on Metabolism

PubMed Central

Schwahn, Kevin; Nikoloski, Zoran

2018-01-01

The availability of high-throughput data from transcriptomics and metabolomics technologies provides the opportunity to characterize the transcriptional effects on metabolism. Here we propose and evaluate two computational approaches rooted in data reduction techniques to identify and categorize transcriptional effects on metabolism by combining data on gene expression and metabolite levels. The approaches determine the partial correlation between two metabolite data profiles upon control of given principal components extracted from transcriptomics data profiles. Therefore, they allow us to investigate both data types with all features simultaneously without doing preselection of genes. The proposed approaches allow us to categorize the relation between pairs of metabolites as being under transcriptional or post-transcriptional regulation. The resulting classification is compared to existing literature and accumulated evidence about regulatory mechanism of reactions and pathways in the cases of Escherichia coli, Saccharomycies cerevisiae, and Arabidopsis thaliana. PMID:29731765

Identifying Subgroups among Hardcore Smokers: a Latent Profile Approach

PubMed Central

Bommelé, Jeroen; Kleinjan, Marloes; Schoenmakers, Tim M.; Burk, William J.; van den Eijnden, Regina; van de Mheen, Dike

2015-01-01

Introduction Hardcore smokers are smokers who have little to no intention to quit. Previous research suggests that there are distinct subgroups among hardcore smokers and that these subgroups vary in the perceived pros and cons of smoking and quitting. Identifying these subgroups could help to develop individualized messages for the group of hardcore smokers. In this study we therefore used the perceived pros and cons of smoking and quitting to identify profiles among hardcore smokers. Methods A sample of 510 hardcore smokers completed an online survey on the perceived pros and cons of smoking and quitting. We used these perceived pros and cons in a latent profile analysis to identify possible subgroups among hardcore smokers. To validate the profiles identified among hardcore smokers, we analysed data from a sample of 338 non-hardcore smokers in a similar way. Results We found three profiles among hardcore smokers. ‘Receptive’ hardcore smokers (36%) perceived many cons of smoking and many pros of quitting. ‘Ambivalent’ hardcore smokers (59%) were rather undecided towards quitting. ‘Resistant’ hardcore smokers (5%) saw few cons of smoking and few pros of quitting. Among non-hardcore smokers, we found similar groups of ‘receptive’ smokers (30%) and ‘ambivalent’ smokers (54%). However, a third group consisted of ‘disengaged’ smokers (16%), who saw few pros and cons of both smoking and quitting. Discussion Among hardcore smokers, we found three distinct profiles based on perceived pros and cons of smoking. This indicates that hardcore smokers are not a homogenous group. Each profile might require a different tobacco control approach. Our findings may help to develop individualized tobacco control messages for the particularly hard-to-reach group of hardcore smokers. PMID:26207829

Identifying Mother-Child Interaction Styles Using a Person-Centered Approach

PubMed Central

Nelson, Jackie A.; O’Brien, Marion; Grimm, Kevin J.; Leerkes, Esther M.

2016-01-01

Parent-child conflict in the context of a supportive relationship has been discussed as a potentially constructive interaction pattern; the current study is the first to test this using a holistic analytic approach. Interaction styles, defined as mother-child conflict in the context of maternal sensitivity, were identified and described with demographic and stress-related characteristics of families. Longitudinal associations were tested between interaction styles and children’s later social competence. Participants included 814 partnered mothers with a first-grade child. Latent profile analysis identified agreeable, dynamic, and disconnected interaction styles. Mothers’ intimacy with a partner, depressive symptoms, and authoritarian childrearing beliefs, along with children’s later conflict with a best friend and externalizing problems, were associated with group membership. Notably, the dynamic style, characterized by high sensitivity and high conflict, included families who experienced psychological and relational stressors. Findings are discussed with regard to how family stressors shape parent-child interaction patterns. PMID:28751818

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

PubMed

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

2015-06-01

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

Identifying and Characterizing the Effects of Nutrition on Hippocampal Memory123

PubMed Central

Monti, Jim M.; Baym, Carol L.; Cohen, Neal J.

2014-01-01

In this review we provide evidence linking relational memory to the hippocampus, as well as examples of sensitive relational memory tasks that may help characterize the subtle effects of nutrition on learning and memory. Research into dietary effects on cognition is in its nascent stages, and many studies have cast a wide net with respect to areas of cognition to investigate. However, it may be that nutrition will have a disproportionate effect on particular cognitive domains. Thus, researchers interested in nutrition-cognition interactions may wish to apply a more targeted approach when selecting cognitive domains. We suggest that hippocampus-based relational memory may be extraordinarily sensitive to the effects of nutrition. The hippocampus shows unique plastic capabilities, making its structure and function responsive to an array of lifestyle factors and environmental conditions, including dietary intake. A major function of the hippocampus is relational memory, defined as learning and memory for the constituent elements and facts that comprise events. Here we identify several sensitive tests of relational memory that may be used to examine what may be subtle effects of nutrition on hippocampus and memory. We then turn to the literature on aerobic exercise and cognition to provide examples of translational research programs that have successfully applied this targeted approach centering on the hippocampus and sensitive relational memory tools. Finally, we discuss selected findings from animal and human research on nutrition and the hippocampus and advocate for the role of relational memory tasks in future research. PMID:24829486

A large shRNA library approach identifies lncRNA Ntep as an essential regulator of cell proliferation

PubMed Central

Beermann, Julia; Kirste, Dominique; Iwanov, Katharina; Lu, Dongchao; Kleemiß, Felix; Kumarswamy, Regalla; Schimmel, Katharina; Bär, Christian; Thum, Thomas

2018-01-01

The mammalian cell cycle is a complex and tightly controlled event. Myriads of different control mechanisms are involved in its regulation. Long non-coding RNAs (lncRNA) have emerged as important regulators of many cellular processes including cellular proliferation. However, a more global and unbiased approach to identify lncRNAs with importance for cell proliferation is missing. Here, we present a lentiviral shRNA library-based approach for functional lncRNA profiling. We validated our library approach in NIH3T3 (3T3) fibroblasts by identifying lncRNAs critically involved in cell proliferation. Using stringent selection criteria we identified lncRNA NR_015491.1 out of 3842 different RNA targets represented in our library. We termed this transcript Ntep (non-coding transcript essential for proliferation), as a bona fide lncRNA essential for cell cycle progression. Inhibition of Ntep in 3T3 and primary fibroblasts prevented normal cell growth and expression of key fibroblast markers. Mechanistically, we discovered that Ntep is important to activate P53 concomitant with increased apoptosis and cell cycle blockade in late G2/M. Our findings suggest Ntep to serve as an important regulator of fibroblast proliferation and function. In summary, our study demonstrates the applicability of an innovative shRNA library approach to identify long non-coding RNA functions in a massive parallel approach. PMID:29099486

Coalitional game theory as a promising approach to identify candidate autism genes.

PubMed

Gupta, Anika; Sun, Min Woo; Paskov, Kelley Marie; Stockham, Nate Tyler; Jung, Jae-Yoon; Wall, Dennis Paul

2018-01-01

Despite mounting evidence for the strong role of genetics in the phenotypic manifestation of Autism Spectrum Disorder (ASD), the specific genes responsible for the variable forms of ASD remain undefined. ASD may be best explained by a combinatorial genetic model with varying epistatic interactions across many small effect mutations. Coalitional or cooperative game theory is a technique that studies the combined effects of groups of players, known as coalitions, seeking to identify players who tend to improve the performance--the relationship to a specific disease phenotype--of any coalition they join. This method has been previously shown to boost biologically informative signal in gene expression data but to-date has not been applied to the search for cooperative mutations among putative ASD genes. We describe our approach to highlight genes relevant to ASD using coalitional game theory on alteration data of 1,965 fully sequenced genomes from 756 multiplex families. Alterations were encoded into binary matrices for ASD (case) and unaffected (control) samples, indicating likely gene-disrupting, inherited mutations in altered genes. To determine individual gene contributions given an ASD phenotype, a "player" metric, referred to as the Shapley value, was calculated for each gene in the case and control cohorts. Sixty seven genes were found to have significantly elevated player scores and likely represent significant contributors to the genetic coordination underlying ASD. Using network and cross-study analysis, we found that these genes are involved in biological pathways known to be affected in the autism cases and that a subset directly interact with several genes known to have strong associations to autism. These findings suggest that coalitional game theory can be applied to large-scale genomic data to identify hidden yet influential players in complex polygenic disorders such as autism.

MADGiC: a model-based approach for identifying driver genes in cancer

PubMed Central

Korthauer, Keegan D.; Kendziorski, Christina

2015-01-01

Motivation: Identifying and prioritizing somatic mutations is an important and challenging area of cancer research that can provide new insights into gene function as well as new targets for drug development. Most methods for prioritizing mutations rely primarily on frequency-based criteria, where a gene is identified as having a driver mutation if it is altered in significantly more samples than expected according to a background model. Although useful, frequency-based methods are limited in that all mutations are treated equally. It is well known, however, that some mutations have no functional consequence, while others may have a major deleterious impact. The spatial pattern of mutations within a gene provides further insight into their functional consequence. Properly accounting for these factors improves both the power and accuracy of inference. Also important is an accurate background model. Results: Here, we develop a Model-based Approach for identifying Driver Genes in Cancer (termed MADGiC) that incorporates both frequency and functional impact criteria and accommodates a number of factors to improve the background model. Simulation studies demonstrate advantages of the approach, including a substantial increase in power over competing methods. Further advantages are illustrated in an analysis of ovarian and lung cancer data from The Cancer Genome Atlas (TCGA) project. Availability and implementation: R code to implement this method is available at http://www.biostat.wisc.edu/ kendzior/MADGiC/. Contact: kendzior@biostat.wisc.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25573922

New approach for identifying the zero-order fringe in variable wavelength interferometry

NASA Astrophysics Data System (ADS)

Galas, Jacek; Litwin, Dariusz; Daszkiewicz, Marek

2016-12-01

The family of VAWI techniques (for transmitted and reflected light) is especially efficient for characterizing objects, when in the interference system the optical path difference exceeds a few wavelengths. The classical approach that consists in measuring the deflection of interference fringes fails because of strong edge effects. Broken continuity of interference fringes prevents from correct identification of the zero order fringe, which leads to significant errors. The family of these methods has been proposed originally by Professor Pluta in the 1980s but that time image processing facilities and computers were hardly available. Automated devices unfold a completely new approach to the classical measurement procedures. The Institute team has taken that new opportunity and transformed the technique into fully automated measurement devices offering commercial readiness of industry-grade quality. The method itself has been modified and new solutions and algorithms simultaneously have extended the field of application. This has concerned both construction aspects of the systems and software development in context of creating computerized instruments. The VAWI collection of instruments constitutes now the core of the Institute commercial offer. It is now practically applicable in industrial environment for measuring textile and optical fibers, strips of thin films, testing of wave plates and nonlinear affects in different materials. This paper describes new algorithms for identifying the zero order fringe, which increases the performance of the system as a whole and presents some examples of measurements of optical elements.

An Integrated Human/Murine Transcriptome and Pathway Approach To Identify Prenatal Treatments For Down Syndrome.

PubMed

Guedj, Faycal; Pennings, Jeroen LA; Massingham, Lauren J; Wick, Heather C; Siegel, Ashley E; Tantravahi, Umadevi; Bianchi, Diana W

2016-09-02

Anatomical and functional brain abnormalities begin during fetal life in Down syndrome (DS). We hypothesize that novel prenatal treatments can be identified by targeting signaling pathways that are consistently perturbed in cell types/tissues obtained from human fetuses with DS and mouse embryos. We analyzed transcriptome data from fetuses with trisomy 21, age and sex-matched euploid controls, and embryonic day 15.5 forebrains from Ts1Cje, Ts65Dn, and Dp16 mice. The new datasets were compared to other publicly available datasets from humans with DS. We used the human Connectivity Map (CMap) database and created a murine adaptation to identify FDA-approved drugs that can rescue affected pathways. USP16 and TTC3 were dysregulated in all affected human cells and two mouse models. DS-associated pathway abnormalities were either the result of gene dosage specific effects or the consequence of a global cell stress response with activation of compensatory mechanisms. CMap analyses identified 56 molecules with high predictive scores to rescue abnormal gene expression in both species. Our novel integrated human/murine systems biology approach identified commonly dysregulated genes and pathways. This can help to prioritize therapeutic molecules on which to further test safety and efficacy. Additional studies in human cells are ongoing prior to pre-clinical prenatal treatment in mice.

An innovative and integrated approach based on DNA walking to identify unauthorised GMOs.

PubMed

Fraiture, Marie-Alice; Herman, Philippe; Taverniers, Isabel; De Loose, Marc; Deforce, Dieter; Roosens, Nancy H

2014-03-15

In the coming years, the frequency of unauthorised genetically modified organisms (GMOs) being present in the European food and feed chain will increase significantly. Therefore, we have developed a strategy to identify unauthorised GMOs containing a pCAMBIA family vector, frequently present in transgenic plants. This integrated approach is performed in two successive steps on Bt rice grains. First, the potential presence of unauthorised GMOs is assessed by the qPCR SYBR®Green technology targeting the terminator 35S pCAMBIA element. Second, its presence is confirmed via the characterisation of the junction between the transgenic cassette and the rice genome. To this end, a DNA walking strategy is applied using a first reverse primer followed by two semi-nested PCR rounds using primers that are each time nested to the previous reverse primer. This approach allows to rapidly identify the transgene flanking region and can easily be implemented by the enforcement laboratories. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

Identifying Variability in Permanent Supportive Housing: A comparative effectiveness approach to measuring health outcomes

PubMed Central

Dickson-Gomez, Julia; Quinn, Katherine; Bendixen, Arturo; Johnson, Amy; Nowicki, Kelly; Ko, Thant Ko; Galletly, Carol

2017-01-01

Supportive housing has become the dominant model in the United States to provide housing to chronically homeless and to improve their housing stability and health. Most supportive housing programs follow a “housing first” paradigm modeled after the Pathways to Housing program in New York City. However, components of housing first supportive housing models were poorly defined and supportive models have varied considerably in their dissemination and implementation to other parts of the country. Recently, research has been conducted to determine the fidelity by which specific housing programs adhere to the Pathways Housing First model. However, evidence regarding which combination of components leads to better health outcomes for particular subpopulations is lacking. This paper presents results from qualitative interviews with supportive housing providers in the Chicago Metropolitan area. Supportive housing varied according to housing configuration (scattered-site versus project-based) and service provision model (low-intensity case management, intensive case management and behavioral health) resulting in six basic types. Supportive housing programs also differed in services they provided in addition to case management and the extent to which they followed harm reduction versus abstinence policies. Results showed advantages and disadvantages to each of the six basic types. Comparative effectiveness research may help identify which program components lead to better health outcomes among different subpopulations of homeless. Future longitudinal research will use the identified typology and other factors to compare the housing stability and health outcomes of supportive housing residents in programs that differ along these dimensions. PMID:28301175

Identifying key performance indicators for nursing and midwifery care using a consensus approach.

PubMed

McCance, Tanya; Telford, Lorna; Wilson, Julie; Macleod, Olive; Dowd, Audrey

2012-04-01

The aim of this study was to gain consensus on key performance indicators that are appropriate and relevant for nursing and midwifery practice in the current policy context. There is continuing demand to demonstrate effectiveness and efficiency in health and social care and to communicate this at boardroom level. Whilst there is substantial literature on the use of clinical indicators and nursing metrics, there is less evidence relating to indicators that reflect the patient experience. A consensus approach was used to identify relevant key performance indicators. A nominal group technique was used comprising two stages: a workshop involving all grades of nursing and midwifery staff in two HSC trusts in Northern Ireland (n = 50); followed by a regional Consensus Conference (n = 80). During the workshop, potential key performance indicators were identified. This was used as the basis for the Consensus Conference, which involved two rounds of consensus. Analysis was based on aggregated scores that were then ranked. Stage one identified 38 potential indicators and stage two prioritised the eight top-ranked indicators as a core set for nursing and midwifery. The relevance and appropriateness of these indicators were confirmed with nurses and midwives working in a range of settings and from the perspective of service users. The eight indicators identified do not conform to the majority of other nursing metrics generally reported in the literature. Furthermore, they are strategically aligned to work on the patient experience and are reflective of the fundamentals of nursing and midwifery practice, with the focus on person-centred care. Nurses and midwives have a significant contribution to make in determining the extent to which these indicators are achieved in practice. Furthermore, measurement of such indicators provides an opportunity to evidence of the unique impact of nursing/midwifery care on the patient experience. © 2011 Blackwell Publishing Ltd.

Identifying Effective and Sustainable Measures for Community-Based Environmental Monitoring

NASA Astrophysics Data System (ADS)

McKay, Ariana J.; Johnson, Chris J.

2017-09-01

Resource development projects typically result in monitoring programs that fail to fully consider the values and participation of surrounding communities. Also, monitoring protocols for single environmental values can be insufficient for addressing the cumulative impacts of resource development. Community-based environmental monitoring (CBEM) has emerged as a way to meaningfully include local citizens in the decision-making process and assessment of the development of natural resources. Our research explored how to develop effective and sustainable CBEM. Interviews were conducted with staff from 15 CBEM programs established across Canada to identify criteria of what constitutes effective CBEM. Results demonstrate that CBEM offers an effective, locally adapted, and culturally applicable approach to facilitate community participation in natural resource management and to track environmental change. Benefits of CBEM include: locally relevant monitoring protocols, inclusion of cumulative impacts, better informed decision-making, and increased awareness and collaboration amongst community, governments, and proponents. Challenges associated with CBEM are cost, capacity, longevity, distribution of results, and establishing credibility. This research validates the use of CBEM for improving resource management.

A decision-theoretic approach to identifying future high-cost patients.

PubMed

Pietz, Kenneth; Byrne, Margaret M; Petersen, Laura A

2006-09-01

The objective of this study was to develop and evaluate a method of allocating funding for very-high-cost (VHC) patients among hospitals. Diagnostic cost groups (DCGs) were used for risk adjustment. The patient population consisted of 253,013 veterans who used Department of Veterans Affairs (VA) medical care services in fiscal year (FY) 2003 (October 1, 2002-September 30, 2003) in a network of 8 VA hospitals. We defined VHC as greater than 75,000 dollars (0.81%). The upper fifth percentile was also used for comparison. A Bayesian decision rule for classifying patients as VHC/not VHC using DCGs was developed and evaluated. The method uses FY 2003 DCGs to allocate VHC funds for FY 2004. We also used FY 2002 DCGs to allocate VHC funds for FY 2003 for comparison. The resulting allocation was compared with using the allocation of VHC patients among the hospitals in the previous year. The decision rule identified DCG 17 as the optimal cutoff for identifying VHC patients for the next year. The previous year's allocation came closest to the actual distribution of VHC patients. The decision-theoretic approach may provide insight into the economic consequences of classifying a patient as VHC or not VHC. More research is needed into methods of identifying future VHC patients so that capitation plans can fairly reimburse healthcare systems for appropriately treating these patients.

Network-based approach to identify prognostic biomarkers for estrogen receptor-positive breast cancer treatment with tamoxifen.

PubMed

Liu, Rong; Guo, Cheng-Xian; Zhou, Hong-Hao

2015-01-01

This study aims to identify effective gene networks and prognostic biomarkers associated with estrogen receptor positive (ER+) breast cancer using human mRNA studies. Weighted gene coexpression network analysis was performed with a complex ER+ breast cancer transcriptome to investigate the function of networks and key genes in the prognosis of breast cancer. We found a significant correlation of an expression module with distant metastasis-free survival (HR = 2.25; 95% CI .21.03-4.88 in discovery set; HR = 1.78; 95% CI = 1.07-2.93 in validation set). This module contained genes enriched in the biological process of the M phase. From this module, we further identified and validated 5 hub genes (CDK1, DLGAP5, MELK, NUSAP1, and RRM2), the expression levels of which were strongly associated with poor survival. Highly expressed MELK indicated poor survival in luminal A and luminal B breast cancer molecular subtypes. This gene was also found to be associated with tamoxifen resistance. Results indicated that a network-based approach may facilitate the discovery of biomarkers for the prognosis of ER+ breast cancer and may also be used as a basis for establishing personalized therapies. Nevertheless, before the application of this approach in clinical settings, in vivo and in vitro experiments and multi-center randomized controlled clinical trials are still needed.

Identifying and assessing the application of ecosystem services approaches in environmental policies and decision making.

PubMed

Van Wensem, Joke; Calow, Peter; Dollacker, Annik; Maltby, Lorraine; Olander, Lydia; Tuvendal, Magnus; Van Houtven, George

2017-01-01

The presumption is that ecosystem services (ES) approaches provide a better basis for environmental decision making than do other approaches because they make explicit the connection between human well-being and ecosystem structures and processes. However, the existing literature does not provide a precise description of ES approaches for environmental policy and decision making, nor does it assess whether these applications will make a difference in terms of changing decisions and improving outcomes. We describe 3 criteria that can be used to identify whether and to what extent ES approaches are being applied: 1) connect impacts all the way from ecosystem changes to human well-being, 2) consider all relevant ES affected by the decision, and 3) consider and compare the changes in well-being of different stakeholders. As a demonstration, we then analyze retrospectively whether and how the criteria were met in different decision-making contexts. For this assessment, we have developed an analysis format that describes the type of policy, the relevant scales, the decisions or questions, the decision maker, and the underlying documents. This format includes a general judgment of how far the 3 ES criteria have been applied. It shows that the criteria can be applied to many different decision-making processes, ranging from the supranational to the local scale and to different parts of decision-making processes. In conclusion we suggest these criteria could be used for assessments of the extent to which ES approaches have been and should be applied, what benefits and challenges arise, and whether using ES approaches made a difference in the decision-making process, decisions made, or outcomes of those decisions. Results from such studies could inform future use and development of ES approaches, draw attention to where the greatest benefits and challenges are, and help to target integration of ES approaches into policies, where they can be most effective. Integr Environ

Novel approach identifies SNPs in SLC2A10 and KCNK9 with evidence for parent-of-origin effect on body mass index.

PubMed

Hoggart, Clive J; Venturini, Giulia; Mangino, Massimo; Gomez, Felicia; Ascari, Giulia; Zhao, Jing Hua; Teumer, Alexander; Winkler, Thomas W; Tšernikova, Natalia; Luan, Jian'an; Mihailov, Evelin; Ehret, Georg B; Zhang, Weihua; Lamparter, David; Esko, Tõnu; Macé, Aurelien; Rüeger, Sina; Bochud, Pierre-Yves; Barcella, Matteo; Dauvilliers, Yves; Benyamin, Beben; Evans, David M; Hayward, Caroline; Lopez, Mary F; Franke, Lude; Russo, Alessia; Heid, Iris M; Salvi, Erika; Vendantam, Sailaja; Arking, Dan E; Boerwinkle, Eric; Chambers, John C; Fiorito, Giovanni; Grallert, Harald; Guarrera, Simonetta; Homuth, Georg; Huffman, Jennifer E; Porteous, David; Moradpour, Darius; Iranzo, Alex; Hebebrand, Johannes; Kemp, John P; Lammers, Gert J; Aubert, Vincent; Heim, Markus H; Martin, Nicholas G; Montgomery, Grant W; Peraita-Adrados, Rosa; Santamaria, Joan; Negro, Francesco; Schmidt, Carsten O; Scott, Robert A; Spector, Tim D; Strauch, Konstantin; Völzke, Henry; Wareham, Nicholas J; Yuan, Wei; Bell, Jordana T; Chakravarti, Aravinda; Kooner, Jaspal S; Peters, Annette; Matullo, Giuseppe; Wallaschofski, Henri; Whitfield, John B; Paccaud, Fred; Vollenweider, Peter; Bergmann, Sven; Beckmann, Jacques S; Tafti, Mehdi; Hastie, Nicholas D; Cusi, Daniele; Bochud, Murielle; Frayling, Timothy M; Metspalu, Andres; Jarvelin, Marjo-Riitta; Scherag, André; Smith, George Davey; Borecki, Ingrid B; Rousson, Valentin; Hirschhorn, Joel N; Rivolta, Carlo; Loos, Ruth J F; Kutalik, Zoltán

2014-07-01

The phenotypic effect of some single nucleotide polymorphisms (SNPs) depends on their parental origin. We present a novel approach to detect parent-of-origin effects (POEs) in genome-wide genotype data of unrelated individuals. The method exploits increased phenotypic variance in the heterozygous genotype group relative to the homozygous groups. We applied the method to >56,000 unrelated individuals to search for POEs influencing body mass index (BMI). Six lead SNPs were carried forward for replication in five family-based studies (of ∼4,000 trios). Two SNPs replicated: the paternal rs2471083-C allele (located near the imprinted KCNK9 gene) and the paternal rs3091869-T allele (located near the SLC2A10 gene) increased BMI equally (beta = 0.11 (SD), P<0.0027) compared to the respective maternal alleles. Real-time PCR experiments of lymphoblastoid cell lines from the CEPH families showed that expression of both genes was dependent on parental origin of the SNPs alleles (P<0.01). Our scheme opens new opportunities to exploit GWAS data of unrelated individuals to identify POEs and demonstrates that they play an important role in adult obesity.

Novel Approach Identifies SNPs in SLC2A10 and KCNK9 with Evidence for Parent-of-Origin Effect on Body Mass Index

PubMed Central

Hoggart, Clive J.; Venturini, Giulia; Mangino, Massimo; Gomez, Felicia; Ascari, Giulia; Zhao, Jing Hua; Teumer, Alexander; Winkler, Thomas W.; Tšernikova, Natalia; Luan, Jian'an; Mihailov, Evelin; Ehret, Georg B.; Zhang, Weihua; Lamparter, David; Esko, Tõnu; Macé, Aurelien; Rüeger, Sina; Bochud, Pierre-Yves; Barcella, Matteo; Dauvilliers, Yves; Benyamin, Beben; Evans, David M.; Hayward, Caroline; Lopez, Mary F.; Franke, Lude; Russo, Alessia; Heid, Iris M.; Salvi, Erika; Vendantam, Sailaja; Arking, Dan E.; Boerwinkle, Eric; Chambers, John C.; Fiorito, Giovanni; Grallert, Harald; Guarrera, Simonetta; Homuth, Georg; Huffman, Jennifer E.; Porteous, David; Moradpour, Darius; Iranzo, Alex; Hebebrand, Johannes; Kemp, John P.; Lammers, Gert J.; Aubert, Vincent; Heim, Markus H.; Martin, Nicholas G.; Montgomery, Grant W.; Peraita-Adrados, Rosa; Santamaria, Joan; Negro, Francesco; Schmidt, Carsten O.; Scott, Robert A.; Spector, Tim D.; Strauch, Konstantin; Völzke, Henry; Wareham, Nicholas J.; Yuan, Wei; Bell, Jordana T.; Chakravarti, Aravinda; Kooner, Jaspal S.; Peters, Annette; Matullo, Giuseppe; Wallaschofski, Henri; Whitfield, John B.; Paccaud, Fred; Vollenweider, Peter; Bergmann, Sven; Beckmann, Jacques S.; Tafti, Mehdi; Hastie, Nicholas D.; Cusi, Daniele; Bochud, Murielle; Frayling, Timothy M.; Metspalu, Andres; Jarvelin, Marjo-Riitta; Scherag, André; Smith, George Davey; Borecki, Ingrid B.; Rousson, Valentin; Hirschhorn, Joel N.; Rivolta, Carlo; Loos, Ruth J. F.; Kutalik, Zoltán

2014-01-01

The phenotypic effect of some single nucleotide polymorphisms (SNPs) depends on their parental origin. We present a novel approach to detect parent-of-origin effects (POEs) in genome-wide genotype data of unrelated individuals. The method exploits increased phenotypic variance in the heterozygous genotype group relative to the homozygous groups. We applied the method to >56,000 unrelated individuals to search for POEs influencing body mass index (BMI). Six lead SNPs were carried forward for replication in five family-based studies (of ∼4,000 trios). Two SNPs replicated: the paternal rs2471083-C allele (located near the imprinted KCNK9 gene) and the paternal rs3091869-T allele (located near the SLC2A10 gene) increased BMI equally (beta = 0.11 (SD), P<0.0027) compared to the respective maternal alleles. Real-time PCR experiments of lymphoblastoid cell lines from the CEPH families showed that expression of both genes was dependent on parental origin of the SNPs alleles (P<0.01). Our scheme opens new opportunities to exploit GWAS data of unrelated individuals to identify POEs and demonstrates that they play an important role in adult obesity. PMID:25078964

A biochemical approach to identifying microRNA targets

PubMed Central

Karginov, Fedor V.; Conaco, Cecilia; Xuan, Zhenyu; Schmidt, Bryan H.; Parker, Joel S.; Mandel, Gail; Hannon, Gregory J.

2007-01-01

Identifying the downstream targets of microRNAs (miRNAs) is essential to understanding cellular regulatory networks. We devised a direct biochemical method for miRNA target discovery that combined RNA-induced silencing complex (RISC) purification with microarray analysis of bound mRNAs. Because targets of miR-124a have been analyzed, we chose it as our model. We honed our approach both by examining the determinants of stable binding between RISC and synthetic target RNAs in vitro and by determining the dependency of both repression and RISC coimmunoprecipitation on miR-124a seed sites in two of its well characterized targets in vivo. Examining the complete spectrum of miR-124 targets in 293 cells yielded both a set that were down-regulated at the mRNA level, as previously observed, and a set whose mRNA levels were unaffected by miR-124a. Reporter assays validated both classes, extending the spectrum of mRNA targets that can be experimentally linked to the miRNA pathway. PMID:18042700

Identifying predictors of physics item difficulty: A linear regression approach

NASA Astrophysics Data System (ADS)

Mesic, Vanes; Muratovic, Hasnija

2011-06-01

Large-scale assessments of student achievement in physics are often approached with an intention to discriminate students based on the attained level of their physics competencies. Therefore, for purposes of test design, it is important that items display an acceptable discriminatory behavior. To that end, it is recommended to avoid extraordinary difficult and very easy items. Knowing the factors that influence physics item difficulty makes it possible to model the item difficulty even before the first pilot study is conducted. Thus, by identifying predictors of physics item difficulty, we can improve the test-design process. Furthermore, we get additional qualitative feedback regarding the basic aspects of student cognitive achievement in physics that are directly responsible for the obtained, quantitative test results. In this study, we conducted a secondary analysis of data that came from two large-scale assessments of student physics achievement at the end of compulsory education in Bosnia and Herzegovina. Foremost, we explored the concept of “physics competence” and performed a content analysis of 123 physics items that were included within the above-mentioned assessments. Thereafter, an item database was created. Items were described by variables which reflect some basic cognitive aspects of physics competence. For each of the assessments, Rasch item difficulties were calculated in separate analyses. In order to make the item difficulties from different assessments comparable, a virtual test equating procedure had to be implemented. Finally, a regression model of physics item difficulty was created. It has been shown that 61.2% of item difficulty variance can be explained by factors which reflect the automaticity, complexity, and modality of the knowledge structure that is relevant for generating the most probable correct solution, as well as by the divergence of required thinking and interference effects between intuitive and formal physics knowledge

Integrative biology approach identifies cytokine targeting strategies for psoriasis.

PubMed

Perera, Gayathri K; Ainali, Chrysanthi; Semenova, Ekaterina; Hundhausen, Christian; Barinaga, Guillermo; Kassen, Deepika; Williams, Andrew E; Mirza, Muddassar M; Balazs, Mercedesz; Wang, Xiaoting; Rodriguez, Robert Sanchez; Alendar, Andrej; Barker, Jonathan; Tsoka, Sophia; Ouyang, Wenjun; Nestle, Frank O

2014-02-12

Cytokines are critical checkpoints of inflammation. The treatment of human autoimmune disease has been revolutionized by targeting inflammatory cytokines as key drivers of disease pathogenesis. Despite this, there exist numerous pitfalls when translating preclinical data into the clinic. We developed an integrative biology approach combining human disease transcriptome data sets with clinically relevant in vivo models in an attempt to bridge this translational gap. We chose interleukin-22 (IL-22) as a model cytokine because of its potentially important proinflammatory role in epithelial tissues. Injection of IL-22 into normal human skin grafts produced marked inflammatory skin changes resembling human psoriasis. Injection of anti-IL-22 monoclonal antibody in a human xenotransplant model of psoriasis, developed specifically to test potential therapeutic candidates, efficiently blocked skin inflammation. Bioinformatic analysis integrating both the IL-22 and anti-IL-22 cytokine transcriptomes and mapping them onto a psoriasis disease gene coexpression network identified key cytokine-dependent hub genes. Using knockout mice and small-molecule blockade, we show that one of these hub genes, the so far unexplored serine/threonine kinase PIM1, is a critical checkpoint for human skin inflammation and potential future therapeutic target in psoriasis. Using in silico integration of human data sets and biological models, we were able to identify a new target in the treatment of psoriasis.

The metabolomic approach identifies a biological signature of low-dose chronic exposure to cesium 137.

PubMed

Grison, Stéphane; Martin, Jean-Charles; Grandcolas, Line; Banzet, Nathalie; Blanchardon, Eric; Tourlonias, Elie; Defoort, Catherine; Favé, Gaëlle; Bott, Romain; Dublineau, Isabelle; Gourmelon, Patrick; Souidi, Maâmar

2012-01-01

Reports have described apparent biological effects of (137)Cs (the most persistent dispersed radionuclide) irradiation in people living in Chernobyl-contaminated territory. The sensitive analytical technology described here should now help assess the relation of this contamination to the observed effects. A rat model chronically exposed to (137)Cs through drinking water was developed to identify biomarkers of radiation-induced metabolic disorders, and the biological impact was evaluated by a metabolomic approach that allowed us to detect several hundred metabolites in biofluids and assess their association with disease states. After collection of plasma and urine from contaminated and non-contaminated rats at the end of the 9-months contamination period, analysis with a LC-MS system detected 742 features in urine and 1309 in plasma. Biostatistical discriminant analysis extracted a subset of 26 metabolite signals (2 urinary, 4 plasma non-polar, and 19 plasma polar metabolites) that in combination were able to predict from 68 up to 94% of the contaminated rats, depending on the prediction method used, with a misclassification rate as low as 5.3%. The difference in this metabolic score between the contaminated and non-contaminated rats was highly significant (P = 0.019 after ANOVA cross-validation). In conclusion, our proof-of-principle study demonstrated for the first time the usefulness of a metabolomic approach for addressing biological effects of chronic low-dose contamination. We can conclude that a metabolomic signature discriminated (137)Cs-contaminated from control animals in our model. Further validation is nevertheless required together with full annotation of the metabolic indicators.

Master Logic Diagram: An Approach to Identify Initiating Events of HTGRs

NASA Astrophysics Data System (ADS)

Purba, J. H.

2018-02-01

Initiating events of a nuclear power plant being evaluated need to be firstly identified prior to applying probabilistic safety assessment on that plant. Various types of master logic diagrams (MLDs) have been proposedforsearching initiating events of the next generation of nuclear power plants, which have limited data and operating experiences. Those MLDs are different in the number of steps or levels and different in the basis for developing them. This study proposed another type of MLD approach to find high temperature gas cooled reactor (HTGR) initiating events. It consists of five functional steps starting from the top event representing the final objective of the safety functions to the basic event representing the goal of the MLD development, which is an initiating event. The application of the proposed approach to search for two HTGR initiating events, i.e. power turbine generator trip and loss of offsite power, is provided. The results confirmed that the proposed MLD is feasiblefor finding HTGR initiating events.

Improving accuracy for identifying related PubMed queries by an integrated approach.

PubMed

Lu, Zhiyong; Wilbur, W John

2009-10-01

PubMed is the most widely used tool for searching biomedical literature online. As with many other online search tools, a user often types a series of multiple related queries before retrieving satisfactory results to fulfill a single information need. Meanwhile, it is also a common phenomenon to see a user type queries on unrelated topics in a single session. In order to study PubMed users' search strategies, it is necessary to be able to automatically separate unrelated queries and group together related queries. Here, we report a novel approach combining both lexical and contextual analyses for segmenting PubMed query sessions and identifying related queries and compare its performance with the previous approach based solely on concept mapping. We experimented with our integrated approach on sample data consisting of 1539 pairs of consecutive user queries in 351 user sessions. The prediction results of 1396 pairs agreed with the gold-standard annotations, achieving an overall accuracy of 90.7%. This demonstrates that our approach is significantly better than the previously published method. By applying this approach to a one day query log of PubMed, we found that a significant proportion of information needs involved more than one PubMed query, and that most of the consecutive queries for the same information need are lexically related. Finally, the proposed PubMed distance is shown to be an accurate and meaningful measure for determining the contextual similarity between biological terms. The integrated approach can play a critical role in handling real-world PubMed query log data as is demonstrated in our experiments.

Identifying the Etiology: A Systematic Approach Using Delayed Enhancement Cardiovascular Magnetic Resonance

PubMed Central

Senthilkumar, Annamalai; Majmudar, Maulik D.; Shenoy, Chetan; Kim, Han W.; Kim, Raymond J.

2009-01-01

SYNOPSIS In patients with heart failure, treatment and survival are directly related to the etiology. Clinically, as a practical first step, patients are classified as having either ischemic or nonischemic cardiomyopathy and this delineation is usually based on the presence or absence of epicardial coronary artery disease. However, this approach does not account for patients with nonischemic cardiomyopathy who also have coronary artery disease, which may be either incidental or partly contributing to myocardial dysfunction (mixed cardiomyopathy). By allowing direct assessment of the myocardium, delayed enhancement cardiovascular magnetic resonance (DE-CMR) may aid in addressing these conundrums. In this article we explore how DE-CMR may be helpful in identifying ischemic and nonischemic myopathic processes and detail a systematic approach using this technique to determine the etiology of cardiomyopathy. PMID:19564013

Systems approaches in osteoarthritis: Identifying routes to novel diagnostic and therapeutic strategies

PubMed Central

Mueller, Alan J.; Peffers, Mandy J.; Proctor, Carole J.

2017-01-01

ABSTRACT Systems orientated research offers the possibility of identifying novel therapeutic targets and relevant diagnostic markers for complex diseases such as osteoarthritis. This review demonstrates that the osteoarthritis research community has been slow to incorporate systems orientated approaches into research studies, although a number of key studies reveal novel insights into the regulatory mechanisms that contribute both to joint tissue homeostasis and its dysfunction. The review introduces both top‐down and bottom‐up approaches employed in the study of osteoarthritis. A holistic and multiscale approach, where clinical measurements may predict dysregulation and progression of joint degeneration, should be a key objective in future research. The review concludes with suggestions for further research and emerging trends not least of which is the coupled development of diagnostic tests and therapeutics as part of a concerted effort by the osteoarthritis research community to meet clinical needs. © 2017 The Authors. Journal of Orthopaedic Research Published by Wiley Periodicals, Inc. on behalf of Orthopaedic Research Society. J Orthop Res 35:1573–1588, 2017. PMID:28318047

The Voice of the Patient Methodology: A Novel Mixed-Methods Approach to Identifying Treatment Goals for Men with Prostate Cancer.

PubMed

Saigal, Christopher S; Lambrechts, Sylvia I; Seenu Srinivasan, V; Dahan, Ely

2017-06-01

Many guidelines advocate the use of shared decision making for men with newly diagnosed prostate cancer. Decision aids can facilitate the process of shared decision making. Implicit in this approach is the idea that physicians understand which elements of treatment matter to patients. Little formal work exists to guide physicians or developers of decision aids in identifying these attributes. We use a mixed-methods technique adapted from marketing science, the 'Voice of the Patient', to describe and identify treatment elements of value for men with localized prostate cancer. We conducted semi-structured interviews with 30 men treated for prostate cancer in the urology clinic of the West Los Angeles Veteran Affairs Medical Center. We used a qualitative analysis to generate themes in patient narratives, and a quantitative approach, agglomerative hierarchical clustering, to identify attributes of treatment that were most relevant to patients making decisions about prostate cancer. We identified five 'traditional' prostate cancer treatment attributes: sexual dysfunction, bowel problems, urinary problems, lifespan, and others' opinions. We further identified two novel treatment attributes: a treatment's ability to validate a sense of proactivity and the need for an incision (separate from risks of surgery). Application of a successful marketing technique, the 'Voice of the Customer', in a clinical setting elicits non-obvious attributes that highlight unique patient decision-making concerns. Use of this method in the development of decision aids may result in more effective decision support.

A new approach to hazardous materials transportation risk analysis: decision modeling to identify critical variables.

PubMed

Clark, Renee M; Besterfield-Sacre, Mary E

2009-03-01

We take a novel approach to analyzing hazardous materials transportation risk in this research. Previous studies analyzed this risk from an operations research (OR) or quantitative risk assessment (QRA) perspective by minimizing or calculating risk along a transport route. Further, even though the majority of incidents occur when containers are unloaded, the research has not focused on transportation-related activities, including container loading and unloading. In this work, we developed a decision model of a hazardous materials release during unloading using actual data and an exploratory data modeling approach. Previous studies have had a theoretical perspective in terms of identifying and advancing the key variables related to this risk, and there has not been a focus on probability and statistics-based approaches for doing this. Our decision model empirically identifies the critical variables using an exploratory methodology for a large, highly categorical database involving latent class analysis (LCA), loglinear modeling, and Bayesian networking. Our model identified the most influential variables and countermeasures for two consequences of a hazmat incident, dollar loss and release quantity, and is one of the first models to do this. The most influential variables were found to be related to the failure of the container. In addition to analyzing hazmat risk, our methodology can be used to develop data-driven models for strategic decision making in other domains involving risk.

Understanding identifiability as a crucial step in uncertainty assessment

NASA Astrophysics Data System (ADS)

Jakeman, A. J.; Guillaume, J. H. A.; Hill, M. C.; Seo, L.

2016-12-01

The topic of identifiability analysis offers concepts and approaches to identify why unique model parameter values cannot be identified, and can suggest possible responses that either increase uniqueness or help to understand the effect of non-uniqueness on predictions. Identifiability analysis typically involves evaluation of the model equations and the parameter estimation process. Non-identifiability can have a number of undesirable effects. In terms of model parameters these effects include: parameters not being estimated uniquely even with ideal data; wildly different values being returned for different initialisations of a parameter optimisation algorithm; and parameters not being physically meaningful in a model attempting to represent a process. This presentation illustrates some of the drastic consequences of ignoring model identifiability analysis. It argues for a more cogent framework and use of identifiability analysis as a way of understanding model limitations and systematically learning about sources of uncertainty and their importance. The presentation specifically distinguishes between five sources of parameter non-uniqueness (and hence uncertainty) within the modelling process, pragmatically capturing key distinctions within existing identifiability literature. It enumerates many of the various approaches discussed in the literature. Admittedly, improving identifiability is often non-trivial. It requires thorough understanding of the cause of non-identifiability, and the time, knowledge and resources to collect or select new data, modify model structures or objective functions, or improve conditioning. But ignoring these problems is not a viable solution. Even simple approaches such as fixing parameter values or naively using a different model structure may have significant impacts on results which are too often overlooked because identifiability analysis is neglected.

Identifying potential selective fluorescent probes for cancer-associated protein carbonic anhydrase IX using a computational approach.

PubMed

Kamstra, Rhiannon L; Floriano, Wely B

2014-11-01

Carbonic anhydrase IX (CAIX) is a biomarker for tumor hypoxia. Fluorescent inhibitors of CAIX have been used to study hypoxic tumor cell lines. However, these inhibitor-based fluorescent probes may have a therapeutic effect that is not appropriate for monitoring treatment efficacy. In the search for novel fluorescent probes that are not based on known inhibitors, a database of 20,860 fluorescent compounds was virtually screened against CAIX using hierarchical virtual ligand screening (HierVLS). The screening database contained 14,862 compounds tagged with the ATTO680 fluorophore plus an additional 5998 intrinsically fluorescent compounds. Overall ranking of compounds to identify hit molecular probe candidates utilized a principal component analysis (PCA) approach. Four potential binding sites, including the catalytic site, were identified within the structure of the protein and targeted for virtual screening. Available sequence information for 23 carbonic anhydrase isoforms was used to prioritize the four sites based on the estimated "uniqueness" of each site in CAIX relative to the other isoforms. A database of 32 known inhibitors and 478 decoy compounds was used to validate the methodology. A receiver-operating characteristic (ROC) analysis using the first principal component (PC1) as predictive score for the validation database yielded an area under the curve (AUC) of 0.92. AUC is interpreted as the probability that a binder will have a better score than a non-binder. The use of first component analysis of binding energies for multiple sites is a novel approach for hit selection. The very high prediction power for this approach increases confidence in the outcome from the fluorescent library screening. Ten of the top scoring candidates for isoform-selective putative binding sites are suggested for future testing as fluorescent molecular probe candidates. Copyright © 2014 Elsevier Inc. All rights reserved.

The HepTestContest: a global innovation contest to identify approaches to hepatitis B and C testing.

PubMed

Tucker, Joseph D; Meyers, Kathrine; Best, John; Kaplan, Karyn; Pendse, Razia; Fenton, Kevin A; Andrieux-Meyer, Isabelle; Figueroa, Carmen; Goicochea, Pedro; Gore, Charles; Ishizaki, Azumi; Khwairakpam, Giten; Miller, Veronica; Mozalevskis, Antons; Ninburg, Michael; Ocama, Ponsiano; Peeling, Rosanna; Walsh, Nick; Colombo, Massimo G; Easterbrook, Philippa

2017-11-01

Innovation contests are a novel approach to elicit good ideas and innovative practices in various areas of public health. There remains limited published literature on approaches to deliver hepatitis testing. The purpose of this innovation contest was to identify examples of different hepatitis B and C approaches to support countries in their scale-up of hepatitis testing and to supplement development of formal recommendations on service delivery in the 2017 World Health Organization hepatitis B and C testing guidelines. This contest involved four steps: 1) establishment of a multisectoral steering committee to coordinate a call for contest entries; 2) dissemination of the call for entries through diverse media (Facebook, Twitter, YouTube, email listservs, academic journals); 3) independent ranking of submissions by a panel of judges according to pre-specified criteria (clarity of testing model, innovation, effectiveness, next steps) using a 1-10 scale; 4) recognition of highly ranked entries through presentation at international conferences, commendation certificate, and inclusion as a case study in the WHO 2017 testing guidelines. The innovation contest received 64 entries from 27 countries and took a total of 4 months to complete. Sixteen entries were directly included in the WHO testing guidelines. The entries covered testing in different populations, including primary care patients (n = 5), people who inject drugs (PWID) (n = 4), pregnant women (n = 4), general populations (n = 4), high-risk groups (n = 3), relatives of people living with hepatitis B and C (n = 2), migrants (n = 2), incarcerated individuals (n = 2), workers (n = 2), and emergency department patients (n = 2). A variety of different testing delivery approaches were employed, including integrated HIV-hepatitis testing (n = 12); integrated testing with harm reduction and addiction services (n = 9); use of electronic medical records to support targeted testing (n = 8

A multi-criteria decision making approach to identify a vaccine formulation.

PubMed

Dewé, Walthère; Durand, Christelle; Marion, Sandie; Oostvogels, Lidia; Devaster, Jeanne-Marie; Fourneau, Marc

2016-01-01

This article illustrates the use of a multi-criteria decision making approach, based on desirability functions, to identify an appropriate adjuvant composition for an influenza vaccine to be used in elderly. The proposed adjuvant system contained two main elements: monophosphoryl lipid and α-tocopherol with squalene in an oil/water emulsion. The objective was to elicit a stronger immune response while maintaining an acceptable reactogenicity and safety profile. The study design, the statistical models, the choice of the desirability functions, the computation of the overall desirability index, and the assessment of the robustness of the ranking are all detailed in this manuscript.

Identifying niche-mediated regulatory factors of stem cell phenotypic state: a systems biology approach.

PubMed

Ravichandran, Srikanth; Del Sol, Antonio

2017-02-01

Understanding how the cellular niche controls the stem cell phenotype is often hampered due to the complexity of variegated niche composition, its dynamics, and nonlinear stem cell-niche interactions. Here, we propose a systems biology view that considers stem cell-niche interactions as a many-body problem amenable to simplification by the concept of mean field approximation. This enables approximation of the niche effect on stem cells as a constant field that induces sustained activation/inhibition of specific stem cell signaling pathways in all stem cells within heterogeneous populations exhibiting the same phenotype (niche determinants). This view offers a new basis for the development of single cell-based computational approaches for identifying niche determinants, which has potential applications in regenerative medicine and tissue engineering. © 2017 The Authors. FEBS Letters published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.

Identifying bully victims: definitional versus behavioral approaches.

PubMed

Green, Jennifer Greif; Felix, Erika D; Sharkey, Jill D; Furlong, Michael J; Kras, Jennifer E

2013-06-01

Schools frequently assess bullying and the Olweus Bully/Victimization Questionnaire (BVQ; Olweus, 1996) is the most widely adopted tool for this purpose. The BVQ is a self-report survey that uses a definitional measurement method--describing "bullying" as involving repeated, intentional aggression in a relationship where there is an imbalance of power and then asking respondents to indicate how frequently they experienced this type of victimization. Few studies have examined BVQ validity and whether this definitional method truly identifies the repetition and power differential that distinguish bullying from other forms of peer victimization. This study examined the concurrent validity of the BVQ definitional question among 435 students reporting peer victimization. BVQ definitional responses were compared with responses to a behavioral measure that did not use the term "bullying" but, instead, included items that asked about its defining characteristics (repetition, intentionality, power imbalance). Concordance between the two approaches was moderate, with an area under the receiver operating curve of .72. BVQ responses were more strongly associated with students indicating repeated victimization and multiple forms of victimization, than with power imbalance in their relationship with the bully. Findings indicate that the BVQ is a valid measure of repeated victimization and a broad range of victimization experiences but may not detect the more subtle and complex power imbalances that distinguish bullying from other forms of peer victimization. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Identifying biomarkers for asthma diagnosis using targeted metabolomics approaches.

PubMed

Checkley, William; Deza, Maria P; Klawitter, Jost; Romero, Karina M; Klawitter, Jelena; Pollard, Suzanne L; Wise, Robert A; Christians, Uwe; Hansel, Nadia N

2016-12-01

The diagnosis of asthma in children is challenging and relies on a combination of clinical factors and biomarkers including methacholine challenge, lung function, bronchodilator responsiveness, and presence of airway inflammation. No single test is diagnostic. We sought to identify a pattern of inflammatory biomarkers that was unique to asthma using a targeted metabolomics approach combined with data science methods. We conducted a nested case-control study of 100 children living in a peri-urban community in Lima, Peru. We defined cases as children with current asthma, and controls as children with no prior history of asthma and normal lung function. We further categorized enrollment following a factorial design to enroll equal numbers of children as either overweight or not. We obtained a fasting venous blood sample to characterize a comprehensive panel of targeted markers using a metabolomics approach based on high performance liquid chromatography-mass spectrometry. A statistical comparison of targeted metabolites between children with asthma (n = 50) and healthy controls (n = 49) revealed distinct patterns in relative concentrations of several metabolites: children with asthma had approximately 40-50% lower relative concentrations of ascorbic acid, 2-isopropylmalic acid, shikimate-3-phosphate, and 6-phospho-d-gluconate when compared to children without asthma, and 70% lower relative concentrations of reduced glutathione (all p < 0.001 after Bonferroni correction). Moreover, a combination of 2-isopropylmalic acid and betaine strongly discriminated between children with asthma (2-isopropylmalic acid ≤ 13 077 normalized counts/second) and controls (2-isopropylmalic acid > 13 077 normalized counts/second and betaine ≤ 16 47 121 normalized counts/second). By using a metabolomics approach applied to serum, we were able to discriminate between children with and without asthma by revealing different metabolic patterns. These results suggest that

Improving accuracy for identifying related PubMed queries by an integrated approach

PubMed Central

Lu, Zhiyong; Wilbur, W. John

2009-01-01

PubMed is the most widely used tool for searching biomedical literature online. As with many other online search tools, a user often types a series of multiple related queries before retrieving satisfactory results to fulfill a single information need. Meanwhile, it is also a common phenomenon to see a user type queries on unrelated topics in a single session. In order to study PubMed users’ search strategies, it is necessary to be able to automatically separate unrelated queries and group together related queries. Here, we report a novel approach combining both lexical and contextual analyses for segmenting PubMed query sessions and identifying related queries and compare its performance with the previous approach based solely on concept mapping. We experimented with our integrated approach on sample data consisting of 1,539 pairs of consecutive user queries in 351 user sessions. The prediction results of 1,396 pairs agreed with the gold-standard annotations, achieving an overall accuracy of 90.7%. This demonstrates that our approach is significantly better than the previously published method. By applying this approach to a one day query log of PubMed, we found that a significant proportion of information needs involved more than one PubMed query, and that most of the consecutive queries for the same information need are lexically related. Finally, the proposed PubMed distance is shown to be an accurate and meaningful measure for determining the contextual similarity between biological terms. The integrated approach can play a critical role in handling real-world PubMed query log data as is demonstrated in our experiments. PMID:19162232

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

PubMed

Richardson, Miles

2017-04-01

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

Identifying chromatin readers using a SILAC-based histone peptide pull-down approach.

