The impact of organisational factors on horizontal bullying and turnover intentions in the nursing workplace.

PubMed

Blackstock, Sheila; Harlos, Karen; Macleod, Martha L P; Hardy, Cindy L

2015-11-01

To examine the impact of organisational factors on bullying among peers (i.e. horizontal) and its effect on turnover intentions among Canadian registered nurses (RNs). Bullying among nurses is an international problem. Few studies have examined factors specific to nursing work environments that may increase exposure to bullying. An Australian model of nurse bullying was tested among Canadian registered nurse coworkers using a web-based survey (n = 103). Three factors - misuse of organisational processes/procedures, organisational tolerance and reward of bullying, and informal organisational alliances - were examined as predictors of horizontal bullying, which in turn was examined as a predictor of turnover intentions. The construct validity of model measures was explored. Informal organisational alliances and misuse of organisational processes/procedures predicted increased horizontal bullying that, in turn, predicted increased turnover intentions. Construct validity of model measures was supported. Negative informal alliances and misuse of organisational processes are antecedents to bullying, which adversely affects employment relationship stability. The results suggest that reforming flawed organisational processes that contribute to registered nurses' bullying experiences may help to reduce chronically high turnover. Nurse leaders and managers need to create workplace processes that foster positive networks, fairness and respect through more transparent and accountable practices. © 2014 John Wiley & Sons Ltd.

Right Fronto-Subcortical White Matter Microstructure Predicts Cognitive Control Ability on the Go/No-go Task in a Community Sample.

PubMed

Hinton, Kendra E; Lahey, Benjamin B; Villalta-Gil, Victoria; Boyd, Brian D; Yvernault, Benjamin C; Werts, Katherine B; Plassard, Andrew J; Applegate, Brooks; Woodward, Neil D; Landman, Bennett A; Zald, David H

2018-01-01

Go/no-go tasks are widely used to index cognitive control. This construct has been linked to white matter microstructure in a circuit connecting the right inferior frontal gyrus (IFG), subthalamic nucleus (STN), and pre-supplementary motor area. However, the specificity of this association has not been tested. A general factor of white matter has been identified that is related to processing speed. Given the strong processing speed component in successful performance on the go/no-go task, this general factor could contribute to task performance, but the general factor has often not been accounted for in past studies of cognitive control. Further, studies on cognitive control have generally employed small unrepresentative case-control designs. The present study examined the relationship between go/no-go performance and white matter microstructure in a large community sample of 378 subjects that included participants with a range of both clinical and subclinical nonpsychotic psychopathology. We found that white matter microstructure properties in the right IFG-STN tract significantly predicted task performance, and remained significant after controlling for dimensional psychopathology. The general factor of white matter only reached statistical significance when controlling for dimensional psychopathology. Although the IFG-STN and general factor tracts were highly correlated, when both were included in the model, only the IFG-STN remained a significant predictor of performance. Overall, these findings suggest that while a general factor of white matter can be identified in a young community sample, white matter microstructure properties in the right IFG-STN tract show a specific relationship to cognitive control. The findings highlight the importance of examining both specific and general correlates of cognition, especially in tasks with a speeded component.

The role of personality in predicting drug and alcohol use among sexual minorities.

PubMed

Livingston, Nicholas A; Oost, Kathryn M; Heck, Nicholas C; Cochran, Bryan N

2015-06-01

Research consistently demonstrates that sexual minority status is associated with increased risk of problematic substance use. Existing literature in this area has focused on group-specific minority stress factors (e.g., victimization and internalized heterosexism). However, no known research has tested the incremental validity of personality traits as predictors of substance use beyond identified group-specific risk factors. A sample of 704 sexual minority adults was recruited nationally from lesbian, gay, bisexual, transgender, queer, and questioning community organizations and social networking Web sites and asked to complete an online survey containing measures of personality, sexual minority stress, and substance use. Hierarchical regression models were constructed to test the incremental predictive validity of five-factor model personality traits over and above known sexual minority risk factors. Consistent with hypotheses, extraversion and conscientiousness were associated with drug and alcohol use after accounting for minority stress factors, and all factors except agreeableness were associated with substance use at the bivariate level of analysis. Future research should seek to better understand the role of normal personality structures and processes conferring risk for substance use among sexual minorities. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Computer-Related Success and Failure: A Longitudinal Field Study of the Factors Influencing Computer-Related Performance.

ERIC Educational Resources Information Center

Rozell, E. J.; Gardner, W. L., III

1999-01-01

A model of the intrapersonal processes impacting computer-related performance was tested using data from 75 manufacturing employees in a computer training course. Gender, computer experience, and attributional style were predictive of computer attitudes, which were in turn related to computer efficacy, task-specific performance expectations, and…

Multiple brain networks for visual self-recognition with different sensitivity for motion and body part.

PubMed

Sugiura, Motoaki; Sassa, Yuko; Jeong, Hyeonjeong; Miura, Naoki; Akitsuki, Yuko; Horie, Kaoru; Sato, Shigeru; Kawashima, Ryuta

2006-10-01

Multiple brain networks may support visual self-recognition. It has been hypothesized that the left ventral occipito-temporal cortex processes one's own face as a symbol, and the right parieto-frontal network processes self-image in association with motion-action contingency. Using functional magnetic resonance imaging, we first tested these hypotheses based on the prediction that these networks preferentially respond to a static self-face and to moving one's whole body, respectively. Brain activation specifically related to self-image during familiarity judgment was compared across four stimulus conditions comprising a two factorial design: factor Motion contrasted picture (Picture) and movie (Movie), and factor Body part a face (Face) and whole body (Body). Second, we attempted to segregate self-specific networks using a principal component analysis (PCA), assuming an independent pattern of inter-subject variability in activation over the four stimulus conditions in each network. The bilateral ventral occipito-temporal and the right parietal and frontal cortices exhibited self-specific activation. The left ventral occipito-temporal cortex exhibited greater self-specific activation for Face than for Body, in Picture, consistent with the prediction for this region. The activation profiles of the right parietal and frontal cortices did not show preference for Movie Body predicted by the assumed roles of these regions. The PCA extracted two cortical networks, one with its peaks in the right posterior, and another in frontal cortices; their possible roles in visuo-spatial and conceptual self-representations, respectively, were suggested by previous findings. The results thus supported and provided evidence of multiple brain networks for visual self-recognition.

Universal gestational age effects on cognitive and basic mathematic processing: 2 cohorts in 2 countries.

PubMed

Wolke, Dieter; Strauss, Vicky Yu-Chun; Johnson, Samantha; Gilmore, Camilla; Marlow, Neil; Jaekel, Julia

2015-06-01

To determine whether general cognitive ability, basic mathematic processing, and mathematic attainment are universally affected by gestation at birth, as well as whether mathematic attainment is more strongly associated with cohort-specific factors such as schooling than basic cognitive and mathematical abilities. The Bavarian Longitudinal Study (BLS, 1289 children, 27-41 weeks gestational age [GA]) was used to estimate effects of GA on IQ, basic mathematic processing, and mathematic attainment. These estimations were used to predict IQ, mathematic processing, and mathematic attainment in the EPICure Study (171 children <26 weeks GA). For children born <34 weeks GA, each lower week decreased IQ and mathematic attainment scores by 2.34 (95% CI: -2.99, -1.70) and 2.76 (95% CI: -3.40, -2.11) points, respectively. There were no differences among children born 34-41 weeks GA. Similarly, for children born <36 weeks GA, mathematic processing scores decreased by 1.77 (95% CI: -2.20, -1.34) points with each lower GA week. The prediction function generated using BLS data accurately predicted the effect of GA on IQ and mathematic processing among EPICure children. However, these children had better attainment than predicted by BLS. Prematurity has adverse effects on basic mathematic processing following birth at all gestations <36 weeks and on IQ and mathematic attainment <34 weeks GA. The ability to predict IQ and mathematic processing scores from one cohort to another among children cared for in different eras and countries suggests that universal neurodevelopmental factors may explain the effects of gestation at birth. In contrast, mathematic attainment may be improved by schooling. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Universal Gestational Age Effects on Cognitive and Basic Mathematic Processing: 2 Cohorts in 2 Countries

PubMed Central

Wolke, Dieter; Strauss, Vicky Yu-Chun; Johnson, Samantha; Gilmore, Camilla; Marlow, Neil; Jaekel, Julia

2015-01-01

Objective To determine whether general cognitive ability, basic mathematic processing, and mathematic attainment are universally affected by gestation at birth, as well as whether mathematic attainment is more strongly associated with cohort-specific factors such as schooling than basic cognitive and mathematical abilities. Study design The Bavarian Longitudinal Study (BLS, 1289 children, 27-41 weeks gestational age [GA]) was used to estimate effects of GA on IQ, basic mathematic processing, and mathematic attainment. These estimations were used to predict IQ, mathematic processing, and mathematic attainment in the EPICure Study (171 children <26 weeks GA). Results For children born <34 weeks GA, each lower week decreased IQ and mathematic attainment scores by 2.34 (95% CI: −2.99, −1.70) and 2.76 (95% CI: −3.40, −2.11) points, respectively. There were no differences among children born 34-41 weeks GA. Similarly, for children born <36 weeks GA, mathematic processing scores decreased by 1.77 (95% CI: −2.20, −1.34) points with each lower GA week. The prediction function generated using BLS data accurately predicted the effect of GA on IQ and mathematic processing among EPICure children. However, these children had better attainment than predicted by BLS. Conclusions Prematurity has adverse effects on basic mathematic processing following birth at all gestations <36 weeks and on IQ and mathematic attainment <34 weeks GA. The ability to predict IQ and mathematic processing scores from one cohort to another among children cared for in different eras and countries suggests that universal neurodevelopmental factors may explain the effects of gestation at birth. In contrast, mathematic attainment may be improved by schooling. PMID:25842966

The generality of working memory capacity: a latent-variable approach to verbal and visuospatial memory span and reasoning.

PubMed

Kane, Michael J; Hambrick, David Z; Tuholski, Stephen W; Wilhelm, Oliver; Payne, Tabitha W; Engle, Randall W

2004-06-01

A latent-variable study examined whether verbal and visuospatial working memory (WM) capacity measures reflect a primarily domain-general construct by testing 236 participants in 3 span tests each of verbal WM. visuospatial WM, verbal short-term memory (STM), and visuospatial STM. as well as in tests of verbal and spatial reasoning and general fluid intelligence (Gf). Confirmatory' factor analyses and structural equation models indicated that the WM tasks largely reflected a domain-general factor, whereas STM tasks, based on the same stimuli as the WM tasks, were much more domain specific. The WM construct was a strong predictor of Gf and a weaker predictor of domain-specific reasoning, and the reverse was true for the STM construct. The findings support a domain-general view of WM capacity, in which executive-attention processes drive the broad predictive utility of WM span measures, and domain-specific storage and rehearsal processes relate more strongly to domain-specific aspects of complex cognition. ((c) 2004 APA, all rights reserved)

The Complexity of Vesicle Transport Factors in Plants Examined by Orthology Search

PubMed Central

Mirus, Oliver; Scharf, Klaus-Dieter; Fragkostefanakis, Sotirios; Schleiff, Enrico

2014-01-01

Vesicle transport is a central process to ensure protein and lipid distribution in eukaryotic cells. The current knowledge on the molecular components and mechanisms of this process is majorly based on studies in Saccharomyces cerevisiae and Arabidopsis thaliana, which revealed 240 different proteinaceous factors either experimentally proven or predicted to be involved in vesicle transport. In here, we performed an orthologue search using two different algorithms to identify the components of the secretory pathway in yeast and 14 plant genomes by using the ‘core-set’ of 240 factors as bait. We identified 4021 orthologues and (co-)orthologues in the discussed plant species accounting for components of COP-II, COP-I, Clathrin Coated Vesicles, Retromers and ESCRTs, Rab GTPases, Tethering factors and SNAREs. In plants, we observed a significantly higher number of (co-)orthologues than yeast, while only 8 tethering factors from yeast seem to be absent in the analyzed plant genomes. To link the identified (co-)orthologues to vesicle transport, the domain architecture of the proteins from yeast, genetic model plant A. thaliana and agriculturally relevant crop Solanum lycopersicum has been inspected. For the orthologous groups containing (co-)orthologues from yeast, A. thaliana and S. lycopersicum, we observed the same domain architecture for 79% (416/527) of the (co-)orthologues, which documents a very high conservation of this process. Further, publically available tissue-specific expression profiles for a subset of (co-)orthologues found in A. thaliana and S. lycopersicum suggest that some (co-)orthologues are involved in tissue-specific functions. Inspection of localization of the (co-)orthologues based on available proteome data or localization predictions lead to the assignment of plastid- as well as mitochondrial localized (co-)orthologues of vesicle transport factors and the relevance of this is discussed. PMID:24844592

Prognostics

NASA Technical Reports Server (NTRS)

Goebel, Kai; Vachtsevanos, George; Orchard, Marcos E.

2013-01-01

Knowledge discovery, statistical learning, and more specifically an understanding of the system evolution in time when it undergoes undesirable fault conditions, are critical for an adequate implementation of successful prognostic systems. Prognosis may be understood as the generation of long-term predictions describing the evolution in time of a particular signal of interest or fault indicator, with the purpose of estimating the remaining useful life (RUL) of a failing component/subsystem. Predictions are made using a thorough understanding of the underlying processes and factor in the anticipated future usage.

Crew Interface Analysis: Selected Articles on Space Human Factors Research, 1987 - 1991

DTIC Science & Technology

1993-07-01

recognitions to that distractor ) suggest that the perceptual type of the graph has a strong representation in memory . We found that both training with... processing strategy. If my goal were to compare the value of variables or (possibly) to compare a trend, I would select a perceptual strategy. If...be needed to determine specific processing models for different questions using the perceptual strategy. In addition, predictions about the memory

A protective factors model for alcohol abuse and suicide prevention among Alaska Native youth.

PubMed

Allen, James; Mohatt, Gerald V; Fok, Carlotta Ching Ting; Henry, David; Burkett, Rebekah

2014-09-01

This study provides an empirical test of a culturally grounded theoretical model for prevention of alcohol abuse and suicide risk with Alaska Native youth, using a promising set of culturally appropriate measures for the study of the process of change and outcome. This model is derived from qualitative work that generated an heuristic model of protective factors from alcohol (Allen et al. in J Prev Interv Commun 32:41-59, 2006; Mohatt et al. in Am J Commun Psychol 33:263-273, 2004a; Harm Reduct 1, 2004b). Participants included 413 rural Alaska Native youth ages 12-18 who assisted in testing a predictive model of Reasons for Life and Reflective Processes about alcohol abuse consequences as co-occurring outcomes. Specific individual, family, peer, and community level protective factor variables predicted these outcomes. Results suggest prominent roles for these predictor variables as intermediate prevention strategy target variables in a theoretical model for a multilevel intervention. The model guides understanding of underlying change processes in an intervention to increase the ultimate outcome variables of Reasons for Life and Reflective Processes regarding the consequences of alcohol abuse.

Optimum surface roughness prediction for titanium alloy by adopting response surface methodology

NASA Astrophysics Data System (ADS)

Yang, Aimin; Han, Yang; Pan, Yuhang; Xing, Hongwei; Li, Jinze

Titanium alloy has been widely applied in industrial engineering products due to its advantages of great corrosion resistance and high specific strength. This paper investigated the processing parameters for finish turning of titanium alloy TC11. Firstly, a three-factor central composite design of experiment, considering the cutting speed, feed rate and depth of cut, are conducted in titanium alloy TC11 and the corresponding surface roughness are obtained. Then a mathematic model is constructed by the response surface methodology to fit the relationship between the process parameters and the surface roughness. The prediction accuracy was verified by the one-way ANOVA. Finally, the contour line of the surface roughness under different combination of process parameters are obtained and used for the optimum surface roughness prediction. Verification experimental results demonstrated that material removal rate (MRR) at the obtained optimum can be significantly improved without sacrificing the surface roughness.

Linguistic and Cognitive Profiles of 8- to 15-Year-Old Children With Specific Reading Comprehension Difficulties.

PubMed

Potocki, Anna; Sanchez, Monique; Ecalle, Jean; Magnan, Annie

This article presents two studies investigating the role of executive functioning in written text comprehension in children and adolescents. In a first study, the involvement of executive functions in reading comprehension performance was examined in normally developing children in fifth grade. Two aspects of text comprehension were differentiated: literal and inferential processes. The results demonstrated that while three aspects of executive functioning (working memory, planning, and inhibition processes) were significantly predictive of the performance on the inferential questions of the comprehension test, these factors did not predict the scores on the literal tasks of the test. In a second experiment, the linguistic and cognitive profiles of children in third/fifth and seventh/ninth grades with a specific reading comprehension deficit were examined. This analysis revealed that the deficits experienced by the less skilled comprehenders in both the linguistic and the executive domains could evolve over time. As a result, linguistic factors do not make it possible to distinguish between good and poor comprehenders among the group of older children, whereas the difficulties relating to executive processing remain stable over development. These findings are discussed in the context of the need to take account of the executive difficulties that characterize less skilled comprehenders of any age, especially for remediation purposes.

Use of refinery computer model to predict fuel production

NASA Technical Reports Server (NTRS)

Flores, F. J.

1979-01-01

Several factors (crudes, refinery operation and specifications) that affect yields and properties of broad specification jet fuel were parameterized using the refinery simulation model which can simulate different types of refineries were used to make the calculations. Results obtained from the program are used to correlate yield as a function of final boiling point, hydrogen content and freezing point for jet fuels produced in two refinery configurations, each one processing a different crude mix. Refinery performances are also compared in terms of energy consumption.

Transcription Factors Expressed in Lateral Organ Boundaries: Identification of Downstream Targets

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

Springer, Patricia S

2010-07-12

The processes of lateral organ initiation and patterning are central to the generation of mature plant form. Characterization of the molecular mechanisms underlying these processes is essential to our understanding of plant development. Communication between the shoot apical meristem and initiating organ primordia is important both for functioning of the meristem and for proper organ patterning, and very little is known about this process. In particular, the boundary between meristem and leaf is emerging as a critical region that is important for SAM maintenance and regulation of organogenesis. The goal of this project was to characterize three boundary-expressed genes thatmore » encode predicted transcription factors. Specifically, we have studied LATERAL ORGAN BOUNDARIES (LOB), LATERAL ORGAN FUSION1 (LOF1), and LATERAL ORGAN FUSION2 (LOF2). LOB encodes the founding member of the LOB-DOMAIN (LBD) plant-specific DNA binding transcription factor family and LOF1 and LOF2 encode paralogous MYB-domain transcription factors. We characterized the genetic relationship between these three genes and other boundary and meristem genes. We also used an ectopic inducible expression system to identify direct targets of LOB.« less

One wouldn't expect an expert bowler to hit only two pins: Hierarchical predictive processing of agent-caused events.

PubMed

Heil, Lieke; Kwisthout, Johan; van Pelt, Stan; van Rooij, Iris; Bekkering, Harold

2018-01-01

Evidence is accumulating that our brains process incoming information using top-down predictions. If lower level representations are correctly predicted by higher level representations, this enhances processing. However, if they are incorrectly predicted, additional processing is required at higher levels to "explain away" prediction errors. Here, we explored the potential nature of the models generating such predictions. More specifically, we investigated whether a predictive processing model with a hierarchical structure and causal relations between its levels is able to account for the processing of agent-caused events. In Experiment 1, participants watched animated movies of "experienced" and "novice" bowlers. The results are in line with the idea that prediction errors at a lower level of the hierarchy (i.e., the outcome of how many pins fell down) slow down reporting of information at a higher level (i.e., which agent was throwing the ball). Experiments 2 and 3 suggest that this effect is specific to situations in which the predictor is causally related to the outcome. Overall, the study supports the idea that a hierarchical predictive processing model can account for the processing of observed action outcomes and that the predictions involved are specific to cases where action outcomes can be predicted based on causal knowledge.

Personality and Defense Styles: Clinical Specificities and Predictive Factors of Alcohol Use Disorder in Women.

PubMed

Ribadier, Aurélien; Dorard, Géraldine; Varescon, Isabelle

2016-01-01

This study investigated personality traits and defense styles in order to determine clinical specificities and predictive factors of alcohol use disorders (AUDs) in women. A female sample, composed of AUD outpatients (n = 48) and a control group (n = 50), completed a sociodemographic self-report and questionnaires assessing personality traits (BFI), defense mechanisms and defense styles (DSQ-40). Comparative and correlational analyses, as well as univariate and multivariate logistic regressions, were performed. AUD women presented with higher neuroticism and lower extraversion and conscientiousness. They used less mature and more neurotic and immature defense styles than the control group. Concerning personality traits, high neuroticism and lower conscientiousness were predictive of AUD, as well as low mature, high neurotic, and immature defense styles. Including personality traits and defense styles in a logistic model, high neuroticism was the only AUD predictive factor. AUD women presented clinical specificities and predictive factors in personality traits and defense styles that must be taken into account in AUD studies. Implications for specific treatment for women are discussed.

Construct and Predictive Validity of the Core Phonics Survey: A Diagnostic Assessment for Students with Specific Learning Disabilities

ERIC Educational Resources Information Center

Park, Yujeong; Benedict, Amber E.; Brownell, Mary T.

2014-01-01

The factor structure of the CORE Phonics Survey was analyzed using a sample of 165 students in upper elementary school with specific learning disabilities. Confirmatory factor analysis was used to identify the hypothesized constructs of the CORE Phonics Survey and predictive validity of the CORE Phonics Survey to predict students' success in word…

Perinatal Factors, Parenting Behavior, and Reactive Aggression: Does Cortisol Reactivity Mediate This Developmental Risk Process?

ERIC Educational Resources Information Center

Ryan, Stacy R.; Schechter, Julia C.; Brennan, Patricia A.

2012-01-01

Little is known about the mechanisms of action that link perinatal risk and the development of aggressive behavior. The aim of this study was to examine whether perinatal risk and parenting interacted to specifically predict reactive aggression, as opposed to general aggressive behavior, and to examine cortisol reactivity as a mediator of this…

Driving factors for torrential mass-movements occurrence in the Western Alps

NASA Astrophysics Data System (ADS)

Tiranti, Davide; Cremonini, Roberto; Asprea, Irene; Marco, Federica

2016-02-01

To understand the behaviour of torrential processes in the alpine environment, the conditions mainly responsiblefor the occurrence of these phenomena have to be identified and distinguished(classified) aspredisposing and triggering factors. In this regard, this study is aimed to understanding which factors lead to the occurrence of a given torrential processes in alpine catchments in the Western Alps, where information on past events are exhaustive and characterized by a long historical series. More than 769 documented torrential eventsoccurred from 1728 to 2015 within 78 catchments. Datasets concerning climate, geology and morphology, land use and the presence of historical landslide activity have been elaborated as input for multivariate statistical analysis to characterize the behaviour of the catchments. The results pinpoint the factors that mainly drive the type of torrential dominant process occurring in a given catchment, its occurrence probability, and its frequency. This study has demonstrated that catchments characterized by a significant percentage of outcropping rocks show a greater occurrence of torrential processes, especially hyperconcentrated flows and debris flows; on the contrary highly vegetated catchments are typically subject to water flows. This result can be a useful tool for the evaluation of hazards related to this specific phenomenon, making it possible to predict the most likely torrential processes that can be generated in a specific basin, given the characteristics of outcropping rock and vegetation cover.

Self-perceived Coparenting of Nonresident Fathers: Scale Development and Validation.

PubMed

Dyer, W Justin; Fagan, Jay; Kaufman, Rebecca; Pearson, Jessica; Cabrera, Natasha

2017-11-16

This study reports on the development and validation of the Fatherhood Research and Practice Network coparenting perceptions scale for nonresident fathers. Although other measures of coparenting have been developed, this is the first measure developed specifically for low-income, nonresident fathers. Focus groups were conducted to determine various aspects of coparenting. Based on this, a scale was created and administered to 542 nonresident fathers. Participants also responded to items used to examine convergent and predictive validity (i.e., parental responsibility, contact with the mother, father self-efficacy and satisfaction, child behavior problems, and contact and engagement with the child). Factor analyses and reliability tests revealed three distinct and reliable perceived coparenting factors: undermining, alliance, and gatekeeping. Validity tests suggest substantial overlap between the undermining and alliance factors, though undermining was uniquely related to child behavior problems. The alliance and gatekeeping factors showed strong convergent validity and evidence for predictive validity. Taken together, results suggest this relatively short measure (11 items) taps into three coparenting dimensions significantly predictive of aspects of individual and family life. © 2017 Family Process Institute.

In vivo serial MRI-based models and statistical methods to quantify sensitivity and specificity of mechanical predictors for carotid plaque rupture: location and beyond.

PubMed

Wu, Zheyang; Yang, Chun; Tang, Dalin

2011-06-01

It has been hypothesized that mechanical risk factors may be used to predict future atherosclerotic plaque rupture. Truly predictive methods for plaque rupture and methods to identify the best predictor(s) from all the candidates are lacking in the literature. A novel combination of computational and statistical models based on serial magnetic resonance imaging (MRI) was introduced to quantify sensitivity and specificity of mechanical predictors to identify the best candidate for plaque rupture site prediction. Serial in vivo MRI data of carotid plaque from one patient was acquired with follow-up scan showing ulceration. 3D computational fluid-structure interaction (FSI) models using both baseline and follow-up data were constructed and plaque wall stress (PWS) and strain (PWSn) and flow maximum shear stress (FSS) were extracted from all 600 matched nodal points (100 points per matched slice, baseline matching follow-up) on the lumen surface for analysis. Each of the 600 points was marked "ulcer" or "nonulcer" using follow-up scan. Predictive statistical models for each of the seven combinations of PWS, PWSn, and FSS were trained using the follow-up data and applied to the baseline data to assess their sensitivity and specificity using the 600 data points for ulcer predictions. Sensitivity of prediction is defined as the proportion of the true positive outcomes that are predicted to be positive. Specificity of prediction is defined as the proportion of the true negative outcomes that are correctly predicted to be negative. Using probability 0.3 as a threshold to infer ulcer occurrence at the prediction stage, the combination of PWS and PWSn provided the best predictive accuracy with (sensitivity, specificity) = (0.97, 0.958). Sensitivity and specificity given by PWS, PWSn, and FSS individually were (0.788, 0.968), (0.515, 0.968), and (0.758, 0.928), respectively. The proposed computational-statistical process provides a novel method and a framework to assess the sensitivity and specificity of various risk indicators and offers the potential to identify the optimized predictor for plaque rupture using serial MRI with follow-up scan showing ulceration as the gold standard for method validation. While serial MRI data with actual rupture are hard to acquire, this single-case study suggests that combination of multiple predictors may provide potential improvement to existing plaque assessment schemes. With large-scale patient studies, this predictive modeling process may provide more solid ground for rupture predictor selection strategies and methods for image-based plaque vulnerability assessment.

Impulsivity, Impulsive and Reflective Processes and the Development of Alcohol Use and Misuse in Adolescents and Young Adults

PubMed Central

Wiers, Reinout W.; Ames, Susan L.; Hofmann, Wilhelm; Krank, Marvin; Stacy, Alan W.

2010-01-01

This paper contrasts dual-process and personality approaches in the prediction of addictive behaviors and related risk behaviors. In dual-process models, behavior is described as the joint outcome of qualitatively different “impulsive” (or associative) and “reflective” processes. There are important individual differences regarding both types of processes, and the relative strength of both in a specific situation is influenced by prior behavior and state variables (e.g., fatigue, alcohol use). From this perspective, a specific behavior (e.g., alcohol misuse) can be predicted by the combined indices of the behavior-related impulsive processes (e.g., associations with alcohol), and reflective processes, including the ability to refrain from a motivationally salient action. Personality approaches have reported that general traits such as impulsivity predict addictive behaviors. Here we contrast these two approaches, with supplementary analyses on four datasets. We hypothesized that trait impulsivity can predict specific risky behaviors, but that its predictive power disappears once specific behavior-related associations, indicators of executive functioning, and their interaction are entered into the equation. In all four studies the observed interaction between specific associations and executive control (EC) was robust: trait impulsivity did not diminish the prediction of alcohol use by the interaction. Trait impulsivity was not always related to alcohol use, and when it was, the predictive power disappeared after entering the interaction between behavior-specific associations and EC in one study, but not in the other. These findings are interpreted in relation to the validity of the measurements used, which leads to a more refined hypothesis. PMID:21833213

Prediction of endoplasmic reticulum resident proteins using fragmented amino acid composition and support vector machine.

PubMed

Kumar, Ravindra; Kumari, Bandana; Kumar, Manish

2017-01-01

The endoplasmic reticulum plays an important role in many cellular processes, which includes protein synthesis, folding and post-translational processing of newly synthesized proteins. It is also the site for quality control of misfolded proteins and entry point of extracellular proteins to the secretory pathway. Hence at any given point of time, endoplasmic reticulum contains two different cohorts of proteins, (i) proteins involved in endoplasmic reticulum-specific function, which reside in the lumen of the endoplasmic reticulum, called as endoplasmic reticulum resident proteins and (ii) proteins which are in process of moving to the extracellular space. Thus, endoplasmic reticulum resident proteins must somehow be distinguished from newly synthesized secretory proteins, which pass through the endoplasmic reticulum on their way out of the cell. Approximately only 50% of the proteins used in this study as training data had endoplasmic reticulum retention signal, which shows that these signals are not essentially present in all endoplasmic reticulum resident proteins. This also strongly indicates the role of additional factors in retention of endoplasmic reticulum-specific proteins inside the endoplasmic reticulum. This is a support vector machine based method, where we had used different forms of protein features as inputs for support vector machine to develop the prediction models. During training leave-one-out approach of cross-validation was used. Maximum performance was obtained with a combination of amino acid compositions of different part of proteins. In this study, we have reported a novel support vector machine based method for predicting endoplasmic reticulum resident proteins, named as ERPred. During training we achieved a maximum accuracy of 81.42% with leave-one-out approach of cross-validation. When evaluated on independent dataset, ERPred did prediction with sensitivity of 72.31% and specificity of 83.69%. We have also annotated six different proteomes to predict the candidate endoplasmic reticulum resident proteins in them. A webserver, ERPred, was developed to make the method available to the scientific community, which can be accessed at http://proteininformatics.org/mkumar/erpred/index.html. We found that out of 124 proteins of the training dataset, only 66 proteins had endoplasmic reticulum retention signals, which shows that these signals are not an absolute necessity for endoplasmic reticulum resident proteins to remain inside the endoplasmic reticulum. This observation also strongly indicates the role of additional factors in retention of proteins inside the endoplasmic reticulum. Our proposed predictor, ERPred, is a signal independent tool. It is tuned for the prediction of endoplasmic reticulum resident proteins, even if the query protein does not contain specific ER-retention signal.

The relative importance of regional, local, and evolutionary factors structuring cryptobenthic coral-reef assemblages

NASA Astrophysics Data System (ADS)

Ahmadia, Gabby N.; Tornabene, Luke; Smith, David J.; Pezold, Frank L.

2018-03-01

Factors shaping coral-reef fish species assemblages can operate over a wide range of spatial scales (local versus regional) and across both proximate and evolutionary time. Niche theory and neutral theory provide frameworks for testing assumptions and generating insights about the importance of local versus regional processes. Niche theory postulates that species assemblages are an outcome of evolutionary processes at regional scales followed by local-scale interactions, whereas neutral theory presumes that species assemblages are formed by largely random processes drawing from regional species pools. Indo-Pacific cryptobenthic coral-reef fishes are highly evolved, ecologically diverse, temporally responsive, and situated on a natural longitudinal diversity gradient, making them an ideal group for testing predictions from niche and neutral theories and effects of regional and local processes on species assemblages. Using a combination of ecological metrics (fish density, diversity, assemblage composition) and evolutionary analyses (testing for phylogenetic niche conservatism), we demonstrate that the structure of cryptobenthic fish assemblages can be explained by a mixture of regional factors, such as the size of regional species pools and broad-scale barriers to gene flow/drivers of speciation, coupled with local-scale factors, such as the relative abundance of specific microhabitat types. Furthermore, species of cryptobenthic fishes have distinct microhabitat associations that drive significant differences in assemblage community structure between microhabitat types, and these distinct microhabitat associations are phylogenetically conserved over evolutionary timescales. The implied differential fitness of cryptobenthic fishes across varied microhabitats and the conserved nature of their ecology are consistent with predictions from niche theory. Neutral theory predictions may still hold true for early life-history stages, where stochastic factors may be more important in explaining recruitment. Overall, through integration of ecological and evolutionary techniques, and using multiple spatial scales, our study offers a unique perspective on factors determining coral-reef fish assemblages.

Attention toward contexts modulates context-specificity of behavior in human predictive learning: Evidence from the n-back task.

PubMed

Uengoer, Metin; Lucke, Sara; Lachnit, Harald

2018-02-20

According to the attentional theory of context processing (ATCP), learning becomes context specific when acquired under conditions that promote attention toward contextual stimuli regardless of whether attention deployment is guided by learning experience or by other factors unrelated to learning. In one experiment with humans, we investigated whether performance in a predictive learning task can be brought under contextual control by means of a secondary task that was unrelated to predictive learning, but supposed to modulate participants' attention toward contexts. Initially, participants acquired cue-outcome relationships presented in contexts that were each composed of two elements from two dimensions. Acquisition training in the predictive learning task was combined with a one-back task that required participants to match across consecutive trials context elements belonging to one of the two dimensions. During a subsequent test, we observed that acquisition behavior in the predictive learning task was disrupted by changing the acquisition context along the dimension that was relevant for the one-back task, while there was no evidence for context specificity of predictive learning when the acquisition context was changed along the dimension that was irrelevant for the one-back task. Our results support the generality of the principles advocated by ATCP.

Temperamental factors in remitted depression: The role of effortful control and attentional mechanisms.

PubMed

Marchetti, Igor; Shumake, Jason; Grahek, Ivan; Koster, Ernst H W

2018-08-01

Temperamental effortful control and attentional networks are increasingly viewed as important underlying processes in depression and anxiety. However, it is still unknown whether these factors facilitate depressive and anxiety symptoms in the general population and, more specifically, in remitted depressed individuals. We investigated to what extent effortful control and attentional networks (i.e., Attention Network Task) explain concurrent depressive and anxious symptoms in healthy individuals (n = 270) and remitted depressed individuals (n = 90). Both samples were highly representative of the US population. Increased effortful control predicted a substantial decrease in symptoms of both depression and anxiety in the whole sample, whereas decreased efficiency of executive attention predicted a modest increase in depressive symptoms. Remitted depressed individuals did not show less effortful control nor less efficient attentional networks than healthy individuals. Moreover, clinical status did not moderate the relationship between temperamental factors and either depressive or anxiety symptoms. Limitations include the cross-sectional nature of the study. Our study shows that temperamental effortful control represents an important transdiagnostic process for depressive and anxiety symptoms in adults. Copyright © 2018 Elsevier B.V. All rights reserved.

A dynamic spatio-temporal model for spatial data

USGS Publications Warehouse

Hefley, Trevor J.; Hooten, Mevin B.; Hanks, Ephraim M.; Russell, Robin; Walsh, Daniel P.

2017-01-01

Analyzing spatial data often requires modeling dependencies created by a dynamic spatio-temporal data generating process. In many applications, a generalized linear mixed model (GLMM) is used with a random effect to account for spatial dependence and to provide optimal spatial predictions. Location-specific covariates are often included as fixed effects in a GLMM and may be collinear with the spatial random effect, which can negatively affect inference. We propose a dynamic approach to account for spatial dependence that incorporates scientific knowledge of the spatio-temporal data generating process. Our approach relies on a dynamic spatio-temporal model that explicitly incorporates location-specific covariates. We illustrate our approach with a spatially varying ecological diffusion model implemented using a computationally efficient homogenization technique. We apply our model to understand individual-level and location-specific risk factors associated with chronic wasting disease in white-tailed deer from Wisconsin, USA and estimate the location the disease was first introduced. We compare our approach to several existing methods that are commonly used in spatial statistics. Our spatio-temporal approach resulted in a higher predictive accuracy when compared to methods based on optimal spatial prediction, obviated confounding among the spatially indexed covariates and the spatial random effect, and provided additional information that will be important for containing disease outbreaks.

Data mining techniques for assisting the diagnosis of pressure ulcer development in surgical patients.

PubMed

Su, Chao-Ton; Wang, Pa-Chun; Chen, Yan-Cheng; Chen, Li-Fei

2012-08-01

Pressure ulcer is a serious problem during patient care processes. The high risk factors in the development of pressure ulcer remain unclear during long surgery. Moreover, past preventive policies are hard to implement in a busy operation room. The objective of this study is to use data mining techniques to construct the prediction model for pressure ulcers. Four data mining techniques, namely, Mahalanobis Taguchi System (MTS), Support Vector Machines (SVMs), decision tree (DT), and logistic regression (LR), are used to select the important attributes from the data to predict the incidence of pressure ulcers. Measurements of sensitivity, specificity, F(1), and g-means were used to compare the performance of four classifiers on the pressure ulcer data set. The results show that data mining techniques obtain good results in predicting the incidence of pressure ulcer. We can conclude that data mining techniques can help identify the important factors and provide a feasible model to predict pressure ulcer development.

Identification and Characterization of FGF2-Dependent mRNA: microRNA Networks During Lens Fiber Cell Differentiation

PubMed Central

Wolf, Louise; Gao, Chun S.; Gueta, Karen; Xie, Qing; Chevallier, Tiphaine; Podduturi, Nikhil R.; Sun, Jian; Conte, Ivan; Zelenka, Peggy S.; Ashery-Padan, Ruth; Zavadil, Jiri; Cvekl, Ales

2013-01-01

MicroRNAs (miRNAs) and fibroblast growth factor (FGF) signaling regulate a wide range of cellular functions, including cell specification, proliferation, migration, differentiation, and survival. In lens, both these systems control lens fiber cell differentiation; however, a possible link between these processes remains to be examined. Herein, the functional requirement for miRNAs in differentiating lens fiber cells was demonstrated via conditional inactivation of Dicer1 in mouse (Mus musculus) lens. To dissect the miRNA-dependent pathways during lens differentiation, we used a rat (Rattus norvegicus) lens epithelial explant system, induced by FGF2 to differentiate, followed by mRNA and miRNA expression profiling. Transcriptome and miRNome analysis identified extensive FGF2-regulated cellular responses that were both independent and dependent on miRNAs. We identified 131 FGF2-regulated miRNAs. Seventy-six of these miRNAs had at least two in silico predicted and inversely regulated target mRNAs. Genes modulated by the greatest number of FGF-regulated miRNAs include DNA-binding transcription factors Nfib, Nfat5/OREBP, c-Maf, Ets1, and N-Myc. Activated FGF signaling influenced bone morphogenetic factor/transforming growth factor-β, Notch, and Wnt signaling cascades implicated earlier in lens differentiation. Specific miRNA:mRNA interaction networks were predicted for c-Maf, N-Myc, and Nfib (DNA-binding transcription factors); Cnot6, Cpsf6, Dicer1, and Tnrc6b (RNA to miRNA processing); and Ash1l, Med1/PBP, and Kdm5b/Jarid1b/Plu1 (chromatin remodeling). Three miRNAs, including miR-143, miR-155, and miR-301a, down-regulated expression of c-Maf in the 3′-UTR luciferase reporter assays. These present studies demonstrate for the first time global impact of activated FGF signaling in lens cell culture system and predicted novel gene regulatory networks connected by multiple miRNAs that regulate lens differentiation. PMID:24142921

Automated chart review utilizing natural language processing algorithm for asthma predictive index.

PubMed

Kaur, Harsheen; Sohn, Sunghwan; Wi, Chung-Il; Ryu, Euijung; Park, Miguel A; Bachman, Kay; Kita, Hirohito; Croghan, Ivana; Castro-Rodriguez, Jose A; Voge, Gretchen A; Liu, Hongfang; Juhn, Young J

2018-02-13

Thus far, no algorithms have been developed to automatically extract patients who meet Asthma Predictive Index (API) criteria from the Electronic health records (EHR) yet. Our objective is to develop and validate a natural language processing (NLP) algorithm to identify patients that meet API criteria. This is a cross-sectional study nested in a birth cohort study in Olmsted County, MN. Asthma status ascertained by manual chart review based on API criteria served as gold standard. NLP-API was developed on a training cohort (n = 87) and validated on a test cohort (n = 427). Criterion validity was measured by sensitivity, specificity, positive predictive value and negative predictive value of the NLP algorithm against manual chart review for asthma status. Construct validity was determined by associations of asthma status defined by NLP-API with known risk factors for asthma. Among the eligible 427 subjects of the test cohort, 48% were males and 74% were White. Median age was 5.3 years (interquartile range 3.6-6.8). 35 (8%) had a history of asthma by NLP-API vs. 36 (8%) by abstractor with 31 by both approaches. NLP-API predicted asthma status with sensitivity 86%, specificity 98%, positive predictive value 88%, negative predictive value 98%. Asthma status by both NLP and manual chart review were significantly associated with the known asthma risk factors, such as history of allergic rhinitis, eczema, family history of asthma, and maternal history of smoking during pregnancy (p value < 0.05). Maternal smoking [odds ratio: 4.4, 95% confidence interval 1.8-10.7] was associated with asthma status determined by NLP-API and abstractor, and the effect sizes were similar between the reviews with 4.4 vs 4.2 respectively. NLP-API was able to ascertain asthma status in children mining from EHR and has a potential to enhance asthma care and research through population management and large-scale studies when identifying children who meet API criteria.

An updated concept of coagulation with clinical implications.

PubMed

Romney, Gregory; Glick, Michael

2009-05-01

Over the past century, a series of models have been put forth to explain the coagulation mechanism. The coagulation cascade/waterfall model has gained the most widespread acceptance. This model, however, has problems when it is used in different clinical scenarios. A more recently proposed cell-based model better describes the coagulation process in vivo and provides oral health care professionals (OHCPs) with a better understanding of the clinical implications of providing dental care to patients with potentially increased bleeding tendencies. The authors conducted a literature search using the PubMed database. They searched for key words including "coagulation," "hemostasis," "bleeding," "coagulation factors," "models," "prothrombin time," "activated partial thromboplastin time," "international normalized ratio," "anticoagulation therapy" and "hemophilia" separately and in combination. The coagulation cascade/waterfall model is insufficient to explain coagulation in vivo, predict a patient's bleeding tendency, or correlate clinical outcomes with specific laboratory screening tests such as prothrombin time, activated partial thromboplastin time and international normalized ratio. However, the cell-based model of coagulation that reflects the in vivo process of coagulation provides insight into the clinical ramifications of treating dental patients with specific coagulation factor deficiencies. Understanding the in vivo coagulation process will help OHCPs better predict a patient's bleeding tendency. In addition, applying the theoretical concept of the cell-based model of coagulation to commonly used laboratory screening tests for coagulation and bleeding will result in safer and more appropriate dental care.

Conscious motor processing and movement self-consciousness: two dimensions of personality that influence laparoscopic training.

PubMed

Malhotra, Neha; Poolton, Jamie M; Wilson, Mark R; Fan, Joe K M; Masters, Rich S W

2014-01-01

Identifying personality factors that account for individual differences in surgical training and performance has practical implications for surgical education. Movement-specific reinvestment is a potentially relevant personality factor that has a moderating effect on laparoscopic performance under time pressure. Movement-specific reinvestment has 2 dimensions, which represent an individual's propensity to consciously control movements (conscious motor processing) or to consciously monitor their 'style' of movement (movement self-consciousness). This study aimed at investigating the moderating effects of the 2 dimensions of movement-specific reinvestment in the learning and updating (cross-handed technique) of laparoscopic skills. Medical students completed the Movement-Specific Reinvestment Scale, a psychometric assessment tool that evaluates the conscious motor processing and movement self-consciousness dimensions of movement-specific reinvestment. They were then trained to a criterion level of proficiency on a fundamental laparoscopic skills task and were tested on a novel cross-handed technique. Completion times were recorded for early-learning, late-learning, and cross-handed trials. Propensity for movement self-consciousness but not conscious motor processing was a significant predictor of task completion times both early (p = 0.036) and late (p = 0.002) in learning, but completion times during the cross-handed trials were predicted by the propensity for conscious motor processing (p = 0.04) rather than movement self-consciousness (p = 0.21). Higher propensity for movement self-consciousness is associated with slower performance times on novel and well-practiced laparoscopic tasks. For complex surgical techniques, however, conscious motor processing plays a more influential role in performance than movement self-consciousness. The findings imply that these 2 dimensions of movement-specific reinvestment have a differential influence in the learning and updating of laparoscopic skills. Copyright © 2014 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Hydrologic modeling strategy for the Islamic Republic of Mauritania, Africa

USGS Publications Warehouse

Friedel, Michael J.

2008-01-01

The government of Mauritania is interested in how to maintain hydrologic balance to ensure a long-term stable water supply for minerals-related, domestic, and other purposes. Because of the many complicating and competing natural and anthropogenic factors, hydrologists will perform quantitative analysis with specific objectives and relevant computer models in mind. Whereas various computer models are available for studying water-resource priorities, the success of these models to provide reliable predictions largely depends on adequacy of the model-calibration process. Predictive analysis helps us evaluate the accuracy and uncertainty associated with simulated dependent variables of our calibrated model. In this report, the hydrologic modeling process is reviewed and a strategy summarized for future Mauritanian hydrologic modeling studies.

ADOT state-specific crash prediction models : an Arizona needs study.

DOT National Transportation Integrated Search

2016-12-01

The predictive method in the Highway Safety Manual (HSM) includes a safety performance function (SPF), : crash modification factors (CMFs), and a local calibration factor (C), if available. Two alternatives exist for : applying the HSM prediction met...

What Are the Predictors of Altered Central Pain Modulation in Chronic Musculoskeletal Pain Populations? A Systematic Review.

PubMed

Clark, Jacqui; Nijs, Jo; Yeowell, Gillian; Goodwin, Peter Charles

2017-09-01

Altered central pain modulation is the predominant pain mechanism in a proportion of chronic musculoskeletal pain disorders and is associated with poor outcomes. Although existing studies predict poor outcomes such as persistent pain and disability, to date there is little consensus on what factors specifically predict altered central pain modulation. To review the existing literature on the predictive factors specifically for altered central pain modulation in musculoskeletal pain populations. This is a systematic review in accordance with supplemented PRISMA guidelines. A systematic search was performed by 2 mutually blinded reviewers. Relevant articles were screened by title and abstract from Medline, Embase, PubMed, CINAHL, and Web of Science electronic databases. Alternative sources were also sought to locate missed potential articles. Eligibility included studies published in English, adults aged 18 to 65, musculoskeletal pain, baseline measurements taken at the pre-morbid or acute stage, > 3-month follow-up time after pain onset, and primary outcome measures specific to altered central pain modulation. Studies were excluded where there were concurrent diseases or they were non-predictive studies. Risk of bias was assessed using the quality in prognostic studies (QUIPS) tool. Study design, demographics, musculoskeletal region, inclusion/exclusion criteria, measurement timelines, predictor and primary outcome measures, and results were extracted. Data were synthesized qualitatively and strength of evidence was scored using the grading of recommendations, assessment, development, and evaluations (GRADE) scoring system. Nine eligible articles were located, in various musculoskeletal populations (whiplash, n = 2; widespread pain, n = 5; temporomandibular disorder, n = 2). Moderate evidence was found for 2 predictive factors of altered central pain modulation: 1) high sensory sensitivity (using genetic testing or quantitative sensory tests), and 2) psychological factors (somatization and poor self-expectation of recovery), at a pre-morbid or acute stage baseline. At the times of the article publications, the current definitions and clinical guidelines for identifying altered central pain modulation were not yet available. Careful interpretation of the information provided using current knowledge and published guidelines was necessary to extract information specific to altered central pain modulation in some of the studies, avoiding unwarranted assumptions. Premorbid and acute stage high sensory sensitivity and/or somatization are the strongest predictors of altered central pain modulation in chronic musculoskeletal pain to date. This is the first systematic review specifically targeting altered central pain modulation as the primary outcome in musculoskeletal pain populations. Early identification of people at risk of developing chronic pain with altered central pain modulation may guide clinicians in appropriate management, diminishing the burden of persistent pain on patients and heath care providers alike. Systematic Review Registration no.: PROSPERO 2015:CRD42015032394.Key words: Predictive factors, pre-morbid and acute stage baselines, altered central pain modulation, chronic musculoskeletal pain, sensory processing, somatization.

Predicting homophobic behavior among heterosexual youth: domain general and sexual orientation-specific factors at the individual and contextual level.

PubMed

Poteat, V Paul; DiGiovanni, Craig D; Scheer, Jillian R

2013-03-01

As a form of bias-based harassment, homophobic behavior remains prominent in schools. Yet, little attention has been given to factors that underlie it, aside from bullying and sexual prejudice. Thus, we examined multiple domain general (empathy, perspective-taking, classroom respect norms) and sexual orientation-specific factors (sexual orientation identity importance, number of sexual minority friends, parents' sexual minority attitudes, media messages). We documented support for a model in which these sets of factors converged to predict homophobic behavior, mediated through bullying and prejudice, among 581 students in grades 9-12 (55 % female). The structural equation model indicated that, with the exception of media messages, these additional factors predicted levels of prejudice and bullying, which in turn predicted the likelihood of students to engage in homophobic behavior. These findings highlight the importance of addressing multiple interrelated factors in efforts to reduce bullying, prejudice, and discrimination among youth.

Cognitive components of a mathematical processing network in 9-year-old children.

PubMed

Szűcs, Dénes; Devine, Amy; Soltesz, Fruzsina; Nobes, Alison; Gabriel, Florence

2014-07-01

We determined how various cognitive abilities, including several measures of a proposed domain-specific number sense, relate to mathematical competence in nearly 100 9-year-old children with normal reading skill. Results are consistent with an extended number processing network and suggest that important processing nodes of this network are phonological processing, verbal knowledge, visuo-spatial short-term and working memory, spatial ability and general executive functioning. The model was highly specific to predicting arithmetic performance. There were no strong relations between mathematical achievement and verbal short-term and working memory, sustained attention, response inhibition, finger knowledge and symbolic number comparison performance. Non-verbal intelligence measures were also non-significant predictors when added to our model. Number sense variables were non-significant predictors in the model and they were also non-significant predictors when entered into regression analysis with only a single visuo-spatial WM measure. Number sense variables were predicted by sustained attention. Results support a network theory of mathematical competence in primary school children and falsify the importance of a proposed modular 'number sense'. We suggest an 'executive memory function centric' model of mathematical processing. Mapping a complex processing network requires that studies consider the complex predictor space of mathematics rather than just focusing on a single or a few explanatory factors.

Cognitive components of a mathematical processing network in 9-year-old children

PubMed Central

Szűcs, Dénes; Devine, Amy; Soltesz, Fruzsina; Nobes, Alison; Gabriel, Florence

2014-01-01

We determined how various cognitive abilities, including several measures of a proposed domain-specific number sense, relate to mathematical competence in nearly 100 9-year-old children with normal reading skill. Results are consistent with an extended number processing network and suggest that important processing nodes of this network are phonological processing, verbal knowledge, visuo-spatial short-term and working memory, spatial ability and general executive functioning. The model was highly specific to predicting arithmetic performance. There were no strong relations between mathematical achievement and verbal short-term and working memory, sustained attention, response inhibition, finger knowledge and symbolic number comparison performance. Non-verbal intelligence measures were also non-significant predictors when added to our model. Number sense variables were non-significant predictors in the model and they were also non-significant predictors when entered into regression analysis with only a single visuo-spatial WM measure. Number sense variables were predicted by sustained attention. Results support a network theory of mathematical competence in primary school children and falsify the importance of a proposed modular ‘number sense’. We suggest an ‘executive memory function centric’ model of mathematical processing. Mapping a complex processing network requires that studies consider the complex predictor space of mathematics rather than just focusing on a single or a few explanatory factors. PMID:25089322

A specific glycerol kinase induces rapid cold hardening of the diamondback moth, Plutella xylostella.

PubMed

Park, Youngjin; Kim, Yonggyun

2014-08-01

Insects in temperate zones survive low temperatures by migrating or tolerating the cold. The diamondback moth, Plutella xylostella, is a serious insect pest on cabbage and other cruciferous crops worldwide. We showed that P. xylostella became cold-tolerant by expressing rapid cold hardiness (RCH) in response to a brief exposure to moderately low temperature (4°C) for 7h along with glycerol accumulation in hemolymph. Glycerol played a crucial role in the cold-hardening process because exogenously supplying glycerol significantly increased the cold tolerance of P. xylostella larvae without cold acclimation. To determine the genetic factor(s) responsible for RCH and the increase of glycerol, four glycerol kinases (GKs), and glycerol-3-phosphate dehydrogenase (PxGPDH) were predicted from the whole P. xylostella genome and analyzed for their function associated with glycerol biosynthesis. All predicted genes were expressed, but differed in their expression during different developmental stages and in different tissues. Expression of the predicted genes was individually suppressed by RNA interference (RNAi) using double-stranded RNAs specific to target genes. RNAi of PxGPDH expression significantly suppressed RCH and glycerol accumulation. Only PxGK1 among the four GKs was responsible for RCH and glycerol accumulation. Furthermore, PxGK1 expression was significantly enhanced during RCH. These results indicate that a specific GK, the terminal enzyme to produce glycerol, is specifically inducible during RCH to accumulate the main cryoprotectant. Copyright © 2014 Elsevier Ltd. All rights reserved.

Posture and activity recognition and energy expenditure prediction in a wearable platform.

PubMed

Sazonova, Nadezhda; Browning, Raymond; Melanson, Edward; Sazonov, Edward

2014-01-01

The use of wearable sensors coupled with the processing power of mobile phones may be an attractive way to provide real-time feedback about physical activity and energy expenditure (EE). Here we describe use of a shoe-based wearable sensor system (SmartShoe) with a mobile phone for real-time prediction and display of time spent in various postures/physical activities and the resulting EE. To deal with processing power and memory limitations of the phone, we introduce new algorithms that require substantially less computational power. The algorithms were validated using data from 15 subjects who performed up to 15 different activities of daily living during a four-hour stay in a room calorimeter. Use of Multinomial Logistic Discrimination (MLD) for posture and activity classification resulted in an accuracy comparable to that of Support Vector Machines (SVM) (90% vs. 95%-98%) while reducing the running time by a factor of 190 and reducing the memory requirement by a factor of 104. Per minute EE estimation using activity-specific models resulted in an accurate EE prediction (RMSE of 0.53 METs vs. RMSE of 0.69 METs using previously reported SVM-branched models). These results demonstrate successful implementation of real-time physical activity monitoring and EE prediction system on a wearable platform.

Quantifying the Effect of DNA Packaging on Gene Expression Level

NASA Astrophysics Data System (ADS)

Kim, Harold

2010-10-01

Gene expression, the process by which the genetic code comes alive in the form of proteins, is one of the most important biological processes in living cells, and begins when transcription factors bind to specific DNA sequences in the promoter region upstream of a gene. The relationship between gene expression output and transcription factor input which is termed the gene regulation function is specific to each promoter, and predicting this gene regulation function from the locations of transcription factor binding sites is one of the challenges in biology. In eukaryotic organisms (for example, animals, plants, fungi etc), DNA is highly compacted into nucleosomes, 147-bp segments of DNA tightly wrapped around histone protein core, and therefore, the accessibility of transcription factor binding sites depends on their locations with respect to nucleosomes - sites inside nucleosomes are less accessible than those outside nucleosomes. To understand how transcription factor binding sites contribute to gene expression in a quantitative manner, we obtain gene regulation functions of promoters with various configurations of transcription factor binding sites by using fluorescent protein reporters to measure transcription factor input and gene expression output in single yeast cells. In this talk, I will show that the affinity of a transcription factor binding site inside and outside the nucleosome controls different aspects of the gene regulation function, and explain this finding based on a mass-action kinetic model that includes competition between nucleosomes and transcription factors.

Genomics of Mature and Immature Olfactory Sensory Neurons

PubMed Central

Nickell, Melissa D.; Breheny, Patrick; Stromberg, Arnold J.; McClintock, Timothy S.

2014-01-01

The continuous replacement of neurons in the olfactory epithelium provides an advantageous model for investigating neuronal differentiation and maturation. By calculating the relative enrichment of every mRNA detected in samples of mature mouse olfactory sensory neurons (OSNs), immature OSNs, and the residual population of neighboring cell types, and then comparing these ratios against the known expression patterns of >300 genes, enrichment criteria that accurately predicted the OSN expression patterns of nearly all genes were determined. We identified 847 immature OSN-specific and 691 mature OSN-specific genes. The control of gene expression by chromatin modification and transcription factors, and neurite growth, protein transport, RNA processing, cholesterol biosynthesis, and apoptosis via death domain receptors, were overrepresented biological processes in immature OSNs. Ion transport (ion channels), presynaptic functions, and cilia-specific processes were overrepresented in mature OSNs. Processes overrepresented among the genes expressed by all OSNs were protein and ion transport, ER overload response, protein catabolism, and the electron transport chain. To more accurately represent gradations in mRNA abundance and identify all genes expressed in each cell type, classification methods were used to produce probabilities of expression in each cell type for every gene. These probabilities, which identified 9,300 genes expressed in OSNs, were 96% accurate at identifying genes expressed in OSNs and 86% accurate at discriminating genes specific to mature and immature OSNs. This OSN gene database not only predicts the genes responsible for the major biological processes active in OSNs, but also identifies thousands of never before studied genes that support OSN phenotypes. PMID:22252456

Coping with the threat of terrorism: a review.

PubMed

Maguen, Shira; Papa, Anthony; Litz, Brett T

2008-01-01

Terrorism creates a ripple of fear and uncertainty. Although most individuals are resilient and recover over time, a minority remains functionally and psychologically impaired. In this paper, we examine research on coping strategies employed in the aftermath of terrorist events, theories and empirical findings related to appraisal processes that influence individuals' primary attributions of risk, and normative processes that shape secondary appraisals, which predict specific coping behaviors. We also describe individual diatheses and factors promoting resilience that may influence coping and functioning in the face of terrorism. Finally, we offer suggestions for future research.

Natural selection and the predictability of evolution in Timema stick insects.

PubMed

Nosil, Patrik; Villoutreix, Romain; de Carvalho, Clarissa F; Farkas, Timothy E; Soria-Carrasco, Víctor; Feder, Jeffrey L; Crespi, Bernard J; Gompert, Zach

2018-02-16

Predicting evolution remains difficult. We studied the evolution of cryptic body coloration and pattern in a stick insect using 25 years of field data, experiments, and genomics. We found that evolution is more difficult to predict when it involves a balance between multiple selective factors and uncertainty in environmental conditions than when it involves feedback loops that cause consistent back-and-forth fluctuations. Specifically, changes in color-morph frequencies are modestly predictable through time ( r 2 = 0.14) and driven by complex selective regimes and yearly fluctuations in climate. In contrast, temporal changes in pattern-morph frequencies are highly predictable due to negative frequency-dependent selection ( r 2 = 0.86). For both traits, however, natural selection drives evolution around a dynamic equilibrium, providing some predictability to the process. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Specific Rab GTPase-activating proteins define the Shiga toxin and epidermal growth factor uptake pathways.

PubMed

Fuchs, Evelyn; Haas, Alexander K; Spooner, Robert A; Yoshimura, Shin-ichiro; Lord, J Michael; Barr, Francis A

2007-06-18

Rab family guanosine triphosphatases (GTPases) together with their regulators define specific pathways of membrane traffic within eukaryotic cells. In this study, we have investigated which Rab GTPase-activating proteins (GAPs) can interfere with the trafficking of Shiga toxin from the cell surface to the Golgi apparatus and studied transport of the epidermal growth factor (EGF) from the cell surface to endosomes. This screen identifies 6 (EVI5, RN-tre/USP6NL, TBC1D10A-C, and TBC1D17) of 39 predicted human Rab GAPs as specific regulators of Shiga toxin but not EGF uptake. We show that Rab43 is the target of RN-tre and is required for Shiga toxin uptake. In contrast, RabGAP-5, a Rab5 GAP, was unique among the GAPs tested and reduced the uptake of EGF but not Shiga toxin. These results suggest that Shiga toxin trafficking to the Golgi is a multistep process controlled by several Rab GAPs and their target Rabs and that this process is discrete from ligand-induced EGF receptor trafficking.

Allele-Specific Alternative mRNA processing (ASARP) | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

A software pipeline for prediction of allele-specific alternative RNA processing events using single RNA-seq data. The current version focuses on prediction of alternative splicing and alternative polyadenylation modulated by genetic variants.

Predictive Modeling of Risk Factors and Complications of Cataract Surgery

PubMed Central

Gaskin, Gregory L; Pershing, Suzann; Cole, Tyler S; Shah, Nigam H

2016-01-01

Purpose To quantify the relationship between aggregated preoperative risk factors and cataract surgery complications, as well as to build a model predicting outcomes on an individual-level—given a constellation of demographic, baseline, preoperative, and intraoperative patient characteristics. Setting Stanford Hospital and Clinics between 1994 and 2013. Design Retrospective cohort study Methods Patients age 40 or older who received cataract surgery between 1994 and 2013. Risk factors, complications, and demographic information were extracted from the Electronic Health Record (EHR), based on International Classification of Diseases, 9th edition (ICD-9) codes, Current Procedural Terminology (CPT) codes, drug prescription information, and text data mining using natural language processing. We used a bootstrapped least absolute shrinkage and selection operator (LASSO) model to identify highly-predictive variables. We built random forest classifiers for each complication to create predictive models. Results Our data corroborated existing literature on postoperative complications—including the association of intraoperative complications, complex cataract surgery, black race, and/or prior eye surgery with an increased risk of any postoperative complications. We also found a number of other, less well-described risk factors, including systemic diabetes mellitus, young age (<60 years old), and hyperopia as risk factors for complex cataract surgery and intra- and post-operative complications. Our predictive models based on aggregated outperformed existing published models. Conclusions The constellations of risk factors and complications described here can guide new avenues of research and provide specific, personalized risk assessment for a patient considering cataract surgery. The predictive capacity of our models can enable risk stratification of patients, which has utility as a teaching tool as well as informing quality/value-based reimbursements. PMID:26692059

Out Drinking the Joneses: Neighborhood Factors Moderating the Effects of Drinking on Relationship Quality over the First Four Years of Marriage.

PubMed

Crasta, Dev; Funk, Janette L; Lee, Soonhee; Rogge, Ronald D

2017-12-27

Neighborhood quality has been cross-sectionally linked to both relationship behaviors and relationship well-being. Consistent with the Vulnerability Stress-Adaptation model of relationship functioning (Karney & Bradbury, 1995), we hypothesized that associations between social behaviors (e.g., drinking) and relationship quality could be moderated by neighborhood factors. Specifically, we characterized neighborhoods along multiple dimensions using multiple methods (self-report, census) to investigate how neighborhood factors might clarify ambiguous effects of alcohol use on marital functioning. A nationally recruited sample of 303 newlywed couples completed a baseline assessment around the time of marriage and was then assessed yearly across the first 4 years of marriage (94% retention). Three level HLM slope-intercept models were used to model changes in relationship satisfaction across the first 4 years of marriage. Results suggested that, for couples living in highly disordered neighborhoods, positive shifts in overall levels of drinking within specific waves of assessment were associated with corresponding negative shifts in satisfaction whereas in neighborhoods without perceived disorder, this effect was reversed. For couples living in neighborhoods with low levels of domestic structures (high census rates of single renters without children), within-couple discrepancies favoring higher rates of husband drinking in specific waves predicted poorer relationship quality for both partners in those same waves whereas those same discrepancies predicted higher satisfaction in high domesticity neighborhoods (high census rates of married homeowners with children). The findings provide insight into the different roles of alcohol use in relationship maintenance and highlight the importance of using external context to understand intradyadic processes. © 2017 Family Process Institute.

Systems Analysis of the Hydrogen Transition with HyTrans

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

Leiby, Paul Newsome; Greene, David L; Bowman, David Charles

2007-01-01

The U.S. Federal government is carefully considering the merits and long-term prospects of hydrogen-fueled vehicles. NAS (1) has called for the careful application of systems analysis tools to structure the complex assessment required. Others, raising cautionary notes, question whether a consistent and plausible transition to hydrogen light-duty vehicles can identified (2) and whether that transition would, on balance, be environmentally preferred. Modeling the market transition to hydrogen-powered vehicles is an inherently complex process, encompassing hydrogen production, delivery and retailing, vehicle manufacturing, and vehicle choice and use. We describe the integration of key technological and market factors in a dynamic transitionmore » model, HyTrans. The usefulness of HyTrans and its predictions depends on three key factors: (1) the validity of the economic theories that underpin the model, (2) the authenticity with which the key processes are represented, and (3) the accuracy of specific parameter values used in the process representations. This paper summarizes the theoretical basis of HyTrans, and highlights the implications of key parameter specifications with sensitivity analysis.« less

Toward an Integrative Model of Creativity and Personality: Theoretical Suggestions and Preliminary Empirical Testing

ERIC Educational Resources Information Center

Fü rst, Guillaume; Ghisletta, Paolo; Lubart, Todd

2016-01-01

The present work proposes an integrative model of creativity that includes personality traits and cognitive processes. This model hypothesizes that three high-order personality factors predict two main process factors, which in turn predict intensity and achievement of creative activities. The personality factors are: "Plasticity" (high…

[Pernicious anaemia--diagnostic benefit of the detection of autoantibodies against intrinsic factor and gastric parietal cells antigen H+/K+ ATPase].

PubMed

Sedláková, L; Dubská, L; Průcha, M

2010-08-01

Pernicious anaemia is an autoimmune disease that causes acquired vitamin B12 deficiency. The diagnostic process includes the detection of typical changes in the blood count, low serum levels of vitamin B12, endoscopic and histological signs of gastritis and autoantibodies against the gastric parietal cells antigen H+/K+ ATPase and intrinsic factor. Our aims were to establish immunological tests for the detection of autoantibodies against intrinsic factor and target gastric parietal cell antigen H+/K+ ATPase and to evaluate their diagnostic benefits in patients with pernicious anaemia. Sera from 95 patients were tested for autoantibodies against H+/K+ ATPase and intrinsic factor by multiplex Luminex assay. The results were compared with those of the immunofluorescence assay for the detection of autoantibodies against gastric parietal cells and with the diagnostic criteria. The autoantibodies against gastric parietal cell H+/K+ ATPase had a sensitivity of 68.2% with a specificity of 91.7% for the diagnosis of pernicious anaemia. The respective rates for the autoantibodies against intrinsic factor were 40.9% and 98.6%. The combined sensitivity and specificity rates for both autoantibodies were 86.36% and 90.28%, respectively, the combined positive predictive value was 73.08% and the combined negative predictive value was 95.59%. The detection of both autoantibodies is helpful in diagnosing pernicious anaemia and the combination of the two assays increases diagnostic sensitivity.

The multiple subfunctions of attention: differential developmental gateways to literacy and numeracy.

PubMed

Steele, Ann; Karmiloff-Smith, Annette; Cornish, Kim; Scerif, Gaia

2012-11-01

Attention is construed as multicomponential, but the roles of its distinct subfunctions in shaping the broader developing cognitive landscape are poorly understood. The current study assessed 3- to 6-year-olds (N=83) to: (a) trace developmental trajectories of attentional processes and their structure in early childhood and (b) measure the impact of distinct attention subfunctions on concurrent and longitudinal abilities related to literacy and numeracy. Distinct trajectories across attention measures revealed the emergence of 2 attentional factors, encompassing "executive" and "sustained-selective" processes. Executive attention predicted concurrent abilities across domains at Time 1, whereas sustained-selective attention predicted basic numeracy 1 year later. These concurrent and longitudinal constraints cast a broader light on the unfolding relations between domain-general and domain-specific processes over early childhood. © 2012 The Authors. Child Development © 2012 Society for Research in Child Development, Inc.

Global analysis of bacterial transcription factors to predict cellular target processes.

PubMed

Doerks, Tobias; Andrade, Miguel A; Lathe, Warren; von Mering, Christian; Bork, Peer

2004-03-01

Whole-genome sequences are now available for >100 bacterial species, giving unprecedented power to comparative genomics approaches. We have applied genome-context methods to predict target processes that are regulated by transcription factors (TFs). Of 128 orthologous groups of proteins annotated as TFs, to date, 36 are functionally uncharacterized; in our analysis we predict a probable cellular target process or biochemical pathway for half of these functionally uncharacterized TFs.

Specific phobias in older adults: characteristics and differential diagnosis.

PubMed

Coelho, Carlos M; Gonçalves, Daniela C; Purkis, Helena; Pocinho, Margarida; Pachana, Nancy A; Byrne, Gerard J

2010-08-01

Differential diagnosis implies identifying shared and divergent characteristics between clinical states. Clinical work with older adults demands not only the knowledge of nosological features associated with differential diagnosis, but also recognition of idiosyncratic factors associated with this population. Several factors can interfere with an accurate diagnosis of specific phobia in older cohorts. The goal of this paper is to review criteria for specific phobia and its differential diagnosis with panic disorder, agoraphobia, post-traumatic stress disorder and obsessive compulsive disorder, while stressing the specific factors associated with aging. A literature search regarding specific phobia in older adults was carried out using PubMed. Relevant articles were selected and scanned for further pertinent references. In addition, relevant references related to differential diagnosis and assessment were used. Etiologic factors, specificity of feared stimulus or situation, fear predictability and the nature of phobic situations are key points to be assessed when implementing a differential diagnosis of specific phobia. First, age-related sensory impairments are common and interfere both with information processing and communication. Second, medical illnesses create symptoms that might cause, interfere with, or mimic anxiety. Third, cohort effects might result in underreporting, through the inability to communicate or recognize anxiety symptoms, misattributing them to physical conditions. Finally, diagnostic criteria and screening instruments were usually developed using younger samples and are therefore not adapted to the functional and behavioral characteristics of older samples.

Exploring the Structure of Human Defensive Responses from Judgments of Threat Scenarios

PubMed Central

Harrison, Laura A.; Ahn, Curie; Adolphs, Ralph

2015-01-01

How humans react to threats is a topic of broad theoretical importance, and also relevant for understanding anxiety disorders. Many animal threat reactions exhibit a common structure, a finding supported by human evaluations of written threat scenarios that parallel patterns of rodent defensive behavior to actual threats. Yet the factors that underlie these shared behavioral patterns remain unclear. Dimensional accounts rooted in Darwin’s conception of antithesis explain many defensive behaviors. Across species, it is also clear that defensive reactions depend on specific situational factors, a feature long emphasized by psychological appraisal theories. Our study sought to extend prior investigations of human judgments of threat to a broader set of threats, including natural disasters, threats from animals, and psychological (as opposed to physical) threats. Our goal was to test whether dimensional and specific patterns of threat evaluation replicate across different threat classes. 85 healthy adult subjects selected descriptions of defensive behaviors that indicated how they would react to 29 threatening scenarios. Scenarios differed with respect to ten factors, e.g., perceived dangerousness or escapability. Across scenarios, we correlated these factor ratings with the pattern of defensive behaviors subjects endorsed. A decision tree hierarchically organized these correlation patterns to successfully predict each scenario’s most common reaction, both for the original sample of subjects and a separate replication group (n = 22). At the top of the decision tree, degree of dangerousness interacted with threat type (physical or psychological) to predict dimensional approach/avoidance behavior. Subordinate nodes represented specific defensive responses evoked by particular contexts. Our ecological approach emphasizes the interplay of situational factors in evoking a broad range of threat reactions. Future studies could test predictions made by our results to help understand pathological threat processing, such as seen in anxiety disorders, and could begin to test underlying neural mechanisms. PMID:26296201

Mothers of children with externalizing behavior problems: cognitive risk factors for abuse potential and discipline style and practices.

PubMed

McElroy, Erika M; Rodriguez, Christina M

2008-08-01

Utilizing the conceptual framework of the Social Information Processing (SIP) model (Milner, 1993, 2000), associations between cognitive risk factors and child physical abuse risk and maladaptive discipline style and practices were examined in an at-risk population. Seventy-three mothers of 5-12-year-old children, who were identified by their therapist as having an externalizing behavior problem, responded to self-report measures pertaining to cognitive risk factors (empathic perspective taking, frustration tolerance, developmental expectations, parenting locus of control), abuse risk, and discipline style and practices. The Child Behavior Checklist (CBCL) provided a confirmation of the child's externalizing behaviors independent of the therapist's assessment. The results of this study suggest several cognitive risk factors significantly predict risk of parental aggression toward children. A parent's ability to empathize and take the perspective of their child, parental locus of control, and parental level of frustration tolerance were significant predictors of abuse potential (accounting for 63% of the variance) and inappropriate discipline practices (accounting for 55% of the variance). Findings of the present study provide support for processes theorized in the SIP model. Specifically, results underscore the potential role of parents' frustration tolerance, developmental expectations, locus of control, and empathy as predictive of abuse potential and disciplinary style in an at-risk sample.

A Predictive Study of Pre-Service Teachers and Success in Final Student Internship

ERIC Educational Resources Information Center

Ingle, Karen M.

2017-01-01

Student teaching provides the final pre-service clinical teaching experience of an initial teacher preparation program. Research that specifically studies the pre-service student teacher and predictive factors of student teaching is limited. Identifying predictive factors that contribute to the success of student interns' student teaching…

Temporal processing impairment in children with attention-deficit-hyperactivity disorder.

PubMed

Huang, Jia; Yang, Bin-rang; Zou, Xiao-bing; Jing, Jin; Pen, Gang; McAlonan, Gráinne M; Chan, Raymond C K

2012-01-01

The current study aimed to investigate temporal processing in Chinese children with Attention-Deficit-Hyperactivity Disorder(ADHD) using time production, time reproduction paradigm and duration discrimination tasks. A battery of tests specifically designed to measure temporal processing was administered to 94 children with ADHD and 100 demographically matched healthy children. A multivariate analysis of variance (MANOVA) and a repeated measure MANOVA indicated that children with ADHD were impaired in time processing functions. The results of pairwise comparisons showed that the probands with a family history of ADHD performed significantly worse than those without family history in the time production tasks and the time reproduction task. Logistic regression analysis showed duration discrimination had a significant role in predicting whether the children were suffering from ADHD or not, while temporal processing had a significant role in predicting whether the ADHD children had a family history or not. This study provides further support for the existence of a generic temporal processing impairment in ADHD children and suggests that abnormalities in time processing and ADHD share some common genetic factors. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

PubMed

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

2006-01-01

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

Vulnerability-specific stress generation: Childhood emotional abuse and the mediating role of depressogenic interpersonal processes.

PubMed

Hernandez, Evelyn M; Trout, Zoë M; Liu, Richard T

2016-12-01

Stress generation in depression (i.e. the tendency for depression-prone individuals to experience more life stress that is in part influenced by the individual) has been well established. However, more research is necessary to clarify the role of specific types of life stress in this effect. The current study extends the stress generation hypothesis by examining whether the type of stress involved is contingent upon the nature of the individual's particular vulnerability. Childhood emotional abuse and interpersonal vulnerability factors were predicted to be associated with prospective interpersonal dependent but not non-interpersonal or independent stress. These interpersonal factors were examined as mediators of the association between childhood emotional abuse and interpersonal stress generation. Data were collected from 185 undergraduate participants at two time-points, four months apart. At baseline, participants completed assessments of depressive symptoms, childhood abuse history, interpersonal risk factors (rejection sensitivity, excessive reassurance-seeking, and negative feedback-seeking), and a diagnostic interview for depression. At the follow-up assessment, participants completed a life stress interview. Childhood emotional abuse prospectively predicted greater interpersonal dependent stress, but not non-interpersonal dependent or independent stress. Only rejection sensitivity mediated this relationship. Consistent with the stress generation hypothesis, neither childhood emotional abuse nor the three interpersonal risk factors predicted independent stress. These findings suggest that targeting interpersonal vulnerabilities in clinical settings, particularly rejection sensitivity, among individuals with a history of childhood emotional abuse, may help to reduce the occurrence of interpersonal dependent stress, thus possibly decreasing risk for depression. Copyright © 2016 Elsevier Ltd. All rights reserved.

Managing meat tenderness.

PubMed

Thompson, John

2002-11-01

This paper discusses the management of meat tenderness using a carcass grading scheme which utilizes the concept of total quality management of those factors which impact on beef palatability. The scheme called Meat Standards Australia (MSA) has identified the Critical Control Points (CCPs) from the production, pre-slaughter, processing and value adding sectors of the beef supply chain and quantified their relative importance using large-scale consumer testing. These CCPs have been used to manage beef palatability in two ways. Firstly, CCPs from the pre-slaughter and processing sectors have been used as mandatory criteria for carcasses to be graded. Secondly, other CCPs from the production and processing sectors have been incorporated into a model to predict palatability for individual muscles. The evidence for the importance of CCPs from the production (breed, growth path and HGP implants), pre-slaughter and processing (pH/temperature window, alternative carcass suspension, marbling and ageing) sectors are reviewed and the accuracy of the model to predict palatability for specific muscle×cooking techniques is presented.

GC[Formula: see text]NMF: A Novel Matrix Factorization Framework for Gene-Phenotype Association Prediction.