PubMed

Vermeulen, Michiel

2012-01-01

Posttranslational modifications (PTMs) on core histones regulate essential processes inside the nucleus such as transcription, replication, and DNA repair. An important function of histone PTMs is the recruitment or stabilization of chromatin-modifying proteins, which are also called chromatin "readers." We have developed a generic SILAC-based peptide pull-down approach to identify such readers for histone PTMs in an unbiased manner. In this chapter, the workflow behind this method will be presented in detail. Copyright © 2012 Elsevier Inc. All rights reserved.

Identifying functional reorganization of spelling networks: an individual peak probability comparison approach

PubMed Central

Purcell, Jeremy J.; Rapp, Brenda

2013-01-01

Previous research has shown that damage to the neural substrates of orthographic processing can lead to functional reorganization during reading (Tsapkini et al., 2011); in this research we ask if the same is true for spelling. To examine the functional reorganization of spelling networks we present a novel three-stage Individual Peak Probability Comparison (IPPC) analysis approach for comparing the activation patterns obtained during fMRI of spelling in a single brain-damaged individual with dysgraphia to those obtained in a set of non-impaired control participants. The first analysis stage characterizes the convergence in activations across non-impaired control participants by applying a technique typically used for characterizing activations across studies: Activation Likelihood Estimate (ALE) (Turkeltaub et al., 2002). This method was used to identify locations that have a high likelihood of yielding activation peaks in the non-impaired participants. The second stage provides a characterization of the degree to which the brain-damaged individual's activations correspond to the group pattern identified in Stage 1. This involves performing a Mahalanobis distance statistics analysis (Tsapkini et al., 2011) that compares each of a control group's peak activation locations to the nearest peak generated by the brain-damaged individual. The third stage evaluates the extent to which the brain-damaged individual's peaks are atypical relative to the range of individual variation among the control participants. This IPPC analysis allows for a quantifiable, statistically sound method for comparing an individual's activation pattern to the patterns observed in a control group and, thus, provides a valuable tool for identifying functional reorganization in a brain-damaged individual with impaired spelling. Furthermore, this approach can be applied more generally to compare any individual's activation pattern with that of a set of other individuals. PMID:24399981

Systematic Correlation Matrix Evaluation (SCoMaE) - a bottom-up, science-led approach to identifying indicators

NASA Astrophysics Data System (ADS)

Mengis, Nadine; Keller, David P.; Oschlies, Andreas

2018-01-01

This study introduces the Systematic Correlation Matrix Evaluation (SCoMaE) method, a bottom-up approach which combines expert judgment and statistical information to systematically select transparent, nonredundant indicators for a comprehensive assessment of the state of the Earth system. The methods consists of two basic steps: (1) the calculation of a correlation matrix among variables relevant for a given research question and (2) the systematic evaluation of the matrix, to identify clusters of variables with similar behavior and respective mutually independent indicators. Optional further analysis steps include (3) the interpretation of the identified clusters, enabling a learning effect from the selection of indicators, (4) testing the robustness of identified clusters with respect to changes in forcing or boundary conditions, (5) enabling a comparative assessment of varying scenarios by constructing and evaluating a common correlation matrix, and (6) the inclusion of expert judgment, for example, to prescribe indicators, to allow for considerations other than statistical consistency. The example application of the SCoMaE method to Earth system model output forced by different CO2 emission scenarios reveals the necessity of reevaluating indicators identified in a historical scenario simulation for an accurate assessment of an intermediate-high, as well as a business-as-usual, climate change scenario simulation. This necessity arises from changes in prevailing correlations in the Earth system under varying climate forcing. For a comparative assessment of the three climate change scenarios, we construct and evaluate a common correlation matrix, in which we identify robust correlations between variables across the three considered scenarios.

Systems approaches in osteoarthritis: Identifying routes to novel diagnostic and therapeutic strategies.

PubMed

Mueller, Alan J; Peffers, Mandy J; Proctor, Carole J; Clegg, Peter D

2017-08-01

Systems orientated research offers the possibility of identifying novel therapeutic targets and relevant diagnostic markers for complex diseases such as osteoarthritis. This review demonstrates that the osteoarthritis research community has been slow to incorporate systems orientated approaches into research studies, although a number of key studies reveal novel insights into the regulatory mechanisms that contribute both to joint tissue homeostasis and its dysfunction. The review introduces both top-down and bottom-up approaches employed in the study of osteoarthritis. A holistic and multiscale approach, where clinical measurements may predict dysregulation and progression of joint degeneration, should be a key objective in future research. The review concludes with suggestions for further research and emerging trends not least of which is the coupled development of diagnostic tests and therapeutics as part of a concerted effort by the osteoarthritis research community to meet clinical needs. © 2017 The Authors. Journal of Orthopaedic Research Published by Wiley Periodicals, Inc. on behalf of Orthopaedic Research Society. J Orthop Res 35:1573-1588, 2017. © 2017 The Authors. Journal of Orthopaedic Research Published by Wiley Periodicals, Inc. on behalf of Orthopaedic Research Society.

Identifying novel members of the Wntless interactome through genetic and candidate gene approaches.

PubMed

Petko, Jessica; Tranchina, Trevor; Patel, Goral; Levenson, Robert; Justice-Bitner, Stephanie

2018-04-01

Wnt signaling is an important pathway that regulates several aspects of embryogenesis, stem cell maintenance, and neural connectivity. We have recently determined that opioids decrease Wnt secretion, presumably by inhibiting the recycling of the Wnt trafficking protein Wntless (Wls). This effect appears to be mediated by protein-protein interaction between Wls and the mu-opioid receptor (MOR), the primary cellular target of opioid drugs. The goal of this study was to identify novel protein interactors of Wls that are expressed in the brain and may also play a role in reward or addiction. Using genetic and candidate gene approaches, we show that among a variety of protein, Wls interacts with the dopamine transporter (target of cocaine), cannabinoid receptors (target of THC), Adenosine A2A receptor (target of caffeine), and SGIP1 (endocytic regulator of cannabinoid receptors). Our study shows that aside from opioid receptors, Wntless interacts with additional proteins involved in reward and/or addiction. Future studies will determine whether Wntless and WNT signaling play a more universal role in these processes. Copyright © 2017 Elsevier Inc. All rights reserved.

Newer Approaches to Identify Potential Untoward Effects in Functional Foods.

PubMed

Marone, Palma Ann; Birkenbach, Victoria L; Hayes, A Wallace

2016-01-01

Globalization has greatly accelerated the numbers and variety of food and beverage products available worldwide. The exchange among greater numbers of countries, manufacturers, and products in the United States and worldwide has necessitated enhanced quality measures for nutritional products for larger populations increasingly reliant on functionality. These functional foods, those that provide benefit beyond basic nutrition, are increasingly being used for their potential to alleviate food insufficiency while enhancing quality and longevity of life. In the United States alone, a steady import increase of greater than 15% per year or 24 million shipments, over 70% products of which are food related, is regulated under the Food and Drug Administration (FDA). This unparalleled growth has resulted in the need for faster, cheaper, and better safety and efficacy screening methods in the form of harmonized guidelines and recommendations for product standardization. In an effort to meet this need, the in vitro toxicology testing market has similarly grown with an anticipatory 15% increase between 2010 and 2015 of US$1.3 to US$2.7 billion. Although traditionally occupying a small fraction of the market behind pharmaceuticals and cosmetic/household products, the scope of functional food testing, including additives/supplements, ingredients, residues, contact/processing, and contaminants, is potentially expansive. Similarly, as functional food testing has progressed, so has the need to identify potential adverse factors that threaten the safety and quality of these products. © The Author(s) 2015.

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

PubMed

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

2018-05-12

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

Clustering approaches to identifying gene expression patterns from DNA microarray data.

PubMed

Do, Jin Hwan; Choi, Dong-Kug

2008-04-30

The analysis of microarray data is essential for large amounts of gene expression data. In this review we focus on clustering techniques. The biological rationale for this approach is the fact that many co-expressed genes are co-regulated, and identifying co-expressed genes could aid in functional annotation of novel genes, de novo identification of transcription factor binding sites and elucidation of complex biological pathways. Co-expressed genes are usually identified in microarray experiments by clustering techniques. There are many such methods, and the results obtained even for the same datasets may vary considerably depending on the algorithms and metrics for dissimilarity measures used, as well as on user-selectable parameters such as desired number of clusters and initial values. Therefore, biologists who want to interpret microarray data should be aware of the weakness and strengths of the clustering methods used. In this review, we survey the basic principles of clustering of DNA microarray data from crisp clustering algorithms such as hierarchical clustering, K-means and self-organizing maps, to complex clustering algorithms like fuzzy clustering.

The Baby TALK Model: An Innovative Approach to Identifying High-Risk Children and Families

ERIC Educational Resources Information Center

Villalpando, Aimee Hilado; Leow, Christine; Hornstein, John

2012-01-01

This research report examines the Baby TALK model, an innovative early childhood intervention approach used to identify, recruit, and serve young children who are at-risk for developmental delays, mental health needs, and/or school failure, and their families. The report begins with a description of the model. This description is followed by an…

Approach for Identifying Human Leukocyte Antigen (HLA)-DR Bound Peptides from Scarce Clinical Samples *

PubMed Central

Heyder, Tina; Kohler, Maxie; Tarasova, Nataliya K.; Haag, Sabrina; Rutishauser, Dorothea; Rivera, Natalia V.; Sandin, Charlotta; Mia, Sohel; Malmström, Vivianne; Wheelock, Åsa M.; Wahlström, Jan; Holmdahl, Rikard; Eklund, Anders; Zubarev, Roman A.; Grunewald, Johan; Ytterberg, A. Jimmy

2016-01-01

Immune-mediated diseases strongly associating with human leukocyte antigen (HLA) alleles are likely linked to specific antigens. These antigens are presented to T cells in the form of peptides bound to HLA molecules on antigen presenting cells, e.g. dendritic cells, macrophages or B cells. The identification of HLA-DR-bound peptides presents a valuable tool to investigate the human immunopeptidome. The lung is likely a key player in the activation of potentially auto-aggressive T cells prior to entering target tissues and inducing autoimmune disease. This makes the lung of exceptional interest and presents an ideal paradigm to study the human immunopeptidome and to identify antigenic peptides. Our previous investigation of HLA-DR peptide presentation in the lung required high numbers of cells (800 × 106 bronchoalveolar lavage (BAL) cells). Because BAL from healthy nonsmokers typically contains 10–15 × 106 cells, there is a need for a highly sensitive approach to study immunopeptides in the lungs of individual patients and controls. In this work, we analyzed the HLA-DR immunopeptidome in the lung by an optimized methodology to identify HLA-DR-bound peptides from low cell numbers. We used an Epstein-Barr Virus (EBV) immortalized B cell line and bronchoalveolar lavage (BAL) cells obtained from patients with sarcoidosis, an inflammatory T cell driven disease mainly occurring in the lung. Specifically, membrane complexes were isolated prior to immunoprecipitation, eluted peptides were identified by nanoLC-MS/MS and processed using the in-house developed ClusterMHCII software. With the optimized procedure we were able to identify peptides from 10 × 106 cells, which on average correspond to 10.9 peptides/million cells in EBV-B cells and 9.4 peptides/million cells in BAL cells. This work presents an optimized approach designed to identify HLA-DR-bound peptides from low numbers of cells, enabling the investigation of the BAL immunopeptidome from individual patients and

Using a distribution and conservation status weighted hotspot approach to identify areas in need of conservation action to benefit Idaho bird species

USGS Publications Warehouse

Haines, Aaron M.; Leu, Matthias; Svancara, Leona K.; Wilson, Gina; Scott, J. Michael

2010-01-01

Identification of biodiversity hotspots (hereafter, hotspots) has become a common strategy to delineate important areas for wildlife conservation. However, the use of hotspots has not often incorporated important habitat types, ecosystem services, anthropogenic activity, or consistency in identifying important conservation areas. The purpose of this study was to identify hotspots to improve avian conservation efforts for Species of Greatest Conservation Need (SGCN) in the state of Idaho, United States. We evaluated multiple approaches to define hotspots and used a unique approach based on weighting species by their distribution size and conservation status to identify hotspot areas. All hotspot approaches identified bodies of water (Bear Lake, Grays Lake, and American Falls Reservoir) as important hotspots for Idaho avian SGCN, but we found that the weighted approach produced more congruent hotspot areas when compared to other hotspot approaches. To incorporate anthropogenic activity into hotspot analysis, we grouped species based on their sensitivity to specific human threats (i.e., urban development, agriculture, fire suppression, grazing, roads, and logging) and identified ecological sections within Idaho that may require specific conservation actions to address these human threats using the weighted approach. The Snake River Basalts and Overthrust Mountains ecological sections were important areas for potential implementation of conservation actions to conserve biodiversity. Our approach to identifying hotspots may be useful as part of a larger conservation strategy to aid land managers or local governments in applying conservation actions on the ground.

The effects of stress on nuclear power plant operational decision making and training approaches to reduce stress effects

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

Mumaw, R.J.

1994-08-01

Operational personnel may be exposed to significant levels of stress during unexpected changes in plant state an plant emergencies. The decision making that identifies operational actions, which is strongly determined by procedures, may be affected by stress, and performance may be impaired. ER report analyzes potential effects of stress in nuclear power plant (NPP) settings, especially in the context of severe accident management (SAM). First, potential sources of stress in the NPP setting are identified. This analysis is followed by a review of the ways in which stress is likely to affect performance, with an emphasis on performance of cognitivemore » skills that are linked to operational decision making. Finally, potential training approaches for reducing or eliminating stress effects are identified. Several training approaches have the potential to eliminate or mitigate stress effects on cognitive skill performance. First, the use of simulated events for training can reduce the novelty and uncertainty that can lead to stress and performance impairments. Second, training to make cognitive processing more efficient and less reliant on attention and memory resources can offset the reductions in these resources that occur under stressful conditions. Third, training that targets crew communications skills can reduce the likelihood that communications will fail under stress.« less

A Pooled Sequencing Approach Identifies a Candidate Meiotic Driver in Drosophila

PubMed Central

Wei, Kevin H.-C.; Reddy, Hemakumar M.; Rathnam, Chandramouli; Lee, Jimin; Lin, Deanna; Ji, Shuqing; Mason, James M.; Clark, Andrew G.; Barbash, Daniel A.

2017-01-01

Meiotic drive occurs when a selfish element increases its transmission frequency above the Mendelian ratio by hijacking the asymmetric divisions of female meiosis. Meiotic drive causes genomic conflict and potentially has a major impact on genome evolution, but only a few drive loci of large effect have been described. New methods to reliably detect meiotic drive are therefore needed, particularly for discovering moderate-strength drivers that are likely to be more prevalent in natural populations than strong drivers. Here, we report an efficient method that uses sequencing of large pools of backcross (BC1) progeny to test for deviations from Mendelian segregation genome-wide with single-nucleotide polymorphisms (SNPs) that distinguish the parental strains. We show that meiotic drive can be detected by a characteristic pattern of decay in distortion of SNP frequencies, caused by recombination unlinking the driver from distal loci. We further show that control crosses allow allele-frequency distortion caused by meiotic drive to be distinguished from distortion resulting from developmental effects. We used this approach to test whether chromosomes with extreme telomere-length differences segregate at Mendelian ratios, as telomeric regions are a potential hotspot for meiotic drive due to their roles in meiotic segregation and multiple observations of high rates of telomere sequence evolution. Using four different pairings of long and short telomere strains, we find no evidence that extreme telomere-length variation causes meiotic drive in Drosophila. However, we identify one candidate meiotic driver in a centromere-linked region that shows an ∼8% increase in transmission frequency, corresponding to a ∼54:46 segregation ratio. Our results show that candidate meiotic drivers of moderate strength can be readily detected and localized in pools of BC1 progeny. PMID:28258181

A Bayesian approach to identifying structural nonlinearity using free-decay response: Application to damage detection in composites

USGS Publications Warehouse

Nichols, J.M.; Link, W.A.; Murphy, K.D.; Olson, C.C.

2010-01-01

This work discusses a Bayesian approach to approximating the distribution of parameters governing nonlinear structural systems. Specifically, we use a Markov Chain Monte Carlo method for sampling the posterior parameter distributions thus producing both point and interval estimates for parameters. The method is first used to identify both linear and nonlinear parameters in a multiple degree-of-freedom structural systems using free-decay vibrations. The approach is then applied to the problem of identifying the location, size, and depth of delamination in a model composite beam. The influence of additive Gaussian noise on the response data is explored with respect to the quality of the resulting parameter estimates.

Proteomics-based approach identified differentially expressed proteins with potential roles in endometrial carcinoma.

PubMed

Li, Zhengyu; Min, Wenjiao; Huang, Canhua; Bai, Shujun; Tang, Minghai; Zhao, Xia

2010-01-01

We used proteomic approaches to identify altered expressed proteins in endometrial carcinoma, with the aim of discovering potential biomarkers or therapeutic targets for endometrial carcinoma. The global proteins extracted from endometrial carcinoma and normal endometrial tissues were separated by 2-dimensional electrophoresis and analyzed with PDQuest (Bio-Rad, Hercules, Calif) software. The differentially expressed spots were identified by mass spectrometry and searched against NCBInr protein database. Those proteins with potential roles were confirmed by Western blotting and immunohistochemical assays. Ninety-nine proteins were identified by mass spectrometry, and a cluster diagram analysis indicated that these proteins were involved in metabolism, cell transformation, protein folding, translation and modification, proliferation and apoptosis, signal transduction, cytoskeleton, and so on. In confirmatory immunoblotting and immunohistochemical analyses, overexpressions of epidermal fatty acid-binding protein, calcyphosine, and cyclophilin A were also observed in endometrial carcinoma tissues, which were consistent with the proteomic results. Our results suggested that these identified proteins, including epidermal fatty acid-binding protein, calcyphosine, and cyclophilin A, might be of potential values in the studies of endometrial carcinogenesis or investigations of diagnostic biomarkers or treatment targets for endometrial carcinoma.

An Integrated Approach to Change the Outcome Part II: Targeted Neuromuscular Training Techniques to Reduce Identified ACL Injury Risk Factors

PubMed Central

Myer, Gregory D.; Ford, Kevin R.; Brent, Jensen L.; Hewett, Timothy E.

2014-01-01

Prior reports indicate that female athletes who demonstrate high knee abduction moments (KAMs) during landing are more responsive to neuromuscular training designed to reduce KAM. Identification of female athletes who demonstrate high KAM, which accurately identifies those at risk for noncontact anterior cruciate ligament (ACL) injury, may be ideal for targeted neuromuscular training. Specific neuromuscular training targeted to the underlying biomechanical components that increase KAM may provide the most efficient and effective training strategy to reduce noncontact ACL injury risk. The purpose of the current commentary is to provide an integrative approach to identify and target mechanistic underpinnings to increased ACL injury in female athletes. Specific neuromuscular training techniques will be presented that address individual algorithm components related to high knee load landing patterns. If these integrated techniques are employed on a widespread basis, prevention strategies for noncontact ACL injury among young female athletes may prove both more effective and efficient. PMID:22580980

A geometric approach to identify cavities in particle systems

NASA Astrophysics Data System (ADS)

Voyiatzis, Evangelos; Böhm, Michael C.; Müller-Plathe, Florian

2015-11-01

The implementation of a geometric algorithm to identify cavities in particle systems in an open-source python program is presented. The algorithm makes use of the Delaunay space tessellation. The present python software is based on platform-independent tools, leading to a portable program. Its successful execution provides information concerning the accessible volume fraction of the system, the size and shape of the cavities and the group of atoms forming each of them. The program can be easily incorporated into the LAMMPS software. An advantage of the present algorithm is that no a priori assumption on the cavity shape has to be made. As an example, the cavity size and shape distributions in a polyethylene melt system are presented for three spherical probe particles. This paper serves also as an introductory manual to the script. It summarizes the algorithm, its implementation, the required user-defined parameters as well as the format of the input and output files. Additionally, we demonstrate possible applications of our approach and compare its capability with the ones of well documented cavity size estimators.

Using a competency-based approach to identify the management behaviours required to manage workplace stress in nursing: a critical incident study.

PubMed

Lewis, Rachel; Yarker, Joanna; Donaldson-Feilder, Emma; Flaxman, Paul; Munir, Fehmidah

2010-03-01

To identify the specific management behaviours associated with the effective management of stress in nursing; and to build a stress management competency framework that can be integrated and compared with nurse management frameworks. Workplace stress is a significant problem in healthcare, especially within nursing. While there is a reasonable consensus regarding the sources of stress and its impact on health and well-being, little is known about the specific line manager behaviours that are associated with the effective and ineffective management of stress. Semi-structured interviews using critical incident technique were conducted with 41 employees working within 5 National Health Service (NHS) trusts within the United Kingdom. Data were transcribed and analysed using content analysis. 19 competencies (or sets of behaviour) were identified in the management of stress in employees. The 3 most frequently reported competencies: managing workload and resources, individual consideration and participative approach, are discussed in detail with illustrative quotes. Managers are vital in the reduction and management of stress at work. Importantly, the 2 of the 3 dominant competencies, managing workload and resources and individual consideration, do not feature in the UK's NHS Knowledge and Skills Framework, suggesting there are important skills gaps with regard to managing workplace stress. The implications of this approach for training and development, performance appraisal and assessment are discussed. Interventions to support managers develop effective behaviours are required to help reduce and manage stress at work. Copyright 2009 Elsevier Ltd. All rights reserved.

Using Bioinformatic Approaches to Identify Pathways Targeted by Human Leukemogens

PubMed Central

Thomas, Reuben; Phuong, Jimmy; McHale, Cliona M.; Zhang, Luoping

2012-01-01

We have applied bioinformatic approaches to identify pathways common to chemical leukemogens and to determine whether leukemogens could be distinguished from non-leukemogenic carcinogens. From all known and probable carcinogens classified by IARC and NTP, we identified 35 carcinogens that were associated with leukemia risk in human studies and 16 non-leukemogenic carcinogens. Using data on gene/protein targets available in the Comparative Toxicogenomics Database (CTD) for 29 of the leukemogens and 11 of the non-leukemogenic carcinogens, we analyzed for enrichment of all 250 human biochemical pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The top pathways targeted by the leukemogens included metabolism of xenobiotics by cytochrome P450, glutathione metabolism, neurotrophin signaling pathway, apoptosis, MAPK signaling, Toll-like receptor signaling and various cancer pathways. The 29 leukemogens formed 18 distinct clusters comprising 1 to 3 chemicals that did not correlate with known mechanism of action or with structural similarity as determined by 2D Tanimoto coefficients in the PubChem database. Unsupervised clustering and one-class support vector machines, based on the pathway data, were unable to distinguish the 29 leukemogens from 11 non-leukemogenic known and probable IARC carcinogens. However, using two-class random forests to estimate leukemogen and non-leukemogen patterns, we estimated a 76% chance of distinguishing a random leukemogen/non-leukemogen pair from each other. PMID:22851955

Modelling Creativity: Identifying Key Components through a Corpus-Based Approach

PubMed Central

2016-01-01

Creativity is a complex, multi-faceted concept encompassing a variety of related aspects, abilities, properties and behaviours. If we wish to study creativity scientifically, then a tractable and well-articulated model of creativity is required. Such a model would be of great value to researchers investigating the nature of creativity and in particular, those concerned with the evaluation of creative practice. This paper describes a unique approach to developing a suitable model of how creative behaviour emerges that is based on the words people use to describe the concept. Using techniques from the field of statistical natural language processing, we identify a collection of fourteen key components of creativity through an analysis of a corpus of academic papers on the topic. Words are identified which appear significantly often in connection with discussions of the concept. Using a measure of lexical similarity to help cluster these words, a number of distinct themes emerge, which collectively contribute to a comprehensive and multi-perspective model of creativity. The components provide an ontology of creativity: a set of building blocks which can be used to model creative practice in a variety of domains. The components have been employed in two case studies to evaluate the creativity of computational systems and have proven useful in articulating achievements of this work and directions for further research. PMID:27706185

Modelling Creativity: Identifying Key Components through a Corpus-Based Approach.

PubMed

Jordanous, Anna; Keller, Bill

2016-01-01

Creativity is a complex, multi-faceted concept encompassing a variety of related aspects, abilities, properties and behaviours. If we wish to study creativity scientifically, then a tractable and well-articulated model of creativity is required. Such a model would be of great value to researchers investigating the nature of creativity and in particular, those concerned with the evaluation of creative practice. This paper describes a unique approach to developing a suitable model of how creative behaviour emerges that is based on the words people use to describe the concept. Using techniques from the field of statistical natural language processing, we identify a collection of fourteen key components of creativity through an analysis of a corpus of academic papers on the topic. Words are identified which appear significantly often in connection with discussions of the concept. Using a measure of lexical similarity to help cluster these words, a number of distinct themes emerge, which collectively contribute to a comprehensive and multi-perspective model of creativity. The components provide an ontology of creativity: a set of building blocks which can be used to model creative practice in a variety of domains. The components have been employed in two case studies to evaluate the creativity of computational systems and have proven useful in articulating achievements of this work and directions for further research.

Integrating modelling and phenotyping approaches to identify and screen complex traits - Illustration for transpiration efficiency in cereals.

PubMed

Chenu, K; van Oosterom, E J; McLean, G; Deifel, K S; Fletcher, A; Geetika, G; Tirfessa, A; Mace, E S; Jordan, D R; Sulman, R; Hammer, G L

2018-02-21

Following advances in genetics, genomics, and phenotyping, trait selection in breeding is limited by our ability to understand interactions within the plants and with their environments, and to target traits of most relevance for the target population of environments. We propose an integrated approach that combines insights from crop modelling, physiology, genetics, and breeding to identify traits valuable for yield gain in the target population of environments, develop relevant high-throughput phenotyping platforms, and identify genetic controls and their values in production environments. This paper uses transpiration efficiency (biomass produced per unit of water used) as an example of a complex trait of interest to illustrate how the approach can guide modelling, phenotyping, and selection in a breeding program. We believe that this approach, by integrating insights from diverse disciplines, can increase the resource use efficiency of breeding programs for improving yield gains in target populations of environments.

An unbiased approach to identify genes involved in development in a turtle with temperature-dependent sex determination.

PubMed

Chojnowski, Jena L; Braun, Edward L

2012-07-15

Many reptiles exhibit temperature-dependent sex determination (TSD). The initial cue in TSD is incubation temperature, unlike genotypic sex determination (GSD) where it is determined by the presence of specific alleles (or genetic loci). We used patterns of gene expression to identify candidates for genes with a role in TSD and other developmental processes without making a priori assumptions about the identity of these genes (ortholog-based approach). We identified genes with sexually dimorphic mRNA accumulation during the temperature sensitive period of development in the Red-eared slider turtle (Trachemys scripta), a turtle with TSD. Genes with differential mRNA accumulation in response to estrogen (estradiol-17β; E(2)) exposure and developmental stages were also identified. Sequencing 767 clones from three suppression-subtractive hybridization libraries yielded a total of 581 unique sequences. Screening a macroarray with a subset of those sequences revealed a total of 26 genes that exhibited differential mRNA accumulation: 16 female biased and 10 male biased. Additional analyses revealed that C16ORF62 (an unknown gene) and MALAT1 (a long noncoding RNA) exhibited increased mRNA accumulation at the male producing temperature relative to the female producing temperature during embryonic sexual development. Finally, we identified four genes (C16ORF62, CCT3, MMP2, and NFIB) that exhibited a stage effect and five genes (C16ORF62, CCT3, MMP2, NFIB and NOTCH2) showed a response to E(2) exposure. Here we report a survey of genes identified using patterns of mRNA accumulation during embryonic development in a turtle with TSD. Many previous studies have focused on examining the turtle orthologs of genes involved in mammalian development. Although valuable, the limitations of this approach are exemplified by our identification of two genes (MALAT1 and C16ORF62) that are sexually dimorphic during embryonic development. MALAT1 is a noncoding RNA that has not been implicated

A Multiomics Approach to Identify Genes Associated with Childhood Asthma Risk and Morbidity.

PubMed

Forno, Erick; Wang, Ting; Yan, Qi; Brehm, John; Acosta-Perez, Edna; Colon-Semidey, Angel; Alvarez, Maria; Boutaoui, Nadia; Cloutier, Michelle M; Alcorn, John F; Canino, Glorisa; Chen, Wei; Celedón, Juan C

2017-10-01

Childhood asthma is a complex disease. In this study, we aim to identify genes associated with childhood asthma through a multiomics "vertical" approach that integrates multiple analytical steps using linear and logistic regression models. In a case-control study of childhood asthma in Puerto Ricans (n = 1,127), we used adjusted linear or logistic regression models to evaluate associations between several analytical steps of omics data, including genome-wide (GW) genotype data, GW methylation, GW expression profiling, cytokine levels, asthma-intermediate phenotypes, and asthma status. At each point, only the top genes/single-nucleotide polymorphisms/probes/cytokines were carried forward for subsequent analysis. In step 1, asthma modified the gene expression-protein level association for 1,645 genes; pathway analysis showed an enrichment of these genes in the cytokine signaling system (n = 269 genes). In steps 2-3, expression levels of 40 genes were associated with intermediate phenotypes (asthma onset age, forced expiratory volume in 1 second, exacerbations, eosinophil counts, and skin test reactivity); of those, methylation of seven genes was also associated with asthma. Of these seven candidate genes, IL5RA was also significant in analytical steps 4-8. We then measured plasma IL-5 receptor α levels, which were associated with asthma age of onset and moderate-severe exacerbations. In addition, in silico database analysis showed that several of our identified IL5RA single-nucleotide polymorphisms are associated with transcription factors related to asthma and atopy. This approach integrates several analytical steps and is able to identify biologically relevant asthma-related genes, such as IL5RA. It differs from other methods that rely on complex statistical models with various assumptions.

An in silico approach helped to identify the best experimental design, population, and outcome for future randomized clinical trials.

PubMed

Bajard, Agathe; Chabaud, Sylvie; Cornu, Catherine; Castellan, Anne-Charlotte; Malik, Salma; Kurbatova, Polina; Volpert, Vitaly; Eymard, Nathalie; Kassai, Behrouz; Nony, Patrice

2016-01-01

The main objective of our work was to compare different randomized clinical trial (RCT) experimental designs in terms of power, accuracy of the estimation of treatment effect, and number of patients receiving active treatment using in silico simulations. A virtual population of patients was simulated and randomized in potential clinical trials. Treatment effect was modeled using a dose-effect relation for quantitative or qualitative outcomes. Different experimental designs were considered, and performances between designs were compared. One thousand clinical trials were simulated for each design based on an example of modeled disease. According to simulation results, the number of patients needed to reach 80% power was 50 for crossover, 60 for parallel or randomized withdrawal, 65 for drop the loser (DL), and 70 for early escape or play the winner (PW). For a given sample size, each design had its own advantage: low duration (parallel, early escape), high statistical power and precision (crossover), and higher number of patients receiving the active treatment (PW and DL). Our approach can help to identify the best experimental design, population, and outcome for future RCTs. This may be particularly useful for drug development in rare diseases, theragnostic approaches, or personalized medicine. Copyright © 2016 Elsevier Inc. All rights reserved.

A comprehensive iterative approach is highly effective in diagnosing individuals who are exome negative.

PubMed

Shashi, Vandana; Schoch, Kelly; Spillmann, Rebecca; Cope, Heidi; Tan, Queenie K-G; Walley, Nicole; Pena, Loren; McConkie-Rosell, Allyn; Jiang, Yong-Hui; Stong, Nicholas; Need, Anna C; Goldstein, David B

2018-06-15

Sixty to seventy-five percent of individuals with rare and undiagnosed phenotypes remain undiagnosed after exome sequencing (ES). With standard ES reanalysis resolving 10-15% of the ES negatives, further approaches are necessary to maximize diagnoses in these individuals. In 38 ES negative patients an individualized genomic-phenotypic approach was employed utilizing (1) phenotyping; (2) reanalyses of FASTQ files, with innovative bioinformatics; (3) targeted molecular testing; (4) genome sequencing (GS); and (5) conferring of clinical diagnoses when pathognomonic clinical findings occurred. Certain and highly likely diagnoses were made in 18/38 (47%) individuals, including identifying two new developmental disorders. The majority of diagnoses (>70%) were due to our bioinformatics, phenotyping, and targeted testing identifying variants that were undetected or not prioritized on prior ES. GS diagnosed 3/18 individuals with structural variants not amenable to ES. Additionally, tentative diagnoses were made in 3 (8%), and in 5 individuals (13%) candidate genes were identified. Overall, diagnoses/potential leads were identified in 26/38 (68%). Our comprehensive approach to ES negatives maximizes the ES and clinical data for both diagnoses and candidate gene identification, without GS in the majority. This iterative approach is cost-effective and is pertinent to the current conundrum of ES negatives.

The effectiveness of current approaches to workplace stress management in the nursing profession: an evidence based literature review

PubMed Central

Mimura, C; Griffiths, P

2003-01-01

The effectiveness of current approaches to workplace stress management for nurses was assessed through a systematic review. Seven randomised controlled trials and three prospective cohort studies assessing the effectiveness of a stress management programmes were identified and reviewed. The quality of research identified was weak. There is more evidence for the effectiveness of programmes based on providing personal support than environmental management to reduce stressors. However, since the number and quality of studies is low, the question as to which, if any, approach is more effective cannot be answered definitively. Further research is required before clear recommendations for the use of particular interventions for nursing work related stress can be made. PMID:12499451

SU-E-J-212: Identifying Bones From MRI: A Dictionary Learnign and Sparse Regression Approach

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

Ruan, D; Yang, Y; Cao, M

2014-06-01

Purpose: To develop an efficient and robust scheme to identify bony anatomy based on MRI-only simulation images. Methods: MRI offers important soft tissue contrast and functional information, yet its lack of correlation to electron-density has placed it as an auxiliary modality to CT in radiotherapy simulation and adaptation. An effective scheme to identify bony anatomy is an important first step towards MR-only simulation/treatment paradigm and would satisfy most practical purposes. We utilize a UTE acquisition sequence to achieve visibility of the bone. By contrast to manual + bulk or registration-to identify bones, we propose a novel learning-based approach for improvedmore » robustness to MR artefacts and environmental changes. Specifically, local information is encoded with MR image patch, and the corresponding label is extracted (during training) from simulation CT aligned to the UTE. Within each class (bone vs. nonbone), an overcomplete dictionary is learned so that typical patches within the proper class can be represented as a sparse combination of the dictionary entries. For testing, an acquired UTE-MRI is divided to patches using a sliding scheme, where each patch is sparsely regressed against both bone and nonbone dictionaries, and subsequently claimed to be associated with the class with the smaller residual. Results: The proposed method has been applied to the pilot site of brain imaging and it has showed general good performance, with dice similarity coefficient of greater than 0.9 in a crossvalidation study using 4 datasets. Importantly, it is robust towards consistent foreign objects (e.g., headset) and the artefacts relates to Gibbs and field heterogeneity. Conclusion: A learning perspective has been developed for inferring bone structures based on UTE MRI. The imaging setting is subject to minimal motion effects and the post-processing is efficient. The improved efficiency and robustness enables a first translation to MR-only routine. The

Annual Report, Fall 2016: Identifying Cost Effective Tank Waste Characterization Approaches

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

Reboul, S. H.; DiPrete, D. P.

2016-12-12

This report documents the activities that were performed during the second year of a project undertaken to improve the cost effectiveness and timeliness of SRNL’s tank closure characterization practices. The activities performed during the first year of the project were previously reported in SRNL-STI-2015-00144. The scope of the second year activities was divided into the following three primary tasks: 1) develop a technical basis and strategy for improving the cost effectiveness and schedule of SRNL’s tank closure characterization program; 2) initiate the design and assembly of a new waste removal system for improving the throughput and reducing the personnel dosemore » associated with extraction chromatography radiochemical separations; and 3) develop and perform feasibility testing of three alternative radiochemical separation protocols holding promise for improving high resource demand/time consuming tank closure sample analysis methods.« less

Identifying Influential Young People to Undertake Effective Peer-Led Health Promotion: the example of A Stop Smoking In Schools Trial (ASSIST)

ERIC Educational Resources Information Center

Starkey, Fenella; Audrey, Suzanne; Holliday, Jo; Moore, Laurence; Campbell, Rona

2009-01-01

The objective of the study was to develop and evaluate an effective whole-community approach to identifying a diverse group of influential young people to effectively diffuse health promotion messages among their peers. A peer nomination questionnaire, developed through extensive piloting work, was completed by 10 730 Year 8 students (aged 12-13…

Consensus–based approach to develop a measurement framework and identify a core set of indicators to track implementation and progress towards effective coverage of facility–based Kangaroo Mother Care

PubMed Central

Guenther, Tanya; Moxon, Sarah; Valsangkar, Bina; Wetzel, Greta; Ruiz, Juan; Kerber, Kate; Blencowe, Hannah; Dube, Queen; Vani, Shashi N; Vivio, Donna; Magge, Hema; De Leon–Mendoza, Socorro; Patterson, Janna; Mazia, Goldy

2017-01-01

Background As efforts to scale up the delivery of Kangaroo Mother Care (KMC) in facilities are increasing, a standardized approach to measure implementation and progress towards effective coverage is needed. Here, we describe a consensus–based approach to develop a measurement framework and identify a core set of indicators for monitoring facility–based KMC that would be feasible to measure within existing systems. Methods The KMC measurement framework and core list of indicators were developed through: 1) scoping exercise to identify potential indicators through literature review and requests from researchers and program implementers; and 2) face–to–face consultations with KMC and measurement experts working at country and global levels to review candidate indicators and finalize selection and definitions. Results The KMC measurement framework includes two main components: 1) service readiness, based on the WHO building blocks framework; and 2) service delivery action sequence covering identification, service initiation, continuation to discharge, and follow–up to graduation. Consensus was reached on 10 core indicators for KMC, which were organized according to the measurement framework. We identified 4 service readiness indicators, capturing national level policy for KMC, availability of KMC indicators in HMIS, costed operational plans for KMC and availability of KMC services at health facilities with inpatient maternity services. Six indicators were defined for service delivery, including weighing of babies at birth, identification of those ≤2000 g, initiation of facility–based KMC, monitoring the quality of KMC, status of babies at discharge from the facility and levels of follow–up (according to country–specific protocol). Conclusions These core KMC indicators, identified with input from a wide range of global and country–level KMC and measurement experts, can aid efforts to strengthen monitoring systems and facilitate global tracking of

Consensus-based approach to develop a measurement framework and identify a core set of indicators to track implementation and progress towards effective coverage of facility-based Kangaroo Mother Care.

PubMed

Guenther, Tanya; Moxon, Sarah; Valsangkar, Bina; Wetzel, Greta; Ruiz, Juan; Kerber, Kate; Blencowe, Hannah; Dube, Queen; Vani, Shashi N; Vivio, Donna; Magge, Hema; De Leon-Mendoza, Socorro; Patterson, Janna; Mazia, Goldy

2017-12-01

As efforts to scale up the delivery of Kangaroo Mother Care (KMC) in facilities are increasing, a standardized approach to measure implementation and progress towards effective coverage is needed. Here, we describe a consensus-based approach to develop a measurement framework and identify a core set of indicators for monitoring facility-based KMC that would be feasible to measure within existing systems. The KMC measurement framework and core list of indicators were developed through: 1) scoping exercise to identify potential indicators through literature review and requests from researchers and program implementers; and 2) face-to-face consultations with KMC and measurement experts working at country and global levels to review candidate indicators and finalize selection and definitions. The KMC measurement framework includes two main components: 1) service readiness, based on the WHO building blocks framework; and 2) service delivery action sequence covering identification, service initiation, continuation to discharge, and follow-up to graduation. Consensus was reached on 10 core indicators for KMC, which were organized according to the measurement framework. We identified 4 service readiness indicators, capturing national level policy for KMC, availability of KMC indicators in HMIS, costed operational plans for KMC and availability of KMC services at health facilities with inpatient maternity services. Six indicators were defined for service delivery, including weighing of babies at birth, identification of those ≤2000 g, initiation of facility-based KMC, monitoring the quality of KMC, status of babies at discharge from the facility and levels of follow-up (according to country-specific protocol). These core KMC indicators, identified with input from a wide range of global and country-level KMC and measurement experts, can aid efforts to strengthen monitoring systems and facilitate global tracking of KMC implementation. As data collection systems advance, we

SPARQL-enabled identifier conversion with Identifiers.org

PubMed Central

Wimalaratne, Sarala M.; Bolleman, Jerven; Juty, Nick; Katayama, Toshiaki; Dumontier, Michel; Redaschi, Nicole; Le Novère, Nicolas; Hermjakob, Henning; Laibe, Camille

2015-01-01

Motivation: On the semantic web, in life sciences in particular, data is often distributed via multiple resources. Each of these sources is likely to use their own International Resource Identifier for conceptually the same resource or database record. The lack of correspondence between identifiers introduces a barrier when executing federated SPARQL queries across life science data. Results: We introduce a novel SPARQL-based service to enable on-the-fly integration of life science data. This service uses the identifier patterns defined in the Identifiers.org Registry to generate a plurality of identifier variants, which can then be used to match source identifiers with target identifiers. We demonstrate the utility of this identifier integration approach by answering queries across major producers of life science Linked Data. Availability and implementation: The SPARQL-based identifier conversion service is available without restriction at http://identifiers.org/services/sparql. Contact: sarala@ebi.ac.uk PMID:25638809

SPARQL-enabled identifier conversion with Identifiers.org.

PubMed

Wimalaratne, Sarala M; Bolleman, Jerven; Juty, Nick; Katayama, Toshiaki; Dumontier, Michel; Redaschi, Nicole; Le Novère, Nicolas; Hermjakob, Henning; Laibe, Camille

2015-06-01

On the semantic web, in life sciences in particular, data is often distributed via multiple resources. Each of these sources is likely to use their own International Resource Identifier for conceptually the same resource or database record. The lack of correspondence between identifiers introduces a barrier when executing federated SPARQL queries across life science data. We introduce a novel SPARQL-based service to enable on-the-fly integration of life science data. This service uses the identifier patterns defined in the Identifiers.org Registry to generate a plurality of identifier variants, which can then be used to match source identifiers with target identifiers. We demonstrate the utility of this identifier integration approach by answering queries across major producers of life science Linked Data. The SPARQL-based identifier conversion service is available without restriction at http://identifiers.org/services/sparql. © The Author 2015. Published by Oxford University Press.

High-Throughput Effect-Directed Analysis Using Downscaled in Vitro Reporter Gene Assays To Identify Endocrine Disruptors in Surface Water

PubMed Central

2018-01-01

Effect-directed analysis (EDA) is a commonly used approach for effect-based identification of endocrine disruptive chemicals in complex (environmental) mixtures. However, for routine toxicity assessment of, for example, water samples, current EDA approaches are considered time-consuming and laborious. We achieved faster EDA and identification by downscaling of sensitive cell-based hormone reporter gene assays and increasing fractionation resolution to allow testing of smaller fractions with reduced complexity. The high-resolution EDA approach is demonstrated by analysis of four environmental passive sampler extracts. Downscaling of the assays to a 384-well format allowed analysis of 64 fractions in triplicate (or 192 fractions without technical replicates) without affecting sensitivity compared to the standard 96-well format. Through a parallel exposure method, agonistic and antagonistic androgen and estrogen receptor activity could be measured in a single experiment following a single fractionation. From 16 selected candidate compounds, identified through nontargeted analysis, 13 could be confirmed chemically and 10 were found to be biologically active, of which the most potent nonsteroidal estrogens were identified as oxybenzone and piperine. The increased fractionation resolution and the higher throughput that downscaling provides allow for future application in routine high-resolution screening of large numbers of samples in order to accelerate identification of (emerging) endocrine disruptors. PMID:29547277

A similarity based approach to identify homogeneous regions for seasonal forecasting

NASA Astrophysics Data System (ADS)

Schick, Simon; Rössler, Ole; Weingartner, Rolf

2015-04-01

Seasonal runoff forecasting using statistical models is challenged by a large number of candidate predictors and a general weak predictor-predictand relationship. As the area of the target basin increases, often also the available data sets do, thus reinforcing the predictor selection challenge. We propose an approach which follows the idea of 'divide and conquer' as developed in computational sciences and machine learning: First, the macroscale target basin is partitioned into homogeneous regions using all its gauged mesoscale subbasins. Second, one representative subbasin per homogeneous region is identified, for which models are fitted and applied. Third, the resulting forecasts are combined at the scale of the macroscale target basin. This approach requires a suitable method to identify homogeneous regions and representative subbasins. We suggest a way based on hydrological similarity, as catchment similarity estimated with respect to physiographic-climatic descriptors does not necessarily imply similar runoff response. Each descriptor is derived from daily runoff series and aimed to reflect a specific catchment characteristic: autocorrelation coefficient, parameters of fitted Gamma distribution and low/high flow indices (based on daily runoff values) fluctuation of the standard deviation within the yearly cycle (based on weekly runoff values) dominant harmonics obtained from the discrete Fourier transform (based on monthly runoff values) long term trend (based on yearly runoff values) Where necessary, the runoff series first need to be standardized, aggregated, detrended or deseasonalized. As a preliminary study we present the results of a cluster analysis for the Swiss Rhine River as macroscale target basin, which leads to about 40 mesoscale subbasins with runoff series for the period 1991-2010. Problems we have to address include the choice of a clustering algorithm, the identification of an appropriate number of regions and the selection of representative

Combined semi-empirical screening and design of experiments (DOE) approach to identify candidate formulations of a lyophilized live attenuated tetravalent viral vaccine candidate.

PubMed

Patel, Ashaben; Erb, Steven M; Strange, Linda; Shukla, Ravi S; Kumru, Ozan S; Smith, Lee; Nelson, Paul; Joshi, Sangeeta B; Livengood, Jill A; Volkin, David B

2018-05-24

A combination experimental approach, utilizing semi-empirical excipient screening followed by statistical modeling using design of experiments (DOE), was undertaken to identify stabilizing candidate formulations for a lyophilized live attenuated Flavivirus vaccine candidate. Various potential pharmaceutical compounds used in either marketed or investigative live attenuated viral vaccine formulations were first identified. The ability of additives from different categories of excipients, either alone or in combination, were then evaluated for their ability to stabilize virus against freeze-thaw, freeze-drying, and accelerated storage (25°C) stresses by measuring infectious virus titer. An exploratory data analysis and predictive DOE modeling approach was subsequently undertaken to gain a better understanding of the interplay between the key excipients and stability of virus as well as to determine which combinations were interacting to improve virus stability. The lead excipient combinations were identified and tested for stabilizing effects using a tetravalent mixture of viruses in accelerated and real time (2-8°C) stability studies. This work demonstrates the utility of combining semi-empirical excipient screening and DOE experimental design strategies in the formulation development of lyophilized live attenuated viral vaccine candidates. Copyright © 2017 Elsevier Ltd. All rights reserved.

Effectiveness of Instruction Based on the Constructivist Approach on Understanding Chemical Equilibrium Concepts

ERIC Educational Resources Information Center

Akkus, Huseyin; Kadayifci, Hakki; Atasoy, Basri; Geban, Omer

2003-01-01

The purpose of this study was to identify misconceptions concerning chemical equilibrium concepts and to investigate the effectiveness of instruction based on the constructivist approach over traditional instruction on 10th grade students' understanding of chemical equilibrium concepts. The subjects of this study consisted of 71 10th grade…

Genome-Scale Approaches to Identify Genes Essential for Haemophilus influenzae Pathogenesis

PubMed Central

Wong, Sandy M. S.; Akerley, Brian J.

2012-01-01

Haemophilus influenzae is a Gram-negative bacterium that has no identified natural niche outside of the human host. It primarily colonizes the nasopharyngeal mucosa in an asymptomatic mode, but has the ability to disseminate to other anatomical sites to cause otitis media, upper, and lower respiratory tract infections, septicemia, and meningitis. To persist in diverse environments the bacterium must exploit and utilize the nutrients and other resources available in these sites for optimal growth/survival. Recent evidence suggests that regulatory factors that direct such adaptations also control virulence determinants required to resist and evade immune clearance mechanisms. In this review, we describe the recent application of whole-genome approaches that together provide insight into distinct survival mechanisms of H. influenzae in the context of different sites of pathogenesis. PMID:22919615

Genome-scale approaches to identify genes essential for Haemophilus influenzae pathogenesis.

PubMed

Wong, Sandy M S; Akerley, Brian J

2012-01-01

Haemophilus influenzae is a Gram-negative bacterium that has no identified natural niche outside of the human host. It primarily colonizes the nasopharyngeal mucosa in an asymptomatic mode, but has the ability to disseminate to other anatomical sites to cause otitis media, upper, and lower respiratory tract infections, septicemia, and meningitis. To persist in diverse environments the bacterium must exploit and utilize the nutrients and other resources available in these sites for optimal growth/survival. Recent evidence suggests that regulatory factors that direct such adaptations also control virulence determinants required to resist and evade immune clearance mechanisms. In this review, we describe the recent application of whole-genome approaches that together provide insight into distinct survival mechanisms of H. influenzae in the context of different sites of pathogenesis.

A review of approaches to identifying patient phenotype cohorts using electronic health records

PubMed Central

Shivade, Chaitanya; Raghavan, Preethi; Fosler-Lussier, Eric; Embi, Peter J; Elhadad, Noemie; Johnson, Stephen B; Lai, Albert M

2014-01-01

Objective To summarize literature describing approaches aimed at automatically identifying patients with a common phenotype. Materials and methods We performed a review of studies describing systems or reporting techniques developed for identifying cohorts of patients with specific phenotypes. Every full text article published in (1) Journal of American Medical Informatics Association, (2) Journal of Biomedical Informatics, (3) Proceedings of the Annual American Medical Informatics Association Symposium, and (4) Proceedings of Clinical Research Informatics Conference within the past 3 years was assessed for inclusion in the review. Only articles using automated techniques were included. Results Ninety-seven articles met our inclusion criteria. Forty-six used natural language processing (NLP)-based techniques, 24 described rule-based systems, 41 used statistical analyses, data mining, or machine learning techniques, while 22 described hybrid systems. Nine articles described the architecture of large-scale systems developed for determining cohort eligibility of patients. Discussion We observe that there is a rise in the number of studies associated with cohort identification using electronic medical records. Statistical analyses or machine learning, followed by NLP techniques, are gaining popularity over the years in comparison with rule-based systems. Conclusions There are a variety of approaches for classifying patients into a particular phenotype. Different techniques and data sources are used, and good performance is reported on datasets at respective institutions. However, no system makes comprehensive use of electronic medical records addressing all of their known weaknesses. PMID:24201027

Identifying Effectiveness Criteria for Internet Payment Systems.

ERIC Educational Resources Information Center

Shon, Tae-Hwan; Swatman, Paula M. C.

1998-01-01

Examines Internet payment systems (IPS): third-party, card, secure Web server, electronic token, financial electronic data interchange (EDI), and micropayment based. Reports the results of a Delphi survey of experts identifying and classifying IPS effectiveness criteria and classifying types of IPS providers. Includes the survey invitation letter…

Tiered High-Throughput Screening Approach to Identify ...

EPA Pesticide Factsheets

High-throughput screening (HTS) for potential thyroid–disrupting chemicals requires a system of assays to capture multiple molecular-initiating events (MIEs) that converge on perturbed thyroid hormone (TH) homeostasis. Screening for MIEs specific to TH-disrupting pathways is limited in the US EPA ToxCast screening assay portfolio. To fill one critical screening gap, the Amplex UltraRed-thyroperoxidase (AUR-TPO) assay was developed to identify chemicals that inhibit TPO, as decreased TPO activity reduces TH synthesis. The ToxCast Phase I and II chemical libraries, comprised of 1,074 unique chemicals, were initially screened using a single, high concentration to identify potential TPO inhibitors. Chemicals positive in the single concentration screen were retested in concentration-response. Due to high false positive rates typically observed with loss-of-signal assays such as AUR-TPO, we also employed two additional assays in parallel to identify possible sources of nonspecific assay signal loss, enabling stratification of roughly 300 putative TPO inhibitors based upon selective AUR-TPO activity. A cell-free luciferase inhibition assay was used to identify nonspecific enzyme inhibition among the putative TPO inhibitors, and a cytotoxicity assay using a human cell line was used to estimate the cellular tolerance limit. Additionally, the TPO inhibition activities of 150 chemicals were compared between the AUR-TPO and an orthogonal peroxidase oxidation assay using

Structured methodology review identified seven (RETREAT) criteria for selecting qualitative evidence synthesis approaches.

PubMed

Booth, Andrew; Noyes, Jane; Flemming, Kate; Gerhardus, Ansgar; Wahlster, Philip; van der Wilt, Gert Jan; Mozygemba, Kati; Refolo, Pietro; Sacchini, Dario; Tummers, Marcia; Rehfuess, Eva

2018-07-01

To compare and contrast different methods of qualitative evidence synthesis (QES) against criteria identified from the literature and to map their attributes to inform selection of the most appropriate QES method to answer research questions addressed by qualitative research. Electronic databases, citation searching, and a study register were used to identify studies reporting QES methods. Attributes compiled from 26 methodological papers (2001-2014) were used as a framework for data extraction. Data were extracted into summary tables by one reviewer and then considered within the author team. We identified seven considerations determining choice of methods from the methodological literature, encapsulated within the mnemonic Review question-Epistemology-Time/Timescale-Resources-Expertise-Audience and purpose-Type of data. We mapped 15 different published QES methods against these seven criteria. The final framework focuses on stand-alone QES methods but may also hold potential when integrating quantitative and qualitative data. These findings offer a contemporary perspective as a conceptual basis for future empirical investigation of the advantages and disadvantages of different methods of QES. It is hoped that this will inform appropriate selection of QES approaches. Copyright © 2018 Elsevier Inc. All rights reserved.

Effects-Directed Analysis (EDA) and Toxicity Identification Evaluation (TIE): Complementary but Different Approaches for Diagnosing Causes of Environmental Toxicity

EPA Science Inventory

Currently, two approaches are available for performing environmental diagnostics on samples like municipal and industrial effluents, interstitial waters and whole sediments in order to identify anthropogenic contaminants causing toxicological effects. One approach is Toxicity Id...

Identifying Technical Vocabulary

ERIC Educational Resources Information Center

Chung, Teresa Mihwa; Nation, Paul

2004-01-01

This study compared four different approaches to identifying technical words in an anatomy text. The first approach used a four step rating scale, and was used as the comparison for evaluating the other three approaches. It had a high degree of reliability. The least successful approach was that using clues provided by the writer such as labels in…

Identifying typical patterns of vulnerability: A 5-step approach based on cluster analysis

NASA Astrophysics Data System (ADS)

Sietz, Diana; Lüdeke, Matthias; Kok, Marcel; Lucas, Paul; Carsten, Walther; Janssen, Peter

2013-04-01

Specific processes that shape the vulnerability of socio-ecological systems to climate, market and other stresses derive from diverse background conditions. Within the multitude of vulnerability-creating mechanisms, distinct processes recur in various regions inspiring research on typical patterns of vulnerability. The vulnerability patterns display typical combinations of the natural and socio-economic properties that shape a systems' vulnerability to particular stresses. Based on the identification of a limited number of vulnerability patterns, pattern analysis provides an efficient approach to improving our understanding of vulnerability and decision-making for vulnerability reduction. However, current pattern analyses often miss explicit descriptions of their methods and pay insufficient attention to the validity of their groupings. Therefore, the question arises as to how do we identify typical vulnerability patterns in order to enhance our understanding of a systems' vulnerability to stresses? A cluster-based pattern recognition applied at global and local levels is scrutinised with a focus on an applicable methodology and practicable insights. Taking the example of drylands, this presentation demonstrates the conditions necessary to identify typical vulnerability patterns. They are summarised in five methodological steps comprising the elicitation of relevant cause-effect hypotheses and the quantitative indication of mechanisms as well as an evaluation of robustness, a validation and a ranking of the identified patterns. Reflecting scale-dependent opportunities, a global study is able to support decision-making with insights into the up-scaling of interventions when available funds are limited. In contrast, local investigations encourage an outcome-based validation. This constitutes a crucial step in establishing the credibility of the patterns and hence their suitability for informing extension services and individual decisions. In this respect, working at

Collective feature selection to identify crucial epistatic variants.

PubMed

Verma, Shefali S; Lucas, Anastasia; Zhang, Xinyuan; Veturi, Yogasudha; Dudek, Scott; Li, Binglan; Li, Ruowang; Urbanowicz, Ryan; Moore, Jason H; Kim, Dokyoon; Ritchie, Marylyn D

2018-01-01

Machine learning methods have gained popularity and practicality in identifying linear and non-linear effects of variants associated with complex disease/traits. Detection of epistatic interactions still remains a challenge due to the large number of features and relatively small sample size as input, thus leading to the so-called "short fat data" problem. The efficiency of machine learning methods can be increased by limiting the number of input features. Thus, it is very important to perform variable selection before searching for epistasis. Many methods have been evaluated and proposed to perform feature selection, but no single method works best in all scenarios. We demonstrate this by conducting two separate simulation analyses to evaluate the proposed collective feature selection approach. Through our simulation study we propose a collective feature selection approach to select features that are in the "union" of the best performing methods. We explored various parametric, non-parametric, and data mining approaches to perform feature selection. We choose our top performing methods to select the union of the resulting variables based on a user-defined percentage of variants selected from each method to take to downstream analysis. Our simulation analysis shows that non-parametric data mining approaches, such as MDR, may work best under one simulation criteria for the high effect size (penetrance) datasets, while non-parametric methods designed for feature selection, such as Ranger and Gradient boosting, work best under other simulation criteria. Thus, using a collective approach proves to be more beneficial for selecting variables with epistatic effects also in low effect size datasets and different genetic architectures. Following this, we applied our proposed collective feature selection approach to select the top 1% of variables to identify potential interacting variables associated with Body Mass Index (BMI) in ~ 44,000 samples obtained from Geisinger

Partially Identifying Treatment Effects with an Application to Covering the Uninsured

ERIC Educational Resources Information Center

Kreider, Brent; Hill, Steven C.

2009-01-01

We extend the nonparametric literature on partially identified probability distributions and use our analytical results to provide sharp bounds on the impact of universal health insurance on provider visits and medical expenditures. Our approach accounts for uncertainty about the reliability of self-reported insurance status as well as uncertainty…

Reverse Vaccinology: An Approach for Identifying Leptospiral Vaccine Candidates

PubMed Central

Dellagostin, Odir A.; Grassmann, André A.; Rizzi, Caroline; Schuch, Rodrigo A.; Jorge, Sérgio; Oliveira, Thais L.; McBride, Alan J. A.; Hartwig, Daiane D.

2017-01-01

Leptospirosis is a major public health problem with an incidence of over one million human cases each year. It is a globally distributed, zoonotic disease and is associated with significant economic losses in farm animals. Leptospirosis is caused by pathogenic Leptospira spp. that can infect a wide range of domestic and wild animals. Given the inability to control the cycle of transmission among animals and humans, there is an urgent demand for a new vaccine. Inactivated whole-cell vaccines (bacterins) are routinely used in livestock and domestic animals, however, protection is serovar-restricted and short-term only. To overcome these limitations, efforts have focused on the development of recombinant vaccines, with partial success. Reverse vaccinology (RV) has been successfully applied to many infectious diseases. A growing number of leptospiral genome sequences are now available in public databases, providing an opportunity to search for prospective vaccine antigens using RV. Several promising leptospiral antigens were identified using this approach, although only a few have been characterized and evaluated in animal models. In this review, we summarize the use of RV for leptospirosis and discuss the need for potential improvements for the successful development of a new vaccine towards reducing the burden of human and animal leptospirosis. PMID:28098813

A Sparse Reconstruction Approach for Identifying Gene Regulatory Networks Using Steady-State Experiment Data

PubMed Central

Zhang, Wanhong; Zhou, Tong

2015-01-01

Motivation Identifying gene regulatory networks (GRNs) which consist of a large number of interacting units has become a problem of paramount importance in systems biology. Situations exist extensively in which causal interacting relationships among these units are required to be reconstructed from measured expression data and other a priori information. Though numerous classical methods have been developed to unravel the interactions of GRNs, these methods either have higher computing complexities or have lower estimation accuracies. Note that great similarities exist between identification of genes that directly regulate a specific gene and a sparse vector reconstruction, which often relates to the determination of the number, location and magnitude of nonzero entries of an unknown vector by solving an underdetermined system of linear equations y = Φx. Based on these similarities, we propose a novel framework of sparse reconstruction to identify the structure of a GRN, so as to increase accuracy of causal regulation estimations, as well as to reduce their computational complexity. Results In this paper, a sparse reconstruction framework is proposed on basis of steady-state experiment data to identify GRN structure. Different from traditional methods, this approach is adopted which is well suitable for a large-scale underdetermined problem in inferring a sparse vector. We investigate how to combine the noisy steady-state experiment data and a sparse reconstruction algorithm to identify causal relationships. Efficiency of this method is tested by an artificial linear network, a mitogen-activated protein kinase (MAPK) pathway network and the in silico networks of the DREAM challenges. The performance of the suggested approach is compared with two state-of-the-art algorithms, the widely adopted total least-squares (TLS) method and those available results on the DREAM project. Actual results show that, with a lower computational cost, the proposed method can

Determining the optimal approach to identifying individuals with chronic obstructive pulmonary disease: The DOC study.

PubMed

Ronaldson, Sarah J; Dyson, Lisa; Clark, Laura; Hewitt, Catherine E; Torgerson, David J; Cooper, Brendan G; Kearney, Matt; Laughey, William; Raghunath, Raghu; Steele, Lisa; Rhodes, Rebecca; Adamson, Joy

2018-06-01

Early identification of chronic obstructive pulmonary disease (COPD) results in patients receiving appropriate management for their condition at an earlier stage in their disease. The determining the optimal approach to identifying individuals with chronic obstructive pulmonary disease (DOC) study was a case-finding study to enhance early identification of COPD in primary care, which evaluated the diagnostic accuracy of a series of simple lung function tests and symptom-based case-finding questionnaires. Current smokers aged 35 or more were invited to undertake a series of case-finding tools, which comprised lung function tests (specifically, spirometry, microspirometry, peak flow meter, and WheezoMeter) and several case-finding questionnaires. The effectiveness of these tests, individually or in combination, to identify small airways obstruction was evaluated against the gold standard of spirometry, with the quality of spirometry tests assessed by independent overreaders. The study was conducted with general practices in the Yorkshire and Humberside area, in the UK. Six hundred eighty-one individuals met the inclusion criteria, with 444 participants completing their study appointments. A total of 216 (49%) with good-quality spirometry readings were included in the analysis. The most effective case-finding tools were found to be the peak flow meter alone, the peak flow meter plus WheezoMeter, and microspirometry alone. In addition to the main analysis, where the severity of airflow obstruction was based on fixed ratios and percent of predicted values, sensitivity analyses were conducted by using lower limit of normal values. This research informs the choice of test for COPD identification; case-finding by use of the peak flow meter or microspirometer could be used routinely in primary care for suspected COPD patients. Only those testing positive to these tests would move on to full spirometry, thereby reducing unnecessary spirometric testing. © 2018 John Wiley

Approaches to Identifying the Emerging Innovative Water Technology Industry in the United States

PubMed Central

WOOD, ALLISON R.; HARTEN, TERESA; GUTIERREZ, SALLY C.

2018-01-01

Clean water is vital to sustaining our natural environment, human health, and our economy. As infrastructure continues to deteriorate and water resources become increasingly threatened, new technologies will be needed to ensure safe and sustainable water in the future. Though the US water industry accounts for approximately 1% gross domestic product and regional “clusters” for water technology exist throughout the country, this emerging industry has not been captured by recent studies. As use of the term “cluster” becomes more prevalent, regional mapping efforts have revealed international differences in definition yet showcase this industry’s economic impact. In reality, institutional processes may inhibit altering industry coding to better describe water technology. Forgoing the benefits of national economic tracking, alternative data sets are available, which may support new ways of identifying these clusters. This work provides cluster definitions; summarizes current approaches to identifying industry activity using data, interviews, and literature; and sets a foundation for future research. PMID:29937546

Approaches to Identifying the Emerging Innovative Water Technology Industry in the United States.

PubMed

Wood, Allison R; Harten, Teresa; Gutierrez, Sally C

2018-04-25

Clean water is vital to sustaining our natural environment, human health, and our economy. As infrastructure continues to deteriorate and water resources become increasingly threatened, new technologies will be needed to ensure safe and sustainable water in the future. Though the US water industry accounts for approximately 1% gross domestic product and regional "clusters" for water technology exist throughout the country, this emerging industry has not been captured by recent studies. As use of the term "cluster" becomes more prevalent, regional mapping efforts have revealed international differences in definition yet showcase this industry's economic impact. In reality, institutional processes may inhibit altering industry coding to better describe water technology. Forgoing the benefits of national economic tracking, alternative data sets are available, which may support new ways of identifying these clusters. This work provides cluster definitions; summarizes current approaches to identifying industry activity using data, interviews, and literature; and sets a foundation for future research.

A novel approach identifying hybrid sterility QTL on the autosomes of Drosophila simulans and D. mauritiana.

PubMed

Dickman, Christopher T D; Moehring, Amanda J

2013-01-01

When species interbreed, the hybrid offspring that are produced are often sterile. If only one hybrid sex is sterile, it is almost always the heterogametic (XY or ZW) sex. Taking this trend into account, the predominant model used to explain the genetic basis of F1 sterility involves a deleterious interaction between recessive sex-linked loci from one species and dominant autosomal loci from the other species. This model is difficult to evaluate, however, as only a handful of loci influencing interspecies hybrid sterility have been identified, and their autosomal genetic interactors have remained elusive. One hindrance to their identification has been the overwhelming effect of the sex chromosome in mapping studies, which could 'mask' the ability to accurately map autosomal factors. Here, we use a novel approach employing attached-X chromosomes to create reciprocal backcross interspecies hybrid males that have a non-recombinant sex chromosome and recombinant autosomes. The heritable variation in phenotype is thus solely caused by differences in the autosomes, thereby allowing us to accurately identify the number and location of autosomal sterility loci. In one direction of backcross, all males were sterile, indicating that sterility could be entirely induced by the sex chromosome complement in these males. In the other direction, we identified nine quantitative trait loci that account for a surprisingly large amount (56%) of the autosome-induced phenotypic variance in sterility, with a large contribution of autosome-autosome epistatic interactions. These loci are capable of acting dominantly, and thus could contribute to F1 hybrid sterility.

Pharmacophore Based Virtual Screening Approach to Identify Selective PDE4B Inhibitors

PubMed Central

Gaurav, Anand; Gautam, Vertika

2017-01-01

Phosphodiesterase 4 (PDE4) has been established as a promising target in asthma and chronic obstructive pulmonary disease. PDE4B subtype selective inhibitors are known to reduce the dose limiting adverse effect associated with non-selective PDE4B inhibitors. This makes the development of PDE4B subtype selective inhibitors a desirable research goal. To achieve this goal, ligand based pharmacophore modeling approach is employed. Separate pharmacophore hypotheses for PDE4B and PDE4D inhibitors were generated using HypoGen algorithm and 106 PDE4 inhibitors from literature having thiopyrano [3,2-d] Pyrimidines, 2-arylpyrimidines, and triazines skeleton. Suitable training and test sets were created using the molecules as per the guidelines available for HypoGen program. Training set was used for hypothesis development while test set was used for validation purpose. Fisher validation was also used to test the significance of the developed hypothesis. The validated pharmacophore hypotheses for PDE4B and PDE4D inhibitors were used in sequential virtual screening of zinc database of drug like molecules to identify selective PDE4B inhibitors. The hits were screened for their estimated activity and fit value. The top hit was subjected to docking into the active sites of PDE4B and PDE4D to confirm its selectivity for PDE4B. The hits are proposed to be evaluated further using in-vitro assays. PMID:29201082

Mixed Integer Linear Programming based machine learning approach identifies regulators of telomerase in yeast.

PubMed

Poos, Alexandra M; Maicher, André; Dieckmann, Anna K; Oswald, Marcus; Eils, Roland; Kupiec, Martin; Luke, Brian; König, Rainer

2016-06-02

Understanding telomere length maintenance mechanisms is central in cancer biology as their dysregulation is one of the hallmarks for immortalization of cancer cells. Important for this well-balanced control is the transcriptional regulation of the telomerase genes. We integrated Mixed Integer Linear Programming models into a comparative machine learning based approach to identify regulatory interactions that best explain the discrepancy of telomerase transcript levels in yeast mutants with deleted regulators showing aberrant telomere length, when compared to mutants with normal telomere length. We uncover novel regulators of telomerase expression, several of which affect histone levels or modifications. In particular, our results point to the transcription factors Sum1, Hst1 and Srb2 as being important for the regulation of EST1 transcription, and we validated the effect of Sum1 experimentally. We compiled our machine learning method leading to a user friendly package for R which can straightforwardly be applied to similar problems integrating gene regulator binding information and expression profiles of samples of e.g. different phenotypes, diseases or treatments. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Identifying the Effects of Environmental and Policy Change Interventions on Healthy Eating

PubMed Central

Bowen, Deborah J.; Barrington, Wendy E.; Beresford, Shirley A.A.

2015-01-01

Obesity has been characterized as a disease. Strategies to change the incidence and prevalence of this disease include a focus on changing physical and social environments, over and above individual-level strategies, using a multilevel or systems approach. We focus our attention on evidence published between 2008 and 2013 on the effectiveness of interventions in nutrition environments, i.e., environmental interventions designed to influence the intake of healthful foods and amount of energy consumed. An overarching socioecological framework that has guided much of this research was used to characterize different types of environmental strategies. Intervention examples in each area of the framework are provided with a discussion of key findings and related conceptual and methodological issues. The emphasis in this review is on adults, but clearly this literature is only one part of the picture. Much research has been focused on child-specific interventions, including environmental interventions. Some evidence suggests effectiveness of policy-based or other types of interventions that aim to regulate or restructure environments to promote healthy dietary choices, and these strategies would apply to both children and adults. Opportunities to evaluate these policy changes in adults’ social and physical environments are rare. Much of the existing research has been with children. As conceptual and methodological issues continue to be identified and resolved, we hope that future research in this domain will identify environmental strategies that can be included in intervention toolboxes to build healthy nutrition environments for both adults and children. PMID:25785891

Identifying the effects of environmental and policy change interventions on healthy eating.

PubMed

Bowen, Deborah J; Barrington, Wendy E; Beresford, Shirley A A

2015-03-18

Obesity has been characterized as a disease. Strategies to change the incidence and prevalence of this disease include a focus on changing physical and social environments, over and above individual-level strategies, using a multilevel or systems approach. We focus our attention on evidence published between 2008 and 2013 on the effectiveness of interventions in nutrition environments, i.e., environmental interventions designed to influence the intake of healthful foods and amount of energy consumed. An overarching socioecological framework that has guided much of this research was used to characterize different types of environmental strategies. Intervention examples in each area of the framework are provided with a discussion of key findings and related conceptual and methodological issues. The emphasis in this review is on adults, but clearly this literature is only one part of the picture. Much research has been focused on child-specific interventions, including environmental interventions. Some evidence suggests effectiveness of policy-based or other types of interventions that aim to regulate or restructure environments to promote healthy dietary choices, and these strategies would apply to both children and adults. Opportunities to evaluate these policy changes in adults' social and physical environments are rare. Much of the existing research has been with children. As conceptual and methodological issues continue to be identified and resolved, we hope that future research in this domain will identify environmental strategies that can be included in intervention toolboxes to build healthy nutrition environments for both adults and children.

Identifying determinants of medication adherence following myocardial infarction using the Theoretical Domains Framework and the Health Action Process Approach.

PubMed

Presseau, Justin; Schwalm, J D; Grimshaw, Jeremy M; Witteman, Holly O; Natarajan, Madhu K; Linklater, Stefanie; Sullivan, Katrina; Ivers, Noah M

2017-10-01

Despite evidence-based recommendations, adherence with secondary prevention medications post-myocardial infarction (MI) remains low. Taking medication requires behaviour change, and using behavioural theories to identify what factors determine adherence could help to develop novel adherence interventions. Compare the utility of different behaviour theory-based approaches for identifying modifiable determinants of medication adherence post-MI that could be targeted by interventions. Two studies were conducted with patients 0-2, 3-12, 13-24 or 25-36 weeks post-MI. Study 1: 24 patients were interviewed about barriers and facilitators to medication adherence. Interviews were conducted and coded using the Theoretical Domains Framework. Study 2: 201 patients answered a telephone questionnaire assessing Health Action Process Approach constructs to predict intention and medication adherence (MMAS-8). Study 1: domains identified: Beliefs about Consequences, Memory/Attention/Decision Processes, Behavioural Regulation, Social Influences and Social Identity. Study 2: 64, 59, 42 and 58% reported high adherence at 0-2, 3-12, 13-24 and 25-36 weeks. Social Support and Action Planning predicted adherence at all time points, though the relationship between Action Planning and adherence decreased over time. Using two behaviour theory-based approaches provided complimentary findings and identified modifiable factors that could be targeted to help translate Intention into action to improve medication adherence post-MI.

An integrated approach to identify the origin of PM10 exceedances.

PubMed

Amodio, M; Andriani, E; de Gennaro, G; Demarinis Loiotile, A; Di Gilio, A; Placentino, M C

2012-09-01

This study was aimed to the development of an integrated approach for the characterization of particulate matter (PM) pollution events in the South of Italy. PM(10) and PM(2.5) daily samples were collected from June to November 2008 at an urban background site located in Bari (Puglia Region, South of Italy). Meteorological data, particle size distributions and atmospheric dispersion conditions were also monitored in order to provide information concerning the different features of PM sources. The collected data allowed suggesting four indicators to characterize different PM(10) exceedances. PM(2.5)/PM(10) ratio, natural radioactivity, aerosol maps and back-trajectory analysis and particle distributions were considered in order to evaluate the contribution of local anthropogenic sources and to determine the different origins of intrusive air mass coming from long-range transport, such as African dust outbreaks and aerosol particles from Central and Eastern Europe. The obtained results were confirmed by applying principal component analysis to the number particle concentration dataset and by the chemical characterization of the samples (PM(10) and PM(2.5)). The integrated approach for PM study suggested in this paper can be useful to support the air quality managers for the development of cost-effective control strategies and the application of more suitable risk management approaches.

Identifying an influential spreader from a single seed in complex networks via a message-passing approach

NASA Astrophysics Data System (ADS)

Min, Byungjoon

2018-01-01

Identifying the most influential spreaders is one of outstanding problems in physics of complex systems. So far, many approaches have attempted to rank the influence of nodes but there is still the lack of accuracy to single out influential spreaders. Here, we directly tackle the problem of finding important spreaders by solving analytically the expected size of epidemic outbreaks when spreading originates from a single seed. We derive and validate a theory for calculating the size of epidemic outbreaks with a single seed using a message-passing approach. In addition, we find that the probability to occur epidemic outbreaks is highly dependent on the location of the seed but the size of epidemic outbreaks once it occurs is insensitive to the seed. We also show that our approach can be successfully adapted into weighted networks.

Identifying Useful Auxiliary Variables for Incomplete Data Analyses: A Note on a Group Difference Examination Approach

ERIC Educational Resources Information Center

Raykov, Tenko; Marcoulides, George A.

2014-01-01

This research note contributes to the discussion of methods that can be used to identify useful auxiliary variables for analyses of incomplete data sets. A latent variable approach is discussed, which is helpful in finding auxiliary variables with the property that if included in subsequent maximum likelihood analyses they may enhance considerably…

Identifying cut points for biomarker defined subset effects in clinical trials with survival endpoints.

PubMed

He, Pei

2014-07-01

The advancements in biotechnology and genetics lead to an increasing research interest in personalized medicine, where a patient's genetic profile or biological traits contribute to choosing the most effective treatment for the patient. The process starts with finding a specific biomarker among all possible candidates that can best predict the treatment effect. After a biomarker is chosen, identifying a cut point of the biomarker value that splits the patients into treatment effective and non-effective subgroups becomes an important scientific problem. Numerous methods have been proposed to validate the predictive marker and select the appropriate cut points either prospectively or retrospectively using clinical trial data. In trials with survival outcomes, the current practice applies an interaction testing procedure and chooses the cut point that minimizes the p-values for the tests. Such method assumes independence between the baseline hazard and biomarker value. In reality, however, this assumption is often violated, as the chosen biomarker might also be prognostic in addition to its predictive nature for treatment effect. In this paper we propose a block-wise estimation and a sequential testing approach to identify the cut point in biomarkers that can group the patients into subsets based on their distinct treatment outcomes without assuming independence between the biomarker and baseline hazard. Numerical results based on simulated survival data show that the proposed method could pinpoint accurately the cut points in biomarker values that separate the patient subpopulations into subgroups with distinctive treatment outcomes. Copyright © 2014 Elsevier Inc. All rights reserved.

An Integrative Genetics Approach to Identify Candidate Genes Regulating BMD: Combining Linkage, Gene Expression, and Association

PubMed Central

Farber, Charles R; van Nas, Atila; Ghazalpour, Anatole; Aten, Jason E; Doss, Sudheer; Sos, Brandon; Schadt, Eric E; Ingram-Drake, Leslie; Davis, Richard C; Horvath, Steve; Smith, Desmond J; Drake, Thomas A; Lusis, Aldons J

2009-01-01

Numerous quantitative trait loci (QTLs) affecting bone traits have been identified in the mouse; however, few of the underlying genes have been discovered. To improve the process of transitioning from QTL to gene, we describe an integrative genetics approach, which combines linkage analysis, expression QTL (eQTL) mapping, causality modeling, and genetic association in outbred mice. In C57BL/6J × C3H/HeJ (BXH) F2 mice, nine QTLs regulating femoral BMD were identified. To select candidate genes from within each QTL region, microarray gene expression profiles from individual F2 mice were used to identify 148 genes whose expression was correlated with BMD and regulated by local eQTLs. Many of the genes that were the most highly correlated with BMD have been previously shown to modulate bone mass or skeletal development. Candidates were further prioritized by determining whether their expression was predicted to underlie variation in BMD. Using network edge orienting (NEO), a causality modeling algorithm, 18 of the 148 candidates were predicted to be causally related to differences in BMD. To fine-map QTLs, markers in outbred MF1 mice were tested for association with BMD. Three chromosome 11 SNPs were identified that were associated with BMD within the Bmd11 QTL. Finally, our approach provides strong support for Wnt9a, Rasd1, or both underlying Bmd11. Integration of multiple genetic and genomic data sets can substantially improve the efficiency of QTL fine-mapping and candidate gene identification. PMID:18767929

Assessment Approach for Identifying Compatibility of Restoration Projects with Geomorphic and Flooding Processes in Gravel Bed Rivers

NASA Astrophysics Data System (ADS)

DeVries, Paul; Aldrich, Robert

2015-08-01

A critical requirement for a successful river restoration project in a dynamic gravel bed river is that it be compatible with natural hydraulic and sediment transport processes operating at the reach scale. The potential for failure is greater at locations where the influence of natural processes is inconsistent with intended project function and performance. We present an approach using practical GIS, hydrologic, hydraulic, and sediment transport analyses to identify locations where specific restoration project types have the greatest likelihood of working as intended because their function and design are matched with flooding and morphologic processes. The key premise is to identify whether a specific river analysis segment (length ~1-10 bankfull widths) within a longer reach is geomorphically active or inactive in the context of vertical and lateral stabilities, and hydrologically active for floodplain connectivity. Analyses involve empirical channel geometry relations, aerial photographic time series, LiDAR data, HEC-RAS hydraulic modeling, and a time-integrated sediment transport budget to evaluate trapping efficiency within each segment. The analysis segments are defined by HEC-RAS model cross sections. The results have been used effectively to identify feasible projects in a variety of alluvial gravel bed river reaches with lengths between 11 and 80 km and 2-year flood magnitudes between ~350 and 1330 m3/s. Projects constructed based on the results have all performed as planned. In addition, the results provide key criteria for formulating erosion and flood management plans.

Assessment Approach for Identifying Compatibility of Restoration Projects with Geomorphic and Flooding Processes in Gravel Bed Rivers.

PubMed

DeVries, Paul; Aldrich, Robert

2015-08-01

A critical requirement for a successful river restoration project in a dynamic gravel bed river is that it be compatible with natural hydraulic and sediment transport processes operating at the reach scale. The potential for failure is greater at locations where the influence of natural processes is inconsistent with intended project function and performance. We present an approach using practical GIS, hydrologic, hydraulic, and sediment transport analyses to identify locations where specific restoration project types have the greatest likelihood of working as intended because their function and design are matched with flooding and morphologic processes. The key premise is to identify whether a specific river analysis segment (length ~1-10 bankfull widths) within a longer reach is geomorphically active or inactive in the context of vertical and lateral stabilities, and hydrologically active for floodplain connectivity. Analyses involve empirical channel geometry relations, aerial photographic time series, LiDAR data, HEC-RAS hydraulic modeling, and a time-integrated sediment transport budget to evaluate trapping efficiency within each segment. The analysis segments are defined by HEC-RAS model cross sections. The results have been used effectively to identify feasible projects in a variety of alluvial gravel bed river reaches with lengths between 11 and 80 km and 2-year flood magnitudes between ~350 and 1330 m(3)/s. Projects constructed based on the results have all performed as planned. In addition, the results provide key criteria for formulating erosion and flood management plans.

Chemical proteomics approaches for identifying the cellular targets of natural products

PubMed Central

Sieber, S. A.

2016-01-01

Covering: 2010 up to 2016 Deconvoluting the mode of action of natural products and drugs remains one of the biggest challenges in chemistry and biology today. Chemical proteomics is a growing area of chemical biology that seeks to design small molecule probes to understand protein function. In the context of natural products, chemical proteomics can be used to identify the protein binding partners or targets of small molecules in live cells. Here, we highlight recent examples of chemical probes based on natural products and their application for target identification. The review focuses on probes that can be covalently linked to their target proteins (either via intrinsic chemical reactivity or via the introduction of photocrosslinkers), and can be applied “in situ” – in living systems rather than cell lysates. We also focus here on strategies that employ a click reaction, the copper-catalysed azide–alkyne cycloaddition reaction (CuAAC), to allow minimal functionalisation of natural product scaffolds with an alkyne or azide tag. We also discuss ‘competitive mode’ approaches that screen for natural products that compete with a well-characterised chemical probe for binding to a particular set of protein targets. Fuelled by advances in mass spectrometry instrumentation and bioinformatics, many modern strategies are now embracing quantitative proteomics to help define the true interacting partners of probes, and we highlight the opportunities this rapidly evolving technology provides in chemical proteomics. Finally, some of the limitations and challenges of chemical proteomics approaches are discussed. PMID:27098809

Chemical proteomics approaches for identifying the cellular targets of natural products.

PubMed

Wright, M H; Sieber, S A

2016-05-04

Covering: 2010 up to 2016Deconvoluting the mode of action of natural products and drugs remains one of the biggest challenges in chemistry and biology today. Chemical proteomics is a growing area of chemical biology that seeks to design small molecule probes to understand protein function. In the context of natural products, chemical proteomics can be used to identify the protein binding partners or targets of small molecules in live cells. Here, we highlight recent examples of chemical probes based on natural products and their application for target identification. The review focuses on probes that can be covalently linked to their target proteins (either via intrinsic chemical reactivity or via the introduction of photocrosslinkers), and can be applied "in situ" - in living systems rather than cell lysates. We also focus here on strategies that employ a click reaction, the copper-catalysed azide-alkyne cycloaddition reaction (CuAAC), to allow minimal functionalisation of natural product scaffolds with an alkyne or azide tag. We also discuss 'competitive mode' approaches that screen for natural products that compete with a well-characterised chemical probe for binding to a particular set of protein targets. Fuelled by advances in mass spectrometry instrumentation and bioinformatics, many modern strategies are now embracing quantitative proteomics to help define the true interacting partners of probes, and we highlight the opportunities this rapidly evolving technology provides in chemical proteomics. Finally, some of the limitations and challenges of chemical proteomics approaches are discussed.

Modelling the mating system of polar bears: a mechanistic approach to the Allee effect.

PubMed

Molnár, Péter K; Derocher, Andrew E; Lewis, Mark A; Taylor, Mitchell K

2008-01-22

Allee effects may render exploited animal populations extinction prone, but empirical data are often lacking to describe the circumstances leading to an Allee effect. Arbitrary assumptions regarding Allee effects could lead to erroneous management decisions so that predictive modelling approaches are needed that identify the circumstances leading to an Allee effect before such a scenario occurs. We present a predictive approach of Allee effects for polar bears where low population densities, an unpredictable habitat and harvest-depleted male populations result in infrequent mating encounters. We develop a mechanistic model for the polar bear mating system that predicts the proportion of fertilized females at the end of the mating season given population density and operational sex ratio. The model is parametrized using pairing data from Lancaster Sound, Canada, and describes the observed pairing dynamics well. Female mating success is shown to be a nonlinear function of the operational sex ratio, so that a sudden and rapid reproductive collapse could occur if males are severely depleted. The operational sex ratio where an Allee effect is expected is dependent on population density. We focus on the prediction of Allee effects in polar bears but our approach is also applicable to other species.

A Multiplexed High-Content Screening Approach Using the Chromobody Technology to Identify Cell Cycle Modulators in Living Cells.

PubMed

Schorpp, Kenji; Rothenaigner, Ina; Maier, Julia; Traenkle, Bjoern; Rothbauer, Ulrich; Hadian, Kamyar

2016-10-01

Many screening hits show relatively poor quality regarding later efficacy and safety. Therefore, small-molecule screening efforts shift toward high-content analysis providing more detailed information. Here, we describe a novel screening approach to identify cell cycle modulators with low toxicity by combining the Cell Cycle Chromobody (CCC) technology with the CytoTox-Glo (CTG) cytotoxicity assay. The CCC technology employs intracellularly functional single-domain antibodies coupled to a fluorescent protein (chromobodies) to visualize the cell cycle-dependent redistribution of the proliferating cell nuclear antigen (PCNA) in living cells. This image-based cell cycle analysis was combined with determination of dead-cell protease activity in cell culture supernatants by the CTG assay. We adopted this multiplex approach to high-throughput format and screened 960 Food and Drug Administration (FDA)-approved drugs. By this, we identified nontoxic compounds, which modulate different cell cycle stages, and validated selected hits in diverse cell lines stably expressing CCC. Additionally, we independently validated these hits by flow cytometry as the current state-of-the-art format for cell cycle analysis. This study demonstrates that CCC imaging is a versatile high-content screening approach to identify cell cycle modulators, which can be multiplexed with cytotoxicity assays for early elimination of toxic compounds during screening. © 2016 Society for Laboratory Automation and Screening.

To be or not to be associated: power study of four statistical modeling approaches to identify parasite associations in cross-sectional studies

PubMed Central

Vaumourin, Elise; Vourc'h, Gwenaël; Telfer, Sandra; Lambin, Xavier; Salih, Diaeldin; Seitzer, Ulrike; Morand, Serge; Charbonnel, Nathalie; Vayssier-Taussat, Muriel; Gasqui, Patrick

2014-01-01

A growing number of studies are reporting simultaneous infections by parasites in many different hosts. The detection of whether these parasites are significantly associated is important in medicine and epidemiology. Numerous approaches to detect associations are available, but only a few provide statistical tests. Furthermore, they generally test for an overall detection of association and do not identify which parasite is associated with which other one. Here, we developed a new approach, the association screening approach, to detect the overall and the detail of multi-parasite associations. We studied the power of this new approach and of three other known ones (i.e., the generalized chi-square, the network and the multinomial GLM approaches) to identify parasite associations either due to parasite interactions or to confounding factors. We applied these four approaches to detect associations within two populations of multi-infected hosts: (1) rodents infected with Bartonella sp., Babesia microti and Anaplasma phagocytophilum and (2) bovine population infected with Theileria sp. and Babesia sp. We found that the best power is obtained with the screening model and the generalized chi-square test. The differentiation between associations, which are due to confounding factors and parasite interactions was not possible. The screening approach significantly identified associations between Bartonella doshiae and B. microti, and between T. parva, T. mutans, and T. velifera. Thus, the screening approach was relevant to test the overall presence of parasite associations and identify the parasite combinations that are significantly over- or under-represented. Unraveling whether the associations are due to real biological interactions or confounding factors should be further investigated. Nevertheless, in the age of genomics and the advent of new technologies, it is a considerable asset to speed up researches focusing on the mechanisms driving interactions between

Identifying nitrogen sources to thermal tide pools in Kapoho, Hawai'i, U.S.A, using a multi-stable isotope approach.

PubMed

Wiegner, Tracy N; Mokiao-Lee, Ambyr U; Johnson, Erik E

2016-02-15

Nitrogen (N) enrichment often results in coastal eutrophication, even in remote areas like Hawai'i. Therefore, determining N sources to coastal waters is important for their management. This study identified N sources to tide pools in Kapoho, Hawai'i, and determined their relative importance using three stable isotopes (δ(15)N, δ(18)O, δ(11)B). Surface waters and macroalgal tissues were collected along 100-m onshore-offshore transects in areas of high groundwater input for three months at low tide. Water samples from possible N sources were also collected. Mixing model output, along with macroalgal δ(15)N values, indicated that agriculture soil (34%) was the largest anthropogenic N source followed by sewage (27%). These findings suggest that more effective fertilizer application techniques and upgrading sewage treatment systems can minimize N leaching into groundwater. Overall, our multi-stable isotope approach for identifying N sources was successful and may be useful in other coastal waters. Copyright © 2015 Elsevier Ltd. All rights reserved.

Integrative screening approach identifies regulators of polyploidization and targets for acute megakaryocytic leukemia

PubMed Central

Wen, Qiang; Goldenson, Benjamin; Silver, Serena J.; Schenone, Monica; Dancik, Vladimir; Huang, Zan; Wang, Ling-Zhi; Lewis, Timothy; An, W. Frank; Li, Xiaoyu; Bray, Mark-Anthony; Thiollier, Clarisse; Diebold, Lauren; Gilles, Laure; Vokes, Martha S.; Moore, Christopher B.; Bliss-Moreau, Meghan; VerPlank, Lynn; Tolliday, Nicola J.; Mishra, Rama; Vemula, Sasidhar; Shi, Jianjian; Wei, Lei; Kapur, Reuben; Lopez, Cécile K.; Gerby, Bastien; Ballerini, Paola; Pflumio, Francoise; Gilliland, D. Gary; Goldberg, Liat; Birger, Yehudit; Izraeli, Shai; Gamis, Alan S.; Smith, Franklin O.; Woods, William G.; Taub, Jeffrey; Scherer, Christina A.; Bradner, James; Goh, Boon-Cher; Mercher, Thomas; Carpenter, Anne E.; Gould, Robert J.; Clemons, Paul A.; Carr, Steven A.; Root, David E.; Schreiber, Stuart L.; Stern, Andrew M.; Crispino, John D.

2012-01-01

Summary The mechanism by which cells decide to skip mitosis to become polyploid is largely undefined. Here we used a high-content image-based screen to identify small-molecule probes that induce polyploidization of megakaryocytic leukemia cells and serve as perturbagens to help understand this process. We found that dimethylfasudil (diMF, H-1152P) selectively increased polyploidization, mature cell-surface marker expression, and apoptosis of malignant megakaryocytes. A broadly applicable, highly integrated target identification approach employing proteomic and shRNA screening revealed that a major target of diMF is Aurora A kinase (AURKA), which has not been studied extensively in megakaryocytes. Moreover, we discovered that MLN8237 (Alisertib), a selective inhibitor of AURKA, induced polyploidization and expression of mature megakaryocyte markers in AMKL blasts and displayed potent anti-AMKL activity in vivo. This research provides the rationale to support clinical trials of MLN8237 and other inducers of polyploidization in AMKL. Finally, we have identified five networks of kinases that regulate the switch to polyploidy. PMID:22863010

Evaluation of Bayesian approaches to identify DDT source contributions to soils in Southeast China.

PubMed

Zeng, Faming; Yang, Dan; Xing, Xinli; Qi, Shihua

2017-06-01

Dicofol application may be an important source to elevate the dichlorodiphenyltrichloroethane (DDT) residues to soils in Fujian, Southeast China, after the technical DDT was banned, which left DDT residues from the historical application. The DDT residues varied geographically, corresponding to the varied potential sources of DDT. In this study, a novel approach based on the Bayesian method (BM) was developed to identify the source contributions of DDT to soils, composed with both historical DDT and dicofol. The Naive Bayesian classifier was used basing on the subset of the samples, which were determined by chemical analysis independent of the Bayesian approach. The results show that BM (95%) was higher than that using the ratio of o, p'-/p, p'-DDT (84%) to identify DDT source contributions. High detection rate (97%) of dicofol (p, p'-OH-DDT) was observed in the subset, showing dicofol application influenced the DDX levels in soils in Fujian. However, the contribution from historical technical DDT source was greater than that from dicofol in Fujian, indicating historical technical DDT was still an important pollution source to soils. In addition, both the DDX (DDT isomers and derivatives) level and dicofol contribution in non-agricultural soils were higher than other agricultural land uses, especially in hilly regions, the potential cause may be the atmospheric transport of dicofol type DDT, after spraying during daytime, or regional difference on production and application. Copyright © 2017 Elsevier Ltd. All rights reserved.

Identifying gene networks underlying the neurobiology of ethanol and alcoholism.

PubMed

Wolen, Aaron R; Miles, Michael F

2012-01-01

For complex disorders such as alcoholism, identifying the genes linked to these diseases and their specific roles is difficult. Traditional genetic approaches, such as genetic association studies (including genome-wide association studies) and analyses of quantitative trait loci (QTLs) in both humans and laboratory animals already have helped identify some candidate genes. However, because of technical obstacles, such as the small impact of any individual gene, these approaches only have limited effectiveness in identifying specific genes that contribute to complex diseases. The emerging field of systems biology, which allows for analyses of entire gene networks, may help researchers better elucidate the genetic basis of alcoholism, both in humans and in animal models. Such networks can be identified using approaches such as high-throughput molecular profiling (e.g., through microarray-based gene expression analyses) or strategies referred to as genetical genomics, such as the mapping of expression QTLs (eQTLs). Characterization of gene networks can shed light on the biological pathways underlying complex traits and provide the functional context for identifying those genes that contribute to disease development.

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

EPA Science Inventory

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

A hierarchy of unhealthy food promotion effects: identifying methodological approaches and knowledge gaps.

PubMed

Kelly, Bridget; King MPsy, Lesley; Chapman Mnd, Kathy; Boyland, Emma; Bauman, Adrian E; Baur, Louise A

2015-04-01

We assessed the evidence for a conceptual "hierarchy of effects" of marketing, to guide understanding of the relationship between children's exposure to unhealthy food marketing and poor diets and overweight, and drive the research agenda. We reviewed studies assessing the impact of food promotions on children from MEDLINE, Web of Science, ABI Inform, World Health Organization library database, and The Gray Literature Report. We included articles published in English from 2009 to 2013, with earlier articles from a 2009 systematic review. We grouped articles by outcome of exposure and assessed outcomes within a framework depicting a hierarchy of effects of marketing exposures. Evidence supports a logical sequence of effects linking food promotions to individual-level weight outcomes. Future studies should demonstrate the sustained effects of marketing exposure, and exploit variations in exposures to assess differences in outcomes longitudinally.

A weight-of-evidence approach to identify nanomaterials in consumer products: a case study of nanoparticles in commercial sunscreens.

PubMed

Cuddy, Michael F; Poda, Aimee R; Moser, Robert D; Weiss, Charles A; Cairns, Carolyn; Steevens, Jeffery A

2016-01-01

Nanoscale ingredients in commercial products represent a point of emerging environmental concern due to recent findings that correlate toxicity with small particle size. A weight-of-evidence (WOE) approach based upon multiple lines of evidence (LOE) is developed here to assess nanomaterials as they exist in consumer product formulations, providing a qualitative assessment regarding the presence of nanomaterials, along with a baseline estimate of nanoparticle concentration if nanomaterials do exist. Electron microscopy, analytical separations, and X-ray detection methods were used to identify and characterize nanomaterials in sunscreen formulations. The WOE/LOE approach as applied to four commercial sunscreen products indicated that all four contained at least 10% dispersed primary particles having at least one dimension <100 nm in size. Analytical analyses confirmed that these constituents were comprised of zinc oxide (ZnO) or titanium dioxide (TiO2). The screening approaches developed herein offer a streamlined, facile means to identify potentially hazardous nanomaterial constituents with minimal abrasive processing of the raw material.

An Ensemble Approach for Drug Side Effect Prediction

PubMed Central

Jahid, Md Jamiul; Ruan, Jianhua

2014-01-01

In silico prediction of drug side-effects in early stage of drug development is becoming more popular now days, which not only reduces the time for drug design but also reduces the drug development costs. In this article we propose an ensemble approach to predict drug side-effects of drug molecules based on their chemical structure. Our idea originates from the observation that similar drugs have similar side-effects. Based on this observation we design an ensemble approach that combine the results from different classification models where each model is generated by a different set of similar drugs. We applied our approach to 1385 side-effects in the SIDER database for 888 drugs. Results show that our approach outperformed previously published approaches and standard classifiers. Furthermore, we applied our method to a number of uncharacterized drug molecules in DrugBank database and predict their side-effect profiles for future usage. Results from various sources confirm that our method is able to predict the side-effects for uncharacterized drugs and more importantly able to predict rare side-effects which are often ignored by other approaches. The method described in this article can be useful to predict side-effects in drug design in an early stage to reduce experimental cost and time. PMID:25327524

Identifying spatial priorities for protecting ecosystem services

PubMed Central

Luck, Gary W

2012-01-01

Priorities for protecting ecosystem services must be identified to ensure future human well-being. Approaches to broad-scale spatial prioritization of ecosystem services are becoming increasingly popular and are a vital precursor to identifying locations where further detailed analyses of the management of ecosystem services is required (e.g., examining trade-offs among management actions). Prioritization approaches often examine the spatial congruence between priorities for protecting ecosystem services and priorities for protecting biodiversity; therefore, the spatial prioritization method used is crucial because it will influence the alignment of service protection and conservation goals. While spatial prioritization of ecosystem services and prioritization for conservation share similarities, such as the need to document threats and costs, the former differs substantially from the latter owing to the requirement to measure the following components: supply of services; availability of human-derived alternatives to service provision; capacity to meet beneficiary demand; and site dependency in and scale of service delivery. We review studies that identify broad-scale spatial priorities for managing ecosystem services and demonstrate that researchers have used different approaches and included various measures for identifying priorities, and most studies do not consider all of the components listed above. We describe a conceptual framework for integrating each of these components into spatial prioritization of ecosystem services and illustrate our approach using a worked example for water provision. A fuller characterization of the biophysical and social context for ecosystem services that we call for should improve future prioritization and the identification of locations where ecosystem-service management is especially important or cost effective. PMID:24555017

Metabolomics approach to reduce the Crabtree effect in continuous culture of Saccharomyces cerevisiae.

PubMed

Imura, Makoto; Iwakiri, Ryo; Bamba, Takeshi; Fukusaki, Eiichiro

2018-04-20

The budding yeast Saccharomyces cerevisiae is an important microorganism for fermentation and the food industry. However, during production, S. cerevisiae commonly uses the ethanol fermentation pathway for glucose utilization if excess sugar is present, even in the presence of sufficient oxygen levels. This aerobic ethanol fermentation, referred to as "the Crabtree effect" is one of the most significant reasons for low cell yield. To weaken the Crabtree effect in fed-batch and continuous culture, sugar flow should be limited. In addition, in continuous culture, the dilution rate must be reduced to avoid washing out cells. However, under such conditions, production speed might be sacrificed. It is difficult to solve this problem with the tradeoff between cell yield and production speed by using conventional tactics. However, a metabolomics approach may be an effective way to search for clues regarding metabolic modulation. Therefore, the purpose of this study was to reduce ethanol production in continuous culture of S. cerevisiae at a higher dilution rate through a metabolomics approach. We used a metabolomics analysis to identify metabolites that were drastically increased or decreased in continuous culture when the dilution rate shifted from biomass formation to ethanol fermentation. The individual addition of two of the selected metabolites, fumaric acid and malic acid, reduced ethanol production at a higher dilution rate. This result demonstrates the potential for using metabolomics approaches to identify metabolites that reduce ethanol production in continuous culture at high dilution rates. Copyright © 2018 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Identifying Mentors for Student Employees on Campus

ERIC Educational Resources Information Center

Frock, David

2015-01-01

Purpose: This exploratory research project aims to seek an effective process for identifying supervisors of part-time student employees who also serve in a mentoring capacity. Design/methodology/approach: This paper is based on a review of literature and an evaluation process focused on established traits and functions of mentoring as applied to…

Moving Beyond Drinking to Have a Good Time: a Person-Centered Approach to Identifying Reason Typologies in Legal-Aged College Student Drinkers.

PubMed

Weybright, Elizabeth H; Cooper, Brittany R; Beckmeyer, Jonathon; Bumpus, Matthew F; Hill, Laura G; Agley, Jon

2016-08-01

Alcohol use, reasons for use, and consequences of use continue to be a major concern in college student populations. This is especially true for students of legal drinking age who may experience different reasons for and greater negative consequences of alcohol use than students under 21 years old. Although multiple studies have used person-centered approaches to understand motivations for and ultimately prevent alcohol use, few have identified multiple typologies of reasons for alcohol use. The current study used latent class analysis to identify homogeneous subtypes of reasons for alcohol use and how classification was associated with alcohol-related consequences in college students aged 21 years old and older (N = 2300) from the 2013 Indiana College Substance Use Survey. Four profiles of reasons for alcohol use emerged across males and females: social drinkers, feel good drinkers, relaxed escaping drinkers, and emotion coping drinkers. Although the likelihood of consequences differed across gender, the emotion coping drinkers were more likely to experience all negative consequences, suggesting that it was a high-risk class. In general, this pattern of risk continued with the feel good drinkers and female relaxed escaping drinkers. These results can help optimize college substance use prevention and intervention efforts to (1) identify and understand characteristics of high- and low-risk student drinkers and (2) tailor the content of interventions to those specific profiles resulting in more effective approaches to reducing alcohol use.