PubMed

Zhang, Yaogong; Liu, Jiahui; Liu, Xiaohu; Hong, Yuxiang; Fan, Xin; Huang, Yalou; Wang, Yuan; Xie, Maoqiang

2018-04-24

Gene-phenotype association prediction can be applied to reveal the inherited basis of human diseases and facilitate drug development. Gene-phenotype associations are related to complex biological processes and influenced by various factors, such as relationship between phenotypes and that among genes. While due to sparseness of curated gene-phenotype associations and lack of integrated analysis of the joint effect of multiple factors, existing applications are limited to prediction accuracy and potential gene-phenotype association detection. In this paper, we propose a novel method by exploiting weighted graph constraint learned from hierarchical structures of phenotype data and group prior information among genes by inheriting advantages of Non-negative Matrix Factorization (NMF), called Weighted Graph Constraint and Group Centric Non-negative Matrix Factorization (GC[Formula: see text]NMF). Specifically, first we introduce the depth of parent-child relationships between two adjacent phenotypes in hierarchical phenotypic data as weighted graph constraint for a better phenotype understanding. Second, we utilize intra-group correlation among genes in a gene group as group constraint for gene understanding. Such information provides us with the intuition that genes in a group probably result in similar phenotypes. The model not only allows us to achieve a high-grade prediction performance, but also helps us to learn interpretable representation of genes and phenotypes simultaneously to facilitate future biological analysis. Experimental results on biological gene-phenotype association datasets of mouse and human demonstrate that GC[Formula: see text]NMF can obtain superior prediction accuracy and good understandability for biological explanation over other state-of-the-arts methods.

Task-Relevant Information Modulates Primary Motor Cortex Activity Before Movement Onset.

PubMed

Calderon, Cristian B; Van Opstal, Filip; Peigneux, Philippe; Verguts, Tom; Gevers, Wim

2018-01-01

Monkey neurophysiology research supports the affordance competition hypothesis (ACH) proposing that cognitive information useful for action selection is integrated in sensorimotor areas. In this view, action selection would emerge from the simultaneous representation of competing action plans, in parallel biased by relevant task factors. This biased competition would take place up to primary motor cortex (M1). Although ACH is plausible in environments affording choices between actions, its relevance for human decision making is less clear. To address this issue, we designed an functional magnetic resonance imaging (fMRI) experiment modeled after monkey neurophysiology studies in which human participants processed cues conveying predictive information about upcoming button presses. Our results demonstrate that, as predicted by the ACH, predictive information (i.e., the relevant task factor) biases activity of primary motor regions. Specifically, first, activity before movement onset in contralateral M1 increases as the competition is biased in favor of a specific button press relative to activity in ipsilateral M1. Second, motor regions were more tightly coupled with fronto-parietal regions when competition between potential actions was high, again suggesting that motor regions are also part of the biased competition network. Our findings support the idea that action planning dynamics as proposed in the ACH are valid both in human and non-human primates.

SENSITIVITY ANALYSIS AND EVALUATION OF MICROFACPM: A MICROSCALE MOTOR VEHICLE EMISSION FACTOR MODEL FOR PARTICULATE MATTER EMISSIONS

EPA Science Inventory

A microscale emission factor model (MicroFacPM) for predicting real-time site-specific motor vehicle particulate matter emissions was presented in the companion paper entitled "Development of a Microscale Emission Factor Model for Particulate Matter (MicroFacPM) for Predicting Re...

Discriminative value of FRAX for fracture prediction in a cohort of Chinese postmenopausal women.

PubMed

Cheung, E Y N; Bow, C H; Cheung, C L; Soong, C; Yeung, S; Loong, C; Kung, A

2012-03-01

We followed 2,266 postmenopausal Chinese women for 4.5 years to determine which model best predicts osteoporotic fracture. A model that contains ethnic-specific risk factors, some of which reflect frailty, performed as well as or better than the well-established FRAX model. Clinical risk assessment, with or without T-score, can predict fractures in Chinese postmenopausal women although it is unknown which combination of clinical risk factors is most effective. This prospective study sought to compare the accuracy for fracture prediction using various models including FRAX, our ethnic-specific clinical risk factors (CRF) and other simple models. This study is part of the Hong Kong Osteoporosis Study. A total of 2,266 treatment naïve postmenopausal women underwent clinical risk factor and bone mineral density assessment. Subjects were followed up for outcome of major osteoporotic fracture and receiver operating characteristic (ROC) curves for different models were compared. The percentage of subjects in different quartiles of risk according to various models who actually fractured was also compared. The mean age at baseline was 62.1 ± 8.5 years and mean follow-up time was 4.5 ± 2.8 years. A total of 106 new major osteoporotic fractures were reported, of which 21 were hip fractures. Ethnic-specific CRF with T-score performed better than FRAX with T-score (based on both Chinese normative and National Health and Nutrition Examination Survey (NHANES) databases) in terms of AUC comparison for prediction of major osteoporotic fracture. The two models were similar in hip fracture prediction. The ethnic-specific CRF model had a 10% higher sensitivity than FRAX at a specificity of 0.8 or above. CRF related to frailty and differences in lifestyle between populations are likely to be important in fracture prediction. Further work is required to determine which and how CRF can be applied to develop a fracture prediction model in our population.

The Future of Medical Dosimetry

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

Adams, Robert D., E-mail: robert_adams@med.unc.edu

2015-07-01

The world of health care delivery is becoming increasingly complex. The purpose of this manuscript is to analyze current metrics and analytically predict future practices and principles of medical dosimetry. The results indicate five potential areas precipitating change factors: a) evolutionary and revolutionary thinking processes, b) social factors, c) economic factors, d) political factors, and e) technological factors. Outcomes indicate that significant changes will occur in the job structure and content of being a practicing medical dosimetrist. Discussion indicates potential variables that can occur within each process and change factor and how the predicted outcomes can deviate from normative values.more » Finally, based on predicted outcomes, future opportunities for medical dosimetrists are given.« less

Acute stress alters transcript expression pattern and reduces processing of proBDNF to mature BDNF in Dicentrarchus labrax

PubMed Central

2010-01-01

Background Stress involves alterations of brain functioning that may precipitate to mood disorders. The neurotrophin Brain Derived Neurotrophic Factor (BDNF) has recently been involved in stress-induced adaptation. BDNF is a key regulator of neuronal plasticity and adaptive processes. Regulation of BDNF is complex and may reflect not only stress-specific mechanisms but also hormonal and emotional responses. For this reason we used, as an animal model of stress, a fish whose brain organization is very similar to that of higher vertebrates, but is generally considered free of emotional reactions. Results We provide a comprehensive characterization of BDNF gene in the Dicentrarchus labrax and its transcriptional, translational and post-translational regulation following acute stress. While total BDNF mRNA levels are unchanged, BDNF transcripts 1c and 1d resulted down regulated after acute stress. Acute stress induces also a significant increase in proBDNF levels and reduction in mature BDNF suggesting altered regulation of proBDNF proteolytic processing. Notably, we provide here the first evidence that fishes possess a simplified proteolytic regulation of BDNF since the pro28Kda form, generated by the SKI-1 protease in mammals, is absent in fishes because the cleavage site has first emerged in reptilians. Finally, we show that the proBDNF/totBDNF ratio is a highly predictive novel quantitative biomarker to detect stress in fishes with sensitivity = 100%, specificity = 87%, and Negative Predictive Value = 100%. Conclusion The high predictivity of proBDNF/totBDNF ratio for stress in lower vertebrates indicates that processing of BDNF is a central mechanism in adaptation to stress and predicts that a similar regulation of pro/mature BDNF has likely been conserved throughout evolution of vertebrates from fish to man. PMID:20074340

Acute stress alters transcript expression pattern and reduces processing of proBDNF to mature BDNF in Dicentrarchus labrax.

PubMed

Tognoli, Chiara; Rossi, Federica; Di Cola, Francesco; Baj, Gabriele; Tongiorgi, Enrico; Terova, Genciana; Saroglia, Marco; Bernardini, Giovanni; Gornati, Rosalba

2010-01-14

Stress involves alterations of brain functioning that may precipitate to mood disorders. The neurotrophin Brain Derived Neurotrophic Factor (BDNF) has recently been involved in stress-induced adaptation. BDNF is a key regulator of neuronal plasticity and adaptive processes. Regulation of BDNF is complex and may reflect not only stress-specific mechanisms but also hormonal and emotional responses. For this reason we used, as an animal model of stress, a fish whose brain organization is very similar to that of higher vertebrates, but is generally considered free of emotional reactions. We provide a comprehensive characterization of BDNF gene in the Dicentrarchus labrax and its transcriptional, translational and post-translational regulation following acute stress. While total BDNF mRNA levels are unchanged, BDNF transcripts 1c and 1d resulted down regulated after acute stress. Acute stress induces also a significant increase in proBDNF levels and reduction in mature BDNF suggesting altered regulation of proBDNF proteolytic processing. Notably, we provide here the first evidence that fishes possess a simplified proteolytic regulation of BDNF since the pro28Kda form, generated by the SKI-1 protease in mammals, is absent in fishes because the cleavage site has first emerged in reptilians. Finally, we show that the proBDNF/totBDNF ratio is a highly predictive novel quantitative biomarker to detect stress in fishes with sensitivity = 100%, specificity = 87%, and Negative Predictive Value = 100%. The high predictivity of proBDNF/totBDNF ratio for stress in lower vertebrates indicates that processing of BDNF is a central mechanism in adaptation to stress and predicts that a similar regulation of pro/mature BDNF has likely been conserved throughout evolution of vertebrates from fish to man.

Exploring Cognitive Relations Between Prediction in Language and Music.

PubMed

Patel, Aniruddh D; Morgan, Emily

2017-03-01

The online processing of both music and language involves making predictions about upcoming material, but the relationship between prediction in these two domains is not well understood. Electrophysiological methods for studying individual differences in prediction in language processing have opened the door to new questions. Specifically, we ask whether individuals with musical training predict upcoming linguistic material more strongly and/or more accurately than non-musicians. We propose two reasons why prediction in these two domains might be linked: (a) Musicians may have greater verbal short-term/working memory; (b) music may specifically reward predictions based on hierarchical structure. We provide suggestions as to how to expand upon recent work on individual differences in language processing to test these hypotheses. Copyright © 2016 Cognitive Science Society, Inc.

Effectiveness of the GoCheck Kids Vision Screener in Detecting Amblyopia Risk Factors.

PubMed

Peterseim, M Millicent W; Rhodes, Ryan S; Patel, Rupa N; Wilson, M Edward; Edmondson, Luke E; Logan, Sarah A; Cheeseman, Edward W; Shortridge, Emily; Trivedi, Rupal H

2018-03-01

The GoCheck Kids smartphone photoscreening app (Gobiquity Mobile Health, Scottsdale, Arizona, USA), introduced in 2014, is marketed to pediatricians with little published validation. We wished to evaluate the GoCheck Kids Screener for accuracy in detecting amblyopia risk factors (ARF) using 2013 American Association for Pediatric Ophthalmology and Strabismus guidelines. Validity assessment. Children 6 months to 6 years of age presenting from October 2016 to August 2017 were included. Children were screened with the GoCheck preloaded Nokia Lumia 1020, software version 4.6 with image processing version R4d, prior to undergoing a comprehensive eye examination by a pediatric ophthalmologist masked to the screener results. Determination of the presence of age-specific ARF was made based upon the examination and compared with the GoCheck recommendation. A total of 206 children were included (average age 43 months). When compared to examination, GoCheck had a sensitivity of 76.0% and specificity of 67.2% in detecting ARF. Positive predictive value was 57.0% and negative predictive value 83.0%. The screener results of 13 children were changed from "no risk factors" to "risk factors identified" based on the GoCheck remote review process. Four images remained "not gradable" and screening was unsuccessful in 3 children. In our high-risk population, this version of the Gocheck Kids smartphone app was useful in identifying ARF in children who are often not able to cooperate with visual acuity testing. This study informs pediatricians about the efficacy of this new screener as they make decisions about how to best detect vision problems in young children. Copyright © 2018 Elsevier Inc. All rights reserved.

P-class pentatricopeptide repeat proteins are required for efficient 5′ end formation of plant mitochondrial transcripts

PubMed Central

Binder, Stefan; Stoll, Katrin; Stoll, Birgit

2013-01-01

It is well recognized that flowering plants maintain a particularly broad spectrum of factors to support gene expression in mitochondria. Many of these factors are pentatricopeptide repeat (PPR) proteins that participate in virtually all processes dealing with RNA. One of these processes is the post-transcriptional generation of mature 5′ termini of RNA. Several PPR proteins are required for efficient 5′ maturation of mitochondrial mRNA and rRNA. These so-called RNA PROCESSING FACTORs (RPF) exclusively represent P-class PPR proteins, mainly composed of canonical PPR motifs without any extra domains. Applying the recent PPR-nucleotide recognition code, binding sites of RPF are predicted on the 5′ leader sequences. The sequence-specific interaction of an RPF with one or a few RNA substrates probably directly or indirectly recruits an as-yet-unidentified endonuclease to the processing site(s). The identification and characterization of RPF is a major step toward the understanding of the role of 5′ end maturation in flowering plant mitochondria. PMID:24184847

Modelling oxygen transfer using dynamic alpha factors.

PubMed

Jiang, Lu-Man; Garrido-Baserba, Manel; Nolasco, Daniel; Al-Omari, Ahmed; DeClippeleir, Haydee; Murthy, Sudhir; Rosso, Diego

2017-11-01

Due to the importance of wastewater aeration in meeting treatment requirements and due to its elevated energy intensity, it is important to describe the real nature of an aeration system to improve design and specification, performance prediction, energy consumption, and process sustainability. Because organic loadings drive aeration efficiency to its lowest value when the oxygen demand (energy) is the highest, the implications of considering their dynamic nature on energy costs are of utmost importance. A dynamic model aimed at identifying conservation opportunities is presented. The model developed describes the correlation between the COD concentration and the α factor in activated sludge. Using the proposed model, the aeration efficiency is calculated as a function of the organic loading (i.e. COD). This results in predictions of oxygen transfer values that are more realistic than the traditional method of assuming constant α values. The model was applied to two water resource recovery facilities, and was calibrated and validated with time-sensitive databases. Our improved aeration model structure increases the quality of prediction of field data through the recognition of the dynamic nature of the alpha factor (α) as a function of the applied oxygen demand. For the cases presented herein, the model prediction of airflow improved by 20-35% when dynamic α is used. The proposed model offers a quantitative tool for the prediction of energy demand and for minimizing aeration design uncertainty. Copyright © 2017 Elsevier Ltd. All rights reserved.

Job stress models for predicting burnout syndrome: a review.

PubMed

Chirico, Francesco

2016-01-01

In Europe, the Council Directive 89/391 for improvement of workers' safety and health has emphasized the importance of addressing all occupational risk factors, and hence also psychosocial and organizational risk factors. Nevertheless, the construct of "work-related stress" elaborated from EU-OSHA is not totally corresponding with the "psychosocial" risk, that is a broader category of risk, comprising various and different psychosocial risk factors. The term "burnout", without any binding definition, tries to integrate symptoms as well as cause of the burnout process. In Europe, the most important methods developed for the work related stress risk assessment are based on the Cox's transactional model of job stress. Nevertheless, there are more specific models for predicting burnout syndrome. This literature review provides an overview of job burnout, highlighting the most important models of job burnout, such as the Job Strain, the Effort/Reward Imbalance and the Job Demands-Resources models. The difference between these models and the Cox's model of job stress is explored.

Bifactor latent structure of attention-deficit/hyperactivity disorder (ADHD)/oppositional defiant disorder (ODD) symptoms and first-order latent structure of sluggish cognitive tempo symptoms.

PubMed

Lee, SoYean; Burns, G Leonard; Beauchaine, Theodore P; Becker, Stephen P

2016-08-01

The objective was to determine if the latent structure of attention-deficit/hyperactivity disorder (ADHD) and oppositional defiant disorder (ODD) symptoms is best explained by a general disruptive behavior factor along with specific inattention (IN), hyperactivity/impulsivity (HI), and ODD factors (a bifactor model) whereas the latent structure of sluggish cognitive tempo (SCT) symptoms is best explained by a first-order factor independent of the bifactor model of ADHD/ODD. Parents' (n = 703) and teachers' (n = 366) ratings of SCT, ADHD-IN, ADHD-HI, and ODD symptoms on the Child and Adolescent Disruptive Behavior Inventory (CADBI) in a community sample of children (ages 5-13; 55% girls) were used to evaluate 4 models of symptom organization. Results indicated that a bifactor model of ADHD/ODD symptoms, in conjunction with a separate first-order SCT factor, was the best model for both parent and teacher ratings. The first-order SCT factor showed discriminant validity with the general disruptive behavior and specific IN factors in the bifactor model. In addition, higher scores on the SCT factor predicted greater academic and social impairment, even after controlling for the general disruptive behavior and 3 specific factors. Consistent with predictions from the trait-impulsivity etiological model of externalizing liability, a single, general disruptive behavior factor accounted for nearly all common variance in ADHD/ODD symptoms, whereas SCT symptoms represented a factor different from the general disruptive behavior and specific IN factor. These results provide additional support for distinguishing between SCT and ADHD-IN. The study also demonstrates how etiological models can be used to predict specific latent structures of symptom organization. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Confidence in memory and other cognitive processes in obsessive-compulsive disorder.

PubMed

Nedeljkovic, Maja; Kyrios, Michael

2007-12-01

Previous studies have implicated beliefs about one's memory (i.e., meta-memory), in maintaining the symptoms of obsessive-compulsive disorder (OCD), particularly with respect to checking rituals. However, most research has focused on task- or situation-specific perceptions about memory performance. Expanding on this research, we undertook two studies with analogue and clinical cohorts to examine the relationship between general 'trait' beliefs about memory and related processes and OCD symptoms. Trait meta-memory as measured in the current study was conceptualised as a multi-dimensional construct encompassing a range of beliefs about memory and related processes including confidence in one's general memory abilities, decision-making abilities, concentration and attention, as well as perfectionistic standards regarding one's memory. Meta-memory factors were associated with OCD symptoms, predicting OCD symptoms over-and-above mood and other OCD-relevant cognitions. Meta-memory factors were found to be particularly relevant to checking symptoms. Implications for theory and research are discussed.

Building a Bridge into the Future: Dynamic Connectionist Modeling as an Integrative Tool for Research on Intertemporal Choice

PubMed Central

Scherbaum, Stefan; Dshemuchadse, Maja; Goschke, Thomas

2012-01-01

Temporal discounting denotes the fact that individuals prefer smaller rewards delivered sooner over larger rewards delivered later, often to a higher extent than suggested by normative economical theories. In this article, we identify three lines of research studying this phenomenon which aim (i) to describe temporal discounting mathematically, (ii) to explain observed choice behavior psychologically, and (iii) to predict the influence of specific factors on intertemporal decisions. We then opt for an approach integrating postulated mechanisms and empirical findings from these three lines of research. Our approach focuses on the dynamical properties of decision processes and is based on computational modeling. We present a dynamic connectionist model of intertemporal choice focusing on the role of self-control and time framing as two central factors determining choice behavior. Results of our simulations indicate that the two influences interact with each other, and we present experimental data supporting this prediction. We conclude that computational modeling of the decision process dynamics can advance the integration of different strands of research in intertemporal choice. PMID:23181048

Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) Core Measures: Psychosocial Domain.

PubMed

Sutin, Angelina R; Boutelle, Kerri; Czajkowski, Susan M; Epel, Elissa S; Green, Paige A; Hunter, Christine M; Rice, Elise L; Williams, David M; Young-Hyman, Deborah; Rothman, Alexander J

2018-04-01

Within the Accumulating Data to Optimally Predict obesity Treatment (ADOPT) Core Measures Project, the psychosocial domain addresses how psychosocial processes underlie the influence of obesity treatment strategies on weight loss and weight maintenance. The subgroup for the psychosocial domain identified an initial list of high-priority constructs and measures that ranged from relatively stable characteristics about the person (cognitive function, personality) to dynamic characteristics that may change over time (motivation, affect). This paper describes (a) how the psychosocial domain fits into the broader model of weight loss and weight maintenance as conceptualized by ADOPT; (b) the guiding principles used to select constructs and measures for recommendation; (c) the high-priority constructs recommended for inclusion; (d) domain-specific issues for advancing the science; and (e) recommendations for future research. The inclusion of similar measures across trials will help to better identify how psychosocial factors mediate and moderate the weight loss and weight maintenance process, facilitate research into dynamic interactions with factors in the other ADOPT domains, and ultimately improve the design and delivery of effective interventions. © 2018 The Obesity Society.

Building a bridge into the future: dynamic connectionist modeling as an integrative tool for research on intertemporal choice.

PubMed

Scherbaum, Stefan; Dshemuchadse, Maja; Goschke, Thomas

2012-01-01

Temporal discounting denotes the fact that individuals prefer smaller rewards delivered sooner over larger rewards delivered later, often to a higher extent than suggested by normative economical theories. In this article, we identify three lines of research studying this phenomenon which aim (i) to describe temporal discounting mathematically, (ii) to explain observed choice behavior psychologically, and (iii) to predict the influence of specific factors on intertemporal decisions. We then opt for an approach integrating postulated mechanisms and empirical findings from these three lines of research. Our approach focuses on the dynamical properties of decision processes and is based on computational modeling. We present a dynamic connectionist model of intertemporal choice focusing on the role of self-control and time framing as two central factors determining choice behavior. Results of our simulations indicate that the two influences interact with each other, and we present experimental data supporting this prediction. We conclude that computational modeling of the decision process dynamics can advance the integration of different strands of research in intertemporal choice.

Mapping Frequency-Specific Tone Predictions in the Human Auditory Cortex at High Spatial Resolution.

PubMed

Berlot, Eva; Formisano, Elia; De Martino, Federico

2018-05-23

Auditory inputs reaching our ears are often incomplete, but our brains nevertheless transform them into rich and complete perceptual phenomena such as meaningful conversations or pleasurable music. It has been hypothesized that our brains extract regularities in inputs, which enables us to predict the upcoming stimuli, leading to efficient sensory processing. However, it is unclear whether tone predictions are encoded with similar specificity as perceived signals. Here, we used high-field fMRI to investigate whether human auditory regions encode one of the most defining characteristics of auditory perception: the frequency of predicted tones. Two pairs of tone sequences were presented in ascending or descending directions, with the last tone omitted in half of the trials. Every pair of incomplete sequences contained identical sounds, but was associated with different expectations about the last tone (a high- or low-frequency target). This allowed us to disambiguate predictive signaling from sensory-driven processing. We recorded fMRI responses from eight female participants during passive listening to complete and incomplete sequences. Inspection of specificity and spatial patterns of responses revealed that target frequencies were encoded similarly during their presentations, as well as during omissions, suggesting frequency-specific encoding of predicted tones in the auditory cortex (AC). Importantly, frequency specificity of predictive signaling was observed already at the earliest levels of auditory cortical hierarchy: in the primary AC. Our findings provide evidence for content-specific predictive processing starting at the earliest cortical levels. SIGNIFICANCE STATEMENT Given the abundance of sensory information around us in any given moment, it has been proposed that our brain uses contextual information to prioritize and form predictions about incoming signals. However, there remains a surprising lack of understanding of the specificity and content of such prediction signaling; for example, whether a predicted tone is encoded with similar specificity as a perceived tone. Here, we show that early auditory regions encode the frequency of a tone that is predicted yet omitted. Our findings contribute to the understanding of how expectations shape sound processing in the human auditory cortex and provide further insights into how contextual information influences computations in neuronal circuits. Copyright © 2018 the authors 0270-6474/18/384934-09$15.00/0.

Lifestyle and Genetic Predictors of Stiffness Index in Community-dwelling Elderly Korean Men and Women.

PubMed

Park, Kyung-Ae; Park, Yeon-Hwan; Suh, Min-Hee; Choi-Kwon, Smi

2015-09-01

Differing lifestyle, nutritional, and genetic factors may lead to a differing stiffness index (SI) determined by quantitative ultrasound in elderly men and women. The purpose of this study was to determine SI and the gender-specific factors associated with low SI in a Korean elderly cohort. This was a cross-sectional descriptive study identifying the gender-specific factors related to SI in 252 men and women aged 65 years and greater from local senior centers in Seoul, Korea between January and February 2009. The mean SI of elderly men was significantly higher than that of the women's. A multiple regression analysis reveals that age, nutritional status, and physical activity were predictive factors of lower SI in men, whereas age, alcohol consumption, educational level, and genetic polymorphism were predictive factors for elderly women. Low SI was common in both elderly men and women. We found gender differences in factors linked to low SI. In multiple regression analysis, nutritional status and physical activity were more important factors in men, whereas alcohol consumption, educational level, and genetic polymorphism were significant factors predicting low SI in women. Gender-specific modifiable risk factors associated with low SI should be considered when developing osteoporosis prevention programs for the elderly. Copyright © 2015. Published by Elsevier B.V.

Interpretation bias and anxiety in childhood: stability, specificity and longitudinal associations.

PubMed

Creswell, Cathy; O'Connor, Thomas G

2011-03-01

Biases in the interpretation of ambiguous material are central to cognitive models of anxiety; however, understanding of the association between interpretation and anxiety in childhood is limited. To address this, a prospective investigation of the stability and specificity of anxious cognitions and anxiety and the relationship between these factors was conducted. Sixty-five children (10-11 years) from a community sample completed measures of self-reported anxiety, depression, and conduct problems, and responded to ambiguous stories at three time points over one-year. Individual differences in biases in interpretation of ambiguity (specifically "anticipated distress" and "threat interpretation") were stable over time. Furthermore, anticipated distress and threat interpretation were specifically associated with anxiety symptoms. Distress anticipation predicted change in anxiety symptoms over time. In contrast, anxiety scores predicted change in threat interpretation over time. The results suggest that different cognitive constructs may show different longitudinal links with anxiety. These preliminary findings extend research and theory on anxious cognitions and their link with anxiety in children, and suggest that these cognitive processes may be valuable targets for assessment and intervention.

The impact of neighborhood disadvantage and exposure to violence on self-report of antisocial behavior among girls in the juvenile justice system.

PubMed

Chauhan, Preeti; Reppucci, N Dickon

2009-03-01

The current study extended previous research with adults and boys to girls in the juvenile justice system (N = 122; M = 16.7; SD = 1.3). Using a longitudinal research design, neighborhood disadvantage and exposure to violence (i.e., physical abuse by parents, physical abuse by peers, and witnessing violence) were assessed during incarceration. These risk factors were used to predict violent and delinquent behavior post-release. Furthermore, race specific pathways were examined to determine if the impact of these risk factors varied among Black (n = 69) and White girls (n = 53). Results indicated that Black girls were more likely than White girls to live in disadvantaged neighborhoods, but both reported similar levels of exposure to violence and self-report of antisocial behavior. Physical abuse by parents, time at risk, and age were related to violent behavior, while witnessing violence and time at risk were related to delinquent behavior. Multiple group analyses indicated the existence of race specific pathways. Specifically, physical abuse by parents was related to violent behavior for White girls while witnessing violence was related to violent and delinquent behaviors for Black girls. Results suggest that contextual processes play an important role in predicting antisocial behavior for Black girls.

What is interesting? Exploring the appraisal structure of interest.

PubMed

Silvia, Paul J

2005-03-01

Relative to other emotions, interest is poorly understood. On the basis of theories of appraisal process and structure, it was predicted that interest consists of appraisals of novelty (factors related to unfamiliarity and complexity) and appraisals of coping potential (the ability to understand the new, complex thing). Four experiments, using in vivo rather than retrospective methods, supported this appraisal structure. The findings were general across measured and manipulated appraisals, interesting stimuli (random polygons, visual art, poetry), and measures of interest (self-reports, forced-choice, behavioral measures). Furthermore, the appraisal structure was specific to interest (it did not predict enjoyment, a related positive emotion), and appraisals predicted interest beyond relevant traits (curiosity, openness). The appraisal perspective offers a powerful way of construing the causes of interest. Copyright 2005 APA, all rights reserved.

Describing and Predicting Developmental Profiles of Externalizing Problems from Childhood to Adulthood

PubMed Central

Petersen, Isaac T.; Bates, John E.; Dodge, Kenneth A.; Lansford, Jennifer E.; Pettit, Gregory S.

2014-01-01

This longitudinal study considers externalizing behavior problems from ages 5 to 27 (N = 585). Externalizing problem ratings by mothers, fathers, teachers, peers, and self-report were modeled with growth curves. Risk and protective factors across many different domains and time frames were included as predictors of the trajectories. A major contribution of the study is in demonstrating how heterotypic continuity and changing measures can be handled in modeling changes in externalizing behavior over long developmental periods. On average, externalizing problems decreased from early childhood to preadolescence, increased during adolescence, and decreased from late adolescence to adulthood. There was strong nonlinear continuity in externalizing problems over time. Family process, peer process, stress, and individual characteristics predicted externalizing problems beyond the strong continuity of externalizing problems. The model accounted for 70% of the variability in the development of externalizing problems. The model’s predicted values showed moderate sensitivity and specificity in prediction of arrests, illegal drug use, and drunk driving. Overall, the study showed that by using changing, developmentally-relevant measures and simultaneously taking into account numerous characteristics of children and their living situations, research can model lengthy spans of development and improve predictions of the development of later, severe externalizing problems. PMID:25166430

Benefits of fidelity: does host specialization impact nematode parasite life history and fecundity?

PubMed

Koprivnikar, J; Randhawa, H S

2013-04-01

The range of hosts used by a parasite is influenced by macro-evolutionary processes (host switching, host-parasite co-evolution), as well as 'encounter filters' and 'compatibility filters' at the micro-evolutionary level driven by host/parasite ecology and physiology. Host specialization is hypothesized to result in trade-offs with aspects of parasite life history (e.g. reproductive output), but these have not been well studied. We used previously published data to create models examining general relationships among host specificity and important aspects of life history and reproduction for nematodes parasitizing animals. Our results indicate no general trade-off between host specificity and the average pre-patent period (time to first reproduction), female size, egg size, or fecundity of these nematodes. However, female size was positively related to egg size, fecundity, and pre-patent period. Host compatibility may thus not be the primary determinant of specificity in these parasitic nematodes if there are few apparent trade-offs with reproduction, but rather, the encounter opportunities for new host species at the micro-evolutionary level, and other processes at the macro-evolutionary level (i.e. phylogeny). Because host specificity is recognized as a key factor determining the spread of parasitic diseases understanding factors limiting host use are essential to predict future changes in parasite range and occurrence.

Personality traits as risk factors of depression and anxiety among Japanese students.

PubMed

Matsudaira, Tomomi; Kitamura, Toshinori

2006-01-01

The aim of this study is to examine the effects of personality (temperament and character) on specific depression and specific anxiety. A total of 541 Japanese undergraduates were investigated by using the Temperament and Character Inventory (TCI) and the Hospital Anxiety and Depression (HAD) scale. Hierarchical multiple regression analyses demonstrated that specific depression was predicted by lower Reward-Dependence, Persistence, Self-Directedness, Cooperativeness, and Self-Transcendence; specific anxiety was predicted by higher Novelty-Seeking, Harm-Avoidance, Persistence, and Self-Transcendence, and lower Self-Directedness. Immaturity of Self-Directedness is a risk factor for negative affectivity. Immaturity of all character dimensions is a risk factor for specific depression. The relationship between Harm-Avoidance and depression in previous studies may be linked partly to somatic symptoms that were deliberately eliminated in the HAD scale.

Predicting Incursion of Plant Invaders into Kruger National Park, South Africa: The Interplay of General Drivers and Species-Specific Factors

PubMed Central

Jarošík, Vojtěch; Pyšek, Petr; Foxcroft, Llewellyn C.; Richardson, David M.; Rouget, Mathieu; MacFadyen, Sandra

2011-01-01

Background Overcoming boundaries is crucial for incursion of alien plant species and their successful naturalization and invasion within protected areas. Previous work showed that in Kruger National Park, South Africa, this process can be quantified and that factors determining the incursion of invasive species can be identified and predicted confidently. Here we explore the similarity between determinants of incursions identified by the general model based on a multispecies assemblage, and those identified by species-specific models. We analyzed the presence and absence of six invasive plant species in 1.0×1.5 km segments along the border of the park as a function of environmental characteristics from outside and inside the KNP boundary, using two data-mining techniques: classification trees and random forests. Principal Findings The occurrence of Ageratum houstonianum, Chromolaena odorata, Xanthium strumarium, Argemone ochroleuca, Opuntia stricta and Lantana camara can be reliably predicted based on landscape characteristics identified by the general multispecies model, namely water runoff from surrounding watersheds and road density in a 10 km radius. The presence of main rivers and species-specific combinations of vegetation types are reliable predictors from inside the park. Conclusions The predictors from the outside and inside of the park are complementary, and are approximately equally reliable for explaining the presence/absence of current invaders; those from the inside are, however, more reliable for predicting future invasions. Landscape characteristics determined as crucial predictors from outside the KNP serve as guidelines for management to enact proactive interventions to manipulate landscape features near the KNP to prevent further incursions. Predictors from the inside the KNP can be used reliably to identify high-risk areas to improve the cost-effectiveness of management, to locate invasive plants and target them for eradication. PMID:22194893

Predicting incursion of plant invaders into Kruger National Park, South Africa: the interplay of general drivers and species-specific factors.

PubMed

Jarošík, Vojtěch; Pyšek, Petr; Foxcroft, Llewellyn C; Richardson, David M; Rouget, Mathieu; MacFadyen, Sandra

2011-01-01

Overcoming boundaries is crucial for incursion of alien plant species and their successful naturalization and invasion within protected areas. Previous work showed that in Kruger National Park, South Africa, this process can be quantified and that factors determining the incursion of invasive species can be identified and predicted confidently. Here we explore the similarity between determinants of incursions identified by the general model based on a multispecies assemblage, and those identified by species-specific models. We analyzed the presence and absence of six invasive plant species in 1.0×1.5 km segments along the border of the park as a function of environmental characteristics from outside and inside the KNP boundary, using two data-mining techniques: classification trees and random forests. The occurrence of Ageratum houstonianum, Chromolaena odorata, Xanthium strumarium, Argemone ochroleuca, Opuntia stricta and Lantana camara can be reliably predicted based on landscape characteristics identified by the general multispecies model, namely water runoff from surrounding watersheds and road density in a 10 km radius. The presence of main rivers and species-specific combinations of vegetation types are reliable predictors from inside the park. The predictors from the outside and inside of the park are complementary, and are approximately equally reliable for explaining the presence/absence of current invaders; those from the inside are, however, more reliable for predicting future invasions. Landscape characteristics determined as crucial predictors from outside the KNP serve as guidelines for management to enact proactive interventions to manipulate landscape features near the KNP to prevent further incursions. Predictors from the inside the KNP can be used reliably to identify high-risk areas to improve the cost-effectiveness of management, to locate invasive plants and target them for eradication.

Testing the Sensory Drive Hypothesis: Geographic variation in echolocation frequencies of Geoffroy's horseshoe bat (Rhinolophidae: Rhinolophus clivosus)

PubMed Central

Catto, Sarah; Mutumi, Gregory L.; Finger, Nikita; Webala, Paul W.

2017-01-01

Geographic variation in sensory traits is usually influenced by adaptive processes because these traits are involved in crucial life-history aspects including orientation, communication, lineage recognition and mate choice. Studying this variation can therefore provide insights into lineage diversification. According to the Sensory Drive Hypothesis, lineage diversification may be driven by adaptation of sensory systems to local environments. It predicts that acoustic signals vary in association with local climatic conditions so that atmospheric attenuation is minimized and transmission of the signals maximized. To test this prediction, we investigated the influence of climatic factors (specifically relative humidity and temperature) on geographic variation in the resting frequencies of the echolocation pulses of Geoffroy’s horseshoe bat, Rhinolophus clivosus. If the evolution of phenotypic variation in this lineage tracks climate variation, human induced climate change may lead to decreases in detection volumes and a reduction in foraging efficiency. A complex non-linear interaction between relative humidity and temperature affects atmospheric attenuation of sound and principal components composed of these correlated variables were, therefore, used in a linear mixed effects model to assess their contribution to observed variation in resting frequencies. A principal component composed predominantly of mean annual temperature (factor loading of -0.8455) significantly explained a proportion of the variation in resting frequency across sites (P < 0.05). Specifically, at higher relative humidity (around 60%) prevalent across the distribution of R. clivosus, increasing temperature had a strong negative effect on resting frequency. Climatic factors thus strongly influence acoustic signal divergence in this lineage, supporting the prediction of the Sensory Drive Hypothesis. The predicted future increase in temperature due to climate change is likely to decrease the detection volume in echolocating bats and adversely impact their foraging efficiency. PMID:29186147

Testing the Sensory Drive Hypothesis: Geographic variation in echolocation frequencies of Geoffroy's horseshoe bat (Rhinolophidae: Rhinolophus clivosus).

PubMed

Jacobs, David S; Catto, Sarah; Mutumi, Gregory L; Finger, Nikita; Webala, Paul W

2017-01-01

Geographic variation in sensory traits is usually influenced by adaptive processes because these traits are involved in crucial life-history aspects including orientation, communication, lineage recognition and mate choice. Studying this variation can therefore provide insights into lineage diversification. According to the Sensory Drive Hypothesis, lineage diversification may be driven by adaptation of sensory systems to local environments. It predicts that acoustic signals vary in association with local climatic conditions so that atmospheric attenuation is minimized and transmission of the signals maximized. To test this prediction, we investigated the influence of climatic factors (specifically relative humidity and temperature) on geographic variation in the resting frequencies of the echolocation pulses of Geoffroy's horseshoe bat, Rhinolophus clivosus. If the evolution of phenotypic variation in this lineage tracks climate variation, human induced climate change may lead to decreases in detection volumes and a reduction in foraging efficiency. A complex non-linear interaction between relative humidity and temperature affects atmospheric attenuation of sound and principal components composed of these correlated variables were, therefore, used in a linear mixed effects model to assess their contribution to observed variation in resting frequencies. A principal component composed predominantly of mean annual temperature (factor loading of -0.8455) significantly explained a proportion of the variation in resting frequency across sites (P < 0.05). Specifically, at higher relative humidity (around 60%) prevalent across the distribution of R. clivosus, increasing temperature had a strong negative effect on resting frequency. Climatic factors thus strongly influence acoustic signal divergence in this lineage, supporting the prediction of the Sensory Drive Hypothesis. The predicted future increase in temperature due to climate change is likely to decrease the detection volume in echolocating bats and adversely impact their foraging efficiency.

Cortical region-specific sleep homeostasis in mice: effects of time of day and waking experience.

PubMed

Guillaumin, Mathilde C C; McKillop, Laura E; Cui, Nanyi; Fisher, Simon P; Foster, Russell G; de Vos, Maarten; Peirson, Stuart N; Achermann, Peter; Vyazovskiy, Vladyslav V

2018-04-25

Sleep-wake history, wake behaviours, lighting conditions and circadian time influence sleep, but neither their relative contribution, nor the underlying mechanisms are fully understood. The dynamics of EEG slow-wave activity (SWA) during sleep can be described using the two-process model, whereby the parameters of homeostatic Process S are estimated using empirical EEG SWA (0.5-4 Hz) in non-rapid eye movement sleep (NREM), and the 24-h distribution of vigilance states. We hypothesised that the influence of extrinsic factors on sleep homeostasis, such as the time of day or wake behaviour, would manifest in systematic deviations between empirical SWA and model predictions. To test this hypothesis, we performed parameter estimation and tested model predictions using NREM SWA derived from continuous EEG recordings from the frontal and occipital cortex in mice. The animals showed prolonged wake periods, followed by consolidated sleep, both during the dark and light phases, and wakefulness primarily consisted of voluntary wheel running, learning a new motor skill or novel object exploration. Simulated SWA matched empirical levels well across conditions, and neither waking experience nor time of day had a significant influence on the fit between data and simulation. However, we consistently observed that Process S declined during sleep significantly faster in the frontal than in the occipital area of the neocortex. The striking resilience of the model to specific wake behaviours, lighting conditions and time of day suggests that intrinsic factors underpinning the dynamics of Process S are robust to extrinsic influences, despite their major role in shaping the overall amount and distribution of vigilance states across 24 h.

Inferring genome-wide functional modulatory network: a case study on NF-κB/RelA transcription factor.

PubMed

Li, Xueling; Zhu, Min; Brasier, Allan R; Kudlicki, Andrzej S

2015-04-01

How different pathways lead to the activation of a specific transcription factor (TF) with specific effects is not fully understood. We model context-specific transcriptional regulation as a modulatory network: triplets composed of a TF, target gene, and modulator. Modulators usually affect the activity of a specific TF at the posttranscriptional level in a target gene-specific action mode. This action may be classified as enhancement, attenuation, or inversion of either activation or inhibition. As a case study, we inferred, from a large collection of expression profiles, all potential modulations of NF-κB/RelA. The predicted modulators include many proteins previously not reported as physically binding to RelA but with relevant functions, such as RNA processing, cell cycle, mitochondrion, ubiquitin-dependent proteolysis, and chromatin modification. Modulators from different processes exert specific prevalent action modes on distinct pathways. Modulators from noncoding RNA, RNA-binding proteins, TFs, and kinases modulate the NF-κB/RelA activity with specific action modes consistent with their molecular functions and modulation level. The modulatory networks of NF-κB/RelA in the context epithelial-mesenchymal transition (EMT) and burn injury have different modulators, including those involved in extracellular matrix (FBN1), cytoskeletal regulation (ACTN1), and metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), a long intergenic nonprotein coding RNA, and tumor suppression (FOXP1) for EMT, and TXNIP, GAPDH, PKM2, IFIT5, LDHA, NID1, and TPP1 for burn injury.

Inference of Expanded Lrp-Like Feast/Famine Transcription Factor Targets in a Non-Model Organism Using Protein Structure-Based Prediction

PubMed Central

Ashworth, Justin; Plaisier, Christopher L.; Lo, Fang Yin; Reiss, David J.; Baliga, Nitin S.

2014-01-01

Widespread microbial genome sequencing presents an opportunity to understand the gene regulatory networks of non-model organisms. This requires knowledge of the binding sites for transcription factors whose DNA-binding properties are unknown or difficult to infer. We adapted a protein structure-based method to predict the specificities and putative regulons of homologous transcription factors across diverse species. As a proof-of-concept we predicted the specificities and transcriptional target genes of divergent archaeal feast/famine regulatory proteins, several of which are encoded in the genome of Halobacterium salinarum. This was validated by comparison to experimentally determined specificities for transcription factors in distantly related extremophiles, chromatin immunoprecipitation experiments, and cis-regulatory sequence conservation across eighteen related species of halobacteria. Through this analysis we were able to infer that Halobacterium salinarum employs a divergent local trans-regulatory strategy to regulate genes (carA and carB) involved in arginine and pyrimidine metabolism, whereas Escherichia coli employs an operon. The prediction of gene regulatory binding sites using structure-based methods is useful for the inference of gene regulatory relationships in new species that are otherwise difficult to infer. PMID:25255272

Inference of expanded Lrp-like feast/famine transcription factor targets in a non-model organism using protein structure-based prediction.

PubMed

Ashworth, Justin; Plaisier, Christopher L; Lo, Fang Yin; Reiss, David J; Baliga, Nitin S

2014-01-01

Widespread microbial genome sequencing presents an opportunity to understand the gene regulatory networks of non-model organisms. This requires knowledge of the binding sites for transcription factors whose DNA-binding properties are unknown or difficult to infer. We adapted a protein structure-based method to predict the specificities and putative regulons of homologous transcription factors across diverse species. As a proof-of-concept we predicted the specificities and transcriptional target genes of divergent archaeal feast/famine regulatory proteins, several of which are encoded in the genome of Halobacterium salinarum. This was validated by comparison to experimentally determined specificities for transcription factors in distantly related extremophiles, chromatin immunoprecipitation experiments, and cis-regulatory sequence conservation across eighteen related species of halobacteria. Through this analysis we were able to infer that Halobacterium salinarum employs a divergent local trans-regulatory strategy to regulate genes (carA and carB) involved in arginine and pyrimidine metabolism, whereas Escherichia coli employs an operon. The prediction of gene regulatory binding sites using structure-based methods is useful for the inference of gene regulatory relationships in new species that are otherwise difficult to infer.

The use of patient factors to improve the prediction of operative duration using laparoscopic cholecystectomy.

PubMed

Thiels, Cornelius A; Yu, Denny; Abdelrahman, Amro M; Habermann, Elizabeth B; Hallbeck, Susan; Pasupathy, Kalyan S; Bingener, Juliane

2017-01-01

Reliable prediction of operative duration is essential for improving patient and care team satisfaction, optimizing resource utilization and reducing cost. Current operative scheduling systems are unreliable and contribute to costly over- and underestimation of operative time. We hypothesized that the inclusion of patient-specific factors would improve the accuracy in predicting operative duration. We reviewed all elective laparoscopic cholecystectomies performed at a single institution between 01/2007 and 06/2013. Concurrent procedures were excluded. Univariate analysis evaluated the effect of age, gender, BMI, ASA, laboratory values, smoking, and comorbidities on operative duration. Multivariable linear regression models were constructed using the significant factors (p < 0.05). The patient factors model was compared to the traditional surgical scheduling system estimates, which uses historical surgeon-specific and procedure-specific operative duration. External validation was done using the ACS-NSQIP database (n = 11,842). A total of 1801 laparoscopic cholecystectomy patients met inclusion criteria. Female sex was associated with reduced operative duration (-7.5 min, p < 0.001 vs. male sex) while increasing BMI (+5.1 min BMI 25-29.9, +6.9 min BMI 30-34.9, +10.4 min BMI 35-39.9, +17.0 min BMI 40 + , all p < 0.05 vs. normal BMI), increasing ASA (+7.4 min ASA III, +38.3 min ASA IV, all p < 0.01 vs. ASA I), and elevated liver function tests (+7.9 min, p < 0.01 vs. normal) were predictive of increased operative duration on univariate analysis. A model was then constructed using these predictive factors. The traditional surgical scheduling system was poorly predictive of actual operative duration (R 2  = 0.001) compared to the patient factors model (R 2  = 0.08). The model remained predictive on external validation (R 2  = 0.14).The addition of surgeon as a variable in the institutional model further improved predictive ability of the model (R 2  = 0.18). The use of routinely available pre-operative patient factors improves the prediction of operative duration during cholecystectomy.

Genome-wide analysis of the Dof transcription factor gene family reveals soybean-specific duplicable and functional characteristics.

PubMed

Guo, Yong; Qiu, Li-Juan

2013-01-01

The Dof domain protein family is a classic plant-specific zinc-finger transcription factor family involved in a variety of biological processes. There is great diversity in the number of Dof genes in different plants. However, there are only very limited reports on the characterization of Dof transcription factors in soybean (Glycine max). In the present study, 78 putative Dof genes were identified from the whole-genome sequence of soybean. The predicted GmDof genes were non-randomly distributed within and across 19 out of 20 chromosomes and 97.4% (38 pairs) were preferentially retained duplicate paralogous genes located in duplicated regions of the genome. Soybean-specific segmental duplications contributed significantly to the expansion of the soybean Dof gene family. These Dof proteins were phylogenetically clustered into nine distinct subgroups among which the gene structure and motif compositions were considerably conserved. Comparative phylogenetic analysis of these Dof proteins revealed four major groups, similar to those reported for Arabidopsis and rice. Most of the GmDofs showed specific expression patterns based on RNA-seq data analyses. The expression patterns of some duplicate genes were partially redundant while others showed functional diversity, suggesting the occurrence of sub-functionalization during subsequent evolution. Comprehensive expression profile analysis also provided insights into the soybean-specific functional divergence among members of the Dof gene family. Cis-regulatory element analysis of these GmDof genes suggested diverse functions associated with different processes. Taken together, our results provide useful information for the functional characterization of soybean Dof genes by combining phylogenetic analysis with global gene-expression profiling.

The Prioritization of Clinical Risk Factors of Obstructive Sleep Apnea Severity Using Fuzzy Analytic Hierarchy Process

PubMed Central

Maranate, Thaya; Pongpullponsak, Adisak; Ruttanaumpawan, Pimon

2015-01-01

Recently, there has been a problem of shortage of sleep laboratories that can accommodate the patients in a timely manner. Delayed diagnosis and treatment may lead to worse outcomes particularly in patients with severe obstructive sleep apnea (OSA). For this reason, the prioritization in polysomnography (PSG) queueing should be endorsed based on disease severity. To date, there have been conflicting data whether clinical information can predict OSA severity. The 1,042 suspected OSA patients underwent diagnostic PSG study at Siriraj Sleep Center during 2010-2011. A total of 113 variables were obtained from sleep questionnaires and anthropometric measurements. The 19 groups of clinical risk factors consisting of 42 variables were categorized into each OSA severity. This study aimed to array these factors by employing Fuzzy Analytic Hierarchy Process approach based on normalized weight vector. The results revealed that the first rank of clinical risk factors in Severe, Moderate, Mild, and No OSA was nighttime symptoms. The overall sensitivity/specificity of the approach to these groups was 92.32%/91.76%, 89.52%/88.18%, 91.08%/84.58%, and 96.49%/81.23%, respectively. We propose that the urgent PSG appointment should include clinical risk factors of Severe OSA group. In addition, the screening for Mild from No OSA patients in sleep center setting using symptoms during sleep is also recommended (sensitivity = 87.12% and specificity = 72.22%). PMID:26221183

Exploring Cognitive Relations between Prediction in Language and Music

ERIC Educational Resources Information Center

Patel, Aniruddh D.; Morgan, Emily

2017-01-01

The online processing of both music and language involves making predictions about upcoming material, but the relationship between prediction in these two domains is not well understood. Electrophysiological methods for studying individual differences in prediction in language processing have opened the door to new questions. Specifically, we ask…

Psychological Processes Mediate the Impact of Familial Risk, Social Circumstances and Life Events on Mental Health

PubMed Central

Kinderman, Peter; Schwannauer, Matthias; Pontin, Eleanor; Tai, Sara

2013-01-01

Background Despite widespread acceptance of the ‘biopsychosocial model’, the aetiology of mental health problems has provoked debate amongst researchers and practitioners for decades. The role of psychological factors in the development of mental health problems remains particularly contentious, and to date there has not been a large enough dataset to conduct the necessary multivariate analysis of whether psychological factors influence, or are influenced by, mental health. This study reports on the first empirical, multivariate, test of the relationships between the key elements of the biospychosocial model of mental ill-health. Methods and Findings Participants were 32,827 (age 18–85 years) self-selected respondents from the general population who completed an open-access online battery of questionnaires hosted by the BBC. An initial confirmatory factor analysis was performed to assess the adequacy of the proposed factor structure and the relationships between latent and measured variables. The predictive path model was then tested whereby the latent variables of psychological processes were positioned as mediating between the causal latent variables (biological, social and circumstantial) and the outcome latent variables of mental health problems and well-being. This revealed an excellent fit to the data, S-B χ2 (3199, N = 23,397) = 126654·8, p<·001; RCFI = ·97; RMSEA = ·04 (·038–·039). As hypothesised, a family history of mental health difficulties, social deprivation, and traumatic or abusive life-experiences all strongly predicted higher levels of anxiety and depression. However, these relationships were strongly mediated by psychological processes; specifically lack of adaptive coping, rumination and self-blame. Conclusion These results support a significant revision of the biopsychosocial model, as psychological processes determine the causal impact of biological, social, and circumstantial risk factors on mental health. This has clear implications for policy, education and clinical practice as psychological processes such as rumination and self-blame are amenable to evidence-based psychological therapies. PMID:24146890

Psychological processes mediate the impact of familial risk, social circumstances and life events on mental health.

PubMed

Kinderman, Peter; Schwannauer, Matthias; Pontin, Eleanor; Tai, Sara

2013-01-01

Despite widespread acceptance of the 'biopsychosocial model', the aetiology of mental health problems has provoked debate amongst researchers and practitioners for decades. The role of psychological factors in the development of mental health problems remains particularly contentious, and to date there has not been a large enough dataset to conduct the necessary multivariate analysis of whether psychological factors influence, or are influenced by, mental health. This study reports on the first empirical, multivariate, test of the relationships between the key elements of the biospychosocial model of mental ill-health. Participants were 32,827 (age 18-85 years) self-selected respondents from the general population who completed an open-access online battery of questionnaires hosted by the BBC. An initial confirmatory factor analysis was performed to assess the adequacy of the proposed factor structure and the relationships between latent and measured variables. The predictive path model was then tested whereby the latent variables of psychological processes were positioned as mediating between the causal latent variables (biological, social and circumstantial) and the outcome latent variables of mental health problems and well-being. This revealed an excellent fit to the data, S-B χ(2) (3199, N = 23,397) = 126654.8, p<.001; RCFI = .97; RMSEA = .04 (.038-.039). As hypothesised, a family history of mental health difficulties, social deprivation, and traumatic or abusive life-experiences all strongly predicted higher levels of anxiety and depression. However, these relationships were strongly mediated by psychological processes; specifically lack of adaptive coping, rumination and self-blame. These results support a significant revision of the biopsychosocial model, as psychological processes determine the causal impact of biological, social, and circumstantial risk factors on mental health. This has clear implications for policy, education and clinical practice as psychological processes such as rumination and self-blame are amenable to evidence-based psychological therapies.

The effect of machine learning regression algorithms and sample size on individualized behavioral prediction with functional connectivity features.

PubMed

Cui, Zaixu; Gong, Gaolang

2018-06-02

Individualized behavioral/cognitive prediction using machine learning (ML) regression approaches is becoming increasingly applied. The specific ML regression algorithm and sample size are two key factors that non-trivially influence prediction accuracies. However, the effects of the ML regression algorithm and sample size on individualized behavioral/cognitive prediction performance have not been comprehensively assessed. To address this issue, the present study included six commonly used ML regression algorithms: ordinary least squares (OLS) regression, least absolute shrinkage and selection operator (LASSO) regression, ridge regression, elastic-net regression, linear support vector regression (LSVR), and relevance vector regression (RVR), to perform specific behavioral/cognitive predictions based on different sample sizes. Specifically, the publicly available resting-state functional MRI (rs-fMRI) dataset from the Human Connectome Project (HCP) was used, and whole-brain resting-state functional connectivity (rsFC) or rsFC strength (rsFCS) were extracted as prediction features. Twenty-five sample sizes (ranged from 20 to 700) were studied by sub-sampling from the entire HCP cohort. The analyses showed that rsFC-based LASSO regression performed remarkably worse than the other algorithms, and rsFCS-based OLS regression performed markedly worse than the other algorithms. Regardless of the algorithm and feature type, both the prediction accuracy and its stability exponentially increased with increasing sample size. The specific patterns of the observed algorithm and sample size effects were well replicated in the prediction using re-testing fMRI data, data processed by different imaging preprocessing schemes, and different behavioral/cognitive scores, thus indicating excellent robustness/generalization of the effects. The current findings provide critical insight into how the selected ML regression algorithm and sample size influence individualized predictions of behavior/cognition and offer important guidance for choosing the ML regression algorithm or sample size in relevant investigations. Copyright © 2018 Elsevier Inc. All rights reserved.

Learning the facts in medical school is not enough: which factors predict successful application of procedural knowledge in a laboratory setting?

PubMed

Schmidmaier, Ralf; Eiber, Stephan; Ebersbach, Rene; Schiller, Miriam; Hege, Inga; Holzer, Matthias; Fischer, Martin R

2013-02-22

Medical knowledge encompasses both conceptual (facts or "what" information) and procedural knowledge ("how" and "why" information). Conceptual knowledge is known to be an essential prerequisite for clinical problem solving. Primarily, medical students learn from textbooks and often struggle with the process of applying their conceptual knowledge to clinical problems. Recent studies address the question of how to foster the acquisition of procedural knowledge and its application in medical education. However, little is known about the factors which predict performance in procedural knowledge tasks. Which additional factors of the learner predict performance in procedural knowledge? Domain specific conceptual knowledge (facts) in clinical nephrology was provided to 80 medical students (3rd to 5th year) using electronic flashcards in a laboratory setting. Learner characteristics were obtained by questionnaires. Procedural knowledge in clinical nephrology was assessed by key feature problems (KFP) and problem solving tasks (PST) reflecting strategic and conditional knowledge, respectively. Results in procedural knowledge tests (KFP and PST) correlated significantly with each other. In univariate analysis, performance in procedural knowledge (sum of KFP+PST) was significantly correlated with the results in (1) the conceptual knowledge test (CKT), (2) the intended future career as hospital based doctor, (3) the duration of clinical clerkships, and (4) the results in the written German National Medical Examination Part I on preclinical subjects (NME-I). After multiple regression analysis only clinical clerkship experience and NME-I performance remained independent influencing factors. Performance in procedural knowledge tests seems independent from the degree of domain specific conceptual knowledge above a certain level. Procedural knowledge may be fostered by clinical experience. More attention should be paid to the interplay of individual clinical clerkship experiences and structured teaching of procedural knowledge and its assessment in medical education curricula.

The development of local calibration factors for implementing the highway safety manual in Maryland.

DOT National Transportation Integrated Search

2014-03-01

The goal of the study was to determine local calibration factors (LCFs) to adjust predicted motor : vehicle traffic crashes for the Maryland-specific application of the Highway Safety Manual : (HSM). Since HSM predictive models were developed using d...

Ability among adolescents for the metabolic syndrome to predict elevations in factors associated with type 2 diabetes and cardiovascular disease: data from the national health and nutrition examination survey 1999-2006.

PubMed

DeBoer, Mark D; Gurka, Matthew J

2010-08-01

The aim of this study was to compare currently proposed sets of pediatric metabolic syndrome criteria for the ability to predict elevations in "surrogate" factors that are associated with metabolic syndrome and with future cardiovascular disease and type 2 diabetes mellitus. These surrogate factors were fasting insulin, hemoglobin A1c (HbA1c), high-sensitivity C-reactive protein (hsCRP), and uric acid. Waist circumference (WC), blood pressure, triglycerides, high-density lipoprotein cholesterol (HDL-C), fasting glucose, fasting insulin, HbA1c, hsCRP, and uric acid measurements were obtained from 2,624 adolescent (12-18 years old) participants of the 1999-2006 National Health and Nutrition Examination Surveys. We identified children with metabolic syndrome as defined by six commonly used sets of pediatric metabolic syndrome criteria. We then defined elevations in the surrogate factors as values in the top 5% for the cohort and calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for each set of metabolic syndrome criteria and for each surrogate factor. Current pediatric metabolic syndrome criteria exhibited variable sensitivity and specificity for surrogate predictions. Metabolic syndrome criteria had the highest sensitivity for predicting fasting insulin (40-70%), followed by uric acid (31-54%), hsCRP (13-31%), and HbA1c (7-21%). The criteria of de Ferranti (which includes children with WC >75(th) percentile, compared to all other sets including children with WC >90(th) percentile) exhibited the highest sensitivity for predicting each of the surrogates, with only modest decrease in specificity compared to the other sets of criteria. However, the de Ferranti criteria also exhibited the lowest PPV values. Conversely, the pediatric International Diabetes Federation criteria exhibited the lowest sensitivity and the highest specificity. Pediatric metabolic syndrome criteria exhibit moderate sensitivity for detecting elevations in surrogate factors associated with metabolic syndrome and with risk for future disease. Inclusion of children with more modestly elevated WC improved sensitivity.

A Theoretical and Clinical Framework for Parental Burnout: The Balance Between Risks and Resources (BR2)

PubMed Central

Mikolajczak, Moïra; Roskam, Isabelle

2018-01-01

Parental burnout is a specific syndrome resulting from enduring exposure to chronic parenting stress. But why do some parents burn out while others, facing the same stressors, do not? The main aim of this paper was to propose a theory of parental burnout capable of predicting who is at risk of burnout, explaining why a particular parent burned out and why at that specific point in time, and providing directions for intervention. The secondary goal was to operationalize this theory in a tool that would be easy to use for both researchers and clinicians. The results of this two-wave longitudinal study conducted on 923 parents suggest that the Balance between Risks and Resources (BR2) theory proposed here is a relevant framework to predict and explain parental burnout. More specifically, the results show that (1) the BR2 instrument reliably measures parents' balance between risks (parental stress-enhancing factors) and resources (parental stress-alleviating factors), (2) there is a strong linear relationship between BR2 score and parental burnout, (3) parental burnout results from a chronic imbalance of risks over resources, (4) BR2 predicts parental burnout better than job burnout and (5) among the risk and resource factors measured in BR2, risks and resources non-specific to parenting (e.g., low stress-management abilities, perfectionism) equally predict parental and job burnout, while risks and resources specific to parenting (e.g., childrearing practices, coparenting) uniquely predict parental burnout. PMID:29946278

A 3-Year Study of Predictive Factors for Positive and Negative Appendicectomies.

PubMed

Chang, Dwayne T S; Maluda, Melissa; Lee, Lisa; Premaratne, Chandrasiri; Khamhing, Srisongham

2018-03-06

Early and accurate identification or exclusion of acute appendicitis is the key to avoid the morbidity of delayed treatment for true appendicitis or unnecessary appendicectomy, respectively. We aim (i) to identify potential predictive factors for positive and negative appendicectomies; and (ii) to analyse the use of ultrasound scans (US) and computed tomography (CT) scans for acute appendicitis. All appendicectomies that took place at our hospital from the 1st of January 2013 to the 31st of December 2015 were retrospectively recorded. Test results of potential predictive factors of acute appendicitis were recorded. Statistical analysis was performed using Fisher exact test, logistic regression analysis, sensitivity, specificity, and positive and negative predictive values calculation. 208 patients were included in this study. 184 patients had histologically proven acute appendicitis. The other 24 patients had either nonappendicitis pathology or normal appendix. Logistic regression analysis showed statistically significant associations between appendicitis and white cell count, neutrophil count, C-reactive protein, and bilirubin. Neutrophil count was the test with the highest sensitivity and negative predictive values, whereas bilirubin was the test with the highest specificity and positive predictive values (PPV). US and CT scans had high sensitivity and PPV for diagnosing appendicitis. No single test was sufficient to diagnose or exclude acute appendicitis by itself. Combining tests with high sensitivity (abnormal neutrophil count, and US and CT scans) and high specificity (raised bilirubin) may predict acute appendicitis more accurately.

[Hematopoietic stem cell transplantation. Indications, foundations and perspective].

PubMed

Buchholz, S; Ganser, A

2009-05-01

The hematopoietic stem cell transplantation (HSCT) has become a standard therapy for many inherited and acquired disorders of the bone marrow and immune system. Autologous HSCT is mainly done as part of the primary therapy in multiple myeloma and as part of relapse therapy in malignant lymphoma. In contrast, allogeneic HSCT is predominantly performed in patients with acute leukemias. The selection process for allogeneic HSCT takes disease-specific as well as patient-specific factors into account. Risk factors which can predict for poor response to chemotherapy can now be identified in acute myeloid as well as lymphoid leukemia, based on phenotype, cytogenetics, molecular genetics and response to therapy. In these patients allogeneic HSCT can improve overall survival from 0-20% to 30-60%. New conditioning protocols have now raised the upper age limit for transplantation to 70 years. In elderly patients the selection of patients based on absence of comorbidities becomes especially important. The increasing number of long-term survivors requires knowledge of organ-specific late toxicities including secondary malignancies.

Vegetation cover, tidal amplitude and land area predict short-term marsh vulnerability in Coastal Louisiana

USGS Publications Warehouse

Schoolmaster, Donald; Stagg, Camille L.; Sharp, Leigh Anne; McGinnis, Tommy S.; Wood, Bernard; Piazza, Sarai

2018-01-01

The loss of coastal marshes is a topic of great concern, because these habitats provide tangible ecosystem services and are at risk from sea-level rise and human activities. In recent years, significant effort has gone into understanding and modeling the relationships between the biological and physical factors that contribute to marsh stability. Simulation-based process models suggest that marsh stability is the product of a complex feedback between sediment supply, flooding regime and vegetation response, resulting in elevation gains sufficient to match the combination of relative sea-level rise and losses from erosion. However, there have been few direct, empirical tests of these models, because long-term datasets that have captured sufficient numbers of marsh loss events in the context of a rigorous monitoring program are rare. We use a multi-year data set collected by the Coastwide Reference Monitoring System (CRMS) that includes transitions of monitored vegetation plots to open water to build and test a predictive model of near-term marsh vulnerability. We found that despite the conclusions of previous process models, elevation change had no ability to predict the transition of vegetated marsh to open water. However, we found that the processes that drive elevation change were significant predictors of transitions. Specifically, vegetation cover in prior year, land area in the surrounding 1 km2 (an estimate of marsh fragmentation), and the interaction of tidal amplitude and position in tidal frame were all significant factors predicting marsh loss. This suggests that 1) elevation change is likely better a predictor of marsh loss at time scales longer than we consider in this study and 2) the significant predictive factors affect marsh vulnerability through pathways other than elevation change, such as resistance to erosion. In addition, we found that, while sensitivity of marsh vulnerability to the predictive factors varied spatially across coastal Louisiana, vegetation cover in prior year was the best single predictor of subsequent loss in most sites followed by changes in percent land and tidal amplitude. The model’s predicted land loss rates correlated well with land loss rates derived from satellite data, although agreement was spatially variable. These results indicate 1) monitoring the loss of small scale vegetation plots can inform patterns of land loss at larger scales 2) the drivers of land loss vary spatially across coastal Louisiana, and 3) relatively simple models have potential as highly informative tools for bioassessment, directing future research, and management planning.

Modeling regeneration responses of big sagebrush (Artemisia tridentata) to abiotic conditions

USGS Publications Warehouse

Schlaepfer, Daniel R.; Lauenroth, William K.; Bradford, John B.

2014-01-01

Ecosystems dominated by big sagebrush, Artemisia tridentata Nuttall (Asteraceae), which are the most widespread ecosystems in semiarid western North America, have been affected by land use practices and invasive species. Loss of big sagebrush and the decline of associated species, such as greater sage-grouse, are a concern to land managers and conservationists. However, big sagebrush regeneration remains difficult to achieve by restoration and reclamation efforts and there is no regeneration simulation model available. We present here the first process-based, daily time-step, simulation model to predict yearly big sagebrush regeneration including relevant germination and seedling responses to abiotic factors. We estimated values, uncertainty, and importance of 27 model parameters using a total of 1435 site-years of observation. Our model explained 74% of variability of number of years with successful regeneration at 46 sites. It also achieved 60% overall accuracy predicting yearly regeneration success/failure. Our results identify specific future research needed to improve our understanding of big sagebrush regeneration, including data at the subspecies level and improved parameter estimates for start of seed dispersal, modified wet thermal-time model of germination, and soil water potential influences. We found that relationships between big sagebrush regeneration and climate conditions were site specific, varying across the distribution of big sagebrush. This indicates that statistical models based on climate are unsuitable for understanding range-wide regeneration patterns or for assessing the potential consequences of changing climate on sagebrush regeneration and underscores the value of this process-based model. We used our model to predict potential regeneration across the range of sagebrush ecosystems in the western United States, which confirmed that seedling survival is a limiting factor, whereas germination is not. Our results also suggested that modeled regeneration suitability is necessary but not sufficient to explain sagebrush presence. We conclude that future assessment of big sagebrush responses to climate change will need to account for responses of regenerative stages using a process-based understanding, such as provided by our model.

Influence of rainfall and catchment characteristics on urban stormwater quality.

PubMed

Liu, An; Egodawatta, Prasanna; Guan, Yuntao; Goonetilleke, Ashantha

2013-02-01

The accuracy and reliability of urban stormwater quality modelling outcomes are important for stormwater management decision making. The commonly adopted approach where only a limited number of factors are used to predict urban stormwater quality may not adequately represent the complexity of the quality response to a rainfall event or site-to-site differences to support efficient treatment design. This paper discusses an investigation into the influence of rainfall and catchment characteristics on urban stormwater quality in order to investigate the potential areas for errors in current stormwater quality modelling practices. It was found that the influence of rainfall characteristics on pollutant wash-off is step-wise based on specific thresholds. This means that a modelling approach where the wash-off process is predicted as a continuous function of rainfall intensity and duration is not appropriate. Additionally, other than conventional catchment characteristics, namely, land use and impervious surface fraction, other catchment characteristics such as impervious area layout, urban form and site specific characteristics have an important influence on both, pollutant build-up and wash-off processes. Finally, the use of solids as a surrogate to estimate other pollutant species was found to be inappropriate. Individually considering build-up and wash-off processes for each pollutant species should be the preferred option. Copyright © 2012 Elsevier B.V. All rights reserved.

Persistent Physical Symptoms as Perceptual Dysregulation: A Neuropsychobehavioral Model and Its Clinical Implications.

PubMed

Henningsen, Peter; Gündel, Harald; Kop, Willem J; Löwe, Bernd; Martin, Alexandra; Rief, Winfried; Rosmalen, Judith G M; Schröder, Andreas; van der Feltz-Cornelis, Christina; Van den Bergh, Omer

2018-06-01

The mechanisms underlying the perception and experience of persistent physical symptoms are not well understood, and in the models, the specific relevance of peripheral input versus central processing, or of neurobiological versus psychosocial factors in general, is not clear. In this article, we proposed a model for this clinical phenomenon that is designed to be coherent with an underlying, relatively new model of the normal brain functions involved in the experience of bodily signals. Based on a review of recent literature, we describe central elements of this model and its clinical implications. In the model, the brain is seen as an active predictive processing or inferential device rather than one that is passively waiting for sensory input. A central aspect of the model is the attempt of the brain to minimize prediction errors that result from constant comparisons of predictions and sensory input. Two possibilities exist: adaptation of the generative model underlying the predictions or alteration of the sensory input via autonomic nervous activation (in the case of interoception). Following this model, persistent physical symptoms can be described as "failures of inference" and clinically well-known factors such as expectation are assigned a role, not only in the later amplification of bodily signals but also in the very basis of symptom perception. We discuss therapeutic implications of such a model including new interpretations for established treatments as well as new options such as virtual reality techniques combining exteroceptive and interoceptive information.

Production against static electricity

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

Shteiner, A.L.; Minaev, G.S.; Shatkov, O.P.

1978-01-01

Coke industry shops process electrifiable, highly inflammable and explosive substances (benzene, toluene, xylenes, sulfur, coal dust, and coke-oven gas). The electrification of those materials creates a danger of buildup of static electricity charges in them and on the surface of objects interacting with them, followed by an electrical discharge which may cause explosion, fire, or disruption of the technological process. Some of the regulations for protection against static electricity do not reflect modern methods of static electricity control. The regulations are not always observed by workers in the plant services. The main means of protection used to remove static electricitymore » charges in grounding. In many cases it completely drains the charge from the surface of the electrifiable bodies. However, in the processing of compounds with a high specific volumetric electrical resistence grounding is insufficient, since it does not drain the charge from the interior of the substance. Gigh adsorption capacity) are generally met by brown coal low-temperature ompared with predictions using the hourly computer program. The concept of a lumped thermal network for predicting heat losses from in-ground heat storage tanks, developed earlier in the project, has beethe cased-hole log data from various companies and additional comparison factors were calculated for the cased-hole log data. These comparison factors allow for some quantification of these uncalibrated log data.« less

Regional variations in the diversity and predicted metabolic potential of benthic prokaryotes in coastal northern Zhejiang, East China Sea

PubMed Central

Wang, Kai; Ye, Xiansen; Zhang, Huajun; Chen, Heping; Zhang, Demin; Liu, Lian

2016-01-01

Knowledge about the drivers of benthic prokaryotic diversity and metabolic potential in interconnected coastal sediments at regional scales is limited. We collected surface sediments across six zones covering ~200 km in coastal northern Zhejiang, East China Sea and combined 16 S rRNA gene sequencing, community-level metabolic prediction, and sediment physicochemical measurements to investigate variations in prokaryotic diversity and metabolic gene composition with geographic distance and under local environmental conditions. Geographic distance was the most influential factor in prokaryotic β-diversity compared with major environmental drivers, including temperature, sediment texture, acid-volatile sulfide, and water depth, but a large unexplained variation in community composition suggested the potential effects of unmeasured abiotic/biotic factors and stochastic processes. Moreover, prokaryotic assemblages showed a biogeographic provincialism across the zones. The predicted metabolic gene composition similarly shifted as taxonomic composition did. Acid-volatile sulfide was strongly correlated with variation in metabolic gene composition. The enrichments in the relative abundance of sulfate-reducing bacteria and genes relevant with dissimilatory sulfate reduction were observed and predicted, respectively, in the Yushan area. These results provide insights into the relative importance of geographic distance and environmental condition in driving benthic prokaryotic diversity in coastal areas and predict specific biogeochemically-relevant genes for future studies. PMID:27917954

Predicting intentions to donate blood among nondonors in Australia: an extended theory of planned behavior.

PubMed

Robinson, Natalie G; Masser, Barbara M; White, Katherine M; Hyde, Melissa K; Terry, Deborah J

2008-12-01

With an increasing demand for blood and blood products in Australia, there is a continual need to recruit blood donors. As such, it is important to investigate the factors that impact on nondonors' decision-making processes with regard to donating blood for the first time. Previous research has established the efficacy of the theory of planned behavior (TPB) in predicting blood donor intentions. The current research aimed to test a TPB model augmented with constructs implicated in previous blood donor research; specifically descriptive norm, moral norm, anticipated regret, and donation anxiety. Participants completed measures assessing the standard TPB variables of attitude, subjective norm, and perceived behavioral control (PBC) as well as descriptive norm, moral norm, donation anxiety, and anticipated regret. Path analysis examined the utility of the augmented TPB model to predict 195 non-blood donors' intentions to donate blood. A final revised model provided a very good fit to the data and included attitude, PBC, moral norm, descriptive norm, anticipated regret, and donation anxiety as direct predictors of intention, with these factors accounting for 70 percent of the variance in intentions to donate blood. A revised TPB model provided a more efficacious predictor of nondonors' intentions to donate than the standard TPB model and highlights the role that norm-based factors and affective-laden constructs play in predicting non-blood donors' intentions to donate.

The Temporal Prediction of Stress in Speech and Its Relation to Musical Beat Perception.

PubMed

Beier, Eleonora J; Ferreira, Fernanda

2018-01-01

While rhythmic expectancies are thought to be at the base of beat perception in music, the extent to which stress patterns in speech are similarly represented and predicted during on-line language comprehension is debated. The temporal prediction of stress may be advantageous to speech processing, as stress patterns aid segmentation and mark new information in utterances. However, while linguistic stress patterns may be organized into hierarchical metrical structures similarly to musical meter, they do not typically present the same degree of periodicity. We review the theoretical background for the idea that stress patterns are predicted and address the following questions: First, what is the evidence that listeners can predict the temporal location of stress based on preceding rhythm? If they can, is it thanks to neural entrainment mechanisms similar to those utilized for musical beat perception? And lastly, what linguistic factors other than rhythm may account for the prediction of stress in natural speech? We conclude that while expectancies based on the periodic presentation of stresses are at play in some of the current literature, other processes are likely to affect the prediction of stress in more naturalistic, less isochronous speech. Specifically, aspects of prosody other than amplitude changes (e.g., intonation) as well as lexical, syntactic and information structural constraints on the realization of stress may all contribute to the probabilistic expectation of stress in speech.

Understanding social anxiety as a risk for alcohol use disorders: Fear of scrutiny, not social interaction fears, prospectively predicts alcohol use disorders

PubMed Central

Buckner, Julia D.; Schmidt, Norman B.

2009-01-01

Increasing evidence indicates that social anxiety may be a premorbid risk factor for alcohol use disorders (AUD). The aim of this study was to replicate and extend previous work examining whether social anxiety is a risk factor for AUD by evaluating both the temporal antecedence and non-spuriousness of this relationship. We also examined whether social anxiety first-order factors (social interaction anxiety, observation anxieties) served as specific predictors of AUD. A non-referred sample of 404 psychologically healthy young adults (i.e. free from current or past Axis I psychopathology) was prospectively followed over approximately two years. Social anxiety (but not depression or trait anxiety) at baseline significantly predicted subsequent AUD onset. The relationship between social anxiety and AUD remained even after controlling for relevant variables (gender, depression, trait anxiety). Further, social anxiety first-order factors differentially predicted AUD onset, such that observation anxieties (but not social interaction anxiety) were prospectively linked to AUD onset. This study provides further support that social anxiety (and fear of scrutiny specifically) appears to serve as an important and potentially specific AUD-related variable that deserves serious attention as a potential vulnerability factor. PMID:18547587

Cognitive and Social Processes Predicting Partner Psychological Adaptation to Early Stage Breast Cancer

PubMed Central

Manne, Sharon; Ostroff, Jamie; Fox, Kevin; Grana, Generosa; Winkel, Gary

2009-01-01

Introduction The diagnosis and subsequent treatment for early stage breast cancer is stressful for partners. Little is known about the role of cognitive and social processes predicting the longitudinal course of partners’ psychosocial adaptation. This study evaluated the role of cognitive and social processing in partner psychological adaptation to early stage breast cancer, evaluating both main and moderator effect models. Moderating effects for meaning-making, acceptance, and positive reappraisal on the predictive association of searching for meaning, emotional processing, and emotional expression on partner psychological distress were examined. Materials and Methods Partners of women diagnosed with early stage breast cancer were evaluated shortly after the ill partner’s diagnosis (n= 253), nine (n = 167), and 18 months (n = 149) later. Partners completed measures of emotional expression, emotional processing, acceptance, meaning-making, and general and cancer-specific distress at all time points. Results Lower satisfaction with partner support predicted greater global distress, and greater use of positive reappraisal was associated with greater distress. The predicted moderator effects for found meaning on the associations between the search for meaning and cancer-specific distress were found and similar moderating effects for positive reappraisal on the associations between emotional expression and global distress and for acceptance on the association between emotional processing and cancer-specific distress were found. Conclusions Results indicate several cognitive-social processes directly predict partner distress. However, moderator effect models in which the effects of partners’ processing depends upon whether these efforts result changes in perceptions of the cancer experience may add to the understanding of partners’ adaptation to cancer. PMID:18435865

Cognitive and social processes predicting partner psychological adaptation to early stage breast cancer.

PubMed

Manne, Sharon; Ostroff, Jamie; Fox, Kevin; Grana, Generosa; Winkel, Gary

2009-02-01

The diagnosis and subsequent treatment for early stage breast cancer is stressful for partners. Little is known about the role of cognitive and social processes predicting the longitudinal course of partners' psychosocial adaptation. This study evaluated the role of cognitive and social processing in partner psychological adaptation to early stage breast cancer, evaluating both main and moderator effect models. Moderating effects for meaning making, acceptance, and positive reappraisal on the predictive association of searching for meaning, emotional processing, and emotional expression on partner psychological distress were examined. Partners of women diagnosed with early stage breast cancer were evaluated shortly after the ill partner's diagnosis (N=253), 9 (N=167), and 18 months (N=149) later. Partners completed measures of emotional expression, emotional processing, acceptance, meaning making, and general and cancer-specific distress at all time points. Lower satisfaction with partner support predicted greater global distress, and greater use of positive reappraisal was associated with greater distress. The predicted moderator effects for found meaning on the associations between the search for meaning and cancer-specific distress were found and similar moderating effects for positive reappraisal on the associations between emotional expression and global distress and for acceptance on the association between emotional processing and cancer-specific distress were found. Results indicate several cognitive-social processes directly predict partner distress. However, moderator effect models in which the effects of partners' processing depends upon whether these efforts result in changes in perceptions of the cancer experience may add to the understanding of partners' adaptation to cancer.

Internalizing and externalizing problems in adolescence: general and dimension-specific effects of familial loadings and preadolescent temperament traits.

PubMed

Ormel, J; Oldehinkel, A J; Ferdinand, R F; Hartman, C A; De Winter, A F; Veenstra, R; Vollebergh, W; Minderaa, R B; Buitelaar, J K; Verhulst, F C

2005-12-01

We investigated the links between familial loading, preadolescent temperament, and internalizing and externalizing problems in adolescence, hereby distinguishing effects on maladjustment in general versus dimension-specific effects on either internalizing or externalizing problems. In a population-based sample of 2230 preadolescents (10-11 years) familial loading (parental lifetime psychopathology) and offspring temperament were assessed at baseline by parent report, and offspring psychopathology at 2.5-years follow-up by self-report, teacher report and parent report. We used purified measures of temperament and psychopathology and partialled out shared variance between internalizing and externalizing problems. Familial loading of internalizing psychopathology predicted offspring internalizing but not externalizing problems, whereas familial loading of externalizing psychopathology predicted offspring externalizing but not internalizing problems. Both familial loadings were associated with Frustration, low Effortful Control, and Fear. Frustration acted as a general risk factor predicting severity of maladjustment; low Effortful Control and Fear acted as dimension-specific risk factors that predicted a particular type of psychopathology; whereas Shyness, High-Intensity Pleasure, and Affiliation acted as direction markers that steered the conditional probability of internalizing versus externalizing problems, in the event of maladjustment. Temperament traits mediated one-third of the association between familial loading and psychopathology. Findings were robust across different composite measures of psychopathology, and applied to girls as well as boys. With regard to familial loading and temperament, it is important to distinguish general risk factors (Frustration) from dimension-specific risk factors (familial loadings, Effortful Control, Fear), and direction markers that act as pathoplastic factors (Shyness, High-Intensity Pleasure, Affiliation) from both types of risk factors. About one-third of familial loading effects on psychopathology in early adolescence are mediated by temperament.

Complexes of metal chlorides with proton donors — promising polyfunctional catalysts for electrophilic processes

NASA Astrophysics Data System (ADS)

Minsker, Karl S.; Ivanova, S. R.; Biglova, Raisa Z.

1995-05-01

The Bronsted acids formed as a result of the interaction of aluminium chlorides with Group I and II metal chlorides in the presence of proton-donating compounds are promising polyfunctional catalysts for electrophilic processes (polymerisation, depolymerisation and degradation of macromolecules, alkylation, desulfurisation, and hydrogenation). The factor determing the electrophilic activity and selectivity of the action of the catalysts is their acidity. This makes it possible to predict the direction of the changes in the activity and selectivity of the catalyst in specific chemical processes in conformity with the opposite variation rule: with increase in the acidity of the electrophilic catalyst, their activity increases but the selectivity of their action diminishes. The bibliography includes 72 references.

Social cognition and functional capacity in bipolar disorder and schizophrenia.

PubMed

Thaler, Nicholas S; Sutton, Griffin P; Allen, Daniel N

2014-12-15

Social cognition is a functionally relevant predictor of capacity in schizophrenia (SZ), though research concerning its value for bipolar disorder (BD) is limited. The current investigation examined the relationship between two social cognitive factors and functional capacity in bipolar disorder. This study included 48 individuals with bipolar disorder (24 with psychotic features) and 30 patients with schizophrenia. Multiple regression controlling for estimated IQ scores was used to assess the predictive value of social cognitive factors on the UCSD Performance-Based Functional Skills Assessment (UPSA). Results found that for the bipolar with psychosis and schizophrenia groups, the social/emotion processing factor predicted the UPSA. The theory of mind factor only predicted the UPSA for the schizophrenia group.. Findings support the clinical utility of evaluating emotion processing in individuals with a history of psychosis. For BD, theory of mind may be better explained by a generalized cognitive deficit. In contrast, social/emotion processing may be linked to distinct neurobiological processes associated with psychosis. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Cognitive domains that predict time to diagnosis in prodromal Huntington disease.

PubMed

Harrington, Deborah Lynn; Smith, Megan M; Zhang, Ying; Carlozzi, Noelle E; Paulsen, Jane S

2012-06-01

Prodromal Huntington's disease (prHD) is associated with a myriad of cognitive changes but the domains that best predict time to clinical diagnosis have not been studied. This is a notable gap because some domains may be more sensitive to cognitive decline, which would inform clinical trials. The present study sought to characterise cognitive domains underlying a large test battery and for the first time, evaluate their ability to predict time to diagnosis. Participants included gene negative and gene positive prHD participants who were enrolled in the PREDICT-HD study. The CAG-age product (CAP) score was the measure of an individual's genetic signature. A factor analysis of 18 tests was performed to identify sets of measures or latent factors that elucidated core constructs of tests. Factor scores were then fit to a survival model to evaluate their ability to predict time to diagnosis. Six factors were identified: (1) speed/inhibition, (2) verbal working memory, (3) motor planning/speed, (4) attention-information integration, (5) sensory-perceptual processing and (6) verbal learning/memory. Factor scores were sensitive to worsening of cognitive functioning in prHD, typically more so than performances on individual tests comprising the factors. Only the motor planning/speed and sensory-perceptual processing factors predicted time to diagnosis, after controlling for CAP scores and motor symptoms. Conclusions The results suggest that motor planning/speed and sensory-perceptual processing are important markers of disease prognosis. The findings also have implications for using composite indices of cognition in preventive Huntington's disease trials where they may be more sensitive than individual tests.

Electrophysiological evidence for preserved primacy of lexical prediction in aging.

PubMed

Dave, Shruti; Brothers, Trevor A; Traxler, Matthew J; Ferreira, Fernanda; Henderson, John M; Swaab, Tamara Y

2018-05-28

Young adults show consistent neural benefits of predictable contexts when processing upcoming words, but these benefits are less clear-cut in older adults. Here we disentangle the neural correlates of prediction accuracy and contextual support during word processing, in order to test current theories that suggest that neural mechanisms underlying predictive processing are specifically impaired in older adults. During a sentence comprehension task, older and younger readers were asked to predict passage-final words and report the accuracy of these predictions. Age-related reductions were observed for N250 and N400 effects of prediction accuracy, as well as for N400 effects of contextual support independent of prediction accuracy. Furthermore, temporal primacy of predictive processing (i.e., earlier facilitation for successful predictions) was preserved across the lifespan, suggesting that predictive mechanisms are unlikely to be uniquely impaired in older adults. In addition, older adults showed prediction effects on frontal post-N400 positivities (PNPs) that were similar in amplitude to PNPs in young adults. Previous research has shown correlations between verbal fluency and lexical prediction in older adult readers, suggesting that the production system may be linked to capacity for lexical prediction, especially in aging. The current study suggests that verbal fluency modulates PNP effects of contextual support, but not prediction accuracy. Taken together, our findings suggest that aging does not result in specific declines in lexical prediction. Copyright © 2018 Elsevier Ltd. All rights reserved.

The influence of work characteristics, emotional display rules and affectivity on burnout and job satisfaction: A survey among geriatric care workers.

PubMed

Rouxel, Géraldine; Michinov, Estelle; Dodeler, Virginie

2016-10-01

Previous studies have demonstrated that geriatric care employees are exposed to a large number of factors that can affect their levels of job satisfaction and occupational stress. Although working with elderly people is emotionally demanding, little research has been done on the role played by perceptions of emotional display rules, alongside more traditional work characteristics and individual factors, in the prediction of geriatric care employees' wellbeing. The aim of the present study was to examine the role played by work characteristics (job demands, job control, emotional display rules) and individual (affectivity) factors to predict job satisfaction and burnout among French geriatric care nurses. Questionnaires were sent to 891 employees working in 32 geriatric care centers in France. A total of 371 valid questionnaires (response rate: 41.60%) were analyzed using structural equation modeling techniques. Results revealed two main processes of burnout and job satisfaction among women geriatric care workers, namely a salutogenic process and a pathogenic process. As expected, negative affectivity, low job status, perceived negative display rules and job demands are involved in the pathogenic process; while positive affectivity, perceived positive display rules and job control are implied in the salutogenic one. More specifically, as expected, negative affectivity is a positive predictor of burnout, both directly and indirectly through its impact on perceived negative display rules and job demands. Moreover, negative affectivity was negatively related to job satisfaction. Simultaneously, positive affectivity can predict job satisfaction, both directly and indirectly through its impact on perceived positive display rules and job control. Positive affectivity is also a negative predictor of burnout. Practical implications are discussed to support intervention programs that develop healthy workplaces, and also to inform nurses about how to manage emotional display rules in retirement homes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Self-referent information processing in individuals with bipolar spectrum disorders.

PubMed

Molz Adams, Ashleigh; Shapero, Benjamin G; Pendergast, Laura H; Alloy, Lauren B; Abramson, Lyn Y

2014-01-01

Bipolar spectrum disorders (BSDs) are common and impairing, which has led to an examination of risk factors for their development and maintenance. Historically, research has examined cognitive vulnerabilities to BSDs derived largely from the unipolar depression literature. Specifically, theorists propose that dysfunctional information processing guided by negative self-schemata may be a risk factor for depression. However, few studies have examined whether BSD individuals also show self-referent processing biases. This study examined self-referent information processing differences between 66 individuals with and 58 individuals without a BSD in a young adult sample (age M=19.65, SD=1.74; 62% female; 47% Caucasian). Repeated measures multivariate analysis of variance (MANOVA) was conducted to examine multivariate effects of BSD diagnosis on 4 self-referent processing variables (self-referent judgments, response latency, behavioral predictions, and recall) in response to depression-related and nondepression-related stimuli. Bipolar individuals endorsed and recalled more negative and fewer positive self-referent adjectives, as well as made more negative and fewer positive behavioral predictions. Many of these information-processing biases were partially, but not fully, mediated by depressive symptoms. Our sample was not a clinical or treatment-seeking sample, so we cannot generalize our results to clinical BSD samples. No participants had a bipolar I disorder at baseline. This study provides further evidence that individuals with BSDs exhibit a negative self-referent information processing bias. This may mean that those with BSDs have selective attention and recall of negative information about themselves, highlighting the need for attention to cognitive biases in therapy. © 2013 Elsevier B.V. All rights reserved.

Self-referent information processing in individuals with bipolar spectrum disorders

PubMed Central

Molz Adams, Ashleigh; Shapero, Benjamin G.; Pendergast, Laura H.; Alloy, Lauren B.; Abramson, Lyn Y.

2014-01-01

Background Bipolar spectrum disorders (BSDs) are common and impairing, which has led to an examination of risk factors for their development and maintenance. Historically, research has examined cognitive vulnerabilities to BSDs derived largely from the unipolar depression literature. Specifically, theorists propose that dysfunctional information processing guided by negative self-schemata may be a risk factor for depression. However, few studies have examined whether BSD individuals also show self-referent processing biases. Methods This study examined self-referent information processing differences between 66 individuals with and 58 individuals without a BSD in a young adult sample (age M = 19.65, SD = 1.74; 62% female; 47% Caucasian). Repeated measures multivariate analysis of variance (MANOVA) was conducted to examine multivariate effects of BSD diagnosis on 4 self-referent processing variables (self-referent judgments, response latency, behavioral predictions, and recall) in response to depression-related and nondepression-related stimuli. Results Bipolar individuals endorsed and recalled more negative and fewer positive self-referent adjectives, as well as made more negative and fewer positive behavioral predictions. Many of these information-processing biases were partially, but not fully, mediated by depressive symptoms. Limitations Our sample was not a clinical or treatment-seeking sample, so we cannot generalize our results to clinical BSD samples. No participants had a bipolar I disorder at baseline. Conclusions This study provides further evidence that individuals with BSDs exhibit a negative self-referent information processing bias. This may mean that those with BSDs have selective attention and recall of negative information about themselves, highlighting the need for attention to cognitive biases in therapy. PMID:24074480

What basic number processing measures in kindergarten explain unique variability in first-grade arithmetic proficiency?

PubMed

Bartelet, Dimona; Vaessen, Anniek; Blomert, Leo; Ansari, Daniel

2014-01-01

Relations between children's mathematics achievement and their basic number processing skills have been reported in both cross-sectional and longitudinal studies. Yet, some key questions are currently unresolved, including which kindergarten skills uniquely predict children's arithmetic fluency during the first year of formal schooling and the degree to which predictors are contingent on children's level of arithmetic proficiency. The current study assessed kindergarteners' non-symbolic and symbolic number processing efficiency. In addition, the contribution of children's underlying magnitude representations to differences in arithmetic achievement was assessed. Subsequently, in January of Grade 1, their arithmetic proficiency was assessed. Hierarchical regression analysis revealed that children's efficiency to compare digits, count, and estimate numerosities uniquely predicted arithmetic differences above and beyond the non-numerical factors included. Moreover, quantile regression analysis indicated that symbolic number processing efficiency was consistently a significant predictor of arithmetic achievement scores regardless of children's level of arithmetic proficiency, whereas their non-symbolic number processing efficiency was not. Finally, none of the task-specific effects indexing children's representational precision was significantly associated with arithmetic fluency. The implications of the results are 2-fold. First, the findings indicate that children's efficiency to process symbols is important for the development of their arithmetic fluency in Grade 1 above and beyond the influence of non-numerical factors. Second, the impact of children's non-symbolic number processing skills does not depend on their arithmetic achievement level given that they are selected from a nonclinical population. Copyright © 2013 Elsevier Inc. All rights reserved.

A mixture model with a reference-based automatic selection of components for disease classification from protein and/or gene expression levels

PubMed Central

2011-01-01

Background Bioinformatics data analysis is often using linear mixture model representing samples as additive mixture of components. Properly constrained blind matrix factorization methods extract those components using mixture samples only. However, automatic selection of extracted components to be retained for classification analysis remains an open issue. Results The method proposed here is applied to well-studied protein and genomic datasets of ovarian, prostate and colon cancers to extract components for disease prediction. It achieves average sensitivities of: 96.2 (sd = 2.7%), 97.6% (sd = 2.8%) and 90.8% (sd = 5.5%) and average specificities of: 93.6% (sd = 4.1%), 99% (sd = 2.2%) and 79.4% (sd = 9.8%) in 100 independent two-fold cross-validations. Conclusions We propose an additive mixture model of a sample for feature extraction using, in principle, sparseness constrained factorization on a sample-by-sample basis. As opposed to that, existing methods factorize complete dataset simultaneously. The sample model is composed of a reference sample representing control and/or case (disease) groups and a test sample. Each sample is decomposed into two or more components that are selected automatically (without using label information) as control specific, case specific and not differentially expressed (neutral). The number of components is determined by cross-validation. Automatic assignment of features (m/z ratios or genes) to particular component is based on thresholds estimated from each sample directly. Due to the locality of decomposition, the strength of the expression of each feature across the samples can vary. Yet, they will still be allocated to the related disease and/or control specific component. Since label information is not used in the selection process, case and control specific components can be used for classification. That is not the case with standard factorization methods. Moreover, the component selected by proposed method as disease specific can be interpreted as a sub-mode and retained for further analysis to identify potential biomarkers. As opposed to standard matrix factorization methods this can be achieved on a sample (experiment)-by-sample basis. Postulating one or more components with indifferent features enables their removal from disease and control specific components on a sample-by-sample basis. This yields selected components with reduced complexity and generally, it increases prediction accuracy. PMID:22208882

Predicting Homophobic Behavior among Heterosexual Youth: Domain General and Sexual Orientation-Specific Factors at the Individual and Contextual Level

ERIC Educational Resources Information Center

Poteat, V. Paul; DiGiovanni, Craig D.; Scheer, Jillian R.

2013-01-01

As a form of bias-based harassment, homophobic behavior remains prominent in schools. Yet, little attention has been given to factors that underlie it, aside from bullying and sexual prejudice. Thus, we examined multiple domain general (empathy, perspective-taking, classroom respect norms) and sexual orientation-specific factors (sexual…

Two unconventional risk factors for major adverse cardiovascular events in subjects with sexual dysfunction: low education and reported partner's hypoactive sexual desire in comparison with conventional risk factors.

PubMed

Rastrelli, Giulia; Corona, Giovanni; Fisher, Alessandra D; Silverii, Antonio; Mannucci, Edoardo; Maggi, Mario

2012-12-01

The classification of subjects as low or high cardiovascular (CV) risk is usually performed by risk engines, based upon multivariate prediction algorithms. However, their accuracy in predicting major adverse CV events (MACEs) is lower in high-risk populations as they take into account only conventional risk factors. To evaluate the accuracy of Progetto Cuore risk engine in predicting MACE in subjects with erectile dysfunction (ED) and to test the role of unconventional CV risk factors, specifically identified for ED. A consecutive series of 1,233 men (mean age 53.33 ± 9.08 years) attending our outpatient clinic for sexual dysfunction was longitudinally studied for a mean period of 4.4 ± 2.6 years. Several clinical, biochemical, and instrumental parameters were evaluated. Subjects were classified as high or low risk, according to previously reported ED-specific risk factors. In the overall population, Progetto Cuore-predicted population survival was not significantly different from the observed one (P = 0.545). Accordingly, receiver operating characteristic (ROC) analysis shows that Progetto Cuore has an accuracy of 0.697 ± 0.037 (P < 0.001) in predicting MACE. Considering subjects at high risk according to ED-specific risk factors, the observed incidence of MACE was significantly higher than the expected for both low educated and patients reporting partner's hypoactive sexual desire (HSD, both <0.05), but not for other described factors. The area under ROC curves of Progetto Cuore for MACE in subjects with low education and reported partner's HSD were 0.659 ± 0.053 (P = 0.008) and 0.550 ± 0.076 (P = 0.570), respectively. Overall, Progetto Cuore is a proper instrument for evaluating CV risk in ED subjects. However, in ED, other factors such as low education and partner's HSD concur to risk profile. At variance with low education, Progetto Cuore is not accurate enough to predict MACE in subjects with partner's HSD, suggesting that the latter effect is not mediated by conventional risk factors included in the algorithm. © 2012 International Society for Sexual Medicine.

Pressure prediction model for compression garment design.

PubMed

Leung, W Y; Yuen, D W; Ng, Sun Pui; Shi, S Q

2010-01-01

Based on the application of Laplace's law to compression garments, an equation for predicting garment pressure, incorporating the body circumference, the cross-sectional area of fabric, applied strain (as a function of reduction factor), and its corresponding Young's modulus, is developed. Design procedures are presented to predict garment pressure using the aforementioned parameters for clinical applications. Compression garments have been widely used in treating burning scars. Fabricating a compression garment with a required pressure is important in the healing process. A systematic and scientific design method can enable the occupational therapist and compression garments' manufacturer to custom-make a compression garment with a specific pressure. The objectives of this study are 1) to develop a pressure prediction model incorporating different design factors to estimate the pressure exerted by the compression garments before fabrication; and 2) to propose more design procedures in clinical applications. Three kinds of fabrics cut at different bias angles were tested under uniaxial tension, as were samples made in a double-layered structure. Sets of nonlinear force-extension data were obtained for calculating the predicted pressure. Using the value at 0° bias angle as reference, the Young's modulus can vary by as much as 29% for fabric type P11117, 43% for fabric type PN2170, and even 360% for fabric type AP85120 at a reduction factor of 20%. When comparing the predicted pressure calculated from the single-layered and double-layered fabrics, the double-layered construction provides a larger range of target pressure at a particular strain. The anisotropic and nonlinear behaviors of the fabrics have thus been determined. Compression garments can be methodically designed by the proposed analytical pressure prediction model.

Response Monitoring and Adjustment: Differential Relations with Psychopathic Traits

PubMed Central

Bresin, Konrad; Finy, M. Sima; Sprague, Jenessa; Verona, Edelyn

2014-01-01

Studies on the relation between psychopathy and cognitive functioning often show mixed results, partially because different factors of psychopathy have not been considered fully. Based on previous research, we predicted divergent results based on a two-factor model of psychopathy (interpersonal-affective traits and impulsive-antisocial traits). Specifically, we predicted that the unique variance of interpersonal-affective traits would be related to increased monitoring (i.e., error-related negativity) and adjusting to errors (i.e., post-error slowing), whereas impulsive-antisocial traits would be related to reductions in these processes. Three studies using a diverse selection of assessment tools, samples, and methods are presented to identify response monitoring correlates of the two main factors of psychopathy. In Studies 1 (undergraduates), 2 (adolescents), and 3 (offenders), interpersonal-affective traits were related to increased adjustment following errors and, in Study 3, to enhanced monitoring of errors. Impulsive-antisocial traits were not consistently related to error adjustment across the studies, although these traits were related to a deficient monitoring of errors in Study 3. The results may help explain previous mixed findings and advance implications for etiological models of psychopathy. PMID:24933282

Petri Net computational modelling of Langerhans cell Interferon Regulatory Factor Network predicts their role in T cell activation.

PubMed

Polak, Marta E; Ung, Chuin Ying; Masapust, Joanna; Freeman, Tom C; Ardern-Jones, Michael R

2017-04-06

Langerhans cells (LCs) are able to orchestrate adaptive immune responses in the skin by interpreting the microenvironmental context in which they encounter foreign substances, but the regulatory basis for this has not been established. Utilising systems immunology approaches combining in silico modelling of a reconstructed gene regulatory network (GRN) with in vitro validation of the predictions, we sought to determine the mechanisms of regulation of immune responses in human primary LCs. The key role of Interferon regulatory factors (IRFs) as controllers of the human Langerhans cell response to epidermal cytokines was revealed by whole transcriptome analysis. Applying Boolean logic we assembled a Petri net-based model of the IRF-GRN which provides molecular pathway predictions for the induction of different transcriptional programmes in LCs. In silico simulations performed after model parameterisation with transcription factor expression values predicted that human LC activation of antigen-specific CD8 T cells would be differentially regulated by epidermal cytokine induction of specific IRF-controlled pathways. This was confirmed by in vitro measurement of IFN-γ production by activated T cells. As a proof of concept, this approach shows that stochastic modelling of a specific immune networks renders transcriptome data valuable for the prediction of functional outcomes of immune responses.

A note on evaluating VAN earthquake predictions

NASA Astrophysics Data System (ADS)

Tselentis, G.-Akis; Melis, Nicos S.

The evaluation of the success level of an earthquake prediction method should not be based on approaches that apply generalized strict statistical laws and avoid the specific nature of the earthquake phenomenon. Fault rupture processes cannot be compared to gambling processes. The outcome of the present note is that even an ideal earthquake prediction method is still shown to be a matter of a “chancy” association between precursors and earthquakes if we apply the same procedure proposed by Mulargia and Gasperini [1992] in evaluating VAN earthquake predictions. Each individual VAN prediction has to be evaluated separately, taking always into account the specific circumstances and information available. The success level of epicenter prediction should depend on the earthquake magnitude, and magnitude and time predictions may depend on earthquake clustering and the tectonic regime respectively.

The influence of socioeconomic factors on cardiovascular disease risk factors in the context of economic development in the Samoan archipelago.

PubMed

Ezeamama, Amara E; Viali, Satupaitea; Tuitele, John; McGarvey, Stephen T

2006-11-01

Early in economic development there are positive associations between socioeconomic status (SES) and cardiovascular disease (CVD) risk factors, and in the most developed market economy societies there are negative associations. The purpose of this report is to describe cross-sectional and longitudinal associations between indicators of SES and CVD risk factors in a genetically homogenous population of Samoans at different levels of economic development. At baseline 1289 participants 25-58yrs, and at 4-year follow-up, 963 participants were studied in less economically developed Samoa and in more developed American Samoa. SES was assessed by education, occupation, and material lifestyle at baseline. The CVD risk factors, obesity, type-2 diabetes and hypertension were measured at baseline and 4-year follow-up, and an index of any incident CVD risk factor at follow-up was calculated. Sex and location (Samoa and American Samoa) specific multivariable logistic regression models were used to test for relationships between SES and CVD risk factors at baseline after adjustment for age and the other SES indicators. In addition an ordinal SES index was constructed for each individual based on all three SES indicators, and used in a multivariable model to estimate the predicted probability of CVD risk factors across the SES index for the two locations. In both the models using specific SES measures and CVD risk factor outcomes, and the models using the ordinal SES index and predicted probabilities of CVD risk factors, we detected a pattern of high SES associated with: (1) elevated odds of CVD risk factors in less developed Samoa, and (2) decreased odds of CVD risk factors in more developed American Samoa. We conclude that the pattern of inverse associations between SES and CVD risk factors in Samoa and direct associations in American Samoa is attributable to the heterogeneity across the Samoas in specific exposures to social processes of economic development and the natural history of individual CVD risk factors. The findings suggest that interventions on non-communicable diseases in the Samoas must be devised based on the level of economic development, the socio-economic context of risk factor exposures, and individual characteristics such as age, sex and education level.

Emotional processing and self-control in adolescents with type 1 diabetes.

PubMed

Hughes, Amy E; Berg, Cynthia A; Wiebe, Deborah J

2012-09-01

This study examined whether emotional processing (understanding emotions), self-control (regulation of thoughts, emotions, and behavior), and their interaction predicted HbA1c for adolescents with type 1 diabetes over and above diabetes-specific constructs. Self-report measures of self-control, emotional processing, self-efficacy for diabetes management, diabetes-specific negative affect, and adherence, and HbA1c from medical records were obtained from 137 adolescents with type 1 diabetes (M age = 13.48 years). Emotional processing interacted with self-control to predict HbA1c, such that when adolescents had both low emotional processing and low self-control, HbA1c was poorest. Also, both high emotional processing and self-control buffered negative effects of low capacity in the other in relation to HbA1c. The interaction of emotional processing × self-control predicted HbA1c over diabetes-specific self-efficacy, negative affect, and adherence. These findings suggest the importance of emotional processing and self-control for health outcomes in adolescents with diabetes.

Emotional Processing and Self-Control in Adolescents With Type 1 Diabetes

PubMed Central

Hughes, Amy E.; Wiebe, Deborah J.

2012-01-01

Objective This study examined whether emotional processing (understanding emotions), self-control (regulation of thoughts, emotions, and behavior), and their interaction predicted HbA1c for adolescents with type 1 diabetes over and above diabetes-specific constructs. Methods Self-report measures of self-control, emotional processing, self-efficacy for diabetes management, diabetes-specific negative affect, and adherence, and HbA1c from medical records were obtained from 137 adolescents with type 1 diabetes (M age = 13.48 years). Results Emotional processing interacted with self-control to predict HbA1c, such that when adolescents had both low emotional processing and low self-control, HbA1c was poorest. Also, both high emotional processing and self-control buffered negative effects of low capacity in the other in relation to HbA1c. The interaction of emotional processing × self-control predicted HbA1c over diabetes-specific self-efficacy, negative affect, and adherence. Conclusions These findings suggest the importance of emotional processing and self-control for health outcomes in adolescents with diabetes. PMID:22523404

Implementation of Cyber-Physical Production Systems for Quality Prediction and Operation Control in Metal Casting.

PubMed

Lee, JuneHyuck; Noh, Sang Do; Kim, Hyun-Jung; Kang, Yong-Shin

2018-05-04

The prediction of internal defects of metal casting immediately after the casting process saves unnecessary time and money by reducing the amount of inputs into the next stage, such as the machining process, and enables flexible scheduling. Cyber-physical production systems (CPPS) perfectly fulfill the aforementioned requirements. This study deals with the implementation of CPPS in a real factory to predict the quality of metal casting and operation control. First, a CPPS architecture framework for quality prediction and operation control in metal-casting production was designed. The framework describes collaboration among internet of things (IoT), artificial intelligence, simulations, manufacturing execution systems, and advanced planning and scheduling systems. Subsequently, the implementation of the CPPS in actual plants is described. Temperature is a major factor that affects casting quality, and thus, temperature sensors and IoT communication devices were attached to casting machines. The well-known NoSQL database, HBase and the high-speed processing/analysis tool, Spark, are used for IoT repository and data pre-processing, respectively. Many machine learning algorithms such as decision tree, random forest, artificial neural network, and support vector machine were used for quality prediction and compared with R software. Finally, the operation of the entire system is demonstrated through a CPPS dashboard. In an era in which most CPPS-related studies are conducted on high-level abstract models, this study describes more specific architectural frameworks, use cases, usable software, and analytical methodologies. In addition, this study verifies the usefulness of CPPS by estimating quantitative effects. This is expected to contribute to the proliferation of CPPS in the industry.

Child, parent and family factors as predictors of adjustment for siblings of children with a disability.

PubMed

Giallo, R; Gavidia-Payne, S

2006-12-01

Siblings adjust to having a brother or sister with a disability in diverse ways. This study investigated a range of child, parent and family factors as predictors of sibling adjustment outcomes. Forty-nine siblings (aged 7-16 years) and parents provided information about (1) sibling daily hassles and uplifts; (2) sibling coping; (3) parent stress; (4) parenting; and (5) family resilience. Multiple regression techniques were used. It was found that parent and family factors were stronger predictors of sibling adjustment difficulties than siblings' own experiences of stress and coping. Specifically, socio-economic status, past attendance at a sibling support group, parent stress, family time and routines, family problem-solving and communication, and family hardiness-predicted sibling adjustment difficulties. Finally, siblings' perceived intensity of daily uplifts significantly predicted sibling prosocial behaviour. The results revealed that the family level of risk and resilience factors were better predictors of sibling adjustment than siblings' own experiences of stress and coping resources, highlighting the importance of familial and parental contributions to the sibling adjustment process. The implications of these results for the design of interventions and supports for siblings are discussed.

Psychiatric Outcomes at Age Seven for Very Preterm Children: Rates and Predictors

ERIC Educational Resources Information Center

Treyvaud, Karli; Ure, Alexandra; Doyle, Lex W.; Lee, Katherine J.; Rogers, Cynthia E.; Kidokoro, Hiroyuki; Inder, Terrie E.; Anderson, Peter J.

2013-01-01

Background: Uncertainty remains about the rate of specific psychiatric disorders and associated predictive factors for very preterm (VPT) children. The aims of this study were to document rates of psychiatric disorders in VPT children aged 7 years compared with term born children, and to examine potential predictive factors for psychiatric…

Cognitive processing in the aftermath of relationship dissolution: Associations with concurrent and prospective distress and posttraumatic growth.

PubMed

Del Palacio-González, Adriana; Clark, David A; O'Sullivan, Lucia F

2017-12-01

Non-marital romantic relationship dissolution is amongst the most stressful life events experienced by young adults. Yet, some individuals experience posttraumatic growth following relationship dissolution. Little is known about the specific and differential contribution of trait-like and event-specific cognitive processing styles to each of these outcomes. A longitudinal design was employed in which trait-like (brooding and reflection) and dissolution-specific (intrusive and deliberate) cognitive processing was examined as predictors of growth (Posttraumatic Growth Inventory) and distress (Breakup Distress Scale) following a recent relationship dissolution. Initially, 148 participants completed measures of trait-like and dissolution-specific cognitive processing, growth, and distress (T1). A subsample completed a seven-month follow-up (T2). Higher frequency of relationship-dissolution intrusive thoughts predicted concurrent distress after accounting for brooding and relationship characteristics. Further, higher brooding and lower reflection predicted higher distress prospectively. Concurrent growth was predicted by both higher brooding and more deliberate relationship-dissolution thoughts. Prospectively, T1 dissolution intrusive thoughts predicted higher T2 deliberate thoughts, and the interaction between these two constructs predicted higher T2 growth. Therefore, deliberately thinking of the dissolution was related to positive psychological outcomes. In contrast, intrusive dissolution cognitions and a tendency for brooding had a mixed (paradoxical) association with psychological adjustment. Copyright © 2016 John Wiley & Sons, Ltd.

High-Level Prediction Signals in a Low-Level Area of the Macaque Face-Processing Hierarchy.

PubMed

Schwiedrzik, Caspar M; Freiwald, Winrich A

2017-09-27

Theories like predictive coding propose that lower-order brain areas compare their inputs to predictions derived from higher-order representations and signal their deviation as a prediction error. Here, we investigate whether the macaque face-processing system, a three-level hierarchy in the ventral stream, employs such a coding strategy. We show that after statistical learning of specific face sequences, the lower-level face area ML computes the deviation of actual from predicted stimuli. But these signals do not reflect the tuning characteristic of ML. Rather, they exhibit identity specificity and view invariance, the tuning properties of higher-level face areas AL and AM. Thus, learning appears to endow lower-level areas with the capability to test predictions at a higher level of abstraction than what is afforded by the feedforward sweep. These results provide evidence for computational architectures like predictive coding and suggest a new quality of functional organization of information-processing hierarchies beyond pure feedforward schemes. Copyright © 2017 Elsevier Inc. All rights reserved.

Adaptation and readaptation medical concerns of a Mars trip

NASA Technical Reports Server (NTRS)

Johnson, Philip C.

1986-01-01

The ability of the human body to adapt to microgravity environments and to later readapt to a gravity environment was examined. Issues specifically relating to the effects of long duration space flight on the adaptation/readaptation process are discussed. The need for better health prediction techniques is stressed in order to be able to better anticipate crew health problems and to perform corrective actions. Several specific examples are discussed of latent diseases which could occur during a long duration space mission, even after having subjected the crew to thorough premission checkups. The need for learning how to prevent or ameliorate such problems as space adaptation syndrome, bone and muscle (and possibly tissue) atrophy, immune system atrophy, and heart arrythmias is also discussed. The implications of the age of the crew, the influence of an onboard low level gravity field, and drugs are briefly addressed as factors in the adaptation/readaptation process.

Design of Critical Components

NASA Technical Reports Server (NTRS)

Hendricks, Robert C.; Zaretsky, Erwin V.

2001-01-01

Critical component design is based on minimizing product failures that results in loss of life. Potential catastrophic failures are reduced to secondary failures where components removed for cause or operating time in the system. Issues of liability and cost of component removal become of paramount importance. Deterministic design with factors of safety and probabilistic design address but lack the essential characteristics for the design of critical components. In deterministic design and fabrication there are heuristic rules and safety factors developed over time for large sets of structural/material components. These factors did not come without cost. Many designs failed and many rules (codes) have standing committees to oversee their proper usage and enforcement. In probabilistic design, not only are failures a given, the failures are calculated; an element of risk is assumed based on empirical failure data for large classes of component operations. Failure of a class of components can be predicted, yet one can not predict when a specific component will fail. The analogy is to the life insurance industry where very careful statistics are book-kept on classes of individuals. For a specific class, life span can be predicted within statistical limits, yet life-span of a specific element of that class can not be predicted.

A modified fall risk assessment tool that is specific to physical function predicts falls in community-dwelling elderly people.

PubMed

Hirase, Tatsuya; Inokuchi, Shigeru; Matsusaka, Nobuou; Nakahara, Kazumi; Okita, Minoru

2014-01-01

Developing a practical fall risk assessment tool to predict the occurrence of falls in the primary care setting is important because investigators have reported deterioration of physical function associated with falls. Researchers have used many performance tests to predict the occurrence of falls. These performance tests predict falls and also assess physical function and determine exercise interventions. However, the need for such specialists as physical therapists to accurately conduct these tests limits their use in the primary care setting. Questionnaires for fall prediction offer an easy way to identify high-risk fallers without requiring specialists. Using an existing fall assessment questionnaire, this study aimed to identify items specific to physical function and determine whether those items were able to predict falls and estimate physical function of high-risk fallers. The analysis consisted of both retrospective and prospective studies and used 2 different samples (retrospective, n = 1871; prospective, n = 292). The retrospective study and 3-month prospective study comprised community-dwelling individuals aged 65 years or older and older adults using community day centers. The number of falls, risk factors for falls (15 risk factors on the questionnaire), and physical function determined by chair standing test (CST) and Timed Up and Go Test (TUGT) were assessed. The retrospective study selected fall risk factors related to physical function. The prospective study investigated whether the number of selected risk factors could predict falls. The predictive power was determined using the area under the receiver operating characteristic curve. Seven of the 15 risk factors were related to physical function. The area under the receiver operating characteristic curve for the sum of the selected risk factors of previous falls plus the other risk factors was 0.82 (P = .00). The best cutoff point was 4 risk factors, with sensitivity and specificity of 84% and 68%, respectively. The mean values for the CST and TUGT at the best cutoff point were 12.9 and 12.5 seconds, respectively. In the retrospective study, the values for the CST and TUGT corresponding to the best cutoff point from the prospective study were 13.2 and 11.4 seconds, respectively. This study confirms that a screening tool comprising 7 fall risk factors can be used to predict falls. The values for the CST and TUGT corresponding to the best cutoff point for the selected 7 risk factors determined in our prospective study were similar to the cutoff points for the CST and TUGT in previous studies for fall prediction. We propose that the sum of the selected risk factors of previous falls plus the other risk factors may be identified as the estimated value for physical function. These findings may contribute to earlier identification of high-risk fallers and intervention for fall prevention.

Differential miRNA expression in B cells is associated with inter-individual differences in humoral immune response to measles vaccination.

PubMed

Haralambieva, Iana H; Kennedy, Richard B; Simon, Whitney L; Goergen, Krista M; Grill, Diane E; Ovsyannikova, Inna G; Poland, Gregory A

2018-01-01

MicroRNAs are important mediators of post-transcriptional regulation of gene expression through RNA degradation and translational repression, and are emerging biomarkers of immune system activation/response after vaccination. We performed Next Generation Sequencing (mRNA-Seq) of intracellular miRNAs in measles virus-stimulated B and CD4+ T cells from high and low antibody responders to measles vaccine. Negative binomial generalized estimating equation (GEE) models were used for miRNA assessment and the DIANA tool was used for gene/target prediction and pathway enrichment analysis. We identified a set of B cell-specific miRNAs (e.g., miR-151a-5p, miR-223, miR-29, miR-15a-5p, miR-199a-3p, miR-103a, and miR-15a/16 cluster) and biological processes/pathways, including regulation of adherens junction proteins, Fc-receptor signaling pathway, phosphatidylinositol-mediated signaling pathway, growth factor signaling pathway/pathways, transcriptional regulation, apoptosis and virus-related processes, significantly associated with neutralizing antibody titers after measles vaccination. No CD4+ T cell-specific miRNA expression differences between high and low antibody responders were found. Our study demonstrates that miRNA expression directly or indirectly influences humoral immunity to measles vaccination and suggests that B cell-specific miRNAs may serve as useful predictive biomarkers of vaccine humoral immune response.

Multimethod Prediction of Physical Parent-Child Aggression Risk in Expectant Mothers and Fathers with Social Information Processing Theory

PubMed Central

Rodriguez, Christina M.; Smith, Tamika L.; Silvia, Paul J.

2015-01-01

The Social Information Processing (SIP) model postulates that parents undergo a series of stages in implementing physical discipline that can escalate into physical child abuse. The current study utilized a multimethod approach to investigate whether SIP factors can predict risk of parent-child aggression (PCA) in a diverse sample of expectant mothers and fathers. SIP factors of PCA attitudes, negative child attributions, reactivity, and empathy were considered as potential predictors of PCA risk; additionally, analyses considered whether personal history of PCA predicted participants’ own PCA risk through its influence on their attitudes and attributions. Findings indicate that, for both mothers and fathers, history influenced attitudes but not attributions in predicting PCA risk, and attitudes and attributions predicted PCA risk; empathy and reactivity predicted negative child attributions for expectant mothers, but only reactivity significantly predicted attributions for expectant fathers. Path models for expectant mothers and fathers were remarkably similar. Overall, the findings provide support for major aspects of the SIP model. Continued work is needed in studying the progression of these factors across time for both mothers and fathers as well as the inclusion of other relevant ecological factors to the SIP model. PMID:26631420

Effect of body size and temperature on respiration of Galaxias maculatus (Pisces: Galaxiidae)

USGS Publications Warehouse

Milano, D.; Vigliano, P.H.; Beauchamp, David A.

2017-01-01

Body mass and temperature are primary determinants of metabolic rate in ectothermic animals. Oxygen consumption of post-larval Galaxias maculatus was measured in respirometry trials under different temperatures (5–21°C) and varying body masses (0.1–>1.5 g) spanning a relevant range of thermal conditions and sizes. Specific respiration rates (R in g O2 g−1 d−1) declined as a power function of body mass and increased exponentially with temperature and was expressed as: R = 0.0007 * W −0.31 * e 0.13 * T. The ability of this model to predict specific respiration rate was evaluated by comparing observed values with those predicted by the model. Our findings suggest that the respiration rate of G. maculatus is the result of multiple interactive processes (intrinsic and extrinsic factors) that modulate each other in ‘meta-mechanistic’ ways; this would help to explain the species’ ability to undergo the complex ontogenetic habitat shifts observed in the lakes of the Andean Patagonic range.

The relation of respiratory sinus arrhythmia to later shyness: Moderation by neighborhood quality.

PubMed

Zhang, Hui; Spinrad, Tracy L; Eisenberg, Nancy; Zhang, Linlin

2018-05-21

The purpose of the study was to predict young children's shyness from both internal/biological (i.e., resting respiratory sinus arrhythmia; RSA) and external (i.e., neighborhood quality) factors. Participants were 180 children at 42 (Time 1; T1), 72 (T2), and 84 (T3) months of age. RSA data were obtained at T1 during a neutral film in the laboratory. Mothers reported perceived neighborhood quality at T2 and children's dispositional shyness at T1 and T3. Path analyses indicated that resting RSA interacted with neighborhood quality to predict T3 shyness, even after controlling for earlier family income and T1 shyness. Specifically, high levels of resting RSA predicted low levels of shyness in the context of high neighborhood quality. When neighborhood quality was low, resting RSA was positively related to later shyness. These findings indicate that children's shyness is predicted by more than biological processes and that consideration of the broader context is critical to understanding children's social behavior. © 2018 Wiley Periodicals, Inc.

Body composition, muscle capacity, and physical function in older adults: an integrated conceptual model.

PubMed

Brady, Anne O; Straight, Chad R; Evans, Ellen M

2014-07-01

The aging process leads to adverse changes in body composition (increases in fat mass and decreases in skeletal muscle mass), declines in physical function (PF), and ultimately increased risk for disability and loss of independence. Specific components of body composition or muscle capacity (strength and power) may be useful in predicting PF; however, findings have been mixed regarding the most salient predictor of PF. The development of a conceptual model potentially aids in understanding the interrelated factors contributing to PF with the factors of interest being physical activity, body composition, and muscle capacity. This article also highlights sex differences in these domains. Finally, factors known to affect PF, such as sleep, depression, fatigue, and self-efficacy, are discussed. Development of a comprehensive conceptual model is needed to better characterize the most salient factors contributing to PF and to subsequently inform the development of interventions to reduce physical disability in older adults.

Wearable physiological sensors and real-time algorithms for detection of acute mountain sickness.

PubMed

Muza, Stephen R

2018-03-01

This is a minireview of potential wearable physiological sensors and algorithms (process and equations) for detection of acute mountain sickness (AMS). Given the emerging status of this effort, the focus of the review is on the current clinical assessment of AMS, known risk factors (environmental, demographic, and physiological), and current understanding of AMS pathophysiology. Studies that have examined a range of physiological variables to develop AMS prediction and/or detection algorithms are reviewed to provide insight and potential technological roadmaps for future development of real-time physiological sensors and algorithms to detect AMS. Given the lack of signs and nonspecific symptoms associated with AMS, development of wearable physiological sensors and embedded algorithms to predict in the near term or detect established AMS will be challenging. Prior work using [Formula: see text], HR, or HRv has not provided the sensitivity and specificity for useful application to predict or detect AMS. Rather than using spot checks as most prior studies have, wearable systems that continuously measure SpO 2 and HR are commercially available. Employing other statistical modeling approaches such as general linear and logistic mixed models or time series analysis to these continuously measured variables is the most promising approach for developing algorithms that are sensitive and specific for physiological prediction or detection of AMS.

Predicting Resilience in Sexually Abused Adolescents

ERIC Educational Resources Information Center

Williams, Javonda; Nelson-Gardell, Debra

2012-01-01

This research examined factors that predicted resilience in sexually abused adolescents. Using Bronfenbrenner's Process-Person-Context-Time (PPCT) ecological model, this study considered the proximal and distal factors that would contribute to adolescents' reactions to sexual victimization. This correlational study used hierarchical regression…

Dissociative absorption: An empirically unique, clinically relevant, dissociative factor.

PubMed

Soffer-Dudek, Nirit; Lassri, Dana; Soffer-Dudek, Nir; Shahar, Golan

2015-11-01

Research of dissociative absorption has raised two questions: (a) Is absorption a unique dissociative factor within a three-factor structure, or a part of one general dissociative factor? Even when three factors are found, the specificity of the absorption factor is questionable. (b) Is absorption implicated in psychopathology? Although commonly viewed as "non-clinical" dissociation, absorption was recently hypothesized to be specifically associated with obsessive-compulsive symptoms. To address these questions, we conducted exploratory and confirmatory factor analyses on 679 undergraduates. Analyses supported the three-factor model, and a "purified" absorption scale was extracted from the original inclusive absorption factor. The purified scale predicted several psychopathology scales. As hypothesized, absorption was a stronger predictor of obsessive-compulsive symptoms than of general psychopathology. In addition, absorption was the only dissociative scale that longitudinally predicted obsessive-compulsive symptoms. We conclude that absorption is a unique and clinically relevant dissociative tendency that is particularly meaningful to obsessive-compulsive symptoms. Copyright © 2015 Elsevier Inc. All rights reserved.

Advanced Neutronics Tools for BWR Design Calculations

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

Santamarina, A.; Hfaiedh, N.; Letellier, R.

2006-07-01

This paper summarizes the developments implemented in the new APOLLO2.8 neutronics tool to meet the required target accuracy in LWR applications, particularly void effects and pin-by-pin power map in BWRs. The Method Of Characteristics was developed to allow efficient LWR assembly calculations in 2D-exact heterogeneous geometry; resonant reaction calculation was improved by the optimized SHEM-281 group mesh, which avoids resonance self-shielding approximation below 23 eV, and the new space-dependent method for resonant mixture that accounts for resonance overlapping. Furthermore, a new library CEA2005, processed from JEFF3.1 evaluations involving feedback from Critical Experiments and LWR P.I.E, is used. The specific '2005-2007more » BWR Plan' settled to demonstrate the validation/qualification of this neutronics tool is described. Some results from the validation process are presented: the comparison of APOLLO2.8 results to reference Monte Carlo TRIPOLI4 results on specific BWR benchmarks emphasizes the ability of the deterministic tool to calculate BWR assembly multiplication factor within 200 pcm accuracy for void fraction varying from 0 to 100%. The qualification process against the BASALA mock-up experiment stresses APOLLO2.8/CEA2005 performances: pin-by-pin power is always predicted within 2% accuracy, reactivity worth of B4C or Hf cruciform control blade, as well as Gd pins, is predicted within 1.2% accuracy. (authors)« less

Combined fluorescence and reflectance spectroscopy for in vivo quantification of cancer biomarkers in low- and high-grade glioma surgery

PubMed Central

Valdés, Pablo A.; Kim, Anthony; Leblond, Frederic; Conde, Olga M.; Harris, Brent T.; Paulsen, Keith D.; Wilson, Brian C.; Roberts, David W.

2011-01-01

Biomarkers are indicators of biological processes and hold promise for the diagnosis and treatment of disease. Gliomas represent a heterogeneous group of brain tumors with marked intra- and inter-tumor variability. The extent of surgical resection is a significant factor influencing post-surgical recurrence and prognosis. Here, we used fluorescence and reflectance spectral signatures for in vivo quantification of multiple biomarkers during glioma surgery, with fluorescence contrast provided by exogenously-induced protoporphyrin IX (PpIX) following administration of 5-aminolevulinic acid. We performed light-transport modeling to quantify multiple biomarkers indicative of tumor biological processes, including the local concentration of PpIX and associated photoproducts, total hemoglobin concentration, oxygen saturation, and optical scattering parameters. We developed a diagnostic algorithm for intra-operative tissue delineation that accounts for the combined tumor-specific predictive capabilities of these quantitative biomarkers. Tumor tissue delineation achieved accuracies of up to 94% (specificity = 94%, sensitivity = 94%) across a range of glioma histologies beyond current state-of-the-art optical approaches, including state-of-the-art fluorescence image guidance. This multiple biomarker strategy opens the door to optical methods for surgical guidance that use quantification of well-established neoplastic processes. Future work would seek to validate the predictive power of this proof-of-concept study in a separate larger cohort of patients. PMID:22112112

Combined fluorescence and reflectance spectroscopy for in vivo quantification of cancer biomarkers in low- and high-grade glioma surgery

NASA Astrophysics Data System (ADS)

Valdés, Pablo A.; Kim, Anthony; Leblond, Frederic; Conde, Olga M.; Harris, Brent T.; Paulsen, Keith D.; Wilson, Brian C.; Roberts, David W.

2011-11-01

Biomarkers are indicators of biological processes and hold promise for the diagnosis and treatment of disease. Gliomas represent a heterogeneous group of brain tumors with marked intra- and inter-tumor variability. The extent of surgical resection is a significant factor influencing post-surgical recurrence and prognosis. Here, we used fluorescence and reflectance spectral signatures for in vivo quantification of multiple biomarkers during glioma surgery, with fluorescence contrast provided by exogenously-induced protoporphyrin IX (PpIX) following administration of 5-aminolevulinic acid. We performed light-transport modeling to quantify multiple biomarkers indicative of tumor biological processes, including the local concentration of PpIX and associated photoproducts, total hemoglobin concentration, oxygen saturation, and optical scattering parameters. We developed a diagnostic algorithm for intra-operative tissue delineation that accounts for the combined tumor-specific predictive capabilities of these quantitative biomarkers. Tumor tissue delineation achieved accuracies of up to 94% (specificity = 94%, sensitivity = 94%) across a range of glioma histologies beyond current state-of-the-art optical approaches, including state-of-the-art fluorescence image guidance. This multiple biomarker strategy opens the door to optical methods for surgical guidance that use quantification of well-established neoplastic processes. Future work would seek to validate the predictive power of this proof-of-concept study in a separate larger cohort of patients.

Risk Factors in Preschool Children for Predicting Asthma During the Preschool Age and the Early School Age: a Systematic Review and Meta-Analysis.

PubMed

Bao, Yixia; Chen, Zhimin; Liu, Enmei; Xiang, Li; Zhao, Deyu; Hong, Jianguo

2017-11-18

The aim of this study was to identify risk factors of asthma among children < 6 years old (preschool age) for predicting asthma during the preschool age and early school age (≤ 10 years of age). MEDLINE, Cochrane, EMBASE, and Google Scholar databases were searched until June 30, 2017. Prospective or retrospective cohort and case-control studies were included. Studies had to have evaluated risk factors or a predictive model for developing asthma in children ≤ 6 years of age or persistent asthma in early school age. A total of 17 studies were included in the analysis. Factors associated with developing asthma in children ≤ 10 years of age (both pre-school and early school age) included male gender (pooled OR = 1.70, P < 0.001), atopic dermatitis (pooled OR = 2.02, P < 0.001), a family history of asthma (pooled OR = 2.20, P < 0.001), and serum IgE levels ≥ 60 kU/l or having specific IgE (pooled OR = 2.36, P < 0.001). A history of exposure to smoke or wheezing was also associated with persistent asthma in early school age (pooled OR = 1.51, P = 0.030 and pooled OR = 2.59, P < 0.001, respectively). In general, asthma predictive models (e.g., API, PIAMA, PAPS) had relatively low sensitivity (range, 21% to 71.4%) but high specificity (range, 69% to 98%). The study found that male gender, exposure to smoke, atopic dermatitis, family history of asthma, history of wheezing, and serum IgE level ≥ 60 kU/l or having specific IgE were significantly associated with developing asthma by either preschool or early school age. Asthma predictive models can be developed by those risk factors.

Biophysically inspired model for functionalized nanocarrier adhesion to cell surface: roles of protein expression and mechanical factors

NASA Astrophysics Data System (ADS)

Ramakrishnan, N.; Tourdot, Richard W.; Eckmann, David M.; Ayyaswamy, Portonovo S.; Muzykantov, Vladimir R.; Radhakrishnan, Ravi

2016-06-01

In order to achieve selective targeting of affinity-ligand coated nanoparticles to the target tissue, it is essential to understand the key mechanisms that govern their capture by the target cell. Next-generation pharmacokinetic (PK) models that systematically account for proteomic and mechanical factors can accelerate the design, validation and translation of targeted nanocarriers (NCs) in the clinic. Towards this objective, we have developed a computational model to delineate the roles played by target protein expression and mechanical factors of the target cell membrane in determining the avidity of functionalized NCs to live cells. Model results show quantitative agreement with in vivo experiments when specific and non-specific contributions to NC binding are taken into account. The specific contributions are accounted for through extensive simulations of multivalent receptor-ligand interactions, membrane mechanics and entropic factors such as membrane undulations and receptor translation. The computed NC avidity is strongly dependent on ligand density, receptor expression, bending mechanics of the target cell membrane, as well as entropic factors associated with the membrane and the receptor motion. Our computational model can predict the in vivo targeting levels of the intracellular adhesion molecule-1 (ICAM1)-coated NCs targeted to the lung, heart, kidney, liver and spleen of mouse, when the contributions due to endothelial capture are accounted for. The effect of other cells (such as monocytes, etc.) do not improve the model predictions at steady state. We demonstrate the predictive utility of our model by predicting partitioning coefficients of functionalized NCs in mice and human tissues and report the statistical accuracy of our model predictions under different scenarios.

Do the same factors predict outcome in schizophrenia and non-schizophrenia syndromes after first-episode psychosis? A two-year follow-up study.

PubMed

Peña, Javier; Segarra, Rafael; Ojeda, Natalia; García, Jon; Eguiluz, José I; Gutiérrez, Miguel

2012-06-01

The aim of this two-year longitudinal study was to identify the best baseline predictors of functional outcome in first-episode psychosis (FEP). We tested whether the same factors predict functional outcomes in two different subsamples of FEP patients: schizophrenia and non-schizophrenia syndrome groups. Ninety-five patients with FEP underwent a full clinical evaluation (i.e., PANSS, Mania, Depression and Insight). Functional outcome measurements included the WHO Disability Assessment Schedule (DAS-WHO), Global Assessment of Functioning (GAF) and Clinical Global Impression (CGI). Estimation of cognition was obtained by a neuropsychological battery which included attention, processing speed, language, memory and executive functioning. Greater severity of visuospatial functioning at baseline predicted poorer functional outcome as measured by the three functional scales (GAF, CGI and DAS-WHO) in the pooled FEP sample (explaining ut to the 12%, 9% and 10% of the variance, respectively). Negative symptoms also effectively contributed to predict GAF scores (8%). However, we obtained different predictive values after differentiating sample diagnoses. Processing speed significantly predicted most functional outcome measures in patients with schizophrenia, whereas visuospatial functioning was the only significant predictor of functional outcomes in the non-schizophrenia subgroup. Our results suggest that processing speed, visuospatial functioning and negative symptoms significantly (but differentially) predict outcomes in patients with FEP, depending on their clinical progression. For patients without a schizophrenia diagnosis, visuospatial functioning was the best predictor of functional outcome. The performance on processing speed seemed to be a key factor in more severe syndromes. However, only a small proportion of the variance could be explained by the model, so there must be many other factors that have to be considered. Copyright © 2012 Elsevier Ltd. All rights reserved.

[From "deadly quartet" to "metabolic syndrome". An analysis of its clinical relevance].

PubMed

Vancheri, Federico; Burgio, Antonio; Dovico, Rossana

2007-03-01

The metabolic syndrome denotes a clustering of specific risk factors for both cardiovascular disease and type 2 diabetes, whose underlying pathophysiology is believed to include insulin resistance. It has been widely reported that the syndrome is a simple clinical tool to identify people at high long term risk of cardiovascular disease and diabetes. However, its clinical importance is under debate. There are substantial uncertainties about the clinical definition of the syndrome, as to whether the risk factors clustering indicates a single unifying disorder, whether the risk conferred by the condition as a whole is higher risk than its individual components, and whether its predictive value of future cardiovascular events or diabetes is greater than established predicting models such as the Framingham Risk Score and the Diabetes Risk Score. We undertook an extensive review of the literature. Our analysis indicates that current definitions of the syndrome are incomplete or ambiguous, more than one pathophysiological process underlies the syndrome, although the combination of insulin resistance and hyperinsulinemia are related to most cases; the risk associated with the syndrome is no greater than that explained by the presence of its components, and the syndrome is less effective in predicting the future development of cardiovascular events and diabetes than established predicting models. Although the syndrome has some importance in understanding the pathophysiology of cardiovascular and diabetes risk factors clustering, its use as a clinical syndrome is not justified by current data.

Feasibility of developing LSI microcircuit reliability prediction models

NASA Technical Reports Server (NTRS)

Ryerson, C. M.

1972-01-01

In the proposed modeling approach, when any of the essential key factors are not known initially, they can be approximated in various ways with a known impact on the accuracy of the final predictions. For example, on any program where reliability predictions are started at interim states of project completion, a-priori approximate estimates of the key factors are established for making preliminary predictions. Later these are refined for greater accuracy as subsequent program information of a more definitive nature becomes available. Specific steps to develop, validate and verify these new models are described.

The Gastric/Pancreatic Amylase Ratio Predicts Postoperative Pancreatic Fistula With High Sensitivity and Specificity

PubMed Central

Jin, Shuo; Shi, Xiao-Ju; Sun, Xiao-Dong; Zhang, Ping; Lv, Guo-Yue; Du, Xiao-Hong; Wang, Si-Yuan; Wang, Guang-Yi

2015-01-01

Abstract This article aims to identify risk factors for postoperative pancreatic fistula (POPF) and evaluate the gastric/pancreatic amylase ratio (GPAR) on postoperative day (POD) 3 as a POPF predictor in patients who undergo pancreaticoduodenectomy (PD). POPF significantly contributes to mortality and morbidity in patients who undergo PD. Previously identified predictors for POPF often have low predictive accuracy. Therefore, accurate POPF predictors are needed. In this prospective cohort study, we measured the clinical and biochemical factors of 61 patients who underwent PD and diagnosed POPF according to the definition of the International Study Group of Pancreatic Fistula. We analyzed the association between POPF and various factors, identified POPF risk factors, and evaluated the predictive power of the GPAR on POD3 and the levels of serum and ascites amylase. Of the 61 patients, 21 developed POPF. The color of the pancreatic drain fluid, POD1 serum, POD1 median output of pancreatic drain fluid volume, and GPAR were significantly associated with POPF. The color of the pancreatic drain fluid and high GPAR were independent risk factors. Although serum and ascites amylase did not predict POPF accurately, the cutoff value was 1.24, and GPAR predicted POPF with high sensitivity and specificity. This is the first report demonstrating that high GPAR on POD3 is a risk factor for POPF and showing that GPAR is a more accurate predictor of POPF than the previously reported amylase markers. PMID:25621676

The gastric/pancreatic amylase ratio predicts postoperative pancreatic fistula with high sensitivity and specificity.

PubMed

Jin, Shuo; Shi, Xiao-Ju; Sun, Xiao-Dong; Zhang, Ping; Lv, Guo-Yue; Du, Xiao-Hong; Wang, Si-Yuan; Wang, Guang-Yi

2015-01-01

This article aims to identify risk factors for postoperative pancreatic fistula (POPF) and evaluate the gastric/pancreatic amylase ratio (GPAR) on postoperative day (POD) 3 as a POPF predictor in patients who undergo pancreaticoduodenectomy (PD).POPF significantly contributes to mortality and morbidity in patients who undergo PD. Previously identified predictors for POPF often have low predictive accuracy. Therefore, accurate POPF predictors are needed.In this prospective cohort study, we measured the clinical and biochemical factors of 61 patients who underwent PD and diagnosed POPF according to the definition of the International Study Group of Pancreatic Fistula. We analyzed the association between POPF and various factors, identified POPF risk factors, and evaluated the predictive power of the GPAR on POD3 and the levels of serum and ascites amylase.Of the 61 patients, 21 developed POPF. The color of the pancreatic drain fluid, POD1 serum, POD1 median output of pancreatic drain fluid volume, and GPAR were significantly associated with POPF. The color of the pancreatic drain fluid and high GPAR were independent risk factors. Although serum and ascites amylase did not predict POPF accurately, the cutoff value was 1.24, and GPAR predicted POPF with high sensitivity and specificity.This is the first report demonstrating that high GPAR on POD3 is a risk factor for POPF and showing that GPAR is a more accurate predictor of POPF than the previously reported amylase markers.

Simple processes drive unpredictable differences in estuarine fish assemblages: Baselines for understanding site-specific ecological and anthropogenic impacts

NASA Astrophysics Data System (ADS)

Sheaves, Marcus

2016-03-01

Predicting patterns of abundance and composition of biotic assemblages is essential to our understanding of key ecological processes, and our ability to monitor, evaluate and manage assemblages and ecosystems. Fish assemblages often vary from estuary to estuary in apparently unpredictable ways, making it challenging to develop a general understanding of the processes that determine assemblage composition. This makes it problematic to transfer understanding from one estuary situation to another and therefore difficult to assemble effective management plans or to assess the impacts of natural and anthropogenic disturbance. Although system-to-system variability is a common property of ecological systems, rather than being random it is the product of complex interactions of multiple causes and effects at a variety of spatial and temporal scales. I investigate the drivers of differences in estuary fish assemblages, to develop a simple model explaining the diversity and complexity of observed estuary-to-estuary differences, and explore its implications for management and conservation. The model attributes apparently unpredictable differences in fish assemblage composition from estuary to estuary to the interaction of species-specific, life history-specific and scale-specific processes. In explaining innate faunal differences among estuaries without the need to invoke complex ecological or anthropogenic drivers, the model provides a baseline against which the effects of additional natural and anthropogenic factors can be evaluated.

Development and Preliminary Performance of a Risk Factor Screen to Predict Posttraumatic Psychological Disorder After Trauma Exposure

PubMed Central

Carlson, Eve B.; Palmieri, Patrick A.; Spain, David A.

2017-01-01

Objective We examined data from a prospective study of risk factors that increase vulnerability or resilience, exacerbate distress, or foster recovery to determine whether risk factors accurately predict which individuals will later have high posttraumatic (PT) symptom levels and whether brief measures of risk factors also accurately predict later symptom elevations. Method Using data from 129 adults exposed to traumatic injury of self or a loved one, we conducted receiver operating characteristic (ROC) analyses of 14 risk factors assessed by full-length measures, determined optimal cutoff scores and calculated predictive performance for the nine that were most predictive. For five risk factors, we identified sets of items that accounted for 90% of variance in total scores and calculated predictive performance for sets of brief risk measures. Results A set of nine risk factors assessed by full measures identified 89% of those who later had elevated PT symptoms (sensitivity) and 78% of those who did not (specificity). A set of four brief risk factor measures assessed soon after injury identified 86% of those who later had elevated PT symptoms and 72% of those who did not. Conclusions Use of sets of brief risk factor measures shows promise of accurate prediction of PT psychological disorder and probable PTSD or depression. Replication of predictive accuracy is needed in a new and larger sample. PMID:28622811

Mismatch repair factor MSH2-MSH3 binds and alters the conformation of branched DNA structures predicted to form during genetic recombination.

PubMed

Surtees, Jennifer A; Alani, Eric

2006-07-14

Genetic studies in Saccharomyces cerevisiae predict that the mismatch repair (MMR) factor MSH2-MSH3 binds and stabilizes branched recombination intermediates that form during single strand annealing and gene conversion. To test this model, we constructed a series of DNA substrates that are predicted to form during these recombination events. We show in an electrophoretic mobility shift assay that S. cerevisiae MSH2-MSH3 specifically binds branched DNA substrates containing 3' single-stranded DNA and that ATP stimulates its release from these substrates. Chemical footprinting analyses indicate that MSH2-MSH3 specifically binds at the double-strand/single-strand junction of branched substrates, alters its conformation and opens up the junction. Therefore, MSH2-MSH3 binding to its substrates creates a unique nucleoprotein structure that may signal downstream steps in repair that include interactions with MMR and nucleotide excision repair factors.

Characterizing the Ruminative Process in Young Adolescents

PubMed Central

Hilt, Lori M.; Pollak, Seth D.

2014-01-01

Objective Rumination involves repeatedly and passively dwelling on negative feelings and brooding about their causes and consequences. Prior work has found that rumination predicts many forms of psychopathology including anxiety, binge eating, binge drinking, self-injury, and especially depression (Nolen-Hoeksema, Wisco, & Lyubomirsky, 2008). In the present study, we attempt to characterize the ruminative process in real time in young adolescents, specifically by examining factors that predict rumination following an interpersonal stressor. Method A community sample of 105 youth ages 9-14 (70% girls; 66% Caucasian) completed questionnaires regarding depressive symptoms and trait rumination along with an assessment of selective attention using an emotional faces dot-probe task. Participants then underwent an interpersonal stressor and audio rumination induction in the laboratory during which time thoughts were sampled regularly and coded. Results Results indicate that negative self-referential thought is a common response to the stressor and is predicted by trait rumination scores. While most participants were able to disengage from this type of thinking, 10.5% persisted through (i.e., ruminated) until the end of the study. These individuals were characterized by higher depressive symptoms and an attentional bias away from happy (relative to neutral) faces. Conclusions Differences in attentional processes may characterize rumination in youth. Implications for the measurement of rumination as well as treatment are discussed. PMID:23477416

Simplified procedures for correlation of experimentally measured and predicted thrust chamber performance

NASA Technical Reports Server (NTRS)

Powell, W. B.

1973-01-01

Thrust chamber performance is evaluated in terms of an analytical model incorporating all the loss processes that occur in a real rocket motor. The important loss processes in the real thrust chamber were identified, and a methodology and recommended procedure for predicting real thrust chamber vacuum specific impulse were developed. Simplified equations for the calculation of vacuum specific impulse are developed to relate the delivered performance (both vacuum specific impulse and characteristic velocity) to the ideal performance as degraded by the losses corresponding to a specified list of loss processes. These simplified equations enable the various performance loss components, and the corresponding efficiencies, to be quantified separately (except that interaction effects are arbitrarily assigned in the process). The loss and efficiency expressions presented can be used to evaluate experimentally measured thrust chamber performance, to direct development effort into the areas most likely to yield improvements in performance, and as a basis to predict performance of related thrust chamber configurations.

Detection of Cardiovascular Disease Risk's Level for Adults Using Naive Bayes Classifier.

PubMed

Miranda, Eka; Irwansyah, Edy; Amelga, Alowisius Y; Maribondang, Marco M; Salim, Mulyadi

2016-07-01

The number of deaths caused by cardiovascular disease and stroke is predicted to reach 23.3 million in 2030. As a contribution to support prevention of this phenomenon, this paper proposes a mining model using a naïve Bayes classifier that could detect cardiovascular disease and identify its risk level for adults. The process of designing the method began by identifying the knowledge related to the cardiovascular disease profile and the level of cardiovascular disease risk factors for adults based on the medical record, and designing a mining technique model using a naïve Bayes classifier. Evaluation of this research employed two methods: accuracy, sensitivity, and specificity calculation as well as an evaluation session with cardiologists and internists. The characteristics of cardiovascular disease are identified by its primary risk factors. Those factors are diabetes mellitus, the level of lipids in the blood, coronary artery function, and kidney function. Class labels were assigned according to the values of these factors: risk level 1, risk level 2 and risk level 3. The evaluation of the classifier performance (accuracy, sensitivity, and specificity) in this research showed that the proposed model predicted the class label of tuples correctly (above 80%). More than eighty percent of respondents (including cardiologists and internists) who participated in the evaluation session agree till strongly agreed that this research followed medical procedures and that the result can support medical analysis related to cardiovascular disease. The research showed that the proposed model achieves good performance for risk level detection of cardiovascular disease.

Which Working Memory Functions Predict Intelligence?

ERIC Educational Resources Information Center

Oberauer, Klaus; Sub, Heinz-Martin; Wilhelm, Oliver; Wittmann, Werner W.

2008-01-01

Investigates the relationship between three factors of working memory (storage and processing, relational integration, and supervision) and four factors of intelligence (reasoning, speed, memory, and creativity) using structural equation models. Relational integration predicted reasoning ability at least as well as the storage-and-processing…

The individual therapy process questionnaire: development and validation of a revised measure to evaluate general change mechanisms in psychotherapy.

PubMed

Mander, Johannes

2015-01-01

There is a dearth of measures specifically designed to assess empirically validated mechanisms of therapeutic change. To fill in this research gap, the aim of the current study was to develop a measure that covers a large variety of empirically validated mechanisms of change with corresponding versions for the patient and therapist. To develop an instrument that is based on several important change process frameworks, we combined two established change mechanisms instruments: the Scale for the Multiperspective Assessment of General Change Mechanisms in Psychotherapy (SACiP) and the Scale of the Therapeutic Alliance-Revised (STA-R). In our study, 457 psychosomatic inpatients completed the SACiP and the STA-R and diverse outcome measures in early, middle and late stages of psychotherapy. Data analyses were conducted using factor analyses and multilevel modelling. The psychometric properties of the resulting Individual Therapy Process Questionnaire were generally good to excellent, as demonstrated by (a) exploratory factor analyses on both patient and therapist ratings, (b) CFA on later measuring times, (c) high internal consistencies and (d) significant outcome predictive effects. The parallel forms of the ITPQ deliver opportunities to compare the patient and therapist perspectives for a broader range of facets of change mechanisms than was hitherto possible. Consequently, the measure can be applied in future research to more specifically analyse different change mechanism profiles in session-to-session development and outcome prediction. Key Practitioner Message This article describes the development of an instrument that measures general mechanisms of change in psychotherapy from both the patient and therapist perspectives. Post-session item ratings from both the patient and therapist can be used as feedback to optimize therapeutic processes. We provide a detailed discussion of measures developed to evaluate therapeutic change mechanisms. Copyright © 2014 John Wiley & Sons, Ltd.

Cerebellar tDCS Modulates Neural Circuits during Semantic Prediction: A Combined tDCS-fMRI Study.

PubMed

D'Mello, Anila M; Turkeltaub, Peter E; Stoodley, Catherine J

2017-02-08

It has been proposed that the cerebellum acquires internal models of mental processes that enable prediction, allowing for the optimization of behavior. In language, semantic prediction speeds speech production and comprehension. Right cerebellar lobules VI and VII (including Crus I/II) are engaged during a variety of language processes and are functionally connected with cerebral cortical language networks. Further, right posterolateral cerebellar neuromodulation modifies behavior during predictive language processing. These data are consistent with a role for the cerebellum in semantic processing and semantic prediction. We combined transcranial direct current stimulation (tDCS) and fMRI to assess the behavioral and neural consequences of cerebellar tDCS during a sentence completion task. Task-based and resting-state fMRI data were acquired in healthy human adults ( n = 32; μ = 23.1 years) both before and after 20 min of 1.5 mA anodal ( n = 18) or sham ( n = 14) tDCS applied to the right posterolateral cerebellum. In the sentence completion task, the first four words of the sentence modulated the predictability of the final target word. In some sentences, the preceding context strongly predicted the target word, whereas other sentences were nonpredictive. Completion of predictive sentences increased activation in right Crus I/II of the cerebellum. Relative to sham tDCS, anodal tDCS increased activation in right Crus I/II during semantic prediction and enhanced resting-state functional connectivity between hubs of the reading/language networks. These results are consistent with a role for the right posterolateral cerebellum beyond motor aspects of language, and suggest that cerebellar internal models of linguistic stimuli support semantic prediction. SIGNIFICANCE STATEMENT Cerebellar involvement in language tasks and language networks is now well established, yet the specific cerebellar contribution to language processing remains unclear. It is thought that the cerebellum acquires internal models of mental processes that enable prediction, allowing for the optimization of behavior. Here we combined neuroimaging and neuromodulation to provide evidence that the cerebellum is specifically involved in semantic prediction during sentence processing. We found that activation within right Crus I/II was enhanced when semantic predictions were made, and we show that modulation of this region with transcranial direct current stimulation alters both activation patterns and functional connectivity within whole-brain language networks. For the first time, these data show that cerebellar neuromodulation impacts activation patterns specifically during predictive language processing. Copyright © 2017 the authors 0270-6474/17/371604-10$15.00/0.

Explosion of autoimmune diseases and the mosaic of old and novel factors

PubMed Central

Agmon-Levin, Nancy; Lian, Zhexiong; Shoenfeld, Yehuda

2011-01-01

In recent decades, an enormous effort has been made to elucidate the pathogenesis of autoimmune and autoinflammatory diseases. Autoimmunity is a multifactorial process in which genetic, immunological, environmental and hormonal factors play in concert, together representing what was termed years ago the ‘mosaic of autoimmunity'. To date, more than 80 systemic and organ-specific autoimmune diseases have been defined, and their cumulative burden is substantial, both medically and financially. Furthermore, the burden of autoimmune and autoinflammatory diseases is rising, making these diseases a ubiquitous global phenomenon that is predicted to further increase in the coming decades. In this issue of the journal, additional aspects of autoimmunity are detailed. Immune dysregulation and loss of self-tolerance are the cornerstones of autoimmunity. PMID:21358666

A dynamic, climate-driven model of Rift Valley fever.

PubMed

Leedale, Joseph; Jones, Anne E; Caminade, Cyril; Morse, Andrew P

2016-03-31

Outbreaks of Rift Valley fever (RVF) in eastern Africa have previously occurred following specific rainfall dynamics and flooding events that appear to support the emergence of large numbers of mosquito vectors. As such, transmission of the virus is considered to be sensitive to environmental conditions and therefore changes in climate can impact the spatiotemporal dynamics of epizootic vulnerability. Epidemiological information describing the methods and parameters of RVF transmission and its dependence on climatic factors are used to develop a new spatio-temporal mathematical model that simulates these dynamics and can predict the impact of changes in climate. The Liverpool RVF (LRVF) model is a new dynamic, process-based model driven by climate data that provides a predictive output of geographical changes in RVF outbreak susceptibility as a result of the climate and local livestock immunity. This description of the multi-disciplinary process of model development is accessible to mathematicians, epidemiological modellers and climate scientists, uniting dynamic mathematical modelling, empirical parameterisation and state-of-the-art climate information.

Japanese scoring systems to predict resistance to intravenous immunoglobulin in Kawasaki disease were unreliable for Caucasian Israeli children.

PubMed

Arane, Karen; Mendelsohn, Kerry; Mimouni, Michael; Mimouni, Francis; Koren, Yael; Simon, Dafna Brik; Bahat, Hilla; Helou, Mona Hanna; Mendelson, Amir; Hezkelo, Nofar; Glatstein, Miguel; Berkun, Yackov; Eisenstein, Eli; Aviel, Yonatan Butbul; Brik, Riva; Hashkes, Philip J; Uziel, Yosef; Harel, Liora; Amarilyo, Gil

2018-05-24

This study assessed the validity of using established Japanese risk scoring methods to predict intravenous immunoglobulin (IVIG) resistance to Kawasaki disease in Israeli children. We reviewed the medical records of 282 patients (70% male) with Kawasaki disease from six Israeli medical centres between 2004-2013. Their mean age was 2.5 years. The risk scores were calculated using the Kobayashi, Sano and Egami scoring methods and analysed to determine if a higher risk score predicted IVIG resistance in this population. Factors that predicted a lack of response to the initial IVIG dose were identified. We found that 18% did not respond to the first IVIG dose. The three scoring methods were unable to reliably predict IVIG resistance, with sensitivities of 23-32% and specificities of 67-87%. Calculating a predictive score that was specific for this population was also unsuccessful. The factors that predicted a lacked of response to the first IVIG dose included low albumin, elevated total bilirubin and ethnicity. The established risk scoring methods created for Japanese populations with Kawasaki disease were not suitable for predicting IVIG resistance in Caucasian Israeli children and we were unable to create a specific scoring method that was able to do this. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Characterization and optimization of cell seeding in scaffolds by factorial design: quality by design approach for skeletal tissue engineering.

PubMed

Chen, Yantian; Bloemen, Veerle; Impens, Saartje; Moesen, Maarten; Luyten, Frank P; Schrooten, Jan

2011-12-01

Cell seeding into scaffolds plays a crucial role in the development of efficient bone tissue engineering constructs. Hence, it becomes imperative to identify the key factors that quantitatively predict reproducible and efficient seeding protocols. In this study, the optimization of a cell seeding process was investigated using design of experiments (DOE) statistical methods. Five seeding factors (cell type, scaffold type, seeding volume, seeding density, and seeding time) were selected and investigated by means of two response parameters, critically related to the cell seeding process: cell seeding efficiency (CSE) and cell-specific viability (CSV). In addition, cell spatial distribution (CSD) was analyzed by Live/Dead staining assays. Analysis identified a number of statistically significant main factor effects and interactions. Among the five seeding factors, only seeding volume and seeding time significantly affected CSE and CSV. Also, cell and scaffold type were involved in the interactions with other seeding factors. Within the investigated ranges, optimal conditions in terms of CSV and CSD were obtained when seeding cells in a regular scaffold with an excess of medium. The results of this case study contribute to a better understanding and definition of optimal process parameters for cell seeding. A DOE strategy can identify and optimize critical process variables to reduce the variability and assists in determining which variables should be carefully controlled during good manufacturing practice production to enable a clinically relevant implant.