An Iterative Approach for Identifying the Causes of Reduced Benthic Macroinvertebrate Diversity in the Willimantic River, Connecticut (Final)

EPA Science Inventory

EPA announced the availability of the final report, An Iterative Approach for Identifying the Causes of Reduced Benthic Macroinvertebrate Diversity in the Willimantic River, Connecticut. This study demonstrates that a screening assessment can help to focus sampling for ...

Identifying Requirements for Effective Human-Automation Teamwork

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

Jeffrey C. Joe; John O'Hara; Heather D. Medema

Previous studies have shown that poorly designed human-automation collaboration, such as poorly designed communication protocols, often leads to problems for the human operators, such as: lack of vigilance, complacency, and loss of skills. These problems often lead to suboptimal system performance. To address this situation, a considerable amount of research has been conducted to improve human-automation collaboration and to make automation function better as a “team player.” Much of this research is based on an understanding of what it means to be a good team player from the perspective of a human team. However, the research is often based onmore » a simplified view of human teams and teamwork. In this study, we sought to better understand the capabilities and limitations of automation from the standpoint of human teams. We first examined human teams to identify the principles for effective teamwork. We next reviewed the research on integrating automation agents and human agents into mixed agent teams to identify the limitations of automation agents to conform to teamwork principles. This research resulted in insights that can lead to more effective human-automation collaboration by enabling a more realistic set of requirements to be developed based on the strengths and limitations of all agents.« less

Integrated pathway-based approach identifies association between genomic regions at CTCF and CACNB2 and schizophrenia.

PubMed

Juraeva, Dilafruz; Haenisch, Britta; Zapatka, Marc; Frank, Josef; Witt, Stephanie H; Mühleisen, Thomas W; Treutlein, Jens; Strohmaier, Jana; Meier, Sandra; Degenhardt, Franziska; Giegling, Ina; Ripke, Stephan; Leber, Markus; Lange, Christoph; Schulze, Thomas G; Mössner, Rainald; Nenadic, Igor; Sauer, Heinrich; Rujescu, Dan; Maier, Wolfgang; Børglum, Anders; Ophoff, Roel; Cichon, Sven; Nöthen, Markus M; Rietschel, Marcella; Mattheisen, Manuel; Brors, Benedikt

2014-06-01

In the present study, an integrated hierarchical approach was applied to: (1) identify pathways associated with susceptibility to schizophrenia; (2) detect genes that may be potentially affected in these pathways since they contain an associated polymorphism; and (3) annotate the functional consequences of such single-nucleotide polymorphisms (SNPs) in the affected genes or their regulatory regions. The Global Test was applied to detect schizophrenia-associated pathways using discovery and replication datasets comprising 5,040 and 5,082 individuals of European ancestry, respectively. Information concerning functional gene-sets was retrieved from the Kyoto Encyclopedia of Genes and Genomes, Gene Ontology, and the Molecular Signatures Database. Fourteen of the gene-sets or pathways identified in the discovery dataset were confirmed in the replication dataset. These include functional processes involved in transcriptional regulation and gene expression, synapse organization, cell adhesion, and apoptosis. For two genes, i.e. CTCF and CACNB2, evidence for association with schizophrenia was available (at the gene-level) in both the discovery study and published data from the Psychiatric Genomics Consortium schizophrenia study. Furthermore, these genes mapped to four of the 14 presently identified pathways. Several of the SNPs assigned to CTCF and CACNB2 have potential functional consequences, and a gene in close proximity to CACNB2, i.e. ARL5B, was identified as a potential gene of interest. Application of the present hierarchical approach thus allowed: (1) identification of novel biological gene-sets or pathways with potential involvement in the etiology of schizophrenia, as well as replication of these findings in an independent cohort; (2) detection of genes of interest for future follow-up studies; and (3) the highlighting of novel genes in previously reported candidate regions for schizophrenia.

Identifying New Candidate Genes and Chemicals Related to Prostate Cancer Using a Hybrid Network and Shortest Path Approach

PubMed Central

Wang, Meng; Wu, Kai; Lu, Changhong; Kong, Xiangyin

2015-01-01

Prostate cancer is a type of cancer that occurs in the male prostate, a gland in the male reproductive system. Because prostate cancer cells may spread to other parts of the body and can influence human reproduction, understanding the mechanisms underlying this disease is critical for designing effective treatments. The identification of as many genes and chemicals related to prostate cancer as possible will enhance our understanding of this disease. In this study, we proposed a computational method to identify new candidate genes and chemicals based on currently known genes and chemicals related to prostate cancer by applying a shortest path approach in a hybrid network. The hybrid network was constructed according to information concerning chemical-chemical interactions, chemical-protein interactions, and protein-protein interactions. Many of the obtained genes and chemicals are associated with prostate cancer. PMID:26504486

Identifying the critical financial ratios for stocks evaluation: A fuzzy delphi approach

NASA Astrophysics Data System (ADS)

Mokhtar, Mazura; Shuib, Adibah; Mohamad, Daud

2014-12-01

Stocks evaluation has always been an interesting and challenging problem for both researchers and practitioners. Generally, the evaluation can be made based on a set of financial ratios. Nevertheless, there are a variety of financial ratios that can be considered and if all ratios in the set are placed into the evaluation process, data collection would be more difficult and time consuming. Thus, the objective of this paper is to identify the most important financial ratios upon which to focus in order to evaluate the stock's performance. For this purpose, a survey was carried out using an approach which is based on an expert judgement, namely the Fuzzy Delphi Method (FDM). The results of this study indicated that return on equity, return on assets, net profit margin, operating profit margin, earnings per share and debt to equity are the most important ratios.

The Promise of Multi-Omics and Clinical Data Integration to Identify and Target Personalized Healthcare Approaches in Autism Spectrum Disorders

PubMed Central

Higdon, Roger; Earl, Rachel K.; Stanberry, Larissa; Hudac, Caitlin M.; Montague, Elizabeth; Stewart, Elizabeth; Janko, Imre; Choiniere, John; Broomall, William; Kolker, Natali

2015-01-01

Abstract Complex diseases are caused by a combination of genetic and environmental factors, creating a difficult challenge for diagnosis and defining subtypes. This review article describes how distinct disease subtypes can be identified through integration and analysis of clinical and multi-omics data. A broad shift toward molecular subtyping of disease using genetic and omics data has yielded successful results in cancer and other complex diseases. To determine molecular subtypes, patients are first classified by applying clustering methods to different types of omics data, then these results are integrated with clinical data to characterize distinct disease subtypes. An example of this molecular-data-first approach is in research on Autism Spectrum Disorder (ASD), a spectrum of social communication disorders marked by tremendous etiological and phenotypic heterogeneity. In the case of ASD, omics data such as exome sequences and gene and protein expression data are combined with clinical data such as psychometric testing and imaging to enable subtype identification. Novel ASD subtypes have been proposed, such as CHD8, using this molecular subtyping approach. Broader use of molecular subtyping in complex disease research is impeded by data heterogeneity, diversity of standards, and ineffective analysis tools. The future of molecular subtyping for ASD and other complex diseases calls for an integrated resource to identify disease mechanisms, classify new patients, and inform effective treatment options. This in turn will empower and accelerate precision medicine and personalized healthcare. PMID:25831060

The Effect of Two Different Cooperative Approaches on Students' Learning and Practices within the Context of a WebQuest Science Investigation

ERIC Educational Resources Information Center

Zacharia, Zacharias C.; Xenofontos, Nikoletta A.; Manoli, Constantinos C.

2011-01-01

The goal of this study was to investigate the effect of two different cooperative learning approaches, namely, the Jigsaw Cooperative Approach (JCA) and the Traditional Cooperative Approach (TCA), on students' learning and practices/actions within the context of a WebQuest science investigation. Another goal of this study was to identify possible…

A likelihood-based approach to identifying contaminated food products using sales data: performance and challenges.

PubMed

Kaufman, James; Lessler, Justin; Harry, April; Edlund, Stefan; Hu, Kun; Douglas, Judith; Thoens, Christian; Appel, Bernd; Käsbohrer, Annemarie; Filter, Matthias

2014-07-01

Foodborne disease outbreaks of recent years demonstrate that due to increasingly interconnected supply chains these type of crisis situations have the potential to affect thousands of people, leading to significant healthcare costs, loss of revenue for food companies, and--in the worst cases--death. When a disease outbreak is detected, identifying the contaminated food quickly is vital to minimize suffering and limit economic losses. Here we present a likelihood-based approach that has the potential to accelerate the time needed to identify possibly contaminated food products, which is based on exploitation of food products sales data and the distribution of foodborne illness case reports. Using a real world food sales data set and artificially generated outbreak scenarios, we show that this method performs very well for contamination scenarios originating from a single "guilty" food product. As it is neither always possible nor necessary to identify the single offending product, the method has been extended such that it can be used as a binary classifier. With this extension it is possible to generate a set of potentially "guilty" products that contains the real outbreak source with very high accuracy. Furthermore we explore the patterns of food distributions that lead to "hard-to-identify" foods, the possibility of identifying these food groups a priori, and the extent to which the likelihood-based method can be used to quantify uncertainty. We find that high spatial correlation of sales data between products may be a useful indicator for "hard-to-identify" products.

A multi-scale spatial approach to address environmental effects of small hydropower development.

PubMed

McManamay, Ryan A; Samu, Nicole; Kao, Shih-Chieh; Bevelhimer, Mark S; Hetrick, Shelaine C

2015-01-01

Hydropower development continues to grow worldwide in developed and developing countries. While the ecological and physical responses to dam construction have been well documented, translating this information into planning for hydropower development is extremely difficult. Very few studies have conducted environmental assessments to guide site-specific or widespread hydropower development. Herein, we propose a spatial approach for estimating environmental effects of hydropower development at multiple scales, as opposed to individual site-by-site assessments (e.g., environmental impact assessment). Because the complex, process-driven effects of future hydropower development may be uncertain or, at best, limited by available information, we invested considerable effort in describing novel approaches to represent environmental concerns using spatial data and in developing the spatial footprint of hydropower infrastructure. We then use two case studies in the US, one at the scale of the conterminous US and another within two adjoining rivers basins, to examine how environmental concerns can be identified and related to areas of varying energy capacity. We use combinations of reserve-design planning and multi-metric ranking to visualize tradeoffs among environmental concerns and potential energy capacity. Spatial frameworks, like the one presented, are not meant to replace more in-depth environmental assessments, but to identify information gaps and measure the sustainability of multi-development scenarios as to inform policy decisions at the basin or national level. Most importantly, the approach should foster discussions among environmental scientists and stakeholders regarding solutions to optimize energy development and environmental sustainability.

Release of genetically engineered insects: a framework to identify potential ecological effects

PubMed Central

David, Aaron S; Kaser, Joe M; Morey, Amy C; Roth, Alexander M; Andow, David A

2013-01-01

Genetically engineered (GE) insects have the potential to radically change pest management worldwide. With recent approvals of GE insect releases, there is a need for a synthesized framework to evaluate their potential ecological and evolutionary effects. The effects may occur in two phases: a transitory phase when the focal population changes in density, and a steady state phase when it reaches a new, constant density. We review potential effects of a rapid change in insect density related to population outbreaks, biological control, invasive species, and other GE organisms to identify a comprehensive list of potential ecological and evolutionary effects of GE insect releases. We apply this framework to the Anopheles gambiae mosquito – a malaria vector being engineered to suppress the wild mosquito population – to identify effects that may occur during the transitory and steady state phases after release. Our methodology reveals many potential effects in each phase, perhaps most notably those dealing with immunity in the transitory phase, and with pathogen and vector evolution in the steady state phase. Importantly, this framework identifies knowledge gaps in mosquito ecology. Identifying effects in the transitory and steady state phases allows more rigorous identification of the potential ecological effects of GE insect release. PMID:24198955

A Hierarchy of Unhealthy Food Promotion Effects: Identifying Methodological Approaches and Knowledge Gaps

PubMed Central

King, MPsy, Lesley; Chapman, MND, Kathy; Boyland, Emma; Bauman, Adrian E.; Baur, Louise A.

2015-01-01

We assessed the evidence for a conceptual “hierarchy of effects” of marketing, to guide understanding of the relationship between children’s exposure to unhealthy food marketing and poor diets and overweight, and drive the research agenda. We reviewed studies assessing the impact of food promotions on children from MEDLINE, Web of Science, ABI Inform, World Health Organization library database, and The Gray Literature Report. We included articles published in English from 2009 to 2013, with earlier articles from a 2009 systematic review. We grouped articles by outcome of exposure and assessed outcomes within a framework depicting a hierarchy of effects of marketing exposures. Evidence supports a logical sequence of effects linking food promotions to individual-level weight outcomes. Future studies should demonstrate the sustained effects of marketing exposure, and exploit variations in exposures to assess differences in outcomes longitudinally. PMID:25713968

MSBIS: A Multi-Step Biomedical Informatics Screening Approach for Identifying Medications that Mitigate the Risks of Metoclopramide-Induced Tardive Dyskinesia.

PubMed

Xu, Dong; Ham, Alexandrea G; Tivis, Rickey D; Caylor, Matthew L; Tao, Aoxiang; Flynn, Steve T; Economen, Peter J; Dang, Hung K; Johnson, Royal W; Culbertson, Vaughn L

2017-12-01

In 2009 the U.S. Food and Drug Administration (FDA) placed a black box warning on metoclopramide (MCP) due to the increased risks and prevalence of tardive dyskinesia (TD). In this study, we developed a multi-step biomedical informatics screening (MSBIS) approach leveraging publicly available bioactivity and drug safety data to identify concomitant drugs that mitigate the risks of MCP-induced TD. MSBIS includes (1) TargetSearch (http://dxulab.org/software) bioinformatics scoring for drug anticholinergic activity using CHEMBL bioactivity data; (2) unadjusted odds ratio (UOR) scoring for indications of TD-mitigating effects using the FDA Adverse Event Reporting System (FAERS); (3) adjusted odds ratio (AOR) re-scoring by removing the effect of cofounding factors (age, gender, reporting year); (4) logistic regression (LR) coefficient scoring for confirming the best TD-mitigating drug candidates. Drugs with increasing TD protective potential and statistical significance were obtained at each screening step. Fentanyl is identified as the most promising drug against MCP-induced TD (coefficient: -2.68; p-value<0.01). The discovery is supported by clinical reports that patients fully recovered from MCP-induced TD after fentanyl-induced general anesthesia. Loperamide is identified as a potent mitigating drug against a broader range of drug-induced movement disorders through pharmacokinetic modifications. Using drug-induced TD as an example, we demonstrated that MSBIS is an efficient in silico tool for unknown drug-drug interaction detection, drug repurposing, and combination therapy design. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

The quantum Hall effects: Philosophical approach

NASA Astrophysics Data System (ADS)

Lederer, P.

2015-05-01

The Quantum Hall Effects offer a rich variety of theoretical and experimental advances. They provide interesting insights on such topics as gauge invariance, strong interactions in Condensed Matter physics, emergence of new paradigms. This paper focuses on some related philosophical questions. Various brands of positivism or agnosticism are confronted with the physics of the Quantum Hall Effects. Hacking's views on Scientific Realism, Chalmers' on Non-Figurative Realism are discussed. It is argued that the difficulties with those versions of realism may be resolved within a dialectical materialist approach. The latter is argued to provide a rational approach to the phenomena, theory and ontology of the Quantum Hall Effects.

Identifying novel drug indications through automated reasoning.

PubMed

Tari, Luis; Vo, Nguyen; Liang, Shanshan; Patel, Jagruti; Baral, Chitta; Cai, James

2012-01-01

With the large amount of pharmacological and biological knowledge available in literature, finding novel drug indications for existing drugs using in silico approaches has become increasingly feasible. Typical literature-based approaches generate new hypotheses in the form of protein-protein interactions networks by means of linking concepts based on their cooccurrences within abstracts. However, this kind of approaches tends to generate too many hypotheses, and identifying new drug indications from large networks can be a time-consuming process. In this work, we developed a method that acquires the necessary facts from literature and knowledge bases, and identifies new drug indications through automated reasoning. This is achieved by encoding the molecular effects caused by drug-target interactions and links to various diseases and drug mechanism as domain knowledge in AnsProlog, a declarative language that is useful for automated reasoning, including reasoning with incomplete information. Unlike other literature-based approaches, our approach is more fine-grained, especially in identifying indirect relationships for drug indications. To evaluate the capability of our approach in inferring novel drug indications, we applied our method to 943 drugs from DrugBank and asked if any of these drugs have potential anti-cancer activities based on information on their targets and molecular interaction types alone. A total of 507 drugs were found to have the potential to be used for cancer treatments. Among the potential anti-cancer drugs, 67 out of 81 drugs (a recall of 82.7%) are indeed known cancer drugs. In addition, 144 out of 289 drugs (a recall of 49.8%) are non-cancer drugs that are currently tested in clinical trials for cancer treatments. These results suggest that our method is able to infer drug indications (original or alternative) based on their molecular targets and interactions alone and has the potential to discover novel drug indications for existing drugs.

Integrated Bioinformatics, Environmental Epidemiologic and Genomic Approaches to Identify Environmental and Molecular Links between Endometriosis and Breast Cancer

PubMed Central

Roy, Deodutta; Morgan, Marisa; Yoo, Changwon; Deoraj, Alok; Roy, Sandhya; Yadav, Vijay Kumar; Garoub, Mohannad; Assaggaf, Hamza; Doke, Mayur

2015-01-01

We present a combined environmental epidemiologic, genomic, and bioinformatics approach to identify: exposure of environmental chemicals with estrogenic activity; epidemiologic association between endocrine disrupting chemical (EDC) and health effects, such as, breast cancer or endometriosis; and gene-EDC interactions and disease associations. Human exposure measurement and modeling confirmed estrogenic activity of three selected class of environmental chemicals, polychlorinated biphenyls (PCBs), bisphenols (BPs), and phthalates. Meta-analysis showed that PCBs exposure, not Bisphenol A (BPA) and phthalates, increased the summary odds ratio for breast cancer and endometriosis. Bioinformatics analysis of gene-EDC interactions and disease associations identified several hundred genes that were altered by exposure to PCBs, phthalate or BPA. EDCs-modified genes in breast neoplasms and endometriosis are part of steroid hormone signaling and inflammation pathways. All three EDCs–PCB 153, phthalates, and BPA influenced five common genes—CYP19A1, EGFR, ESR2, FOS, and IGF1—in breast cancer as well as in endometriosis. These genes are environmentally and estrogen responsive, altered in human breast and uterine tumors and endometriosis lesions, and part of Mitogen Activated Protein Kinase (MAPK) signaling pathways in cancer. Our findings suggest that breast cancer and endometriosis share some common environmental and molecular risk factors. PMID:26512648

Identifying research priorities for effective retention strategies in clinical trials.

PubMed

Kearney, Anna; Daykin, Anne; Shaw, Alison R G; Lane, Athene J; Blazeby, Jane M; Clarke, Mike; Williamson, Paula; Gamble, Carrol

2017-08-31

The failure to retain patients or collect primary-outcome data is a common challenge for trials and reduces the statistical power and potentially introduces bias into the analysis. Identifying strategies to minimise missing data was the second highest methodological research priority in a Delphi survey of the Directors of UK Clinical Trial Units (CTUs) and is important to minimise waste in research. Our aim was to assess the current retention practices within the UK and priorities for future research to evaluate the effectiveness of strategies to reduce attrition. Seventy-five chief investigators of NIHR Health Technology Assessment (HTA)-funded trials starting between 2009 and 2012 were surveyed to elicit their awareness about causes of missing data within their trial and recommended practices for improving retention. Forty-seven CTUs registered within the UKCRC network were surveyed separately to identify approaches and strategies being used to mitigate missing data across trials. Responses from the current practice surveys were used to inform a subsequent two-round Delphi survey with registered CTUs. A consensus list of retention research strategies was produced and ranked by priority. Fifty out of seventy-five (67%) chief investigators and 33/47 (70%) registered CTUs completed the current practice surveys. Seventy-eight percent of trialists were aware of retention challenges and implemented strategies at trial design. Patient-initiated withdrawal was the most common cause of missing data. Registered CTUs routinely used newsletters, timeline of participant visits, and telephone reminders to mitigate missing data. Whilst 36 out of 59 strategies presented had been formally or informally evaluated, some frequently used strategies, such as site initiation training, have had no research to inform practice. Thirty-five registered CTUs (74%) participated in the Delphi survey. Research into the effectiveness of site initiation training, frequency of patient contact

Systemic approaches identify a garlic-derived chemical, Z-ajoene, as a glioblastoma multiforme cancer stem cell-specific targeting agent.

PubMed

Jung, Yuchae; Park, Heejoo; Zhao, Hui-Yuan; Jeon, Raok; Ryu, Jae-Ha; Kim, Woo-Young

2014-07-01

Glioblastoma multiforme (GBM) is one of the most common brain malignancies and has a very poor prognosis. Recent evidence suggests that the presence of cancer stem cells (CSC) in GBM and the rare CSC subpopulation that is resistant to chemotherapy may be responsible for the treatment failure and unfavorable prognosis of GBM. A garlic-derived compound, Z-ajoene, has shown a range of biological activities, including anti-proliferative effects on several cancers. Here, we demonstrated for the first time that Z-ajoene specifically inhibits the growth of the GBM CSC population. CSC sphere-forming inhibition was achieved at a concentration that did not exhibit a cytotoxic effect in regular cell culture conditions. The specificity of this inhibitory effect on the CSC population was confirmed by detecting CSC cell surface marker CD133 expression and biochemical marker ALDH activity. In addition, stem cell-related mRNA profiling and real-time PCR revealed the differential expression of CSC-specific genes, including Notch, Wnt, and Hedgehog, upon treatment with Z-ajoene. A proteomic approach, i.e., reverse-phase protein array (RPPA) and Western blot analysis, showed decreased SMAD4, p-AKT, 14.3.3 and FOXO3A expression. The protein interaction map (http://string-db.org/) of the identified molecules suggested that the AKT, ERK/p38 and TGFβ signaling pathways are key mediators of Z-ajoene's action, which affects the transcriptional network that includes FOXO3A. These biological and bioinformatic analyses collectively demonstrate that Z-ajoene is a potential candidate for the treatment of GBM by specifically targeting GBM CSCs. We also show how this systemic approach strengthens the identification of new therapeutic agents that target CSCs.

An Integrative data mining approach to identifying Adverse ...

EPA Pesticide Factsheets

The Adverse Outcome Pathway (AOP) framework is a tool for making biological connections and summarizing key information across different levels of biological organization to connect biological perturbations at the molecular level to adverse outcomes for an individual or population. Computational approaches to explore and determine these connections can accelerate the assembly of AOPs. By leveraging the wealth of publicly available data covering chemical effects on biological systems, computationally-predicted AOPs (cpAOPs) were assembled via data mining of high-throughput screening (HTS) in vitro data, in vivo data and other disease phenotype information. Frequent Itemset Mining (FIM) was used to find associations between the gene targets of ToxCast HTS assays and disease data from Comparative Toxicogenomics Database (CTD) by using the chemicals as the common aggregators between datasets. The method was also used to map gene expression data to disease data from CTD. A cpAOP network was defined by considering genes and diseases as nodes and FIM associations as edges. This network contained 18,283 gene to disease associations for the ToxCast data and 110,253 for CTD gene expression. Two case studies show the value of the cpAOP network by extracting subnetworks focused either on fatty liver disease or the Aryl Hydrocarbon Receptor (AHR). The subnetwork surrounding fatty liver disease included many genes known to play a role in this disease. When querying the cpAOP

Whole exome sequencing for familial bicuspid aortic valve identifies putative variants.

PubMed

Martin, Lisa J; Pilipenko, Valentina; Kaufman, Kenneth M; Cripe, Linda; Kottyan, Leah C; Keddache, Mehdi; Dexheimer, Phillip; Weirauch, Matthew T; Benson, D Woodrow

2014-10-01

Bicuspid aortic valve (BAV) is the most common congenital cardiovascular malformation. Although highly heritable, few causal variants have been identified. The purpose of this study was to identify genetic variants underlying BAV by whole exome sequencing a multiplex BAV kindred. Whole exome sequencing was performed on 17 individuals from a single family (BAV=3; other cardiovascular malformation, 3). Postvariant calling error control metrics were established after examining the relationship between Mendelian inheritance error rate and coverage, quality score, and call rate. To determine the most effective approach to identifying susceptibility variants from among 54 674 variants passing error control metrics, we evaluated 3 variant selection strategies frequently used in whole exome sequencing studies plus extended family linkage. No putative rare, high-effect variants were identified in all affected but no unaffected individuals. Eight high-effect variants were identified by ≥2 of the commonly used selection strategies; however, these were either common in the general population (>10%) or present in the majority of the unaffected family members. However, using extended family linkage, 3 synonymous variants were identified; all 3 variants were identified by at least one other strategy. These results suggest that traditional whole exome sequencing approaches, which assume causal variants alter coding sense, may be insufficient for BAV and other complex traits. Identification of disease-associated variants is facilitated by the use of segregation within families. © 2014 American Heart Association, Inc.

Mapping of neuron soma size as an effective approach to delineate differences between neural populations.

PubMed

Lingley, Alexander J; Bowdridge, Joshua C; Farivar, Reza; Duffy, Kevin R

2018-04-30

A single histological marker applied to a slice of tissue often reveals myriad cytoarchitectonic characteristics that can obscure differences between neuron populations targeted for study. Isolation and measurement of a single feature from the tissue is possible through a variety of approaches, however, visualizing the data numerically or through graphs alone can preclude being able to identify important features and effects that are not obvious from direct observation of the tissue. We demonstrate an efficient, effective, and robust approach to quantify and visualize cytoarchitectural features in histologically prepared brain sections. We demonstrate that this approach is able to reveal small differences between populations of neurons that might otherwise have gone undiscovered. We used stereological methods to record the cross-sectional soma area and in situ position of neurons within sections of the cat, monkey, and human visual system. The two-dimensional coordinate of every measured cell was used to produce a scatter plot that recapitulated the natural spatial distribution of cells, and each point in the plot was color-coded according to its respective soma area. The final graphic display was a multi-dimensional map of neuron soma size that revealed subtle differences across neuron aggregations, permitted delineation of regional boundaries, and identified small differences between populations of neurons modified by a period of sensory deprivation. This approach to collecting and displaying cytoarchitectonic data is simple, efficient, and provides a means of investigating small differences between neuron populations. Copyright © 2018. Published by Elsevier B.V.

An integrative data mining approach to identifying adverse outcome pathway signatures.

PubMed

Oki, Noffisat O; Edwards, Stephen W

2016-03-28

The Adverse Outcome Pathway (AOP) framework is a tool for making biological connections and summarizing key information across different levels of biological organization to connect biological perturbations at the molecular level to adverse outcomes for an individual or population. Computational approaches to explore and determine these connections can accelerate the assembly of AOPs. By leveraging the wealth of publicly available data covering chemical effects on biological systems, computationally-predicted AOPs (cpAOPs) were assembled via data mining of high-throughput screening (HTS) in vitro data, in vivo data and other disease phenotype information. Frequent Itemset Mining (FIM) was used to find associations between the gene targets of ToxCast HTS assays and disease data from Comparative Toxicogenomics Database (CTD) by using the chemicals as the common aggregators between datasets. The method was also used to map gene expression data to disease data from CTD. A cpAOP network was defined by considering genes and diseases as nodes and FIM associations as edges. This network contained 18,283 gene to disease associations for the ToxCast data and 110,253 for CTD gene expression. Two case studies show the value of the cpAOP network by extracting subnetworks focused either on fatty liver disease or the Aryl Hydrocarbon Receptor (AHR). The subnetwork surrounding fatty liver disease included many genes known to play a role in this disease. When querying the cpAOP network with the AHR gene, an interesting subnetwork including glaucoma was identified. While substantial literature exists to support the potential for AHR ligands to elicit glaucoma, it was not explicitly captured in the public annotation information in CTD. The subnetwork from this analysis suggests a cpAOP that includes changes in CYP1B1 expression, which has been previously established in the literature as a primary cause of glaucoma. These case studies highlight the value in integrating multiple data

Components of Effective Cognitive-Behavioral Therapy for Pediatric Headache: A Mixed Methods Approach

PubMed Central

Law, Emily F.; Beals-Erickson, Sarah E.; Fisher, Emma; Lang, Emily A.; Palermo, Tonya M.

2017-01-01

Internet-delivered treatment has the potential to expand access to evidence-based cognitive-behavioral therapy (CBT) for pediatric headache, and has demonstrated efficacy in small trials for some youth with headache. We used a mixed methods approach to identify effective components of CBT for this population. In Study 1, component profile analysis identified common interventions delivered in published RCTs of effective CBT protocols for pediatric headache delivered face-to-face or via the Internet. We identified a core set of three treatment components that were common across face-to-face and Internet protocols: 1) headache education, 2) relaxation training, and 3) cognitive interventions. Biofeedback was identified as an additional core treatment component delivered in face-to-face protocols only. In Study 2, we conducted qualitative interviews to describe the perspectives of youth with headache and their parents on successful components of an Internet CBT intervention. Eleven themes emerged from the qualitative data analysis, which broadly focused on patient experiences using the treatment components and suggestions for new treatment components. In the Discussion, these mixed methods findings are integrated to inform the adaptation of an Internet CBT protocol for youth with headache. PMID:29503787

Components of Effective Cognitive-Behavioral Therapy for Pediatric Headache: A Mixed Methods Approach.

PubMed

Law, Emily F; Beals-Erickson, Sarah E; Fisher, Emma; Lang, Emily A; Palermo, Tonya M

2017-01-01

Internet-delivered treatment has the potential to expand access to evidence-based cognitive-behavioral therapy (CBT) for pediatric headache, and has demonstrated efficacy in small trials for some youth with headache. We used a mixed methods approach to identify effective components of CBT for this population. In Study 1, component profile analysis identified common interventions delivered in published RCTs of effective CBT protocols for pediatric headache delivered face-to-face or via the Internet. We identified a core set of three treatment components that were common across face-to-face and Internet protocols: 1) headache education, 2) relaxation training, and 3) cognitive interventions. Biofeedback was identified as an additional core treatment component delivered in face-to-face protocols only. In Study 2, we conducted qualitative interviews to describe the perspectives of youth with headache and their parents on successful components of an Internet CBT intervention. Eleven themes emerged from the qualitative data analysis, which broadly focused on patient experiences using the treatment components and suggestions for new treatment components. In the Discussion, these mixed methods findings are integrated to inform the adaptation of an Internet CBT protocol for youth with headache.

A Genetic Approach to Identifying Signal Transduction Mechanisms Initiated by Receptors for TGF-B-Related Factors.

DTIC Science & Technology

1998-10-01

resistant to TGF-ß-induced growth arrest suggest that both types of receptors are required for signaling (Boyd and Massague, 1989; Laiho et ah, 1990...II in TGF-ß- resistant cell mutants implicates both receptor types in signal transduction. J. Biol. Chem. 265, 18518-18524. Lechleider, R. J., de...I-1 « -J AD GRANT NUMBER DAMD17-94-J-4339 TITLE: A Genetic Approach to Identifying Signal Transduction Mechanisms Initiated by Receptors

Computational Approaches to Identify Promoters and cis-Regulatory Elements in Plant Genomes1

PubMed Central

Rombauts, Stephane; Florquin, Kobe; Lescot, Magali; Marchal, Kathleen; Rouzé, Pierre; Van de Peer, Yves

2003-01-01

The identification of promoters and their regulatory elements is one of the major challenges in bioinformatics and integrates comparative, structural, and functional genomics. Many different approaches have been developed to detect conserved motifs in a set of genes that are either coregulated or orthologous. However, although recent approaches seem promising, in general, unambiguous identification of regulatory elements is not straightforward. The delineation of promoters is even harder, due to its complex nature, and in silico promoter prediction is still in its infancy. Here, we review the different approaches that have been developed for identifying promoters and their regulatory elements. We discuss the detection of cis-acting regulatory elements using word-counting or probabilistic methods (so-called “search by signal” methods) and the delineation of promoters by considering both sequence content and structural features (“search by content” methods). As an example of search by content, we explored in greater detail the association of promoters with CpG islands. However, due to differences in sequence content, the parameters used to detect CpG islands in humans and other vertebrates cannot be used for plants. Therefore, a preliminary attempt was made to define parameters that could possibly define CpG and CpNpG islands in Arabidopsis, by exploring the compositional landscape around the transcriptional start site. To this end, a data set of more than 5,000 gene sequences was built, including the promoter region, the 5′-untranslated region, and the first introns and coding exons. Preliminary analysis shows that promoter location based on the detection of potential CpG/CpNpG islands in the Arabidopsis genome is not straightforward. Nevertheless, because the landscape of CpG/CpNpG islands differs considerably between promoters and introns on the one side and exons (whether coding or not) on the other, more sophisticated approaches can probably be

A sequential factorial analysis approach to characterize the effects of uncertainties for supporting air quality management

NASA Astrophysics Data System (ADS)

Wang, S.; Huang, G. H.; Veawab, A.

2013-03-01

This study proposes a sequential factorial analysis (SFA) approach for supporting regional air quality management under uncertainty. SFA is capable not only of examining the interactive effects of input parameters, but also of analyzing the effects of constraints. When there are too many factors involved in practical applications, SFA has the advantage of conducting a sequence of factorial analyses for characterizing the effects of factors in a systematic manner. The factor-screening strategy employed in SFA is effective in greatly reducing the computational effort. The proposed SFA approach is applied to a regional air quality management problem for demonstrating its applicability. The results indicate that the effects of factors are evaluated quantitatively, which can help decision makers identify the key factors that have significant influence on system performance and explore the valuable information that may be veiled beneath their interrelationships.

Assessing urban potential flooding risk and identifying effective risk-reduction measures.

PubMed

Cherqui, Frédéric; Belmeziti, Ali; Granger, Damien; Sourdril, Antoine; Le Gauffre, Pascal

2015-05-01

Flood protection is one of the traditional functions of any drainage system, and it remains a major issue in many cities because of economic and health impact. Heavy rain flooding has been well studied and existing simulation software can be used to predict and improve level of protection. However, simulating minor flooding remains highly complex, due to the numerous possible causes related to operational deficiencies or negligent behaviour. According to the literature, causes of blockages vary widely from one case to another: it is impossible to provide utility managers with effective recommendations on how to improve the level of protection. It is therefore vital to analyse each context in order to define an appropriate strategy. Here we propose a method to represent and assess the flooding risk, using GIS and data gathered during operation and maintenance. Our method also identifies potential management responses. The approach proposed aims to provide decision makers with clear and comprehensible information. Our method has been successfully applied to the Urban Community of Bordeaux (France) on 4895 interventions related to flooding recorded during the 2009-2011 period. Results have shown the relative importance of different issues, such as human behaviour (grease, etc.) or operational deficiencies (roots, etc.), and lead to identify corrective and proactive. This study also confirms that blockages are not always directly due to the network itself and its deterioration. Many causes depend on environmental and operating conditions on the network and often require collaboration between municipal departments in charge of roads, green spaces, etc. Copyright © 2015 Elsevier B.V. All rights reserved.

Identifying approaches for assessing methodological and reporting quality of systematic reviews: a descriptive study.

PubMed

Pussegoda, Kusala; Turner, Lucy; Garritty, Chantelle; Mayhew, Alain; Skidmore, Becky; Stevens, Adrienne; Boutron, Isabelle; Sarkis-Onofre, Rafael; Bjerre, Lise M; Hróbjartsson, Asbjørn; Altman, Douglas G; Moher, David

2017-06-19

The methodological quality and completeness of reporting of the systematic reviews (SRs) is fundamental to optimal implementation of evidence-based health care and the reduction of research waste. Methods exist to appraise SRs yet little is known about how they are used in SRs or where there are potential gaps in research best-practice guidance materials. The aims of this study are to identify reports assessing the methodological quality (MQ) and/or reporting quality (RQ) of a cohort of SRs and to assess their number, general characteristics, and approaches to 'quality' assessment over time. The Cochrane Library, MEDLINE®, and EMBASE® were searched from January 1990 to October 16, 2014, for reports assessing MQ and/or RQ of SRs. Title, abstract, and full-text screening of all reports were conducted independently by two reviewers. Reports assessing the MQ and/or RQ of a cohort of ten or more SRs of interventions were included. All results are reported as frequencies and percentages of reports. Of 20,765 unique records retrieved, 1189 of them were reviewed for full-text review, of which 76 reports were included. Eight previously published approaches to assessing MQ or reporting guidelines used as proxy to assess RQ were used in 80% (61/76) of identified reports. These included two reporting guidelines (PRISMA and QUOROM) and five quality assessment tools (AMSTAR, R-AMSTAR, OQAQ, Mulrow, Sacks) and GRADE criteria. The remaining 24% (18/76) of reports developed their own criteria. PRISMA, OQAQ, and AMSTAR were the most commonly used published tools to assess MQ or RQ. In conjunction with other approaches, published tools were used in 29% (22/76) of reports, with 36% (8/22) assessing adherence to both PRISMA and AMSTAR criteria and 26% (6/22) using QUOROM and OQAQ. The methods used to assess quality of SRs are diverse, and none has become universally accepted. The most commonly used quality assessment tools are AMSTAR, OQAQ, and PRISMA. As new tools and guidelines are

Identifying MMORPG Bots: A Traffic Analysis Approach

NASA Astrophysics Data System (ADS)

Chen, Kuan-Ta; Jiang, Jhih-Wei; Huang, Polly; Chu, Hao-Hua; Lei, Chin-Laung; Chen, Wen-Chin

2008-12-01

Massively multiplayer online role playing games (MMORPGs) have become extremely popular among network gamers. Despite their success, one of MMORPG's greatest challenges is the increasing use of game bots, that is, autoplaying game clients. The use of game bots is considered unsportsmanlike and is therefore forbidden. To keep games in order, game police, played by actual human players, often patrol game zones and question suspicious players. This practice, however, is labor-intensive and ineffective. To address this problem, we analyze the traffic generated by human players versus game bots and propose general solutions to identify game bots. Taking Ragnarok Online as our subject, we study the traffic generated by human players and game bots. We find that their traffic is distinguishable by 1) the regularity in the release time of client commands, 2) the trend and magnitude of traffic burstiness in multiple time scales, and 3) the sensitivity to different network conditions. Based on these findings, we propose four strategies and two ensemble schemes to identify bots. Finally, we discuss the robustness of the proposed methods against countermeasures of bot developers, and consider a number of possible ways to manage the increasingly serious bot problem.

Identifying Key Words in 9-1-1 Calls for Stroke: A Mixed Methods Approach.

PubMed

Richards, Christopher T; Wang, Baiyang; Markul, Eddie; Albarran, Frank; Rottman, Doreen; Aggarwal, Neelum T; Lindeman, Patricia; Stein-Spencer, Leslee; Weber, Joseph M; Pearlman, Kenneth S; Tataris, Katie L; Holl, Jane L; Klabjan, Diego; Prabhakaran, Shyam

2017-01-01

Identifying stroke during a 9-1-1 call is critical to timely prehospital care. However, emergency medical dispatchers (EMDs) recognize stroke in less than half of 9-1-1 calls, potentially due to the words used by callers to communicate stroke signs and symptoms. We hypothesized that callers do not typically use words and phrases considered to be classical descriptors of stroke, such as focal neurologic deficits, but that a mixed-methods approach can identify words and phrases commonly used by 9-1-1 callers to describe acute stroke victims. We performed a mixed-method, retrospective study of 9-1-1 call audio recordings for adult patients with confirmed stroke who were transported by ambulance in a large urban city. Content analysis, a qualitative methodology, and computational linguistics, a quantitative methodology, were used to identify key words and phrases used by 9-1-1 callers to describe acute stroke victims. Because a caller's level of emotional distress contributes to the communication during a 9-1-1 call, the Emotional Content and Cooperation Score was scored by a multidisciplinary team. A total of 110 9-1-1 calls, received between June and September 2013, were analyzed. EMDs recognized stroke in 48% of calls, and the emotional state of most callers (95%) was calm. In 77% of calls in which EMDs recognized stroke, callers specifically used the word "stroke"; however, the word "stroke" was used in only 38% of calls. Vague, non-specific words and phrases were used to describe stroke victims' symptoms in 55% of calls, and 45% of callers used distractor words and phrases suggestive of non-stroke emergencies. Focal neurologic symptoms were described in 39% of calls. Computational linguistics identified 9 key words that were more commonly used in calls where the EMD identified stroke. These words were concordant with terms identified through qualitative content analysis. Most 9-1-1 callers used vague, non-specific, or distractor words and phrases and infrequently

An alternative approach for modeling strength differential effect in sheet metals with symmetric yield functions

NASA Astrophysics Data System (ADS)

Kurukuri, Srihari; Worswick, Michael J.

2013-12-01

An alternative approach is proposed to utilize symmetric yield functions for modeling the tension-compression asymmetry commonly observed in hcp materials. In this work, the strength differential (SD) effect is modeled by choosing separate symmetric plane stress yield functions (for example, Barlat Yld 2000-2d) for the tension i.e., in the first quadrant of principal stress space, and compression i.e., third quadrant of principal stress space. In the second and fourth quadrants, the yield locus is constructed by adopting interpolating functions between uniaxial tensile and compressive stress states. In this work, different interpolating functions are chosen and the predictive capability of each approach is discussed. The main advantage of this proposed approach is that the yield locus parameters are deterministic and relatively easy to identify when compared to the Cazacu family of yield functions commonly used for modeling SD effect observed in hcp materials.

Differentiating Performance Approach Goals and Their Unique Effects

ERIC Educational Resources Information Center

Edwards, Ordene V.

2014-01-01

The study differentiates between two types of performance approach goals (competence demonstration performance approach goal and normative performance approach goal) by examining their unique effects on self-efficacy, interest, and fear of failure. Seventy-nine students completed questionnaires that measure performance approach goals,…

Participatory approach to identify interventions to improve the health, safety, and work productivity of smallholder women vegetable farmers in the Gambia.

PubMed

Vanderwal, Londa; Rautiainen, Risto; Ramirez, Marizen; Kuye, Rex; Peek-Asa, Corinne; Cook, Thomas; Culp, Kennith; Donham, Kelley

2011-03-01

This paper describes the qualitative, community-based participatory approach used to identify culturally-acceptable and sustainable interventions to improve the occupational health, safety, and productivity of smallholder women vegetable farmers in The Gambia (West Africa). This approach was used to conduct: 1) analysis of the tasks and methods traditionally used in vegetable production, and 2) selection of interventions. The most arduous garden tasks that were amenable to interventions were identified, and the interventions were selected through a participatory process for further evaluation. Factors contributing to the successful implementation of the participatory approach used in this study included the following: 1) ensuring that cultural norms were respected and observed; 2) working closely with the existing garden leadership structure; and 3) research team members working with the subjects for an extended period of time to gain first-hand understanding of the selected tasks and to build credibility with the subjects.

Method for Identifying Probable Archaeological Sites from Remotely Sensed Data

NASA Technical Reports Server (NTRS)

Tilton, James C.; Comer, Douglas C.; Priebe, Carey E.; Sussman, Daniel

2011-01-01

Archaeological sites are being compromised or destroyed at a catastrophic rate in most regions of the world. The best solution to this problem is for archaeologists to find and study these sites before they are compromised or destroyed. One way to facilitate the necessary rapid, wide area surveys needed to find these archaeological sites is through the generation of maps of probable archaeological sites from remotely sensed data. We describe an approach for identifying probable locations of archaeological sites over a wide area based on detecting subtle anomalies in vegetative cover through a statistically based analysis of remotely sensed data from multiple sources. We further developed this approach under a recent NASA ROSES Space Archaeology Program project. Under this project we refined and elaborated this statistical analysis to compensate for potential slight miss-registrations between the remote sensing data sources and the archaeological site location data. We also explored data quantization approaches (required by the statistical analysis approach), and we identified a superior data quantization approached based on a unique image segmentation approach. In our presentation we will summarize our refined approach and demonstrate the effectiveness of the overall approach with test data from Santa Catalina Island off the southern California coast. Finally, we discuss our future plans for further improving our approach.

Identifying Differences among Novice Database Users: Implications for Training Material Effectiveness.

ERIC Educational Resources Information Center

Antonucci, Yvonne Lederer; Wozny, Lucy Anne

1996-01-01

Identifies and describes sublevels of novices using a database management package, clustering those whose interaction is effective, partially effective, and totally ineffective. Among assistance documentation, functional tree diagrams (FTDs) were more beneficial to partially effective users than traditional reference material. The results have…

Identifying barriers to and facilitators of tuberculosis contact investigation in Kampala, Uganda: a behavioral approach.

PubMed

Ayakaka, Irene; Ackerman, Sara; Ggita, Joseph M; Kajubi, Phoebe; Dowdy, David; Haberer, Jessica E; Fair, Elizabeth; Hopewell, Philip; Handley, Margaret A; Cattamanchi, Adithya; Katamba, Achilles; Davis, J Lucian

2017-03-09

The World Health Organization recommends routine household tuberculosis contact investigation in high-burden countries but adoption has been limited. We sought to identify barriers to and facilitators of TB contact investigation during its introduction in Kampala, Uganda. We collected cross-sectional qualitative data through focus group discussions and interviews with stakeholders, addressing three core activities of contact investigation: arranging household screening visits through index TB patients, visiting households to screen contacts and refer them to clinics, and evaluating at-risk contacts coming to clinics. We analyzed the data using a validated theory of behavior change, the Capability, Opportunity, and Motivation determine Behavior (COM-B) model, and sought to identify targeted interventions using the related Behavior Change Wheel implementation framework. We led seven focus-group discussions with 61 health-care workers, two with 21 lay health workers (LHWs), and one with four household contacts of newly diagnosed TB patients. We, in addition, performed 32 interviews with household contacts from 14 households of newly diagnosed TB patients. Commonly noted barriers included stigma, limited knowledge about TB among contacts, insufficient time and space in clinics for counselling, mistrust of health-center staff among index patients and contacts, and high travel costs for LHWs and contacts. The most important facilitators identified were the personalized and enabling services provided by LHWs. We identified education, persuasion, enablement, modeling of health-positive behaviors, incentivization, and restructuring of the service environment as relevant intervention functions with potential to alleviate barriers to and enhance facilitators of TB contact investigation. The use of a behavioral theory and a validated implementation framework provided a comprehensive approach for systematically identifying barriers to and facilitators of TB contact

Fetal alcohol-spectrum disorders: identifying at-risk mothers

PubMed Central

Montag, Annika C

2016-01-01

Fetal alcohol-spectrum disorders (FASDs) are a collection of physical and neurobehavioral disabilities caused by prenatal exposure to alcohol. To prevent or mitigate the costly effects of FASD, we must identify mothers at risk for having a child with FASD, so that we may reach them with interventions. Identifying mothers at risk is beneficial at all time points, whether prior to pregnancy, during pregnancy, or following the birth of the child. In this review, three approaches to identifying mothers at risk are explored: using characteristics of the mother and her pregnancy, using laboratory biomarkers, and using self-report assessment of alcohol-consumption risk. At present, all approaches have serious limitations. Research is needed to improve the sensitivity and specificity of biomarkers and screening instruments, and to link them to outcomes as opposed to exposure. Universal self-report screening of all women of childbearing potential should ideally be incorporated into routine obstetric and gynecologic care, followed by brief interventions, including education and personalized feedback for all who consume alcohol, and referral to treatment as indicated. Effective biomarkers or combinations of biomarkers may be used during pregnancy and at birth to determine maternal and fetal alcohol exposure. The combination of self-report and biomarker screening may help identify a greater proportion of women at risk for having a child with FASD, allowing them to access information and treatment, and empowering them to make decisions that benefit their children. PMID:27499649

A Machine Learning Approach to Identifying Placebo Responders in Late-Life Depression Trials.

PubMed

Zilcha-Mano, Sigal; Roose, Steven P; Brown, Patrick J; Rutherford, Bret R

2018-01-11

Despite efforts to identify characteristics associated with medication-placebo differences in antidepressant trials, few consistent findings have emerged to guide participant selection in drug development settings and differential therapeutics in clinical practice. Limitations in the methodologies used, particularly searching for a single moderator while treating all other variables as noise, may partially explain the failure to generate consistent results. The present study tested whether interactions between pretreatment patient characteristics, rather than a single-variable solution, may better predict who is most likely to benefit from placebo versus medication. Data were analyzed from 174 patients aged 75 years and older with unipolar depression who were randomly assigned to citalopram or placebo. Model-based recursive partitioning analysis was conducted to identify the most robust significant moderators of placebo versus citalopram response. The greatest signal detection between medication and placebo in favor of medication was among patients with fewer years of education (≤12) who suffered from a longer duration of depression since their first episode (>3.47 years) (B = 2.53, t(32) = 3.01, p = 0.004). Compared with medication, placebo had the greatest response for those who were more educated (>12 years), to the point where placebo almost outperformed medication (B = -0.57, t(96) = -1.90, p = 0.06). Machine learning approaches capable of evaluating the contributions of multiple predictor variables may be a promising methodology for identifying placebo versus medication responders. Duration of depression and education should be considered in the efforts to modulate placebo magnitude in drug development settings and in clinical practice. Copyright © 2018 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.

Identifying Similarities in Cognitive Subtest Functional Requirements: An Empirical Approach

ERIC Educational Resources Information Center

Frisby, Craig L.; Parkin, Jason R.

2007-01-01

In the cognitive test interpretation literature, a Rational/Intuitive, Indirect Empirical, or Combined approach is typically used to construct conceptual taxonomies of the functional (behavioral) similarities between subtests. To address shortcomings of these approaches, the functional requirements for 49 subtests from six individually…

A methodological approach to identify agro-biodiversity hotspots for priority in situ conservation of plant genetic resources

PubMed Central

Pacicco, Luca; Bodesmo, Mara; Torricelli, Renzo

2018-01-01

Agro-biodiversity is seriously threatened worldwide and strategies to preserve it are dramatically required. We propose here a methodological approach aimed to identify areas with a high level of agro-biodiversity in which to set or enhance in situ conservation of plant genetic resources. These areas are identified using three criteria: Presence of Landrace diversity, Presence of wild species and Agro-ecosystem ecological diversity. A Restrictive and an Additive prioritization strategy has been applied on the entire Italian territory and has resulted in establishing nationwide 53 and 197 agro-biodiversity hotspots respectively. At present the strategies can easily be applied at a European level and can be helpful to develop conservation strategies everywhere. PMID:29856765

Is my study system good enough? A case study for identifying maternal effects.

PubMed

Holand, Anna Marie; Steinsland, Ingelin

2016-06-01

In this paper, we demonstrate how simulation studies can be used to answer questions about identifiability and consequences of omitting effects from a model. The methodology is presented through a case study where identifiability of genetic and/or individual (environmental) maternal effects is explored. Our study system is a wild house sparrow ( Passer domesticus ) population with known pedigree. We fit pedigree-based (generalized) linear mixed models (animal models), with and without additive genetic and individual maternal effects, and use deviance information criterion (DIC) for choosing between these models. Pedigree and R-code for simulations are available. For this study system, the simulation studies show that only large maternal effects can be identified. The genetic maternal effect (and similar for individual maternal effect) has to be at least half of the total genetic variance to be identified. The consequences of omitting a maternal effect when it is present are explored. Our results indicate that the total (genetic and individual) variance are accounted for. When an individual (environmental) maternal effect is omitted from the model, this only influences the estimated (direct) individual (environmental) variance. When a genetic maternal effect is omitted from the model, both (direct) genetic and (direct) individual variance estimates are overestimated.

Identifying Green Infrastructure from Social Media and Crowdsourcing- An Image Based Machine-Learning Approach.