Armed Services Vocational Aptitude Battery (ASVAB): Predicting Military Criteria from General and Specific Abilities

DTIC Science & Technology

1990-11-01

intelligence was composed of two factors: one general factor, g, which was common to all tests of cogr’itive ability, and a specific factor s that...s in piediction prompted a special edition of the Journal of Vocational Behavior ( Gottfredson , 1986). Mayr (1982) and Weinberg (1988) have described...Personnel Psychology, 26, 461-477. Gottfredson , L.S. (1986). Foreword, the g factor in emp~oyment. Journal of Vocational Behavior, 29, 293-296. Guzzo

Analysis of algae growth mechanism and water bloom prediction under the effect of multi-affecting factor.

PubMed

Wang, Li; Wang, Xiaoyi; Jin, Xuebo; Xu, Jiping; Zhang, Huiyan; Yu, Jiabin; Sun, Qian; Gao, Chong; Wang, Lingbin

2017-03-01

The formation process of algae is described inaccurately and water blooms are predicted with a low precision by current methods. In this paper, chemical mechanism of algae growth is analyzed, and a correlation analysis of chlorophyll-a and algal density is conducted by chemical measurement. Taking into account the influence of multi-factors on algae growth and water blooms, the comprehensive prediction method combined with multivariate time series and intelligent model is put forward in this paper. Firstly, through the process of photosynthesis, the main factors that affect the reproduction of the algae are analyzed. A compensation prediction method of multivariate time series analysis based on neural network and Support Vector Machine has been put forward which is combined with Kernel Principal Component Analysis to deal with dimension reduction of the influence factors of blooms. Then, Genetic Algorithm is applied to improve the generalization ability of the BP network and Least Squares Support Vector Machine. Experimental results show that this method could better compensate the prediction model of multivariate time series analysis which is an effective way to improve the description accuracy of algae growth and prediction precision of water blooms.

Factors Predicting Academic Success in Second and Third Language among Russian-Speaking Immigrant Students Studying in Israeli Schools

ERIC Educational Resources Information Center

Haim, Orly

2014-01-01

The purpose of this study was to investigate the factors predicting academic proficiency (AP), the specialised domains required for performing academic tasks, among Russian speaking (L1) immigrants currently studying Hebrew as a second language (L2) and English as a third language (L3) in Israeli schools. Specifically, the study examined the…

Predictive Factors in Undergraduates' Involvement in Campus Secret Cults in Public Universities in Edo State of Nigeria

ERIC Educational Resources Information Center

Azetta Arhedo, Philip; Aluede, Oyaziwo; Adomeh, Ilu O. C.

2011-01-01

This study examined the predictive factors in undergraduates' involvement in campus secret cults in public universities in Edo State of Nigeria. The study employed the descriptive method, specifically the survey format. A random sample of three hundred and eighty (380) undergraduates was drawn from the two public universities. Data were elicited…

Implementation of Cyber-Physical Production Systems for Quality Prediction and Operation Control in Metal Casting

PubMed Central

Lee, JuneHyuck; Noh, Sang Do; Kim, Hyun-Jung; Kang, Yong-Shin

2018-01-01

The prediction of internal defects of metal casting immediately after the casting process saves unnecessary time and money by reducing the amount of inputs into the next stage, such as the machining process, and enables flexible scheduling. Cyber-physical production systems (CPPS) perfectly fulfill the aforementioned requirements. This study deals with the implementation of CPPS in a real factory to predict the quality of metal casting and operation control. First, a CPPS architecture framework for quality prediction and operation control in metal-casting production was designed. The framework describes collaboration among internet of things (IoT), artificial intelligence, simulations, manufacturing execution systems, and advanced planning and scheduling systems. Subsequently, the implementation of the CPPS in actual plants is described. Temperature is a major factor that affects casting quality, and thus, temperature sensors and IoT communication devices were attached to casting machines. The well-known NoSQL database, HBase and the high-speed processing/analysis tool, Spark, are used for IoT repository and data pre-processing, respectively. Many machine learning algorithms such as decision tree, random forest, artificial neural network, and support vector machine were used for quality prediction and compared with R software. Finally, the operation of the entire system is demonstrated through a CPPS dashboard. In an era in which most CPPS-related studies are conducted on high-level abstract models, this study describes more specific architectural frameworks, use cases, usable software, and analytical methodologies. In addition, this study verifies the usefulness of CPPS by estimating quantitative effects. This is expected to contribute to the proliferation of CPPS in the industry. PMID:29734699

Partner aggression in high-risk families from birth to age 3 years: associations with harsh parenting and child maladjustment.

PubMed

Graham, Alice M; Kim, Hyoun K; Fisher, Philip A

2012-02-01

Aggression between partners represents a potential guiding force in family dynamics. However, research examining the influence of partner aggression (physically and psychologically aggressive acts by both partners) on harsh parenting and young child adjustment has been limited by a frequent focus on low-risk samples and by the examination of partner aggression at a single time point. Especially in the context of multiple risk factors and around transitions such as childbirth, partner aggression might be better understood as a dynamic process. In the present study, longitudinal trajectories of partner aggression from birth to age 3 years in a large, high-risk, and ethnically diverse sample (N = 461) were examined. Specific risk factors were tested as predictors of aggression over time, and the longitudinal effects of partner aggression on maternal harsh parenting and child maladjustment were examined. Partner aggression decreased over time, with higher maternal depression and lower maternal age predicting greater decreases in partner aggression. While taking into account contextual and psychosocial risk factors, higher partner aggression measured at birth and a smaller decrease over time independently predicted higher levels of maternal harsh parenting at age 3 years. Initial level of partner aggression and change over time predicted child maladjustment indirectly (via maternal harsh parenting). The implications of understanding change in partner aggression over time as a path to harsh parenting and young children's maladjustment in the context of multiple risk factors are discussed.

Partner Aggression in High-Risk Families From Birth to Age 3: Associations With Harsh Parenting and Child Maladjustment

PubMed Central

Graham, Alice M.; Kim, Hyoun K.; Fisher, Philip A.

2012-01-01

Aggression between partners represents a potential guiding force in family dynamics. However, research examining the influence of partner aggression (physically and psychologically aggressive acts by both partners) on harsh parenting and young child adjustment has been limited by a frequent focus on low risk samples and by the examination of partner aggression at a single time point. Especially in the context of multiple risk factors and around transitions such as childbirth, partner aggression might be better understood as a dynamic process. In the present study, longitudinal trajectories of partner aggression from birth to age 3 years in a large, high-risk, and ethnically diverse sample (N = 461) were examined. Specific risk factors were tested as predictors of aggression over time, and the longitudinal effects of partner aggression on maternal harsh parenting and child maladjustment were examined. Partner aggression decreased over time, with higher maternal depression and lower maternal age predicting greater decreases in partner aggression. While taking into account contextual and psychosocial risk factors, higher partner aggression measured at birth and a smaller decrease over time independently predicted higher levels of maternal harsh parenting at age 3 years. Initial level of partner aggression and change over time predicted child maladjustment indirectly (via maternal harsh parenting). The implications of understanding change in partner aggression over time as a path to harsh parenting and young children's maladjustment in the context of multiple risk factors are discussed. PMID:22201248

A gentle introduction to quantile regression for ecologists

USGS Publications Warehouse

Cade, B.S.; Noon, B.R.

2003-01-01

Quantile regression is a way to estimate the conditional quantiles of a response variable distribution in the linear model that provides a more complete view of possible causal relationships between variables in ecological processes. Typically, all the factors that affect ecological processes are not measured and included in the statistical models used to investigate relationships between variables associated with those processes. As a consequence, there may be a weak or no predictive relationship between the mean of the response variable (y) distribution and the measured predictive factors (X). Yet there may be stronger, useful predictive relationships with other parts of the response variable distribution. This primer relates quantile regression estimates to prediction intervals in parametric error distribution regression models (eg least squares), and discusses the ordering characteristics, interval nature, sampling variation, weighting, and interpretation of the estimates for homogeneous and heterogeneous regression models.

Typical intellectual engagement, Big Five personality traits, approaches to learning and cognitive ability predictors of academic performance.

PubMed

Furnham, Adrian; Monsen, Jeremy; Ahmetoglu, Gorkan

2009-12-01

Both ability (measured by power tests) and non-ability (measured by preference tests) individual difference measures predict academic school outcomes. These include fluid as well as crystalized intelligence, personality traits, and learning styles. This paper examines the incremental validity of five psychometric tests and the sex and age of pupils to predict their General Certificate in Secondary Education (GCSE) test results. The aim was to determine how much variance ability and non-ability tests can account for in predicting specific GCSE exam scores. The sample comprised 212 British schoolchildren. Of these, 123 were females. Their mean age was 15.8 years (SD 0.98 years). Pupils completed three self-report tests: the Neuroticism-Extroversion-Openness-Five-Factor Inventory (NEO-FFI) which measures the 'Big Five' personality traits, (Costa & McCrae, 1992); the Typical Intellectual Engagement Scale (Goff & Ackerman, 1992) and a measure of learning style, the Study Process Questionnaire (SPQ; Biggs, 1987). They also completed two ability tests: the Wonderlic Personnel Test (Wonderlic, 1992) a short measure of general intelligence and the General Knowledge Test (Irving, Cammock, & Lynn, 2001) a measure of crystallized intelligence. Six months later they took their (10th grade) GCSE exams comprising four 'core' compulsory exams as well as a number of specific elective subjects. Correlational analysis suggested that intelligence was the best predictors of school results. Preference test measures accounted for relatively little variance. Regressions indicated that over 50% of the variance in school exams for English (Literature and Language) and Maths and Science combined could be accounted for by these individual difference factors. Data from less than an hour's worth of testing pupils could predict school exam results 6 months later. These tests could, therefore, be used to reliably inform important decisions about how pupils are taught.

Empathy-Related Responses to Depicted People in Art Works

PubMed Central

Kesner, Ladislav; Horáček, Jiří

2017-01-01

Existing theories of empathic response to visual art works postulate the primacy of automatic embodied reaction to images based on mirror neuron mechanisms. Arguing for a more inclusive concept of empathy-related response and integrating four distinct bodies of literature, we discuss contextual, and personal factors which modulate empathic response to depicted people. We then present an integrative model of empathy-related responses to depicted people in art works. The model assumes that a response to empathy-eliciting figural artworks engages the dynamic interaction of two mutually interlinked sets of processes: socio-affective/cognitive processing, related to the person perception, and esthetic processing, primarily concerned with esthetic appreciation and judgment and attention to non-social aspects of the image. The model predicts that the specific pattern of interaction between empathy-related and esthetic processing is co-determined by several sets of factors: (i) the viewer's individual characteristics, (ii) the context variables (which include various modes of priming by narratives and other images), (iii) multidimensional features of the image, and (iv) aspects of a viewer's response. Finally we propose that the model is implemented by the interaction of functionally connected brain networks involved in socio-cognitive and esthetic processing. PMID:28286487

Tracking competition and cognitive control during language comprehension with multi-voxel pattern analysis

PubMed Central

Musz, Elizabeth; Thompson-Schill, Sharon L.

2017-01-01

To successfully comprehend a sentence that contains a homonym, readers must select the ambiguous word’s context-appropriate meaning. The outcome of this process is influenced both by top-down contextual support and bottom-up, word-specific characteristics. We examined how these factors jointly affect the neural signatures of lexical ambiguity resolution. We measured the similarity between multi-voxel patterns evoked by the same homonym in two distinct linguistic contexts: once after subjects read sentences that biased interpretation toward each homonym’s most frequent, dominant meaning, and again after interpretation was biased toward a weaker, subordinate meaning. We predicted that, following a subordinate-biasing context, the dominant yet inappropriate meaning would nevertheless compete for activation, manifesting in increased similarity between the neural patterns evoked by the two word meanings. In left anterior temporal lobe (ATL), degree of within-word pattern similarity was positively predicted by the association strength of each homonym’s dominant meaning. Further, within-word pattern similarity in left ATL was negatively predicted by item-specific responses in a region of left ventrolateral prefrontal cortex (VLPFC) sensitive to semantic conflict. These findings have implications for psycholinguistic models of lexical ambiguity resolution, and for the role of left VLPFC function during this process. Moreover, these findings demonstrate the utility of item-level, similarity-based analyses of fMRI data for our understanding of competition between co-activated word meanings during language comprehension. PMID:27898341

Learning the facts in medical school is not enough: which factors predict successful application of procedural knowledge in a laboratory setting?

PubMed Central

2013-01-01

Background Medical knowledge encompasses both conceptual (facts or “what” information) and procedural knowledge (“how” and “why” information). Conceptual knowledge is known to be an essential prerequisite for clinical problem solving. Primarily, medical students learn from textbooks and often struggle with the process of applying their conceptual knowledge to clinical problems. Recent studies address the question of how to foster the acquisition of procedural knowledge and its application in medical education. However, little is known about the factors which predict performance in procedural knowledge tasks. Which additional factors of the learner predict performance in procedural knowledge? Methods Domain specific conceptual knowledge (facts) in clinical nephrology was provided to 80 medical students (3rd to 5th year) using electronic flashcards in a laboratory setting. Learner characteristics were obtained by questionnaires. Procedural knowledge in clinical nephrology was assessed by key feature problems (KFP) and problem solving tasks (PST) reflecting strategic and conditional knowledge, respectively. Results Results in procedural knowledge tests (KFP and PST) correlated significantly with each other. In univariate analysis, performance in procedural knowledge (sum of KFP+PST) was significantly correlated with the results in (1) the conceptual knowledge test (CKT), (2) the intended future career as hospital based doctor, (3) the duration of clinical clerkships, and (4) the results in the written German National Medical Examination Part I on preclinical subjects (NME-I). After multiple regression analysis only clinical clerkship experience and NME-I performance remained independent influencing factors. Conclusions Performance in procedural knowledge tests seems independent from the degree of domain specific conceptual knowledge above a certain level. Procedural knowledge may be fostered by clinical experience. More attention should be paid to the interplay of individual clinical clerkship experiences and structured teaching of procedural knowledge and its assessment in medical education curricula. PMID:23433202

The Role of Dysfunctional Myths in a Decision-Making Process under Bounded Rationality: A Complex Dynamical Systems Perspective.

PubMed

Stamovlasis, Dimitrios; Vaiopoulou, Julie

2017-07-01

The present study examines the factors influencing a decision-making process, with specific focus on the role of dysfunctional myths (DM). DM are thoughts or beliefs that are rather irrational, however influential to people's decisions. In this paper a decision-making process regarding the career choice of university students majoring in natural sciences and education (N=496) is examined by analyzing survey data taken via Career Decision Making Difficulties Questionnaire (CDDQ). The difficulty of making the choice and the certainty about one's decision were the state variables, while the independent variables were factors related to the lack of information or knowledge needed, which actually reflect a bounded rationality. Cusp catastrophe analysis, based on both least squares and maximum likelihood procedures, showed that the nonlinear models predicting the two state variables were superior to linear alternatives. Factors related to lack of knowledge about the steps involved in the process of career decision-making, lack of information about the various occupations, lack of information about self and lack of motivation acted as asymmetry, while dysfunctional myths acted as bifurcation factor for both state variables. The catastrophe model, grounded in empirical data, revealed a unique role for DM and a better interpretation within the context of complexity and the notion of bounded rationality. The analysis opens the nonlinear dynamical systems (NDS) perspective in studying decision-making processes. Theoretical and practical implications are discussed.

The effects of early positive parenting and developmental delay status on child emotion dysregulation.

PubMed

Norona, A N; Baker, B L

2017-02-01

Emotion regulation has been identified as a robust predictor of adaptive functioning across a variety of domains (Aldao et al. ). Furthermore, research examining early predictors of competence and deficits in ER suggests that factors internal to the individual (e.g. neuroregulatory reactivity, behavioural traits and cognitive ability) and external to the individual (e.g. caregiving styles and explicit ER training) contribute to the development of ER (Calkins ). Many studies have focused on internal sources or external sources; however, few have studied them simultaneously within one model, especially in studies examining children with developmental delays (DD). Here, we addressed this specific research gap and examined the contributions of one internal factor and one external factor on emotion dysregulation outcomes in middle childhood. Specifically, our current study used structural equation modelling (SEM) to examine prospective, predictive relationships between DD status, positive parenting at age 4 years and child emotion dysregulation at age 7 years. Participants were 151 families in the Collaborative Family Study, a longitudinal study of young children with and without DD. A positive parenting factor was composed of sensitivity and scaffolding scores from mother-child interactions at home and in the research centre at child age 4 years. A child dysregulation factor was composed of a dysregulation code from mother-child interactions and a parent-report measure of ER and lability/negativity at age 7 years. Finally, we tested the hypothesis that positive parenting would mediate the relationship between DD and child dysregulation. Mothers of children with DD exhibited fewer sensitive and scaffolding behaviours compared with mothers of typically developing children, and children with DD were more dysregulated on all measures of ER. SEM revealed that both DD status and early positive parenting predicted emotion dysregulation in middle childhood. Furthermore, findings provided support for our hypothesis that early positive parenting mediated the relationship between DD and dysregulation. This work enhances our understanding of the development of ER across childhood and how endogenous child factors (DD status) and exogenous family factors (positive parenting) affect this process. Our findings provide clear implications for early intervention programmes for children with DD. Because of the predictive relationships between (a) developmental status and ER and (b) parenting and ER, the results imply that sensitive parenting behaviours should be specifically targeted in parent interventions for children with DD. © 2016 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

Correlation of proteome-wide changes with social immunity behaviors provides insight into resistance to the parasitic mite, Varroa destructor, in the honey bee (Apis mellifera)

PubMed Central

2012-01-01

Background Disease is a major factor driving the evolution of many organisms. In honey bees, selection for social behavioral responses is the primary adaptive process facilitating disease resistance. One such process, hygienic behavior, enables bees to resist multiple diseases, including the damaging parasitic mite Varroa destructor. The genetic elements and biochemical factors that drive the expression of these adaptations are currently unknown. Proteomics provides a tool to identify proteins that control behavioral processes, and these proteins can be used as biomarkers to aid identification of disease tolerant colonies. Results We sampled a large cohort of commercial queen lineages, recording overall mite infestation, hygiene, and the specific hygienic response to V. destructor. We performed proteome-wide correlation analyses in larval integument and adult antennae, identifying several proteins highly predictive of behavior and reduced hive infestation. In the larva, response to wounding was identified as a key adaptive process leading to reduced infestation, and chitin biosynthesis and immune responses appear to represent important disease resistant adaptations. The speed of hygienic behavior may be underpinned by changes in the antenna proteome, and chemosensory and neurological processes could also provide specificity for detection of V. destructor in antennae. Conclusions Our results provide, for the first time, some insight into how complex behavioural adaptations manifest in the proteome of honey bees. The most important biochemical correlations provide clues as to the underlying molecular mechanisms of social and innate immunity of honey bees. Such changes are indicative of potential divergence in processes controlling the hive-worker maturation. PMID:23021491

Correlation of proteome-wide changes with social immunity behaviors provides insight into resistance to the parasitic mite, Varroa destructor, in the honey bee (Apis mellifera).

PubMed

Parker, Robert; Guarna, M Marta; Melathopoulos, Andony P; Moon, Kyung-Mee; White, Rick; Huxter, Elizabeth; Pernal, Stephen F; Foster, Leonard J

2012-06-29

Disease is a major factor driving the evolution of many organisms. In honey bees, selection for social behavioral responses is the primary adaptive process facilitating disease resistance. One such process, hygienic behavior, enables bees to resist multiple diseases, including the damaging parasitic mite Varroa destructor. The genetic elements and biochemical factors that drive the expression of these adaptations are currently unknown. Proteomics provides a tool to identify proteins that control behavioral processes, and these proteins can be used as biomarkers to aid identification of disease tolerant colonies. We sampled a large cohort of commercial queen lineages, recording overall mite infestation, hygiene, and the specific hygienic response to V. destructor. We performed proteome-wide correlation analyses in larval integument and adult antennae, identifying several proteins highly predictive of behavior and reduced hive infestation. In the larva, response to wounding was identified as a key adaptive process leading to reduced infestation, and chitin biosynthesis and immune responses appear to represent important disease resistant adaptations. The speed of hygienic behavior may be underpinned by changes in the antenna proteome, and chemosensory and neurological processes could also provide specificity for detection of V. destructor in antennae. Our results provide, for the first time, some insight into how complex behavioural adaptations manifest in the proteome of honey bees. The most important biochemical correlations provide clues as to the underlying molecular mechanisms of social and innate immunity of honey bees. Such changes are indicative of potential divergence in processes controlling the hive-worker maturation.

In silico mining and PCR-based approaches to transcription factor discovery in non-model plants: gene discovery of the WRKY transcription factors in conifers.

PubMed

Liu, Jun-Jun; Xiang, Yu

2011-01-01

WRKY transcription factors are key regulators of numerous biological processes in plant growth and development, as well as plant responses to abiotic and biotic stresses. Research on biological functions of plant WRKY genes has focused in the past on model plant species or species with largely characterized transcriptomes. However, a variety of non-model plants, such as forest conifers, are essential as feed, biofuel, and wood or for sustainable ecosystems. Identification of WRKY genes in these non-model plants is equally important for understanding the evolutionary and function-adaptive processes of this transcription factor family. Because of limited genomic information, the rarity of regulatory gene mRNAs in transcriptomes, and the sequence divergence to model organism genes, identification of transcription factors in non-model plants using methods similar to those generally used for model plants is difficult. This chapter describes a gene family discovery strategy for identification of WRKY transcription factors in conifers by a combination of in silico-based prediction and PCR-based experimental approaches. Compared to traditional cDNA library screening or EST sequencing at transcriptome scales, this integrated gene discovery strategy provides fast, simple, reliable, and specific methods to unveil the WRKY gene family at both genome and transcriptome levels in non-model plants.

Biochemical, endocrine, and hematological factors in human oxygen tolerance extension: Predictive studies 6

NASA Technical Reports Server (NTRS)

Lambertsen, C. J.; Clark, J. M.

1992-01-01

The Predictive Studies VI (Biochemical, endocrine, and hematological factors in human oxygen tolerance extension) Program consisted of two related areas of research activity, integrated in design and performance, that were each based on an ongoing analysis of human organ oxygen tolerance data obtained for the continuous oxygen exposures of the prior Predictive Studies V Program. The two research areas effectively blended broad investigation of systematically varied intermittent exposure patterns in animals with very selective evaluation of specific exposure patterns in man.

Multimethod prediction of physical parent-child aggression risk in expectant mothers and fathers with Social Information Processing theory.

PubMed

Rodriguez, Christina M; Smith, Tamika L; Silvia, Paul J

2016-01-01

The Social Information Processing (SIP) model postulates that parents undergo a series of stages in implementing physical discipline that can escalate into physical child abuse. The current study utilized a multimethod approach to investigate whether SIP factors can predict risk of parent-child aggression (PCA) in a diverse sample of expectant mothers and fathers. SIP factors of PCA attitudes, negative child attributions, reactivity, and empathy were considered as potential predictors of PCA risk; additionally, analyses considered whether personal history of PCA predicted participants' own PCA risk through its influence on their attitudes and attributions. Findings indicate that, for both mothers and fathers, history influenced attitudes but not attributions in predicting PCA risk, and attitudes and attributions predicted PCA risk; empathy and reactivity predicted negative child attributions for expectant mothers, but only reactivity significantly predicted attributions for expectant fathers. Path models for expectant mothers and fathers were remarkably similar. Overall, the findings provide support for major aspects of the SIP model. Continued work is needed in studying the progression of these factors across time for both mothers and fathers as well as the inclusion of other relevant ecological factors to the SIP model. Copyright © 2015 Elsevier Ltd. All rights reserved.

Predicting Trihalomethanes (THMs) in the New York City Water Supply

NASA Astrophysics Data System (ADS)

Mukundan, R.; Van Dreason, R.

2013-12-01

Chlorine, a commonly used disinfectant in most water supply systems, can combine with organic carbon to form disinfectant byproducts including carcinogenic trihalomethanes (THMs). We used water quality data from 24 monitoring sites within the New York City (NYC) water supply distribution system, measured between January 2009 and April 2012, to develop site-specific empirical models for predicting total trihalomethane (TTHM) levels. Terms in the model included various combinations of the following water quality parameters: total organic carbon, pH, specific conductivity, and water temperature. Reasonable estimates of TTHM levels were achieved with overall R2 of about 0.87 and predicted values within 5 μg/L of measured values. The relative importance of factors affecting TTHM formation was estimated by ranking the model regression coefficients. Site-specific models showed improved model performance statistics compared to a single model for the entire system most likely because the single model did not consider locational differences in the water treatment process. Although never out of compliance in 2011, the TTHM levels in the water supply increased following tropical storms Irene and Lee with 45% of the samples exceeding the 80 μg/L Maximum Contaminant Level (MCL) in October and November. This increase was explained by changes in water quality parameters, particularly by the increase in total organic carbon concentration and pH during this period.

Risk Factors for Invasive Fungal Disease in Pediatric Cancer and Hematopoietic Stem Cell Transplantation: A Systematic Review.

PubMed

Fisher, Brian T; Robinson, Paula D; Lehrnbecher, Thomas; Steinbach, William J; Zaoutis, Theoklis E; Phillips, Bob; Sung, Lillian

2017-05-26

Although a number of risk factors have been associated with invasive fungal disease (IFD), a systematic review of the literature to document pediatric-specific factors has not been performed. We used the Ovid SP platform to search Medline, Medline In-Process, and Embase for studies that identified risk factors for IFD in children with cancer or those who undergo hematopoietic stem cell transplantation (HSCT). We included studies if they consisted of children or adolescents (<25 years) who were receiving treatment for cancer or undergoing HSCT and if the study evaluated risk factors among patients with and those without IFD. Among the 3566 studies screened, 22 studies were included. A number of pediatric factors commonly associated with an increased risk for IFD were confirmed, including prolonged neutropenia, high-dose steroid exposure, intensive-timing chemotherapy for acute myeloid leukemia, and acute and chronic graft-versus-host disease. Increasing age, a factor not commonly associated with IFD risk, was identified as a risk factor in multiple published cohorts. With this systematic review, we have confirmed IFD risk factors that are considered routinely in daily clinical practice. Increasing age should also be considered when assessing patient risk for IFD. Future efforts should focus on defining more precise thresholds for a particular risk factor (ie, age, neutropenia duration) and on development of prediction rules inclusive of individual factors to further refine the risk prediction. © The Author 2017. Published by Oxford University Press on behalf of The Journal of the Pediatric Infectious Diseases Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Modeling of Broadband Liners Applied to the Advanced Noise Control Fan

NASA Technical Reports Server (NTRS)

Nark, Douglas M.; Jones, Michael G.; Sutliff, Daniel L.

2015-01-01

The broadband component of fan noise has grown in relevance with an increase in bypass ratio and incorporation of advanced fan designs. Therefore, while the attenuation of fan tones remains a major factor in engine nacelle acoustic liner design, the simultaneous reduction of broadband fan noise levels has received increased interest. As such, a previous investigation focused on improvements to an established broadband acoustic liner optimization process using the Advanced Noise Control Fan (ANCF) rig as a demonstrator. Constant-depth, double-degree of freedom and variable-depth, multi-degree of freedom liner designs were carried through design, fabrication, and testing. This paper addresses a number of areas for further research identified in the initial assessment of the ANCF study. Specifically, incident source specification and uncertainty in some aspects of the predicted liner impedances are addressed. This information is incorporated in updated predictions of the liner performance and comparisons with measurement are greatly improved. Results illustrate the value of the design process in concurrently evaluating the relative costs/benefits of various liner designs. This study also provides further confidence in the integrated use of duct acoustic propagation/radiation and liner modeling tools in the design and evaluation of novel broadband liner concepts for complex engine configurations.

Assessing groundwater vulnerability to agrichemical contamination in the Midwest US

USGS Publications Warehouse

Burkart, M.R.; Kolpin, D.W.; James, D.E.

1999-01-01

Agrichemicals (herbicides and nitrate) are significant sources of diffuse pollution to groundwater. Indirect methods are needed to assess the potential for groundwater contamination by diffuse sources because groundwater monitoring is too costly to adequately define the geographic extent of contamination at a regional or national scale. This paper presents examples of the application of statistical, overlay and index, and process-based modeling methods for groundwater vulnerability assessments to a variety of data from the Midwest U.S. The principles for vulnerability assessment include both intrinsic (pedologic, climatologic, and hydrogeologic factors) and specific (contaminant and other anthropogenic factors) vulnerability of a location. Statistical methods use the frequency of contaminant occurrence, contaminant concentration, or contamination probability as a response variable. Statistical assessments are useful for defining the relations among explanatory and response variables whether they define intrinsic or specific vulnerability. Multivariate statistical analyses are useful for ranking variables critical to estimating water quality responses of interest. Overlay and index methods involve intersecting maps of intrinsic and specific vulnerability properties and indexing the variables by applying appropriate weights. Deterministic models use process-based equations to simulate contaminant transport and are distinguished from the other methods in their potential to predict contaminant transport in both space and time. An example of a one-dimensional leaching model linked to a geographic information system (GIS) to define a regional metamodel for contamination in the Midwest is included.

Predictive models and prognostic factors for upper tract urothelial carcinoma: a comprehensive review of the literature.

PubMed

Mbeutcha, Aurélie; Mathieu, Romain; Rouprêt, Morgan; Gust, Kilian M; Briganti, Alberto; Karakiewicz, Pierre I; Shariat, Shahrokh F

2016-10-01

In the context of customized patient care for upper tract urothelial carcinoma (UTUC), decision-making could be facilitated by risk assessment and prediction tools. The aim of this study was to provide a critical overview of existing predictive models and to review emerging promising prognostic factors for UTUC. A literature search of articles published in English from January 2000 to June 2016 was performed using PubMed. Studies on risk group stratification models and predictive tools in UTUC were selected, together with studies on predictive factors and biomarkers associated with advanced-stage UTUC and oncological outcomes after surgery. Various predictive tools have been described for advanced-stage UTUC assessment, disease recurrence and cancer-specific survival (CSS). Most of these models are based on well-established prognostic factors such as tumor stage, grade and lymph node (LN) metastasis, but some also integrate newly described prognostic factors and biomarkers. These new prediction tools seem to reach a high level of accuracy, but they lack external validation and decision-making analysis. The combinations of patient-, pathology- and surgery-related factors together with novel biomarkers have led to promising predictive tools for oncological outcomes in UTUC. However, external validation of these predictive models is a prerequisite before their introduction into daily practice. New models predicting response to therapy are urgently needed to allow accurate and safe individualized management in this heterogeneous disease.

Unpacking Trauma Exposure Risk Factors and Differential Pathways of Influence: Predicting Postwar Mental Distress in Bosnian Adolescents

ERIC Educational Resources Information Center

Layne, Christopher M.; Olsen, Joseph A.; Baker, Aaron; Legerski, John-Paul; Isakson, Brian; Pasalic, Alma; Durakovic-Belko, Elvira; Dapo, Nermin; Campara, Nihada; Arslanagic, Berina; Saltzman, William R.; Pynoos, Robert S.

2010-01-01

Methods are needed for quantifying the potency and differential effects of risk factors to identify at-risk groups for theory building and intervention. Traditional methods for constructing war exposure measures are poorly suited to "unpack" differential relations between specific types of exposure and specific outcomes. This study of…

Modeling Equilibrium Fe Isotope Fractionation in Fe-Organic Complexes: Implications for the use of Fe Isotopes as a Biomarker and Trends Based on the Properties of Bound Ligands

NASA Astrophysics Data System (ADS)

Domagal-Goldman, S.; Kubicki, J. D.

2006-05-01

Fe Isotopes have been proposed as a useful tracer of biological and geochemical processes. Key to understanding the effects these various processes have on Fe isotopes is accurate modeling of the reactions responsible for the isotope fractionations. In this study, we examined the theoretical basis for the claims that Fe isotopes can be used as a biomarker. This was done by using molecular orbital/density functional theory (MO/DFT) calculations to predict the equilibrium fractionation of Fe isotopes due to changes in the redox state and the bonding environment of Fe. Specifically, we predicted vibrational frequencies for iron desferrioxamine (Fe-DFOB), iron triscatechol (Fe(cat)3), iron trisoxalate (Fe(ox)3), and hexaaquo iron (Fe(H2O)6) for complexes containing both ferrous (Fe2+) and ferric (Fe3+) iron. Using these vibrational frequencies, we then predicted fractionation factors between these six complexes. The predicted fractionation factors resulting from changes in the redox state of Fe fell in the range 2.5- 3.5‰. The fractionation factors resulting from changes in the bonding environment of Fe ranged from 0.2 to 1.4‰. These results indicate that changes in the bonding strength of Fe ligands are less important to Fe isotope fractionation processes than are changes to the redox state of Fe. The implications for use of Fe as a tracer of biological processes is clear: abiological redox changes must be ruled out in a sample before Fe isotopes are considered as a potential biomarker. Furthermore, the use of Fe isotopes to measure the redox state of the Earths surface environment through time is supported by this work, since changes in the redox state of Fe appear to be the more important driver of isotopic fractionations. In addition to the large differences between redox-driven fractionations and ligand-driven fractionations, we will also show general trends in the demand for heavy Fe isotopes as a function of properties of the bound ligand. This will help the future analysis of Fe isotope fractionation. Future directions in the theoretical study of metal isotope fractionations will also be discussed, including the modeling of reactions on mineral surfaces.

A daily process examination of episode-specific drinking to cope motivation among college students.

PubMed

Ehrenberg, Ethan; Armeli, Stephen; Howland, Maryhope; Tennen, Howard

2016-06-01

Theory suggests that state- and trait-like factors should interact in predicting drinking to cope (DTC) motivation, yet no research to date has demonstrated this at the drinking episode level of analysis. Thus, we examined whether daily variation in positive and negative affect and avoidance and active coping were associated with DTC motivation during discrete drinking episodes and whether these associations were moderated by tension-reduction expectancies and other person-level risk factors. Using a secure website, 722 college student drinkers completed a one-time survey regarding their tension reduction expectancies and then reported daily for 30 days on their affect, coping strategies, drinking behaviors and motives for drinking. Individuals reported higher levels of DTC motivation on days when negative affect and avoidance coping were high and positive affect was low. We found only little support for the predicted interactive effects among the day- and person-level predictors. Our results support the state and trait conceptualizations of DTC motivation and provide evidence for the antecedent roles of proximal levels of daily affect and avoidance coping. Our inconsistent results for interaction effects including day-level antecedents raise the possibility that some of these synergistic processes might not generalize across level of analysis. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Daily Process Examination of Episode-Specific Drinking to Cope Motivation among College Students

PubMed Central

HOWLAND, MARYHOPE; TENNEN, HOWARD

2016-01-01

Objective Theory suggests that state- and trait-like factors should interact in predicting drinking to cope (DTC) motivation, yet no research to date has demonstrated this at the drinking episode level of analysis. Thus, we examined whether daily variation in positive and negative affect and avoidance and active coping were associated with DTC motivation during discrete drinking episodes and whether these associations were moderated by tension-reduction expectancies and other person-level risk factors. Methods Using a secure website, 722 college student drinkers completed a one-time survey regarding their tension reduction expectancies and then reported daily for 30 days on their affect, coping strategies, drinking behaviors and motives for drinking. Results Individuals reported higher levels of DTC motivation on days when negative affect and avoidance coping were high and positive affect was low. We found only little support for the predicted interactive effects among the day- and person-level predictors. Conclusion Our results support the state and trait conceptualizations of DTC motivation and provide evidence for the antecedent roles of proximal levels of daily affect and avoidance coping. Our inconsistent results for interaction effects including day-level antecedents raises the possibility that some of these synergistic processes might not generalize across level of analysis. PMID:26894551

Financial Distress Prediction Using Discrete-time Hazard Model and Rating Transition Matrix Approach

NASA Astrophysics Data System (ADS)

Tsai, Bi-Huei; Chang, Chih-Huei

2009-08-01

Previous studies used constant cut-off indicator to distinguish distressed firms from non-distressed ones in the one-stage prediction models. However, distressed cut-off indicator must shift according to economic prosperity, rather than remains fixed all the time. This study focuses on Taiwanese listed firms and develops financial distress prediction models based upon the two-stage method. First, this study employs the firm-specific financial ratio and market factors to measure the probability of financial distress based on the discrete-time hazard models. Second, this paper further focuses on macroeconomic factors and applies rating transition matrix approach to determine the distressed cut-off indicator. The prediction models are developed by using the training sample from 1987 to 2004, and their levels of accuracy are compared with the test sample from 2005 to 2007. As for the one-stage prediction model, the model in incorporation with macroeconomic factors does not perform better than that without macroeconomic factors. This suggests that the accuracy is not improved for one-stage models which pool the firm-specific and macroeconomic factors together. In regards to the two stage models, the negative credit cycle index implies the worse economic status during the test period, so the distressed cut-off point is adjusted to increase based on such negative credit cycle index. After the two-stage models employ such adjusted cut-off point to discriminate the distressed firms from non-distressed ones, their error of misclassification becomes lower than that of one-stage ones. The two-stage models presented in this paper have incremental usefulness in predicting financial distress.

Application of physicochemical properties and process parameters in the development of a neural network model for prediction of tablet characteristics.

PubMed

Sovány, Tamás; Papós, Kitti; Kása, Péter; Ilič, Ilija; Srčič, Stane; Pintye-Hódi, Klára

2013-06-01

The importance of in silico modeling in the pharmaceutical industry is continuously increasing. The aim of the present study was the development of a neural network model for prediction of the postcompressional properties of scored tablets based on the application of existing data sets from our previous studies. Some important process parameters and physicochemical characteristics of the powder mixtures were used as training factors to achieve the best applicability in a wide range of possible compositions. The results demonstrated that, after some pre-processing of the factors, an appropriate prediction performance could be achieved. However, because of the poor extrapolation capacity, broadening of the training data range appears necessary.

Congenital candidiasis as a subject of research in medicine and human ecology.

PubMed

Skoczylas, Michał M; Walat, Anna; Kordek, Agnieszka; Loniewska, Beata; Rudnicki, Jacek; Maleszka, Romuald; Torbé, Andrzej

2014-01-01

Congenital candidiasis is a severe complication of candidal vulvovaginitis. It occurs in two forms,congenital mucocutaneous candidiasis and congenital systemic candidiasis. Also newborns are in age group the most vulnerable to invasive candidiasis. Congenital candidiasis should be considered as an interdisciplinary problem including maternal and fetal condition (including antibiotic therapy during pregnancy), birth age and rare genetic predispositions as severe combined immunodeficiency or neutrophil-specific granule deficiency. Environmental factors are no less important to investigate in diagnosing, treatment and prevention. External factors (e.g., food) and microenvironment of human organism (microflora of the mouth, intestine and genitalia) are important for solving clinical problems connected to congenital candidiasis. Physician knowledge about microorganisms in a specific compartments of the microenvironment of human organism and in the course of defined disorders of homeostasis makes it easier to predict the course of the disease and allows the development of procedures that can be extremely helpful in individualized diagnostic and therapeutic process.

[Spanish drivers' beliefs about speed. Speeding is a major issue of road safety].

PubMed

Montoro González, Luis; Roca Ruiz, Javier; Lucas-Alba, Antonio

2010-11-01

Extending and updating our knowledge concerning drivers' motivational and cognitive processes is of essential importance if we are to apply policies with long-lasting effects. This study presents data from a representative national survey analyzing the Spanish drivers' beliefs about speed, the risks of speeding, the degree of violation of speed-limits and the reasons for speeding. Results indicate that Spanish drivers rate speeding as a serious offence, yet not among the most dangerous ones. All in all, they claim to comply mostly with the speed limits. However, some interesting violation patterns emerge: observance is lower for generic speed limits according to road type (vs. specific limits shown by certain road signs), and particularly in motorways (vs. single carriageways and urban areas). Risk perception and reasons for speeding emerge as the main factors predicting the levels of speed violations reported. Results suggest that any effective intervention strategy should consider such factors, namely the link between speed, road safety, and drivers' specific reasons for speeding.

Interaction between Digestive Strategy and Niche Specialization Predicts Speciation Rates across Herbivorous Mammals.

PubMed

Tran, Lucy A P

2016-04-01

Biotic and abiotic factors often are treated as mutually exclusive drivers of diversification processes. In this framework, ecological specialists are expected to have higher speciation rates than generalists if abiotic factors are the primary controls on species diversity but lower rates if biotic interactions are more important. Speciation rate is therefore predicted to positively correlate with ecological specialization in the purely abiotic model but negatively correlate in the biotic model. In this study, I show that the positive relationship between ecological specialization and speciation expected from the purely abiotic model is recovered only when a species-specific trait, digestive strategy, is modeled in the terrestrial, herbivorous mammals (Mammalia). This result suggests a more nuanced model in which the response of specialized lineages to abiotic factors is dependent on a biological trait. I also demonstrate that the effect of digestive strategy on the ecological specialization-speciation rate relationship is not due to a difference in either the degree of ecological specialization or the speciation rate between foregut- and hindgut-fermenting mammals. Together, these findings suggest that a biological trait, alongside historical abiotic events, played an important role in shaping mammal speciation at long temporal and large geographic scales.

Predictors of medical and mental health care use in patients with irritable bowel syndrome in the United States.

PubMed

Gudleski, Gregory D; Satchidanand, Nikhil; Dunlap, Laura J; Tahiliani, Varnita; Li, Xiaohua; Keefer, Laurie; Lackner, Jeffrey M

2017-01-01

Because health care demand among IBS patients imposes a heavy economic burden, identifying high utilizers has potential for improving quality and efficiency of care. Previous research has not identified reliable predictors of utilization of IBS patients. We sought to identify factors predictive of health care utilization among severe IBS patients. 291 IBS patients completed testing whose content mapped onto the Andersen model of health care utilization. 2-stage hurdle models were used to determine predictors of health care use (probability and frequency). Separate analyses were conducted for mental health and medical services. Whether patients used any medical care was predicted by diet and insurance status. Tobacco use, education, and health insurance predicted the probability of using mental health care. The frequency of medical care was associated with alcohol use and physical health status, while frequency of mental health services was associated with marital status, tobacco use, education, distress, stress, and control beliefs over IBS symptoms. For IBS patients, the demand for health care involves a complex decision-making process influenced by many factors. Particularly strong determinants include predisposing characteristics (e.g., dietary pattern, tobacco use) and enabling factors (e.g., insurance coverage) that impede or facilitate demand. Which factors impact use depends on whether the focus is on the decision to use care or how much care is used. Decisions to use medical and mental health care are not simply influenced by symptom-specific factors but by a variety of lifestyle (e.g., dietary pattern, education, smoking) and economic (e.g., insurance coverage) factors. Copyright © 2016 Elsevier Ltd. All rights reserved.

Family-specific Kinesin Structures Reveal Neck-linker Length Based on Initiation of the Coiled-coil*

PubMed Central

Phillips, Rebecca K.; Peter, Logan G.; Gilbert, Susan P.

2016-01-01

Kinesin-1, -2, -5, and -7 generate processive hand-over-hand 8-nm steps to transport intracellular cargoes toward the microtubule plus end. This processive motility requires gating mechanisms to coordinate the mechanochemical cycles of the two motor heads to sustain the processive run. A key structural element believed to regulate the degree of processivity is the neck-linker, a short peptide of 12–18 residues, which connects the motor domain to its coiled-coil stalk. Although a shorter neck-linker has been correlated with longer run lengths, the structural data to support this hypothesis have been lacking. To test this hypothesis, seven kinesin structures were determined by x-ray crystallography. Each included the neck-linker motif, followed by helix α7 that constitutes the start of the coiled-coil stalk. In the majority of the structures, the neck-linker length differed from predictions because helix α7, which initiates the coiled-coil, started earlier in the sequence than predicted. A further examination of structures in the Protein Data Bank reveals that there is a great disparity between the predicted and observed starting residues. This suggests that an accurate prediction of the start of a coiled-coil is currently difficult to achieve. These results are significant because they now exclude simple comparisons between members of the kinesin superfamily and add a further layer of complexity when interpreting the results of mutagenesis or protein fusion. They also re-emphasize the need to consider factors beyond the kinesin neck-linker motif when attempting to understand how inter-head communication is tuned to achieve the degree of processivity required for cellular function. PMID:27462072

Genetic influences on functional connectivity associated with feedback processing and prediction error: Phase coupling of theta-band oscillations in twins.

PubMed

Demiral, Şükrü Barış; Golosheykin, Simon; Anokhin, Andrey P

2017-05-01

Detection and evaluation of the mismatch between the intended and actually obtained result of an action (reward prediction error) is an integral component of adaptive self-regulation of behavior. Extensive human and animal research has shown that evaluation of action outcome is supported by a distributed network of brain regions in which the anterior cingulate cortex (ACC) plays a central role, and the integration of distant brain regions into a unified feedback-processing network is enabled by long-range phase synchronization of cortical oscillations in the theta band. Neural correlates of feedback processing are associated with individual differences in normal and abnormal behavior, however, little is known about the role of genetic factors in the cerebral mechanisms of feedback processing. Here we examined genetic influences on functional cortical connectivity related to prediction error in young adult twins (age 18, n=399) using event-related EEG phase coherence analysis in a monetary gambling task. To identify prediction error-specific connectivity pattern, we compared responses to loss and gain feedback. Monetary loss produced a significant increase of theta-band synchronization between the frontal midline region and widespread areas of the scalp, particularly parietal areas, whereas gain resulted in increased synchrony primarily within the posterior regions. Genetic analyses showed significant heritability of frontoparietal theta phase synchronization (24 to 46%), suggesting that individual differences in large-scale network dynamics are under substantial genetic control. We conclude that theta-band synchronization of brain oscillations related to negative feedback reflects genetically transmitted differences in the neural mechanisms of feedback processing. To our knowledge, this is the first evidence for genetic influences on task-related functional brain connectivity assessed using direct real-time measures of neuronal synchronization. Copyright © 2016 Elsevier B.V. All rights reserved.

Modelling Influence and Opinion Evolution in Online Collective Behaviour

PubMed Central

Gend, Pascal; Rentfrow, Peter J.; Hendrickx, Julien M.; Blondel, Vincent D.

2016-01-01

Opinion evolution and judgment revision are mediated through social influence. Based on a large crowdsourced in vitro experiment (n = 861), it is shown how a consensus model can be used to predict opinion evolution in online collective behaviour. It is the first time the predictive power of a quantitative model of opinion dynamics is tested against a real dataset. Unlike previous research on the topic, the model was validated on data which did not serve to calibrate it. This avoids to favor more complex models over more simple ones and prevents overfitting. The model is parametrized by the influenceability of each individual, a factor representing to what extent individuals incorporate external judgments. The prediction accuracy depends on prior knowledge on the participants’ past behaviour. Several situations reflecting data availability are compared. When the data is scarce, the data from previous participants is used to predict how a new participant will behave. Judgment revision includes unpredictable variations which limit the potential for prediction. A first measure of unpredictability is proposed. The measure is based on a specific control experiment. More than two thirds of the prediction errors are found to occur due to unpredictability of the human judgment revision process rather than to model imperfection. PMID:27336834

Cyclic AMP-dependent modification of gonad-selective TAF(II)105 in a human ovarian granulosa cell line.

PubMed

Wu, Yimin; Lu, Yunzhe; Hu, Yanfen; Li, Rong

2005-11-01

In response to gonadotropins, the elevated level of intracellular-cyclic AMP (cAMP) in ovarian granulosa cells triggers an ordered activation of multiple ovarian genes, which in turn promotes various ovarian functions including folliculogenesis and steroidogenesis. Identification and characterization of transcription factors that control ovarian gene expression are pivotal to the understanding of the molecular basis of the tissue-specific gene regulation programs. The recent discovery of the mouse TATA binding protein (TBP)-associated factor 105 (TAF(II)105) as a gonad-selective transcriptional co-activator strongly suggests that general transcription factors such as TFIID may play a key role in regulating tissue-specific gene expression. Here we show that the human TAF(II)105 protein is preferentially expressed in ovarian granulosa cells. We also identified a novel TAF(II)105 mRNA isoform that results from alternative exon inclusion and is predicted to encode a dominant negative mutant of TAF(II)105. Following stimulation by the adenylyl cyclase activator forskolin, TAF(II)105 in granulosa cells undergoes rapid and transient phosphorylation that is dependent upon protein kinase A (PKA). Thus, our work suggests that pre-mRNA processing and post-translational modification represent two important regulatory steps for the gonad-specific functions of human TAF(II)105. Copyright 2005 Wiley-Liss, Inc.

Factors predicting work outcome in Japanese patients with schizophrenia: role of multiple functioning levels.

PubMed

Sumiyoshi, Chika; Harvey, Philip D; Takaki, Manabu; Okahisa, Yuko; Sato, Taku; Sora, Ichiro; Nuechterlein, Keith H; Subotnik, Kenneth L; Sumiyoshi, Tomiki

2015-09-01

Functional outcomes in individuals with schizophrenia suggest recovery of cognitive, everyday, and social functioning. Specifically improvement of work status is considered to be most important for their independent living and self-efficacy. The main purposes of the present study were 1) to identify which outcome factors predict occupational functioning, quantified as work hours, and 2) to provide cut-offs on the scales for those factors to attain better work status. Forty-five Japanese patients with schizophrenia and 111 healthy controls entered the study. Cognition, capacity for everyday activities, and social functioning were assessed by the Japanese versions of the MATRICS Cognitive Consensus Battery (MCCB), the UCSD Performance-based Skills Assessment-Brief (UPSA-B), and the Social Functioning Scale Individuals' version modified for the MATRICS-PASS (Modified SFS for PASS), respectively. Potential factors for work outcome were estimated by multiple linear regression analyses (predicting work hours directly) and a multiple logistic regression analyses (predicting dichotomized work status based on work hours). ROC curve analyses were performed to determine cut-off points for differentiating between the better- and poor work status. The results showed that a cognitive component, comprising visual/verbal learning and emotional management, and a social functioning component, comprising independent living and vocational functioning, were potential factors for predicting work hours/status. Cut-off points obtained in ROC analyses indicated that 60-70% achievements on the measures of those factors were expected to maintain the better work status. Our findings suggest that improvement on specific aspects of cognitive and social functioning are important for work outcome in patients with schizophrenia.

Thyroid-specific questions on work ability showed known-groups validity among Danes with thyroid diseases.

PubMed

Nexo, Mette Andersen; Watt, Torquil; Bonnema, Steen Joop; Hegedüs, Laszlo; Rasmussen, Åse Krogh; Feldt-Rasmussen, Ulla; Bjorner, Jakob Bue

2015-07-01

We aimed to identify the best approach to work ability assessment in patients with thyroid disease by evaluating the factor structure, measurement equivalence, known-groups validity, and predictive validity of a broad set of work ability items. Based on the literature and interviews with thyroid patients, 24 work ability items were selected from previous questionnaires, revised, or developed anew. Items were tested among 632 patients with thyroid disease (non-toxic goiter, toxic nodular goiter, Graves' disease (with or without orbitopathy), autoimmune hypothyroidism, and other thyroid diseases), 391 of which had participated in a study 5 years previously. Responses to select items were compared to general population data. We used confirmatory factor analyses for categorical data, logistic regression analyses and tests of differential item function, and head-to-head comparisons of relative validity in distinguishing known groups. Although all work ability items loaded on a common factor, the optimal factor solution included five factors: role physical, role emotional, thyroid-specific limitations, work limitations (without disease attribution), and work performance. The scale on thyroid-specific limitations showed the most power in distinguishing clinical groups and time since diagnosis. A global single item proved useful for comparisons with the general population, and a thyroid-specific item predicted labor market exclusion within the next 5 years (OR 5.0, 95 % CI 2.7-9.1). Items on work limitations with attribution to thyroid disease were most effective in detecting impact on work ability and showed good predictive validity. Generic work ability items remain useful for general population comparisons.

Individual Differences in the Speed of Facial Emotion Recognition Show Little Specificity but Are Strongly Related with General Mental Speed: Psychometric, Neural and Genetic Evidence

PubMed Central

Liu, Xinyang; Hildebrandt, Andrea; Recio, Guillermo; Sommer, Werner; Cai, Xinxia; Wilhelm, Oliver

2017-01-01

Facial identity and facial expression processing are crucial socio-emotional abilities but seem to show only limited psychometric uniqueness when the processing speed is considered in easy tasks. We applied a comprehensive measurement of processing speed and contrasted performance specificity in socio-emotional, social and non-social stimuli from an individual differences perspective. Performance in a multivariate task battery could be best modeled by a general speed factor and a first-order factor capturing some specific variance due to processing emotional facial expressions. We further tested equivalence of the relationships between speed factors and polymorphisms of dopamine and serotonin transporter genes. Results show that the speed factors are not only psychometrically equivalent but invariant in their relation with the Catechol-O-Methyl-Transferase (COMT) Val158Met polymorphism. However, the 5-HTTLPR/rs25531 serotonin polymorphism was related with the first-order factor of emotion perception speed, suggesting a specific genetic correlate of processing emotions. We further investigated the relationship between several components of event-related brain potentials with psychometric abilities, and tested emotion specific individual differences at the neurophysiological level. Results revealed swifter emotion perception abilities to go along with larger amplitudes of the P100 and the Early Posterior Negativity (EPN), when emotion processing was modeled on its own. However, after partialling out the shared variance of emotion perception speed with general processing speed-related abilities, brain-behavior relationships did not remain specific for emotion. Together, the present results suggest that speed abilities are strongly interrelated but show some specificity for emotion processing speed at the psychometric level. At both genetic and neurophysiological levels, emotion specificity depended on whether general cognition is taken into account or not. These findings keenly suggest that general speed abilities should be taken into account when the study of emotion recognition abilities is targeted in its specificity. PMID:28848411

Proposal for a recovery prediction method for patients affected by acute mediastinitis

PubMed Central

2012-01-01

Background An attempt to find a prediction method of death risk in patients affected by acute mediastinitis. There is not such a tool described in available literature for that serious disease. Methods The study comprised 44 consecutive cases of acute mediastinitis. General anamnesis and biochemical data were included. Factor analysis was used to extract the risk characteristic for the patients. The most valuable results were obtained for 8 parameters which were selected for further statistical analysis (all collected during few hours after admission). Three factors reached Eigenvalue >1. Clinical explanations of these combined statistical factors are: Factor1 - proteinic status (serum total protein, albumin, and hemoglobin level), Factor2 - inflammatory status (white blood cells, CRP, procalcitonin), and Factor3 - general risk (age, number of coexisting diseases). Threshold values of prediction factors were estimated by means of statistical analysis (factor analysis, Statgraphics Centurion XVI). Results The final prediction result for the patients is constructed as simultaneous evaluation of all factor scores. High probability of death should be predicted if factor 1 value decreases with simultaneous increase of factors 2 and 3. The diagnostic power of the proposed method was revealed to be high [sensitivity =90%, specificity =64%], for Factor1 [SNC = 87%, SPC = 79%]; for Factor2 [SNC = 87%, SPC = 50%] and for Factor3 [SNC = 73%, SPC = 71%]. Conclusion The proposed prediction method seems a useful emergency signal during acute mediastinitis control in affected patients. PMID:22574625

Development of a CSP plant energy yield calculation tool applying predictive models to analyze plant performance sensitivities

NASA Astrophysics Data System (ADS)

Haack, Lukas; Peniche, Ricardo; Sommer, Lutz; Kather, Alfons

2017-06-01

At early project stages, the main CSP plant design parameters such as turbine capacity, solar field size, and thermal storage capacity are varied during the techno-economic optimization to determine most suitable plant configurations. In general, a typical meteorological year with at least hourly time resolution is used to analyze each plant configuration. Different software tools are available to simulate the annual energy yield. Software tools offering a thermodynamic modeling approach of the power block and the CSP thermal cycle, such as EBSILONProfessional®, allow a flexible definition of plant topologies. In EBSILON, the thermodynamic equilibrium for each time step is calculated iteratively (quasi steady state), which requires approximately 45 minutes to process one year with hourly time resolution. For better presentation of gradients, 10 min time resolution is recommended, which increases processing time by a factor of 5. Therefore, analyzing a large number of plant sensitivities, as required during the techno-economic optimization procedure, the detailed thermodynamic simulation approach becomes impracticable. Suntrace has developed an in-house CSP-Simulation tool (CSPsim), based on EBSILON and applying predictive models, to approximate the CSP plant performance for central receiver and parabolic trough technology. CSPsim significantly increases the speed of energy yield calculations by factor ≥ 35 and has automated the simulation run of all predefined design configurations in sequential order during the optimization procedure. To develop the predictive models, multiple linear regression techniques and Design of Experiment methods are applied. The annual energy yield and derived LCOE calculated by the predictive model deviates less than ±1.5 % from the thermodynamic simulation in EBSILON and effectively identifies the optimal range of main design parameters for further, more specific analysis.

Differential miRNA expression in B cells is associated with inter-individual differences in humoral immune response to measles vaccination

PubMed Central

Haralambieva, Iana H.; Kennedy, Richard B.; Simon, Whitney L.; Goergen, Krista M.; Grill, Diane E.; Ovsyannikova, Inna G.

2018-01-01

Background MicroRNAs are important mediators of post-transcriptional regulation of gene expression through RNA degradation and translational repression, and are emerging biomarkers of immune system activation/response after vaccination. Methods We performed Next Generation Sequencing (mRNA-Seq) of intracellular miRNAs in measles virus-stimulated B and CD4+ T cells from high and low antibody responders to measles vaccine. Negative binomial generalized estimating equation (GEE) models were used for miRNA assessment and the DIANA tool was used for gene/target prediction and pathway enrichment analysis. Results We identified a set of B cell-specific miRNAs (e.g., miR-151a-5p, miR-223, miR-29, miR-15a-5p, miR-199a-3p, miR-103a, and miR-15a/16 cluster) and biological processes/pathways, including regulation of adherens junction proteins, Fc-receptor signaling pathway, phosphatidylinositol-mediated signaling pathway, growth factor signaling pathway/pathways, transcriptional regulation, apoptosis and virus-related processes, significantly associated with neutralizing antibody titers after measles vaccination. No CD4+ T cell-specific miRNA expression differences between high and low antibody responders were found. Conclusion Our study demonstrates that miRNA expression directly or indirectly influences humoral immunity to measles vaccination and suggests that B cell-specific miRNAs may serve as useful predictive biomarkers of vaccine humoral immune response. PMID:29381765

Spatial Bayesian Latent Factor Regression Modeling of Coordinate-based Meta-analysis Data

PubMed Central

Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D.; Nichols, Thomas E.

2017-01-01

Summary Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the paper are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to 1) identify areas of consistent activation; and 2) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterised as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. PMID:28498564

Neuroticism explains unwanted variance in Implicit Association Tests of personality: possible evidence for an affective valence confound.

PubMed

Fleischhauer, Monika; Enge, Sören; Miller, Robert; Strobel, Alexander; Strobel, Anja

2013-01-01

Meta-analytic data highlight the value of the Implicit Association Test (IAT) as an indirect measure of personality. Based on evidence suggesting that confounding factors such as cognitive abilities contribute to the IAT effect, this study provides a first investigation of whether basic personality traits explain unwanted variance in the IAT. In a gender-balanced sample of 204 volunteers, the Big-Five dimensions were assessed via self-report, peer-report, and IAT. By means of structural equation modeling (SEM), latent Big-Five personality factors (based on self- and peer-report) were estimated and their predictive value for unwanted variance in the IAT was examined. In a first analysis, unwanted variance was defined in the sense of method-specific variance which may result from differences in task demands between the two IAT block conditions and which can be mirrored by the absolute size of the IAT effects. In a second analysis, unwanted variance was examined in a broader sense defined as those systematic variance components in the raw IAT scores that are not explained by the latent implicit personality factors. In contrast to the absolute IAT scores, this also considers biases associated with the direction of IAT effects (i.e., whether they are positive or negative in sign), biases that might result, for example, from the IAT's stimulus or category features. None of the explicit Big-Five factors was predictive for method-specific variance in the IATs (first analysis). However, when considering unwanted variance that goes beyond pure method-specific variance (second analysis), a substantial effect of neuroticism occurred that may have been driven by the affective valence of IAT attribute categories and the facilitated processing of negative stimuli, typically associated with neuroticism. The findings thus point to the necessity of using attribute category labels and stimuli of similar affective valence in personality IATs to avoid confounding due to recoding.

Can Rheumatologists Predict Eventual Need for Orthopaedic Intervention in Patients with Rheumatoid Arthritis? Results of a Systematic Review and Analysis of Two UK Inception Cohorts.

PubMed

Nikiphorou, Elena; Carpenter, Lewis; Norton, Sam; Morris, Stephen; MacGregor, Alex; Dixey, Josh; Williams, Peter; Kiely, Patrick; Walsh, David Andrew; Young, Adam

2017-03-01

The structural damage caused by rheumatoid arthritis (RA) can often be mitigated by orthopaedic surgery in late disease. This study evaluates the value of predictive factors for orthopaedic intervention. A systematic review of literature was undertaken to identify papers describing predictive factors for orthopaedic surgery in RA. Manuscripts were selected if they met inclusion criteria of cohort study design, diagnosis of RA, follow-up duration/disease duration ≥3 years, any orthopaedic surgical interventions recorded, and then summarised for predictive factors. A separate predictive analysis was performed on two consecutive UK Early RA cohorts, linked to national datasets. The literature search identified 15 reports examining predictive factors for orthopaedic intervention, 4 inception, 5 prospective and 6 retrospective. Despite considerable variation, acute phase, x-ray scores, women and genotyping were the most commonly reported prognostic markers. The current predictive analysis included 1602 procedures performed in 711 patients (25-year cumulative incidence 26%). Earlier recruitment year, erosions and lower haemoglobin predicted both intermediate and major surgery (P<0.05). Studies report variations in type of and predictive power of clinical and laboratory parameters for different surgical interventions suggesting specific contributions from different pathological and/or patient-level factors. Our current analysis suggests that attention to non-inflammatory factors in addition to suppression of inflammation is needed to minimise the burden of orthopaedic surgery.

Marijuana protective behavioral strategies as a moderator of the effects of risk/protective factors on marijuana-related outcomes.

PubMed

Bravo, Adrian J; Anthenien, Amber M; Prince, Mark A; Pearson, Matthew R

2017-06-01

Given that both marijuana use and cannabis use disorder peak among college students, it is imperative to determine the factors that may reduce risk of problematic marijuana use and/or the development of cannabis use disorder. From a harm reduction perspective, the present study examined whether the use of marijuana protective behavioral strategies (PBS) buffers or amplifies the effects of several distinct risk and protective factors that have been shown to relate to marijuana-related outcomes (i.e., use frequency and consequences). Specifically, we examined marijuana-PBS use as a moderator of the effects of impulsivity-like traits, marijuana use motives, gender, and marijuana use frequency on marijuana-related outcomes in a large sample of college students (n=2093 past month marijuana users across 11 universities). In all models PBS use was robustly related with use frequency and consequences (i.e., strongly negatively associated with marijuana outcomes). Among interactions, we found: 1) unique significant interactions between specific impulsivity-like traits (i.e., premeditation, perseverance, and sensation seeking) and marijuana-PBS use in predicting marijuana consequences, 2) unique significant interactions between each marijuana use motive and marijuana-PBS use in predicting marijuana use frequency and 3) marijuana-PBS use buffered the risk associated with male gender in predicting both marijuana outcomes. Our results suggest that marijuana-PBS use can buffer risk factors and enhance protective factors among marijuana using college students. Future research is needed to understand context-specific factors and individual-level factors that may make marijuana-PBS use more effective. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluation of the Enhanced Integrated Climatic Model for modulus-based construction specification for Oklahoma pavements.

DOT National Transportation Integrated Search

2013-07-01

The study provides estimation of site specific variation in environmental factors that can be : used in predicting seasonal and long-term variations in moduli of unbound materials. Using : these site specific estimates, the EICM climatic input files ...

Formation of the Embryonic Head in the Mouse: Attributes of a Gene Regulatory Network.

PubMed

Tam, Patrick P L; Fossat, Nicolas; Wilkie, Emilie; Loebel, David A F; Ip, Chi Kin; Ramialison, Mirana

2016-01-01

The embryonic head is the first major body part to be constructed during embryogenesis. The allocation and the assembly of the progenitor tissues, which start at gastrulation, are accompanied by the spatiotemporal activity of transcription factors and signaling pathways that drives lineage specification, germ layer formation, and cell/tissue movement. The morphogenesis, regionalization, and patterning of the brain and craniofacial structures rely on the function of LIM-domain, homeodomain, and basic helix-loop-helix transcription factors. These factors constitute the central nodes of a gene regulatory network (GRN) which encompasses and intersects with signaling pathways involved with head formation. It is predicted that the functional output of this "head GRN" impacts on cellular function and cell-cell interactions that are essential for lineage differentiation and tissue modeling, which are key processes underpinning the formation of the head. © 2016 Elsevier Inc. All rights reserved.

Ultrasound-enhanced bioscouring of greige cotton: regression analysis of process factors

USDA-ARS?s Scientific Manuscript database

Ultrasound-enhanced bioscouring process factors for greige cotton fabric are examined using custom experimental design utilizing statistical principles. An equation is presented which predicts bioscouring performance based upon percent reflectance values obtained from UV-Vis measurements of rutheniu...

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for the prediction of non-union consolidation.

PubMed

Fischer, Christian; Nissen, Mareike; Schmidmaier, Gerhard; Bruckner, Thomas; Kauczor, Hans-Ulrich; Weber, Marc-André

2017-02-01

Non-union perfusion can be visualized with dynamic contrast-enhanced (DCE) MRI. This study evaluated DCE-MRI to predict non-union consolidation after surgery and detect factors that affect bone healing. Between 2010 and 2015 non-union perfusion was prospectively quantified in 205 patients (mean age, 51.5 years, 129 men, 76 women) before intervention and at 6, 12, 26, 52 and more weeks follow-up. DCE-MRI results were related to the osseous consolidation, the ability to predict successful outcome was estimated by ROC analysis. The relevance of the body mass index (BMI) and the non-union severity score (NUSS) to the healing process was assessed. Tibial (n=99) and femoral (n=76) non-unions were most common. Consolidation could be assessed in 169 patients, of these 103 (61%) showed eventual healing and demonstrated higher perfusion than in failed consolidation at 6 (p=0.0226), 12 (p=0.0252) and 26 (p=0.0088) weeks follow-up. DCE-MRI at 26 weeks follow-up predicted non-union consolidation with a sensitivity of 75% and a specificity of 87% (false classification rate 19%). Higher BMI (p=0.041) and NUSS (p<0.0001) were associated with treatment failure. DCE-MRI perfusion analysis after non-union surgery predicts successful outcome and could facilitate the decision of early intervention. NUSS and BMI are important prognostic factors concerning consolidation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Separating Common from Unique Variance Within Emotional Distress: An Examination of Reliability and Relations to Worry.

PubMed

Marshall, Andrew J; Evanovich, Emma K; David, Sarah Jo; Mumma, Gregory H

2018-01-17

High comorbidity rates among emotional disorders have led researchers to examine transdiagnostic factors that may contribute to shared psychopathology. Bifactor models provide a unique method for examining transdiagnostic variables by modelling the common and unique factors within measures. Previous findings suggest that the bifactor model of the Depression Anxiety and Stress Scale (DASS) may provide a method for examining transdiagnostic factors within emotional disorders. This study aimed to replicate the bifactor model of the DASS, a multidimensional measure of psychological distress, within a US adult sample and provide initial estimates of the reliability of the general and domain-specific factors. Furthermore, this study hypothesized that Worry, a theorized transdiagnostic variable, would show stronger relations to general emotional distress than domain-specific subscales. Confirmatory factor analysis was used to evaluate the bifactor model structure of the DASS in 456 US adult participants (279 females and 177 males, mean age 35.9 years) recruited online. The DASS bifactor model fitted well (CFI = 0.98; RMSEA = 0.05). The General Emotional Distress factor accounted for most of the reliable variance in item scores. Domain-specific subscales accounted for modest portions of reliable variance in items after accounting for the general scale. Finally, structural equation modelling indicated that Worry was strongly predicted by the General Emotional Distress factor. The DASS bifactor model is generalizable to a US community sample and General Emotional Distress, but not domain-specific factors, strongly predict the transdiagnostic variable Worry.

Mining nutrigenetics patterns related to obesity: use of parallel multifactor dimensionality reduction.

PubMed

Karayianni, Katerina N; Grimaldi, Keith A; Nikita, Konstantina S; Valavanis, Ioannis K

2015-01-01

This paper aims to enlighten the complex etiology beneath obesity by analysing data from a large nutrigenetics study, in which nutritional and genetic factors associated with obesity were recorded for around two thousand individuals. In our previous work, these data have been analysed using artificial neural network methods, which identified optimised subsets of factors to predict one's obesity status. These methods did not reveal though how the selected factors interact with each other in the obtained predictive models. For that reason, parallel Multifactor Dimensionality Reduction (pMDR) was used here to further analyse the pre-selected subsets of nutrigenetic factors. Within pMDR, predictive models using up to eight factors were constructed, further reducing the input dimensionality, while rules describing the interactive effects of the selected factors were derived. In this way, it was possible to identify specific genetic variations and their interactive effects with particular nutritional factors, which are now under further study.

Enhancing the Value of Population-Based Risk Scores for Institutional-Level Use.

PubMed

Raza, Sajjad; Sabik, Joseph F; Rajeswaran, Jeevanantham; Idrees, Jay J; Trezzi, Matteo; Riaz, Haris; Javadikasgari, Hoda; Nowicki, Edward R; Svensson, Lars G; Blackstone, Eugene H

2016-07-01

We hypothesized that factors associated with an institution's residual risk unaccounted for by population-based models may be identifiable and used to enhance the value of population-based risk scores for quality improvement. From January 2000 to January 2010, 4,971 patients underwent aortic valve replacement (AVR), either isolated (n = 2,660) or with concomitant coronary artery bypass grafting (AVR+CABG; n = 2,311). Operative mortality and major morbidity and mortality predicted by The Society of Thoracic Surgeons (STS) risk models were compared with observed values. After adjusting for patients' STS score, additional and refined risk factors were sought to explain residual risk. Differences between STS model coefficients (risk-factor strength) and those specific to our institution were calculated. Observed operative mortality was less than predicted for AVR (1.6% [42 of 2,660] vs 2.8%, p < 0.0001) and AVR+CABG (2.6% [59 of 2,311] vs 4.9%, p < 0.0001). Observed major morbidity and mortality was also lower than predicted for isolated AVR (14.6% [389 of 2,660] vs 17.5%, p < 0.0001) and AVR+CABG (20.0% [462 of 2,311] vs 25.8%, p < 0.0001). Shorter height, higher bilirubin, and lower albumin were identified as additional institution-specific risk factors, and body surface area, creatinine, glomerular filtration rate, blood urea nitrogen, and heart failure across all levels of functional class were identified as refined risk-factor variables associated with residual risk. In many instances, risk-factor strength differed substantially from that of STS models. Scores derived from population-based models can be enhanced for institutional level use by adjusting for institution-specific additional and refined risk factors. Identifying these and measuring differences in institution-specific versus population-based risk-factor strength can identify areas to target for quality improvement initiatives. Copyright © 2016 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

MAGIA2: from miRNA and genes expression data integrative analysis to microRNA–transcription factor mixed regulatory circuits (2012 update)

PubMed Central

Bisognin, Andrea; Sales, Gabriele; Coppe, Alessandro; Bortoluzzi, Stefania; Romualdi, Chiara

2012-01-01

MAGIA2 (http://gencomp.bio.unipd.it/magia2) is an update, extension and evolution of the MAGIA web tool. It is dedicated to the integrated analysis of in silico target prediction, microRNA (miRNA) and gene expression data for the reconstruction of post-transcriptional regulatory networks. miRNAs are fundamental post-transcriptional regulators of several key biological and pathological processes. As miRNAs act prevalently through target degradation, their expression profiles are expected to be inversely correlated to those of the target genes. Low specificity of target prediction algorithms makes integration approaches an interesting solution for target prediction refinement. MAGIA2 performs this integrative approach supporting different association measures, multiple organisms and almost all target predictions algorithms. Nevertheless, miRNAs activity should be viewed as part of a more complex scenario where regulatory elements and their interactors generate a highly connected network and where gene expression profiles are the result of different levels of regulation. The updated MAGIA2 tries to dissect this complexity by reconstructing mixed regulatory circuits involving either miRNA or transcription factor (TF) as regulators. Two types of circuits are identified: (i) a TF that regulates both a miRNA and its target and (ii) a miRNA that regulates both a TF and its target. PMID:22618880

How personal resources predict work engagement and self-rated performance among construction workers: a social cognitive perspective.

PubMed

Lorente, Laura; Salanova, Marisa; Martínez, Isabel M; Vera, María

2014-06-01

Traditionally, research focussing on psychosocial factors in the construction industry has focused mainly on the negative aspects of health and on results such as occupational accidents. This study, however, focuses on the specific relationships among the different positive psychosocial factors shared by construction workers that could be responsible for occupational well-being and outcomes such as performance. The main objective of this study was to test whether personal resources predict self-rated job performance through job resources and work engagement. Following the predictions of Bandura's Social Cognitive Theory and the motivational process of the Job Demands-Resources Model, we expect that the relationship between personal resources and performance will be fully mediated by job resources and work engagement. The sample consists of 228 construction workers. Structural equation modelling supports the research model. Personal resources (i.e. self-efficacy, mental and emotional competences) play a predicting role in the perception of job resources (i.e. job control and supervisor social support), which in turn leads to work engagement and self-rated performance. This study emphasises the crucial role that personal resources play in determining how people perceive job resources by determining the levels of work engagement and, hence, their self-rated job performance. Theoretical and practical implications are discussed. © 2014 International Union of Psychological Science.

Explicit Processing Demands Reveal Language Modality-Specific Organization of Working Memory

ERIC Educational Resources Information Center

Rudner, Mary; Ronnberg, Jerker

2008-01-01

The working memory model for Ease of Language Understanding (ELU) predicts that processing differences between language modalities emerge when cognitive demands are explicit. This prediction was tested in three working memory experiments with participants who were Deaf Signers (DS), Hearing Signers (HS), or Hearing Nonsigners (HN). Easily nameable…

Marital Processes, Neuroticism, and Stress as Risk Factors for Internalizing Symptoms

PubMed Central

Brock, Rebecca L.; Lawrence, Erika

2013-01-01

Objective Marital discord has a robust association with depression, yet it is rarely considered within broader etiological frameworks of psychopathology. Further, little is known about the particular aspects of relationships that have the greatest impact on psychopathology. The purpose of the present study was to test a novel conceptual framework including neuroticism, specific relationship processes (conflict management, partner support, emotional intimacy, and distribution of power and control), and stress as predictors of internalizing symptoms (depression and anxiety). Method Questionnaire and interview data were collected from 103 husbands and wives 5 times over the first 7 years of marriage. Results Results suggest that neuroticism (an expression of the underlying vulnerability for internalizing disorders) contributes to symptoms primarily through high levels of non-marital stress, an imbalance of power/control in one’s marriage, and poor partner support for husbands, and through greater emotional disengagement for wives. Conclusions Marital processes, neuroticism, and stress work together to significantly predict internalizing symptoms, demonstrating the need to routinely consider dyadic processes in etiological models of individual psychopathology. Specific recommendations for adapting and implementing couple interventions to prevent and treat individual psychopathology are discussed. PMID:24818069

Pornography use and sexual aggression: the impact of frequency and type of pornography use on recidivism among sexual offenders.

PubMed

Kingston, Drew A; Fedoroff, Paul; Firestone, Philip; Curry, Susan; Bradford, John M

2008-01-01

In this study, we examined the unique contribution of pornography consumption to the longitudinal prediction of criminal recidivism in a sample of 341 child molesters. We specifically tested the hypothesis, based on predictions informed by the confluence model of sexual aggression that pornography will be a risk factor for recidivism only for those individuals classified as relatively high risk for re-offending. Pornography use (frequency and type) was assessed through self-report and recidivism was measured using data from a national database from the Royal Canadian Mounted Police. Indices of recidivism, which were assessed up to 15 years after release, included an overall criminal recidivism index, as well as subcategories focusing on violent (including sexual) recidivism and sexual recidivism alone. Results for both frequency and type of pornography use were generally consistent with our predictions. Most importantly, after controlling for general and specific risk factors for sexual aggression, pornography added significantly to the prediction of recidivism. Statistical interactions indicated that frequency of pornography use was primarily a risk factor for higher-risk offenders, when compared with lower-risk offenders, and that content of pornography (i.e., pornography containing deviant content) was a risk factor for all groups. The importance of conceptualizing particular risk factors (e.g., pornography), within the context of other individual characteristics is discussed.

Harnessing system models of cell death signalling for cytotoxic chemotherapy: towards personalised medicine approaches?