NASA Astrophysics Data System (ADS)

Rai, A.; Minsker, B. S.

2016-12-01

In this work we introduce a novel dataset GRID: GReen Infrastructure Detection Dataset and a framework for identifying urban green storm water infrastructure (GI) designs (wetlands/ponds, urban trees, and rain gardens/bioswales) from social media and satellite aerial images using computer vision and machine learning methods. Along with the hydrologic benefits of GI, such as reducing runoff volumes and urban heat islands, GI also provides important socio-economic benefits such as stress recovery and community cohesion. However, GI is installed by many different parties and cities typically do not know where GI is located, making study of its impacts or siting new GI difficult. We use object recognition learning methods (template matching, sliding window approach, and Random Hough Forest method) and supervised machine learning algorithms (e.g., support vector machines) as initial screening approaches to detect potential GI sites, which can then be investigated in more detail using on-site surveys. Training data were collected from GPS locations of Flickr and Instagram image postings and Amazon Mechanical Turk identification of each GI type. Sliding window method outperformed other methods and achieved an average F measure, which is combined metric for precision and recall performance measure of 0.78.

DNA enrichment approaches to identify unauthorized genetically modified organisms (GMOs).

PubMed

Arulandhu, Alfred J; van Dijk, Jeroen P; Dobnik, David; Holst-Jensen, Arne; Shi, Jianxin; Zel, Jana; Kok, Esther J

2016-07-01

With the increased global production of different genetically modified (GM) plant varieties, chances increase that unauthorized GM organisms (UGMOs) may enter the food chain. At the same time, the detection of UGMOs is a challenging task because of the limited sequence information that will generally be available. PCR-based methods are available to detect and quantify known UGMOs in specific cases. If this approach is not feasible, DNA enrichment of the unknown adjacent sequences of known GMO elements is one way to detect the presence of UGMOs in a food or feed product. These enrichment approaches are also known as chromosome walking or gene walking (GW). In recent years, enrichment approaches have been coupled with next generation sequencing (NGS) analysis and implemented in, amongst others, the medical and microbiological fields. The present review will provide an overview of these approaches and an evaluation of their applicability in the identification of UGMOs in complex food or feed samples.

Integrating virtual screening and biochemical experimental approach to identify potential anti-cancer agents from drug databank.

PubMed

Deka, Suman Jyoti; Roy, Ashalata; Manna, Debasis; Trivedi, Vishal

2018-06-01

Chemical libraries constitute a reservoir of pharmacophoric molecules to identify potent anti-cancer agents. Virtual screening of heterocyclic compound library in conjugation with the agonist-competition assay, toxicity-carcinogenicity analysis, and string-based structural searches enabled us to identify several drugs as potential anti-cancer agents targeting protein kinase C (PKC) as a target. Molecular modeling study indicates that Cinnarizine fits well within the PKC C2 domain and exhibits extensive interaction with the protein residues. Molecular dynamics simulation of PKC-Cinnarizine complex at different temperatures (300, 325, 350, 375, and 400[Formula: see text]K) confirms that Cinnarizine fits nicely into the C2 domain and forms a stable complex. The drug Cinnarizine was found to bind PKC with a dissociation constant Kd of [Formula: see text]M. The breast cancer cells stimulated with Cinnarizine causes translocation of PKC-[Formula: see text] to the plasma membrane as revealed by immunoblotting and immunofluorescence studies. Cinnarizine also dose dependently reduced the viability of MDAMB-231 and MCF-7 breast cancer cells with an IC[Formula: see text] of [Formula: see text] and [Formula: see text]g/mL, respectively. It is due to the disturbance of cell cycle of breast cancer cells with reduction of S-phase and accumulation of cells in G1-phase. It disturbs mitochondrial membrane potentials to release cytochrome C into the cytosol and activates caspase-3 to induce apoptosis in cancer cells. The cell death was due to induction of apoptosis involving mitochondrial pathway. Hence, the current study has assigned an additional role to Cinnarizine as an activator of PKC and potentials of the approach to identify new molecules for anti-cancer therapy. Thus, in silico screening along with biochemical experimentation is a robust approach to assign additional roles to the drugs present in the databank for anti-cancer therapy.

A phenotypic screening approach to identify anticancer compounds derived from marine fungi.

PubMed

Ellinger, Bernhard; Silber, Johanna; Prashar, Anjali; Landskron, Johannes; Weber, Jonas; Rehermann, Sarah; Müller, Franz-Josef; Smith, Stephen; Wrigley, Stephen; Taskén, Kjetil; Gribbon, Philip; Labes, Antje; Imhoff, Johannes F

2014-04-01

This study covers the isolation, testing, and identification of natural products with anticancer properties. Secondary metabolites were isolated from fungal strains originating from a variety of marine habitats. Strain culture protocols were optimized with respect to growth media composition and fermentation conditions. From these producers, isolated compounds were screened for their effect on the viability and proliferation of a subset of the NCI60 panel of cancer cell lines. Active compounds of interest were identified and selected for detailed assessments and structural elucidation using nuclear magnetic resonance. This revealed the majority of fungal-derived compounds represented known anticancer chemotypes, confirming the integrity of the process and the ability to identify suitable compounds. Examination of effects of selected compounds on cancer-associated cell signaling pathways used phospho flow cytometry in combination with 3D fluorescent cell barcoding. In parallel, the study addressed the logistical aspects of maintaining multiple cancer cell lines in culture simultaneously. A potential solution involving microbead-based cell culture was investigated (BioLevitator, Hamilton). Selected cell lines were cultured in microbead and 2D methods and cell viability tests showed comparable compound inhibition in both methods (R2=0.95). In a further technology assessment, an image-based assay system was investigated for its utility as a possible complement to ATP-based detection for quantifying cell growth and viability in a label-free manner.

Identifying Behavioral Barriers to Campus Sustainability: A Multi-Method Approach

ERIC Educational Resources Information Center

Horhota, Michelle; Asman, Jenni; Stratton, Jeanine P.; Halfacre, Angela C.

2014-01-01

Purpose: The purpose of this paper is to assess the behavioral barriers to sustainable action in a campus community. Design/methodology/approach: This paper reports three different methodological approaches to the assessment of behavioral barriers to sustainable actions on a college campus. Focus groups and surveys were used to assess campus…

Mindfulness practice: A promising approach to reducing the effects of clinician implicit bias on patients.

PubMed

Burgess, Diana J; Beach, Mary Catherine; Saha, Somnath

2017-02-01

Like the population at large, health care providers hold implicit racial and ethnic biases that may contribute to health care disparities. Little progress has been made in identifying and implementing effective strategies to address these normal but potentially harmful unconscious cognitive processes. We propose that meditation training designed to increase healthcare providers' mindfulness skills is a promising and potentially sustainable way to address this problem. Emerging evidence suggests that mindfulness practice can reduce the provider contribution to healthcare disparities through several mechanisms including: reducing the likelihood that implicit biases will be activated in the mind, increasing providers' awareness of and ability to control responses to implicit biases once activated, increasing self-compassion and compassion toward patients, and reducing internal sources of cognitive load (e.g., stress, burnout, and compassion fatigue). Mindfulness training may also have advantages over current approaches to addressing implicit bias because it focuses on the development of skills through practice, promotes a nonjudgmental approach, can circumvent resistance some providers feel when directly confronted with evidence of racism, and constitutes a holistic approach to promoting providers' well-being. We close with suggestions for how a mindfulness approach can be practically implemented and identify potential challenges and research gaps to be addressed. Published by Elsevier B.V.

Adverse Effects of Electronic Cigarette Use: A Concept Mapping Approach

PubMed Central

Nasim, Aashir; Rosas, Scott

2016-01-01

Abstract Introduction: Electronic cigarette (ECIG) use has grown rapidly in popularity within a short period of time. As ECIG products continue to evolve and more individuals begin using ECIGs, it is important to understand the potential adverse effects that are associated with ECIG use. The purpose of this study was to examine and describe the acute adverse effects associated with ECIG use. Methods: This study used an integrated, mixed-method participatory approach called concept mapping (CM). Experienced ECIG users ( n = 85) provided statements that answered the focus prompt “A specific negative or unpleasant effect (ie, physical or psychological) that I have experienced either during or immediately after using an electronic cigarette device is…” in an online program. Participants sorted these statements into piles of common themes and rated each statement. Using multidimensional scaling and hierarchical cluster analysis, a concept map of the adverse effects statements was created. Results: Participants generated 79 statements that completed the focus prompt and were retained by researchers. Analysis generated a map containing five clusters that characterized perceived adverse effects of ECIG use: Stigma, Worry/Guilt, Addiction Signs, Physical Effects, and Device/Vapor Problems. Conclusions: ECIG use is associated with adverse effects that should be monitored as ECIGs continue to grow in popularity. If ECIGs are to be regulated, policies should be created that minimize the likelihood of user identified adverse effects. Implications: This article provides a list of adverse effects reported by experienced ECIG users. This article organizes these effects into a conceptual model that may be useful for better understanding the adverse outcomes associated with ECIG use. These identified adverse effects may be useful for health professionals and policy makers. Health professionals should be aware of potential negative health effects that may be associated with

An ontological approach to identifying cases of chronic kidney disease from routine primary care data: a cross-sectional study.

PubMed

Cole, Nicholas I; Liyanage, Harshana; Suckling, Rebecca J; Swift, Pauline A; Gallagher, Hugh; Byford, Rachel; Williams, John; Kumar, Shankar; de Lusignan, Simon

2018-04-10

Accurately identifying cases of chronic kidney disease (CKD) from primary care data facilitates the management of patients, and is vital for surveillance and research purposes. Ontologies provide a systematic and transparent basis for clinical case definition and can be used to identify clinical codes relevant to all aspects of CKD care and its diagnosis. We used routinely collected primary care data from the Royal College of General Practitioners Research and Surveillance Centre. A domain ontology was created and presented in Ontology Web Language (OWL). The identification and staging of CKD was then carried out using two parallel approaches: (1) clinical coding consistent with a diagnosis of CKD; (2) laboratory-confirmed CKD, based on estimated glomerular filtration rate (eGFR) or the presence of proteinuria. The study cohort comprised of 1.2 million individuals aged 18 years and over. 78,153 (6.4%) of the population had CKD on the basis of an eGFR of < 60 mL/min/1.73m 2 , and a further 7366 (0.6%) individuals were identified as having CKD due to proteinuria. 19,504 (1.6%) individuals without laboratory-confirmed CKD had a clinical code consistent with the diagnosis. In addition, a subset of codes allowed for 1348 (0.1%) individuals receiving renal replacement therapy to be identified. Finding cases of CKD from primary care data using an ontological approach may have greater sensitivity than less comprehensive methods, particularly for identifying those receiving renal replacement therapy or with CKD stages 1 or 2. However, the possibility of inaccurate coding may limit the specificity of this method.

Neural underpinnings of the identifiable victim effect: affect shifts preferences for giving.

PubMed

Genevsky, Alexander; Västfjäll, Daniel; Slovic, Paul; Knutson, Brian

2013-10-23

The "identifiable victim effect" refers to peoples' tendency to preferentially give to identified versus anonymous victims of misfortune, and has been proposed to partly depend on affect. By soliciting charitable donations from human subjects during behavioral and neural (i.e., functional magnetic resonance imaging) experiments, we sought to determine whether and how affect might promote the identifiable victim effect. Behaviorally, subjects gave more to orphans depicted by photographs versus silhouettes, and their shift in preferences was mediated by photograph-induced feelings of positive arousal, but not negative arousal. Neurally, while photographs versus silhouettes elicited activity in widespread circuits associated with facial and affective processing, only nucleus accumbens activity predicted and could statistically account for increased donations. Together, these findings suggest that presenting evaluable identifiable information can recruit positive arousal, which then promotes giving. We propose that affect elicited by identifiable stimuli can compel people to give more to strangers, even despite costs to the self.

A Simple Test Identifies Selection on Complex Traits.

PubMed

Beissinger, Tim; Kruppa, Jochen; Cavero, David; Ha, Ngoc-Thuy; Erbe, Malena; Simianer, Henner

2018-05-01

Important traits in agricultural, natural, and human populations are increasingly being shown to be under the control of many genes that individually contribute only a small proportion of genetic variation. However, the majority of modern tools in quantitative and population genetics, including genome-wide association studies and selection-mapping protocols, are designed to identify individual genes with large effects. We have developed an approach to identify traits that have been under selection and are controlled by large numbers of loci. In contrast to existing methods, our technique uses additive-effects estimates from all available markers, and relates these estimates to allele-frequency change over time. Using this information, we generate a composite statistic, denoted [Formula: see text] which can be used to test for significant evidence of selection on a trait. Our test requires pre- and postselection genotypic data but only a single time point with phenotypic information. Simulations demonstrate that [Formula: see text] is powerful for identifying selection, particularly in situations where the trait being tested is controlled by many genes, which is precisely the scenario where classical approaches for selection mapping are least powerful. We apply this test to breeding populations of maize and chickens, where we demonstrate the successful identification of selection on traits that are documented to have been under selection. Copyright © 2018 Beissinger et al.

Myth 8: The "Patch-On" Approach to Programming Is Effective

ERIC Educational Resources Information Center

Tomlinson, Carol Ann

2009-01-01

It is not likely that any group of educators of the gifted ever sat around a table and came to the decision that a "patch-on" approach to programming for bright learners represented best practice. Nonetheless, it is as common today as 25 years ago that programming for students identified as gifted often represents such an approach. Patch-on…

A cost-effective approach to the development of printed materials: a randomized controlled trial of three strategies.

PubMed

Paul, C L; Redman, S; Sanson-Fisher, R W

2004-12-01

Printed materials have been a primary mode of communication in public health education. Three major approaches to the development of these materials--the application of characteristics identified in the literature, behavioral strategies and marketing strategies--have major implications for both the effectiveness and cost of materials. However, little attention has been directed towards the cost-effectiveness of such approaches. In the present study, three pamphlets were developed using successive addition of each approach: first literature characteristics only ('C' pamphlet), then behavioral strategies ('C + B' pamphlet) and then marketing strategies ('C + B + M' pamphlet). Each pamphlet encouraged women to join a Pap Test Reminder Service (PTRS). Each pamphlet was mailed to a randomly selected sample of 2700 women aged 50-69 years. Registrations with the PTRS were monitored and 420 women in each pamphlet group were surveyed by telephone. It was reported that the 'C + B' and 'C + B + M' pamphlets were significantly more effective than the 'C' pamphlet. The 'C + B' pamphlet was the most cost-effective of the three pamphlets. There were no significant differences between any of the pamphlet groups on acceptability, knowledge or attitudes. It was suggested that the inclusion of behavioral strategies is likely to be a cost-effective approach to the development of printed health education materials.

Identifying Personal Goals of Patients With Long Term Condition: A Service Design Thinking Approach.

PubMed

Lee, Eunji; Gammon, Deede

2017-01-01

Care for patients with long term conditions is often characterized as fragmented and ineffective, and fails to engage the resources of patients and their families in the care process. Information and communication technology can potentially help bridge the gap between patients' lives and resources and services provided by professionals. However, there is little attention on how to identify and incorporate the patients' individual needs, values, preferences and care goals into the digitally driven care settings. We conducted a case study with healthcare professionals and patients participated applying a service design thinking approach. The participants could elaborate some personal goals of patients with long term condition which can potentially be incorporated in digitally driven care plans using examples from their own experiences.

A Likelihood-Based Approach to Identifying Contaminated Food Products Using Sales Data: Performance and Challenges

PubMed Central

Kaufman, James; Lessler, Justin; Harry, April; Edlund, Stefan; Hu, Kun; Douglas, Judith; Thoens, Christian; Appel, Bernd; Käsbohrer, Annemarie; Filter, Matthias

2014-01-01

Foodborne disease outbreaks of recent years demonstrate that due to increasingly interconnected supply chains these type of crisis situations have the potential to affect thousands of people, leading to significant healthcare costs, loss of revenue for food companies, and—in the worst cases—death. When a disease outbreak is detected, identifying the contaminated food quickly is vital to minimize suffering and limit economic losses. Here we present a likelihood-based approach that has the potential to accelerate the time needed to identify possibly contaminated food products, which is based on exploitation of food products sales data and the distribution of foodborne illness case reports. Using a real world food sales data set and artificially generated outbreak scenarios, we show that this method performs very well for contamination scenarios originating from a single “guilty” food product. As it is neither always possible nor necessary to identify the single offending product, the method has been extended such that it can be used as a binary classifier. With this extension it is possible to generate a set of potentially “guilty” products that contains the real outbreak source with very high accuracy. Furthermore we explore the patterns of food distributions that lead to “hard-to-identify” foods, the possibility of identifying these food groups a priori, and the extent to which the likelihood-based method can be used to quantify uncertainty. We find that high spatial correlation of sales data between products may be a useful indicator for “hard-to-identify” products. PMID:24992565

A new approach to identify, classify and count drugrelated events

PubMed Central

Bürkle, Thomas; Müller, Fabian; Patapovas, Andrius; Sonst, Anja; Pfistermeister, Barbara; Plank-Kiegele, Bettina; Dormann, Harald; Maas, Renke

2013-01-01

Aims The incidence of clinical events related to medication errors and/or adverse drug reactions reported in the literature varies by a degree that cannot solely be explained by the clinical setting, the varying scrutiny of investigators or varying definitions of drug-related events. Our hypothesis was that the individual complexity of many clinical cases may pose relevant limitations for current definitions and algorithms used to identify, classify and count adverse drug-related events. Methods Based on clinical cases derived from an observational study we identified and classified common clinical problems that cannot be adequately characterized by the currently used definitions and algorithms. Results It appears that some key models currently used to describe the relation of medication errors (MEs), adverse drug reactions (ADRs) and adverse drug events (ADEs) can easily be misinterpreted or contain logical inconsistencies that limit their accurate use to all but the simplest clinical cases. A key limitation of current models is the inability to deal with complex interactions such as one drug causing two clinically distinct side effects or multiple drugs contributing to a single clinical event. Using a large set of clinical cases we developed a revised model of the interdependence between MEs, ADEs and ADRs and extended current event definitions when multiple medications cause multiple types of problems. We propose algorithms that may help to improve the identification, classification and counting of drug-related events. Conclusions The new model may help to overcome some of the limitations that complex clinical cases pose to current paper- or software-based drug therapy safety. PMID:24007453

Selected approaches for rational drug design and high throughput screening to identify anti-cancer molecules.

PubMed

Hedvat, Michael; Emdad, Luni; Das, Swadesh K; Kim, Keetae; Dasgupta, Santanu; Thomas, Shibu; Hu, Bin; Zhu, Shan; Dash, Rupesh; Quinn, Bridget A; Oyesanya, Regina A; Kegelman, Timothy P; Sokhi, Upneet K; Sarkar, Siddik; Erdogan, Eda; Menezes, Mitchell E; Bhoopathi, Praveen; Wang, Xiang-Yang; Pomper, Martin G; Wei, Jun; Wu, Bainan; Stebbins, John L; Diaz, Paul W; Reed, John C; Pellecchia, Maurizio; Sarkar, Devanand; Fisher, Paul B

2012-11-01

Structure-based modeling combined with rational drug design, and high throughput screening approaches offer significant potential for identifying and developing lead compounds with therapeutic potential. The present review focuses on these two approaches using explicit examples based on specific derivatives of Gossypol generated through rational design and applications of a cancer-specificpromoter derived from Progression Elevated Gene-3. The Gossypol derivative Sabutoclax (BI-97C1) displays potent anti-tumor activity against a diverse spectrum of human tumors. The model of the docked structure of Gossypol bound to Bcl-XL provided a virtual structure-activity-relationship where appropriate modifications were predicted on a rational basis. These structure-based studies led to the isolation of Sabutoclax, an optically pure isomer of Apogossypol displaying superior efficacy and reduced toxicity. These studies illustrate the power of combining structure-based modeling with rational design to predict appropriate derivatives of lead compounds to be empirically tested and evaluated for bioactivity. Another approach to cancer drug discovery utilizes a cancer-specific promoter as readouts of the transformed state. The promoter region of Progression Elevated Gene-3 is such a promoter with cancer-specific activity. The specificity of this promoter has been exploited as a means of constructing cancer terminator viruses that selectively kill cancer cells and as a systemic imaging modality that specifically visualizes in vivo cancer growth with no background from normal tissues. Screening of small molecule inhibitors that suppress the Progression Elevated Gene-3-promoter may provide relevant lead compounds for cancer therapy that can be combined with further structure-based approaches leading to the development of novel compounds for cancer therapy.

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

Simple Shared Motifs (SSM) in conserved region of promoters: a new approach to identify co-regulation patterns.

PubMed

Gruel, Jérémy; LeBorgne, Michel; LeMeur, Nolwenn; Théret, Nathalie

2011-09-12

Regulation of gene expression plays a pivotal role in cellular functions. However, understanding the dynamics of transcription remains a challenging task. A host of computational approaches have been developed to identify regulatory motifs, mainly based on the recognition of DNA sequences for transcription factor binding sites. Recent integration of additional data from genomic analyses or phylogenetic footprinting has significantly improved these methods. Here, we propose a different approach based on the compilation of Simple Shared Motifs (SSM), groups of sequences defined by their length and similarity and present in conserved sequences of gene promoters. We developed an original algorithm to search and count SSM in pairs of genes. An exceptional number of SSM is considered as a common regulatory pattern. The SSM approach is applied to a sample set of genes and validated using functional gene-set enrichment analyses. We demonstrate that the SSM approach selects genes that are over-represented in specific biological categories (Ontology and Pathways) and are enriched in co-expressed genes. Finally we show that genes co-expressed in the same tissue or involved in the same biological pathway have increased SSM values. Using unbiased clustering of genes, Simple Shared Motifs analysis constitutes an original contribution to provide a clearer definition of expression networks.

Simple Shared Motifs (SSM) in conserved region of promoters: a new approach to identify co-regulation patterns

PubMed Central

2011-01-01

Background Regulation of gene expression plays a pivotal role in cellular functions. However, understanding the dynamics of transcription remains a challenging task. A host of computational approaches have been developed to identify regulatory motifs, mainly based on the recognition of DNA sequences for transcription factor binding sites. Recent integration of additional data from genomic analyses or phylogenetic footprinting has significantly improved these methods. Results Here, we propose a different approach based on the compilation of Simple Shared Motifs (SSM), groups of sequences defined by their length and similarity and present in conserved sequences of gene promoters. We developed an original algorithm to search and count SSM in pairs of genes. An exceptional number of SSM is considered as a common regulatory pattern. The SSM approach is applied to a sample set of genes and validated using functional gene-set enrichment analyses. We demonstrate that the SSM approach selects genes that are over-represented in specific biological categories (Ontology and Pathways) and are enriched in co-expressed genes. Finally we show that genes co-expressed in the same tissue or involved in the same biological pathway have increased SSM values. Conclusions Using unbiased clustering of genes, Simple Shared Motifs analysis constitutes an original contribution to provide a clearer definition of expression networks. PMID:21910886

Systematic approach identifies RHOA as a potential biomarker therapeutic target for Asian gastric cancer.

PubMed

Chang, Hae Ryung; Nam, Seungyoon; Lee, Jinhyuk; Kim, Jin-Hee; Jung, Hae Rim; Park, Hee Seo; Park, Sungjin; Ahn, Young Zoo; Huh, Iksoo; Balch, Curt; Ku, Ja-Lok; Powis, Garth; Park, Taesung; Jeong, Jin-Hyun; Kim, Yon Hui

2016-12-06

Gastric cancer (GC) is a highly heterogeneous disease, in dire need of specific, biomarker-driven cancer therapies. While the accumulation of cancer "Big Data" has propelled the search for novel molecular targets for GC, its specific subpathway and cellular functions vary from patient to patient. In particular, mutations in the small GTPase gene RHOA have been identified in recent genome-wide sequencing of GC tumors. Moreover, protein overexpression of RHOA was reported in Chinese populations, while RHOA mutations were found in Caucasian GC tumors. To develop evidence-based precision medicine for heterogeneous cancers, we established a systematic approach to integrate transcriptomic and genomic data. Predicted signaling subpathways were then laboratory-validated both in vitro and in vivo, resulting in the identification of new candidate therapeutic targets. Here, we show: i) differences in RHOA expression patterns, and its pathway activity, between Asian and Caucasian GC tumors; ii) in vitro and in vivo perturbed RHOA expression inhibits GC cell growth in high RHOA-expressing cell lines; iii) inverse correlation between RHOA and RHOB expression; and iv) an innovative small molecule design strategy for RHOA inhibitors. In summary, RHOA, and its oncogenic signaling pathway, represent a strong biomarker-driven therapeutic target for Asian GC. This comprehensive strategy represents a promising approach for the development of "hit" compounds.

A Neural Network Approach for Identifying Particle Pitch Angle Distributions in Van Allen Probes Data

NASA Technical Reports Server (NTRS)

Souza, V. M.; Vieira, L. E. A.; Medeiros, C.; Da Silva, L. A.; Alves, L. R.; Koga, D.; Sibeck, D. G.; Walsh, B. M.; Kanekal, S. G.; Jauer, P. R.;

Using Social Media Data to Identify Potential Candidates for Drug Repurposing: A Feasibility Study.

PubMed

Rastegar-Mojarad, Majid; Liu, Hongfang; Nambisan, Priya

2016-06-16

Drug repurposing (defined as discovering new indications for existing drugs) could play a significant role in drug development, especially considering the declining success rates of developing novel drugs. Typically, new indications for existing medications are identified by accident. However, new technologies and a large number of available resources enable the development of systematic approaches to identify and validate drug-repurposing candidates. Patients today report their experiences with medications on social media and reveal side effects as well as beneficial effects of those medications. Our aim was to assess the feasibility of using patient reviews from social media to identify potential candidates for drug repurposing. We retrieved patient reviews of 180 medications from an online forum, WebMD. Using dictionary-based and machine learning approaches, we identified disease names in the reviews. Several publicly available resources were used to exclude comments containing known indications and adverse drug effects. After manually reviewing some of the remaining comments, we implemented a rule-based system to identify beneficial effects. The dictionary-based system and machine learning system identified 2178 and 6171 disease names respectively in 64,616 patient comments. We provided a list of 10 common patterns that patients used to report any beneficial effects or uses of medication. After manually reviewing the comments tagged by our rule-based system, we identified five potential drug repurposing candidates. To our knowledge, this is the first study to consider using social media data to identify drug-repurposing candidates. We found that even a rule-based system, with a limited number of rules, could identify beneficial effect mentions in patient comments. Our preliminary study shows that social media has the potential to be used in drug repurposing.

Integrated genomic approaches identify major pathways and upstream regulators in late onset Alzheimer’s disease

PubMed Central

Li, Xinzhong; Long, Jintao; He, Taigang; Belshaw, Robert; Scott, James

2015-01-01

Previous studies have evaluated gene expression in Alzheimer’s disease (AD) brains to identify mechanistic processes, but have been limited by the size of the datasets studied. Here we have implemented a novel meta-analysis approach to identify differentially expressed genes (DEGs) in published datasets comprising 450 late onset AD (LOAD) brains and 212 controls. We found 3124 DEGs, many of which were highly correlated with Braak stage and cerebral atrophy. Pathway Analysis revealed the most perturbed pathways to be (a) nitric oxide and reactive oxygen species in macrophages (NOROS), (b) NFkB and (c) mitochondrial dysfunction. NOROS was also up-regulated, and mitochondrial dysfunction down-regulated, in healthy ageing subjects. Upstream regulator analysis predicted the TLR4 ligands, STAT3 and NFKBIA, for activated pathways and RICTOR for mitochondrial genes. Protein-protein interaction network analysis emphasised the role of NFKB; identified a key interaction of CLU with complement; and linked TYROBP, TREM2 and DOK3 to modulation of LPS signalling through TLR4 and to phosphatidylinositol metabolism. We suggest that NEUROD6, ZCCHC17, PPEF1 and MANBAL are potentially implicated in LOAD, with predicted links to calcium signalling and protein mannosylation. Our study demonstrates a highly injurious combination of TLR4-mediated NFKB signalling, NOROS inflammatory pathway activation, and mitochondrial dysfunction in LOAD. PMID:26202100

A Novel Proteomics Approach to Identify SUMOylated Proteins and Their Modification Sites in Human Cells*

PubMed Central

Galisson, Frederic; Mahrouche, Louiza; Courcelles, Mathieu; Bonneil, Eric; Meloche, Sylvain; Chelbi-Alix, Mounira K.; Thibault, Pierre

2011-01-01

The small ubiquitin-related modifier (SUMO) is a small group of proteins that are reversibly attached to protein substrates to modify their functions. The large scale identification of protein SUMOylation and their modification sites in mammalian cells represents a significant challenge because of the relatively small number of in vivo substrates and the dynamic nature of this modification. We report here a novel proteomics approach to selectively enrich and identify SUMO conjugates from human cells. We stably expressed different SUMO paralogs in HEK293 cells, each containing a His6 tag and a strategically located tryptic cleavage site at the C terminus to facilitate the recovery and identification of SUMOylated peptides by affinity enrichment and mass spectrometry. Tryptic peptides with short SUMO remnants offer significant advantages in large scale SUMOylome experiments including the generation of paralog-specific fragment ions following CID and ETD activation, and the identification of modified peptides using conventional database search engines such as Mascot. We identified 205 unique protein substrates together with 17 precise SUMOylation sites present in 12 SUMO protein conjugates including three new sites (Lys-380, Lys-400, and Lys-497) on the protein promyelocytic leukemia. Label-free quantitative proteomics analyses on purified nuclear extracts from untreated and arsenic trioxide-treated cells revealed that all identified SUMOylated sites of promyelocytic leukemia were differentially SUMOylated upon stimulation. PMID:21098080

Identifying a set of influential spreaders in complex networks

NASA Astrophysics Data System (ADS)

Zhang, Jian-Xiong; Chen, Duan-Bing; Dong, Qiang; Zhao, Zhi-Dan

2016-06-01

Identifying a set of influential spreaders in complex networks plays a crucial role in effective information spreading. A simple strategy is to choose top-r ranked nodes as spreaders according to influence ranking method such as PageRank, ClusterRank and k-shell decomposition. Besides, some heuristic methods such as hill-climbing, SPIN, degree discount and independent set based are also proposed. However, these approaches suffer from a possibility that some spreaders are so close together that they overlap sphere of influence or time consuming. In this report, we present a simply yet effectively iterative method named VoteRank to identify a set of decentralized spreaders with the best spreading ability. In this approach, all nodes vote in a spreader in each turn, and the voting ability of neighbors of elected spreader will be decreased in subsequent turn. Experimental results on four real networks show that under Susceptible-Infected-Recovered (SIR) and Susceptible-Infected (SI) models, VoteRank outperforms the traditional benchmark methods on both spreading rate and final affected scale. What’s more, VoteRank has superior computational efficiency.

Identifying the "Truly Disadvantaged": A Comprehensive Biosocial Approach

ERIC Educational Resources Information Center

Barnes, J. C.; Beaver, Kevin M.; Connolly, Eric J.; Schwartz, Joseph A.

2016-01-01

There has been significant interest in examining the developmental factors that predispose individuals to chronic criminal offending. This body of research has identified some social-environmental risk factors as potentially important. At the same time, the research producing these results has generally failed to employ genetically sensitive…

From partnerships to networks: new approaches for measuring U.S. National Heritage Area effectiveness.

PubMed

Laven, Daniel N; Krymkowski, Daniel H; Ventriss, Curtis L; Manning, Robert E; Mitchell, Nora J

2010-08-01

National Heritage Areas (NHAs) are an alternative and increasingly popular form of protected area management in the United States. NHAs seek to integrate environmental objectives with community and economic objectives at regional or landscape scales. NHA designations have increased rapidly in the last 20 years, generating a substantial need for evaluative information about (a) how NHAs work; (b) outcomes associated with the NHA process; and (c) the costs and benefits of investing public moneys into the NHA approach. Qualitative evaluation studies recently conducted at three NHAs have identified the importance of understanding network structure and function in the context of evaluating NHA management effectiveness. This article extends these case studies by examining quantitative network data from each of the sites. The authors analyze these data using both a descriptive approach and a statistically more robust approach known as exponential random graph modeling. Study findings indicate the presence of transitive structures and the absence of three-cycle structures in each of these networks. This suggests that these networks are relatively ''open,'' which may be desirable, given the uncertainty of the environments in which they operate. These findings also suggest, at least at the sites reported here, that the NHA approach may be an effective way to activate and develop networks of intersectoral organizational partners. Finally, this study demonstrates the utility of using quantitative network analysis to better understand the effectiveness of protected area management models that rely on partnership networks to achieve their intended outcomes.

Novel colchicine-site binders with a cyclohexanedione scaffold identified through a ligand-based virtual screening approach.

PubMed

Canela, María-Dolores; Pérez-Pérez, María-Jesús; Noppen, Sam; Sáez-Calvo, Gonzalo; Díaz, J Fernando; Camarasa, María-José; Liekens, Sandra; Priego, Eva-María

2014-05-22

Vascular disrupting agents (VDAs) constitute an innovative anticancer therapy that targets the tumor endothelium, leading to tumor necrosis. Our approach for the identification of new VDAs has relied on a ligand 3-D shape similarity virtual screening (VS) approach using the ROCS program as the VS tool and as query colchicine and TN-16, which both bind the α,β-tubulin dimer. One of the hits identified, using TN-16 as query, has been explored by the synthesis of its structural analogues, leading to 2-(1-((2-methoxyphenyl)amino)ethylidene)-5-phenylcyclohexane-1,3-dione (compound 16c) with an IC50 = 0.09 ± 0.01 μM in HMEC-1 and BAEC, being 100-fold more potent than the initial hit. Compound 16c caused cell cycle arrest in the G2/M phase and interacted with the colchicine-binding site in tubulin, as confirmed by a competition assay with N,N'-ethylenebis(iodoacetamide) and by fluorescence spectroscopy. Moreover, 16c destroyed an established endothelial tubular network at 1 μM and inhibited the migration and invasion of human breast carcinoma cells at 0.4 μM. In conclusion, our approach has led to a new chemotype of promising antiproliferative compounds with antimitotic and potential VDA properties.

Identifying effective pathways in a successful continuous quality improvement programme: the GEDAPS study.

PubMed

Bodicoat, Danielle H; Mundet, Xavier; Gray, Laura J; Cos, Xavier; Davies, Melanie J; Khunti, Kamlesh; Cano, Juan-Franciso

2014-12-01

Continuous quality improvement programmes often target several aspects of care, some of which may be more effective meaning that resources could be focussed on these. The objective was to identify the effective and ineffective aspects of a successful continuous quality improvement programme for individuals with type 2 diabetes in primary care. Data were from a series of cross-sectional studies (GEDAPS) in primary care, Catalonia, Spain, in 55 centres (2239 participants) in 1993, and 92 centres (5819 participants) in 2002. A structural equation modelling approach was used. The intervention was associated with improved microvascular outcomes through microalbuminuria and funduscopy screening, which had a direct effect on microvascular outcomes, and through attending 2-4 nurse visits and having ≥1 blood pressure measurement, which acted through reducing systolic blood pressure. The intervention was associated with improved macrovascular outcomes through blood pressure measurement and attending 2-4 nurse visits (through systolic blood pressure) and having ≥3 education topics, ≥1 HbA1c measurement and adequate medication (through HbA1c). Cholesterol measurement, weight measurement and foot examination did not contribute towards the effectiveness of the intervention. The pathways through which a continuous quality improvement programme appeared to act to reduce microvascular and macrovascular complications were driven by reductions in systolic blood pressure and HbA1c, which were attained through changes in nurse and education visits, measurement and medication. This suggests that these factors are potential areas on which future quality improvement programmes should focus. © 2014 John Wiley & Sons, Ltd.

The anterior interhemispheric approach: a safe and effective approach to anterior skull base lesions.

PubMed

Mielke, Dorothee; Mayfrank, Lothar; Psychogios, Marios Nikos; Rohde, Veit

2014-04-01

Many approaches to the anterior skull base have been reported. Frequently used are the pterional, the unilateral or bilateral frontobasal, the supraorbital and the frontolateral approach. Recently, endoscopic transnasal approaches have become more popular. The benefits of each approach has to be weighted against its complications and limitations. The aim of this study was to investigate if the anterior interhemispheric approach (AIA) could be a safe and effective alternative approach to tumorous and non-tumorous lesions of the anterior skull base. We screened the operative records of all patients with an anterior skull base lesion undergoing transcranial surgery. We have used the AIA in 61 patients. These were exclusively patients with either olfactory groove meningioma (OGM) (n = 43), ethmoidal dural arteriovenous fistula (dAVF) ( n = 6) or frontobasal fractures of the anterior midline with cerebrospinal fluid (CSF) leakage ( n = 12). Patient records were evaluated concerning accessibility of the lesion, realization of surgical aims (complete tumor removal, dAVF obliteration, closure of the dural tear), and approach related complications. The use of the AIA exclusively in OGMs, ethmoidal dAVFs and midline frontobasal fractures indicated that we considered lateralized frontobasal lesions not suitable to be treated successfully. If restricted to these three pathologies, the AIA is highly effective and safe. The surgical aim (complete tumor removal, complete dAVF occlusion, no rhinorrhea) was achieved in all patients. The complication rate was 11.5 % (wound infection (n = 2; 3.2 %), contusion of the genu of the corpus callosum, subdural hygroma, epileptic seizure, anosmia and asymptomatic bleed into the tumor cavity (n = 1 each). Only the contusion of the corpus callosum was directly related to the approach (1.6 %). Olfaction, if present before surgery, was preserved in all patients, except one (1.6 %). The AIA is an effective and a safe approach

Identifying Disease Associated miRNAs Based on Protein Domains.

PubMed

Qin, Gui-Min; Li, Rui-Yi; Zhao, Xing-Ming

2016-01-01

MicroRNAs (miRNAs) are a class of small endogenous non-coding genes, acting as regulators in the post-transcriptional processes. Recently, the miRNAs are found to be widely involved in different types of diseases. Therefore, the identification of disease associated miRNAs can help understand the mechanisms that underlie the disease and identify new biomarkers. However, it is not easy to identify the miRNAs related to diseases due to its extensive involvements in various biological processes. In this work, we present a new approach to identify disease associated miRNAs based on domains, the functional and structural blocks of proteins. The results on real datasets demonstrate that our method can effectively identify disease related miRNAs with high precision.

Analysis of bullwhip effect on supply chain with Q model using Hadley-Within approach

NASA Astrophysics Data System (ADS)

Siregar, I.; Nasution, A. A.; Matondang, N.; Persada, M. R.; Syahputri, K.

2018-02-01

This research held on a tapioca flour industry company that uses cassava as raw material to produce tapioca starch product. Problems that occur in this company is inaccurate planning, consequently there is a shortage of variation between the number of requests with the total supply is met, so it is necessary to do research with the formulation of the problem that is how to analyze the Bullwhip Effect on the supply chain using Q model through Hadley-Within approach so as not to disturb the product distribution system at the company. Product distribution system at the company, obtained by the number of requests. The 2015 forecast result is lower than actual demand for distributors and manufactures in 2016 with average percentage difference for Supermarket A distributor, Supermarket B and manufacturing respectively 38.24%, 89.57% and 43.11%. The occurrence of information distortion to the demand of this product can identify the existence of bullwhip effect on the supply chain. The proposed improvement to overcome the bullwhip effect is by doing inventory control policy with Q model using Hadley-Within approach.

Developing the practice context to enable more effective pain management with older people: an action research approach

PubMed Central

2011-01-01

Background This paper, which draws upon an Emancipatory Action Research (EAR) approach, unearths how the complexities of context influence the realities of nursing practice. While the intention of the project was to identify and change factors in the practice context that inhibit effective person-centred pain management practices with older people (65 years or older), reflective critical engagement with the findings identified that enhancing pain management practices with older people was dependent on cultural change in the unit as a whole. Methods An EAR approach was utilised. The project was undertaken in a surgical unit that conducted complex abdominal surgery. Eighty-five percent (n = 48) of nursing staff participated in the two-year project (05/NIR02/107). Data were obtained through the use of facilitated critical reflection with nursing staff. Results Three key themes (psychological safety, leadership, oppression) and four subthemes (power, horizontal violence, distorted perceptions, autonomy) were found to influence the way in which effective nursing practice was realised. Within the theme of 'context,' effective leadership and the creation of a psychologically safe environment were key elements in the enhancement of all aspects of nursing practice. Conclusions Whilst other research has identified the importance of 'practice context' and models and frameworks are emerging to address this issue, the theme of 'psychological safety' has been given little attention in the knowledge translation/implementation literature. Within the principles of EAR, facilitated reflective sessions were found to create 'psychologically safe spaces' that supported practitioners to develop effective person-centred nursing practices in complex clinical environments. PMID:21284857

Effectively identifying user profiles in network and host metrics

NASA Astrophysics Data System (ADS)

Murphy, John P.; Berk, Vincent H.; Gregorio-de Souza, Ian

2010-04-01

This work presents a collection of methods that is used to effectively identify users of computers systems based on their particular usage of the software and the network. Not only are we able to identify individual computer users by their behavioral patterns, we are also able to detect significant deviations in their typical computer usage over time, or compared to a group of their peers. For instance, most people have a small, and relatively unique selection of regularly visited websites, certain email services, daily work hours, and typical preferred applications for mandated tasks. We argue that these habitual patterns are sufficiently specific to identify fully anonymized network users. We demonstrate that with only a modest data collection capability, profiles of individual computer users can be constructed so as to uniquely identify a profiled user from among their peers. As time progresses and habits or circumstances change, the methods presented update each profile so that changes in user behavior can be reliably detected over both abrupt and gradual time frames, without losing the ability to identify the profiled user. The primary benefit of our methodology allows one to efficiently detect deviant behaviors, such as subverted user accounts, or organizational policy violations. Thanks to the relative robustness, these techniques can be used in scenarios with very diverse data collection capabilities, and data privacy requirements. In addition to behavioral change detection, the generated profiles can also be compared against pre-defined examples of known adversarial patterns.

Identifying strategies to improve the effectiveness of booster seat laws

DOT National Transportation Integrated Search

2008-05-01

The objective of this project was to identify strategies to improve the effectiveness of booster seat laws. The project explored the possible factors that relate to the use and nonuse of booster seats, and examined the attitudes of law enforcement of...

Metabolomic approach to identifying bioactive compounds in berries: advances toward fruit nutritional enhancement.

PubMed

Stewart, Derek; McDougall, Gordon J; Sungurtas, Julie; Verrall, Susan; Graham, Julie; Martinussen, Inger

2007-06-01

Plant polyphenolics continue to be the focus of attention with regard to their putative impact on human health. An increasing and ageing human population means that the focus on nutrition and nutritional enhancement or optimisation of our foodstuffs is paramount. Using the raspberry as a model, we have shown how modern metabolic profiling approaches can be used to identify the changes in the level of beneficial polyphenolics in fruit breeding segregating populations and how the level of these components is determined by genetic and/or environmental control. Interestingly, the vitamin C content appeared to be significantly influenced by environment (growth conditions) whilst the content of the polyphenols such as cyanidin, pelargonidin and quercetin glycosides appeared much more tightly regulated, suggesting a rigorous genetic control. Preliminary metabolic profiling showed that the fruit polyphenolic profiles divided into two gross groups segregating on the basis of relative levels of cyanidin-3-sophoroside and cyanidin-3-rutinoside, compounds implicated as conferring human health benefits.

Developing a model for effective leadership in healthcare: a concept mapping approach.

PubMed

Hargett, Charles William; Doty, Joseph P; Hauck, Jennifer N; Webb, Allison Mb; Cook, Steven H; Tsipis, Nicholas E; Neumann, Julie A; Andolsek, Kathryn M; Taylor, Dean C

2017-01-01

Despite increasing awareness of the importance of leadership in healthcare, our understanding of the competencies of effective leadership remains limited. We used a concept mapping approach (a blend of qualitative and quantitative analysis of group processes to produce a visual composite of the group's ideas) to identify stakeholders' mental model of effective healthcare leadership, clarifying the underlying structure and importance of leadership competencies. Literature review, focus groups, and consensus meetings were used to derive a representative set of healthcare leadership competency statements. Study participants subsequently sorted and rank-ordered these statements based on their perceived importance in contributing to effective healthcare leadership in real-world settings. Hierarchical cluster analysis of individual sortings was used to develop a coherent model of effective leadership in healthcare. A diverse group of 92 faculty and trainees individually rank-sorted 33 leadership competency statements. The highest rated statements were "Acting with Personal Integrity", "Communicating Effectively", "Acting with Professional Ethical Values", "Pursuing Excellence", "Building and Maintaining Relationships", and "Thinking Critically". Combining the results from hierarchical cluster analysis with our qualitative data led to a healthcare leadership model based on the core principle of Patient Centeredness and the core competencies of Integrity, Teamwork, Critical Thinking, Emotional Intelligence, and Selfless Service. Using a mixed qualitative-quantitative approach, we developed a graphical representation of a shared leadership model derived in the healthcare setting. This model may enhance learning, teaching, and patient care in this important area, as well as guide future research.

Combinatorial Drug Screening Identifies Ewing Sarcoma-specific Sensitivities.

PubMed

Radic-Sarikas, Branka; Tsafou, Kalliopi P; Emdal, Kristina B; Papamarkou, Theodore; Huber, Kilian V M; Mutz, Cornelia; Toretsky, Jeffrey A; Bennett, Keiryn L; Olsen, Jesper V; Brunak, Søren; Kovar, Heinrich; Superti-Furga, Giulio

2017-01-01

Improvements in survival for Ewing sarcoma pediatric and adolescent patients have been modest over the past 20 years. Combinations of anticancer agents endure as an option to overcome resistance to single treatments caused by compensatory pathways. Moreover, combinations are thought to lessen any associated adverse side effects through reduced dosing, which is particularly important in childhood tumors. Using a parallel phenotypic combinatorial screening approach of cells derived from three pediatric tumor types, we identified Ewing sarcoma-specific interactions of a diverse set of targeted agents including approved drugs. We were able to retrieve highly synergistic drug combinations specific for Ewing sarcoma and identified signaling processes important for Ewing sarcoma cell proliferation determined by EWS-FLI1 We generated a molecular target profile of PKC412, a multikinase inhibitor with strong synergistic propensity in Ewing sarcoma, revealing its targets in critical Ewing sarcoma signaling routes. Using a multilevel experimental approach including quantitative phosphoproteomics, we analyzed the molecular rationale behind the disease-specific synergistic effect of simultaneous application of PKC412 and IGF1R inhibitors. The mechanism of the drug synergy between these inhibitors is different from the sum of the mechanisms of the single agents. The combination effectively inhibited pathway crosstalk and averted feedback loop repression, in EWS-FLI1-dependent manner. Mol Cancer Ther; 16(1); 88-101. ©2016 AACR. ©2016 American Association for Cancer Research.

Identifying and mitigating batch effects in whole genome sequencing data.

PubMed

Tom, Jennifer A; Reeder, Jens; Forrest, William F; Graham, Robert R; Hunkapiller, Julie; Behrens, Timothy W; Bhangale, Tushar R

2017-07-24

Large sample sets of whole genome sequencing with deep coverage are being generated, however assembling datasets from different sources inevitably introduces batch effects. These batch effects are not well understood and can be due to changes in the sequencing protocol or bioinformatics tools used to process the data. No systematic algorithms or heuristics exist to detect and filter batch effects or remove associations impacted by batch effects in whole genome sequencing data. We describe key quality metrics, provide a freely available software package to compute them, and demonstrate that identification of batch effects is aided by principal components analysis of these metrics. To mitigate batch effects, we developed new site-specific filters that identified and removed variants that falsely associated with the phenotype due to batch effect. These include filtering based on: a haplotype based genotype correction, a differential genotype quality test, and removing sites with missing genotype rate greater than 30% after setting genotypes with quality scores less than 20 to missing. This method removed 96.1% of unconfirmed genome-wide significant SNP associations and 97.6% of unconfirmed genome-wide significant indel associations. We performed analyses to demonstrate that: 1) These filters impacted variants known to be disease associated as 2 out of 16 confirmed associations in an AMD candidate SNP analysis were filtered, representing a reduction in power of 12.5%, 2) In the absence of batch effects, these filters removed only a small proportion of variants across the genome (type I error rate of 3%), and 3) in an independent dataset, the method removed 90.2% of unconfirmed genome-wide SNP associations and 89.8% of unconfirmed genome-wide indel associations. Researchers currently do not have effective tools to identify and mitigate batch effects in whole genome sequencing data. We developed and validated methods and filters to address this deficiency.

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

PubMed

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

2009-02-01

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

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

PubMed Central

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

2009-01-01

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

Students' Perceptions about Online Teaching Effectiveness: A Bottom-Up Approach for Identifying Online Instructors' Roles

ERIC Educational Resources Information Center

Gómez-Rey, Pilar; Barbera, Elena; Fernández-Navarro, Francisco

2018-01-01

The topic of online instructors' roles has been of interest to the educational community since the late twentieth century. In previous studies, the identification of online instructors' roles was done using a top-down (deductive) approach. This study applied a bottom-up (inductive) procedure to examine not only the roles of online instructors from…

Instructional Approaches in Teaching the Holocaust

ERIC Educational Resources Information Center

Lindquist, David H.

2011-01-01

Holocaust education requires teachers to carefully determine which instructional approaches ensure effective teaching of the subject while avoiding potential difficulties. The article identifies several complicating factors that must be considered when making pedagogical decisions. It then examines five methodological approaches that can be used…

Omics Approaches for Identifying Physiological Adaptations to Genome Instability in Aging.

PubMed

Edifizi, Diletta; Schumacher, Björn

2017-11-04

DNA damage causally contributes to aging and age-related diseases. The declining functioning of tissues and organs during aging can lead to the increased risk of succumbing to aging-associated diseases. Congenital syndromes that are caused by heritable mutations in DNA repair pathways lead to cancer susceptibility and accelerated aging, thus underlining the importance of genome maintenance for withstanding aging. High-throughput mass-spectrometry-based approaches have recently contributed to identifying signalling response networks and gaining a more comprehensive understanding of the physiological adaptations occurring upon unrepaired DNA damage. The insulin-like signalling pathway has been implicated in a DNA damage response (DDR) network that includes epidermal growth factor (EGF)-, AMP-activated protein kinases (AMPK)- and the target of rapamycin (TOR)-like signalling pathways, which are known regulators of growth, metabolism, and stress responses. The same pathways, together with the autophagy-mediated proteostatic response and the decline in energy metabolism have also been found to be similarly regulated during natural aging, suggesting striking parallels in the physiological adaptation upon persistent DNA damage due to DNA repair defects and long-term low-level DNA damage accumulation occurring during natural aging. These insights will be an important starting point to study the interplay between signalling networks involved in progeroid syndromes that are caused by DNA repair deficiencies and to gain new understanding of the consequences of DNA damage in the aging process.

The interprocess NIR sampling as an alternative approach to multivariate statistical process control for identifying sources of product-quality variability.

PubMed

Marković, Snežana; Kerč, Janez; Horvat, Matej

2017-03-01

We are presenting a new approach of identifying sources of variability within a manufacturing process by NIR measurements of samples of intermediate material after each consecutive unit operation (interprocess NIR sampling technique). In addition, we summarize the development of a multivariate statistical process control (MSPC) model for the production of enteric-coated pellet product of the proton-pump inhibitor class. By developing provisional NIR calibration models, the identification of critical process points yields comparable results to the established MSPC modeling procedure. Both approaches are shown to lead to the same conclusion, identifying parameters of extrusion/spheronization and characteristics of lactose that have the greatest influence on the end-product's enteric coating performance. The proposed approach enables quicker and easier identification of variability sources during manufacturing process, especially in cases when historical process data is not straightforwardly available. In the presented case the changes of lactose characteristics are influencing the performance of the extrusion/spheronization process step. The pellet cores produced by using one (considered as less suitable) lactose source were on average larger and more fragile, leading to consequent breakage of the cores during subsequent fluid bed operations. These results were confirmed by additional experimental analyses illuminating the underlying mechanism of fracture of oblong pellets during the pellet coating process leading to compromised film coating.