PubMed

Huber, Heinrich J; McKiernan, Ross G; Prehn, Jochen H M

2014-03-01

Most cytotoxic chemotherapeutics are believed to kill cancer cells by inducing apoptosis. Understanding the factors that contribute to impairment of apoptosis in cancer cells is therefore critical for the development of novel therapies that circumvent the widespread chemoresistance. Apoptosis, however, is a complex and tightly controlled process that can be induced by different classes of chemotherapeutics targeting different signalling nodes and pathways. Moreover, apoptosis initiation and apoptosis execution strongly depend on patient-specific, genomic and proteomic signatures. Here, we will review recent translational studies that suggest a critical link between the sensitivity of cancer cells to initiate apoptosis and clinical outcome. Next we will discuss recent advances in the field of system modelling of apoptosis pathways for the prediction of treatment responses. We propose that initiation of mitochondrial apoptosis, defined as the process of mitochondrial outer membrane permeabilisation (MOMP), is a dose-dependent decision process that allows for a prediction of individual therapy responses and therapeutic windows. We provide evidence in contrast that apoptosis execution post-MOMP may be a binary decision that dictates whether apoptosis is executed or not. We will discuss the implications of this concept for the future use of novel adjuvant therapeutics that specifically target apoptosis signalling pathways or which may be used to reduce the impact of cell-to-cell heterogeneity on therapy responses. Finally, we will discuss the technical and regulatory requirements surrounding the use and implications of system-based patient stratification tools for the future of personalised oncology.

Examining the relationship between coping strategies and suicidal desire in a sample of United States military personnel.

PubMed

Khazem, Lauren R; Law, Keyne C; Green, Bradley A; Anestis, Michael D

2015-02-01

Suicidal desire in the military has been previously examined through the lens of the Interpersonal-Psychological Theory of Suicide (IPTS). However, no research has examined the impact of specific coping strategies on perceived burdensomeness, thwarted belongingness, and suicidal ideation in a large population of individuals serving in the US military. Furthermore, the factor structure of previously utilized coping clusters did not apply to our sample of military personnel. Therefore, we found a three-factor solution to be tested in this sample. We hypothesized that specific types of coping behavior clusters (Adaptive and Maladaptive) would predict both IPTS constructs and suicidal ideation. Results indicated that Adaptive and Maladaptive coping clusters predicted the IPTS constructs in the hypothesized directions. However, only the Maladaptive cluster predicted suicidal ideation. These findings implicate the need for further research and suicide prevention efforts focusing on coping strategies, specifically those that are maladaptive in nature, in relation to suicidal ideation in military members. Copyright © 2014 Elsevier Inc. All rights reserved.

Predicting factors for malaria re-introduction: an applied model in an elimination setting to prevent malaria outbreaks.

PubMed

Ranjbar, Mansour; Shoghli, Alireza; Kolifarhood, Goodarz; Tabatabaei, Seyed Mehdi; Amlashi, Morteza; Mohammadi, Mahdi

2016-03-02

Malaria re-introduction is a challenge in elimination settings. To prevent re-introduction, receptivity, vulnerability, and health system capacity of foci should be monitored using appropriate tools. This study aimed to design an applicable model to monitor predicting factors of re-introduction of malaria in highly prone areas. This exploratory, descriptive study was conducted in a pre-elimination setting with a high-risk of malaria transmission re-introduction. By using nominal group technique and literature review, a list of predicting indicators for malaria re-introduction and outbreak was defined. Accordingly, a checklist was developed and completed in the field for foci affected by re-introduction and for cleared-up foci as a control group, for a period of 12 weeks before re-introduction and for the same period in the previous year. Using field data and analytic hierarchical process (AHP), each variable and its sub-categories were weighted, and by calculating geometric means for each sub-category, score of corresponding cells of interaction matrices, lower and upper threshold of different risks strata, including low and mild risk of re-introduction and moderate and high risk of malaria outbreaks, were determined. The developed predictive model was calibrated through resampling with different sets of explanatory variables using R software. Sensitivity and specificity of the model were calculated based on new samples. Twenty explanatory predictive variables of malaria re-introduction were identified and a predictive model was developed. Unpermitted immigrants from endemic neighbouring countries were determined as a pivotal factor (AHP score: 0.181). Moreover, quality of population movement (0.114), following malaria transmission season (0.088), average daily minimum temperature in the previous 8 weeks (0.062), an outdoor resting shelter for vectors (0.045), and rainfall (0.042) were determined. Positive and negative predictive values of the model were 81.8 and 100 %, respectively. This study introduced a new, simple, yet reliable model to forecast malaria re-introduction and outbreaks eight weeks in advance in pre-elimination and elimination settings. The model incorporates comprehensive deterministic factors that can easily be measured in the field, thereby facilitating preventive measures.

The Assessment of Bipolar Disorder in Children and Adolescents

PubMed Central

Youngstrom, Eric A.; Freeman, Andrew J.; Jenkins, Melissa McKeown

2010-01-01

The overarching goal of this review is to examine the current best evidence for assessing bipolar disorder in children and adolescents and provide a comprehensive, evidence-based approach to diagnosis. Evidence-based assessment strategies are organized around the “3 Ps” of clinical assessment: Predict important criteria or developmental trajectories, Prescribe a change in treatment choice, and inform Process of treating the youth and his/her family. The review characterizes bipolar disorder in youths - specifically addressing bipolar diagnoses and clinical subtypes; then provides an actuarial approach to assessment - using prevalence of disorder, risk factors, and questionnaires; discusses treatment thresholds; and identifies practical measures of process and outcomes. The clinical tools and risk factors selected for inclusion in this review represent the best empirical evidence in the literature. By the end of the review, clinicians will have a framework and set of clinically useful tools with which to effectively make evidence-based decisions regarding the diagnosis of bipolar disorder in children and adolescents. PMID:19264268

Spontaneous mentalizing predicts the fundamental attribution error.

PubMed

Moran, Joseph M; Jolly, Eshin; Mitchell, Jason P

2014-03-01

When explaining the reasons for others' behavior, perceivers often overemphasize underlying dispositions and personality traits over the power of the situation, a tendency known as the fundamental attribution error. One possibility is that this bias results from the spontaneous processing of others' mental states, such as their momentary feelings or more enduring personality characteristics. Here, we use fMRI to test this hypothesis. Participants read a series of stories that described a target's ambiguous behavior in response to a specific social situation and later judged whether that act was attributable to the target's internal dispositions or to external situational factors. Neural regions consistently associated with mental state inference-especially, the medial pFC-strongly predicted whether participants later made dispositional attributions. These results suggest that the spontaneous engagement of mentalizing may underlie the biased tendency to attribute behavior to dispositional over situational forces.

Risk factors of non-specific spinal pain in childhood.

PubMed

Szita, Julia; Boja, Sara; Szilagyi, Agnes; Somhegyi, Annamaria; Varga, Peter Pal; Lazary, Aron

2018-05-01

Non-specific spinal pain can occur at all ages and current evidence suggests that pediatric non-specific spinal pain is predictive for adult spinal conditions. A 5-year long, prospective cohort study was conducted to identify the lifestyle and environmental factors leading to non-specific spinal pain in childhood. Data were collected from school children aged 7-16 years, who were randomly selected from three different geographic regions in Hungary. The risk factors were measured with a newly developed patient-reported questionnaire (PRQ). The quality of the instrument was assessed by the reliability with the test-retest method. Test (N = 952) and validity (N = 897) datasets were randomly formed. Risk factors were identified with uni- and multivariate logistic regression models and the predictive performance of the final model was evaluated using the receiver operating characteristic (ROC) method. The final model was built up by seven risk factors for spinal pain for days; age > 12 years, learning or watching TV for more than 2 h/day, uncomfortable school-desk, sleeping problems, general discomfort and positive familiar medical history (χ 2  = 101.07; df = 8; p < 0.001). The probabilistic performance was confirmed with ROC analysis on the test and validation cohorts (AUC = 0.76; 0.71). A simplified risk scoring system showed increasing possibility for non-specific spinal pain depending on the number of the identified risk factors (χ 2  = 65.0; df = 4; p < 0.001). Seven significant risk factors of non-specific spinal pain in childhood were identified using the new, easy to use and reliable PRQ which makes it possible to stratify the children according to their individual risk. These slides can be retrieved under Electronic Supplementary Material.

Clinical Utility of Five Genetic Variants for Predicting Prostate Cancer Risk and Mortality

PubMed Central

Salinas, Claudia A.; Koopmeiners, Joseph S.; Kwon, Erika M.; FitzGerald, Liesel; Lin, Daniel W.; Ostrander, Elaine A.; Feng, Ziding; Stanford, Janet L.

2009-01-01

Background A recent report suggests that the combination of five single-nucleotide polymorphisms (SNPs) at 8q24, 17q12, 17q24.3 and a family history of the disease may predict risk of prostate cancer. The present study tests the performance of these factors in prediction models for prostate cancer risk and prostate cancer-specific mortality. Methods SNPs were genotyped in population-based samples from Caucasians in King County, Washington. Incident cases (n=1308), aged 35–74, were compared to age-matched controls (n=1266) using logistic regression to estimate odds ratios (OR) associated with genotypes and family history. Cox proportional hazards models estimated hazard ratios for prostate cancer-specific mortality according to genotypes. Results The combination of SNP genotypes and family history was significantly associated with prostate cancer risk (ptrend=1.5 × 10−20). Men with ≥ five risk factors had an OR of 4.9 (95% CI 1.6 to 18.5) compared to men with none. However, this combination of factors did not improve the ROC curve after accounting for known risk predictors (i.e., age, serum PSA, family history). Neither the individual nor combined risk factors was associated with prostate cancer-specific mortality. Conclusion Genotypes for five SNPs plus family history are associated with a significant elevation in risk for prostate cancer and may explain up to 45% of prostate cancer in our population. However, they do not improve prediction models for assessing who is at risk of getting or dying from the disease, once known risk or prognostic factors are taken into account. Thus, this SNP panel may have limited clinical utility. PMID:19058137

Berry Flesh and Skin Ripening Features in Vitis vinifera as Assessed by Transcriptional Profiling

PubMed Central

Grimplet, Jérôme; Bravo, Gema; Flores, Pilar; Fenoll, José; Hellín, Pilar; Oliveros, Juan Carlos; Martínez-Zapater, José M.

2012-01-01

Background Ripening of fleshy fruit is a complex developmental process involving the differentiation of tissues with separate functions. During grapevine berry ripening important processes contributing to table and wine grape quality take place, some of them flesh- or skin-specific. In this study, transcriptional profiles throughout flesh and skin ripening were followed during two different seasons in a table grape cultivar ‘Muscat Hamburg’ to determine tissue-specific as well as common developmental programs. Methodology/Principal Findings Using an updated GrapeGen Affymetrix GeneChip® annotation based on grapevine 12×v1 gene predictions, 2188 differentially accumulated transcripts between flesh and skin and 2839 transcripts differentially accumulated throughout ripening in the same manner in both tissues were identified. Transcriptional profiles were dominated by changes at the beginning of veraison which affect both pericarp tissues, although frequently delayed or with lower intensity in the skin than in the flesh. Functional enrichment analysis identified the decay on biosynthetic processes, photosynthesis and transport as a major part of the program delayed in the skin. In addition, a higher number of functional categories, including several related to macromolecule transport and phenylpropanoid and lipid biosynthesis, were over-represented in transcripts accumulated to higher levels in the skin. Functional enrichment also indicated auxin, gibberellins and bHLH transcription factors to take part in the regulation of pre-veraison processes in the pericarp, whereas WRKY and C2H2 family transcription factors seems to more specifically participate in the regulation of skin and flesh ripening, respectively. Conclusions/Significance A transcriptomic analysis indicates that a large part of the ripening program is shared by both pericarp tissues despite some components are delayed in the skin. In addition, important tissue differences are present from early stages prior to the ripening onset including tissue-specific regulators. Altogether, these findings provide key elements to understand berry ripening and its differential regulation in flesh and skin. PMID:22768087

The factor structure of complex posttraumatic stress disorder in traumatized refugees.

PubMed

Nickerson, Angela; Cloitre, Marylene; Bryant, Richard A; Schnyder, Ulrich; Morina, Naser; Schick, Matthis

2016-01-01

The construct of complex posttraumatic stress disorder (CPTSD) has attracted much research attention in previous years, however it has not been systematically evaluated in individuals exposed to persecution and displacement. Given that CPTSD has been proposed as a diagnostic category in the ICD-11, it is important that it be examined in refugee groups. In the current study, we proposed to test, for the first time, the factor structure of CPTSD proposed for the ICD-11 in a sample of resettled treatment-seeking refugees. The study sample consisted of 134 traumatized refugees from a variety of countries of origin, with approximately 93% of the sample having been exposed to torture. We used confirmatory factor analysis to examine the factor structure of CPTSD in this sample and examined the sensitivity, specificity, positive predictive power and negative predictive power of individual items in relation to the CPTSD diagnosis. Findings revealed that a two-factor higher-order model of CPTSD comprising PTSD and Difficulties in Self-Organization (χ 2 (47)=57.322, p =0.144, RMSEA=0.041, CFI=0.981, TLI=0.974) evidenced superior fit compared to a one-factor higher-order model of CPTSD (χ 2 (48)=65.745, p =0.045, RMSEA=0.053, CFI=0.968, TLI=0.956). Overall, items evidenced strong sensitivity and negative predictive power, moderate positive predictive power, and poor specificity. Findings provide preliminary evidence for the validity of the CPTSD construct with highly traumatized treatment-seeking refugees.

Cognitive processes in children's reading and attention: the role of working memory, divided attention, and response inhibition.

PubMed

Savage, Robert; Cornish, Kim; Manly, Tom; Hollis, Chris

2006-08-01

Children experiencing attention difficulties have documented cognitive deficits in working memory (WM), response inhibition and dual tasks. Recent evidence suggests however that these same cognitive processes are also closely associated with reading acquisition. This paper therefore explores whether these variables predicted attention difficulties or reading among 123 children with and without significant attention problems sampled from the school population. Children were screened using current WM and attention task measures. Three factors explained variance in WM and attention tasks. Response inhibition tasks loaded mainly with central executive measures, but a dual processing task loaded with the visual-spatial WM measures. Phonological loop measures loaded independently of attention measures. After controls for age, IQ and attention-group membership, phonological loop and 'central processing' measures both predicted reading ability. A 'visual memory/dual-task' factor predicted attention group membership after controls for age, IQ and reading ability. Results thus suggest that some of the processes previously assumed to be predictive of attention problems may reflect processes involved in reading acquisition. Visual memory and dual-task functioning are, however, purer indices of cognitive difficulty in children experiencing attention problems.

Temperature distribution analysis of tissue water vaporization during microwave ablation: experiments and simulations.

PubMed

Ai, Haiming; Wu, Shuicai; Gao, Hongjian; Zhao, Lei; Yang, Chunlan; Zeng, Yi

2012-01-01

The temperature distribution in the region near a microwave antenna is a critical factor that affects the entire temperature field during microwave ablation of tissue. It is challenging to predict this distribution precisely, because the temperature in the near-antenna region varies greatly. The effects of water vaporisation and subsequent tissue carbonisation in an ex vivo porcine liver were therefore studied experimentally and in simulations. The enthalpy and high-temperature specific absorption rate (SAR) of liver tissues were calculated and incorporated into the simulation process. The accuracy of predictions for near-field temperatures in our simulations has reached the level where the average maximum error is less than 5°C. In addition, a modified thermal model that accounts for water vaporisation and the change in the SAR distribution pattern is proposed and validated with experiment. The results from this study may be useful in the clinical practice of microwave ablation and can be applied to predict the temperature field in surgical planning.

Heavy Mettle: Stories of Transition for Delinquent Youth.

ERIC Educational Resources Information Center

Yellin, Eileen Mayer; Quinn, Mary Magee; Hoffinan, Catherine Corinne

1998-01-01

Interviews with four delinquent youth in the process of real-life transitions reveal that predicting resilience or recidivism is not always as simple as quantifying research-identified risk or protective factors. Suggests that there may be other factors that have not yet been pinpointed that should be explored when trying to predict resilience or…

Distinct work-related, clinical and psychological factors predict return to work following treatment in four different cancer types.

PubMed

Cooper, Alethea F; Hankins, Matthew; Rixon, Lorna; Eaton, Emma; Grunfeld, Elizabeth A

2013-03-01

Many factors influence return to work (RTW) following cancer treatment. However specific factors affecting RTW across different cancer types are unclear. This study examined the role of clinical, sociodemographic, work and psychological factors in RTW following treatment for breast, gynaecological, head and neck, and urological cancer. A 12-month prospective questionnaire study was conducted with 290 patients. Cox regression analyses were conducted to calculate hazard ratios (HR) for time to RTW. Between 89-94% of cancer survivors returned to work. Breast cancer survivors took the longest to return (median 30 weeks), and urology cancer survivors returned the soonest (median 5 weeks). Earlier return among breast cancer survivors was predicted by a greater sense of control over their cancer at work (HR 1.2; 95% CI: 1.09-1.37) and by full-time work (HR 2.1; CI: 1.24-3.4). Predictive of a longer return among gynaecological cancer survivors was a belief that cancer treatment may impair ability to work (HR 0.75; CI: 0.62-0.91). Among urological cancer survivors constipation was predictive of longer RTW (HR 0.99; CI: 0.97-1.00), whereas undertaking flexible working was predictive of returning sooner (HR 1.70; CI: 1.07-2.7). Head and neck cancer survivors who perceived greater negative consequences of their cancer took longer to return (HR 0.27; CI: 0.11-0.68). Those reporting better physical functioning returned sooner (HR1.04; CI: 1.01-1.08). A different profile of predictive factors emerged for the four cancer types. In addition to optimal symptom management and workplace adaptations, the findings suggest that eliciting and challenging specific cancer and treatment-related perceptions may facilitate RTW. Copyright © 2012 John Wiley & Sons, Ltd.

Theory-of-mind development influences suggestibility and source monitoring.

PubMed

Bright-Paul, Alexandra; Jarrold, Christopher; Wright, Daniel B

2008-07-01

According to the mental-state reasoning model of suggestibility, 2 components of theory of mind mediate reductions in suggestibility across the preschool years. The authors examined whether theory-of-mind performance may be legitimately separated into 2 components and explored the memory processes underlying the associations between theory of mind and suggestibility, independent of verbal ability. Children 3 to 6 years old completed 6 theory-of-mind tasks and a postevent misinformation procedure. Contrary to the model's prediction, a single latent theory-of-mind factor emerged, suggesting a single-component rather than a dual-component conceptualization of theory-of-mind performance. This factor provided statistical justification for computing a single composite theory-of-mind score. Improvements in theory of mind predicted reductions in suggestibility, independent of verbal ability (Study 1, n = 72). Furthermore, once attribution biases were controlled (Study 2, n = 45), there was also a positive relationship between theory of mind and source memory, but not recognition performance. The findings suggest a substantial, and possibly causal, association between theory-of-mind development and resistance to suggestion, driven specifically by improvements in source monitoring.

Measurements of nonlinear Hall-driven reconnection in the reversed field pinch

NASA Astrophysics Data System (ADS)

Tharp, Timothy D.

Complex organisms are able to develop because of the complex regulatory systems that control their gene expression. The first step in this regulation, transcription initiation, is controlled by transcription factors. Transcription factors are modular proteins composed of two distinct domains, the DNA binding domain and the regulatory domain. These molecules are involved in a plethora of important biological processes including embryogenesis, development, cell health, and cancer. Tissue enriched transcription factors Nkx-2.5 and Gata4 are involved in cardiac development and cardiac health. In this thesis the DNA binding specificity of Nkx-2.5 will be analyzed using a high throughput double stranded DNA platform called Cognate Site Identifier (CSI) arrays (Chapter 2). The full DNA binding specificity of Nkx-2.5 and Nkx-2.5 mutants will be visualized using Sequence Specificity Landscapes (SSLs). In Chapter 3, the definition of binding specificity will be investigated by evaluating a number of different DNA binding folds by CSI and SSLs. CSI and SSLs will also be used to evaluate different pyrrole/imidazole hairpin polyamides in order to better characterize these small molecule DNA binding domains. CSI and SSL data will be applied to the genome in order to explain the biological function an artificial transcription factor. Chapter 4 will discuss the mechanism of nonspecific DNA binding. The historical means of predicting DNA binding will be challenged by utilizing high throughput experiments. The effect of salt concentration on both specific and nonspecific binding will also be investigated. Finally, in Chapter 5, a generation of Protein DNA Dimerizer will be discussed. A PDD that regulates transcription on genomic DNA by binding cooperatively with the heart IF Gata4 will be characterized. These studies provide understanding of, and a means to control, how transcription factors sample the endless sea of DNA in the genome in order to regulate gene expression with such wonderful specificity.

Using the Positive and Negative Syndrome Scale (PANSS) to Define Different Domains of Negative Symptoms

PubMed Central

Khan, Anzalee; Keefe, Richard S. E.

2017-01-01

Background: Reduced emotional experience and expression are two domains of negative symptoms. The authors assessed these two domains of negative symptoms using previously developed Positive and Negative Syndrome Scale (PANSS) factors. Using an existing dataset, the authors predicted three different elements of everyday functioning (social, vocational, and everyday activities) with these two factors, as well as with performance on measures of functional capacity. Methods: A large (n=630) sample of people with schizophrenia was used as the data source of this study. Using regression analyses, the authors predicted the three different aspects of everyday functioning, first with just the two Positive and Negative Syndrome Scale factors and then with a global negative symptom factor. Finally, we added neurocognitive performance and functional capacity as predictors. Results: The Positive and Negative Syndrome Scale reduced emotional experience factor accounted for 21 percent of the variance in everyday social functioning, while reduced emotional expression accounted for no variance. The total Positive and Negative Syndrome Scale negative symptom factor accounted for less variance (19%) than the reduced experience factor alone. The Positive and Negative Syndrome Scale expression factor accounted for, at most, one percent of the variance in any of the functional outcomes, with or without the addition of other predictors. Implications: Reduced emotional experience measured with the Positive and Negative Syndrome Scale, often referred to as “avolition and anhedonia,” specifically predicted impairments in social outcomes. Further, reduced experience predicted social impairments better than emotional expression or the total Positive and Negative Syndrome Scale negative symptom factor. In this cross-sectional study, reduced emotional experience was specifically related with social outcomes, accounting for essentially no variance in work or everyday activities, and being the sole meaningful predictor of impairment in social outcomes. PMID:29410933

Disparities in the diagnostic process of Duchenne and Becker muscular dystrophy.

PubMed

Holtzer, Caleb; Meaney, F John; Andrews, Jennifer; Ciafaloni, Emma; Fox, Deborah J; James, Katherine A; Lu, Zhenqiang; Miller, Lisa; Pandya, Shree; Ouyang, Lijing; Cunniff, Christopher

2011-11-01

To determine whether sociodemographic factors are associated with delays at specific steps in the diagnostic process of Duchenne and Becker muscular dystrophy. We examined abstracted medical records for 540 males from population-based surveillance sites in Arizona, Colorado, Georgia, Iowa, and western New York. We used linear regressions to model the association of three sociodemographic characteristics with age at initial medical evaluation, first creatine kinase measurement, and earliest DNA analysis while controlling for changes in the diagnostic process over time. The analytical dataset included 375 males with information on family history of Duchenne and Becker muscular dystrophy, neighborhood poverty levels, and race/ethnicity. Black and Hispanic race/ethnicity predicted older ages at initial evaluation, creatine kinase measurement, and DNA testing (P < 0.05). A positive family history of Duchenne and Becker muscular dystrophy predicted younger ages at initial evaluation, creatine kinase measurement and DNA testing (P < 0.001). Higher neighborhood poverty was associated with earlier ages of evaluation (P < 0.05). Racial and ethnic disparities in the diagnostic process for Duchenne and Becker muscular dystrophy are evident even after adjustment for family history of Duchenne and Becker muscular dystrophy and changes in the diagnostic process over time. Black and Hispanic children are initially evaluated at older ages than white children, and the gap widens at later steps in the diagnostic process.

[Serum PTH levels as a predictive factor of hypocalcaemia after total thyroidectomy].

PubMed

Díez Alonso, Manuel; Sánchez López, José Daniel; Sánchez-Seco Peña, María Isabel; Ratia Jiménez, Tomás; Arribas Gómez, Ignacio; Rodríguez Pascual, Angel; Martín-Duce, Antonio; Guadalix Hidalgo, Gregorio; Hernández Domínguez, Sara; Granell Vicent, Javier

2009-02-01

Postoperative parathyroid hormone (PTH) levels as a predictor of hypocalcaemia in patients subjected to total thyroidectomy is analyzed. Prospective study involving 67 patients who underwent total thyroidectomy due to a benign disease. Serum PTH and ionised calcium were measured 20 h after surgery. Sensitivity, specificity and predictive values of PTH and ionised calcium levels were calculated to predict clinical and analytical hypocalcaemia. A total of 42 (62.7%) patients developed hypocalcaemia (ionised calcium<0.95 mmol/l), but only 20 (29.9%) presented with symptoms. PTH concentration the day after surgery was significantly lower in the group that developed symptomatic hypocalcaemia (5.57+/-6.4 pg/ml) than in the asymptomatic (21.5+/-15.3 pg/ml) or normocalcaemic (26.8+/-24.9 pg/ml) groups (p=0.001). Taking the value of 13 pg/ml as a cut-off point of PTH levels, sensitivity, specificity, positive predictive value and negative predictive value were 54%, 72%, 76% and 48%, respectively. On the other hand, sensitivity for predicting symptomatic hypocalcaemia was 95% and specificity was 76%. The test showed a high incidence of false positives (11/30, 36%). Negative predictive value was 97% and positive predictive value was 65%. In multivariate analysis, PTH and ionised calcium were the only perioperative factors that showed an independent predictive value as risk indicators of symptomatic hypocalcaemia. Normal PTH levels 20 h after surgery practically rule out the subsequent appearance of hypocalcaemia symptoms. On the other hand, low PTH levels are not necessarily associated to symptomatic hypocalcaemia due to the high number of false positives.

Life cycle based risk assessment of recycled materials in roadway construction.

PubMed

Carpenter, A C; Gardner, K H; Fopiano, J; Benson, C H; Edil, T B

2007-01-01

This paper uses a life-cycle assessment (LCA) framework to characterize comparative environmental impacts from the use of virgin aggregate and recycled materials in roadway construction. To evaluate site-specific human toxicity potential (HTP) in a more robust manner, metals release data from a demonstration site were combined with an unsaturated contaminant transport model to predict long-term impacts to groundwater. The LCA determined that there were reduced energy and water consumption, air emissions, Pb, Hg and hazardous waste generation and non-cancer HTP when bottom ash was used in lieu of virgin crushed rock. Conversely, using bottom ash instead of virgin crushed rock increased the cancer HTP risk due to potential leachate generation by the bottom ash. At this scale of analysis, the trade-offs are clearly between the cancer HTP (higher for bottom ash) and all of the other impacts listed above (lower for bottom ash). The site-specific analysis predicted that the contaminants (Cd, Cr, Se and Ag for this study) transported from the bottom ash to the groundwater resulted in very low unsaturated zone contaminant concentrations over a 200 year period due to retardation in the vadose zone. The level of contaminants predicted to reach the groundwater after 200 years was significantly less than groundwater maximum contaminant levels (MCL) set by the US Environmental Protection Agency for drinking water. Results of the site-specific contaminant release estimates vary depending on numerous site and material specific factors. However, the combination of the LCA and the site specific analysis can provide an appropriate context for decision making. Trade-offs are inherent in making decisions about recycled versus virgin material use, and regulatory frameworks should recognize and explicitly acknowledge these trade-offs in decision processes.

Using the Positive and Negative Syndrome Scale (PANSS) to Define Different Domains of Negative Symptoms: Prediction of Everyday Functioning by Impairments in Emotional Expression and Emotional Experience.

PubMed

Harvey, Philip D; Khan, Anzalee; Keefe, Richard S E

2017-12-01

Background: Reduced emotional experience and expression are two domains of negative symptoms. The authors assessed these two domains of negative symptoms using previously developed Positive and Negative Syndrome Scale (PANSS) factors. Using an existing dataset, the authors predicted three different elements of everyday functioning (social, vocational, and everyday activities) with these two factors, as well as with performance on measures of functional capacity. Methods: A large (n=630) sample of people with schizophrenia was used as the data source of this study. Using regression analyses, the authors predicted the three different aspects of everyday functioning, first with just the two Positive and Negative Syndrome Scale factors and then with a global negative symptom factor. Finally, we added neurocognitive performance and functional capacity as predictors. Results: The Positive and Negative Syndrome Scale reduced emotional experience factor accounted for 21 percent of the variance in everyday social functioning, while reduced emotional expression accounted for no variance. The total Positive and Negative Syndrome Scale negative symptom factor accounted for less variance (19%) than the reduced experience factor alone. The Positive and Negative Syndrome Scale expression factor accounted for, at most, one percent of the variance in any of the functional outcomes, with or without the addition of other predictors. Implications: Reduced emotional experience measured with the Positive and Negative Syndrome Scale, often referred to as "avolition and anhedonia," specifically predicted impairments in social outcomes. Further, reduced experience predicted social impairments better than emotional expression or the total Positive and Negative Syndrome Scale negative symptom factor. In this cross-sectional study, reduced emotional experience was specifically related with social outcomes, accounting for essentially no variance in work or everyday activities, and being the sole meaningful predictor of impairment in social outcomes.

Development of a process-based model to predict pathogen budgets for the Sydney drinking water catchment.

PubMed

Ferguson, Christobel M; Croke, Barry F W; Beatson, Peter J; Ashbolt, Nicholas J; Deere, Daniel A

2007-06-01

In drinking water catchments, reduction of pathogen loads delivered to reservoirs is an important priority for the management of raw source water quality. To assist with the evaluation of management options, a process-based mathematical model (pathogen catchment budgets - PCB) is developed to predict Cryptosporidium, Giardia and E. coli loads generated within and exported from drinking water catchments. The model quantifies the key processes affecting the generation and transport of microorganisms from humans and animals using land use and flow data, and catchment specific information including point sources such as sewage treatment plants and on-site systems. The resultant pathogen catchment budgets (PCB) can be used to prioritize the implementation of control measures for the reduction of pathogen risks to drinking water. The model is applied in the Wingecarribee catchment and used to rank those sub-catchments that would contribute the highest pathogen loads in dry weather, and in intermediate and large wet weather events. A sensitivity analysis of the model identifies that pathogen excretion rates from animals and humans, and manure mobilization rates are significant factors determining the output of the model and thus warrant further investigation.

The predictive influence of family and neighborhood assets on fighting and weapon carrying from mid- to late adolescence.

PubMed

Haegerich, Tamara M; Oman, Roy F; Vesely, Sara K; Aspy, Cheryl B; Tolma, Eleni L

2014-08-01

Using a developmental, social-ecological approach to understand the etiology of health-risk behavior and inform primary prevention efforts, we assess the predictive effects of family and neighborhood social processes on youth physical fighting and weapon carrying. Specifically, we focus on relationships among youth and their parents, family communication, parental monitoring, as well as sense of community and neighborhood informal social control, support, concerns, and disorder. This study advances knowledge through its investigation of family and neighborhood structural factors and social processes together, employment of longitudinal models that estimate effects over adolescent development, and use of self-report and observational measures. Data from 1,093 youth/parent pairs were analyzed from the Youth Assets Study using a Generalized Estimating Equation approach; family and neighborhood assets and risks were analyzed as time varying and lagged. Similar family assets affected physical fighting and weapon carrying, whereas different neighborhood social processes influenced the two forms of youth violence. Study findings have implications for the primary prevention of youth violence, including the use of family-based approaches that build relationships and parental monitoring skills and community-level change approaches that promote informal social control and reduce neighborhood concerns about safety.

Basolateral amygdala rapid glutamate release encodes an outcome-specific representation vital for reward-predictive cues to selectively invigorate reward-seeking actions

PubMed Central

Malvaez, Melissa; Greenfield, Venuz Y.; Wang, Alice S.; Yorita, Allison M.; Feng, Lili; Linker, Kay E.; Monbouquette, Harold G.; Wassum, Kate M.

2015-01-01

Environmental stimuli have the ability to generate specific representations of the rewards they predict and in so doing alter the selection and performance of reward-seeking actions. The basolateral amygdala participates in this process, but precisely how is unknown. To rectify this, we monitored, in near-real time, basolateral amygdala glutamate concentration changes during a test of the ability of reward-predictive cues to influence reward-seeking actions (Pavlovian-instrumental transfer). Glutamate concentration was found to be transiently elevated around instrumental reward seeking. During the Pavlovian-instrumental transfer test these glutamate transients were time-locked to and correlated with only those actions invigorated by outcome-specific motivational information provided by the reward-predictive stimulus (i.e., actions earning the same specific outcome as predicted by the presented CS). In addition, basolateral amygdala AMPA, but not NMDA glutamate receptor inactivation abolished the selective excitatory influence of reward-predictive cues over reward seeking. These data the hypothesis that transient glutamate release in the BLA can encode the outcome-specific motivational information provided by reward-predictive stimuli. PMID:26212790

TRASYS form factor matrix normalization

NASA Technical Reports Server (NTRS)

Tsuyuki, Glenn T.

1992-01-01

A method has been developed for adjusting a TRASYS enclosure form factor matrix to unity. This approach is not limited to closed geometries, and in fact, it is primarily intended for use with open geometries. The purpose of this approach is to prevent optimistic form factors to space. In this method, nodal form factor sums are calculated within 0.05 of unity using TRASYS, although deviations as large as 0.10 may be acceptable, and then, a process is employed to distribute the difference amongst the nodes. A specific example has been analyzed with this method, and a comparison was performed with a standard approach for calculating radiation conductors. In this comparison, hot and cold case temperatures were determined. Exterior nodes exhibited temperature differences as large as 7 C and 3 C for the hot and cold cases, respectively when compared with the standard approach, while interior nodes demonstrated temperature differences from 0 C to 5 C. These results indicate that temperature predictions can be artificially biased if the form factor computation error is lumped into the individual form factors to space.

Estimating drought risk across Europe from reported drought impacts, drought indices, and vulnerability factors

NASA Astrophysics Data System (ADS)

Blauhut, Veit; Stahl, Kerstin; Stagge, James Howard; Tallaksen, Lena M.; De Stefano, Lucia; Vogt, Jürgen

2016-07-01

Drought is one of the most costly natural hazards in Europe. Due to its complexity, drought risk, meant as the combination of the natural hazard and societal vulnerability, is difficult to define and challenging to detect and predict, as the impacts of drought are very diverse, covering the breadth of socioeconomic and environmental systems. Pan-European maps of drought risk could inform the elaboration of guidelines and policies to address its documented severity and impact across borders. This work tests the capability of commonly applied drought indices and vulnerability factors to predict annual drought impact occurrence for different sectors and macro regions in Europe and combines information on past drought impacts, drought indices, and vulnerability factors into estimates of drought risk at the pan-European scale. This hybrid approach bridges the gap between traditional vulnerability assessment and probabilistic impact prediction in a statistical modelling framework. Multivariable logistic regression was applied to predict the likelihood of impact occurrence on an annual basis for particular impact categories and European macro regions. The results indicate sector- and macro-region-specific sensitivities of drought indices, with the Standardized Precipitation Evapotranspiration Index (SPEI) for a 12-month accumulation period as the overall best hazard predictor. Vulnerability factors have only limited ability to predict drought impacts as single predictors, with information about land use and water resources being the best vulnerability-based predictors. The application of the hybrid approach revealed strong regional and sector-specific differences in drought risk across Europe. The majority of the best predictor combinations rely on a combination of SPEI for shorter and longer accumulation periods, and a combination of information on land use and water resources. The added value of integrating regional vulnerability information with drought risk prediction could be proven. Thus, the study contributes to the overall understanding of drivers of drought impacts, appropriateness of drought indices selection for specific applications, and drought risk assessment.

Bacterial Community Dynamics in Full-Scale Activated Sludge Bioreactors: Operational and Ecological Factors Driving Community Assembly and Performance

PubMed Central

Valentín-Vargas, Alexis; Toro-Labrador, Gladys; Massol-Deyá, Arturo A.

2012-01-01

The assembling of bacterial communities in conventional activated sludge (CAS) bioreactors was thought, until recently, to be chaotic and mostly unpredictable. Studies done over the last decade have shown that specific, and often, predictable random and non-random factors could be responsible for that process. These studies have also motivated a “structure–function” paradigm that is yet to be resolved. Thus, elucidating the factors that affect community assembly in the bioreactors is necessary for predicting fluctuations in community structure and function. For this study activated sludge samples were collected during a one-year period from two geographically distant CAS bioreactors of different size. Combining community fingerprinting analysis and operational parameters data with a robust statistical analysis, we aimed to identify relevant links between system performance and bacterial community diversity and dynamics. In addition to revealing a significant β-diversity between the bioreactors’ communities, results showed that the largest bioreactor had a less dynamic but more efficient and diverse bacterial community throughout the study. The statistical analysis also suggests that deterministic factors, as opposed to stochastic factors, may have a bigger impact on the community structure in the largest bioreactor. Furthermore, the community seems to rely mainly on mechanisms of resistance and functional redundancy to maintain functional stability. We suggest that the ecological theories behind the Island Biogeography model and the species-area relationship were appropriate to predict the assembly of bacterial communities in these CAS bioreactors. These results are of great importance for engineers and ecologists as they reveal critical aspects of CAS systems that could be applied towards improving bioreactor design and operation. PMID:22880016

Prediction of Balance Compensation After Vestibular Schwannoma Surgery.

PubMed

Parietti-Winkler, Cécile; Lion, Alexis; Frère, Julien; Perrin, Philippe P; Beurton, Renaud; Gauchard, Gérome C

2016-06-01

Background Balance compensation after vestibular schwannoma (VS) surgery is under the influence of specific preoperative patient and tumor characteristics. Objective To prospectively identify potential prognostic factors for balance recovery, we compared the respective influence of these preoperative characteristics on balance compensation after VS surgery. Methods In 50 patients scheduled for VS surgical ablation, we measured postural control before surgery (BS), 8 (AS8) days after, and 90 (AS90) days after surgery. Based on factors found previously in the literature, we evaluated age, body mass index and preoperative physical activity (PA), tumor grade, vestibular status, and preference for visual cues to control balance as potential prognostic factors using stepwise multiple regression models. Results An asymmetric vestibular function was the sole significant explanatory factor for impaired balance performance BS, whereas the preoperative PA alone significantly contributed to higher performance at AS8. An evaluation of patients' balance recovery over time showed that PA and vestibular status were the 2 significant predictive factors for short-term postural compensation (BS to AS8), whereas none of these preoperative factors was significantly predictive for medium-term postoperative postural recovery (AS8 to AS90). Conclusions We identified specific preoperative patient and vestibular function characteristics that may predict postoperative balance recovery after VS surgery. Better preoperative characterization of these factors in each patient could inform more personalized presurgical and postsurgical management, leading to a better, more rapid balance recovery, earlier return to normal daily activities and work, improved quality of life, and reduced medical and societal costs. © The Author(s) 2015.

Mediators of exposure therapy for youth obsessive-compulsive disorder: specificity and temporal sequence of client and treatment factors.

PubMed

Chu, Brian C; Colognori, Daniela B; Yang, Guang; Xie, Min-ge; Lindsey Bergman, R; Piacentini, John

2015-05-01

Behavioral engagement and cognitive coping have been hypothesized to mediate effectiveness of exposure-based therapies. Identifying which specific child factors mediate successful therapy and which therapist factors facilitate change can help make our evidence-based treatments more efficient and robust. The current study examines the specificity and temporal sequence of relations among hypothesized client and therapist mediators in exposure therapy for pediatric Obsessive Compulsive Disorder (OCD). Youth coping (cognitive, behavioral), youth safety behaviors (avoidance, escape, compulsive behaviors), therapist interventions (cognitive, exposure extensiveness), and youth anxiety were rated via observational ratings of therapy sessions of OCD youth (N=43; ages=8 - 17; 62.8% male) who had received Exposure and Response Prevention (ERP). Regression analysis using Generalized Estimation Equations and cross-lagged panel analysis (CLPA) were conducted to model anxiety change within and across sessions, to determine formal mediators of anxiety change, and to establish sequence of effects. Anxiety ratings decreased linearly across exposures within sessions. Youth coping and therapist interventions significantly mediated anxiety change across exposures, and youth-interfering behavior mediated anxiety change at the trend level. In CLPA, youth-interfering behaviors predicted, and were predicted by, changes in anxiety. Youth coping was predicted by prior anxiety change. The study provides a preliminary examination of specificity and temporal sequence among child and therapist behaviors in predicting youth anxiety. Results suggest that therapists should educate clients in the natural rebound effects of anxiety between sessions and should be aware of the negatively reinforcing properties of avoidance during exposure. Copyright © 2015. Published by Elsevier Ltd.

Predicting the probability of mortality of gastric cancer patients using decision tree.

PubMed

Mohammadzadeh, F; Noorkojuri, H; Pourhoseingholi, M A; Saadat, S; Baghestani, A R

2015-06-01

Gastric cancer is the fourth most common cancer worldwide. This reason motivated us to investigate and introduce gastric cancer risk factors utilizing statistical methods. The aim of this study was to identify the most important factors influencing the mortality of patients who suffer from gastric cancer disease and to introduce a classification approach according to decision tree model for predicting the probability of mortality from this disease. Data on 216 patients with gastric cancer, who were registered in Taleghani hospital in Tehran,Iran, were analyzed. At first, patients were divided into two groups: the dead and alive. Then, to fit decision tree model to our data, we randomly selected 20% of dataset to the test sample and remaining dataset considered as the training sample. Finally, the validity of the model examined with sensitivity, specificity, diagnosis accuracy and the area under the receiver operating characteristic curve. The CART version 6.0 and SPSS version 19.0 softwares were used for the analysis of the data. Diabetes, ethnicity, tobacco, tumor size, surgery, pathologic stage, age at diagnosis, exposure to chemical weapons and alcohol consumption were determined as effective factors on mortality of gastric cancer. The sensitivity, specificity and accuracy of decision tree were 0.72, 0.75 and 0.74 respectively. The indices of sensitivity, specificity and accuracy represented that the decision tree model has acceptable accuracy to prediction the probability of mortality in gastric cancer patients. So a simple decision tree consisted of factors affecting on mortality of gastric cancer may help clinicians as a reliable and practical tool to predict the probability of mortality in these patients.

Predictors of participation in sports after hip and knee arthroplasty.

PubMed

Williams, Daniel H; Greidanus, Nelson V; Masri, Bassam A; Duncan, Clive P; Garbuz, Donald S

2012-02-01

While the primary objective of joint arthroplasty is to improve patient quality of life, pain, and function, younger active patients often demand a return to higher function that includes sporting activity. Knowledge of rates and predictors of return to sports will help inform expectations in patients anticipating return to sports after joint arthroplasty. We measured the rate of sports participation at 1 year using the UCLA activity score and explored 11 variables, including choice of procedure/prosthesis, that might predict return to a high level of sporting activity, when controlling for potential confounding variables. We retrospectively evaluated 736 patients who underwent primary metal-on-polyethylene THA, metal-on-metal THA, hip resurfacing arthroplasty, revision THA, primary TKA, unicompartmental knee arthroplasty, and revision TKA between May 2005 and June 2007. We obtained UCLA activity scores on all patients; we defined high activity as a UCLA score of 7 or more. We evaluated patient demographics (age, sex, BMI, comorbidity), quality of life (WOMAC score, Oxford Hip Score, SF-12 score), and surgeon- and procedural/implant-specific variables to identify factors associated with postoperative activity score. Minimum followup was 11 months (mean, 12.1 months; range, 11-13 months). Preoperative UCLA activity score, age, male sex, and BMI predicted high activity scores. The type of operation and implant characteristics did not predict return to high activity sports. Our data suggest patient-specific factors predict postoperative activity rather than factors specific to type of surgery, implant, or surgeon factors. Level II, prognostic study. See the Guidelines for Authors for a complete description of levels of evidence.

Genome-wide patterns of promoter sharing and co-expression in bovine skeletal muscle.

PubMed

Gu, Quan; Nagaraj, Shivashankar H; Hudson, Nicholas J; Dalrymple, Brian P; Reverter, Antonio

2011-01-12

Gene regulation by transcription factors (TF) is species, tissue and time specific. To better understand how the genetic code controls gene expression in bovine muscle we associated gene expression data from developing Longissimus thoracis et lumborum skeletal muscle with bovine promoter sequence information. We created a highly conserved genome-wide promoter landscape comprising 87,408 interactions relating 333 TFs with their 9,242 predicted target genes (TGs). We discovered that the complete set of predicted TGs share an average of 2.75 predicted TF binding sites (TFBSs) and that the average co-expression between a TF and its predicted TGs is higher than the average co-expression between the same TF and all genes. Conversely, pairs of TFs sharing predicted TGs showed a co-expression correlation higher that pairs of TFs not sharing TGs. Finally, we exploited the co-occurrence of predicted TFBS in the context of muscle-derived functionally-coherent modules including cell cycle, mitochondria, immune system, fat metabolism, muscle/glycolysis, and ribosome. Our findings enabled us to reverse engineer a regulatory network of core processes, and correctly identified the involvement of E2F1, GATA2 and NFKB1 in the regulation of cell cycle, fat, and muscle/glycolysis, respectively. The pivotal implication of our research is two-fold: (1) there exists a robust genome-wide expression signal between TFs and their predicted TGs in cattle muscle consistent with the extent of promoter sharing; and (2) this signal can be exploited to recover the cellular mechanisms underpinning transcription regulation of muscle structure and development in bovine. Our study represents the first genome-wide report linking tissue specific co-expression to co-regulation in a non-model vertebrate.

Climatic and biotic stochasticity: disparate causes of convergent demographies in rare, sympatric plants.

PubMed

Fox, Laurel R

2007-12-01

Species with known demographies may be used as proxies, or approximate models, to predict vital rates and ecological properties of target species that either have not been studied or are species for which data may be difficult to obtain. These extrapolations assume that model and target species with similar properties respond in the same ways to the same ecological factors, that they have similar population dynamics, and that the similarity of vital rates reflects analogous responses to the same factors. I used two rare, sympatric annual plants (sand gilia [Gilia tenuiflora arenaria] and Monterey spineflower [Chorizanthe pungens pungens]) to test these assumptions experimentally. The vital rates of these species are similar and strongly correlated with rainfall, and I added water and/or prevented herbivore access to experimental plots. Their survival and reproduction were driven by different, largely stochastic factors and processes: sand gilia by herbivory and Monterey spineflower by rainfall. Because the causal agents and processes generating similar demographic patterns were species specific, these results demonstrate, both theoretically and empirically, that it is critical to identify the ecological processes generating observed effects and that experimental manipulations are usually needed to determine causal mechanisms. Without such evidence to identify mechanisms, extrapolations among species may lead to counterproductive management and conservation practices.

The Roles of Dispersal, Fecundity, and Predation in the Population Persistence of an Oak (Quercus engelmannii) under Global Change

PubMed Central

Conlisk, Erin; Lawson, Dawn; Syphard, Alexandra D.; Franklin, Janet; Flint, Lorraine; Flint, Alan; Regan, Helen M.

2012-01-01

A species’ response to climate change depends on the interaction of biotic and abiotic factors that define future habitat suitability and species’ ability to migrate or adapt. The interactive effects of processes such as fire, dispersal, and predation have not been thoroughly addressed in the climate change literature. Our objective was to examine how life history traits, short-term global change perturbations, and long-term climate change interact to affect the likely persistence of an oak species - Quercus engelmannii (Engelmann oak). Specifically, we combined dynamic species distribution models, which predict suitable habitat, with stochastic, stage-based metapopulation models, which project population trajectories, to evaluate the effects of three global change factors – climate change, land use change, and altered fire frequency – emphasizing the roles of dispersal and seed predation. Our model predicted dramatic reduction in Q. engelmannii abundance, especially under drier climates and increased fire frequency. When masting lowers seed predation rates, decreased masting frequency leads to large abundance decreases. Current rates of dispersal are not likely to prevent these effects, although increased dispersal could mitigate population declines. The results suggest that habitat suitability predictions by themselves may under-estimate the impact of climate change for other species and locations. PMID:22623955

Harnessing expert knowledge: Defining a Bayesian network decision model with limited data-Model structure for the vibration qualification problem

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

Rizzo, Davinia B.; Blackburn, Mark R.

As systems become more complex, systems engineers rely on experts to inform decisions. There are few experts and limited data in many complex new technologies. This challenges systems engineers as they strive to plan activities such as qualification in an environment where technical constraints are coupled with the traditional cost, risk, and schedule constraints. Bayesian network (BN) models provide a framework to aid systems engineers in planning qualification efforts with complex constraints by harnessing expert knowledge and incorporating technical factors. By quantifying causal factors, a BN model can provide data about the risk of implementing a decision supplemented with informationmore » on driving factors. This allows a systems engineer to make informed decisions and examine “what-if” scenarios. This paper discusses a novel process developed to define a BN model structure based primarily on expert knowledge supplemented with extremely limited data (25 data sets or less). The model was developed to aid qualification decisions—specifically to predict the suitability of six degrees of freedom (6DOF) vibration testing for qualification. The process defined the model structure with expert knowledge in an unbiased manner. Finally, validation during the process execution and of the model provided evidence the process may be an effective tool in harnessing expert knowledge for a BN model.« less

Harnessing expert knowledge: Defining a Bayesian network decision model with limited data-Model structure for the vibration qualification problem

DOE PAGES

Rizzo, Davinia B.; Blackburn, Mark R.

2018-03-30

As systems become more complex, systems engineers rely on experts to inform decisions. There are few experts and limited data in many complex new technologies. This challenges systems engineers as they strive to plan activities such as qualification in an environment where technical constraints are coupled with the traditional cost, risk, and schedule constraints. Bayesian network (BN) models provide a framework to aid systems engineers in planning qualification efforts with complex constraints by harnessing expert knowledge and incorporating technical factors. By quantifying causal factors, a BN model can provide data about the risk of implementing a decision supplemented with informationmore » on driving factors. This allows a systems engineer to make informed decisions and examine “what-if” scenarios. This paper discusses a novel process developed to define a BN model structure based primarily on expert knowledge supplemented with extremely limited data (25 data sets or less). The model was developed to aid qualification decisions—specifically to predict the suitability of six degrees of freedom (6DOF) vibration testing for qualification. The process defined the model structure with expert knowledge in an unbiased manner. Finally, validation during the process execution and of the model provided evidence the process may be an effective tool in harnessing expert knowledge for a BN model.« less

SVM-Based System for Prediction of Epileptic Seizures from iEEG Signal

PubMed Central

Cherkassky, Vladimir; Lee, Jieun; Veber, Brandon; Patterson, Edward E.; Brinkmann, Benjamin H.; Worrell, Gregory A.

2017-01-01

Objective This paper describes a data-analytic modeling approach for prediction of epileptic seizures from intracranial electroencephalogram (iEEG) recording of brain activity. Even though it is widely accepted that statistical characteristics of iEEG signal change prior to seizures, robust seizure prediction remains a challenging problem due to subject-specific nature of data-analytic modeling. Methods Our work emphasizes understanding of clinical considerations important for iEEG-based seizure prediction, and proper translation of these clinical considerations into data-analytic modeling assumptions. Several design choices during pre-processing and post-processing are considered and investigated for their effect on seizure prediction accuracy. Results Our empirical results show that the proposed SVM-based seizure prediction system can achieve robust prediction of preictal and interictal iEEG segments from dogs with epilepsy. The sensitivity is about 90–100%, and the false-positive rate is about 0–0.3 times per day. The results also suggest good prediction is subject-specific (dog or human), in agreement with earlier studies. Conclusion Good prediction performance is possible only if the training data contain sufficiently many seizure episodes, i.e., at least 5–7 seizures. Significance The proposed system uses subject-specific modeling and unbalanced training data. This system also utilizes three different time scales during training and testing stages. PMID:27362758

Nonperturbative Transverse Momentum Effects in p +p and p +A Collisions at PHENIX

NASA Astrophysics Data System (ADS)

Skoby, Michael; Phenix Collaboration

2017-09-01

Due to the non-Abelian nature of QCD, there is a prediction that quarks can become correlated across colliding protons in hadron production processes sensitive to nonperturbative transverse momentum effects. Measuring the evolution of nonperturbative transverse momentum widths as a function of the hard interaction scale can help distinguish these effects from other possibilities. Collins-Soper-Sterman evolution comes directly from the proof of transverse-momentum-dependent (TMD) factorization for processes such as Drell-Yan, semi-inclusive deep-inelastic scattering, and e +e- annihilation and predicts nonperturbative momentum widths to increase with hard scale. Experimental results from proton-proton and proton-nucleus collisions, in which TMD factorization is predicted to be broken, will be presented. The results show that these widths decrease with hard scale, suggesting possible effects from TMD factorization breaking.

Development of a Patient-Specific Multi-Scale Model to Understand Atherosclerosis and Calcification Locations: Comparison with In vivo Data in an Aortic Dissection

PubMed Central

Alimohammadi, Mona; Pichardo-Almarza, Cesar; Agu, Obiekezie; Díaz-Zuccarini, Vanessa

2016-01-01

Vascular calcification results in stiffening of the aorta and is associated with hypertension and atherosclerosis. Atherogenesis is a complex, multifactorial, and systemic process; the result of a number of factors, each operating simultaneously at several spatial and temporal scales. The ability to predict sites of atherogenesis would be of great use to clinicians in order to improve diagnostic and treatment planning. In this paper, we present a mathematical model as a tool to understand why atherosclerotic plaque and calcifications occur in specific locations. This model is then used to analyze vascular calcification and atherosclerotic areas in an aortic dissection patient using a mechanistic, multi-scale modeling approach, coupling patient-specific, fluid-structure interaction simulations with a model of endothelial mechanotransduction. A number of hemodynamic factors based on state-of-the-art literature are used as inputs to the endothelial permeability model, in order to investigate plaque and calcification distributions, which are compared with clinical imaging data. A significantly improved correlation between elevated hydraulic conductivity or volume flux and the presence of calcification and plaques was achieved by using a shear index comprising both mean and oscillatory shear components (HOLMES) and a non-Newtonian viscosity model as inputs, as compared to widely used hemodynamic indicators. The proposed approach shows promise as a predictive tool. The improvements obtained using the combined biomechanical/biochemical modeling approach highlight the benefits of mechanistic modeling as a powerful tool to understand complex phenomena and provides insight into the relative importance of key hemodynamic parameters. PMID:27445834

mRNA stability in mammalian cells.

PubMed Central

Ross, J

1995-01-01

This review concerns how cytoplasmic mRNA half-lives are regulated and how mRNA decay rates influence gene expression. mRNA stability influences gene expression in virtually all organisms, from bacteria to mammals, and the abundance of a particular mRNA can fluctuate manyfold following a change in the mRNA half-life, without any change in transcription. The processes that regulate mRNA half-lives can, in turn, affect how cells grow, differentiate, and respond to their environment. Three major questions are addressed. Which sequences in mRNAs determine their half-lives? Which enzymes degrade mRNAs? Which (trans-acting) factors regulate mRNA stability, and how do they function? The following specific topics are discussed: techniques for measuring eukaryotic mRNA stability and for calculating decay constants, mRNA decay pathways, mRNases, proteins that bind to sequences shared among many mRNAs [like poly(A)- and AU-rich-binding proteins] and proteins that bind to specific mRNAs (like the c-myc coding-region determinant-binding protein), how environmental factors like hormones and growth factors affect mRNA stability, and how translation and mRNA stability are linked. Some perspectives and predictions for future research directions are summarized at the end. PMID:7565413

Predicting the short-term risk of diabetes in HIV-positive patients: the Data Collection on Adverse Events of Anti-HIV Drugs (D:A:D) study

PubMed Central

Petoumenos, Kathy; Worm, Signe W; Fontas, Eric; Weber, Rainer; De Wit, Stephane; Bruyand, Mathias; Reiss, Peter; El-Sadr, Wafaa; Monforte, Antonella D'Arminio; Friis-Møller, Nina; Lundgren, Jens D; Law, Matthew G

2012-01-01

Introduction HIV-positive patients receiving combination antiretroviral therapy (cART) frequently experience metabolic complications such as dyslipidemia and insulin resistance, as well as lipodystrophy, increasing the risk of cardiovascular disease (CVD) and diabetes mellitus (DM). Rates of DM and other glucose-associated disorders among HIV-positive patients have been reported to range between 2 and 14%, and in an ageing HIV-positive population, the prevalence of DM is expected to continue to increase. This study aims to develop a model to predict the short-term (six-month) risk of DM in HIV-positive populations and to compare the existing models developed in the general population. Methods All patients recruited to the Data Collection on Adverse events of Anti-HIV Drugs (D:A:D) study with follow-up data, without prior DM, myocardial infarction or other CVD events and with a complete DM risk factor profile were included. Conventional risk factors identified in the general population as well as key HIV-related factors were assessed using Poisson-regression methods. Expected probabilities of DM events were also determined based on the Framingham Offspring Study DM equation. The D:A:D and Framingham equations were then assessed using an internal-external validation process; area under the receiver operating characteristic (AUROC) curve and predicted DM events were determined. Results Of 33,308 patients, 16,632 (50%) patients were included, with 376 cases of new onset DM during 89,469 person-years (PY). Factors predictive of DM included higher glucose, body mass index (BMI) and triglyceride levels, and older age. Among HIV-related factors, recent CD4 counts of<200 cells/µL and lipodystrophy were predictive of new onset DM. The mean performance of the D:A:D and Framingham equations yielded AUROC of 0.894 (95% CI: 0.849, 0.940) and 0.877 (95% CI: 0.823, 0.932), respectively. The Framingham equation over-predicted DM events compared to D:A:D for lower glucose and lower triglycerides, and for BMI levels below 25 kg/m2. Conclusions The D:A:D equation performed well in predicting the short-term onset of DM in the validation dataset and for specific subgroups provided better estimates of DM risk than the Framingham. PMID:23078769

Extremely preterm birth affects boys more and socio-economic and neonatal variables pose sex-specific risks.

PubMed

Månsson, Johanna; Fellman, Vineta; Stjernqvist, Karin

2015-05-01

The early identification of at-risk extremely preterm (EPT) children could improve long-term outcomes. This study sought to investigate sex differences in developmental outcomes and to identify sex-specific predictors at two and a half years of age. We assessed 217 boys and 181 girls born before 27-week gestation using the Bayley Scales of Infant and Toddler Development, third edition (Bayley-III), as a part of the Extremely Preterm Infants in Sweden Study. Sex-specific differences were calculated. Socio-economic, birth and neonatal factors were calculated separately for boys and girls using regression models. Girls scored significantly higher than boys on all Bayley-III indices. In both sexes, brain injury, long-term ventilator treatment and foreign-born mothers predicted lower scores. Receiving breast milk by hospital discharge predicted higher scores. Severe retinopathy of prematurity was the strongest predictor of cognitive and language deficits in boys. High parental education predicted higher cognitive and language scores in girls, whereas severe bronchopulmonary dysplasia was the strongest predictor of motor deficits. Extreme prematurity seems to affect boys more than girls. Socio-economic and neonatal factors confer similar risks or protections on both sexes, but some variables pose sex-specific risks. An awareness of risk factors may provide the basis for treatment and follow-up guidelines. ©2015 Foundation Acta Paediatrica. Published by John Wiley & Sons Ltd.

Dynamic Simulation and Static Matching for Action Prediction: Evidence from Body Part Priming

ERIC Educational Resources Information Center

Springer, Anne; Brandstadter, Simone; Prinz, Wolfgang

2013-01-01

Accurately predicting other people's actions may involve two processes: internal real-time simulation (dynamic updating) and matching recently perceived action images (static matching). Using a priming of body parts, this study aimed to differentiate the two processes. Specifically, participants played a motion-controlled video game with…

Neurobiological factors as predictors of cognitive-behavioral therapy outcome in individuals with antisocial behavior: a review of the literature.

PubMed

Cornet, Liza J M; de Kogel, Catharina H; Nijman, Henk L I; Raine, Adrian; van der Laan, Peter H

2014-11-01

This review focuses on the predictive value of neurobiological factors in relation to cognitive-behavioral therapy outcome among individuals with antisocial behavior. Ten relevant studies were found. Although the literature on this topic is scarce and diverse, it appears that specific neurobiological characteristics, such as physiological arousal levels, can predict treatment outcome. The predictive value of neurobiological factors is important as it could give more insight into the causes of variability in treatment outcome among individuals with antisocial behavior. Furthermore, results can contribute to improvement in current treatment selection procedures and to the development of alternative treatment options. © The Author(s) 2013.

Identification of regulatory targets of tissue-specific transcription factors: application to retina-specific gene regulation

PubMed Central

Qian, Jiang; Esumi, Noriko; Chen, Yangjian; Wang, Qingliang; Chowers, Itay; Zack, Donald J.

2005-01-01

Identification of tissue-specific gene regulatory networks can yield insights into the molecular basis of a tissue's development, function and pathology. Here, we present a computational approach designed to identify potential regulatory target genes of photoreceptor cell-specific transcription factors (TFs). The approach is based on the hypothesis that genes related to the retina in terms of expression, disease and/or function are more likely to be the targets of retina-specific TFs than other genes. A list of genes that are preferentially expressed in retina was obtained by integrating expressed sequence tag, SAGE and microarray datasets. The regulatory targets of retina-specific TFs are enriched in this set of retina-related genes. A Bayesian approach was employed to integrate information about binding site location relative to a gene's transcription start site. Our method was applied to three retina-specific TFs, CRX, NRL and NR2E3, and a number of potential targets were predicted. To experimentally assess the validity of the bioinformatic predictions, mobility shift, transient transfection and chromatin immunoprecipitation assays were performed with five predicted CRX targets, and the results were suggestive of CRX regulation in 5/5, 3/5 and 4/5 cases, respectively. Together, these experiments strongly suggest that RP1, GUCY2D, ABCA4 are novel targets of CRX. PMID:15967807

A method for grounding grid corrosion rate prediction

NASA Astrophysics Data System (ADS)

Han, Juan; Du, Jingyi

2017-06-01

Involved in a variety of factors, prediction of grounding grid corrosion complex, and uncertainty in the acquisition process, we propose a combination of EAHP (extended AHP) and fuzzy nearness degree of effective grounding grid corrosion rate prediction model. EAHP is used to establish judgment matrix and calculate the weight of each factors corrosion of grounding grid; different sample classification properties have different corrosion rate of contribution, and combining the principle of close to predict corrosion rate.The application result shows, the model can better capture data variation, thus to improve the validity of the model to get higher prediction precision.

Wafer hot spot identification through advanced photomask characterization techniques: part 2

NASA Astrophysics Data System (ADS)

Choi, Yohan; Green, Michael; Cho, Young; Ham, Young; Lin, Howard; Lan, Andy; Yang, Richer; Lung, Mike

2017-03-01

Historically, 1D metrics such as Mean to Target (MTT) and CD Uniformity (CDU) have been adequate for mask end users to evaluate and predict the mask impact on the wafer process. However, the wafer lithographer's process margin is shrinking at advanced nodes to a point that classical mask CD metrics are no longer adequate to gauge the mask contribution to wafer process error. For example, wafer CDU error at advanced nodes is impacted by mask factors such as 3-dimensional (3D) effects and mask pattern fidelity on sub-resolution assist features (SRAFs) used in Optical Proximity Correction (OPC) models of ever-increasing complexity. To overcome the limitation of 1D metrics, there are numerous on-going industry efforts to better define wafer-predictive metrics through both standard mask metrology and aerial CD methods. Even with these improvements, the industry continues to struggle to define useful correlative metrics that link the mask to final device performance. In part 1 of this work, we utilized advanced mask pattern characterization techniques to extract potential hot spots on the mask and link them, theoretically, to issues with final wafer performance. In this paper, part 2, we complete the work by verifying these techniques at wafer level. The test vehicle (TV) that was used for hot spot detection on the mask in part 1 will be used to expose wafers. The results will be used to verify the mask-level predictions. Finally, wafer performance with predicted and verified mask/wafer condition will be shown as the result of advanced mask characterization. The goal is to maximize mask end user yield through mask-wafer technology harmonization. This harmonization will provide the necessary feedback to determine optimum design, mask specifications, and mask-making conditions for optimal wafer process margin.

Carving Executive Control At Its Joints: Working Memory Capacity Predicts Stimulus-Stimulus, But Not Stimulus-Response, Conflict

PubMed Central

Meier, Matt E.; Kane, Michael J.

2015-01-01

Three experiments examined the relation between working memory capacity (WMC) and two different forms of cognitive conflict: stimulus-stimulus (S-S) and stimulus-response (SR) interference. Our goal was to test whether WMC’s relation to conflict-task performance is mediated by stimulus-identification processes (captured by S-S conflict), response-selection processes (captured by S-R conflict), or both. In Experiment 1, subjects completed a single task presenting both S-S and S-R conflict trials, plus trials that combined the two conflict types. We limited ostensible goal-maintenance contributions to performance by requiring the same goal for all trial types and by presenting frequent conflict trials that reinforced the goal. WMC predicted resolution of S-S conflict as expected: Higher-WMC subjects showed reduced response time interference. Although WMC also predicted S-R interference, here, higher-WMC subjects showed increased error interference. Experiment 2A replicated these results in a version of the conflict task without combined S-S/S-R trials. Experiment 2B increased the proportion of congruent (non-conflict) trials to promote reliance on goal-maintenance processes. Here, higher-WMC subjects resolved both S-S and S-R conflict more successfully than did lower-WMC subjects. The results were consistent with Kane and Engle’s (2003) two-factor theory of cognitive control, according to which WMC predicts executive-task performance through goal-maintenance and conflict-resolution processes. However, the present results add specificity to the account by suggesting that higher-WMC subjects better resolve cognitive conflict because they more efficiently select relevant stimulus features against irrelevant, distracting ones. PMID:26120774

Carving executive control at its joints: Working memory capacity predicts stimulus-stimulus, but not stimulus-response, conflict.

PubMed

Meier, Matt E; Kane, Michael J

2015-11-01

Three experiments examined the relation between working memory capacity (WMC) and 2 different forms of cognitive conflict: stimulus-stimulus (S-S) and stimulus-response (S-R) interference. Our goal was to test whether WMC's relation to conflict-task performance is mediated by stimulus-identification processes (captured by S-S conflict), response-selection processes (captured by S-R conflict), or both. In Experiment 1, subjects completed a single task presenting both S-S and S-R conflict trials, plus trials that combined the 2 conflict types. We limited ostensible goal-maintenance contributions to performance by requiring the same goal for all trial types and by presenting frequent conflict trials that reinforced the goal. WMC predicted resolution of S-S conflict as expected: Higher WMC subjects showed reduced response time interference. Although WMC also predicted S-R interference, here, higher WMC subjects showed increased error interference. Experiment 2A replicated these results in a version of the conflict task without combined S-S/S-R trials. Experiment 2B increased the proportion of congruent (nonconflict) trials to promote reliance on goal-maintenance processes. Here, higher WMC subjects resolved both S-S and S-R conflict more successfully than did lower WMC subjects. The results were consistent with Kane and Engle's (2003) 2-factor theory of cognitive control, according to which WMC predicts executive-task performance through goal-maintenance and conflict-resolution processes. However, the present results add specificity to the account by suggesting that higher WMC subjects better resolve cognitive conflict because they more efficiently select relevant stimulus features against irrelevant, distracting ones. (c) 2015 APA, all rights reserved).

Choosing the Right Systems Integration

NASA Astrophysics Data System (ADS)

Péči, Matúš; Važan, Pavel

2014-12-01

The paper examines systems integration and its main levels at higher levels of control. At present, the systems integration is one of the main aspects participating in the consolidation processes and financial flows of a company. Systems Integration is a complicated emotionconsuming process and it is often a problem to choose the right approach and level of integration. The research focused on four levels of integration, while each of them is characterized by specific conditions. At each level, there is a summary of recommendations and practical experience. The paper also discusses systems integration between the information and MES levels. The main part includes user-level integration where we describe an example of such integration. Finally, we list recommendations and also possible predictions of the systems integration as one of the important factors in the future.

Generalized and event-specific hopelessness: salvaging the mediation hypothesis of the hopelessness theory.

PubMed

Lynd-Stevenson, R M

1997-02-01

Present research provides little support for the prediction central to hopelessness theory that hopelessness mediates the full relationship between vulnerability factors (e.g. stressful life-events, attributional style) and depression. Indeed, contrary to hopelessness theory, an accumulating body of research indicates that hopelessness moderates the relationship between vulnerability factors and depression. The proposal in the present study was that the type of hopelessness typically measured in the research literature has trait-like characteristics and cannot be used to test the mediation hypothesis. The prediction was that hopelessness would operate as a mediator and not a moderator if items in a measure of generalized hopelessness were reworded to measure event-specific hopelessness. A sample of 153 unemployed people completed measures of attributional style for positive and negative outcomes, stress associated with being unemployed, job hopelessness, and depressive symptoms. The results supported the hypothesis that event-specific hopelessness mediates, but does not moderate, the relationship between vulnerability factors and depression. Implications for hopelessness theory and future research are discussed.

Treatment-Related Predictive and Prognostic Factors in Trimodality Approach in Stage IIIA/N2 Non-Small Cell Lung Cancer.

PubMed

Jeremić, Branislav; Casas, Francesc; Dubinsky, Pavol; Gomez-Caamano, Antonio; Čihorić, Nikola; Videtic, Gregory; Igrutinovic, Ivan

2018-01-01

While there are no established pretreatment predictive and prognostic factors in patients with stage IIIA/pN2 non-small cell lung cancer (NSCLC) indicating a benefit to surgery as a part of trimodality approach, little is known about treatment-related predictive and prognostic factors in this setting. A literature search was conducted to identify possible treatment-related predictive and prognostic factors for patients for whom trimodality approach was reported on. Overall survival was the primary endpoint of this study. Of 30 identified studies, there were two phase II studies, 5 "prospective" studies, and 23 retrospective studies. No study was found which specifically looked at treatment-related predictive factors of improved outcomes in trimodality treatment. Of potential treatment-related prognostic factors, the least frequently analyzed factors among 30 available studies were overall pathologic stage after preoperative treatment and UICC downstaging. Evaluation of treatment response before surgery and by pathologic tumor stage after induction therapy were analyzed in slightly more than 40% of studies and found not to influence survival. More frequently studied factors-resection status, degree of tumor regression, and pathologic nodal stage after induction therapy as well as the most frequently studied factor, the treatment (in almost 75% studies)-showed no discernible impact on survival, due to conflicting results. Currently, it is impossible to identify any treatment-related predictive or prognostic factors for selecting surgery in the treatment of patients with stage IIIA/pN2 NSCLC.

Utilization of the NSQIP-Pediatric Database in Development and Validation of a New Predictive Model of Pediatric Postoperative Wound Complications.

PubMed

Maizlin, Ilan I; Redden, David T; Beierle, Elizabeth A; Chen, Mike K; Russell, Robert T

2017-04-01

Surgical wound classification, introduced in 1964, stratifies the risk of surgical site infection (SSI) based on a clinical estimate of the inoculum of bacteria encountered during the procedure. Recent literature has questioned the accuracy of predicting SSI risk based on wound classification. We hypothesized that a more specific model founded on specific patient and perioperative factors would more accurately predict the risk of SSI. Using all observations from the 2012 to 2014 pediatric National Surgical Quality Improvement Program-Pediatric (NSQIP-P) Participant Use File, patients were randomized into model creation and model validation datasets. Potential perioperative predictive factors were assessed with univariate analysis for each of 4 outcomes: wound dehiscence, superficial wound infection, deep wound infection, and organ space infection. A multiple logistic regression model with a step-wise backwards elimination was performed. A receiver operating characteristic curve with c-statistic was generated to assess the model discrimination for each outcome. A total of 183,233 patients were included. All perioperative NSQIP factors were evaluated for clinical pertinence. Of the original 43 perioperative predictive factors selected, 6 to 9 predictors for each outcome were significantly associated with postoperative SSI. The predictive accuracy level of our model compared favorably with the traditional wound classification in each outcome of interest. The proposed model from NSQIP-P demonstrated a significantly improved predictive ability for postoperative SSIs than the current wound classification system. This model will allow providers to more effectively counsel families and patients of these risks, and more accurately reflect true risks for individual surgical patients to hospitals and payers. Copyright © 2017 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

Integrating cognitive and peripheral factors in predicting hearing-aid processing effectiveness

PubMed Central

Kates, James M.; Arehart, Kathryn H.; Souza, Pamela E.

2013-01-01

Individual factors beyond the audiogram, such as age and cognitive abilities, can influence speech intelligibility and speech quality judgments. This paper develops a neural network framework for combining multiple subject factors into a single model that predicts speech intelligibility and quality for a nonlinear hearing-aid processing strategy. The nonlinear processing approach used in the paper is frequency compression, which is intended to improve the audibility of high-frequency speech sounds by shifting them to lower frequency regions where listeners with high-frequency loss have better hearing thresholds. An ensemble averaging approach is used for the neural network to avoid the problems associated with overfitting. Models are developed for two subject groups, one having nearly normal hearing and the other mild-to-moderate sloping losses. PMID:25669257

Validity of Teacher-Based Vision Screening and Factors Associated with the Accuracy of Vision Screening in Vietnamese Children.

PubMed

Paudel, Prakash; Kovai, Vilas; Naduvilath, Thomas; Phuong, Ha Thanh; Ho, Suit May; Giap, Nguyen Viet

2016-01-01

To assess validity of teacher-based vision screening and elicit factors associated with accuracy of vision screening in Vietnam. After brief training, teachers independently measured visual acuity (VA) in 555 children aged 12-15 years in Ba Ria - Vung Tau Province. Teacher VA measurements were compared to those of refractionists. Sensitivity, specificity, positive predictive value and negative predictive value were calculated for uncorrected VA (UVA) and presenting VA (PVA) 20/40 or worse in either eye. Chi-square, Fisher's exact test and multivariate logistic regression were used to assess factors associated with accuracy of vision screening. Level of significance was set at 5%. Trained teachers in Vietnam demonstrated 86.7% sensitivity, 95.7% specificity, 86.7% positive predictive value and 95.7% negative predictive value in identifying children with visual impairment using the UVA measurement. PVA measurement revealed low accuracy for teachers, which was significantly associated with child's age, sex, spectacle wear and myopic status, but UVA measurement showed no such associations. Better accuracy was achieved in measurement of VA and identification of children with visual impairment using UVA measurement compared to PVA. UVA measurement is recommended for teacher-based vision screening programs.

Identifying Factors that Most Strongly Predict Aircraft Reliability Behavior

DTIC Science & Technology

2013-06-01

time to perform a specific airlift mission or category of missions based on all pertinent operational and logistical factors.” ( Randall , 2004, p. 64...resources are contingent upon the demand and airfield environment. ( Randall , 2004) The challenge with researching and predicting MC rates is its...Departmental Publishing Office. http://www.e- publishing.af.mil/shared/media/epubs/AFDD3-17.pdf McClave JT, Benson PG, Sincich TS, (2011). Statistics for

Robust functional regression model for marginal mean and subject-specific inferences.

PubMed

Cao, Chunzheng; Shi, Jian Qing; Lee, Youngjo

2017-01-01

We introduce flexible robust functional regression models, using various heavy-tailed processes, including a Student t-process. We propose efficient algorithms in estimating parameters for the marginal mean inferences and in predicting conditional means as well as interpolation and extrapolation for the subject-specific inferences. We develop bootstrap prediction intervals (PIs) for conditional mean curves. Numerical studies show that the proposed model provides a robust approach against data contamination or distribution misspecification, and the proposed PIs maintain the nominal confidence levels. A real data application is presented as an illustrative example.

Individual differences in emotion word processing: A diffusion model analysis.

PubMed

Mueller, Christina J; Kuchinke, Lars

2016-06-01

The exploratory study investigated individual differences in implicit processing of emotional words in a lexical decision task. A processing advantage for positive words was observed, and differences between happy and fear-related words in response times were predicted by individual differences in specific variables of emotion processing: Whereas more pronounced goal-directed behavior was related to a specific slowdown in processing of fear-related words, the rate of spontaneous eye blinks (indexing brain dopamine levels) was associated with a processing advantage of happy words. Estimating diffusion model parameters revealed that the drift rate (rate of information accumulation) captures unique variance of processing differences between happy and fear-related words, with highest drift rates observed for happy words. Overall emotion recognition ability predicted individual differences in drift rates between happy and fear-related words. The findings emphasize that a significant amount of variance in emotion processing is explained by individual differences in behavioral data.

Differential Risk Factors for HIV Drug and Sex Risk-Taking Among Non-treatment-seeking Hospitalized Injection Drug Users

PubMed Central

Crooks, Denise; Tsui, Judith; Anderson, Bradley; Dossabhoy, Shernaz; Herman, Debra; Liebschutz, Jane M.; Stein, Michael D.

2016-01-01

Injection drug users (IDUs) are at increased risk of contracting HIV. From a clinical trial assessing an intervention to enhance the linkage of hospitalized patients to opioid treatment after discharge, we conducted multivariate analysis of baseline data from hospitalized IDUs with a history of opioid dependence (n = 104) to identify differences in factors predicting HIV drug and sex risk behaviors. Factors significantly associated with HIV drug risk were being non-Hispanic Caucasian and recent cocaine use. Being female, binge drinking, and poorer mental health were significantly associated with higher sex risk. Because factors predicting HIV sex risk behaviors differ from those predicting HIV drug risk, interventions aimed at specific HIV risks should have different behavioral and substance use targets. PMID:25063229

Modelling the molecular mechanisms of aging

PubMed Central

Mc Auley, Mark T.; Guimera, Alvaro Martinez; Hodgson, David; Mcdonald, Neil; Mooney, Kathleen M.; Morgan, Amy E.