New probiotic strains for inflammatory bowel disease management identified by combining in vitro and in vivo approaches.

PubMed

Alard, J; Peucelle, V; Boutillier, D; Breton, J; Kuylle, S; Pot, B; Holowacz, S; Grangette, C

2018-02-27

Alterations in the gut microbiota composition play a key role in the development of chronic diseases such as inflammatory bowel disease (IBD). The potential use of probiotics therefore gained attention, although outcomes were sometimes conflicting and results largely strain-dependent. The present study aimed to identify new probiotic strains that have a high potential for the management of this type of pathologies. Strains were selected from a large collection by combining different in vitro and in vivo approaches, addressing both anti-inflammatory potential and ability to improve the gut barrier function. We identified six strains with an interesting anti-inflammatory profile on peripheral blood mononuclear cells and with the ability to restore the gut barrier using a gut permeability model based on Caco-2 cells sensitized with hydrogen peroxide. The in vivo evaluation in two 2,4,6-trinitrobenzene sulfonic acid-induced murine models of colitis highlighted that some of the strains exhibited beneficial activities against acute colitis while others improved chronic colitis. Bifidobacterium bifidum PI22, the strain that exhibited the most protective capacities against acute colitis was only slightly efficacious against chronic colitis, while Bifidobacterium lactis LA804 which was less efficacious in the acute model was the most protective against chronic colitis. Lactobacillus helveticus PI5 was not anti-inflammatory in vitro but the best in strengthening the epithelial barrier and as such able to significantly dampen murine acute colitis. Interestingly, Lactobacillus salivarius LA307 protected mice significantly against both types of colitis. This work provides crucial clues for selecting the best strains for more efficacious therapeutic approaches in the management of chronic inflammatory diseases. The strategy employed allowed us to identify four strains with different characteristics and a high potential for the management of inflammatory diseases, such as IBD.

Curricular Approaches in Research Ethics Education: Reflecting on More and Less Effective Practices in Instructional Content.

PubMed

Torrence, Brett S; Watts, Logan L; Mulhearn, Tyler J; Turner, Megan R; Todd, E Michelle; Mumford, Michael D; Connelly, Shane

2017-01-01

Over the past decade, the effectiveness of ethics education programs has increased with regard to trainee outcomes, such as knowledge, awareness, and ethical decision making. However, despite the overall improvement in training effectiveness, considerable variability still exists across programs. One potential source of variability arises from the substantial range in instructional training content utilized across ethics training courses. The goal of the present effort was to clarify which approaches in ethics education result in positive training outcomes through the identification of instructional content themes. Through a qualitative review of ethics training courses, we identified key themes in instructional content curriculum associated with effective courses: domain-general, domain-specific, standard compliance, professionalism, and process-based. In addition, we identified key themes associated with less effective courses: mixed-specificity, narrow coverage, and idealized ethics. Descriptions and key characteristics of each theme along with example courses are provided. Implications of the content themes for ethics education are discussed.

Identifying Creatively Gifted Students: Necessity of a Multi-Method Approach

ERIC Educational Resources Information Center

Ambrose, Laura; Machek, Greg R.

2015-01-01

The process of identifying students as creatively gifted provides numerous challenges for educators. Although many schools assess for creativity in identifying students for gifted and talented services, the relationship between creativity and giftedness is often not fully understood. This article reviews commonly used methods of creativity…

An integrated approach towards identifying age-related mechanisms of slip initiated falls

PubMed Central

Lockhart, Thurmon E.

2008-01-01

The causes of slip and fall accidents, both in terms of extrinsic and intrinsic factors and their associations are not yet fully understood. Successful intervention solutions for reducing slip and fall accidents require a more complete understanding of the mechanisms involved. Before effective fall prevention strategies can be put into practice, it is central to examine the chain of events in an accident, comprising the exposure to hazards, initiation of events and the final outcome leading to injury and disability. These events can be effectively identified and analyzed by applying epidemiological, psychophysical, biomechanical and tribological research principles and methodologies. In this manuscript, various methods available to examine fall accidents and their underlying mechanisms are presented to provide a comprehensive array of information to help pinpoint the needs and requirements of new interventions aimed at reducing the risk of falls among the growing elderly population. PMID:17768070

A Psychoevolutionary Approach to Identifying Preferred Nature Scenes With Potential to Provide Restoration From Stress.

PubMed

Thake, Carol L; Bambling, Matthew; Edirippulige, Sisira; Marx, Eric

2017-10-01

Research supports therapeutic use of nature scenes in healthcare settings, particularly to reduce stress. However, limited literature is available to provide a cohesive guide for selecting scenes that may provide optimal therapeutic effect. This study produced and tested a replicable process for selecting nature scenes with therapeutic potential. Psychoevolutionary theory informed the construction of the Importance for Survival Scale (IFSS), and its usefulness for identifying scenes that people generally prefer to view and that hold potential to reduce stress was tested. Relationships between Importance for Survival (IFS), preference, and restoration were tested. General community participants ( N = 20 males, 20 females; M age = 48 years) Q-sorted sets of landscape photographs (preranked by the researcher in terms of IFS using the IFSS) from most to least preferred, and then completed the Short-Version Revised Restoration Scale in response to viewing a selection of the scenes. Results showed significant positive relationships between IFS and each of scene preference (large effect), and restoration potential (medium effect), as well as between scene preference and restoration potential across the levels of IFS (medium effect), and for individual participants and scenes (large effect). IFS was supported as a framework for identifying nature scenes that people will generally prefer to view and that hold potential for restoration from emotional distress; however, greater therapeutic potential may be expected when people can choose which of the scenes they would prefer to view. Evidence for the effectiveness of the IFSS was produced.

Systematic approach identifies RHOA as a potential biomarker therapeutic target for Asian gastric cancer

PubMed Central

Jung, Hae Rim; Park, Hee Seo; Park, Sungjin; Ahn, Young Zoo; Huh, Iksoo; Balch, Curt; Ku, Ja-Lok; Powis, Garth; Park, Taesung; Jeong, Jin-Hyun; Kim, Yon Hui

2016-01-01

Gastric cancer (GC) is a highly heterogeneous disease, in dire need of specific, biomarker-driven cancer therapies. While the accumulation of cancer “Big Data” has propelled the search for novel molecular targets for GC, its specific subpathway and cellular functions vary from patient to patient. In particular, mutations in the small GTPase gene RHOA have been identified in recent genome-wide sequencing of GC tumors. Moreover, protein overexpression of RHOA was reported in Chinese populations, while RHOA mutations were found in Caucasian GC tumors. To develop evidence-based precision medicine for heterogeneous cancers, we established a systematic approach to integrate transcriptomic and genomic data. Predicted signaling subpathways were then laboratory-validated both in vitro and in vivo, resulting in the identification of new candidate therapeutic targets. Here, we show: i) differences in RHOA expression patterns, and its pathway activity, between Asian and Caucasian GC tumors; ii) in vitro and in vivo perturbed RHOA expression inhibits GC cell growth in high RHOA-expressing cell lines; iii) inverse correlation between RHOA and RHOB expression; and iv) an innovative small molecule design strategy for RHOA inhibitors. In summary, RHOA, and its oncogenic signaling pathway, represent a strong biomarker-driven therapeutic target for Asian GC. This comprehensive strategy represents a promising approach for the development of “hit” compounds. PMID:27806312

Characteristics of effective clinical teachers identified by dental students: a qualitative study.

PubMed

Jahangiri, L; McAndrew, M; Muzaffar, A; Mucciolo, T W

2013-02-01

This qualitative research study identified criteria for clinical teacher quality preferences as perceived by dental students. Third and fourth year dental students at New York University College of Dentistry were given a two question, open-ended survey asking what qualities they liked most and least in a clinical teacher. Responses were collected until data saturation was achieved. A total of 157 respondents provided a total of 995 written comments. Descriptive words within the responses were coded and grouped into key words, according to similar relationships, and further refined into 17 defined categories. Three core themes, Character, Competence and Communication, emerged from these 17 categories, which were validated according to specific references found in the existing educational literature. 'Character' comprised nine of the 17 defined categories: (caring, motivation, empathy, patience, professionalism, available, fairness, happiness, patient-centred) and yielded 59.1% of total student responses; 'Competence' consisted of five categories: knowledgeable, expertise, efficient, skilful, effective (29.2%); and 'Communication' represented the remaining three categories: feedback, approachable and interpersonal communication (11.7%). Positive and negative responses related to the defined category of caring were cited by 59.2% of all students. Motivation was the next highest category, cited by 45.9% of students. Non-cognitive attributes, especially those in the Character theme, comprised the majority of student comments. Because students' perceptions are so critical to understanding clinical teaching effectiveness in dental education, these findings can be used to develop assessments to measure clinical teaching effectiveness, to create criteria for the hiring and promotion of clinical faculty and to plan faculty development programming. © 2012 John Wiley & Sons A/S. Published by Blackwell Publishing Ltd.

Molecular forensics in avian conservation: a DNA-based approach for identifying mammalian predators of ground-nesting birds and eggs.

PubMed

Hopken, Matthew W; Orning, Elizabeth K; Young, Julie K; Piaggio, Antoinette J

2016-01-07

The greater sage-grouse (Centrocercus urophasianus) is a ground-nesting bird from the Northern Rocky Mountains and a species at risk of extinction in in multiple U.S. states and Canada. Herein we report results from a proof of concept that mitochondrial and nuclear DNAs from mammalian predator saliva could be non-invasively collected from depredated greater sage-grouse eggshells and carcasses and used for predator species identification. Molecular forensic approaches have been applied to identify predators from depredated remains as one strategy to better understand predator-prey dynamics and guide management strategies. This can aid conservation efforts by correctly identifying predators most likely to impact threatened and endangered species. DNA isolated from non-invasive samples around nesting sites (e.g. fecal or hair samples) is one method that can increase the success and accuracy of predator species identification when compared to relying on nest remains alone. Predator saliva DNA was collected from depredated eggshells and carcasses using swabs. We sequenced two partial fragments of two mitochondrial genes and obtained microsatellite genotypes using canid specific primers for species and individual identification, respectively. Using this multilocus approach we were able to identify predators, at least down to family, from 11 out of 14 nests (79%) and three out of seven carcasses (47%). Predators detected most frequently were canids (86%), while other taxa included rodents, a striped skunk, and cattle. We attempted to match the genotypes of individual coyotes obtained from eggshells and carcasses with those obtained from fecal samples and coyotes collected in the areas, but no genotype matches were found. Predation is a main cause of nest failure in ground-nesting birds and can impact reproduction and recruitment. To inform predator management for ground-nesting bird conservation, accurate identification of predator species is necessary. Considering

A network approach for identifying and delimiting biogeographical regions.

PubMed

Vilhena, Daril A; Antonelli, Alexandre

2015-04-24

Biogeographical regions (geographically distinct assemblages of species and communities) constitute a cornerstone for ecology, biogeography, evolution and conservation biology. Species turnover measures are often used to quantify spatial biodiversity patterns, but algorithms based on similarity can be sensitive to common sampling biases in species distribution data. Here we apply a community detection approach from network theory that incorporates complex, higher-order presence-absence patterns. We demonstrate the performance of the method by applying it to all amphibian species in the world (c. 6,100 species), all vascular plant species of the USA (c. 17,600) and a hypothetical data set containing a zone of biotic transition. In comparison with current methods, our approach tackles the challenges posed by transition zones and succeeds in retrieving a larger number of commonly recognized biogeographical regions. This method can be applied to generate objective, data-derived identification and delimitation of the world's biogeographical regions.

Identifying Topics in Microblogs Using Wikipedia.

PubMed

Yıldırım, Ahmet; Üsküdarlı, Suzan; Özgür, Arzucan

2016-01-01

Twitter is an extremely high volume platform for user generated contributions regarding any topic. The wealth of content created at real-time in massive quantities calls for automated approaches to identify the topics of the contributions. Such topics can be utilized in numerous ways, such as public opinion mining, marketing, entertainment, and disaster management. Towards this end, approaches to relate single or partial posts to knowledge base items have been proposed. However, in microblogging systems like Twitter, topics emerge from the culmination of a large number of contributions. Therefore, identifying topics based on collections of posts, where individual posts contribute to some aspect of the greater topic is necessary. Models, such as Latent Dirichlet Allocation (LDA), propose algorithms for relating collections of posts to sets of keywords that represent underlying topics. In these approaches, figuring out what the specific topic(s) the keyword sets represent remains as a separate task. Another issue in topic detection is the scope, which is often limited to specific domain, such as health. This work proposes an approach for identifying domain-independent specific topics related to sets of posts. In this approach, individual posts are processed and then aggregated to identify key tokens, which are then mapped to specific topics. Wikipedia article titles are selected to represent topics, since they are up to date, user-generated, sophisticated articles that span topics of human interest. This paper describes the proposed approach, a prototype implementation, and a case study based on data gathered during the heavily contributed periods corresponding to the four US election debates in 2012. The manually evaluated results (0.96 precision) and other observations from the study are discussed in detail.

Identifying Topics in Microblogs Using Wikipedia

PubMed Central

Yıldırım, Ahmet; Üsküdarlı, Suzan; Özgür, Arzucan

2016-01-01

Twitter is an extremely high volume platform for user generated contributions regarding any topic. The wealth of content created at real-time in massive quantities calls for automated approaches to identify the topics of the contributions. Such topics can be utilized in numerous ways, such as public opinion mining, marketing, entertainment, and disaster management. Towards this end, approaches to relate single or partial posts to knowledge base items have been proposed. However, in microblogging systems like Twitter, topics emerge from the culmination of a large number of contributions. Therefore, identifying topics based on collections of posts, where individual posts contribute to some aspect of the greater topic is necessary. Models, such as Latent Dirichlet Allocation (LDA), propose algorithms for relating collections of posts to sets of keywords that represent underlying topics. In these approaches, figuring out what the specific topic(s) the keyword sets represent remains as a separate task. Another issue in topic detection is the scope, which is often limited to specific domain, such as health. This work proposes an approach for identifying domain-independent specific topics related to sets of posts. In this approach, individual posts are processed and then aggregated to identify key tokens, which are then mapped to specific topics. Wikipedia article titles are selected to represent topics, since they are up to date, user-generated, sophisticated articles that span topics of human interest. This paper describes the proposed approach, a prototype implementation, and a case study based on data gathered during the heavily contributed periods corresponding to the four US election debates in 2012. The manually evaluated results (0.96 precision) and other observations from the study are discussed in detail. PMID:26991442

An integrated chemical biology approach identifies specific vulnerability of Ewing's sarcoma to combined inhibition of Aurora kinases A and B.

PubMed

Winter, Georg E; Rix, Uwe; Lissat, Andrej; Stukalov, Alexey; Müllner, Markus K; Bennett, Keiryn L; Colinge, Jacques; Nijman, Sebastian M; Kubicek, Stefan; Kovar, Heinrich; Kontny, Udo; Superti-Furga, Giulio

2011-10-01

Ewing's sarcoma is a pediatric cancer of the bone that is characterized by the expression of the chimeric transcription factor EWS-FLI1 that confers a highly malignant phenotype and results from the chromosomal translocation t(11;22)(q24;q12). Poor overall survival and pronounced long-term side effects associated with traditional chemotherapy necessitate the development of novel, targeted, therapeutic strategies. We therefore conducted a focused viability screen with 200 small molecule kinase inhibitors in 2 different Ewing's sarcoma cell lines. This resulted in the identification of several potential molecular intervention points. Most notably, tozasertib (VX-680, MK-0457) displayed unique nanomolar efficacy, which extended to other cell lines, but was specific for Ewing's sarcoma. Furthermore, tozasertib showed strong synergies with the chemotherapeutic drugs etoposide and doxorubicin, the current standard agents for Ewing's sarcoma. To identify the relevant targets underlying the specific vulnerability toward tozasertib, we determined its cellular target profile by chemical proteomics. We identified 20 known and unknown serine/threonine and tyrosine protein kinase targets. Additional target deconvolution and functional validation by RNAi showed simultaneous inhibition of Aurora kinases A and B to be responsible for the observed tozasertib sensitivity, thereby revealing a new mechanism for targeting Ewing's sarcoma. We further corroborated our cellular observations with xenograft mouse models. In summary, the multilayered chemical biology approach presented here identified a specific vulnerability of Ewing's sarcoma to concomitant inhibition of Aurora kinases A and B by tozasertib and danusertib, which has the potential to become a new therapeutic option.

Under What Assumptions Do Site-by-Treatment Instruments Identify Average Causal Effects?

ERIC Educational Resources Information Center

Reardon, Sean F.; Raudenbush, Stephen W.

2013-01-01

The increasing availability of data from multi-site randomized trials provides a potential opportunity to use instrumental variables methods to study the effects of multiple hypothesized mediators of the effect of a treatment. We derive nine assumptions needed to identify the effects of multiple mediators when using site-by-treatment interactions…

Equipment Level Fallout Radiation Effects Approach

DTIC Science & Technology

1989-02-10

Electromagnetic Pulse (EMP) mitigation Program to evaluate and, where possible, mitigate the effects of the nuclear attack. Fallout radiation has been identified as an environment which may effect the performance of the regional and national telecommunication system. This report presents the investigations in the network level fallout radiation methodology used to determine the effects of this environment. Alternative techniques are presented to improve the

Identifying transit corridors for elephant using a long time-series

NASA Astrophysics Data System (ADS)

Pittiglio, Claudia; Skidmore, Andrew K.; van Gils, Hein A. M. J.; Prins, Herbert H. T.

2012-02-01

The role of corridors in mitigating the effects of landscape fragmentation on biodiversity is controversial. Recent studies have highlighted the need for new approaches in corridor design using long-term datasets. We present a method to identify transit corridors for elephant at a population scale over a large area and an extended period of time using long-term aerial surveys. We investigated environmental and anthropogenic factors directly and indirectly related to the wet versus dry season distribution of elephant and its transit corridors. Four environmental variables predicted the presence of elephant at the landscape scale in both seasons: distance from permanent water, protected areas and settlements and vegetation structure. Path analysis revealed that altitude and monthly average NDVI, and distance from temporary water had a significant indirect effect on elephant distribution at local scale in dry and wet seasons respectively. Five transit corridors connecting Tarangire National Park and the northern as well as south-eastern wet season dispersal areas were identified and matched the wildlife migration routes described in the 1960s. The corridors are stable over the decades, providing landscape connectivity for elephant. Our approach yielded insights how advanced spatial analysis can be integrated with biological data available from long-term datasets to identify actual transit corridors and predictors of species distribution.

A hybrid approach identifies metabolic signatures of high-producers for chinese hamster ovary clone selection and process optimization.

PubMed

Popp, Oliver; Müller, Dirk; Didzus, Katharina; Paul, Wolfgang; Lipsmeier, Florian; Kirchner, Florian; Niklas, Jens; Mauch, Klaus; Beaucamp, Nicola

2016-09-01

In-depth characterization of high-producer cell lines and bioprocesses is vital to ensure robust and consistent production of recombinant therapeutic proteins in high quantity and quality for clinical applications. This requires applying appropriate methods during bioprocess development to enable meaningful characterization of CHO clones and processes. Here, we present a novel hybrid approach for supporting comprehensive characterization of metabolic clone performance. The approach combines metabolite profiling with multivariate data analysis and fluxomics to enable a data-driven mechanistic analysis of key metabolic traits associated with desired cell phenotypes. We applied the methodology to quantify and compare metabolic performance in a set of 10 recombinant CHO-K1 producer clones and a host cell line. The comprehensive characterization enabled us to derive an extended set of clone performance criteria that not only captured growth and product formation, but also incorporated information on intracellular clone physiology and on metabolic changes during the process. These criteria served to establish a quantitative clone ranking and allowed us to identify metabolic differences between high-producing CHO-K1 clones yielding comparably high product titers. Through multivariate data analysis of the combined metabolite and flux data we uncovered common metabolic traits characteristic of high-producer clones in the screening setup. This included high intracellular rates of glutamine synthesis, low cysteine uptake, reduced excretion of aspartate and glutamate, and low intracellular degradation rates of branched-chain amino acids and of histidine. Finally, the above approach was integrated into a workflow that enables standardized high-content selection of CHO producer clones in a high-throughput fashion. In conclusion, the combination of quantitative metabolite profiling, multivariate data analysis, and mechanistic network model simulations can identify metabolic

Instruction-Based Approach-Avoidance Effects: Changing Stimulus Evaluation via the Mere Instruction to Approach or Avoid Stimuli.

PubMed

Van Dessel, Pieter; De Houwer, Jan; Gast, Anne; Tucker Smith, Colin

2015-01-01

Prior research suggests that repeatedly approaching or avoiding a certain stimulus changes the liking of this stimulus. We investigated whether these effects of approach and avoidance training occur also when participants do not perform these actions but are merely instructed about the stimulus-action contingencies. Stimulus evaluations were registered using both implicit (Implicit Association Test and evaluative priming) and explicit measures (valence ratings). Instruction-based approach-avoidance effects were observed for relatively neutral fictitious social groups (i.e., Niffites and Luupites), but not for clearly valenced well-known social groups (i.e., Blacks and Whites). We conclude that instructions to approach or avoid stimuli can provide sufficient bases for establishing both implicit and explicit evaluations of novel stimuli and discuss several possible reasons for why similar instruction-based approach-avoidance effects were not found for valenced well-known stimuli.

Identifying the Average Causal Mediation Effects with Multiple Mediators in the Presence of Treatment Non-Compliance

ERIC Educational Resources Information Center

Park, Soojin

2015-01-01

Identifying the causal mechanisms is becoming more essential in social and medical sciences. In the presence of treatment non-compliance, the Intent-To-Treated effect (hereafter, ITT effect) is identified as long as the treatment is randomized (Angrist et al., 1996). However, the mediated portion of effect is not identified without additional…

Practical limitations to a positive deviance approach for identifying dietary patterns compatible with the reduction of cancer risk.

PubMed

Vossenaar, M; Bermúdez, O I; Anderson, A S; Solomons, N W

2010-08-01

The positive deviance (PD) approach seeks to devise and promote health-promoting practices identified within the most successful member of a society. The World Cancer Research Fund and the American Institute for Cancer Research (WCRF/AICR) recommendations indicate the need for specific dietary behaviours, which may be considered impractical. Thus, it is important to demonstrate ways in which these dietary practices have been achieved from concordant individuals. The present study aimed to assess the feasibility of constructing healthy eating guides in four international settings. Adult participants from the Netherlands (n = 1052), Scotland (n = 849), Mexico (n = 790) and Guatemala (n = 873) enrolled in an international diet survey project. Participants with inadequate diets and current smokers were excluded from the analysis. Concordance with selected WCRF/AICR individual guideline components related to diet and lifestyle were evaluated. A selection of participants was made towards making a set of 14 rotating menus for a cancer-prevention healthy-eating guide. Overall concordance with the WCRF/AICR recommendations was low in all four nations and no participants with an ideal behaviour were found. The selection of candidates for constructing 14 daily menus for a single national guide identified 51, 13 and 12 individuals concordant with 11 of 14 WCRF/AICR recommendation components in Guatemala, Scotland and Mexico, respectively, and 24 individuals concordant with eight of 14 WCRF/AICR components in the Netherlands. The basis for PD guidance for developing dietary recommendations for cancer prevention was strong across all social classes in Guatemala, marginal for Mexico and Scotland, and effectively impossible for the Netherlands.

Bridge approach slabs for Missouri DOT looking at alternative and cost efficient approaches.

DOT National Transportation Integrated Search

2010-12-01

The objective of this project is to develop innovative and cost effective structural solutions for the construction of : both new and replacement deteriorated Bridge Approach Slabs (BAS). A cost study and email survey was performed to identify : stat...

QTL-seq approach identified genomic regions and diagnostic markers for rust and late leaf spot resistance in groundnut (Arachis hypogaea L.).

PubMed

Pandey, Manish K; Khan, Aamir W; Singh, Vikas K; Vishwakarma, Manish K; Shasidhar, Yaduru; Kumar, Vinay; Garg, Vanika; Bhat, Ramesh S; Chitikineni, Annapurna; Janila, Pasupuleti; Guo, Baozhu; Varshney, Rajeev K

2017-08-01

Rust and late leaf spot (LLS) are the two major foliar fungal diseases in groundnut, and their co-occurrence leads to significant yield loss in addition to the deterioration of fodder quality. To identify candidate genomic regions controlling resistance to rust and LLS, whole-genome resequencing (WGRS)-based approach referred as 'QTL-seq' was deployed. A total of 231.67 Gb raw and 192.10 Gb of clean sequence data were generated through WGRS of resistant parent and the resistant and susceptible bulks for rust and LLS. Sequence analysis of bulks for rust and LLS with reference-guided resistant parent assembly identified 3136 single-nucleotide polymorphisms (SNPs) for rust and 66 SNPs for LLS with the read depth of ≥7 in the identified genomic region on pseudomolecule A03. Detailed analysis identified 30 nonsynonymous SNPs affecting 25 candidate genes for rust resistance, while 14 intronic and three synonymous SNPs affecting nine candidate genes for LLS resistance. Subsequently, allele-specific diagnostic markers were identified for three SNPs for rust resistance and one SNP for LLS resistance. Genotyping of one RIL population (TAG 24 × GPBD 4) with these four diagnostic markers revealed higher phenotypic variation for these two diseases. These results suggest usefulness of QTL-seq approach in precise and rapid identification of candidate genomic regions and development of diagnostic markers for breeding applications. © 2016 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Conceptualizing and Assessing Self-Enhancement Bias: A Componential Approach

PubMed Central

Kwan, Virginia S. Y.; Kuang, Lu Lu; John, Oliver P.; Robins, Richard W.

2014-01-01

Four studies implemented a componential approach to assessing self-enhancement and contrasted this approach with 2 earlier ones: social comparison (comparing self-ratings with ratings of others) and self-insight (comparing self-ratings with ratings by others). In Study 1, the authors varied the traits being rated to identify conditions that lead to more or less similarity between approaches. In Study 2, the authors examined the effects of acquaintance on the conditions identified in Study 1. In Study 3, the authors showed that using rankings renders the self-insight approach equivalent to the component-based approach but also has limitations in assessing self-enhancement. In Study 4, the authors compared the social-comparison and the component-based approaches in terms of their psychological implications; the relation between self-enhancement and adjustment depended on the self-enhancement approach used, and the positive-adjustment correlates of the social-comparison approach disappeared when the confounding influence of the target effect was controlled. PMID:18505318

A Systems Approach to Identifying and Managing Opportunities and Constraints to Delivering Innovation Policy for Agriculture: An Analysis of the Australian Cooperative Research Centres (CRC) Program

ERIC Educational Resources Information Center

Sandall, Jean; Cooksey, Ray; Wright, Vic

2011-01-01

In this paper we outline an analytical approach to identifying points in the policy process where management intervention to adjust organizational design could enhance delivery of innovation policy over time. We illustrate this approach using an example from native vegetation policy in the state of Victoria, Australia. We then use this approach to…

Omics Approaches for Identifying Physiological Adaptations to Genome Instability in Aging

PubMed Central

Edifizi, Diletta; Schumacher, Björn

2017-01-01

DNA damage causally contributes to aging and age-related diseases. The declining functioning of tissues and organs during aging can lead to the increased risk of succumbing to aging-associated diseases. Congenital syndromes that are caused by heritable mutations in DNA repair pathways lead to cancer susceptibility and accelerated aging, thus underlining the importance of genome maintenance for withstanding aging. High-throughput mass-spectrometry-based approaches have recently contributed to identifying signalling response networks and gaining a more comprehensive understanding of the physiological adaptations occurring upon unrepaired DNA damage. The insulin-like signalling pathway has been implicated in a DNA damage response (DDR) network that includes epidermal growth factor (EGF)-, AMP-activated protein kinases (AMPK)- and the target of rapamycin (TOR)-like signalling pathways, which are known regulators of growth, metabolism, and stress responses. The same pathways, together with the autophagy-mediated proteostatic response and the decline in energy metabolism have also been found to be similarly regulated during natural aging, suggesting striking parallels in the physiological adaptation upon persistent DNA damage due to DNA repair defects and long-term low-level DNA damage accumulation occurring during natural aging. These insights will be an important starting point to study the interplay between signalling networks involved in progeroid syndromes that are caused by DNA repair deficiencies and to gain new understanding of the consequences of DNA damage in the aging process. PMID:29113067

Identifying Successful Advancement Approaches in Four Catholic Universities: The Effectiveness of the Four Advancement Models of Communication

ERIC Educational Resources Information Center

Bonglia, Jean-Pierre K.

2010-01-01

The current longitudinal study of the most successful Catholic universities in the United States identifies the prevalence of four advancement models of communication that have contributed to make those institutions successful in their philanthropic efforts. While research by Grunig and Kelly maintained that the two-way symmetrical model of…

The pulling power of chocolate: Effects of approach-avoidance training on approach bias and consumption.

PubMed

Dickson, Hugh; Kavanagh, David J; MacLeod, Colin

2016-04-01

Previous research has shown that action tendencies to approach alcohol may be modified using computerized Approach-Avoidance Task (AAT), and that this impacted on subsequent consumption. A recent paper in this journal (Becker, Jostman, Wiers, & Holland, 2015) failed to show significant training effects for food in three studies: Nor did it find effects on subsequent consumption. However, avoidance training to high calorie foods was tested against a control rather than Approach training. The present study used a more comparable paradigm to the alcohol studies. It randomly assigned 90 participants to 'approach' or 'avoid' chocolate images on the AAT, and then asked them to taste and rate chocolates. A significant interaction of condition and time showed that training to avoid chocolate resulted in faster avoidance responses to chocolate images, compared with training to approach it. Consistent with Becker et al.'s Study 3, no effect was found on amounts of chocolate consumed, although a newly published study in this journal (Schumacher, Kemps, & Tiggemann, 2016) did do so. The collective evidence does not as yet provide solid basis for the application of AAT training to reduction of problematic food consumption, although clinical trials have yet to be conducted. Copyright © 2016 Elsevier Ltd. All rights reserved.

Enhancing Basic Skill Levels of Marketing and Distributive Education Students Identified as Disadvantaged--A Tutorial Approach. Final Report, July 1, 1980-June 30, 1981.

ERIC Educational Resources Information Center

Wells, Randall L.

A project was undertaken to enhance the basic skill levels of marketing and distributive education students identified as disadvantaged by using a tutorial approach. After determining the basic skill competencies needed for students to succeed in marketing and distributive education, project staff identified existing materials in the areas of math…

Targeted Approach to Identify Genetic Loci Associated with ...

EPA Pesticide Factsheets

Extreme tolerance to highly toxic dioxin-like contaminants (DLCs) has evolved independently and contemporaneously in (at least) four populations of Atlantic killifish (Fundulus heteroclitus). Surprisingly, the magnitude and phenotype of DLC tolerance is similar among these killifish populations that have adapted to varied, but highly contaminated urban/industrialized estuaries of the US Atlantic coast. We hypothesized that comparisons among tolerant populations and in contrast to their sensitive neighboring killifish might reveal genetic loci associated with DLC tolerance. Since the aryl hydrocarbon receptor (AHR) pathway partly or fully mediates DLC toxicity in vertebrates, we identified single nucleotide polymorphisms (SNPs) from 43 genes associated with the AHR to serve as targeted markers. Wild fish from the four highly tolerant killifish populations and four nearby sensitive populations were genotyped using 59 SNP markers. Consistent with other killifish population genetic analyses, our results revealed strong genetic differentiation among populations, consistent with isolation by distance models. Pairwise comparisons of nearby tolerant and sensitive populations revealed differentiation among these loci: AHR 1 and 2, cathepsin Z, the cytochrome P450s (CYP) 1A and 3A30, and the NADH ubiquinone oxidoreductase MLRQ subunit. By grouping tolerant versus sensitive populations, we also identified cytochrome P450 1A and the AHR2 loci as under selection, lend

Screening approach for identifying candidate drugs and drug-drug interactions related to hip fracture risk in persons with Alzheimer disease.

PubMed

Tolppanen, Anna-Maija; Taipale, Heidi; Koponen, Marjaana; Tanskanen, Antti; Lavikainen, Piia; Paananen, Jussi; Tiihonen, Jari; Hartikainen, Sirpa

2017-08-01

To assess whether a "drugome-wide" screen with case-crossover design is a feasible approach for identifying candidate drugs and drug-drug interactions. All community-dwelling residents of Finland who received a clinically verified Alzheimer disease diagnosis in 2005 to 2011 and experienced incident hip fracture (HF) afterwards (N = 4851). Three scenarios were used to test the sensitivity of this approach (1) hazard period 0 to 30 and control period 31 to 61 days before HF, (2) hazard period 0 to 30 and control period 336 to 366 days before HF, and (3) hazard period 0 to 14 and control period 16 to 30 days before HF. Nine, 44, and 5 drugs were associated with increased HF risk and 8, 23, and 4 with decreased risk in scenarios 1, 2, and 3, respectively. Six drugs were identified with scenario 1 only and 54 and 1 with scenarios 2 and 3, respectively. Only six drugs (metoprolol, simvastatin, trimethoprim, codeine combinations, fentanyl, and paracetamol) were associated with HF in all scenarios, four with 1 and 2 (cefalexin, buprenorphine, olanzapine, and memantine), and one with 1 and 3 (enalapril) or 2 and 3 (ciprofloxacin). The direction of associations was the same in all/both scenarios. The interaction results were equally versatile, with hydroxocobalamin*oxazepam being the only interaction observed in all scenarios. Case-crossover analysis is a potential approach for identifying candidate drugs and drug-drug interactions associated with adverse events as it implicitly controls for fixed confounders. The results are highly dependent on applied hazard and control periods, but the choice of periods can help in targeting the analyses to different phases of drug use. Copyright © 2017 John Wiley & Sons, Ltd.

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

PubMed Central

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

2018-01-01

Background Crop response to the changing climate and unpredictable effects of global warming with adverse conditions such as drought stress has brought concerns about food security to the fore; crop yield loss is a major cause of concern in this regard. Identification of genes with multiple responses across environmental stresses is the genetic foundation that leads to crop adaptation to environmental perturbations. Methods In this paper, we introduce an integrated approach to assess candidate genes for multiple stress responses across-species. The approach combines ontology based semantic data integration with expression profiling, comparative genomics, phylogenomics, functional gene enrichment and gene enrichment network analysis to identify genes associated with plant stress phenotypes. Five different ontologies, viz., Gene Ontology (GO), Trait Ontology (TO), Plant Ontology (PO), Growth Ontology (GRO) and Environment Ontology (EO) were used to semantically integrate drought related information. Results Target genes linked to Quantitative Trait Loci (QTLs) controlling yield and stress tolerance in sorghum (Sorghum bicolor (L.) Moench) and closely related species were identified. Based on the enriched GO terms of the biological processes, 1116 sorghum genes with potential responses to 5 different stresses, such as drought (18%), salt (32%), cold (20%), heat (8%) and oxidative stress (25%) were identified to be over-expressed. Out of 169 sorghum drought responsive QTLs associated genes that were identified based on expression datasets, 56% were shown to have multiple stress responses. On the other hand, out of 168 additional genes that have been evaluated for orthologous pairs, 90% were conserved across species for drought tolerance. Over 50% of identified maize and rice genes were responsive to drought and salt stresses and were co-located within multifunctional QTLs. Among the total identified multi-stress responsive genes, 272 targets were shown to be co

A geospatial approach to identify water quality issues for National Wildlife Refuges in Oregon and Washington

USGS Publications Warehouse

Hinck, Jo Ellen; Chojnacki, Kimberly; Finger, Susan E.; Linder, Greg; Kilbride, Kevin

2011-01-01

Many National Wildlife Refuges (Refuges) have impaired water quality resulting from historic and current land uses, upstream sources, and aerial pollutant deposition. Competing duties limit the time available for Refuge staff to identify and evaluate potential water quality issues. As a result, water quality–related issues may not be resolved until a problem has already arisen. This study developed a geospatial approach for identifying and prioritizing water quality issues affecting natural resources (including migratory birds and federally listed species) within Refuge boundaries. We assessed the location and status of streams pursuant to the Clean Water Act in relation to individual Refuges in Oregon and Washington, United States. Although twelve Refuges in Oregon (60%) and eight Refuges in Washington (40%) were assessed under the Clean Water Act, only 12% and 3% of total Refuge stream lengths were assessed, respectively. Very few assessed Refuge streams were not designated as impaired (0% in Oregon, 1% in Washington). Despite the low proportions of stream lengths assessed, most Refuges in Oregon (70%) and Washington (65%) are located in watersheds with approved total maximum daily loads. We developed summaries of current water quality issues for individual Refuges and identified large gaps for Refuge-specific water quality data and habitat utilization by sensitive species. We conclude that monitoring is warranted on many Refuges to better characterize water quality under the Clean Water Act.

Peptidomic approach identifies cruzioseptins, a new family of potent antimicrobial peptides in the splendid leaf frog, Cruziohyla calcarifer.

PubMed

Proaño-Bolaños, Carolina; Zhou, Mei; Wang, Lei; Coloma, Luis A; Chen, Tianbao; Shaw, Chris

2016-09-02

Phyllomedusine frogs are an extraordinary source of biologically active peptides. At least 8 families of antimicrobial peptides have been reported in this frog clade, the dermaseptins being the most diverse. By a peptidomic approach, integrating molecular cloning, Edman degradation sequencing and tandem mass spectrometry, a new family of antimicrobial peptides has been identified in Cruziohyla calcarifer. These 15 novel antimicrobial peptides of 20-32 residues in length are named cruzioseptins. They are characterized by having a unique shared N-terminal sequence GFLD- and the sequence motifs -VALGAVSK- or -GKAAL(N/G/S) (V/A)V- in the middle of the peptide. Cruzioseptins have a broad spectrum of antimicrobial activity and low haemolytic effect. The most potent cruzioseptin was CZS-1 that had a MIC of 3.77μM against the Gram positive bacterium, Staphylococcus aureus and the yeast Candida albicans. In contrast, CZS-1 was 3-fold less potent against the Gram negative bacterium, Escherichia coli (MIC 15.11μM). CZS-1 reached 100% haemolysis at 120.87μM. Skin secretions from unexplored species such as C. calcarifer continue to demonstrate the enormous molecular diversity hidden in the amphibian skin. Some of these novel peptides may provide lead structures for the development of a new class of antibiotics and antifungals of therapeutic use. Through the combination of molecular cloning, Edman degradation sequencing, tandem mass spectrometry and MALDI-TOF MS we have identified a new family of 15 antimicrobial peptides in the skin secretion of Cruziohyla calcarifer. The novel family is named "Cruzioseptins" and contains cationic amphipathic peptides of 20-32 residues. They have a broad range of antimicrobial activity that also includes effective antifungals with low haemolytic activity. Therefore, C. calcarifer has proven to be a rich source of novel peptides, which could become leading structures for the development of novel antibiotics and antifungals of clinical

Using multi-scale distribution and movement effects along a montane highway to identify optimal crossing locations for a large-bodied mammal community

PubMed Central

Römer, Heinrich; Germain, Ryan R.

2013-01-01

Roads are a major cause of habitat fragmentation that can negatively affect many mammal populations. Mitigation measures such as crossing structures are a proposed method to reduce the negative effects of roads on wildlife, but the best methods for determining where such structures should be implemented, and how their effects might differ between species in mammal communities is largely unknown. We investigated the effects of a major highway through south-eastern British Columbia, Canada on several mammal species to determine how the highway may act as a barrier to animal movement, and how species may differ in their crossing-area preferences. We collected track data of eight mammal species across two winters, along both the highway and pre-marked transects, and used a multi-scale modeling approach to determine the scale at which habitat characteristics best predicted preferred crossing sites for each species. We found evidence for a severe barrier effect on all investigated species. Freely-available remotely-sensed habitat landscape data were better than more costly, manually-digitized microhabitat maps in supporting models that identified preferred crossing sites; however, models using both types of data were better yet. Further, in 6 of 8 cases models which incorporated multiple spatial scales were better at predicting preferred crossing sites than models utilizing any single scale. While each species differed in terms of the landscape variables associated with preferred/avoided crossing sites, we used a multi-model inference approach to identify locations along the highway where crossing structures may benefit all of the species considered. By specifically incorporating both highway and off-highway data and predictions we were able to show that landscape context plays an important role for maximizing mitigation measurement efficiency. Our results further highlight the need for mitigation measures along major highways to improve connectivity between mammal

Using multi-scale distribution and movement effects along a montane highway to identify optimal crossing locations for a large-bodied mammal community.

PubMed

Schuster, Richard; Römer, Heinrich; Germain, Ryan R

2013-01-01

Roads are a major cause of habitat fragmentation that can negatively affect many mammal populations. Mitigation measures such as crossing structures are a proposed method to reduce the negative effects of roads on wildlife, but the best methods for determining where such structures should be implemented, and how their effects might differ between species in mammal communities is largely unknown. We investigated the effects of a major highway through south-eastern British Columbia, Canada on several mammal species to determine how the highway may act as a barrier to animal movement, and how species may differ in their crossing-area preferences. We collected track data of eight mammal species across two winters, along both the highway and pre-marked transects, and used a multi-scale modeling approach to determine the scale at which habitat characteristics best predicted preferred crossing sites for each species. We found evidence for a severe barrier effect on all investigated species. Freely-available remotely-sensed habitat landscape data were better than more costly, manually-digitized microhabitat maps in supporting models that identified preferred crossing sites; however, models using both types of data were better yet. Further, in 6 of 8 cases models which incorporated multiple spatial scales were better at predicting preferred crossing sites than models utilizing any single scale. While each species differed in terms of the landscape variables associated with preferred/avoided crossing sites, we used a multi-model inference approach to identify locations along the highway where crossing structures may benefit all of the species considered. By specifically incorporating both highway and off-highway data and predictions we were able to show that landscape context plays an important role for maximizing mitigation measurement efficiency. Our results further highlight the need for mitigation measures along major highways to improve connectivity between mammal

A new simplex chemometric approach to identify olive oil blends with potentially high traceability.

PubMed

Semmar, N; Laroussi-Mezghani, S; Grati-Kamoun, N; Hammami, M; Artaud, J

2016-10-01

Olive oil blends (OOBs) are complex matrices combining different cultivars at variable proportions. Although qualitative determinations of OOBs have been subjected to several chemometric works, quantitative evaluations of their contents remain poorly developed because of traceability difficulties concerning co-occurring cultivars. Around this question, we recently published an original simplex approach helping to develop predictive models of the proportions of co-occurring cultivars from chemical profiles of resulting blends (Semmar & Artaud, 2015). Beyond predictive model construction and validation, this paper presents an extension based on prediction errors' analysis to statistically define the blends with the highest predictability among all the possible ones that can be made by mixing cultivars at different proportions. This provides an interesting way to identify a priori labeled commercial products with potentially high traceability taking into account the natural chemical variability of different constitutive cultivars. Copyright © 2016 Elsevier Ltd. All rights reserved.

Identifying medication error chains from critical incident reports: a new analytic approach.

PubMed

Huckels-Baumgart, Saskia; Manser, Tanja

2014-10-01

Research into the distribution of medication errors usually focuses on isolated stages within the medication use process. Our study aimed to provide a novel process-oriented approach to medication incident analysis focusing on medication error chains. Our study was conducted across a 900-bed teaching hospital in Switzerland. All reported 1,591 medication errors 2009-2012 were categorized using the Medication Error Index NCC MERP and the WHO Classification for Patient Safety Methodology. In order to identify medication error chains, each reported medication incident was allocated to the relevant stage of the hospital medication use process. Only 25.8% of the reported medication errors were detected before they propagated through the medication use process. The majority of medication errors (74.2%) formed an error chain encompassing two or more stages. The most frequent error chain comprised preparation up to and including medication administration (45.2%). "Non-consideration of documentation/prescribing" during the drug preparation was the most frequent contributor for "wrong dose" during the administration of medication. Medication error chains provide important insights for detecting and stopping medication errors before they reach the patient. Existing and new safety barriers need to be extended to interrupt error chains and to improve patient safety. © 2014, The American College of Clinical Pharmacology.

A Collaborative Approach to Identifying Social Media Markers of Schizophrenia by Employing Machine Learning and Clinical Appraisals.

PubMed

Birnbaum, Michael L; Ernala, Sindhu Kiranmai; Rizvi, Asra F; De Choudhury, Munmun; Kane, John M

2017-08-14

Linguistic analysis of publicly available Twitter feeds have achieved success in differentiating individuals who self-disclose online as having schizophrenia from healthy controls. To date, limited efforts have included expert input to evaluate the authenticity of diagnostic self-disclosures. This study aims to move from noisy self-reports of schizophrenia on social media to more accurate identification of diagnoses by exploring a human-machine partnered approach, wherein computational linguistic analysis of shared content is combined with clinical appraisals. Twitter timeline data, extracted from 671 users with self-disclosed diagnoses of schizophrenia, was appraised for authenticity by expert clinicians. Data from disclosures deemed true were used to build a classifier aiming to distinguish users with schizophrenia from healthy controls. Results from the classifier were compared to expert appraisals on new, unseen Twitter users. Significant linguistic differences were identified in the schizophrenia group including greater use of interpersonal pronouns (P<.001), decreased emphasis on friendship (P<.001), and greater emphasis on biological processes (P<.001). The resulting classifier distinguished users with disclosures of schizophrenia deemed genuine from control users with a mean accuracy of 88% using linguistic data alone. Compared to clinicians on new, unseen users, the classifier's precision, recall, and accuracy measures were 0.27, 0.77, and 0.59, respectively. These data reinforce the need for ongoing collaborations integrating expertise from multiple fields to strengthen our ability to accurately identify and effectively engage individuals with mental illness online. These collaborations are crucial to overcome some of mental illnesses' biggest challenges by using digital technology. ©Michael L Birnbaum, Sindhu Kiranmai Ernala, Asra F Rizvi, Munmun De Choudhury, John M Kane. Originally published in the Journal of Medical Internet Research (http

Identifying postpartum intervention approaches to reduce cardiometabolic risk among American Indian women with prior gestational diabetes, Oklahoma, 2012-2013.

PubMed

Jones, Emily J; Peercy, Michael; Woods, J Cedric; Parker, Stephany P; Jackson, Teresa; Mata, Sara A; McCage, Shondra; Levkoff, Sue E; Nicklas, Jacinda M; Seely, Ellen W

2015-04-02

Innovative approaches are needed to reduce cardiometabolic risk among American Indian women with a history of gestational diabetes. We assessed beliefs of Oklahoma American Indian women about preventing type 2 diabetes and cardiovascular disease after having gestational diabetes. We also assessed barriers and facilitators to healthy lifestyle changes postpartum and intervention approaches that facilitate participation in a postpartum lifestyle program. In partnership with a tribal health system, we conducted a mixed-method study with American Indian women aged 19 to 45 years who had prior gestational diabetes, using questionnaires, focus groups, and individual interviews. Questionnaires were used to identify women's cardiometabolic risk perceptions and feasibility and acceptability of Internet or mobile phone technology for delivery of a postpartum lifestyle modification program. Focus groups and individual interviews were conducted to identify key perspectives and preferences related to a potential program. Participants were 26 women, all of whom completed surveys; 11 women participated in focus group sessions, and 15 participated in individual interviews. Most women believed they would inevitably develop diabetes, cardiovascular disease, or both; however, they were optimistic that they could delay onset with lifestyle change. Most women expressed enthusiasm for a family focused, technology-based intervention that emphasizes the importance of delaying disease onset, provides motivation, and promotes accountability while accommodating women's competing priorities. Our findings suggest that an intervention that uses the Internet, text messaging, or both and that emphasizes the benefits of delaying disease onset should be tested as a novel, culturally relevant approach to reducing rates of diabetes and cardiovascular disease in this high-risk population.

A comprehensive strategy for identifying long-distance mobile peptides in xylem sap.

PubMed

Okamoto, Satoru; Suzuki, Takamasa; Kawaguchi, Masayoshi; Higashiyama, Tetsuya; Matsubayashi, Yoshikatsu

2015-11-01

There is a growing awareness that secreted pemediate organ-to-organ communication in higher plants. Xylem sap peptidomics is an effective but challenging approach for identifying long-distance mobile peptides. In this study we developed a simple, gel-free purification system that combines o-chlorophenol extraction with HPLC separation. Using this system, we successfully identified seven oligopeptides from soybean xylem sap exudate that had one or more post-transcriptional modifications: glycosylation, sulfation and/or hydroxylation. RNA sequencing and quantitative PCR analyses showed that the peptide-encoding genes are expressed in multiple tissues. We further analyzed the long-distance translocation of four of the seven peptides using gene-encoding peptides with single amino acid substitutions, and identified these four peptides as potential root-to-shoot mobile oligopeptides. Promoter-GUS analysis showed that all four peptide-encoding genes were expressed in the inner tissues of the root endodermis. Moreover, we found that some of these peptide-encoding genes responded to biotic and/or abiotic factors. These results indicate that our purification system provides a comprehensive approach for effectively identifying endogenous small peptides and reinforce the concept that higher plants employ various peptides in root-to-shoot signaling. © 2015 The Authors The Plant Journal © 2015 John Wiley & Sons Ltd.

Global Effects of DDX3 Inhibition on Cell Cycle Regulation Identified by a Combined Phosphoproteomics and Single Cell Tracking Approach.

PubMed

Heerma van Voss, Marise R; Kammers, Kai; Vesuna, Farhad; Brilliant, Justin; Bergman, Yehudit; Tantravedi, Saritha; Wu, Xinyan; Cole, Robert N; Holland, Andrew; van Diest, Paul J; Raman, Venu

2018-06-01

DDX3 is an RNA helicase with oncogenic properties. The small molecule inhibitor RK-33 is designed to fit into the ATP binding cleft of DDX3 and hereby block its activity. RK-33 has shown potent activity in preclinical cancer models. However, the mechanism behind the antineoplastic activity of RK-33 remains largely unknown. In this study we used a dual phosphoproteomic and single cell tracking approach to evaluate the effect of RK-33 on cancer cells. MDA-MB-435 cells were treated for 24 hours with RK-33 or vehicle control. Changes in phosphopeptide abundance were analyzed with quantitative mass spectrometry using isobaric mass tags (Tandem Mass Tags). At the proteome level we mainly observed changes in mitochondrial translation, cell division pathways and proteins related to cell cycle progression. Analysis of the phosphoproteome indicated decreased CDK1 activity after RK-33 treatment. To further evaluate the effect of DDX3 inhibition on cell cycle progression over time, we performed timelapse microscopy of Fluorescent Ubiquitin Cell Cycle Indicators labeled cells after RK-33 or siDDX3 exposure. Single cell tracking indicated that DDX3 inhibition resulted in a global delay in cell cycle progression in interphase and mitosis. In addition, we observed an increase in endoreduplication. Overall, we conclude that DDX3 inhibition affects cells in all phases and causes a global cell cycle progression delay. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Identifying Meaningful Behaviors for Social Competence: A Contextual Approach.

ERIC Educational Resources Information Center

Warnes, Emily D.; Sheridan, Susan M.; Geske, Jenenne; Warnes, William A.

An exploratory study was conducted which assessed behaviors that characterize social competence in the 2nd and 5th grades. A contextual approach was used to gather information from 2nd and 5th grade children and their parents and teachers regarding the behaviors they perceived to be important for getting along well with peers. Data were gathered…

Effective Learning Approaches for Sustainability: A Student Perspective

ERIC Educational Resources Information Center

Erskine, Laura; Johnson, Scott D.

2012-01-01

The authors offer an exploratory glimpse into the perceived effectiveness of learning approaches presently being used to teach students about sustainability in a business school setting. Sustainability is a topic of growing importance in business and business education. Using teaching approaches generated through self-reports related to the…

Drug Repurposing Screening Identifies Novel Compounds That Effectively Inhibit Toxoplasma gondii Growth

PubMed Central

Dittmar, Ashley J.; Drozda, Allison A.

2016-01-01

ABSTRACT The urgent need to develop new antimicrobial therapies has spawned the development of repurposing screens in which well-studied drugs and other types of compounds are tested for potential off-label uses. As a proof-of-principle screen to identify compounds effective against Toxoplasma gondii, we screened a collection of 1,120 compounds for the ability to significantly reduce Toxoplasma replication. A total of 94 compounds blocked parasite replication with 50% inhibitory concentrations of <5 µM. A significant number of these compounds are established inhibitors of dopamine or estrogen signaling. Follow-up experiments with the dopamine receptor inhibitor pimozide revealed that the drug impacted both parasite invasion and replication but did so independently of inhibition of dopamine or other neurotransmitter receptor signaling. Tamoxifen, which is an established inhibitor of the estrogen receptor, also reduced parasite invasion and replication. Even though Toxoplasma can activate the estrogen receptor, tamoxifen inhibits parasite growth independently of this transcription factor. Tamoxifen is also a potent inducer of autophagy, and we find that the drug stimulates recruitment of the autophagy marker light chain 3-green fluorescent protein onto the membrane of the vacuolar compartment in which the parasite resides and replicates. In contrast to other antiparasitic drugs, including pimozide, tamoxifen treatment of infected cells leads to a time-dependent elimination of intracellular parasites. Taken together, these data suggest that tamoxifen restricts Toxoplasma growth by inducing xenophagy or autophagic destruction of this obligate intracellular parasite. IMPORTANCE There is an urgent need to develop new therapies to treat microbial infections, and the repurposing of well-characterized compounds is emerging as one approach to achieving this goal. Using the protozoan parasite Toxoplasma gondii, we screened a library of 1,120 compounds and identified several

A Network Biology Approach Identifies Molecular Cross-Talk between Normal Prostate Epithelial and Prostate Carcinoma Cells

PubMed Central

Trevino, Victor; Cassese, Alberto; Nagy, Zsuzsanna; Zhuang, Xiaodong; Herbert, John; Antzack, Philipp; Clarke, Kim; Davies, Nicholas; Rahman, Ayesha; Campbell, Moray J.; Bicknell, Roy; Vannucci, Marina; Falciani, Francesco

2016-01-01

Abstract The advent of functional genomics has enabled the genome-wide characterization of the molecular state of cells and tissues, virtually at every level of biological organization. The difficulty in organizing and mining this unprecedented amount of information has stimulated the development of computational methods designed to infer the underlying structure of regulatory networks from observational data. These important developments had a profound impact in biological sciences since they triggered the development of a novel data-driven investigative approach. In cancer research, this strategy has been particularly successful. It has contributed to the identification of novel biomarkers, to a better characterization of disease heterogeneity and to a more in depth understanding of cancer pathophysiology. However, so far these approaches have not explicitly addressed the challenge of identifying networks representing the interaction of different cell types in a complex tissue. Since these interactions represent an essential part of the biology of both diseased and healthy tissues, it is of paramount importance that this challenge is addressed. Here we report the definition of a network reverse engineering strategy designed to infer directional signals linking adjacent cell types within a complex tissue. The application of this inference strategy to prostate cancer genome-wide expression profiling data validated the approach and revealed that normal epithelial cells exert an anti-tumour activity on prostate carcinoma cells. Moreover, by using a Bayesian hierarchical model integrating genetics and gene expression data and combining this with survival analysis, we show that the expression of putative cell communication genes related to focal adhesion and secretion is affected by epistatic gene copy number variation and it is predictive of patient survival. Ultimately, this study represents a generalizable approach to the challenge of deciphering cell communication

A Network Biology Approach Identifies Molecular Cross-Talk between Normal Prostate Epithelial and Prostate Carcinoma Cells.

PubMed

Trevino, Victor; Cassese, Alberto; Nagy, Zsuzsanna; Zhuang, Xiaodong; Herbert, John; Antczak, Philipp; Clarke, Kim; Davies, Nicholas; Rahman, Ayesha; Campbell, Moray J; Guindani, Michele; Bicknell, Roy; Vannucci, Marina; Falciani, Francesco

2016-04-01

The advent of functional genomics has enabled the genome-wide characterization of the molecular state of cells and tissues, virtually at every level of biological organization. The difficulty in organizing and mining this unprecedented amount of information has stimulated the development of computational methods designed to infer the underlying structure of regulatory networks from observational data. These important developments had a profound impact in biological sciences since they triggered the development of a novel data-driven investigative approach. In cancer research, this strategy has been particularly successful. It has contributed to the identification of novel biomarkers, to a better characterization of disease heterogeneity and to a more in depth understanding of cancer pathophysiology. However, so far these approaches have not explicitly addressed the challenge of identifying networks representing the interaction of different cell types in a complex tissue. Since these interactions represent an essential part of the biology of both diseased and healthy tissues, it is of paramount importance that this challenge is addressed. Here we report the definition of a network reverse engineering strategy designed to infer directional signals linking adjacent cell types within a complex tissue. The application of this inference strategy to prostate cancer genome-wide expression profiling data validated the approach and revealed that normal epithelial cells exert an anti-tumour activity on prostate carcinoma cells. Moreover, by using a Bayesian hierarchical model integrating genetics and gene expression data and combining this with survival analysis, we show that the expression of putative cell communication genes related to focal adhesion and secretion is affected by epistatic gene copy number variation and it is predictive of patient survival. Ultimately, this study represents a generalizable approach to the challenge of deciphering cell communication networks

Identifying Liver Cancer and Its Relations with Diseases, Drugs, and Genes: A Literature-Based Approach

PubMed Central

Song, Min

2016-01-01

In biomedicine, scientific literature is a valuable source for knowledge discovery. Mining knowledge from textual data has become an ever important task as the volume of scientific literature is growing unprecedentedly. In this paper, we propose a framework for examining a certain disease based on existing information provided by scientific literature. Disease-related entities that include diseases, drugs, and genes are systematically extracted and analyzed using a three-level network-based approach. A paper-entity network and an entity co-occurrence network (macro-level) are explored and used to construct six entity specific networks (meso-level). Important diseases, drugs, and genes as well as salient entity relations (micro-level) are identified from these networks. Results obtained from the literature-based literature mining can serve to assist clinical applications. PMID:27195695

A hierarchical modeling approach to estimate regional acute health effects of particulate matter sources

PubMed Central

Krall, J. R.; Hackstadt, A. J.; Peng, R. D.

2017-01-01

Exposure to particulate matter (PM) air pollution has been associated with a range of adverse health outcomes, including cardiovascular disease (CVD) hospitalizations and other clinical parameters. Determining which sources of PM, such as traffic or industry, are most associated with adverse health outcomes could help guide future recommendations aimed at reducing harmful pollution exposure for susceptible individuals. Information obtained from multisite studies, which is generally more precise than information from a single location, is critical to understanding how PM impacts health and to informing local strategies for reducing individual-level PM exposure. However, few methods exist to perform multisite studies of PM sources, which are not generally directly observed, and adverse health outcomes. We developed SHARE, a hierarchical modeling approach that facilitates reproducible, multisite epidemiologic studies of PM sources. SHARE is a two-stage approach that first summarizes information about PM sources across multiple sites. Then, this information is used to determine how community-level (i.e. county- or city-level) health effects of PM sources should be pooled to estimate regional-level health effects. SHARE is a type of population value decomposition that aims to separate out regional-level features from site-level data. Unlike previous approaches for multisite epidemiologic studies of PM sources, the SHARE approach allows the specific PM sources identified to vary by site. Using data from 2000–2010 for 63 northeastern US counties, we estimated regional-level health effects associated with short-term exposure to major types of PM sources. We found PM from secondary sulfate, traffic, and metals sources was most associated with CVD hospitalizations. PMID:28098412

An integrated approach for identifying wrongly labelled samples when performing classification in microarray data.

PubMed

Leung, Yuk Yee; Chang, Chun Qi; Hung, Yeung Sam

2012-01-01

Using hybrid approach for gene selection and classification is common as results obtained are generally better than performing the two tasks independently. Yet, for some microarray datasets, both classification accuracy and stability of gene sets obtained still have rooms for improvement. This may be due to the presence of samples with wrong class labels (i.e. outliers). Outlier detection algorithms proposed so far are either not suitable for microarray data, or only solve the outlier detection problem on their own. We tackle the outlier detection problem based on a previously proposed Multiple-Filter-Multiple-Wrapper (MFMW) model, which was demonstrated to yield promising results when compared to other hybrid approaches (Leung and Hung, 2010). To incorporate outlier detection and overcome limitations of the existing MFMW model, three new features are introduced in our proposed MFMW-outlier approach: 1) an unbiased external Leave-One-Out Cross-Validation framework is developed to replace internal cross-validation in the previous MFMW model; 2) wrongly labeled samples are identified within the MFMW-outlier model; and 3) a stable set of genes is selected using an L1-norm SVM that removes any redundant genes present. Six binary-class microarray datasets were tested. Comparing with outlier detection studies on the same datasets, MFMW-outlier could detect all the outliers found in the original paper (for which the data was provided for analysis), and the genes selected after outlier removal were proven to have biological relevance. We also compared MFMW-outlier with PRAPIV (Zhang et al., 2006) based on same synthetic datasets. MFMW-outlier gave better average precision and recall values on three different settings. Lastly, artificially flipped microarray datasets were created by removing our detected outliers and flipping some of the remaining samples' labels. Almost all the 'wrong' (artificially flipped) samples were detected, suggesting that MFMW-outlier was

Using 50 years of soil radiocarbon data to identify optimal approaches for estimating soil carbon residence times

NASA Astrophysics Data System (ADS)

Baisden, W. T.; Canessa, S.

2013-01-01

In 1959, Athol Rafter began a substantial programme of systematically monitoring the flow of 14C produced by atmospheric thermonuclear tests through organic matter in New Zealand soils under stable land use. A database of ∼500 soil radiocarbon measurements spanning 50 years has now been compiled, and is used here to identify optimal approaches for soil C-cycle studies. Our results confirm the potential of 14C to determine residence times, by estimating the amount of ‘bomb 14C’ incorporated. High-resolution time series confirm this approach is appropriate, and emphasise that residence times can be calculated routinely with two or more time points as little as 10 years apart. This approach is generally robust to the key assumptions that can create large errors when single time-point 14C measurements are modelled. The three most critical assumptions relate to: (1) the distribution of turnover times, and particularly the proportion of old C (‘passive fraction’), (2) the lag time between photosynthesis and C entering the modelled pool, (3) changes in the rates of C input. When carrying out approaches using robust assumptions on time-series samples, multiple soil layers can be aggregated using a mixing equation. Where good archived samples are available, AMS measurements can develop useful understanding for calibrating models of the soil C cycle at regional to continental scales with sample numbers on the order of hundreds rather than thousands. Sample preparation laboratories and AMS facilities can play an important role in coordinating the efficient delivery of robust calculated residence times for soil carbon.

Identifying Shared Values for School-Affiliated Student Organizations

PubMed Central

Bush, Antonio A.; Buhlinger, Kaitlyn M.

2017-01-01

Objective. To identify shared values for student organizations. Methods. A three-round Delphi approach was utilized to identify and prioritize shared values among student organization leadership. In round 1, student leaders selected 15 values from a list of 36 organizational values and were given an opportunity to include up to five suggestions not incorporated within the original list. Student leaders narrowed the 15 values to 12 in round 2. The top 12 priorities were ranked in round 3 and participants were invited to write a brief statement regarding their perspectives of the results. Results. Twelve shared values were identified and ranked: professional development, improving leadership of your members, advancing the role of pharmacy, planning quality events, networking, improving the academic experience for peers, community service, learning from pharmacy shadowing/speakers, social outlet, recruitment/gaining student membership, attracting students to events, and gaining national/local attention or awards. Conclusion. This study contributes to the small but growing body of literature concerning student organizations in pharmacy education and provides a foundation by which this work could be advanced. Given the importance of student organizations in promoting student development, identifying strategies for supporting and facilitating the effectiveness of these groups is critical for optimizing student outcomes and institutional effectiveness. PMID:29302089

Novel Tonoplast Transporters Identified Using a Proteomic Approach with Vacuoles Isolated from Cauliflower Buds1[W][OA

PubMed Central

Schmidt, Ulrike G.; Endler, Anne; Schelbert, Silvia; Brunner, Arco; Schnell, Magali; Neuhaus, H. Ekkehard; Marty-Mazars, Daniéle; Marty, Francis; Baginsky, Sacha; Martinoia, Enrico

2007-01-01

Young meristematic plant cells contain a large number of small vacuoles, while the largest part of the vacuome in mature cells is composed by a large central vacuole, occupying 80% to 90% of the cell volume. Thus far, only a limited number of vacuolar membrane proteins have been identified and characterized. The proteomic approach is a powerful tool to identify new vacuolar membrane proteins. To analyze vacuoles from growing tissues we isolated vacuoles from cauliflower (Brassica oleracea) buds, which are constituted by a large amount of small cells but also contain cells in expansion as well as fully expanded cells. Here we show that using purified cauliflower vacuoles and different extraction procedures such as saline, NaOH, acetone, and chloroform/methanol and analyzing the data against the Arabidopsis (Arabidopsis thaliana) database 102 cauliflower integral proteins and 214 peripheral proteins could be identified. The vacuolar pyrophosphatase was the most prominent protein. From the 102 identified proteins 45 proteins were already described. Nine of these, corresponding to 46% of peptides detected, are known vacuolar proteins. We identified 57 proteins (55.9%) containing at least one membrane spanning domain with unknown subcellular localization. A comparison of the newly identified proteins with expression profiles from in silico data revealed that most of them are highly expressed in young, developing tissues. To verify whether the newly identified proteins were indeed localized in the vacuole we constructed and expressed green fluorescence protein fusion proteins for five putative vacuolar membrane proteins exhibiting three to 11 transmembrane domains. Four of them, a putative organic cation transporter, a nodulin N21 family protein, a membrane protein of unknown function, and a senescence related membrane protein were localized in the vacuolar membrane, while a white-brown ATP-binding cassette transporter homolog was shown to reside in the plasma membrane

Integrating Adult Learning and Technologies for Effective Education: Strategic Approaches

ERIC Educational Resources Information Center

Wang, Victor C. X.

2010-01-01

As adult learners and educators pioneer the use of technology in the new century, attention has been focused on developing strategic approaches to effectively integrate adult learning and technology in different learning environments. "Integrating Adult Learning and Technologies for Effective Education: Strategic Approaches" provides innovative…

Poly-victimization from different methodological approaches using the juvenile victimization questionnaire: Are we identifying the same victims?

PubMed

Segura, Anna; Pereda, Noemí; Guilera, Georgina

2018-01-01

This study aims to determine whether three different methodological approaches used to assess poly-victimization that apply the Juvenile Victimization Questionnaire (JVQ; Finkelhor, Hamby, Ormrod, & Turner, 2005) identify the same group of adolescent poly-victims. The sample consisted of 1,105 adolescents (590 males and 515 females), aged 12-17 years old (M = 14.52, SD = 1.76) and recruited from seven secondary schools in Spain. The JVQ was used to assess lifetime and past-year experiences of victimization. Poly-victims were more likely to experience all types of victimization than victims, regardless of the method used. The degree of agreement between the methods for identifying poly-victimization was moderate for both timeframes, with the highest agreements being recorded between the one-above-the-mean number of victimizations and Latent Class Analysis (LCA) for lifetime, and between the top 10% and LCA for past-year victimization. Researchers and clinicians should be aware that the use of different methods to define poly-victimization may mean that different victims are identified. The choice of one method or another may have important implications. In consequence, focusing on how we operationalize poly-victimization should be a priority in the near future.

Developing a model for effective leadership in healthcare: a concept mapping approach

PubMed Central

Hargett, Charles William; Doty, Joseph P; Hauck, Jennifer N; Webb, Allison MB; Cook, Steven H; Tsipis, Nicholas E; Neumann, Julie A; Andolsek, Kathryn M; Taylor, Dean C

2017-01-01

Purpose Despite increasing awareness of the importance of leadership in healthcare, our understanding of the competencies of effective leadership remains limited. We used a concept mapping approach (a blend of qualitative and quantitative analysis of group processes to produce a visual composite of the group’s ideas) to identify stakeholders’ mental model of effective healthcare leadership, clarifying the underlying structure and importance of leadership competencies. Methods Literature review, focus groups, and consensus meetings were used to derive a representative set of healthcare leadership competency statements. Study participants subsequently sorted and rank-ordered these statements based on their perceived importance in contributing to effective healthcare leadership in real-world settings. Hierarchical cluster analysis of individual sortings was used to develop a coherent model of effective leadership in healthcare. Results A diverse group of 92 faculty and trainees individually rank-sorted 33 leadership competency statements. The highest rated statements were “Acting with Personal Integrity”, “Communicating Effectively”, “Acting with Professional Ethical Values”, “Pursuing Excellence”, “Building and Maintaining Relationships”, and “Thinking Critically”. Combining the results from hierarchical cluster analysis with our qualitative data led to a healthcare leadership model based on the core principle of Patient Centeredness and the core competencies of Integrity, Teamwork, Critical Thinking, Emotional Intelligence, and Selfless Service. Conclusion Using a mixed qualitative-quantitative approach, we developed a graphical representation of a shared leadership model derived in the healthcare setting. This model may enhance learning, teaching, and patient care in this important area, as well as guide future research. PMID:29355249

An integrated approach for identifying priority contaminant in the Great Lakes Basin - Investigations in the Lower Green Bay/Fox River and Milwaukee Estuary areas of concern.

PubMed

Li, Shibin; Villeneuve, Daniel L; Berninger, Jason P; Blackwell, Brett R; Cavallin, Jenna E; Hughes, Megan N; Jensen, Kathleen M; Jorgenson, Zachary; Kahl, Michael D; Schroeder, Anthony L; Stevens, Kyle E; Thomas, Linnea M; Weberg, Matthew A; Ankley, Gerald T

2017-02-01

Environmental assessment of complex mixtures typically requires integration of chemical and biological measurements. This study demonstrates the use of a combination of instrumental chemical analyses, effects-based monitoring, and bio-effects prediction approaches to help identify potential hazards and priority contaminants in two Great Lakes Areas of Concern (AOCs), the Lower Green Bay/Fox River located near Green Bay, WI, USA and the Milwaukee Estuary, located near Milwaukee, WI, USA. Fathead minnows were caged at four sites within each AOC (eight sites total). Following 4d of in situ exposure, tissues and biofluids were sampled and used for targeted biological effects analyses. Additionally, 4d composite water samples were collected concurrently at each caged fish site and analyzed for 132 analytes as well as evaluated for total estrogenic and androgenic activity using cell-based bioassays. Of the analytes examined, 75 were detected in composite samples from at least one site. Based on multiple analyses, one site in the East River and another site near a paper mill discharge in the Lower Green Bay/Fox River AOC, were prioritized due to their estrogenic and androgenic activity, respectively. The water samples from other sites generally did not exhibit significant estrogenic or androgenic activity, nor was there evidence for endocrine disruption in the fish exposed at these sites as indicated by the lack of alterations in ex vivo steroid production, circulating steroid concentrations, or vitellogenin mRNA expression in males. Induction of hepatic cyp1a mRNA expression was detected at several sites, suggesting the presence of chemicals that activate the aryl hydrocarbon receptor. To expand the scope beyond targeted investigation of endpoints selected a priori, several bio-effects prediction approaches were employed to identify other potentially disturbed biological pathways and related chemical constituents that may warrant future monitoring at these sites. For

A Coordinated Approach to Curricular Review and Development in Undergraduate Geoscience Programs: Using a Matrix to Identify and Track Skills and Skill Development

NASA Astrophysics Data System (ADS)

MacDonald, R.; Savina, M. E.

2003-12-01

assignment or activities. We have found that much conversation among faculty and change within courses happens simply as a result of compiling the matrix. One effect of the use of the matrix is that faculty in the department know fairly specifically what skills students are learning and practicing in their other geology courses. Moreover, some faculty members are better suited by background or inclination to teach certain sets of skills. This coordinated approach avoids unnecessary duplication and allows faculty to build on skills and topics developed in previous courses. The matrix can also be used as a planning tool to identify gaps in the curriculum. In our experience, the skills matrix is a powerful organizational and communication tool. The skills matrix is a representation of what the department believes actually happens in the curriculum. Thus, development of a skills matrix provides a basis for departmental discussions of student learning goals and objectives as well as for describing the existing curriculum. The matrix is also a graphic representation, to college administrators and outside evaluators, of the "intentionality" of an entire curriculum, going beyond single courses and their syllabi. It can be used effectively to engage administration in discussions of departmental planning and needs analysis.

Procedural instruction in invasive bedside procedures: a systematic review and meta-analysis of effective teaching approaches.

PubMed

Huang, Grace C; McSparron, Jakob I; Balk, Ethan M; Richards, Jeremy B; Smith, C Christopher; Whelan, Julia S; Newman, Lori R; Smetana, Gerald W

2016-04-01

Optimal approaches to teaching bedside procedures are unknown. To identify effective instructional approaches in procedural training. We searched PubMed, EMBASE, Web of Science and Cochrane Library through December 2014. We included research articles that addressed procedural training among physicians or physician trainees for 12 bedside procedures. Two independent reviewers screened 9312 citations and identified 344 articles for full-text review. Two independent reviewers extracted data from full-text articles. We included measurements as classified by translational science outcomes T1 (testing settings), T2 (patient care practices) and T3 (patient/public health outcomes). Due to incomplete reporting, we post hoc classified study outcomes as 'negative' or 'positive' based on statistical significance. We performed meta-analyses of outcomes on the subset of studies sharing similar outcomes. We found 161 eligible studies (44 randomised controlled trials (RCTs), 34 non-RCTs and 83 uncontrolled trials). Simulation was the most frequently published educational mode (78%). Our post hoc classification showed that studies involving simulation, competency-based approaches and RCTs had higher frequencies of T2/T3 outcomes. Meta-analyses showed that simulation (risk ratio (RR) 1.54 vs 0.55 for studies with vs without simulation, p=0.013) and competency-based approaches (RR 3.17 vs 0.89, p<0.001) were effective forms of training. This systematic review of bedside procedural skills demonstrates that the current literature is heterogeneous and of varying quality and rigour. Evidence is strongest for the use of simulation and competency-based paradigms in teaching procedures, and these approaches should be the mainstay of programmes that train physicians to perform procedures. Further research should clarify differences among instructional methods (eg, forms of hands-on training) rather than among educational modes (eg, lecture vs simulation). Published by the BMJ Publishing

Genomic approaches to identifying transcriptional regulators of osteoblast differentiation

NASA Technical Reports Server (NTRS)

Stains, Joseph P.; Civitelli, Roberto

2003-01-01

Recent microarray studies of mouse and human osteoblast differentiation in vitro have identified novel transcription factors that may be important in the establishment and maintenance of differentiation. These findings help unravel the pattern of gene-expression changes that underly the complex process of bone formation.

A Methodology for Identifying Cost Effective Strategic Force Mixes.

DTIC Science & Technology

1984-12-01

is not to say that the model could not be used to examine force increases. Given that the strategic force is already a mix of weapons, what is the...rules allow for the determination of what weapon mix to buy based on only the relative prices of the weapons and the parameters of the CES production...AD-A 151 773 AFIT/GOR/OS/84j /r A METHODOLOGY FOR IDENTIFYING COST EFFECTIVE STRATEGIC FORCE MIXES THESIS D I Thomas W. Manacapilli

Combining a nontargeted and targeted metabolomics approach to identify metabolic pathways significantly altered in polycystic ovary syndrome.

PubMed

Chang, Alice Y; Lalia, Antigoni Z; Jenkins, Gregory D; Dutta, Tumpa; Carter, Rickey E; Singh, Ravinder J; Nair, K Sreekumaran

2017-06-01

Polycystic ovary syndrome (PCOS) is a condition of androgen excess and chronic anovulation frequently associated with insulin resistance. We combined a nontargeted and targeted metabolomics approach to identify pathways and metabolites that distinguished PCOS from metabolic syndrome (MetS). Twenty obese women with PCOS were compared with 18 obese women without PCOS. Both groups met criteria for MetS but could not have diabetes mellitus or take medications that treat PCOS or affect lipids or insulin sensitivity. Insulin sensitivity was derived from the frequently sampled intravenous glucose tolerance test. A nontargeted metabolomics approach was performed on fasting plasma samples to identify differentially expressed metabolites, which were further evaluated by principal component and pathway enrichment analysis. Quantitative targeted metabolomics was then applied on candidate metabolites. Measured metabolites were tested for associations with PCOS and clinical variables by logistic and linear regression analyses. This multiethnic, obese sample was matched by age (PCOS, 37±6; MetS, 40±6years) and body mass index (BMI) (PCOS, 34.6±5.1; MetS, 33.7±5.2kg/m 2 ). Principal component analysis of the nontargeted metabolomics data showed distinct group separation of PCOS from MetS controls. From the subset of 385 differentially expressed metabolites, 22% were identified by accurate mass, resulting in 19 canonical pathways significantly altered in PCOS, including amino acid, lipid, steroid, carbohydrate, and vitamin D metabolism. Targeted metabolomics identified many essential amino acids, including branched-chain amino acids (BCAA) that were elevated in PCOS compared with MetS. PCOS was most associated with BCAA (P=.02), essential amino acids (P=.03), the essential amino acid lysine (P=.02), and the lysine metabolite α-aminoadipic acid (P=.02) in models adjusted for surrogate variables representing technical variation in metabolites. No significant differences between

Combining a Nontargeted and Targeted Metabolomics Approach to Identify Metabolic Pathways Significantly Altered in Polycystic Ovary Syndrome

PubMed Central

Chang, Alice Y.; Lalia, Antigoni Z.; Jenkins, Gregory D.; Dutta, Tumpa; Carter, Rickey E.; Singh, Ravinder J.; Sreekumaran Nair, K.

2017-01-01

Objective Polycystic ovary syndrome (PCOS) is a condition of androgen excess and chronic anovulation frequently associated with insulin resistance. We combined a nontargeted and targeted metabolomics approach to identify pathways and metabolites that distinguished PCOS from metabolic syndrome (MetS). Methods Twenty obese women with PCOS were compared with 18 obese women without PCOS. Both groups met criteria for MetS but could not have diabetes mellitus or take medications that treat PCOS or affect lipids or insulin sensitivity. Insulin sensitivity was derived from the frequently sampled intravenous glucose tolerance test. A nontargeted metabolomics approach was performed on fasting plasma samples to identify differentially expressed metabolites, which were further evaluated by principal component and pathway enrichment analysis. Quantitative targeted metabolomics was then applied on candidate metabolites. Measured metabolites were tested for associations with PCOS and clinical variables by logistic and linear regression analyses. Results This multiethnic, obese sample was matched by age (PCOS, 37 ± 6; MetS, 40 ± 6 years) and body mass index (BMI) (PCOS, 34.6 ± 5.1; MetS, 33.7 ± 5.2 kg/m2). Principal component analysis of the nontargeted metabolomics data showed distinct group separation of PCOS from MetS controls. From the subset of 385 differentially expressed metabolites, 22% were identified by accurate mass, resulting in 19 canonical pathways significantly altered in PCOS, including amino acid, lipid, steroid, carbohydrate, and vitamin D metabolism. Targeted metabolomics identified many essential amino acids, including branched-chain amino acids (BCAA) that were elevated in PCOS compared with MetS. PCOS was most associated with BCAA (P = .02), essential amino acids (P = .03), the essential amino acid lysine (P = .02), and the lysine metabolite α-aminoadipic acid (P = .02) in models adjusted for surrogate variables representing technical variation in

A proteomic approach to identifying new drug targets (potentiating topoisomerase II poisons).

PubMed

Jenkins, J R

2008-10-01

Topoisomerase II poisons are an established part of best clinical practice for the treatment of a number of solid tumours and haematological malignancies. However, toxicity and resistance to chemotherapeutic drugs often complicate the treatment. Furthermore, topoisomerase II poisons can also induce sister chromatid exchange, chromosomal recombination and chromosome aberrations and are associated with a significant risk of secondary leukaemia. It would therefore be of great clinical benefit if the efficacy of topoisomerase II inhibitors could be enhanced without the increased toxic side effects. It is proposed that clinical agents targeting topoisomerase II can be enhanced by inhibiting proteins that modulate topoisomerase II. The aim is to identify proteins, that by the nature of their interaction with topoisomerase II, represent putative drug targets.

A Bioinformatic Approach for the Discovery of Antiaging Effects of Baicalein from Scutellaria baicalensis Georgi.

PubMed

Gao, Li; Duan, Dan-Dan; Zhang, Jian-Qin; Zhou, Yu-Zhi; Qin, Xue-Mei; Du, Guan-Hua

2016-03-15

Aging is one of the most complicated phenomena and is the main risk factor for age-related diseases. Based on the public aging-related gene data, we propose a computational approach to predict the antiaging activities of compounds. This approach integrates network pharmacology and target fishing methods with the aim of identifying a potential antiaging compound from Scutellaria baicalensis Georgi. Utilizing this approach and subsequent experimental validation, it was found that baicalein at concentrations of 0.04, 0.2, and 1 mg/mL extended the mean, median, and maximum life spans in Drosophila melanogaster. Particularly, 0.2 mg/mL baicalein extends the mean and median life spans in male flies by 19.80% and 25.64%, respectively. Meanwhile, it was discovered that baicalein improved fertility in flies. Baicalein exerts antiaging effects likely through attenuating oxidative stress, including increases of CAT activity and GSH level and decrease of GSSG level.

Parallel approach to identifying the well-test interpretation model using a neurocomputer

NASA Astrophysics Data System (ADS)

May, Edward A., Jr.; Dagli, Cihan H.

1996-03-01

The well test is one of the primary diagnostic and predictive tools used in the analysis of oil and gas wells. In these tests, a pressure recording device is placed in the well and the pressure response is recorded over time under controlled flow conditions. The interpreted results are indicators of the well's ability to flow and the damage done to the formation surrounding the wellbore during drilling and completion. The results are used for many purposes, including reservoir modeling (simulation) and economic forecasting. The first step in the analysis is the identification of the Well-Test Interpretation (WTI) model, which determines the appropriate solution method. Mis-identification of the WTI model occurs due to noise and non-ideal reservoir conditions. Previous studies have shown that a feed-forward neural network using the backpropagation algorithm can be used to identify the WTI model. One of the drawbacks to this approach is, however, training time, which can run into days of CPU time on personal computers. In this paper a similar neural network is applied using both a personal computer and a neurocomputer. Input data processing, network design, and performance are discussed and compared. The results show that the neurocomputer greatly eases the burden of training and allows the network to outperform a similar network running on a personal computer.

Identifying partial topology of complex dynamical networks via a pinning mechanism

NASA Astrophysics Data System (ADS)

Zhu, Shuaibing; Zhou, Jin; Lu, Jun-an

2018-04-01

In this paper, we study the problem of identifying the partial topology of complex dynamical networks via a pinning mechanism. By using the network synchronization theory and the adaptive feedback controlling method, we propose a method which can greatly reduce the number of nodes and observers in the response network. Particularly, this method can also identify the whole topology of complex networks. A theorem is established rigorously, from which some corollaries are also derived in order to make our method more cost-effective. Several numerical examples are provided to verify the effectiveness of the proposed method. In the simulation, an approach is also given to avoid possible identification failure caused by inner synchronization of the drive network.

An extended transfer operator approach to identify separatrices in open flows

NASA Astrophysics Data System (ADS)

Lünsmann, Benedict; Kantz, Holger

2018-05-01

Vortices of coherent fluid volume are considered to have a substantial impact on transport processes in turbulent media. Yet, due to their Lagrangian nature, detecting these structures is highly nontrivial. In this respect, transfer operator approaches have been proven to provide useful tools: Approximating a possibly time-dependent flow as a discrete Markov process in space and time, information about coherent structures is contained in the operator's eigenvectors, which is usually extracted by employing clustering methods. Here, we propose an extended approach that couples surrounding filaments using "mixing boundary conditions" and focuses on the separation of the inner coherent set and embedding outer flow. The approach refrains from using unsupervised machine learning techniques such as clustering and uses physical arguments by maximizing a coherence ratio instead. We show that this technique improves the reconstruction of separatrices in stationary open flows and succeeds in finding almost-invariant sets in periodically perturbed flows.

To Infinity and Beyond: Using a Narrative Approach to Identify Training Needs for Unknown and Dynamic Situations

ERIC Educational Resources Information Center

Dachner, Alison M.; Saxton, Brian M.; Noe, Raymond A.; Keeton, Kathryn E.

2013-01-01

Training effectiveness depends on conducting a thorough needs assessment. Traditional needs assessment methods are insufficient for today's business environment characterized by rapid pace, risk, and uncertainty. To overcome the deficiencies of traditional needs assessment methods, a narrative-based unstructured interview approach with subject…

The RESPECT Approach to Tailored Telephone Education

ERIC Educational Resources Information Center

Brouse, Corey H.; Basch, Charles E.; Wolf, Randi L.

2008-01-01

Objective: The objective of the RESPECT approach to tailored telephone education (TTE) is described. This approach was shown to be highly effective through a randomized intervention trial for increasing the rate of colorectal cancer (CRC) screening. Methods: At the conclusion of the trial, the investigators identified the main principles that…

Neural Underpinnings of the Identifiable Victim Effect: Affect Shifts Preferences for Giving

PubMed Central

Västfjäll, Daniel; Slovic, Paul; Knutson, Brian

2013-01-01

The “identifiable victim effect” refers to peoples' tendency to preferentially give to identified versus anonymous victims of misfortune, and has been proposed to partly depend on affect. By soliciting charitable donations from human subjects during behavioral and neural (i.e., functional magnetic resonance imaging) experiments, we sought to determine whether and how affect might promote the identifiable victim effect. Behaviorally, subjects gave more to orphans depicted by photographs versus silhouettes, and their shift in preferences was mediated by photograph-induced feelings of positive arousal, but not negative arousal. Neurally, while photographs versus silhouettes elicited activity in widespread circuits associated with facial and affective processing, only nucleus accumbens activity predicted and could statistically account for increased donations. Together, these findings suggest that presenting evaluable identifiable information can recruit positive arousal, which then promotes giving. We propose that affect elicited by identifiable stimuli can compel people to give more to strangers, even despite costs to the self. PMID:24155323

Identifying Obstacles and Research Gaps of Telemedicine Projects: Approach for a State-of-the-Art Analysis.

PubMed

Harst, Lorenz; Timpel, Patrick; Otto, Lena; Wollschlaeger, Bastian; Richter, Peggy; Schlieter, Hannes

2018-01-01

This paper presents an approach for an evaluation of finished telemedicine projects using qualitative methods. Telemedicine applications are said to improve the performance of health care systems. While there are countless telemedicine projects, the vast majority never makes the threshold from testing to implementation and diffusion. Projects were collected from German project databases in the area of telemedicine following systematically developed criteria. In a testing phase, ten projects were subject to a qualitative content analysis to identify limitations, need for further research, and lessons learned. Using Mayring's method of inductive category development, six categories of possible future research were derived. Thus, the proposed method is an important contribution to diffusion and translation research regarding telemedicine, as it is applicable to a systematic research of databases.

The comparative cost-effectiveness of an equity-focused approach to child survival, health, and nutrition: a modelling approach.

PubMed

Carrera, Carlos; Azrack, Adeline; Begkoyian, Genevieve; Pfaffmann, Jerome; Ribaira, Eric; O'Connell, Thomas; Doughty, Patricia; Aung, Kyaw Myint; Prieto, Lorena; Rasanathan, Kumanan; Sharkey, Alyssa; Chopra, Mickey; Knippenberg, Rudolf

2012-10-13

Progress on child mortality and undernutrition has seen widening inequities and a concentration of child deaths and undernutrition in the most deprived communities, threatening the achievement of the Millennium Development Goals. Conversely, a series of recent process and technological innovations have provided effective and efficient options to reach the most deprived populations. These trends raise the possibility that the perceived trade-off between equity and efficiency no longer applies for child health--that prioritising services for the poorest and most marginalised is now more effective and cost effective than mainstream approaches. We tested this hypothesis with a mathematical-modelling approach by comparing the cost-effectiveness in terms of child deaths and stunting events averted between two approaches (from 2011-15 in 14 countries and one province): an equity-focused approach that prioritises the most deprived communities, and a mainstream approach that is representative of current strategies. We combined some existing models, notably the Marginal Budgeting for Bottlenecks Toolkit and the Lives Saved Tool, to do our analysis. We showed that, with the same level of investment, disproportionately higher effects are possible by prioritising the poorest and most marginalised populations, for averting both child mortality and stunting. Our results suggest that an equity-focused approach could result in sharper decreases in child mortality and stunting and higher cost-effectiveness than mainstream approaches, while reducing inequities in effective intervention coverage, health outcomes, and out-of-pocket spending between the most and least deprived groups and geographic areas within countries. Our findings should be interpreted with caution due to uncertainties around some of the model parameters and baseline data. Further research is needed to address some of these gaps in the evidence base. Strategies for improving child nutrition and survival, however

A systems biology approach identified different regulatory networks targeted by KSHV miR-K12-11 in B cells and endothelial cells.

PubMed

Yang, Yajie; Boss, Isaac W; McIntyre, Lauren M; Renne, Rolf

2014-08-08

Kaposi's sarcoma associated herpes virus (KSHV) is associated with tumors of endothelial and lymphoid origin. During latent infection, KSHV expresses miR-K12-11, an ortholog of the human tumor gene hsa-miR-155. Both gene products are microRNAs (miRNAs), which are important post-transcriptional regulators that contribute to tissue specific gene expression. Advances in target identification technologies and molecular interaction databases have allowed a systems biology approach to unravel the gene regulatory networks (GRNs) triggered by miR-K12-11 in endothelial and lymphoid cells. Understanding the tissue specific function of miR-K12-11 will help to elucidate underlying mechanisms of KSHV pathogenesis. Ectopic expression of miR-K12-11 differentially affected gene expression in BJAB cells of lymphoid origin and TIVE cells of endothelial origin. Direct miRNA targeting accounted for a small fraction of the observed transcriptome changes: only 29 genes were identified as putative direct targets of miR-K12-11 in both cell types. However, a number of commonly affected biological pathways, such as carbohydrate metabolism and interferon response related signaling, were revealed by gene ontology analysis. Integration of transcriptome profiling, bioinformatic algorithms, and databases of protein-protein interactome from the ENCODE project identified different nodes of GRNs utilized by miR-K12-11 in a tissue-specific fashion. These effector genes, including cancer associated transcription factors and signaling proteins, amplified the regulatory potential of a single miRNA, from a small set of putative direct targets to a larger set of genes. This is the first comparative analysis of miRNA-K12-11's effects in endothelial and B cells, from tissues infected with KSHV in vivo. MiR-K12-11 was able to broadly modulate gene expression in both cell types. Using a systems biology approach, we inferred that miR-K12-11 establishes its GRN by both repressing master TFs and influencing

Human effects on ecological connectivity in aquatic ecosystems: Integrating scientific approaches to support management and mitigation.

PubMed

Crook, David A; Lowe, Winsor H; Allendorf, Frederick W; Erős, Tibor; Finn, Debra S; Gillanders, Bronwyn M; Hadwen, Wade L; Harrod, Chris; Hermoso, Virgilio; Jennings, Simon; Kilada, Raouf W; Nagelkerken, Ivan; Hansen, Michael M; Page, Timothy J; Riginos, Cynthia; Fry, Brian; Hughes, Jane M

2015-11-15

Understanding the drivers and implications of anthropogenic disturbance of ecological connectivity is a key concern for the conservation of biodiversity and ecosystem processes. Here, we review human activities that affect the movements and dispersal of aquatic organisms, including damming of rivers, river regulation, habitat loss and alteration, human-assisted dispersal of organisms and climate change. Using a series of case studies, we show that the insight needed to understand the nature and implications of connectivity, and to underpin conservation and management, is best achieved via data synthesis from multiple analytical approaches. We identify four key knowledge requirements for progressing our understanding of the effects of anthropogenic impacts on ecological connectivity: autecology; population structure; movement characteristics; and environmental tolerance/phenotypic plasticity. Structuring empirical research around these four broad data requirements, and using this information to parameterise appropriate models and develop management approaches, will allow for mitigation of the effects of anthropogenic disturbance on ecological connectivity in aquatic ecosystems. Copyright © 2015 Elsevier B.V. All rights reserved.

Identifying Successful Practices to Overcome Access to Care Challenges in Community Health Centers: A "Positive Deviance" Approach.

PubMed

Toscos, Tammy; Carpenter, Maria; Flanagan, Mindy; Kunjan, Kislaya; Doebbeling, Bradley N

2018-01-01

Despite health care access challenges among underserved populations, patients, providers, and staff at community health clinics (CHCs) have developed practices to overcome limited access. These "positive deviant" practices translate into organizational policies to improve health care access and patient experience. To identify effective practices to improve access to health care for low-income, uninsured or underinsured, and minority adults and their families. Seven CHC systems, involving over 40 clinics, distributed across one midwestern state in the United States. Ninety-two key informants, comprised of CHC patients (42%) and clinic staff (53%), participated in semi-structured interviews. Interview transcripts were subjected to thematic analysis to identify patient-centered solutions for managing access challenges to primary care for underserved populations. Transcripts were coded using qualitative analytic software. Practices to improve access to care included addressing illiteracy and low health literacy, identifying cost-effective resources, expanding care offerings, enhancing the patient-provider relationship, and cultivating a culture of teamwork and customer service. Helping patients find the least expensive options for transportation, insurance, and medication was the most compelling patient-centered strategy. Appointment reminders and confirmation of patient plans for transportation to appointments reduced no-show rates. We identified nearly 35 practices for improving health care access. These were all patient-centric, uncovered by both clinic staff and patients who had successfully navigated the health care system to improve access.

Instrumental variable approaches to identifying the causal effect of educational attainment on dementia risk

PubMed Central

Nguyen, Thu T.; Tchetgen Tchetgen, Eric J.; Kawachi, Ichiro; Gilman, Stephen E.; Walter, Stefan; Liu, Sze Y.; Manly, Jennifer; Glymour, M. Maria

2015-01-01

Purpose Education is an established correlate of cognitive status in older adulthood, but whether expanding educational opportunities would improve cognitive functioning remains unclear given limitations of prior studies for causal inference. Therefore, we conducted instrumental variable (IV) analyses of the association between education and dementia risk, using for the first time in this area, genetic variants as instruments as well as state-level school policies. Methods IV analyses in the Health and Retirement Study cohort (1998–2010) used two sets of instruments: 1) a genetic risk score constructed from three single nucleotide polymorphisms (SNPs) (n=8,054); and 2) compulsory schooling laws (CSLs) and state school characteristics (term length, student teacher ratios, and expenditures) (n=13,167). Results Employing the genetic risk score as an IV, there was a 1.1% reduction in dementia risk per year of schooling (95% CI: −2.4, 0.02). Leveraging compulsory schooling laws and state school characteristics as IVs, there was a substantially larger protective effect (−9.5%; 95% CI: −14.8, −4.2). Analyses evaluating the plausibility of the IV assumptions indicated estimates derived from analyses relying on CSLs provide the best estimates of the causal effect of education. Conclusion IV analyses suggest education is protective against risk of dementia in older adulthood. PMID:26633592

Social interactions and college enrollment: A combined school fixed effects/instrumental variables approach.

PubMed

Fletcher, Jason M

2015-07-01

This paper provides some of the first evidence of peer effects in college enrollment decisions. There are several empirical challenges in assessing the influences of peers in this context, including the endogeneity of high school, shared group-level unobservables, and identifying policy-relevant parameters of social interactions models. This paper addresses these issues by using an instrumental variables/fixed effects approach that compares students in the same school but different grade-levels who are thus exposed to different sets of classmates. In particular, plausibly exogenous variation in peers' parents' college expectations are used as an instrument for peers' college choices. Preferred specifications indicate that increasing a student's exposure to college-going peers by ten percentage points is predicted to raise the student's probability of enrolling in college by 4 percentage points. This effect is roughly half the magnitude of growing up in a household with married parents (vs. an unmarried household). Copyright © 2015 Elsevier Inc. All rights reserved.

Social Interactions and College Enrollment: A Combined School Fixed Effects/Instrumental Variables Approach

PubMed Central

Fletcher, Jason M.

2015-01-01

This paper provides some of the first evidence of peer effects in college enrollment decisions. There are several empirical challenges in assessing the influences of peers in this context, including the endogeneity of high school, shared group-level unobservables, and identifying policy-relevant parameters of social interactions models. This paper addresses these issues by using an instrumental variables/fixed effects approach that compares students in the same school but different grade-levels who are thus exposed to different sets of classmates. In particular, plausibly exogenous variation in peers’ parents’ college expectations are used as an instrument for peers’ college choices. Preferred specifications indicate that increasing a student’s exposure to college-going peers by ten percentage points is predicted to raise the student’s probability of enrolling in college by 4 percentage points. This effect is roughly half the magnitude of growing up in a household with married parents (vs. an unmarried household). PMID:26004476

Isolating social influences on vulnerability to earthquake shaking: identifying cost-effective mitigation strategies.

NASA Astrophysics Data System (ADS)

Bhloscaidh, Mairead Nic; McCloskey, John; Pelling, Mark; Naylor, Mark

2013-04-01

strong shaking, also identifies both anomalously resilient and anomalously vulnerable countries. We argue that this approach has the potential to direct sociological investigations to expose the underlying causes of the observed non-economic differentiation of vulnerability. At one level, closer study of the earthquakes represented by these data points might expose local or national interventions which are increasing resilience of communities to strong shaking in the absence of major national investment. Ultimately it may contribute to the development of a quantitative evaluation of risk management effectiveness at the national level that can be used better to target and track risk management investments.

Coconut matting bezoar identified by a combined analytical approach.

PubMed Central

Levison, D A; Crocker, P R; Boxall, T A; Randall, K J

1986-01-01

A rare type of bezoar composed of coconut matting was found in the stomach of a caucasian man. The exact identity of the fibres was established by scanning electron microscopy, x-ray energy spectroscopy, and microscopic infrared spectroscopy. This report illustrates the importance of these techniques for identifying the nature of foreign material. Images PMID:3950038

Motivation modulates the effect of approach on implicit preferences.

PubMed

Zogmaister, Cristina; Perugini, Marco; Richetin, Juliette

2016-08-01

With three studies, we investigated whether motivational states can modulate the formation of implicit preferences. In Study 1, participants played a video game in which they repeatedly approached one of two similar beverages, while disregarding the other. A subsequent implicit preference for the target beverage emerged, which increased with participants' thirst. In Study 2, participants approached one brand of potato chips while avoiding the other: Conceptually replicating the moderation observed in Study 1, the implicit preference for the approached brand increased with the number of hours from last food intake. In Study 3, we experimentally manipulated hunger, and the moderation effect emerged again, with hungry participants displaying a higher implicit preference for the approached brand, as compared to satiated participants. In the three studies, the moderation effect was not paralleled in explicit preferences although the latter were affected by the preference inducing manipulation. Theoretical implications and open questions are discussed.

Cost-effectiveness analysis of diarrhoea management approaches in Nigeria: A decision analytical model

PubMed Central

Ekwunife, Obinna I.

2017-01-01

Background Diarrhoea is a leading cause of death in Nigerian children under 5 years. Implementing the most cost-effective approach to diarrhoea management in Nigeria will help optimize health care resources allocation. This study evaluated the cost-effectiveness of various approaches to diarrhoea management namely: the ‘no treatment’ approach (NT); the preventive approach with rotavirus vaccine; the integrated management of childhood illness for diarrhoea approach (IMCI); and rotavirus vaccine plus integrated management of childhood illness for diarrhoea approach (rotavirus vaccine + IMCI). Methods Markov cohort model conducted from the payer’s perspective was used to calculate the cost-effectiveness of the four interventions. The markov model simulated a life cycle of 260 weeks for 33 million children under five years at risk of having diarrhoea (well state). Disability adjusted life years (DALYs) averted was used to quantify clinical outcome. Incremental cost-effectiveness ratio (ICER) served as measure of cost-effectiveness. Results Based on cost-effectiveness threshold of $2,177.99 (i.e. representing Nigerian GDP/capita), all the approaches were very cost-effective but rotavirus vaccine approach was dominated. While IMCI has the lowest ICER of $4.6/DALY averted, the addition of rotavirus vaccine was cost-effective with an ICER of $80.1/DALY averted. Rotavirus vaccine alone was less efficient in optimizing health care resource allocation. Conclusion Rotavirus vaccine + IMCI approach was the most cost-effective approach to childhood diarrhoea management. Its awareness and practice should be promoted in Nigeria. Addition of rotavirus vaccine should be considered for inclusion in the national programme of immunization. Although our findings suggest that addition of rotavirus vaccine to IMCI for diarrhoea is cost-effective, there may be need for further vaccine demonstration studies or real life studies to establish the cost-effectiveness of the vaccine in

Identifying Electromagnetic Attacks against Airports

NASA Astrophysics Data System (ADS)

Kreth, A.; Genender, E.; Doering, O.; Garbe, H.

2012-05-01

This work presents a new and sophisticated approach to detect and locate the origin of electromagnetic attacks. At the example of an airport, a normal electromagnetic environment is defined, in which electromagnetic attacks shall be identified. After a brief consideration of the capabilities of high power electromagnetic sources to produce high field strength values, this contribution finally presents the approach of a sensor network, realizing the identification of electromagnetic attacks.

A Socio-Ecological Approach for Identifying and Contextualising Spatial Ecosystem-Based Adaptation Priorities at the Sub-National Level

PubMed Central

Bourne, Amanda; Holness, Stephen; Holden, Petra; Scorgie, Sarshen; Donatti, Camila I.; Midgley, Guy

2016-01-01

Climate change adds an additional layer of complexity to existing sustainable development and biodiversity conservation challenges. The impacts of global climate change are felt locally, and thus local governance structures will increasingly be responsible for preparedness and local responses. Ecosystem-based adaptation (EbA) options are gaining prominence as relevant climate change solutions. Local government officials seldom have an appropriate understanding of the role of ecosystem functioning in sustainable development goals, or access to relevant climate information. Thus the use of ecosystems in helping people adapt to climate change is limited partially by the lack of information on where ecosystems have the highest potential to do so. To begin overcoming this barrier, Conservation South Africa in partnership with local government developed a socio-ecological approach for identifying spatial EbA priorities at the sub-national level. Using GIS-based multi-criteria analysis and vegetation distribution models, the authors have spatially integrated relevant ecological and social information at a scale appropriate to inform local level political, administrative, and operational decision makers. This is the first systematic approach of which we are aware that highlights spatial priority areas for EbA implementation. Nodes of socio-ecological vulnerability are identified, and the inclusion of areas that provide ecosystem services and ecological resilience to future climate change is innovative. The purpose of this paper is to present and demonstrate a methodology for combining complex information into user-friendly spatial products for local level decision making on EbA. The authors focus on illustrating the kinds of products that can be generated from combining information in the suggested ways, and do not discuss the nuance of climate models nor present specific technical details of the model outputs here. Two representative case studies from rural South Africa

A Socio-Ecological Approach for Identifying and Contextualising Spatial Ecosystem-Based Adaptation Priorities at the Sub-National Level.