2017-01-01

The aging process is driven at the cellular level by random molecular damage that slowly accumulates with age. Although cells possess mechanisms to repair or remove damage, they are not 100% efficient and their efficiency declines with age. There are many molecular mechanisms involved and exogenous factors such as stress also contribute to the aging process. The complexity of the aging process has stimulated the use of computational modelling in order to increase our understanding of the system, test hypotheses and make testable predictions. As many different mechanisms are involved, a wide range of models have been developed. This paper gives an overview of the types of models that have been developed, the range of tools used, modelling standards and discusses many specific examples of models that have been grouped according to the main mechanisms that they address. We conclude by discussing the opportunities and challenges for future modelling in this field. PMID:28096317

Pedestrians' intention to jaywalk: Automatic or planned? A study based on a dual-process model in China.

PubMed

Xu, Yaoshan; Li, Yongjuan; Zhang, Feng

2013-01-01

The present study investigates the determining factors of Chinese pedestrians' intention to violate traffic laws using a dual-process model. This model divides the cognitive processes of intention formation into controlled analytical processes and automatic associative processes. Specifically, the process explained by the augmented theory of planned behavior (TPB) is controlled, whereas the process based on past behavior is automatic. The results of a survey conducted on 323 adult pedestrian respondents showed that the two added TPB variables had different effects on the intention to violate, i.e., personal norms were significantly related to traffic violation intention, whereas descriptive norms were non-significant predictors. Past behavior significantly but uniquely predicted the intention to violate: the results of the relative weight analysis indicated that the largest percentage of variance in pedestrians' intention to violate was explained by past behavior (42%). According to the dual-process model, therefore, pedestrians' intention formation relies more on habit than on cognitive TPB components and social norms. The implications of these findings for the development of intervention programs are discussed. Copyright © 2012 Elsevier Ltd. All rights reserved.

Lymphopenia predicts poor prognosis in patients with esophageal squamous cell carcinoma.

PubMed

Feng, Ji-Feng; Liu, Jin-Shi; Huang, Ying

2014-12-01

Lymphopenia is a useful predictive factor in several cancers. The aim of this study was to determine the prognostic value of lymphopenia in patients with esophageal squamous cell carcinoma (ESCC).A retrospective analysis of 307 consecutive patients who had undergone esophagectomy for ESCC was conducted. In our study, a lymphocyte count (LC) of fewer than 1.0 Giga/L was defined as lymphopenia. Kaplan-Meier method was used to calculate the cancer-specific survival (CSS). Cox regression analyses were performed to evaluate the prognostic factors. Receiver operating characteristic (ROC) curve was also plotted to verify the accuracy of LC for CSS prediction.The mean LC was 1.55 ± 0.64 Giga/L (range 0.4-3.7 Giga/L). The incidence of lymphopenia (LC < 1.0 Giga/L) was 16.6% (51/307). Patients with lymphopenia (LC < 1.0 Giga/L) had a significantly shorter 5-year CSS (21.6% vs 43.8%, P = 0.004). On multivariate analysis, lymphopenia (LC < 1.0 Giga/L) was an independent prognostic factor in patients with ESCC (P = 0.013). Lymphopenia had a hazard ratio (HR) of 1.579 [95% confidence interval (CI): 1.100-2.265] for CSS. ROC curve demonstrated that lymphopenia (LC < 1.0 Giga/L) predicts survival with a sensitivity of 86.2% and a specificity of 27.2%. Lymphopenia (LC < 1.0 Giga/L) is still an independent predictive factor for long-term survival in patients with ESCC.

Academic success across the transition from primary to secondary schooling among lower-income adolescents: understanding the effects of family resources and gender.

PubMed

Serbin, Lisa A; Stack, Dale M; Kingdon, Danielle

2013-09-01

Successful academic performance during adolescence is a key predictor of lifetime achievement, including occupational and social success. The present study investigated the important transition from primary to secondary schooling during early adolescence, when academic performance among youth often declines. The goal of the study was to understand how risk factors, specifically lower family resources and male gender, threaten academic success following this "critical transition" in schooling. The study involved a longitudinal examination of the predictors of academic performance in grades 7-8 among 127 (56 % girls) French-speaking Quebec (Canada) adolescents from lower-income backgrounds. As hypothesized based on transition theory, hierarchical regression analyses showed that supportive parenting and specific academic, social and behavioral competencies (including spelling ability, social skills, and lower levels of attention problems) predicted success across this transition among at-risk youth. Multiple-mediation procedures demonstrated that the set of compensatory factors fully mediated the negative impact of lower family resources on academic success in grades 7-8. Unique mediators (social skills, spelling ability, supportive parenting) also were identified. In addition, the "gender gap" in performance across the transition could be attributed statistically to differences between boys and girls in specific competencies observed prior to the transition, as well as differential parenting (i.e., support from mother) towards girls and boys. The present results contribute to our understanding of the processes by which established risk factors, such as low family income and gender impact development and academic performance during early adolescence. These "transitional" processes and subsequent academic performance may have consequences across adolescence and beyond, with an impact on lifetime patterns of achievement and occupational success.

Heat Transfer during Blanching and Hydrocooling of Broccoli Florets.

PubMed

Iribe-Salazar, Rosalina; Caro-Corrales, José; Hernández-Calderón, Óscar; Zazueta-Niebla, Jorge; Gutiérrez-Dorado, Roberto; Carrazco-Escalante, Marco; Vázquez-López, Yessica

2015-12-01

The objective of this work was to simulate heat transfer during blanching (90 °C) and hydrocooling (5 °C) of broccoli florets (Brassica oleracea L. Italica) and to evaluate the impact of these processes on the physicochemical and nutrimental quality properties. Thermophysical properties (thermal conductivity [line heat source], specific heat capacity [differential scanning calorimetry], and bulk density [volume displacement]) of stem and inflorescence were measured as a function of temperature (5, 10, 20, 40, 60, and 80 °C). The activation energy and the frequency factor (Arrhenius model) of these thermophysical properties were calculated. A 3-dimensional finite element model was developed to predict the temperature history at different points inside the product. Comparison of the theoretical and experimental temperature histories was carried out. Quality parameters (firmness, total color difference, and vitamin C content) and peroxidase activity were measured. The satisfactory validation of the finite element model allows the prediction of temperature histories and profiles under different process conditions, which could lead to an eventual optimization aimed to minimize the nutritional and sensorial losses in broccoli florets. © 2015 Institute of Food Technologists®

Measures of Microbial Biomass for Soil Carbon Decomposition Models

NASA Astrophysics Data System (ADS)

Mayes, M. A.; Dabbs, J.; Steinweg, J. M.; Schadt, C. W.; Kluber, L. A.; Wang, G.; Jagadamma, S.

2014-12-01

Explicit parameterization of the decomposition of plant inputs and soil organic matter by microbes is becoming more widely accepted in models of various complexity, ranging from detailed process models to global-scale earth system models. While there are multiple ways to measure microbial biomass, chloroform fumigation-extraction (CFE) is commonly used to parameterize models.. However CFE is labor- and time-intensive, requires toxic chemicals, and it provides no specific information about the composition or function of the microbial community. We investigated correlations between measures of: CFE; DNA extraction yield; QPCR base-gene copy numbers for Bacteria, Fungi and Archaea; phospholipid fatty acid analysis; and direct cell counts to determine the potential for use as proxies for microbial biomass. As our ultimate goal is to develop a reliable, more informative, and faster methods to predict microbial biomass for use in models, we also examined basic soil physiochemical characteristics including texture, organic matter content, pH, etc. to identify multi-factor predictive correlations with one or more measures of the microbial community. Our work will have application to both microbial ecology studies and the next generation of process and earth system models.

Cold air investigation of 4 1/2-stage turbine with stage loading factor of 4.66 and high specific work output. 1: Overall performance

NASA Technical Reports Server (NTRS)

Whitney, W. J.; Behning, F. P.; Moffitt, T. P.; Hotz, G. M.

1977-01-01

The turbine developed design specific work output at design speed at a total pressure ratio of 6.745 with a corresponding efficiency of 0.855. The efficiency (0.855)was 3.1 points lower than the estimated efficiency quoted by the contractor in the design report and 0.7 of a point lower than that determined by a reference prediction method. The performance of the turbine, which was a forced vortex design, agreed with the performance determined by the prediction method to about the same extent as did the performance of three reference high stage loading factor turbines, which were free vortex designs.

In silico analysis of stomach lineage specific gene set expression pattern in gastric cancer.

PubMed

Pandi, Narayanan Sathiya; Suganya, Sivagurunathan; Rajendran, Suriliyandi

2013-10-04

Stomach lineage specific gene products act as a protective barrier in the normal stomach and their expression maintains the normal physiological processes, cellular integrity and morphology of the gastric wall. However, the regulation of stomach lineage specific genes in gastric cancer (GC) is far less clear. In the present study, we sought to investigate the role and regulation of stomach lineage specific gene set (SLSGS) in GC. SLSGS was identified by comparing the mRNA expression profiles of normal stomach tissue with other organ tissue. The obtained SLSGS was found to be under expressed in gastric tumors. Functional annotation analysis revealed that the SLSGS was enriched for digestive function and gastric epithelial maintenance. Employing a single sample prediction method across GC mRNA expression profiles identified the under expression of SLSGS in proliferative type and invasive type gastric tumors compared to the metabolic type gastric tumors. Integrative pathway activation prediction analysis revealed a close association between estrogen-α signaling and SLSGS expression pattern in GC. Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. In conclusion, our results highlight that estrogen mediated regulation of SLSGS in gastric tumor is a molecular predictor of metabolic type GC and prognostic factor in GC. Copyright © 2013 Elsevier Inc. All rights reserved.

Brief Self-Efficacy Scales for use in Weight-Loss Trials: Preliminary Evidence of Validity

PubMed Central

Wilson, Kathryn E.; Harden, Samantha M.; Almeida, Fabio A.; You, Wen; Hill, Jennie L.; Goessl, Cody; Estabrooks, Paul A.

2015-01-01

Self-efficacy is a commonly included cognitive variable in weight-loss trials, but there is little uniformity in its measurement. Weight-loss trials frequently focus on physical activity (PA) and eating behavior, as well as weight loss, but no survey is available that offers reliable measurement of self-efficacy as it relates to each of these targeted outcomes. The purpose of this study was to test the psychometric properties of brief, pragmatic self-efficacy scales specific to PA, healthful eating and weight-loss (4 items each). An adult sample (n=1790) from 28 worksites enrolled in a worksite weight-loss program completed the self-efficacy scale, as well as measures of PA, dietary fat intake, and weight, at baseline, 6-, and 12-months. The hypothesized factor structure was tested through confirmatory factor analysis, which supported the expected factor structure for three latent self-efficacy factors, specific to PA, healthful eating, and weight-loss. Measurement equivalence/invariance between relevant demographic groups, and over time was also supported. Parallel growth processes in self-efficacy factors and outcomes (PA, fat intake, and weight) support the predictive validity of score interpretations. Overall, this initial series of psychometric analyses supports the interpretation that scores on these scales reflect self-efficacy for PA, healthful eating, and weight-loss. The use of this instrument in large-scale weight-loss trials is encouraged. PMID:26619093

Fixed and dynamic predictors of treatment process in therapeutic communities for substance abusers in Belgium.

PubMed

Goethals, Ilse; Vanderplasschen, Wouter; Vandevelde, Stijn; Broekaert, Eric

2012-10-11

Research on substance abuse treatment services in general reflects substantial attention to the notion of treatment process. Despite the growing popularity of process studies, only a few researchers have used instruments specifically tailored to measure the therapeutic community (TC) treatment process, and even fewer have investigated client attributes in relation to early TC treatment process experiences. The aim of the current study is to address this gap by exploring clients' early in-treatment experiences and to determine the predictors that are related to the treatment process, using a TC-specific multidimensional instrument. Data was gathered among 157 adults in five TCs in Flanders (Belgium). Descriptive statistics were used to explore clients' early in-treatment experiences and multiple linear regressions were conducted to determine the fixed and dynamic predictors of Community Environment and Personal Development and Change (two indicators of TC treatment process). Clients reveal a more positive first-month response to TC social processes than to personal-development processes that require self-reflection and insight. The variance in clients' ratings of Community Environment was primarily due to dynamic client factors, while the variance in clients' ratings of Personal Development and Change was only related to fixed client factors. Suitability for treatment was the strongest predictor of Community Environment ratings, whereas a judicial referral more strongly predicted Personal Development and Change scores. Special attention should be devoted to suitability for treatment as part of motivational assessment as this seems to be a very strong predictor of how clients react to the initiation stage of TC treatment. To help improve clients' (meta-)cognitive skills needed to achieve insight and self-reflection and perhaps speed up the process of recovery, the authors suggest the introduction of (meta-)cognitive training strategies in the pre-program and/or the induction stage of a TC program.

Young adults' internet addiction: Prediction by the interaction of parental marital conflict and respiratory sinus arrhythmia.

PubMed

Zhang, Hui; Spinrad, Tracy L; Eisenberg, Nancy; Luo, Yun; Wang, Zhenhong

2017-10-01

The aim of the current study was to address the potential moderating roles of respiratory sinus arrhythmia (RSA; baseline and suppression) and participant sex in the relation between parents' marital conflict and young adults' internet addiction. Participants included 105 (65 men) Chinese young adults who reported on their internet addiction and their parents' marital conflict. Marital conflict interacted with RSA suppression to predict internet addiction. Specifically, high RSA suppression was associated with low internet addiction, regardless of parental marital conflict; however, for participants with low RSA suppression, a positive relation between marital conflict and internet addiction was found. Internet addiction also was predicted by a significant three-way interaction among baseline RSA, marital conflict, and participant sex. Specifically, for men, marital conflict positively predicted internet addiction under conditions of low (but not high) baseline RSA. For women, marital conflict positively predicted internet addiction under conditions of high (but not low) baseline RSA. Findings highlight the importance of simultaneous consideration of physiological factors, in conjunction with family factors, in the prediction of young adults' internet addiction. Copyright © 2017 Elsevier B.V. All rights reserved.

Leveraging Call Center Logs for Customer Behavior Prediction

NASA Astrophysics Data System (ADS)

Parvathy, Anju G.; Vasudevan, Bintu G.; Kumar, Abhishek; Balakrishnan, Rajesh

Most major businesses use business process outsourcing for performing a process or a part of a process including financial services like mortgage processing, loan origination, finance and accounting and transaction processing. Call centers are used for the purpose of receiving and transmitting a large volume of requests through outbound and inbound calls to customers on behalf of a business. In this paper we deal specifically with the call centers notes from banks. Banks as financial institutions provide loans to non-financial businesses and individuals. Their call centers act as the nuclei of their client service operations and log the transactions between the customer and the bank. This crucial conversation or information can be exploited for predicting a customer’s behavior which will in turn help these businesses to decide on the next action to be taken. Thus the banks save considerable time and effort in tracking delinquent customers to ensure minimum subsequent defaulters. Majority of the time the call center notes are very concise and brief and often the notes are misspelled and use many domain specific acronyms. In this paper we introduce a novel domain specific spelling correction algorithm which corrects the misspelled words in the call center logs to meaningful ones. We also discuss a procedure that builds the behavioral history sequences for the customers by categorizing the logs into one of the predefined behavioral states. We then describe a pattern based predictive algorithm that uses temporal behavioral patterns mined from these sequences to predict the customer’s next behavioral state.

Methods for Improving Information from ’Undesigned’ Human Factors Experiments.

DTIC Science & Technology

Human factors engineering, Information processing, Regression analysis , Experimental design, Least squares method, Analysis of variance, Correlation techniques, Matrices(Mathematics), Multiple disciplines, Mathematical prediction

Value of the CHA2DS2-VASc score and Fabry-specific score for predicting new-onset or recurrent stroke/TIA in Fabry disease patients without atrial fibrillation.

PubMed

Liu, Dan; Hu, Kai; Schmidt, Marie; Müntze, Jonas; Maniuc, Octavian; Gensler, Daniel; Oder, Daniel; Salinger, Tim; Weidemann, Frank; Ertl, Georg; Frantz, Stefan; Wanner, Christoph; Nordbeck, Peter

2018-05-24

To evaluate potential risk factors for stroke or transient ischemic attacks (TIA) and to test the feasibility and efficacy of a Fabry-specific stroke risk score in Fabry disease (FD) patients without atrial fibrillation (AF). FD patients often experience cerebrovascular events (stroke/TIA) at young age. 159 genetically confirmed FD patients without AF (aged 40 ± 14 years, 42.1% male) were included, and risk factors for stroke/TIA events were determined. All patients were followed up over a median period of 60 (quartiles 35-90) months. The pre-defined primary outcomes included new-onset or recurrent stroke/TIA and all-cause death. Prior stroke/TIA (HR 19.97, P < .001), angiokeratoma (HR 4.06, P = .010), elevated creatinine (HR 3.74, P = .011), significant left ventricular hypertrophy (HR 4.07, P = .017), and reduced global systolic strain (GLS, HR 5.19, P = .002) remained as independent risk predictors of new-onset or recurrent stroke/TIA in FD patients without AF. A Fabry-specific score was established based on above defined risk factors, proving somehow superior to the CHA 2 DS 2 -VASc score in predicting new-onset or recurrent stroke/TIA in this cohort (AUC 0.87 vs. 0.75, P = .199). Prior stroke/TIA, angiokeratoma, renal dysfunction, left ventricular hypertrophy, and global systolic dysfunction are independent risk factors for new-onset or recurrent stroke/TIA in FD patients without AF. It is feasible to predict new or recurrent cerebral events with the Fabry-specific score based on the above defined risk factors. Future studies are warranted to test if FD patients with high risk for new-onset or recurrent stroke/TIA, as defined by the Fabry-specific score (≥ 2 points), might benefit from antithrombotic therapy. Clinical trial registration HEAL-FABRY (evaluation of HEArt invoLvement in patients with FABRY disease, NCT03362164).

Understanding the factors affecting the postpartum depression in the mothers of Isfahan city

PubMed Central

Mazaheri, Maryam Amidi; Rabiei, Leili; Masoudi, Reza; Hamidizadeh, Saeid; Nooshabadi, Mohammad Reza Rashidi; Najimi, Arash

2014-01-01

Background and Objective: Depression is one of the most common and specific problems during pregnancy and after it. Maternal postpartum depression compromises mother's health and affects social relationship, and has negative effect on infant development. The aim of this study was to investigate the prevalence of postpartum depression and its related factors in Isfahanian mothers. Materials and Methods: This is a cross - sectional study. The study populations were 133 women who at the last 8-4 weeks of labor referred to Isfahan health centers. Demographic information and obstetric and Beck Depression Inventory were applied. Three categories emerged according to the degree of scale: Mild, moderate, and severe depression. Statistical analysis was used with the Pearson correlation and linear regression in SPSS version 18. Results: A total of 73 mothers had mild depression (10-19) and 56 had moderate depressions (20-29). Among the factors related to depression such as maternal education, financial status, unwanted pregnancy, premenstrual syndrome, and maternal occupational history, there was a significant correlation with postpartum depression (P > 0.05). Variables in the regression analysis include maternal education, financial status, unwanted pregnancy, history of premenstrual syndrome, maternal occupation, type of delivery, history of miscarriage, and having a satisfaction with baby gender. And, a total of 27.7% variance explains the postpartum depression. Among these factors, the predictive variables of maternal education, type of delivery, financial condition, unwanted pregnancy, premenstrual syndrome, and maternal occupational history were significant in the meantime; the prediction of unplanned pregnancy was more than other variables (ß = 0.24). Conclusions: With attention to factors associated with postpartum depression, the healthcare planner will help to better manage the problem. The results of this study will help to better understand the factors influencing mothers in the labor process, and mothers in the labor process, experiences minimum mental health disorders. PMID:25077158

40 CFR Table 1 to Subpart Wwww of... - Equations To Calculate Organic HAP Emissions Factors for Specific Open Molding and Centrifugal...

Code of Federal Regulations, 2010 CFR

2010-07-01

... Emissions Factors for Specific Open Molding and Centrifugal Casting Process Streams 1 Table 1 to Subpart... Standards for Hazardous Air Pollutants: Reinforced Plastic Composites Production Pt. 63, Subpt. WWWW, Table... Specific Open Molding and Centrifugal Casting Process Streams ER25AU05.020 ER25AU05.021 [70 FR 50129, Aug...

Finding the Perfect Match: Factors That Influence Family Medicine Residency Selection.

PubMed

Wright, Katherine M; Ryan, Elizabeth R; Gatta, John L; Anderson, Lauren; Clements, Deborah S

2016-04-01

Residency program selection is a significant experience for emerging physicians, yet there is limited information about how applicants narrow their list of potential programs. This study examines factors that influence residency program selection among medical students interested in family medicine at the time of application. Medical students with an expressed interest in family medicine were invited to participate in a 37-item, online survey. Students were asked to rate factors that may impact residency selection on a 6-point Likert scale in addition to three open-ended qualitative questions. Mean values were calculated for each survey item and were used to determine a rank order for selection criteria. Logistic regression analysis was performed to identify factors that predict a strong interest in urban, suburban, and rural residency programs. Logistic regression was also used to identify factors that predict a strong interest in academic health center-based residencies, community-based residencies, and community-based residencies with an academic affiliation. A total of 705 medical students from 32 states across the country completed the survey. Location, work/life balance, and program structure (curriculum, schedule) were rated the most important factors for residency selection. Logistic regression analysis was used to refine our understanding of how each factor relates to specific types of residencies. These findings have implications for how to best advise students in selecting a residency, as well as marketing residencies to the right candidates. Refining the recruitment process will ensure a better fit between applicants and potential programs. Limited recruitment resources may be better utilized by focusing on targeted dissemination strategies.

Parent and family stress factors predict health-related quality in pediatric patients with new-onset epilepsy.

PubMed

Wu, Yelena P; Follansbee-Junger, Katherine; Rausch, Joseph; Modi, Avani

2014-06-01

To examine the influence of parent and family general and epilepsy-related stress on longitudinal generic and epilepsy-specific health-related quality of life (HRQOL) for children with new-onset epilepsy, while controlling for demographic characteristics, disease factors, and antiepileptic drug (AED) adherence. This prospective, longitudinal study included 124 children with new-onset epilepsy (mean age 7.2 years, standard deviation [SD] 2.9 years). Parents completed questionnaires on parenting stress, perceived stigma, fears and concerns, and HRQOL at 1, 13, and 25 months after diagnosis. Adherence to AEDs was assessed using electronic monitors. A medical chart review was conducted at each visit to obtain seizure and side effect data. Higher levels of general and epilepsy-specific parent and family stress, fears and concerns, and perceived stigma negatively affected child generic and epilepsy-specific HRQOL, above and beyond disease and demographic factors. General parenting and family stress affected child generic and epilepsy-specific HRQOL more in the first year of disease management than at 2 years after diagnosis. Higher fears and concerns predicted higher epilepsy-specific HRQOL at 13 months postdiagnosis, whereas 2 years postdiagnosis, higher fears and concerns predicted lower epilepsy-specific HRQOL. Several demographic (i.e., age) and disease-related variables (i.e., side effects and AED adherence) influenced child generic and epilepsy-specific HRQOL. Although some findings were consistent across generic and epilepsy-specific HRQOL measures, others were unique. Modifiable parent factors (i.e., general and disease-specific parent and family stress, perceived stigma) impact HRQOL for children with new-onset epilepsy differently over the first 2 years postdiagnosis. Psychosocial interventions to improve HRQOL within the first year postdiagnosis should address parenting and family stress, overall coping, and anticipatory guidance on managing epilepsy. Interventions targeting adherence, perceived stigma, and fears and concerns could improve HRQOL. Promoting parent management of stress, fears/concerns, and perceived stigma may lead to improved child HRQOL outcomes. A PowerPoint slide summarizing this article is available for download in the Supporting Information section here. Wiley Periodicals, Inc. © 2014 International League Against Epilepsy.

NucPosPred: Predicting species-specific genomic nucleosome positioning via four different modes of general PseKNC.

PubMed

Jia, Cangzhi; Yang, Qing; Zou, Quan

2018-04-18

The nucleosome is the basic structure of chromatin in eukaryotic cells, with essential roles in the regulation of many biological processes, such as DNA transcription, replication and repair, and RNA splicing. Because of the importance of nucleosomes, the factors that determine their positioning within genomes should be investigated. High-resolution nucleosome-positioning maps are now available for organisms including Saccharomyces cerevisiae, Drosophila melanogaster and Caenorhabditis elegans, enabling the identification of nucleosome positioning by application of computational tools. Here, we describe a novel predictor called NucPosPred, which was specifically designed for large-scale identification of nucleosome positioning in C. elegans and D. melanogaster genomes. NucPosPred was separately optimized for each species for four types of DNA sequence feature extraction, with consideration of two classification algorithms (gradient-boosting decision tree and support vector machine). The overall accuracy obtained with NucPosPred was 92.29% for C. elegans and 88.26% for D. melanogaster, outperforming previous methods and demonstrating the potential for species-specific prediction of nucleosome positioning. For the convenience of most experimental scientists, a web-server for the predictor NucPosPred is available at http://121.42.167.206/NucPosPred/index.jsp. Copyright © 2018 Elsevier Ltd. All rights reserved.

Alcohol expectancy multiaxial assessment: a memory network-based approach.

PubMed

Goldman, Mark S; Darkes, Jack

2004-03-01

Despite several decades of activity, alcohol expectancy research has yet to merge measurement approaches with developing memory theory. This article offers an expectancy assessment approach built on a conceptualization of expectancy as an information processing network. The authors began with multidimensional scaling models of expectancy space, which served as heuristics to suggest confirmatory factor analytic dimensional models for entry into covariance structure predictive models. It is argued that this approach permits a relatively thorough assessment of the broad range of potential expectancy dimensions in a format that is very flexible in terms of instrument length and specificity versus breadth of focus. ((c) 2004 APA, all rights reserved)

Sentence Processing Factors in Adults with Specific Language Impairment

ERIC Educational Resources Information Center

Poll, Gerard H.

2012-01-01

Sentence imitation effectively discriminates between adults with and without specific language impairment (SLI). Little is known, however, about the factors that result in performance differences. This study evaluated the effects of working memory, processing speed, and argument status on sentence imitation. Working memory was measured by both a…

Attitudes toward emotions.

PubMed

Harmon-Jones, Eddie; Harmon-Jones, Cindy; Amodio, David M; Gable, Philip A

2011-12-01

The present work outlines a theory of attitudes toward emotions, provides a measure of attitudes toward emotions, and then tests several predictions concerning relationships between attitudes toward specific emotions and emotional situation selection, emotional traits, emotional reactivity, and emotion regulation. The present conceptualization of individual differences in attitudes toward emotions focuses on specific emotions and presents data indicating that 5 emotions (anger, sadness, joy, fear, and disgust) load on 5 separate attitude factors (Study 1). Attitudes toward emotions predicted emotional situation selection (Study 2). Moreover, attitudes toward approach emotions (e.g., anger, joy) correlated directly with the associated trait emotions, whereas attitudes toward withdrawal emotions (fear, disgust) correlated inversely with associated trait emotions (Study 3). Similar results occurred when attitudes toward emotions were used to predict state emotional reactivity (Study 4). Finally, attitudes toward emotions predicted specific forms of emotion regulation (Study 5).

Protein Structure Prediction with Evolutionary Algorithms

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

Hart, W.E.; Krasnogor, N.; Pelta, D.A.

1999-02-08

Evolutionary algorithms have been successfully applied to a variety of molecular structure prediction problems. In this paper we reconsider the design of genetic algorithms that have been applied to a simple protein structure prediction problem. Our analysis considers the impact of several algorithmic factors for this problem: the confirmational representation, the energy formulation and the way in which infeasible conformations are penalized, Further we empirically evaluated the impact of these factors on a small set of polymer sequences. Our analysis leads to specific recommendations for both GAs as well as other heuristic methods for solving PSP on the HP model.

Personality traits and individual differences predict threat-induced changes in postural control.

PubMed

Zaback, Martin; Cleworth, Taylor W; Carpenter, Mark G; Adkin, Allan L

2015-04-01

This study explored whether specific personality traits and individual differences could predict changes in postural control when presented with a height-induced postural threat. Eighty-two healthy young adults completed questionnaires to assess trait anxiety, trait movement reinvestment (conscious motor processing, movement self-consciousness), physical risk-taking, and previous experience with height-related activities. Tests of static (quiet standing) and anticipatory (rise to toes) postural control were completed under low and high postural threat conditions. Personality traits and individual differences significantly predicted height-induced changes in static, but not anticipatory postural control. Individuals less prone to taking physical risks were more likely to lean further away from the platform edge and sway at higher frequencies and smaller amplitudes. Individuals more prone to conscious motor processing were more likely to lean further away from the platform edge and sway at larger amplitudes. Individuals more self-conscious about their movement appearance were more likely to sway at smaller amplitudes. Evidence is also provided that relationships between physical risk-taking and changes in static postural control are mediated through changes in fear of falling and physiological arousal. Results from this study may have indirect implications for balance assessment and treatment; however, further work exploring these factors in patient populations is necessary. Copyright © 2015 Elsevier B.V. All rights reserved.

Bioinformatic identification and expression analysis of banana microRNAs and their targets.

PubMed

Chai, Juan; Feng, Renjun; Shi, Hourui; Ren, Mengyun; Zhang, Yindong; Wang, Jingyi

2015-01-01

MicroRNAs (miRNAs) represent a class of endogenous non-coding small RNAs that play important roles in multiple biological processes by degrading targeted mRNAs or repressing mRNA translation. Thousands of miRNAs have been identified in many plant species, whereas only a limited number of miRNAs have been predicted in M. acuminata (A genome) and M. balbisiana (B genome). Here, previously known plant miRNAs were BLASTed against the Expressed Sequence Tag (EST) and Genomic Survey Sequence (GSS), a database of banana genes. A total of 32 potential miRNAs belonging to 13 miRNAs families were detected using a range of filtering criteria. 244 miRNA:target pairs were subsequently predicted, most of which encode transcription factors or enzymes that participate in the regulation of development, growth, metabolism, and other physiological processes. In order to validate the predicted miRNAs and the mutual relationship between miRNAs and their target genes, qRT-PCR was applied to detect the tissue-specific expression levels of 12 putative miRNAs and 6 target genes in roots, leaves, flowers, and fruits. This study provides some important information about banana pre-miRNAs, mature miRNAs, and miRNA target genes and these findings can be applied to future research of miRNA functions.

Bioinformatic Identification and Expression Analysis of Banana MicroRNAs and Their Targets

PubMed Central

Shi, Hourui; Ren, Mengyun; Zhang, Yindong; Wang, Jingyi

2015-01-01

MicroRNAs (miRNAs) represent a class of endogenous non-coding small RNAs that play important roles in multiple biological processes by degrading targeted mRNAs or repressing mRNA translation. Thousands of miRNAs have been identified in many plant species, whereas only a limited number of miRNAs have been predicted in M. acuminata (A genome) and M. balbisiana (B genome). Here, previously known plant miRNAs were BLASTed against the Expressed Sequence Tag (EST) and Genomic Survey Sequence (GSS), a database of banana genes. A total of 32 potential miRNAs belonging to 13 miRNAs families were detected using a range of filtering criteria. 244 miRNA:target pairs were subsequently predicted, most of which encode transcription factors or enzymes that participate in the regulation of development, growth, metabolism, and other physiological processes. In order to validate the predicted miRNAs and the mutual relationship between miRNAs and their target genes, qRT-PCR was applied to detect the tissue-specific expression levels of 12 putative miRNAs and 6 target genes in roots, leaves, flowers, and fruits. This study provides some important information about banana pre-miRNAs, mature miRNAs, and miRNA target genes and these findings can be applied to future research of miRNA functions. PMID:25856313

Wraparound Retrospective: Factors Predicting Positive Outcomes

ERIC Educational Resources Information Center

Cox, Kathy; Baker, Dawniel; Wong, Mary Ann

2010-01-01

While research regarding the effectiveness of the wraparound process is steadily mounting, little is known about how this service delivery model works and for whom. Using data gathered on 176 youth who participated in the wraparound process, the authors examine client and service factors associated with outcomes. Bivariate logistic regression…

Prediction of uncomplicated pregnancies in obese women: a prospective multicentre study.

PubMed

Vieira, Matias C; White, Sara L; Patel, Nashita; Seed, Paul T; Briley, Annette L; Sandall, Jane; Welsh, Paul; Sattar, Naveed; Nelson, Scott M; Lawlor, Debbie A; Poston, Lucilla; Pasupathy, Dharmintra

2017-11-03

All obese pregnant women are considered at equal high risk with respect to complications in pregnancy and birth, and are commonly managed through resource-intensive care pathways. However, the identification of maternal characteristics associated with normal pregnancy outcomes could assist in the management of these pregnancies. The present study aims to identify the factors associated with uncomplicated pregnancy and birth in obese women, and to assess their predictive performance. Data form obese women (BMI ≥ 30 kg/m 2 ) with singleton pregnancies included in the UPBEAT trial were used in this analysis. Multivariable logistic regression was used to identify sociodemographic, clinical and biochemical factors at 15 +0 to 18 +6 weeks' gestation associated with uncomplicated pregnancy and birth, defined as delivery of a term live-born infant without antenatal or labour complications. Predictive performance was assessed using area under the receiver operating characteristic curve (AUROC). Internal validation and calibration were also performed. Women were divided into fifths of risk and pregnancy outcomes were compared between groups. Sensitivity, specificity, and positive and negative predictive values were calculated using the upper fifth as the positive screening group. Amongst 1409 participants (BMI 36.4, SD 4.8 kg/m 2 ), the prevalence of uncomplicated pregnancy and birth was 36% (505/1409). Multiparity and increased plasma adiponectin, maternal age, systolic blood pressure and HbA1c were independently associated with uncomplicated pregnancy and birth. These factors achieved an AUROC of 0.72 (0.68-0.76) and the model was well calibrated. Prevalence of gestational diabetes, preeclampsia and other hypertensive disorders, preterm birth, and postpartum haemorrhage decreased whereas spontaneous vaginal delivery increased across the fifths of increasing predicted risk of uncomplicated pregnancy and birth. Sensitivity, specificity, and positive and negative predictive values were 38%, 89%, 63% and 74%, respectively. A simpler model including clinical factors only (no biomarkers) achieved an AUROC of 0.68 (0.65-0.71), with sensitivity, specificity, and positive and negative predictive values of 31%, 86%, 56% and 69%, respectively. Clinical factors and biomarkers can be used to help stratify pregnancy and delivery risk amongst obese pregnant women. Further studies are needed to explore alternative pathways of care for obese women demonstrating different risk profiles for uncomplicated pregnancy and birth.

Developmental Trajectories in Toddlers’ Self-restraint Predict Individual Differences in Executive Functions 14 Years Later: A Behavioral Genetic Analysis

PubMed Central

Friedman, Naomi P.; Miyake, Akira; Robinson, JoAnn L.; Hewitt, John K.

2011-01-01

We examined whether self-restraint in early childhood predicted individual differences in three executive functions (EFs; inhibiting prepotent responses, updating working memory, and shifting task sets) in late adolescence in a sample of ~950 twins. At ages 14, 20, 24, and 36 months, the children were shown an attractive toy and told not to touch it for 30 seconds. Latency to touch the toy increased with age, and latent class growth modeling distinguished two groups of children that differed in their latencies to touch the toy at all 4 time points. Using confirmatory factor analysis, the three EFs (measured with latent variables at age 17 years) were decomposed into a Common EF factor (isomorphic to response inhibition ability) and two factors specific to updating and shifting, respectively. Less restrained children had significantly lower scores on the Common EF factor, equivalent scores on the Updating-specific factor, and higher scores on the Shifting-specific factor than the more restrained children. The less restrained group also had lower IQ scores, but this effect was entirely mediated by the EF components. Twin models indicated that the associations were primarily genetic in origin for the Common EF variable but split between genetics and nonshared environment for the Shifting-specific variable. These results suggest a biological relation between individual differences in self-restraint and EFs, one that begins early in life and persists into late adolescence. PMID:21668099

Sasquatch: predicting the impact of regulatory SNPs on transcription factor binding from cell- and tissue-specific DNase footprints

PubMed Central

Suciu, Maria C.; Telenius, Jelena

2017-01-01

In the era of genome-wide association studies (GWAS) and personalized medicine, predicting the impact of single nucleotide polymorphisms (SNPs) in regulatory elements is an important goal. Current approaches to determine the potential of regulatory SNPs depend on inadequate knowledge of cell-specific DNA binding motifs. Here, we present Sasquatch, a new computational approach that uses DNase footprint data to estimate and visualize the effects of noncoding variants on transcription factor binding. Sasquatch performs a comprehensive k-mer-based analysis of DNase footprints to determine any k-mer's potential for protein binding in a specific cell type and how this may be changed by sequence variants. Therefore, Sasquatch uses an unbiased approach, independent of known transcription factor binding sites and motifs. Sasquatch only requires a single DNase-seq data set per cell type, from any genotype, and produces consistent predictions from data generated by different experimental procedures and at different sequence depths. Here we demonstrate the effectiveness of Sasquatch using previously validated functional SNPs and benchmark its performance against existing approaches. Sasquatch is available as a versatile webtool incorporating publicly available data, including the human ENCODE collection. Thus, Sasquatch provides a powerful tool and repository for prioritizing likely regulatory SNPs in the noncoding genome. PMID:28904015

Patient-specific non-linear finite element modelling for predicting soft organ deformation in real-time: application to non-rigid neuroimage registration.

PubMed

Wittek, Adam; Joldes, Grand; Couton, Mathieu; Warfield, Simon K; Miller, Karol

2010-12-01

Long computation times of non-linear (i.e. accounting for geometric and material non-linearity) biomechanical models have been regarded as one of the key factors preventing application of such models in predicting organ deformation for image-guided surgery. This contribution presents real-time patient-specific computation of the deformation field within the brain for six cases of brain shift induced by craniotomy (i.e. surgical opening of the skull) using specialised non-linear finite element procedures implemented on a graphics processing unit (GPU). In contrast to commercial finite element codes that rely on an updated Lagrangian formulation and implicit integration in time domain for steady state solutions, our procedures utilise the total Lagrangian formulation with explicit time stepping and dynamic relaxation. We used patient-specific finite element meshes consisting of hexahedral and non-locking tetrahedral elements, together with realistic material properties for the brain tissue and appropriate contact conditions at the boundaries. The loading was defined by prescribing deformations on the brain surface under the craniotomy. Application of the computed deformation fields to register (i.e. align) the preoperative and intraoperative images indicated that the models very accurately predict the intraoperative deformations within the brain. For each case, computing the brain deformation field took less than 4 s using an NVIDIA Tesla C870 GPU, which is two orders of magnitude reduction in computation time in comparison to our previous study in which the brain deformation was predicted using a commercial finite element solver executed on a personal computer. Copyright © 2010 Elsevier Ltd. All rights reserved.

Modelling language evolution: Examples and predictions

NASA Astrophysics Data System (ADS)

Gong, Tao; Shuai, Lan; Zhang, Menghan

2014-06-01

We survey recent computer modelling research of language evolution, focusing on a rule-based model simulating the lexicon-syntax coevolution and an equation-based model quantifying the language competition dynamics. We discuss four predictions of these models: (a) correlation between domain-general abilities (e.g. sequential learning) and language-specific mechanisms (e.g. word order processing); (b) coevolution of language and relevant competences (e.g. joint attention); (c) effects of cultural transmission and social structure on linguistic understandability; and (d) commonalities between linguistic, biological, and physical phenomena. All these contribute significantly to our understanding of the evolutions of language structures, individual learning mechanisms, and relevant biological and socio-cultural factors. We conclude the survey by highlighting three future directions of modelling studies of language evolution: (a) adopting experimental approaches for model evaluation; (b) consolidating empirical foundations of models; and (c) multi-disciplinary collaboration among modelling, linguistics, and other relevant disciplines.

HITS-CLIP yields genome-wide insights into brain alternative RNA processing

NASA Astrophysics Data System (ADS)

Licatalosi, Donny D.; Mele, Aldo; Fak, John J.; Ule, Jernej; Kayikci, Melis; Chi, Sung Wook; Clark, Tyson A.; Schweitzer, Anthony C.; Blume, John E.; Wang, Xuning; Darnell, Jennifer C.; Darnell, Robert B.

2008-11-01

Protein-RNA interactions have critical roles in all aspects of gene expression. However, applying biochemical methods to understand such interactions in living tissues has been challenging. Here we develop a genome-wide means of mapping protein-RNA binding sites in vivo, by high-throughput sequencing of RNA isolated by crosslinking immunoprecipitation (HITS-CLIP). HITS-CLIP analysis of the neuron-specific splicing factor Nova revealed extremely reproducible RNA-binding maps in multiple mouse brains. These maps provide genome-wide in vivo biochemical footprints confirming the previous prediction that the position of Nova binding determines the outcome of alternative splicing; moreover, they are sufficiently powerful to predict Nova action de novo. HITS-CLIP revealed a large number of Nova-RNA interactions in 3' untranslated regions, leading to the discovery that Nova regulates alternative polyadenylation in the brain. HITS-CLIP, therefore, provides a robust, unbiased means to identify functional protein-RNA interactions in vivo.

Novel Hybrid Scheduling Technique for Sensor Nodes with Mixed Criticality Tasks.

PubMed

Micea, Mihai-Victor; Stangaciu, Cristina-Sorina; Stangaciu, Valentin; Curiac, Daniel-Ioan

2017-06-26

Sensor networks become increasingly a key technology for complex control applications. Their potential use in safety- and time-critical domains has raised the need for task scheduling mechanisms specially adapted to sensor node specific requirements, often materialized in predictable jitter-less execution of tasks characterized by different criticality levels. This paper offers an efficient scheduling solution, named Hybrid Hard Real-Time Scheduling (H²RTS), which combines a static, clock driven method with a dynamic, event driven scheduling technique, in order to provide high execution predictability, while keeping a high node Central Processing Unit (CPU) utilization factor. From the detailed, integrated schedulability analysis of the H²RTS, a set of sufficiency tests are introduced and demonstrated based on the processor demand and linear upper bound metrics. The performance and correct behavior of the proposed hybrid scheduling technique have been extensively evaluated and validated both on a simulator and on a sensor mote equipped with ARM7 microcontroller.

Factors predicting change in hospital safety climate and capability in a multi-site patient safety collaborative: a longitudinal survey study.

PubMed

Benn, Jonathan; Burnett, Susan; Parand, Anam; Pinto, Anna; Vincent, Charles

2012-07-01

The study had two specific objectives: (1) To analyse change in a survey measure of organisational patient safety climate and capability (SCC) resulting from participation in the UK Safer Patients Initiative and (2) To investigate the role of a range of programme and contextual factors in predicting change in SCC scores. Single group longitudinal design with repeated measurement at 12-month follow-up. Multiple service areas within NHS hospital sites across England, Wales, Scotland and Northern Ireland. Stratified sample of 284 respondents representing programme teams at 19 hospital sites. A complex intervention comprising a multi-component quality improvement collaborative focused upon patient safety and designed to impact upon hospital leadership, communication, organisation and safety climate. A survey including a 31-item SCC scale was administered at two time-points. Modest but significant positive movement in SCC score was observed between the study time-points. Individual programme responsibility, availability of early adopters, multi-professional collaboration and extent of process measurement were significant predictors of change in SCC. Hospital type and size, along with a range of programme preconditions, were not found to be significant. A range of social, cultural and organisational factors may be sensitive to this type of intervention but the measurable effect is small. Supporting critical local programme implementation factors may be an effective strategy in achieving development in organisational patient SCC, regardless of contextual factors and organisational preconditions.

kmer-SVM: a web server for identifying predictive regulatory sequence features in genomic data sets

PubMed Central

Fletez-Brant, Christopher; Lee, Dongwon; McCallion, Andrew S.; Beer, Michael A.

2013-01-01

Massively parallel sequencing technologies have made the generation of genomic data sets a routine component of many biological investigations. For example, Chromatin immunoprecipitation followed by sequence assays detect genomic regions bound (directly or indirectly) by specific factors, and DNase-seq identifies regions of open chromatin. A major bottleneck in the interpretation of these data is the identification of the underlying DNA sequence code that defines, and ultimately facilitates prediction of, these transcription factor (TF) bound or open chromatin regions. We have recently developed a novel computational methodology, which uses a support vector machine (SVM) with kmer sequence features (kmer-SVM) to identify predictive combinations of short transcription factor-binding sites, which determine the tissue specificity of these genomic assays (Lee, Karchin and Beer, Discriminative prediction of mammalian enhancers from DNA sequence. Genome Res. 2011; 21:2167–80). This regulatory information can (i) give confidence in genomic experiments by recovering previously known binding sites, and (ii) reveal novel sequence features for subsequent experimental testing of cooperative mechanisms. Here, we describe the development and implementation of a web server to allow the broader research community to independently apply our kmer-SVM to analyze and interpret their genomic datasets. We analyze five recently published data sets and demonstrate how this tool identifies accessory factors and repressive sequence elements. kmer-SVM is available at http://kmersvm.beerlab.org. PMID:23771147

kmer-SVM: a web server for identifying predictive regulatory sequence features in genomic data sets.

PubMed

Fletez-Brant, Christopher; Lee, Dongwon; McCallion, Andrew S; Beer, Michael A

2013-07-01

Massively parallel sequencing technologies have made the generation of genomic data sets a routine component of many biological investigations. For example, Chromatin immunoprecipitation followed by sequence assays detect genomic regions bound (directly or indirectly) by specific factors, and DNase-seq identifies regions of open chromatin. A major bottleneck in the interpretation of these data is the identification of the underlying DNA sequence code that defines, and ultimately facilitates prediction of, these transcription factor (TF) bound or open chromatin regions. We have recently developed a novel computational methodology, which uses a support vector machine (SVM) with kmer sequence features (kmer-SVM) to identify predictive combinations of short transcription factor-binding sites, which determine the tissue specificity of these genomic assays (Lee, Karchin and Beer, Discriminative prediction of mammalian enhancers from DNA sequence. Genome Res. 2011; 21:2167-80). This regulatory information can (i) give confidence in genomic experiments by recovering previously known binding sites, and (ii) reveal novel sequence features for subsequent experimental testing of cooperative mechanisms. Here, we describe the development and implementation of a web server to allow the broader research community to independently apply our kmer-SVM to analyze and interpret their genomic datasets. We analyze five recently published data sets and demonstrate how this tool identifies accessory factors and repressive sequence elements. kmer-SVM is available at http://kmersvm.beerlab.org.

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

PubMed

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

2016-08-01

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

A provisional regulatory gene network for specification of endomesoderm in the sea urchin embryo

NASA Technical Reports Server (NTRS)

Davidson, Eric H.; Rast, Jonathan P.; Oliveri, Paola; Ransick, Andrew; Calestani, Cristina; Yuh, Chiou-Hwa; Minokawa, Takuya; Amore, Gabriele; Hinman, Veronica; Arenas-Mena, Cesar;

A novel neural-inspired learning algorithm with application to clinical risk prediction.

PubMed

Tay, Darwin; Poh, Chueh Loo; Kitney, Richard I

2015-04-01

Clinical risk prediction - the estimation of the likelihood an individual is at risk of a disease - is a coveted and exigent clinical task, and a cornerstone to the recommendation of life saving management strategies. This is especially important for individuals at risk of cardiovascular disease (CVD) given the fact that it is the leading causes of death in many developed counties. To this end, we introduce a novel learning algorithm - a key factor that influences the performance of machine learning-based prediction models - and utilities it to develop CVD risk prediction tool. This novel neural-inspired algorithm, called the Artificial Neural Cell System for classification (ANCSc), is inspired by mechanisms that develop the brain and empowering it with capabilities such as information processing/storage and recall, decision making and initiating actions on external environment. Specifically, we exploit on 3 natural neural mechanisms responsible for developing and enriching the brain - namely neurogenesis, neuroplasticity via nurturing and apoptosis - when implementing ANCSc algorithm. Benchmark testing was conducted using the Honolulu Heart Program (HHP) dataset and results are juxtaposed with 2 other algorithms - i.e. Support Vector Machine (SVM) and Evolutionary Data-Conscious Artificial Immune Recognition System (EDC-AIRS). Empirical experiments indicate that ANCSc algorithm (statistically) outperforms both SVM and EDC-AIRS algorithms. Key clinical markers identified by ANCSc algorithm include risk factors related to diet/lifestyle, pulmonary function, personal/family/medical history, blood data, blood pressure, and electrocardiography. These clinical markers, in general, are also found to be clinically significant - providing a promising avenue for identifying potential cardiovascular risk factors to be evaluated in clinical trials. Copyright © 2015 Elsevier Inc. All rights reserved.

Cell density dependence of Microcystis aeruginosa responses to copper algaecide concentrations: Implications for microcystin-LR release.

PubMed

Kinley, Ciera M; Iwinski, Kyla J; Hendrikse, Maas; Geer, Tyler D; Rodgers, John H

2017-11-01

Along with mechanistic models, predictions of exposure-response relationships for copper are often derived from laboratory toxicity experiments with standardized experimental exposures and conditions. For predictions of copper toxicity to algae, cell density is a critical factor often overlooked. For pulse exposures of copper-based algaecides in aquatic systems, cell density can significantly influence copper sorbed by the algal population, and consequent responses. A cyanobacterium, Microcystis aeruginosa, was exposed to a copper-based algaecide over a range of cell densities to model the density-dependence of exposures, and effects on microcystin-LR (MC-LR) release. Copper exposure concentrations were arrayed to result in a gradient of MC-LR release, and masses of copper sorbed to algal populations were measured following exposures. While copper exposure concentrations eliciting comparable MC-LR release ranged an order of magnitude (24-h EC50s 0.03-0.3mg Cu/L) among cell densities of 10 6 through 10 7 cells/mL, copper doses (mg Cu/mg algae) were similar (24-h EC50s 0.005-0.006mg Cu/mg algae). Comparisons of MC-LR release as a function of copper exposure concentrations and doses provided a metric of the density dependence of algal responses in the context of copper-based algaecide applications. Combined with estimates of other site-specific factors (e.g. water characteristics) and fate processes (e.g. dilution and dispersion, sorption to organic matter and sediments), measuring exposure-response relationships for specific cell densities can refine predictions for in situ exposures and algal responses. These measurements can in turn decrease the likelihood of amending unnecessary copper concentrations to aquatic systems, and minimize risks for non-target aquatic organisms. Copyright © 2017 Elsevier Inc. All rights reserved.

Coating process optimization through in-line monitoring for coating weight gain using Raman spectroscopy and design of experiments.

PubMed

Kim, Byungsuk; Woo, Young-Ah

2018-05-30

In this study the authors developed a real-time Process Analytical Technology (PAT) of a coating process by applying in-line Raman spectroscopy to evaluate the coating weight gain, which is a quantitative analysis of the film coating layer. The wide area illumination (WAI) Raman probe was connected to the pan coater for real-time monitoring of changes in the weight gain of coating layers. Under the proposed in-line Raman scheme, a non-contact, non-destructive analysis was performed using WAI Raman probes with a spot size of 6 mm. The in-line Raman probe maintained a focal length of 250 mm, and a compressed air line was designed to protect the lens surface from spray droplets. The Design of Experiment (DOE) was applied to identify factors affecting the Raman spectra background of laser irradiation. The factors selected for DOE were the strength of compressed air connected to the probe, and the shielding of light by the transparent door connecting the probe to the pan coater. To develop a quantitative model, partial least squares (PLS) models as multivariate calibration were developed based on the three regions showing the specificity of TiO 2 individually or in combination. For the three single peaks (636 cm -1 , 512 cm -1 , 398 cm -1 ), least squares method (LSM) was applied to develop three univariate quantitative analysis models. One of best multivariate quantitative model having a factor of 1 gave the lowest RMSEP of 0.128, 0.129, and 0.125, respectively for prediction batches. When LSM was applied to the single peak at 636 cm -1 , the univariate quantitative model with an R 2 of 0.9863, slope of 0.5851, and y-intercept of 0.8066 had the lowest RMSEP of 0.138, 0.144, and 0.153, respectively for prediction batches. The in-line Raman spectroscopic method for the analysis of coating weight gain was verified by considering system suitability and parameters such as specificity, range, linearity, accuracy, and precision in accordance with ICH Q2 regarding method validation. The proposed in-line Raman spectroscopy can be utilized as a PAT for product quality assurance as it offers real-time monitoring of quantitative changes in coating weight gain and process end-points during the film coating process. Copyright © 2018 Elsevier B.V. All rights reserved.

Towards a consensus-based biokinetic model for green microalgae - The ASM-A.

PubMed

Wágner, Dorottya S; Valverde-Pérez, Borja; Sæbø, Mariann; Bregua de la Sotilla, Marta; Van Wagenen, Jonathan; Smets, Barth F; Plósz, Benedek Gy

2016-10-15

Cultivation of microalgae in open ponds and closed photobioreactors (PBRs) using wastewater resources offers an opportunity for biochemical nutrient recovery. Effective reactor system design and process control of PBRs requires process models. Several models with different complexities have been developed to predict microalgal growth. However, none of these models can effectively describe all the relevant processes when microalgal growth is coupled with nutrient removal and recovery from wastewaters. Here, we present a mathematical model developed to simulate green microalgal growth (ASM-A) using the systematic approach of the activated sludge modelling (ASM) framework. The process model - identified based on a literature review and using new experimental data - accounts for factors influencing photoautotrophic and heterotrophic microalgal growth, nutrient uptake and storage (i.e. Droop model) and decay of microalgae. Model parameters were estimated using laboratory-scale batch and sequenced batch experiments using the novel Latin Hypercube Sampling based Simplex (LHSS) method. The model was evaluated using independent data obtained in a 24-L PBR operated in sequenced batch mode. Identifiability of the model was assessed. The model can effectively describe microalgal biomass growth, ammonia and phosphate concentrations as well as the phosphorus storage using a set of average parameter values estimated with the experimental data. A statistical analysis of simulation and measured data suggests that culture history and substrate availability can introduce significant variability on parameter values for predicting the reaction rates for bulk nitrate and the intracellularly stored nitrogen state-variables, thereby requiring scenario specific model calibration. ASM-A was identified using standard cultivation medium and it can provide a platform for extensions accounting for factors influencing algal growth and nutrient storage using wastewater resources. Copyright © 2016 Elsevier Ltd. All rights reserved.

Inter-species investigation of the mechano-regulation of bone healing: comparison of secondary bone healing in sheep and rat.

PubMed

Checa, Sara; Prendergast, Patrick J; Duda, Georg N

2011-04-29

Inter-species differences in regeneration exist in various levels. One aspect is the dynamics of bone regeneration and healing, e.g. small animals show a faster healing response when compared to large animals. Mechanical as well as biological factors are known to play a key role in the process. However, it remains so far unknown whether different animals follow at all comparable mechano-biological rules during tissue regeneration, and in particular during bone healing. In this study, we investigated whether differences observed in vivo in the dynamics of bone healing between rat and sheep are only due to differences in the animal size or whether these animals have a different mechano-biological response during the healing process. Histological sections from in vivo experiments were compared to in silico predictions of a mechano-biological computer model for the simulation of bone healing. Investigations showed that the healing processes in both animal models occur under significantly different levels of mechanical stimuli within the callus region, which could explain histological observations of early intramembranous ossification at the endosteal side. A species-specific adaptation of a mechano-biological model allowed a qualitative match of model predictions with histological observations. Specifically, when keeping cell activity processes at the same rate, the amount of tissue straining defining favorable mechanical conditions for the formation of bone had to be increased in the large animal model, with respect to the small animal, to achieve a qualitative agreement of model predictions with histological data. These findings illustrate that geometrical (size) differences alone cannot explain the distinctions seen in the histological appearance of secondary bone healing in sheep and rat. It can be stated that significant differences in the mechano-biological regulation of the healing process exist between these species. Future investigations should aim towards understanding whether these differences are due to differences in cell behavior, material properties of the newly formed tissues within the callus and/or differences in response to the mechanical environment. Copyright © 2011 Elsevier Ltd. All rights reserved.

Prediction of 30-year risk for cardiovascular mortality by fitness and risk factor levels: the Cooper Center Longitudinal Study.

PubMed

Wickramasinghe, Chanaka D; Ayers, Colby R; Das, Sandeep; de Lemos, James A; Willis, Benjamin L; Berry, Jarett D

2014-07-01

Fitness and traditional risk factors have well-known associations with cardiovascular disease (CVD) death in both short-term (10 years) and across the remaining lifespan. However, currently available short-term and long-term risk prediction tools do not incorporate measured fitness. We included 16 533 participants from the Cooper Center Longitudinal Study (CCLS) without prior CVD. Fitness was measured using the Balke protocol. Sex-specific fitness levels were derived from the Balke treadmill times and categorized into low, intermediate, and high fit according to age- and sex-specific treadmill times. Sex-specific 30-year risk estimates for CVD death adjusted for competing risk of non-CVD death were estimated using the cause-specific hazards model and included age, body mass index, systolic blood pressure, fitness, diabetes mellitus, total cholesterol, and smoking. During a median follow-up period of 28 years, there were 1123 CVD deaths. The 30-year risk estimates for CVD mortality derived from the cause-specific hazards model demonstrated overall good calibration (Nam-D'Agostino χ(2) [men, P=0.286; women, P=0.664] and discrimination (c statistic; men, 0.81 [0.80-0.82] and women, 0.86 [0.82-0.91]). Across all risk factor strata, the presence of low fitness was associated with a greater 30-year risk for CVD death. Fitness represents an important additional covariate in 30-year risk prediction functions that may serve as a useful tool in clinical practice. © 2014 American Heart Association, Inc.

PREDICTING POPULATION EXPOSURES TO PM10 AND PM 2.5

EPA Science Inventory

An improved model for human exposure to particulate matter (PM), specifically PM10 and PM2.5 is under development by the U.S. EPA/NERL. This model will incorporate data from new PM exposure measurement and exposure factors research. It is intended to be used to predict exposure...

Sex specific differences in the predictive value of cholesterol homeostasis markers and 10-Year CVD event rate in Framingham Offspring Study participants

USDA-ARS?s Scientific Manuscript database

Available data are inconsistent on factors influencing plasma cholesterol homeostasis marker concentrations and their value in predicting subsequent cardiovascular disease (CVD) events. To address this issue the relationship between markers of cholesterol absorption (campesterol, sitosterol, cholest...

Parent-Teen Communication about Premarital Sex: Factors Associated with the Extent of Communication.

ERIC Educational Resources Information Center

Jaccard, James; Dittus, Patricia J.; Gordon, Vivian V.

2000-01-01

This study explored topic-specific reservations about discussing sex and birth control among inner-city African American mothers and their 14- to 17-year-olds. Findings showed that reservations predicted communication behavior beyond that predicted by general family environment variables. Interaction effects suggested differential impact of…

Prediction and Stability of Mathematics Skill and Difficulty

ERIC Educational Resources Information Center

Martin, Rebecca B.; Cirino, Paul T.; Barnes, Marcia A.; Ewing-Cobbs, Linda; Fuchs, Lynn S.; Stuebing, Karla K.; Fletcher, Jack M.

2013-01-01

The present study evaluated the stability of math learning difficulties over a 2-year period and investigated several factors that might influence this stability (categorical vs. continuous change, liberal vs. conservative cut point, broad vs. specific math assessment); the prediction of math performance over time and by performance level was also…

Genome wide predictions of miRNA regulation by transcription factors.

PubMed

Ruffalo, Matthew; Bar-Joseph, Ziv

2016-09-01

Reconstructing regulatory networks from expression and interaction data is a major goal of systems biology. While much work has focused on trying to experimentally and computationally determine the set of transcription-factors (TFs) and microRNAs (miRNAs) that regulate genes in these networks, relatively little work has focused on inferring the regulation of miRNAs by TFs. Such regulation can play an important role in several biological processes including development and disease. The main challenge for predicting such interactions is the very small positive training set currently available. Another challenge is the fact that a large fraction of miRNAs are encoded within genes making it hard to determine the specific way in which they are regulated. To enable genome wide predictions of TF-miRNA interactions, we extended semi-supervised machine-learning approaches to integrate a large set of different types of data including sequence, expression, ChIP-seq and epigenetic data. As we show, the methods we develop achieve good performance on both a labeled test set, and when analyzing general co-expression networks. We next analyze mRNA and miRNA cancer expression data, demonstrating the advantage of using the predicted set of interactions for identifying more coherent and relevant modules, genes, and miRNAs. The complete set of predictions is available on the supporting website and can be used by any method that combines miRNAs, genes, and TFs. Code and full set of predictions are available from the supporting website: http://cs.cmu.edu/~mruffalo/tf-mirna/ zivbj@cs.cmu.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Prostate-specific antigen density is predictive of outcome in suboptimal prostate seed brachytherapy.

PubMed

Benzaquen, David; Delouya, Guila; Ménard, Cynthia; Barkati, Maroie; Taussky, Daniel

In prostate seed brachytherapy, a D 90 of <130 Gy is an accepted predictive factor for biochemical failure (BF). We studied whether there is a subpopulation that does not need additional treatment after a suboptimal permanent seed brachytherapy implantation. A total of 486 patients who had either BF or a minimum followup of 48 months without BF were identified. BF was defined according to the Phoenix definition (nadir prostate-specific antigen + 2). Univariate and multivariate analyses were performed, adjusting for known prognostic factors such as D 90 and prostate-specific antigen density (PSAD) of ≥0.15 ng/mL/cm 3 , to evaluate their ability to predict BF. Median followup for patients without BF was 72 months (interquartile range 56-96). BF-free recurrence rate at 5 years was 95% and at 8 years 88%. In univariate analysis, PSAD and cancer of the prostate risk assessment score were predictive of BF. On multivariate analysis, none of the factors remained significant. The best prognosis had patients with a low PSAD (<0.15 ng/mL/cm 3 ) and an optimal implant at 30 days after implantation (as defined by D 90  ≥ 130 Gy) compared to patients with both factors unfavorable (p = 0.006). A favorable PSAD was associate with a good prognosis, independently of the D 90 (<130 Gy vs. ≥130 Gy, p = 0.7). Patients with a PSAD of <0.15 ng/mL/cm 3 have little risk of BF, even in the case of a suboptimal implant. These results need to be validated in other patients' cohorts. Copyright © 2016 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

Interactome analysis of transcriptional coactivator multiprotein bridging factor 1 unveils a yeast AP-1-like transcription factor involved in oxidation tolerance of mycopathogen Beauveria bassiana.

PubMed

Chu, Xin-Ling; Dong, Wei-Xia; Ding, Jin-Li; Feng, Ming-Guang; Ying, Sheng-Hua

2018-02-01

Oxidation tolerance is an important determinant to predict the virulence and biocontrol potential of Beauveria bassiana, a well-known entomopathogenic fungus. As a transcriptional coactivator, multiprotein bridging factor 1 mediates the activity of transcription factor in diverse physiological processes, and its homolog in B. bassiana (BbMBF1) contributes to fungal oxidation tolerance. In this study, the BbMBF1-interactomes under oxidative stress and normal growth condition were deciphered by mass spectrometry integrated with the immunoprecipitation. BbMBF1p factor has a broad interaction with proteins that are involved in various cellular processes, and this interaction is dynamically regulated by oxidative stress. Importantly, a B. bassiana homolog of yeast AP-1-like transcription factor (BbAP-1) was specifically associated with the BbMBF1-interactome under oxidation and significantly contributed to fungal oxidation tolerance. In addition, qPCR analysis revealed that several antioxidant genes are jointly controlled by BbAP-1 and BbMBF1. Conclusively, it is proposed that BbMBF1p protein mediates BbAP-1p factor to transcribe the downstream antioxidant genes in B. bassiana under oxidative stress. This study demonstrates for the first time a proteomic view of the MBF1-interactome in fungi, and presents an initial framework to probe the transcriptional mechanism involved in fungal response to oxidation, which will provide a new strategy to improve the biocontrol efficacy of B. bassiana.

RAYLEIGH–TAYLOR UNSTABLE FLAMES—FAST OR FASTER?

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

Hicks, E. P., E-mail: eph2001@columbia.edu

2015-04-20

Rayleigh–Taylor (RT) unstable flames play a key role in the explosions of supernovae Ia. However, the dynamics of these flames are still not well understood. RT unstable flames are affected by both the RT instability of the flame front and by RT-generated turbulence. The coexistence of these factors complicates the choice of flame speed subgrid models for full-star Type Ia simulations. Both processes can stretch and wrinkle the flame surface, increasing its area and, therefore, the burning rate. In past research, subgrid models have been based on either the RT instability or turbulence setting the flame speed. We evaluate bothmore » models, checking their assumptions and their ability to correctly predict the turbulent flame speed. Specifically, we analyze a large parameter study of 3D direct numerical simulations of RT unstable model flames. This study varies both the simulation domain width and the gravity in order to probe a wide range of flame behaviors. We show that RT unstable flames are different from traditional turbulent flames: they are thinner rather than thicker when turbulence is stronger. We also show that none of the several different types of turbulent flame speed models accurately predicts measured flame speeds. In addition, we find that the RT flame speed model only correctly predicts the measured flame speed in a certain parameter regime. Finally, we propose that the formation of cusps may be the factor causing the flame to propagate more quickly than predicted by the RT model.« less

Predicting long-term risk for relationship dissolution using nonparametric conditional survival trees.

PubMed

Kliem, Sören; Weusthoff, Sarah; Hahlweg, Kurt; Baucom, Katherine J W; Baucom, Brian R

2015-12-01

Identifying risk factors for divorce or separation is an important step in the prevention of negative individual outcomes and societal costs associated with relationship dissolution. Programs that aim to prevent relationship distress and dissolution typically focus on changing processes that occur during couple conflict, although the predictive ability of conflict-specific variables has not been examined in the context of other factors related to relationship dissolution. The authors examine whether emotional responding and communication during couple conflict predict relationship dissolution after controlling for overall relationship quality and individual well-being. Using nonparametric conditional survival trees, the study at hand simultaneously examined the predictive abilities of physiological (systolic and diastolic blood pressure, heart rate, cortisol) and behavioral (fundamental frequency; f0) indices of emotional responding, as well as observationally coded positive and negative communication behavior, on long-term relationship stability after controlling for relationship satisfaction and symptoms of depression. One hundred thirty-six spouses were assessed after participating in a randomized clinical trial of a relationship distress prevention program as well as 11 years thereafter; 32.5% of the couples' relationships had dissolved by follow up. For men, the only significant predictor of relationship dissolution was cortisol change score (p = .012). For women, only f0 range was a significant predictor of relationship dissolution (p = .034). These findings highlight the importance of emotional responding during couple conflict for long-term relationship stability. (c) 2015 APA, all rights reserved).

Rayleigh-Taylor Unstable Flames -- Fast or Faster?

NASA Astrophysics Data System (ADS)

Hicks, E. P.

2015-04-01

Rayleigh-Taylor (RT) unstable flames play a key role in the explosions of supernovae Ia. However, the dynamics of these flames are still not well understood. RT unstable flames are affected by both the RT instability of the flame front and by RT-generated turbulence. The coexistence of these factors complicates the choice of flame speed subgrid models for full-star Type Ia simulations. Both processes can stretch and wrinkle the flame surface, increasing its area and, therefore, the burning rate. In past research, subgrid models have been based on either the RT instability or turbulence setting the flame speed. We evaluate both models, checking their assumptions and their ability to correctly predict the turbulent flame speed. Specifically, we analyze a large parameter study of 3D direct numerical simulations of RT unstable model flames. This study varies both the simulation domain width and the gravity in order to probe a wide range of flame behaviors. We show that RT unstable flames are different from traditional turbulent flames: they are thinner rather than thicker when turbulence is stronger. We also show that none of the several different types of turbulent flame speed models accurately predicts measured flame speeds. In addition, we find that the RT flame speed model only correctly predicts the measured flame speed in a certain parameter regime. Finally, we propose that the formation of cusps may be the factor causing the flame to propagate more quickly than predicted by the RT model.

A Personalized Predictive Framework for Multivariate Clinical Time Series via Adaptive Model Selection.

PubMed

Liu, Zitao; Hauskrecht, Milos

2017-11-01

Building of an accurate predictive model of clinical time series for a patient is critical for understanding of the patient condition, its dynamics, and optimal patient management. Unfortunately, this process is not straightforward. First, patient-specific variations are typically large and population-based models derived or learned from many different patients are often unable to support accurate predictions for each individual patient. Moreover, time series observed for one patient at any point in time may be too short and insufficient to learn a high-quality patient-specific model just from the patient's own data. To address these problems we propose, develop and experiment with a new adaptive forecasting framework for building multivariate clinical time series models for a patient and for supporting patient-specific predictions. The framework relies on the adaptive model switching approach that at any point in time selects the most promising time series model out of the pool of many possible models, and consequently, combines advantages of the population, patient-specific and short-term individualized predictive models. We demonstrate that the adaptive model switching framework is very promising approach to support personalized time series prediction, and that it is able to outperform predictions based on pure population and patient-specific models, as well as, other patient-specific model adaptation strategies.

Demonstration and Characterization of Biomolecular Enrichment on Microfluidic Aptamer-Functionalized Surfaces

PubMed Central

Nguyen, Thai Huu; Pei, Renjun; Stojanovic, Milan; Lin, Qiao

2010-01-01

This paper demonstrates and systematically characterizes the enrichment of biomolecular compounds using aptamer-functionalized surfaces within a microfluidic device. The device consists of a microchamber packed with aptamer-functionalized microbeads and integrated with a microheater and temperature sensor to enable thermally controlled binding and release of biomolecules by the aptamer. We first present an equilibrium binding-based analytical model to understand the enrichment process. The characteristics of the aptamer-analyte binding and enrichment are then experimentally studied, using adenosine monophosphate (AMP) and a specific RNA aptamer as a model system. The temporal process of AMP binding to the aptamer is found to be primarily determined by the aptamer-AMP binding kinetics. The temporal process of aptamer-AMP dissociation at varying temperatures is also obtained and observed to occur relatively rapidly (< 2 s). The specificity of the enrichment is next confirmed by performing selective enrichment of AMP from a sample containing biomolecular impurities. Finally, we investigate the enrichment of AMP by either discrete or continuous introduction of a dilute sample into the microchamber, demonstrating enrichment factors ranging from 566 to 686×, which agree with predictions of the analytical model. PMID:21765612

Processes in the Resolution of Ambiguous Words: Towards a Model of Selective Inhibition. Cognitive Science Program, Technical Report No. 86-6.

ERIC Educational Resources Information Center

Yee, Penny L.

This study investigates the role of specific inhibitory processes in lexical ambiguity resolution. An attentional view of inhibition and a view based on specific automatic inhibition between nodes predict different results when a neutral item is processed between an ambiguous word and a related target. Subjects were 32 English speakers with normal…

A model for predicting field-directed particle transport in the magnetofection process.

PubMed

Furlani, Edward P; Xue, Xiaozheng

2012-05-01

To analyze the magnetofection process in which magnetic carrier particles with surface-bound gene vectors are attracted to target cells for transfection using an external magnetic field and to obtain a fundamental understanding of the impact of key factors such as particle size and field strength on the gene delivery process. A numerical model is used to study the field-directed transport of the carrier particle-gene vector complex to target cells in a conventional multiwell culture plate system. The model predicts the transport dynamics and the distribution of particle accumulation at the target cells. The impact of several factors that strongly influence gene vector delivery is assessed including the properties of the carrier particles, the strength of the field source, and its extent and proximity relative to the target cells. The study demonstrates that modeling can be used to predict and optimize gene vector delivery in the magnetofection process for novel and conventional in vitro systems.

Development and validation of the trait and state versions of the Post-Event Processing Inventory.

PubMed

Blackie, Rebecca A; Kocovski, Nancy L

2017-03-01

Post-event processing (PEP) refers to negative and prolonged rumination following anxiety-provoking social situations. Although there are scales to assess PEP, they are situation-specific, some targeting only public-speaking situations. Furthermore, there are no trait measures to assess the tendency to engage in PEP. The purpose of this research was to create a new measure of PEP, the Post-Event Processing Inventory (PEPI), which can be employed following all types of social situations and includes both trait and state forms. Over two studies (study 1, N = 220; study 2, N = 199), we explored and confirmed the factor structure of the scale with student samples. For each form of the scale, we found and confirmed that a higher-order, general PEP factor could be inferred from three sub-domains (intensity, frequency, and self-judgment). We also found preliminary evidence for the convergent, concurrent, discriminant/divergent, incremental, and predictive validity for each version of the scale. Both forms of the scale demonstrated excellent internal consistency and the trait form had excellent two-week test-retest reliability. Given the utility and versatility of the scale, the PEPI may provide a useful alternative to existing measures of PEP and rumination.

Spatial Bayesian latent factor regression modeling of coordinate-based meta-analysis data.

PubMed

Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D; Nichols, Thomas E

2018-03-01

Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the article are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to (i) identify areas of consistent activation; and (ii) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterized as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. © 2017, The International Biometric Society.

A data-driven network model of primary myelofibrosis: transcriptional and post-transcriptional alterations in CD34+ cells.

PubMed

Calura, E; Pizzini, S; Bisognin, A; Coppe, A; Sales, G; Gaffo, E; Fanelli, T; Mannarelli, C; Zini, R; Norfo, R; Pennucci, V; Manfredini, R; Romualdi, C; Guglielmelli, P; Vannucchi, A M; Bortoluzzi, S

2016-06-24

microRNAs (miRNAs) are relevant in the pathogenesis of primary myelofibrosis (PMF) but our understanding is limited to specific target genes and the overall systemic scenario islacking. By both knowledge-based and ab initio approaches for comparative analysis of CD34+ cells of PMF patients and healthy controls, we identified the deregulated pathways involving miRNAs and genes and new transcriptional and post-transcriptional regulatory circuits in PMF cells. These converge in a unique and integrated cellular process, in which the role of specific miRNAs is to wire, co-regulate and allow a fine crosstalk between the involved processes. The PMF pathway includes Akt signaling, linked to Rho GTPases, CDC42, PLD2, PTEN crosstalk with the hypoxia response and Calcium-linked cellular processes connected to cyclic AMP signaling. Nested on the depicted transcriptional scenario, predicted circuits are reported, opening new hypotheses. Links between miRNAs (miR-106a-5p, miR-20b-5p, miR-20a-5p, miR-17-5p, miR-19b-3p and let-7d-5p) and key transcription factors (MYCN, ATF, CEBPA, REL, IRF and FOXJ2) and their common target genes tantalizingly suggest new path to approach the disease. The study provides a global overview of transcriptional and post-transcriptional deregulations in PMF, and, unifying consolidated and predicted data, could be helpful to identify new combinatorial therapeutic strategy. Interactive PMF network model: http://compgen.bio.unipd.it/pmf-net/.

An Elevated Maternal Plasma Soluble fms-Like Tyrosine Kinase-1 to Placental Growth Factor Ratio at Midtrimester Is a Useful Predictor for Preeclampsia.

PubMed

Hassan, Mahmoud Fathy; Rund, Nancy Mohamed Ali; Salama, Ahmed Husseiny

2013-01-01

Background. To assess the ability of mid-trimester sFlt-1/PlGF ratio for prediction of preeclampsia in two different Arabic populations. Methods. This study measured levels of sFlt-1, PlGF, and sFlt-1/PlGF ratio at midtrimester in 83 patients who developed preeclampsia with contemporary 250 matched controls. Results. Women subsequently developed preeclampsia had significantly lower PlGF levels and higher sFlt-1 and sFlt-1/PlGF ratio levels than women with normal pregnancies (P < 0.0001 for all). Women who with preterm preeclampsia had significantly higher sFlt-1 and sFlt-1/PlGF ratio than term preeclamptic women (P = 0.01, 0.003, resp.). A cutoff value of 3198 pg/mL for sFlt-1 was able to predict preeclampsia with sensitivity, specificity, and accuracy of 88%, 83.6%, and 84.7%, respectively, with odds ratio (OR) 37.2 [95% confidence interval (CI) 17.7-78.1]. PIGF at cutoff value of 138 pg/mL was able to predict preeclampsia with sensitivity, specificity, and accuracy of 85.5%, 77.2%, and 79.3%, respectively, with OR 20 [95% CI, 10.2-39.5]. The sFlt-1/PIGF ratio at cutoff value of 24.5 was able to predict preeclampsia with sensitivity, specificity, and accuracy of 91.6%, 86.4%, and 87.7%, respectively with OR 67 [95% CI, 29.3-162.1]. Conclusion. Midtrimester sFlt-1/PlGF ratio displayed the highest sensitivity, specificity, accuracy, and OR for prediction of preeclampsia, demonstrating that it may stipulate more effective prediction of preeclampsia development than individual factor assay.

Assessment of left atrial appendage function by transthoracic pulsed Doppler echocardiography: Comparing against transesophageal interrogation and predicting echocardiographic risk factors for stroke.

PubMed

Wai, Shin Hnin; Kyu, Kyu; Galupo, Mary Joyce; Songco, Geronica G; Kong, William K F; Lee, Chi Hang; Yeo, Tiong Cheng; Poh, Kian Keong

2017-10-01

Transesophageal echocardiographic (TEE) findings of left atrial appendage (LAA) thrombus, spontaneous echo contrast (SEC), and LAA dysfunction are established risk factors of cardioembolic stroke. The semi-invasive nature of TEE limits its utility as a routine risk stratification tool. We aim to correlate TEE and transthoracic echocardiography (TTE) pulsed Doppler measurements of LAA flow velocities and use TTE measurements to predict TEE findings. We prospectively measured pulsed Doppler LAA flow velocities in 103 consecutive patients on TEE and TTE. There was a strong correlation between TEE and TTE LAA emptying velocity (LAA E) (r = .88, P < .001) and a moderate correlation between LAA filling velocities (r = .50, P < .001). TTE LAA E predicted the presence of thrombus or SEC independent of atrial fibrillation (AF). To predict the presence of thrombus or SEC, the optimal TTE LAA E cutoff was ≤30 cm/s in all patients (75% sensitive, 90% specific) and ≤31 cm/s in AF patients (80% sensitive, 79% specific). To predict LAA dysfunction (TEE E ≤ 20 cm/s), the optimal TTE LAA E cutoff was ≤27 cm/s (100% sensitive, 89% specific in all patients and 100% sensitive, 74% specific in AF patients). TTE assessment of LAA function is feasible and correlates well with the more invasive TEE method. It predicts the presence of thrombus, SEC, and LAA dysfunction on TEE. TTE LAA assessment has incremental value in thromboembolic risk stratification and should be utilized more frequently. © 2017, Wiley Periodicals, Inc.

Prediction of winter vitamin D status and requirements in the UK population based on 25(OH) vitamin D half-life and dietary intake data.

PubMed

Schoenmakers, Inez; Gousias, Petros; Jones, Kerry S; Prentice, Ann

2016-11-01

On a population basis, there is a gradual decline in vitamin D status (plasma 25(OH)D) throughout winter. We developed a mathematical model to predict the population winter plasma 25(OH)D concentration longitudinally, using age-specific values for 25(OH)D expenditure (25(OH)D 3 t 1/2 ), cross-sectional plasma 25(OH)D concentration and vitamin D intake (VDI) data from older (70+ years; n=492) and younger adults (18-69 years; n=448) participating in the UK National Diet and Nutrition Survey. From this model, the population VDI required to maintain the mean plasma 25(OH)D at a set concentration can be derived. As expected, both predicted and measured population 25(OH)D (mean (95%CI)) progressively declined from September to March (from 51 (40-61) to 38 (36-41)nmol/L (predicted) vs 38 (27-48)nmol/L (measured) in older people and from 59 (54-65) to 34 (31-37)nmol/L (predicted) vs 37 (31-44)nmol/L (measured) in younger people). The predicted and measured mean values closely matched. The predicted VDIs required to maintain mean winter plasma 25(OH)D at 50nmol/L at the population level were 10 (0-20) to 11 (9-14) and 11 (6-16) to 13(11-16)μg/d for older and younger adults, respectively dependent on the month. In conclusion, a prediction model accounting for 25(OH)D 3 t 1/2 , VDI and scaling factor for the 25(OH)D response to VDI, closely predicts measured population winter values. Refinements of this model may include specific scaling factors accounting for the 25(OH)D response at different VDIs and as influenced by body composition and specific values for 25(OH)D 3 t 1/2 dependent on host factors such as kidney function. This model may help to reduce the need for longitudinal measurements. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Sensitivity Analysis of the Sheet Metal Stamping Processes Based on Inverse Finite Element Modeling and Monte Carlo Simulation

NASA Astrophysics Data System (ADS)

Yu, Maolin; Du, R.

2005-08-01

Sheet metal stamping is one of the most commonly used manufacturing processes, and hence, much research has been carried for economic gain. Searching through the literatures, however, it is found that there are still a lots of problems unsolved. For example, it is well known that for a same press, same workpiece material, and same set of die, the product quality may vary owing to a number of factors, such as the inhomogeneous of the workpice material, the loading error, the lubrication, and etc. Presently, few seem able to predict the quality variation, not to mention what contribute to the quality variation. As a result, trial-and-error is still needed in the shop floor, causing additional cost and time delay. This paper introduces a new approach to predict the product quality variation and identify the sensitive design / process parameters. The new approach is based on a combination of inverse Finite Element Modeling (FEM) and Monte Carlo Simulation (more specifically, the Latin Hypercube Sampling (LHS) approach). With an acceptable accuracy, the inverse FEM (also called one-step FEM) requires much less computation load than that of the usual incremental FEM and hence, can be used to predict the quality variations under various conditions. LHS is a statistical method, through which the sensitivity analysis can be carried out. The result of the sensitivity analysis has clear physical meaning and can be used to optimize the die design and / or the process design. Two simulation examples are presented including drawing a rectangular box and drawing a two-step rectangular box.

How the brain attunes to sentence processing: Relating behavior, structure, and function

PubMed Central

Fengler, Anja; Meyer, Lars; Friederici, Angela D.

2016-01-01

Unlike other aspects of language comprehension, the ability to process complex sentences develops rather late in life. Brain maturation as well as verbal working memory (vWM) expansion have been discussed as possible reasons. To determine the factors contributing to this functional development, we assessed three aspects in different age-groups (5–6 years, 7–8 years, and adults): first, functional brain activity during the processing of increasingly complex sentences; second, brain structure in language-related ROIs; and third, the behavioral comprehension performance on complex sentences and the performance on an independent vWM test. At the whole-brain level, brain functional data revealed a qualitatively similar neural network in children and adults including the left pars opercularis (PO), the left inferior parietal lobe together with the posterior superior temporal gyrus (IPL/pSTG), the supplementary motor area, and the cerebellum. While functional activation of the language-related ROIs PO and IPL/pSTG predicted sentence comprehension performance for all age-groups, only adults showed a functional selectivity in these brain regions with increased activation for more complex sentences. The attunement of both the PO and IPL/pSTG toward a functional selectivity for complex sentences is predicted by region-specific gray matter reduction while that of the IPL/pSTG is additionally predicted by vWM span. Thus, both structural brain maturation and vWM expansion provide the basis for the emergence of functional selectivity in language-related brain regions leading to more efficient sentence processing during development. PMID:26777477

Clinical Significance of Cerebrovascular Biomarkers and White Matter Tract Integrity in Alzheimer Disease: Clinical correlations With Neurobehavioral Data in Cross-Sectional and After 18 Months Follow-ups.

PubMed

Wu, Ming-Kung; Lu, Yan-Ting; Huang, Chi-Wei; Lin, Pin-Hsuan; Chen, Nai-Ching; Lui, Chun-Chung; Chang, Wen-Neng; Lee, Chen-Chang; Chang, Ya-Ting; Chen, Sz-Fan; Chang, Chiung-Chih

2015-07-01

Cerebrovascular risk factors and white matter (WM) damage lead to worse cognitive performance in Alzheimer dementia (AD). This study investigated WM microstructure using diffusion tensor imaging in patients with mild to moderate AD and investigated specific fiber tract involvement with respect to predefined cerebrovascular risk factors and neurobehavioral data prediction cross-sectionally and after 18 months. To identify the primary pathoanatomic relationships of risk biomarkers to fiber tract integrity, we predefined 11 major association tracts and calculated tract specific fractional anisotropy (FA) values. Eighty-five patients with AD underwent neurobehavioral assessments including the minimental state examination (MMSE) and 12-item neuropsychiatric inventory twice with a 1.5-year interval to represent major outcome factors. In the cross-sectional data, total cholesterol, low-density lipoprotein, vitamin B12, and homocysteine levels correlated variably with WM FA values. After entering the biomarkers and WM FA into a regression model to predict neurobehavioral outcomes, only fiber tract FA or homocysteine level predicted the MMSE score, and fiber tract FA or age predicted the neuropsychiatric inventory total scores and subdomains of apathy, disinhibition, and aberrant motor behavior. In the follow-up neurobehavioral data, the mean global FA value predicted the MMSE and aberrant motor behavior subdomain, while age predicted the anxiety and elation subdomains. Cerebrovascular risk biomarkers may modify WM microstructural organization, while the association with fiber integrity showed greater clinical significance to the prediction of neurobehavioral outcomes both cross-sectionally and longitudinally.

Prognostic factors for specific lower extremity and spinal musculoskeletal injuries identified through medical screening and training load monitoring in professional football (soccer): a systematic review

PubMed Central

Sergeant, Jamie C; Parkes, Matthew J; Callaghan, Michael J

2017-01-01

Background Medical screening and load monitoring procedures are commonly used in professional football to assess factors perceived to be associated with injury. Objectives To identify prognostic factors (PFs) and models for lower extremity and spinal musculoskeletal injuries in professional/elite football players from medical screening and training load monitoring processes. Methods The MEDLINE, AMED, EMBASE, CINAHL Plus, SPORTDiscus and PubMed electronic bibliographic databases were searched (from inception to January 2017). Prospective and retrospective cohort studies of lower extremity and spinal musculoskeletal injury incidence in professional/elite football players aged between 16 and 40 years were included. The Quality in Prognostic Studies appraisal tool and the modified Grading of Recommendations Assessment, Development and Evaluation synthesis approach was used to assess the quality of the evidence. Results Fourteen studies were included. 16 specific lower extremity injury outcomes were identified. No spinal injury outcomes were identified. Meta-analysis was not possible due to heterogeneity and study quality. All evidence related to PFs and specific lower extremity injury outcomes was of very low to low quality. On the few occasions where multiple studies could be used to compare PFs and outcomes, only two factors demonstrated consensus. A history of previous hamstring injuries (HSI) and increasing age may be prognostic for future HSI in male players. Conclusions The assumed ability of medical screening tests to predict specific musculoskeletal injuries is not supported by the current evidence. Screening procedures should currently be considered as benchmarks of function or performance only. The prognostic value of load monitoring modalities is unknown. PMID:29177074

Communication Efficacy and Couples’ Cancer Management: Applying a Dyadic Appraisal Model

PubMed Central

Magsamen-Conrad, Kate; Checton, Maria G.; Venetis, Maria K.; Greene, Kathryn

2014-01-01

The purpose of the present study was to apply Berg and Upchurch’s (2007) developmental-conceptual model to understand better how couples cope with cancer. Specifically, we hypothesized a dyadic appraisal model in which proximal factors (relational quality), dyadic appraisal (prognosis uncertainty), and dyadic coping (communication efficacy) predicted adjustment (cancer management). The study was cross-sectional and included 83 dyads in which one partner had been diagnosed with and/or treated for cancer. For both patients and partners, multilevel analyses using the actor-partner interdependence model (APIM) indicated that proximal contextual factors predicted dyadic appraisal and dyadic coping. Dyadic appraisal predicted dyadic coping, which then predicted dyadic adjustment. Patients’ confidence in their ability to talk about the cancer predicted their own cancer management. Partners’ confidence predicted their own and the patient’s ability to cope with cancer, which then predicted patients’ perceptions of their general health. Implications and future research are discussed. PMID:25983382

Communication Efficacy and Couples' Cancer Management: Applying a Dyadic Appraisal Model.

PubMed

Magsamen-Conrad, Kate; Checton, Maria G; Venetis, Maria K; Greene, Kathryn

2015-06-01

The purpose of the present study was to apply Berg and Upchurch's (2007) developmental-conceptual model to understand better how couples cope with cancer. Specifically, we hypothesized a dyadic appraisal model in which proximal factors (relational quality), dyadic appraisal (prognosis uncertainty), and dyadic coping (communication efficacy) predicted adjustment (cancer management). The study was cross-sectional and included 83 dyads in which one partner had been diagnosed with and/or treated for cancer. For both patients and partners, multilevel analyses using the actor-partner interdependence model (APIM) indicated that proximal contextual factors predicted dyadic appraisal and dyadic coping. Dyadic appraisal predicted dyadic coping, which then predicted dyadic adjustment. Patients' confidence in their ability to talk about the cancer predicted their own cancer management. Partners' confidence predicted their own and the patient's ability to cope with cancer, which then predicted patients' perceptions of their general health. Implications and future research are discussed.

A Subject-Specific Kinematic Model to Predict Human Motion in Exoskeleton-Assisted Gait.

PubMed

Torricelli, Diego; Cortés, Camilo; Lete, Nerea; Bertelsen, Álvaro; Gonzalez-Vargas, Jose E; Del-Ama, Antonio J; Dimbwadyo, Iris; Moreno, Juan C; Florez, Julian; Pons, Jose L

2018-01-01

The relative motion between human and exoskeleton is a crucial factor that has remarkable consequences on the efficiency, reliability and safety of human-robot interaction. Unfortunately, its quantitative assessment has been largely overlooked in the literature. Here, we present a methodology that allows predicting the motion of the human joints from the knowledge of the angular motion of the exoskeleton frame. Our method combines a subject-specific skeletal model with a kinematic model of a lower limb exoskeleton (H2, Technaid), imposing specific kinematic constraints between them. To calibrate the model and validate its ability to predict the relative motion in a subject-specific way, we performed experiments on seven healthy subjects during treadmill walking tasks. We demonstrate a prediction accuracy lower than 3.5° globally, and around 1.5° at the hip level, which represent an improvement up to 66% compared to the traditional approach assuming no relative motion between the user and the exoskeleton.

A Subject-Specific Kinematic Model to Predict Human Motion in Exoskeleton-Assisted Gait

PubMed Central

Torricelli, Diego; Cortés, Camilo; Lete, Nerea; Bertelsen, Álvaro; Gonzalez-Vargas, Jose E.; del-Ama, Antonio J.; Dimbwadyo, Iris; Moreno, Juan C.; Florez, Julian; Pons, Jose L.

2018-01-01

The relative motion between human and exoskeleton is a crucial factor that has remarkable consequences on the efficiency, reliability and safety of human-robot interaction. Unfortunately, its quantitative assessment has been largely overlooked in the literature. Here, we present a methodology that allows predicting the motion of the human joints from the knowledge of the angular motion of the exoskeleton frame. Our method combines a subject-specific skeletal model with a kinematic model of a lower limb exoskeleton (H2, Technaid), imposing specific kinematic constraints between them. To calibrate the model and validate its ability to predict the relative motion in a subject-specific way, we performed experiments on seven healthy subjects during treadmill walking tasks. We demonstrate a prediction accuracy lower than 3.5° globally, and around 1.5° at the hip level, which represent an improvement up to 66% compared to the traditional approach assuming no relative motion between the user and the exoskeleton. PMID:29755336

Estimating drought risk across Europe from reported drought impacts, hazard indicators and vulnerability factors

NASA Astrophysics Data System (ADS)

Blauhut, V.; Stahl, K.; Stagge, J. H.; Tallaksen, L. M.; De Stefano, L.; Vogt, J.

2015-12-01

Drought is one of the most costly natural hazards in Europe. Due to its complexity, drought risk, the combination of the natural hazard and societal vulnerability, is difficult to define and challenging to detect and predict, as the impacts of drought are very diverse, covering the breadth of socioeconomic and environmental systems. Pan-European maps of drought risk could inform the elaboration of guidelines and policies to address its documented severity and impact across borders. This work (1) tests the capability of commonly applied hazard indicators and vulnerability factors to predict annual drought impact occurrence for different sectors and macro regions in Europe and (2) combines information on past drought impacts, drought hazard indicators, and vulnerability factors into estimates of drought risk at the pan-European scale. This "hybrid approach" bridges the gap between traditional vulnerability assessment and probabilistic impact forecast in a statistical modelling framework. Multivariable logistic regression was applied to predict the likelihood of impact occurrence on an annual basis for particular impact categories and European macro regions. The results indicate sector- and macro region specific sensitivities of hazard indicators, with the Standardised Precipitation Evapotranspiration Index for a twelve month aggregation period (SPEI-12) as the overall best hazard predictor. Vulnerability factors have only limited ability to predict drought impacts as single predictor, with information about landuse and water resources as best vulnerability-based predictors. (3) The application of the "hybrid approach" revealed strong regional (NUTS combo level) and sector specific differences in drought risk across Europe. The majority of best predictor combinations rely on a combination of SPEI for shorter and longer aggregation periods, and a combination of information on landuse and water resources. The added value of integrating regional vulnerability information with drought risk prediction could be proven. Thus, the study contributes to the overall understanding of drivers of drought impacts, current practice of drought indicators selection for specific application, and drought risk assessment.

[A prediction model for internet game addiction in adolescents: using a decision tree analysis].

PubMed

Kim, Ki Sook; Kim, Kyung Hee

2010-06-01

This study was designed to build a theoretical frame to provide practical help to prevent and manage adolescent internet game addiction by developing a prediction model through a comprehensive analysis of related factors. The participants were 1,318 students studying in elementary, middle, and high schools in Seoul and Gyeonggi Province, Korea. Collected data were analyzed using the SPSS program. Decision Tree Analysis using the Clementine program was applied to build an optimum and significant prediction model to predict internet game addiction related to various factors, especially parent related factors. From the data analyses, the prediction model for factors related to internet game addiction presented with 5 pathways. Causative factors included gender, type of school, siblings, economic status, religion, time spent alone, gaming place, payment to Internet café, frequency, duration, parent's ability to use internet, occupation (mother), trust (father), expectations regarding adolescent's study (mother), supervising (both parents), rearing attitude (both parents). The results suggest preventive and managerial nursing programs for specific groups by path. Use of this predictive model can expand the role of school nurses, not only in counseling addicted adolescents but also, in developing and carrying out programs with parents and approaching adolescents individually through databases and computer programming.

Perceptual Processing Affects Conceptual Processing

ERIC Educational Resources Information Center

van Dantzig, Saskia; Pecher, Diane; Zeelenberg, Rene; Barsalou, Lawrence W.

2008-01-01

According to the Perceptual Symbols Theory of cognition (Barsalou, 1999), modality-specific simulations underlie the representation of concepts. A strong prediction of this view is that perceptual processing affects conceptual processing. In this study, participants performed a perceptual detection task and a conceptual property-verification task…

Adolescent eating disorder behaviours and cognitions: gender-specific effects of child, maternal and family risk factors

PubMed Central

Micali, N.; De Stavola, B.; Ploubidis, G.; Simonoff, E.; Treasure, J.; Field, A. E.

2015-01-01

Background Eating disorder behaviours begin in adolescence. Few longitudinal studies have investigated childhood risk and protective factors. Aims To investigate the prevalence of eating disorder behaviours and cognitions and associated childhood psychological, physical and parental risk factors among a cohort of 14-year-old children. Method Data were collected from 6140 boys and girls aged 14 years. Gender-stratified models were used to estimate prospective associations between childhood body dissatisfaction, body mass index (BMI), self-esteem, maternal eating disorder and family economic disadvantage on adolescent eating disorder behaviours and cognitions. Results Childhood body dissatisfaction strongly predicted eating disorder cognitions in girls, but only in interaction with BMI in boys. Higher self-esteem had a protective effect, particularly in boys. Maternal eating disorder predicted body dissatisfaction and weight/shape concern in adolescent girls and dieting in boys. Conclusions Risk factors for eating disorder behaviours and cognitions vary according to gender. Prevention strategies should be gender-specific and target modifiable predictors in childhood and early adolescence. PMID:26206865

Working alliance and empathy as mediators of brief telephone counseling for cigarette smokers who are not ready to quit

PubMed Central

Klemperer, Elias M.; Hughes, John R.; Callas, Peter W.; Solomon, Laura J.

2016-01-01

Working alliance and empathy are believed to be important components of counseling, though few studies have empirically tested this. We recently conducted a randomized controlled trial in which brief motivational and reduction counseling failed to increase the number of participants who made a quit attempt (QA) in comparison to usual care (i.e., brief advice to quit). Our negative findings could have been due to non-specific factors. This secondary analysis used a subset of participants (n=347) to test a) whether, in comparison to usual care, brief telephone-based motivational or reduction counseling predicted greater working alliance or empathy, b) whether changes in these non-specific factors predicted an increased probability of a QA at a 6-month follow-up, and c) whether counseling affected the probability of a QA via working alliance or empathy (i.e., mediation). Findings were similar for both active counseling conditions (motivational and reduction) vs usual care. In comparison to usual care, active counseling predicted greater working alliance (p<.001) and empathy (p<.05). Greater working alliance predicted a greater probability of a QA (p<.001) but, surprisingly, greater empathy predicted a decreased probability of a QA (p<.05) at the 6-month follow-up. Both working alliance (p<.001) and empathy (p<.05) mediated the active counseling's effects on the probability of a QA. One explanation for our motivational and reduction interventions' failure to influence QAs in comparison to usual care is that working alliance and empathy had opposing effects on quitting. Our analyses illustrate how testing non-specific factors as mediators can help explain why a treatment failed. PMID:28165273

Treatment default amongst patients with tuberculosis in urban Morocco: predicting and explaining default and post-default sputum smear and drug susceptibility results.

PubMed

Cherkaoui, Imad; Sabouni, Radia; Ghali, Iraqi; Kizub, Darya; Billioux, Alexander C; Bennani, Kenza; Bourkadi, Jamal Eddine; Benmamoun, Abderrahmane; Lahlou, Ouafae; Aouad, Rajae El; Dooley, Kelly E

2014-01-01

Public tuberculosis (TB) clinics in urban Morocco. Explore risk factors for TB treatment default and develop a prediction tool. Assess consequences of default, specifically risk for transmission or development of drug resistance. Case-control study comparing patients who defaulted from TB treatment and patients who completed it using quantitative methods and open-ended questions. Results were interpreted in light of health professionals' perspectives from a parallel study. A predictive model and simple tool to identify patients at high risk of default were developed. Sputum from cases with pulmonary TB was collected for smear and drug susceptibility testing. 91 cases and 186 controls enrolled. Independent risk factors for default included current smoking, retreatment, work interference with adherence, daily directly observed therapy, side effects, quick symptom resolution, and not knowing one's treatment duration. Age >50 years, never smoking, and having friends who knew one's diagnosis were protective. A simple scoring tool incorporating these factors was 82.4% sensitive and 87.6% specific for predicting default in this population. Clinicians and patients described additional contributors to default and suggested locally-relevant intervention targets. Among 89 cases with pulmonary TB, 71% had sputum that was smear positive for TB. Drug resistance was rare. The causes of default from TB treatment were explored through synthesis of qualitative and quantitative data from patients and health professionals. A scoring tool with high sensitivity and specificity to predict default was developed. Prospective evaluation of this tool coupled with targeted interventions based on our findings is warranted. Of note, the risk of TB transmission from patients who default treatment to others is likely to be high. The commonly-feared risk of drug resistance, though, may be low; a larger study is required to confirm these findings.

Specificity Determinants of Proteolytic Processing of Aspergillus PacC Transcription Factor Are Remote from the Processing Site, and Processing Occurs in Yeast If pH Signalling Is Bypassed

PubMed Central

Mingot, José-Manuel; Tilburn, Joan; Diez, Eliecer; Bignell, Elaine; Orejas, Margarita; Widdick, David A.; Sarkar, Sovan; Brown, Christopher V.; Caddick, Mark X.; Espeso, Eduardo A.; Arst, Herbert N.; Peñalva, Miguel A.

1999-01-01

The Aspergillus nidulans transcription factor PacC, which mediates pH regulation, is proteolytically processed to a functional form in response to ambient alkaline pH. The full-length PacC form is unstable in the presence of an operational pH signal transduction pathway, due to processing to the relatively stable short functional form. We have characterized and used an extensive collection of pacC mutations, including a novel class of “neutrality-mimicking” pacC mutations having aspects of both acidity- and alkalinity-mimicking phenotypes, to investigate a number of important features of PacC processing. Analysis of mutant proteins lacking the major translation initiation residue or truncated at various distances from the C terminus showed that PacC processing does not remove N-terminal residues, indicated that processing yields slightly heterogeneous products, and delimited the most upstream processing site to residues ∼252 to 254. Faithful processing of three mutant proteins having deletions of a region including the predicted processing site(s) and of a fourth having 55 frameshifted residues following residue 238 indicated that specificity determinants reside at sequences or structural features located upstream of residue 235. Thus, the PacC protease cuts a peptide bond(s) remote from these determinants, possibly thereby resembling type I endonucleases. Downstream of the cleavage site, residues 407 to 678 are not essential for processing, but truncation at or before residue 333 largely prevents it. Ambient pH apparently regulates the accessibility of PacC to proteolytic processing. Alkalinity-mimicking mutations L259R, L266F, and L340S favor the protease-accessible conformation, whereas a protein with residues 465 to 540 deleted retains a protease-inaccessible conformation, leading to acidity mimicry. Finally, not only does processing constitute a crucial form of modulation for PacC, but there is evidence for its conservation during fungal evolution. Transgenic expression of a truncated PacC protein, which was processed in a pH-independent manner, showed that appropriate processing can occur in Saccharomyces cerevisiae. PMID:9891072

Tetanus toxoid IgE may be useful in predicting allergy during childhood.

PubMed

Ciprandi, G; De Amici, M; Quaglini, S; Labò, E; Castellazzi, A M; Miraglia Del Giudice, M; Marseglia, A; Bianchi, L; Moratti, R; Marseglia, G L

2012-01-01

Hypersensitivity reactions after immunization with tetanus toxoid are occasionally observed in atopic and non-atopic individuals. High IgE levels in infancy may predict subsequent allergy. The aims of this study were: i) to evaluate the role of specific IgE to tetanus toxoid in children in response to tetanus immunization and the possible factors associated with specific IgE levels, and ii) to investigate the correlation between specific IgE levels to tetanus toxoid and the late development of allergy (up to 12 years). Initially, 278 healthy infants (152 males and 126 females, aged 12 months) living in an urban city were screened for serum total IgE and specific IgE to tetanus toxoid, after having obtained informed consent from parents. After 12 years, 151 children could be evaluated. Total IgE summed with tetanus specific IgE were significantly associated with allergy at 12 years. In conclusion, this study demonstrates that serum total IgE and tetanus specific IgE may be predictive of subsequent allergy onset.

Progressive and Regressive Developmental Changes in Neural Substrates for Face Processing: Testing Specific Predictions of the Interactive Specialization Account

ERIC Educational Resources Information Center

Joseph, Jane E.; Gathers, Ann D.; Bhatt, Ramesh S.

2011-01-01

Face processing undergoes a fairly protracted developmental time course but the neural underpinnings are not well understood. Prior fMRI studies have only examined progressive changes (i.e. increases in specialization in certain regions with age), which would be predicted by both the Interactive Specialization (IS) and maturational theories of…

Identifying potential dropouts from college physics classes

NASA Astrophysics Data System (ADS)

Wollman, Warren; Lawrenz, Frances

Hudson and Rottman (1981) established that mathematics ability is probably a secondary factor influencing dropout from college physics courses. Other factors remain to be found for predicting who will drop out or at least have difficulty with the course. When mathematics ability is coupled with general indicators of performance (total GPA and ACT natural science), prediction of performance for those who complete the course is substantially improved. Moreover, discriminant analyses reveal who will have at least some difficulty, but not who will drop out. The problem of isolating specific weaknesses of students who have difficulty persists. Physics achievement appears to depend on mathematics ability only to the extent that students possess the ability to utilize mathematics knowledge for solving physics problems. Identification of the specific aspects of this ability as well as the specific deficiencies leading to dropout should be the object of future research. For the present, interviews might be more revealing than group testing methods.

Prediction of soil urea conversion and quantification of the importance degrees of influencing factors through a new combinatorial model based on cluster method and artificial neural network.

PubMed

Lei, Tao; Guo, Xianghong; Sun, Xihuan; Ma, Juanjuan; Zhang, Shaowen; Zhang, Yong

2018-05-01

Quantitative prediction of soil urea conversion is crucial in determining the mechanism of nitrogen transformation and understanding the dynamics of soil nutrients. This study aimed to establish a combinatorial prediction model (MCA-F-ANN) for soil urea conversion and quantify the relative importance degrees (RIDs) of influencing factors with the MCA-F-ANN method. Data samples were obtained from laboratory culture experiments, and soil nitrogen content and physicochemical properties were measured every other day. Results showed that when MCA-F-ANN was used, the mean-absolute-percent error values of NH 4 + -N, NO 3 - -N, and NH 3 contents were 3.180%, 2.756%, and 3.656%, respectively. MCA-F-ANN predicted urea transformation under multi-factor coupling conditions more accurately than traditional models did. The RIDs of reaction time (RT), electrical conductivity (EC), temperature (T), pH, nitrogen application rate (F), and moisture content (W) were 32.2%-36.5%, 24.0%-28.9%, 12.8%-15.2%, 9.8%-12.5%, 7.8%-11.0%, and 3.5%-6.0%, respectively. The RIDs of the influencing factors in a descending order showed the pattern RT > EC > T > pH > F > W. RT and EC were the key factors in the urea conversion process. The prediction accuracy of urea transformation process was improved, and the RIDs of the influencing factors were quantified. Copyright © 2018 Elsevier Ltd. All rights reserved.

Nonrandom community assembly and high temporal turnover promote regional coexistence in tropics but not temperate zone.

PubMed

Freestone, Amy L; Inouye, Brian D

2015-01-01

A persistent challenge for ecologists is understanding the ecological mechanisms that maintain global patterns of biodiversity, particularly the latitudinal diversity gradient of peak species richness in the tropics. Spatial and temporal variation in community composition contribute to these patterns of biodiversity, but how this variation and its underlying processes change across latitude remains unresolved. Using a model system of sessile marine invertebrates across 25 degrees of latitude, from the temperate zone to the tropics, we tested the prediction that spatial and temporal patterns of taxonomic richness and composition, and the community assembly processes underlying these patterns, will differ across latitude. Specifically, we predicted that high beta diversity (spatial variation in composition) and high temporal turnover contribute to the high species richness of the tropics. Using a standardized experimental approach that controls for several confounding factors that hinder interpretation of prior studies, we present results that support our predictions. In the temperate zone, communities were more similar across spatial scales from centimeters to tens of kilometers and temporal scales up to one year than at lower latitudes. Since the patterns at northern latitudes were congruent with a null model, stochastic assembly processes are implicated. In contrast, the communities in the tropics were a dynamic spatial and temporal mosaic, with low similarity even across small spatial scales and high temporal turnover at both local and regional scales. Unlike the temperate zone, deterministic community assembly processes such as predation likely contributed to the high beta diversity in the tropics. Our results suggest that community assembly processes and temporal dynamics vary across latitude and help structure and maintain latitudinal patterns of diversity.

Reading Behind the Lines: The Factors Affecting the Text Reception Threshold in Hearing Aid Users.

PubMed

Zekveld, Adriana A; Pronk, Marieke; Danielsson, Henrik; Rönnberg, Jerker

2018-03-15

The visual Text Reception Threshold (TRT) test (Zekveld et al., 2007) has been designed to assess modality-general factors relevant for speech perception in noise. In the last decade, the test has been adopted in audiology labs worldwide. The 1st aim of this study was to examine which factors best predict interindividual differences in the TRT. Second, we aimed to assess the relationships between the TRT and the speech reception thresholds (SRTs) estimated in various conditions. First, we reviewed studies reporting relationships between the TRT and the auditory and/or cognitive factors and formulated specific hypotheses regarding the TRT predictors. These hypotheses were tested using a prediction model applied to a rich data set of 180 hearing aid users. In separate association models, we tested the relationships between the TRT and the various SRTs and subjective hearing difficulties, while taking into account potential confounding variables. The results of the prediction model indicate that the TRT is predicted by the ability to fill in missing words in incomplete sentences, by lexical access speed, and by working memory capacity. Furthermore, in line with previous studies, a moderate association between higher age, poorer pure-tone hearing acuity, and poorer TRTs was observed. Better TRTs were associated with better SRTs for the correct perception of 50% of Hagerman matrix sentences in a 4-talker babble, as well as with better subjective ratings of speech perception. Age and pure-tone hearing thresholds significantly confounded these associations. The associations of the TRT with SRTs estimated in other conditions and with subjective qualities of hearing were not statistically significant when adjusting for age and pure-tone average. We conclude that the abilities tapped into by the TRT test include processes relevant for speeded lexical decision making when completing partly masked sentences and that these processes require working memory capacity. Furthermore, the TRT is associated with the SRT of hearing aid users as estimated in a challenging condition that includes informational masking and with experienced difficulties with speech perception in daily-life conditions. The current results underline the value of using the TRT test in studies involving speech perception and aid in the interpretation of findings acquired using the test.

The effects of Wechsler Intelligence Scale for Children-Fourth Edition cognitive abilities on math achievement.

PubMed

Parkin, Jason R; Beaujean, A Alexander

2012-02-01

This study used structural equation modeling to examine the effect of Stratum III (i.e., general intelligence) and Stratum II (i.e., Comprehension-Knowledge, Fluid Reasoning, Short-Term Memory, Processing Speed, and Visual Processing) factors of the Cattell-Horn-Carroll (CHC) cognitive abilities, as operationalized by the Wechsler Intelligence Scale for Children, Fourth Edition (WISC-IV; Wechsler, 2003a) subtests, on Quantitative Knowledge, as operationalized by the Wechsler Individual Achievement Test, Second Edition (WIAT-II; Wechsler, 2002) subtests. Participants came from the WISC-IV/WIAT-II linking sample (n=550). We compared models that predicted Quantitative Knowledge using only Stratum III factors, only Stratum II factors, and both Stratum III and Stratum II factors. Results indicated that the model with only the Stratum III factor predicting Quantitative Knowledge best fit the data. Copyright © 2011 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Increasing organizational energy conservation behaviors: Comparing the theory of planned behavior and reasons theory for identifying specific motivational factors to target for change

NASA Astrophysics Data System (ADS)

Finlinson, Scott Michael

Social scientists frequently assess factors thought to underlie behavior for the purpose of designing behavioral change interventions. Researchers commonly identify these factors by examining relationships between specific variables and the focal behaviors being investigated. Variables with the strongest relationships to the focal behavior are then assumed to be the most influential determinants of that behavior, and therefore often become the targets for change in a behavioral change intervention. In the current proposal, multiple methods are used to compare the effectiveness of two theoretical frameworks for identifying influential motivational factors. Assessing the relative influence of all factors and sets of factors for driving behavior should clarify which framework and methodology is the most promising for identifying effective change targets. Results indicated each methodology adequately predicted the three focal behaviors examined. However, the reasons theory approach was superior for predicting factor influence ratings compared to the TpB approach. While common method variance contamination had minimal impact on the results or conclusions derived from the present study's findings, there were substantial differences in conclusions depending on the questionnaire design used to collect the data. Examples of applied uses of the present study are discussed.

Predictors and Effects of Knowledge Management in U.S. Colleges and Schools of Pharmacy

NASA Astrophysics Data System (ADS)

Watcharadamrongkun, Suntaree

Public demands for accountability in higher education have placed increasing pressure on institutions to document their achievement of critical outcomes. These demands also have had wide-reaching implications for the development and enforcement of accreditation standards, including those governing pharmacy education. The knowledge management (KM) framework provides perspective for understanding how organizations evaluate themselves and guidance for how to improve their performance. In this study, we explore knowledge management processes, how these processes are affected by organizational structure and by information technology resources, and how these processes affect organizational performance. This is done in the context of Accreditation Standards and Guidelines for the Professional Program in Pharmacy Leading to the Doctor of Pharmacy Degree (Standards 2007). Data were collected using an online census survey of 121 U.S. Colleges and Schools of Pharmacy and supplemented with archival data. A key informant method was used with CEO Deans and Assessment leaders serving as respondents. The survey yielded a 76.0% (92/121) response rate. Exploratory factor analysis was used to construct scales (and scales) describing core KM processes: Knowledge Acquisition, Knowledge Integration, and Institutionalization; all scale reliabilities were found to be acceptable. Analysis showed that, as expected, greater Knowledge Acquisition predicts greater Knowledge Integration and greater Knowledge Integration predicts greater Institutionalization. Predictive models were constructed using hierarchical multiple regression and path analysis. Overall, information technology resources had stronger effects on KM processes than did characteristics of organizational structure. Greater Institutionalization predicted better outcomes related to direct measures of performance (i.e., NAPLEX pass rates, Accreditation actions) but Institutionalization was unrelated to an indirect measure of performance (i.e., USNWR ratings). Several organizational structure characteristics (i.e., size, age, and being part of an academic health center) were significant predictors of organizational performance; in contrast, IT resources had no direct effects on performance. Findings suggest that knowledge management processes, organizational structures and IT resources are related to better performance for Colleges and Schools of Pharmacy. Further research is needed to understand mechanisms through which specific knowledge management processes translate into better performance and, relatedly, to establish how enhancing KM processes can be used to improve institutional quality.

Understanding Transcription Factor Regulation by Integrating Gene Expression and DNase I Hypersensitive Sites.

PubMed

Wang, Guohua; Wang, Fang; Huang, Qian; Li, Yu; Liu, Yunlong; Wang, Yadong

2015-01-01

Transcription factors are proteins that bind to DNA sequences to regulate gene transcription. The transcription factor binding sites are short DNA sequences (5-20 bp long) specifically bound by one or more transcription factors. The identification of transcription factor binding sites and prediction of their function continue to be challenging problems in computational biology. In this study, by integrating the DNase I hypersensitive sites with known position weight matrices in the TRANSFAC database, the transcription factor binding sites in gene regulatory region are identified. Based on the global gene expression patterns in cervical cancer HeLaS3 cell and HelaS3-ifnα4h cell (interferon treatment on HeLaS3 cell for 4 hours), we present a model-based computational approach to predict a set of transcription factors that potentially cause such differential gene expression. Significantly, 6 out 10 predicted functional factors, including IRF, IRF-2, IRF-9, IRF-1 and IRF-3, ICSBP, belong to interferon regulatory factor family and upregulate the gene expression levels responding to the interferon treatment. Another factor, ISGF-3, is also a transcriptional activator induced by interferon alpha. Using the different transcription factor binding sites selected criteria, the prediction result of our model is consistent. Our model demonstrated the potential to computationally identify the functional transcription factors in gene regulation.

Application of GA-SVM method with parameter optimization for landslide development prediction

NASA Astrophysics Data System (ADS)

Li, X. Z.; Kong, J. M.

2013-10-01

Prediction of landslide development process is always a hot issue in landslide research. So far, many methods for landslide displacement series prediction have been proposed. Support vector machine (SVM) has been proved to be a novel algorithm with good performance. However, the performance strongly depends on the right selection of the parameters (C and γ) of SVM model. In this study, we presented an application of GA-SVM method with parameter optimization in landslide displacement rate prediction. We selected a typical large-scale landslide in some hydro - electrical engineering area of Southwest China as a case. On the basis of analyzing the basic characteristics and monitoring data of the landslide, a single-factor GA-SVM model and a multi-factor GA-SVM model of the landslide were built. Moreover, the models were compared with single-factor and multi-factor SVM models of the landslide. The results show that, the four models have high prediction accuracies, but the accuracies of GA-SVM models are slightly higher than those of SVM models and the accuracies of multi-factor models are slightly higher than those of single-factor models for the landslide prediction. The accuracy of the multi-factor GA-SVM models is the highest, with the smallest RSME of 0.0009 and the biggest RI of 0.9992.

A risk-based approach to management of leachables utilizing statistical analysis of extractables.

PubMed

Stults, Cheryl L M; Mikl, Jaromir; Whelehan, Oliver; Morrical, Bradley; Duffield, William; Nagao, Lee M

2015-04-01

To incorporate quality by design concepts into the management of leachables, an emphasis is often put on understanding the extractable profile for the materials of construction for manufacturing disposables, container-closure, or delivery systems. Component manufacturing processes may also impact the extractable profile. An approach was developed to (1) identify critical components that may be sources of leachables, (2) enable an understanding of manufacturing process factors that affect extractable profiles, (3) determine if quantitative models can be developed that predict the effect of those key factors, and (4) evaluate the practical impact of the key factors on the product. A risk evaluation for an inhalation product identified injection molding as a key process. Designed experiments were performed to evaluate the impact of molding process parameters on the extractable profile from an ABS inhaler component. Statistical analysis of the resulting GC chromatographic profiles identified processing factors that were correlated with peak levels in the extractable profiles. The combination of statistically significant molding process parameters was different for different types of extractable compounds. ANOVA models were used to obtain optimal process settings and predict extractable levels for a selected number of compounds. The proposed paradigm may be applied to evaluate the impact of material composition and processing parameters on extractable profiles and utilized to manage product leachables early in the development process and throughout the product lifecycle.

Prediction of non-biochemical recurrence rate after radical prostatectomy in a Japanese cohort: development of a postoperative nomogram.

PubMed

Okubo, Hidenori; Ohori, Makoto; Ohno, Yoshio; Nakashima, Jun; Inoue, Rie; Nagao, Toshitaka; Tachibana, Masaaki

2014-05-01

To develop a nomogram based on postoperative factors and prostate-specific antigen levels to predict the non-biochemical recurrence rate after radical prostatectomy ina Japanese cohort. A total of 606 Japanese patients with T1-3N0M0 prostate cancer who underwent radical prostatectomy and pelvic lymph node dissection at Tokyo Medical University hospital from 2000 to 2010 were studied. A nomogram was constructed based on Cox hazard regression analysis evaluating the prognostic significance of serum prostate-specific antigen and pathological factors in the radical prostatectomy specimens. The discriminating ability of the nomogram was assessed by the concordance index (C-index), and the predicted and actual outcomes were compared with a bootstrapped calibration plot. With a mean follow up of 60.0 months, a total of 187 patients (30.9%) experienced biochemical recurrence, with a 5-year non-biochemical recurrence rate of 72.3%. Based on a Cox hazard regression model, a nomogram was constructed to predict non-biochemical recurrence using serum prostate-specific antigen level and pathological features in radical prostatectomy specimens. The concordance index was 0.77, and the calibration plots appeared to be accurate. The postoperative nomogram described here can provide valuable information regarding the need for adjuvant/salvage radiation or hormonal therapy in patients after radical prostatectomy.

[Predicting the probability of development and progression of primary open angle glaucoma by regression modeling].

PubMed

Likhvantseva, V G; Sokolov, V A; Levanova, O N; Kovelenova, I V

2018-01-01

Prediction of the clinical course of primary open-angle glaucoma (POAG) is one of the main directions in solving the problem of vision loss prevention and stabilization of the pathological process. Simple statistical methods of correlation analysis show the extent of each risk factor's impact, but do not indicate the total impact of these factors in personalized combinations. The relationships between the risk factors is subject to correlation and regression analysis. The regression equation represents the dependence of the mathematical expectation of the resulting sign on the combination of factor signs. To develop a technique for predicting the probability of development and progression of primary open-angle glaucoma based on a personalized combination of risk factors by linear multivariate regression analysis. The study included 66 patients (23 female and 43 male; 132 eyes) with newly diagnosed primary open-angle glaucoma. The control group consisted of 14 patients (8 male and 6 female). Standard ophthalmic examination was supplemented with biochemical study of lacrimal fluid. Concentration of matrix metalloproteinase MMP-2 and MMP-9 in tear fluid in both eyes was determined using 'sandwich' enzyme-linked immunosorbent assay (ELISA) method. The study resulted in the development of regression equations and step-by-step multivariate logistic models that can help calculate the risk of development and progression of POAG. Those models are based on expert evaluation of clinical and instrumental indicators of hydrodynamic disturbances (coefficient of outflow ease - C, volume of intraocular fluid secretion - F, fluctuation of intraocular pressure), as well as personalized morphometric parameters of the retina (central retinal thickness in the macular area) and concentration of MMP-2 and MMP-9 in the tear film. The newly developed regression equations are highly informative and can be a reliable tool for studying of the influence vector and assessment of pathogenic potential of the independent risk factors in specific personalized combinations.

Specific headache factors predict sleep disturbances among youth with migraine.

PubMed

Heyer, Geoffrey L; Rose, Sean C; Merison, Kelsey; Perkins, Sara Q; Lee, Jo Ellen M

2014-10-01

There is a paucity of pediatric data addressing the complex relationship between primary headaches and sleep disturbances. Our study objective was to explore headache-related factors that predict sleep disturbance and to compare sleep complaints with other forms of headache-related disability among youth with migraines. A prospective cohort study was conducted in patients 10-18 years old with migraine or probable migraine and without daily sleep complaints. The patients completed a 90-day internet-based headache diary. On headache days, patients rated headache intensity, answered Pediatric Migraine Disability Assessment-based questions modified for daily scoring, and reported sleep disturbances that resulted as a direct effect of proximate headaches. Fifty-two patients generated 4680 diary entries, 984 patients (21%) involved headaches. Headache intensity (P = 0.009) and timing of headache onset (P < 0.001) were predictive of sleep disturbances. Three Pediatric Migraine Disability Assessment-based items were also associated with sleep disturbances: partial school-day absence (P = 0.04), recreational activities prevented (P < 0.001), and decreased functioning during recreational activities (P < 0.001). Sleep disturbances correlated positively and significantly with daily headache disability scores (rpb = 0.35; P < 0.01). We conclude that specific headache factors predict sleep disturbances among youth with primary headaches. Copyright © 2014 Elsevier Inc. All rights reserved.

Runoff as a factor in USLE/RUSLE technology

NASA Astrophysics Data System (ADS)

Kinnell, Peter

2014-05-01

Modelling erosion for prediction purposes started with the development of the Universal Soil Loss Equation the focus of which was the prediction of long term (~20) average annul soil loss from field sized areas. That purpose has been maintained in the subsequent revision RUSLE, the most widely used erosion prediction model in the world. The lack of ability to predict short term soil loss saw the development of so-called process based models like WEPP and EUROSEM which focussed on predicting event erosion but failed to improve the prediction of long term erosion where the RUSLE worked well. One of the features of erosion recognised in the so-called process based modes is the fact that runoff is a primary factor in rainfall erosion and some modifications of USLE/RUSLE model have been proposed have included runoff as in independent factor in determining event erosivity. However, these models have ignored fundamental mathematical rules. The USLE-M which replaces the EI30 index by the product of the runoff ratio and EI30 was developed from the concept that soil loss is the product of runoff and sediment concentration and operates in a way that obeys the mathematical rules upon which the USLE/RUSLE model was based. In accounts for event soil loss better that the EI30 index where runoff values are known or predicted adequately. RUSLE2 now includes a capacity to model runoff driven erosion.

Practical approach to subject-specific estimation of knee joint contact force.

PubMed

Knarr, Brian A; Higginson, Jill S

2015-08-20

Compressive forces experienced at the knee can significantly contribute to cartilage degeneration. Musculoskeletal models enable predictions of the internal forces experienced at the knee, but validation is often not possible, as experimental data detailing loading at the knee joint is limited. Recently available data reporting compressive knee force through direct measurement using instrumented total knee replacements offer a unique opportunity to evaluate the accuracy of models. Previous studies have highlighted the importance of subject-specificity in increasing the accuracy of model predictions; however, these techniques may be unrealistic outside of a research setting. Therefore, the goal of our work was to identify a practical approach for accurate prediction of tibiofemoral knee contact force (KCF). Four methods for prediction of knee contact force were compared: (1) standard static optimization, (2) uniform muscle coordination weighting, (3) subject-specific muscle coordination weighting and (4) subject-specific strength adjustments. Walking trials for three subjects with instrumented knee replacements were used to evaluate the accuracy of model predictions. Predictions utilizing subject-specific muscle coordination weighting yielded the best agreement with experimental data; however this method required in vivo data for weighting factor calibration. Including subject-specific strength adjustments improved models' predictions compared to standard static optimization, with errors in peak KCF less than 0.5 body weight for all subjects. Overall, combining clinical assessments of muscle strength with standard tools available in the OpenSim software package, such as inverse kinematics and static optimization, appears to be a practical method for predicting joint contact force that can be implemented for many applications. Copyright © 2015 Elsevier Ltd. All rights reserved.

Practical approach to subject-specific estimation of knee joint contact force

PubMed Central

Knarr, Brian A.; Higginson, Jill S.

2015-01-01

Compressive forces experienced at the knee can significantly contribute to cartilage degeneration. Musculoskeletal models enable predictions of the internal forces experienced at the knee, but validation is often not possible, as experimental data detailing loading at the knee joint is limited. Recently available data reporting compressive knee force through direct measurement using instrumented total knee replacements offer a unique opportunity to evaluate the accuracy of models. Previous studies have highlighted the importance of subject-specificity in increasing the accuracy of model predictions; however, these techniques may be unrealistic outside of a research setting. Therefore, the goal of our work was to identify a practical approach for accurate prediction of tibiofemoral knee contact force (KCF). Four methods for prediction of knee contact force were compared: (1) standard static optimization, (2) uniform muscle coordination weighting, (3) subject-specific muscle coordination weighting and (4) subject-specific strength adjustments. Walking trials for three subjects with instrumented knee replacements were used to evaluate the accuracy of model predictions. Predictions utilizing subject-specific muscle coordination weighting yielded the best agreement with experimental data, however this method required in vivo data for weighting factor calibration. Including subject-specific strength adjustments improved models’ predictions compared to standard static optimization, with errors in peak KCF less than 0.5 body weight for all subjects. Overall, combining clinical assessments of muscle strength with standard tools available in the OpenSim software package, such as inverse kinematics and static optimization, appears to be a practical method for predicting joint contact force that can be implemented for many applications. PMID:25952546

Development of a Liner Design Methodology and Relevant Results of Acoustic Suppression in the Farfield for Mixer-Ejector Nozzles

NASA Technical Reports Server (NTRS)

Salikuddin, M.

2006-01-01

We have developed a process to predict noise field interior to the ejector and in the farfield for any liner design for a mixer-ejector of arbitrary scale factor. However, a number of assumptions, not verified for the current application, utilized in this process, introduce uncertainties in the final result, especially, on a quantitative basis. The normal impedance model for bulk with perforated facesheet is based on homogeneous foam materials of low resistivity. The impact of flow conditions for HSCT application as well as the impact of perforated facesheet on predicted impedance is not properly accounted. Based on the measured normal impedance for deeper bulk samples (i.e., 2.0 in.) the predicted reactance is much higher compared to the data at frequencies above 2 kHz for T-foam and 200 ppi SiC. The resistance is under predicted at lower frequencies (below 4 kHz) for these samples. Thus, the use of such predicted data in acoustic suppression is likely to introduce inaccuracies. It should be noted that the impedance prediction methods developed recently under liner technology program are not utilized in the studies described in this report due to the program closeout. Acoustic suppression prediction is based on the uniform flow and temperature conditions in a two-sided treated constant area rectangular duct. In addition, assumptions of equal energy per mode noise field and interaction of all frequencies with the treated surface for the entire ejector length may not be accurate. While, the use of acoustic transfer factor minimizes the inaccuracies associated with the prediction for a known test case, the assumption of the same factor for other liner designs and with different linear scale factor ejectors seems to be very optimistic. As illustrated in appendix D that the predicted noise suppression for LSM-1 is lower compared to the measured data is an indication of the above argument. However, the process seems to be more reliable when used for the same scale models for different liner designs as demonstrated for Gen. 1 mixer-ejectors.

GPU-based RFA simulation for minimally invasive cancer treatment of liver tumours.

PubMed

Mariappan, Panchatcharam; Weir, Phil; Flanagan, Ronan; Voglreiter, Philip; Alhonnoro, Tuomas; Pollari, Mika; Moche, Michael; Busse, Harald; Futterer, Jurgen; Portugaller, Horst Rupert; Sequeiros, Roberto Blanco; Kolesnik, Marina

2017-01-01

Radiofrequency ablation (RFA) is one of the most popular and well-standardized minimally invasive cancer treatments (MICT) for liver tumours, employed where surgical resection has been contraindicated. Less-experienced interventional radiologists (IRs) require an appropriate planning tool for the treatment to help avoid incomplete treatment and so reduce the tumour recurrence risk. Although a few tools are available to predict the ablation lesion geometry, the process is computationally expensive. Also, in our implementation, a few patient-specific parameters are used to improve the accuracy of the lesion prediction. Advanced heterogeneous computing using personal computers, incorporating the graphics processing unit (GPU) and the central processing unit (CPU), is proposed to predict the ablation lesion geometry. The most recent GPU technology is used to accelerate the finite element approximation of Penne's bioheat equation and a three state cell model. Patient-specific input parameters are used in the bioheat model to improve accuracy of the predicted lesion. A fast GPU-based RFA solver is developed to predict the lesion by doing most of the computational tasks in the GPU, while reserving the CPU for concurrent tasks such as lesion extraction based on the heat deposition at each finite element node. The solver takes less than 3 min for a treatment duration of 26 min. When the model receives patient-specific input parameters, the deviation between real and predicted lesion is below 3 mm. A multi-centre retrospective study indicates that the fast RFA solver is capable of providing the IR with the predicted lesion in the short time period before the intervention begins when the patient has been clinically prepared for the treatment.

[Lightning-caused fire, its affecting factors and prediction: a review].

PubMed

Zhang, Ji-Li; Bi, Wu; Wang, Xiao-Hong; Wang, Zi-Bo; Li, Di-Fei

2013-09-01

Lightning-caused fire is the most important natural fire source. Its induced forest fire brings enormous losses to human beings and ecological environment. Many countries have paid great attention to the prediction of lightning-caused fire. From the viewpoint of the main factors affecting the formation of lightning-caused fire, this paper emphatically analyzed the effects and action mechanisms of cloud-to-ground lightning, fuel, meteorology, and terrain on the formation and development process of lightning-caused fire, and, on the basis of this, summarized and reviewed the logistic model, K-function, and other mathematical methods widely used in prediction research of lightning-caused fire. The prediction methods and processes of lightning-caused fire in America and Canada were also introduced. The insufficiencies and their possible solutions for the present researches as well as the directions of further studies were proposed, aimed to provide necessary theoretical basis and literature reference for the prediction of lightning-caused fire in China.

Biogeochemical Factors Influencing the Transport and Fate of Colloids and Colloid-Associated Contaminants in the Vadose Zone

NASA Astrophysics Data System (ADS)

Bradford, S. A.

2016-12-01

The vadose zone exhibits large spatial and temporal variability in many physical, chemical, and biological factors that strongly influence the transport and fate of colloids (e.g., microbes, nanoparticles, clays, and dissolved organic matter) and colloid-associated contaminants (e.g., heavy metals, radionuclides, pesticides, and antibiotics). This presentation highlights our research activities to better understand and predict the influence of specific biogeochemical processes on colloid and colloid-facilitated transport. Results demonstrate the sensitivity of colloid transport, retention, release, and clogging to transients in solution chemistry (e.g., ionic strength, pH, cation and anion type, and surfactants), water velocity and saturation, and preferential flow. Mathematical modeling at interface-, pore-, and continuum-scales is shown to be a critical tool to quantify the relative importance and coupling of these biogeochemical factors on colloid and contaminant transport and fate, which otherwise might be experimentally intractable. Existing gaps in knowledge and model limitations are identified.

OCT-based deep learning algorithm for the evaluation of treatment indication with anti-vascular endothelial growth factor medications.

PubMed

Prahs, Philipp; Radeck, Viola; Mayer, Christian; Cvetkov, Yordan; Cvetkova, Nadezhda; Helbig, Horst; Märker, David

2018-01-01

Intravitreal injections with anti-vascular endothelial growth factor (anti-VEGF) medications have become the standard of care for their respective indications. Optical coherence tomography (OCT) scans of the central retina provide detailed anatomical data and are widely used by clinicians in the decision-making process of anti-VEGF indication. In recent years, significant progress has been made in artificial intelligence and computer vision research. We trained a deep convolutional artificial neural network to predict treatment indication based on central retinal OCT scans without human intervention. A total of 183,402 retinal OCT B-scans acquired between 2008 and 2016 were exported from the institutional image archive of a university hospital. OCT images were cross-referenced with the electronic institutional intravitreal injection records. OCT images with a following intravitreal injection during the first 21 days after image acquisition were assigned into the 'injection' group, while the same amount of random OCT images without intravitreal injections was labeled as 'no injection'. After image preprocessing, OCT images were split in a 9:1 ratio to training and test datasets. We trained a GoogLeNet inception deep convolutional neural network and assessed its performance on the validation dataset. We calculated prediction accuracy, sensitivity, specificity, and receiver operating characteristics. The deep convolutional neural network was successfully trained on the extracted clinical data. The trained neural network classifier reached a prediction accuracy of 95.5% on the images in the validation dataset. For single retinal B-scans in the validation dataset, a sensitivity of 90.1% and a specificity of 96.2% were achieved. The area under the receiver operating characteristic curve was 0.968 on a per B-scan image basis, and 0.988 by averaging over six B-scans per examination on the validation dataset. Deep artificial neural networks show impressive performance on classification of retinal OCT scans. After training on historical clinical data, machine learning methods can offer the clinician support in the decision-making process. Care should be taken not to mistake neural network output as treatment recommendation and to ensure a final thorough evaluation by the treating physician.

Natural Language Processing for Asthma Ascertainment in Different Practice Settings.

PubMed

Wi, Chung-Il; Sohn, Sunghwan; Ali, Mir; Krusemark, Elizabeth; Ryu, Euijung; Liu, Hongfang; Juhn, Young J

We developed and validated NLP-PAC, a natural language processing (NLP) algorithm based on predetermined asthma criteria (PAC) for asthma ascertainment using electronic health records at Mayo Clinic. To adapt NLP-PAC in a different health care setting, Sanford Children Hospital, by assessing its external validity. The study was designed as a retrospective cohort study that used a random sample of 2011-2012 Sanford Birth cohort (n = 595). Manual chart review was performed on the cohort for asthma ascertainment on the basis of the PAC. We then used half of the cohort as a training cohort (n = 298) and the other half as a blind test cohort to evaluate the adapted NLP-PAC algorithm. Association of known asthma-related risk factors with the Sanford-NLP algorithm-driven asthma ascertainment was tested. Among the eligible test cohort (n = 297), 160 (53%) were males, 268 (90%) white, and the median age was 2.3 years (range, 1.5-3.1 years). NLP-PAC, after adaptation, and the human abstractor identified 74 (25%) and 72 (24%) subjects, respectively, with 66 subjects identified by both approaches. Sensitivity, specificity, positive predictive value, and negative predictive value for the NLP algorithm in predicting asthma status were 92%, 96%, 89%, and 97%, respectively. The known risk factors for asthma identified by NLP (eg, smoking history) were similar to the ones identified by manual chart review. Successful implementation of NLP-PAC for asthma ascertainment in 2 different practice settings demonstrates the feasibility of automated asthma ascertainment leveraging electronic health record data with a potential to enable large-scale, multisite asthma studies to improve asthma care and research. Copyright © 2017 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Emotion perception and executive functioning predict work status in euthymic bipolar disorder.

PubMed

Ryan, Kelly A; Vederman, Aaron C; Kamali, Masoud; Marshall, David; Weldon, Anne L; McInnis, Melvin G; Langenecker, Scott A

2013-12-15

Functional recovery, including return to work, in Bipolar Disorder (BD) lags behind clinical recovery and may be incomplete when acute mood symptoms have subsided. We examined impact of cognition on work status and underemployment in a sample of 156 Euthymic-BD and 143 controls (HC) who were divided into working/not working groups. Clinical, health, social support, and personality data were collected, and eight cognitive factors were derived from a battery of neuropsychological tests. The HC groups outperformed the BD groups on seven of eight cognitive factors. The working-BD group outperformed the not working-BD group on 4 cognitive factors composed of tasks of emotion processing and executive functioning including processing speed and set shifting. Emotion processing and executive tasks were predictive of BD unemployment, after accounting for number of mood episodes. Four cognitive factors accounted for a significant amount of the variance in work status among the BD participants. Results indicate that patients with BD who are unemployed/unable to work exhibit greater difficulties processing emotional information and on executive tasks that comprise a set shifting or interference resolution component as compared to those who are employed, independent of other factors. These cognitive and affective factors are suggested as targets for treatment and/or accommodations. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Strain-specific differences in pili formation and the interaction of Corynebacterium diphtheriae with host cells

PubMed Central

2010-01-01

Background Corynebacterium diphtheriae, the causative agent of diphtheria, is well-investigated in respect to toxin production, while little is known about C. diphtheriae factors crucial for colonization of the host. In this study, we investigated strain-specific differences in adhesion, invasion and intracellular survival and analyzed formation of pili in different isolates. Results Adhesion of different C. diphtheriae strains to epithelial cells and invasion of these cells are not strictly coupled processes. Using ultrastructure analyses by atomic force microscopy, significant differences in macromolecular surface structures were found between the investigated C. diphtheriae strains in respect to number and length of pili. Interestingly, adhesion and pili formation are not coupled processes and also no correlation between invasion and pili formation was found. Using RNA hybridization and Western blotting experiments, strain-specific pili expression patterns were observed. None of the studied C. diphtheriae strains had a dramatic detrimental effect on host cell viability as indicated by measurements of transepithelial resistance of Detroit 562 cell monolayers and fluorescence microscopy, leading to the assumption that C. diphtheriae strains might use epithelial cells as an environmental niche supplying protection against antibodies and macrophages. Conclusions The results obtained suggest that it is necessary to investigate various isolates on a molecular level to understand and to predict the colonization process of different C. diphtheriae strains. PMID:20942914

Neural Network of Predictive Motor Timing in the Context of Gender Differences

PubMed Central

Lošák, Jan; Kašpárek, Tomáš; Vaníček, Jiří; Bareš, Martin

2016-01-01

Time perception is an essential part of our everyday lives, in both the prospective and the retrospective domains. However, our knowledge of temporal processing is mainly limited to the networks responsible for comparing or maintaining specific intervals or frequencies. In the presented fMRI study, we sought to characterize the neural nodes engaged specifically in predictive temporal analysis, the estimation of the future position of an object with varying movement parameters, and the contingent neuroanatomical signature of differences in behavioral performance between genders. The established dominant cerebellar engagement offers novel evidence in favor of a pivotal role of this structure in predictive short-term timing, overshadowing the basal ganglia reported together with the frontal cortex as dominant in retrospective temporal processing in the subsecond spectrum. Furthermore, we discovered lower performance in this task and massively increased cerebellar activity in women compared to men, indicative of strategy differences between the genders. This promotes the view that predictive temporal computing utilizes comparable structures in the retrospective timing processes, but with a definite dominance of the cerebellum. PMID:27019753

Current advances in mathematical modeling of anti-cancer drug penetration into tumor tissues.

PubMed

Kim, Munju; Gillies, Robert J; Rejniak, Katarzyna A

2013-11-18

Delivery of anti-cancer drugs to tumor tissues, including their interstitial transport and cellular uptake, is a complex process involving various biochemical, mechanical, and biophysical factors. Mathematical modeling provides a means through which to understand this complexity better, as well as to examine interactions between contributing components in a systematic way via computational simulations and quantitative analyses. In this review, we present the current state of mathematical modeling approaches that address phenomena related to drug delivery. We describe how various types of models were used to predict spatio-temporal distributions of drugs within the tumor tissue, to simulate different ways to overcome barriers to drug transport, or to optimize treatment schedules. Finally, we discuss how integration of mathematical modeling with experimental or clinical data can provide better tools to understand the drug delivery process, in particular to examine the specific tissue- or compound-related factors that limit drug penetration through tumors. Such tools will be important in designing new chemotherapy targets and optimal treatment strategies, as well as in developing non-invasive diagnosis to monitor treatment response and detect tumor recurrence.

A Dynamic Hydrology-Critical Zone Framework for Rainfall-triggered Landslide Hazard Prediction

NASA Astrophysics Data System (ADS)

Dialynas, Y. G.; Foufoula-Georgiou, E.; Dietrich, W. E.; Bras, R. L.

2017-12-01

Watershed-scale coupled hydrologic-stability models are still in their early stages, and are characterized by important limitations: (a) either they assume steady-state or quasi-dynamic watershed hydrology, or (b) they simulate landslide occurrence based on a simple one-dimensional stability criterion. Here we develop a three-dimensional landslide prediction framework, based on a coupled hydrologic-slope stability model and incorporation of the influence of deep critical zone processes (i.e., flow through weathered bedrock and exfiltration to the colluvium) for more accurate prediction of the timing, location, and extent of landslides. Specifically, a watershed-scale slope stability model that systematically accounts for the contribution of driving and resisting forces in three-dimensional hillslope segments was coupled with a spatially-explicit and physically-based hydrologic model. The landslide prediction framework considers critical zone processes and structure, and explicitly accounts for the spatial heterogeneity of surface and subsurface properties that control slope stability, including soil and weathered bedrock hydrological and mechanical characteristics, vegetation, and slope morphology. To test performance, the model was applied in landslide-prone sites in the US, the hydrology of which has been extensively studied. Results showed that both rainfall infiltration in the soil and groundwater exfiltration exert a strong control on the timing and magnitude of landslide occurrence. We demonstrate the extent to which three-dimensional slope destabilizing factors, which are modulated by dynamic hydrologic conditions in the soil-bedrock column, control landslide initiation at the watershed scale.

Dose-dependent model of caffeine effects on human vigilance during total sleep deprivation.

PubMed

Ramakrishnan, Sridhar; Laxminarayan, Srinivas; Wesensten, Nancy J; Kamimori, Gary H; Balkin, Thomas J; Reifman, Jaques

2014-10-07

Caffeine is the most widely consumed stimulant to counter sleep-loss effects. While the pharmacokinetics of caffeine in the body is well-understood, its alertness-restoring effects are still not well characterized. In fact, mathematical models capable of predicting the effects of varying doses of caffeine on objective measures of vigilance are not available. In this paper, we describe a phenomenological model of the dose-dependent effects of caffeine on psychomotor vigilance task (PVT) performance of sleep-deprived subjects. We used the two-process model of sleep regulation to quantify performance during sleep loss in the absence of caffeine and a dose-dependent multiplier factor derived from the Hill equation to model the effects of single and repeated caffeine doses. We developed and validated the model fits and predictions on PVT lapse (number of reaction times exceeding 500 ms) data from two separate laboratory studies. At the population-average level, the model captured the effects of a range of caffeine doses (50-300 mg), yielding up to a 90% improvement over the two-process model. Individual-specific caffeine models, on average, predicted the effects up to 23% better than population-average caffeine models. The proposed model serves as a useful tool for predicting the dose-dependent effects of caffeine on the PVT performance of sleep-deprived subjects and, therefore, can be used for determining caffeine doses that optimize the timing and duration of peak performance. Published by Elsevier Ltd.

Predicting What Will Happen When You Intervene.

PubMed

Cartwright, Nancy; Hardie, Jeremy

2017-01-01

This paper offers some rules of thumb that practicing social workers can use for case studies that aim to construct, albeit not fully and never entirely reliably, models designed to help predict what will happen if they intervene in specific ways to help this particular client, here and now. We call these 'ex ante case-specific causal models'. 'Ex ante' because they are for before-the-fact prediction of what the likely effects of proposed actions are. 'Case-specific' because we are not concerned with studies that provide evidence for some general conclusion but rather with using what general and local knowledge one can get to predict what will happen to a specific client in the real settings in which they live. 'Causal' because this kind of case study aims to trace out as best possible the web of causal processes that will be responsible for what happens. In this sense our case studies resemble post facto realist evaluations.

The Predictive Influence of Family and Neighborhood Assets on Fighting and Weapon Carrying from Mid- to Late-Adolescence

PubMed Central

Haegerich, Tamara M.; Oman, Roy F.; Vesely, Sara K.; Aspy, Cheryl B.; Tolma, Eleni L.

2015-01-01

Using a developmental, social-ecological approach to understand the etiology of health risk behavior and inform primary prevention efforts, we assess the predictive effects of family and neighborhood social processes on youth physical fighting and weapon carrying. Specifically, we focus on relationships among youth and their parents, family communication, and parental monitoring, as well as sense of community and neighborhood informal social control, support, concerns, and disorder. This study advances knowledge through its investigation of family and neighborhood structural factors and social processes together, employment of longitudinal models that estimate effects over adolescent development, and use of self-report and observational measures. Data from 1,093 youth/parent pairs were analyzed from the Youth Assets Study using a Generalized Estimating Equation (GEE) approach; family and neighborhood assets and risks were analyzed as time-varying and lagged. Similar family assets affected physical fighting and weapon carrying, whereas different neighborhood social processes influenced the two forms of youth violence. Study findings have implications for the primary prevention of youth violence, including the use of family-based approaches that build relationships and parental monitoring skills, and community-level change approaches that promote informal social control and reduce neighborhood concerns about safety. PMID:23677457

Predicting Academic Success in Higher Education: What's More Important than Being Smart?

ERIC Educational Resources Information Center

Kappe, Rutger; van der Flier, Henk

2012-01-01

This study investigated the combined predictive validity of intelligence and personality factors on multiple measures of academic achievement. Students in a college of higher education in the Netherlands (N = 137) completed a survey that measured intelligence, the Big Five personality traits, motivation, and four specific personality traits.…

Predicting University Performance in Psychology: The Role of Previous Performance and Discipline-Specific Knowledge

ERIC Educational Resources Information Center

Betts, Lucy R.; Elder, Tracey J.; Hartley, James; Blurton, Anthony

2008-01-01

Recent initiatives to enhance retention and widen participation ensure it is crucial to understand the factors that predict students' performance during their undergraduate degree. The present research used Structural Equation Modeling (SEM) to test three separate models that examined the extent to which British Psychology students' A-level entry…

Validation of a multifactorial risk factor model used for predicting future caries risk with Nevada adolescents.

PubMed

Ditmyer, Marcia M; Dounis, Georgia; Howard, Katherine M; Mobley, Connie; Cappelli, David

2011-05-20

The objective of this study was to measure the validity and reliability of a multifactorial Risk Factor Model developed for use in predicting future caries risk in Nevada adolescents in a public health setting. This study examined retrospective data from an oral health surveillance initiative that screened over 51,000 students 13-18 years of age, attending public/private schools in Nevada across six academic years (2002/2003-2007/2008). The Risk Factor Model included ten demographic variables: exposure to fluoridation in the municipal water supply, environmental smoke exposure, race, age, locale (metropolitan vs. rural), tobacco use, Body Mass Index, insurance status, sex, and sealant application. Multiple regression was used in a previous study to establish which significantly contributed to caries risk. Follow-up logistic regression ascertained the weight of contribution and odds ratios of the ten variables. Researchers in this study computed sensitivity, specificity, positive predictive value (PVP), negative predictive value (PVN), and prevalence across all six years of screening to assess the validity of the Risk Factor Model. Subjects' overall mean caries prevalence across all six years was 66%. Average sensitivity across all six years was 79%; average specificity was 81%; average PVP was 89% and average PVN was 67%. Overall, the Risk Factor Model provided a relatively constant, valid measure of caries that could be used in conjunction with a comprehensive risk assessment in population-based screenings by school nurses/nurse practitioners, health educators, and physicians to guide them in assessing potential future caries risk for use in prevention and referral practices.

Modeling Vascularized Bone Regeneration Within a Porous Biodegradable CaP Scaffold Loaded with Growth Factors

PubMed Central

Sun, X; Kang, Y; Bao, J; Zhang, Y; Yang, Y; Zhou, X

2013-01-01

Osteogenetic microenvironment is a complex constitution in which extracellular matrix (ECM) molecules, stem cells and growth factors each interact to direct the coordinate regulation of bone tissue development. Importantly, angiogenesis improvement and revascularization are critical for osteogenesis during bone tissue regeneration processes. In this study, we developed a three-dimensional (3D) multi-scale system model to study cell response to growth factors released from a 3D biodegradable porous calcium phosphate (CaP) scaffold. Our model reconstructed the 3D bone regeneration system and examined the effects of pore size and porosity on bone formation and angiogenesis. The results suggested that scaffold porosity played a more dominant role in affecting bone formation and angiogenesis compared with pore size, while the pore size could be controlled to tailor the growth factor release rate and release fraction. Furthermore, a combination of gradient VEGF with BMP2 and Wnt released from the multi-layer scaffold promoted angiogenesis and bone formation more readily than single growth factors. These results demonstrated that the developed model can be potentially applied to predict vascularized bone regeneration with specific scaffold and growth factors. PMID:23566802

Prediction of Protein Modification Sites of Pyrrolidone Carboxylic Acid Using mRMR Feature Selection and Analysis

PubMed Central

Zheng, Lu-Lu; Niu, Shen; Hao, Pei; Feng, KaiYan; Cai, Yu-Dong; Li, Yixue

2011-01-01

Pyrrolidone carboxylic acid (PCA) is formed during a common post-translational modification (PTM) of extracellular and multi-pass membrane proteins. In this study, we developed a new predictor to predict the modification sites of PCA based on maximum relevance minimum redundancy (mRMR) and incremental feature selection (IFS). We incorporated 727 features that belonged to 7 kinds of protein properties to predict the modification sites, including sequence conservation, residual disorder, amino acid factor, secondary structure and solvent accessibility, gain/loss of amino acid during evolution, propensity of amino acid to be conserved at protein-protein interface and protein surface, and deviation of side chain carbon atom number. Among these 727 features, 244 features were selected by mRMR and IFS as the optimized features for the prediction, with which the prediction model achieved a maximum of MCC of 0.7812. Feature analysis showed that all feature types contributed to the modification process. Further site-specific feature analysis showed that the features derived from PCA's surrounding sites contributed more to the determination of PCA sites than other sites. The detailed feature analysis in this paper might provide important clues for understanding the mechanism of the PCA formation and guide relevant experimental validations. PMID:22174779

Re-calibration of coronary risk prediction: an example of the Seven Countries Study.

PubMed

Puddu, Paolo Emilio; Piras, Paolo; Kromhout, Daan; Tolonen, Hanna; Kafatos, Anthony; Menotti, Alessandro

2017-12-14

We aimed at performing a calibration and re-calibration process using six standard risk factors from Northern (NE, N = 2360) or Southern European (SE, N = 2789) middle-aged men of the Seven Countries Study, whose parameters and data were fully known, to establish whether re-calibration gave the right answer. Greenwood-Nam-D'Agostino technique as modified by Demler (GNDD) in 2015 produced chi-squared statistics using 10 deciles of observed/expected CHD mortality risk, corresponding to Hosmer-Lemeshaw chi-squared employed for multiple logistic equations whereby binary data are used. Instead of the number of events, the GNDD test uses survival probabilities of observed and predicted events. The exercise applied, in five different ways, the parameters of the NE-predictive model to SE (and vice-versa) and compared the outcome of the simulated re-calibration with the real data. Good re-calibration could be obtained only when risk factor coefficients were substituted, being similar in magnitude and not significantly different between NE-SE. In all other ways, a good re-calibration could not be obtained. This is enough to praise for an overall need of re-evaluation of most investigations that, without GNDD or another proper technique for statistically assessing the potential differences, concluded that re-calibration is a fair method and might therefore be used, with no specific caution.

A reciprocal model of face recognition and autistic traits: evidence from an individual differences perspective.

PubMed

Halliday, Drew W R; MacDonald, Stuart W S; Scherf, K Suzanne; Sherf, Suzanne K; Tanaka, James W

2014-01-01

Although not a core symptom of the disorder, individuals with autism often exhibit selective impairments in their face processing abilities. Importantly, the reciprocal connection between autistic traits and face perception has rarely been examined within the typically developing population. In this study, university participants from the social sciences, physical sciences, and humanities completed a battery of measures that assessed face, object and emotion recognition abilities, general perceptual-cognitive style, and sub-clinical autistic traits (the Autism Quotient (AQ)). We employed separate hierarchical multiple regression analyses to evaluate which factors could predict face recognition scores and AQ scores. Gender, object recognition performance, and AQ scores predicted face recognition behaviour. Specifically, males, individuals with more autistic traits, and those with lower object recognition scores performed more poorly on the face recognition test. Conversely, university major, gender and face recognition performance reliably predicted AQ scores. Science majors, males, and individuals with poor face recognition skills showed more autistic-like traits. These results suggest that the broader autism phenotype is associated with lower face recognition abilities, even among typically developing individuals.

A Reciprocal Model of Face Recognition and Autistic Traits: Evidence from an Individual Differences Perspective

PubMed Central

Halliday, Drew W. R.; MacDonald, Stuart W. S.; Sherf, Suzanne K.; Tanaka, James W.

2014-01-01

Although not a core symptom of the disorder, individuals with autism often exhibit selective impairments in their face processing abilities. Importantly, the reciprocal connection between autistic traits and face perception has rarely been examined within the typically developing population. In this study, university participants from the social sciences, physical sciences, and humanities completed a battery of measures that assessed face, object and emotion recognition abilities, general perceptual-cognitive style, and sub-clinical autistic traits (the Autism Quotient (AQ)). We employed separate hierarchical multiple regression analyses to evaluate which factors could predict face recognition scores and AQ scores. Gender, object recognition performance, and AQ scores predicted face recognition behaviour. Specifically, males, individuals with more autistic traits, and those with lower object recognition scores performed more poorly on the face recognition test. Conversely, university major, gender and face recognition performance reliably predicted AQ scores. Science majors, males, and individuals with poor face recognition skills showed more autistic-like traits. These results suggest that the broader autism phenotype is associated with lower face recognition abilities, even among typically developing individuals. PMID:24853862

Multivariable Time Series Prediction for the Icing Process on Overhead Power Transmission Line

PubMed Central

Li, Peng; Zhao, Na; Zhou, Donghua; Cao, Min; Li, Jingjie; Shi, Xinling

2014-01-01

The design of monitoring and predictive alarm systems is necessary for successful overhead power transmission line icing. Given the characteristics of complexity, nonlinearity, and fitfulness in the line icing process, a model based on a multivariable time series is presented here to predict the icing load of a transmission line. In this model, the time effects of micrometeorology parameters for the icing process have been analyzed. The phase-space reconstruction theory and machine learning method were then applied to establish the prediction model, which fully utilized the history of multivariable time series data in local monitoring systems to represent the mapping relationship between icing load and micrometeorology factors. Relevant to the characteristic of fitfulness in line icing, the simulations were carried out during the same icing process or different process to test the model's prediction precision and robustness. According to the simulation results for the Tao-Luo-Xiong Transmission Line, this model demonstrates a good accuracy of prediction in different process, if the prediction length is less than two hours, and would be helpful for power grid departments when deciding to take action in advance to address potential icing disasters. PMID:25136653

Assessing local resilience to typhoon disasters: A case study in Nansha, Guangzhou.