PubMed

Bourne, Amanda; Holness, Stephen; Holden, Petra; Scorgie, Sarshen; Donatti, Camila I; Midgley, Guy

2016-01-01

Climate change adds an additional layer of complexity to existing sustainable development and biodiversity conservation challenges. The impacts of global climate change are felt locally, and thus local governance structures will increasingly be responsible for preparedness and local responses. Ecosystem-based adaptation (EbA) options are gaining prominence as relevant climate change solutions. Local government officials seldom have an appropriate understanding of the role of ecosystem functioning in sustainable development goals, or access to relevant climate information. Thus the use of ecosystems in helping people adapt to climate change is limited partially by the lack of information on where ecosystems have the highest potential to do so. To begin overcoming this barrier, Conservation South Africa in partnership with local government developed a socio-ecological approach for identifying spatial EbA priorities at the sub-national level. Using GIS-based multi-criteria analysis and vegetation distribution models, the authors have spatially integrated relevant ecological and social information at a scale appropriate to inform local level political, administrative, and operational decision makers. This is the first systematic approach of which we are aware that highlights spatial priority areas for EbA implementation. Nodes of socio-ecological vulnerability are identified, and the inclusion of areas that provide ecosystem services and ecological resilience to future climate change is innovative. The purpose of this paper is to present and demonstrate a methodology for combining complex information into user-friendly spatial products for local level decision making on EbA. The authors focus on illustrating the kinds of products that can be generated from combining information in the suggested ways, and do not discuss the nuance of climate models nor present specific technical details of the model outputs here. Two representative case studies from rural South Africa

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.

Virtual High-Throughput Screening To Identify Novel Activin Antagonists

PubMed Central

Zhu, Jie; Mishra, Rama K.; Schiltz, Gary E.; Makanji, Yogeshwar; Scheidt, Karl A.; Mazar, Andrew P.; Woodruff, Teresa K.

2015-01-01

Activin belongs to the TGFβ superfamily, which is associated with several disease conditions, including cancer-related cachexia, preterm labor with delivery, and osteoporosis. Targeting activin and its related signaling pathways holds promise as a therapeutic approach to these diseases. A small-molecule ligand-binding groove was identified in the interface between the two activin βA subunits and was used for a virtual high-throughput in silico screening of the ZINC database to identify hits. Thirty-nine compounds without significant toxicity were tested in two well-established activin assays: FSHβ transcription and HepG2 cell apoptosis. This screening workflow resulted in two lead compounds: NUCC-474 and NUCC-555. These potential activin antagonists were then shown to inhibit activin A-mediated cell proliferation in ex vivo ovary cultures. In vivo testing showed that our most potent compound (NUCC-555) caused a dose-dependent decrease in FSH levels in ovariectomized mice. The Blitz competition binding assay confirmed target binding of NUCC-555 to the activin A:ActRII that disrupts the activin A:ActRII complex’s binding with ALK4-ECD-Fc in a dose-dependent manner. The NUCC-555 also specifically binds to activin A compared with other TGFβ superfamily member myostatin (GDF8). These data demonstrate a new in silico-based strategy for identifying small-molecule activin antagonists. Our approach is the first to identify a first-in-class small-molecule antagonist of activin binding to ALK4, which opens a completely new approach to inhibiting the activity of TGFβ receptor superfamily members. in addition, the lead compound can serve as a starting point for lead optimization toward the goal of a compound that may be effective in activin-mediated diseases. PMID:26098096

Identifying Effective Pedagogical Approaches for Online Workplace Training: A Case Study of the South African Wood Products Manufacturing Sector

ERIC Educational Resources Information Center

Macdonald, Ian S.; Bullen, Mark; Kozak, R. A.

2007-01-01

This study investigated appropriate pedagogical techniques for workplace e-learning programs in the South African wood products (furniture) manufacturing sector. The study found that learners responded favourably to constructivist teaching approaches, such as asynchronous discussions, open-ended task-based activities, and assignments incorporating…

What Are the Characteristics of Principals Identified As Effective by Teachers?

ERIC Educational Resources Information Center

Fowler, William J., Jr.

This exploratory study investigated which characteristics of a principal are identified as effective by teachers in the same school setting. The data were obtained from the Schools and Staffing Study of 1988, from the National Center for Education Statistics (NCES). The Teacher Questionnaire of the Schools and Staffing Survey (SASS) questioned…

Identifying environmental correlates of intraspecific genetic variation.

PubMed

Harrisson, K A; Yen, J D L; Pavlova, A; Rourke, M L; Gilligan, D; Ingram, B A; Lyon, J; Tonkin, Z; Sunnucks, P

2016-09-01

Genetic variation is critical to the persistence of populations and their capacity to adapt to environmental change. The distribution of genetic variation across a species' range can reveal critical information that is not necessarily represented in species occurrence or abundance patterns. We identified environmental factors associated with the amount of intraspecific, individual-based genetic variation across the range of a widespread freshwater fish species, the Murray cod Maccullochella peelii. We used two different approaches to statistically quantify the relative importance of predictor variables, allowing for nonlinear relationships: a random forest model and a Bayesian approach. The latter also accounted for population history. Both approaches identified associations between homozygosity by locus and both disturbance to the natural flow regime and mean annual flow. Homozygosity by locus was negatively associated with disturbance to the natural flow regime, suggesting that river reaches with more disturbed flow regimes may support larger, more genetically diverse populations. Our findings are consistent with the hypothesis that artificially induced perennial flows in regulated channels may provide greater and more consistent habitat and reduce the frequency of population bottlenecks that can occur frequently under the highly variable and unpredictable natural flow regime of the system. Although extensive river regulation across eastern Australia has not had an overall positive effect on Murray cod numbers over the past century, regulation may not represent the primary threat to Murray cod survival. Instead, pressures other than flow regulation may be more critical to the persistence of Murray cod (for example, reduced frequency of large floods, overfishing and chemical pollution).

A drug repositioning approach identifies tricyclic antidepressants as inhibitors of small cell lung cancer and other neuroendocrine tumors

PubMed Central

Jahchan, Nadine S; Dudley, Joel T; Mazur, Pawel K; Flores, Natasha; Yang, Dian; Palmerton, Alec; Zmoos, Anne-Flore; Vaka, Dedeepya; Tran, Kim QT; Zhou, Margaret; Krasinska, Karolina; Riess, Jonathan W; Neal, Joel W; Khatri, Purvesh; Park, Kwon S; Butte, Atul J; Sage, Julien

2013-01-01

Small cell lung cancer (SCLC) is an aggressive neuroendocrine subtype of lung cancer with high mortality. We used a systematic drug-repositioning bioinformatics approach querying a large compendium of gene expression profiles to identify candidate FDA-approved drugs to treat SCLC. We found that tricyclic antidepressants and related molecules potently induce apoptosis in both chemonaïve and chemoresistant SCLC cells in culture, in mouse and human SCLC tumors transplanted into immunocompromised mice, and in endogenous tumors from a mouse model for human SCLC. The candidate drugs activate stress pathways and induce cell death in SCLC cells, at least in part by disrupting autocrine survival signals involving neurotransmitters and their G protein-coupled receptors. The candidate drugs inhibit the growth of other neuroendocrine tumors, including pancreatic neuroendocrine tumors and Merkel cell carcinoma. These experiments identify novel targeted strategies that can be rapidly evaluated in patients with neuroendocrine tumors through the repurposing of approved drugs. PMID:24078773

Complementary Approaches to Existing Target Based Drug Discovery for Identifying Novel Drug Targets.

PubMed

Vasaikar, Suhas; Bhatia, Pooja; Bhatia, Partap G; Chu Yaiw, Koon

2016-11-21

In the past decade, it was observed that the relationship between the emerging New Molecular Entities and the quantum of R&D investment has not been favorable. There might be numerous reasons but few studies stress the introduction of target based drug discovery approach as one of the factors. Although a number of drugs have been developed with an emphasis on a single protein target, yet identification of valid target is complex. The approach focuses on an in vitro single target, which overlooks the complexity of cell and makes process of validation drug targets uncertain. Thus, it is imperative to search for alternatives rather than looking at success stories of target-based drug discovery. It would be beneficial if the drugs were developed to target multiple components. New approaches like reverse engineering and translational research need to take into account both system and target-based approach. This review evaluates the strengths and limitations of known drug discovery approaches and proposes alternative approaches for increasing efficiency against treatment.

Identifying treatment effect heterogeneity in clinical trials using subpopulations of events: STEPP.

PubMed

Lazar, Ann A; Bonetti, Marco; Cole, Bernard F; Yip, Wai-Ki; Gelber, Richard D

2016-04-01

Investigators conducting randomized clinical trials often explore treatment effect heterogeneity to assess whether treatment efficacy varies according to patient characteristics. Identifying heterogeneity is central to making informed personalized healthcare decisions. Treatment effect heterogeneity can be investigated using subpopulation treatment effect pattern plot (STEPP), a non-parametric graphical approach that constructs overlapping patient subpopulations with varying values of a characteristic. Procedures for statistical testing using subpopulation treatment effect pattern plot when the endpoint of interest is survival remain an area of active investigation. A STEPP analysis was used to explore patterns of absolute and relative treatment effects for varying levels of a breast cancer biomarker, Ki-67, in the phase III Breast International Group 1-98 randomized clinical trial, comparing letrozole to tamoxifen as adjuvant therapy for postmenopausal women with hormone receptor-positive breast cancer. Absolute treatment effects were measured by differences in 4-year cumulative incidence of breast cancer recurrence, while relative effects were measured by the subdistribution hazard ratio in the presence of competing risks using O-E (observed-minus-expected) methodology, an intuitive non-parametric method. While estimation of hazard ratio values based on O-E methodology has been shown, a similar development for the subdistribution hazard ratio has not. Furthermore, we observed that the subpopulation treatment effect pattern plot analysis may not produce results, even with 100 patients within each subpopulation. After further investigation through simulation studies, we observed inflation of the type I error rate of the traditional test statistic and sometimes singular variance-covariance matrix estimates that may lead to results not being produced. This is due to the lack of sufficient number of events within the subpopulations, which we refer to as instability of

Measuring management's perspective of data quality in Pakistan's Tuberculosis control programme: a test-based approach to identify data quality dimensions.

PubMed

Ali, Syed Mustafa; Anjum, Naveed; Kamel Boulos, Maged N; Ishaq, Muhammad; Aamir, Javariya; Haider, Ghulam Rasool

2018-01-16

Data quality is core theme of programme's performance assessment and many organizations do not have any data quality improvement strategy, wherein data quality dimensions and data quality assessment framework are important constituents. As there is limited published research about the data quality specifics that are relevant to the context of Pakistan's Tuberculosis control programme, this study aims at identifying the applicable data quality dimensions by using the 'fitness-for-purpose' perspective. Forty-two respondents pooled a total of 473 years of professional experience, out of which 223 years (47%) were in TB control related programmes. Based on the responses against 11 practical cases, adopted from the routine recording and reporting system of Pakistan's TB control programme (real identities of patient were masked), completeness, accuracy, consistency, vagueness, uniqueness and timeliness are the applicable data quality dimensions relevant to the programme's context, i.e. work settings and field of practice. Based on a 'fitness-for-purpose' approach to data quality, this study used a test-based approach to measure management's perspective and identified data quality dimensions pertinent to the programme and country specific requirements. Implementation of a data quality improvement strategy and achieving enhanced data quality would greatly help organizations in promoting data use for informed decision making.

AbsIDconvert: An absolute approach for converting genetic identifiers at different granularities

PubMed Central

2012-01-01

Background High-throughput molecular biology techniques yield vast amounts of data, often by detecting small portions of ribonucleotides corresponding to specific identifiers. Existing bioinformatic methodologies categorize and compare these elements using inferred descriptive annotation given this sequence information irrespective of the fact that it may not be representative of the identifier as a whole. Results All annotations, no matter the granularity, can be aligned to genomic sequences and therefore annotated by genomic intervals. We have developed AbsIDconvert, a methodology for converting between genomic identifiers by first mapping them onto a common universal coordinate system using an interval tree which is subsequently queried for overlapping identifiers. AbsIDconvert has many potential uses, including gene identifier conversion, identification of features within a genomic region, and cross-species comparisons. The utility is demonstrated in three case studies: 1) comparative genomic study mapping plasmodium gene sequences to corresponding human and mosquito transcriptional regions; 2) cross-species study of Incyte clone sequences; and 3) analysis of human Ensembl transcripts mapped by Affymetrix®; and Agilent microarray probes. AbsIDconvert currently supports ID conversion of 53 species for a given list of input identifiers, genomic sequence, or genome intervals. Conclusion AbsIDconvert provides an efficient and reliable mechanism for conversion between identifier domains of interest. The flexibility of this tool allows for custom definition identifier domains contingent upon the availability and determination of a genomic mapping interval. As the genomes and the sequences for genetic elements are further refined, this tool will become increasingly useful and accurate. AbsIDconvert is freely available as a web application or downloadable as a virtual machine at: http://bioinformatics.louisville.edu/abid/. PMID:22967011

An Approach for Identifying Benefit Segments among Prospective College Students.

ERIC Educational Resources Information Center

Miller, Patrick; And Others

1990-01-01

A study investigated the importance to 578 applicants of various benefits offered by a moderately selective private university. Applicants rated the institution on 43 academic, social, financial, religious, and curricular attributes. The objective was to test the efficacy of one approach to college market segmentation. Results support the utility…

Effectiveness of a Social Change Approach to Sexual Assault Prevention

ERIC Educational Resources Information Center

Edwards, Keith E.

2009-01-01

The author examined the impact on resident assistants of a social change approach to sexual assault prevention. The interactive multi-media program focused on engaging men on sexual assault prevention, accurately defining rape for college men and women, identifying aspects of the rape culture in society and on-campus, and empowering college…

The differential effects of intrinsic and identified motivation on well-being and performance: prospective, experimental, and implicit approaches to self-determination theory.

PubMed

Burton, Kimberly D; Lydon, John E; D'Alessandro, David U; Koestner, Richard

2006-10-01

Self-determination theory research has demonstrated that intrinsic and identified self-regulations are associated with successful adaptation. However, few distinctions are typically made between these regulations and their outcomes. In the present studies, the associations between intrinsic and identified motivations and outcomes of psychological well-being and academic performance are compared in educational settings. In Study 1, intrinsic self-regulation predicted psychological well-being, independent of academic performance. In contrast, identified regulation predicted academic performance. Additionally, the more that students demonstrated an identified academic regulation, the more that their psychological well-being was contingent on performance. In Study 2a, priming intrinsic self-regulation led to greater psychological well-being 10 days later. In Study 2b, an implicit measure of identified regulation predicted academic performance 6 weeks later. Results indicate the need to address important distinctions between intrinsic and identified regulations. 2006 APA, all rights reserved

Identifying Effective Components of Child Maltreatment Interventions: A Meta-analysis.

PubMed

van der Put, Claudia E; Assink, Mark; Gubbels, Jeanne; Boekhout van Solinge, Noëlle F

2018-06-01

There is a lack of knowledge about specific components that make interventions effective in preventing or reducing child maltreatment. The aim of the present meta-analysis was to increase this knowledge by summarizing findings on effects of interventions for child maltreatment and by examining potential moderators of this effect, such as intervention components and study characteristics. Identifying effective components is essential for developing or improving child maltreatment interventions. A literature search yielded 121 independent studies (N = 39,044) examining the effects of interventions for preventing or reducing child maltreatment. From these studies, 352 effect sizes were extracted. The overall effect size was significant and small in magnitude for both preventive interventions (d = 0.26, p < .001) and curative interventions (d = 0.36, p < .001). Cognitive behavioral therapy, home visitation, parent training, family-based/multisystemic, substance abuse, and combined interventions were effective in preventing and/or reducing child maltreatment. For preventive interventions, larger effect sizes were found for short-term interventions (0-6 months), interventions focusing on increasing self-confidence of parents, and interventions delivered by professionals only. Further, effect sizes of preventive interventions increased as follow-up duration increased, which may indicate a sleeper effect of preventive interventions. For curative interventions, larger effect sizes were found for interventions focusing on improving parenting skills and interventions providing social and/or emotional support. Interventions can be effective in preventing or reducing child maltreatment. Theoretical and practical implications are discussed.

Genetic Mapping Identifies Novel Highly Protective Antigens for an Apicomplexan Parasite

PubMed Central

Blake, Damer P.; Billington, Karen J.; Copestake, Susan L.; Oakes, Richard D.; Quail, Michael A.; Wan, Kiew-Lian; Shirley, Martin W.; Smith, Adrian L.

2011-01-01

Apicomplexan parasites are responsible for a myriad of diseases in humans and livestock; yet despite intensive effort, development of effective sub-unit vaccines remains a long-term goal. Antigenic complexity and our inability to identify protective antigens from the pool that induce response are serious challenges in the development of new vaccines. Using a combination of parasite genetics and selective barriers with population-based genetic fingerprinting, we have identified that immunity against the most important apicomplexan parasite of livestock (Eimeria spp.) was targeted against a few discrete regions of the genome. Herein we report the identification of six genomic regions and, within two of those loci, the identification of true protective antigens that confer immunity as sub-unit vaccines. The first of these is an Eimeria maxima homologue of apical membrane antigen-1 (AMA-1) and the second is a previously uncharacterised gene that we have termed ‘immune mapped protein-1’ (IMP-1). Significantly, homologues of the AMA-1 antigen are protective with a range of apicomplexan parasites including Plasmodium spp., which suggest that there may be some characteristic(s) of protective antigens shared across this diverse group of parasites. Interestingly, homologues of the IMP-1 antigen, which is protective against E. maxima infection, can be identified in Toxoplasma gondii and Neospora caninum. Overall, this study documents the discovery of novel protective antigens using a population-based genetic mapping approach allied with a protection-based screen of candidate genes. The identification of AMA-1 and IMP-1 represents a substantial step towards development of an effective anti-eimerian sub-unit vaccine and raises the possibility of identification of novel antigens for other apicomplexan parasites. Moreover, validation of the parasite genetics approach to identify effective antigens supports its adoption in other parasite systems where legitimate protective

Identifying Predictors of Physics Item Difficulty: A Linear Regression Approach

ERIC Educational Resources Information Center

Mesic, Vanes; Muratovic, Hasnija

2011-01-01

Large-scale assessments of student achievement in physics are often approached with an intention to discriminate students based on the attained level of their physics competencies. Therefore, for purposes of test design, it is important that items display an acceptable discriminatory behavior. To that end, it is recommended to avoid extraordinary…

A human genome-wide loss-of-function screen identifies effective chikungunya antiviral drugs

PubMed Central

Karlas, Alexander; Berre, Stefano; Couderc, Thérèse; Varjak, Margus; Braun, Peter; Meyer, Michael; Gangneux, Nicolas; Karo-Astover, Liis; Weege, Friderike; Raftery, Martin; Schönrich, Günther; Klemm, Uwe; Wurzlbauer, Anne; Bracher, Franz; Merits, Andres; Meyer, Thomas F.; Lecuit, Marc

2016-01-01

Chikungunya virus (CHIKV) is a globally spreading alphavirus against which there is no commercially available vaccine or therapy. Here we use a genome-wide siRNA screen to identify 156 proviral and 41 antiviral host factors affecting CHIKV replication. We analyse the cellular pathways in which human proviral genes are involved and identify druggable targets. Twenty-one small-molecule inhibitors, some of which are FDA approved, targeting six proviral factors or pathways, have high antiviral activity in vitro, with low toxicity. Three identified inhibitors have prophylactic antiviral effects in mouse models of chikungunya infection. Two of them, the calmodulin inhibitor pimozide and the fatty acid synthesis inhibitor TOFA, have a therapeutic effect in vivo when combined. These results demonstrate the value of loss-of-function screening and pathway analysis for the rational identification of small molecules with therapeutic potential and pave the way for the development of new, host-directed, antiviral agents. PMID:27177310

A human genome-wide loss-of-function screen identifies effective chikungunya antiviral drugs.

PubMed

Karlas, Alexander; Berre, Stefano; Couderc, Thérèse; Varjak, Margus; Braun, Peter; Meyer, Michael; Gangneux, Nicolas; Karo-Astover, Liis; Weege, Friderike; Raftery, Martin; Schönrich, Günther; Klemm, Uwe; Wurzlbauer, Anne; Bracher, Franz; Merits, Andres; Meyer, Thomas F; Lecuit, Marc

2016-05-12

Chikungunya virus (CHIKV) is a globally spreading alphavirus against which there is no commercially available vaccine or therapy. Here we use a genome-wide siRNA screen to identify 156 proviral and 41 antiviral host factors affecting CHIKV replication. We analyse the cellular pathways in which human proviral genes are involved and identify druggable targets. Twenty-one small-molecule inhibitors, some of which are FDA approved, targeting six proviral factors or pathways, have high antiviral activity in vitro, with low toxicity. Three identified inhibitors have prophylactic antiviral effects in mouse models of chikungunya infection. Two of them, the calmodulin inhibitor pimozide and the fatty acid synthesis inhibitor TOFA, have a therapeutic effect in vivo when combined. These results demonstrate the value of loss-of-function screening and pathway analysis for the rational identification of small molecules with therapeutic potential and pave the way for the development of new, host-directed, antiviral agents.

Identifying active foraminifera in the Sea of Japan using metatranscriptomic approach

NASA Astrophysics Data System (ADS)

Lejzerowicz, Franck; Voltsky, Ivan; Pawlowski, Jan

2013-02-01

Metagenetics represents an efficient and rapid tool to describe environmental diversity patterns of microbial eukaryotes based on ribosomal DNA sequences. However, the results of metagenetic studies are often biased by the presence of extracellular DNA molecules that are persistent in the environment, especially in deep-sea sediment. As an alternative, short-lived RNA molecules constitute a good proxy for the detection of active species. Here, we used a metatranscriptomic approach based on RNA-derived (cDNA) sequences to study the diversity of the deep-sea benthic foraminifera and compared it to the metagenetic approach. We analyzed 257 ribosomal DNA and cDNA sequences obtained from seven sediments samples collected in the Sea of Japan at depths ranging from 486 to 3665 m. The DNA and RNA-based approaches gave a similar view of the taxonomic composition of foraminiferal assemblage, but differed in some important points. First, the cDNA dataset was dominated by sequences of rotaliids and robertiniids, suggesting that these calcareous species, some of which have been observed in Rose Bengal stained samples, are the most active component of foraminiferal community. Second, the richness of monothalamous (single-chambered) foraminifera was particularly high in DNA extracts from the deepest samples, confirming that this group of foraminifera is abundant but not necessarily very active in the deep-sea sediments. Finally, the high divergence of undetermined sequences in cDNA dataset indicate the limits of our database and lack of knowledge about some active but possibly rare species. Our study demonstrates the capability of the metatranscriptomic approach to detect active foraminiferal species and prompt its use in future high-throughput sequencing-based environmental surveys.

DSPCP: A Data Scalable Approach for Identifying Relationships in Parallel Coordinates.

PubMed

Nguyen, Hoa; Rosen, Paul

2018-03-01

Parallel coordinates plots (PCPs) are a well-studied technique for exploring multi-attribute datasets. In many situations, users find them a flexible method to analyze and interact with data. Unfortunately, using PCPs becomes challenging as the number of data items grows large or multiple trends within the data mix in the visualization. The resulting overdraw can obscure important features. A number of modifications to PCPs have been proposed, including using color, opacity, smooth curves, frequency, density, and animation to mitigate this problem. However, these modified PCPs tend to have their own limitations in the kinds of relationships they emphasize. We propose a new data scalable design for representing and exploring data relationships in PCPs. The approach exploits the point/line duality property of PCPs and a local linear assumption of data to extract and represent relationship summarizations. This approach simultaneously shows relationships in the data and the consistency of those relationships. Our approach supports various visualization tasks, including mixed linear and nonlinear pattern identification, noise detection, and outlier detection, all in large data. We demonstrate these tasks on multiple synthetic and real-world datasets.

Identifying Postpartum Intervention Approaches to Reduce Cardiometabolic Risk Among American Indian Women With Prior Gestational Diabetes, Oklahoma, 2012–2013

PubMed Central

Peercy, Michael; Woods, J. Cedric; Parker, Stephany P.; Jackson, Teresa; Mata, Sara A.; McCage, Shondra; Levkoff, Sue E.; Nicklas, Jacinda M.; Seely, Ellen W.

2015-01-01

Introduction Innovative approaches are needed to reduce cardiometabolic risk among American Indian women with a history of gestational diabetes. We assessed beliefs of Oklahoma American Indian women about preventing type 2 diabetes and cardiovascular disease after having gestational diabetes. We also assessed barriers and facilitators to healthy lifestyle changes postpartum and intervention approaches that facilitate participation in a postpartum lifestyle program. Methods In partnership with a tribal health system, we conducted a mixed-method study with American Indian women aged 19 to 45 years who had prior gestational diabetes, using questionnaires, focus groups, and individual interviews. Questionnaires were used to identify women’s cardiometabolic risk perceptions and feasibility and acceptability of Internet or mobile phone technology for delivery of a postpartum lifestyle modification program. Focus groups and individual interviews were conducted to identify key perspectives and preferences related to a potential program. Results Participants were 26 women, all of whom completed surveys; 11 women participated in focus group sessions, and 15 participated in individual interviews. Most women believed they would inevitably develop diabetes, cardiovascular disease, or both; however, they were optimistic that they could delay onset with lifestyle change. Most women expressed enthusiasm for a family focused, technology-based intervention that emphasizes the importance of delaying disease onset, provides motivation, and promotes accountability while accommodating women’s competing priorities. Conclusions Our findings suggest that an intervention that uses the Internet, text messaging, or both and that emphasizes the benefits of delaying disease onset should be tested as a novel, culturally relevant approach to reducing rates of diabetes and cardiovascular disease in this high-risk population. PMID:25837258

Identifying Treatment Effect Modifiers in the STarT Back Trial: A Secondary Analysis.

PubMed

Beneciuk, Jason M; Hill, Jonathan C; Campbell, Paul; Afolabi, Ebenezer; George, Steven Z; Dunn, Kate M; Foster, Nadine E

2017-01-01

Identification of patient characteristics influencing treatment outcomes is a top low back pain (LBP) research priority. Results from the STarT Back trial support the effectiveness of prognostic stratified care for LBP compared with current best care, however, patient characteristics associated with treatment response have not yet been explored. The purpose of this secondary analysis was to identify treatment effect modifiers within the STarT Back trial at 4-month follow-up (n = 688). Treatment response was dichotomized using back-specific physical disability measured using the Roland-Morris Disability Questionnaire (≥7). Candidate modifiers were identified using previous literature and evaluated using logistic regression with statistical interaction terms to provide preliminary evidence of treatment effect modification. Socioeconomic status (SES) was identified as an effect modifier for disability outcomes (odds ratio [OR] = 1.71, P = .028). High SES patients receiving prognostic stratified care were 2.5 times less likely to have a poor outcome compared with low SES patients receiving best current care (OR = .40, P = .006). Education level (OR = 1.33, P = .109) and number of pain medications (OR = .64, P = .140) met our criteria for effect modification with weaker evidence (.20 > P ≥ .05). These findings provide preliminary evidence for SES, education, and number of pain medications as treatment effect modifiers of prognostic stratified care delivered in the STarT Back Trial. This analysis provides preliminary exploratory findings about the characteristics of patients who might least likely benefit from targeted treatment using prognostic stratified care for LBP. Copyright © 2016 American Pain Society. Published by Elsevier Inc. All rights reserved.

On discounting of health gains from human papillomavirus vaccination: effects of different approaches.

PubMed

Westra, Tjalke A; Parouty, Mehraj; Brouwer, Werner B; Beutels, Philippe H; Rogoza, Raina M; Rozenbaum, Mark H; Daemen, Toos; Wilschut, Jan C; Boersma, Cornelis; Postma, Maarten J

2012-05-01

Discounting has long been a matter of controversy in the field of health economic evaluations. How to weigh future health effects has resulted in ongoing discussions. These discussions are imminently relevant for health care interventions with current costs but future benefits. Different approaches to discount health effects have been proposed. In this study, we estimated the impact of different approaches for discounting health benefits of human papillomavirus (HPV) vaccination. An HPV model was used to estimate the impact of different discounting approaches on the present value of health effects. For the constant discount approaches, we varied the discount rate for health effects ranging from 0% to 4%. Next, the impact of relevant alternative discounting approaches was estimated, including hyperbolic, proportional, stepwise, and time-shifted discounting. The present value of health effects gained through HPV vaccination varied strongly when varying discount rates and approaches. The application of the current Dutch guidelines resulted in a present value of health effects that was eight or two times higher than that produced when using the proportional discounting approach or when using the internationally more common 4% discount rate for health effects, respectively. Obviously, such differences translate into large variations in corresponding incremental cost-effectiveness ratios. The exact discount rate and approach chosen in an economic evaluation importantly impact the projected value of health benefits of HPV vaccination. Investigating alternative discounting approaches in health-economic analysis is important, especially for vaccination programs yielding health effects far into the future. Our study underlines the relevance of ongoing discussions on how and at what rates to discount. Copyright © 2012 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

SU-F-T-247: Collision Risks in a Modern Radiation Oncology Department: An Efficient Approach to Failure Modes and Effects Analysis

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

Schubert, L; Westerly, D; Vinogradskiy, Y

Purpose: Collisions between treatment equipment and patients are potentially catastrophic. Modern technology now commonly involves automated remote motion during imaging and treatment, yet a systematic assessment to identify and mitigate collision risks has yet to be performed. Failure modes and effects analysis (FMEA) is a method of risk assessment that has been increasingly used in healthcare, yet can be resource intensive. This work presents an efficient approach to FMEA to identify collision risks and implement practical interventions within a modern radiation therapy department. Methods: Potential collisions (e.g. failure modes) were assessed for all treatment and simulation rooms by teams consistingmore » of physicists, therapists, and radiation oncologists. Failure modes were grouped into classes according to similar characteristics. A single group meeting was held to identify implementable interventions for the highest priority classes of failure modes. Results: A total of 60 unique failure modes were identified by 6 different teams of physicists, therapists, and radiation oncologists. Failure modes were grouped into four main classes: specific patient setups, automated equipment motion, manual equipment motion, and actions in QA or service mode. Two of these classes, unusual patient setups and automated machine motion, were identified as being high priority in terms severity of consequence and addressability by interventions. The two highest risk classes consisted of 33 failure modes (55% of the total). In a single one hour group meeting, 6 interventions were identified. Those interventions addressed 100% of the high risk classes of failure modes (55% of all failure modes identified). Conclusion: A class-based approach to FMEA was developed to efficiently identify collision risks and implement interventions in a modern radiation oncology department. Failure modes and interventions will be listed, and a comparison of this approach against traditional FMEA

The Effects of Different Teaching Approaches in Introductory Financial Accounting

ERIC Educational Resources Information Center

Chiang, Bea; Nouri, Hossein; Samanta, Subarna

2014-01-01

The purpose of the research is to examine the effect of the two different teaching approaches in the first accounting course on student performance in a subsequent finance course. The study compares 128 accounting and finance students who took introductory financial accounting by either a user approach or a traditional preparer approach to examine…

An original phylogenetic approach identified mitochondrial haplogroup T1a1 as inversely associated with breast cancer risk in BRCA2 mutation carriers.

PubMed

Blein, Sophie; Bardel, Claire; Danjean, Vincent; McGuffog, Lesley; Healey, Sue; Barrowdale, Daniel; Lee, Andrew; Dennis, Joe; Kuchenbaecker, Karoline B; Soucy, Penny; Terry, Mary Beth; Chung, Wendy K; Goldgar, David E; Buys, Saundra S; Janavicius, Ramunas; Tihomirova, Laima; Tung, Nadine; Dorfling, Cecilia M; van Rensburg, Elizabeth J; Neuhausen, Susan L; Ding, Yuan Chun; Gerdes, Anne-Marie; Ejlertsen, Bent; Nielsen, Finn C; Hansen, Thomas Vo; Osorio, Ana; Benitez, Javier; Conejero, Raquel Andrés; Segota, Ena; Weitzel, Jeffrey N; Thelander, Margo; Peterlongo, Paolo; Radice, Paolo; Pensotti, Valeria; Dolcetti, Riccardo; Bonanni, Bernardo; Peissel, Bernard; Zaffaroni, Daniela; Scuvera, Giulietta; Manoukian, Siranoush; Varesco, Liliana; Capone, Gabriele L; Papi, Laura; Ottini, Laura; Yannoukakos, Drakoulis; Konstantopoulou, Irene; Garber, Judy; Hamann, Ute; Donaldson, Alan; Brady, Angela; Brewer, Carole; Foo, Claire; Evans, D Gareth; Frost, Debra; Eccles, Diana; Douglas, Fiona; Cook, Jackie; Adlard, Julian; Barwell, Julian; Walker, Lisa; Izatt, Louise; Side, Lucy E; Kennedy, M John; Tischkowitz, Marc; Rogers, Mark T; Porteous, Mary E; Morrison, Patrick J; Platte, Radka; Eeles, Ros; Davidson, Rosemarie; Hodgson, Shirley; Cole, Trevor; Godwin, Andrew K; Isaacs, Claudine; Claes, Kathleen; De Leeneer, Kim; Meindl, Alfons; Gehrig, Andrea; Wappenschmidt, Barbara; Sutter, Christian; Engel, Christoph; Niederacher, Dieter; Steinemann, Doris; Plendl, Hansjoerg; Kast, Karin; Rhiem, Kerstin; Ditsch, Nina; Arnold, Norbert; Varon-Mateeva, Raymonda; Schmutzler, Rita K; Preisler-Adams, Sabine; Markov, Nadja Bogdanova; Wang-Gohrke, Shan; de Pauw, Antoine; Lefol, Cédrick; Lasset, Christine; Leroux, Dominique; Rouleau, Etienne; Damiola, Francesca; Dreyfus, Hélène; Barjhoux, Laure; Golmard, Lisa; Uhrhammer, Nancy; Bonadona, Valérie; Sornin, Valérie; Bignon, Yves-Jean; Carter, Jonathan; Van Le, Linda; Piedmonte, Marion; DiSilvestro, Paul A; de la Hoya, Miguel; Caldes, Trinidad; Nevanlinna, Heli; Aittomäki, Kristiina; Jager, Agnes; van den Ouweland, Ans Mw; Kets, Carolien M; Aalfs, Cora M; van Leeuwen, Flora E; Hogervorst, Frans Bl; Meijers-Heijboer, Hanne Ej; Oosterwijk, Jan C; van Roozendaal, Kees Ep; Rookus, Matti A; Devilee, Peter; van der Luijt, Rob B; Olah, Edith; Diez, Orland; Teulé, Alex; Lazaro, Conxi; Blanco, Ignacio; Del Valle, Jesús; Jakubowska, Anna; Sukiennicki, Grzegorz; Gronwald, Jacek; Lubinski, Jan; Durda, Katarzyna; Jaworska-Bieniek, Katarzyna; Agnarsson, Bjarni A; Maugard, Christine; Amadori, Alberto; Montagna, Marco; Teixeira, Manuel R; Spurdle, Amanda B; Foulkes, William; Olswold, Curtis; Lindor, Noralane M; Pankratz, Vernon S; Szabo, Csilla I; Lincoln, Anne; Jacobs, Lauren; Corines, Marina; Robson, Mark; Vijai, Joseph; Berger, Andreas; Fink-Retter, Anneliese; Singer, Christian F; Rappaport, Christine; Kaulich, Daphne Geschwantler; Pfeiler, Georg; Tea, Muy-Kheng; Greene, Mark H; Mai, Phuong L; Rennert, Gad; Imyanitov, Evgeny N; Mulligan, Anna Marie; Glendon, Gord; Andrulis, Irene L; Tchatchou, Sandrine; Toland, Amanda Ewart; Pedersen, Inge Sokilde; Thomassen, Mads; Kruse, Torben A; Jensen, Uffe Birk; Caligo, Maria A; Friedman, Eitan; Zidan, Jamal; Laitman, Yael; Lindblom, Annika; Melin, Beatrice; Arver, Brita; Loman, Niklas; Rosenquist, Richard; Olopade, Olufunmilayo I; Nussbaum, Robert L; Ramus, Susan J; Nathanson, Katherine L; Domchek, Susan M; Rebbeck, Timothy R; Arun, Banu K; Mitchell, Gillian; Karlan, Beth Y; Lester, Jenny; Orsulic, Sandra; Stoppa-Lyonnet, Dominique; Thomas, Gilles; Simard, Jacques; Couch, Fergus J; Offit, Kenneth; Easton, Douglas F; Chenevix-Trench, Georgia; Antoniou, Antonis C; Mazoyer, Sylvie; Phelan, Catherine M; Sinilnikova, Olga M; Cox, David G

2015-04-25

Individuals carrying pathogenic mutations in the BRCA1 and BRCA2 genes have a high lifetime risk of breast cancer. BRCA1 and BRCA2 are involved in DNA double-strand break repair, DNA alterations that can be caused by exposure to reactive oxygen species, a main source of which are mitochondria. Mitochondrial genome variations affect electron transport chain efficiency and reactive oxygen species production. Individuals with different mitochondrial haplogroups differ in their metabolism and sensitivity to oxidative stress. Variability in mitochondrial genetic background can alter reactive oxygen species production, leading to cancer risk. In the present study, we tested the hypothesis that mitochondrial haplogroups modify breast cancer risk in BRCA1/2 mutation carriers. We genotyped 22,214 (11,421 affected, 10,793 unaffected) mutation carriers belonging to the Consortium of Investigators of Modifiers of BRCA1/2 for 129 mitochondrial polymorphisms using the iCOGS array. Haplogroup inference and association detection were performed using a phylogenetic approach. ALTree was applied to explore the reference mitochondrial evolutionary tree and detect subclades enriched in affected or unaffected individuals. We discovered that subclade T1a1 was depleted in affected BRCA2 mutation carriers compared with the rest of clade T (hazard ratio (HR) = 0.55; 95% confidence interval (CI), 0.34 to 0.88; P = 0.01). Compared with the most frequent haplogroup in the general population (that is, H and T clades), the T1a1 haplogroup has a HR of 0.62 (95% CI, 0.40 to 0.95; P = 0.03). We also identified three potential susceptibility loci, including G13708A/rs28359178, which has demonstrated an inverse association with familial breast cancer risk. This study illustrates how original approaches such as the phylogeny-based method we used can empower classical molecular epidemiological studies aimed at identifying association or risk modification effects.

Biomedical Informatics Approaches to Identifying Drug-Drug Interactions: Application to Insulin Secretagogues

PubMed Central

Han, Xu; Chiang, ChienWei; Leonard, Charles E.; Bilker, Warren B.; Brensinger, Colleen M.; Li, Lang; Hennessy, Sean

2017-01-01

Background Drug-drug interactions with insulin secretagogues are associated with increased risk of serious hypoglycemia in patients with type 2 diabetes. We aimed to systematically screen for drugs that interact with the five most commonly used secretagogues―glipizide, glyburide, glimepiride, repaglinide, and nateglinide―to cause serious hypoglycemia. Methods We screened 400 drugs frequently co-prescribed with the secretagogues as candidate interacting precipitants. We first predicted the drug–drug interaction potential based on the pharmacokinetics of each secretagogue–precipitant pair. We then performed pharmacoepidemiologic screening for each secretagogue of interest, and for metformin as a negative control, using an administrative claims database and the self-controlled case series design. The overall rate ratios (RRs) and those for four predefined risk periods were estimated using Poisson regression. The RRs were adjusted for multiple estimation using semi-Bayes method, and then adjusted for metformin results to distinguish native effects of the precipitant from a drug–drug interaction. Results We predicted 34 pharmacokinetic drug–drug interactions with the secretagogues, nine moderate and 25 weak. There were 140 and 61 secretagogue–precipitant pairs associated with increased rates of serious hypoglycemia before and after the metformin adjustment, respectively. The results from pharmacokinetic prediction correlated poorly with those from pharmacoepidemiologic screening. Conclusions The self-controlled case series design has the potential to be widely applicable to screening for drug–drug interactions that lead to adverse outcomes identifiable in healthcare databases. Coupling pharmacokinetic prediction with pharmacoepidemiologic screening did not notably improve the ability to identify drug–drug interactions in this case. PMID:28169935

A reverse genetics approach identifies novel mutants in light responses and anthocyanin metabolism in petunia.

PubMed

Berenschot, Amanda S; Quecini, Vera

2014-01-01

Flower color and plant architecture are important commercially valuable features for ornamental petunias (Petunia x hybrida Vilm.). Photoperception and light signaling are the major environmental factors controlling anthocyanin and chlorophyll biosynthesis and shade-avoidance responses in higher plants. The genetic regulators of these processes were investigated in petunia by in silico analyses and the sequence information was used to devise a reverse genetics approach to probe mutant populations. Petunia orthologs of photoreceptor, light-signaling components and anthocyanin metabolism genes were identified and investigated for functional conservation by phylogenetic and protein motif analyses. The expression profiles of photoreceptor gene families and of transcription factors regulating anthocyanin biosynthesis were obtained by bioinformatic tools. Two mutant populations, generated by an alkalyting agent and by gamma irradiation, were screened using a phenotype-independent, sequence-based method by high-throughput PCR-based assay. The strategy allowed the identification of novel mutant alleles for anthocyanin biosynthesis (CHALCONE SYNTHASE) and regulation (PH4), and for light signaling (CONSTANS) genes.

Cocrystal dissociation in the presence of water: a general approach for identifying stable cocrystal forms.

PubMed

Eddleston, Mark D; Madusanka, Nadeesh; Jones, William

2014-09-01

In previous studies, cocrystals have been shown to be susceptible to dissociation at high humidity because of differences in the solubilities of the two coformer molecules, especially when these molecules can form hydrates. Contrastingly, however, the propensity of the pharmaceutically active compound caffeine to hydrate formation is reduced by cocrystallization with oxalic acid. Here, the stability of the oxalic acid cocrystal of caffeine is investigated from a thermodynamic perspective through the use of aqueous slurries of caffeine hydrate and oxalic acid dihydrate. Conversion to the anhydrous caffeine-oxalic acid cocrystal occurred under these conditions confirming that this form is thermodynamically stable in an aqueous environment. The slurry methodology was further developed as a general approach to screening for cocrystals that are not susceptible to dissociation at high humidity. In this manner, cocrystals of the hydrate-forming molecules theophylline, carbamazepine, and piroxicam that are stable at high humidity, indefinitely avoiding hydrate formation, were identified. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

A Systems Biology Framework Identifies Molecular Underpinnings of Coronary Heart Disease

PubMed Central

Huan, Tianxiao; Zhang, Bin; Wang, Zhi; Joehanes, Roby; Zhu, Jun; Johnson, Andrew D.; Ying, Saixia; Munson, Peter J.; Raghavachari, Nalini; Wang, Richard; Liu, Poching; Courchesne, Paul; Hwang, Shih-Jen; Assimes, Themistocles L.; McPherson, Ruth; Samani, Nilesh J.; Schunkert, Heribert; Meng, Qingying; Suver, Christine; O'Donnell, Christopher J.; Derry, Jonathan; Yang, Xia; Levy, Daniel

2013-01-01

Objective Genetic approaches have identified numerous loci associated with coronary heart disease (CHD). The molecular mechanisms underlying CHD gene-disease associations, however, remain unclear. We hypothesized that genetic variants with both strong and subtle effects drive gene subnetworks that in turn affect CHD. Approach and Results We surveyed CHD-associated molecular interactions by constructing coexpression networks using whole blood gene expression profiles from 188 CHD cases and 188 age- and sex-matched controls. 24 coexpression modules were identified including one case-specific and one control-specific differential module (DM). The DMs were enriched for genes involved in B-cell activation, immune response, and ion transport. By integrating the DMs with altered gene expression associated SNPs (eSNPs) and with results of GWAS of CHD and its risk factors, the control-specific DM was implicated as CHD-causal based on its significant enrichment for both CHD and lipid eSNPs. This causal DM was further integrated with tissue-specific Bayesian networks and protein-protein interaction networks to identify regulatory key driver (KD) genes. Multi-tissue KDs (SPIB and TNFRSF13C) and tissue-specific KDs (e.g. EBF1) were identified. Conclusions Our network-driven integrative analysis not only identified CHD-related genes, but also defined network structure that sheds light on the molecular interactions of genes associated with CHD risk. PMID:23539213

A NEW APPROACH TO IDENTIFYING THE MOST POWERFUL GRAVITATIONAL LENSING TELESCOPES

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

Wong, Kenneth C.; Zabludoff, Ann I.; Ammons, S. Mark

2013-05-20

The best gravitational lenses for detecting distant galaxies are those with the largest mass concentrations and the most advantageous configurations of that mass along the line of sight. Our new method for finding such gravitational telescopes uses optical data to identify projected concentrations of luminous red galaxies (LRGs). LRGs are biased tracers of the underlying mass distribution, so lines of sight with the highest total luminosity in LRGs are likely to contain the largest total mass. We apply this selection technique to the Sloan Digital Sky Survey and identify the 200 fields with the highest total LRG luminosities projected withinmore » a 3.'5 radius over the redshift range 0.1 {<=} z {<=} 0.7. The redshift and angular distributions of LRGs in these fields trace the concentrations of non-LRG galaxies. These fields are diverse; 22.5% contain one known galaxy cluster and 56.0% contain multiple known clusters previously identified in the literature. Thus, our results confirm that these LRGs trace massive structures and that our selection technique identifies fields with large total masses. These fields contain two to three times higher total LRG luminosities than most known strong-lensing clusters and will be among the best gravitational lensing fields for the purpose of detecting the highest redshift galaxies.« less

Using a multi-scale approach to identify and quantify oil and gas emissions: a case study for GHG emissions verification

NASA Astrophysics Data System (ADS)

Sweeney, C.; Kort, E. A.; Rella, C.; Conley, S. A.; Karion, A.; Lauvaux, T.; Frankenberg, C.

2015-12-01

Along with a boom in oil and natural gas production in the US, there has been a substantial effort to understand the true environmental impact of these operations on air and water quality, as well asnet radiation balance. This multi-institution effort funded by both governmental and non-governmental agencies has provided a case study for identification and verification of emissions using a multi-scale, top-down approach. This approach leverages a combination of remote sensing to identify areas that need specific focus and airborne in-situ measurements to quantify both regional and large- to mid-size single-point emitters. Ground-based networks of mobile and stationary measurements provide the bottom tier of measurements from which process-level information can be gathered to better understand the specific sources and temporal distribution of the emitters. The motivation for this type of approach is largely driven by recent work in the Barnett Shale region in Texas as well as the San Juan Basin in New Mexico and Colorado; these studies suggest that relatively few single-point emitters dominate the regional emissions of CH4.

A Model-Based Approach for Identifying Signatures of Ancient Balancing Selection in Genetic Data

PubMed Central

DeGiorgio, Michael; Lohmueller, Kirk E.; Nielsen, Rasmus

2014-01-01

While much effort has focused on detecting positive and negative directional selection in the human genome, relatively little work has been devoted to balancing selection. This lack of attention is likely due to the paucity of sophisticated methods for identifying sites under balancing selection. Here we develop two composite likelihood ratio tests for detecting balancing selection. Using simulations, we show that these methods outperform competing methods under a variety of assumptions and demographic models. We apply the new methods to whole-genome human data, and find a number of previously-identified loci with strong evidence of balancing selection, including several HLA genes. Additionally, we find evidence for many novel candidates, the strongest of which is FANK1, an imprinted gene that suppresses apoptosis, is expressed during meiosis in males, and displays marginal signs of segregation distortion. We hypothesize that balancing selection acts on this locus to stabilize the segregation distortion and negative fitness effects of the distorter allele. Thus, our methods are able to reproduce many previously-hypothesized signals of balancing selection, as well as discover novel interesting candidates. PMID:25144706

A model-based approach for identifying signatures of ancient balancing selection in genetic data.

PubMed

DeGiorgio, Michael; Lohmueller, Kirk E; Nielsen, Rasmus

2014-08-01

While much effort has focused on detecting positive and negative directional selection in the human genome, relatively little work has been devoted to balancing selection. This lack of attention is likely due to the paucity of sophisticated methods for identifying sites under balancing selection. Here we develop two composite likelihood ratio tests for detecting balancing selection. Using simulations, we show that these methods outperform competing methods under a variety of assumptions and demographic models. We apply the new methods to whole-genome human data, and find a number of previously-identified loci with strong evidence of balancing selection, including several HLA genes. Additionally, we find evidence for many novel candidates, the strongest of which is FANK1, an imprinted gene that suppresses apoptosis, is expressed during meiosis in males, and displays marginal signs of segregation distortion. We hypothesize that balancing selection acts on this locus to stabilize the segregation distortion and negative fitness effects of the distorter allele. Thus, our methods are able to reproduce many previously-hypothesized signals of balancing selection, as well as discover novel interesting candidates.

Meta-analysis identifies gene-by-environment interactions as demonstrated in a study of 4,965 mice.

PubMed

Kang, Eun Yong; Han, Buhm; Furlotte, Nicholas; Joo, Jong Wha J; Shih, Diana; Davis, Richard C; Lusis, Aldons J; Eskin, Eleazar

2014-01-01

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta

Meta-Analysis Identifies Gene-by-Environment Interactions as Demonstrated in a Study of 4,965 Mice

PubMed Central

Joo, Jong Wha J.; Shih, Diana; Davis, Richard C.; Lusis, Aldons J.; Eskin, Eleazar

2014-01-01

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta

Stress Management: A Rational Approach.

ERIC Educational Resources Information Center

Reeves, Cecil

This workbook was designed for use as the primary resource tool during a l-day participatory stress management seminar in which participants identify stressful situations, conduct analyses, and develop approaches to manage the stressful situations more effectively. Small group warm-up activities designed to introduce participants, encourage…

Discrepancy Approaches for Identifying Learning Disabilities. Quick Turn Around (QTA).

ERIC Educational Resources Information Center

Schrag, Judy A.

A study reviewed recent trends, issues, and changes within the states related to the use of discrepancy formulas and other approaches for determining eligibility of students with learning disabilities (LD) for special education and related services. A survey of the 50 states and the District of Columbia found they all have a statement in their…

A Combined Metabonomic and Proteomic Approach Identifies Frontal Cortex Changes in a Chronic Phencyclidine Rat Model in Relation to Human Schizophrenia Brain Pathology

PubMed Central

Wesseling, Hendrik; Chan, Man K; Tsang, T M; Ernst, Agnes; Peters, Fabian; Guest, Paul C; Holmes, Elaine; Bahn, Sabine

2013-01-01

Current schizophrenia (SCZ) treatments fail to treat the broad range of manifestations associated with this devastating disorder. Thus, new translational models that reproduce the core pathological features are urgently needed to facilitate novel drug discovery efforts. Here, we report findings from the first comprehensive label-free liquid-mass spectrometry proteomic- and proton nuclear magnetic resonance-based metabonomic profiling of the rat frontal cortex after chronic phencyclidine (PCP) intervention, which induces SCZ-like symptoms. The findings were compared with results from a proteomic profiling of post-mortem prefrontal cortex from SCZ patients and with relevant findings in the literature. Through this approach, we identified proteomic alterations in glutamate-mediated Ca2+ signaling (Ca2+/calmodulin-dependent protein kinase II, PPP3CA, and VISL1), mitochondrial function (GOT2 and PKLR), and cytoskeletal remodeling (ARP3). Metabonomic profiling revealed changes in the levels of glutamate, glutamine, glycine, pyruvate, and the Ca2+ regulator taurine. Effects on similar pathways were also identified in the prefrontal cortex tissue from human SCZ subjects. The discovery of similar but not identical proteomic and metabonomic alterations in the chronic PCP rat model and human brain indicates that this model recapitulates only some of the molecular alterations of the disease. This knowledge may be helpful in understanding mechanisms underlying psychosis, which, in turn, can facilitate improved therapy and drug discovery for SCZ and other psychiatric diseases. Most importantly, these molecular findings suggest that the combined use of multiple models may be required for more effective translation to studies of human SCZ. PMID:23942359

NetCoffee: a fast and accurate global alignment approach to identify functionally conserved proteins in multiple networks.