PubMed

Song, Jinglu; Huang, Bo; Li, Rongrong

2018-01-01

Building communities' resilience to natural weather hazards requires the appropriate assessment of such capabilities. The resilience of a community is affected not only by social, economic, and infrastructural factors but also by natural factors (including both site characteristics and the intensity and frequency of events). To date, studies of natural factors have tended to draw on annual censuses and to use aggregated data, thus allowing only a limited understanding of site-specific hot or cold spots of resilience. To improve this situation, we carried out a comprehensive assessment of resilience to typhoon disasters in Nansha district, Guangzhou, China. We measured disaster resilience on 1×1-km grid units with respect to socioeconomic and infrastructural dimensions using a set of variables and also estimated natural factors in a detailed manner with a meteorological modeling tool, the Weather Research and Forecast model. We selected typhoon samples over the past 10 years, simulated the maximum typhoon-borne strong winds and precipitation of each sample, and predicted the wind speed and precipitation volume at the 100-year return-level on the basis of extreme value analysis. As a result, a composite resilience index was devised by combining factors in different domains using factor analysis coupled with the analytic hierarchy process. Resilience mapping using this composite resilience index allows local governments and planners to identify potential hot or cold spots of resilience and the dominant factors in particular locations, thereby assisting them in making more rational site-specific measures to improve local resilience to future typhoon disasters.

Assessing local resilience to typhoon disasters: A case study in Nansha, Guangzhou

PubMed Central

Huang, Bo; Li, Rongrong

2018-01-01

Building communities’ resilience to natural weather hazards requires the appropriate assessment of such capabilities. The resilience of a community is affected not only by social, economic, and infrastructural factors but also by natural factors (including both site characteristics and the intensity and frequency of events). To date, studies of natural factors have tended to draw on annual censuses and to use aggregated data, thus allowing only a limited understanding of site-specific hot or cold spots of resilience. To improve this situation, we carried out a comprehensive assessment of resilience to typhoon disasters in Nansha district, Guangzhou, China. We measured disaster resilience on 1×1-km grid units with respect to socioeconomic and infrastructural dimensions using a set of variables and also estimated natural factors in a detailed manner with a meteorological modeling tool, the Weather Research and Forecast model. We selected typhoon samples over the past 10 years, simulated the maximum typhoon-borne strong winds and precipitation of each sample, and predicted the wind speed and precipitation volume at the 100-year return-level on the basis of extreme value analysis. As a result, a composite resilience index was devised by combining factors in different domains using factor analysis coupled with the analytic hierarchy process. Resilience mapping using this composite resilience index allows local governments and planners to identify potential hot or cold spots of resilience and the dominant factors in particular locations, thereby assisting them in making more rational site-specific measures to improve local resilience to future typhoon disasters. PMID:29522526

Mental stress and psychosocial factors at work in relation to multiple-site musculoskeletal pain: a longitudinal study of kitchen workers.

PubMed

Haukka, Eija; Leino-Arjas, Päivi; Ojajärvi, Anneli; Takala, Esa-Pekka; Viikari-Juntura, Eira; Riihimäki, Hilkka

2011-04-01

Among 385 female kitchen workers, we examined (1) whether mental stress and psychosocial factors at work (job control, skill discretion, supervisor support, co-worker relationships, and hurry) predict multiple-site musculoskeletal pain (MSP; defined as pain at ≥ 3 of seven sites) and (2) reversedly, whether MSP predicts these psychosocial factors. Data were collected by questionnaire at 3-month intervals during 2 years. Trajectory analysis was applied. Four trajectories of MSP prevalence emerged: Low, Descending, Ascending, and High. For the psychosocial factors, a two-trajectory model (Ascending or High vs. Low) yielded the best fit. In logistic regression analysis, with the Low MSP trajectory as reference, poor co-worker relationships (odds ratio [OR] 3.9), mental stress (3.1) and hurry (2.1) at baseline predicted belonging to the High MSP trajectory. Also MSP at baseline predicted the trajectories (Ascending vs. Low) of low job control (2.2) and mental stress (3.2). Adverse changes in most psychosocial factors were associated with belonging to the High (ORs between 2.3 and 8.6) and Ascending (2.7-5.5) MSP trajectories. In generalized estimating equations, time-lagged by 3 months, all psychosocial factors but two predicted MSP (1.4-2.1), allowing, e.g. for MSP at baseline, and vice versa, MSP predicted low job control, low supervisor support, and mental stress (1.4-2.0), after adjustment for e.g. the relevant psychosocial factor at baseline. In conclusion, we found that several psychosocial factors predicted MSP and that MSP predicted several psychosocial factors. The results suggest a cumulative process in which adverse psychosocial factors and MSP influence each other. Copyright © 2010 European Federation of International Association for the Study of Pain Chapters. Published by Elsevier Ltd. All rights reserved.

Modeling Systems-Level Regulation of Host Immune Responses

PubMed Central

Thakar, Juilee; Pilione, Mylisa; Kirimanjeswara, Girish; Harvill, Eric T; Albert, Réka

2007-01-01

Many pathogens are able to manipulate the signaling pathways responsible for the generation of host immune responses. Here we examine and model a respiratory infection system in which disruption of host immune functions or of bacterial factors changes the dynamics of the infection. We synthesize the network of interactions between host immune components and two closely related bacteria in the genus Bordetellae. We incorporate existing experimental information on the timing of immune regulatory events into a discrete dynamic model, and verify the model by comparing the effects of simulated disruptions to the experimental outcome of knockout mutations. Our model indicates that the infection time course of both Bordetellae can be separated into three distinct phases based on the most active immune processes. We compare and discuss the effect of the species-specific virulence factors on disrupting the immune response during their infection of naive, antibody-treated, diseased, or convalescent hosts. Our model offers predictions regarding cytokine regulation, key immune components, and clearance of secondary infections; we experimentally validate two of these predictions. This type of modeling provides new insights into the virulence, pathogenesis, and host adaptation of disease-causing microorganisms and allows systems-level analysis that is not always possible using traditional methods. PMID:17559300

Modeling the probability of arsenic in groundwater in New England as a tool for exposure assessment.

PubMed

Ayotte, Joseph D; Nolan, Bernard T; Nuckols, John R; Cantor, Kenneth P; Robinson, Gilpin R; Baris, Dalsu; Hayes, Laura; Karagas, Margaret; Bress, William; Silverman, Debra T; Lubin, Jay H

2006-06-01

We developed a process-based model to predict the probability of arsenic exceeding 5 microg/L in drinking water wells in New England bedrock aquifers. The model is being used for exposure assessment in an epidemiologic study of bladder cancer. One important study hypothesis that may explain increased bladder cancer risk is elevated concentrations of inorganic arsenic in drinking water. In eastern New England, 20-30% of private wells exceed the arsenic drinking water standard of 10 micrograms per liter. Our predictive model significantly improves the understanding of factors associated with arsenic contamination in New England. Specific rock types, high arsenic concentrations in stream sediments, geochemical factors related to areas of Pleistocene marine inundation and proximity to intrusive granitic plutons, and hydrologic and landscape variables relating to groundwater residence time increase the probability of arsenic occurrence in groundwater. Previous studies suggest that arsenic in bedrock groundwater may be partly from past arsenical pesticide use. Variables representing historic agricultural inputs do not improve the model, indicating that this source does not significantly contribute to current arsenic concentrations. Due to the complexity of the fractured bedrock aquifers in the region, well depth and related variables also are not significant predictors.

Hierarchical Bayesian Markov switching models with application to predicting spawning success of shovelnose sturgeon

USGS Publications Warehouse

Holan, S.H.; Davis, G.M.; Wildhaber, M.L.; DeLonay, A.J.; Papoulias, D.M.

2009-01-01

The timing of spawning in fish is tightly linked to environmental factors; however, these factors are not very well understood for many species. Specifically, little information is available to guide recruitment efforts for endangered species such as the sturgeon. Therefore, we propose a Bayesian hierarchical model for predicting the success of spawning of the shovelnose sturgeon which uses both biological and behavioural (longitudinal) data. In particular, we use data that were produced from a tracking study that was conducted in the Lower Missouri River. The data that were produced from this study consist of biological variables associated with readiness to spawn along with longitudinal behavioural data collected by using telemetry and archival data storage tags. These high frequency data are complex both biologically and in the underlying behavioural process. To accommodate such complexity we developed a hierarchical linear regression model that uses an eigenvalue predictor, derived from the transition probability matrix of a two-state Markov switching model with generalized auto-regressive conditional heteroscedastic dynamics. Finally, to minimize the computational burden that is associated with estimation of this model, a parallel computing approach is proposed. ?? Journal compilation 2009 Royal Statistical Society.

Simulations in Cyber-Security: A Review of Cognitive Modeling of Network Attackers, Defenders, and Users.

PubMed

Veksler, Vladislav D; Buchler, Norbou; Hoffman, Blaine E; Cassenti, Daniel N; Sample, Char; Sugrim, Shridat

2018-01-01

Computational models of cognitive processes may be employed in cyber-security tools, experiments, and simulations to address human agency and effective decision-making in keeping computational networks secure. Cognitive modeling can addresses multi-disciplinary cyber-security challenges requiring cross-cutting approaches over the human and computational sciences such as the following: (a) adversarial reasoning and behavioral game theory to predict attacker subjective utilities and decision likelihood distributions, (b) human factors of cyber tools to address human system integration challenges, estimation of defender cognitive states, and opportunities for automation, (c) dynamic simulations involving attacker, defender, and user models to enhance studies of cyber epidemiology and cyber hygiene, and (d) training effectiveness research and training scenarios to address human cyber-security performance, maturation of cyber-security skill sets, and effective decision-making. Models may be initially constructed at the group-level based on mean tendencies of each subject's subgroup, based on known statistics such as specific skill proficiencies, demographic characteristics, and cultural factors. For more precise and accurate predictions, cognitive models may be fine-tuned to each individual attacker, defender, or user profile, and updated over time (based on recorded behavior) via techniques such as model tracing and dynamic parameter fitting.

Perceived threat and corroboration: key factors that improve a predictive model of trust in internet-based health information and advice.

PubMed

Harris, Peter R; Sillence, Elizabeth; Briggs, Pam

2011-07-27

How do people decide which sites to use when seeking health advice online? We can assume, from related work in e-commerce, that general design factors known to affect trust in the site are important, but in this paper we also address the impact of factors specific to the health domain. The current study aimed to (1) assess the factorial structure of a general measure of Web trust, (2) model how the resultant factors predicted trust in, and readiness to act on, the advice found on health-related websites, and (3) test whether adding variables from social cognition models to capture elements of the response to threatening, online health-risk information enhanced the prediction of these outcomes. Participants were asked to recall a site they had used to search for health-related information and to think of that site when answering an online questionnaire. The questionnaire consisted of a general Web trust questionnaire plus items assessing appraisals of the site, including threat appraisals, information checking, and corroboration. It was promoted on the hungersite.com website. The URL was distributed via Yahoo and local print media. We assessed the factorial structure of the measures using principal components analysis and modeled how well they predicted the outcome measures using structural equation modeling (SEM) with EQS software. We report an analysis of the responses of participants who searched for health advice for themselves (N = 561). Analysis of the general Web trust questionnaire revealed 4 factors: information quality, personalization, impartiality, and credible design. In the final SEM model, information quality and impartiality were direct predictors of trust. However, variables specific to eHealth (perceived threat, coping, and corroboration) added substantially to the ability of the model to predict variance in trust and readiness to act on advice on the site. The final model achieved a satisfactory fit: χ(2) (5) = 10.8 (P = .21), comparative fit index = .99, root mean square error of approximation = .052. The model accounted for 66% of the variance in trust and 49% of the variance in readiness to act on the advice. Adding variables specific to eHealth enhanced the ability of a model of trust to predict trust and readiness to act on advice.

Perceived Threat and Corroboration: Key Factors That Improve a Predictive Model of Trust in Internet-based Health Information and Advice

PubMed Central

Harris, Peter R; Briggs, Pam

2011-01-01

Background How do people decide which sites to use when seeking health advice online? We can assume, from related work in e-commerce, that general design factors known to affect trust in the site are important, but in this paper we also address the impact of factors specific to the health domain. Objective The current study aimed to (1) assess the factorial structure of a general measure of Web trust, (2) model how the resultant factors predicted trust in, and readiness to act on, the advice found on health-related websites, and (3) test whether adding variables from social cognition models to capture elements of the response to threatening, online health-risk information enhanced the prediction of these outcomes. Methods Participants were asked to recall a site they had used to search for health-related information and to think of that site when answering an online questionnaire. The questionnaire consisted of a general Web trust questionnaire plus items assessing appraisals of the site, including threat appraisals, information checking, and corroboration. It was promoted on the hungersite.com website. The URL was distributed via Yahoo and local print media. We assessed the factorial structure of the measures using principal components analysis and modeled how well they predicted the outcome measures using structural equation modeling (SEM) with EQS software. Results We report an analysis of the responses of participants who searched for health advice for themselves (N = 561). Analysis of the general Web trust questionnaire revealed 4 factors: information quality, personalization, impartiality, and credible design. In the final SEM model, information quality and impartiality were direct predictors of trust. However, variables specific to eHealth (perceived threat, coping, and corroboration) added substantially to the ability of the model to predict variance in trust and readiness to act on advice on the site. The final model achieved a satisfactory fit: χ2 5 = 10.8 (P = .21), comparative fit index = .99, root mean square error of approximation = .052. The model accounted for 66% of the variance in trust and 49% of the variance in readiness to act on the advice. Conclusions Adding variables specific to eHealth enhanced the ability of a model of trust to predict trust and readiness to act on advice. PMID:21795237

Cell-line-specific stimulation of tumor cell aggressiveness by wound healing factors - a central role for STAT3.

PubMed

Ekblad, Lars; Lindgren, Gustaf; Persson, Emma; Kjellén, Elisabeth; Wennerberg, Johan

2013-01-25

Local recurrence is a major factor affecting survival after treatment for head and neck squamous cell carcinoma (HNSCC). It is possible that the normal processes involved in wound healing after surgical removal of a primary tumor can boost the regrowth of residual cancer cells, thereby contributing to the recurrent growth. In this work, we collected human wound fluids and used them to investigate the effect of wound healing factors on HNSCC cell lines in vitro. Wound fluids were collected from thyroidectomized patients diagnosed with benign disease and were included in assays of cell proliferation, migration, cell scattering, and invasion. The involvement of intracellular signaling pathways and membrane receptors were investigated by western blotting and the inclusion of specific inhibitors. One out of four cell lines was greatly stimulated in proliferation, migration, cell scattering, and invasion by the addition of wound fluid as compared with addition of fetal bovine or human serum. These effects were accompanied by a sharp increase in activation of signal transducer and activator of transcription 3 (STAT3). Inhibition of STAT3 activation abolished the wound fluid response, showing that STAT3 plays an important role in the wound healing response. Several of the observed phenotypic changes were epithelial-to-mesenchymal transition (EMT)-like, but the appropriate changes were not seen in any of the EMT markers investigated. The involvement of c-Met or epidermal growth factor receptor family members was excluded, while the interleukin-6 receptor was found to be partly responsible for the activation of STAT3. In conclusion, we found cell-line-specific effects of wound healing factors on HNSCC, setting the stage for therapy development and predictive opportunities.

Does experience of the 'occult' predict use of complementary medicine? Experience of, and beliefs about, both complementary medicine and ways of telling the future.

PubMed

Furnham, A

2000-12-01

This study looked at the relationship between ratings of the perceived effectiveness of 24 methods for telling the future, 39 complementary therapies (CM) and 12 specific attitude statements about science and medicine. A total of 159 participants took part. The results showed that the participants were deeply sceptical of the effectiveness of the methods for telling the future which factored into meaningful and interpretable factors. Participants were much more positive about particular, but not all, specialties of complementary medicine (CM). These also factored into a meaningful factor structure. Finally, the 12 attitude to science/medicine statements revealed four factors: scepticism of medicine; the importance of psychological factors; patient protection; and the importance of scientific evaluation. Regressional analysis showed that belief in the total effectiveness of different ways of predicting the future was best predicted by beliefs in the effectiveness of the CM therapies. Although interest in the occult was associated with interest in CM, participants were able to distinguish between the two, and displayed scepticism about the effectiveness of methods of predicting the future and some CM therapies. Copyright 2000 Harcourt Publishers Ltd.

Cardiovascular Comorbidity and Mortality in Men With Prostate Cancer Treated With Brachytherapy-Based Radiation With or Without Hormonal Therapy

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

Nanda, Akash, E-mail: akash.nanda@orlandohealth.com; Chen, Ming-Hui; Moran, Brian J.

Purpose: To assess the impact of coronary artery disease (CAD) risk factors and sequelae on the risk of all-cause mortality (ACM) in men treated for prostate cancer (PC). Methods and Materials: The study cohort comprised 5077 men with PC consecutively treated with curative intent between 1997 and 2006 at the Chicago Prostate Cancer Center. Cox and Fine and Gray's competing risks regression multivariable analyses were performed, assessing whether cardiovascular comorbidity impacted the risk of ACM and PC-specific mortality, respectively, adjusting for CAD risk factors (diabetes mellitus, hypercholesterolemia, or hypertension) and sequelae (congestive heart failure or myocardial infarction), age, year andmore » type of treatment, and known PC prognostic factors. Results: When compared with men with no comorbidity there was a significantly increased risk of ACM in men with congestive heart failure or myocardial infarction (adjusted hazard ratio [AHR] 1.96, P<.001) and in men with diabetes mellitus (AHR 1.60, P=.03) and hypertension (AHR 1.25, P=.04). In contrast, men with hypercholesterolemia had a similar risk of ACM (AHR 0.68, P=.17) when compared with men with no comorbidity. Other factors associated with a significantly increased risk of ACM included age (AHR 1.09, P<.001), prostate-specific antigen level (AHR 1.25, P=.008), and Gleason score 8-10 disease (AHR 1.71, P=.003). Cardiovascular comorbidity did not impact the risk of PC-specific mortality. Conclusions: In addition to age and unfavorable PC prognostic factors, select CAD risk factors and sequelae are associated with an increased risk of ACM in men treated for PC. These comorbidity prognostic factors predict time courses of mortality from competing causes, which may be factored into the decision-making process when considering management options for PC in a given individual.« less

Long-Term Deflection Prediction from Computer Vision-Measured Data History for High-Speed Railway Bridges

PubMed Central

Lee, Jaebeom; Lee, Young-Joo

2018-01-01

Management of the vertical long-term deflection of a high-speed railway bridge is a crucial factor to guarantee traffic safety and passenger comfort. Therefore, there have been efforts to predict the vertical deflection of a railway bridge based on physics-based models representing various influential factors to vertical deflection such as concrete creep and shrinkage. However, it is not an easy task because the vertical deflection of a railway bridge generally involves several sources of uncertainty. This paper proposes a probabilistic method that employs a Gaussian process to construct a model to predict the vertical deflection of a railway bridge based on actual vision-based measurement and temperature. To deal with the sources of uncertainty which may cause prediction errors, a Gaussian process is modeled with multiple kernels and hyperparameters. Once the hyperparameters are identified through the Gaussian process regression using training data, the proposed method provides a 95% prediction interval as well as a predictive mean about the vertical deflection of the bridge. The proposed method is applied to an arch bridge under operation for high-speed trains in South Korea. The analysis results obtained from the proposed method show good agreement with the actual measurement data on the vertical deflection of the example bridge, and the prediction results can be utilized for decision-making on railway bridge maintenance. PMID:29747421

Long-Term Deflection Prediction from Computer Vision-Measured Data History for High-Speed Railway Bridges.

PubMed

Lee, Jaebeom; Lee, Kyoung-Chan; Lee, Young-Joo

2018-05-09

Management of the vertical long-term deflection of a high-speed railway bridge is a crucial factor to guarantee traffic safety and passenger comfort. Therefore, there have been efforts to predict the vertical deflection of a railway bridge based on physics-based models representing various influential factors to vertical deflection such as concrete creep and shrinkage. However, it is not an easy task because the vertical deflection of a railway bridge generally involves several sources of uncertainty. This paper proposes a probabilistic method that employs a Gaussian process to construct a model to predict the vertical deflection of a railway bridge based on actual vision-based measurement and temperature. To deal with the sources of uncertainty which may cause prediction errors, a Gaussian process is modeled with multiple kernels and hyperparameters. Once the hyperparameters are identified through the Gaussian process regression using training data, the proposed method provides a 95% prediction interval as well as a predictive mean about the vertical deflection of the bridge. The proposed method is applied to an arch bridge under operation for high-speed trains in South Korea. The analysis results obtained from the proposed method show good agreement with the actual measurement data on the vertical deflection of the example bridge, and the prediction results can be utilized for decision-making on railway bridge maintenance.

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

PubMed Central

Kuang, Zheng; Ji, Zhicheng

2018-01-01

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

Stress and anger as contextual factors and preexisting cognitive schemas: predicting parental child maltreatment risk.

PubMed

Rodriguez, Christina M; Richardson, Michael J

2007-11-01

Progress in the child maltreatment field depends on refinements in leading models. This study examines aspects of social information processing theory (Milner, 2000) in predicting physical maltreatment risk in a community sample. Consistent with this theory, selected preexisting schema (external locus-of-control orientation, inappropriate developmental expectations, low empathic perspective-taking ability, and low perceived attachment relationship to child) were expected to predict child abuse risk beyond contextual factors (parenting stress and anger expression). Based on 115 parents' self-report, results from this study support cognitive factors that predict abuse risk (with locus of control, perceived attachment, or empathy predicting different abuse risk measures, but not developmental expectations), although the broad contextual factors involving negative affectivity and stress were consistent predictors across abuse risk markers. Findings are discussed with regard to implications for future model evaluations, with indications the model may apply to other forms of maltreatment, such as psychological maltreatment or neglect.

Factors Affecting Nuclear Export of the 60S Ribosomal Subunit In Vivo

PubMed Central

Stage-Zimmermann, Tracy; Schmidt, Ute; Silver, Pamela A.

2000-01-01

In Saccharomyces cerevisiae, the 60S ribosomal subunit assembles in the nucleolus and then is exported to the cytoplasm, where it joins the 40S subunit for translation. Export of the 60S subunit from the nucleus is known to be an energy-dependent and factor-mediated process, but very little is known about the specifics of its transport. To begin to address this problem, an assay was developed to follow the localization of the 60S ribosomal subunit in S. cerevisiae. Ribosomal protein L11b (Rpl11b), one of the ∼45 ribosomal proteins of the 60S subunit, was tagged at its carboxyl terminus with the green fluorescent protein (GFP) to enable visualization of the 60S subunit in living cells. A panel of mutant yeast strains was screened for their accumulation of Rpl11b–GFP in the nucleus as an indicator of their involvement in ribosome synthesis and/or transport. This panel included conditional alleles of several rRNA-processing factors, nucleoporins, general transport factors, and karyopherins. As predicted, conditional alleles of rRNA-processing factors that affect 60S ribosomal subunit assembly accumulated Rpl11b–GFP in the nucleus. In addition, several of the nucleoporin mutants as well as a few of the karyopherin and transport factor mutants also mislocalized Rpl11b–GFP. In particular, deletion of the previously uncharacterized karyopherin KAP120 caused accumulation of Rpl11b–GFP in the nucleus, whereas ribosomal protein import was not impaired. Together, these data further define the requirements for ribosomal subunit export and suggest a biological function for KAP120. PMID:11071906

Predictive factors for moderate or severe exacerbations in asthma patients receiving outpatient care.

PubMed

Gutiérrez, Francisco Javier Álvarez; Galván, Marta Ferrer; Gallardo, Juan Francisco Medina; Mancera, Marta Barrera; Romero, Beatriz Romero; Falcón, Auxiliadora Romero

2017-05-02

Asthma exacerbations are important events that affect disease control, but predictive factors for severe or moderate exacerbations are not known. The objective was to study the predictive factors for moderate (ME) and severe (SE) exacerbations in asthma patients receiving outpatient care. Patients aged > 12 years with asthma were included in the study and followed-up at 4-monthly intervals over a 12-month period. Clinical (severity, level of control, asthma control test [ACT]), atopic, functional, inflammatory, SE and ME parameters were recorded. Univariate analysis was used to compare data from patients presenting at least 1 SE or ME during the follow-up period vs no exacerbations. Statistically significant (p <0.1) factors were then subjected to multiple analysis by binary logistic regression. A total of 330 patients completed the study, most of whom were atopic (76%), women (nearly 70%), with moderate and mild persistent asthma (>80%). Twenty-seven patients (8%) had a SE and 183 had a ME (58.5%) during follow-up. In the case of SEs, the only predictive factor identified in the multiple analysis was previous SE (baseline visit OR 4.218 95% CI 1.53-11.58, 4-month follow-up OR 6.88 95% CI 2.018-23.51) and inhalation technique (OR 3.572 95% CI 1.324-9.638). In the case of MEs, the only predictive factor found in the multiple analysis were previous ME (baseline visit OR 2.90 95% CI 1.54-5.48, 4-month follow- up OR 1.702 95% CI 1.146-2.529). The primary predictive factor for SE or ME is prior SE or ME, respectively. SEs seem to constitute a specific patient "phenotype", in which the sole predictive factor is prior SEs.

A Novel Model for Predicting Rehospitalization Risk Incorporating Physical Function, Cognitive Status, and Psychosocial Support Using Natural Language Processing.

PubMed

Greenwald, Jeffrey L; Cronin, Patrick R; Carballo, Victoria; Danaei, Goodarz; Choy, Garry

2017-03-01

With the increasing focus on reducing hospital readmissions in the United States, numerous readmissions risk prediction models have been proposed, mostly developed through analyses of structured data fields in electronic medical records and administrative databases. Three areas that may have an impact on readmission but are poorly captured using structured data sources are patients' physical function, cognitive status, and psychosocial environment and support. The objective of the study was to build a discriminative model using information germane to these 3 areas to identify hospitalized patients' risk for 30-day all cause readmissions. We conducted clinician focus groups to identify language used in the clinical record regarding these 3 areas. We then created a dataset including 30,000 inpatients, 10,000 from each of 3 hospitals, and searched those records for the focus group-derived language using natural language processing. A 30-day readmission prediction model was developed on 75% of the dataset and validated on the other 25% and also on hospital specific subsets. Focus group language was aggregated into 35 variables. The final model had 16 variables, a validated C-statistic of 0.74, and was well calibrated. Subset validation of the model by hospital yielded C-statistics of 0.70-0.75. Deriving a 30-day readmission risk prediction model through identification of physical, cognitive, and psychosocial issues using natural language processing yielded a model that performs similarly to the better performing models previously published with the added advantage of being based on clinically relevant factors and also automated and scalable. Because of the clinical relevance of the variables in the model, future research may be able to test if targeting interventions to identified risks results in reductions in readmissions.

Smoker Characteristics and Smoking-Cessation Milestones

PubMed Central

Japuntich, Sandra J.; Leventhal, Adam M.; Piper, Megan E.; Bolt, Daniel M.; Roberts, Linda J.; Fiore, Michael C.; Baker, Timothy B.

2011-01-01

Background Contextual variables often predict long-term abstinence, but little is known about how these variables exert their effects. These variables could influence abstinence by affecting the ability to quit at all, or by altering risk of lapsing, or progressing from a lapse to relapse. Purpose To examine the effect of common predictors of smoking-cessation failure on smoking-cessation processes. Methods The current study (N = 1504, 58% female, 84% Caucasian; recruited from January 2005 to June 2007; data analyzed in 2009) uses the approach advocated by Shiffman et al., (2006), which measures cessation outcomes on three different cessation milestones (achieving initial abstinence, lapse risk, and the lapse-relapse transition) to examine relationships of smoker characteristics (dependence, contextual and demographic factors) with smoking-cessation process. Results High nicotine dependence strongly predicted all milestones: not achieving initial abstinence, and a higher risk of both lapse and transitioning from lapse to complete relapse. Numerous contextual and demographic variables were associated with higher initial cessation rates and/or decreased lapse risk at 6 months post-quit (e.g., ethnicity, gender, marital status, education, smoking in the workplace, number of smokers in the social network, and number of supportive others). However, aside from nicotine dependence, only gender significantly predicted the risk of transition from lapse to relapse. Conclusions These findings demonstrate that: (1) higher nicotine dependence predicted worse outcomes across every cessation milestone; (2) demographic and contextual variables are generally associated with initial abstinence rates and lapse risk and not the lapse-relapse transition. These results identify groups who are at risk for failure at specific stages of the smoking-cessation process, and this may have implications for treatment. PMID:21335259

Material Stream Strategy for Lithium and Inorganics (U)

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

Safarik, Douglas Joseph; Dunn, Paul Stanton; Korzekwa, Deniece Rochelle

Design Agency Responsibilities: Manufacturing Support to meet Stockpile Stewardship goals for maintaining the nuclear stockpile through experimental and predictive modeling capability. Development and maintenance of Manufacturing Science expertise to assess material specifications and performance boundaries, and their relationship to processing parameters. Production Engineering Evaluations with competence in design requirements, material specifications, and manufacturing controls. Maintenance and enhancement of Aging Science expertise to support Stockpile Stewardship predictive science capability.

The Evidential Basis of Decision Making in Plant Disease Management.

PubMed

Hughes, Gareth

2017-08-04

The evidential basis for disease management decision making is provided by data relating to risk factors. The decision process involves an assessment of the evidence leading to taking (or refraining from) action on the basis of a prediction. The primary objective of the decision process is to identify-at the time the decision is made-the control action that provides the best predicted end-of-season outcome, calculated in terms of revenue or another appropriate metric. Data relating to disease risk factors may take a variety of forms (e.g., continuous, discrete, categorical) on measurement scales in a variety of units. Log 10 -likelihood ratios provide a principled basis for the accumulation of evidence based on such data and allow predictions to be made via Bayesian updating of prior probabilities.

Contraceptive Method Choice Among Young Adults: Influence of Individual and Relationship Factors.

PubMed

Harvey, S Marie; Oakley, Lisa P; Washburn, Isaac; Agnew, Christopher R

2018-01-26

Because decisions related to contraceptive behavior are often made by young adults in the context of specific relationships, the relational context likely influences use of contraceptives. Data presented here are from in-person structured interviews with 536 Black, Hispanic, and White young adults from East Los Angeles, California. We collected partner-specific relational and contraceptive data on all sexual partnerships for each individual, on four occasions, over one year. Using three-level multinomial logistic regression models, we examined individual and relationship factors predictive of contraceptive use. Results indicated that both individual and relationship factors predicted contraceptive use, but factors varied by method. Participants reporting greater perceived partner exclusivity and relationship commitment were more likely to use hormonal/long-acting methods only or a less effective method/no method versus condoms only. Those with greater participation in sexual decision making were more likely to use any method over a less effective method/no method and were more likely to use condoms only or dual methods versus a hormonal/long-acting method only. In addition, for women only, those who reported greater relationship commitment were more likely to use hormonal/long-acting methods or a less effective method/no method versus a dual method. In summary, interactive relationship qualities and dynamics (commitment and sexual decision making) significantly predicted contraceptive use.

The relevance of cultural factors in predicting condom-use intentions among immigrants from the Netherlands Antilles.

PubMed

Kocken, Pl; van Dorst, Ag; Schaalma, H

2006-04-01

A study into the relevance of cultural factors in predicting condom-use intentions among Antillean migrants in the Netherlands is described in this article. The association between the intention to use condoms with a new sexual partner and a perceived taboo on discussing sex, beliefs about sex education and machismo beliefs on gender and power relationships is addressed. The study was conducted among 346 Dutch Antilleans from a random sample of an Antillean population aged 15-50 years. The response rate was 37.8%. The results showed that condom-use intentions were primarily determined by perceived subjective norms, the perceived taboo on discussing sex, machismo attitudes, gender, age and educational background. Moreover, the respondent's opinion regarding machismo was an effect modificator for the association between condom-use intentions and subjective social norm. It is concluded that, in predicting condom-use intentions, factors specific to the culture of a population contribute significantly to the determinants drawn from the general social-cognition models. It is recommended that future research should use measurement instruments that are adapted to culture-specific beliefs, and should explore the influence of cultural factors on actual condom use. Moreover, interventions promoting condom use among migrant populations should target the cultural correlates of condom use.

Empathy and contextual social cognition.

PubMed

Melloni, Margherita; Lopez, Vladimir; Ibanez, Agustin

2014-03-01

Empathy is a highly flexible and adaptive process that allows for the interplay of prosocial behavior in many different social contexts. Empathy appears to be a very situated cognitive process, embedded with specific contextual cues that trigger different automatic and controlled responses. In this review, we summarize relevant evidence regarding social context modulation of empathy for pain. Several contextual factors, such as stimulus reality and personal experience, affectively link with other factors, emotional cues, threat information, group membership, and attitudes toward others to influence the affective, sensorimotor, and cognitive processing of empathy. Thus, we propose that the frontoinsular-temporal network, the so-called social context network model (SCNM), is recruited during the contextual processing of empathy. This network would (1) update the contextual cues and use them to construct fast predictions (frontal regions), (2) coordinate the internal (body) and external milieus (insula), and (3) consolidate the context-target associative learning of empathic processes (temporal sites). Furthermore, we propose these context-dependent effects of empathy in the framework of the frontoinsular-temporal network and examine the behavioral and neural evidence of three neuropsychiatric conditions (Asperger syndrome, schizophrenia, and the behavioral variant of frontotemporal dementia), which simultaneously present with empathy and contextual integration impairments. We suggest potential advantages of a situated approach to empathy in the assessment of these neuropsychiatric disorders, as well as their relationship with the SCNM.

Burgers or tofu? Eating between two worlds: risk information seeking and processing during dietary acculturation.

PubMed

Lu, Hang

2015-01-01

This study attempted to examine what factors might motivate Chinese international students, the fastest growing ethnic student group in the United States, to seek and process information about potential health risks from eating American-style food. This goal was accomplished by applying the Risk Information Seeking and Processing (RISP) model to this study. An online 2 (severity: high vs. low) × 2 (coping strategies: present vs. absent) between-subjects experiment was conducted via Qualtrics to evaluate the effects of the manipulated variables on the dependent variables of interest as well as various relationships proposed in the RISP model. A convenience sample of 635 participants was recruited online. Data were analyzed primarily using structural equation modeling (SEM) in AMOS 21.0 with maximum likelihood estimation. The final conceptual model has a good model fit to the data given the sample size. The results showed that although the experimentally manipulated variables failed to cause any significant differences in individuals' perceived severity and self-efficacy, this study largely supported the RISP model's propositions about the sociopsychological factors that explain individual variations in information seeking and processing. More specifically, the findings indicated a prominent role of informational subjective norms and affective responses (both negative and positive emotions) in predicting individuals' information seeking and processing. Future implications and limitations are also discussed.

A retrospective analysis to identify the factors affecting infection in patients undergoing chemotherapy.

PubMed

Park, Ji Hyun; Kim, Hyeon-Young; Lee, Hanna; Yun, Eun Kyoung

2015-12-01

This study compares the performance of the logistic regression and decision tree analysis methods for assessing the risk factors for infection in cancer patients undergoing chemotherapy. The subjects were 732 cancer patients who were receiving chemotherapy at K university hospital in Seoul, Korea. The data were collected between March 2011 and February 2013 and were processed for descriptive analysis, logistic regression and decision tree analysis using the IBM SPSS Statistics 19 and Modeler 15.1 programs. The most common risk factors for infection in cancer patients receiving chemotherapy were identified as alkylating agents, vinca alkaloid and underlying diabetes mellitus. The logistic regression explained 66.7% of the variation in the data in terms of sensitivity and 88.9% in terms of specificity. The decision tree analysis accounted for 55.0% of the variation in the data in terms of sensitivity and 89.0% in terms of specificity. As for the overall classification accuracy, the logistic regression explained 88.0% and the decision tree analysis explained 87.2%. The logistic regression analysis showed a higher degree of sensitivity and classification accuracy. Therefore, logistic regression analysis is concluded to be the more effective and useful method for establishing an infection prediction model for patients undergoing chemotherapy. Copyright © 2015 Elsevier Ltd. All rights reserved.

Social cognition and African American men: The roles of perceived discrimination and experimenter race on task performance.

PubMed

Nagendra, Arundati; Twery, Benjamin L; Neblett, Enrique W; Mustafic, Hasan; Jones, Tevin S; Gatewood, D'Angelo; Penn, David L

2018-01-01

The Social Cognition Psychometric Evaluation (SCOPE) study consists of a battery of eight tasks selected to measure social-cognitive deficits in individuals with schizophrenia. The battery is currently in a multisite validation process. While the SCOPE study collects basic demographic data, more nuanced race-related factors might artificially inflate cross-cultural differences in social cognition. As an initial step, we investigated whether race, independent of mental illness status, affects performance on the SCOPE battery. Thus, we examined the effects of perceived discrimination and experimenter race on the performance of 51 non-clinical African American men on the SCOPE battery. Results revealed that these factors impacted social cognitive task performance. Specifically, participants performed better on a skills-based task factor in the presence of Black experimenters, and frequency of perceived racism predicted increased perception of hostility in negative interpersonal situations with accidental causes. Thus, race-related factors are important to identify and explore in the measurement of social cognition in African Americans. Copyright © 2017 Elsevier B.V. All rights reserved.

Analysis of SEER Adenosquamous Carcinoma Data to Identify Cause Specific Survival Predictors and Socioeconomic Disparities.

PubMed

Cheung, Rex

2016-01-01

This study used receiver operating characteristic curve to analyze Surveillance, Epidemiology and End Results (SEER) adenosquamous carcinoma data to identify predictive models and potential disparities in outcome. This study analyzed socio-economic, staging and treatment factors available in the SEER database for adenosquamous carcinoma. For the risk modeling, each factor was fitted by a generalized linear model to predict the cause specific survival. An area under the receiver operating characteristic curve (ROC) was computed. Similar strata were combined to construct the most parsimonious models. A total of 20,712 patients diagnosed from 1973 to 2009 were included in this study. The mean follow up time (S.D.) was 54.2 (78.4) months. Some 2/3 of the patients were female. The mean (S.D.) age was 63 (13.8) years. SEER stage was the most predictive factor of outcome (ROC area of 0.71). 13.9% of the patients were un-staged and had risk of cause specific death of 61.3% that was higher than the 45.3% risk for the regional disease and lower than the 70.3% for metastatic disease. Sex, site, radiotherapy, and surgery had ROC areas of about 0.55-0.65. Rural residence and race contributed to socioeconomic disparity for treatment outcome. Radiotherapy was underused even with localized and regional stages when the intent was curative. This under use was most pronounced in older patients. Anatomic stage was predictive and useful in treatment selection. Under-staging may have contributed to poor outcome.

Real-data comparison of data mining methods in prediction of diabetes in iran.

PubMed

Tapak, Lily; Mahjub, Hossein; Hamidi, Omid; Poorolajal, Jalal

2013-09-01

Diabetes is one of the most common non-communicable diseases in developing countries. Early screening and diagnosis play an important role in effective prevention strategies. This study compared two traditional classification methods (logistic regression and Fisher linear discriminant analysis) and four machine-learning classifiers (neural networks, support vector machines, fuzzy c-mean, and random forests) to classify persons with and without diabetes. The data set used in this study included 6,500 subjects from the Iranian national non-communicable diseases risk factors surveillance obtained through a cross-sectional survey. The obtained sample was based on cluster sampling of the Iran population which was conducted in 2005-2009 to assess the prevalence of major non-communicable disease risk factors. Ten risk factors that are commonly associated with diabetes were selected to compare the performance of six classifiers in terms of sensitivity, specificity, total accuracy, and area under the receiver operating characteristic (ROC) curve criteria. Support vector machines showed the highest total accuracy (0.986) as well as area under the ROC (0.979). Also, this method showed high specificity (1.000) and sensitivity (0.820). All other methods produced total accuracy of more than 85%, but for all methods, the sensitivity values were very low (less than 0.350). The results of this study indicate that, in terms of sensitivity, specificity, and overall classification accuracy, the support vector machine model ranks first among all the classifiers tested in the prediction of diabetes. Therefore, this approach is a promising classifier for predicting diabetes, and it should be further investigated for the prediction of other diseases.

Limb-Enhancer Genie: An accessible resource of accurate enhancer predictions in the developing limb

DOE PAGES

Monti, Remo; Barozzi, Iros; Osterwalder, Marco; ...

2017-08-21

Epigenomic mapping of enhancer-associated chromatin modifications facilitates the genome-wide discovery of tissue-specific enhancers in vivo. However, reliance on single chromatin marks leads to high rates of false-positive predictions. More sophisticated, integrative methods have been described, but commonly suffer from limited accessibility to the resulting predictions and reduced biological interpretability. Here we present the Limb-Enhancer Genie (LEG), a collection of highly accurate, genome-wide predictions of enhancers in the developing limb, available through a user-friendly online interface. We predict limb enhancers using a combination of > 50 published limb-specific datasets and clusters of evolutionarily conserved transcription factor binding sites, taking advantage ofmore » the patterns observed at previously in vivo validated elements. By combining different statistical models, our approach outperforms current state-of-the-art methods and provides interpretable measures of feature importance. Our results indicate that including a previously unappreciated score that quantifies tissue-specific nuclease accessibility significantly improves prediction performance. We demonstrate the utility of our approach through in vivo validation of newly predicted elements. Moreover, we describe general features that can guide the type of datasets to include when predicting tissue-specific enhancers genome-wide, while providing an accessible resource to the general biological community and facilitating the functional interpretation of genetic studies of limb malformations.« less

Age and Vascular Burden Determinants of Cortical Hemodynamics Underlying Verbal Fluency.

PubMed

Heinzel, Sebastian; Metzger, Florian G; Ehlis, Ann-Christine; Korell, Robert; Alboji, Ahmed; Haeussinger, Florian B; Wurster, Isabel; Brockmann, Kathrin; Suenkel, Ulrike; Eschweiler, Gerhard W; Maetzler, Walter; Berg, Daniela; Fallgatter, Andreas J

2015-01-01

Aging processes and several vascular burden factors have been shown to increase the risk of dementia including Alzheimer's disease. While pathological alterations in dementia precede diagnosis by many years, reorganization of brain processing might temporarily delay cognitive decline. We hypothesized that in healthy elderly individuals both age-related neural and vascular factors known to be related to the development of dementia impact functional cortical hemodynamics during increased cognitive demands. Vascular burden factors and cortical functional hemodynamics during verbal fluency were assessed in 1052 non-demented elderly individuals (51 to 83 years; cross-sectional data of the longitudinal TREND study) using functional near-infrared spectroscopy (fNIRS). The prediction of functional hemodynamic responses by age in multiple regressions and the impact of single and cumulative vascular burden factors including hypertension, diabetes, obesity, smoking and atherosclerosis were investigated. Replicating and extending previous findings we could show that increasing age predicted functional hemodynamics to be increased in right prefrontal and bilateral parietal cortex, and decreased in bilateral inferior frontal junction during phonological fluency. Cumulative vascular burden factors, with hypertension in particular, decreased left inferior frontal junction hemodynamic responses during phonological fluency. However, age and vascular burden factors showed no statistical interaction on functional hemodynamics. Based on these findings, one might hypothesize that increased fronto-parietal processing may represent age-related compensatory reorganization during increased cognitive demands. Vascular burden factors, such as hypertension, may contribute to regional cerebral hypoperfusion. These neural and vascular hemodynamic determinants should be investigated longitudinally and combined with other markers to advance the prediction of future cognitive decline and dementia.

Structural modeling for multicell composite rotor blades

NASA Technical Reports Server (NTRS)

Rehfield, Lawrence W.; Atilgan, Ali R.

1987-01-01

Composite material systems are currently good candidates for aerospace structures, primarily for the design flexibility they offer, i.e., it is possible to tailor the material and manufacturing approach to the application. A working definition of elastic or structural tailoring is the use of structural concept, fiber orientation, ply stacking sequence, and a blend of materials to achieve specific performance goals. In the design process, choices of materials and dimensions are made which produce specific response characteristics, and which permit the selected goals to be achieved. Common choices for tailoring goals are preventing instabilities or vibration resonances or enhancing damage tolerance. An essential, enabling factor in the design of tailored composite structures is structural modeling that accurately, but simply, characterizes response. The objective of this paper is to present a new multicell beam model for composite rotor blades and to validate predictions based on the new model by comparison with a finite element simulation in three benchmark static load cases.

Fueling the Flames of the Green-Eyed Monster: The Role of Ruminative Thought in Reaction to Romantic Jealousy.

ERIC Educational Resources Information Center

Carson, Christine L.; Cupach, William R.

2000-01-01

Examines factors predicted to influence individuals' responses to romantic jealousy. Details a study in which undergraduate students completed scales measuring relationship-specific linking, relationship-specific rumination, possessiveness, trust, and communicative responses to jealousy. Suggests that jealous rumination is an important cognitive…

Principals' Perceptions of Barriers to Dismissal of Poor-Performing Teachers

ERIC Educational Resources Information Center

Dandoy, Jason R.

2012-01-01

The purpose of this study is to determine which factors influence items that school principals consider "barriers" to dismissal of "incompetent" or "poor performing" teachers. This study determines if specific characteristics of schools, principals, or a combination of the two can predict the specific barriers cited…

Registrar Staging Assistant (SEER*RSA) - SEER

Cancer.gov

Use this site for cases diagnosed 2018 and forward to code Extent of Disease 2018, Summary Stage 2018, Site-Specific Data Items, and Grade. Use it for 2016 and 2017 cases to determine UICC TNM 7th edition stage, Collaborative Stage v.02.05.50, and Site-Specific predictive and prognostic factors.

Sasquatch: predicting the impact of regulatory SNPs on transcription factor binding from cell- and tissue-specific DNase footprints.

PubMed

Schwessinger, Ron; Suciu, Maria C; McGowan, Simon J; Telenius, Jelena; Taylor, Stephen; Higgs, Doug R; Hughes, Jim R

2017-10-01

In the era of genome-wide association studies (GWAS) and personalized medicine, predicting the impact of single nucleotide polymorphisms (SNPs) in regulatory elements is an important goal. Current approaches to determine the potential of regulatory SNPs depend on inadequate knowledge of cell-specific DNA binding motifs. Here, we present Sasquatch, a new computational approach that uses DNase footprint data to estimate and visualize the effects of noncoding variants on transcription factor binding. Sasquatch performs a comprehensive k -mer-based analysis of DNase footprints to determine any k -mer's potential for protein binding in a specific cell type and how this may be changed by sequence variants. Therefore, Sasquatch uses an unbiased approach, independent of known transcription factor binding sites and motifs. Sasquatch only requires a single DNase-seq data set per cell type, from any genotype, and produces consistent predictions from data generated by different experimental procedures and at different sequence depths. Here we demonstrate the effectiveness of Sasquatch using previously validated functional SNPs and benchmark its performance against existing approaches. Sasquatch is available as a versatile webtool incorporating publicly available data, including the human ENCODE collection. Thus, Sasquatch provides a powerful tool and repository for prioritizing likely regulatory SNPs in the noncoding genome. © 2017 Schwessinger et al.; Published by Cold Spring Harbor Laboratory Press.

Elevated Responding to Safe Conditions as a Specific Risk Factor for Anxiety Versus Depressive Disorders: Evidence From a Longitudinal Investigation

PubMed Central

Craske, Michelle G.; Wolitzky–Taylor, Kate B.; Mineka, Susan; Zinbarg, Richard; Waters, Allison M.; Vrshek–Schallhorn, Suzanne; Epstein, Alyssa; Naliboff, Bruce; Ornitz, Edward

2013-01-01

The current study evaluated the degree to which startle reflexes (SRs) in safe conditions versus danger conditions were predictive of the onset of anxiety disorders. Specificity of these effects to anxiety disorders was evaluated in comparison to unipolar depressive disorders and with consideration of level of neuroticism. A startle paradigm was administered at baseline to 132 nondisordered adolescents as part of a longitudinal study examining risk factors for emotional disorders. Participants underwent a repetition of eight safe-danger sequences and were told that delivery of an aversive stimulus leading to a muscle contraction of the arm would occur only in the late part of danger conditions. One aversive stimulus occurred midway in the safe-danger sequences. Participants were assessed for the onset of anxiety and unipolar depressive disorders annually over the next 3 to 4 years. Larger SR magnitude during safe conditions following delivery of the aversive stimulus predicted the subsequent first onset of anxiety disorders. Moreover, prediction of the onset of anxiety disorders remained significant above and beyond the effects of comorbid unipolar depression, neuroticism, and subjective ratings of intensity of the aversive stimulus. In sum, elevated responding to safe conditions following an aversive stimulus appears to be a specific, prospective risk factor for the first onset of anxiety disorders. PMID:21988452

Selection of the most influential factors on the water-jet assisted underwater laser process by adaptive neuro-fuzzy technique

NASA Astrophysics Data System (ADS)

Nikolić, Vlastimir; Petković, Dalibor; Lazov, Lyubomir; Milovančević, Miloš

2016-07-01

Water-jet assisted underwater laser cutting has shown some advantages as it produces much less turbulence, gas bubble and aerosols, resulting in a more gentle process. However, this process has relatively low efficiency due to different losses in water. It is important to determine which parameters are the most important for the process. In this investigation was analyzed the water-jet assisted underwater laser cutting parameters forecasting based on the different parameters. The method of ANFIS (adaptive neuro fuzzy inference system) was applied to the data in order to select the most influential factors for water-jet assisted underwater laser cutting parameters forecasting. Three inputs are considered: laser power, cutting speed and water-jet speed. The ANFIS process for variable selection was also implemented in order to detect the predominant factors affecting the forecasting of the water-jet assisted underwater laser cutting parameters. According to the results the combination of laser power cutting speed forms the most influential combination foe the prediction of water-jet assisted underwater laser cutting parameters. The best prediction was observed for the bottom kerf-width (R2 = 0.9653). The worst prediction was observed for dross area per unit length (R2 = 0.6804). According to the results, a greater improvement in estimation accuracy can be achieved by removing the unnecessary parameter.

PDSM, a motif for phosphorylation-dependent SUMO modification

PubMed Central

Hietakangas, Ville; Anckar, Julius; Blomster, Henri A.; Fujimoto, Mitsuaki; Palvimo, Jorma J.; Nakai, Akira; Sistonen, Lea

2006-01-01

SUMO (small ubiquitin-like modifier) modification regulates many cellular processes, including transcription. Although sumoylation often occurs on specific lysines within the consensus tetrapeptide ΨKxE, other modifications, such as phosphorylation, may regulate the sumoylation of a substrate. We have discovered PDSM (phosphorylation-dependent sumoylation motif), composed of a SUMO consensus site and an adjacent proline-directed phosphorylation site (ΨKxExxSP). The highly conserved motif regulates phosphorylation-dependent sumoylation of multiple substrates, such as heat-shock factors (HSFs), GATA-1, and myocyte enhancer factor 2. In fact, the majority of the PDSM-containing proteins are transcriptional regulators. Within the HSF family, PDSM is conserved between two functionally distinct members, HSF1 and HSF4b, whose transactivation capacities are repressed through the phosphorylation-dependent sumoylation. As the first recurrent sumoylation determinant beyond the consensus tetrapeptide, the PDSM provides a valuable tool in predicting new SUMO substrates. PMID:16371476

Microcomputer Calculation of Theoretical Pre-Exponential Factors for Bimolecular Reactions.

ERIC Educational Resources Information Center

Venugopalan, Mundiyath

1991-01-01

Described is the application of microcomputers to predict reaction rates based on theoretical atomic and molecular properties taught in undergraduate physical chemistry. Listed is the BASIC program which computes the partition functions for any specific bimolecular reactants. These functions are then used to calculate the pre-exponential factor of…

Five-Factor Model of Personality and Career Exploration

ERIC Educational Resources Information Center

Reed, Mary Beth; Bruch, Monroe A.; Haase, Richard F.

2004-01-01

This study investigates whether the dimensions of the five-factor model (FFM) of personality are related to specific career exploration variables. Based on the FFM, predictions were made about the relevance of particular traits to career exploration variables. Results from a canonical correlation analysis showed that variable loadings on three…

Functions of Marijuana Use in College Students

ERIC Educational Resources Information Center

Bates, Julie K.; Accordino, Michael P.; Hewes, Robert L.

2010-01-01

Hierarchical regression analysis was used to test the hypothesis that specific functional factors of marijuana use would predict past 30-day marijuana use in 425 college students more precisely than demographic variables alone. This hypothesis was confirmed. Functional factors of personal/physical enhancement as well as activity enhancement were…

Parasite infracommunities of a specialized marine fish species in a compound community dominated by generalist parasites.

PubMed

Lanfranchi, A L; Rossin, M A; Timi, J T

2009-12-01

The structure and composition of parasite communities of Mullus argentinae were analysed under two alternative hypotheses in a sample of 75 specimens caught off Mar del Plata, Argentina (38 degrees 27'S, 57 degrees 90'W). The first, based on the dominance of trophically transmitted larval parasites of low host-specificity among fish species in the region, predicts that infracommunities will be random subsets of regionally available species. The second, based on previous studies on other mullids, predicts that infracommunities will be dominated by adult digeneans. The parasite fauna of goatfishes was mainly composed of endoparasites, with metacercariae of Prosorhynchus australis accounting for most individual parasites and greatly affecting infracommunity descriptors. Its importance was reinforced by the low number of trophically transmitted larval parasites. Both hypotheses were refuted; parasite communities were not dominated either by trophically transmitted larval parasites of low host-specificity or by adult digeneans. Prosorhynchus australis was the only species displaying any degree of phylogenetic specificity. Therefore, the influence of phylogenetic factors seems to exceed that of ecological ones in determining the observed structure of infracommunities. However, it is precisely host ecology that allows P. australis to become the determinant of infracommunity structure by constraining the acquisition of other parasites. Studies aiming to determine the relative importance of evolutionary and ecological processes as structuring forces of parasite communities should take into account not only the identity and specificity of their component parasites, but also their availability in the compound community.

[Factors associated with malignancy in gallbladder polyps without gallbladder stone].

PubMed

Lee, Jae Seung; Lee, Kyu Taek; Jung, Jae Hong; Ok, Sung Wook; Choi, Sung Chul; Lee, Kwang Hyuck; Lee, Jong Kyun; Heo, Jin Seok; Choi, Seong Ho; Rhee, Jong Chul

2008-08-01

The purpose of this study was to find the factors predicting the neoplastic polyp of gallbladder and analyze the size criteria associated with malignancy. A total of 354 subjects with gallbladder polyps confirmed by tissue pathology were included for the analysis. The clinical and radiological features of the polyps were compared between the two groups (neoplastic vs. non-neoplastic) and in the three groups (non-neoplastic vs. adenoma vs. adenocarcinoma). The independent factors associated with malignancy were studied. Of 354 patients, non-neoplastic polyps were observed in 229 (64.7%) patents, adenoma in 85 (24.0%) and adenocarcinoma in 40 (11.3%). The mean diameter of non-neoplastic polyp, adenoma, and adenocarcinoma were 11.3+/-2.8 mm, 16.0+/-7.2 mm, and 27.0+/-8.9 mm, respectively. The mean age of patients with non-neoplastic polyp, adenoma, and adenocarcinoma were 44.8+/-11.3, 49.9+/-12.5, and 60.8+/-9.6, respectively. Age, size of polyp, number of polyp, presence of diabetes, and presence of symptom showed statistically significant difference between the neoplastic polyp and non-neoplastic polyp groups. But only age, size of polyp, number of polyp were statistically independent factors associated with neoplastic polyp (p<0.05). To predict the neoplastic polyp, sensitivity was 94.4%, but specificity was 18.3% on the basis of 10 mm criteria. whereas sensitivity and specificity was 76.0% and 55.5% on the 12 mm-criteria. On the basis of our analysis, the size of polyp is the most important factor to predict the malignancy. In the 10 mm criteria, sensitivity is satisfactory but specificity is very low. Therefore 10 mm size should not be considered to be the absolute size-criterion for surgery.

Brain Substrates of Recovery from Misleading Influence

PubMed Central

Dudai, Yadin; Dolan, Raymond J.; Sharot, Tali

2014-01-01

Humans are strongly influenced by their environment, a dependence that can lead to errors in judgment. Although a rich literature describes how people are influenced by others, little is known regarding the factors that predict subsequent rectification of misleading influence. Using a mediation model in combination with brain imaging, we propose a model for the correction of misinformation. Specifically, our data suggest that amygdala modulation of hippocampal mnemonic representations, during the time of misleading social influence, is associated with reduced subsequent anterior–lateral prefrontal cortex activity that reflects correction. These findings illuminate the process by which erroneous beliefs are, or fail to be, rectified and highlight how past influence constrains subsequent correction. PMID:24899698

To master or perform? Exploring relations between achievement goals and conceptual change learning.

PubMed

Ranellucci, John; Muis, Krista R; Duffy, Melissa; Wang, Xihui; Sampasivam, Lavanya; Franco, Gina M

2013-09-01

Research is needed to explore conceptual change in relation to achievement goal orientations and depth of processing. To address this need, we examined relations between achievement goals, use of deep versus shallow processing strategies, and conceptual change learning using a think-aloud protocol. Seventy-three undergraduate students were assessed on their prior knowledge and misconceptions about Newtonian mechanics, and then reported their achievement goals and participated in think-aloud protocols while reading Newtonian physics texts. A mastery-approach goal orientation positively predicted deep processing strategies, shallow processing strategies, and conceptual change. In contrast, a performance-approach goal orientation did not predict either of the processing strategies, but negatively predicted conceptual change. A performance-avoidance goal orientation negatively predicted deep processing strategies and conceptual change. Moreover, deep and shallow processing strategies positively predicted conceptual change as well as recall. Finally, both deep and shallow processing strategies mediated relations between mastery-approach goals and conceptual change. Results provide some support for Dole and Sinatra's (1998) Cognitive Reconstruction of Knowledge Model of conceptual change but also challenge specific facets with regard to the role of depth of processing in conceptual change. © 2012 The British Psychological Society.

Evaluating Aerosol Process Modules within the Framework of the Aerosol Modeling Testbed

NASA Astrophysics Data System (ADS)

Fast, J. D.; Velu, V.; Gustafson, W. I.; Chapman, E.; Easter, R. C.; Shrivastava, M.; Singh, B.

2012-12-01

Factors that influence predictions of aerosol direct and indirect forcing, such as aerosol mass, composition, size distribution, hygroscopicity, and optical properties, still contain large uncertainties in both regional and global models. New aerosol treatments are usually implemented into a 3-D atmospheric model and evaluated using a limited number of measurements from a specific case study. Under this modeling paradigm, the performance and computational efficiency of several treatments for a specific aerosol process cannot be adequately quantified because many other processes among various modeling studies (e.g. grid configuration, meteorology, emission rates) are different as well. The scientific community needs to know the advantages and disadvantages of specific aerosol treatments when the meteorology, chemistry, and other aerosol processes are identical in order to reduce the uncertainties associated with aerosols predictions. To address these issues, an Aerosol Modeling Testbed (AMT) has been developed that systematically and objectively evaluates new aerosol treatments for use in regional and global models. The AMT consists of the modular Weather Research and Forecasting (WRF) model, a series testbed cases for which extensive in situ and remote sensing measurements of meteorological, trace gas, and aerosol properties are available, and a suite of tools to evaluate the performance of meteorological, chemical, aerosol process modules. WRF contains various parameterizations of meteorological, chemical, and aerosol processes and includes interactive aerosol-cloud-radiation treatments similar to those employed by climate models. In addition, the physics suite from the Community Atmosphere Model version 5 (CAM5) have also been ported to WRF so that they can be tested at various spatial scales and compared directly with field campaign data and other parameterizations commonly used by the mesoscale modeling community. Data from several campaigns, including the 2006 MILAGRO, 2008 ISDAC, 2008 VOCALS, 2010 CARES, and 2010 CalNex campaigns, have been incorporated into the AMT as testbed cases. Data from operational networks (e.g. air quality, meteorology, satellite) are also included in the testbed cases to supplement the field campaign data. The CARES and CalNex testbed cases are used to demonstrate how the AMT can be used to assess the strengths and weaknesses of simple and complex representations of aerosol processes in relation to computational cost. Anticipated enhancements to the AMT and how this type of testbed can be used by the scientific community to foster collaborations and coordinate aerosol modeling research will also be discussed.

Coupling of snow and permafrost processes using the Basic Modeling Interface (BMI)

NASA Astrophysics Data System (ADS)

Wang, K.; Overeem, I.; Jafarov, E. E.; Piper, M.; Stewart, S.; Clow, G. D.; Schaefer, K. M.

2017-12-01

We developed a permafrost modeling tool based by implementing the Kudryavtsev empirical permafrost active layer depth model (the so-called "Ku" component). The model is specifically set up to have a basic model interface (BMI), which enhances the potential coupling to other earth surface processes model components. This model is accessible through the Web Modeling Tool in Community Surface Dynamics Modeling System (CSDMS). The Kudryavtsev model has been applied for entire Alaska to model permafrost distribution at high spatial resolution and model predictions have been verified by Circumpolar Active Layer Monitoring (CALM) in-situ observations. The Ku component uses monthly meteorological forcing, including air temperature, snow depth, and snow density, and predicts active layer thickness (ALT) and temperature on the top of permafrost (TTOP), which are important factors in snow-hydrological processes. BMI provides an easy approach to couple the models with each other. Here, we provide a case of coupling the Ku component to snow process components, including the Snow-Degree-Day (SDD) method and Snow-Energy-Balance (SEB) method, which are existing components in the hydrological model TOPOFLOW. The work flow is (1) get variables from meteorology component, set the values to snow process component, and advance the snow process component, (2) get variables from meteorology and snow component, provide these to the Ku component and advance, (3) get variables from snow process component, set the values to meteorology component, and advance the meteorology component. The next phase is to couple the permafrost component with fully BMI-compliant TOPOFLOW hydrological model, which could provide a useful tool to investigate the permafrost hydrological effect.

Domain-General and Domain-Specific Patterns of Activity Supporting Metacognition in Human Prefrontal Cortex

PubMed Central

2018-01-01

Metacognition is the capacity to evaluate the success of one's own cognitive processes in various domains; for example, memory and perception. It remains controversial whether metacognition relies on a domain-general resource that is applied to different tasks or if self-evaluative processes are domain specific. Here, we investigated this issue directly by examining the neural substrates engaged when metacognitive judgments were made by human participants of both sexes during perceptual and memory tasks matched for stimulus and performance characteristics. By comparing patterns of fMRI activity while subjects evaluated their performance, we revealed both domain-specific and domain-general metacognitive representations. Multivoxel activity patterns in anterior prefrontal cortex predicted levels of confidence in a domain-specific fashion, whereas domain-general signals predicting confidence and accuracy were found in a widespread network in the frontal and posterior midline. The demonstration of domain-specific metacognitive representations suggests the presence of a content-rich mechanism available to introspection and cognitive control. SIGNIFICANCE STATEMENT We used human neuroimaging to investigate processes supporting memory and perceptual metacognition. It remains controversial whether metacognition relies on a global resource that is applied to different tasks or if self-evaluative processes are specific to particular tasks. Using multivariate decoding methods, we provide evidence that perceptual- and memory-specific metacognitive representations coexist with generic confidence signals. Our findings reconcile previously conflicting results on the domain specificity/generality of metacognition and lay the groundwork for a mechanistic understanding of metacognitive judgments. PMID:29519851

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.

Predicting patriarchy: using individual and contextual factors to examine patriarchal endorsement in communities.

PubMed

Crittenden, Courtney A; Wright, Emily M

2013-04-01

In much feminist literature, patriarchy has often been studied as a predictive variable for attitudes toward or acts of violence against women. However, rarely has patriarchy been examined as an outcome across studies. The current study works toward filling this gap by examining several individual-and neighborhood-level factors that might influence patriarchy. Specifically, this research seeks to determine if neighborhood-level attributes related to socioeconomic status, family composition, and demographic information affect patriarchal views after individual-level correlates of patriarchy were controlled. Findings suggest that factors at both the individual- and neighborhood levels, particularly familial characteristics and dynamics, do influence the endorsement of patriarchal views.

Algorithm for cellular reprogramming.

PubMed

Ronquist, Scott; Patterson, Geoff; Muir, Lindsey A; Lindsly, Stephen; Chen, Haiming; Brown, Markus; Wicha, Max S; Bloch, Anthony; Brockett, Roger; Rajapakse, Indika

2017-11-07

The day we understand the time evolution of subcellular events at a level of detail comparable to physical systems governed by Newton's laws of motion seems far away. Even so, quantitative approaches to cellular dynamics add to our understanding of cell biology. With data-guided frameworks we can develop better predictions about, and methods for, control over specific biological processes and system-wide cell behavior. Here we describe an approach for optimizing the use of transcription factors (TFs) in cellular reprogramming, based on a device commonly used in optimal control. We construct an approximate model for the natural evolution of a cell-cycle-synchronized population of human fibroblasts, based on data obtained by sampling the expression of 22,083 genes at several time points during the cell cycle. To arrive at a model of moderate complexity, we cluster gene expression based on division of the genome into topologically associating domains (TADs) and then model the dynamics of TAD expression levels. Based on this dynamical model and additional data, such as known TF binding sites and activity, we develop a methodology for identifying the top TF candidates for a specific cellular reprogramming task. Our data-guided methodology identifies a number of TFs previously validated for reprogramming and/or natural differentiation and predicts some potentially useful combinations of TFs. Our findings highlight the immense potential of dynamical models, mathematics, and data-guided methodologies for improving strategies for control over biological processes. Copyright © 2017 the Author(s). Published by PNAS.

Neural Correlates of Semantic Prediction and Resolution in Sentence Processing.

PubMed

Grisoni, Luigi; Miller, Tally McCormick; Pulvermüller, Friedemann

2017-05-03

Most brain-imaging studies of language comprehension focus on activity following meaningful stimuli. Testing adult human participants with high-density EEG, we show that, already before the presentation of a critical word, context-induced semantic predictions are reflected by a neurophysiological index, which we therefore call the semantic readiness potential (SRP). The SRP precedes critical words if a previous sentence context constrains the upcoming semantic content (high-constraint contexts), but not in unpredictable (low-constraint) contexts. Specific semantic predictions were indexed by SRP sources within the motor system-in dorsolateral hand motor areas for expected hand-related words (e.g., "write"), but in ventral motor cortex for face-related words ("talk"). Compared with affirmative sentences, negated ones led to medial prefrontal and more widespread motor source activation, the latter being consistent with predictive semantic computation of alternatives to the negated expected concept. Predictive processing of semantic alternatives in negated sentences is further supported by a negative-going event-related potential at ∼400 ms (N400), which showed the typical enhancement to semantically incongruent sentence endings only in high-constraint affirmative contexts, but not to high-constraint negated ones. These brain dynamics reveal the interplay between semantic prediction and resolution (match vs error) processing in sentence understanding. SIGNIFICANCE STATEMENT Most neuroscientists agree on the eminent importance of predictive mechanisms for understanding basic as well as higher brain functions. This contrasts with a sparseness of brain measures that directly reflects specific aspects of prediction, as they are relevant in the processing of language and thought. Here we show that when critical words are strongly expected in their sentence context, a predictive brain response reflects meaning features of these anticipated symbols already before they appear. The granularity of the semantic predictions was so fine grained that the cortical sources in sensorimotor and medial prefrontal cortex even distinguished between predicted face- or hand-related action words (e.g., the words "lick" or "pick") and between affirmative and negated sentence meanings. Copyright © 2017 Grisoni et al.

Neural Correlates of Semantic Prediction and Resolution in Sentence Processing

PubMed Central

2017-01-01

Most brain-imaging studies of language comprehension focus on activity following meaningful stimuli. Testing adult human participants with high-density EEG, we show that, already before the presentation of a critical word, context-induced semantic predictions are reflected by a neurophysiological index, which we therefore call the semantic readiness potential (SRP). The SRP precedes critical words if a previous sentence context constrains the upcoming semantic content (high-constraint contexts), but not in unpredictable (low-constraint) contexts. Specific semantic predictions were indexed by SRP sources within the motor system—in dorsolateral hand motor areas for expected hand-related words (e.g., “write”), but in ventral motor cortex for face-related words (“talk”). Compared with affirmative sentences, negated ones led to medial prefrontal and more widespread motor source activation, the latter being consistent with predictive semantic computation of alternatives to the negated expected concept. Predictive processing of semantic alternatives in negated sentences is further supported by a negative-going event-related potential at ∼400 ms (N400), which showed the typical enhancement to semantically incongruent sentence endings only in high-constraint affirmative contexts, but not to high-constraint negated ones. These brain dynamics reveal the interplay between semantic prediction and resolution (match vs error) processing in sentence understanding. SIGNIFICANCE STATEMENT Most neuroscientists agree on the eminent importance of predictive mechanisms for understanding basic as well as higher brain functions. This contrasts with a sparseness of brain measures that directly reflects specific aspects of prediction, as they are relevant in the processing of language and thought. Here we show that when critical words are strongly expected in their sentence context, a predictive brain response reflects meaning features of these anticipated symbols already before they appear. The granularity of the semantic predictions was so fine grained that the cortical sources in sensorimotor and medial prefrontal cortex even distinguished between predicted face- or hand-related action words (e.g., the words “lick” or “pick”) and between affirmative and negated sentence meanings. PMID:28411271

Preliminary Empirical Models for Predicting Shrinkage, Part Geometry and Metallurgical Aspects of Ti-6Al-4V Shaped Metal Deposition Builds

NASA Astrophysics Data System (ADS)

Escobar-Palafox, Gustavo; Gault, Rosemary; Ridgway, Keith

2011-12-01

Shaped Metal Deposition (SMD) is an additive manufacturing process which creates parts layer by layer by weld depositions. In this work, empirical models that predict part geometry (wall thickness and outer diameter) and some metallurgical aspects (i.e. surface texture, portion of finer Widmanstätten microstructure) for the SMD process were developed. The models are based on an orthogonal fractional factorial design of experiments with four factors at two levels. The factors considered were energy level (a relationship between heat source power and the rate of raw material input.), step size, programmed diameter and travel speed. The models were validated using previous builds; the prediction error for part geometry was under 11%. Several relationships between the factors and responses were identified. Current had a significant effect on wall thickness; thickness increases with increasing current. Programmed diameter had a significant effect on percentage of shrinkage; this decreased with increasing component size. Surface finish decreased with decreasing step size and current.

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

PubMed

Plint, Simon; Patterson, Fiona

2010-06-01

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

Which neuropsychological functions predict various processing speed components in children with and without attention-deficit/hyperactivity disorder?

PubMed

Vadnais, Sarah A; Kibby, Michelle Y; Jagger-Rickels, Audreyana C

2018-01-01

We identified statistical predictors of four processing speed (PS) components in a sample of 151 children with and without attention-deficit/hyperactivity disorder (ADHD). Performance on perceptual speed was predicted by visual attention/short-term memory, whereas incidental learning/psychomotor speed was predicted by verbal working memory. Rapid naming was predictive of each PS component assessed, and inhibition predicted all but one task, suggesting a shared need to identify/retrieve stimuli rapidly and inhibit incorrect responding across PS components. Hence, we found both shared and unique predictors of perceptual, cognitive, and output speed, suggesting more specific terminology should be used in future research on PS in ADHD.

Evaluation of an artificial intelligence program for estimating occupational exposures.

PubMed

Johnston, Karen L; Phillips, Margaret L; Esmen, Nurtan A; Hall, Thomas A

2005-03-01

Estimation and Assessment of Substance Exposure (EASE) is an artificial intelligence program developed by UK's Health and Safety Executive to assess exposure. EASE computes estimated airborne concentrations based on a substance's vapor pressure and the types of controls in the work area. Though EASE is intended only to make broad predictions of exposure from occupational environments, some occupational hygienists might attempt to use EASE for individual exposure characterizations. This study investigated whether EASE would accurately predict actual sampling results from a chemical manufacturing process. Personal breathing zone time-weighted average (TWA) monitoring data for two volatile organic chemicals--a common solvent (toluene) and a specialty monomer (chloroprene)--present in this manufacturing process were compared to EASE-generated estimates. EASE-estimated concentrations for specific tasks were weighted by task durations reported in the monitoring record to yield TWA estimates from EASE that could be directly compared to the measured TWA data. Two hundred and six chloroprene and toluene full-shift personal samples were selected from eight areas of this manufacturing process. The Spearman correlation between EASE TWA estimates and measured TWA values was 0.55 for chloroprene and 0.44 for toluene, indicating moderate predictive values for both compounds. For toluene, the interquartile range of EASE estimates at least partially overlapped the interquartile range of the measured data distributions in all process areas. The interquartile range of EASE estimates for chloroprene fell above the interquartile range of the measured data distributions in one process area, partially overlapped the third quartile of the measured data in five process areas and fell within the interquartile range in two process areas. EASE is not a substitute for actual exposure monitoring. However, EASE can be used in conditions that cannot otherwise be sampled and in preliminary exposure assessment if it is recognized that the actual interquartile range could be much wider and/or offset by a factor of 10 or more.

Modelling and analysis of ozone concentration by artificial intelligent techniques for estimating air quality

NASA Astrophysics Data System (ADS)

Taylan, Osman

2017-02-01

High ozone concentration is an important cause of air pollution mainly due to its role in the greenhouse gas emission. Ozone is produced by photochemical processes which contain nitrogen oxides and volatile organic compounds in the lower atmospheric level. Therefore, monitoring and controlling the quality of air in the urban environment is very important due to the public health care. However, air quality prediction is a highly complex and non-linear process; usually several attributes have to be considered. Artificial intelligent (AI) techniques can be employed to monitor and evaluate the ozone concentration level. The aim of this study is to develop an Adaptive Neuro-Fuzzy inference approach (ANFIS) to determine the influence of peripheral factors on air quality and pollution which is an arising problem due to ozone level in Jeddah city. The concentration of ozone level was considered as a factor to predict the Air Quality (AQ) under the atmospheric conditions. Using Air Quality Standards of Saudi Arabia, ozone concentration level was modelled by employing certain factors such as; nitrogen oxide (NOx), atmospheric pressure, temperature, and relative humidity. Hence, an ANFIS model was developed to observe the ozone concentration level and the model performance was assessed by testing data obtained from the monitoring stations established by the General Authority of Meteorology and Environment Protection of Kingdom of Saudi Arabia. The outcomes of ANFIS model were re-assessed by fuzzy quality charts using quality specification and control limits based on US-EPA air quality standards. The results of present study show that the ANFIS model is a comprehensive approach for the estimation and assessment of ozone level and is a reliable approach to produce more genuine outcomes.

Visual form predictions facilitate auditory processing at the N1.

PubMed

Paris, Tim; Kim, Jeesun; Davis, Chris

2017-02-20

Auditory-visual (AV) events often involve a leading visual cue (e.g. auditory-visual speech) that allows the perceiver to generate predictions about the upcoming auditory event. Electrophysiological evidence suggests that when an auditory event is predicted, processing is sped up, i.e., the N1 component of the ERP occurs earlier (N1 facilitation). However, it is not clear (1) whether N1 facilitation is based specifically on predictive rather than multisensory integration and (2) which particular properties of the visual cue it is based on. The current experiment used artificial AV stimuli in which visual cues predicted but did not co-occur with auditory cues. Visual form cues (high and low salience) and the auditory-visual pairing were manipulated so that auditory predictions could be based on form and timing or on timing only. The results showed that N1 facilitation occurred only for combined form and temporal predictions. These results suggest that faster auditory processing (as indicated by N1 facilitation) is based on predictive processing generated by a visual cue that clearly predicts both what and when the auditory stimulus will occur. Copyright © 2016. Published by Elsevier Ltd.

Prognostic factors for acute myeloid leukaemia in adults--biological significance and clinical use.

PubMed

Liersch, Ruediger; Müller-Tidow, Carsten; Berdel, Wolfgang E; Krug, Utz

2014-04-01

Acute myeloid leukaemia (AML) is a heterogeneous disease. Prognosis of AML is influenced both by patient-specific as well as disease-specific factors. Age is the most prominent patient-specific risk factor, while chromosomal aberrations are the strongest disease-specific risk factors. For patients with cytogenetically normal AML, prognosis can be specified by mutational status of the genes NPM1, FLT3 and CEBPA. A growing number of recurrent mutations in additional genes have recently been identified, for which the prognostic effect yet has to be determined. Performance status, geriatric assessment, secondary leukaemia following myelodysplastic syndrome or cytotoxic treatment, common laboratory parameters, leukaemic stem cell frequency, bone marrow microenvironment, gene expression levels, epigenetic changes, micro-RNA's as well as kinetics and depth of response to treatment influence prognosis of AML patients. Despite the high number of established risk factors, only few predictive markers exist which can truly aid therapy decisions in patients with AML. © 2014 John Wiley & Sons Ltd.

Specificity of disgust domains in the prediction of contamination anxiety and avoidance: a multimodal examination.

PubMed

Olatunji, Bunmi O; Ebesutani, Chad; Haidt, Jonathan; Sawchuk, Craig N

2014-07-01

Although core, animal-reminder, and contamination disgust are viewed as distinct "types" of disgust vulnerabilities, the extent to which individual differences in the three disgust domains uniquely predict contamination-related anxiety and avoidance remains unclear. Three studies were conducted to fill this important gap in the literature. Study 1 was conducted to first determine if the three types of disgust could be replicated in a larger and more heterogeneous sample. Confirmatory factor analysis revealed that a bifactor model consisting of a "general disgust" dimension and the three distinct disgust dimensions yielded a better fit than a one-factor model. Structural equation modeling in Study 2 showed that while latent core, animal-reminder, and contamination disgust factors each uniquely predicted a latent "contamination anxiety" factor above and beyond general disgust, only animal-reminder uniquely predicted a latent "non-contamination anxiety" factor above and beyond general disgust. However, Study 3 found that only contamination disgust uniquely predicted behavioral avoidance in a public restroom where contamination concerns are salient. These findings suggest that although the three disgust domains are associated with contamination anxiety and avoidance, individual differences in contamination disgust sensitivity appear to be most uniquely predictive of contamination-related distress. The implications of these findings for the development and maintenance of anxiety-related disorders marked by excessive contamination concerns are discussed. Copyright © 2014. Published by Elsevier Ltd.